Do-it-yourself protein arrays as high-throughput immunoassays enabled by confined droplets on patterned plasmonic chips

Domain: neuroscience
Published: 2026-02-14
Editorial outcome: major_revision

Abstract
Proteinchipsandarraysinparallelenablehigh-throughputproteindetection
insmall-volumebiologicalfluids,however,thelimitationsinsensitivity,
dependenceonexpensive/bulkyexternalequipment,andtheneedforspe-
cializedtechnicalpersonnelhaverestrictedtheirapplicationinclinicaland
laboratorysettings.Here,wepresentadroplet-baseddo-it-yourself(DBDIY)
arrayonpatternedplasmonicchipsforhigh-throughputimmunoassays,via
confineddropletsandplasmonicenhancednear-infrared(NIR)fluorescence.
Theassayallowsequipment-freemicroarrayfabricationandhighlysensitive
detectionusingonlyapipette.Itdynamicallyprofiles10cytokinesover40
daysinindividualmicewithjust6µLofserum/bloodpertimepointand
achieves100%sensitivityandspecificityforC-reactiveprotein(CRP)in1nLof
peripheralwholebloodsamplesfrom112children.Scalabletohigh-
throughputanalysisofcellcultureandserum,thisaccessiblesystemsimplifies
workflows,extendsutilityinresource-limitedsettings,andoffersanext-
generationtoolforlongitudinalanimalstudiesandclinicaldiagnostics.

Introduction
Accurate, high-throughput measurement of protein levels in small- detection on a single platform, with advantages of high specificity,
volume biological fluids is critical in both clinical and laboratory highthroughput,andlowreagentconsumption10–13.Althoughprotein
settings1–3.Forclinicaldiagnosisandprognosis,thisisespeciallyvitalin chipshavemanyadvantagesforhigh-throughputdetection,thesignal
vulnerablepopulationssuchaschildrenandcriticallyillpatients.In readoutoflowconcentrationanalytes(cytokines,tumormarkers)is
preclinical research, it enables longitudinal monitoring in experi- quite challenging, simultaneously, current protein chips rely on
mental animals with minimal physiological impact. Compared with expensive and bulky production/detection components to achieve
widely used protein detection techniques such as enzyme-linked highsensitivityandappropriatedynamicrange14,15.
immunosorbent assay (ELISA)4, chemiluminescence (CLIA)5, flow Although protein chips benefit from plasmonic enhanced sub-
cytometry(FCM)6,westernblot(WB)7,massspectrometry(MS)8,and strates,suchasplasmonicgold(pGold)slidesandthermal-annealing
single molecule array (SIMOA)9, protein chips allow for multiplex gold nanoparticle (TA-GNP) platforms, their further development is
limited by the need for expensive/large plotters, costly frames, and
specializedtechnicalpersonnel16–28.Therefore,thereisanurgentneed
todevelopadetectionplatformthatisindependentofplotters,easyto
operate, expandable, and highly sensitive, in order to lower the
thresholdforusingproteinchipsandfacilitaterapiddevelopmentand
clinicaltranslationofproteinmicroarraytechnology29.Overthepast
decade,hydrophilic-hydrophobicdropletchipshavefoundemerging
application in sample analysis within the fields of chemistry and
biology30,31. Unlike closed microfluidic systems or planar physical
confinementsystems,hydrophilic-hydrophobicdropletchipsconfine
droplets to predetermined planar regions through a pattern of
hydrophilicity and hydrophobicity32,33. This facilitates a variety of
dropletgenerationmethods,includingmanualtechniquesaswellas
automatedadditionusingspecializedliquiddispensers34.Despitethe
greatpotentialofdropletmicroarraychipsforminiaturizedanalysis,
thesinglearraystructureandnon-specificadsorptioncausedbysur-
facemodificationsposeseriouschallengestotheirdevelopmentinthe
realmofproteinchips35,36.
Here,wedevelopadroplet-baseddo-it-yourself(DBDIY)arrayon
hierarchicalTA-GNParray(TA-GNP-Array)chipsforhigh-throughput
immunoassay, via confined droplets and plasmonic enhanced near-
infrared(NIR)fluorescence.Wedesign andfabricatea seriesofTA-
GNP-Array chips utilizing photolithographic patterning and hydro-
phobicmodificationtechniques(SupplementaryFig.1).TheTA-GNP-
Array chip allows for DBDIYarrayfor high-throughput detection of
small-volume samples (Fig. 1a, b). This assay manipulates droplets
using the edge of hydrophilic-hydrophobic patterns (three-phase
contactline)onthechipsurface,andrequiresonlyapipettetocom-
pletetheworkflowfromantibodycoatingtofinaldetectionreadout.
The air plotter (air/droplets/printing area contact line replaces
expensive plotter) achieves protein array enrichment/generation
through localized protein microdroplets, simplifying the workflow.
The air frame (air/droplets/testing area contact line replaces costly
frame)incubatesmicrovolumesamplesbylocalizedsampledroplets,
flexibly adjusting sample volume and detection throughput. Impor-
tantly,thistechnologyexhibitshighsensitivityandspecificity,enables
rapidandconvenientdetection,andcanbefullycustomizedtosuitall
immunoassayneeds.Itenablesdynamicmonitoringoftencytokinesin
individualmouse(bloodcollectionat20differenttimepoints)within
40days,withtheserum/bloodvolumerequiredaslowas6µLpertest,
thus minimizing animal discomfort and extending their lifespan. In
clinicalCRPtestingon112children’speripheralbloodsamples,only1
nLofwholebloodwasneeded,with100%sensitivityandspecificity.
Thisassayisexpandedtohigh-throughputproteindetectionincell
cultureandserumsamples.Byeliminatingtheneedforplottingand
incubation equipment, the workflow for protein chips is simplified,
reducing the thresholdfor their use and making them more widely
applicableinclinicalandlaboratorytesting,particularlyforresource-
limitedsettings.

Results
Designandfabricationofthepatternedplasmonicchips
Our aim was to utilize surface patterning methods to simplify the
workflowofassaysbycontrollingconfineddroplets.Simultaneously,
plasmonic-enhanced substrate (TA-GNP) was applied to further
enhancethesensitivityofpatternedplasmonicchips.Duetothe240-
fold fluorescence enhancement of TA-GNP in the NIR region, we
developedahierarchicalpatternedplasmonicchip,namedTA-GNP-
Array29. TA-GNP-Array consisted of gold nanoisland regions and tri-
chloro (1H, 1H, 2H, 2H-perfluorooctyl) silane (PFOCTS) regions.The
goldnanoislandspossessedabundantnanogaps,whichfacilitatedthe
amplification of fluorescence signals when the target fluorophores
wereplacedwithinthesedenselycoupledelectromagneticnanogaps,
therebyimprovingdetectionsensitivity(SupplementaryFig.1c,d).The
staticwatercontactangleofthehydrophobicPFOCTSregion(106.1°)
wasgreaterthanthatofthegoldnanoparticleislandregion(46.6°),
enablingtheconfinementofdroplets.
Tofacilitatemultiplexeddetectionofmultiplesamples/analytes,
wefunctionallydividedtheTA-GNP-Arrayintofourmodules:module1
wasthechip,module2wasthetestingarea,module3wastheprinting
area,andmodule4wasthesandwichstructurethatcorrespondsto
detection. Here, we presented a TA-GNP-Array capable of accom-
modating 24 samples and 12 analytes, which was divided into 24
testing areas, with each testing area containing 12 printing areas,
incorporating 4 spots within each printing region to enhance the
parallelismofdetection(Fig.1a).Forpersonalizedcustomization,the
dimensionofthedetectionarea,thenumberofprintingarea,andthe
immunesandwichsystemcanbeflexiblyconfiguredbasedondetec-
tionrequirementsandsamplevolume.Weshoweddifferentdesignsof
theTA-GNP-Array,withthenumberofsamplesgraduallyincreasing
fromthetoptothebottom,whilethenumberofanalytesandsample
volumegraduallydecreasing(Fig.1b).

DevelopmentoftheDBDIYarrayonTA-GNP-Array
We developed a DBDIY array on TA-GNP-Array. A pipette gun was
employed to dispense 0.2µL of various capture antibodies (CAb)
microdropletsintoeachairplotter(Fig.1candSupplementaryFig.2a-
c).As the CAb microdroplets evaporated, antibody enrichment and
array preparation were achieved. By utilizing the spatial position
information of the air plotter array, multi-analyte detection was
achieved.Followingtheblockingandmicro-samplingprocesses,30µL
ofdiversesamplesolutionswerepipettedintoeachairframe(Fig.1d).
Subsequently, biotinylated detection antibody (DAb-biotin) and
IRDye800CWlabeledstreptavidin(SA-IRDye800CW)wereintroduced
tocompletethespecificrecognitionandfluorescentlabeling(Fig.1e).
In contrast to traditional protein chip technologies, the air plotter
replacedexpensive/bulkyplotterbyconfiningproteinmicrodroplets,
whiletheairframesubstitutedcostlyframesbylimitingsampledro-
plets.TheDBDIYarrayenabledthepreparationofproteinmicroarrays
of various sizes, shapes, and letters, demonstrating good stability.
(SupplementaryFig.2d-g,SupplementaryFig.3,andSupplementary
Fig.4).Notably,theDBDIYarrayrequiredonlyapipettegunforthe
preparationofproteinmicroarrays,aswellasfortheincubationand
labelingofthesamplestobetested(Fig.1f,g,SupplementaryFig.5,
andSupplementaryMovie1-3).
Wenextevaluatedmouseinterleukin-6(mIL-6)arraysonTA-GNP-
Arrayalongsidetraditionalproteinchips.Gradientconcentrationsof
CAbfromanuncoatedELISAkit(250Xstock)werearrayedonglass,
TA-GNP, and TA-GNP-Array substrates, followed by mIL-6 detection
(Fig.1h).TheoptimalCAbconcentrationwasdeterminedtobe5Xfor
the DBDIY-fabricated TA-GNP-Array, compared to 50X for Nano-
Plotter-printedarraysonglassandTA-GNP.Notably,bothTA-GNPand
TA-GNP-Array exhibited substantiallyhigher fluorescence intensities
thantheglasssubstrate,consistentwiththesignalamplificationeffect
ofgoldnanoislands(Fig.1i,j).Remarkably,evenata10-foldlowerCAb
concentration, the TA-GNP-Array achieved a better detection limit
thantraditionalchips(Fig.1k).
AsimilaradvantagewasobservedforCRParrays:theDBDIYsys-
tem reduced the CAb working concentration from 50μgmL⁻¹ to
5μgmL⁻¹whilemaintainingatotalCAbmassof1ngperbiomarker,a
valuecomparabletocommercialplotters(SupplementaryTable1).In
addition,theDBDIYarrayprovidedsuperiorcontroloverspotsizeand
spacingrelativetoconventionalplatforms(SupplementaryFig.6).We
attribute this overall enhancement to the surface modifications
introducedduringpatterning,whichimprovetheefficiencyofprotein
immobilization(SupplementaryFig.7).

Multi-cytokinedetectioninbloodandserumoflipopoly-
saccharide(LPS)-injectedmice
TodemonstratethemultiplexingcapabilityoftheDBDIYarray,mice
wereinjectedwithLPStoinducechangesinvariouscytokines.Two
hours post-injection, blood samples were collected from the retro-
orbital sinus of both control (n=12) and LPS-injected (n=12) mice
using capillarytubes. Portions of the blood samples wereplaced in
anticoagulanttubes,whileotherswere centrifugedtoisolateserum
(Fig.2a).Toenablethedetectionofmultipleanalyteswithinthesame
air frame, it was criticalto prevent cross-reactivity among different
antibodypairs.Initially,wepreparedCAbarraysfortencytokines,the
layout of which was depicted in Fig. 2b. Following blocking and
washing, standards of interleukin-1 beta (IL-1β), interleukin-2 (IL-2),
interleukin-4 (IL-4), IL-6, interleukin-10 (IL-10), interleukin-12 (IL-12),
interleukin-17A (IL-17A), tumor necrosis factor-alpha (TNF-α),
interferon-gamma(IFN-γ),andC-Cmotifchemokineligand2(CCL2)
were added to different air frames for incubation. Subsequently, a
mixtureofallDAb-biotinwasaddedforspecificidentification.Finally,
SA-IRDye800CWwasaddedforfluorescentlabeling.Notably,onlythe
correspondingairplotterexhibitedbrightfluorescentsignals(Fig.2c,
d).TheseresultsrobustlydemonstratedthecapabilityoftheDBDIY
array to analyze 10 cytokines with high specificity in a multiplexed
mannerontheTA-GNP-Array.
Understandingthedistributionofcytokinesinwholebloodand
serumiscrucialforelucidatingimmuneresponsesanddeveloping
diagnostic tools. We thus investigated the differences in the
expression of 10 cytokines in the whole blood and serum of LPS-
injectedmice.Followingbloodcollection,wholebloodunderwenta
single freeze-thaw cycle to release intracellular cytokines. Subse-
quently,6µLofwholebloodand6µLofserumfromthesamemouse
wereeachdilutedfivetimesin5%bovineserumalbumin(BSA)and
placedintoairframesfordetection.Digitalphotographsindicated
thattheairframeseffectivelyconfinedthesamplesforbothwhole
blood and serum (Fig. 2e). Fluorescence images and fluorescence
intensityrevealedsignificantdifferencesintheexpressionlevelsof
IL-6,andCCL2betweencontrolandLPSgroupsinbothserumand
whole blood samples. Notably, TNF-α expression was significantly
differentonlyinserumsamples(Fig.2f–handSupplementaryFig.8).
In addition, the background signal in whole blood from the same
group of mice was higher than that in serum, likely due to non-
specific adsorption arising from the complex matrix environment
presentinwholeblood.However,thesignal-to-backgroundratiofor
both whole blood and serum did not show significant differences
within the same group of mice, indicating the feasibility of con-
ductingassayswithwholeblood(SupplementaryFig.9).Ourstrat-
egyprovidedinsightsintoimmuneresponsesandpotentialavenues
fordiagnosticdevelopment.TheDBDIYarrayrequiresonlyasmall
amountofsampletodetectmultiplecytokines,makingitpromising
for dynamic monitoring of cytokine levels in the serum of the
samemouse.

Dynamicmonitoringofmultiplexedcytokinesinserumofmice
withinflammationandtumor
ToillustratethedynamicmonitoringcapabilityoftheDBDIYarray,we
conductedanextensiveinvestigationintoserumcytokinefluctuations
usingtwodistinctmousemodels:aninflammatoryboweldisease(IBD)
modelanda4T1(mousebreastcancercells)tumormodel.FortheIBD
model, acute colitis was induced in mice by administering feeding
watersupplementedwith3%dextransulfatesodiumsalt(DSS)fora
period of 7 days. Blood samples were micro-collected via orbital
puncturefromboththecontrolgroup(n=3)andtheDSSgroup(n=3)
atdesignatedtimepoints:days1,3,5and7(Fig.3a).Post-collection,
thebloodsamplesweresubjectedtocentrifugationtoseparatethe
serum,fromwhich6µLwasextractedforanalysis.Atotalof10cyto-
kines were quantified using the DBDIY array. For each biological
sample,measurementswereperformedinquadruplicatespots,with
the final value representing the mean after excluding the highest
outlier to ensure reliability. Fluorescence images and heat maps
revealedthatcytokinelevelsinthecontrolgroupexhibitedminimal
variationacrossthedifferenttimepoints.Incontrast,theDSSgroup
demonstrated a marked increase in fluorescence signals, with
particularemphasisonthecytokinesIL-6andIFN-γ,whichshoweda
progressiveenhancementthroughoutthemonitoringperiod(Fig.3b,c).
BytheseventhdayofDSSadministration,IFN-γlevelsintheDSSgroup
weresignificantlyelevatedcomparedtothoseinthecontrolgroup.The
remarked elevation of IFN-γ was noteworthy, as it may trigger the
releaseofadditionalinflammatoryfactors,indicatingafurtherexacer-
bation of the inflammatory state within the intestinal environment
(SupplementaryFig.10).
In contrast to the acute inflammatory response observed in the
enteritismodel,theserumcytokinealterationsintumor-bearingmice
requireaprolongedobservationperiodforaccurateassessment.Tra-
ditionaldetectionmethodsrequirealargevolumeofserum,makingit
impossibletoconductbloodsamplingandmonitoringatmultipletime
pointsfromthesamemouse.Toestablishanin-situbreasttumormodel,
weinjected5×1064T1cellsintothemammaryfatpadofBALB/cmice.
Followinga21-dayincubationperiodpost-injection,onecohortofthe
tumor-bearingmicereceiveddoxorubicintreatmentviatailveininjec-
tion,administeredthreetimesatintervalsofoneday.Bloodsamples
werecollectedfromcontrol,tumor-bearing,andtreatedmiceeverytwo
days,resultinginatotalof20consecutivesamplescollectedovera40-
dayobservationperiod(Fig.3d).Remarkably,allmiceremainedalive
throughout the entire monitoring period. The results indicated that
serumcytokinelevelsinthecontrolmouseshowednosignificantfluc-
tuations, whereas the tumor mouse exhibited a steady increase in
multiplecytokinesovertime.Interestingly,thetreatedmouseinitially
demonstratedanincreaseinserumcytokinelevels,followedbyasub-
sequentdecline(Fig.3eandSupplementaryFig.11).Thepresenceofthe
tumor was associated with increased IL-1β, suggesting active inflam-
mation,whilethetumormicroenvironmentappearedtopromoteaTh2-
skewedimmuneresponseevidencedbystableIL-12levels(Fig.3f,g).
Critically, the expanded cohort (n=3 per group) in the 24-day study
confirmedthereproducibilityofthecytokinedynamicswhilerevealing
substantial inter-individual variations (Supplementary Fig. 12). This
capacitytoresolvesubject-specifictrajectoriesrepresentsakeyadvan-
tage of our longitudinal monitoring approach over traditional group-
meananalyses.
Collectively,thesestudiesestablishtheDBDIYarrayasametho-
dological platform for longitudinal biomarker monitoring, enabling
insights into dynamic immune responses across different disease
models.Theabilitytotrackcytokinefluctuationsovertimewithinthe
sameanimalsprovidesapowerfultoolforinvestigatinginflammatory
mechanismsandtherapeuticinterventions,withparticularvaluefor
studies where individual trajectory mapping and minimal sample
volumesarecriticalconsiderations.

DetectionofCRPinchildren’speripheralblood
TestingforCRPcanassistdoctorsinfastdeterminingwhetherachild
hasaninfectionandtheinfectioniscausedbybacterial,viral,ordueto
other inflammatory diseases. Given that the total blood volume in
children is relatively small, excessive blood collection can lead to
anemia orheightenedpainandpsychologicalstress.Therefore,per-
ipheralwholebloodtestingisparticularlyimportantinpediatriccare.
Tofurtherreducethesamplevolume,theTA-GNP-Arrayof80samples
and4analyteswasselectedtodetectCRPlevelintheperipheralblood
of children. First, the child’s whole peripheral blood was diluted
10,000-foldandincubatedinablockedairframewithprintedCAb.
Afterincubation,thesampleswerecleaned,andIRDye800CW-labeled
DAbwasaddedforspecificidentification.Finally,fluorescencesignals
from the air plotter array were scanned, corresponding to the CRP
levels(Fig.4a).Notably,only1nLofwholebloodwassufficientforthe
entire process, with accurate detection of CRP completed
within1hour.
ToestablishtheanalyticalperformanceoftheDBDIYplatform,we
first generated a calibration curve using CRP standards at varying
concentrations.Boththefluorescenceimagesandthestandardcurve
confirmedhighsensitivity,withacalculatedlimitofdetection(LOD)of
9.573pgmL⁻¹andalimitofquantification(LOQ)of20.273pgmL⁻¹,
demonstratingitswidedynamicrange(Fig.4b,c).Wethenvalidated
itsquantitativedetectioncapabilityusing112peripheralbloodsamples
prospectivelycollectedfromchildrenwithsuspectedinfectionacross
multipleclinicaldepartments,includingpediatricrespiratory,pedia-
tric emergency, neonatology, pediatric ICU, pediatric clinic, and
pediatric gastroenterology (Supplementary Data 1). The study was
conductedinablindedmanner.Tominimizebiasintroducedbydif-
ferences in reference standards, we constructed a calibration curve
using samples with known clinical values, thereby deriving con-
centration results traceable to the clinical context. Following
unblinding,75sampleswereclassifiedasCRP-positiveand37asCRP-
negativebytheclinicaldryfluorescenceimmunoassay(DFIA).Com-
pared against this clinical classification, the DBDIYarrayshowedno
falsepositivesorfalsenegatives,achieving100%sensitivityandspe-
cificity(95%CI:95.2%to100%)(Fig.4d).Thefluorescencesignalsfrom
strongpositivesamples(#76,#37,and#36)werenotablyhigh,while
signalsfromweakpositivesamples(#46,#84,and#28)approached
the critical threshold. Conversely, negative samples (#38, #39, and
#78)exhibitedextremelylowfluorescencesignals(Fig.4e).Notably,
evenwhentheCRPlevelswerebelow0.5μgmL−1(thedetectionlimit
of the clinicalmethod), the DBDIYarraycanstill output detectable
signals(Fig.4d).Forthecorrelationanalysis,35samplesreportingCRP
levelsbelowthelowerLODoftheclinicalmethod(<0.5μgmL⁻¹)were
excluded,asthesevalueslackedprecisenumericalquantification.A
strongcorrelation(R2=0.940)wasobservedbetweentheDBDIYarray
and the clinical method for CRP quantification (Fig. 4f and Supple-
mentaryFig.13).Bland-Altmananalysisshowedameanbiasof−1.78%,
withthemajorityofdatapointsfallingwithinthe±1.96SDlimitsof
agreement, indicating good concordance between the DBDIY array
and the DFIA (Fig. 4g).
ConsideringthatthedynamicrangeoftheDFIAislimitedto0.5-
200μgmL⁻¹, we further evaluated the DBDIY platform against a
clinical high-sensitivity CRP (hs-CRP) immunoturbidimetry assay,
which offers higher sensitivity and a broader measurable range.
Using 192 independent clinical serum samples, the correlation
coefficient between the DBDIY array and immunoturbidimetry
reached 0.973, demonstrating excellent agreement across a wide
concentration span (Fig. 4h, Supplementary Data 2, and Supple-
mentaryFig.14).Building on the high sensitivity of the platform,
whichaffordsconsiderableprotocolflexibility,wefurthershortened
the total assay time by reducing the sample dilution factor while
maintaining classification agreement with the clinical reference, as
demonstratedinSupplementaryFig.15.Toverifythegeneralityof
theplatform,NT-proBNPwasmeasuredin30clinicalserumsamples,
yielding100% sensitivity and specificity and a correlationof 0.973
with the clinical method (Supplementary Fig. 16 and Supplemen-
taryData3).
The strong concordance between raw DBDIY signals and the
concentrations determined by different clinical methods (DFIA,
immunoturbidimetry,andCLIA)evidentforbothCRPandNT‑proBNP
indicates that the platform supports semi-quantitative analysis and
longitudinal tracking without requiring a standard curve (Supple-
mentary Fig. 13 and Supplementary Fig. 17). This enables visual
assessmentofrelativetrendsdirectlyfromfluorescenceimages.Such
functionalityisparticularlyadvantageousinresource-limitedsettings
whereas in laboratory or clinical environments, quantitative results
remainreadilyaccessiblethroughstandardcalibrationanddatapro-
cessing.Collectively,theDBDIYarrayexhibitsexcellentsensitivityand
reliabilityindetectingCRPlevelsinwholebloodandserum,providing
a practical tool for pediatric infection screening and monitoring of
diseaseprogression.

Cytokineprofilinginanti-CD3/28-stimulatedCD4+Tcellsand
infectedpatientsera
The regulation of cytokine production is crucial for understanding
immune responses. We further evaluated the effects of anti-CD3/
28stimulationoncytokinesecretionbyhumanumbilicalcordblood
mononuclear cells (CBMC) and spleen cells from human immune
system(HIS)mice.AfterisolatingCBMCandspleenCD4+Tcells,we
cultured them in vitroand activated T cells using anti-CD3/28 anti-
bodies.Thesupernatantswerecollected,andsubsequentchangesin
cytokinelevelswereanalyzedonTA-GNP-Array,includingIL-2,IL-4,IL-
6,IL-10,IL-17A,TNF-α,andIFN-γ(Fig.5a).ThelayoutofCAbwasillu-
stratedinFig.5b.Toensuremulti-cytokinedetectionfromthesame
cell medium, we first verified the specificity of the seven human
cytokines. The results indicated that the TA-GNP-Array displayed
excellentspecificityforthesecytokines(Fig.5c).
ThedetectionresultsrevealedthatthelevelsofIL-2,IL-6,IL-10,IL-
17A,TNF-α,andIFN-γweresignificantlyelevatedinthesupernatantsof
anti-CD3/28-stimulated cells compared to the control group. In
contrast,IL-4levelsdidnotdifferbetweenthestimulationandcontrol
groups (Fig. 5d, e). The notableincreasein IL-2suggested a robust
responseofTcellstothestimulation.Similarly,IL-6alsoexhibiteda
significant increase, indicating the pro-inflammatory effects of the
stimulation.Furthermore,theelevationofIL-10indicatedapotential
regulatory feedback mechanism accompanying enhanced immune
activation.ThesubstantialincreaseinIL-17Areflectedashifttowards
Th17-mediatedimmuneresponses.Inaddition,bothTNF-αandIFN-γ
demonstrated significant increases in the stimulated supernatants.
Thesefindingscollectivelyillustratedtheobviouseffectsofanti-CD3/
28 stimulation on the cytokine profiles of CBMC and spleen cells,
revealingpowerfulimmuneactivation.Tocorroboratetheseresults,
we performed parallel analyses using cytometric bead array (CBA),
whichconfirmedthecytokinetrendsobtainedfromtheDBDIYarray
(Fig.5f).Theobserveddifferencesinabsolutequantificationbetween
platforms,attributabletotheirdistinctdetectionprinciplesandcali-
bration systems, did not compromise the consistent biological
responsesdetectedacrossallsevencytokines.Thisconsistencycon-
firmsthatbothmethodsprovidecomparabledynamicrangessuitable
formonitoringimmuneactivationdynamics.
Toassessclinicalrelevance,weanalyzedsevencytokinesinserum
from 12infected patients (samples were collectedin departmentof
infectiousdisease)and12non-infectedcontrols(Fig.5g,Supplemen-
taryData 4andSupplementaryFig.18).Infection cohorts exhibited
significantlyelevatedIL-6,IL-10,andIL-17Alevelscomparedtocon-
trols,withnodifferencesinIL-2,IL-4,TNF-α,andIFN-γ(Fig.5h).This
patternwaspartiallymirroredinvitrostimulationprofiles,suggesting
shared inflammatory pathways in clinical infections and antibody-
drivenimmuneactivation.

Methods
FabricationofTA-GNP
A glass slide was immersed in a solution containing 40nm gold
nanoparticles.Toestablishawater/oilinterface,n-hexanewasadded
tothesolution.Ethanolwasthencarefullyinjectedalongthewallofthe
container.Asthevolumeofethanolincreased,adensemonolayerfilm
ofgoldnanoparticlesgraduallyassembledatthewater/oilinterface.
Followingthis,thesolutionwasslowlyreleasedfromthebottomofthe
container,allowingthegoldnanoparticlemonolayertobetransferred
ontotheglassslideastheliquidleveldecreased.Subsequently,the
substrateunderwentthermalannealinginatubularfurnaceunderan
argonatmosphere,withanannealingtemperaturesetto300°C.The
thermal annealing process consisted of an initial 10-minute flow of
argongas,followedbyaheatingrateof10°C/mintoreachthetarget
temperature, which was maintained for 1hour before the system
automaticallycooledtoroomtemperature.

FabricationofTA-GNP-Array
The positive photoresist (Kempur Microelectronics) was spin-coated
ontoaTA-GNPsubstrateataspeedof3000rpmfor30seconds.The
coatedsubstratewasthenbakedinanovenat60°Cfor1hour.After
cooling, a photomask was placed over the substrate, and it was
exposedtoUVlight.Followingexposure,thesubstratewasdeveloped
usingadevelopersolution.Next,thesubstratewasimmersedinagold
etchant(SigmaAldrich)for5seconds,rinsed,andblow-dried.Thechip
wasthentreatedwithoxygenplasmafor10minutes.Subsequently,the
substratewasplacedinaglasscontainerforliquid-phasegraftingof
PFOCTS(SigmaAldrich)for5minutes,usingn-hexaneasthesolventat
avolumeratioof1:20.Finally,thesubstratewaswashedwithethanol
andblow-driedwithnitrogen.

SA/DAbconjugatedwithIRDye800CW
NHS-IRDye800CW (LI-COR Biosciences) was mixed with SA (Sigma
Aldrich)/DAb (Abcam) at a molar ratio of 20:1 to avoid light for
1.5hours,andwashedinanultrafiltrationtube(Sartorius)withPBSfor
3timestoobtainfluorescentlylabeledSA/DAb-IRDye800CW.

DetectionofmIL-6onglass,TA-GNP,andTA-GNP-Array
CAb, mIL-6, and DAb were derived from mIL-6 uncoated ELISA kit
(Thermo Fisher), and the concentration of the CAb and DAb stock
solutionswereboth250X.5nLofCAb(10,20,50,100X)wasprintedby
Nano-PlotteronglassandTA-GNP.0.2μLofCAb(2,5,10,20X)was
addedtoeachairplotteronTA-GNP-Arrayusingapipette.Thechips
werethenallowedtodryatroomtemperaturefor2hours,afterwhich
the glass and TA-GNP were assembled using frames (Nirmidas Bio-
tech). Afterward, 80μL of 5% BSA (Sigma Aldrich) was added and
sealed for 30minutes.The chips were washed twicewith PBST and
oncewithPBS.Next,60μLofthemIL-6(500pgmL-1)wasaddedfor
overnight incubation. Following incubation, the chips were washed
threetimeswithPBSTandoncewithPBS.Subsequently,60μLofDAb-
biotin(1.5X)wasaddedandincubatedfor1hour.Finally,60μLofSA-
IRDye800CW(10nM)wasaddedandincubatedfor30minutes.The
chips were washed three times with PBST and once with PBS, then
immersedindeionizedwateranddriedwithnitrogenuponremoval.

DetectionofCRPonglass,TA-GNP,andTA-GNP-Array
5 nL of CAb (10, 20, 50, 100μgmL-1, Abcam) wasprinted by Nano-
PlotteronglassandTA-GNP.0.2μLofCAb(2,5,10,20μgmL-1)was
addedtoeachairplotteronTA-GNP-Arrayusingapipette.Theslides
wereallowedtodryatroomtemperaturefor2hours,afterwhichthe
glassandTA-GNPwereassembledusingframes.Afterthis,80μLof5%
BSAwasaddedandsealedfor30minutes.Thechipswerethenwashed
twicewithPBSTandoncewithPBS.Subsequently,60μLoftheCRP
(500 pM, Abcam) to be detected was added and incubated for
30minutes.ThechipswerewashedthreetimeswithPBSTandonce
with PBS. Next, 60μL ofDAb-IRDye800CW (10nM)wasadded and
incubated for 30minutes. The chips were washed three times with
PBSTandoncewithPBS,thenimmersedindeionizedwateranddried
withnitrogenuponremoval.

DetectionofmousecytokinesonTA-GNP-Array
CAb and DAb were derived from the mouse uncoated ELISA kit
(ThermoFisher)ofIL-1β,IL-2,IL-4,IL-6,IL-10,IL-12,IL-17A,TNF-α,IFN-γ,
andCCL2.TheconcentrationoftheCAbandDAbstocksolutionwere
both250X.TodetectmousecytokinesontheTA-GNP-Array,0.2μLof
CAb(5X)wasaddedtoeachairplotterusingapipette.Thechipwas
thenallowedtodryatroomtemperaturefor2hours.Afterward,80μL
of5%BSAwasaddedandsealedfor30minutes.Thechipwaswashed
twicewithPBSTandoncewithPBS.Next,30μLofthe5-folddiluted
sample(preparedfrom6μLofserum/blood)wasaddedforovernight
incubation. Following incubation, the chip was washed three times
withPBSTandoncewithPBS.Subsequently,60μLofDAb-biotin(1.5X)
wasaddedandincubatedfor1hour.Finally,60μLofSA-IRDye800CW
(10nM)wasaddedandincubatedfor30minutes.Thechipwaswashed
threetimeswithPBSTandoncewithPBS,thenimmersedindeionized
wateranddriedwithnitrogenuponremoval.

DetectionofhumancytokinesonTA-GNP-Array
CAb and DAb were derived from the human uncoated ELISA kit
(ThermoFisher)ofIL-2,IL-4,IL-6,IL-10,IL-17A,TNF-α,andIFN-γ.The
concentrationoftheCAbandDAbstocksolutionwereboth250X.For
thedetectionofhumancytokinesontheTA-GNP-Arraychip,0.2μLof
CAb(10X)wasaddedtoeachairplotterusingapipetteandallowedto
dryatroomtemperaturefor2hours.Followingthis,80μLof5%BSA
was added, and the chip was sealed for 30minutes. The chip was
subsequentlywashedtwicewithPBSTandoncewithPBS.Then,30μL
ofthe2-folddilutedsample(preparedfrom15μLofserum/cellcul-
ture)wasaddedandincubatedfor2hours.Afterincubation,thechip
waswashedthreetimeswithPBSTandoncewithPBS.Next,60μLof
DAb-biotin(1.5X)wasaddedandincubatedfor1hour.Finally,60μLof
SA-IRDye800CW (10nM) was added and incubated for 30minutes.
ThechipwaswashedthreetimeswithPBSTandoncewithPBS,then
immersedindeionizedwateranddriedwithnitrogenuponremoval.

DetectionofCRPonTA-GNP-Array
TodetectCRPontheTA-GNP-Arraychip,0.2μLofCAb(5μgmL−1)was
addedtoeachairplotterusingapipetteandallowedtodryatroom
temperaturefor2hours.Afterthis,20μLof5%BSAwasaddedand
sealedfor30minutes.ThechipwasthenwashedtwicewithPBSTand
oncewithPBS.Subsequently,10μLofthesample(10,000-folddilu-
tion)tobedetectedwasaddedandincubatedfor30minutes.Thechip
waswashedthreetimeswithPBSTandoncewithPBS.Next,10μLof
DAb-IRDye800CW(10nM)wasaddedandincubatedfor30minutes.
ThechipwaswashedthreetimeswithPBSTandoncewithPBS,then
immersedindeionizedwateranddriedwithnitrogenuponremoval.

AdministrationofLPSinC57BL/6Mice
Twenty-four C57BL/6 mice were utilized. The mice were randomly
assignedtoreceiveintraperitonealinjectionsofLPS(5mgkg−1,Sigma
Aldrich) or an equivalent volume of sterile saline. Two hours post-
injection,80μLofbloodsampleswerecollectedfromtheretro-orbital
sinus ofeachmouseusingcapillary tubes. Ofthe collectedsample,
20μL was placed into an anticoagulant tube, while the remaining
bloodsamplewasallowedtositat4°Cforonehour.Thesamplewas
thencentrifugedat478×gfor10minutestoobtainserumfromthe
supernatant.

EstablishmentoftheIBDmodelinC57BL/6mice
SixC57BL/6micewereutilized,ofwhichthreewerecontinuouslyfed
3%DSS,whiletheremainingthreewereprovidedwithregularultra-
purewaterforsevendays.Thedrinkingwaterwaschangedeverytwo
days,during which the remaining water in the drinking bottles was
weighedtoensurethatthewaterintakeremainedconsistentbetween
thetwogroups.Bloodsampleswerecollectedfromtheretro-orbital
venousplexusofeachmouseeverytwodays,with60µLtakenateach
sampling.Thebloodsampleswereallowedtostandat4°Cforone
hour,followedbycentrifugationat478×gfor10minutestoobtainthe
serum, which was subsequently stored at −20°C. Throughout the
seven-day observation period, four samples were collected from
eachmouse.

Establishmentofthe4T1tumormodelinBALB/cmice
The4T1tumormodelwasestablishedinBALB/cmicethroughortho-
topicinjectionof5×10⁶cellsintothemammaryfatpad.Thestudy
consistedoftwosequentialphaseswithdistinctexperimentaldesigns.
Intheinitialfeasibilitystudy,threecohorts(onemousepercohort)
wereutilized.Twocohortsreceivedtumorcellinjectionstoestablish
the 4T1 model, while one cohort of tumor-bearing mice received
doxorubicintreatment(DOX,2mgkg⁻¹,200μL)viatailveininjection
beginningat21dayspost-injection.Thetreatmentwasadministered
everyotherdayforatotalofthreedoses.Thiscohortwasmonitored
for40dayswithbloodcollectioneverytwodays.Inthesubsequent
expandedvalidationstudy,threecohorts(threemicepercohort)were
employed. Two cohorts received tumor cell injections, with one
tumor-bearingcohortreceivingDOXtreatment(2mgkg⁻¹,200μL)via
tailveininjectionat15dayspost-injection,administeredeveryother
dayforthreedoses.Thiscohortwasmonitoredfor24dayswithblood
collection every two days. For both studies, blood samples (60μL)
werecollectedfromtheretro-orbitalsinususingcapillarytubes.The
sampleswereprocessedat4°Cforonehourbeforecentrifugationat
478×gfor10minutestoobtainserum,whichwasstoredat−20°C.

Anti-CD3/28antibodiesstimulationofCBMCandspleenCD4+
Tcells
Umbilicalcordbloodwascollectedanddiluted2-foldwithPBS,then
mixed with human lymphocyte isolation solution at a 1:1 ratio. The
mixturewascentrifugedat796×gfor30minutesatroomtempera-
ture, with a gradual increase and decrease in speed to prevent dis-
ruption of the cell layers. The white blood cell layer was carefully
collected and subjected to a second centrifugation at 575×g for
10minutes,afterwhichthesupernatantwasdiscarded.Thecellpellet
wasthenresuspendedin2mLofredbloodcelllysisbufferandincu-
batedonicefor5minutestolyseremainingredbloodcells.Subse-
quently, the solution was diluted with 15mL of PBS. Following this,
cellswerepelletedandwashedtwicewithPBS.Finally,thepelletwas
resuspendedin1mLofPBSforcellcounting.
Spleensfromhumanizedmicewerehomogenized,theresultant
cellsuspensionwasfilteredthrougha70µmfilter,followedbycen-
trifugation at 542×gfor 5minutes, discarding the supernatant. The
cellpelletunderwentredbloodcelllysisusing2mLofredbloodcell
lysisbuffer,withasubsequenticebathfor5minutesanddilutionwith
15mL of PBS. Subsequently, the cells were centrifuged and washed
twice in PBS. The final pellet was resuspended in 1mL of PBS for
counting.
For magnetic beads sorting of CD4+ T cells, 1×107 cells were
resuspendedin80µLofMACSbuffer(PBSsupplementedwith0.5%
BSAand2mMEDTA)andincubatedwith20µLofCD4MicroBeads
(Miltenyi)at4°Cinthedarkfor15minutes.Afterincubation,thecells
werewashedwithMACSbufferandcentrifugedat542×gfor5min-
utes,discarding the supernatant. The labeled cells werethen resus-
pended in 1mL of MACS buffer and loaded onto a pre-treated
magneticseparationcolumn.Thecolumnwaswashedthreetimeswith
1mLofbuffereachtime.Afterwashing,theseparationcolumnwas
removed,and1mLofbufferwasaddedtoelutethepositivecellsusing
aplunger.
ToassessthepurityoftheisolatedCD4+Tcells,2 ×105cellswere
stainedwithCD45andCD4antibodiesandincubatedat4°Cinthe
darkfor30minutes.FollowingPBSwashing,the purityoftheCD4+
Tcellswasanalyzedusingflowcytometry(CytekAurora).Oncethe
puritywasconfirmedtobegreaterthan95%,5×104cellswerecultured
ina96-wellU-shapedplatewith5µLofaCD3/CD28activator(Immu-
noCult™HumanCD3/CD28TCellActivator,StemCell)and195µLof
complete medium (RPMI 1640supplemented with 10% fetal bovine
serum).Thecellswerethoroughlymixedandculturedfor5days,after
whichthesupernatantwascollectedforfurtheranalysis.

Characterizationanddataanalysis
TheSEMimageswereobtainedusingaJEOL-JSM-6700Ffieldemission
scanningelectronmicroscope.TheAFMimagewastakenbyBruker’s
Dimension FastScan atomic force microscope. Digital photos and
videoswerecapturedwithanApplesmartphone.Theproteinmicro-
arrayswerepreparedusingaNano-Plotter2.1,witheachproteinspot
havingavolumeof5nL.Contactanglemeasurementswereconducted
using a Data Physics OCA instrument. Fluorescence images were
acquiredwithaMidaScanscanner(NirmidasBiotechInc.),utilizinga
785nmwavelength,anintensitysettingof10%,andaresolutionof10
μm. The mean fluorescence intensity (MFI) signals from four spots
within each air plotter were quantified using MidaScan software
(v2.0.0).Fluorescenceintensityvaluesarereportedinarbitraryunits
(arb. units). Data were subsequently processed and analyzed with
Origin2025.Forstatisticalanalysis,thespotwiththehighestdeviation
wasexcluded,andtheaverageMFIwascalculatedfromtheremaining
threespots.TheaverageMFIfromthelastairplotterwithineachair
framewasdesignatedasthebackgroundsignalforthatsamplewell.

Statisticsandreproducibility
Nostatisticalmethodwasusedtopredeterminesamplesizes,which
were chosen based on common practice in preclinical studies and
specimenavailabilityforclinicalcohorts.Nodatawereexcludedfrom
theanalysesexceptforpredefinedremovalofthemostdevianttech-
nicalreplicateinquadruplicatespotmeasurements.Investigatorswere
notblindedtogroupallocationduringanimalexperimentsbutwere
blindedduringdataanalysisforclinicalvalidation.Dataarepresented
as mean values±SD. All statistical comparisons, specific tests used,
and exact P-values are reported in the relevant figure legends and
Source Data file. The reproducibility of representative images was
confirmedinaminimumofthreeindependentexperiments.

Blindingprocedureandcutoffdetermination
Tominimizebias,allanalyseswereconductedinablindedmanner.
TheresearchersperformingtheDBDIYarrayassaysanddataanalysis
were unaware of the sample status (positive or negative) and the
resultsfromtheclinicalreferencemethods.Similarly,clinicallabora-
torytechniciansconductingthestandardDFIA,immunoturbidimetry,
andCLIAwereunawareoftheresultsgeneratedbytheDBDIYplat-
form.Allexperimentaldatawerecollectedindependently,andblind-
ing was maintained until all assays and initial data processing were
completed. Afterward, results were unblinded for final comparative
analysis.Sampleswereexcludedfromthefinalcomparativeanalysisif
they had insufficient volume for both analytical methods or if they
showedgrosshemolysis.
ThediagnosticcutofffortheDBDIYarraywasdeterminedbased
ontheclinicalclassifications(positiveornegative)establishedbythe
reference methods. Under the blinded protocol, ROC analysis was
performed toidentifytheraw fluorescence signalcorrespondingto
optimalclassificationperformance.Inthepresentcohort,thethresh-
oldthatyielded100%sensitivityand100%specificitycoincidedwith
thepointofmaximumYouden’sindex.Toensurestatisticalrobustness
and generalizability across assay conditions and future studies, we
adopted this threshold, corresponding to the maximum Youden’s
index,asthereportedcutoff.Thiswidelyacceptedapproachprovides
abalancedandresilientcriterionfordiagnosticthresholdselection,
regardlessofsamplesize.

Ethicalstatement
AllstudiesinvolvinghumanparticipantswereapprovedbytheEthics
Committee of the First Hospital of Jilin University (22K006-002).
Writteninformedconsentwasobtainedfromalladultparticipants.For
pediatricparticipants,writteninformedconsentwasprovidedbytheir
parentsorlegalguardians.Writteninformedconsentwasobtainedto
publish the potentially identifying individual-level data in Supple-
mentaryData 1-4. Allclinical samples (serum and peripheral blood)
wereresidualspecimensobtainedaftercompletionofroutineclinical
testing. All samples were fully anonymized prior to analysis in this
researchstudy.
Animal experiments were conducted under the institutional
guidelines and were approved by the Experimental Animal Ethical
CommitteeofTheFirstHospitalofJilinUniversity(20210642).Mice
werehousedunderstandardspecificpathogen-freeconditionsatan
ambienttemperatureof20-22°C,with35-45%relativehumidity,anda
12-hlight/darkcycle.Bedding,nestingmaterial,food,andwaterwere
providedadlibitumandwereregularlyrefreshed.Theapprovedpro-
tocolstipulatedthatthemaximalpermittedtumorburdenshouldnot
exceed2000mm³involumeor15mmindiameter.Thislimitwasnot
exceededinanyanimalduringthestudy.Todemonstratethelong-
itudinalmonitoring capability ofthe DBDIY arraywhile adhering to
ethical reduction principles, we implemented a two-phase study
design that leveraged the inherent variability in individual tumor
growth kinetics. For the initial 40-day feasibility study, we selected
mice with slower tumor progression to accommodate an extended
observationwindow.Inthesubsequent24-dayexpandedvalidation,
cohortswithfaster-growingtumorswereincluded,andthemonitoring
period wasshortened. Throughoutbothphases,tumorvolume and
diameter were strictly monitored and remained within the ethically
approvedlimits.Crucially,ourmethodrequiresonlyminimalblood
volume(6µLpertimepoint).Thisenablesdense,repeatedsampling
fromthesameanimalovertime,allowingdetailedlongitudinalpro-
filingofdiseaseprogressionwithinasinglesubject.Thisdesignmini-
mizes animal distress and highlights the utility of our platform for
comprehensive studies that track the complete disease trajectory
withinanindividual.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In their paper, Yue et al. present a “droplet-based do-it-yourself” (DBDIY) protein array platform utilizing a patterned plasmonic substrate. Their approach simplifies and increases sensitivity of the multiplexed immunoassays using low sample volumes. The platform does not rely on traditional spotting and incubation but rather uses confined droplet patterning and plasmonic-enhanced near-infrared fluorescence (NIRF) to enhance signal sensitivity. The authors show some applications, including detection of cytokines in blood, within cell cultures, etc. Finally, the authors report dynamic cytokine profiling and C-reactive protein (CRP) detection from as little as 1 nL of whole blood.\n\nThe study is technically solid, with a well-designed experiments and good validation. The manuscript contributes to the field of miniaturized immunoassays and has potential relevance for translational applications, especially in resource-limited diagnostic environments. I therefore can recommend the manuscript for publication, provided the following concerns and inconsistencies have been solved:\n\n1. The authors report 100% sensitivity and specificity, but fail to provide confidence intervals. Furthermore, the reported R² value of 90.3% suggests the presence of discrepancies. Please calculate and include confidence intervals and clarify how statistical robustness was evaluated.\n2. It is unclear how the analytical detection limit for CRP was determined. Please describe the methodology used to establish the detection limit, including any calibration curves and statistical thresholds.\n3. Blood volume discrepancy in abstract (\"with a required serum/blood volume of only 6 µL per test...\") vs methods (\"60 µL taken at each sampling via retro-orbital bleeding\"). Resolve the apparent inconsistency between the stated minimal volume requirement and the actual sampling protocol.\n4. The ROC curve was generated after excluding 24 samples. The justification (\"clinical method did not provide clear values\") is vague. Recommendation: Provide a more detailed explanation of the exclusion criteria and how they may impact the interpretation of diagnostic performance.\n5. It is currently unclear whether the fluorescence intensity values reported in Figure 5 can be quantitatively converted into analyte concentrations. The authors should clarify whether fluorescence intensity values can be directly converted to absolute concentrations (e.g., pg/mL). If conversion to pg/mL is possible, present a representative example (e.g., calibration curve used for CRP measurements, including the concentration points, curve fit (e.g., linear, 4-parameter logistic), and associated statistics (R², LOD, LOQ)). If such conversion is not possible with the current data, this should be explicitly stated and discussed as a limitation.\n6. Supplementary tables lack units for CRP. The CRP cut-off used in Fig. 4b is not explained.\nThe authors should clearly define the units and describe how clinical or analytical thresholds were determined. Define the threshold values for presented clinical applications and their basis (e.g., literature, ROC-derived, clinical standard)\n7. What equipment was used for pipetting (e.g., Nanoplotter), see Fig 4? Please discuss reproducibility and potential variability across arrays.\n8. Include a reference or detailed methodology explaining how the amplification was quantified (the manuscript reports a 240-fold signal amplification using TA-GNP).\n9. Blurred Spots in Fig. 1i: Are the spots still evaluable despite blurring? Is there supporting data on reproducibility or signal consistency? Address the reliability of such spots and whether they influence quantitation.\n10. The sentence \"It was found that DBDIY not only reduced the concentration of CAb but also maintained a total mass of CAb comparable to commercial plotters\" is unclear. Clarify whether quantification was performed and specify the values if available.\n11. The method and experimental details about the fabrication of the array are not complete and need to described in detail. Silanization process is either not described or wrong (“trifluoro (1H, 1H, 2H, 2H-perfluorooctyl) silane (PFOCTS) (L.98)” should be probably trichloro... silane). The authors should describe in detail how the fabrication procedure was done. Including silanization etc.including silanization, patterning etc.\n12. The manuscript mentions \"low production costs\" and minimal need for specialized personnel. No cost comparison to commercial systems is provided. Pipetting 0.2 µL across ~100 spots requires skills—can this realistically be performed by non-specialists? The authors should provide a cost analysis and discuss the operational feasibility in real clinical laboratory or field settings.\n13. Plasmonic-enhanced NIRF is a highly specialized technology, requiring sophisticated equipment. The DIY nature of the array seems at odds with the complexity of the readout system. The authors should either rename the method or explain and discuss the practicality of implementing this platform in low-resource or point-of-care settings.\n14. Most clinical laboratories use quantitative high-sensitivity CRP (hsCRP) assays based on immunoturbidimetry, ELISA, or nephelometry, which report concentrations in mg/L or pg/mL. The developed CRP assay is compared against a qualitative reference assay. Without comparing the DBDIY assay to such established quantitative methods, it is difficult to assess its clinical relevance, especially for applications like cardiovascular risk assessment or sepsis monitoring, where precise CRP levels are critical.\nProvide justification for this comparison, or if possible, re-analyze the CRP data using a quantitative clinical reference method to provide a more meaningful benchmark. Clearly report the analytical performance parameters of the platform: LOD, LOQ, precision (intra-/inter-assay CV), and linear range. If only a qualitative comparison is possible at this stage, clearly state this limitation and discuss its implications for future validation.\nEnglish grammar in some places of the manuscript needs to be improved. For example: “accurate measurement of high-throughput protein levels” (p 2), etc. Please check the grammar throughout the MS.\nIt should be specified what kind of “contact angle” was used in the characterization (advancing, stating, water, etc.).", "reviewer_2": "The authors should be congratulated on an interesting piece of research, which, I believe after further improvement will be a substantive contribution to the field. The work combines the enhancement of plasmonic arrays with hydrophobic/ hydrophilic interfaces to create an easy-to-use, yet sensitive platform. Both of the initial techniques are well known, however their integration is technically astute in enabling the level of control of surface properties on a plasmonic substrate. This is therefore a clever miniaturisation of a popular technique used in laboratories and serves to minimise reagent consumption.\nIn general the ideas and results presented are strong in concept, illustrated with a well-conceived assay and underpinned by strong materials engineering.\nHowever, I have a number of general and more specific suggestions.\nAs a starting point, I think the biological/clinical validation could be stronger (for example, colloidal gold immunochromatography is not a gold standard for CRP and the authors may have chosen an established ELISA). Can they clearly justify their choice?\nThere are also statistical issues throughout the paper, which are exacerbated by the small sample sizes and in many cases unclear presentation (e.g. in the figure legends).\nThere are a few major shortcomings that must be addressed before publication which include the fact that:\n(i) there is a lack of power calculations, and it is often not clear how many technical replicates were done. Is the study not under-powered? If it is this should be clearly stated and conclusions;\n(ii) the use of a ROC analysis is actually inappropriate and should be removed – these “curves” are based on a single point;\n(iiii) from a robust statistical viewpoint, the data could be re-presented using a Bland Altman analysis, with confidence intervals and error bars shown on all figures throughout\nSome specific comments relevant to each figure/experiment:\nFig 2: It seems like there are 4 mice per group? (authors need clear labels in legend). This is probably under-powered and care needs to be taken when drawing conclusions from this number. How many technical replicates were run.\nFig 3: There are no error bars, no confidence intervals, and definitely no proper statistical testing for the temporal changes. For a 40-day longitudinal study, where is the quantitative analysis of stability or drift over time? Again, this is a small sample size for this type of analysis.\nFig 4: As mentioned, colloidal gold is not a clinical gold standard for CRP, and so a comparison to this alone weakens the claims. There is no explanation for how the positive/negative thresholds were set.\nFig 5: There is missing statistical analysis for method agreement with CBA. No assessment of measurement range differences or matrix effects between platforms was performed.\nBelow are a few further points that need addressing\nAlthough the authors claim you only need a pipette, it is likely that the spotting inside the arrays is difficult by hand (and indeed in the supplementary they show some holders to do it). Although these are not expensive, but they are not ‘just a pipette’.\nIt would be useful to comment on drying of the devices for storage and testing. The use of water and the binders could denature the proteins on the surface. Is it normal to dry such surfaces without protective layers?\nThe patient studies are not described in the Methods and this will be required/important (were the studies blinded?) Ethics is stated in the acknowledgement and does not include inclusion/exclusion criteria.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Point-to-point replies to reviewers and revisions made.\nReviewer #1:\nIn their paper, Yue et al. present a “droplet-based do-it-yourself” (DBDIY) protein array platform utilizing a patterned plasmonic substrate. Their approach simplifies and increases sensitivity of the multiplexed immunoassays using low sample volumes. The platform does not rely on traditional spotting and incubation but rather uses confined droplet patterning and plasmonic-enhanced near-infrared fluorescence (NIRF) to enhance signal sensitivity. The authors show some applications, including detection of cytokines in blood, within cell cultures, etc. Finally, the authors report dynamic cytokine profiling and C-reactive protein (CRP) detection from as little as 1 nL of whole blood.\n\nThe study is technically solid, with a well-designed experiments and good validation. The manuscript contributes to the field of miniaturized immunoassays and has potential relevance for translational applications, especially in resource-limited diagnostic environments. I therefore can recommend the manuscript for publication, provided the following concerns and inconsistencies have been solved:\n1. The authors report 100% sensitivity and specificity, but fail to provide confidence intervals. Furthermore, the reported R² value of 90.3% suggests the presence of discrepancies. Please calculate and include confidence intervals and clarify how statistical robustness was evaluated.\nResponse: We thank the reviewer for these important statistical suggestions regarding confidence intervals and the interpretation of the R² value. We have addressed these points as follows:\n1. Confidence intervals for sensitivity and specificity\nWe have now calculated and included the 95% confidence intervals (CIs) for sensitivity and specificity using the Clopper-Pearson method, which is specifically recommended for binomial proportions with our sample size. For both sensitivity and specificity (50/50 correct classifications), the 95% CIs are [92.9%, 100%]. These values have been added to the Results section and the Figure 4 legend to provide a more statistically robust interpretation of our diagnostic accuracy data.\n2. Clarification on R² value and statistical robustness\nRegarding the R² value of 0.903, we appreciate the opportunity to clarify that this represents strong agreement between methods. The observed discrepancies primarily reflect the enhanced sensitivity of our DBDIY platform in the low concentration range. Specifically, for samples where the reference method approached its detection limit, our array provided more precise quantitative measurements, leading to minor deviations that actually demonstrate our method's superior performance in this critical range. This enhanced low-end sensitivity represents a key advantage rather than a limitation in method agreement.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n“The DBDIY array showed 100% sensitivity and specificity (95% CI: 92.9% to 100%).”\nIn the Revised Manuscript (Page 29), the following figure panel was refined:\n“d, The specificity and sensitivity of NT-proBNP detected by DBDIY in 29 clinical samples were 100% (95% CI: 66.37% to 100%).”\n2. It is unclear how the analytical detection limit for CRP was determined. Please describe the methodology used to establish the detection limit, including any calibration curves and statistical thresholds.\nResponse: We thank the reviewer for prompting us to clarify this important methodological detail.\nThe analytical detection limit (LOD) for CRP was determined empirically from the calibration curve.\nSpecifically, a series of CRP standard solutions at known concentrations were analyzed to generate\nthe calibration curve. The LOD was then calculated as the concentration corresponding to the mean\nfluorescence intensity of the blank samples (5% BSA) plus three times its standard deviation. This\nvalue was interpolated from the calibration curve.\nRevisions:\nIn the Revised Manuscript (Page 20), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“e, Fluorescence images corresponding to CRP standards at various concentrations. f, The\ncalibration curve for CRP standards. The limit of detection (LOD) was defined as the mean blank signal plus three times its standard deviation (3 SD), while the limit of quantification (LOQ) was defined as the mean blank signal plus ten times the standard deviation (10 SD).”\n3. Blood volume discrepancy in abstract (\"with a required serum/blood volume of only 6 µL per test\") vs methods (\"60 µL taken at each sampling via retro-orbital bleeding\"). Resolve the apparent inconsistency between the stated minimal volume requirement and the actual sampling protocol.\nResponse: We thank the reviewer for highlighting this point, which allows us to clarify the\ndistinction between the total blood volume collected per sampling event and the minimal volume\nconsumed per individual assay. The statement in the Methods, \"60 µL taken at each sampling,\" refers to the total volume of blood collected from the mouse retro-orbital sinus at a single time point. This volume was necessary to obtain sufficient serum for potential multi-analyte profiling and replicate analyses within our experimental design. In contrast, the claim in the Abstract, \"a required serum/blood volume of only 6 µL per test,\" indicates the exceptionally low volume that our DBDIY array technology actually consumes to perform a complete multiplexed assay for 10 cytokines. This means that from a single 60 µL blood draw (yielding approximately 20-30 µL of serum), we were able to conduct multiple tests or retain sample for future analysis, thereby enabling the intensive longitudinal monitoring over 40 days with 20 time points without excessively stressing the animals. We have revised the Methods section to explicitly state this distinction and avoid any potential misunderstanding.\nRevisions:\nIn the Revised Manuscript (Page 10 and Page 11), the following paragraph was refined:\n“Next, 30 μL of the 5-fold diluted sample (prepared from 6 μL of serum/blood) was added for\novernight incubation.”\n“Then, 30 μL of the 2-fold diluted sample (prepared from 15 μL of serum/cell culture) was added\nand incubated for 2 hours.”\n4. The ROC curve was generated after excluding 24 samples. The justification (\"clinical method did not provide clear values\") is vague. Recommendation: Provide a more detailed explanation of the exclusion criteria and how they may impact the interpretation of diagnostic performance.\nResponse: We thank the reviewer for pointing out the need for clarity. The exclusion of 26 samples\n(originally misstated as 24, now corrected) was necessitated by the specifications of the clinical\nreference method. For these specific samples, the dry chemiluminescence immunoassay reported\nCRP concentrations below its lower limit of detection (<0.5 μg mL⁻¹). As these values lacked precise\nnumerical quantification, they could not be included in the quantitative correlation analysis\nbetween our DBDIY array and the clinical method. This exclusion ensures the accuracy of the\ncomparative analysis, which for the fully quantifiable samples demonstrated a strong correlation\n(R² = 0.903), as now detailed in the Revised Manuscript on Page 6.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n“A strong correlation (R2 = 0.903) was observed between the DBDIY array and the clinical method\nfor CRP quantification. For this correlation analysis, 26 samples were excluded where the clinical\nmethod reported CRP levels below its lower limit of detection (<0.5 μg/mL), as these values could\nnot be precisely quantified for numerical correlation (Fig. 4d).”\n5. It is currently unclear whether the fluorescence intensity values reported in Figure 5 can be quantitatively converted into analyte concentrations. The authors should clarify whether fluorescence intensity values can be directly converted to absolute concentrations (e.g., pg/mL). If conversion to pg/mL is possible, present a representative example (e.g., calibration curve used for CRP measurements, including the concentration points, curve fit (e.g., linear, 4-parameter logistic), and associated statistics (R², LOD, LOQ)). If such conversion is not possible with the current data, this should be explicitly stated and discussed as a limitation.\nResponse: We thank the reviewer for raising this important point regarding the quantitative\ncapability of our platform. We confirm that the fluorescence intensity values obtained from the\nDBDIY array can indeed be directly converted into absolute analyte concentrations. This\nquantitative conversion is achieved through the use of a standard calibration curve, as we have\nnow explicitly demonstrated for CRP.\nIn direct response to this comment, we have included a representative calibration curve for CRP in\nthe Revised Manuscript (Fig. 4f). This curve was generated using a serial dilution of CRP standards\nand was fitted with a linear model, which is the standard and most appropriate model for\nimmunoassay dose-response data. The associated performance statistics are as follows:\n• R²: 0.995\n• LOD: 9.573 pg mL⁻¹ (calculated as the mean blank signal + 3 SD)\n• LOQ: 20.273 pg mL⁻¹ (calculated as the mean blank signal + 10 SD)\n• The high R² value (R²=0.999) confirms an excellent fit of the linear model to our data. The\nexceptionally low LOD and LOQ values underscore the high sensitivity of the DBDIY platform,\nfacilitated by the plasmonic enhancement of the TA-GNP-Array substrate.\nTo further validate the quantitative accuracy of this conversion in a clinically relevant context, we\nanalyzed 192 independent clinical serum samples. The CRP concentrations determined by the\nDBDIY array showed excellent agreement with those measured by immunoturbidimetry, a\nstandard quantitative clinical method, with a correlation coefficient of 0.973 (Fig. 4g). Bland-\nAltman analysis further confirmed good agreement, with a minimal mean bias of -0.96% and the\nmajority of data points within the ±1.96 SD limits of agreement (Fig. 4h). The corresponding\nfluorescence images for these 192 samples are provided in Supplementary Fig. 6.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n“To further validate the quantitative capability of the DBDIY platform, we established a calibration\ncurve using CRP standards at varying concentrations, based on the corresponding fluorescence\nintensities. Both the fluorescence images and standard curve confirmed the high sensitivity of the\nDBDIY array for CRP detection, with a calculated LOD of 9.573 pg mL⁻¹ and limit of quantification\n(LOQ) of 20.273 pg mL⁻¹ (Fig. 4e, f). We further evaluated the platform using 192 clinical serum\nsamples, comparing the results with a clinical high-sensitivity CRP (hs-CRP) immunoturbidimetry\nassay. The correlation coefficient between the two methods reached 0.973 (Fig. 4g and\nSupplementary Table 3). Bland-Altman analysis indicated a mean bias of -0.96%. Although a slight\npositive deviation was observed, most data points fell within the ±1.96 SD agreement limits,\ndemonstrating good concordance between the DBDIY array and immunoturbidimetry (Fig. 4h and\nSupplementary Fig. 6).\nCollectively, the DBDIY array demonstrated excellent performance in quantitatively detecting CRP\nlevels in whole blood and serum samples, enabling faster and more accurate diagnosis of infections\nin children, as well as effective monitoring of infection progression trends (Extended Data Fig. 8).”\nIn the Revised Manuscript (Page 20), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“e, Fluorescence images corresponding to CRP standards at various concentrations. f, The calibration\ncurve for CRP standards. The limit of detection (LOD) was defined as the mean blank signal plus three\ntimes its standard deviation (3 SD), while the limit of quantification (LOQ) was defined as the mean\nblank signal plus ten times the standard deviation (10 SD). g, h, Comparative assessment of the DBDIY\nmethod and immunoturbidimetry for measuring CRP in 192 clinical serum samples, presented as a\ncorrelation plot (g) and a Bland-Altman analysis (h).”\nIn the Revised Supplementary Information (Page 8), the following figure panel was added as follows:\n“Supplementary Fig. 6 | Fluorescence images of CRP detection in 192 clinical serum samples.”\n6. Supplementary tables lack units for CRP. The CRP cut-off used in Fig. 4b is not explained.\nThe authors should clearly define the units and describe how clinical or analytical thresholds were determined. Define the threshold values for presented clinical applications and their basis (e.g., literature, ROC-derived, clinical standard)\nResponse: We thank the reviewer for these pertinent observations. We have clearly defined the\nunits for CRP (µg mL⁻¹) and NT-proBNP (ng mL⁻¹) in the respective supplementary tables to avoid\nany ambiguity. Furthermore, the cut-off value for CRP used in Fig. 4b is now explicitly stated and\njustified in the manuscript. This threshold was determined objectively through Receiver Operating\nCharacteristic (ROC) curve analysis, by selecting the value that maximized Youden's Index (J =\nSensitivity + Specificity - 1) to ensure optimal diagnostic performance.\nRevisions:\nIn the Revised Supplementary Information (Page 10 and Page 18), the units were added as follows:\nCRP level\nSample ID Sex Age Positive/Negative Department\n(µg mL-1)\nSample ID Sex Age NT-ProBNP level Positive/Negative\n(ng mL-1)\nIn the Revised Manuscript (Page 19), the sentence in the figure legend was added as follows:\n“The cutoff value corresponding to the maximum value of Youden’s index was selected as the\nsensitivity and specificity of the detection system.”\n7. What equipment was used for pipetting (e.g., Nanoplotter), see Fig 4? Please discuss reproducibility and potential variability across arrays.\nResponse: We thank the reviewer for these important questions regarding the pipetting\nequipment and reproducibility of our DBDIY platform.\nFor all manual spotting steps in Fig. 4 and throughout the study, a standard electronic pipette\n(Rainin® NanoRep, 0.1 μL) equipped with low-retention tips was used. This contrasts with the non-\ncontact nano-plotter (e.g., Nanoplotter 2.1) used for traditional protein chip fabrication in control\nexperiments. The use of a routine electronic pipette, rather than specialized robotic equipment,\nunderscores the accessibility of our method.\nTo quantitatively assess reproducibility across different areas of the chip, we prepared an \"ARRAY\"\npattern of SA-IR800 across five separate regions via manual pipetting (Extended Data Fig. 3a).\nQuantitative analysis of fluorescence signals revealed excellent reproducibility with a 7.65% RSD\nacross the five patterned regions. The non-patterned background areas showed minimal variation\n(1.79% RSD), demonstrating both the precision of our manual spotting technique and the effective\nconfinement of proteins within their designated hydrophilic regions without significant spillover or\ncross-contamination. These results, visually confirmed by the clear \"ARRAY\" pattern in the\nheatmap (Extended Data Fig. 3b) and quantitative intensity measurements (Extended Data Fig. 3c),\nprovide strong evidence that the DBDIY method maintains high reproducibility and minimal spatial\nvariability across arrays. This performance level, achieved with basic pipetting equipment, makes\nour platform particularly suitable for applications requiring reliable multiplexed analysis without\nspecialized robotics.\nExtended Data Fig. 3 | Stability of DBDIY array on TA-GNP-Array. a, Fluorescence images of the SA-\nIR800 array (letter pattern \"ARRAY\" across five areas) prepared on the TA-GNP-Array via DBDIY. SA-IR800\n(0.2 µL, 400 pM) was added to each air plotter and washed three times with PBS. b, Heatmap of\nfluorescence signals from the five areas clearly displayed the \"ARRAY\" letter pattern. c, Fluorescence\nintensity of the lettered and non-lettered sections within the five areas.\n8. Include a reference or detailed methodology explaining how the amplification was quantified (the manuscript reports a 240-fold signal amplification using TA-GNP).\nResponse: We thank the reviewer for this comment. The quantification of the 240-fold\nfluorescence enhancement for TA-GNP is based on our previous work, which provides detailed\nmethodological and quantitative analysis. We have now cited this foundational study accordingly\n(Ref. 29) in the Revised Manuscript to provide the necessary reference for this claim.\nRevisions:\nIn the Revised Manuscript (Page 3), the following paragraph was refined:\n“Due to the 240-fold fluorescence enhancement of TA-GNP in the NIR region, we developed a\nhierarchical patterned plasmonic chip, named TA-GNP-Array29.”\n9. Blurred Spots in Fig. 1i: Are the spots still evaluable despite blurring? Is there supporting data on reproducibility or signal consistency? Address the reliability of such spots and whether they influence quantitation.\nResponse: We thank the reviewer for raising this important point regarding image quality. In\nresponse, we have replaced the original panel with a new, higher-quality image in the revised\nversion of Fig. 1i. The spots in this updated figure are clear and well-defined, ensuring they are fully\nevaluable and that quantitative analysis is reliable.\nRevisions:\nIn the Revised Manuscript (Page 17), the following figure panel was revised:\n10. The sentence \"It was found that DBDIY not only reduced the concentration of CAb but also maintained a total mass of CAb comparable to commercial plotters\" is unclear. Clarify whether quantification was performed and specify the values if available.\nResponse: We thank the reviewer for pointing out the lack of clarity. Quantification was indeed\nperformed, and we have revised the relevant paragraph in the main text to explicitly state the\ncomparative values. The sentence in question has been replaced with a clear, quantitative\nstatement: \"the DBDIY system reduced the CAb working concentration from 50 μg mL⁻¹ to 5 μg\nmL⁻¹ while maintaining a total CAb mass of 1 ng per biomarker, a value comparable to commercial\nplotters (Supplementary Table 1).\"\nFurthermore, we have added a new Supplementary Table 1 that provides a detailed side-by-side\ncomparison of the key performance metrics, including the CAb working concentration and mass,\nbetween the traditional protein chip and our DBDIY array. This table offers comprehensive\nnumerical data to fully support our claims and ensure clarity.\nRevisions:\nIn the Revised Manuscript (Page 4), the following paragraph was refined:\n“We next evaluated mouse interleukin-6 (mIL-6) arrays on TA-GNP-Array alongside traditional\nprotein chips. Gradient concentrations of CAb from an uncoated ELISA kit (250X stock) were\narrayed on glass, TA-GNP, and TA-GNP-Array substrates, followed by mIL-6 detection (Fig. 1h and\nExtended Data Fig. 2g). The optimal CAb concentration was determined to be 5× for the DBDIY-\nfabricated TA-GNP-Array, compared to 50X for Nano-plotter-printed arrays on glass and TA-GNP.\nNotably, both TA-GNP and TA-GNP-Array exhibited substantially higher fluorescence intensities\nthan the glass substrate, consistent with the signal amplification effect of gold nanoislands (Fig. 1i,\nj). Remarkably, even at a 10-fold lower CAb concentration, the TA-GNP-Array achieved a better\ndetection limit than traditional chips (Fig. 1k).\nA similar advantage was observed for CRP arrays: the DBDIY system reduced the CAb working\nconcentration from 50 μg mL⁻¹ to 5 μg mL⁻¹ while maintaining a total CAb mass of 1 ng per\nbiomarker, a value comparable to commercial plotters (Supplementary Table 1). In addition, the\nDBDIY array provided superior control over spot size and spacing relative to conventional platforms\n(Extended Data Fig. 4). We attribute this overall enhancement to the surface modifications\nintroduced during patterning, which improve the efficiency of protein immobilization (Extended\nData Fig. 5).”\nIn the Revised Supplementary Information (Page 9), the following table was added:\nSupplementary Table 1 | Comparative performance and operational characteristics of the\ntraditional protein chip and the DBDIY array platform\nTraditional protein chip DBDIY array\n(TA-GNP) (TA-GNP-Array)\nCAb working concentration 50 μg mL-1 5 μg mL-1\nCAb Mass per biomarker 1 ng 1 ng\nTest sample flux 16 24/80/800\nTest index flux 12 800/12/1\nSpot size ~400 μm 5-500 μm (Tunable)\nSpot shape Circle only Various shapes\nMinimum suction volume 1.5 μL 0.2 μL\nMinimum sample volume 20 μL 0.2 μL\nMinimum extrusion volume 0.5 nL 200 nL\nNano-plotter required Yes No\nFrame required Yes No\n11. The method and experimental details about the fabrication of the array are not complete and need to described in detail. Silanization process is either not described or wrong (“trifluoro (1H, 1H, 2H, 2H-perfluorooctyl) silane (PFOCTS) (L.98)” should be probably trichloro... silane). The authors should describe in detail how the fabrication procedure was done. Including silanization etc.including silanization, patterning etc.\nResponse: We are grateful to the reviewer for their careful reading and for identifying this\ninaccuracy in the chemical name. The correct chemical name, \"trichloro(1H,1H,2H,2H-\nperfluorooctyl) silane (PFOCTS),\" has been replaced in the Revised Manuscript. We apologize for\nany confusion this may have caused.\nRevisions:\nIn the Revised Manuscript (Page 3), the following paragraph was refined:\n“TA-GNP-Array consisted of gold nanoisland regions and trichloro (1H, 1H, 2H, 2H-perfluorooctyl)\nsilane (PFOCTS) regions.”\n12. The manuscript mentions \"low production costs\" and minimal need for specialized personnel. No cost comparison to commercial systems is provided. Pipetting 0.2 µL across ~100 spots requires skills—can this realistically be performed by non-specialists? The authors should provide a cost analysis and discuss the operational feasibility in real clinical laboratory or field settings.\nResponse: We thank the reviewer for these insightful comments regarding the practical\nimplementation and cost-effectiveness of our DBDIY platform. We have addressed these points in\ndetail below:\n• Cost analysis and comparison to commercial systems\nWe agree that a quantitative cost analysis is important. The primary cost advantage of our platform\nlies in the elimination of two major capital expenditures: the automated nano-plotter (which can\ncost $50,000 - $100,000 USD) and the specialized incubation framing systems. In contrast, the core\nconsumable is our patterned plasmonic chip.\nA preliminary cost breakdown for the DBDIY array is as follows:\nPatterned Plasmonic Chip: $30-50 per chip (based on raw material and fabrication costs).\nAssay Reagents: Comparable to standard immunoassay reagent costs.\nEquipment: Requires only a standard electronic pipette (a ubiquitous tool in clinical and research\nlabs, $500 - $2,000) and a fluorescence scanner.\nWhen compared to a commercial high-throughput protein array system, which requires a\nsignificant initial investment in the plotter and reader (often exceeding $150,000), our platform\noffers a reduction in initial capital outlay of over 90%.\n• Operational feasibility and skill requirements\nConcerning operational feasibility, we acknowledge that manual pipetting of 0.2 µL could present\nchallenges. However, we have introduced low-cost, reusable positioning guides, demonstrated in\nSupplementary Video 1, to facilitate rapid and accurate alignment without requiring specialized\nskills. More importantly, the hydrophilic-hydrophobic patterned surface itself provides inherent\ntolerance to positioning variations. As systematically evaluated in Supplementary Video 2, even\nwith deliberate pipetting deviations, droplets are effectively guided and confined to intended areas\nwithout affecting assay performance, as further supported by Supplementary Fig. 1.\nFurthermore, Supplementary Video 3 demonstrates continuous manual spotting of over 100 spots\nsmoothly and efficiently, confirming the practicality and robustness of this process for non-\nspecialists.\nIn summary, the DBDIY platform significantly lowers both cost and technical barriers, making it\nhighly suitable for resource-limited settings, satellite clinics, or research laboratories without\naccess to core facilities.\nRevisions:\nIn the Revised Supplementary Information (Page 3), the following figure panel was added:\n“Supplementary Fig. 1 | Evaluation of tolerance for plotting position deviation. a, Schematic\ndiagram illustrating plotting position deviation. The arrow indicates the direction of droplet sliding.\nb, Schematic of the plotting model system (SA-IR800).\nc, Photographs of SA-IR800 arrays spotted\nwith different predefined positional deviations. The inset in the bottom right corner illustrates the\ncorresponding deviation patterns. Scale bar: 1 mm. Droplets were stained with food coloring for\nvisualization. d, Fluorescence images of the SA-IR800 arrays. Top: unblocked array; Bottom: blocked\narray. e, Quantitative analysis of fluorescence intensity for unblocked and blocked SA-IR800 arrays.\nThe data indicate that variations in spotting position within the allowable deviation range do not\nsignificantly affect the final fluorescence signal.”\n13. Plasmonic-enhanced NIRF is a highly specialized technology, requiring sophisticated equipment. The DIY nature of the array seems at odds with the complexity of the readout system. The authors should either rename the method or explain and discuss the practicality of implementing this platform in low-resource or point-of-care settings.\nResponse: We thank the reviewer for raising this important point regarding the perceived\ncomplexity of the readout system in relation to the \"Do-It-Yourself\" (DIY) nature of the array. We\nagree that the term \"DIY\" primarily refers to the straightforward, bench-top fabrication and\nassembly process of the detection array itself, which, as shown in Fig. R1a, requires only common\nand inexpensive laboratory consumables. This distinguishes our method from those requiring\ncleanroom facilities or complex microfluidic systems for chip production.\nRegarding the readout system, we acknowledge that plasmonic-enhanced NIRF is a sophisticated\ntechnique. However, the commercial benchtop scanner used in our study (Fig. R1b) is a compact,\npre-calibrated, and user-friendly instrument. Its operation is as simple as inserting the array chip\nand initiating a pre-programmed measurement protocol, requiring minimal technical expertise.\nCrucially, the core advantage of our DBDIY platform lies in its system-level simplicity and cost-\neffectiveness. The combination of an ultra-low-cost, user-assembled array with a compact, \"plug-\nand-play\" scanner results in a system with a minimal laboratory footprint and significantly lower\noverall cost than conventional setups. This integrated approach makes the platform particularly\nsuitable for low-resource or point-of-care settings, where the primary constraints are space, budget,\nand the need for operational simplicity rather than the ability to build every component from\nscratch.\nFig. R1 | Cost-effective setup of the DBDIY platform. a, The minimal consumables required for the\nDBDIY array, including a TA-GNP-Array chip, standard pipette, low-retention tips, reagent reservoir,\ntube strip, and centrifuge (all commonly available and inexpensive laboratory items). b, The\ncompact benchtop fluorescence scanner (25 × 35 × 45 cm3) used for signal readout. Together, these\ncomponents demonstrate the platform's minimal laboratory footprint, low cost, and operational\nsimplicity, making it particularly suitable for resource-limited settings where space and budget\nconstraints are critical considerations.\n14. Most clinical laboratories use quantitative high-sensitivity CRP (hsCRP) assays based on\nimmunoturbidimetry, ELISA, or nephelometry, which report concentrations in mg/L or pg/mL. The\ndeveloped CRP assay is compared against a qualitative reference assay. Without comparing the\nDBDIY assay to such established quantitative methods, it is difficult to assess its clinical relevance, especially for applications like cardiovascular risk assessment or sepsis monitoring, where precise CRP levels are critical.\nProvide justification for this comparison, or if possible, re-analyze the CRP data using a quantitative clinical reference method to provide a more meaningful benchmark. Clearly report the analytical performance parameters of the platform: LOD, LOQ, precision (intra-/inter-assay CV), and linear range. If only a qualitative comparison is possible at this stage, clearly state this limitation and discuss its implications for future validation.\nResponse: We sincerely thank the reviewer for this critical suggestion regarding the need for\ncomparison with established quantitative methods. We fully agree that such validation is essential\nfor assessing the clinical relevance of our CRP assay, particularly for applications requiring high\nsensitivity such as cardiovascular risk assessment. In direct response to this comment, we have\nconducted an additional comprehensive validation study comparing our DBDIY array against\nimmunoturbidimetry, the standard quantitative method for high-sensitivity CRP (hs-CRP) testing in\nclinical laboratories.\nThis comparison was performed using 192 clinical serum samples specifically intended for hsCRP\nanalysis. The results demonstrate excellent quantitative agreement between the two methods:\n• The correlation coefficient reached 0.973 (Fig. 4g)\n• Bland-Altman analysis revealed a minimal mean bias of -0.96%, with the vast majority of data\npoints falling within the ±1.96 SD limits of agreement (Fig. 4h)\nFurthermore, we have now explicitly reported the complete analytical performance parameters of\nour platform for CRP detection:\n• Limit of Detection (LOD): 9.573 pg mL⁻¹\n• Limit of Quantification (LOQ): 20.273 pg mL⁻¹\n• Linear Range: The working range spans from the LOD up to 64 ng mL⁻¹ (covering approximately\n5 orders of magnitude with 10,000-fold serum dilution), comprehensively encompassing both\ninfection monitoring and cardiovascular risk assessment ranges\n• Calibration: The quantitative conversion is achieved through a linear calibration model (R² =\n0.999) as shown in Fig. 4f\nWe are particularly grateful for this suggestion, as the additional validation has significantly\nstrengthened our study by unequivocally demonstrating that the DBDIY platform serves not as\nmerely a qualitative tool, but as a highly sensitive and precise quantitative platform with\nperformance directly benchmarked against clinical gold standards. This robust validation confirms\nits potential for demanding clinical applications including cardiovascular risk stratification and\nsepsis monitoring.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n“To further validate the quantitative capability of the DBDIY platform, we established a calibration\ncurve using CRP standards at varying concentrations, based on the corresponding fluorescence\nintensities. Both the fluorescence images and standard curve confirmed the high sensitivity of the\nDBDIY array for CRP detection, with a calculated LOD of 9.573 pg mL⁻¹ and limit of quantification\n(LOQ) of 20.273 pg mL⁻¹ (Fig. 4e, f). We further evaluated the platform using 192 clinical serum\nsamples, comparing the results with a clinical high-sensitivity CRP (hs-CRP) immunoturbidimetry\nassay. The correlation coefficient between the two methods reached 0.973 (Fig. 4g and\nSupplementary Table 3). Bland-Altman analysis indicated a mean bias of -0.96%. Although a slight\npositive deviation was observed, most data points fell within the ±1.96 SD agreement limits,\ndemonstrating good concordance between the DBDIY array and immunoturbidimetry (Fig. 4h and\nSupplementary Fig. 6).\nCollectively, the DBDIY array demonstrated excellent performance in quantitatively detecting CRP\nlevels in whole blood and serum samples, enabling faster and more accurate diagnosis of infections\nin children, as well as effective monitoring of infection progression trends (Extended Data Fig. 8).”\nIn the Revised Manuscript (Page 20), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“e, Fluorescence images corresponding to CRP standards at various concentrations. f, The calibration\ncurve for CRP standards. The limit of detection (LOD) was defined as the mean blank signal plus three\ntimes its standard deviation (3 SD), while the limit of quantification (LOQ) was defined as the mean\nblank signal plus ten times the standard deviation (10 SD). g, h, Comparative assessment of the DBDIY\nmethod and immunoturbidimetry for measuring CRP in 192 clinical serum samples, presented as a\ncorrelation plot (g) and a Bland-Altman analysis (h).”\nIn the Revised Supplementary Information (Page 8), the following figure panel was added as follows:\n“Supplementary Fig. 6 | Fluorescence images of CRP detection in 192 clinical serum samples.”\nEnglish grammar in some places of the manuscript needs to be improved. For example: “accurate\nmeasurement of high-throughput protein levels” (p 2), etc. Please check the grammar throughout\nthe MS.\nResponse: We thank the reviewer for highlighting the need for improved grammar and clarity. We\nhave thoroughly checked and refined the English language throughout the entire manuscript to\nenhance readability and precision (Table R1).\nRevisions:\nIn the Revised Manuscript, the following paragraph was refined:\nTable R1 Grammatical errors present in the manuscript and the corresponding corrections\nGrammatical errors Corresponding corrections\nIn clinical diagnosis and laboratory testing, In clinical diagnosis and laboratory testing, the\naccurate measurement of high-throughput accurate, high-throughput measurement of\nprotein levels in small volume biological fluids protein levels in small volume biological fluids\nis crucial for disease diagnosis and prognosis is crucial for disease diagnosis and prognosis\nespecially in children, specific disease patients, especially in children, specific disease patients,\nand experimental animals1-3. and experimental animals1-3. (Page 2)\nThe assay enables equipment-free protein The assay enables equipment-free protein\nmicroarray fabrication and high-sensitive microarray fabrication and highly sensitive\ndetection using only a pipette. detection using only a pipette. (Page 1)\nIt enables the dynamic monitoring of 10 It enables the dynamic monitoring of 10\ncytokines in only 6 μL serum/blood samples cytokines in only 6 μL of serum/blood samples\nfrom individual mice over a 40-day period with from individual mice over a 40-day period with\n20 blood collection time points. 20 blood collection time points. (Page 1)\nFurthermore, it exhibits 100% sensitivity and Furthermore, it exhibits 100% sensitivity and\nspecificity for detecting C-reactive protein specificity for detecting C-reactive protein\n(CRP) levels in 1 nL peripheral whole blood (CRP) levels in 1 nL of peripheral whole blood\nsamples from 100 children in a clinical setting. samples from 100 children in a clinical setting.\n(Page 1)\nAlthough proteins chips benefit from Although protein chips benefit from plasmonic\nplasmonic enhanced substrates, such as enhanced substrates, such as plasmonic gold\nplasmonic gold (pGold) slides and thermal- (pGold) slides and thermal-annealing gold\nannealing gold nanoparticle (TA-GNP) nanoparticle (TA-GNP) platforms, their further\nplatforms, their further development is limited development is limited by the need for\nby the need for expensive/large plotters, costly expensive/large plotters, costly frames, and\nframes, and specialized technical personnel16- specialized technical personnel16-28. (Page 2)\n28.\nThe air plotter (air/droplets/printing area The air plotter (air/droplets/printing area\ncontact line replace expensive plotter) contact line replaces expensive plotter)\nachieves protein array enrichment/generation achieves protein array enrichment/generation\nthrough localized protein microdroplets, through localized protein microdroplets,\nsimplifying the workflow. The air frame simplifying the workflow. The air frame\n(air/droplets/testing area contact line replace (air/droplets/testing area contact line replaces\ncostly frame) incubates microvolume samples costly frame) incubates microvolume samples\nby localized sample droplets, flexibly adjusting by localized sample droplets, flexibly adjusting\nsample volume and detection throughput. sample volume and detection throughput.\n(Page 2)\nA total of 100 whole peripheral blood samples A cohort of 100 peripheral blood samples from\nfrom children (50 positive and 50 negative) children (50 positive and 50 negative) were\nwere collected in various clinical settings, collected in various clinical settings, including\nincluding the pediatric emergency, pediatric the pediatric emergency, pediatric respiratory,\nrespiratory, neonatology, pediatric neonatology, pediatric gastroenterology,\ngastroenterology, pediatric endocrinology, and pediatric endocrinology, and pediatric ICU\npediatric ICU (Supplementary Table 2). (Supplementary Table 2). (Page 6)\nIt should be specified what kind of “contact angle” was used in the characterization (advancing,\nstating, water, etc.).\nResponse: We appreciate the reviewer's request for specificity regarding the contact angle\nmeasurements. In all instances within the Revised Manuscript, the reported values refer to the\nstatic water contact angle.\nRevisions:\nIn the Revised Manuscript (Page 3, Page 22, and Page 26), the following paragraph was refined:\n“The static water contact angle of the hydrophobic PFOCTS region (106.1°) was greater than that\nof the gold nanoparticle island region (46.6°), enabling the confinement of droplets.”\n“Extended Data Fig. 1 | Characterization of TA-GNP-Array. a, Schematic diagram of the fabrication\nprocess for the TA-GNP-Array. The static water contact angle of the gold nanoparticle surface was\n46.6°, while the static water contact angle of the PFOCTS surface was 106.1°.”\n“Extended Data Fig. 5 | Comparison of CRP arrays on unmodified and modified photoresist surfaces.\nThe photoresist was spun onto both Glass and TA-GNP substrates, followed by ethanol cleaning to\nsimulate the surface modification induced by the UV lithography process. The modified photoresist\nchips were named Glass-PR and TA-GNP-PR, respectively. a, After the modification process, the\nstatic water contact angle of the Glass substrate increased from 6.3° to 31.7°. Similarly, the static\nwater contact angle of the TA-GNP substrate changed from 15.2° to 46.6° after the modification\nprocess.”\nReviewer #2:\nThe authors should be congratulated on an interesting piece of research, which, I believe after\nfurther improvement will be a substantive contribution to the field. The work combines the\nenhancement of plasmonic arrays with hydrophobic/ hydrophilic interfaces to create an easy-to-\nuse, yet sensitive platform. Both of the initial techniques are well known, however their integration\nis technically astute in enabling the level of control of surface properties on a plasmonic substrate.\nThis is therefore a clever miniaturisation of a popular technique used in laboratories and serves to\nminimise reagent consumption. In general the ideas and results presented are strong in concept,\nillustrated with a well-conceived assay and underpinned by strong materials engineering.\nHowever, I have a number of general and more specific suggestions.\nAs a starting point, I think the biological/clinical validation could be stronger (for example, colloidal\ngold immunochromatography is not a gold standard for CRP and the authors may have chosen an\nestablished ELISA). Can they clearly justify their choice?\nResponse: We appreciate the reviewer's comment regarding the choice of reference method.\nWe acknowledge that our initial description contained an error in identifying the clinical method.\nThe correct reference method used for the initial 100 pediatric whole blood samples was in fact a dry\nfluorescence immunoassay (Getein 1600 analyzer), not colloidal gold immunochromatography.\nThis has been corrected throughout the manuscript. This platform was selected as it represents a\nstandard, clinically implemented system for quantitative CRP testing in pediatric settings,\nparticularly with small-volume peripheral blood samples.\nFurthermore, in direct response to this comment and to substantially strengthen the clinical\nvalidation of our platform, we performed an additional validation study comparing our DBDIY array\nagainst immunoturbidimetry, the established quantitative gold-standard method for high-\nsensitivity CRP (hsCRP) testing. This comparison was conducted using 192 independent clinical\nserum samples. The results demonstrated excellent quantitative agreement:\n• A correlation coefficient of 0.973\n• Bland-Altman analysis showing a mean bias of -0.96% with the majority of data points within\nagreement limits\nThis additional rigorous comparison with a quantitative clinical gold standard provides robust\nevidence of our platform's analytical performance and clinical relevance.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n“These samples were analyzed using dry fluorescence immunoassay (Getein 1600 analyzer) and\nDBDIY array.”\n“To further validate the quantitative capability of the DBDIY platform, we established a calibration\ncurve using CRP standards at varying concentrations, based on the corresponding fluorescence\nintensities. Both the fluorescence images and standard curve confirmed the high sensitivity of the\nDBDIY array for CRP detection, with a calculated LOD of 9.573 pg mL⁻¹ and limit of quantification\n(LOQ) of 20.273 pg mL⁻¹ (Fig. 4e, f). We further evaluated the platform using 192 clinical serum\nsamples, comparing the results with a clinical high-sensitivity CRP (hs-CRP) immunoturbidimetry\nassay. The correlation coefficient between the two methods reached 0.973 (Fig. 4g and\nSupplementary Table 3). Bland-Altman analysis indicated a mean bias of -0.96%. Although a slight\npositive deviation was observed, most data points fell within the ±1.96 SD agreement limits,\ndemonstrating good concordance between the DBDIY array and immunoturbidimetry (Fig. 4h and\nSupplementary Fig. 6).\nCollectively, the DBDIY array demonstrated excellent performance in quantitatively detecting CRP\nlevels in whole blood and serum samples, enabling faster and more accurate diagnosis of infections\nin children, as well as effective monitoring of infection progression trends (Extended Data Fig. 8).”\nIn the Revised Manuscript (Page 20), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“e, Fluorescence images corresponding to CRP standards at various concentrations. f, The calibration\ncurve for CRP standards. The limit of detection (LOD) was defined as the mean blank signal plus three\ntimes its standard deviation (3 SD), while the limit of quantification (LOQ) was defined as the mean\nblank signal plus ten times the standard deviation (10 SD). g, h, Comparative assessment of the DBDIY\nmethod and immunoturbidimetry for measuring CRP in 192 clinical serum samples, presented as a\ncorrelation plot (g) and a Bland-Altman analysis (h).”\nIn the Revised Supplementary Information (Page 8), the following figure panel was added as follows:\n“Supplementary Fig. 6 | Fluorescence images of CRP detection in 192 clinical serum samples.”\nThere are also statistical issues throughout the paper, which are exacerbated by the small sample\nsizes and in many cases unclear presentation (e.g. in the figure legends).\nResponse: We have comprehensively revised our statistical approach and data presentation\nthroughout the manuscript to address the concerns regarding sample sizes and clarity:\n1. Increased sample sizes:\nWe have significantly enhanced the statistical power of key experiments by:\n• Conducting an additional independent validation with 192 clinical serum samples compared\nagainst immunoturbidimetry\n• Increasing the LPS-induced inflammation model from n=4 to n=12 mice per group\n• Expanding the 4T1 tumor model from n=1 to n=3 mice per group\n2. Enhanced statistical reporting:\n• Added error bars to all longitudinal plots (Fig. 3f,g and Supplementary Fig. 4)\n• Implemented Bland-Altman analysis for method comparison studies\n• Calculated and reported 95% confidence intervals for sensitivity and specificity\n• Removed inappropriate ROC curve analysis and replaced with proper reporting of Youden's\nindex\n3. Clarified experimental replication:\n• Explicitly stated throughout Methods and figure legends that each biological sample was\nmeasured with quadruplicate technical spots\n• Detailed the robust data processing method (mean of three spots after outlier exclusion)\n• Clearly defined sample sizes (n) as biologically independent samples in all figure legends\nThese extensive revisions have significantly strengthened both the clinical validation and statistical\nrigor of our study, providing a more solid foundation for the conclusions drawn.\nRevisions:\nIn the Revised Manuscript (Page 19), the following figure panel was revised:\nIn the Revised Supplementary Information (Page 6), the following figure panel was revised:\nIn the Revised Manuscript (Page 20), the following figure panel was added:\nIn the Revised Manuscript (Page 4, Page 6), the following paragraph was refined:\n“Two hours post-injection, blood samples were collected from the retro-orbital sinus of both\ncontrol (n=12) and LPS-injected (n=12) mice using capillary tubes.”\n“The DBDIY array showed 100% sensitivity and specificity (95% CI: 92.9% to 100%).”\nIn the Revised Manuscript (Page 18, Page 19, Page 20, Page 28, Page 30), the following figure legend\nwas revised:\n“a, Schematic of whole blood and serum sampling of control (n=12) and LPS (n=12) group mice.”\n“g, h, Comparing the levels of multiplexed cytokines in blood (g) and serum (h) between the control\ngroup (n=12) and the mice injected with LPS (n=12). **P < 0.01, ****P < 0.0001, as determined by\nWilcoxon–Mann–Whitney test.”\n“b, c, Fluorescence images (b) and heat map (c) of multiplexed cytokine detection in control mice\n(n=3) and 3% DSS treated mice (n=3) on day 1, day 3, day 5, and day 7. d, e, Schematic diagram (d)\nand heat map (e) of micro blood collection and 10 cytokines detection on control (n=1),\ntumor (n=1), and treatment (n=1) mice every two days for 40 days. Image created with BioRender.com.”\n“The cutoff value corresponding to the maximum value of Youden’s index was selected as the sensitivity\nand specificity of the detection system.”\n“e, Fluorescence images corresponding to CRP standards at various concentrations. f, The calibration\ncurve for CRP standards. The limit of detection (LOD) was defined as the mean blank signal plus three\ntimes its standard deviation (3 SD), while the limit of quantification (LOQ) was defined as the mean\nblank signal plus ten times the standard deviation (10 SD). g, h, Comparative assessment of the DBDIY\nmethod and immunoturbidimetry for measuring CRP in 192 clinical serum samples, presented as a\ncorrelation plot (g) and a Bland-Altman analysis (h).”\n“Extended Data Fig. 7 | Cytokine levels in serum of DSS and control mice on day 7. Comparing the\nlevels of multiplexed cytokines in serum between the DSS (n=3) and control group (n=3). *P < 0.05, as\ndetermined by Wilcoxon–Mann–Whitney test.”\n“The cutoff value corresponding to the maximum value of Youden’s index was selected as the sensitivity\nand specificity of the detection system. d, The specificity and sensitivity of NT-proBNP detected by\nDBDIY in 29 clinical samples were 100% (95% CI: 66.37% to 100%).”\nThere are a few major shortcomings that must be addressed before publication which include the\nfact that:\n(i) there is a lack of power calculations, and it is often not clear how many technical replicates were\ndone. Is the study not under-powered? If it is this should be clearly stated and conclusions;\nResponse: We acknowledge that a priori power calculations were not performed for the initial\nanimal studies. In direct response to this comment, we have significantly enhanced the statistical\nfoundation of our study through the following substantive expansions:\n• We supplemented the original 100 whole blood samples with an additional 192 clinical serum\nsamples, providing enhanced statistical power for the quantitative comparison between our\nmethod and the clinical gold standard (immunoturbidimetry).\n• The mouse cohort for the LPS-induced inflammation model (Fig. 2) was increased from n=4 to\nn=12 per group, providing robust statistical power for the comparisons made in this model.\n• The animal numbers in the 4T1 tumor model (Fig. 3) were increased from n=1 to n=3 per group.\nWe understand that this sample size remains limited for rigorous inter-group comparisons,\nreflecting the practical challenges associated with these long-term, high-cost longitudinal\nexperiments. We have explicitly clarified in the Revised Manuscript that the primary aim of this\nparticular experiment was to demonstrate the unique capability of our platform for long-term\ndynamic monitoring with minimal sample volumes, and we have exercised caution in drawing\nconclusions based on this small sample size. This point is now discussed as a study limitation.\nRegarding technical replicates: We apologize for the previous lack of clarity. We have now explicitly\nstated throughout the Methods section and figure legends that while each biological sample was\ntypically assayed once on the array, each analyte was measured in quadruplicate spots within that\nsingle assay. The final data point for each sample represents the mean fluorescence intensity\ncalculated from these replicates after applying a robust outlier exclusion method (removing the\nspot with the highest deviation). This approach ensures measurement reliability while conserving\nprecious biological samples.\nThese enhancements to statistical power and methodological clarity have been fully detailed in our\nresponses to related revisions.\n(ii) the use of a ROC analysis is actually inappropriate and should be removed – these “curves” are\nbased on a single point;\nResponse: We fully concur with the reviewer's expert assessment that presenting a single optimal\ncut-off point as an ROC \"curve\" was statistically inappropriate. In accordance with this\nrecommendation, we have removed the ROC curve from Fig. 4 and implemented the following\nrevisions:\n• We now report the diagnostic sensitivity and specificity values, along with their corresponding\n95% confidence intervals (calculated using the Clopper-Pearson exact method), directly in both the\nmain text and the Fig. 4 legend.\n• We explicitly state that the optimal cut-off value was determined by maximizing Youden's index\n(J) from the dataset.\n• Throughout the Revised Manuscript, we have eliminated any reference to an \"ROC curve\" and\ninstead describe the process objectively as \"determining the optimal diagnostic cut-off through\nYouden's index analysis.\"\nThese modifications ensure proper statistical reporting while maintaining the validity of our\ndiagnostic performance assessment.\nAs noted in our other responses, these statistical corrections have been comprehensively\naddressed throughout the revised manuscript.\n(iiii) from a robust statistical viewpoint, the data could be re-presented using a Bland Altman\nanalysis, with confidence intervals and error bars shown on all figures throughout\nResponse: We thank the reviewer for these excellent suggestions to enhance the robustness of\nour data presentation. We have implemented these changes as follows:\n• Bland-Altman analysis: We have now performed Bland-Altman analysis for all key method-\ncomparison experiments. For the comparison between the DBDIY array and immunoturbidimetry\nfor CRP detection (192 serum samples), a Bland-Altman plot is now included as Fig. 4h.\nThese plots display the mean bias and the 95% limits of agreement (±1.96 SD), providing a clear\nassessment of the agreement between methods.\n• Confidence intervals and error bars: As requested, we have thoroughly revised all data figures\n(Fig. 3f, g and Supplementary Fig. 4) to ensure that all quantitative data are now presented with\nappropriate error bars and that the sample size is explicitly defined in each legend as the number\nof biologically independent samples. Where applicable, confidence intervals for key parameters\nare reported in the text.\nWe refer to our detailed responses above regarding the implementation of these statistical\nimprovements, which have been consistently applied throughout the revised manuscript.\nSome specific comments relevant to each figure/experiment:\nFig 2: It seems like there are 4 mice per group? (authors need clear labels in legend). This is\nprobably under-powered and care needs to be taken when drawing conclusions from this number.\nHow many technical replicates were run.\nResponse: We thank the reviewer for this critical comment regarding the sample size and technical\nreplication. To address the concern about statistical power, we have significantly increased the\nsample size for the experiment presented in Fig. 2. The study now includes 12 mice per group\n(control and LPS-injected), up from the initial 4, and this is clearly stated in the revised figure legend.\nRegarding technical replicates, each biological sample (serum or whole blood from a single mouse)\nwas assayed once on the array. However, within that single assay, the signal for each analyte was\nmeasured from four replicate spots. To ensure robustness, the spot with the highest deviation was\nexcluded, and the mean fluorescence intensity (MFI) was calculated from the remaining three\nspots, as described in the Methods. This approach provides a reliable technical measurement for\neach biological replicate while conserving precious sample volume. The increased sample size\n(n=12 biologically independent samples per group) now provides substantial power for the\nstatistical comparisons made.\nRevisions:\nIn the Revised Manuscript (Page 4), the following paragraph was refined:\n“Two hours post-injection, blood samples were collected from the retro-orbital sinus of both\ncontrol (n=12) and LPS-injected (n=12) mice using capillary tubes.”\n“Fluorescence images and fluorescence intensity revealed significant differences in the expression\nlevels of IL-6, and CCL2 between control and LPS groups in both serum and whole blood samples.\nNotably, TNF-α expression was significantly different only in serum samples (Fig. 2f, g).”\nIn the Revised Manuscript (Page 18 and Page 27), the following figure panel was revised:\nIn the Revised Manuscript (Page 18), the sentence in the figure legend was revised as follows:\n“a, Schematic of whole blood and serum sampling of control (n=12) and LPS group mice (n=12).”\n“g, h, Comparing the levels of multiplexed cytokines in blood (g) and serum (h) between the control\ngroup and the mice injected with LPS. **P < 0.01, ****P < 0.0001, as determined by Wilcoxon–Mann–\nWhitney test.”\nIn the Revised Supplementary Information (Page 4), the following figure panel was added:\n“Supplementary Fig. 3 | Fluorescence images of multiplexed cytokine detection in control mice\n(n=12) and mice injected with LPS (n=12).”\nFig 3: There are no error bars, no confidence intervals, and definitely no proper statistical testing\nfor the temporal changes. For a 40-day longitudinal study, where is the quantitative analysis of\nstability or drift over time? Again, this is a small sample size for this type of analysis.\nResponse: We thank the reviewer for the critical statistical comments regarding the longitudinal\nstudy in Fig. 3. We have comprehensively addressed these concerns in the Revised Manuscript.\nFirst, we sincerely apologize for the initial oversight in data presentation and have now added error\nbars to all relevant longitudinal plots (Fig. 3f, g and Supplementary Fig. 4) to properly represent\ndata variability across time points. Furthermore, we have increased the animal cohort size from\nn=1 to n=3 per group.\nWhile we fully acknowledge that this sample size remains limited for robust inter-group statistical\ncomparisons over the entire time course, we would like to clarify that the primary objective of this\nexperiment was to establish a proof-of-concept for our platform's unique capability to enable high-\ndensity longitudinal monitoring from the same individual mouse over an extended 40-day period\nusing minimal blood volume. This technical advancement represents a significant step forward in\nlongitudinal study design. The substantial individual variations in cytokine dynamics clearly visible\nin the Supplementary Fig. 5c actually underscore a key value of our platform: it can capture such\nsubject-specific trajectories that are typically masked in traditional studies requiring sample\npooling from different animals at each time point.\nWe have revised the text to clearly state that our conclusions focus on demonstrating the feasibility\nof long-term monitoring and describing observed trends, while explicitly acknowledging the\nsample size limitation in both the Fig. 3 legend and the Results section. Future work will utilize this\nvalidated platform for larger-scale studies specifically powered for detailed statistical analysis of\ntemporal changes.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n“Critically, the expanded cohort (n=3 per group) in the 24-day study confirmed the reproducibility\nof the cytokine dynamics while revealing substantial inter-individual variations (Fig. 3c). This\ncapacity to resolve subject-specific trajectories represents a key advantage of our longitudinal\nmonitoring approach over traditional group-mean analyses. The presence of the tumor was\nassociated with increased IL-1β, suggesting active inflammation, while the tumor\nmicroenvironment appeared to promote a Th2-skewed immune response evidenced by stable IL-\n12 levels (Fig. 3f, g).\nCollectively, these studies establish the DBDIY array as a methodological platform for longitudinal\nbiomarker monitoring, enabling insights into dynamic immune responses across different disease\nmodels. The ability to track cytokine fluctuations over time within the same animals provides a\npowerful tool for investigating inflammatory mechanisms and therapeutic interventions, with\nparticular value for studies where individual trajectory mapping and minimal sample volumes are\ncritical considerations.”\nIn the Revised Supplementary Information (Page 7), the following figure panel was added:\n“Supplementary Fig. 5 | Multiplexed cytokines detection of 4T1 mice on TA-GNP-Array. a, b,\nFluorescence images (a) and heat map (b) of micro blood collection and 10 cytokines detection on\ncontrol (n=3), tumor (n=3), and treatment (n=3) mice every two days for 24 days. The treatment\ngroup received DOX injection on day 15. c, Heat map focusing on the cytokine profile dynamics\nacross the three individual tumor-bearing mice during the 24-day observation period.”\nFig 4: As mentioned, colloidal gold is not a clinical gold standard for CRP, and so a comparison to\nthis alone weakens the claims. There is no explanation for how the positive/negative thresholds\nwere set.\nResponse: We sincerely apologize for the inaccuracy in our initial description of the clinical\nreference method. The correct method used for comparison was a quantitative dry fluorescence\nimmunoassay (Getein 1600 analyzer), a clinically established platform for CRP detection in\npediatric settings, particularly suitable for small-volume peripheral blood samples. We have\nthoroughly revised the manuscript to reflect this correction.\nTo further strengthen the clinical validation of our platform, we conducted an additional\nindependent validation study with 192 clinical serum samples analyzed by both our DBDIY array\nand immunoturbidimetry, the established gold standard method for high sensitivity CRP testing.\nThe strong correlation between methods, with a coefficient of 0.973, provides robust evidence of\nour platform's quantitative performance. As this significant enhancement to our clinical validation\nhas been comprehensively described in our response to previous comments, we refer the reviewer\nto those detailed explanations.\nRegarding the threshold determination, the cutoff value for sample classification was objectively\nestablished through ROC curve analysis by maximizing Youden's Index, a standard statistical\nmethod that optimizes diagnostic cutoff points to ensure the best overall diagnostic performance.\nRevisions:\nIn the Revised Manuscript (Page 6 and Page 20), the following paragraph was refined:\n“These samples were analyzed using dry fluorescence immunoassay (Getein 1600 analyzer) and\nDBDIY array.”\n“The cutoff value corresponding to the maximum value of Youden’s index was selected as the\nsensitivity and specificity of the detection system.”\nFig 5: There is missing statistical analysis for method agreement with CBA. No assessment of\nmeasurement range differences or matrix effects between platforms was performed.\nResponse: We thank the reviewer for raising these important methodological considerations\nregarding the comparison with CBA. We acknowledge the observed quantitative differences\nbetween the platforms, where the absolute concentrations measured by our DBDIY array were\ngenerally lower than those obtained by CBA (Fig. R2). This discrepancy can be reasonably attributed\nto several methodological factors.\nFirst, there are inherent standardization differences between the platforms, as each employs\ndistinct antibody pairs and reference standards calibrated through independent systems.\nSecond, the fundamental detection principles differ substantially. CBA utilizes bead-based\nfluorescence detection in solution, whereas our DBDIY platform relies on surface-based capture\ncombined with plasmon-enhanced fluorescence, which may affect binding kinetics and signal\ngeneration. Finally, matrix interactions and solid-phase binding efficiency may vary between the\ntwo systems, potentially influencing absolute recovery rates.\nDespite these expected technical variations in absolute quantification, it is important to emphasize\nthat both platforms demonstrated excellent concordance in detecting the same biological trends.\nAll seven cytokines showed statistically significant and consistent elevation patterns in response to\nanti-CD3/28 stimulation across both methods.\nWhile a formal matrix effects study was beyond the scope of this initial technology validation, the\nconsistent response patterns observed across multiple cytokines in complex cell culture\nsupernatants provide indirect evidence that matrix effects are comparably managed in both\nsystems.\nThe consistent biological conclusions drawn from both platforms, despite technical differences in\nabsolute quantification, strongly support the validity and utility of our DBDIY array for functional\nimmune monitoring applications where relative changes and response patterns are of primary\nimportance.\nFig. R2 | Comparative analysis of cytokine secretion profiles. a, Cytokine levels in supernatants\nfrom control and anti-CD3/28-stimulated CBMC and spleen cells, as quantified by cytometric bead\narray (CBA). b, Corresponding cytokine levels measured in parallel using the DBDIY array. Data\ndemonstrate consistent cytokine elevation patterns in response to T cell stimulation across both\nanalytical platforms.\nIn the Revised Manuscript (Page 7), the following paragraph was refined:\n“To corroborate these results, we performed parallel analyses using cytometric bead array (CBA),\nwhich confirmed the cytokine trends obtained from the DBDIY array (Fig. 5f). The observed\ndifferences in absolute quantification between platforms, attributable to their distinct detection\nprinciples and calibration systems, did not compromise the consistent biological responses\ndetected across all seven cytokines. This consistency confirms that both methods provide\ncomparable dynamic ranges suitable for monitoring immune activation dynamics.”\nBelow are a few further points that need addressing\nAlthough the authors claim you only need a pipette, it is likely that the spotting inside the arrays is\ndifficult by hand (and indeed in the supplementary they show some holders to do it). Although\nthese are not expensive, but they are not ‘just a pipette’.\nResponse: We sincerely thank the reviewer for raising this practical consideration regarding the\nmanual spotting process. We acknowledge that achieving perfect alignment by freehand pipetting\nalone can be challenging, which is why we have systematically evaluated both the operational ease\nand technical robustness of our approach.\nIn direct response to this concern, we have provided three supplementary videos that visually\ndemonstrate the operational workflow. Supplementary Video 1 illustrates the complete DBDIY\nprocess, showing how a standard pipette interacts with our patterned chip. Supplementary Video\n2 specifically highlights the system's built-in tolerance to pipetting position deviations, confirming\nthat the hydrophilic-hydrophobic interface effectively self-guides and confines droplets even with\nintentional misalignment. Most notably, Supplementary Video 3 demonstrates continuous manual\nspotting of over 100 spots in a routine and efficient manner, providing direct evidence of the\nmethod's practicality.\nThese visual demonstrations are supported by quantitative data in Supplementary Fig. 1, where\nwe deliberately introduced positional deviations and found no significant impact on final\nfluorescence signals. This confirms that the chip's patterned design provides intrinsic spatial\nguidance, making the process robust to normal variations in manual pipetting.\nWhile we demonstrate that optional, low-cost guides can further enhance consistency for high-\nthroughput applications, the core technology requires only a standard pipette to achieve reliable\nresults. This stands in clear contrast to systems requiring expensive, high-precision robotic\nplotters. We have revised the manuscript to more precisely describe the operational requirements as\n\"a pipette, aided by the intrinsic guiding properties of the patterned chip.\"\nRevisions:\nIn the Revised Supplementary Information (Page 3), the following figure panel was added:\n“Supplementary Fig. 1 | Evaluation of tolerance for plotting position deviation. a, Schematic\ndiagram illustrating plotting position deviation. The arrow indicates the direction of droplet sliding.\nb, Schematic of the plotting model system (SA-IR800).\nc, Photographs of SA-IR800 arrays spotted\nwith different predefined positional deviations. The inset in the bottom right corner illustrates the\ncorresponding deviation patterns. Scale bar: 1 mm. Droplets were stained with food coloring for\nvisualization. d, Fluorescence images of the SA-IR800 arrays. Top: unblocked array; Bottom: blocked\narray. e, Quantitative analysis of fluorescence intensity for unblocked and blocked SA-IR800 arrays.\nThe data indicate that variations in spotting position within the allowable deviation range do not\nsignificantly affect the final fluorescence signal.”\nIt would be useful to comment on drying of the devices for storage and testing. The use of water\nand the binders could denature the proteins on the surface. Is it normal to dry such surfaces\nwithout protective layers?\nResponse: We thank the reviewer for raising this important point regarding protein stability during drying, which is indeed a critical consideration for any solid-phase immunoassay. In response to the question of whether drying such surfaces without protective layers is normal practice, we would like to clarify that the process of drying spotted capture antibodies to immobilize them on a solid surface is in fact a well established and widely used method in the fabrication of both commercial and research based protein microarrays (Ref. 17-29).\nIn our current protocol, the capture antibodies were prepared in a standard phosphate buffered\nsaline (PBS) solution. The chemical composition of the spotting buffer, including ionic strength and\npH, plays a key role in helping maintain protein structural integrity during the brief drying and\nimmobilization process. This conventional approach has proven effective for laboratory based\nimmunoassays, as supported by the high sensitivity and specificity achieved in our study. These\nperformance metrics confirm that under our controlled conditions, the drying process did not\ncompromise the assay's functionality.\nLooking ahead, we completely agree that developing a formulation for robust, long-term storage\nis a vital next step. This would vitrify upon drying, creating a protective microenvironment around\nthe immobilized antibodies and enabling the development of a ready-to-use, shelf-stable product.\nRevisions:\nIn the Revised Manuscript (Page 9), the following paragraph was added in the Discussion part:\n“The current study employs a standard drying based immobilization protocol that maintains\nantibody functionality, as validated by our experimental results. Future work will explore the\nincorporation of stabilizing additives to further enhance the shelf life and operational convenience\nof the arrays, facilitating their transition to ready to use formats for point-of-care applications.”\nThe patient studies are not described in the Methods and this will be required/important (were\nthe studies blinded?) Ethics is stated in the acknowledgement and does not include\ninclusion/exclusion criteria.\nResponse: We thank the reviewer for raising these critical points regarding the clinical study\nmethodology. This was a method-comparison study. To avoid bias, the analysis was performed in\na blinded manner. The researcher operating the DBDIY platform was unaware of the results from\nthe reference method, and the clinical laboratory technicians performing the reference test were\nunaware of the DBDIY results. The data were unblinded only after all experiments and data\ncollection were completed for subsequent comparative analysis. Samples with insufficient volume\nfor both the DBDIY and reference tests, or samples that were grossly hemolyzed, were excluded\nfrom the analysis.\nRevisions:\nIn the Revised Manuscript (Page 13), the following paragraph was added in the Methods part:\n“Blinding Procedure\nTo minimize bias, the study was performed in a blinded manner. The researchers performing the\nDBDIY array assays and data analysis were kept unaware of the sample status (positive/negative)\nand the corresponding results from the clinical reference methods. Conversely, the clinical\nlaboratory technicians performing the standard dry fluorescence immunoassay and\nimmunoturbidimetry were unaware of the results generated by the DBDIY platform. All\nexperimental data were collected independently, and the blinding was maintained until all assays\nand initial data processing were complete, after which the results were unblinded for the final\ncomparative analysis. Samples were excluded if they were of insufficient volume for both\nanalytical methods or showed gross hemolysis.”\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nPoint-to-point replies to reviewers and revisions made.\nReviewer #2:\nI am content to see the paper accepted. I think the removal of the ROC curve and addition of a\nBland-Altman plot adds rigour in the analysis and presentation of the data, particularly if being\nreviewed by clinical chemists. The additional data, both in the longitudinal model, and the\nincreased number of clinical samples also improves confidence. I appreciate the extra work in\ndemonstrating the spotting technique. Clarification around the reference methods and overall\nstatistical treatment are also important modifications. Clearly the paper has been greatly improved\n(albeit from a very good starting point). Well done to all the authors. It is nice to see peer review\nworking well and leading to an excellent outcome.\nGiven the number of changes it is probably worthwhile for the authors to take a step away from\nthe detail, and read the whole text afresh to check accuracy and the read-through.\nResponse: Thank you for your positive assessment and for acknowledging the improvements made\nto the manuscript. We greatly appreciate your constructive suggestions throughout the review\nprocess, which have significantly strengthened our work.\nIn direct response to your comments, we have made the following key revisions:\n• Removed the ROC curve and incorporated Bland-Altman analysis to enhance statistical rigor.\n• Increased sample sizes in both longitudinal and clinical studies to improve confidence in the\nresults.\n• Provided clearer descriptions of reference methods and overall statistical treatment.\n• Added data and demonstrations to clarify the spotting technique and platform operability.\nYour feedback also underscored the importance of larger sample sizes and more robust\nquantitative validation, helping to align the study more closely with clinical chemistry standards.\nMoreover, it brought to light a distinctive strength of our solid phase chip based platform: the clear\npresentation of fluorescence patterns enables direct visual readout, while the strong concordance\nbetween raw DBDIY signals and clinically determined concentrations supports semi quantitative\nanalysis and longitudinal tracking without requiring a standard curve. This approach simplifies the\nworkflow, reduces operational costs, and offers particular utility in resource limited settings, all\nwhile remaining fully compatible with quantitative calibration in laboratory environments.\nAs suggested, we have carefully re-read the entire manuscript to ensure accuracy, consistency, and\nclarity throughout.\nWe sincerely thank you for your insightful and supportive review, which has been instrumental in\nenhancing the quality and impact of this paper.\nReviewer #3:\nThank you for the authors’ efforts in revising the manuscript. The additional data and clarifications\nhave improved several aspects of the work and in general, the paper is an example of good\nscientific work. However, some important points related to the clinical relevance, interpretation of\ndiagnostic performance, and methodological transparency remain insufficiently addressed.\nResponse: We thank the reviewer for the constructive feedback and for acknowledging the\nimprovements made. We agree that clinical relevance, diagnostic performance interpretation, and\nmethodological transparency are essential for evaluating any novel diagnostic platform. Below we\naddress these points in detail.\n• Clinical relevance and diagnostic performance interpretation\nWe recognize that direct comparison of absolute concentration values between different\nimmunoassay platforms can be challenging due to inherent variations in reagents, detection\nprinciples, calibration, and data processing. Therefore, in validating our DBDIY platform, we\nfocused on demonstrating its ability to accurately reflect clinically relevant biological trends rather\nthan pursuing perfect numerical agreement with a reference method that uses fundamentally\ndifferent reagents and detection principles.\nThis approach is well established in the validation of novel diagnostic technologies, as it prioritizes\ncorrect identification of biomarker patterns, such as elevated CRP during infection or cytokine\ndynamics upon immune stimulation, over absolute concentration concordance. Our results show\nstrong correlation (R² > 0.9) and acceptable limits of agreement in Bland-Altman analysis across a\nlarge cohort of clinical samples, confirming that the DBDIY platform reliably captures the same\nbiological variations as the clinical reference method. This supports its suitability for clinical\nscreening and longitudinal monitoring in volume-limited settings.\n• Enhancing methodological transparency\nTo further improve transparency, we have now clearly specified both concentration-based and raw-\nsignal-based cutoff values. We have also converted the fluorescence signals for CRP and NT-proBNP\ninto concentration units to facilitate visual assessment of diagnostic agreement. Statistically\ninappropriate ROC curve depictions have been removed and replaced with confidence intervals\nand Bland-Altman analyses. These revisions provide a clearer and more statistically rigorous\npresentation of the platform’s diagnostic performance and enhance the reproducibility of our\nassay protocol.\nWe believe these clarifications and additions have strengthened the clinical relevance and\nmethodological transparency of our study, and we thank the reviewer for prompting these\nimportant improvements.\n- Abstract: the concept of high-throughput measurement of protein levels in small-volume\nbiological fluids does not seem compatible with the expression “especially in children (neonates?),\nspecific disease patients, and experimental animals.” In the context of clinical diagnosis and\nlaboratory testing, it is not clear how experimental animals are relevant. This may be of greater\nimportance in the field of intensive care (ICU).\nResponse: We thank the reviewer for this insightful observation regarding the phrasing in the\nAbstract. The original wording did indeed conflate two distinct application contexts, which could\nlead to ambiguity. To clarify the scope and relevance of our platform, we have revised the sentence\nto clearly separate its clinical diagnostic value (particularly for vulnerable populations including\nchildren and critically ill patients) from its preclinical utility (enabling longitudinal monitoring in\nexperimental animals). This modification ensures that the distinct importance of small-volume,\nhigh-throughput protein measurement in each setting is unambiguously communicated.\nRevisions:\nIn the Revised Manuscript (Page 2), the following paragraph was refined:\n“Accurate, high-throughput measurement of protein levels in small-volume biological fluids is\ncritical in both clinical and laboratory settings1-3. For clinical diagnosis and prognosis, this is\nespecially vital in vulnerable populations such as children and critically ill patients. In preclinical\nresearch, it enables longitudinal monitoring in experimental animals with minimal physiological\nimpact.”\n- The cutoffs formulated on the basis of the raw signal between the clinical methods and the DBDIY\nassay differ (Figure 4b, dashed lines).\nResponse: We thank the reviewer for raising the point regarding the different cutoff lines in Fig. 4b.\nThe visual distinction arises because the two lines are plotted using different units. The DBDIY\ncutoff is drawn based on the corresponding raw fluorescence signal, while the clinical cutoff is\nreported as a concentration. This presentation choice was intentional, as we sought to avoid\npotential bias introduced by inter-platform variations in standard sources, detection principles,\ncalibration models, and data processing, all of which can complicate direct concentration-based\ncomparisons.\nTo validate the quantitative performance of the DBDIY platform, we collected 112 pediatric\nperipheral blood samples and measured CRP using both the DBDIY array and the clinical dry\nfluorescence immunoassay (DFIA). To minimize the influence of differences in reference standards,\nwe constructed the calibration curve using samples with known clinical values. The derived\nconcentration results, as shown in Fig. 4, demonstrate that the DBDIY platform achieves 100%\nsensitivity and specificity (95% CI: 95.2 to 100%) and a high correlation (R² = 0.940) with the clinical\nmethod, whether based on raw fluorescence signals or on concentration values.\nThe strong concordance between the raw DBDIY signal and the clinical concentration indicates that\nthe platform can support semi-quantitative analysis and longitudinal monitoring without requiring\na standard curve (Supplementary Fig. 6). This feature is particularly valuable in resource-limited\nsettings, where results can be interpreted visually from the fluorescence pattern for relative trend\nassessment. In laboratory or clinical settings requiring precise quantification, concentration values\ncan be obtained reliably via the standard calibration curve and data processing.\nIn summary, the use of raw signal for cutoff visualization reflects our methodological approach to\ncross-platform comparison, while the additional validation with 112 samples confirms the\nplatform’s robust quantitative performance and operational flexibility.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n“We then validated its quantitative detection capability using 112 peripheral blood samples\nprospectively collected from children with suspected infection across multiple clinical departments,\nincluding pediatric respiratory, pediatric emergency, neonatology, pediatric ICU, pediatric clinic,\nand pediatric gastroenterology (Supplementary Table 2). The study was conducted in a blinded\nmanner. To minimize bias introduced by differences in reference standards, we constructed a\ncalibration curve using samples with known clinical values, thereby deriving concentration results\ntraceable to the clinical context. Following unblinding, 75 samples were classified as CRP-positive\nand 37 as CRP-negative by the clinical dry fluorescence immunoassay (DFIA). Compared against\nthis clinical classification, the DBDIY array showed no false positives or false negatives, achieving\n100% sensitivity and specificity (95% CI: 95.2% to 100%) (Fig. 4d). The fluorescence signals from\nstrong positive samples (#76, #37, and #36) were notably high, while signals from weak positive\nsamples (#46, #84, and #28) approached the critical threshold. Conversely, negative samples (#38,\n#39, and #78) exhibited extremely low fluorescence signals (Fig. 4e). Notably, even when the CRP\nlevels were below 0.5 μg mL-1 (the detection limit of the clinical method), the DBDIY array can still\noutput detectable signals (Fig. 4d). For the correlation analysis, 35 samples reporting CRP levels\nbelow the lower limit of detection (LOD) of the clinical method (< 0.5 μg mL⁻¹) were excluded, as\nthese values lacked precise numerical quantification. A strong correlation (R2 = 0.940) was\nobserved between the DBDIY array and the clinical method for CRP quantification (Fig. 4f and\nSupplementary Fig. 6). Bland-Altman analysis showed a mean bias of -1.78%, with the majority of\ndata points falling within the ±1.96 SD limits of agreement, indicating good concordance between\nthe DBDIY array and the DFIA (Fig. 4g).\nConsidering that the dynamic range of the DFIA is limited to 0.5-200 μg mL⁻¹, we further\nevaluated the DBDIY platform against a clinical high-sensitivity CRP (hs-CRP) immunoturbidimetry\nassay, which offers higher sensitivity and a broader measurable range. Using 192 independent\nclinical serum samples, the correlation coefficient between the DBDIY array and\nimmunoturbidimetry reached 0.973, demonstrating excellent agreement across a wide\nconcentration span (Fig. 4h, Supplementary Table 3, and Supplementary Fig. 7). Building on the\nhigh sensitivity of the platform, which affords considerable protocol flexibility, we further\nshortened the total assay time by reducing the sample dilution factor while maintaining\nclassification agreement with the clinical reference, as demonstrated in Extended Data Fig. 8. To\nverify the generality of the platform, NT-proBNP was measured in 30 clinical serum samples,\nyielding 100% sensitivity and specificity and a correlation of 0.973 with the clinical method\n(Extended Data Fig. 9 and Supplementary Table 4).\nThe strong concordance between raw DBDIY signals and the concentrations determined by\ndifferent clinical methods (DFIA, immunoturbidimetry, and CLIA) evident for both CRP and NT‑\nproBNP indicates that the platform supports semi‑quantitative analysis and longitudinal tracking\nwithout requiring a standard curve (Supplementary Fig. 6 and Supplementary Fig. 8). This enables\nvisual assessment of relative trends directly from fluorescence images. Such functionality is\nparticularly advantageous in resource-limited settings whereas in laboratory or clinical\nenvironments, quantitative results remain readily accessible through standard calibration and data\nprocessing. Collectively, the DBDIY array exhibits excellent sensitivity and reliability in detecting\nCRP levels in whole blood and serum, providing a practical tool for pediatric infection screening\nand monitoring of disease progression.”\nIn the Revised Manuscript (Page 20), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“Fig. 4 | Detection of CRP in children’s peripheral blood. a, Schematic diagram of CRP detection\nin children’s peripheral blood. b, Fluorescence images corresponding to CRP standards at various\nconcentrations. c, The calibration curve for CRP standards. The limit of detection (LOD) was defined\nas the mean blank signal plus three times its standard deviation (3 SD), while the limit of\nquantification (LOQ) was defined as the mean blank signal plus ten times the standard deviation\n(10 SD). d, CRP levels in peripheral blood of 110 children were detected by DBDIY (pink) and clinical\nmethod (purple). Dashed line was the cutoff value. The cutoff value corresponding to the maximum\nvalue of Youden’s index was selected as the sensitivity and specificity of the detection system. e,\nFluorescence images of strong positive samples (#76, #37, and #36), positive samples (#46, #84,\nand #28) and negative samples (#38, #39, and #78). f, 77 samples had quantitative detection in\nclinical method value among the 112 samples. Correlation between DBDIY method and clinical\nmethod to detect CRP in 77 samples. g, Bland-Altman analysis comparing DBDIY and dry\nfluorescence immunoassay (DFIA) results. h, Correlation plot comparing DBDIY and\nimmunoturbidimetry for CRP measurement in 192 clinical serum samples.”\nIn the Revised Supplementary Information (Page 8), the following figure was added:\n“Supplementary Fig. 6 | Detection of CRP in 112 clinical peripheral blood samples. a, Mean\nfluorescence intensity (MFI) values obtained from the DBDIY array (pink) and concentration values\nmeasured by the clinical DFIA (purple). The specificity and sensitivity of CRP detected by DBDIY in 112\nclinical samples were 100% (95% CI: 95.2% to 100%). The DBDIY cutoff (dashed line) was determined by\nROC analysis based on clinical classification, selecting the MFI corresponding to 100% sensitivity and\nspecificity. b, Comparison of DBDIY raw MFI against the clinical DFIA concentration for the same 77\nsamples.”\nIn the Revised Supplementary Information (Page 12), the following table was revised:\nCRP level\nSample ID Sex Age Positive/Negative Department\n(µg mL-1)\n#1 Female 8 years 50.1 Positive Pediatric emergency\n#2 Female 2 years 14.6 Positive Pediatric emergency\n#3 Female 5 years 3.6 Positive Pediatric emergency\n#4 Female 4 years 1 Positive Pediatric emergency\n#5 Male 4 years 41 Positive Pediatric emergency\n#6 Male 2 years 33.3 Positive Pediatric emergency\n#7 Male 3 months < 0.5 Negative Pediatric emergency\n#8 Female 4 years <0.5 Negative Pediatric emergency\n#9 Female 1 year 23.9 Positive Pediatric emergency\n#10 Female 9 months < 0.5 Negative Pediatric emergency\n#11 Female 9 months 0.5 Negative Pediatric emergency\n#12 Female 8 years 6.9 Positive Pediatric emergency\n#13 Male 15 years 3.2 Positive Pediatric emergency\n#14 Female 1 year < 0.5 Negative Pediatric emergency\n#15 Female 6 years 13.9 Positive Pediatric emergency\n#16 Male 6 years < 0.5 Negative Pediatric emergency\n#17 Female 14 years < 0.5 Negative Pediatric emergency\n#18 Male 3 years 0.6 Negative Pediatric emergency\n#19 Female 7 years < 0.5 Negative Pediatric emergency\n#20 Male 3 years 20.1 Positive Pediatric emergency\n#21 Female 15 years 2.1 Positive Pediatric emergency\n#22 Female 3 years 4.4 Positive Pediatric emergency\n#23 Female 5 years 36.8 Positive Pediatric emergency\n#24 Male 28 days < 0.5 Negative Neonatology\n#25 Female 3 years 13.3 Positive Pediatric emergency\n#26 Female 2 years 3.4 Positive Pediatric emergency\n#27 Male 2 years < 0.5 Negative Pediatric emergency\n#28 Male 6 months 1.5 Positive Pediatric emergency\n#29 Male 6 years < 0.5 Negative Pediatric emergency\n#30 Male 4 years 17.9 Positive Pediatric respiratory\n#31 Male 2 years < 0.5 Negative Pediatric ICU\n#32 Female 1 year 12.1 Positive Pediatric emergency\n#33 Female 5 years 3 Positive Pediatric respiratory\n#34 Female 6 years 17 Positive Pediatric clinic\n#35 Male 4 years 0.5 Negative Pediatric respiratory\n#36 Male 4 years 9.4 Positive Pediatric respiratory\n#37 Male 11 months 17 Positive Pediatric respiratory\n#38 Female 6 years 0.8 Negative Pediatric emergency\n#39 Male 1 year < 0.5 Negative Pediatric emergency\n#40 Female 2 years 9.9 Positive Pediatric respiratory\n#41 Male 13 years 4.9 Positive Pediatric emergency\n#42 Male 4 years 29.3 Positive Pediatric emergency\n#43 Female 5 years 8.4 Positive Pediatric clinic\n#44 Male 1 year 6.7 Positive Pediatric emergency\n#45 Female 6 years < 0.5 Negative Pediatric emergency\n#46 Male 5 years 2.8 Positive Pediatric emergency\n#47 Female 14 years < 0.5 Negative Pediatric emergency\n#48 Female 6 years < 0.5 Negative Pediatric emergency\n#49 Female 4 years 14.7 Positive Pediatric emergency\n#50 Male 7 years 4.4 Positive Pediatric emergency\n#51 Female 7 years < 0.5 Negative Pediatric emergency\n#52 Male 7 years < 0.5 Negative Pediatric emergency\n#53 Male 6 years < 0.5 Negative Pediatric emergency\n#54 Male 2 years 2.9 Positive Pediatric emergency\n#55 Female 6 years 16.6 Positive Pediatric emergency\n#56 Male 4 years 23.2 Positive Pediatric emergency\n#57 Female 3 years < 0.5 Negative Pediatric emergency\n#58 Male 1 months < 0.5 Negative Pediatric emergency\n#59 Female 15 years 4.6 Positive Pediatric emergency\n#60 Male 3 years 5 Positive Pediatric emergency\n#61 Male 1 year 4.9 Positive Pediatric emergency\n#62 Female 3 years 1.3 Positive Pediatric emergency\n#63 Male 1 year < 0.5 Negative Pediatric emergency\n#64 Female 11 months 2.3 Positive Pediatric emergency\n#65 Male 1 year 6.6 Positive Pediatric respiratory\n#66 Female 4 years 6.2 Positive Pediatric respiratory\n#67 Female 3 years < 0.5 Negative Pediatric respiratory\n#68 Male 5 years 9.5 Positive Pediatric ICU\n#69 Female 5 years 15.9 Positive Pediatric emergency\n#70 Male 7 years 65.6 Positive Pediatric respiratory\n#71 Male 3 years 3.9 Positive Pediatric respiratory\n#72 Female 3 years < 0.5 Negative Pediatric respiratory\n#73 Male 4 years < 0.5 Negative Pediatric emergency\n#74 Female 3 years < 0.5 Negative Pediatric respiratory\n#75 Female 7 years 17.1 Positive Pediatric emergency\n#76 Male 2 months 31.7 Positive Pediatric respiratory\n#77 Female 6 years < 0.5 Negative Pediatric gastroenterology\n#78 Female 3 years < 0.5 Negative Pediatric gastroenterology\n#79 Female 5 years < 0.5 Negative Pediatric respiratory\n#80 Female 7 years < 0.5 Negative Pediatric emergency\n#81 Male 3 years 18.1 Positive Pediatric emergency\n#82 Male 9 years 43.8 Positive Pediatric emergency\n#83 Female 1 year 6.3 Positive Pediatric emergency\n#84 Female 1 year 2.2 Positive Pediatric emergency\n#85 Female 14 years < 0.5 Negative Pediatric emergency\n#86 Male 10 months 1.8 Positive Pediatric emergency\n#87 Male 9 years 2.4 Positive Pediatric emergency\n#88 Female 4 years 34.6 Positive Pediatric emergency\n#89 Male 9 years 53.8 Positive Pediatric emergency\n#90 Male 14 years 32.8 Positive Pediatric emergency\n#91 Female 8 years 3.7 Positive Pediatric emergency\n#92 Male 4 years 55.9 Positive Pediatric emergency\n#93 Female 14 years 3.4 Positive Pediatric emergency\n#94 Male 6 years 23.2 Positive Pediatric emergency\n#95 Female 3 years 2.4 Positive Pediatric emergency\n#96 Female 7 years 2.5 Positive Pediatric respiratory\n#97 Female 5 years 24.5 Positive Pediatric respiratory\n#98 Female 4 years 9.4 Positive Pediatric respiratory\n#99 Female 12 years < 0.5 Negative Pediatric emergency\n#100 Male 9 years < 0.5 Negative Pediatric respiratory\n#101 Female 3 years 3.4 Positive Pediatric emergency\n#102 Female 4 years 12.7 Positive Pediatric emergency\n#103 Female 8 years 31.2 Positive Pediatric emergency\n#104 Male 4 years 29.9 Positive Pediatric emergency\n#105 Female 3 years 5.2 Positive Pediatric respiratory\n#106 Male 3 months < 0.5 Negative Neonatology\n#107 Female 2 years 3.1 Positive Pediatric emergency\n#108 Male 3 years 17.1 Positive Pediatric emergency\n#109 Male 1 year 49.1 Positive Pediatric emergency\n#110 Male 9 years 11.8 Positive Pediatric emergency\n#111 Female 10 years 4 Positive Pediatric emergency\n#112 Male 6 years 23.3 Positive Pediatric emergency\n#113 Male 4 years 58.4 Positive Pediatric emergency\n#114 Male 3 years 10.7 Positive Pediatric respiratory\n#115 Female 7 years 4 Positive Pediatric respiratory\n#116 Male 3 years 3.6 Positive Pediatric respiratory\n#117 Male 2 years 2.6 Negative Pediatric emergency\n#118 Female 7 months 0.9 Negative Pediatric emergency\n#119 Male 1 year < 0.5 Negative Pediatric respiratory\n- Sentence 243, “A cohort of 100 peripheral blood samples from children (50 positive and 50\nnegative)”, indicates that the samples were preselected according to the routine clinical cutoff.\nResponse: We thank the reviewer for this observation. We would like to clarify that the 100\npediatric peripheral blood samples were collected prospectively from children with suspected\ninfection, without any preselection based on prior CRP results. The study was conducted in a\nblinded manner: the DBDIY operator was unaware of the clinical status or reference results, and\nthe clinical laboratory was unaware of the DBDIY results. After unblinding and analysis, we found\nthat 50 samples were classified as positive and 50 as negative by the clinical reference method.\nTo avoid any unintended implication of preselection, we have revised the text in the manuscript to\nclearly state the blinded prospective collection process first, and to present the final count of 50\npositive and 50 negative samples as an analytical outcome, not a selection criterion.\nRevisions:\nIn the Revised Manuscript (Page 6), the following paragraph was refined:\n\"We then validated its quantitative detection capability using 112 peripheral blood samples\nprospectively collected from children with suspected infection across multiple clinical departments,\nincluding pediatric respiratory, pediatric emergency, neonatology, pediatric ICU, pediatric clinic,\nand pediatric gastroenterology (Supplementary Table 2). The study was conducted in a blinded\nmanner. To minimize bias introduced by differences in reference standards, we constructed a\ncalibration curve using samples with known clinical values, thereby deriving concentration results\ntraceable to the clinical context. Following unblinding, 75 samples were classified as CRP-positive\nand 37 as CRP-negative by the clinical dry fluorescence immunoassay (DFIA). Compared against\nthis clinical classification, the DBDIY array showed no false positives or false negatives, achieving\n100% sensitivity and specificity (95% CI: 95.2% to 100%) (Fig. 4d).\"\n- For the newly developed method, the authors selected the cutoff at the maximum value of\nYouden’s index, although this cutoff is not explicitly stated.\nResponse: We appreciate the reviewer’s attention to the cutoff selection process. All tests were\nperformed in a blinded manner. We conducted ROC analysis based on the positive/negative\nclassifications from the clinical reference methods (DFIA and CLIA) and initially identified the raw\nfluorescence signal that yielded 100% sensitivity and 100% specificity as the cutoff for the DBDIY\narray.\nConsidering the limited sample size in our current cohort, and to ensure the robustness and\ngeneralizability of the cutoff across different assay conditions and future larger studies, we adopted\nthe threshold corresponding to the maximum Youden’s index as the reported cutoff criterion in\nthe main text. This approach is widely used and provides a balanced, statistically optimized\ncriterion that is less susceptible to small-sample variability.\nRevisions:\nIn the Revised Manuscript (Page 13), the following paragraph was refined:\n“Blinding procedure and cutoff determination\nTo minimize bias, all analyses were conducted in a blinded manner. The researchers performing the\nDBDIY array assays and data analysis were unaware of the sample status (positive or negative) and\nthe results from the clinical reference methods. Similarly, clinical laboratory technicians conducting\nthe standard DFIA, immunoturbidimetry, and CLIA were unaware of the results generated by the\nDBDIY platform. All experimental data were collected independently, and blinding was maintained\nuntil all assays and initial data processing were completed. Afterward, results were unblinded for\nfinal comparative analysis. Samples were excluded from the final comparative analysis if they had\ninsufficient volume for both analytical methods or if they showed gross hemolysis.\nThe diagnostic cutoff for the DBDIY array was determined based on the clinical classifications\n(positive or negative) established by the reference methods. Under the blinded protocol, ROC\nanalysis was performed to identify the raw fluorescence signal corresponding to optimal\nclassification performance. In the present cohort, the threshold that yielded 100% sensitivity and\n100% specificity coincided with the point of maximum Youden’s index. To ensure statistical\nrobustness and generalizability across assay conditions and future studies, we adopted this\nthreshold, corresponding to the maximum Youden’s index, as the reported cutoff. This widely\naccepted approach provides a balanced and resilient criterion for diagnostic threshold selection,\nregardless of sample size.”\n- It is unusual that both cutoffs in Figures 4b and 9b are defined using raw signals, as cutoffs are\ntypically applied to analyte concentrations. It would be valuable to see how the agreement\nbetween both cutoffs (new and established) appears when expressed in final concentration units,\nand to compare these with those used in routine clinical practice. It would also be helpful to add\ncutoffs and/or error grids to Figure 4g to visualize not only analytical but also clinical agreement.\nResponse: We thank the reviewer for raising this important point regarding cutoff presentation.\nWe acknowledge that diagnostic cutoffs are conventionally expressed in concentration units, and\nwe appreciate the opportunity to clarify our methodology and the steps we have taken to enhance\ninterpretability.\nIn our initial analysis, we presented cutoffs based on raw fluorescence signals to facilitate a direct\ncalibration-independent comparison of signal distribution between positive and negative samples.\nThis approach highlights the inherent separation capability of our raw data and is particularly\nrelevant for demonstrating the platform's potential for semi-quantitative visual assessment.\nHowever, we fully agree with the reviewer that alignment with established clinical practice requires\nevaluation in concentration terms. To address this, we have now performed the following\nadditional analyses and modifications to the manuscript:\nWe have derived concentration values for all clinical samples using our calibration curves. In the\nrevised Manuscript (Fig. 4d for CRP and Extended Data Fig. 9 for NT-proBNP), we present direct\ncomparisons between DBDIY-derived concentrations and the reference method concentrations.\nThese plots include the established clinical decision thresholds, allowing for a clear visual\nassessment of diagnostic agreement in standard units.\nThese revisions provide the requested concentration-based comparison and integrate visual cues\nfor clinical concordance directly into the main analytical figures. We believe these additions\nsignificantly strengthen the clinical interpretability of our validation data and align the presentation\nmore closely with standard diagnostic reporting.\nWe are grateful for this insightful suggestion, which has improved the clarity and clinical relevance\nof our data presentation.\nRevisions:\nIn the Revised Manuscript (Page 20), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“Fig. 4 | Detection of CRP in children’s peripheral blood. a, Schematic diagram of CRP detection\nin children’s peripheral blood. b, Fluorescence images corresponding to CRP standards at various\nconcentrations. c, The calibration curve for CRP standards. The limit of detection (LOD) was defined\nas the mean blank signal plus three times its standard deviation (3 SD), while the limit of\nquantification (LOQ) was defined as the mean blank signal plus ten times the standard deviation\n(10 SD). d, CRP levels in peripheral blood of 110 children were detected by DBDIY (pink) and clinical\nmethod (purple). Dashed line was the cutoff value. The cutoff value corresponding to the maximum\nvalue of Youden’s index was selected as the sensitivity and specificity of the detection system. e,\nFluorescence images of strong positive samples (#76, #37, and #36), positive samples (#46, #84,\nand #28) and negative samples (#38, #39, and #78). f, 77 samples had quantitative detection in\nclinical method value among the 112 samples. Correlation between DBDIY method and clinical\nmethod to detect CRP in 77 samples. g, Bland-Altman analysis comparing DBDIY and dry\nfluorescence immunoassay (DFIA) results. h, Correlation plot comparing DBDIY and\nimmunoturbidimetry for CRP measurement in 192 clinical serum samples.”\nIn the Revised Manuscript (Page 30), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“b, Fluorescence images of NT-proBNP detected by DBDIY in 30 clinical samples. c, NT-proBNP in 30\nclinical serum samples were detected by DBDIY (pink) and clinical method (purple). Dashed line was the\ncutoff value. The specificity and sensitivity of NT-proBNP detected by DBDIY in 30 clinical samples were\n100% (95% CI: 73.5% to 100%). d, e, Comparative assessment of the DBDIY method and CLIA for\nmeasuring NT-proBNP in 30 clinical serum samples, presented as a correlation plot (d) and a Bland-\nAltman analysis (e).”\n- For the Bland–Altman analysis (new figure 4h), the limits of agreement were calculated and could\nbe discussed. For the serum assay measured from the same sample, limits of ±75% are very high.\nResponse: We acknowledge the reviewer’s observation regarding the width of the limits of\nagreement (LoA ±75%) in the Bland-Altman analysis. This degree of variability is not uncommon\nwhen comparing immunoassays based on fundamentally different principles, specifically our solid-\nphase, plasmonic enhanced fluorescence platform versus the solution-phase immunoturbidimetry\nreference method, which employs distinct antibody pairs, calibrators, and signal generation\nmechanisms.\nA closer inspection of the data points contributing to the wider LoA, as exemplified by the samples\nlisted in Table R1 (e.g., #5, #46, #85, #119, #138), reveals that a substantial proportion of the\nobserved dispersion occurs in the low concentration region. In these cases, the DBDIY platform\nfrequently reported higher values than immunoturbidimetry, suggesting a difference in analytical\nsensitivity between the two methods. This pattern is consistent with the enhanced low-end\ndetection capability often afforded by plasmonic enhanced substrates, indicating that our method\nmay retain better performance near the lower limit of quantification.\nImportantly, despite these quantifiable differences in absolute values, which are expected between\nsuch distinct platforms, the mean bias was minimal (-0.96%) and the correlation was exceptionally\nhigh (R² = 0.973). This confirms that both methods capture the same clinical trends and biological\nvariations, which is the primary criterion for a screening and monitoring tool. The calculated LoA\nprovides a transparent and useful measure of the expected inter-method variability for result\ninterpretation in practice.\nTable R1 | Selected samples showing larger deviations between DBDIY and immunoturbidimetry\nDBDIY Immunoturbidimetry\n(µg mL-1) (µg mL-1)\n#5 0.4791 0.23\n#16 31.44029 65.72\n#46 1.32932 0.6\n#47 6.78426 3.29\n#79 4.22116 9.12\n#85 0.49974 0.19\n#87 21.61062 9.66\n#96 0.58871 1.29\n#113 10.03631 3.5\n#115 192.6521 84.12\n#119 0.99616 0.45\n#138 0.17777 0.46\n#170 0.31539 0.88\n#178 0.13934 0.34\n- The authors state that “Collectively, the DBDIY array demonstrated excellent performance in\nquantitatively detecting CRP levels in whole blood and serum samples, enabling faster and more\naccurate diagnosis of infections in children, as well as effective monitoring of infection progression\ntrends (Extended Data Fig. 8).” However, the data in Figure 8 suggest that the DBDIY platform can\ndeliver results within 10 minutes to 1 hour, which is comparable to the normal clinical turnaround\ntime for CRP (approximately 10 minutes). The data presented in Figure 8 do not allow any\nconclusions regarding result accuracy.\nResponse: We thank the reviewer for this critical and constructive observation. We fully agree\nthat the original statement overinterpreted the data presented in Extended Data Fig. 8, which\ndemonstrates the platform’s protocol flexibility and signal stability under shortened incubation\nconditions and does not indicate a direct comparative advantage in diagnostic speed or accuracy\nover established clinical CRP tests.\nTo address this, we have revised the relevant text in the manuscript to accurately reflect the\nintended message:\nThe claim of enabling “faster and more accurate diagnosis” has been removed.\nThe role of Extended Data Fig. 8 is now clearly described as illustrating how the high sensitivity of\nthe platform allows for a reduction in sample dilution, thereby shortening the total assay time\nwhile maintaining classification agreement with the clinical reference.\nRevisions:\nIn the Revised Manuscript (Page 7), the following paragraph was refined:\n“Building on the high sensitivity of the platform, which affords considerable protocol flexibility, we\nfurther shortened the total assay time by reducing the sample dilution factor while maintaining\nclassification agreement with the clinical reference, as demonstrated in Extended Data Fig. 8.”\n“Collectively, the DBDIY array exhibits excellent sensitivity and reliability in detecting CRP levels in\nwhole blood and serum, providing a practical tool for pediatric infection screening and monitoring\nof disease progression.”\nIn the Revised Manuscript (Page 29), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“Extended Data Fig. 8 | Rapid detection of CRP in peripheral blood of children. Four CRP-positive (#113,\n#114, #115, #116) and three CRP-negative (#117, #118, #119) samples were analyzed under two\nconditions: a shortened protocol with 100-fold dilution (5 min sample incubation followed by 5 min\nDAb-IR800 incubation, total 10 min; pink) and the standard protocol with 10,000-fold dilution (30 min\nsample incubation followed by 30 min DAb-IR800 incubation, total 1 h; light purple). The sample\nclassification from both conditions matches the clinical reference (purple), and the signal trends are\nconsistent, demonstrating that reducing the dilution factor shortens the total assay time. The dashed\nline separates positive (left) from negative (right) samples.”\n- Figure 9d (ROC analysis) provides no additional information. Could the ROC curve be\nreconstructed using the calculated confidence bands, and could these confidence bands be\nvisualized in the plot? Analogous to the CRP example, it would be valuable to present the\ncorrelation coefficient for NT-proBNP not for the raw signal, but for the final method comparison.\nResponse: We thank the reviewer for this valuable suggestion. In response, we have removed the\noriginal ROC curve (Figure 9d) and performed an additional validation study using 30 independent\nclinical serum samples. NT-proBNP was measured on these samples with both the DBDIY platform\nand the clinical chemiluminescence immunoassay (CLIA). The fluorescence signals obtained from\nthe DBDIY array were converted to concentration values using a standard calibration curve. As\nshown in Supplementary Fig. 8, excellent agreement was observed between the two methods,\nwhether comparing raw fluorescence signals or derived concentrations. The correlation analysis\nfor the concentration values yielded a high coefficient (R² > 0.95), confirming the quantitative\nreliability of the DBDIY platform for NT-proBNP detection.\nRevisions:\nIn the Revised Manuscript (Page 30), the following figure panel was revised:\nThe sentence in the figure legend was corrected as follows:\n“b, Fluorescence images of NT-proBNP detected by DBDIY in 30 clinical samples. c, NT-proBNP in 30\nclinical serum samples were detected by DBDIY (pink) and clinical method (purple). Dashed line was the\ncutoff value. The specificity and sensitivity of NT-proBNP detected by DBDIY in 30 clinical samples were\n100% (95% CI: 73.5% to 100%). d, e, Comparative assessment of the DBDIY method and CLIA for\nmeasuring NT-proBNP in 30 clinical serum samples, presented as a correlation plot (d) and a Bland-\nAltman analysis (e).”\nIn the Revised Supplementary Information (Page 10), the following figure was added:\n“Supplementary Fig. 8 | Detection of NT-proBNP in 30 clinical serum samples. a, MFI values\nobtained from the DBDIY array (pink) and concentration values measured by the clinical CLIA\n(purple). The specificity and sensitivity of NT-proBNP detected by DBDIY in 30 clinical samples were\n100% (95% CI: 73.5% to 100%). The DBDIY cutoff (dashed line) was determined by ROC analysis\nbased on clinical classification, selecting the MFI corresponding to 100% sensitivity and specificity.\nb, Comparison of DBDIY raw MFI against the clinical CLIA concentration for the same 30 samples.”\nIn the Revised Supplementary Information (Page 19), the following table was revised:\nNT-ProBNP level\nSample ID Sex Age Positive/Negative\n(pg mL-1)\n#1 Male 52 years 125 Negative\n#2 Female 70 years 177 Negative\n#3 Male 62 years 24.2 Negative\n#4 Male 66 years 6840 Positive\n#5 Male 60 years 529 Negative\n#6 Male 68 years 287 Negative\n#7 Female 70 years 232 Negative\n#8 Male 71 years 3200 Positive\n#9 Male 64 years 1050 Positive\n#10 Male 68 years 275 Negative\n#11 Male 66 years 81.4 Negative\n#12 Male 69 years 1080 Positive\n#13 Male 64 years 177 Negative\n#14 Female 63 years 22.5 Negative\n#15 Male 62 years 125 Negative\n#16 Female 71 years 1680 Positive\n#17 Male 57 years 60.3 Negative\n#18 Female 70 years 25200 Positive\n#19 Male 53 years 2370 Positive\n#20 Male 67 years 476 Negative\n#21 Female 58 years 51.2 Negative\n#22 Male 72 years 12800 Positive\n#23 Female 58 years 2380 Positive\n#24 Male 55 years 2660 Positive\n#25 Male 58 years 79 Negative\n#26 Male 59 years 4130 Positive\n#27 Female 69 years 820 Negative\n#28 Male 68 years 775 Negative\n#29 Female 64 years 14900 Positive\n#30 Male 60 years 284 Negative\nPoint-to-point replies to reviewers and revisions made.\nReviewer #3:\nHaving reviewed the authors’ detailed point-by-point response and the corresponding revisions, I\nfind the manuscript significantly and satisfactorily improved. The key issues I raised have been\nthoughtfully addressed.\nThe authors have not only implemented the requested changes but have also provided additional\nvalidation data (e.g., the new 30-sample NT-proBNP study), which strengthens the work beyond\nmy initial requests. The revised manuscript is more balanced, transparent, and clinically\ninterpretable.\nI am satisfied with the revisions. The authors have been diligent in addressing the critiques, and\nthe paper is now much stronger for it. I recommend acceptance of the manuscript in its current\nform. Well done.\nResponse: Thank you very much for your final assessment and your encouraging feedback on our\nrevised manuscript. We sincerely appreciate your recognition of our efforts in addressing your\nearlier critiques. We are delighted to hear that the additional validations, such as the NT-proBNP\nstudy, have further strengthened the manuscript and that you find the revised version to be more\nbalanced, transparent, and clinically interpretable.\nYour constructive suggestions throughout the review process have been invaluable in improving\nthe quality of our work. Thank you again for your time and insightful comments. We are very\npleased that you now recommend acceptance of the manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_2": "I am content to see the paper accepted. I think the removal of the ROC curve and addition of a Bland-Altman plot adds rigour in the analysis and presentation of the data, particularly if being reviewed by clinical chemists. The additional data, both in the longitudinal model, and the increased number of clinical samples also improves confidence. I appreciate the extra work in demonstrating the spotting technique. Clarification around the reference methods and overall statistical treatment are also important modifications. Clearly the paper has been greatly improved (albeit from a very good starting point). Well done to all the authors. It is nice to see peer review working well and leading to an excellent outcome.\nGiven the number of changes it is probably worthwhile for the authors to take a step away from the detail, and read the whole text afresh to check accuracy and the read-through.", "reviewer_3": "Thank you for the authors’ efforts in revising the manuscript. The additional data and clarifications have improved several aspects of the work and in general, the paper is an example of good scientific work. However, some important points related to the clinical relevance, interpretation of diagnostic performance, and methodological transparency remain insufficiently addressed.\n- Abstract: the concept of high-throughput measurement of protein levels in small-volume biological fluids does not seem compatible with the expression “especially in children (neonates?), specific disease patients, and experimental animals.” In the context of clinical diagnosis and laboratory testing, it is not clear how experimental animals are relevant. This may be of greater importance in the field of intensive care (ICU).\n- The cutoffs formulated on the basis of the raw signal between the clinical methods and the DBDIY assay differ (Figure 4b, dashed lines).\n- Sentence 243, “A cohort of 100 peripheral blood samples from children (50 positive and 50 negative)”, indicates that the samples were preselected according to the routine clinical cutoff.\n- For the newly developed method, the authors selected the cutoff at the maximum value of Youden’s index, although this cutoff is not explicitly stated.\n- It is unusual that both cutoffs in Figures 4b and 9b are defined using raw signals, as cutoffs are typically applied to analyte concentrations. It would be valuable to see how the agreement between both cutoffs (new and established) appears when expressed in final concentration units, and to compare these with those used in routine clinical practice. It would also be helpful to add cutoffs and/or error grids to Figure 4g to visualize not only analytical but also clinical agreement.\n- For the Bland–Altman analysis (new figure 4h), the limits of agreement were calculated and could be discussed. For the serum assay measured from the same sample, limits of ±75% are very high.\n- The authors state that “Collectively, the DBDIY array demonstrated excellent performance in quantitatively detecting CRP levels in whole blood and serum samples, enabling faster and more accurate diagnosis of infections in children, as well as effective monitoring of infection progression trends (Extended Data Fig. 8).” However, the data in Figure 8 suggest that the DBDIY platform can deliver results within 10 minutes to 1 hour, which is comparable to the normal clinical turnaround time for CRP (approximately 10 minutes). The data presented in Figure 8 do not allow any conclusions regarding result accuracy.\n- Figure 9d (ROC analysis) provides no additional information. Could the ROC curve be reconstructed using the calculated confidence bands, and could these confidence bands be visualized in the plot? Analogous to the CRP example, it would be valuable to present the correlation coefficient for NT-proBNP not for the raw signal, but for the final method comparison."}, "author_response": "Response: Thank you very much for your final assessment and your encouraging feedback on our revised manuscript. We sincerely appreciate your recognition of our efforts in addressing your earlier critiques. We are delighted to hear that the additional validations, such as the NT-proBNP study, have further strengthened the manuscript and that you find the revised version to be more balanced, transparent, and clinically interpretable.\nYour constructive suggestions throughout the review process have been invaluable in improving the quality of our work. Thank you again for your time and insightful comments. We are very pleased that you now recommend acceptance of the manuscript."}, {"round": 3, "reviewer_comments": {"reviewer_3": "Having reviewed the authors’ detailed point-by-point response and the corresponding revisions, I find the manuscript significantly and satisfactorily improved. The key issues I raised have been thoughtfully addressed.\nThe authors have not only implemented the requested changes but have also provided additional validation data (e.g., the new 30-sample NT-proBNP study), which strengthens the work beyond my initial requests. The revised manuscript is more balanced, transparent, and clinically interpretable.\nI am satisfied with the revisions. The authors have been diligent in addressing the critiques, and the paper is now much stronger for it. I recommend acceptance of the manuscript in its current form. Well done."}, "author_response": ""}]

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