bluuebunny/crossref_metadata_2025 huggingface dataset:
Physical Activity, Sleeping Problems, Weight, Feelings of Social Isolation, and Quality of Life of Older Adults After Coronavirus Infection: A Longitudinal Cohort Study
Authors: Kuijpers Thomas G. , Gerkema Maartje H. , Engels Gwenda , Schipper Maarten , Herber Gerrie-Cor M.
Published: January 2024

Background:

There is debate as to whether a coronavirus infection (SARS-CoV-2) affects older adults’ physical activity, sleeping problems, weight, feelings of social isolation, and quality of life (QoL). We investigated differences in these outcomes between older adults with and without coronavirus infection over 180 days following infection.

Methods:

We included 6789 older adults (65+) from the Lifelines COVID-19 cohort study who provided data between April 2020 and June 2021. Older adults (65+) with and without coronavirus infection were matched on sex, age, education, living situation, body mass index, smoking status, vulnerable health, time of infection, and precoronavirus health outcome. Weighted linear mixed models, adjusted for strictness of governmental policy measures, were used to compare health outcomes after infection between groups.

Results:

In total, 309 participants were tested positive for coronavirus. Eight days after infection, older adults with a coronavirus infection engaged in less physical activity, had more sleeping problems, weighed less, felt more socially isolated, and had a lower QoL than those without an infection. Differences in weight, feelings of social isolation, and QoL were absent after 90 days. However, differences in physical activity were still present at 90 days following infection and sleeping problems were present at 180 days.

Conclusion:

Our findings found negative associations of coronavirus infection with all the examined outcomes, which for physical activity persisted for 90 days and sleeping problems for 180 days. Magnitudes of estimated effects on physical activity and sleeping problems remain uncertain.
Risk Factors and Inequities in Transportation Injury and Mortality in the Canadian Census Health and Environment Cohorts (CanCHECs)
Authors: Branion-Calles Michael , Winters Meghan , Rothman Linda , Harris M. Anne
Published: January 2024

Background:

Road traffic injury contributes substantially to morbidity and mortality. Canada stands out among developed countries in not conducting a national household travel survey, leading to a dearth of national transportation mode data and risk calculations that have appropriate denominators. Since traffic injuries are specific to the mode of travel used, these risk calculations should consider travel mode.

Methods:

Census data on mode of commute is one of the few sources of these data for persons aged 15 and over. This study leveraged a national data linkage cohort, the Canadian Census Health and Environment Cohorts, that connects census sociodemographic and commute mode data with records of deaths and hospitalizations, enabling assessment of road traffic injury associations by indicators of mode of travel (commuter mode). We examined longitudinal (1996–2019) bicyclist, pedestrian, and motor vehicle occupant injury and fatality risk in the Canadian Census Health and Environment Cohorts by commuter mode and sociodemographic characteristics using Cox proportional hazards models within the working adult population.

Results:

We estimated positive associations between commute mode and same mode injury and fatality, particularly for bicycle commuters (hazard ratios for bicycling injury was 9.1 and for bicycling fatality was 11). Low-income populations and Indigenous people had increased injury risk across all modes.

Conclusions:

This study shows inequities in transportation injury risk in Canada and underscores the importance of adjusting for mode of travel when examining differences between population groups.
Update Lessons from PET Imaging Part II: A Systematic Critical Review on Therapeutic Plasma Concentrations of Antidepressants
Authors: Hart Xenia M. , Spangemacher Moritz , Defert Julie , Uchida Hiroyuki , Gründer Gerhard
Published: January 2024

Background:

Compared with antipsychotics, the relationship between antidepressant blood (plasma or serum) concentrations and target engagement is less well-established.

Methods:

We have discussed the literature on the relationship between plasma concentrations of antidepressant drugs and their target occupancy. Antidepressants reviewed in this work are citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, venlafaxine, duloxetine, milnacipran, tricyclic antidepressants (amitriptyline, nortriptyline, and clomipramine), bupropion, tranylcypromine, moclobemide, and vortioxetine. Four electronic databases were systematically searched.

Results:

We included 32 articles published 1996–2022. A strong relationship between serotonin transporter (SERT) occupancy and drug concentration is well established for selective serotonin reuptake inhibitors. Lower limits of recommended therapeutic reference ranges largely corroborate with the findings from positron emission tomography studies (80% SERT occupancy). Only a few novel studies have investigated alternative targets, that is, norepinephrine transporters (NETs), dopamine transporters (DATs), or monoamine oxidase A (MAO-A). For certain classes of drugs, positron emission tomography study data are inconclusive. Low DAT occupancy after bupropion treatment speculates its discussed mechanism of action. For MAO inhibitors, a correlation between drug concentration and MAO-A occupancy could not be established.

Conclusions:

Neuroimaging studies are critical in TDM-guided therapy for certain antidepressants, whereas for bupropion and MAO inhibitors, the available evidence offers no further insight. Evidence for selective serotonin reuptake inhibitors is strong and justifies a titration toward suggested ranges. For SNRIs, duloxetine, and venlafaxine, NETs are sufficiently occupied, well above the SERT efficacy threshold. For these drugs, a titration toward higher concentrations (within the recommended range) should be considered in case of no response at lower concentrations.
Predictive Performance of a Gentamicin Pharmacokinetic Model in Term Neonates with Perinatal Asphyxia Undergoing Controlled Therapeutic Hypothermia
Authors: van der Veer Marlotte A. A. , de Haan Timo R. , Franken Linda G. W. , Groenendaal Floris , Dijk Peter H. , de Boode Willem P. , Simons Sinno , Dijkman Koen P. , van Straaten Henrica L.M. , Rijken Monique , Cools Filip , Nuytemans Debbie H. G. M. , van Kaam Anton H. , Bijleveld Yuma. A. , Mathôt Ron A. A. ,   for the PharmaCool Study Group
Published: January 2024

Background:

Model validation procedures are crucial when population pharmacokinetic (PK) models are used to develop dosing algorithms and to perform model-informed precision dosing. We have previously published a population PK model describing the PK of gentamicin in term neonates with perinatal asphyxia during controlled therapeutic hypothermia (TH), which showed altered gentamicin clearance during the hypothermic phase dependent on gestational age and weight. In this study, the predictive performance and generalizability of this model were assessed using an independent data set of neonates with perinatal asphyxia undergoing controlled TH.

Methods:

The external data set contained a subset of neonates included in the prospective observational multicenter PharmaCool Study. Predictive performance was assessed by visually inspecting observed-versus-predicted concentration plots and calculating bias and precision. In addition, simulation-based diagnostics, model refitting, and bootstrap analyses were performed.

Results:

The external data set included 323 gentamicin concentrations of 39 neonates. Both the model-building and external data set included neonates from multiple centers. The original gentamicin PK model predicted the observed gentamicin concentrations with adequate accuracy and precision during all phases of controlled TH. Model appropriateness was confirmed with prediction-corrected visual predictive checks and normalized prediction distribution error analyses. Model refitting to the merged data set (n = 86 neonates with 935 samples) showed accurate estimation of PK parameters.

Conclusions:

The results of this external validation study justify the generalizability of the gentamicin dosing recommendations made in the original study for neonates with perinatal asphyxia undergoing controlled TH (5 mg/kg every 36 or 24 h with gestational age 36–41 and 42 wk, respectively) and its applicability in model-informed precision dosing.
Fluorescence-Based Lateral Flow Immunoassay for Quantification of Infliximab: Analytical and Clinical Performance Evaluation
Authors: Kim Eun Sil , Chon Hyangah , Kwon Yiyoung , Lee Misook , Kim Mi Jin , Choe Yon Ho
Published: January 2024

Background:

Therapeutic drug monitoring of infliximab (IFX) can improve treatment outcomes; however, the temporal gap between drug concentration monitoring and subsequent availability restricts its practical application. To address this issue, an automated monitoring method, AFIAS IFX, was developed to rapidly and accurately analyze IFX concentration in blood. The analytical and clinical performances of this method were assessed to establish its clinical utility.

Methods:

The analytical performance of AFIAS IFX was evaluated according to Clinical and Laboratory Standard Institute guidelines. For clinical validation, AFIAS IFX was compared with 3 established enzyme-linked immunosorbent assay kits (LISA TRACKER, RIDASCREEN, and ImmunoGuide) using 100 consecutive samples from 28 patients treated with IFX. Passing–Bablok regression and Bland–Altman analyses were performed to compare the methods.

Results:

The detection and quantification limits of AFIAS IFX were 0.12 and 0.20 mcg/mL, respectively. Furthermore, AFIAS IFX analyzed samples within 10 minutes for concentrations up to 50 mcg/mL, exhibiting reproducibility (coefficient of variation [CV] ≤7.8%) and accuracy (recovery 98%–101%) with serum, plasma, and whole blood samples. Clinically, it exhibited a good correlation with the 3 established enzyme-linked immunosorbent assay kits. For patients treated with Remicade (IFX), the Passing–Bablok regression slope was 1.001–1.259, with a mean difference of −1.48 to 0.28 mcg/mL. For patients treated with CT-P13, the Passing–Bablok regression slope was 0.974–1.254, with a mean difference of −2.44 to 0.15 mcg/mL.

Conclusions:

AFIAS IFX, a novel fluorescence-based lateral flow assay, exhibited excellent performance in analyzing IFX trough levels and is a potentially powerful tool for therapeutic drug monitoring in clinical settings, with opportunities for further development.
Bibliometric Analysis of the Relationship between Gut Microbiota and Chronic Kidney Disease from 2001–2022
Authors: Tao Pengyu , Huo Jinlin , Chen Ling
Published: January 2024

Background:

The gut microbiota is closely associated with chronic kidney disease (CKD) development and prognosis. However, a comprehensive understanding of publication trends and research focuses within this domain remains limited. This study aimed to elucidate the relationship between the gut microbiota and CKD through a bibliometric analysis.

Methods:

Literature published between 2001 and 2022 on gut microbiota and CKD was obtained from the Web of Science Core Collection database. Bibliometric analysis tools such as VOSviewer and CiteSpace were used to analyze research trends in this area.

Results:

We extracted 758 articles for further analysis. China ranked first with 240 published documents, followed by the USA with 211. However, the USA ranked first regarding citation frequency with 11,380 citations, while China ranked second. The University of California Irvine and Kidney International emerged as the leading institution and journal, respectively, with the former leading in document production and citations. Although Kidney International featured fewer documents than other journals, it exhibited the highest citation count. The keywords representing the research interests mainly included: (1) gut microbiota influences the development of CKD, (2) application of probiotics in the treatment of CKD, and (3) potential mechanism of gut microbiota in CKD.

Conclusion:

Our analysis indicates significant advancements in understanding the association between gut microbiota and CKD. It also provides a comprehensive overview of publication trends, research hotspots, and frontiers, which may provide guidelines for future research.
Research advancements in the immunomodulating effect of sphingosine-1-phosphate in skin diseases
Authors: Ding Meilin , Li Hongyang , Xu Jingjing , Ren Kun , Zhang Wei
Published: January 2024

Sphingosine-1-phosphate (S1P) is a bioactive lipid metabolite that acts as an extracellular and intracellular messenger in a variety of biological activities, many of which are mediated by binding to S1P-specific G protein-coupled receptors. S1P receptors can affect cell fate by mediating cell differentiation, proliferation, and apoptosis. S1P mainly plays an immunomodulatory role in vivo. In recent years, increasing numbers of studies have shown that S1P is involved in the occurrence and development of immune-related skin diseases by regulating keratinocyte differentiation, proliferation, and apoptosis; lymphocyte migration; and angiogenesis. This review explores the metabolism and signal transduction mechanism of S1P, focusing on research advancements in the immune regulation function of S1P and its impact on immune-related skin diseases. The aim is to provide insights that can contribute to the research and application of S1P in immune-related skin diseases.
Trio Rounding: Perceptions of Acute Inpatient Rehabilitation Nurses and Physicians
Authors: Mannaye Tigist , Mowery Bernice , Friesen Mary Ann , Jones Emily
Published: January 2024

Purpose

The purpose of this study was to explore the process, benefits, and challenges of patient-centered Trio rounding in acute inpatient rehabilitation from the perspectives of nurses and physicians.

Design

A descriptive qualitative design was used in this study.

Methods

Focus group interviews (FGIs) involving 27 nurses and physicians were thematically analyzed using Dedoose. A descriptive survey of rounding practices was conducted.

Findings

Five primary themes were identified: (1) interprofessional team collaboration; (2) patient safety and quality of care; (3) communication, education, and patient/family partnering; (4) synchronicity of workflow; and (5) participants’ recommendation to develop rehabilitation Trio rounding standard process. Themes were consistent with Picker’s patient-centered care principles. Findings from a survey on current rounding practice done prior to the FGI reinforced participants’ discussion on challenges in conducting patient-centered Trio rounding.

Conclusions

Trio rounding in acute inpatient rehabilitation is a complex process challenged by asynchronous workflow and patients’ therapy schedules. Nurses and physicians reported benefits outweighed challenges for Trio rounding in acute rehabilitation.

Clinical Relevance

The study provided valuable recommendations to develop acute inpatient rehabilitation Trio rounding standard process.
Effect of a Nurse-Led Rehabilitation Program: A Quasi-Experimental Study Examining Functional Outcomes in Patients With Hand Burns
Authors: Sofar Samah Mahmoud , Wazqar Dhuha Youssef , Syam Narges Mohammed
Published: January 2024

Purpose

The model of early rehabilitation for people with burns is still relatively novel in developing countries such as Egypt. The study examined the effect of a nurse-led rehabilitation program on functional outcomes in patients with severe hand burns.

Design

A quasi-experimental design was used in this study.

Methods

The study was completed in the burn unit of a teaching university hospital in Alexandria, Egypt, with a convenience sample of 80 patients with severe hand burns. Participants were consecutively assigned to one of two groups: control (n = 40), which received only routine hospital care and clinical interventions, or intervention (n = 40), which received routine hospital care and clinical interventions and a 4-week nurse-led rehabilitation program (health education including audiovisual aids and burn rehabilitation education booklet, social support, and hand rehabilitation exercises). To assess functional outcomes, both groups were given pre- and posttests of the Disabilities of the Arm, Shoulder and Hand outcome and the Hand Motor Function Observational Checklist questionnaires. Descriptive and inferential statistics were conducted.

Results

Functional outcomes were significantly improved in the intervention participants compared to the control participants (t = 5.710, p < .001). The differences in index scores between the two groups were statistically significant (p < .001).

Clinical Relevance

The study provides information for burn rehabilitation nurses in developing countries to develop and test early interventions that improve functional outcomes in this population.

Conclusions

A 4-week nurse-led program can be a beneficial intervention for improving functional outcomes in adult patients with severe hand burns who are undergoing rehabilitation.
The MARECA (national study of management of breast cancer locoregional recurrence and oncological outcomes) study: protocol for a prospective, multicentre cohort study
Authors: Hartup Sue M. , Morgan Jenna L. , Cheng Vinton WT , Barry Peter A. , Copson Ellen , Cutress Ramsey I. , Dave Rajiv , Elsberger Beatrix , Fairbrother Patricia , Hogan Brian , Horgan Kieran , Kirwan Cliona C. , McIntosh Stuart A. , O’Connell Rachel L. , Patani Neill , Potter Shelley , Rattay Tim , Sheehan Lisa , Wyld Lynda , Kim Baek
Published: January 2024

Background:

Despite a UK 5-year breast cancer survival rate of 86.6%, patients may develop breast cancer recurrence within the same breast after breast conserving surgery, as well as in the remaining skin or chest wall after mastectomy or in the ipsilateral lymph glands. These recurrences, collectively termed locoregional recurrence (LRR), occur in around 8% of patients within 10 years of their original diagnosis. Currently, there is a lack of robust information on the presentation and prevalence of LRR with no UK-specific clinical guidelines available for the optimal management of this patient group. Additionally, there is a need to identify patterns of LRR presentation and their progression, which will enable prognostic factors to be determined. This will subsequently enable the tailoring of treatment and improve patient outcome.

Methods:

The MARECA study is a prospective, multicentre cohort study recruiting patients diagnosed with breast cancer LRR +/- associated distant metastases. Over 50 UK breast units are participating in the study with the aim of recruiting at least 500 patients over a recruitment period of 24 months. The data collected will detail the tumour pathology, imaging results, surgical treatment, radiotherapy and systemic therapy of the primary and recurrent breast cancer. Study follow-up will be for up to 5 years following LRR diagnosis to determine subsequent oncological outcomes and evaluate potential prognostic factors.

Discussion:

This study will address the current knowledge gap and identify subgroups of patients who have less successful treatment outcomes. The results will determine the current management of LRR and the prognosis of patients diagnosed with breast cancer LRR +/- distant metastases in the UK, with the aim of establishing best practice and informing future national guidelines. The results will direct future research and inform the design of additional interventional trials and translational studies.
Proteomic Analysis and Sex-Specific Changes in Chronically Ischemic Swine Myocardium Treated with Sodium-Glucose Cotransporter-2 Inhibitor Canagliflozin
Authors: Harris Dwight D , Sabe Sharif A , Broadwin Mark , Stone Christopher , Malhotra Akshay , Xu Cynthia M , Sabra Mohamed , Abid M Ruhul , Sellke Frank W
Published: January 2024

BACKGROUND:

Although sodium-glucose cotransporter-2 inhibitors have been shown to improve cardiovascular outcomes in general, little is presently known about any sex-specific changes that may result from this therapy. We sought to investigate and quantify potential sex-specific changes seen with the sodium-glucose cotransporter-2 inhibitor canagliflozin (CAN) in a swine model of chronic myocardial ischemia.

STUDY DESIGN:

Eighteen Yorkshire swine underwent left thoracotomy with placement of an ameroid constrictor. Two weeks postop, swine were assigned to receive either control (F = 5 and M = 5) or CAN 300 mg daily (F = 4 and M = 4). After 5 weeks of therapy, swine underwent myocardial functional measurements, and myocardial tissue was sent for proteomic analysis.

RESULTS:

Functional measurements showed increased cardiac output, stroke volume, ejection fraction, and ischemic myocardial flow at rest in male swine treated with CAN compared with control male swine (all p < 0.05). The female swine treated with CAN had no change in cardiac function as compared with control female swine. Proteomic analysis demonstrated 6 upregulated and 97 downregulated proteins in the CAN female group compared with the control female group. Pathway analysis showed decreases in proteins in the tricarboxylic acidic cycle. The CAN male group had 639 upregulated and 172 downregulated proteins compared with control male group. Pathway analysis showed increases in pathways related to cellular metabolism and decreases in pathways relevant to the development of cardiomyopathy and to oxidative phosphorylation.

CONCLUSIONS:

Male swine treated with CAN had significant improvements in cardiac function that were not observed in female swine treated with CAN. Moreover, CAN treatment in male swine was associated with significantly more changes in protein expression than in female swine treated with CAN. The increased proteomic changes seen in the CAN male group likely contributed to the more robust changes in cardiac function seen in male swine treated with CAN.
Construction and characterisation of a structured, tuneable, and transparent 3D culture platform for soil bacteria
Authors: Rooney Liam M. , Dupuy Lionel X. , Hoskisson Paul A. , McConnell Gail
Published: January 2024

Graphical Abstract

A step-by-step method for creating a tailored 3D culture medium for study of soil microbes. The complete workflow can be split into three parts: growth and observation, metabolic profiling to provide a stable refractive index matching solution, and production of the 3D soil environment. The 3D culture scaffold was created by cryomilling Nafion resin pellets and size filtration. Chemical processing altered the surface chemistry of Nafion particles and facilitated nutrient binding by titration of a defined liquid culture medium. Metabolic profiling determined non-metabolisable sugars and provided an inert refractive index matching substrate, which was added to the final nutrient titration. Inoculation and growth of the test strain allowed for downstream assessment of colonisation behaviours and community dynamics in situ by, for example, optical microscopy.
A practical guide to time-resolved fluorescence microscopy and spectroscopy
Authors: Clark Benjamin S. , Silvernail Irene , Gordon Kenya , Castaneda Jose F. , Morgan Andi N. , Rolband Lewis A. , LeBlanc Sharonda J.
Published: January 2024

Time-correlated single photon counting (TCSPC) coupled with confocal microscopy is a versatile biophysical tool that enables real-time monitoring of biomolecular dynamics across many timescales. With TCSPC, Fluorescence correlation spectroscopy (FCS) and pulsed interleaved excitation-Förster resonance energy transfer (PIE-FRET) are collected simultaneously on diffusing molecules to extract diffusion characteristics and proximity information. This article is a guide to calibrating FCS and PIE-FRET measurements with several biological samples including liposomes, streptavidin-coated quantum dots, proteins, and nucleic acids for reliable determination of diffusion coefficients and FRET efficiency. The FRET efficiency results are also compared to surface-attached single molecules using fluorescence lifetime imaging microscopy (FLIM-FRET). Combining the methods is a powerful approach to revealing mechanistic details of biological processes and pathways.
A method for mining condition-specific co-expressed genes inCamellia sinensisbased on K-means clustering: A case study of “Anji Baicha” tea cultivar
Authors: Zheng Xinghai , Lim Peng Ken , Mutwil Marek , Wang Yuefei
Published: January 2024

As one of the world’s most important beverage crops, tea plants (Camellia sinensis) are renowned for their unique flavors and numerous beneficial secondary metabolites, attracting researchers to investigate the formation of tea quality. With the increasing availability of transcriptome data on tea plants in public databases, conducting large-scale co-expression analyses has become feasible to meet the demand for functional characterization of tea plant genes. However, as the multidimensional noise increases, larger-scale co-expression analyses are not always effective. Analyzing a subset of samples generated by effectively downsampling and reorganizing the global sample set often leads to more accurate results in co-expression analysis. Meanwhile, global-based co-expression analyses are more likely to overlook condition-specific gene interactions, which may be more important and worthy of exploration and research. Here, we employed the k-means clustering method to organize and classify the global samples of tea plants, resulting in clustered samples. Metadata annotations were then performed on these clustered samples to determine the “conditions” represented by each cluster. Subsequently, we conducted gene co-expression network analysis (WGCNA) separately on the global samples and the clustered samples, resulting in global modules and cluster-specific modules. Comparative analyses of global modules and cluster-specific modules have demonstrated that cluster-specific modules exhibit higher accuracy in co-expression analysis. To measure the degree of condition specificity of genes within condition-specific clusters, we introduced the correlation difference value (CDV). By incorporating the CDV into co-expression analyses, we can assess the condition specificity of genes. This approach proved instrumental in identifying a PPR-type RNA editing factor gene (CWM1) that specifically functions during the bud-prealbinism stage of theCamellia sinensiscultivar “Anji Baicha”. We hypothesize that this gene may be upregulated and play a role in inhibiting chloroplast development, ultimately resulting in albino phenotypes in “Anji Baicha”.
The spatial structure of the tumor immune microenvironment can explain and predict patient response in high-grade serous carcinoma
Authors: Kleunen Lucy Van , Ahmadian Mansooreh , Post Miriam D , Wolsky Rebecca J , Rickert Christian , Jordan Kimberly , Hu Junxiao , Richer Jennifer K. , Marjon Nicole A. , Behbakht Kian , Sikora Matthew J. , Bitler Benjamin G. , Clauset Aaron
Published: January 2024

Despite ovarian cancer being the deadliest gynecological malignancy, there has been little change to therapeutic options and mortality rates over the last three decades. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes but are limited by a lack of spatial understanding. We performed multiplexed ion beam imaging (MIBI) on 83 human high-grade serous carcinoma tumors — one of the largest protein-based, spatially-intact, single-cell resolution tumor datasets assembled — and used statistical and machine learning approaches to connect features of the TIME spatial organization to patient outcomes. Along with traditional clinical/immunohistochemical attributes and indicators of TIME composition, we found that several features of TIME spatial organization had significant univariate correlations and/or high relative importance in high-dimensional predictive models. The top performing predictive model for patient progression-free survival (PFS) used a combination of TIME composition and spatial features. Results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.
TFEB-Mediated Pro-inflammatory Response in Murine Macrophages Induced by Acute Alpha7 Nicotinic Receptor Activation
Authors: Honwad Havisha H. , Najibi Mehran , Koscso Balazs , Bogunovic Milena , Irazoqui Javier E.
Published: January 2024

Transcription factors TFEB and TFE3 are crucial for regulating autophagy, lysosomal biogenesis, and lipid metabolism, and have significant roles in macrophage function and innate immunity. The alpha7 nicotinic acetylcholine receptor (α7nAChR), a ligand-gated Ca2+channel known for its therapeutic potential in neurological and inflammatory disorders, has been implicated in modulating immune responses by modulating macrophage function. Stimulation of α7nAChR with chemical agonists has been claimed to activate TFEB in pancreatic acinar cells and neurons. However, the impact of α7nAChR activation on TFEB and TFE3 in macrophages remained unknown, posing an important question due to the potential implications for inflammation regulation. This study investigates the effects of acute α7nAChR activation on TFEB-mediated responses in murine macrophages using the specific agonist PNU-282987. We demonstrate that α7nAChR stimulation triggers TFEB nuclear translocation and lysosomal expansion. Surprisingly, PNU-282987 induces a broad pro-inflammatory gene signature without concomitant cytokine secretion, suggesting an uncoupling of gene expression from cytokine release. Mechanistically, TFEB activation requires the lysosomal Ca2+exporter MCOLN1 and the Ca2+-dependent phosphatase PPP3/calcineurin. Additionally, PNU-282987 elevates reactive oxygen species (ROS) levels, and ROS are involved in TFEB activation by PNU-282987. Notably, even with α7nAChR deletion, compensatory ROS-mediated TFEB activation persists, suggesting the involvement of additional nicotinic receptors. Our findings reveal a novel α7nAChR-TFEB signaling axis in macrophages, offer new insights into the cholinergic regulation of immune responses, establish a baseline for comparison with disease states, and identify potential therapeutic targets for modulating inflammation.
Suspension Electrospinning of Decellularized Extracellular Matrix
Authors: Jones Sarah , VandenHeuval Sabrina , Martinez Andres Luengo , Burgeson Eric , Raghavan Shreya , Rogers Simon , Cosgriff-Hernandez Elizabeth
Published: January 2024

Decellularized extracellular matrices (dECM) have strong regenerative potential as tissue engineering scaffolds; however, current clinical options for dECM are limited to freeze-drying its native form into sheets. Electrospinning is a versatile scaffold fabrication technique that allows control of macro- and microarchitecture. It remains challenging to electrospin dECM; which has led researchers to either blend it with synthetic materials or use enzymatic digestion to fully solubilize the dECM. Both strategies reduce the innate bioactivity of dECM and limit its regenerative potential. Herein, we developed a new suspension electrospinning method to fabricate a pure dECM scaffold that retains its innate bioactivity. Systematic investigation of suspension parameters was used to identify critical rheological properties required to instill “spinnability,” including homogenization, concentration, and particle size. Homogenization enhanced particle interaction to impart the requisite elastic behavior to withstand electrostatic drawing without breaking. A direct correlation between concentration and viscosity was observed that altered fiber morphology; whereas, particle size had minimal impact on suspension properties and fiber morphology. The versatility of this new method was demonstrated by electrospinning dECM with three common decellularization techniques (Abraham, Badylak, Luo) and tissue origins (intestinal submucosa, heart, skin). Bioactivity retention after electrospinning was confirmed using cell proliferation, angiogenesis, and macrophage assays. Collectively, these findings provide a framework for researchers to electrospin dECM for diverse tissue engineering applications.

Abstract Figure
Polycaprolactone-based shape memory foams as self-fitting vaginal stents
Authors: Hicks Ashley , Roberts Courteney , Robinson Andrew , Wilson Kailey , Kotamreddy Varsha , LaRue Trace , Veyssi Arian , Beltran Felipe , Hakim Julie , Rausch Manuel , Grunlan Melissa , Cosgriff-Hernandez Elizabeth
Published: January 2024

There is an urgent critical need for a patient-forward vaginal stent that can prevent debilitating vaginal stenosis that occurs in up to 75% of patients who undergo pelvic radiation treatments and adolescent patients after vaginal reconstruction. To this end, we developed a self-fitting vaginal stent based on a shape-memory polymer (SMP) foam that can assume a secondary, compressed shape for ease of deployment. Upon insertion, the change in temperature and hydration initiates foam expansion to shape fit to the individual patient and restore the lumen of the stent to allow egress of vaginal secretions. To achieve rapid actuation at physiological temperature, we investigated the effect of architecture of two photocurable, polycaprolactone (PCL) macromers. Star-PCL-tetraacrylate displayed reduced melting temperature in the target range as compared to the linear-PCL-diacrylate. Emulsion-templating was then used to fabricate foams from 75:25 water-in-oil (W/O) emulsions that were subsequently annealed to yield high-porosity SMP foams. Upon axial shape memory testing, both foams displayed excellent shape fixity (90%); however, only the PCLstar-foams displayed shape recovery (∼84%) at 37°C to its permanent shape. A custom mold and curing system was then used to fabricate PCLstar-foams into hollow, cylindrical stents. The stent was crimped to its temporary insertion shape (50% reduction in diameter, OD ∼ 11 mm) with a custom radial crimper and displayed excellent shape fixity for deployment (> 95%) and shape recovery (∼ 100%). To screen vaginal stents, we developed a custom benchtop pelvic model that simulated vaginal anatomy, temperatures, and pressures with an associated computational model. A hysteroscope was used to visualize stent expansion and deformation via a scope port near the cervix of the benchtop model. A crimped SMP vaginal stent was deployed in the model and expanded to walls of the canal (∼70% increase in cross-sectional area) in less than 5 minutes after irrigation with warm water. The vaginal stent demonstrated retention of vaginal caliber with less than 1% decrease in cross-sectional area under physiological pressure. Collectively, this work demonstrates the potential for SMP foams as self-fitting vaginal stents to prevent stenosis. Additionally, this work provides new open-source tools for the iterative design of other gynecological devices.

Abstract Figure

Created in BioRender
A Multiscale Spatial Modeling Framework for the Germinal Center Response
Authors: Mu Derek P. , Scharer Christopher D. , Kaminski Norbert E. , Zhang Qiang
Published: January 2024

The germinal center response or reaction (GCR) is a hallmark event of adaptive humoral immunity. Unfolding in the B cell follicles of the secondary lymph organs, a GC culminates in the production of high-affinity antibody-secreting plasma cells along with memory B cells. By interacting with follicular dendritic cells (FDC) and T follicular helper (Tfh) cells, GC B cells exhibit complex spatiotemporal dynamics. Driving the B cell dynamics are the intracellular signal transduction and gene regulatory network that responds to cell surface signaling molecules, cytokines, and chemokines. As our knowledge of the GC continues to expand in depth and in scope, mathematical modeling has become an important tool to help disentangle the intricacy of the GCR and inform novel mechanistic and clinical insights. While the GC has been modeled at different granularities, a multiscale spatial simulation framework – integrating molecular, cellular, and tissue-level responses – is still rare. Here, we report our recent progress toward this end with a hybrid stochastic GC framework developed on the Cellular Potts Model-based CompuCell3D platform. Tellurium is used to simulate the B cell intracellular molecular network comprising NF-κB, FOXO1, MYC, AP4, CXCR4, and BLIMP1 that responds to B cell receptor (BCR) and CD40-mediated signaling. The molecular outputs of the network drive the spatiotemporal behaviors of B cells, including cyclic migration between the dark zone (DZ) and light zone (LZ) via chemotaxis; clonal proliferative bursts, somatic hypermutation, and DNA damage-induced apoptosis in the DZ; and positive selection, apoptosis via a death timer, and emergence of plasma cells in the LZ. Our simulations are able to recapitulate key molecular, cellular, and morphological GC events including B cell population growth, affinity maturation, and clonal dominance. This novel modeling framework provides an open-source, customizable, and multiscale virtual GC simulation platform that enables qualitative and quantitativein silicoinvestigations of a range of mechanic and applied research questions in future.
yQTL Pipeline: a structured computational workflow for large scale quantitative trait loci discovery and downstream visualization
Authors: Li Mengze , Song Zeyuan , Gurinovich Anastasia , Schork Nicholas , Sebastiani Paola , Monti Stefano
Published: January 2024

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Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. In order to facilitate and automate large-scale QTL analysis, we developed theyQTL Pipeline, where the ‘y’indicates the dependent quantitative variable being modeled.

Prior to genome-wide association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. Upon uploading the result file, it can generate Manhattan plots of user-selected phenotype traits and trait-QTL connection networks based on user-specified p-value thresholds.

We applied theyQTL Pipelineto analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs cumulatively associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ∼90 min to ∼26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. TheyQTL Pipelineis available with documentation on GitHub athttps://github.com/montilab/yQTL-Pipeline.
Identification of anisotropy in chromosome dynamics by principal component analysis using integrated spatial genomics
Authors: Nara Takuya , Takahashi Haruko , Awazu Akinori , Kikuchi Yutaka
Published: January 2024

Eukaryotic interphase chromosomes maintain a three-dimensional structure within the nucleus and undergo fluctuations. It has been reported that such dynamics are involved in transcription, replication, and DNA repair. However, the analysis of chromosomal dynamics has been limited to high-throughput chromosome conformation capture data, which records the contact frequencies between chromosomal regions and lack direct information about the dynamic. Herein, we investigated chromosome fluctuations as polymers based on experimental data from sequential fluorescencein situhybridization (seqFISH)+ using a multiomics methodology. To describe the principal modes of chromosome fluctuations, we applied principal component analysis to the three-dimensional structure information of single chromosomes in 446 mouse embryonic stem cells (mESCs) obtained from seqFISH+ data analysis for spatial genomics and signals of nuclear factors (SNFs: histone marks, repeat DNAs, and nuclear compartments). We found that chromosome fluctuations exhibit both isotropic and anisotropic modes. The properties of anisotropy in chromosome fluctuation vary among chromosomes and appear to depend on the interaction between repeat DNAs on the chromosomes and nuclear compartments. Furthermore, our principal component analysis revealed anisotropic chromosome fluctuations before and after the mitotic phase, specifically when chromosomes adopt a spindle-like shape. This result suggests the potential involvement of anisotropic chromosomal fluctuations in the transition of nuclear organization during the cell cycle. Our results represent the first study to elucidate the dynamics of chromosomes as polymers based on real multiomics data.
Parameter-Efficient Fine-Tuning Enhances Adaptation of Single Cell Large Language Model for Cell Type Identification
Authors: He Fei , Fei Ruixin , Gao Mingyue , Su Li , Zhang Xinyu , Xu Dong
Published: January 2024

Single-cell sequencing transformed biology and medicine, providing an unprecedented high-resolution view at the cellular level. However, the vast variability inherent in single-cell sequencing data impedes its utility for in-depth downstream analysis. Inspired by the foundation models in natural language processing, recent advancements have led to the development of single-cell Large Language Models (scLLMs). These models are designed to discern universal patterns across diverse single-cell datasets, thereby enhancing the signal-to-noise ratio. Despite their potential, multiple studies indicate existing scLLMs do not perform well in zero-short settings, highlighting a pressing need for more effective adaptation techniques. This research proposes several adaptation techniques for scLLMs by preserving the original model parameters while selectively updating newly introduced tensors. This approach aims to overcome the limitations associated with traditional fine-tuning practices, such as catastrophic forgetting and computational inefficiencies. We introduce two Parameter-Efficient Fine-Tuning (PEFT) strategies specifically tailored to refine scLLMs for cell type identification. Our investigations utilizing scGPT demonstrate that PEFT can enhance performance, with the added benefit of up to a 90% reduction in parameter training compared to conventional fine-tuning methodologies. This work paves the way for a new direction in leveraging single-cell models with greater efficiency and efficacy in single-cell biology.
Harnessing AlphaFold to reveal hERG channel conformational state secrets
Authors: Ngo Khoa , Yang Pei-Chi , Yarov-Yarovoy Vladimir , Clancy Colleen E. , Vorobyov Igor
Published: January 2024

To design safe, selective, and effective new therapies, there must be a deep understanding of the structure and function of the drug target. One of the most difficult problems to solve has been resolution of discrete conformational states of transmembrane ion channel proteins. An example is Kv11.1 (hERG), comprising the primary cardiac repolarizing current,Ikr. hERG is a notorious drug anti-target against which all promising drugs are screened to determine potential for arrhythmia. Drug interactions with the hERG inactivated state are linked to elevated arrhythmia risk, and drugs may become trapped during channel closure. However, the structural details of multiple conformational states have remained elusive. Here, we guided AlphaFold2 to predict plausible hERG inactivated and closed conformations, obtaining results consistent with multiple available experimental data. Drug docking simulations demonstrated hERG state-specific drug interactions in good agreement with experimental results, revealing that most drugs bind more effectively in the inactivated state and are trapped in the closed state. Molecular dynamics simulations demonstrated ion conduction for an open but not AlphaFold2 predicted inactivated state that aligned with earlier studies. Finally, we identified key molecular determinants of state transitions by analyzing interaction networks across closed, open, and inactivated states in agreement with earlier mutagenesis studies. Here, we demonstrate a readily generalizable application of AlphaFold2 as an effective and robust method to predict discrete protein conformations, reconcile seemingly disparate data and identify novel linkages from structure to function.
Epigenomics coverage data extraction and aggregation in R with tidyCoverage
Authors: Serizay Jacques , Koszul Romain
Published: January 2024

ThetidyCoverageR package provides a framework for intuitive investigation of collections of genomic tracks over genomic features, relying on the principle of tidy data manipulation. It defines two data structures,CoverageExperimentandAggregatedCoverageclasses, directly extending theSummarizedExperimentfundamental class, and introduces a principled approach to exploring genome-wide data. This infrastructure facilitates the extraction and manipulation of genomic coverage track data across individual or multiple sets of thousands of genomic loci. This allows the end user to rapidly visualize track coverage at individual genomic loci or aggregated coverage profiles over sets of genomic loci.tidyCoverageseamlessly combines with the existing Bioconductor ecosystem to accelerate the integration of genome-wide track data in epigenomic analysis workflows.tidyCoverageemerges as a valuable tool, contributing to the advancement of epigenomics research by promoting consistency, reproducibility, and accessibility in data analysis.

Availability and implementation

tidyCoverageis an R package freely available from Bioconductor ≥ 3.19 (https://www.bioconductor.org/packages/tidyCoverage) for R ≥ 4.4. The software is distributed under the MIT License and is accompanied by example files and data.

Contact

jacques.serizay@pasteur.fr

Supplementary information

Additional documentation is available fromhttps://js2264.github.io/tidyCoverage/andhttps://js2264.github.io/tidyCoverage/articles/tidyCoverage.html.
For antibody sequence generative modeling, mixture models may be all you need
Authors: Parkinson Jonathan , Wang Wei
Published: January 2024

Antibody therapeutic candidates must exhibit not only tight binding to their target but also good developability properties, especially low risk of immunogenicity. In this work, we fit a simple generative model, SAM, to sixty million human heavy and seventy million human light chains. We show that the probability of a sequence calculated by the model distinguishes human sequences from other species with the same or better accuracy on a variety of benchmark datasets containing >400 million sequences than any other model in the literature, outperforming large language models (LLMs) by large margins. SAM can humanize sequences, generate new sequences, and score sequences for humanness. It is both fast and fully interpretable. Our results highlight the importance of using simple models as baselines for protein engineering tasks. We additionally introduce a new tool for numbering antibody sequences which is orders of magnitude faster than existing tools in the literature. Both these tools are available athttps://github.com/Wang-lab-UCSD/AntPack.