zilongwang/ReadingBank huggingface dataset:
Supplementary data 1 Degradation curves and Arrhenius plots similar to Figure 4. Composition is the same compared to Fig.4 except that 6% lecithin was used. A and B, normalized Vit.A degradation curves in percent for standard palm oil at 30°C (●), 45°C (o) and 60°C (▼) and interesterified palm stearin oil at 30°C (●), 45°C (o) and 60°C (▼), respectively. Initial vit.A palmitate, lecithin and palm oil contents were 0.33%, 6% and 93.67%, respectively. All tests were performed at 68% RH. Reaction rates at each temperature are represented in the form of y=ax+b corresponding to [Vit.A]=-kt+[Vit.A]0 . Those reactions rates are expressed as follows: -0.0691x + 100 (30°C) , -0.2986x + 100 (45°C), -1.2791x + 100 (60°C) for standard palm oil and -0.0502x + 100 (30°C), -0.2204x + 100 (45°C), -0.7882x + 100 (60°C) for interesterified stearin palm oil, respectively. C, comparison of normalized Vit.A degradation curves as function of oil crystallinity for standard palm oil at 30°C (●) and 60°C (o) and interesterified palm stearin oil at 30°C (▼) and 60°C (Δ), respectively. D, comparison of Arrhenius plots extracted from the above equations by plotting lnk as function of 1/T in Kelvin at each temperature for standard palm oil (●) and interesterified palm stearin oil (o). Coefficients of determination (R2) are 0.9907 and 0.9988 for standard and interesterified stearin palm oils, respectively.
Fraction Standard palm oil content (%) Interesterified palm stearin content (%) Lecithin content (%) Vit.A content (%) Liquid 93.67 - 6 0.33 93.67 - 6 0.27 Liquid** - 93.67 6 No separation Solid** - 93.67 6 No separation **For this composition, no liquid rich fraction was present centrifugation. Supplementary data 5 Comparison of vit.A palmitate concentration in triglycerides with degradation kinetics. Concentration of Vitamin A palmitate in oil [wt%] Concentration ratio Degradation rate [%/day] Degradation 0.1% 6.6 1.29 1.9 0.66 % 2.45
soyasaponin γg 101643969 OJLGASCOGOIOJR-KIMDOUHKSA-N soyasaponin γa 101643970 BJSYIEDSMIGNCZ-VRTJPDHZSA-N
Table S1 Primer set used for RT-PCR analysis Target Gene Primer sequence (5’-3’) Amplicon length (in bp) No. of cycles Annealing temperature ( in ° C) Accession number Reference Reference gene 18SrRNA F: GGTAGACACACGCTGATCCA R: CATGGCCGTTCTTAGTTGGT 216 35 56 KX572356 Purohit et al., 2016 Fatty acid related genes fadsd6 F: CATCACGCTAAACCCAACATC R: GCTCTCCATAAACCTGACGAAA 250 40 48 KT634297 Ishak et al., 2008 elovl5 F: TGGACACCTTCTTCTTCATCC R: TCTTCTCGCTGGACATCACTC 461 35 50 KT634298 et al., 2008 fas F: AGGTGACACTATAGAATAGCTA TCCTGGCAGCCTACTG R: GTACGACTCACTATAGGGACTG AGCCTTACACTCTGCCC 283 35 58 KX572358 Manor et al., 2015 acc F: AGGTGACACTATAGAATAGGAC AAAGAAGCGGTAGTCG R: GTACGACTCACTATAGGGAAT GCGTAACTTTGCCCTGAC 152 35 58 - Manor et al., 2015 lpl F: AGCGATTGGTGGGAGGATTAT R: TGAGCACGGTCCAGTTTCCT 173 40 50 JX992743 (Tachysurus fulvidraco) Zheng et al., 2013 aco F: CCTTCATTGTACCTCTCCGCA R: CATTTCAACCTCATCAAAGCCAA 101 35 45 DQ364432 ( Salmo salar) Schiller Vestergren et al., 2012 cd36 F: GTCGTGGCTCAAGTCTTCCA R: CTTGCCCCCTGCTAAGAACA 171 40 50 KU361231 (Ctenopharyngodon idella), KM030422 ( Cyprinus carpio) - srb1 F: GTGGAGCAGAGAGGTCCCTA 220 35 55 DQ266043 -
Table S2. Comparison of pooled mortality data between bile derivatives and between sites of injection Treatment Mortality N p c Bile Derivative a bile salts 1.00 25 0.022 oxgall 0.76 25 Site of Injection b arm – distal 0.80 10 0.891 arm – middle 1.00 10 arm – proximal 0.90 10 central disk 0.90 10 Dosage c Single Dose 0.80 10 1.000 Double Dose 0.80 10 a data pooled across all bile derivative concentrations and sites of injection b data pooled across all bile derivatives and concentrations c data pooled across all bile derivatives injected on central disk d Fisher’s Exact Test (Sokal & Rohlf, 1995)
Table S1: Primers used in this study Gene Forward primer Reverse Primer Amplification efficiency (AE) NCBI accession number reference PPIA 98.8% XM_003402218.2 () PPIA (dsRNA synthesis) XM_003402218.2 RPL23 98.5% XM_003400707.2 () UBI (qPCR) 100.3% XM_003402262.2 () IAPV (amply partial genome) EU436443.1 IAPV (qPCR) CCATGCCTGGCGATTCAC EU436443.1 () SBPV (amply partial genome) GU938761.1 SBPV (qPCR) GU938761.1
References: Zemlicka, J.; A.; Bhuta, P. J. Med. Chem. 1983, 26, 167. Kwon, C.H.; Iqbal, M.T.; Wurpel, J.N.D. J. Med. Chem. 1991, 34, 1845. Conley, J. D.; Kohn, H. J. Med. Chem. 1987, 30, 567. Van Tamelen, E. E.; Baran, J. S. J. Am. Chem. Soc. 1958, 80, 4659. Kolar, P.; Tisler, M. J. Het. Chem. 1993, 30, 1253. Abiraj, K.; Gowda, D. C. J. Chem. Res. Synop. 2003, 6, 332. Reichardt, C.; Che, D.; Heckenkemper, G.; Schafer, G. Eur. J. Org. Chem. 2001, 2343. Kolar, P.; Petric, A.; Tisler, M.; Felluga, F. J. Heterocycl. Chem. 1991, 28, 1715.
Parthenolide x P 0.30 0.73 Arborescin P 0.26 0.87 Artemorin P 0.22 0.70 Caffeine x P 0.22 0.17 Cascarillin P 0.22 0.12 Chloramphenicol x P 0.22 0.03 Quassin x P 0.22 0.42 Yohimbine x P 0.22 0.94
Carisoprodol x S 0.04 0.01 1,10-phenanthroline S 0.04 0.07 2-Acetylpyrazine S 0.04 0.02 6-Methyl-2-thiouracil S 0.04 0.12 Acesulfame K S 0.04 0.00 Acetylthiourea S 0.04 0.02 isothiocyanate S 0.04 0.04
Aloin S 0.04 0.29 Benzamide S 0.04 0.11 Chlorhexidine S 0.04 0.27 Cnicin S 0.04 0.28 Crispolide S 0.04 0.56 Cromolyn S 0.04 0.00 Cucurbitacin E S 0.04 0.56 Cycloheximide S 0.04 0.13
Dimethylthioformamide S 0.04 0.09 D-Salicin S 0.04 0.04 Erythromycin x S 0.04 0.03 Ethylpyrazine S 0.04 0.01 Flufenamic Acid S 0.04 0.28 Helicin S 0.04 0.12 Hydrocortisone S 0.04 0.26
Limonin x S 0.04 0.50 Methimazole S 0.04 0.15 N,N-ethylene thiourea S 0.04 0.07 N-methylthiourea S 0.04 0.03 Noscapine x S 0.04 0.07 Orphenadrine S 0.04 0.53 Phenethyl isothiocyanate S 0.04 0.04 Phenylthiocarbamide x S 0.04 0.07
Propylthiouracil S 0.04 0.12 Sodium Benzoate S 0.04 0.00 Tatridin B S 0.04 0.30 Absinthin x 0.17 Camphor x 0.17 Andrographolide x 0.13 Falcarindiol x 0.09
G Table S2. Structures, names, THR and promiscuity prediction of Validation Set. Structure Name THR (hTAS2Rs) Probability of promiscuity compound 1 0.18 0.42 compound 2 0.23 0.43 compound 3 0.04 0.20 compound 4 0.04 0.03 compound 5 0.04 0.01 compound 6 0.04 0.03
Plant name Parts Voucher specimen no. 1. Carissa carandas Linn. Karamarda; Crane berry Leaves NIP-H-203 Roots 2. Capparis deciduas (Forssk.) Edgew. Karir; Caper berry Roots NIP-NPM-CD-183 Aerial part NIP-NPM-CD-077 Fruits NIP-NPM-CD-076 3. Cassia siamea Lam. Kassod; Siamese cassia Leaves NIP-H-228 Roots 4. Limonia acidissima Groff Kapittha; Wood Apple Leaves NIP-NPM-CD-187 Bark NIP-NPM-CD-186 Fruit pulp NIP-NPM-CD-188 Fruit shell 5. Swertia chirayita (Roxb.) Buch.-Ham. Kiratatikta; Chitretta herb NIP-NPM-CD-090 6. Oroxylum indicum (L.) Kurz Shyonaka; Midnight horror Bark NIP-NPM-CD-184 Table S1. Voucher specimen no. of collected plant materials Table S2. Effect of extracts on cell viability in 3T3-L1 cells during adipogenesis. Plant Name Parts % Cell Viabilitya Hexane DCM EtOAc MeOH Carissa carandas Linn. Leaves 96.72 ± 1.29 4.34 ± 0.29*** 93.61 ± 2.56 97.83 ± 1.06 Roots 93.12 ± 1.92* 95.17 ± 0.76 94.48 ± 2.87 90.59 ± 0.81 Capparis deciduas (Forssk.) Edgew. Roots 103.53 ± 2.86 98.03 ± 2.36 98.49 ± 0.20 93.52 ± 1.13 Aerial part 98.22 ± 3.23 97.75 ± 2.12 106.38 ± 3.39 93.74 ± 0.52 Fruits 101.53 ± 0.41 100.48 ± 0.57 102.51 ± 0.29 107.41 ± 2.45 Leaves 96.92 ± 1.17 97.16 ± 2.88 96.55 ± 2.04 95.01 ± 1.02
Fig. S5. 13C NMR spectra of comp. 2 (Chrysin) Fig. S6. 13C NMR spectra of comp. 3 (Baicalein) Fig. S7. Mass spectra of comp. 1 (Oroxylin A) Fig. S8. Mass spectra of comp. 2 (Chrysin) Fig. S9. Mass spectra of comp. 3 (Baicalein) Fig. S10. HPLC chromatogram with ƛmax of comp. 1 (Oroxylin A) Fig. S11. HPLC chromatogram with ƛmax of comp. 2 (Chrysin) Fig. S12. HPLC chromatogram with ƛmax of comp. 3 (Baicalein)
Figure 1. Chemical structure of isolated compounds from Campylotropis hirtella. 1. Inhibitory effects of compounds (1–j) on tyrosinase activities. compound L-tyrosine L-DOPA IC50 (M)a Inhibition type (Ki, M)b IC50 (M) Inhibition type (Ki, M) 1 2 3 4 a b c d e f g h i j Kojic acidc 2.90.3 92.00.2 0.030.006 18.40.5 >200 >200 >200 >200 >200 >200 >200 >200 >200 >200 13.20.8 Competitive (1.8) Competitive (49.7) Competitive (0.019) Competitive (7.5) - - - - - - - - - - Not tested 128.20.5 >200 0.50.003 144.01.2 >200 >200 >200 146.40.4 >200 >200 >200 >200 >200 >200 26.51.6 Competitive (76.4) - Competitive (0.13) Competitive (81.4) - - - Competitive (56.67) - - - - - - Not tested aAll compounds were examined in a set of experiments repeated three times; IC50 values of compounds represent the concentration that caused 50% enzyme activity loss. bValues of inhibition constant. cKojic acid is positive control.
(C18 Plus SepPak) using anhydrous acetonitrile to elute. 50 mg of N-hydroxysuccinimide (NHS) was added to the purified product and cooled to 0 ºC in an ice bath for 5 minutes followed by the addition of (diacetoxyiodo)benzene then stirred at 0 ºC for 15 minutes. The reaction was warmed to room temperature for 5 minutes prior to semi-preparative RP-HPLC purification using a Phenomenex C18(2) 100Å, 250x10 mm, 5 µ column, 35/65 acetonitrile/water with 0.1% TFA solvent system at a flow rate of 7 mL/min and UV detection at 254 nm. [18F]SFB was collected and concentrated via SPE and eluted in ACN. Radiochemical yields ranged from decay-corrected from fluoride. Section 2- IC50 and mode of inhibition determinations: General method for IC50 value determination: Working solutions of the substrate acid, (PABGgG) and inhibitor were prepared in Tris buffer (50 mM, pH 7.4). Working solutions of purified PSMA were diluted in Tris buffer (50 mM, pH 7.4 containing 1% Triton X-100) to provide 15-20% conversion of substrate to product in the absence of inhibitor. A typical incubation mixture (final volume of 250 μL) was prepared by the addition of either 25 μL of an inhibitor solution or 25 μL TRIS buffer (50 mM, pH 7.4) to 175 μL TRIS buffer (50 mM, pH 7.4). PABGgG (25 μL, 10 μM) was added to the above solution. The enzymatic reaction was initiated by the addition of 25 μL of the PSMA working solution. In all cases, the final concentration of PABGgG was 1 μM while the enzyme was incubated with five serially diluted inhibitor concentrations providing a range of inhibition from 10% to 90%. The reaction was allowed to proceed for 15 min with constant shaking at 37 oC and was terminated by the addition of 25 μL methanolic TFA (2% v/v trifluoroacetic acid in
Table A.2 No changes of Ppargc1a and target genes in tissue of Fus∆NLS mice Region Gene Fus+/+ Gene Fus+/+ Spinal cord Canonical Ppargc1a 100 ± 9.45 76.96 ± 6.11 CNS-specific Ppargc1a 100 ± 4.23 108.35 ± 12.11 Cortex Canonical Ppargc1a 100 ± 5.24 90.27 ± 6.24 CNS-specific Ppargc1a 100 ± 8.22 100.45 ± 6.24 Gastrocnemius Canonical Ppargc1a 100 ± 14.36 74.77 ± 7.52 Tfam 100 ± 12.58 105.18 ± 19.7 BAT Canonical Ppargc1a 100 ± 11.97 172.66 ± 43.59 Ucp1 100 ± 6.36 135.29 ± 16.71 Spinal cord, cortex, gastrocnemius and brown adipose tissue (BAT) of Fus∆NLS mice were lysed and mRNA of canonical Ppargc1a, CNS-specific Ppargc1a, Tfam and Ucp1 were quantified by qPCR and normalized to Tbp and Polr2a. Data are presented as mean in % of control ± SEM, n = 5-6.
Name Forward primer (5'to3') Reverse primer (5'to3') OsmiR GCTGGAAATGATGCTGGTAGC CTCCTTTGGCACGAGATCTGT OsmiR399j GGAGCATGTAAGTCTTTTGTAGC GGCAACTCTCCTTTGGCAGA OsPHR2 AGCCAATGCCTCAGTGAGAT GACCAGAATTGTCTGAAGGTTCTT OsPHO2 GCTTTCATGCTTCCCTTATGC TTCCGATAGCCGTTTGAGTG OsMYB4P CCATCCCCAAGCTCTTCCAG GAGCCCTCTTGCTCCTCTTG OsActin1 GAACTGGTATGGTCAAGGCTG ACACGGAGCTCGTTGTAGAAG OsPT1 CGCTTCCGTACGAGTGGTAGT GGTTCTTTCAAATCCAGGGAAA OsPT2 GACGAGACCGCCCAAGAAG TTTTCAGTCACTCACGTCGAGAC OsPT3 TGCGACTGCTGATTCAGTACGT ACAAATGCCATCAAATATGAACAGA OsPT4 TTCTGCTAGTGTACCAAACAAAATTACA CTAAGTGGCATTTATAATATCAACAGTAACC OsPT5 TGCTACTGCCCATGACTAGGATT CCATAGAAGAGATCCAGAGAAGCTGTA OsPT6 CCGCCCCTGCAAACTGTA CAACTGGCGGTTTCTTCGAT OsPT7 GCAAGTCGCTCGAGGAGATG TGGAATTAACGGGTGGATCAC OsPT8 AGAAGGCAAAAGAAATGTGTGTTAAAT AAAATGTATTCGTGCCAAATTGCT OsPT9 AGAAAAACATAGGCTTGTCATCCTTT AAAACCTAAGAAGCACTGTAAATAAATCC OsPT10 ATGTCGCCCATCCTTCCA TCGCTTTCCGACGATGATC OsPT11 GAGAAGTTCCCTGCTTCAAGCA TGCATATCCCAGATGAGCGTATC OsPT12 AACGAGATGACGAACACTTGCA TCCTGTACCTAAAAAGCAAGTACTAACATAGT Supplemental Table S1. List of primers used for qRT-PCR analysis in this study
cow milk plain nonon shanu 11 11 in porridge fura 28 28 thickened milk kindirmo 5 5 yogurt 19 19 cottage cheese dakashi 1 1 goat milk Plain nonon akunya 0 0 in porridge nonon akunya da fura 4 4 with cow milk and porridge nonon akuya da na shanu da fura 7 7 cottage cheese dakashi 6 2 maize (corn) boiled dafaffe masara 21 4 roasted gasassa masara 21 4 cooked, pounded tuwo masara 28 27 cake masara 23 23 grits roasted dambu masara 6 3 porridge pap 7 7 bula 22 21 bread hoche masara 14 12 pounded with ground nut cake datun tuwo masara da kuli 11 10 grits fried faten zakin masara 9 6 guinea corn (sorghum) boiled dawa 1 1 cooked, pounded, tuwon dawa 27 27 cake masar dawa 21 21 porridge puran dawa 19 17 grits dambun dawa 15 9 bread hoche dawa 24 24 pounded with ground nut cake datun tuwon dawa da kuli 11 11 grits fried faten tsakin dawa 10 10 millet roasted tumu 10 1 cooked, pounded tuwon gero 4 2 cake masar gero 4 4 porridge gero 26 26 grits dambun gero 5 3 bula 13 11 bread hoche gero 1 1
tree leaf mix cooked kayan magani 15 7 wild plant seeds cooked, pounded dadawa 23 23 red meat cow naman shanu 24 24 camel rakumi 11 7 horse doki 0 0 donkey jaki 0 0 goat akuya, bunsuru 25 24 white meat chicken kaza 24 24 guinea fowl zabo 15 13 birds tsuntsaye 4 2 wild game lizard damo, tsari 9 5 rabbit zomo 5 4 snake maciji 1 1 rat bera 6 3 mice kahiya 4 3 crocodile kada 0 0 porcupine bushiya 7 6 egg chicken kwan kaji 22 19 guinea fowl kwan zabo 18 10 fish locally caught kifi 25 23 canned sardines kifin gwangwani 4 3 spices / flavoring soil for flavor jarkasa 2 2 soil for flavor kanwa 14 14 ginger 10 10 tamarind tsamiya 12 9 purchased / processed biscuit biskin 24 24 bread biredi 25 25 macaroni/spaghetti taliya 20 19 indomie taliya 14 13 coffee or tea shayi 19 17 soda coca cola/fanta 12 12 margarine blue band 0 0
ΔH° (kJ/mol) -17.47 -40.63 -35.96 -31.22 -21.82 ΔS° (kJ/(mol·K)) -37.13 -118.08 -108.07 -96.14 -59.58 Parameters PCB 180 75 µm 100 µm 200 µm 300 µm 425 µm Temperature Kd ΔG° (kJ/mol) Kd ΔG° (kJ/mol) Kd ΔG° (kJ/mol) Kd ΔG° (kJ/mol) Kd ΔG° (kJ/mol) 283 19.42 -6.98 12.26 -5.90 6.80 -4.51 3.41 -2.88 4.02 -3.28 293 15.11 -6.62 11.97 -6.05 6.43 -4.53 2.96 -2.64 3.83 -3.27 298 11.51 -6.05 6.01 -4.44 3.69 -3.24 2.37 -2.14 3.25 -2.92 303 10.18 -5.84 1.59 -1.16 3.05 -2.81 1.56 -1.13 2.55 -2.36 313 7.43 -5.22 1.15 -0.36 1.63 -1.28 1.36 -0.80 2.11 -1.95 ΔH° (kJ/mol) -24.11 -66.78 -36.69 -24.93 -17.10 ΔS° (kJ/(mol·K)) -60.31 -212.07 -112.15 -77.24 -48.13
Fig. S2. Adsorption isotherms fitted to Langmuir model for copper ions adsorption onto APBC obtained at different hydrothermal temperature of 140 oC (a), 180 oC (b) and 220 oC (c) (hydrothermal time=8 hr and impregnation ratio=0, 0.5, 1.0, 1.5).
In fluorescence titration, it was assumed that sub-fractions of molecules in FA had consistent fluorescence characteristics. Intensification of fluorescence intensity and the concentrations of [HL] was described linearly (Equation B5). (B5) where: F0 indicated the maximum fluorescence intensity of peaks in EEM recorded at pH 7.0 and normalized by concentration of sub-fractions of FA in the study; F indicated the fluorescence intensity during titration; Fend indicated the fluorescence intensity at the end of titration. From equation (B4) and (B5), (B6) Letting f= in combination with equation (B6), Equation (B7) can be obtained: (B7) Where: ∆F represents the fluorescence intensity of peaks in D-EEMs at acidic pH range of 7.5-11.5; f represents the fraction of the initial EEM fluorescence that corresponding to the binding fluorophores. f and Ka2 can be solved by plotting F0/∆F against 1/[H] using SigmaPlot 12.5 software.
Electronic Supplementary Information (ESI) Artificial pheomelanin nanoparticles and their photo-sensitization property Jung Pyo, Kuk-Youn Ju and Jin-Kyu Lee Department of chemistry, Seoul National University, Seoul, Korea
Cisplatin + etoposide – 2 patients Major outcome(s): Association between candidate gene variants implicated in CTX drug metabolism and CINV occurrence NQO1 rs1800566 Nucleotide excision repair protein ERCC4 rs744154 XPC rs2228001 Transcription factor GTF2E1 rs447978 Voltage gated ion channel KCNC1 rs17718902 Motor protein KLC3 rs13181 Integral membrane protein TMEM63A rs10158985 Tumor suppressor TP53 rs1625895 genotype 63 SNPs in 29 genes Statistical analyses: Genetic models were coded as additive or dominant Cox proportional hazards to determine the association between each SNP and nausea and vomiting No SNPs were to be associated with emesis significant, the 95% CI included 1.0 No report on whether the patients were on an antiemetic regimen Only 80 patients from a total of 635 had blood sample available for genomic analysis
days of CTX infusion and ABCB1 genotype Association between response to antiemetic treatment and ABCB1 haplotypes and dexamethasone (100%) Nausea and vomiting were dichotomized as total control (i.e., absence of any degree of nausea and absence of any degree of vomiting: yes/no) Mann-Whitney U-test used to measure differences in antiemetic response rate ABCB1 genotypes. Logistic regression to determine association between clinical factors, demographic factors, genotype and CINV CINV control than patients with the other genotypes (67.7% versus 47.1%, p = 0.032) Patients with the TT-TT-TT for the gene, as compared to other genotypes, had a higher acute CINV response when using granisetron (68.4% versus 44.1%, p = 0.048) but not ondansetron (66.7% versus 52.8%, p = 0.374) In the delayed phase, no significant change was found between complete control of CINV and genotypes Results of logistic regression analysis found that during the acute phase, total control of CINV was significantly increased by the absence of previous CINV (p < 0.0001) and the ABCB1 3435 TT genotype (p = 0.021), but not by gender (p = 0.052), age (p = 0.071), ABCB1 2677 TT genotype (p = 0.069) and ABCB11236 TT genotype (p = 0.069)
Table S10 Correlations, Means, and Standard Deviations for Grade 10 Observed Variables Variable SG RS V1 V2 V3 D1 D2 DN1 DN2 RC1 RC2 SG 1 RS .80** 1 V1 .71** .74** 1 V2 .57** .60** .67** 1 V3 .66** .62** .68** .81** 1 D1 .43* .35** .47** .40** .44** 1 D2 .46** .37** .48** .40** .43** .90** 1 DN1 .55** .43** .55** .46** .50** .62** .70** 1 DN2 .51** .42** .51** .43** .51** .62** .70** .94** 1 RC1 .55** .52** .74** .68** .66** .44** .36* .40* .36* 1 RC2 .51** .53** .68** .63** .65** .37** .34** .45** .48** .66** 1 n 81 74 84 78 78 70 70 70 70 57 117 Mean 93.63 78.54 106.33 29.69 25.37 88.66 88.57 51.91 52.73 569.81 257.20 SD 10.89 11.71 13.74 4.28 5.06 10.58 9.01 9.47 10.32 21.75 18.38 ** p < 0.01 * p < 0.05 Note. SD = standard deviation, SG = CASL Grammatical Judgement Test, RS = CELF Recalling Sentences, V1= PPVT-4, V2 = SARA Vocabulary, V3 = SARA Morphology, D1 = TOWRE Sight Word Form A, D2 = TOWRE Sight Word Form B, DN1 = TOWRE Non-word Form A, DN2 = TOWRE Non-word Form B, RC1 = GMRT, RC2 = FCAT.
Ticlodipine pos screen 98 ± 2 104 ± 13 95 ± 12 99 ± 10 100 ± 2 93 ± 4 96 ± 5 94 ± 8 Timolol pos screen 89 ± 5 91 ± 4 115 ± 12 111 ± 47 85 ± 6 93 ± 4 105 ± 25 105 ± 15 Tirofiban pos screen 92 ± 9 97 ± 10 105 ± 11 103 ± 13 76 ± 5 85 ± 8 92 ± 20 85 ± 18 Topiramate neg quant 93 ± 7 97 ± 17 115 ± 45 121 ± 31 104 ± 9 98 ± 10 106 ± 16 92 ± 14 Trandolaprilat pos screen 98 ± 13 96 ± 10 113 ± 15 107 ± 19 72 ± 7 77 ± 6 80 ± 13 86 ± 23 Trazodone pos quant 87 ± 6 96 ± 5 90 ± 15 96 ± 15 118 ± 5 107 ± 7 106 ± 7 100 ± 5 Trimethoprim pos quant 93 ± 15 90 ± 6 98 ± 14 109 ± 21 100 ± 7 96 ± 4 107 ± 30 91 ± 17 Trimipramine pos quant 114 ± 13 92 ± 11 99 ± 15 96 ± 15 82 ± 2 95 ± 5 95 ± 5 94 ± 1 Valproic acid neg 99 ± 10 92 ± 11 113 ± 27 108 ± 21 79 ± 4 92 ± 4 86 ± 22 90 ± 10 Valsartan pos screen 94 ± 11 91 ± 18 106 ± 22 103 ± 14 74 ± 6 70 ± 12 81 ± 11 74 ± 29 Warfarin pos quant 95 ± 7 91 ± 14 102 ± 20 107 ± 17 86 ± 4 96 ± 9 103 ± 22 90 ± 11 Zonisamide neg screen 107 ± 19 110 ± 12 124 ± 43 146 ± 41 104 ± 12 92 ± 13 109 ± 27 84 ± 10 (volunteer) blood, 2average, 3standard deviation, 4post-mortem blood
Supplemental Table S1. Sample cross-validation table: reports of cross-hallmark effects of selected metabolic approaches Dysregulated Metabolism Approaches Other cancer hallmarks Resveratrol Metformin (3PB) (PFK15) (TEPP-46) (DCA) (GW5074) sulfide (BPTES) Acid (FX11) Genomic Instability + [1] + [2, 3] 0 + [4] 0 0 + [5] 0 0 - [6] Sustained Proliferative Signaling + [7-9] +/- [10-20] + [21] + [4] 0 + [22-24] + [25] +/- [26] + [27] 0 Tumor Promoting Inflammation + [28] + [29, 30] 0 0 + [31] + [32] 0 0 0 0 Evasion of Anti-growth Signalling + [33, 34] + [35, 36] + [37] + [4] 0 0 + [38] + [26, 39] + [27] 0 Resistance to Cell + [40] + [36] + [41] + [4] 0 0 + [25] 0 0 0 Replicative Immortality + [42, 43] + [12, 44, 45] 0 0 0 0 0 0 0 0 Immune System Evasion +/- [46-49] + [50, 51] 0 0 0 + [32, 52] 0 0 0 0 pyruvate
Angiogenesis +/- [53] + [54, 55] + [56] 0 0 + [23] 0 0 0 0 Tissue Invasion and Metastasis + [57] + [35] + [58] + [4] 0 + [59, 60] + [25, 61] + [62] + [63] 0 Tumor Microenvironment + [64, 65] + [13, 66] + [67] 0 + [31] + [32, 68] 0 0 + [69] + [6]
SPS Resveratrol + + + + + + + +/- +/- + + TIM 0 0 0 0 0 0 0 0 0 + + TIM Cordycepin 0 + + + + 0 + 0 + + + TIM Eicosapentaenoic acid 0 + + + + + 0 0 + + + TIM Gamma linolenic acid 0 + 0 + + 0 + 0 + + + TIM Ganoderic acids 0 + + + + 0 0 0 + + + TIM Grifolin 0 + 0 + + 0 + 0 0 + + TIM Pachymic acid 0 + + + + 0 0 0 0 + + TIM Polysaccharide (G. lucidum) 0 +/- + + + 0 + + + + + TIM Silibinin + + + + + + + + + + + TIM β-(1-6)-D-glucan (A. blazei) 0 + + 0 + 0 + 0 0 + + TME Berberine + + 0 + + + + - + + + TME Curcumin + + + + + + + + + + + TME Desoxyrhapontigenin 0 0 0 0 + 0 0 0 0 0 + TME EGCG + + + + + + + + + + + TME Genistein + +/- +/- +/- + + +/- +/- + + + TME Naringenin + + + 0 +/- 0 + +/- 0 + + TME Onionin A 0 0 0 0 0 0 0 0 0 0 + TME Piperine + + 0 + + 0 + - 0 + + TME Resveratrol + + + + + + + +/- +/- + + TME Zerumbone 0 + 0 0 + 0 + + 0 + + TPI Anthocyanins + + + + + + 0 0 + + + TPI Curcumin + + + + + + + + + + + TPI EGCG + + + + + + + + + + + TPI Genistein + +/- +/- +/- + + +/- +/- + + + TPI Lycopene + + + + + 0 0 0 + + + TPI Resveratrol + + + + + + + +/- +/- + +
Beginning End Duration (s) Velocity (mm/min) Amplitude ROI 1 and 2 Amplitude ROI 3 and 4 Duration (s) Velocity (mm/min) Amplitude ROI 1 and 2 Amplitude ROI 3 and 4 Set 1 (NaCl) Mean 311.9 4.7 20.2 12.8 297.4 3.0 21.0 14.1 Standard Deviation 158.4 3.1 7.5 4.4 142.4 2.4 9.6 7.2 Set 2 (Paraffin) Mean 190.8 5.0 19.1 13.9 117.0 2.6 20.5 11.9 Standard Deviation 117.0 3.3 9.6 9.2 40.7 2.0 8.9 7.1
(1) Pooled OLS (2) Pooled OLS (3) Pooled OLS (4) Industry FE (5) Industry FE (6) Industry FE Adj. R2 -0.02% -0.04% -2.96% -0.04% -0.13% -2.80%
Did the analysis adjust for confounding? Educational attainment or SES BMI/weight Gender Age Baseline behaviour The statistical model used adjusts for all relevant confounding factors. The adjusts for 3 or 4 confounders. The analysis adjusts for fewer than 3 confounders
Complaint/Site Matched Physicians 75 22 .004 10.5 (1.6-69.7) .014 1-P calculated using Pearson’s chi-square test. 2-Adjusted odds ratio, 95% confidence interval, and P value calculated using adjusted conditional logistic model. SDC 2 -2. Sensitivity Analyses Excluding Cases (n=3) in which the physician’s patient complaints were the first signal that raised concerns of probable or possible neurocognitive disorder Cases (n=12) (% with at least one word related to cognitive impairment) Comparison Physicians (n=48) (% with at least one word related to cognitive impairment) p Adjusted Odds Ratio (95% confidence interval)2 p value2 Age/Sex Matched Physicians 67 8 <.001 65.2 (6.0-711.3) <.001 Complaint/Site Matched Physicians 67 17 <.001 14.1 (2.8-71.0) <.001 1-P calculated using Pearson’s chi-square test. 2-Adjusted odds ratio, 95% confidence interval, and P value calculated using adjusted conditional logistic model.
occur because people are too focused on their future goal and discount limited odds, the skills of others, what is unknown, and luck. This causes people to think they are in control of the future. estimated that the rate of success for a business like theirs was 60%. Their optimism bias leads them to believe they would succeed despite the odds.25 State Dependence Decisions are dependent on one’s physical or emotional state. Decisions are made to either mitigate a bad state or boost a good state. Undergoing a state of unemployment may increase the probability that someone will accept a low-paying or otherwise unappealing position.9
Supplementary material, Fig. 1. Growth kinetics of C. perfringens wild type ATCC 13124 in BHI in the absence of (A) and presence of (B) 3.25 μg/ml of penicillin G. The bacteria developed resistance to the drug regardless of the inoculum size. The size of the inoculum was 3 [♦], 1.2 [■], 0.6 [▲], and 0.3 OD units [●]. A B
Table 2S: Bone crises: date and site of events Patient Mutations Year of birth Long bones crisis (bones in the limbs excluding the patella) Main weight bearing bones (vertebra, femoral head, calcaneus) Other bones (pelvis, clavicle, skull, ribs) bones (in hands and feet) 1 N370S/R285C 1982 1996; 1996; 1996 2 N370S/N370S 1965 1982 3 N370S/84GG 1957 1966; 1968; 2011 4 N370S/84GG 1972 1982; 1982; 1982; 1985, 1990; 1994 5 N370S/84GG 1970 1998 6 N370S/84GG 1970 Pre-1993 1993 7 N370S/N370S 1971 1984; 2004 8 N370S/R120W 1956 Many NDD 9 N370S/IVS2+1 1971 - 2002; 2004 2004; 2005; 2007; 2012 10 N370S/84GG 1948 Many NDD 2011; 2012 (NI) 11 N370S/84GG 1977 1995 Pre-2001 (post- 1998) 2004 12 N370S/84GG 1973 1979; 1982; 1984; 1988; 1990; 1991; 1992; 1995; 2009 1982 1998; 1999; 2009; 2009 13 1980 1994; 1994 1996 14 N370S/84GG 1970 1981; 1985; 1990 15 N370S/84GG 1990 1993; 1994; 1995; 2005 2008 16 N370S/84GG 1983 1991; 1992 17 N370S/N370S 1970 1981; 1986; 1990 18 N370S/84GG 1974 1981; 1986; 1990 (NI) 1995; 2004 (NI) 19 N370S/84GG 1975 1984; 1985; 1989 1994; 1995; 1995 20 N370S/84GG 1968 Many (NDD)
4S: Crises in relation to spleen status (excluding patients who underwent partial followed by full splenectomy) Spleen status Crises in long bones (mean events per patient) Crises in weight bearing bones (mean events per patient) Crises in other bones (mean events per patient) Crises in small bones of hands and feet (mean events per patient) N Events before Events same yr Events after >1 yr N Events before Events same yr Events after >1 yr N same yr Events after >1 yr N Events before Events same yr Events after >1 yr Intact 10 21 (2.1) NA NA 1 2 (2.0) NA NA 1 1 NA NA 4 9 (2.3) NA NA Partial splenectomy 6 4 (0.6) 1 (0.2) 20 (3.3) Mean 5.1 yrs; median 2.5 yrs; range 1-27 yrs after surgery. 6 events occurred while treated (mean 2.7 yrs after surgery (median 2 yrs, range yrs) 2 0 1 (0.5) 2 (1) Mean 4 yrs later (untreated) 0 0 0 0 6 0 0 16 (2.7) Mean 13.9 yrs later; median 14 yrs; range yrs later. 14 events occurred while treated (mean 9.4 yrs after ERT initiation; median 7 yrs; range Full splenectomy 4 1 (0.25) 3 (0.75) 15 (3.75) Mean 6 yrs after surgery; median 5 yrs; range yrs) 1 in 1 patient occurred while on ERT (1 yr after ERT initiation) 1 0 1 13 yrs after surgery in same year as starting treatment 1 0 0 3 Mean 17 yrs after surgery; median 15 yrs; range 14-22 yrs All treated : + 1, 2 and 9 yrs after ERT start 3 0 0 12 (4.0) Mean 20.4 yrs; median 15 yrs; range 12-46 yrs later. 11 events occurred after ERT initiation (mean 6.7 yrs; median 3 yrs; range 2-21yrs). Abbreviation: N: number of patients with date-documented crises
Supplementary 1 Calibration curve parameters and repeatability Calibration curve parameters 20 degrees of freedom Mepivacaine 95% CI Lidocaine 95% CI Bupivacaine 95% CI Methylparaben 95% CI Slope (mL/mg) 6525 154 5904 154 5495 28 10250 465 intercept -7.8 6.8 2.8 6.8 -5.8 1.2 -0.5 1.01 r 0.9981 0.9977 0.9999 0.9930 r 2 0.9991 0.9989 1.0000 0.9965 Repeatability, three levels C1, n=6 0.28 % RSD 0.50 % RSD 0.33 % RSD 4.66 C3, n=6 0.22 0.28 0.17 3.08 % RSD C5, n=6 0.63 0.46 0.29 0.29 CI, Confidence intervals; r, correlation coefficient; r 2: Degree of explanation; RSD, Relative standard deviation.
Supplementary Table 1 Summary of clinical trials included in the population pharmacokinetic analysis Trial name Study Population Subjects randomized to nintedanib, n Subjects included in analysis, n Starting dose (mg) doses used (mg) Pharmacokinetic sampling TOMORROW [1] IPF; diagnosis ≤5 years prior to screening visit 343 342 50 qd, 50, 100, 150 bid 0a Pre-dose: days 1, 29, 169, 365 and end-of-trialc Post-dose: day 1 and day 29 at 2 (1-3) h after dosing; day 169 and end-of-trialc at 2 (1-3) and 7 (4-10) h after dosing INPULSIS-1 [2] IPF; diagnosis ≤5 prior to screening visit 309 285 150 bid 100 bidb Pre-dose: days 29 and 169 Post-dose only): days 29 and 169 at 2-4 h after dosing INPULSIS-2 [2] IPF; diagnosis ≤5 years prior to screening visit 329 306 150 bid 100 bidb Pre-dose: days 29 and 169 Post-dose (Japan only): days 29 and 169 at 2-4 h after dosing qd, once daily; bid, twice daily; IPF, idiopathic pulmonary fibrosis a Treatment interruptions or 1-step dose reductions to manage adverse events were allowed: by 50 mg qd for subjects in the 50 mg qd or 50 mg bid and by 50 mg bid for those in the 100 mg bid or 150 mg bid group. No dose reescalation was allowed. b Treatment interruptions or 1-step dose reductions to manage adverse events were allowed: by 50 mg bid to 100 mg bid and then increased again to 150 mg bid after recovery. c End-of trial was day 365 unless a patient discontinued, in which case samples were taken on the day of discontinuation.
NaCl 1.0 MgCl2·6H2O 0.2 CaCl2·2H2O 0.02 K2HPO4 1.5 (NH4)2SO4 2.0 NaHCO3 9.997 Alanine 0.5 144, W381829 Trace metal solutionb 5.0 mL Asparagine 0.5 408, A0884 Ascorbic acid 0.005 371, 795437 Biotin 0.005 40800, B4501 Aspartic acid 0.5 166, A9256 Methionine 0.5 290, M9625 Cysteine 0.5 228, W326305 Ca-Pantothenate 0.005 2575, C8731 Nicotinic acid 0.005 80, N4126 Pyridoxine·HCl 0.005 1185, Prolinec 0.5 453, P0380 Thiamine 0.005 360, T4625 Serine 0.5 576, a Based on the unit prices for each CDM component, CDM is less expensive than the complex medium. All chemical prices were obtained from Sigma. For comparison, relevant components in the complex medium were given; 5 g/L polypeptone ($383/kg, 297110, BD Biosciences), 5 g/L yeast extract ($231/kg, 211929, BD Biosciences). Please note that the medium costs can be reduced by further metabolic engineering of M. succiniciproducens so that the strain does not require these amino acids and vitamins; this work is in progress. b The metal solution contains per liter: 5 mL HCl, 10 g FeSO4·7H2O, 2.25 g ZnSO4·7H2O, 1 g CuSO4·5H2O, 0.5 g MnSO4·5H2O, 0.23 g Na2B4O7·10H2O, 2 g CaCl2·2H2O, and 0.1 g (NH4)6Mo7O24. c The concentration of proline used in fed-batch fermentation was 2.46 g/L.
cysG: Min G homodimer, -37.6 kcal; Min G monodimer, -15 kcal Location of each primer by exon or intron (if applicable) E NA What splice variants are targeted? E NA qPCR oligonucleotides Primer sequences E + See Table S2 RTPrimerDB identification number D NA Probe sequences D NA Location and identity of any modification E NA Manufacturer of oligonucleotides D NA Purification method D NA qPCR protocol Complete reaction conditions E + Reaction volume and amount of cDNA/DNA E + Total volume 20 μl, containing 1 μl of cDNA as template Primer, (probe), Mg2+, and dNTP concentration E + Primer 10 pM, dNTP 25 mM each Polymerase identity and concentration E + Proprietary (Enzynomics) Buffer/kit identity and manufacturer E + TOPrealTM qPCR 2X PreMIX (SYBR Green with high ROX) (Enzynomics, Daejeon, Korea) chemical composition of the buffer D - Proprietary Additives (SYBR Green I, DMSO, and so forth) E + SYBR Green I Manufacturer of plates/tubes and catalog number D + MicroAmp Fast Optical 96-Well Reaction Plate, 0.1 mL (Thermofisher, Cat # : 4346907) Complete thermocycling parameters E + Holding stage (95 °C 10 min), cycling stage (95 °C 10 s, 55 °C 15 s, 72 °C 20 s (+)), and melt curve stage (95 °C 15 s, 1 min, +0.3 °C (+), 95 °C 15 s )(+) Reaction setup (manual/robotic) D + Manual Manufacturer of qPCR instrument E + a StepOnePlus Real-time PCR system (Applied Biosystems, Foster City, CA, USA) qPCR validation Evidence of optimization (from gradients) D + From standard curve
Supplementary materials S1. Patient enrolment flowchart. S2. Prevalence of asymptomatic C. difficile colonisation and median current length of stay by hospital and by survey. Survey RBWH SCGH Prevalence of asymptomatic C. difficile colonisation (%) Median current length of stay (IQR) Prevalence of asymptomatic C. difficile colonisation (%) Median current length of stay (IQR) 1 – Feb/Mar 12 8.1 5 (2-17) 14.4 5 (2-9) 2 – Aug/Sep 12 3.6 6 (3-21) 8.2 5 (2-11) 3 – Feb/Mar 13 3.6 4 (1-13) 11.4 4 (2-9) 4 – Aug/Sep 13 1.1 7 (3-14) 8.2 5 (2-9) 5 – Feb/Mar 14 4.8 6 (2-11) 8.2 4 (1-9) 6 – Aug/Sep 15 3.9 5 (2-8) 6.8 4 (1-8)
Organ/system 0 1 2 3 4 Liver (Bilirubin, mg/dL) <1.2 ≥1.2 to ≤ 2.0 ≥2.0 to < 6.0 ≥6.0 to < 12.0 ≥12.0 Kidney (creatinine mg/dL) <1.2 ≥1.2 to < 2.0 ≥2.0 to < 3.5 ≥3.5 to < 5.0 or use of renal replacement therapy ≥ 5 Cerebral (HE grade) No HE I II III IV Coagulation (international normalized ratio) >1.1 ≥1.1 to < 1.25 ≥1.25 to < 1.5 ≥1.5 to < 2.5 ≥2.5 or platelet ≤ 20 x 109 /L Circulation (mean arterial pressure, mm Hg) ≥ 70 < 70 Dopamine ≤ 5 or dobutamine or terlipressin Dopamine > 5 or Epinephrine ≤0.1 or Norepinephrine ≤ 0.1 Dopamine > 15 or Epinepfrine >0.1 or Norepinephrine > 0.1 Lungs PaO2/FiO2 > 400 > 300 to ≤ 400 > 200 to ≤ 300 > 100 to ≤ 200 ≤ 100 SpO2/FiO2 > 512 > 357 to ≤ 512 > 214 to ≤ 357 > 89 to ≤ 214 ≤ 89
Supplementary Table S3. Etiology of 312 episodes of bloodstream infections in patients with liver cirrhosis stratified by country#. Total, n=312 episodes (100%) Spain n=67 (21%) Israel n=36 episodes (11%) P Gram positive 146 (47) 60 34 (51) 36 14 (39) .02* Coagulase negative staphylococci 25 (8) 10 (7) 6 (9) 6 3 (8) .88 Staphylococcus aureus (MSSA) 41 (13) 13 (9) 8 (12) 16 4 (11) .02* Staphylococcus aureus (MRSA) 12 (4) 7 (5) 4 (6) 0 (0) 1 (3) .39 Streptococcus spp 24 (8) 7 (5) 9 (13) 3 (5) 3 (8) .003 Enterococcus faecalis 15 (5) 7 (5) 1 (1) 4 (7) 3 (8) .45 an
Enterobacter spp 13 (4) 5 (3) 5 (7) 2 (3) 1 (3) .61 Other Enterobactericeae b 15 (5) 10 (6) 1 (2) 2 (3) 2 (6) .48 Non-fermenters 28 (9) 15 5 (7) 2 (3) 6 (17) .22 Pseudomonas aeruginosa 16 (5) 9 (6) 4 (6) 0 (0) 3 (8) Acinetobacter baumanii 3 (1) 3 (2) 1 (2) 0 (0) 0 (0) Stenotrophomonas maltophilia 4 (1) 3 (2) 0 (0) 0 (0) 1 (3) Other non-fermentersc 5 (2) 0 (0) 1 (1) 2 (3) 2 (6) Other Gram-negatived 2 (1) 1 (1) 1 (1) 0 (0) 0 (0) Anaerobes 6 (2) 3 (2) 1 (1) 2 (3) 0 (0) Fungi Candida species 21 (7) 11 (7) 4 (6) 5 (9) 1 (3) .76 infections 30 (10) 16 3 (10) 10 1 (3) .07
Table S3. List of reported performances over PtSn/Al2O3 catalysts for n-butane dehydrogenation. Loading amount of Pt and Sn metals (wt%) Temp. (ºC) GHSV (mL h-1) Initial conversion (%) Initial C4= (%) parameter (%)a Particle size (nm)/ TOF (s-1) 0.5: 0.5 530 5400 30.0 (Time on stream: after 10 min) 94 .0 14.0 (after 120 min) - [1] 0.5: 0.5 530 5400 38.0 (Pulse method: first pulse) 83.0 58.0 (after 20 pulses) - [2] 0.3: 0.3 530 5400 29 (Time on stream: 10 min) 96.0 4 (after 120 min) - [3] 0.5: 0.5 550 18000 41.9 (Time on stream: after 30 min) 83.7 21.0 (after 300 min) 9.3/10.2 [4] 0.49: 0.49 530 5400 31.5 (Time on stream: after 10 min) 84.0 61.9 (after 120 min) - [5] 0.5: 0.5 550 18000 39.4 (Time on stream: after 30 min) 89.0 28.9 (after 300 min) 9.7/11.1 [6] a ΔX/X0: ΔX: initial conversion (X0)−final conversion (Xf). References A.D. Ballarini, P. Zgolicz, I.M.J. Vilella, S.R. de Miguel, A.A. Castro, O.A. Scelza, Appl. Catal. A: Gen. 381 (2010) 83-91. S.R. de Miguel, S.A. Bocanegra, I.M.J. Vilella, A. Guerrero-Ruiz, O.A. Scelza, Catal. Lett. 119 (2007) 5-15. S. Bocanegra, A. Ballarini, P. Zgolicz, O. Scelza, S. de Miguel, Catal. Today 143 (2009) 334-340.
Table S1. Summary of key inclusion and exclusion criteria for the EDITION 1, 2, and 3 trials Key participant criteria Trial EDITION 1 [1] EDITION 2 [2] EDITION 3 [3] Inclusion Age ≥ 18 Type 2 diabetes (WHO Use of basal and mealtime insulin therapy ± MET ≥1 year Basal therapy ≥42 units/day of either Gla100 or NPH Mealtime therapy with insulin lispro, aspart, or glulisine HbA1c 7.0–10.0 % (53–86 mmol/mol) Age ≥ 18 years Type 2 diabetes (WHO definition) for ≥ 1 year before screening ≥ 6 months on basal insulin therapy Recent use (within the last 4 weeks) of ≥42 units/day of Gla-100 or NPH combined with OAD(s) Age ≥ 18 years Type 2 diabetes (WHO definition) for ≥ 1 year before screening Use of OADs for ≥ 6 months before screening* Insulin naïve Exclusion Use of human mealtime insulin or any premixed or basal insulin other than Gla or NPH Oral glucose-lowering drugs other than MET in the last 3 months Injected glucose-lowering agents other than insulin HbA1c < 7.0 % (<53 mmol/mol) or > 10 % (>86 mmol/mol) within the past 3 months Use of premixed insulin, insulin detemir, or new glucose-lowering agents within the past 2 months Use of sulfonylurea for >10 days in the past 3 months < 7.0 % (<53 mmol/mol) or >11.0 % (>97 mmol/mol) at screening trial
References [1] Riddle MC, Bolli GB, Ziemen M, Muehlen-Bartmer I, Bizet F, Home PD. New Insulin Glargine 300 Units/mL Versus Glargine 100 Units/mL in People With Type 2 Diabetes Using Basal and Mealtime Insulin: Glucose Control and Hypoglycemia in a 6-Month Randomized Controlled Trial (EDITION 1). Diabetes Care 2014;37:2755-62. [2] Yki-Jarvinen H, Bergenstal R, Ziemen M, Wardecki M, Muehlen-Bartmer I, Boelle E, et al. New insulin glargine 300 units/mL versus glargine 100 units/mL in people with type 2 diabetes using oral agents and basal insulin: glucose control and hypoglycemia in a 6-month randomized controlled trial (EDITION 2). Diabetes Care 2014;37:3235-43. [3] Bolli GB, Riddle MC, Bergenstal RM, Ziemen M, Sestakauskas K, Goyeau H, et al. New insulin glargine 300 U/ml compared with glargine 100 U/ml in insulin-naive people with type 2 diabetes on oral glucose-lowering drugs: a randomized controlled trial (EDITION 3). Diabetes Obes Metab 2015;17:386-94.
PC-miRNA-16 UCUGGCGGCCUGAGGUCCUGA 22 Novel PC-miRNA-17 UCUGACGGCCUGAGGUCCUGA 22 Novel PC-miRNA-18 AAGCAGGUCCUGUUGGUCCA 21 Novel PC-miRNA-19 CCAUCGUCGGCGCGAGCCGCUUCA 25 Novel PC-miRNA-20 UGGACCAUAGGGCUUCAGCAGA 23 Novel PC-miRNA-21 UCGAAGAGGACUGGGGAAACGGGC 25 Novel AAGCAGGUCCUGUUGGUCCA 21 Novel PC-miRNA-23 UAUGGGUGAUUUAGGGAUCAG 22 Novel PC-miRNA-24 UAGCAUAGCUCGCACCCCACC 22 Novel PC-miRNA-25 UGGCCUCGGAAAGCUCUGCAC 22 Novel PC-miRNA-26 UGGGCGUCGACCAAGUGGAC 21 Novel PC-miRNA-27 UAUGGGUAAUAUGACUAAAGG 22 Novel PC-miRNA-28 GCUUGGUUGGUUUGUCGGCGA 22 Novel PC-miRNA-29 UCAGGGAUUCAAGUUGUAAUAUC 24 Novel PC-miRNA-30 UGGGAUUGCAAGUGAUUGGAAAGA 25 Novel PC-miRNA-31 UAUGGGCAAUGUGAUGUGCUA 22 Novel PC-miRNA-32 GUUCGCGUCGAUGACUUGGAG 22 Novel PC-miRNA-33 GCGGAUGAAAAUGCUCAC 18 Novel PC-miRNA-34 CCCCGGUCCGUCGCGAUGGUGGGC 25 Novel
Supplementary Table 1 SULFO-TAG labeled and biotinylated belimumab solution concentrations used in the ECL assay Company SULFO-TAG labeled belimumab (μg/mL) Biotinylated belimumab (μg/mL) A 0.25 0.75 B 0.5 0.5 C 2.0 1.0 D 0.25 1.0 E 0.5 0.5 F 0.125 0.125 G 0.2 1.0 H 2.0 1.0 J 1.0 1.0 Supplementary Table 2 Experimental condition for determination of minimum required dilution (MRD) Company Dilution (fold) ADA (ng/mL) n run A 2, 5, 10, 50, 100 2.5, 5, 10, 20, 40, 80, 160, 320, 640, 1,280, 2,560 2 1 C 3, 10, 30, 50, 100 5, 25, 125, 625, 3,125, 15,625, 78,125 2 1 D 1, 4, 10, 100 7.41, 20.8, 58.1, 163, 456, 1,276, 3,571, 10,000 2 1 F 1, 2, 5, 10, 100 0.46, 1.4, 4.1, 12, 37, 111, 333 2 1 G 100, 1000, 10000 0.97, 1.95, 3.91, 7.81, 15.6, 31.3, 63, 500, 1,000 2 1 H 1, 2, 10 20, 200, 2,000 2 1 I 1, 2, 10 31.3, 62.5, 125, 250, 500, 1,000, 2,000 2 1 Supplementary Table 3 Experimental conditions for calculation of screening assay precision Company ADA (ng/mL) n Runs A 20, 1000 3 6 B 200, 1,250, 4,000 6 (1 run), 4 (2 runs) 3
Fig. S1. The optimization of extraction parameters. (a) Effect of sample mass. Conditions: extraction solvent volume, 10 mL; extraction solvent, methanol; extraction time, 10 min, extraction temperature, 30oC. (b) Effect of extraction solvent. Conditions: extraction solvent volume, 10 mL; sample mass, 0.1 g; extraction time, 10 min, extraction temperature, 30oC. (c) Effect of % water in methanol. Conditions: extraction solvent volume, 10 mL; sample mass, 0.1 g; extraction time, 10 min, extraction temperature, 30oC. (d) Effect of temperature. Conditions: extraction solvent volume, 10 mL; sample mass, 0.1 g; extraction solvent, 20%
Analyte MDL Analyte MDL Analyte MDL Analyte MDL PCB-30 4.40 3.87 HCB 3.54 PBDE-17 1.01 PCB-18 5.14 2.98 α-HCH 4.57 PBDE- 28 1.16 PCB-31 3.26 5.46 β-HCH 5.44 PBDE- 71 1.30 PCB-28 4.07 2.89 γ-HCH 5.80 PBDE- 47 1.86 PCB-22 5.37 3.54 δ-HCH 3.07 PBDE- 66 3.94 PCB-54 3.40 2.18 HEP 5.87 PBDE-100 2.18 PCB-52 3.25 2.25 ALD 4.51 PBDE- 99 1.85 PCB-49 3.64 2.25 HEPX 6.52 PBDE- 85 3.66 PCB-44 6.31 4.02 CC 2.01 PBDE-154 3.48 3.05 3.10 TC 5.66 PBDE-153 1.41 PCB-74 3.54 2.11 o,p’-DDE 3.72 PBDE-138 1.76 PCB-70 3.02 3.79 α-ENDO 3.39 PBDE-183 1.78 PCB-60 8.85 3.92 DIELD 5.85 PBDE-190 4.23 PCB-56 2.84 3.57 o,p’-DDD 5.08 PBDE-209 4.84 3.22 4.58 p,p’-DDE 5.00 PCB-95 4.02 4.02 END 5.78 4.88 2.10 β-ENDO 3.40 PCB-99 3.60 1.83 o,p’-DDT 4.29 PCB-87 4.25 3.50 p,p’-DDD 4.21 4.11 3.88 ENDOSULP 3.61 3.37 3.26 p,p’-DDT 4.93 3.88 3.17 Mirex 7.32 Bold and underlined numbers represent IDLs 180 167 151 153 132 149 158 110 90/101 157 138 203 104 123 118 170 114 187 183 105 189 174 141
α-HCH 0.8991 δ-HCH 0.8431 o,p’-DDE 0.6021 p,p’-DDD 0.9913 ENDO-SO4 0.9822 ENDO-β 0.9633 o,p’-PDDT 0.5442 DIELD 0.9524 ENDR 0.9502 p,p’-DDE 0.7030 HEPT 0.8241 ENDO-α 0.7538 ALDR 0.8122 MIREX 0.6352 p,p’-DDT 0.7032 HCB -0.6974 Table S10. Eigenvalues, percent and cumulative percent variation explained for PCBs at rural sites Factor Eigenvalue Variation Explained (%) Cumulative Variation Explained (%) 1 15.8 42.6 42.6 2 3.20 8.7 51.2 3 2.73 7.4 58.6 4 2.27 6.1 64.8 5 1.70 4.6 69.4 6 1.61 4.3 73.7 7 1.47 4.0 77.7 8 1.33 3.6 81.3 9 1.17 3.2 84.5
Fuel Load NOX (g/kg-fuel) DMA 25% 66.0 ± 1.4 75% 66.1 ± 0.5 RMB-30 25% 60.1 ± 1.3 75% 61.4 ± 0.8 RMG-380 25% n/a 75% 49.9 ± n/a
Table S8b t-test Comparisons between Fuels at the 75% Load Point Table S9 (a) t-test Comparisons between Instruments at the 25% Load Point Table S9 (b) t-test Comparisons between Instruments at the 75% Load Point BC mass concentration presented in mass per volume units for the 25% load points The graphs in this section show the lower concentration levels from Figure 4, which represent the 25% load points, in greater detail. Figure S4: Various Instrument Responses with respect to PAS Mass Concentration at 25% load BC mass concentrations for the RMB-30 and RMG-380 Fuels Normalized by the DMA Fuels Some additional comparisons were also done by normalizing the results for the different instruments for the RMB-30 and RMG-380 fuels by the corresponding results from the DMA fuel. These results are shown in Figure S5. For the normalized RMB-30 fuel results, there were no significant changes in slope for most instruments relative to the PAS, with the exception of the TOA-ES and the Aethalometer. TOA-ES: A decrease in the slope was observed for the TOA-ES. As mentioned in the BC instrument comparison section, it was observed that the split points for both the DMA and the RMG-380 fuels were early, suggesting either a catalytic effect due to the presence of metal
used as a statistical measure to avoid multicollinearity. VIF values are calculated by using “vif” function from “usdm” package (Naimi, 2015). Figure S4 provides a schematic diagram of data processing and input selection procedure. Figure S4. Schematic diagram of data processing and input selection procedure used to estimate PM2.5 concentration. 5.3 Modelling process The final optimum parameter dataset is used for building BPANN, ANFIS, and SVM models using MATLAB R2014b software. In order to formulate the BPANN model, “mapminmax” function is used to normalize the input values based on the minimum and maximum values. The BPANN network is created by “newff” function from the neural network toolbox (Demuth and Beale, 2000). Then, the network is trained by the “train” function, and the simulation is accomplished by the “sim” function to calculate the final results (Demuth and Beale, 2000). The “mapminmax” function is used to transform the results to original scale.
Similar to the model, an ANFIS model starts with the “mapminmax” function being applied to normalize the input values based on the minimum and maximum values. The “genfis2” function from fuzzy logic toolbox is employed to build Sugeno-type fuzzy inference system from data using subtractive clustering method (Zadeh, 1995). The “anfis” function is used to train the fuzzy inference system and tune the learning parameters. The “evalfis” function is employed to perform fuzzy inference calculations and compute the model’s output (Zadeh, 1995). The “mapminmax” function is used to map the results to original scale. In order to formulate the SVM model, an “initlssvm” function from LS-SVMlab toolbox is employed to define the model (De Brabanter et al., 2011). The model’s parameter is derived from a “tunelssvm” function, and then the “trainlssvm” function is used to train the model. Finally, the simulation is accomplished by using “simlssvm” function which calculates the model’s output (De Brabanter et al., 2011). In this a 10-fold cross-validation (CV) technique is used to evaluate the predictive ability of the different models to identify the optimal model for estimating the PM2.5 concentration. Therefore, the “crossvalind” function is used to generate indices for a 10-fold CV. Then, each candidate model is fitted and cross-validated using these indices and results are averaged to obtain the overall cross validation R2 (CV-R2). Figure S5 provides a schematic diagram of the model building and evaluation process. Figure S5. Schematic diagram of model building and evaluation process used to estimate PM2.5 concentration.
Appendix for consideration for Online Only Publication: Oral Mucositis Scales Oral Mucositis Assessment Scale (OMAS) Ulceration/Pseudomembrane Erythema 0 1 2 3 0 1 2 None < 1cm2 lesion 1 to <3 cm2 lesion 3 cm2 or greater lesion None Not severe Severe Oral Sites Assessed Upper labial mucosa Lower labial mucosa Right buccal mucosa Left buccal mucosa Right lateral tongue Left lateral tongue Floor of mouth Soft palate and tonsil region Hard palate Maximum score of 5 per site: Ulceration maximum-3, Erythema maximum-2 with 9 sites assessed OMAS: Sum of all Ulceration and Erythema scores from all 9 (max 45) /9 OMAS Ulceration score is sum of Ulceration/Pseudomembrane scores from 9 sites (max 27) /9 OMAS Erythema score is sum of Erythema scores from 9 sites (max 18) /9 WHO Oral Mucositis Scale 0 1 2 3 4 None Erythema and Soreness Ulcers, able to eat solids Ulcers, requires liquid diet (due to mucositis) Ulcers, alimentation not possible (due to mucositis) NCI-CTC Oral Mucositis Scale (v2) 0 1 2 3 4 None Erythema of the mucosa Patchy pseudomembranous reaction (patches generally 1.5 cm in diameter and non-contiguous) Confluent pseudomembranous reaction (contiguous patches generally 1.5 cm in diameter) Necrosis or deep ulceration; may include bleeding not induced by minor trauma or abrasion.