dataesr/scientific-paragraphs-categorization huggingface dataset:
Setmelanotide clinical trial The clinical trial protocol was reviewed and approved by Schulman Associates Institutional Review Board, 4445 Lake Forest Drive, Suite 300 Cincinnati, OH 45242, USA. All clinical trial participants provided informed consent prior to enrolling in the study (ClinicalTrials. gov Identifier: NCT02431442). Weight: All measurements were performed in triplicate throughout the study. The same scale was used throughout the study, including the screening visit, and was calibrated daily. Weight was measured when individuals were fasted at approximately the same time each day. Individuals were in scrubs, with no shoes and an empty bladder. Individuals were blinded to their weight throughout the study. Waist circumference: All measurements were performed in triplicate. Measurements occurred during screening, at baseline, once weekly during treatment, and at the follow-up visits.
Vital signs: Blood pressure (BP) and heart rate (HR) were obtained in the supine position following at least 5 min of rest each time they were measured. Pre-dose measurements were taken in triplicate, approximately 2 min apart; the means of these triplicate measurements served as the baseline values. All other BP and HR time-points were single measurements. When possible, BP was taken in the same arm as it was taken at pre-dose baseline. For the first day, vitals were taken every hour for the first 12 h, then every 2 h. On Day 2, vitals were taken every 12 h, followed by once daily thereafter. On days 8, 14, 22, and 28, vitals were taken every 12 h. Ambulatory BP monitoring (ABPM): Equipment and software was provided by CoreLab Partners, Rockville, MD 20850, USA. The ABPM monitor was worn continuously for a minimum of 24 h at 3 timepoints throughout the study: baseline, approximately mid-way through dosing duration, and at the end of dosing.
To enable reliable classification of these variants, we performed functional assays on 22 MC4R variants with unknown, incomplete or ambiguous functional status for which we had clinical data; 5 resulted in a complete LOF, 14 in a partial LOF and 3 were wild type (WT)-like (Figure  1BeD , Table  S1 ). We have made the functional classification dataset with MC4R functional assay data, available as a searchable resource (Table  S2 , www. mc4r. org. uk). Using this functional classification, we examined phenotypic data from 224 children and 264 adults carrying MC4R mutations. We found that MC4R variant homozygotes were significantly more obese than heterozygotes (p < 0. 001); there was no significant difference in BMI between those carrying heterozygous complete vs partial LOF variants (Figure  1E ).
FUNDING This work was supported by the  Wellcome Trust  (I. S. F. ), the  National Institute for Health Research Cambridge Biomedical Research Centre (S. O'R. , I. S. F. ) , the  Bernard Wolfe Health Neuroscience Fund (I. S. F. ) , the  European Research Council  (I. S. F. ), and the  Swiss National Science Foundation  ( PBLAP3-145870 ,  P3SMP3-155318 ,  PZ00P3-167826  to T. -H. C. ). Funds were also obtained from the  Clinical Research Programs on Obesity (Assistance Publique-Hôpitaux de Paris , and the  Direction of Clinical Research (CRC)  ( PHRC 02076  to K. C. ), as well as the  Institut Benjamin Delessert  and the  Fondation pour la Recherche Médicale  and the  National Agency of Research  (program " Investissements d'Avenir " with the reference  ANR-10-IAHU-05 ). The clinical trial was supported by  Rhythm Pharmaceuticals.
OP exposure induces OP-metabolizing machinery of gut microbiota Antibiotics are known to shape the physiology and gene expression of the active human gut microbiome  [22]. In order to understand the functional effects of OP on gut microbiome, we studied metatranscriptomics of bacterial RNA from the caecum of control and MCP-fed animals. Total RNA was isolated from caecum along with its content and the eukaryotic RNAs and bacterial ribosomal RNAs (rRNAs) were selectively removed and bacterial messenger RNA (mRNA) was enriched. RNA sequencing (RNA-seq) was performed yielding millions of reads which were annotated to the mice genome, human microbiome database (2012), and all other RNA libraries (Additional file 4: Table  S15 ). To obtain a high-level view of the transcriptional response of OPs, the number of normalized counts assigned to each KEGG metabolic pathway were tallied.
OP treatment resulted in increased expression of xenobiotic biodegradation and metabolism KEGG category. As previously reported in the case of antibiotic treatment  [22] , the expression of modules linked to genetic information processing, particularly translation, was increased while the transcription module was relatively decreased (Fig. 4a  and Additional file 4: Table  S16 ). Analysis of KEGG module and pathway abundance with HUMAnN and LEfSe confirmed and extended these trends: OPs induced the expression of modules for xenobiotic metabolism, glucose metabolism, phosphate transport, vitamin biosynthesis, nucleotide metabolism, and translation. Further on analysis with the metacyc enzyme database from the human microbiome consortium, we found a significantly increased expression of enzymes linked to OP degradation (Fig.
Oral glucose tolerance test OGTT was performed to analyze how quickly the glucose is cleared from the blood  [41]. The animals were fasted overnight prior to execution of OGTT, blood was sampled by the tail vein, and glucose was measured using the glucometer (0 min). Subsequently, the animals were gavaged with glucose solution (1. 5 g/kg body weight) and blood glucose was monitored at 15, 30, 60, 90, and 120 min. The data were plotted in blood glucose versus time curve and glycemic response was expressed as area under the curve (AUC, × 10 3 ).
RNA sequencing and analysis RNA library was constructed using TruSeq kit (Illumina Inc. , USA) as per the manufacturer's instructions. RNAseq was done at Centre for Cellular & Molecular Platforms (Government of India), Bangalore with paired-end reads in Illumina HiSeq 1000 machine. The sequencing was performed in a blinded way. Raw data were processed using the Solexa software. Low-quality reads were filtered according to the base quality value. The reads were mapped with mouse genome, murine mRNAs, transfer RNAs, and rRNAs by Bowtie 2  [46]  and the annotated sequences were removed. We used a reference database of human microbiome to perform functional analysis of the RNA-seq data. This reference included 538 draft and finished bacterial genomes from the human microbiome consortium. High-quality reads were mapped using Bowtie 2 to our reference bacterial database.
Subsequently, using the KEGG database, all predicted proteins from the reference genome database were annotated with KEGG orthologous groups (KOs). For query genes with multiple matches, the annotated reference gene with the lowest e value was used. When multiple annotated genes with an identical e value were encountered after a BLAST query, we included all KOs assigned to those genes. The number of transcripts assigned to each gene was then tallied and normalized to RPKM. To account for genes that were not detected owing to limited sequencing depth, a pseudocount of 0. 01 was added to all samples. Genes were grouped by taxa, genomes, and KO by calculating the cumulative RPKM for each sample. HUMAnN  [47]  was used for metabolic reconstruction from metagenomic data followed by LefSe  [48]  analysis with bootstraping to identify significant biomarkers.
Acknowledgements The authors extend their deep sense of gratitude to all volunteers who participated in the study. The authors acknowledge  Prof. T. Pradeep ,  Indian Institute of Technology, Chennai, India  for providing access to the  GC/MS facility. The authors acknowledge  Prof. Oliver Fiehn , Director,  West Coast Metabolomics Centre, University of California, UcDavis, USA  for providing metabolomics service under NIH Grant funding  NIH   U24 DKDK097154. The first author expresses his gratitude to  Prof. A. Munirajan ,  Madras University, India  for his support and encouragement. The  Centre for Cellular and Molecular Platforms, India  is acknowledged for next generation sequencing service.
Funding This study was funded by  DBT-IPLS, -RGYI, UGC-UPE , -CAS, -CEGS, -NRCBS, SERB, and  DST-PURSE (Govt. of India). GV is supported by  CSIR  and  UGC (Government of India)  through  Senior Research Fellowship and Fellowship for Meritorious Students , respectively. ARL is supported by a  BHF   Intermediate Research Fellowship   FS/11/67/28954  and the  NIHR Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, UK.
Subjects and study design We conducted a retrospective longitudinal study on all patients from our HD center from July 2014 to July 2015. All patients with data available regarding micronutrients were included, except for pregnant women or patients aged <18 years. Written information was provided to all patients, and all gave consent for their personal data to be used for research purposes. According to French law, it is neither necessary nor possible to obtain approval from an ethical committee (in French CPP, Comité de Protection des Personnes) for this type of noninterventional study. Moreover, CPPs are not entitled to issue waivers of approval for this type of study. Nevertheless, this study obtained approval from the Health Research Data Processing Advisory Committee (in French CCTIRS, Comité consultatif sur le traitement de l'information en matière de recherche dans le domaine de la santé; ref 15.
Clinical, biological, and hemodialysis parameters The following data were collected from the patients' medical files: age, gender, diabetes mellitus, nephropathy, height, post-dialysis weight, vascular access. Evaluation of daily urine output was based on oral questioning of the patients and was therefore semi-quantitative: ≥500 mL/d or <500 mL/d. Body mass index (BMI) was calculated as post-dialysis weight after the mid-week session in kilograms divided by squared height in meters. Survival was assessed for all patients at one year. Dialysis parameters were recorded at the mid-week session, and biological analyses were all performed at the start of this hemodialysis session. Dialysis dose was estimated by a singlepool Kt/V (spKt/V), as recommended by Daugirdas et al. [8]. The ESRD adapted Charlson Comorbidity Index was performed for each patient  [9].
Biological data Albumin, transthyretin, predialysis creatinine and urea as well as C-reactive protein which are performed in routine practice in our hemodialysis center were recorded from patient's medical files. Transthyretin was dosed using an immunoturbidimetry assay (ADVIA® 1800 Clinical Chemistry System, Siemens, France). Albumin was dosed in serum using bromocresol green assay (ADVIA® 1800 Clinical Chemistry System, Siemens, France).
Statistical analyses Kaplan Meier tests were performed to assess association between transthyretin and mortality, as well as retinol and mortality. Univariate linear models were used to assess association between retinol and transthyretin, retinol and RBP4, and predialysis serum creatinine and RBP4. Cox models were used to determine factors associated with mortality. In a first step, variables with a statistical p-value of <0. 10 in the univariate analysis were considered eligible for inclusion in the multivariate analysis. In a second step, using a descending stepwise method, variables with a p<0. 05 in the multivariate analysis were retained within the final model. Results are shown as their medians [IQR] or percentages. Statistical analyses were performed with IBM SPSS 15. 0 software.
The active site geometry of ATX is homologous to that of TNAP, in which two zinc ions are coordinated by the same amino acid residues (one zinc is coordinated by two His and one Asp and the other by one His and two Asp)  (38). This is consistent with our results showing that ZNT5-ZNT6 heterodimers and ZNT7 homodimers are required for ATX activation (much as they are for TNAP activation), although minor differences FIGURE 3. CAIX can acquire zinc from a pathway independent of ZNT5-ZNT6 heterodimers and ZNT7 homodimers. A, confirmation of endogenous caIX mRNA expression in DT40 cells. Expression of the indicated ca genes was examined by performing RT-PCR with appropriate primers. B, example of the raw data from the ⌬pH/⌬t assay used for measuring CAIX activity. Membrane proteins prepared from WT cells and WT cells stably expressing CAIX were used for activity measurement, as described under "Experimental Procedures.
NB100-417, Novus Biologicals, Littleton, CO); anti-MMP9 (1:6000; catalog no. AF911, R&D Systems, Minneapolis, MN); anti-␤-tubulin (1:10,000; catalog no. T7816, Sigma); and anti-calnexin (CNX) (1:6000; catalog no. ADI-SPA-860, Enzo Life Sciences). For detection of immunoreactive bands, we used (at 1:3000 dilution) horseradish peroxidase-conjugated antimouse, -rabbit, or -rat IgG (GE Healthcare, NA931, NA934, or NA935) or anti-goat IgG (catalog no. sc-2020, Santa Cruz Biotechnology) antibodies. Fluoroimages were obtained using an LAS1000 Plus (Fujifilm). Densitometric quantification of the band intensity was performed using ImageQuant TL software (GE Healthcare). Immunofluorescence Staining-Immunostaining for ZNT4-FLAG detection was performed as described  (25). Briefly, cells were stained with polyclonal anti-FLAG (1:2000; MBL) fol-lowed by Alexa 594-conjugated goat anti-rabbit IgG (1:200; catalog no.
The proteins transferred to the PVDF membrane were detected by staining with Coomassie Brilliant Blue. Zinc-specific Fluorescence Staining-Cells were grown in zinc-deficient, normal, or zinc-supplemented (50 M ZnSO 4 ) medium for 48 h and washed once in phosphate-buffered saline. Zinpyr-1 staining was performed as described previously  (34). Briefly, cells were then treated with 5 M Zinpyr-1 ester (Santa Cruz Biotechnology) for 30 min at room temperature. After extensive washing with phosphate-buffered saline containing 20 mM EDTA to remove extracellular zinc, the cells were resuspended in phosphate-buffered saline containing 1% bovine serum albumin and were subjected to flow cytometry analysis using a BD Accuri C6 flow cytometer (BD Biosciences, Ann Arbor, MI). Statistical Analyses-All data are presented as means Ϯ S.
Euglycemic hyperinsulinemic clamps of HFD mice were performed to further assess insulin sensitivity on obesigenic diet. Endo1-CD-HFD mice are characterized by a significant fall in overall glucose uptake (GUR), a lower liver glucose production (EndoRa), and an overall decrease in insulin sensitivity compared to CTRL-CD-HFD, as suggested by the lower glucose infusion rate (Figure  3H ). Altogether, the data indicate that Endo1 silencing in the ARC does not have an impact on CD-fed mice but leads to molecular modifications that worsen the status of  diabetes of silenced mice challenged with a HFD, despite the prevention of obesity. 2. 4. Endo1 silencing in the ARC prior to DIO impairs sympathoadrenal activity and leads to defective glucose-stimulated insulin secretion and to higher glucagon levels on HFD Since Endo1 silencing in obese mice after DIO was characterized by an alteration of insulin secretion, this was later investigated in response to glucose administration in mice silenced for Endo1 prior to DIO.
Proximity ligation assay (PLA) Transfected HeLa cells, plated onto glass coverslips, were fixed with 4% PFA (PolySciences Europe) for 15 min at RT. Fixed cells were permeabilized with 0. 1% Triton X-100 for 10 min, followed by blocking in PBS containing 10% horse serum for 1 h at RT. Cells were incubated with rabbit anti-p85 (1:1000, Millipore) and mouse anti-Myc (1:200, Santa Cruz Biotechnology) antibodies overnight at 4 C. PLA was conducted using Duolink Ò In Situ-Fluorescence kit (Sigma), following the instructions of the manufacturer. Images were captured using a Zeiss Axioskop Observer Z. 1 microscope equipped with epifluorescence, with laser excitation filters at 548e572 nm and emission lines at 590e624 nm. Deconvoluted images were further analyzed with ImageJ software (NIH, Bethesda).
ACKNOWLEDGEMENTS Author Contribution: J. D. and R. J. wrote the manuscript; V. V. , C. R. , M. F. , S. M. , and C. M. reviewed the manuscript and contributed to discussion; J. D and R. J. designed experiments and managed the project; V. V. , C. R. , P. C. , J. D. , and S. M. performed research and analyzed data, C. S. and J. M. helped designing research, T. H. , K. O. , and Y. R. contributed to valuable tools, J. M. L. performed blood sample analysis. This work was supported by grants from the  European Union 's  Seventh Framework Programme  ( FP7/2007e2013 ) under grant agreement n 241592 (JD, RJ), the  Agence Nationale de la Recherche   ANR-12-JSV1-0011  (JD),  Institut National de la Santé et de la Recherche Médicale (INSERM) ,  Centre National de la Recherche Scientifique (CNRS) , a  PhD fellowship  from the  « Ministère de l'Education Nationale et de la Recherche en Technologie » (MNERT ,  ED419 ) (CR), a research fellowship from the  « Fondation pour la Recherche Médicale » (VV, CR).
Nevertheless, there is accumulating evidence of the frequent occurrence of subclinical vitamin D de ciency in populations living in sunny countries  [13] [14] [15] [16] [17]. Moreover, vitamin D insu ciency was recently found to be frequent in healthy Algerian children  [18]. Hence, although extrapolating the prevalence data from countries of similar climates and latitudes should be cautious because of other in uencing factors like diet on vitamin D status, we hypothesized that Algerian postmenopausal women may not be an exception and that vitamin D inadequacy may be relatively prevalent in this age group. To provide an estimation of the magnitude of the problem in our country, a cross-sectional study was carried out to determine the vitamin D status among a healthy postmenopausal women population recruited in Douera, a city located in the extreme northern part of Algeria.
Clinical and Sociodemographic Characteristics. After the participants signed the informed consent, they underwent a clinical examination. e clinical data collected included age, height, and weight. Body mass index (BMI) was then calculated using these anthropometric data as body weight in kilograms divided by height in meter squared. Medical (e. g. , existence of chronic illness) and obstetrical (parity) histories, age at menopause, current medications, and socioeconomic status (education level and profession) were also obtained by an experienced investigator. Participants were also asked to describe their previous fractures, if any (number and site). On the same day, bone mineral density (BMD) at L1-L4 lumbar spine and total hip, expressed in grams per centimeter squared, was measured in all participating women by dual energy X-ray absorptiometry (DXA-QDR-2000/W, Hologic Inc.
Questionnaires. A series of questionnaires were used for data collection. e skin phototype was determined according to the Fitzpatrick classi cation from I (pale white skin) to VI (dark brown or black skin). Daily sun exposure (average duration and sun-exposed body areas) and dressing habits were evaluated by direct questioning. Similarly, the mean weekly vitamin D intake from food was assessed using a sixquestion tool  [22, 23]. e daily calcium intake was calculated using the validated self-questionnaire of Fardellone and coworkers  [24] , adapted to the Algerian eating habits.
Statistical Analysis. Analyses were performed with SAS software (version 9. 4, SAS Institute Inc. , Cary, NC), and statistical signi cance was de ned as a value of p < 0. 05. To compare two groups, we used the chi-square test for categorical variables expressed as frequencies, the t-test for continuous variables expressed as mean ± standard deviation (SD), and the nonparametric Mann-Whitney test when the assumption of normality was questionable. To compare more than two groups, we used the chi-square test for categorical variables, a one-way analysis of variance for continuous variables, and the nonparametric Kruskal-Wallis test when the assumption of normality was questionable. Pearson's correlation was used to study the relationship between quantitative variables. A multiple logistic regression analysis was used to identify the factors best explaining a lower level of 25(OH)D.
Primer sequences, designed using Primer3 software  (Rozen and Skaletsky, 2000) , are listed in Table  1. The data obtained were normalized to the housekeeping gene β-actin (ACTB), and the data were transformed using the equation 2 -Ct , where Ct represents the fractional cycle number when the amount of amplified product reached a fixed threshold for fluorescence. The data are presented as fold changes relative to the C 1 group for statistical analysis.
Statistical Analysis All data were analyzed by one-way ANOVA using the general linear models (GLM) procedure of the Statistical Analysis System (SAS) software (SAS Institute, Cary, NC, USA). The treatment means for food intake and plasma glucose level were compared by Fisher's test or Student t test, while the Duncan's multiple range test option of the GLM procedure for SAS was used to determine significance of mean differences for gene expression analysis. Significance was set at P < 0. 05. fed groups that received a single i. v. injection (1. 5 mL/kg) of either normal guinea pig serum (NS, PromoCell, Heidelberg, Germany) or anti-porcine insulin guinea pig serum (AI) (C 1 and AI 1 groups, respectively), fed groups that received three i. v. injections (1. 5 mL/kg each) at time 0, 2, and 4 h of either NS or AIS (C 5 and AI 5 groups, respectively), and a fasted group that was fasted for 5 h and received three i.
In mammals GLUT2 is also expressed in the hypothalamus, contributing to the control of food intake  (Stolarczyk et al. , 2010). GLUT3 is a high affinity transporter responsible for glucose uptake in tissues and cells where extracellular substrate concentration is low (e. g. , neuronal cells)  (Kono et al. , 2005) , while GLUT8 has been shown to be insulin responsive in the blastocyst of mammals  (Carayannopoulos et al. , 2000). The presence of GLUT1, GLUT3, and GLUT8 mRNAs was confirmed by PCR in brain and liver tissues of chickens. In contrast, mRNA expression of GLUT2 was not detectable in the chicken hypothalamus in the present study (data not shown). Similar expression patterns were observed by  Kono et al. (2005)  in chicken tissues. The 5 h fasting treatment increased hypothalamic mRNA levels for GLUT1, GLUT3, and GLUT8 (Figure  4 ), with GLUT1 demonstrating the largest effect.
Data analysis Data collected was entered into a Microsoft Excel database. Descriptive statistics were undertaken first. Normally distributed data is presented as mean (SD) and non-normally distributed data as median and IQR. The data was then imported into IBM SPSS version 22 for further inferential analysis. Inferential analysis undertaken compared the two groups. Independent t test was used if the data was normally distributed and non-parametric tests, Mann-Whitney and Chi-square used if it was not. A p value < 0. 05 was considered significant and two-tailed tests were used. The UK study was registered as service evaluation with the NHS Trust (reference 5194) and in France, the centre received IRB approval (Reference No. 00009118, Comité de protection des personnes 89 Lyon sudest 2); in both instances, a waiver of consent was granted as no identifiable patient data was collected.
(B) At birth, we kept 12 dams per diet, and we adjusted litter size to 8 pups/litter with a 1:1 male to female ratio. Only the males were then used in this study. For each time point (P25, P45, and P95), one rat per litter was used for behavior and subsequent postmortem analysis. weight was recorded at birth and thereafter every day at 10:00 a. m. until P21 (weaning). After weaning and until the end of the experiment, rats were weighted every 3 days. We present data on male offspring only. Female rats were used for another study (Figure  1 ).