dataesr/scientific-paragraphs-categorization huggingface dataset:
However, NEC occurs during the period of gut microbiota diversification and transition from facultative to strict anaerobes  [4, 5]. To date, no single microorganism has been conclusively associated with NEC. However, several studies have converged on a risk-associated community state consisting of an overrepresentation of bacteria all belonging to the gut commensal microbiota such as the Enterobacteriaceae family and certain Clostridium species  [11, [14] [15] [16] [18] [19] [20] [21] [22]. In particular, uropathogenic Escherichia coli (UPEC), Clostridium butyricum, and Clostridium neaonatale intestinal colonization have been associated with NEC  [11, 14, [22] [23] [24]. In this study, we present data from the nationwide prospective multicenter matched case-control study ClosNEC. Our aim was to compare the diversity and composition of the gut microbiota of French PNs with and without NEC.
Study Design and Patients PNs were recruited over a 16-month period (March 2015 to August 2016) in 20 French NICUs participating in the ClosNEC trial (NCT02444624). Approval was obtained from the National Data Protection Authority (Commission Nationale de l'Informatique et des Libertés, n • 915094) and the Consultative Committee on the Treatment of Information on Personal Health Data for Research Purposes (n • 15. 055). Parents provided informed consent. All enrolled PNs were less than 32 weeks (wks) gestational age. NEC cases and control PNs were from the same NICU and were matched for gestational age, birth weight, feeding type, and mode of delivery. Each NEC case was matched with two controls. NEC was confirmed by the neonatal clinical team and defined as the presence of clinical evidence meeting the modified criteria for NEC Bell's stage II (associated with radiologic pneumatosis intestinalis) or III (definitive intestinal necrosis seen at surgery or autopsy).
DNA Extraction, Sequencing, and Microbiota Analysis Total DNA was extracted from 150 mg aliquots stored at -80 °C without reagents according to Lepage et al. [25]. Bacterial load was assessed by quantitative PCR of the Bacteria domain (F_Bact1369: CGGTGAATACGTTCCCGG and R_Prok1492: TACGGCTACCTT-GTTACGACTT), as previously described  [26]. Standard curves were generated by plotting threshold cycles (Ct) versus bacterial count (CFU) expressed as CFU/g of fecal sample. Microbiota composition and diversity were analyzed by amplicon sequencing of the 16S rRNA V3-V4 region (V3fwd: TACGGRAGGCAGCAG; V4rev: TACCAGGGTATCTAAT)  [27]. Raw reads were analyzed using the Quantitative Insights Into Microbial Ecology (QIIME 2) software package 2018. 4  [28]. After primer and barcode trimming, sequences were filtered for quality (minimum length = 350-bp, minimum quality threshold = 20, and chimera removal) and clustered into de novo operational taxonomic units (OTUs) at a 97% similarity threshold using uclust.
DNA Extraction, Sequencing, and Microbiota Analysis Total DNA was extracted from 150 mg aliquots stored at -80 • C without reagents according to Lepage et al. [25]. Bacterial load was assessed by quantitative PCR of the Bacteria domain (F_Bact1369: CGGTGAATACGTTCCCGG and R_Prok1492: TACGGCTACCTTGT-TACGACTT), as previously described  [26]. Standard curves were generated by plotting threshold cycles (C t ) versus bacterial count (CFU) expressed as CFU/g of fecal sample. Microbiota composition and diversity were analyzed by amplicon sequencing of the 16S rRNA V3-V4 region (V3fwd: TACGGRAGGCAGCAG; V4rev: TACCAGGGTATCTAAT)  [27]. Raw reads were analyzed using the Quantitative Insights Into Microbial Ecology (QIIME 2) software package 2018. 4  [28]. After primer and barcode trimming, sequences were filtered for quality (minimum length = 350-bp, minimum quality threshold = 20, and chimera removal) and clustered into de novo operational taxonomic units (OTUs) at a 97% similarity threshold using uclust.
Study approvals: All animal experiments were approved by the Institutional Animal Care and Use Committee of Vanderbilt University Medical Center. Human samples were obtained under protocols approved by the Necker hospital Institutional Review Board and Boston University Medical Center and Brigham and Women's Hospital. All necessary patient/participant written informed consent was obtained. Statistics. All data were presented as means ±standard deviation (SD). One-way ANOVA and subsequent Tukey's post hoc test was used to determine statistical differences among over three groups. When two groups were compared, the unpaired two-tailed t-test was conducted. Survival curves were derived using the Kaplan-Meier method and compared using a log-rank test. Statistical analysis was performed using GraphPad Prism 7 software (GraphPad Software, San Diego, CA).
Acknowledgements We would like to thank  Dr. Ray Harris ,  Dr. Roy Zent , and  Dr. Ambra Pozzi  for their help in manuscript preparation. We would like to thank  Sushrut S. Waikar  and  Samir M Parikh  for help obtaining biopsy samples. We would also like to acknowledge the  Vanderbilt Cell Imaging Shared Resource and Nikon Center of Excellence  (supported by  NIH  grants  DK020593 ,  CA68485 ,  DK20593 ,  DK58404 ,  DK59637  and  EY08126 ) for help with imaging and analysis.
55: (0. 31, 0. 98)). Total dried fruit intake was not related to breast or ovarian cancer risks; total fruit intake was not associated with breast, endometrial, or ovarian cancer risks. Dried fruit intake and cancer risk were evaluated in the National Institutes of Health-American Association of Retired Persons Diet and Health study, which included 485,403 participants who were 50-71 years old  [61]. In this study, dried fruit intake was associated with lower RR (95% CI) of both liver cancer (0. 73 (0. 60, 0. 89)) and chronic liver disease mortality (0. 59 (0. 48, 0. 73))  [61]. A two-sample Mendelian randomization study utilized ~500,000 samples from the UK Biobank database to investigate dried fruit intake and cancer risk  [62]. In this data set, for one standard deviation increase in genetically predicted dried fruit intake, a reduced risk was observed for oral cavity/pharyngeal cancer, lung cancer, squamous cell lung cancer, breast cancer, pancreatic cancer, and cervical cancer  [62].
Acknowledgements We thank  Christine Lancelon-Pin  ( CERMAV, Grenoble ) for the SEM observations and the  NanoBio-ICMG platform  ( UAR 2607 ,  Grenoble ) for granting access to the  Electron Microscopy facility. This work has been partly performed using infrastructure and technical support of the  Plateforme Serre , cultures et terrains exp erimentaux - Universit e de Lille  for the glasshouse facilities. We thank the  'Plateforme d'Analyse des Glycoconjugu es, Facult e des Sciences et Technologies de Lille, Plateformes Lilloises en Biologie et Sant e (PLBS)   -UAR 2014 -US 41 ' for providing the technical environment conducive to achieving measurements of ADP-Glc. This work was partly supported by the  CPER Alibiotech  project that is financed by the  European Union , the  French State , and the  French Region of Hauts-de-France.
Reactions were run in triplicate. All the RT-qPCR reactions were planned using GENEIO qPCR workflow application (BioSistemika LLC, Ljubljana, Slovenia) and the microplates were pipetted with the assistance of PLATR smart pipetting assistant (Bio-Sistemika LLC, Ljubljana, Slovenia). The quantification cycle (Cq) for each reaction was obtained using the software SDS 2. 4 (AppliedBiosystems, CA, USA). The fluorescence thresholds were manually set for RoV and NoV according to the amplification curve. A positive control (PC) for RoV and NoV was added to monitor each amplification. A sample was considered positive when the reading provided a nonzero Cq. In addition, each positive amplification curve was manually checked and only curves showing a significant slope increase, in contrast with the negative control curves (NTC, NCI, and NCC), were considered as real positives.
Acknowledgments This work was supported by an  NSF   EAR-Postdoctoral Fellowship  and a  Marie Curie Individual Fellowship  ( 833702-MICROPATH ) to J. D. D. ,  AEI/FEDER UE  and  Spanish Office for Research (MINECO)  funded  MEDSOUL  ( CGL2014-59977-C3-2-R ) and  Eco-Reactors  ( PGC2018-101975-B-C22 ) to E. G. , and a  Ramon y Cajal fellowship  ( RYC-2017-22643 ),  CANTERA  ( RTI2018-094521-B-100 ) and  EVA-SIONA  ( PID-2021-122817NB-100 ) to S. B. T. A. acknowledges support by the  French National Research Agency  via the  INFLOW  project  ANR-21-CE29-0008. We thank  G. Carreras ,  O. Garcia Antunez  and  S. Castelar  for their help in the field and lab experiments.
Population and methods This single-centre retrospective observational study included infants born with a birth weight less than 1000 g, admitted within the first 24 h of life to the neonatal intensive care unit of the Croix-Rousse University Hospital in Lyon (France), and still hospitalised at 35 weeks PMA. Infants with serious congenital malformations were excluded. Data were prospectively recorded in the patient's electronic files (ICCA, Philips, Boblingen, Germany). Daily protein and energy intakes were assessed on the first day of each week of life and compared to recommended intakes (protein: < 1 kg: 4. 0-4. 5 g/kg/day, 1-1. 8 kg: 3. 5-4. 0 g/kg/ day, energy: 110-135 kcal/kg/day)  [15]. Serum urea was measured weekly. Bronchopulmonary dysplasia (ventilatory support or oxygen therapy at 36 weeks PMA), intraventricular haemorrhage grade 3 or 4, periventricular leukomalacia, retinopathy of prematurity stage ≥ 3, and necrotising enterocolitis stage ≥ 2 were collected.
Body weight was measured daily during the first week of life, and then weight, crown-heel length, and head circumference (HC) were measured weekly. The length was measured using a rigid measuring board suitable for premature newborns (Premie Stadiometer, Ellard instrumentation, Monroe, USA). Anthropometric data were expressed in absolute values and Z-scores, and differences in Z-scores between birth and discharge were calculated  [16]. Infants were considered to be small for GA (SGA) when the Z-score for body weight was ≤ -1. 28 (10th percentile equivalent)  [16]. PNGF was considered when the Z-score loss between birth and discharge was higher than 1 or when the Z-score for body weight at discharge was ≤ -1. 28. Air displacement plethysmography (PEA POD®, Cosmed France, Brignais, France) was performed between 35 and 41 weeks PMA.
Variables with p < 0. 05 in univariable analysis were retained in the multivariable model. Results are presented as odds ratios and their 95% confidence intervals [95%CI]. The search for factors potentially associated with FM% was carried out using univariable and multivariable linear regression analyses. Variables with p < 0. 05 in univariable analysis were retained in the multivariable model. Results are presented as an estimate with [95%CI]. The alpha-risk significance level for all analyses was set at 0. 05. All analyses were performed using R software version 3. 5. 3 (R Foundation for Statistical Computing, Vienna, Austria). The study was approved by the ethics committee Comité de Protection des Personnes Sud-Est IV (IRB: 00009118), and the institutional review board (Comité scientifique et éthique des Hospices Civils de Lyon, n°22_608) was registered in Clinicaltrials.
However, such intakes supported early postnatal growth, as only a fifth of infants were SGA at 1 month of life, compared to the 75% previously reported, representing a significant improvement in the prevention of initial growth deficit originally described by Embleton et al. [18, 20]. Good protein utilisation was reflected by rather low serum urea. These results suggest that the slightly excessive energy intake relative to the protein intake avoided the restriction of protein utilisation which could be related to a lack of energy. Although such intakes allowed good postnatal growth in most infants, they also likely favoured high FM% at discharge. These data advocate for close monitoring of protein and energy intakes, but also that of the protein-to-energy ratio. The postnatal growth observed in this cohort closely followed that of foetal growth, at least for body weight and HC.
Flash dryer development Based on the design of a prototype flash dryer (100 kg/h) for cassava starch installed at the International Center for Tropical Agriculture (CIAT), Cali, Colombia  (Tran et al. , 2022) , the flash dryer for this study (186. 34 kg/h) was developed. Thus, it is a scaled-up version of the prototype flash dryer that was installed at CIAT. Computer Aided Design (CAD) software, Autodesk Inventor 2012, was used to generate the flash dryer's engineering drawings, followed by the construction of the dryer based on the dimensions specified in the excel tools.
Dryer fabrication The dryer was constructed according to the specifications using the excel tools software. Materials used in the dryer's fabrication were sourced locally, taking into account the environmental, economic, and availability of the dryer to small-holder farmers in order to reduce postharvest loss. Additional criteria for material selection included their capacity to tolerate extreme temperatures and stresses as well as their food grade for sections that come into touch with the products they are intended to dry. The drying duct was built of 1. 2 mm thick stainless steel whereas the hopper, feeder and cyclone were made of 3 mm thick stainless steel. The heat exchanger's combustion tube was constructed of 4 mm thick stainless-steel sheet, while the return tube bundles were made with 60 mm diameter pressure pipe and turbulators were constructed of 1.
138 Thus, because LDs are major cholesterol reservoirs and suppliers, the activity of d-LDs and the IFNs signaling could generate a loop to determine the intensity and duration of the defensive programs. Following the example of f-LDs, we anticipate that the activity of the d-LD proteome is finely modulated by phosphorylation. [142]  Kinase-specific acceptor site prediction and substrate enrichment analysis, using combined machine learning approaches and public datasets, confirmed that the LD proteome is tightly regulated by PKA (PRKACA) (Figure  4B ) but additionally predicted that d-LD proteins are phosphorylated by kinases involved in different aspects of immunity such as PKB (AKT), Glycogen synthase kinase-3 (GSK3), Casein Kinase II Subunit Alpha (CSNK2A), and the I-kappa B kinase (IKK) (Figure  4B ).
Funding information  H2020-MSCA-ITN-2018 , Grant/ Award Number: 953489;  Australian Research Council ;  ERC Synergy , Grant/ Award Number:  ERC-2022-SYG  and  101071784 ;  Instituto de Salud Carlos III (ISCIII) ;  Lady Tata Memorial Trust ;  Marie Skłodowska -CurieActionsPostdoctoral Fellowship; MCIN and the  Pro CNIC Foundation ;  Spanish Ministerio de Innovación y Ciencia , Grant/Award Number:  PID2021-128106NA-I00  and  RYC2020-029690 ;  Severo Ochoa Center of Excellence , Grant/Award Number:  MICIN/AEI/10. 13039/501100011033and CEX2020-001041-S ;  I+D+i RETOS INVESTIGACIÓN; Ministerio de Ciencia e Investigación , Grant/Award Number:  PID2021-127043OB-I00  Summary.
Study design, participants and collection of samples Peripheral blood, saliva and stool samples were obtained from healthy young adults, from 18 to 30 years old. Volunteers were recruited following a medical interview to ascertain that they had no known diseases, no known history of allergies, that they were not under medication, had no drugs intake, no recent alcohol intake and were non-smokers. The GOMMS PRL12009 project was part of the biobank of Biofortis SAS and was designed to enroll 80 participants. Of these, full sample collection and complete data could only be obtained from 72 individuals. This biocollection is registered at the French Research Ministry (AC-2013-1792) and the PRL12009 project was approved by the French Ethic Committee (CPP Ouest IV). All volunteers were aware of the study protocol and fulfilled the informed consent form.
Then, for each sample, a sequencing library was generated by addition of dual indices and Illumina sequencing adapters, using a Nextera XT Index kit (Illumina, San Diego, CA, United States). Each library was cleaned with magnetic beads and its size was determined by capillary electrophoresis. After quantification by fluorimetry (Qubit ® 2. 0 Fluorometer), libraries were normalized and pooled. The pool of libraries was further denatured and sequenced on the Illumina MiSeq platform, using a 2 × 250 paired-end Miseq kit V2 (Illumina, San Diego, CA, United States). Read sequences from fecal microbiota were analyzed using an in-house bioinformatic pipeline based on mothur v1. 33. 3 software  (Schloss et al. , 2009). Briefly, sequences were trimmed and aligned to the V3-V4 region of the 16S gene of the Greengenes database that had been formatted with mothur (gg_13_5_99 release).
Chimera sequences were removed using the UCHIME algorithm. Reads were classified using a naive Bayesian classifier against RDP database release 11 with a bootstrap cut-off of 60%. Sequences were then clustered into operational taxonomic units (OTUs) using furthest-neighbor clustering at a similarity threshold of 97%. qPCR analysis: Quantifications of F. prausnitzii were performed by qPCR using SYBR Green PCR Master Mix (Applied Biosystems) in a StepOnePlus apparatus (Applied Biosystems). Each reaction was done in duplicate in a final volume of 20 μl with 0. 2 μM of each primer and 5 μl of the appropriate dilution of DNA. F. prausnitzii was | quantified using specific primers: sense, 5′-CCATGAATTGCCTTCAAAACTGTT-3′, and antisense, 5′-GAGCCTCAGCGTCAGTTGGT-3′  (Sokol et al. , 2008). Appropriate dilution of stool DNA was assessed by performing an Internal Positive Control (AppliedBiosystems, Ref 4308323).
Acknowledgments We acknowledge the contribution of Cytocell (Flow cytometry and  FACS core facility, BioCore ,  CNRS   3556-Inserm US016-Nantes Université UMS 3556 ,  Nantes ) for expert technical assistance with flow cytometry material and methods, and the  IBISA MicroPICell facility (Biogenouest) , member of the national infrastructure  France-BioImaging  supported by the  French National Research Agency  ( ANR-10-INBS-04 ) for their expert technical assistance. We also thank  Clémentine Méry ,  Yao Amouzou  and  Françoise Le Vacon  from  Biofortis SAS  for their expert assistance and support.
Data collection and processing Anthropometric measurements (height and weight) were collected during clinical examinations at 2 and 5 years or retrieved from health professional records in the child health booklet. Age-and sex-speci c BMI z-scores were computed at both 2 and 5 years according to the WHO growth references and overweight and obesity at 5 years were de ned using the WHO standard cut-offs  (23). Categories were as follows: thinness (BMI z-score < - 2), normal (BMI z-score ≥ - 2 to < 1), overweight (BMI z-score ≥ + 1 to < + 2), and obese (BMI z-score ≥ + 2). Given the low prevalence of the extreme categories children in our study population (Table  1 ), thin and normal children were pooled in a "non-Overweight/Obese" (non-Ow/Ob) group and overweight and obese children were pooled in an "Overweight/Obese" (Ow/Ob) group.
For a subgroup of ELFE children with available data, BMI z-score around 3. 5 years (median age, 39. 6 months, interquartile range [IQR] 37. 4-41. 8 months) was computed. 1 ). For children, information regarding gestational age, delivery mode, and human milk consumption was collected. From available data on human milk consumption in both cohorts, an "human milk consumption" variable was created referring to any human milk intake whatever the source (own mother or donor), the mode (bottle or breast), and exclusively or not. For the ELFE cohort only, information regarding the age at complementary feeding and child diet at 2 years of age was also available: mothers were asked about usual children's diet of their children using 20 questions food frequency questionnaire. Using a Principal Component Analysis (PCA), we identi ed two dietary patterns; "unhealthy" and "healthy" presented in Table  S1.
Samples collection, DNA extraction, sequencing, data processing The stool samples collection, DNA extraction, sequencing, and data processing procedures were performed as previously described  (24). Brie y, DNA extraction was performed according to the International Human Microbiome Standards operating procedure, (25) and the sequencing was performed using Illumina MiSeq technology (V3, 2x 250 bp) targeting the V3-V4 primers (V3fwd: TACGGRAGGCAGCAG, V4rev: TACCAGGGTATCTAAT) regions of the 16S bacterial rRNA gene. To adjust for the in uence of uneven sampling depth, each sample was rare ed to 9258 reads and rare ed data were used for all downstream analyses unless stated otherwise. Furthermore, we performed a quantitative PCR (qPCR) targeting speci cally A. muciniphila (see supplementary materials).
The miRNAs binding relies mainly on 'seed pairing' (the perfect or near-perfect complementary match of nucleotides 2-8 of the mature miRNA Disclaimer/Publisher's Note: The statements, opinions, and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content. product  [5]. In silico database exploration predict binding sites on promoter, 5'UTR, coding domain of mRNA, as well as on lnc-RNA. These molecules can be detected in cytoplasm, nucleus, and nucleolus  [6]. Non-coding RiboNucleic Acids (small or long ncRNA) are involved in epigenetic regulation directly silencing or activating chromatin at specific loci or through their integral role in the machinery that drives DNA methylation.
The main result is to relate miR-186-5p with the glycogen synthase kinase 3 beta (gsk3b) gene in F2-ovaries, a negative regulator of glucose homeostasis, involved in energy metabolism, inflammation, ER-stress, mitochondrial dysfunction, and apoptotic pathways. Defects in this gene have been associated with Parkinson disease and Alzheimer disease. The miR-186-5p expression decreases in F2 milk-siblings, whereas Gsk3b increases compared to control counterparts. These data on breast milk are well in line with those of a pilot study conducted to analyze the miRNA profiling in gastric content from both breast-fed and formula-fed infants  [77, 78]. The gastric content of infants at autopsy were analysed and demonstrate the presence of miRNAs in gastric content. What is more interesting in these findings is the fact that the samples were isolated between 1 month and 2 years after their death.
Overview We combined different sources of data to document the diffusion of food technologies across countries and over time, and its associations with changes in country-level nutritional outcomes. Our final dataset included 38 HIC and 29 MIC in the period 1970-2010. The HIC and MIC groups were defined using the 2014 World Bank income classification. The set of countries was restricted to HIC and MIC that had food-related patent applications, and for which we observed patent, nutrition, trade and other data used in the analysis for at least 16 years during the sample period. The full sample selection process, as well as countries present in the sample are detailed in online supplemental appendix p 3, pp 10-11 and p 12. We eliminated observations after 2010 because application data were incomplete after that date in the PATSTAT database acquired in 2018.