bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developments in pediatrics in 2020: choices in allergy, autoinflammatory disorders, critical care, endocrinology, genetics, infectious diseases, microbiota, neonatology, neurology, nutrition, ortopedics, respiratory tract illnesses and rheumatology
Authors: Caffarelli Carlo , Santamaria Francesca , Procaccianti Michela , Piro Ettore , delle Cave Valeria , Borrelli Melissa , Santoro Angelica , Grassi Federica , Bernasconi Sergio , Corsello Giovanni 
Published: December 2021

AbstractIn this article, we describe the advances in the field of pediatrics that have been published in the Italian Journal of Pediatrics in 2020. We report progresses in understanding allergy, autoinflammatory disorders, critical care, endocrinology, genetics, infectious diseases, microbiota, neonatology, neurology, nutrition, orthopedics, respiratory tract illnesses, rheumatology in childhood.
Development of a new score for early mortality prediction in trauma ICU patients: RETRASCORE
Authors: Serviá Luis , Llompart-Pou Juan Antonio , Chico-Fernández Mario , Montserrat Neus , Badia Mariona , Barea-Mendoza Jesús Abelardo , Ballesteros-Sanz María Ángeles , Trujillano Javier ,   the Neurointensive Care and Trauma Working Group of the Spanish Society of Intensive Care Medicine (SEMICYUC)
Published: December 2021

Abstract
Background
Severity scores are commonly used for outcome adjustment and benchmarking of trauma care provided. No specific models performed only with critically ill patients are available. Our objective was to develop a new score for early mortality prediction in trauma ICU patients.

Methods
This is a retrospective study using the Spanish Trauma ICU registry (RETRAUCI) 2015–2019. Patients were divided and analysed into the derivation (2015–2017) and validation sets (2018–2019). We used as candidate variables to be associated with mortality those available in RETRAUCI that could be collected in the first 24 h after ICU admission. Using logistic regression methodology, a simple score (RETRASCORE) was created with points assigned to each selected variable. The performance of the model was carried out according to global measures, discrimination and calibration.

Results
The analysis included 9465 patients: derivation set 5976 and validation set 3489. Thirty-day mortality was 12.2%. The predicted probability of 30-day mortality was determined by the following equation: 1/(1 + exp (− y)), where y = 0.598 (Age 50–65) + 1.239 (Age 66–75) + 2.198 (Age > 75) + 0.349 (PRECOAG) + 0.336 (Pre-hospital intubation) + 0.662 (High-risk mechanism) + 0.950 (unilateral mydriasis) + 3.217 (bilateral mydriasis) + 0.841 (Glasgow ≤ 8) + 0.495 (MAIS-Head) − 0.271 (MAIS-Thorax) + 1.148 (Haemodynamic failure) + 0.708 (Respiratory failure) + 0.567 (Coagulopathy) + 0.580 (Mechanical ventilation) + 0.452 (Massive haemorrhage) − 5.432. The AUROC was 0.913 (0.903–0.923) in the derivation set and 0.929 (0.918–0.940) in the validation set.

Conclusions
The newly developed RETRASCORE is an early, easy-to-calculate and specific score to predict in-hospital mortality in trauma ICU patients. Although it has achieved adequate internal validation, it must be externally validated.
Hypothalamic-pituitary hormones will be affected by the interaction between 5q13-14-rs2239670 (CARTPT) gene variants and diet in different obesity phenotypes
Authors: Mahmoudinezhad Mahsa , Abbasalizad-Farhangi Mahdieh , Kahroba Houman 
Published: December 2021

Abstract
Objective
Evidence show that cocaine and amphetamine regulated transcript-prepropeptide (CART-PT) gene variants may affect obesity related traits, but little is known about its end points. In the current study, we aimed to evaluate the interaction of CARTPT gene polymorphism with diet quality indices including dietary approaches to stop hypertension (DASH) and Mediterranean diet score (MDS) on cardio-metabolic risk factors. This cross sectional study recruited 288 apparently healthy obese individuals. Diet quality indices including DASH and MDS were evaluated using semi quantitative food frequency questionnaire (FFQ). Polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) was used for CARTPT genotypes.

Results
No significant differences was reported for general characteristics and biochemical parameters across genotypes except for QUICKI among females (P = 0.01) and it was higher in heterozygous genotype. There was significant CARTPT-DASH interactions affecting serum fasting glucose level (P = 0.049). However, in relation to CERTPT-MDS interactions, the highest level of insulin (P = 0.003) and HOMA-IR (P = 0.003) values were shown among AA carriers in high adherence to MDS, while AA carriers in high compliance to MDS experienced decreased level of QUICKI (P = 0.001).
Performance comparison of gel and capillary electrophoresis-based microsatellite genotyping strategies in a population research and kinship testing framework
Authors: Sánchez-Velásquez Julissa J. , Reyes-Flores Lorenzo E. , Yzásiga-Barrera Carmen , Zelada-Mázmela Eliana 
Published: December 2021

Abstract
Objective
The advancement of molecular techniques in an era in which high-throughput sequencing has revolutionized biology renders old-fashioned alternatives to high-throughput methods obsolete. Such advanced molecular techniques, however, are not yet accessible to economically disadvantaged region-based laboratories that still obtain DNA profiles using gel-based techniques. To explore whether cost-efficient techniques can produce results that are as robust as those obtained using high-throughput methods, we compared the performance of polyacrylamide gel electrophoresis (PAGE)- and capillary electrophoresis (CE)-derived genomic data in estimating genetic diversity and inferring relatedness using 70 individuals of fine flounder (Paralichthys adspersus) selected from a hatchery population and genotyped for five microsatellite loci.

Results
Here, we show that PAGE- and CE-derived genomic datasets yield comparable genetic diversity levels regarding allelic diversity measures and heterozygosity. However, relatedness inferred from each dataset showed that the categorization of dyads in the different relationship categories strongly differed. This suggests that while scientists can reliably use PAGE-derived genomic data to estimate genetic diversity, they cannot use the same for parentage testing. The findings could help laboratories committed to population research not be discouraged from using the PAGE system if high-throughput technologies are unavailable and the method is adequate to address the biological question.
Characterization of β-galactosidase and α-galactosidase activities from the halophilic bacterium Gracilibacillus dipsosauri
Authors: Deutch Charles E. , Farden Amy M. , DiCesare Emily S. 
Published: December 2021

AbstractPurposeGracilibacillus dipsosauristrain DD1 is a salt-tolerant Gram-positive bacterium that can hydrolyze the synthetic substrateso-nitrophenyl-β-d-galactopyranoside (β-ONP-galactose) andp-nitrophenyl-α-d-galactopyranoside (α-PNP-galactose). The goals of this project were to characterize the enzymes responsible for these activities and to identify the genes encoding them.MethodsG. dipsosauristrain DD1 was grown in tryptic soy broth containing various carbohydrates at 37 °C with aeration. Enzyme activities in cell extracts and whole cells were measured colorimetrically by hydrolysis of synthetic substrates containing nitrophenyl moieties. Two enzymes with β-galactosidase activity and one with α-galactosidase activity were partially purified by ammonium sulfate fractionation, ion-exchange chromatography, and gel-filtration chromatography fromG. dipsosauri. Coomassie Blue-stained bands corresponding to each activity were excised from nondenaturing polyacrylamide gels and subjected to peptide sequencing after trypsin digestion and HPLC/MS analysis.ResultFormation of β-galactosidase and α-galactosidase activities was repressed byd-glucose and not induced by lactose ord-melibiose. β-Galactosidase I had hydrolytic and transgalactosylation activity with lactose as the substrate but β-galactosidase II showed no activity towards lactose. The α-galactosidase had hydrolytic and transgalactosylation activity withd-melibiose but not withd-raffinose. β-Galactosidase I had a lowerKmwith β-ONP-galactose as the substrate (0.693 mmol l−1) than β-galactosidase II (1.662 mmol l−1), was active at more alkaline pH, and was inhibited by the productd-galactose. β-Galactosidase II was active at more acidic pH, was partially inhibited by ammonium salts, and showed higher activity with α-PNP-arabinose as a substrate. The α-galactosidase had a lowKmwith α-PNP-galactose as the substrate (0.338 mmol l−1), a pH optimum of about 7, and was inhibited by chloride-containing salts. β-Galactosidase I activity was found to be due to the protein A0A317L6F0 (encoded by gene DLJ74_04930), β-galactosidase II activity to the protein A0A317KZG3 (encoded by gene DLJ74_12640), and the α-galactosidase activity to the protein A0A317KU47 (encoded by gene DLJ74_17745).ConclusionsG. dipsosauriforms three intracellular enzymes with different physiological properties which are responsible for the hydrolysis of β-ONP-galactose and α-PNP-galactose. BLAST analysis indicated that similar β-galactosidases may be formed byG.ureilyticus,G. orientalis, andG. kekensisand similar α-galactosidases by these bacteria andG. halophilus.
Mesenchymal stem cell transplantation after acute myocardial infarction: a meta-analysis of clinical trials
Authors: Attar Armin , Bahmanzadegan Jahromi Fateme , Kavousi Shahin , Monabati Ahmad , Kazemi Asma 
Published: December 2021

Abstract
Background
Trials investigating the role of mesenchymal stem cells (MSCs) in increasing ejection fraction (LVEF) after acute myocardial infarction (AMI) have raised some controversies. This study was conducted to find whether transplantation of MSCs after AMI can help improve myocardial performance indices or clinical outcomes.

Methods
Randomized trials which evaluated transplantation of MSCs after AMI were enrolled. The primary outcome was LVEF change. We also assessed the role of cell origin, cell number, transplantation time interval after AMI, and route of cell delivery on the primary outcome.

Results
Thirteen trials including 956 patients (468 and 488 in the intervention and control arms) were enrolled. After excluding the biased data, LVEF was significantly increased compared to the baseline among those who received MSC (WMD = 3.78%, 95% CI: 2.14 to 5.42, p < 0.001, I2 = 90.2%) with more pronounced effect if the transplantation occurred within the first week after AMI (MD = 5.74%, 95%CI: 4.297 to 7.183; I2 = 79.2% p < 0.001). The efficacy of trans-endocardial injection was similar to that of intracoronary infusion (4% [95%CI: 2.741 to 5.259, p < 0.001] vs. 3.565% [95%CI: 1.912 to 5.218, p < 0.001], respectively). MSC doses of lower and higher than 107 cells did not improve LVEF differently (5.24% [95%CI: 2.06 to 8.82, p = 0.001] vs. 3.19% [95%CI: 0.17 to 6.12, p = 0.04], respectively).

Conclusion
Transplantation of MSCs after AMI significantly increases LVEF, showing a higher efficacy if done in the first week. Further clinical studies should be conducted to investigate long-term clinical outcomes such as heart failure and cardiovascular mortality.
Co-administration of human MSC overexpressing HIF-1α increases human CD34+ cell engraftment in vivo
Authors: Preciado Silvia , Sirerol-Piquer Mª Salomé , Muntión Sandra , Osugui Lika , Martí-Chillón Gerardo J. , Navarro-Bailón Almudena , Sepúlveda Pilar , Sánchez-Guijo Fermín 
Published: December 2021

Abstract
Background
Poor graft function or graft failure after allogeneic stem cell transplantation is an unmet medical need, in which mesenchymal stromal cells (MSC) constitute an attractive potential therapeutic approach. Hypoxia-inducible factor-1α (HIF-1α) overexpression in MSC (HIF-MSC) potentiates the angiogenic and immunomodulatory properties of these cells, so we hypothesized that co-transplantation of MSC-HIF with CD34+ human cord blood cells would also enhance hematopoietic stem cell engraftment and function both in vitro and in vivo.

Methods
Human MSC were obtained from dental pulp. Lentiviral overexpression of HIF-1α was performed transducing cells with pWPI-green fluorescent protein (GFP) (MSC WT) or pWPI-HIF-1α-GFP (HIF-MSC) expression vectors. Human cord blood CD34+ cells were co-cultured with MSC WT or HIF-MSC (4:1) for 72 h. Then, viability (Annexin V and 7-AAD), cell cycle, ROS expression and immunophenotyping of key molecules involved in engraftment (CXCR4, CD34, ITGA4, c-KIT) were evaluated by flow cytometry in CD34+ cells. In addition, CD34+ cells clonal expansion was analyzed by clonogenic assays. Finally, in vivo engraftment was measured by flow cytometry 4-weeks after CD34+ cell transplantation with or without intrabone MSC WT or HIF-MSC in NOD/SCID mice.

Results
We did not observe significant differences in viability, cell cycle and ROS expression between CD34+ cells co-cultured with MSC WT or HIF-MSC. Nevertheless, a significant increase in CD34, CXCR4 and ITGA4 expression (p = 0.009; p = 0.001; p = 0.013, respectively) was observed in CD34+ cells co-cultured with HIF-MSC compared to MSC WT. In addition, CD34+ cells cultured with HIF-MSC displayed a higher CFU-GM clonogenic potential than those cultured with MSC WT (p = 0.048). We also observed a significant increase in CD34+ cells engraftment ability when they were co-transplanted with HIF-MSC compared to CD34+ co-transplanted with MSC WT (p = 0.016) or alone (p = 0.015) in both the injected and contralateral femurs (p = 0.024, p = 0.008 respectively).

Conclusions
Co-transplantation of human CD34+ cells with HIF-MSC enhances cell engraftment in vivo. This is probably due to the ability of HIF-MSC to increase clonogenic capacity of hematopoietic cells and to induce the expression of adhesion molecules involved in graft survival in the hematopoietic niche.
Splitting chemical structure data sets for federated privacy-preserving machine learning
Authors: Simm Jaak , Humbeck Lina , Zalewski Adam , Sturm Noe , Heyndrickx Wouter , Moreau Yves , Beck Bernd , Schuffenhauer Ansgar 
Published: December 2021

AbstractWith the increase in applications of machine learning methods in drug design and related fields, the challenge of designing sound test sets becomes more and more prominent. The goal of this challenge is to have a realistic split of chemical structures (compounds) between training, validation and test set such that the performance on the test set is meaningful to infer the performance in a prospective application. This challenge is by its own very interesting and relevant, but is even more complex in a federated machine learning approach where multiple partners jointly train a model under privacy-preserving conditions where chemical structures must not be shared between the different participating parties. In this work we discuss three methods which provide a splitting of a data set and are applicable in a federated privacy-preserving setting, namely: a. locality-sensitive hashing (LSH), b. sphere exclusion clustering, c. scaffold-based binning (scaffold network). For evaluation of these splitting methods we consider the following quality criteria (compared to random splitting): bias in prediction performance, classification label and data imbalance, similarity distance between the test and training set compounds. The main findings of the paper are a. both sphere exclusion clustering and scaffold-based binning result in high quality splitting of the data sets, b. in terms of compute costs sphere exclusion clustering is very expensive in the case of federated privacy-preserving setting.
Co-dimension two bifurcations analysis of a delayed tumor model with Allee effect
Authors: Dai Qinrui 
Published: December 2021

AbstractThe mathematical model has become an important means to study tumor treatment and has developed with the discovery of medical phenomena. In this paper, we establish a delayed tumor model, in which the Allee effect is considered. Different from the previous similar tumor models, this model is mainly studied from the point of view of stability and co-dimension two bifurcations, and some nontrivial phenomena and conclusions are obtained. By calculation, there are at most two positive equilibria in the system, and their stability is investigated. Based on these, we find that the system undergoes Bautin bifurcation, zero-Hopf bifurcation, and Hopf–Hopf bifurcation with time delay and tumor growth rate as bifurcation parameters. The interesting thing is that there is a Zero-Hopf bifurcation, which is not common in tumor models, making abundant dynamic phenomena appear in the system. By using the bifurcation theory of functional differential equations, we calculate the normal form of these Co-dimension two bifurcations. Finally, with the aid of MATLAB package DDE-BIFTOOL, some numerical simulations have been performed to support our theoretical results. In particular, we obtain the bifurcation diagram of the system in the two parameter plane and divide its regions according to the bifurcation curves. Meanwhile, the phenomena of multistability and periodic coexistence of some regions can be also demonstrated. Combined with the simulation results, we can know that when the tumor growth rate and the delay of immune cell apoptosis are small, the tumor may tend to be stable, and vice versa.
GR-mediated transcriptional regulation of m6A metabolic genes contributes to diet-induced fatty liver in hens
Authors: Feng Yue , Li Yanlin , Jiang Wenduo , Hu Yun , Jia Yimin , Zhao Ruqian 
Published: December 2021

Abstract
Background
Glucocorticoid receptor (GR) mediated corticosterone-induced fatty liver syndrome (FLS) in the chicken by transactivation of Fat mass and obesity associated gene (FTO), leading to demethylation of N6-methyladenosine (m6A) and post-transcriptional activation of lipogenic genes. Nutrition is considered the main cause of FLS in the modern poultry industry. Therefore, this study was aimed to investigate whether GR and m6A modification are involved in high-energy and low protein (HELP) diet-induced FLS in laying hens, and if true, what specific m6A sites of lipogenic genes are modified and how GR mediates m6A-dependent lipogenic gene activation in HELP diet-induced FLS in the chicken.

Results
Laying hens fed HELP diet exhibit excess (P < 0.05) lipid accumulation and lipogenic genes activation in the liver, which is associated with significantly increased (P < 0.05) GR expression that coincided with global m6A demethylation. Concurrently, the m6A demethylase FTO is upregulated (P < 0.05), whereas the m6A reader YTHDF2 is downregulated (P < 0.05) in the liver of FLS chickens. Further analysis identifies site-specific demethylation (P < 0.05) of m6A in the mRNA of lipogenic genes, including FASN, SREBP1 and SCD. Moreover, GR binding to the promoter of FTO gene is highly enriched (P < 0.05), while GR binding to the promoter of YTHDF2 gene is diminished (P < 0.05).

Conclusions
These results implicate a possible role of GR-mediated transcriptional regulation of m6A metabolic genes on m6A-depenent post-transcriptional activation of lipogenic genes and shed new light in the molecular mechanism of FLS etiology in the chicken.
Performance-efficient distributed transfer and transformation of big spatial histopathology datasets in the cloud
Authors: Yildirim Esma 
Published: December 2021

AbstractWhole Slide Image (WSI) datasets are giga-pixel resolution, unstructured histopathology datasets that consist of extremely big files (each can be as large as multiple GBs in compressed format). These datasets have utility in a wide range of diagnostic and investigative pathology applications. However, the datasets present unique challenges: The size of the files, propriety data formats, and lack of efficient parallel data access libraries limit the scalability of these applications. Commercial clouds provide dynamic, cost-effective, scalable infrastructure to process these datasets, however, we lack the tools and algorithms that will transfer/transform them onto the cloud seamlessly, providing faster speeds and scalable formats. In this study, we present novel algorithms that transfer these datasets onto the cloud while at the same time transforming them into symmetric scalable formats. Our algorithms use intelligent file size distribution, and pipelining transfer and transformation tasks without introducing extra overhead to the underlying system. The algorithms, tested in the Amazon Web Services (AWS) cloud, outperform the widely used transfer tools and algorithms, and also outperform our previous work. The data access to the transformed datasets provides better performance compared to the related work. The transformed symmetric datasets are fed into three different analytics applications: a distributed implementation of a content-based image retrieval (CBIR) application for prostate carcinoma datasets, a deep convolutional neural network application for classification of breast cancer datasets, and to show that the algorithms can work with any spatial dataset, a Canny Edge Detection application on satellite image datasets. Although different in nature, all of the applications can easily work with our new symmetric data format and performance results show near-linear speed-ups as the number of processors increases.
Dynamic order Markov model for categorical sequence clustering
Authors: Chen Rongbo , Sun Haojun , Chen Lifei , Zhang Jianfei , Wang Shengrui 
Published: December 2021

AbstractMarkov models are extensively used for categorical sequence clustering and classification due to their inherent ability to capture complex chronological dependencies hidden in sequential data. Existing Markov models are based on an implicit assumption that the probability of the next state depends on the preceding context/pattern which is consist of consecutive states. This restriction hampers the models since some patterns, disrupted by noise, may be not frequent enough in a consecutive form, but frequent in a sparse form, which can not make use of the information hidden in the sequential data. A sparse pattern corresponds to a pattern in which one or some of the state(s) between the first and last one in the pattern is/are replaced by wildcard(s) that can be matched by a subset of values in the state set. In this paper, we propose a new model that generalizes the conventional Markov approach making it capable of dealing with the sparse pattern and handling the length of the sparse patterns adaptively, i.e. allowing variable length pattern with variable wildcards. The model, named Dynamic order Markov model (DOMM), allows deriving a new similarity measure between a sequence and a set of sequences/cluster. DOMM builds a sparse pattern from sub-frequent patterns that contain significant statistical information veiled by the noise. To implement DOMM, we propose a sparse pattern detector (SPD) based on the probability suffix tree (PST) capable of discovering both sparse and consecutive patterns, and then we develop a divisive clustering algorithm, named DMSC, for Dynamic order Markov model for categorical sequence clustering. Experimental results on real-world datasets demonstrate the promising performance of the proposed model.