bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bronchopulmonary dysplasia in extremely premature infants: A scoping review for identifying risk factors
Authors: Ito Masato , Kato Shin , Saito Makoto , Miyahara Naoyuki , Arai Hirokazu , Namba Fumihiko , Ota Erika , Nakanishi Hidehiko 
Published: September 2022

Abstract
Background: With recent advances in respiratory support and improved survival rate of periviable infants, the etiology of bronchopulmonary dysplasia (BPD) might be changing over time. The aim of this scoping review was to screen available evidence regarding perinatal and neonatal risk factors associated with the development and severity of BPD for future revision of BPD classification.
Methods: The eligibility criteria of the studies were year of publication between 2016 and 2021; setting of a developed country; English or Japanese as study language; and randomized controlled, cohort, or case-control design. The titles and abstracts of the studies were screened by independent reviewers.
Results: Of 8,189 eligible studies, three were included for severe BPD and 26 were included for moderate BPD. The risk factors of severe BPD were male sex, iatrogenic preterm birth, maternal hypertensive disorders of pregnancy (HDP), low gestational age, small-for-gestational-age (SGA) birth weight, mechanical ventilation on day 1, and need for patent ductus arteriosus (PDA) management. The risk factors of moderate or severe BPD included male sex, premature rupture of membranes, chorioamnionitis, maternal HDP, SGA birth weight, bubbly/cystic appearance on X-ray, and PDA management.
Conclusion: We identified several risk factors for BPD that might predict respiratory outcomes earlier. We plan to confirm whether those factors could actually be predictors of BPD using the large cohort.
Machine Learning Soft Voting Algorithm for Prediction and Detection of Nonalcoholic Fatty Liver Disease
Authors: Cao Guoxin , Zhang Haomin 
Published: September 2022

Abstract
Nonalcoholic fatty liver disease (NAFLD) is one of the most commonly diagnosed chronic liver diseases in the world and has become an essential public health problem. Introduction of machine learning algorithms to evaluate the best predictive clinical model for NAFLD. In this paper, this study proposes a machine learning Voting algorithm with Genetic Algorithm, Neural Network, Random Forest, and Logistic Regression for NAFLD detection and diagnosis. First, 2,522 of the 10,508 samples met the diagnostic criteria for NAFLD. Visualizing the distribution of missing values, and KNN algorithm is used to fill the missing values. Doing Kolmogorov-Smirnov Z test and the heatmap of 19 variables. The PPFS feature selection method is used to perform the feature selection and the final 11 features are retained. Alanine aminotransferase (ALT), body mass index (BMI), triglycerides (TG), γ-glutamyl transpeptidase (γGT), and Low-density lipoprotein cholesterol (LDL) were the top 5 features contributing to NAFLD. 10 basic machine learning algorithms were used, and the four machine learning algorithms with the highest accuracy were Genetic Algorithm, Neural Network, Random Forest, and Logistic Regression. These four algorithms are fused into the proposed Voting algorithm through the Soft Voting method of Ensemble learning. 10-fold cross-validation was used in the classification. To verify the proposed Voting algorithm, it is compared with other 10 basic machine learning algorithms It achieved accuracy, recall, precision, \({F}_{1}\) score, AUC of up to 0.846212, 0.573248, 0.725806, 0.640569, 0.894010, respectively. According to the results, the proposed Voting algorithm demonstrated the best performance.
Differential antigen expression between human apocrine sweat glands and eccrine sweat glands
Authors: Cao Manxiu , Zhang Lei , Cheng Jiaqi , Wang Cangyu , Zhao Junhong , Liu Xiang , Yan Yongjing , Tang Yue , Chen Zixiu , Zhang Cuiping , Li Haihong 
Published: September 2022

Abstract
Bromhidrosis has a great negative impact on personal occupation and social psychology. It is not yet clear whether bromhidrosis is caused by apocrine sweat glands or the co-action of apocrine sweat glands and eccrine sweat glands. To distinguish between apocrine sweat glands and eccrine sweat glands, specific antigen markers for apocrine sweat glands and eccrine sweat glands must be found first. In the study, we detected the expression of K7, K18, K19, Na+-K+-2Cl− cotransporter 1 (NKCC1), carbonic anhydrase II (CAII), Forkhead transcription factor a1 (Foxa1), homeobox transcription factor engrailed homeobox1 (En1), gross cystic disease fluid protein-15 (GCDFP-15), mucin-1 (MUC-1), cluster of differentiation 15 (CD15) and apolipoprotein (APOD) in eccrine sweat glands and apocrine sweat glands by immunofluorescence staining. The results showed that K7, K18, K19, Foxa1, GCDFP-15 and MUC-1 were expressed in both apocrine and eccrine sweat glands, CD15 and APOD were only expressed in apocrine sweat glands, and CAII, NKCC1 and En1 were only expressed in eccrine sweat glands. We conclude that CD15 and APOD can serve as specific markers for apocrine sweat glands, while CAII, NKCC1 and En1 can serve as specific markers for eccrine sweat glands to differentiate the two sweat glands.
Offloading compiler to reduce pipeline dependencies through hardware interlocking by rebuilding MIPS
Authors: Khandelwal Rajat 
Published: September 2022

Abstract
MIPS is a family of reduced instruction set computer (RISC) ISAs, developed by Prof. John Hennessey at the Stanford University in the early 80s. The goal was to develop a simple processor with hardware equipped to perform traditional five stage pipelining making a large room for general purpose registers. MIPS has a processor along with a coprocessor designed for floating point arithmetic and logic.
However, MIPS uses software methods to avoid dependencies in its pipeline, hence the complete overload to generate NOPs in case of dependencies is done by the compiler.
RISC aims for a simple processor with pipelining, if possible, making compiler development complex and tricky. The logic to avoid dependencies in the pipeline adds an additional layer of complexity to the compiler which can be inherently avoided by switching to hardware to detect dependencies and act upon it accordingly. The paper aims to refine MIPS with hardware equipped to handle dependencies along with a comprehensive disquisition on its build.
CCDC103: A Novel Biomarker with Potential Prognostic in Glioma
Authors: Xu Haitao , Chen Xi , Niu Xiaoqun , Pu Jun 
Published: September 2022

Abstract
The coiled-coil domain-containing protein 103 (CCDC103), a predicted coiled-coil domain containing (CCDC) protein, whose role in tumors has never been reported. However, the diagnostic value and biological function of CCDC103 have not been elucidated in glioma. In this study, immunohistochemistry, qRT-PCR, GrowthCurve and migration experiments were used to explore the roles of CCDC103 on glioma biological function. Differential expression of CCDC103 at the mRNA level was evaluated using the Cancer Genome Atlas (TCGA), GEO and Chinese Glioma Genome Atlas (CGGA) databases. Correlations between CCDC103 expression and clinical outcomes of glioma were explored by TCGA and CGGA databases. GO, KEGG and GSEA were used to explore the molecular function of CCDC103. Different algorithms of immune infiltration were used to analyze the association between CCDC103 and immune infiltration. We found that CCDC103 was highly expressed in glioma tissues and cells, and knockdown of CCDC103 expression can significantly inhibit the growth and migration of glioma cells. In addition, CCDC103 was associated with immune infiltration in glioma and positively correlated with multiple immune checkpoint molecules. In summary, our study indicated that CCDC103 was highly expressed in glioma tissues and cell lines, and that patients with high expression of CCDC103 have a worse prognosis. In addition, knockdown of CCDC103 significantly inhibited the growth and migration of glioma cell lines. These results suggest that CCDC103 plays a crucial funtion in the development of glioma and may act as a new prognostic marker in glioma.
Manual acupuncture alleviates bladder dysfunction by up-regulating expression of NGF and its receptors in bladder tissue of diabetic neurogenic bladder rats
Authors: He Yujun , Lin Rui , Qin Ningjing , Fan Yushan , Zhang Hui , Miao Furui , Huang Jingwen 
Published: September 2022

Abstract
Objective
To investigate the effect of manual acupuncture on diabetic neurogenic bladder (DNB) rats through the protein and mRNA expression of nerve growth factor (NGF), tropomyosin receptor kinase A (TrkA), p75neurotrophinreceptor (p75NTR) in bladder tissue, as well as the levels of substance P (SP) and calcitonin gene-related peptides (CGRP).
Methods
A DNB rat model was induced using intraperitoneal injection of streptozotocin (STZ). The rats were randomly divided into a blank control group, a model group, and a manual acupuncture group (n = 10). For the manual acupuncture group, the manual acupuncture was applied after modeling. These groups were compared regarding body weight, fasting blood-glucose (FBG), and bladder wet weight. The histomorphology of muscle fibers were observed after hematoxylin and eosin (H&E) staining of bladder tissue sections. Protein and mRNA expression of NGF, TrkA and p75NTR in the bladder tissue were determined by Western blot and real-time PCR analysis, respectively. Levels of SP and CGRP in the bladder tissue were determined by ELISA.
Results
Compared to the blank control group, the model group and manual acupuncture group both showed higher FBG and lower body weight after STZ injection (P < 0.05). Compared to the blank control group, the model group and manual acupuncture group both showed higher bladder wet weight (P < 0.05). Histopathological evaluation indicated that manual acupuncture improved muscle fiber alignment disorders and detrusor cells compensatory hypertrophy in bladder tissue. The protein and mRNA expression of NGF, TrkA, p75NTR and the levels of SP and CGRP in bladder tissue of the manual acupuncture group were significantly higher than those of the model group (P < 0.01).
Conclusions
The therapeutic effect of manual acupuncture on bladder dysfunction in DNB may be mediated by up-regulating of the protein and mRNA expression of NGF, TrkA, p75NTR and the levels of SP and CGRP in bladder tissue.
EIF4A3-induced Circ_0001187 facilitates AML suppression through promoting ubiquitin-proteasomal degradation of METTL3 and decreasing m6A modification level mediated by miR-499a-5p/RNF113A pathway
Authors: Yang Xinyu , Han Fengjiao , Hu Xiang , Wu Hanyang , Can Can , Wei Yihong , Liu Jinting , Wang Ruiqing , Jia Wenbo , ji Chunyan , Ma Daoxin 
Published: September 2022

Abstract
Aberrant expression of circRNAs has been proven to play a crucial role in the progression of acute myeloid leukemia (AML), but its regulatory mechanism remains unclear. Herein, we identify a novel m6A modification-related circRNA, Circ_0001187, which is downregulated in AML patients, and its low level contributes to a poor prognosis. We find that the expression of Circ_0001187 is regulated by the modification of DNA methylation and histone acetylation, and its biogenesis is meditated by splicing factor EIF4A3. Knockdown of Circ_0001187 significantly promotes the proliferation and inhibits the apoptosis of AML cells in vitro and in vivo, while overexpression of Circ_0001187 exerts the opposite effects. Moreover, we prove that Circ_0001187 enhances METTL3 protein degradation, which further decreases mRNA m6A modification in AML cells. Mechanistically, Circ_0001187 sponges miR-499a-5p to enhance the expression RNF113A. And RNF113A functions as an E3 ubiquitin ligase to mediate METTL3 ubiquitin/proteasome-dependent degradation by K48-linked polyubiquitin chains. Collectively, our findings highlight the potential clinical implications of Circ_0001187 as a key tumor suppressor of AML via the miR-499a-5p/RNF113A/METTL3 pathway.
Potential Mechanism of Qinggong Shoutao Pill Alleviates Age-associated Memory Decline in D-Galactose-Injured Mice Based on Network Pharmacology, Molecular Docking, and Experimental Verification Integration Strategy
Authors: Pan Guiyun , Chai Lijuan , Chen Rui , Yuan Qing , Song Zhihui , Feng Wanying , Wei Jinna , Yang Zhihua , Zhang Yuhang , Xie Guinan , Yan An , Lv Qingbo , Wang Caijun , Zhao Yingqiang , Wang Yi 
Published: September 2022

Abstract

Background Qinggong Shoutao Pill (QGSTW) is extensively used as a traditional medicine to prevent and treat age-associated memory decline. However, its potential therapeutic mechanisms and targets are unclear. Methods Network pharmacology and molecular Docking approach was utilized to identified the main active components of QGSTW, the potential pathway and target of QGSTW effect on memory decline. Age-associated memory impairment of mouse model induced by D-galactose was established to verified the pathway and target of QGSTW effectiveness on memory decline, as shown by behavioral tests, immunofluorescence staining and western blot. Results By retrieving, 206 chemical components were identified in QGSTW. Based on these chemical components, network pharmacology demonstrated that the targets of active components were significantly enriched in the pathways in neuroactive ligand-receptor interaction, cAMP signaling pathway and calcium signaling pathway, which were closely related with signal transduction and chemical synaptic transmission. The interrelationships between common targets were analyzed by PPI network and ten biomarkers were discovered. Ten QGSTW active components were revealed furtherly. The affinity between the top five targets and their corresponding active ingredients was predicted by molecular docking. Finally, experiments showed that QGSTW could upregulate the expression of cAMP signaling pathway related targets PKA, CREB, and synaptic plasticity related proteins GluN1, GluA1, CaMKⅡ-α, c-Fos and SYN, contributing to the recovery of memory decline in D-galactose-injured mice. Conclusions This paper revealed the key nodes of QGSTW effect on anti-memory decline are cAMP signaling pathway and synaptic plasticity.
A Framework for Optimizing Ensemble Learning for Offensive Tweet Identification
Authors: Mullah Nanlir Sallau , Zainon Wan Mohd Nazmee Wan , Wahab Mohd Nadhir Ab 
Published: September 2022

Abstract
Online derogatory comments are ubiquitous on social media and areraising serious concerns across the globe. Social media data is riddenwith high dimensional search space due to noise, redundant features,and non-standardized writing style. These problems lead to high computationalcosts, longer training time, and low predictive accuracy inmachine learning models. The researchers proposed a framework for optimizingstacked generalized ensemble learning to address these problemsand enhance model performance. The main components of the frameworkinclude feature optimizer (FO), ensemble classifiers, and stratifiedK-foldCV (skfCV) through stacked generalization ensemble architecture.The ensemble classifiers, FO, and skfCV components make our methodstable and computationally efficient with the best performance. Theproposed method was validated using three benchmark datasets. The proposed method outperformed the state-of-the-art results in all theevaluation metrics used in those three articles adopted for comparison.
Patient and Family Experiences of Lysosomal Storage Diseases: A Qualitative Interview Study
Authors: Awada Nahya , Holcik Martin 
Published: September 2022

Abstract
Background
Patients and families affected by rare genetic lysosomal storage diseases (LSDs) suffer from a variety of challenges related to disease management, including issues navigating healthcare and social support services, access to orphan drugs, and intensive treatment regimens. All of these challenges significantly impact people’s quality of life, yet they remain obscure and have not been the subject of comprehensive analysis. Thus, we conducted qualitative interviews with Canadian patients living with LSDs and their families to enrich and advance current understanding of their experiences with rare-disease management and health systems navigation in order to support patient-focused rare disease policies and programs and improve health outcomes of the 2.8 million Canadians affected by rare diseases.
Methods
This study employed a qualitative research design with inductive thematic content analysis. The data for this study was collected using semi-structured interviews. Thirty Canadian participants were interviewed in person or remotely via video chat service to allow for an interactive discussion and the acquisition of rich, comprehensive data relating to the insights and perceptions of people living with LSDs.
Results
Between April and November 2018, 30 participants (16 patients and 14 parents of children with LSDs) with experiences of nine different types of LSDs and living in seven Canadian provinces were interviewed.
Five themes were identified and categorized using comprehensive thematic analysis for each interview. These themes were the complexity of the diagnosis process; navigation of healthcare systems; the psychological, social, and financial implications of LSDs; access to social support services; and access to orphan drugs.
Conclusion
With regards to participants’ experiences with patient care, the study results highlight the importance of establishing a rare-disease strategy and bridging the gaps that currently exist between health and social care for patients with rare conditions. These findings reveal that the process of accessing orphan drugs is extremely complex and convoluted, and patients’ access to appropriate healthcare and social services are subject to significant delays. In addition, the study’s findings illuminate a lack of coordination between all aspects of rare-disease care, including medical and social support services. Policymakers should utilize these results when developing future policies and programs to employ a holistic approach to rare-disease patient care.
Modulation of gut microbiota and anti-inflammatory effect of a probiotic cocktail in an inflammatory bowel disease-induced mouse model by fecal transplantation
Authors: Salimi Afsaneh , Sepehr Amin , Hejazifar Niloofar , Talebi Maliheh , Rohani Mahdi , Pourshafie Mohammad Reza 
Published: September 2022

Abstract
Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gastrointestinal tract due to altered interaction between the immune system and the gut microbiota. The aim of this study was to investigate the role of a probiotic cocktail in modulating immune dysregulation induced in mice. Mice were divided into five groups (n = 5/group) and inflammation was induced by fecal microbiota transplantation (FMT) from the stool of human with IBD and dextran sulfate sodium (DSS). The cocktail of Lactobacillus spp. and Bifidobacterium spp. (10⁸CFU/kg/day) was administered daily for a total of 28 days. The alteration of the gut microbiota and the expression of some genes involved in the regulation of the inflammatory response were studied in the probiotic-treated and untreated groups by quantitative real-time PCR. The gut microbiota of the FMT and DSS groups showed similar patterns on day 28 after each treatment. In the probiotic-treated groups, the population of the gut microbiota normalized and, in contrast to the DSS and FMT groups, the abundance of phyla Firmicutes and Actinobacteria increased. The expression of genes related to immune response and tight junctions was positively affected by the probiotic. Changes in the gut microbiota could influence the inflammatory status in the gut, and probiotics as a preventive or complementary treatment could improve the well-being of patients with inflammatory bowel disease symptoms.
Prenatal predictors of mortality in fetuses with congenital diaphragmatic hernia: a systematic review and meta-analysis
Authors: Masahata Kazunori , Yamoto Masaya , Umeda Satoshi , Nagata Kouji , Terui Keita , Fujii Makoto , Shiraishi Masayuki , Hayakawa Masahiro , Amari Shoichiro , Masumoto Kouji , Okazaki Tadaharu , Inamura Noboru , Toyoshima Katsuaki , Koike Yuki , Furukawa Taizo , Yazaki Yuta , Yokoi Akiko , Endo Masayuki , Tazuke Yuko , Okuyama Hiroomi , Usui Noriaki 
Published: September 2022

Abstract
Purpose
This study aimed to evaluate prenatal predictors of mortality in fetuses with congenital diaphragmatic hernia (CDH).
Methods
A systematic literature search was performed to identify relevant observational studies that evaluated the ability of lung-to-head ratio (LHR), observed-to-expected LHR (o/e-LHR), observed-to-expected total fetal lung volume (o/e-TFLV), lung-to-thorax transverse area ratio (L/T ratio), intrathoracic herniation of the liver and the stomach, and side of diaphragmatic hernia, using a threshold for the prediction of mortality in fetuses with CDH. Study quality was assessed using the QUADAS-2 tool. Hierarchical summary receiver operating characteristic curves were constructed.
Results
A total of 50 articles were included in this meta-analysis. The QUADAS-2 tool identified a high risk of bias in more than one domain scored in all parameters. Among those parameters, the diagnostic odds ratio of mortality with o/e-LHR < 25%, o/e-TFLV < 25%, and L/T ratio < 0.08 were 11.98 (95% confidence interval (CI), 4.65–30.89), 11.14 (95%CI, 5.19–23.89), and 10.28 (95%CI, 3.38–31.31), respectively. The predictive values for mortality were similar between the presence of liver herniation and retrocardiac fetal stomach position.
Conclusions
This systematic review suggests that o/e-LHR, o/e-TFLV, and L/T ratio are equally good predictors of neonatal mortality in fetuses with isolated CDH.
Impact of pretransplant donor-specific anti-HLA antibodies in HLA-mismatched peripheral blood stem cell transplantation
Authors: Hagino Takeshi , Ikegame Kazuhiro , Tanaka Hidenori , Kanda Yoshinobu , Kaida Katsuji , Fukuda Takahiro , Kondo Yukio , Sato Maho , Doki Noriko , Nakamae Hirohisa , Matsuoka Ken-ichi , Mori Yasuo , Sano Hideki , Eto Tetsuya , Kawakita Toshiro , Hashii Yoshiko , Ichinohe Tatsuo , Atsuta Yoshiko , Kanda Junya 
Published: September 2022

Abstract
The cut-off levels of donor-specific anti-HLA antibodies (DSAs) that are considered to predict a high risk of graft failure remain unclear. Using peripheral blood stem cell transplantation (PBSCT) data from the Japanese Society for Transplantation and Cellular Therapy/Japanese Data Center for Hematopoietic Cell Transplantation (JSTCT/JDCHCT), we examined the role of DSAs, and performed a retrospective analysis of patients whose recipients underwent related PBSCT between 2010 and 2014 with pre-transplant anti-HLA antibodies. Patients were divided into 3 groups using a mean fluorescence intensity (MFI) of 5,000 as a cut-off value: DSA positive (n = 8), anti-HLA antibody-positive (n = 137) and anti-HLA antibody-negative (n = 3657). There was a significant difference in the number of CD34-positive cells (median: 4.31, 3.97, and 5.33×106/kg, respectively; p < 0.05). Regarding the eight DSA-positive patients, only two underwent therapeutic intervention, and neutrophils were engrafted in all but one patient (median, 10 days). Although there was a statistically significant difference in neutrophil and platelet engraftment among the 3 groups (both p < 0.05), neutrophil engraftment was faster in the DSA group, with no significant difference in the overall survival (p = 0.46). Our results, based on JSTCT/JDCHCT data, suggest that DSAs may not affect the risk in related PBSCT.