bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementasi 3 B dalam Manajemen Pondok Pendawa di Parung
Authors: Sukataman Sukataman , Khotimah Khusnul 
Published: January 2025

Pondok pesantren merupakan lembaga pendidikan non formal yang mengajarkan kepada santri ilmu agama. Pondok pesantren yang dahulu dikenal sebagai lembaga pendidikan yang hanya mengajarkan agama sekarang sudah berafiliasi dan mulai mengajarkan ilmu terkait dengan life skill. Pembekalan dan pengajaran life skill diharapkan mampu memberikan bekal kehidupan santri dan siap membangun kemandirian. Pondok Pendawa termasuk salah satu pondok yang menerapkan manajemen penggabungan pembelajaran aspek ilmu dan life skill. Pondok pendawa menuntut santri tidak hanya pandai dalam ilmu agama, ibadah, umum, tapi juga cakap dalam life skill. Hemat kalimat semua kecapakan tersebut terangkum dalam 3 B. Penelitian ini menjadi penelitian yang penting, karena bisa menjadi salah satu alternatif rujukan pondok pesantren mahasiswa dalam pengelolaannya. Metode penelitian yang digunakan penelitia yaitu metode penelitian kualitatif. Penggalian data dilakukan melalui wawancara, observasi dan dokumentasi. Data yang sudah diperoleh diolah dan disajikan dalam bentuk deskriptif. Hasil penelitian menjelaskan bahwa manajemen 3 B (Beribadah, Belajar dan Bekerja) sangat membekas dalam diri santri. Beberapa alumni mempunyai jiwa entrepreneur yang siap membangun usahanya sendiri seperti menjahit, budidaya sayur hidropoinik, jasa penyewaan tempat.
Optimization of erythritol production through fermentation using molasses as carbon source
Authors: Kembaren Riahna , Parikesit Arli Aditya , Nataniel Jocelyn , Dharmawan Nethania Angeline , Dungus Charlivo Mikaichi , Angelique Priscilla , Aslanzadeh Solmaz 
Published: January 2025

Erythritol is a beneficial sugar alcohol that can be used as a sugar substitute for diabetic patients. Erythritol is a bioproduct produced by microorganisms as a response to high osmotic pressure and stress in the growth medium. High concentrations of carbon source substrate can increase the osmotic pressure and provide more nutrient supply for yeast growth and metabolism. Aside from that, an optimal carbon-to-nitrogen (C/N) ratio can also make the erythritol conversion pathway more favorable. Therefore, this research aims to determine the optimal concentrations of molasses as the carbon source, yeast extract as the nitrogen source, and the optimal carbon-to-nitrogen (C/N) ratio to achieve the highest erythritol productivity. The research also seeks to optimize NaCl concentrations and pH while comparing batch and fed-batch fermentation systems to determine which produces a higher erythritol yield. One-Factor-at-A-Time (OFAT) method was used to identify optimal production conditions. The study found that the highest erythritol concentration, 17.48 ± 0.86 g/L, was achieved using 200 g/L of molasses, 7 g/L of yeast extract (200/7), and 25 g/L of NaCl, with a yield mass of 0.262 ± 0.00 g/g and a volumetric productivity of 0.095 ± 0.021 g/Lh. The pH optimization revealed that the best erythritol production occurred within a pH of 5. Furthermore, fed-batch fermentation significantly increased erythritol concentration to 26.52 ± 1.61 g/L, with a yield mass of 0.501 ± 0.032 g/g and a volumetric productivity of 0.158 ± 0.01 g/Lh. These findings emphasize the importance of optimizing carbon source, nitrogen source and NaCl concentration, pH, and fermentation systems, particularly highlighting the benefits of fed-batch fermentation in maximizing erythritol production. These findings provide a solid foundation for improving erythritol yields for industrial applications.
CLIL on the spot: migrant education in Greece
Authors: Mattheoudakis Marina , Fotiadou Georgia , Papadopoulou Despina 
Published: January 2025

IntroductionThis study aims to explore the instructional strategies employed by Greek teachers in primary and secondary school classes attended by large numbers of refugee and migrant students. As there is not a clear methodological ‘blueprint’ for CLIL that teachers are required to follow, our study will investigate which of the principles framed for the CLIL approach are in fact applied by educators.MethodsTo this aim, we adopted a survey-based research methodology (web-based questionnaire) and a phenomenological approach (semi-structured interviews).ResultsResults include data from 125 respondents of the questionnaire, working in 21 different regional units of Greece, and the lived experiences of five educators. Most of the participants had no prior training in bilingual or intercultural education but were highly qualified (holders of at least an MA). Thus, although educational background was not identified as a predictive factor to the teaching strategies, training in topics such as bilingual education and interculturality was. Scaffolding techniques were significantly affected by teachers’ age, training and educational setting (primary vs. secondary). Moreover, the variety of activities offered differed between the two levels of school settings as educators chose strategies they deemed appropriate for the cognitive and proficiency level of their students.DiscussionOverall, our findings suggest that, although educators of Greek state schools lack specific training in managing plurilingual and pluricultural classes, they experiment with a variety of CLIL practices and that those who have had some relevant trainings are more prompt to support their students with multiple scaffolding techniques than those who have had no such prior experience.
Analytical validation of a novel bioassay for thyroid-stimulating immunoglobulin
Authors: Olivo Paul D. , Kim Hannah , Miao Lynn , Houtz Jeffery A. , Kahaly George J. 
Published: January 2025

BackgroundA novel and rapid cell-based bioassay, Turbo TSI, for measurement of thyroid-stimulating immunoglobulins (TSI) was recently reported. An assessment of the analytical performance of this TSI bioassay is described herein.MethodsThawed cells from Turbo TSI kits were treated with different concentrations of a World Health Organization (WHO) international standard (IS) TSI-positive serum. TSI was measured as a function of luciferase activity measured as relative light units (RLU) and converted into international units per liter (IU/L). Analytical performance studies were performed on numerous samples, over multiple days, by two users at two sites.ResultsThe limit of blank, limit of detection and limit of quantitation were determined to be 0.007 IU/L, 0.014 IU/L, and 0.021 IU/L, respectively. Receiver operator characteristics (ROC) analysis determined the cut-off to be 0.0241 IU/L with an area under the curve of 0.984. The linear range was shown to be from 0.015 to 11.958 IU/L. The intra-laboratory precision was ≤15%CV. The overall reproducibility of the assay was ≤20%CV for five concentrations (0.06 to 5.16 IU/L). Interference and cross reactivity studies with a variety of substances showed that the assay was robust. The Turbo TSI bioassay demonstrated 95.2% (95% CI 83.3-98.1) positive percent agreement and 94.8% (95% CI 90.9-97.1) negative percent agreement with an FDA-cleared bioassay (Thyretain® TSI) using serum from 295 patients with autoimmune thyroid disease.ConclusionsThe Turbo TSI bioassay exhibits excellent analytical performance and a high level of reproducibility. The performance compared well with Thyretain® TSI, an FDA-cleared TSI bioassay.
Targeting immune cellular populations and transcription factors: unraveling the therapeutic potential of JQF for NAFLD
Authors: Zhou Lijuan , Zhao Jingyi , Ma Kaile , Hao Rui , Yao Chensi , Gou Xiaowen , Tian Chuanxi , Wan Li , Li Min , Tong Xiaolin 
Published: January 2025

BackgroundNon-alcoholic fatty liver disease (NAFLD) constitutes the most prevalent chronic liver disease worldwide. Progression to non-alcoholic steatohepatitis (NASH), the immune cell reservoir within the liver undergoes remodeling, exacerbating liver inflammation and potentially leading to liver fibrosis. Jiangtang Qingre Formula (JQF) is an effective prescription for the clinical treatment of NAFLD. However, its underlying mechanism of action remains unclear.MethodsUsing a high-fat diet-induced NAFLD mouse model, we evaluated JQF’s effects with biochemical tests and histopathology. Single-cell RNA sequencing and spatial transcriptomics furthered our understanding of NAFLD pathophysiology and JQF’s treatment mechanisms.ResultsOur findings initially revealed significant improvements in JQF on hepatic steatosis, inflammation, fibrosis and glucose tolerance in NAFLD mice. Furthermore, significant changes were observed in the immune cells including monocytes, macrophages, and T cells in the livers of NAFLD mice. Notably, regions infiltrated by T cells presented the most severe liver inflammation and fibrosis. Importantly, JQF effectively modulated these immune cells. Advanced subcluster and cell communication analyses identified key macrophage (KCs, MoMFs) and T cell (Tc, Th2) subpopulations in JQF’s therapeutic actions. Further SCENIC analysis additionally uncovered the essential transcription factors that regulate these cell subclusters, such as Stat2, Mta3, Eomes, and Etv5.ConclusionOverall, our research suggests a promising potential therapeutic agent and identifies critical cell populations and transcription factors that contribute to its therapeutic effects, thereby revealing potential therapeutic targets for NAFLD.
An allelic atlas of immunoglobulin heavy chain variable regions reveals antibody binding epitope preference resilient to SARS-CoV-2 mutation escape
Authors: Deng Weiqi , Niu Xuefeng , He Ping , Yan Qihong , Liang Huan , Wang Yongping , Ning Lishan , Lin Zihan , Zhang Yudi , Zhao Xinwei , Feng Liqiang , Qu Linbing , Chen Ling 
Published: January 2025

BackgroundAlthough immunoglobulin (Ig) alleles play a pivotal role in the antibody response to pathogens, research to understand their role in the humoral immune response is still limited.MethodsWe retrieved the germline sequences for the IGHV from the IMGT database to illustrate the amino acid polymorphism present within germline sequences of IGHV genes. We aassembled the sequences of IgM and IgD repertoire from 130 people to investigate the genetic variations in the population. A dataset comprising 10,643 SARS-CoV-2 spike-specific antibodies, obtained from COV-AbDab, was compiled to assess the impact of SARS-CoV-2 infection on allelic gene utilization. Binding affinity and neutralizing activity were determined using bio-layer interferometry and pseudovirus neutralization assays. Primary docking was performed using ZDOCK (3.0.2) to generate the initial conformation of the antigen-antibody complex, followed by simulations of the complete conformations using Rosetta SnugDock software. The original and simulated structural conformations were visualized and presented using ChimeraX (v1.5).ResultsWe present an allelic atlas of immunoglobulin heavy chain (IgH) variable regions, illustrating the diversity of allelic variants across 33 IGHV family germline sequences by sequencing the IgH repertoire of in the population. Our comprehensive analysis of SARS-CoV-2 spike-specific antibodies revealed the preferential use of specific Ig alleles among these antibodies. We observed an association between Ig alleles and antibody binding epitopes. Different allelic genotypes binding to the same RBD epitope on the spike show different neutralizing potency and breadth. We found that antibodies carrying the IGHV1-69*02 allele tended to bind to the RBD E2.2 epitope. The antibodies carrying G50 and L55 amino acid residues exhibit potential enhancements in binding affinity and neutralizing potency to SARS-CoV-2 variants containing the L452R mutation on RBD, whereas R50 and F55 amino acid residues tend to have reduced binding affinity and neutralizing potency. IGHV2-5*02 antibodies using the D56 allele bind to the RBD D2 epitope with greater binding and neutralizing potency due to the interaction between D56 on HCDR2 and K444 on RBD of most Omicron subvariants. In contrast, IGHV2-5*01 antibodies using the N56 allele show increased binding resistance to the K444T mutation on RBD.DiscussionThis study provides valuable insights into humoral immune responses from the perspective of Ig alleles and population genetics. These findings underscore the importance of Ig alleles in vaccine design and therapeutic antibody development.
Circulating levels of adiponectin and AdipoR expression in peripheral blood mononuclear cells are associated with lower respiratory tract Infection
Authors: Wang Qian , Wang Xuemei , Xu Danning , Jiang Mengjie , Gao Yidan , Jiang Lijuan , Liu Meilian , Tang Haoneng , Tang Lingli 
Published: January 2025

ObjectiveThe role of adiponectin (APN) in regulating inflammation is well recognized in metabolic disease, but the dysregulation of APN in lower respiratory tract infection (LRTI) remains controversial. We aimed to measure APN and its signaling receptors, adiponectin receptor (AdipoR), in peripheral blood mononuclear cells (PBMCs) from LRTI patients to explore their potential roles in the LRTI process.MethodsA total of 99 LRTI patients from the Second Xiangya Hospital of Central South University were categorized into acute (n=35) and non-acute (n=64), and non-severe (n=62) and severe (n=37) groups. Serum APN was quantified using ELISA, and mRNA levels of PBMC AdipoRs were determined by RT-qPCR.ResultsBoth levels of APN in circulation and AdipoR1 mRNA were significantly elevated in the LRTI patients (P=2.61E-04; P=2.49E-08), while no statistical difference was observed for AdipoR2. APN levels were increased in the non-acute group compared to the acute group (P=6.06E-04) and AdipoR1 levels were higher in the severe group (P=0.004). Increased APN and AdipoR1 mRNA levels were positively associated with LRTI even after adjustment for sex, age, BMI and blood lipids (OR=1.10; 95% CI 1.04-1.18; P=9.61E-04; OR=2.69; 95% CI 1.29-5.58; P=0.008). Subgroup analyses based on sex, age, and BMI revealed APN elevation in males, ≥65-year-olds, and overweight individuals, with higher AdipoR2 mRNA in females and those under 65; AdipoR1 was uniformly elevated. Additionally, APN was negatively correlated with lymphocyte count in acute and severe subgroup; AdipoR1 was positively correlated with indicators of inflammation in LRTI group.ConclusionOur study highlights that serum APN and AdipoR1 mRNA in PBMCs are associated with LRTI. Circulating APN and PBMC AdipoR1 have different significances in LRTI acute onset and severity.
Deep learning captures the effect of epistasis in multifactorial diseases
Authors: Perelygin Vladislav , Kamelin Alexey , Syzrantsev Nikita , Shaheen Layal , Kim Anna , Plotnikov Nikolay , Ilinskaya Anna , Ilinsky Valery , Rakitko Alexander , Poptsova Maria 
Published: January 2025

BackgroundPolygenic risk score (PRS) prediction is widely used to assess the risk of diagnosis and progression of many diseases. Routinely, the weights of individual SNPs are estimated by the linear regression model that assumes independent and linear contribution of each SNP to the phenotype. However, for complex multifactorial diseases such as Alzheimer’s disease, diabetes, cardiovascular disease, cancer, and others, association between individual SNPs and disease could be non-linear due to epistatic interactions. The aim of the presented study is to explore the power of non-linear machine learning algorithms and deep learning models to predict the risk of multifactorial diseases with epistasis.MethodsSimulated data with 2- and 3-loci interactions and tested three different models of epistasis: additive, multiplicative and threshold, were generated using the GAMETES. Penetrance tables were generated using PyTOXO package. For machine learning methods we used multilayer perceptron (MLP), convolutional neural network (CNN) and recurrent neural network (RNN), Lasso regression, random forest and gradient boosting models. Performance of machine learning models were assessed using accuracy, AUC-ROC, AUC-PR, recall, precision, and F1 score.ResultsFirst, we tested ensemble tree methods and deep learning neural networks against LASSO linear regression model on simulated data with different types and strength of epistasis. The results showed that with the increase of strength of epistasis effect, non-linear models significantly outperform linear. Then the higher performance of non-linear models over linear was confirmed on real genetic data for multifactorial phenotypes such as obesity, type 1 diabetes, and psoriasis. From non-linear models, gradient boosting appeared to be the best model in obesity and psoriasis while deep learning methods significantly outperform linear approaches in type 1 diabetes.ConclusionOverall, our study underscores the efficacy of non-linear models and deep learning approaches in more accurately accounting for the effects of epistasis in simulations with specific configurations and in the context of certain diseases.
A study on the variability and correlation of ocular biological measurement parameters in adult myopic patients
Authors: Zhou Fangxing , Chen Nan , Qian Hui , Gong Di , Li Kunke 
Published: January 2025

ObjectiveThis study aims to explore the differences in ocular parameters among adult myopic patients with different degrees of myopia and axial lengths, and to investigate the correlations between these ocular parameters.MethodsThis single-center observational study collected clinical data from myopic patients aged 18–45 years who visited the Eye Hospital of Nanjing Medical University between January and June 2023. The data included laterality, diopter of spherical power (DS), diopter of cylindrical power (DC), spherical equivalent (SE), axial length (AL), central corneal thickness (CCT), flat meridian keratometry (K1), steep meridian keratometry (K2), mean keratometry (Km), anterior chamber depth (ACD), corneal radius of curvature (CRC), and axial length/corneal radius of curvature ratio (AL/CRC). Following predefined inclusion and exclusion criteria, 1,026 eyes were included in the study. Patients were grouped based on SE and AL parameters into different degrees of myopia. Analysis of variance (ANOVA) and Welch ANOVA were used to compare intergroup differences. Spearman correlation coefficients were calculated to analyze the correlations between parameters, and linear regression and ROC curve analyses were performed.ResultsSignificant differences (p &lt; 0.05) were found among mild, moderate, and high myopia groups in parameters such as DS, DC, AL, K1, Km, ACD, CRC, and AL/CRC. Significant differences (p &lt; 0.05) were also found in DS, DC, SE, CCT, K1, K2, Km, ACD, CRC, and AL/CRC among different axial length groups. Spearman correlation analysis showed a strong correlation between AL and DS, SE, and between AL/CRC and DS, SE, AL. Linear regression analysis revealed that the coefficient of determination (R2) for AL and SE was 0.699, and for AL/CRC and SE, it was 0.861. ROC curve analysis demonstrated high accuracy for both AL and AL/CRC in identifying high myopia, with an AUC of 0.952 for AL/CRC, which was superior to the AUC of 0.905 for AL (p &lt; 0.05).ConclusionThis study found significant differences in ocular parameters among patients with different degrees of myopia and axial lengths. There was a significant negative correlation between AL, AL/CRC, and SE. Compared to AL, AL/CRC had a stronger correlation with SE and higher accuracy in identifying high myopia.
Exploring the shared gene signatures and mechanism among three autoimmune diseases by bulk RNA sequencing integrated with single-cell RNA sequencing analysis
Authors: Liu Xiaofang , Li Bin , Lin Yuxi , Ma Xueying , Liu Yingying , Ma Lili , Ma Xiaomeng , Wang Xia , Li Nanjing , Liu Xiaoyun , Chen Xiaohong 
Published: January 2025

BackgroundEmerging evidence underscores the comorbidity mechanisms among autoimmune diseases (AIDs), with innovative technologies such as single-cell RNA sequencing (scRNA-seq) significantly advancing the explorations in this field. This study aimed to investigate the shared genes among three AIDs—Multiple Sclerosis (MS), Systemic Lupus Erythematosus (SLE), and Rheumatoid Arthritis (RA) using bioinformatics databases, and to identify potential biomarkers for early diagnosis.MethodsWe retrieved transcriptomic data of MS, SLE, and RA patients from public databases. Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to construct gene co-expression networks and identify disease-associated modules. Functional enrichment analyses and Protein-Protein Interaction (PPI) network was constructed. We used machine learning algorithms to select candidate biomarkers and evaluate their diagnostic value. The Cibersort algorithm was and scRNA-seq analysis was performed to identify key gene expression patterns and assess the infiltration of immune cells in MS patients. Finally, the biomarkers’ expression was validated in human and mice experiments.ResultsSeveral shared genes among MS, SLE, and RA were identified, which play crucial roles in immune responses and inflammation regulation. PPI network analysis highlighted key hub genes, some of which were selected as candidate biomarkers through machine learning algorithms. Receiver Operating Characteristic (ROC) curve analysis indicated that some genes had high diagnostic value (Area Under the Curve, AUC &gt;0.7). Immune cell infiltration pattern analysis showed significant differences in the expression of various immune cells in MS patients. scRNA-seq analysis revealed clusters of genes that were significantly upregulated in the single cells of cerebrospinal fluid in MS patients. The expression of shared genes was validated in the EAE mose model. Validation using clinical samples confirmed the expression of potential diagnostic biomarkers.ConclusionThis study identified shared genes among MS, SLE, and RA and proposed potential early diagnostic biomarkers. These genes are pivotal in regulating immune responses, providing new targets and theoretical basis for the early diagnosis and treatment of autoimmune diseases.
Relationship between BDNF content in cord blood and early neurobehavior in newborns with subclinical hypothyroidism during pregnancy: a preliminary study
Authors: Xu Hui , Du Ya-Nan , Yang Shuai , Guo Yu-Wen 
Published: January 2025

ObjectivesResearch on neurobehavioral abnormalities in neonates of mothers with subclinical hypothyroidism (SCH) is limited. The link between umbilical cord blood brain-derived neurotrophic factor (BDNF) levels and neurobehavioral outcomes in neonates has not been explored. This study investigates the correlation between alterations in umbilical cord blood BDNF levels and early neurobehavioral abnormalities in neonates born to pregnant women with SCH.MethodsThis study recruited 72 pregnant women with SCH and 76 healthy controls (HC). The study collected general information for all subjects, including body mass index, parity, thyroid function assessed during early to late pregnancy, and neonatal birth weight. Neonatal behavioral and neural abilities were evaluated using the Neonatal Behavioral Neurological Assessment (NBNA). BDNF levels in umbilical cord blood were measured using the Enzyme-Linked Immunosorbent Assay method.ResultsThe results indicated that neonates with SCH during pregnancy had lower total NBNA scores, behavioral ability, passive muscle tone, active muscle tone, primitive reflexes, general assessment, and lower levels of cord blood BDNF compared to healthy controls. The cord blood BDNF of newborns with SCH during pregnancy was positively correlated with total NBNA score, behavioral ability, active muscle tone, and general assessment. Moreover, multiple linear regression analysis demonstrated an association between cord blood BDNF levels in pregnant patients with SCH and multiple measures of newborn health, including total NBNA score, behavioral ability, active muscle tone, and general assessment.ConclusionInfants born to pregnant women with SCH exhibit reduced behavioral and neural abilities linked to BDNF levels in umbilical cord blood.