bluuebunny/crossref_metadata_2025_split huggingface dataset:
COMMEMORATIVE PRACTICES AS A FORM OF MENTORING TO PRESERVE THE MEMORY OF THE PAST OF THE FAMILY AND KIN COMMUNITY
Authors: Busyreva Elena V. 
Published: October 2024

The article is devoted to commemorative practices as a form of mentoring. The role of heritage is played by family archives and relics, which contribute to the formation and preservation of family memory and knowledge about the kin community. Families may collect their archives spontaneously, under the influence of social, everyday and individual psychological needs. In the case of mentoring, learning how to preserve information about family history and specific individuals is done purposefully. The study is based on the author’s fieldwork in 2009 — 2023 among the families of Baltic-Finnish and German ancestry (mainly multiethnic) living in the Murmansk region. Most of these families suffered from the Stalinist repressions, since the Finns and Germans were considered “unreliable”. The need for commemorative activities arose because for many decades it was taboo in families to mention the “undesirable” social or ethnic origin. As a result, many facts about the past of the kin and about individual members of such families have been lost. The problem is that some descendants do not realize the need to reconstruct the family history. The purpose of the study is to record and show the process and results of families’ efforts to preserve their memory and to find out whether this experience and its value are transmitted within family groups. The study used oral history methods and the comparative historical method to analyze the data obtained. The article provides examples of mentoring, expressed in the involvement of family members in creating an archive, compiling family trees, collecting photographic material, preserving relics and family traditions. The results show that the preservation and transmission of family memory largely depends on the cultural level of the family and, above all, on representatives of the older generation who act as mentors.
THE CRANIAL DIVERSITY OF THE MODERN POPULATION OF EASTERN EUROPE
Authors: Pestriakov Aleksandr P.  , Grigorieva Olga M. , Rashkovskaya (Pelenitsyna) Yulia V.  , Fedorchuk Olga A.  
Published: October 2024

This paper continues the extensive study of cranial samples representing modern populations worldwide. 11 traits were selected to study neurocranial shape and size. All data come from published sources and cover 6 ethnoterritorial groups: 1) Slavic (mostly Russian) samples from the East European Plain, 2) non-Slavic (mostly Finnish-speaking) samples from the same area, 3) samples from the three Baltic states (Estonia, Latvia, Lithuania), 4) Bashkir samples from the Southern Urals, 5) samples representing the indigenous population of the North Caucasus, 6) samples from Transcaucasia. Cranial analysis has assigned all these samples to several different variants of the same panecumenic craniotype called Holarctides. The Slavic and non-Slavic samples from the East European Plain proved to be particularly close in size and cranial shape. There are two epochal processes in the Holarctid craniotype: a gradual decrease in the overall size of the skull and an increase in its spherification. This is most active in places where there are rapid social processes of mixing of different ethnic groups, which always accompany the formation of state structures. The North Caucasian skull sample differs little from the Slavic and non-Slavic samples of the Eastern European Plain in the shape of the skull, but is significantly larger in size. Bashkir cranial samples have the lowest cranial vault.
The association of plasma asprosin with anthropometric and metabolic parameters in Korean children and adolescents
Authors: Kim Shin-Hee , Kim Sung Eun , Chun Yoon Hong 
Published: October 2024

BackgroundThis study aimed to determine the correlation of plasma asprosin with anthropometric and metabolic parameters in Korean children and adolescents.MethodsThis single-center study included 109 Korean children and adolescents: 62 (56.9%) obese participants with a body mass index (BMI) ≥95th percentile and 47 (43.1%) healthy controls with BMI between the 15th and 85th percentile. Metabolic parameters were measured, including fasting blood glucose, fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), triglyceride and glucose (TyG) index, and lipid profiles.ResultsPlasma asprosin levels were higher in the obese group than in the control group (mean 87.0 vs. 69.3 ng/mL; p = 0.001) and in the IR group than in the non-IR group (mean 98.6 vs. 70.2 ng/mL; p &lt; 0.001). Plasma asprosin levels were not associated with sex or pubertal stage. Plasma asprosin levels were positively correlated with BMI SDS (r = 0.34; p = 0.002), glycated hemoglobin (HbA1c) (r = 0.25; p = 0.02), glucose (r = 0.33; p = 0.002), insulin (r = 0.44; p &lt; 0.001), HOMA-IR (r = 0.47; p &lt; 0.001), triglyceride (TG) (r = 0.33; p = 0.003), high-density lipoprotein (HDL) cholesterol (r = -0.29; p = 0.008), and TyG index (r = 0.38; p &lt; 0.001). Multiple linear regression analysis indicated that plasma asprosin levels were independently associated with HOMA-IR (p &lt; 0.001) and TG/HDL cholesterol ratio (p &lt; 0.001).ConclusionsThis study demonstrated an association between plasma asprosin levels and obesity and insulin resistance in Korean children and adolescents.
The role of lactylation in plasma cells and its impact on rheumatoid arthritis pathogenesis: insights from single-cell RNA sequencing and machine learning
Authors: Fu Weicong , Wang Tianbao , Lu Yehong , Shi Tiejun , Yang Qining 
Published: October 2024

IntroductionRheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovitis, systemic inflammation, and autoantibody production. This study aims to explore the role of lactylation in plasma cells and its impact on RA pathogenesis.MethodsWe utilized single-cell RNA sequencing (scRNA-seq) data and applied bioinformatics and machine learning techniques. A total of 10,163 cells were retained for analysis after quality control. Clustering analysis identified 13 cell clusters, with plasma cells displaying the highest lactylation scores. We performed pathway enrichment analysis to examine metabolic activity, such as oxidative phosphorylation and glycolysis, in highly lactylated plasma cells. Additionally, we employed 134 machine learning algorithms to identify seven core lactylation-promoting genes and constructed a diagnostic model with an average AUC of 0.918.ResultsThe RA lactylation score (RAlac_score) was significantly elevated in RA patients and positively correlated with immune cell infiltration and immune checkpoint molecule expression. Differential expression analysis between two plasma cell clusters revealed distinct metabolic and immunological profiles, with cluster 2 demonstrating increased immune activity and extracellular matrix interactions. qRT-PCR validation confirmed that NDUFB3, NGLY1, and SLC25A4 are highly expressed in RA.ConclusionThis study highlights the critical role of lactylation in plasma cells for RA pathogenesis and identifies potential biomarkers and therapeutic targets, which may offer insights for future therapeutic strategies.
The causality between rheumatoid arthritis and postural deformities: bidirectional Mendelian randomization study and mediation analysis
Authors: Zhao Piqian , Chen Zhe , Wen Ya , Zhang Hongtao , Wen Liangyuan , Pei Zijie 
Published: October 2024

BackgroundTo better understand the preventive or therapeutic clinical interventions that may be supported by the association between rheumatoid arthritis (RA) and postural deformities including hallux valgus, flat foot, and scoliosis, this study was conducted using Mendelian randomization (MR) analysis. It aimed to investigate whether RA is causally associated with postural deformities in European populations.MethodsSummary-level data on RA and postural deformities were obtained from the IEU OpenGWAS project and Finngen database, respectively. LDSC regression analysis was conducted to assess the genetic correlation between these diseases. The inverse variance weighting (IVW) method was employed as the primary approach for two-sample MR analyses to evaluate causality. Supplementary methods included MR-Egger, maximum likelihood, weighted median, and cML-MA. To test for potential horizontal pleiotropy, we performed the MR-Egger intercept test, cML-MA, and secondary analyses after excluding confounders. Additionally, mediation analyses were conducted using two-step MR.ResultsThe IVW method revealed RA to be causally associated with hallux valgus (OR 1.132, 95% CI 1.087-1.178, P &lt; 0.001) and flat foot (OR 1.197, 95% CI 1.110-1.291, P &lt; 0.001). Among postural deformities, hallux valgus was causally associated with flat foot (OR 1.823, 95% CI 1.569-2.119, P &lt; 0.001) and scoliosis (OR 1.150, 95% CI 1.027-1.287, P &lt; 0.05). No significant horizontal pleiotropy was detected. Moreover, mediation analyses indicated that hallux valgus mediates the effect of RA on flat foot (mediation effect 0.024, 95% CI 0.005-0.044, P &lt; 0.05), with a mediation proportion of 41.31%.ConclusionThese findings indicate a potential causal association between genetically predicted RA and both hallux valgus and flat foot. Furthermore, hallux valgus serves as a mediator in the pathway from RA to flat foot. This underscores the importance of early screening and preventive treatment of foot deformities in RA patients. Further research is necessary to determine the applicability of these findings in non-European populations.
scRNA+TCR-seq reveals the pivotal role of dual receptor T lymphocytes in the pathogenesis of Kawasaki disease and during IVIG treatment
Authors: Xu Yuanyuan , Yuan Yi , Mou Lanlan , Hui Linhu , Zhang Xing , Yao Xinsheng , Li Jun 
Published: October 2024

IntroductionKawasaki disease (KD), a common cause of acquired heart disease in children in developed countries, is primarily treated with intravenous immunoglobulin (IVIG), but some children demonstrate IVIG resistance with increased coronary artery injury risk. T cells have been demonstrated to be involved in the pathogenesis of KD and its treatment with IVIG. However, the role and mechanism of dual TCR T lymphocytes in the occurrence of KD and IVIG therapy remain unclear.MethodsThis study, based on scRNA-seq combined with TCR-seq technology, clustered the peripheral blood mononuclear cells of 3 healthy controls and 6 KD patients before and after IVIG treatment. Comparative analysis was conducted to investigate the differences in the proportion of single/dual receptor T cells, the characteristics of CDR3 repertoires, cell types, and the expression of transcription factors among the three groups. The study aimed to explore the correlation between dual TCR T cells and KD as well as IVIG treatment.ResultsIn our experimental results, we observed the presence of dual TCR T cells in all three groups. However, compared to the healthy control group and the IVIG-treated group, the KD patients before IVIG treatment exhibited a lower proportion of dual TCR T cells, with variability between samples, ranging from 4% to 15%. Notably, after IVIG treatment, the proportion of dual TCR T cells significantly increased, stabilizing above 12%, and these T cells also exhibited clonal expansion and a preference for V gene usage. In addition we found differences in dual TCR T cell subsets among the three groups, for example, IVIG treatment increases the proportion of dual TCR Treg cells, but it still remains below that of healthy control groups, significantly higher proportions of both dual TCR CD8 central and effector memory T cells in IVIG-treated KD patients, and differences in the expression of transcription factors between single and dual TCR T cells. These results suggest dual TCR T cells correlate with KD and IVIG treatment.ConclusionDual TCR T lymphocytes, especially dual TCR CD8 T cells and Treg cells, play crucial roles in the pathogenesis of KD and during IVIG treatment, providing strong support for further elucidating KD pathogenesis and optimizing treatment strategies.
Comparative genomics of the Natural Killer Complex in carnivores
Authors: Futas Jan , Jelinek April L. , Burger Pamela A. , Horin Petr 
Published: October 2024

BackgroundThe mammalian Natural Killer Complex (NKC) harbors genes and gene families encoding a variety of C-type lectin-like proteins expressed on various immune cells. The NKC is a complex genomic region well-characterized in mice, humans and domestic animals. The major limitations of automatic annotation of the NKC in non-model animals include short-read based sequencing, methods of assembling highly homologous and repetitive sequences, orthologues missing from reference databases and weak expression. In this situation, manual annotations of complex genomic regions are necessary.MethodsThis study presents a manual annotation of the genomic structure of the NKC region in a high-quality reference genome of the domestic cat and compares it with other felid species and with representatives of other carnivore families. Reference genomes of Carnivora, irrespective of sequencing and assembly methods, were screened by BLAST to retrieve information on their killer cell lectin-like receptor (KLR) gene content. Phylogenetic analysis of in silico translated proteins of expanded subfamilies was carried out.ResultsThe overall genomic structure of the NKC in Carnivora is rather conservative in terms of its C-type lectin receptor gene content. A novel KLRH-like gene subfamily (KLRL) was identified in all Carnivora and a novel KLRJ-like gene was annotated in the Mustelidae. In all six families studied, one subfamily (KLRC) expanded and experienced pseudogenization. The KLRH gene subfamily expanded in all carnivore families except the Canidae. The KLRL gene subfamily expanded in carnivore families except the Felidae and Canidae, and in the Canidae it eroded to fragments.ConclusionsKnowledge of the genomic structure and gene content of the NKC region is a prerequisite for accurate annotations of newly sequenced genomes, especially of endangered wildlife species. Identification of expressed genes, pseudogenes and gene fragments in the context of expanded gene families would allow the assessment of functionally important variability in particular species.
The association of social networks with the job performance of primary health care professionals: the mediating effect of knowledge sharing
Authors: Wang Xiubo , Hou Shengchao , Lv Qiongxin , Liu Yuxin , Wu Huan , Liu Zhiyong 
Published: October 2024

Background and aimsSocial networks formed through social media platforms have facilitated knowledge sharing among primary health care professionals (PHCPs). However, the impact of these networks on PHCPs’ job performance and the mediating role of knowledge sharing remain underexplored. This study aimed to investigate the association between social networks formed via social media and the job performance of PHCPs, and to explore the mediating role of knowledge sharing in this association.MethodsA cross-sectional survey was carried out among PHCPs in Henan Province, China, involving 655 valid responses. Validated scales measured the key variables, and structural equation modeling (SEM) tested the proposed hypotheses, including the mediating effect of knowledge sharing through bootstrap method. Statistical analysis was performed using SPSS 24.0 and AMOS 24.0.ResultsThe degree centrality (β = 0.225; p = 0.001) and network heterogeneity (β = 0.093; p = 0.043) of the social network had a significant direct association with job performance, whereas the direct associations of betweenness centrality and network tie strength with job performance were not significant. Knowledge sharing mediated the relationship between degree centrality (β = 0.147; p = 0.001), network heterogeneity (β = 0.251; p = 0.043), and job performance.ConclusionThe study revealed the internal mechanisms by which social network characteristics influence PHCPs’ job performance, highlighting the mediating role of knowledge sharing. Social networks formed within social media contexts have multifaceted effects on job performance, with knowledge sharing as a critical mediating variable. These findings underscore the importance of leveraging social media for professional networking and knowledge exchange to enhance PHCPs’ job performance.
Cost-effectiveness of home care compared to hospital care in patients with chronic obstructive pulmonary disease (COPD): a systematic review
Authors: Vidigal Maria Tereza Campos , Borges Guilherme Henrique , Rabelo Diogo Henrique , de Andrade Vieira Walbert , Nascimento Gustavo G. , Lima Rafael Rodrigues , Costa Márcio Magno , Herval Álex Moreira , Paranhos Luiz Renato 
Published: October 2024

BackgroundTo compare, through a systematic literature review, the cost-effectiveness ratio of home care compared to hospital care for following up patients with chronic obstructive pulmonary disease (COPD).MethodsThis review was registered in PROSPERO, and the bibliographic search was performed in six primary databases [MedLine (via PubMed), Scopus, LILACS, SciELO, Web of Science, and Embase], two dedicated databases for economic studies (NHS Economic Evaluation Database (NHS EED) and Cost-Effectiveness Analysis (CEA) Registry), and two databases for partially searching the “gray literature” (DansEasy and ProQuest). This review only included studies that compared home and hospital care for patients diagnosed with COPD, regardless of publication year or language. Two reviewers selected the studies, extracted the data, and assessed the risk of bias independently. A JBI tool was used for risk of bias assessment.Results and discussion7,279 studies were found, of which 14 met the eligibility criteria. Only one study adequately met all items of the risk of bias assessment. Thirteen studies found lower costs and higher effectiveness for home care. Home care showed a better cost-effectiveness ratio than hospital care for COPD patients. Regarding effectiveness, there is no possibility of choosing a more effective care for COPD patients, given the incipience of the data presented on eligible studies. However, considering the analyzed data refer only to high-income countries, caution is required when extrapolating this conclusion to low- and low-middle-income countries.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022319488.
Survival prediction for heart failure complicated by sepsis: based on machine learning methods
Authors: Zhang Qitian , Xu Lizhen , He Weibin , Lai Xinqi , Huang Xiaohong 
Published: October 2024

BackgroundHeart failure is a cardiovascular disorder, while sepsis is a common non-cardiac cause of mortality. Patients with combined heart failure and sepsis have a significantly higher mortality rate and poor prognosis, making early identification of high-risk patients and appropriate allocation of medical resources critically important.MethodsWe constructed a survival prediction model for patients with heart failure and sepsis using the eICU-CRD database and externally validated it using the MIMIC-IV database. Our primary outcome is the 28-day all-cause mortality rate. The Boruta method is used for initial feature selection, followed by feature ranking using the XGBoost algorithm. Four machine learning models were compared, including Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), and Gaussian Naive Bayes (GNB). Model performance was assessed using metrics such as area under the curve (AUC), accuracy, sensitivity, and specificity, and the SHAP method was utilized to visualize feature importance and interpret model results. Additionally, we conducted external validation using the MIMIC-IV database.ResultsWe developed a survival prediction model for heart failure complicated by sepsis using data from 3891 patients in the eICU-CRD and validated it externally with 2928 patients from the MIMIC-IV database. The LR model outperformed all other machine learning algorithms with a validation set AUC of 0.746 (XGBoost: 0.726, AdaBoost: 0.744, GNB: 0.722), alongside accuracy (0.685), sensitivity (0.666), and specificity (0.712). The final model incorporates 10 features: age, ventilation, norepinephrine, white blood cell count, total bilirubin, temperature, phenylephrine, respiratory rate, neutrophil count, and systolic blood pressure. We employed the SHAP method to enhance the interpretability of the model based on the LR algorithm. Additionally, external validation was conducted using the MIMIC-IV database, with an external validation AUC of 0.699.ConclusionBased on the LR algorithm, a model was constructed to effectively predict the 28-day all-cause mortality rate in patients with heart failure complicated by sepsis. Utilizing our model predictions, clinicians can promptly identify high-risk patients and receive guidance for clinical practice.
Predicting cerebral edema in patients with spontaneous intracerebral hemorrhage using machine learning
Authors: Xu Jiangbao , Yuan Cuijie , Yu Guofeng , Li Hao , Dong Qiutong , Mao Dandan , Zhan Chengpeng , Yan Xinjiang 
Published: October 2024

BackgroundThe early prediction of cerebral edema changes in patients with spontaneous intracerebral hemorrhage (SICH) may facilitate earlier interventions and result in improved outcomes. This study aimed to develop and validate machine learning models to predict cerebral edema changes within 72 h, using readily available clinical parameters, and to identify relevant influencing factors.MethodsAn observational study was conducted between April 2021 and October 2023 at the Quzhou Affiliated Hospital of Wenzhou Medical University. After preprocessing the data, the study population was randomly divided into training and internal validation cohorts in a 7:3 ratio (training: N = 150; validation: N = 65). The most relevant variables were selected using Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms. The predictive performance of random forest (RF), GDBT, linear regression (LR), and XGBoost models was evaluated using the area under the receiver operating characteristic curve (AUROC), precision–recall curve (AUPRC), accuracy, F1-score, precision, recall, sensitivity, and specificity. Feature importance was calculated, and the SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) methods were employed to explain the top-performing model.ResultsA total of 84 (39.1%) patients developed cerebral edema changes. In the validation cohort, GDBT outperformed LR and RF, achieving an AUC of 0.654 (95% CI: 0.611–0.699) compared to LR of 0.578 (95% CI, 0.535–0.623, DeLong: p = 0.197) and RF of 0.624 (95% CI, 0.588–0.687, DeLong: p = 0.236). XGBoost also demonstrated similar performance with an AUC of 0.660 (95% CI, 0.611–0.711, DeLong: p = 0.963). However, in the training set, GDBT still outperformed XGBoost, with an AUC of 0.603 ± 0.100 compared to XGBoost of 0.575 ± 0.096. SHAP analysis revealed that serum sodium, HDL, subarachnoid hemorrhage volume, sex, and left basal ganglia hemorrhage volume were the top five most important features for predicting cerebral edema changes in the GDBT model.ConclusionThe GDBT model demonstrated the best performance in predicting 72-h changes in cerebral edema. It has the potential to assist clinicians in identifying high-risk patients and guiding clinical decision-making.