bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of genomic regions that differentiate Bos indicus from Bos taurus ancestral breeds for milk yield in Indian crossbred cows
Authors: Al Kalaldeh Mohammad , Swaminathan Marimuthu , Podtar Vinod , Jadhav Santoshkumar , Dhanikachalam Velu , Joshi Akshay , Gibson John P. 
Published: January 2023

Introduction: In India, crossbred cows incorporate the high production of B. taurus dairy breeds and the environmental adaptation of local B. indicus cattle. Adaptation to different environments and selection in milk production have shaped the genetic differences between B. indicus and B. taurus cattle. The aim of this paper was to detect, for milk yield of crossbred cows, quantitative trait loci (QTL) that differentiate B. indicus from B. taurus ancestry, as well as QTL that are segregating within the ancestral breeds.Methods: A total of 123,042 test-day milk records for 4,968 crossbred cows, genotyped with real and imputed 770 K SNP, were used. Breed origins were assigned to haplotypes of crossbred cows, and from that, were assigned to SNP alleles.Results: At a false discovery rate (FDR) of 30%, a large number of genomic regions showed significant effects of B. indicus versus B. taurus origin on milk yield, with positive effects coming from both ancestors. No significant regions were detected for Holstein Friesian (HF) versus Jersey effects on milk yield. Additionally, no regions for SNP alleles segregating within indigenous, within HF, and within Jersey were detected. The most significant effects, at FDR 5%, were found in a region on BTA5 (43.98–49.44 Mbp) that differentiates B. indicus from B. taurus, with an estimated difference between homozygotes of approximately 10% of average yield, in favour of B. indicus origin.Discussion: Our results indicate that evolutionary differences between B. indicus and B. taurus cattle for milk yield, as expressed in crossbred cows, occur at many causative loci across the genome. Although subject to the usual first estimation bias, some of the loci appear to have large effects that might make them useful for genomic selection in crossbreds, if confirmed in subsequent studies.
Telomere maintenance-related genes are important for survival prediction and subtype identification in bladder cancer
Authors: Xiao Yonggui , Xu Danping , Jiang Chonghao , Huili Youlong , Nie Shiwen , Zhu Hongfei , Fan Guorui , Guan Xiaohai 
Published: January 2023

Background: Bladder cancer ranks among the top three in the urology field for both morbidity and mortality. Telomere maintenance-related genes are closely related to the development and progression of bladder cancer, and approximately 60%–80% of mutated telomere maintenance genes can usually be found in patients with bladder cancer.Methods: Telomere maintenance-related gene expression profiles were obtained through limma R packages. Of the 359 differential genes screened, 17 prognostically relevant ones were obtained by univariate independent prognostic analysis, and then analysed by LASSO regression. The best result was selected to output the model formula, and 11 model-related genes were obtained. The TCGA cohort was used as the internal group and the GEO dataset as the external group, to externally validate the model. Then, the HPA database was used to query the immunohistochemistry of the 11 model genes. Integrating model scoring with clinical information, we drew a nomogram. Concomitantly, we conducted an in-depth analysis of the immune profile and drug sensitivity of the bladder cancer. Referring to the matrix heatmap, delta area plot, consistency cumulative distribution function plot, and tracking plot, we further divided the sample into two subtypes and delved into both.Results: Using bioinformatics, we obtained a prognostic model of telomere maintenance-related genes. Through verification with the internal and the external groups, we believe that the model can steadily predict the survival of patients with bladder cancer. Through the HPA database, we found that three genes, namely ABCC9, AHNAK, and DIP2C, had low expression in patients with tumours, and eight other genes—PLOD1, SLC3A2, RUNX2, RAD9A, CHMP4C, DARS2, CLIC3, and POU5F1—were highly expressed in patients with tumours. The model had accurate predictive power for populations with different clinicopathological features. Through the nomogram, we could easily assess the survival rate of patients. Clinicians can formulate targeted diagnosis and treatment plans for patients based on the prediction results of patient survival, immunoassays, and drug susceptibility analysis. Different subtypes help to further subdivide patients for better treatment purposes.Conclusion: According to the results obtained by the nomogram in this study, combined with the results of patient immune-analysis and drug susceptibility analysis, clinicians can formulate diagnosis and personalized treatment plans for patients. Different subtypes can be used to further subdivide the patient for a more precise treatment plan.
Constructing a diversified online neurology teaching model under the COVID-19
Authors: Yang Haojun , Fan Yishu , Chen Zhuohui , Zhang Shiyu , Wu Haiyue , Hu Xinhang , Wu Tong , Zhang Mengqi 
Published: January 2023

PurposeTo construct a diversified and comprehensive network teaching model to provide highly qualified medical teaching in neurology under COVID-19 pandemic.Materials and methodsPublished studies on medical education were systematically reviewed and summarized. Based on previous studies and our experience, we constructed a novel online neurology teaching model and applied it to real scene. Students taking traditional in class lessons and online lessons were asked to finish the test, respectively, to compare the efficiency of learning. Questionnaires were designed and assigned to get the feedback from students.ResultsThe average test score of students who take online class (84.27 ± 4.64) was significantly higher than those who take in class lessons (82.08 ± 6.17) (P &lt; 0.01). According to the feedbacks from students, online classes were more attractive to students than the conventional one.ConclusionTraditional single-mode teaching can no longer meet the needs of current medical education, especially under the rampant epidemic. This novel teaching mode, which orchestrates high-tech tools, diverse teaching methods and traditional teaching concepts, provides the solution to the challenge faced by traditional medical education. We believe that this novel online teaching mode will boost neurology education and inspire educators in other fields during this tough period.
Efficacy and safety of underwater endoscopic mucosal resection for ≤20 mm superficial non-ampullary duodenal epithelial tumors: Systematic review and meta-analysis
Authors: Liu Jixiang , Duan Shaojie , Wang Yichong , Peng Hongye , Kong Youjia , Yao Shukun 
Published: January 2023

Background and aimsSuperficial non-ampullary duodenal epithelial tumors (SNADETs) as a rare disease have gradually increased in recent years. Underwater endoscopic mucosal resection (UEMR) has emerged as a newly available option for the endoscopic resection of SNADETs. This study aimed to evaluate the efficacy and safety of UEMR for ≤20 mm SNADETs.MethodsA literature search was performed across multiple databases, including PubMed, Embase, Scopus, and Clinical trials for studies containing tumors ≤20 mm published from January 1, 2012, to August 8, 2022. Outcomes examined were the pooled rates of en bloc resection, R0 resection, adverse events, and recurrence. Subgroup analyses of the resection rate were conducted stratified by sample size and polyp size.ResultsA total of 10 studies with UEMR performed in a total of 648 tumors were included for analysis. The pooled rate of en bloc resection and R0 resection was 88.2% (95% confidence interval (CI): 82.1–93.2) and 69.1% (95% CI: 62.2–76.1), respectively. The results showed pooled rate of intraoperative bleeding rate was 2.9% (95% CI: 0–9.0), delayed bleeding rate was 0.9% (95% CI: 0.1–2), recurrence rate was 1.5% (95% CI: 0–4.9). In the subgroup analysis, R0 and en-bloc resection rates were significantly higher in &lt;10 mm than 10–20 mm SNADETs subgroups (R0 resection rate 83.1 vs. 48.6%; en bloc resection rate 100.0 vs. 84.0%, P &lt; 0.05).ConclusionUnderwater endoscopic mucosal resection was an effective and safe technique for the optional treatment for ≤20 mm SNADETs, especially of &lt;10 mm.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022340578.
Analysis of the expression and distribution of protein O-linked mannose β1,2-N-acetylglucosaminyltransferase 1 in the normal adult mouse brain
Authors: Jiang Hanxiao , Feng Yuxue , He Guiqiong , Liu Yuanjie , Li Xiaofeng 
Published: January 2023

IntroductionProtein O-linked mannose β1,2-N-acetylglucosaminyltransferase 1 (POMGNT1) is crucial for the elongation of O-mannosyl glycans. Mutations in POMGNT1 cause muscle-eye-brain (MEB) disease, one of the main features of which is anatomical aberrations in the brain. A growing number of studies have shown that defects in POMGNT1 affect neuronal migration and distribution, disrupt basement membranes, and misalign Cajal-Retzius cells. Several studies have examined the distribution and expression of POMGNT1 in the fetal or neonatal brain for neurodevelopmental studies in the mouse or human brain. However, little is known about the neuroanatomical distribution and expression of POMGNT1 in the normal adult mouse brain.MethodsWe analyzed the expression of POMGNT1 mRNA and protein in the brains of various neuroanatomical regions and spinal cords by western blotting and RT-qPCR. We also detected the distribution profile of POMGnT1 in normal adult mouse brains by immunohistochemistry and double-immunofluorescence.ResultsIn the present study, we found that POMGNT1-positive cells were widely distributed in various regions of the brain, with high levels of expression in the cerebral cortex and hippocampus. In terms of cell type, POMGNT1 was predominantly expressed in neurons and was mainly enriched in glutamatergic neurons; to a lesser extent, it was expressed in glial cells. At the subcellular level, POMGNT1 was mainly co-localized with the Golgi apparatus, but expression in the endoplasmic reticulum and mitochondria could not be excluded.DiscussionThe present study suggests that POMGNT1, although widely expressed in various brain regions, may has some regional and cellular specificity, and the outcomes of this study provide a new laboratory basis for revealing the possible involvement of POMGNT1 in normal physiological functions of the brain from a morphological perspective.
Factors associated with poor self-rated health among chronic kidney disease patients and their health care utilization: Insights from LASI wave-1, 2017-18
Authors: Nayak Swetalina , Nayak Soumya Ranjan , Alice Alice , Sahoo Debadutta , Kanungo Srikanta , Rehman Tanveer , Pati Sanghamitra , Palo Subrat Kumar 
Published: January 2023

BackgroundChronic kidney disease (CKD), associated with other chronic conditions affects the physical, behavioral, and psychological aspects of an individual, leading to poor self-rated health. Hence, we aimed to assess the factors associated with poor self-rated health (SRH) in CKD patients. Additionally, we assessed their health care utilization.MethodsThis is an observational study consisting of 527 CKD patients from Longitudinal Aging Study in India (LASI), 2017-2018. A descriptive statistic computed prevalence. Regression analysis assessed the association between poor SRH and socio-demographic variables presented as adjusted odds ratio with a confidence interval of 95%. Health care utilization among CKD patients was graphically presented.ResultsAround 64% of CKD patients had poor SRH. Aged 75 years and above (AOR=1.8, 95% CI= 0.5-6.8), rural residents (AOR= AOR 1.8, 95% CI =1.0 -3.1) and those with other chronic conditions (AOR=5.1, 95% CI= 2.3-11.0) were associated with poor SRH. Overall 79% of the CKD patients availed health care facility, most (44.8%) of those visit private facility.ConclusionWe observed older adults, females, rural residents, and having other chronic conditions were associated with poor SRH among CKD patients which highlights the need for equitable and strengthened health care system. There is an urgent need to provide accessible, affordable and quality healthcare services for these individuals so as to maintain continuity of care.
Persistent pain and numbness in the extremities of an adult due to paraneoplastic peripheral neuropathy caused by olfactory neuroblastoma: A case report
Authors: Liang Wenwen , Wang Yanyan , Sun Wenzhe , Li Dongrui , Zhang Xiaoping , Zhu Pengcheng , Zhu Zhou , Fang Yongkang 
Published: January 2023

BackgroundParaneoplastic peripheral neuropathy (PPN) caused by olfactory neuroblastoma (ONB) has not yet been reported.Case reportWe present a rare case of an adult who hospitalized repeatedly over the past 9 months for persistent pain and numbness in the limbs. This patient was initially diagnosed with chronic inflammatory demyelinating polyneuropathy (CIDP) and treated accordingly, but neurological symptoms did not improve significantly. After this admission, FDG-PET/CT showed focal hypermetabolism of a soft-tissue mass in the nasal cavity, and further lesion biopsy suggested ONB. Combined with positive serum anti-Hu antibody, the diagnosis of PPN associated with ONB was eventually made. Furthermore, the patient's neurological symptoms were relieved after removal of the primary tumor, confirming the accuracy of the diagnosis.ConclusionOur case not only expanded the clinical characteristics of ONB but also highlighted the importance of early and comprehensive tumor screening for the diagnosis of PPN.
Exploring the role of immune checkpoint inhibitors in the etiology of myasthenia gravis and Lambert-Eaton myasthenic syndrome: A systematic review
Authors: Seligman Carly , Chang Yu-Mei , Luo Jie , Garden Oliver A. 
Published: January 2023

BackgroundWhile immune checkpoint inhibitors (ICIs) have been revolutionary in the treatment of cancer, their administration has been associated with a variety of immune-related adverse events (irAEs), including myasthenia gravis (MG), and Lambert-Eaton myasthenic syndrome (LEMS).ObjectiveTo provide a comprehensive synthesis of the evidence supporting an etiological role for ICIs in MG and LEMS in patients with no prior history of autoimmune disease.HypothesisICIs may trigger MG and LEMS in patients with no prior susceptibility to autoimmune disease.MethodsRelevant primary research on Medline was interrogated using a series of search algorithms. Search terms were constructed based on the PICOS tool endorsed by the Cochrane Collaboration, which describes population, intervention, comparison, outcomes, and study design. Papers were screened according to inclusion and exclusion criteria. Additional papers were retrieved from the reference lists of screened papers. Each paper included in the qualitative synthesis was assigned an integrated metric of evidence (IME) value, ranging from 0 to 7, based on study design, quality of data, likelihood of a causal link between the immune checkpoint inhibitor(s) and MG/LEMS, confidence of MG/LEMS diagnosis, and the number of patients treated with an ICI prior to MG/LEMS diagnosis.ResultsNinety-four papers describing at least one patient treated with ICI(s) prior to the onset of MG and/or LEMS were documented. Overall evidence for a causal link between ICI administration and MG/LEMS was low, with a median IME value of 2.88 (range 2.05–6.61).ConclusionsThere is a paucity of evidence in support of an etiological relationship between ICIs and MG/LEMS, due largely to the lack of mechanistic studies and/or prospective clinical trials with relevant study endpoints. The current literature is dominated by case reports and retrospective cohort studies, which inherently yield only low-level evidence, supporting the need for further work in this area. A role of ICIs in the etiology of MG/LEMS remains plausible, arguing for continued vigilance for irAEs in patients treated with these drugs. We argue that there is a need for future mechanistic, high quality, large-scale studies specifically investigating the possible etiological role of ICIs in MG/LEMS.
Impairment of attention network function in posterior circulation ischemia-evidence from the Attention Network Test
Authors: Li Na , Li Chuanjin , Xie Xiaohui , Liu Gang , Wang Kai , Zhang Wendong , Fan Jin 
Published: January 2023

ObjectiveThis study aimed to investigate the effect of posterior circulation ischemia (PCI) on attention network function and to determine whether PCI is holistic or selective attention network deficit and which attention network is affected.MethodsThirty-six PCI patients aged 30 to 75 were assessed using the Attention Network Test and the Mini-Mental State Examination (MMSE). There were no significant differences in age, sex, and education between PCI group and the control group (n = 32). All data were statistically analyzed by SPSS 23.0 software.ResultThere were no significant difference in the MMSE scores between the two groups. Compared with the control group, the PCI group had significantly shorter response time for alerting and orienting network. The executive control network response time was significantly longer in PCI group than in the control group. The overall mean response time was also significantly longer in PCI group than in normal control group. There was no significant difference in mean accuracy between the two groups.ConclusionThe alerting, orienting, and executive control networks were significantly less efficient in PCI group than in the control group (P &lt; 0.01). This indicates impaired attention network in PCI patients. Since transient nerve seizures caused by vertebrobasilar ischemia may precede posterior circulation stroke, early assessment of cognitive function in patients with PCI is particularly important, and ANT is an excellent tool for this assessment.
Ethnicity, minority status, and inter-group bias: A systematic meta-analysis on fMRI studies
Authors: Saarinen Aino , Keltikangas-Järvinen Liisa , Ravaja Niklas 
Published: January 2023

IntroductionThis meta-analysis investigated (1) whether ethnic minority and majority members have a neural inter-group bias toward each other, and (2) whether various ethnic groups (i.e., White, Black, and Asian) are processed in the brain differently by the other respective ethnicities.MethodsA systematic coordinate-based meta-analysis of functional magnetic resonance imaging (fMRI) studies was conducted using Web of Science, PubMed, and PsycINFO (altogether 50 datasets, n = 1211, 50.1% female).ResultsWe found that ethnic minority members did not show any signs of neural inter-group bias (e.g., no majority-group derogation). Ethnic majority members, in turn, expressed biased responses toward minority (vs. majority) members in frontal, parietal, temporal, and occipital regions that are known to be involved in e.g., facial processing, attention, and perspective-taking. We also found differences in neural response patterns toward different ethnic groups (White, Black, and Asian); broadest biases in neural response patterns were evident toward Black individuals (in non-Black individuals). Heterogeneity was mostly minor or low.Discussion:Overall, the findings increase understanding of neural processes involved in ethnicity perception and cognition as well as ethnic prejudices and discrimination. This meta-analysis provides explanations for previous behavioral reports on ethnic discrimination toward minority groups.
Model-based experimental manipulation of probabilistic behavior in interpretable behavioral latent variable models
Authors: Thome Janine , Pinger Mathieu , Durstewitz Daniel , Sommer Wolfgang H. , Kirsch Peter , Koppe Georgia 
Published: January 2023

IntroductionInterpretable latent variable models that probabilistically link behavioral observations to an underlying latent process have increasingly been used to draw inferences on cognition from observed behavior. The latent process usually connects experimental variables to cognitive computation. While such models provide important insights into the latent processes generating behavior, one important aspect has often been overlooked. They may also be used to generate precise and falsifiable behavioral predictions as a function of the modeled experimental variables. In doing so, they pinpoint how experimental conditions must be designed to elicit desired behavior and generate adaptive experiments.MethodsThese ideas are exemplified on the process of delay discounting (DD). After inferring DD models from behavior on a typical DD task, the models are leveraged to generate a second adaptive DD task. Experimental trials in this task are designed to elicit 9 graded behavioral discounting probabilities across participants. Models are then validated and contrasted to competing models in the field by assessing the ouf-of-sample prediction error.ResultsThe proposed framework induces discounting probabilities on nine levels. In contrast to several alternative models, the applied model exhibits high validity as indicated by a comparably low prediction error. We also report evidence for inter-individual differences with respect to the most suitable models underlying behavior. Finally, we outline how to adapt the proposed method to the investigation of other cognitive processes including reinforcement learning.DiscussionInducing graded behavioral frequencies with the proposed framework may help to highly resolve the underlying cognitive construct and associated neuronal substrates.
An attention-based deep learning network for lung nodule malignancy discrimination
Authors: Liu Gang , Liu Fei , Gu Jun , Mao Xu , Xie XiaoTing , Sang Jingyao 
Published: January 2023

IntroductionEffective classification of lung cancers plays a vital role in lung tumor diagnosis and subsequent treatments. However, classification of benign and malignant lung nodules remains inaccurate.MethodsThis study proposes a novel multimodal attention-based 3D convolutional neural network (CNN) which combines computed tomography (CT) imaging features and clinical information to classify benign and malignant nodules.ResultsAn average diagnostic sensitivity of 96.2% for malignant nodules and an average accuracy of 81.6% for classification of benign and malignant nodules were achieved in our algorithm, exceeding results achieved from traditional ResNet network (sensitivity of 89% and accuracy of 80%) and VGG network (sensitivity of 78% and accuracy of 73.1%).DiscussionThe proposed deep learning (DL) model could effectively distinguish benign and malignant nodules with higher precision.