bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the role of type 2 diabetes mellitus in rotator cuff tendinopathy: Development and analysis of a novel rat model
Authors: Xu Kuishuai , Zhang Liang , Ren Zhongkai , Wang Tianrui , Zhang Yingze , Zhao Xia , Yu Tengbo 
Published: October 2022

ObjectiveTo establish and validate an intact rotator cuff rat model for exploring the pathophysiological effects of type 2 diabetes on the rotator cuff tendon in vivo.MethodsA total of 45 adult male rats were randomly divided into a control group (n = 9) and type 2 diabetes group (n=36). The rats were sacrificed at 2 weeks (T2DM-2w group, n=9), 4 weeks (T2DM-4w group, n=9), 8 weeks (T2DM-8w group, n=9), and 12 weeks (T2DM-12w group, n=9) after successful modeling of type 2 diabetes. Bilateral shoulder samples were collected for gross observation and measurement, protein expression(enzyme-linked immunosorbent assay,ELISA), histological evaluation, biomechanical testing, and gene expression (real-time quantitative polymerase chain reaction, qRT-PCR).ResultsProtein expression showed that the expression of IL-6 and Advanced glycation end products (AGEs)in serum increased in type 2 diabetic group compared with the non-diabetic group. Histologically, collagen fibers in rotator cuff tendons of type 2 diabetic rats were disorganized, ruptured, and with scar hyperplasia, neovascularization, and extracellular matrix disturbances, while Bonar score showed significant and continuously aggravated tendinopathy over 12 weeks. The biomechanical evaluation showed that the ultimate load of rotator cuff tendons in type 2 diabetic rats gradually decreased, and the ultimate load was negatively correlated with AGEs content. Gene expression analysis showed increased expression of genes associated with matrix remodeling (COL-1A1), tendon development (TNC), and fatty infiltration (FABP4) in tendon specimens from the type 2 diabetic group.ConclusionPersistent type 2 diabetes is associated with the rupture of collagen fiber structure, disturbance in the extracellular matrix, and biomechanical decline of the rotator cuff tendon. The establishment of this new rat model of rotator cuff tendinopathy provides a valuable research basis for studying the cellular and molecular mechanisms of diabetes-induced rotator cuff tendinopathy.
Analysis of serum bone turnover markers in female cynomolgus monkeys of different ages
Authors: Li Ying , Cai Qijun , Dong Chenchen , Hou Lu , Li Yingxin , Guo Bin , Zeng Chunyuan , Cheng Yong , Shang Jingjie , Ling Xueying , Gong Jian , Xu Hao 
Published: October 2022

ObjectiveThe purpose of this study was to examine bone turnover markers, estradiol, parathyroid hormone, and 25 hydroxyvitamin D, in cynomolgus monkeys at different ages to improve our understanding of the changes in bone turnover markers throughout the life cycle of cynomolgus monkeys and to provide a basis for the establishment of a non-human primate model of osteoporosis.MethodsTotal Body Bone Mineral Density and Total Body Bone Mineral Content were measured using Dual-Energy X-Ray Absorptiometry in cynomolgus monkeys at different ages. Serum bone turnover marker' levels were measured using enzyme immunoassays at each age group, and the relationship between bone turnover markers and age was assessed by Spearman rank correlation analysis to investigate the relationship between bone turnover markers and age in female cynomolgus monkeys.ResultsTotal Body Bone Mineral Density in female cynomolgus monkeys peaked at 10 years of age and then formed a plateau that was maintained until old age. Procollagen I Aminoterminal Propeptide, Bone Alkaline Phosphatase, Osteocalcin, and C-Terminal Telopeptide Of Type I Collagen peaked at 1 to 3 years of age and gradually decreased with age, leveling off by 10 years of age. Estradiol, parathyroid hormone, and 25 hydroxyvitamin D, follicle-stimulating hormone, luteinizing hormone, were not significantly different among age groups.ConclusionThis paper provides data on trends in bone turnover markers throughout the life cycle of female cynomolgus monkeys, which are similar to human changes.
Compositional, genetic and functional characterization of soil culturable microbial communities in polychlorinated dibenzo-p-dioxins/furans contaminated soil
Authors: Mahfouz Sabrin , Mansour Gaytha , Hanano Abdulsamie 
Published: October 2022

Dioxins (PCDD/Fs) are one of the most toxic environmental pollutants known to date. Due to their structural stability and extreme hydrophobicity dioxins persist in the ecosystems and can be bioaccumulated to critical levels in both human and animal food chains. Soils are the most important reservoirs of dioxins, thus soil microbes are highly exposed to dioxins, impacting their diversity, genetics and functional characteristics. To experimentally evaluate these effects, the diversity and functionality of soil microbes were assessed in seven local sites potentially exposed to PCDD/Fs.Concentration of dioxins in soils samples was firstly determined and the soils cultivable microbes were identified and molecularly characterized as a function of their in vitro ability to degrade the TCDD. Our results revealed that the diversity of microbial communities largely varied among the sites and was likely inversely proportional to their level of contamination with PCDD/Fs. Furthermore, the genetics profiling of dioxin-degrading bacteria revealed that the Cytochrome P450 CYPBM3-positive species largely belong to the genus Bacillus and were randomly distributed among the soils samples, while the angular dioxygenase (AD)-positive species were mainly found in highly polluted soils with a major presence of the genus Pseudomonas. Finally, the functionality of dioxin-biodegrading genes (AD or CYPBM3), was confirmed by the ability of bacteria to consume 2,3,7,8-TCDD, and this was synchronized with an induced level of both pathways. Our results suggest that different dioxin-metabolizing pathways exist under the same environmental conditions and work differentially for an effective removal of PCDD/Fs.
Evaluation of the factors affecting arsenic distribution using geospatial analysis techniques in Dongting Plain, China
Authors: Malik Muhammad Akhtar , Tang Zhonghua , Xiao Tianyun 
Published: October 2022

Due to high toxicity, arsenic is regarded as a major global environmental pollutant. The present study is investigated the potential factors influencing to elevate concentration of arsenic in groundwater, surface water, and soil of the Dongting basin. The arsenic contamination potential prediction map and categories were developed using various GIS techniques such as Ordinary Kriging and the Quantile method. Then the “Raster calculator” tool was applied to verify the impact of the factors on arsenic. Eighty-four single-factor, bi-factor, and multi-factor models were established to investigate effective combinations among factors of each phase. Additionally, statistical tests were computed to evaluate arsenic between classes and factors. The arsenic value varies in groundwater from 0.0001 to 0.1582 mg/l, while in surface water between 0.0001–0.0287 mg/l and soil sediments range from 1.8–45.69 mg/kg. JunShan and GongAn groundwater resources have been identified as posing a high risk to human health. The single factors showed the best match frequency of arsenic with a population density of 66.86% in water and land use depicted match frequency of arsenic 73.19% in soil. The statistical calculations with percentage frequency factors also depicted positive trends. The correlation of the factors with arsenic in soil and water showed slow oxidation and reduction in the groundwater system. Treated portable water could be the best option to reduce the health risk of the local community.
Adaptive immunity to SARS-CoV-2 infection: A systematic review
Authors: Silva Marcos Jessé Abrahão , Ribeiro Layana Rufino , Lima Karla Valéria Batista , Lima Luana Nepomuceno Gondim Costa 
Published: October 2022

BackgroundThere is evidence that the adaptive or acquired immune system is one of the crucial variables in differentiating the course of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This work aimed to analyze the immunopathological aspects of adaptive immunity that are involved in the progression of this disease.MethodsThis is a systematic review based on articles that included experimental evidence from in vitro assays, cohort studies, reviews, cross-sectional and case-control studies from PubMed, SciELO, MEDLINE, and Lilacs databases in English, Portuguese, or Spanish between January 2020 and July 2022.ResultsFifty-six articles were finalized for this review. CD4+ T cells were the most resolutive in the health-disease process compared with B cells and CD8+ T lymphocytes. The predominant subpopulations of T helper lymphocytes (Th) in critically ill patients are Th1, Th2, Th17 (without their main characteristics) and regulatory T cells (Treg), while in mild cases there is an influx of Th1, Th2, Th17 and follicular T helper cells (Tfh). These cells are responsible for the secretion of cytokines, including interleukin (IL) - 6, IL-4, IL-10, IL-7, IL-22, IL-21, IL-15, IL-1α, IL-23, IL-5, IL-13, IL-2, IL-17, tumor necrosis factor alpha (TNF-α), CXC motivating ligand (CXCL) 8, CXCL9 and tumor growth factor beta (TGF-β), with the abovementioned first 8 inflammatory mediators related to clinical benefits, while the others to a poor prognosis. Some CD8+ T lymphocyte markers are associated with the severity of the disease, such as human leukocyte antigen (HLA-DR) and programmed cell death protein 1 (PD-1). Among the antibodies produced by SARS-CoV-2, Immunoglobulin (Ig) A stood out due to its potent release associated with a more severe clinical form.ConclusionsIt is concluded that through this study it is possible to have a brief overview of the main immunological biomarkers and their function during SARS-CoV-2 infection in particular cell types. In critically ill individuals, adaptive immunity is varied, aberrantly compromised, and late. In particular, the T-cell response is also an essential and necessary component in immunological memory and therefore should be addressed in vaccine formulation strategies.
ATF6α contributes to rheumatoid arthritis by inducing inflammatory cytokine production and apoptosis resistance
Authors: Ge Luna , Wang Ting , Shi Dandan , Geng Yun , Fan Huancai , Zhang Ruojia , Zhang Yuang , Zhao Jianli , Li Shufeng , Li Yi , Shi Haojun , Song Guanhua , Pan Jihong , Wang Lin , Han Jinxiang 
Published: October 2022

ObjectiveThe contribution of activating transcription factor 6α (ATF6α) in rheumatoid arthritis (RA) pathogenesis, especially on fibroblast-like synoviocytes (FLSs), has been suggested by its sensitivity to inflammatory stimulus. However, the exact role and therapeutic potential of ATF6α in RA remains to be fully elucidated.MethodsATF6α expression was determined in joint tissues and FLS, and gain-of-function and loss-of-function analyses were applied to evaluate the biological roles of ATF6α in RA FLSs. A murine collagen-induced arthritis (CIA) model, combining both gene deletion of ATF6α and treatment with the ATF6α inhibitor Ceapin-A7, was employed. Joint inflammation, tissue destruction, circulating levels of inflammatory cytokines were assessed in CIA mice. Transcriptome sequencing analysis (RNASeq), molecular biology, and biochemical approaches were performed to identify target genes of ATF6α.ResultsATF6α expression was significantly increased in synovium of RA patients and in synovium of mice subjected to CIA. ATF6α silencing or inhibition repressed RA FLSs viability and cytokine production but induced the apoptosis. CIA-model mice with ATF6α deficiency displayed decreased arthritic progression, leading to profound reductions in clinical and proinflammatory markers in the joints. Pharmacological treatment of mice with Ceapin-A7 reduced arthritis severity in CIA models. RNA-sequencing of wild-type and knockdown of ATF6α in RA FLSs revealed a transcriptional program that promotes inflammation and suppresses apoptosis, and subsequent experiments identified Baculoviral IAP Repeat Containing 3 (BIRC3) as the direct target for ATF6α.ConclusionThis study highlights the pathogenic role of ATF6α-BIRC3 axis in RA and identifies a novel pathway for new therapies against RA.
Using stacked deep learning models based on PET/CT images and clinical data to predict EGFR mutations in lung cancer
Authors: Chen Song , Han Xiangjun , Tian Guangwei , Cao Yu , Zheng Xuting , Li Xuena , Li Yaming 
Published: October 2022

PurposeTo determine whether stacked deep learning models based on PET/CT images and clinical data can help to predict epidermal growth factor receptor (EGFR) mutations in lung cancer.MethodsWe analyzed data from two public datasets of patients who underwent 18F-FDG PET/CT. Three PET deep learning ResNet models and one CT deep learning ResNet model were trained as low-level predictors based on PET and CT images, respectively. A high-level Support Vector Machine model (Stack PET/CT and Clinical model) was trained using the prediction results of the low-level predictors and clinical data. The clinical data included sex, age, smoking history, SUVmax and SUVmean of the lesion. Fivefold cross-validation was used in this study to validate the prediction performance of the models. The predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves. The area under the curve (AUC) was calculated.ResultsOne hundred forty-seven patients were included in this study. Among them, 37/147 cases were EGFR mutations, and 110/147 cases were EGFR wild-type. The ROC analysis showed that the Stack PET/CT &amp; Clinical model had the best performance (AUC = 0.85 ± 0.09), with 0.76, 0.85 and 0.83 in sensitivity, specificity and accuracy, respectively. Three ResNet PET models had relatively higher AUCs (0.82 ± 0.07, 0.80 ± 0.08 and 0.79 ± 0.07) and outperformed the CT model (AUC = 0.58 ± 0.12).ConclusionUsing stack generalization, the deep learning model was able to efficiently combine the anatomic and biological imaging information gathered from PET/CT images with clinical data. This stacked deep learning model showed a strong ability to predict EGFR mutations with high accuracy.
Exploration of prognostic factors for prediction of mortality in elderly CAP population using a nomogram model
Authors: Lv Chunxin , Li Mengyuan , Shi Wen , Pan Teng , Muhith Abdul , Peng Weixiong , Xu Jiayi , Deng Jinhai 
Published: October 2022

BackgroundThe incidence and mortality rate of community-acquired pneumonia (CAP) in elderly patients were higher than the younger population. The assessment tools including CURB-65 and qSOFA have been applied in early detection of high-risk patients with CAP. However, several disadvantages exist to limit the efficiency of these tools for accurate assessment in elderly CAP. Therefore, we aimed to explore a more comprehensive tool to predict mortality in elderly CAP population by establishing a nomogram model.MethodsWe retrospectively analyzed elderly patients with CAP in Minhang Hospital, Fudan University. The least absolute shrinkage and selection operator (LASSO) logistic regression combined with multivariate analyses were used to select independent predictive factors and established nomogram models via R software. Calibration plots, decision curve analysis (DCA) and receiver operating characteristic curve (ROC) were generated to assess predictive performance.ResultsLASSO and multiple logistic regression analyses showed the age, pulse, NLR, albumin, BUN, and D-dimer were independent risk predictors. A nomogram model (NB-DAPA model) was established for predicting mortality of CAP in elderly patients. In both training and validation set, the area under the curve (AUC) of the NB-DAPA model showed superiority than CURB-65 and qSOFA. Meanwhile, DCA revealed that the predictive model had significant net benefits for most threshold probabilities.ConclusionOur established NB-DAPA nomogram model is a simple and accurate tool for predicting in-hospital mortality of CAP, adapted for patients aged 65 years and above. The predictive performance of the NB-DAPA model was better than PSI, CURB-65 and qSOFA.
Global, regional, and national burden of Alzheimer's disease and other dementias, 1990–2019
Authors: Li Xue , Feng Xiaojin , Sun Xiaodong , Hou Ningning , Han Fang , Liu Yongping 
Published: October 2022

BackgroundWith the increase in the aging population worldwide, Alzheimer's disease has become a rapidly increasing public health concern. Monitoring the dementia disease burden will support health development strategies by providing scientific data.MethodsBased on the data obtained from the 2019 Global Burden of Disease (GBD) database, the numbers and age-standardized rates (ASRs) of incidence, prevalence, death, and disability-adjusted life-years (DALYs) of Alzheimer's disease and other dementias from 1990 to 2019 were analyzed. Calculated estimated annual percentage changes (EAPCs) and Joinpoint regression analyses were performed to evaluate the trends during this period. We also evaluated the correlations between the epidemiology and the sociodemographic index (SDI), an indicator to evaluate the level of social development in a country or region considering the education rate, economic situation, and total fertility rate.ResultsFrom 1990 to 2019, the incidence and prevalence of Alzheimer's disease and other dementias increased by 147.95 and 160.84%, respectively. The ASR of incidence, prevalence, death, and DALYs in both men and women consistently increased over the study period. All the ASRs in women were consistently higher than those in men, but the increases were more pronounced in men. In addition, the ASRs of incidence, prevalence, and DALYs were positively correlated with the SDI. Moreover, the proportion of patients over 70 years old with dementia was also positively correlated with the SDI level. Smoking was a major risk factor for the disease burden of dementia in men, while obesity was the major risk factor for women.ConclusionFrom 1990 to 2019, the Alzheimer's disease burden increased worldwide. This trend was more serious in high-SDI areas, especially among elderly populations in high-SDI areas, who should receive additional attention. Policy-makers should take steps to reverse this situation. Notably, women were at a higher risk for the disease, but the risk in men showed a faster increase. We should give attention to the aging population, attach importance to interventions targeting dementia risk factors, and formulate action plans to address the increasing incidence of dementia.
Functional topologies of spatial cognition predict cognitive and motor progression in Parkinson’s
Authors: Harrington Deborah L. , Shen Qian , Wei Xiangyu , Litvan Irene , Huang Mingxiong , Lee Roland R. 
Published: October 2022

BackgroundSpatial cognition deteriorates in Parkinson’s disease (PD), but the neural substrates are not understood, despite the risk for future dementia. It is also unclear whether deteriorating spatial cognition relates to changes in other cognitive domains or contributes to motor dysfunction.ObjectiveThis study aimed to identify functional connectivity abnormalities in cognitively normal PD (PDCN) in regions that support spatial cognition to determine their relationship to interfacing cognitive functions and motor disability, and to determine if they predict cognitive and motor progression 2 years later in a PDCN subsample.MethodsSixty-three PDCN and 43 controls underwent functional MRI while judging whether pictures, rotated at various angles, depicted the left or right hand. The task activates systems that respond to increases in rotation angle, a proxy for visuospatial difficulty. Angle-modulated functional connectivity was analyzed for frontal cortex, posterior cortex, and basal ganglia regions.ResultsTwo aberrant connectivity patterns were found in PDCN, which were condensed into principal components that characterized the strength and topology of angle-modulated connectivity. One topology related to a marked failure to amplify frontal, posterior, and basal ganglia connectivity with other brain areas as visuospatial demands increased, unlike the control group (control features). Another topology related to functional reorganization whereby regional connectivity was strengthened with brain areas not recruited by the control group (PDCN features). Functional topologies correlated with diverse cognitive domains at baseline, underscoring their influences on spatial cognition. In PDCN, expression of topologies that were control features predicted greater cognitive progression longitudinally, suggesting inefficient communications within circuitry normally recruited to handle spatial demands. Conversely, stronger expression of topologies that were PDCN features predicted less longitudinal cognitive decline, suggesting functional reorganization was compensatory. Parieto-occipital topologies (control features) had different prognostic implications for longitudinal changes in motor disability. Expression of one topology predicted less motor decline, whereas expression of another predicted increased postural instability and gait disturbance (PIGD) feature severity. Concurrently, greater longitudinal decline in spatial cognition predicted greater motor and PIGD feature progression, suggesting deterioration in shared substrates.ConclusionThese novel discoveries elucidate functional mechanisms of visuospatial cognition in PDCN, which foreshadow future cognitive and motor disability.
Modulating swallowing-related functional connectivity and behavior via modified pharyngeal electrical stimulation: A functional near-infrared spectroscopy evidence
Authors: Zhang Xue , Xie Hui , Wang Xiaolu , Li Zengyong , Song Rong , Shan Yilong , Li Chao , Chen Jiemei , Hong Jiena , Li Xin , Wan Guifang , Zhang Yaowen , An Delian , Dou Zulin , Wen Hongmei 
Published: October 2022

IntroductionModified pharyngeal electrical stimulation (mPES) is a novel therapeutic modality for patients with neurogenic dysphagia. However, the underlying neural mechanism remains poorly understood. This study aimed to use functional near-infrared spectroscopy (fNIRS) to explore the influence of mPES on swallowing-related frequency-specific neural networks and ethology.MethodsTwenty-two healthy right-handed volunteers participated in the study. Each participant was randomly assigned to either the sham or the mPES group and provided a 10-min intervention program every day for 5 days. Oxyhemoglobin and deoxyhemoglobin concentration changes verified by fNIRS were recorded on days 1, 3, and 5. Five characteristic frequency signals (0.0095–2 Hz) were identified using the wavelet transform method. To calculate frequency-specific functional connectivity, wavelet phase coherence (WPCO) was adopted. Furthermore, behavioral performance was assessed pre- and post-mPES using a 150 ml-water swallowing stress test.ResultsCompared with sham stimulation on day 1, the significantly decreased WPCO values were mainly associated with the dorsolateral prefrontal lobe, Broca's area, and middle temporal lobe. Compared with the sham mPES on day 1, the mPES showed a noticeable effect on the total swallow duration. Compared with the baseline, the WPCO values on days 3 and 5 showed a stepwise decrease in connectivity with the application of mPES. Furthermore, the decreased WPCO was associated with a shortened time per swallow after mPES.ConclusionsThe mPES could modulate swallowing-related frequency-specific neural networks and evoke swallowing cortical processing more efficiently. This was associated with improved performance in a water swallowing stress test in healthy participants.