bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated Analysis of Energy Metabolism Signature-Identified Distinct Subtypes of Bladder Urothelial Carcinoma
Authors: Zhang Fan , Liang Jiayu , Feng Dechao , Liu Shengzhuo , Wu Jiapei , Tang Yongquan , Liu Zhihong , Lu Yiping , Wang Xianding , Wei Xin 
Published: February 2022

Background: Bladder urothelial carcinoma (BLCA) is the most common type of bladder cancer. In this study, the correlation between the metabolic status and the outcome of patients with BLCA was evaluated using data from the Cancer Genome Atlas and Gene Expression Omnibus datasets.Methods: The clinical and transcriptomic data of patients with BLCA were downloaded from the Cancer Genome Atlas and cBioPortal datasets, and energy metabolism-related gene sets were obtained from the Molecular Signature Database. A consensus clustering algorithm was then conducted to classify the patients into two clusters. Tumor prognosis, clinicopathological features, mutations, functional analysis, ferroptosis status analysis, immune infiltration, immune checkpoint-related gene expression level, chemotherapy resistance, and tumor stem cells were analyzed between clusters. An energy metabolism-related signature was further developed and verified using data from cBioPortal datasets.Results: Two clusters (C1 and C2) were identified using a consensus clustering algorithm based on an energy metabolism-related signature. The patients with subtype C1 had more metabolism-related pathways, different ferroptosis status, higher cancer stem cell scores, higher chemotherapy resistance, and better prognosis. Subtype C2 was characterized by an increased number of advanced BLCA cases and immune-related pathways. Higher immune and stromal scores were also observed for the C2 subtype. A signature containing 16 energy metabolism-related genes was then identified, which can accurately predict the prognosis of patients with BLCA.Conclusion: We found that the energy metabolism-associated subtypes of BLCA are closely related to the immune microenvironment, immune checkpoint-related gene expression, ferroptosis status, CSCs, chemotherapy resistance, prognosis, and progression of BLCA patients. The established energy metabolism-related gene signature was able to predict survival in patients with BLCA.
Insights Into the Impact of Small RNA SprC on the Metabolism and Virulence of Staphylococcus aureus
Authors: Zhou Jingwen , Zhao Huanqiang , Yang Han , He Chunyan , Shu Wen , Cui Zelin , Liu Qingzhong 
Published: February 2022

AimOur previous proteomic analysis showed that small RNA SprC (one of the small pathogenicity island RNAs) of Staphylococcus aureus possesses the ability to regulate the expression of multiple bacterial proteins. In this study, our objective was to further provide insights into the regulatory role of SprC in gene transcription and metabolism of S. aureus.MethodsGene expression profiles were obtained from S. aureus N315 wild-type and its sprC deletion mutant strains by RNA-sequencing (RNA-seq), and differentially expressed genes (DEGs) were screened by R language with a |log2(fold change)| ≥1 and a false discovery rate (FDR) ≤ 0.05. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out to understand the significance of the DEGs. The quality of RNA-seq was further verified by quantitative real-time PCR (qRT-PCR), mRNA target prediction, metabolomics analysis and transcript-level expression analysis of genes of sprC complementation strain.ResultsA total of 2497 transcripts were identified, of which 60 transcripts expressions in sprC knockout strain were significantly different (37 up-regulated and 23 down-regulated DEGs). GO analysis showed that the functions of these DEGs were mainly concentrated in the biological process and molecular function related to metabolism and pathogenesis, and a higher number of genes were involved in the oxidation-reduction process, catalytic activity and binding. KEGG pathways enrichment analysis demonstrated that metabolism and pathogenesis were the most affected pathways, such as metabolic pathways, biosynthesis of secondary metabolites, purine metabolism, fructose and mannose metabolism and S. aureus infection. The qRT-PCR results of the DEGs with defined functions in the sprC deletion and complementation strains were in general agreement with those obtained by RNA-seq. Metabolomics analysis revealed 77 specific pathways involving metabolic pathways. Among them, many, such as metabolic pathways, biosynthesis of secondary metabolites and purine metabolism, were consistent with those enriched in the RNA-seq analysis.ConclusionThis study offered valuable and reliable information about the regulatory roles of SprC in S. aureus biology through transcriptomics and metabolomics analysis. These results may provide clues for new potential targets for anti-virulence adjuvant therapy on S. aureus infection.
Under-Ice Light Field in the Western Arctic Ocean During Late Summer
Authors: Veyssière Gaëlle , Castellani Giulia , Wilkinson Jeremy , Karcher Michael , Hayward Alexander , Stroeve Julienne C. , Nicolaus Marcel , Kim Joo-Hong , Yang Eun-Jin , Valcic Lovro , Kauker Frank , Khan Alia L. , Rogers Indea , Jung Jinyoung 
Published: February 2022

The Arctic is no longer a region dominated by thick multi-year ice (MYI), but by thinner, more dynamic, first-year-ice (FYI). This shift towards a seasonal ice cover has consequences for the under-ice light field, as sea-ice and its snow cover are a major factor influencing radiative transfer and thus, biological activity within- and under the ice. This work describes in situ measurements of light transmission through different types of sea-ice (MYI and FYI) performed during two expeditions to the Chukchi sea in August 2018 and 2019, as well as a simple characterisation of the biological state of the ice microbial system. Our analysis shows that, in late summer, two different states of FYI exist in this region: 1) FYI in an enhanced state of decay, and 2) robust FYI, more likely to survive the melt season. The two FYI types have different average ice thicknesses: 0.74 ± 0.07 m (N = 9) and 0.93 ± 0.11 m (N = 9), different average values of transmittance: 0.15 ± 0.04 compared to 0.09 ± 0.02, and different ice extinction coefficients: 1.49 ± 0.28 and 1.12 ± 0.19 m−1. The measurements performed over MYI present different characteristics with a higher average ice thickness of 1.56 ± 0.12 m, lower transmittance (0.05 ± 0.01) with ice extinction coefficients of 1.24 ± 0.26 m−1 (N = 12). All ice types show consistently low salinity, chlorophyll a concentrations and nutrients, which may be linked to the timing of the measurements and the flushing of melt-water through the ice. With continued Arctic warming, the summer ice will continue to retreat, and the decayed variant of FYI, with a higher scattering of light, but a reduced thickness, leading to an overall higher light transmittance, may become a more relevant ice type. Our results suggest that in this scenario, more light would reach the ice interior and the upper-ocean.
Determination of Soil Cadmium Threshold for Potato
Authors: Li Wei , He Xue , Zhang Jie , Liu Ke 
Published: February 2022

In this study, pot experiments were conducted to investigate the characteristics of Cd transfer to potato tubers from two types of soil. The results showed that the Log-normal and Burr III functions can be used to determine the sensitivity of different potato varieties to Cd as well as the soil Cd threshold. With regard to the prediction accuracy, the root mean squared error (RMSE) values for the total Cd biaoaccumulation factor (BAFtotal) calculated with both functions were smaller than those for exogenous Cd biaoaccumulation (BAFadd) in acidic and alkaline soils, indicating that BAFtotal is more appropriate for the calculation of the soil Cd threshold. The average Cd threshold values in acidic soil calculated with the Log-normal and Burr III functions were 0.411 and 0.461 mg kg−1, and the average values in alkaline soil were 0.716 and 0.888, respectively. The Log-normal function can also be applied to fit the sensitivity distributions of different species for the development of appropriate soil Cd threshold values for conservation purposes.
CircATRNL1 and circZNF608 Inhibit Ovarian Cancer by Sequestering miR-152-5p and Encoding Protein
Authors: Lyu Mengmeng , Li Xiujuan , Shen Yang , Lu Jin , Zhang Lihua , Zhong Shanliang , Wang Jinhua 
Published: February 2022

Background: CircRNAs have been found to be involved in the pathogenesis of various diseases. We aimed to explore the roles of circRNAs in ovarian cancer.Methods: The expression levels of circRNAs in ovarian cancer and normal ovarian tissues were analyzed using RNA sequencing. Fluorescent in situ hybridization (FISH), proliferation assays and transwell assays were used to assess the effects of circRNAs on ovarian cancer.Results: CircATRNL1 and circZNF608 were downregulated in 20 ovarian cancer tissues compared to normal tissues. CircATRNL1 and circZNF608 are mainly located in the cytoplasm of ovarian cancer cells, and circATRNL1 is a highly conserved circRNA. The overexpression of circATRNL1 and circZNF608 inhibits the proliferation and invasion of ovarian cancer cells. We predicted miRNA–circRNA interactions for circZNF608 and circATRNL1 and obtained 63 interactions. However, a luciferase reporter assay showed that only miR-152-5p was sequestered by circZNF608. Bioinformatics analysis and experiments indicated that circATRNL1 contains an internal ribosome entry site and an open reading frame encoding a 131 aa protein.Conclusion: In conclusion, circATRNL1 and circZNF608 are two downregulated circRNAs in ovarian cancer and work as tumor suppressors. CircZNF608 may exert antitumor activity in ovarian cancer by binding miR-152-5p, and circATRNL1 may encode a 131 aa protein.
The Antibody Assay in Suspected Autoimmune Encephalitis From Positive Rate to Test Strategies
Authors: Deng Qun , Liu Ye , Mao Zhifeng , Chen Yun , Ping Yue , Zhu Guoqiang , Zhao Weiqing , Hu Xiao , Zhou Hao 
Published: February 2022

ObjectiveThe aim of this study was to analyze the positive rate and test strategies of suspected autoimmune encephalitis (SAE) based on an antibody assay.MethodsPatients who were diagnosed with suspected autoimmune encephalitis in Guizhou Province between June 1, 2020, and June 30, 2021 and who had anti-neuronal autoantibodies detected by Guizhou KingMed Diagnostics Group Co., Ltd. were included in this study. The positive rate and the test strategies were analyzed based on the results of the anti-neuronal antibody assay.ResultsA total of 263 patients with SAE were included, 58.2% (153/263) of whom were males, with a median age of 33 years (1-84 years). 84% (221/263) of all patients completed both serum and CSF tests. A total of 46.0% (121/263) of SAE patients received the AE-6 examination package. The antibody-positive rate was 9.9% (26/263) in the current cohort, with an observed incidence of antibody positive of 0.2 in 100,000 (26/11,570,000, 95% CI: 0.15-0.30), and the estimated incidence was 0.9 in 100,000 (95% CI: 0.84-0.95) of the total population. A total of 9 different anti-neuronal antibodies were detected. Anti-NMDAR antibody was the most common antibody in 46.2% (12/26) of subjects, 70.0% (7/10) of whom were children, followed by anti-Caspr2 antibody in 30.8% (8/26); the remaining 7 antibodies were detected in 23.1% (6/26) of the population. There were no obvious differences among age, sex or season in the positive rate of anti-neuronal antibodies. The cost of antibody testing per capita was $439.30 (SD±$195.10). The total cost of AE-14 was the highest at $48.016.81 (41.56%) among all examination packages.ConclusionsThis study described the positive rate associated with AE-related anti-neuronal antibodies and test strategies in the current cohort, which provides a basis for clinicians in clinical practice.
Acute Symptomatic Seizures and Risk of Epilepsy in Autoimmune Encephalitis: A Retrospective Cohort Study
Authors: Zhong Rui , Zhang Xinyue , Chen Qingling , Li Mengmeng , Guo Xin , Lin Weihong 
Published: February 2022

PurposeTo investigate the clinical characteristics of acute symptomatic seizures and the predictors of the development of epilepsy in patients with anti-NMDAR, anti-LGI1, and anti-GABABR encephalitis.MethodsWe retrospectively screened the medical records of 86 hospitalized patients with confirmed autoimmune encephalitis (AE). The clinical characteristics of acute symptomatic seizures were analyzed. The predictors of the development of epilepsy were investigated using logistic regression analysis.ResultsA total of 86 patients with AE were finally included. Eighty-six percent of patients (n = 74) experienced acute symptomatic seizures, and 28.4% of patients developed epilepsy during follow-up. Abnormal EEG findings were more frequent in AE patients with acute symptomatic seizures. A greater number of anti-seizure medications (ASMs), abnormal EEG findings, and delayed immunotherapy were found to be independently associated with the development of epilepsy.ConclusionAcute symptomatic seizures are a common manifestation in AE patients. During follow-up, 28.4% of AE patients developed epilepsy. The independent factors that predicted the development of epilepsy after the acute phase included a larger number of ASMs, EEG abnormalities, and delayed immunotherapy. In clinical practice, we should prioritize immunotherapy to control acute seizures as soon as possible. For AE patients with an increased risk of developing epilepsy, early withdrawal of ASM is not recommended.
Restoration of Default Blood Monocyte-Derived Macrophage Polarization With Adalimumab But Not Etanercept in Rheumatoid Arthritis
Authors: Paoletti Audrey , Ly Bineta , Bitoun Samuel , Nocturne Gaëtane , Rivière Elodie , Manson Jessica J. , Matucci Andrea , Pallardy Marc , De Vries Niek , Mariette Xavier 
Published: February 2022

IntroductionWe previously reported a specific defect of rheumatoid arthritis (RA) monocyte polarization to anti-inflammatory M2-like macrophages related to increased miR-155 expression in all RA patients except those receiving adalimumab (ADA). In this longitudinal study, we examined whether different tumor necrosis factor inhibitors were able to restore monocyte polarization to M2-like macrophages and their effect on the transcriptomic signature.MethodsM2-like polarization induced by human serum AB was studied in 7 healthy donors and 20 RA patients included in the ABIRA cohort before and 3 months after starting ADA or etanercept (ETA). The differential gene expression of M2- and M1-related transcripts was studied in macrophage-derived monocytes after differentiation.ResultsAt baseline, RA monocytes showed a defect of polarization to M2-like macrophages as compared with healthy donor monocytes, which was negatively correlated with disease activity. M2-like polarization from circulating monocytes was restored only with ADA and not ETA treatment. The transcriptomic signature demonstrated downregulation of M2-related transcripts and upregulation of M1-related transcripts in active RA. In patients receiving ADA, the transcriptomic signature of M2-related transcripts was restored.ConclusionThis longitudinal study demonstrates that ADA but not ETA is able to restore the M2-like polarization of monocytes that is defective in RA.
Severe Bilateral Hyperkeratosis of the Nipples and Areolae: A Case Report and Literature Review
Authors: Wei Jiaying , Li Qingshu , Wu He , Yin Xuedong , Ren Guosheng 
Published: February 2022

BackgroundHyperkeratosis of the nipple and areola (HNA) is a rare skin disease with unknown etiology. Some patients are misdiagnosed or never diagnosed, especially during the early stage of this disease. In addition, the mechanism involved in the development of HNA is still unknown, and genomic alterations have not been reported anywhere.Case InformationA 26-year-old female suffered gradual bilateral areola thickening and enlargement, with accompanying intense itching, and was diagnosed with HNA at the First Affiliated Hospital of Chongqing Medical University. No obvious abnormalities were found in laboratory test examinations such as hormone testing for estrogen, progesterone, or prolactin. Typical papillomatous skin with orthokeratotic hyperkeratosis and numerous infiltrating lymphocytes was detected through a histopathological examination. The results from RNA-sequencing showed that the molecular expression between HNA and a normal nipple and areola (NNA) was obviously different. No significant difference was found in the bilateral lesions. In addition, immune-related cell signaling pathways were overactivated in HNA compared to the control HNA.ConclusionThe typical symptoms, clinical features, and histopathological alterations presented in this case lead to a profound understanding of HNA, which can avoid the misdiagnosis and missed diagnosis of this disease at an early stage. The dysfunction of the local immune system, which was demonstrated by pathological examination and genomic analysis, suggests that anti-autoimmune therapy, such as steroid medication, may be an effective treatment for HNA at an early stage.
Machine-Learning Approaches for Predicting the Need of Oxygen Therapy in Early-Stage COVID-19 in Japan: Multicenter Retrospective Observational Study
Authors: Yamanaka Syunsuke , Morikawa Koji , Azuma Hiroyuki , Yamanaka Maki , Shimada Yoshimitsu , Wada Toru , Matano Hideyuki , Yamada Naoki , Yamamura Osamu , Hayashi Hiroyuki 
Published: February 2022

BackgroundEarly prediction of oxygen therapy in patients with coronavirus disease 2019 (COVID-19) is vital for triage. Several machine-learning prognostic models for COVID-19 are currently available. However, external validation of these models has rarely been performed. Therefore, most reported predictive performance is optimistic and has a high risk of bias. This study aimed to develop and validate a model that predicts oxygen therapy needs in the early stages of COVID-19 using a sizable multicenter dataset.MethodsThis multicenter retrospective study included consecutive COVID-19 hospitalized patients confirmed by a reverse transcription chain reaction in 11 medical institutions in Fukui, Japan. We developed and validated seven machine-learning models (e.g., penalized logistic regression model) using routinely collected data (e.g., demographics, simple blood test). The primary outcome was the need for oxygen therapy (≥1 L/min or SpO2 ≤ 94%) during hospitalization. C-statistics, calibration slope, and association measures (e.g., sensitivity) evaluated the performance of the model using the test set (randomly selected 20% of data for internal validation). Among these seven models, the machine-learning model that showed the best performance was re-evaluated using an external dataset. We compared the model performances using the A-DROP criteria (modified version of CURB-65) as a conventional method.ResultsOf the 396 patients with COVID-19 for the model development, 102 patients (26%) required oxygen therapy during hospitalization. For internal validation, machine-learning models, except for the k-point nearest neighbor, had a higher discrimination ability than the A-DORP criteria (P &lt; 0.01). The XGboost had the highest c-statistic in the internal validation (0.92 vs. 0.69 in A-DROP criteria; P &lt; 0.001). For the external validation with 728 temporal independent datasets (106 patients [15%] required oxygen therapy), the XG boost model had a higher c-statistic (0.88 vs. 0.69 in A-DROP criteria; P &lt; 0.001).ConclusionsMachine-learning models demonstrated a more significant performance in predicting the need for oxygen therapy in the early stages of COVID-19.
Computer-Aided Diagnosis of Spinal Tuberculosis From CT Images Based on Deep Learning With Multimodal Feature Fusion
Authors: Li Zhaotong , Wu Fengliang , Hong Fengze , Gai Xiaoyan , Cao Wenli , Zhang Zeru , Yang Timin , Wang Jiu , Gao Song , Peng Chao 
Published: February 2022

BackgroundSpinal tuberculosis (TB) has the highest incidence in remote plateau areas, particularly in Tibet, China, due to inadequate local healthcare services, which not only facilitates the transmission of TB bacteria but also increases the burden on grassroots hospitals. Computer-aided diagnosis (CAD) is urgently required to improve the efficiency of clinical diagnosis of TB using computed tomography (CT) images. However, classical machine learning with handcrafted features generally has low accuracy, and deep learning with self-extracting features relies heavily on the size of medical datasets. Therefore, CAD, which effectively fuses multimodal features, is an alternative solution for spinal TB detection.MethodsA new deep learning method is proposed that fuses four elaborate image features, specifically three handcrafted features and one convolutional neural network (CNN) feature. Spinal TB CT images were collected from 197 patients with spinal TB, from 2013 to 2020, in the People’s Hospital of Tibet Autonomous Region, China; 3,000 effective lumbar spine CT images were randomly screened to our dataset, from which two sets of 1,500 images each were classified as tuberculosis (positive) and health (negative). In addition, virtual data augmentation is proposed to enlarge the handcrafted features of the TB dataset. Essentially, the proposed multimodal feature fusion CNN consists of four main sections: matching network, backbone (ResNet-18/50, VGG-11/16, DenseNet-121/161), fallen network, and gated information fusion network. Detailed performance analyses were conducted based on the multimodal features, proposed augmentation, model stability, and model-focused heatmap.ResultsExperimental results showed that the proposed model with VGG-11 and virtual data augmentation exhibited optimal performance in terms of accuracy, specificity, sensitivity, and area under curve. In addition, an inverse relationship existed between the model size and test accuracy. The model-focused heatmap also shifted from the irrelevant region to the bone destruction caused by TB.ConclusionThe proposed augmentation effectively simulated the real data distribution in the feature space. More importantly, all the evaluation metrics and analyses demonstrated that the proposed deep learning model exhibits efficient feature fusion for multimodal features. Our study provides a profound insight into the preliminary auxiliary diagnosis of spinal TB from CT images applicable to the Tibetan area.