bluuebunny/crossref_metadata_2025_split huggingface dataset:
An artificial intelligence network‐guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms
Authors: Zhang Nan , Zhang Hao , Liu Zaoqu , Dai Ziyu , Wu Wantao , Zhou Ran , Li Shuyu , Wang Zeyu , Liang Xisong , Wen Jie , Zhang Xun , Zhang Bo , Ouyang Sirui , Zhang Jian , Luo Peng , Li Xizhe , Cheng Quan 
Published: February 2023

AbstractThe immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes‐based model remains largely unknown. In the current study, by analysing single‐cell RNA sequencing (scRNA‐seq) data and bulk RNA sequencing data, the tumour‐infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and—most significantly—immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification.
A Machine Learning Approach for the Simultaneous Detection of Preknowledge in Examinees and Items When Both Are Unknown
Authors: Pan Yiqin , Wollack James A. 
Published: February 2023

AbstractPan and Wollack (PW) proposed a machine learning method to detect compromised items. We extend the work of PW to an approach detecting compromised items and examinees with item preknowledge simultaneously and draw on ideas in ensemble learning to relax several limitations in the work of PW. The suggested approach also provides a confidence score, which is based on an autoencoder to represent our confidence that the detection result truly corresponds to item preknowledge. Simulation studies indicate that the proposed approach performs well in the detection of item preknowledge, and the confidence score can provide helpful information for users.
An automated epileptic seizure detection using optimized neural network from EEG signals
Authors: Chanu Maibam Mangalleibi , Singh Ngangbam Herojit , Thongam Khelchandra 
Published: February 2023

AbstractAmong the central nervous system (neurological) disorders, epilepsy is considered to be a dangerous and chronic disorder that causes recurring seizures, showing unusual behaviour for some period of time, shaking of hands and legs, loss of sensation and awareness. It occurs when electrical activities in the brain become abnormal. The test performed in order to detect epileptic seizures is known as electroencephalograph (EEG) signal test which is conducted by analysing the electrical impulses in the brain. The manual identification process of EEG brain signals is time consuming and a laborious task. So the neurologists may sometimes give a varying result which may affect the performance of detecting epileptic seizures. The combination of manual identification of the signal and machine learning technique will be able to provide a correct result in a confusion situation reducing analytic and therapeutic errors that are unavoidable in human clinical practice. The existing approaches of detection of epileptic seizures cannot correctly train their network if the size of the dataset is very large thus obtaining lower classification accuracy. An optimized neural network technique is proposed in this work for automatic detection of Epileptic seizure using EEG signals of the brain. The EEG signals are used for feature extraction by applying Discrete Wavelet Transform (DWT). Using the extracted features, input samples are created and then fed to a hybrid model which is a combination of self‐organizing neural network (SONN) and multilayer perceptron (MLP) trained with a genetic algorithm (GA). This model acts as a classifier for detecting Epileptic seizures by classifying the samples into two classes namely Non‐Epileptic and Epileptic class. Clustering is performed first for the large dataset samples using SONN and for each cluster, an MLP‐GA network is used to train the samples belonging to the same cluster. Performing clustering helps to correctly train the MLP networks for obtaining high classification accuracy. GA has been specifically chosen as a learning algorithm instead of Backpropagation (BP) algorithm for MLP because GA can find the global minima thus solving the local minima problem faced by BP algorithm. The performance measures are evaluated thereby achieving precision value of 98%, recall value of 100%, F1 score value of 98.99% and an overall accuracy of 99.2%. The proposed hybrid method using SONN and MLP‐GA has more potential to classify the EEG signals.
Breaking self‐regulation of Regnase‐1 promotes its own protein expression
Authors: Piboonprai Kitiya , Millius Arthur , Shimoda Mayuko , Tanaka Hiroki , Akira Shizuo , Maeda Kazuhiko 
Published: February 2023

AbstractThe RNA‐binding protein (RBP) Regnase‐1 is an endonuclease that regulates immune responses by modulating target mRNA stability. Regnase‐1 degrades a group of inflammation‐associated mRNAs, which contributes to a balanced immune response and helps prevent autoimmune diseases. Regnase‐1 also cleaves its own mRNA by binding stem‐loop (SL) RNA structures in its 3′UTR. To understand how this autoregulation is important for immune responses, we generated mice with a 2‐bp genome deletion in the target SL of the Regnase‐1 3′‐untranslated region (3′UTR). Deletion of these nucleotides inhibited SL formation and limited Regnase‐1‐mediated mRNA degradation. Mutant mice had normal hematopoietic cell differentiation. Biochemically, mutation of the 3′UTR SL increased Regnase‐1 mRNA stability and enhanced both Regnase‐1 mRNA and protein levels in mouse embryonic fibroblasts (MEFs). The expression of Il6, a Regnase‐1 target gene, was constitutively suppressed at steady‐state in mutant MEFs. Additionally, Regnase‐1 protein expression in mutant MEFs was significantly elevated compared to that in wild‐type MEFs at steady state and upon proinflammatory cytokine stimulation. These data suggest a negative feedback mechanism for Regnase‐1 expression and represent a unique mouse model to probe Regnase‐1 overexpression in vivo.
Development of transgenic corn planthopper Peregrinus maidis that express the tetracycline transactivator
Authors: Patil Anandrao A. , Klobasa William , Espinoza‐Rivera Dina , Baars Oliver , Lorenzen Marcé D. , Scott Maxwell J. 
Published: February 2023

AbstractThe corn planthopper, Peregrinus maidis, is a vector of several maize viruses and is consequently a significant agricultural pest in many tropical and subtropical regions. As P. maidis has developed resistance to insecticides, the aim of this study was to develop transgenic P. maidis strains that could be used for future genetic biocontrol programs. To facilitate the identification of transgenic P. maidis, we isolated and characterized the promoters for the P. maidis ubiquitin‐like and profilin genes. Transient expression assays with P. maidis embryos showed that both promoters were active. Transgenic lines were established using piggyBac vectors and fluorescent protein marker genes. The lines carried an auto‐regulated tetracycline transactivator (tTA) gene, which has been widely used to establish conditional lethal strains in other insect species. The transgenic lines showed low levels of tTA expression but were viable on diet with or without doxycycline, which inhibits the binding of tTA to DNA. We discuss possible modifications to the tTA overexpression system that could lead to the successful development of conditional lethal strains. To our knowledge, this is the first report of a transgenic Hemiptera. The approach we have taken could potentially be applied to other Hemiptera and, for P. maidis, the technology will facilitate future functional genomics studies.
T‐cell activation–induced marker assays in health and disease
Authors: Poloni Chad , Schonhofer Cole , Ivison Sabine , Levings Megan K , Steiner Theodore S , Cook Laura 
Published: February 2023

AbstractActivation‐induced marker (AIM) assays have proven to be an accessible and rapid means of antigen‐specific T‐cell detection. The method typically involves short‐term incubation of whole blood or peripheral blood mononuclear cells with antigens of interest, where autologous antigen‐presenting cells process and present peptides in complex with major histocompatibility complex (MHC) molecules. Recognition of peptide–MHC complexes by T‐cell receptors then induces upregulation of activation markers on the T cells that can be detected by flow cytometry. In this review, we highlight the most widely used activation markers for assays in the literature while identifying nuances and potential downfalls associated with the technique. We provide a summary of how AIM assays have been used in both discovery science and clinical studies, including studies of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) immunity. This review primarily focuses on AIM assays using human blood or peripheral blood mononuclear cell samples, with some considerations noted for tissue‐derived T cells and nonhuman samples. AIM assays are a powerful tool that enables detailed analysis of antigen‐specific T‐cell frequency, phenotype and function without needing to know the precise antigenic peptides and their MHC restriction elements, enabling a wider analysis of immunity generated following infection and/or vaccination.
PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma
Authors: He Kang , Wang Taiwei , Huang Xuemiao , Yang Zhaoyun , Wang Zeyu , Zhang Shuang , Sui Xin , Jiang Junjie , Zhao Lijing 
Published: February 2023

AbstractUterine corpus endometrial carcinoma (UCEC) is one of the most common malignancies of the female genital tract. A recently discovered protein‐coding gene, PPP1R14B, can inhibit protein phosphatase 1 (PP1) as well as different PP1 holoenzymes, which are important proteins regulating cell growth, the cell cycle, and apoptosis. However, the association between PPP1R14B expression and UCEC remains undefined. The expression profiles of PPP1R14B in multiple cancers were analysed based on TCGA and GTE databases. Then, PPP1R14B expression in UCEC was investigated by gene differential analysis and single gene correlation analysis. In addition, we performed gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, gene set enrichment analysis, and Kaplan–Meier survival analysis to predict the potential function of PPP1R14B and its role in the prognosis of UCEC patients. Then, a tool for predicting the prognosis of UCEC, namely, a nomogram model, was constructed. PPP1R14B expression was higher in UCEC tumour tissues than in normal tissues. The results revealed that PPP1R14B expression was indeed closely associated with tumour development. The results of Kaplan–Meier plotter data indicated that patients with high PPP1R14b expression had poorer overall survival, disease‐specific survival, and progression‐free interval than those with low expression. A nomogram based on the results of multifactor Cox regression was generated. PPP1R14B is a key player in UCEC progression, is associated with a range of adverse outcomes, and can serve as a prognostic marker in the clinic.
Preharvest fungicide treatments reduce the effective SO2 threshold of postharvest fumigation to control pathogens and maintain quality of “red globe” (Vitis vinifera) grapes
Authors: Jiang Yuqian , Zhang Lu , Li Xihong , Chen Lan , Yuan Junwei , Wang Haifen , Li Wenhan , Duan Lihua , Jiang Yunbin , Tang Yao 
Published: February 2023

AbstractSulfur dioxide (SO2) fumigation has been widely used to control pathogens and maintain the postharvest quality of table grapes. However, the effective dosage of SO2 treatment is close to causing bleaching damage on fruits. Further, the SO2 potential residue is a risk to human health. In this study, the dominant pathogens in “red globe” grapes during cold storage (0 and 10°C) were identified as Botrytis cinerea, Alternaria alternata, and Penicillium expansum, while Aspergillus niger was dominant pathogen when the grapes were stored at room temperature (25°C). The isolated dominant pathogens were effectively suppressed by SO2 ranging from 500 μl L−1 to 800 μl L−1, but bleaching spots were observed in grapes when SO2 was applied at 800 μl L−1. To reduce the SO2 residue, the fungicides dimethomorph and thiophanate‐methyl were respectively sprayed to control the epiphytic pathogens during the development of grape berries. In addition, the reduced microbial population contributed by fungicide treatments remitted the original density of postharvest microbial growth. The postharvest automated intermittent SO2 fumigation at 500 μl L−1 was subsequently integrated to control the microbial activities. In addition, SO2 maintained the soluble solid content and titratable acid content, which were 22% and 75% higher than the control (p < .05) on 120 days of storage. The inhibition percentage against dominant fungal pathogens by preharvest fungicides spray was approximately 30%, while the postharvest intermittent SO2 fumigation contributed about 50%. We investigated the suppression role of preharvest and postharvest combined treatment for the grapes, which was concluded as a promising application to reduce decay and extend the shelf life of “red globe” grapes.
Systolic blood pressure, antihypertensive treatment, and cardiovascular and mortality risk in VA nursing home residents
Authors: Liu Xiaojuan , Steinman Michael A. , Lee Sei J. , Peralta Carmen A. , Graham Laura A. , Li Yongmei , Jing Bocheng , Fung Kathy Z. , Odden Michelle C. 
Published: February 2023

AbstractBackgroundOptimal systolic BP (SBP) control in nursing home residents is uncertain, largely because this population has been excluded from clinical trials. We examined the association of SBP levels with the risk of cardiovascular (CV) events and mortality in Veterans Affairs (VA) nursing home residents on different numbers of antihypertensive medications.MethodsOur study included 36,634 residents aged ≥65 years with a VA nursing home stay of ≥90 days from October 2006–June 2019. SBP was averaged over the first week after admission and divided into categories. Cause‐specific hazard ratios (HRs) of SBP categories with CV events (primary outcome) and all‐cause mortality (secondary outcome) were examined using Cox regression and multistate modeling stratified by the number of antihypertensive medications used at admission (0, 1 or 2, and ≥3 medications).ResultsMore than 76% of residents were on antihypertensive therapy and 20% received ≥3 medications. In residents on antihypertensive therapy, a low SBP < 110 mmHg (compared with SBP 130 ~ 149 mmHg) was associated with a greater CV risk (adjusted HR [95% confidence interval]: 1.47 [1.28–1.68] in 1 or 2 medications group, and 1.41 [1.19–1.67] in ≥3 medications group). In residents on no antihypertensives, both low SBP < 110 mmHg and high SBP ≥ 150 mmHg were associated with higher mortality; while in residents receiving any antihypertensives, a low SBP was associated with higher mortality and the highest point estimates were for SBP < 110 mmHg (1.36 [1.28–1.45] in 1 or 2 medications group, and 1.47 [1.31–1.64] in ≥3 medications group).ConclusionsThe associations of SBP with CV and mortality risk varied by the intensity of antihypertensive treatment among VA nursing home residents. A low SBP among those receiving antihypertensives was associated with increased CV and mortality risk, and untreated high SBP was associated with higher mortality. More research is needed on the benefits and harms of SBP lowering in long‐term care populations.
Reporting accuracy of pressure injury categorisation in an acute tertiary hospital: A four‐year analysis
Authors: Fulbrook Paul , Lovegrove Josephine 
Published: February 2023

AbstractAimTo determine the reporting accuracy of pressure injury categorisation by bedside clinicians, compared with nurse experts.BackgroundPressure injuries are an enduring complication of hospitalisation. The categorisation of pressure injury affects treatment and management decision‐making and use of resources, and severe hospital‐acquired pressure injury incidence is used to benchmark quality of care. However, it is unclear how accurately pressure injuries are categorised by clinicians in practice.DesignSecondary analysis of hospital pressure injury incident and validation data.MethodsAll pressure injuries reported in adults between 2016 and 2019 that were subsequently validated by nurse experts were analysed. Absolute agreement is reported using percentages, with inter‐rater agreement reported using Kappa measure of agreement. The GRRAS reporting guideline was followed.ResultsOf 6186 pressure injuries that were analysed, the category was reported correctly in 67.3% (n = 4163), with an overall moderate level of inter‐rater agreement by category (Κ = .567, p < .001). Of those found to be non‐pressure injuries when validated (18.3%, n = 1129), most were reported originally as stage II (41.2%, n = 465) or stage I (30.5%, n = 344), and 13.4% (n = 151) were categorised initially as unstageable. The majority reported initially as stage I, stage II, suspected deep tissue injury or mucosal pressure injury were validated, whereas half of those reported initially as stage III or IV were validated and less than a third of those reported initially as unstageable pressure injuries were validated.ConclusionsThis study provides important insight into the accuracy of pressure injury categorisation. Whilst moderate agreement of categorisation was found between reporting clinicians and nurse experts, pressure injury differential diagnosis and categorisation of severe injuries were inadequate.Relevance to Clinical PracticeThese results may be used for benchmarking and provide a focal point for future education and practice improvement efforts.Patient or Public ContributionNeither patients nor the public were directly involved in the project.
Risk of severe disease and mortality of COVID‐19 in patients with Budd‐Chiari syndrome: A population‐based matched cohort study
Authors: Krishnan Arunkumar , Schneider Carolin V. , Schattenberg Jörn M. , Alqahtani Saleh A. 
Published: February 2023

AbstractBackground & AimsBudd‐Chiari syndrome (BCS) is a rare and potentially life‐threatening disorder characterized by obstruction of the hepatic outflow tract. It is unknown whether patients with BCS represent a high risk for severe disease and mortality from coronavirus disease 2019 (COVID‐19). Thus, we aimed to assess hospitalization rates, severe disease, all‐cause mortality, intensive care unit (ICU) requirement and acute kidney injury (AKI) from COVID‐19 diagnoses.Methods & ResultsWe identified 467 patients with BCS with COVID‐19, 96 427 non‐chronic liver disease (CLD) and 9652 non‐BCS CLD. The BCS and non‐CLD cohorts (n = 467 each) and BCS and non‐BCS CLD (n = 440 each) were well balanced after propensity matching. When compared to the non‐CLD cohort, the BCS group had a higher risk of all‐cause mortality (5.1% vs. 2.4%, HR 2.18; 95% CI, 1.08–4.40), severe disease (6.0% vs. 2.4%, HR 2.20; 95% CI, 1.09–4.43), hospitalization (24.6% vs. 13.1%, HR 1.77; 95% CI, 1.30–2.42) and AKI (7.9% vs. 2.8%, HR 2.57; 95% CI, 1.37–4.85), but no significant differences in ICU requirements (2.4% vs. 2.1%, HR 0.75; 95% CI, 0.27–2.08) at 60‐days time points. When compared to the non‐BCS CLD cohort, the BCS group had a higher risk of all‐cause mortality (3.6% vs. 2.5%, HR 3.94; 95% CI, 1.31–11.79), hospitalization (29.8% vs. 21.6%, HR 1.43; 95% CI, 1.09–1.86), but differences in ICU requirements (HR 0.90 (0.38–2.12)), AKI (HR 1.41 (0.86–2.30)) or severe disease (HR 1.92 (0.99–3.71)) did not reach statistical significance at 60‐day follow up.ConclusionIn conclusion, COVID‐19 infection in patients with BCS is associated with poor outcomes. Patients with BCS infected with COVID‐19 carry a significantly higher risk of hospitalization and all‐cause mortality and a possible effect on severe disease and AKI compared with COVID‐19 patients without CLD or with non‐BCS‐CLD.
Remote robotic system for 3D measurement of concrete damage in tunnel with ground vehicle and manipulator
Authors: Shim Seungbo , Lee Seong‐Won , Cho Gye‐Chun , Kim Jin , Kang Sung‐Mo 
Published: February 2023

AbstractTo ensure the safety of a concrete structure, periodic and accurate inspection for damage is necessary. However, there is a high risk of inaccurate diagnosis of the structure condition because the manual inspection method is dependent on operator experience and subjective judgment. Additionally, in future society, it may become increasingly difficult to maintain high‐quality infrastructure, as the number of inspection personnel will also decrease with a decrease in population. For this purpose, the demand for accurate and automated inspection technology is increasing. To meet these issues, in this study, an objective and automated inspection method is proposed by developing an inspection robot and management system. The inspection robot comprises an artificial intelligence sensor, a manipulator, and a ground vehicle; it can autonomously drive inside a tunnel and inspect the damage on concrete surfaces using stereo vision. The management system remotely controls the robot through wireless communication and monitors the inspection status in real time. In addition, damage is automatically restored in three dimensions based on the images, and the physical size of the damage is analyzed with an average relative error of 0.39%. This method is expected to be used as a core technology for unmanned and automated tunnel maintenance in the future.
CACNA1S mutation‐associated dental anomalies: A calcium channelopathy
Authors: Kantaputra P. , Butali A. , Eliason S. , Chalkley C. , Nakornchai S. , Bongkochwilawan C. , Kawasaki K. , Kumchiang A. , Ngamphiw C. , Tongsima S. , Ketudat Cairns J. R. , Olsen B. , Intachai W. , Ohazama A. , Tucker A. S. , Amendt B. A. 
Published: February 2023

AbstractObjectivesTo identify the molecular etiology of distinct dental anomalies found in eight Thai patients and explore the mutational effects on cellular functions.Materials and MethodsClinical and radiographic examinations were performed for eight patients. Whole exome sequencing, mutant protein modelling, qPCR, western blot analysis, scratch assays, immunofluorescence, confocal analysis, in situ hybridization, and scanning electron micrography of teeth were done.ResultsAll patients had molars with multiple supernumerary cusps, single‐cusped premolars, and a reduction in root number. Mutation analysis highlighted a heterozygous c.865A>G; p.Ile289Val mutation in CACNA1S in the patients. CACNA1S is a component of the slowly inactivating L‐type voltage‐dependent calcium channel. Mutant protein modeling suggested that the mutation might allow leakage of Ca2+ or other cations, or a tightening, to restrict calcium flow. Immunohistochemistry analysis showed expression of Cacna1s in the developing murine tooth epithelium during stages of crown and root morphogenesis. In cell culture, the mutation resulted in abnormal cell migration of transfected CHO cells compared to wildtype CACNA1S, with changes to the cytoskeleton and markers of focal adhesion.ConclusionsThe malformations observed in our patients suggest a role for calcium signaling in organization of both cusps and roots, affecting cell dynamics within the dental epithelium.