Frequency and treatment of venous thromboembolic events in patients with space-occupying brain infarction and decompressive craniectomy by Dominik Michalski, Dirk Lindner, Alhuda Dabbagh, Janine Mielke, Katja S Mühlberg, Karl Titus Hoffmann, Charlotte Huber, Johann Otto Pelz

“…Younger age, DC and cumulative duration of central venous catheter were identified as risk factors for VTE. Only three patients had major bleeding events while being anticoagulated (one asymptomatic cerebral and two extracranial bleedings).Discussion Patients with space-occupying brain infarction and DC hold a high risk for VTE. …”
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Changes in the composition of urine over six hours using urine dipstick analysis and automated microscopy by Pranav C. Parikh, Serena D. Souza, Wassim Obeid

“…Methods We obtained 15 mL of urine from the Foley catheters of five patients in the intensive care unit. …”
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Electrocardiogram Parameters That Affect the Success Rate of Radiofrequency Ablation in Patients with Outflow Tract Ventricular Premature Complexes by Zhen Ye, Zhe Xu, Kezeng Gong, Xuehai Chen, Weiwei Wang, Jianhua Chen, Lianglong Chen, Feilong Zhang

“…The objectives of this study are to assess the efficacy of radiofrequency catheter ablation (RFCA) in patients with outflow tract (OT) ventricular premature complexes (VPCs) and to explore the electrocardiographic (ECG) features of initially successful procedures. …”
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Combined surgical and interventional cardiology approach for central venous access salvage in children with intestinal failure: A case series by Emily Byrd, M. Jake Petersen, Minna M. Wieck, Frank Ing, Shinjiro Hirose

“…Long-term central venous access can be complicated by recurrent infections, catheter malfunction, and venous stricture and thrombosis. …”
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Identification and verification of autophagy-related gene signatures and their association with immune infiltration and drug responsiveness in epilepsy by Han-han He, Xiao-ge Zhang, Fen-fang Chen

“…However, the precise mechanisms by which autophagy deficiencies involved in epileptogenesis are still not fully understood.MethodsTwo datasets of epilepsy (GSE143272 and GSE256068) were downloaded from the Gene Expression Omnibus (GEO) database. …”
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Analysing DNA methylation and transcriptomic signatures to predict prostate cancer recurrence risk by Fahad M. Aldakheel, Hadeel Alnajran, Shatha A. Alduraywish, Ayesha Mateen, Mohammed S. Alqahtani, Rabbani Syed

“…This study employs a machine learning approach to identify DNA methylation and RNA expression biomarkers predictive of PCa recurrence using datasets from The Cancer Genome Atlas (TCGA). We analyzed 49,133 genes, identifying 684 differentially methylated genes (DMGs) and 691 differentially expressed genes (DEGs) between recurrence and non-recurrence groups. …”
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Social media discourse and internet search queries on cannabis as a medicine: A systematic scoping review. by Christine Mary Hallinan, Sedigheh Khademi Habibabadi, Mike Conway, Yvonne Ann Bonomo

“…It also demonstrates the need for the development of a systematic approach for evaluating the quality of social media studies and highlights the utility of automatic processing and computational methods (machine learning technologies) for large social media datasets. This systematic scoping review has shown that user-generated content as a data source for studying cannabis as a medicine provides another means to understand how cannabis is perceived and used in the community. …”
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Screening of necroptosis-related genes and evaluating the prognostic capacity, clinical value, and the effect of their copy number variations in acute myeloid leukemia by Dake Wen, Ru Yan, Lin Zhang, Haoyang Zhang, Xuyang Chen, Jian Zhou

“…CNV analysis of the hub-NRDEGs was carried out on the TCGA-LAML datasets from the TCGA database. Kaplan–Meier (K-M) survival analyses were utilized to evaluate the prognostic values along with Cox model. …”
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Integration of histone modification-based risk signature with drug sensitivity analysis reveals novel therapeutic strategies for lower-grade glioma by Jingyuan Wang, Shuai Yan

“…Through integrative analysis of TCGA-LGG (n = 513) and CGGA datasets (n = 693 and n = 325), we constructed a histone modification-related risk signature (HMRS) using machine learning approaches. …”
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Implementing genomic selection in the IMB: challenges and opportunities by Stefano Biffani, Mayra Gómez, Roberta Cimmino, Dario Rossi, Gianluigi Zullo, Riccardo Negrini, Alberto Cesarani, Giuseppe Campanile, Gianluca Neglia

“…On average, the correlation between EBVs from partial and whole datasets estimated with BLUP and ssGBLUP increased from 6 to 49% and from 14 to 17% for production and type traits, respectively. …”
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Relative Fat Mass and Physical Indices as Predictors of Gallstone Formation: Insights From Machine Learning and Logistic Regression by Deng L, Wang S, Wan D, Zhang Q, Shen W, Liu X, Zhang Y

“…The models were validated internally through k-fold cross-validation and externally using independent datasets. Furthermore, we substantiated the link between relative fat mass (RFM) and gallstone formation by employing four logistic regression models, conducting subgroup analyses, and applying restricted cubic spline (RCS) curves.Results: The logistic regression algorithm demonstrated superior predictive capability for all risk factors associated with gallstone occurrence compared to other machine learning models. …”
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Using remote sensing and machine learning to generate 100-cm soil moisture at 30-m resolution for the black soil region of China: Implication for agricultural water management by Liwen Chen, Boting Hu, Jingxuan Sun, Y. Jun Xu, Guangxin Zhang, Hongbo Ma, Jingquan Ren

“…However, soil moisture datasets or algorithms fail to simultaneously meet the requirements of multi-layer, high spatiotemporal resolution soil moisture information for large-scale agricultural production areas. …”
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Dual role of Cathepsin S in cutaneous melanoma: insights from mendelian randomization and bioinformatics analysis by Linsa Zhou, Qiang Zhou, Qian Guo, Peng Lai, Chen Rui, Wanqing Li, Xuemei Chen, Yue Zhuo, Xiaoping Zhong, Sen Lin

“…Result Using matrix data from the GSE15605, GSE46517, and GSE111452 datasets, bioinformatics analysis revealed 232 differentially expressed genes (DEGs) between CM and typical tissues. …”
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Characterizing Tidal Marsh Inundation with Synthetic Aperture Radar, Radiometric Modeling, and In Situ Water Level Observations by Brian T. Lamb, Kyle C. McDonald, Maria A. Tzortziou, Derek S. Tesser

“…These findings have relevance to the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission, as threshold-based classifications of wetland inundation dynamics will be employed to verify that NISAR datasets satisfy associated mission science requirements to map wetland inundation with classification accuracies better than 80% at 1 hectare spatial scales.…”
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Integration of machine learning and experimental validation to identify the prognostic signature related to diverse programmed cell deaths in breast cancer by Longpeng Li, Longpeng Li, Jinfeng Zhao, Yaxin Wang, Zhibin Zhang, Wanquan Chen, Jirui Wang, Yue Cai

“…PCDRS, consisting of seven key genes, showed robust predictive ability over other signatures in different datasets. The high PCDRS group had a poorer prognosis and was strongly associated with a cancer-promoting tumor microenvironment. …”
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Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings by Mosbeh R. Kaloop, Abidhan Bardhan, Pijush Samui, Jong Wan Hu, Mohamed Elsharawy

“…Two deep learning methods viz deep belief network (DBN) and deep neural network (DNN), and five machine learning methods namely feedforward neural network, extreme learning machine, weighted extreme learning machine, random forest, and gradient boosting machine were evaluated, and compared in predicting the design wind pressures on tall buildings. Wind tunnel datasets, used in the current study to develop the proposed computing models, were collected from testing three tall buildings having the same full-scale horizontal dimensions of (40 m and 80 m) and different heights of (80 m, 120 m and 160 m). …”
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The impact of the COVID-19 pandemic on the research activity and working experience of clinical academics, with a focus on gender and ethnicity: a qualitative study in the UK by Carmen Soto, Jessica Elizabeth Morgan, Paul Crampton, Paul Alexander Tiffin, Gabrielle M Finn, Amelia Kehoe, Ellie Taylor, John AG Buchanan, Abisola Olatokunbo Balogun

“…Objective To investigate the impact of the COVID-19 pandemic on the research activity and working experience of clinical academics, with a focus on gender and ethnicity.Design Qualitative study based on interviews and audio/written diary data.Setting UK study within clinical academia.Participants Purposive sample of 82 clinical academics working in medicine and dentistry across all career stages ranging from academic clinical fellows and doctoral candidates to professors.Methods Qualitative semistructured interviews (n=68) and audio diary data (n=30; including 16 participants who were also interviewed) collected over an 8-month period (January–September 2020), thematically analysed.Results 20 of 30 (66.6%) audio diary contributors and 40 of 68 (58.8%) interview participants were female. …”
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Changes over a decade in psychotropic prescribing for people with intellectual disabilities: prospective cohort study by Paula McSkimming, Angela Henderson, Sally-Ann Cooper, Deborah Kinnear, Colin McCowan, Linda Allan, Alasdair McIntosh

“…Longitudinal cohort study with detailed health assessments at T1 and record linkage to T2 prescribing data.Setting General community.Participants 1190 adults with intellectual disabilities in T1 compared with 3906 adults with intellectual disabilities in T2. 545/1190 adults with intellectual disabilities in T1 were alive and their records linked to T2 prescribing data.Main outcome measures Encashed regular and as-required psychotropic prescriptions.Results 50.7% (603/1190) of adults in T1 and 48.2% (1881/3906) in T2 were prescribed at least one psychotropic; antipsychotics: 24.5% (292/1190) in T1 and 16.7% (653/3906) in T2; antidepressants: 11.2% (133/1190) in T1 and 19.1% (746/3906) in T2. 21.2% (62/292) prescribed antipsychotics in T1 had psychosis or bipolar disorder, 33.2% (97/292) had no mental ill health or problem behaviours, 20.6% (60/292) had problem behaviours but no psychosis or bipolar disorder. …”
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Comprehensive Analysis of Competing Endogenous RNA Network Focusing on Long Noncoding RNA Involved in Cirrhotic Hepatocellular Carcinoma by Yuli Zhang, Dinggui Chen, Miaomiao Yang, Xianfeng Qian, Chunmei Long, Zhongwei Zheng

“…The lncRNA, miRNA, and mRNA expression datasets were obtained from Gene Expression Omnibus and The Cancer Genome Atlas. …”
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Genetic variation reveals the therapeutic potential of BRSK2 in idiopathic pulmonary fibrosis by Zhe Chen, Mingyang Tang, Nan Wang, Jiangjiang Liu, Xiaoyan Tan, Haitao Ma, Jing Luo, Kai Xie

“…Methods We employed Mendelian randomization (MR) with three genome-wide association studies and four quantitative trait loci datasets to identify key driver genes for IPF. Prioritized targets were evaluated for respiratory insufficiency and transplant-free survival. …”
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