Developing a ceRNA-based lncRNA-miRNA-mRNA regulatory network to uncover roles in skeletal muscle development by Wang Wenlun, Wang Wenlun, Yu Chaohang, Huang Yan, Li Wenbin, Zhou Nanqing, Hu Qianmin, Wu Shengcai, Yuan Qing, Yu Shirui, Zhang Feng, Zhu Lingyun

“…We conducted a bioinformatic analysis of 26 GEO datasets from mouse studies, encompassing embryonic development, postnatal growth, regeneration, cell proliferation, and differentiation, using R and relevant packages (limma et al.). …”
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Identification and susceptibility assessment of landslide disasters in the red bed formation along the Nanjian-Jingdong Expressway by Yifan Cao, Zhifang Zhao, Mingchun Wen, Xin Zhao, Dingyi Zhou, Jingyi Qin, Liu Ouyang, Jingyao Cao

“…The results indicate that: (1) the analysis of 245 datasets of ascending and descending orbits from 2017 to 2022 yielded deformation rates, with maximum positive and negative deformation rates of 37.02 mm/yr and −46.47 mm/yr, respectively. …”
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RETRACTED ARTICLE: A prospective diagnostic model for breast cancer utilizing machine learning to examine the molecular immune infiltrate in HSPB6 by Lizhe Wang, Yu Wang, Yueyang Li, Li Zhou, Sihan Liu, Yongyi Cao, Yuzhi Li, Shenting Liu, Jiahui Du, Jin Wang, Ting Zhu

“…The objective of this research was to perform bioinformatics analyses on breast cancer-related datasets to gain a comprehensive understanding of the molecular mechanisms at play and to identify key genes associated with the disease. …”
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A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity by Victoria Shevchenko, R. Austin Benn, Robert Scholz, Wei Wei, Carla Pallavicini, Ulysse Klatzmann, Francesco Alberti, Theodore D. Satterthwaite, Demian Wassermann, Pierre-Louis Bazin, Daniel S. Margulies

“…To this end, we leveraged data of 936 individuals from three large open-access datasets: COBRE, LA5c, and SRPBS-1600. We developed a pipeline which allows us to aggregate over a million different features and assess their predictive potential in a single, computationally efficient experiment. …”
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Identification of pyrimidine metabolism-based molecular subtypes and prognostic signature to predict immune landscape and guide clinical treatment in prostate cancer by Yu-Zhong Yu, Xiao Xie, Mao-Ping Cai, Ya-Ying Hong, Yang-Zi Ren, Xi Kang, Hai-Chen Yan, Yang Xiong, Hong Chen, Xing-Cheng Wu, Dao-Sheng Luo, Shan-Chao Zhao

“…Finally, we found that the expression of TK1 was higher in CRPC tissues than in PCa tissues in three GEO datasets. The results indicated that TK1 promotes the growth and metastasis of PCa cells.Conclusions We provide evidence for a PMG signature for PCa patients to accurately predict clinical prognosis. …”
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Heat-related mortality in Mexico: A multi-scale spatial analysis of extreme heat effects and municipality-level vulnerability by Lara Schwarz, Chen Chen, Javier Emmanuel Castillo Quiñones, L.C. Aguilar-Dodier, Kristen Hansen, Jaime Reyes Sanchez, David J.X. González, Gordon McCord, Tarik Benmarhnia

“…Daily all-cause mortality was collected from the Mexican Secretary of Health and municipality-specific extreme heat events were estimated using population-weighted temperatures from 1998 to 2019 using Daymet and WorldPop datasets. We analyzed the association between single-day extreme heat events defined at the 99th percentile of the same-day maximum temperature and mortality, and seven heat threshold metrics based on relative and absolute scales were considered as sensitivity analyses. …”
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Electrocardiography-based artificial intelligence predicts the upcoming future of heart failure with mildly reduced ejection fraction by Dae-Young Kim, Sang-Won Lee, Dong-Ho Lee, Sang-Chul Lee, Sang-Chul Lee, Ji-Hun Jang, Sung-Hee Shin, Dae-Hyeok Kim, Dae-Hyeok Kim, Wonik Choi, Wonik Choi, Yong-Soo Baek, Yong-Soo Baek, Yong-Soo Baek

“…This study aimed to develop artificial intelligence (AI)-electrocardiography (ECG) to identify and predict the prognosis of patients with HFmrEF.MethodsWe collected 104,336 12-lead ECG datasets from April 2009 to December 2021 in a tertiary centre. …”
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Revisiting ABC Transporters and Their Clinical Significance in Glioblastoma by Brandon Wee Siang Phon, Shalini Sundramurthi Chelliah, Dina El-Rabie Osman, Saatheeyavaane Bhuvanendran, Ammu Kutty Radhakrishnan, Muhamad Noor Alfarizal Kamarudin

“…Staple GBM phenotypes, such as GBM stem cells and increased activation of the PI3K/Akt/NF-κB pathway, have been implicated in the expression of several ABC transporters. Using the datasets in The Cancer Genome Atlas and Gene Expression Omnibus, we found upregulated ABC transporters that either negatively impacted survival in univariate analyses (ABCA1, ABCA13, ABCB9, ABCD4) or were independent negative prognosis factors for patients with GBM (ABCA13, ABCB9). …”
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Collagen prolyl 4-hydroxylase subunit α member-induced head and neck squamous cell carcinoma aggressiveness is antagonized by LLGL2 via redu... by Xu Miao, Shi Run, Yang Jie, Chen Heng, Liu Shihua, Yu Shupei, Li Sasa, He Wenqiang, Sy Man-Sun, Lu Mingjian, Zhang Huixia, Li Chaoyang

“…By analyzing TGCA datasets on human head and neck squamous cell carcinoma (HNSC), we find that a higher expression of all three C-P4HAs (the <sc>α subunit</sc> of C-P4Hs) is a superior prognostic indicator than a higher expression of two or a single C-P4HA. …”
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Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study by Guo-kang Sun, Yun-hui Xiang, Lu Wang, Pin-pin Xiang, Zi-xin Wang, Jing Zhang, Ling Wu

“…Logistic regression analysis and receiver operating characteristic (ROC) curves were used to construct a multiple biomarker-based model for the diagnosis of silicosis, which was applied to both the training and the testing datasets.ResultsThe training cohort revealed significant statistical differences (P &lt; 0.05) in multiple hematologic parameters between silicosis patients and healthy individuals. …”
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A DNA-Methylated Sight on Autoimmune Inflammation Network across RA, pSS, and SLE by Xingqiang Wang, Dongyun Lei, Jie Ding, Shuang Liu, Li Tao, Fan Zhang, Jiangyun Peng, Jian Xu

“…In this study, we integrated 5 Cytokine-Chips from genome-wide DNA methylation datasets of the 3 kind of AIDs, delta-beta value was calculated for intergroup difference, and comprehensive bioinformatics analyses of cytokine genes with aberrant methylations were performed. 125 shared differential methylation variabilities (DMVs) were identified. …”
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TOM40 as a prognostic oncogene for oral squamous cell carcinoma prognosis by Lifei Deng, Hong Ran, Dunhui Yang, Zhen Wang, Peng Zhao, Hengjie Huang, Yongjin Wu, Peng Zhang

“…Methods TOM40 expression level in OSCC was evaluated using datasets downloaded from The Cancer Genome Atlas (TCGA), as well as clinical data. …”
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Assessment of Hydrologic Data Estimates From ERA5 Reanalyses in Benin, West Africa by René Bodjrènou, Luc Ollivier Sintondji, Yekambessoun M' Po N'Tcha, Diane Germain, Francis Esse Azonwade, Fernand Sohindji, Gilbert Hounnou, Edid Amouzouvi, Arthur Freud Segnon Kpognin, Françoise Comandan

“…Correcting the variables of these reanalysis datasets could also improve their performance.…”
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A Survey of Camouflaged Object Detection and Beyond by Fengyang Xiao, Sujie Hu, Yuqi Shen, Chengyu Fang, Jinfa Huang, Longxiang Tang, Ziyun Yang, Xiu Li, Chunming He

“…For those interested, a curated list of COD-related techniques, datasets, and additional resources can be found at https://github.com/ChunmingHe/awesome-concealed-object-segmentation.…”
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Defining indicators for disease burden, health outcomes, policies and barriers and facilitators to health services for migrant populations in the Middle East and North African regi... by Charles Agyemang, Ali Ardalan, Farah Seedat, Bouchra Assarag, Nuria Casamitjana, Kolitha Wickramage, Sally Hargreaves, Ana Requena-Mendez, Fouad M Fouad, Dominik Zenner, Anna Deal, Stella Evangelidou, Wafa Saidi, Chiaki Ito, Oumnia Bouaddi, Moudrick Abdellatifi, Alba Cuxart-Graell, Hassan Edries, Eman Elafef, Taha Maatoug, Anissa Ouahchi, Liv Mathilde Pampiri, Sara Arias, Adel Abdelkhalek, Ahmed Hamed Arisha, Ibrahim Ahmed Bani, Aasmaa Chaoui, Wafa Chemao-Elfihri, Kenza Hassouni, Mahmoud Hilali, Mohamed Khalis, Wejdene Mansour, Ali Mtiraoui, MENA Migrant Health Working Group, Asad Adam, Adnene Ben Haj Aissa, Salma Altyib, Hanen Ben Belgacem, Imane Belkhammar, Thomas Calvot, Luciana Ceretti, Nelly Chavassieux, Hassan Chrifi, Mohamed Douagi, Algdail Elnil, Gonzalo Fanjul, Ahmed Hamed, Abdedayem Khelifi, Lora Makhlouf, Maissa Mokni, Davide Olchini, Tarik Oufkir, Nasong Park, Giuseppe Raffa, Sandra Santafé, Alice Sironi, Fatma Temimi, Zeineb Turki

“…We will search for grey literature by hand searching key databases and websites (including regional organisations and MoH websites) for country-specific guidelines and talking to our network of experts for local and regional reports and key datasets. We will assess the studies and policies for their quality using appropriate tools. …”
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Spatially resolved transcriptomics reveals gene expression characteristics in uveal melanoma by Jing-Ying Xiu, Yu-Ning Chen, Ya-Li Mao, Jing-Ting Luo, Hao-Wen Li, Yang Li, Wen-Bin Wei

“…Differentially expressed genes (DEGs) and survival analysis based on datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database further confirmed the correlation between cellular distribution and clinical prognosis. …”
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Bridging animal models and humans: neuroimaging as intermediate phenotypes linking genetic or stress factors to anhedonia by Huiling Guo, Yao Xiao, Shuai Dong, Jingyu Yang, Pengfei Zhao, Tongtong Zhao, Aoling Cai, Lili Tang, Juan Liu, Hui Wang, Ruifang Hua, Rongxun Liu, Yange Wei, Dandan Sun, Zhongchun Liu, Mingrui Xia, Yong He, Yankun Wu, Tianmei Si, Fay Y. Womer, Fuqiang Xu, Yanqing Tang, Jie Wang, Weixiong Zhang, Xizhe Zhang, Fei Wang

“…Methods We analyzed datasets from both rodents and humans. The rodent studies included a genetic model (P11 knockout) and an environmental stress model (chronic unpredictable mild stress), while the human data comprised 748 participants from three cohorts. …”
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Genetically predicted brain cortical structure mediates the causality between insulin resistance and cognitive impairment by Chaojuan Huang, Yuyang Zhang, Mingxu Li, Qiuju Gong, Siqi Yu, Zhiwei Li, Mengmeng Ren, Xia Zhou, Xiaoqun Zhu, Zhongwu Sun

“…Our investigation aims to establish the causal relationship and direction between insulin resistance and cognition, while also quantifying the mediating role of brain cortical structure in this association.MethodsThe publicly available data sources for insulin resistance (fasting insulin, homeostasis model assessment beta-cell function and homeostasis model assessment insulin resistance, proinsulin), brain cortical structure, and cognitive phenotypes (visual memory, reaction time) were obtained from the MAGIC, ENIGMA, and UK Biobank datasets, respectively. We first conducted a bidirectional two-sample Mendelian randomization (MR) analysis to examine the susceptibility of insulin resistance on cognitive phenotypes. …”
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Investigation of a Novel Noninvasive Risk Analytics Algorithm With Laboratory Central Venous Oxygen Saturation Measurements in Critically Ill Pediatric Patients by Sarah A. Teele, MD, MSHPEd, Avihu Z. Gazit, MD, Craig Futterman, MD, William G. La Cava, PhD, David S. Cooper, MD, MPH, MBA, Steven M. Schwartz, MD, MS, Joshua W. Salvin, MD, MPH

“…Area under the receiver operating characteristic curve (AUC) was calculated for each index threshold. Datasets with greater amounts of available data had larger AUC scores. …”
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Causal relationship of familial hypercholesterolemia with risk of intestinal vascular disorders: A mendelian randomization study by Gang Wei, Cheng Zhang, Feng-Jie Shen, Hua-Qi Guo, Lin Liu

“…Methods: A Mendelian randomization (MR) analysis was performed by extracting summary-level datasets for FH or FH concurrently with ischemic heart disease (IHD) and intestinal vascular diseases from the FinnGen study including 329,115, 316,290 and 350,505 individuals. …”
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