Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma by Songyun Zhao, Zihao Li, Kaibo Liu, Gaoyi Wang, Quanqiang Wang, Hua Yu, Wanying Chen, Hao Dai, Yijun Li, Jiaheng Xie, Yucang He, Liqun Li

“…Methods We obtained and processed transcriptomic data, including RNA expression profiles, methylation microarray data, gene mutation data, and clinical information, from the TCGA dataset using multi-omics analysis and machine learning techniques. …”
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Identification of immune-related hub genes and potential molecular mechanisms involved in COVID-19 via integrated bioinformatics analysis by Rui Zhu, Yaping Zhao, Hui Yin, Linfeng Shu, Yuhang Ma, Yingli Tao

“…IRGs were sourced from the ImmPort database. We conducted functional enrichment analysis, pathway analysis, and immune infiltration assessments to determine the biological significance of the identified IRGs. …”
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Factors Influencing Older Adults’ Perception of the Age-Friendliness of Their Environment and the Impact of Loneliness, Technology Use, and Mobility: Quantitative Analysis by Eric Balki, Niall Hayes, Carol Holland

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Analysis of the serum proteome profile of wild stump-tailed macaques (Macaca arctoides) seropositive for Zika virus antibodies in Thailand by Pakorn Ruengket, Sittiruk Roytrakul, Daraka Tongthainan, Kobporn Boonnak, Kanokwan Taruyanon, Bencharong Sangkharak, Wirasak Fungfuang

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Machine learning cluster analysis identifies increased 12-month mortality risk in transcatheter aortic valve replacement recipients by Thomas Meredith, Thomas Meredith, Thomas Meredith, Farhan Mohammed, Amy Pomeroy, Sebastiano Barbieri, Sebastiano Barbieri, Erik Meijering, Louisa Jorm, David Roy, Jason Kovacic, Jason Kovacic, Jason Kovacic, Jason Kovacic, Michael Feneley, Michael Feneley, Michael Feneley, Christopher Hayward, Christopher Hayward, Christopher Hayward, David Muller, David Muller, David Muller, Mayooran Namasivayam, Mayooran Namasivayam, Mayooran Namasivayam

“…Nested cox models were used to identify any incremental prognostic benefit cluster assignment achieved beyond conventional risk scores.ResultsAnalysis identified two distinct clusters. Compared to Cluster 1, Cluster 2 demonstrated significantly worse all-cause mortality at 12 months (HR 6.3, p < 0.01), and was characterised by more advanced cardiac remodelling with worse indices of multi-chamber cardiac function, as quantified by strain imaging. …”
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To construct and validate a risk score model of angiogenesis-related genes to predict the prognosis of hepatocellular carcinoma by Duangui Gao, Yuan Lu, Tianpeng Jiang, Qinghong Duan, Zhi Huang

“…Public RNAseq and clinical data from TCGA and GEO database, download angiogenesis-related genes from the GeneCards, MSigDB database, through the single factor analysis of Cox, LASSO build risk score—Cox regression analysis model and external validation verified from the GEO. …”
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Elevated expression of APOO as a potential prognostic marker in breast cancer: insights from bioinformatic analysis and experimental validation by Yang Bai, Qian Tang, Liang Zheng, Jun He, Wenjian Wang, Liqi Li, Ju Yu

“…Methods Bioinformatic analyses were employed to identify genes’ expression statuses and their relationship with the prognoses of patients. The genes’ functions were determined in cell line by gain or loss of function assays. …”
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Is peri-operative steroid replacement therapy necessary for the pituitary adenomas treated with surgery? A systematic review and meta analysis. by Mamatemin Tohti, Junyang Li, Yuan Zhou, Yuebing Hu, Zhuang Yu, Chiyuan Ma

“…Though randomized controlled trials(RCT) have not been performed to assess the necessity of steroid coverage, there are several studies that explained the changes of adrenal function during peri-operative peroids. The aim of the present study is to investigate whether it is necessary to employ conventional peri-operative glucocorticoid replacement therapy to all the patients undergoing surgery.…”
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Genome-wide analysis of phytochrome-interacting factor (PIF) families and their potential roles in light and gibberellin signaling in Chinese pine by Yingtian Guo, Chengyan Deng, Guizhi Feng, Dan Liu

“…Investigations into protein-protein interactions and co-expression networks speculated the involvement of PtPIFs and PtPHYA/Bs in circadian rhythms and hormone signal transduction. Further analysis of transcriptome data and experimental validation indicated an interaction between PtPIF3 and PtPHYB1, potentially linked to diurnal rhythms. …”
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Risk of unintentional injuries in children and adolescents with ADHD and the impact of ADHD medications: protocol for a systematic review and meta-analysis by Samuele Cortese, Cesar Soutullo, Gonzalo Arrondo, Maite Ruiz-Goikoetxea, Maite Aznarez-Sanado, Sara Magallon, Elkin O Luis, Noelia Alvarez Zallo, Pilar de Castro-Manglano

“…Articles reporting ORs or HRs of suffering an injury in ADHD compared with controls (or enough data to calculate them) will be combined using Robust Variance Estimation, a method that permits to include multiple non-independent outcomes in the analysis. …”
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Monitoring Method and Performance Analysis of Climbing Scaffolds in Super High-Rise Buildings Based on BeiDou/GNSS Technology by Pengfei Wang, Gen Liu, Jian Wang, Ping Zhu, Jiaqi Guo, Jingxuan Zhang, Heyu Zhang, Yijia Liu

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Comparative Analysis of Primary Sarcopenia and End‐Stage Renal Disease–Related Muscle Wasting Using Multi‐Omics Approaches by Daiki Setoyama, Dohyun Han, Jingwen Tian, Ho Yeop Lee, Hyun Suk Shin, Ha Thi Nga, Thi Linh Nguyen, Ji Sun Moon, Hyo Ju Jang, Evonne Kim, Seong‐Kyu Choe, Sang Hyeon Ju, Dae Eun Choi, Obin Kwon, Hyon‐Seung Yi

“…Understanding these molecular nuances is imperative for targeted interventions, and the integration of proteomic and metabolomic data elucidate these intricate processes. Methods We generated detailed clinical data and multi‐omics data (plasma proteomics and metabolomics) for 78 participants to characterise sarcopenia (n = 28; mean age, 72.6 ± 7.0 years) or ESRD (n = 22; 61.6 ± 5.5 years) compared with controls (n = 28; 69.3 ± 5.7 years). …”
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The A2Π–X2Σ+ Band System of ScO for M-type Star Spectral Analysis by Léo Lavy, Adam Pastorek, Peter F Bernath

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Integrated single-cell and bulk transcriptome analysis reveal lactate metabolism-related signature and T cell alteration in atrial fibrillation by Xianglin Long, Junxi Li, Yeshen Zhang, Zhihui Zhang

“…Although lactate metabolism influences T cell differentiation and function, its specific role in AF and associated immune processes remains inadequately understood.MethodsWe performed an integrated transcriptomic analysis utilizing both bulk and single-nucleus RNA sequencing data derived from hearts exhibiting AF and those in sinus rhythm. …”
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Revealing Potential Diagnostic Gene Biomarkers Associated with Immune Infiltration in Patients with Renal Fibrosis Based on Machine Learning Analysis by Yu-Chao Sun, Zhen-Zhen Qiu, Fu-Li Wen, Jin-Quan Yin, Hao Zhou

“…In vitro experiments were applied to examine the function of ISG20 knockdown on the progression of renal fibrosis. …”
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Gene Expression Analysis of (Paired) Primary and Relapsed Wilms Tumor Samples to Unravel the Underlying Factors Driving Tumor Recurrence by Alissa Groenendijk, Jarno Drost, Annelies M. C. Mavinkurve‐Groothuis, Martine vanGrotel, Geert O. Janssens, Annemieke S. Littooij, Alida F. W. van derSteeg, Marry M. van denHeuvel‐Eibrink, Lennart Kester, Ronald R. deKrijger

“…The differential gene expression analysis results were run through ToppGene for functional enrichment. …”
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Energy cataract surgery in the St. Petersburg branch of the S. Fyodorov Eye Microsurgery State Institution: analysis of 27-year experience by E.V. Boiko, M.N. Nemsitsveridze, S.V. Shukhaev, E.A. Simak

“…Material and methods. Analysis of the results of laser cataract extraction, ultrasonic phacoemulsification and combined surgery is based on data from a study of 28 802 surgical interventions (Phacoemulsification (Phaco) – 15 520, laser cataract extraction (LCE) – 7945, FemtoPhaco – 5135, FemtoLCE – 202) performed over the period 1995–2022. …”
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Bidirectional Transcriptome Analysis of Rat Bone Marrow-Derived Mesenchymal Stem Cells and Activated Microglia in an In Vitro Coculture System by Da Yeon Lee, Moon Suk Jin, Balachandran Manavalan, Hak Kyun Kim, Jun Hyeok Song, Tae Hwan Shin, Gwang Lee

“…In this study, we investigated differential gene expression in rat BM-MSCs (rBM-MSCs) that were cocultured with lipopolysaccharide- (LPS-) stimulated primary rat microglia using microarray analysis and evaluated the functional relationships through Ingenuity Pathway Analysis (IPA). …”
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Validation of Reference Genes for Robust qRT-PCR Gene Expression Analysis in the Rice Blast Fungus Magnaporthe oryzae. by Sarena Che Omar, Michael A Bentley, Giulia Morieri, Gail M Preston, Sarah J Gurr

“…We recommend the combinatorial use of two reference genes, belonging to the cytoskeleton and ribosomal synthesis functional groups, MGG_Actin, MGG_40s, MGG_S8 (Ribosomal subunit 40S S8) or MGG_Ef1, which demonstrated low M values across heterogeneous tissues. …”
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Unlocking The Potential of Hybrid Models for Prognostic Biomarker Discovery in Oral Cancer Survival Analysis: A Retrospective Cohort Study by Leila Nezamabadi Farahani, Anoshirvan Kazemnejad, Mahlagha Afrasiabi, Leili Tapak

“…Objective: This study aimed to develop a hybrid model for variable selection in high-dimensional survival analysis using a support vector regression (SVR), to identify prognostic biomarkers associated with survival in oral cancer (OC) patients through the analysis of gene expression data.Materials and Methods: In this retrospective cohort study, gene expression profiles (54,613 probes) related to 97 patients from the GSE41613 dataset from the GEO repository were used. …”
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