Lasso

BACKGROUND: Although anoikis plays a role in cancer migration, metastasis, and aggressiveness, it has rarely been reported in diffuse large B cell lymphoma (DLBCL). METHODS: We obtained RNA sequencing data and matched clinical data from the GEO database. An anoikis-related genes (ARGs)-based risk signature was developed using univariate Cox regression and LASSO regression in GSE10846 training cohort, and was validated in three other cohorts. The expression of candidate genes of the ARG signature was validated by RT-qPCR...

Invasive pulmonary aspergillosis (IPA) is a life-threatening complication in patients with severe fever with thrombocytopenia syndrome (SFTS), yet SFTS-associated IPA (SAPA)'s risk factors remain undefined. A multicenter retrospective cohort study across Hubei and Anhui provinces (May 2013-September 2022) utilized least absolute shrinkage and selection operator (LASSO) regression for variable selection. Multivariable logistic regression identified independent predictors of SAPA, Cox regression highlighted mortality-related risk factors...

OBJECTIVE: To identify the key genes differentially expressed in Wilms tumor and analyze their potential impacts on prognosis and immune responses of the patients. METHODS: High-throughput RNA sequencing was used to identify the differentially expressed mRNAs in clinical samples of Wilms tumor and paired normal tissues, and their biological functions were analyzed using GO, KEGG and GSEA enrichment analyses. The hub genes were identified using STRING database, based on which a prognostic model was constructed using LASSO regression...

OBJECTIVE: This study aimed to understand predictors of inadequate response (IR) to low-dose febuxostat treatment based on clinical variables. METHODS: We pooled data from 340 patients of an observational cohort and two clinical trials who received febuxostat 20 mg/day for at least 3 months. IR was defined as failure to reach the target serum urate level (sUA<6 mg/dL) at any time point during 3 months treatment. The potential predictors associated with short- or mid-term febuxostat IR after pooling the three cohorts were explored using mixed-effect logistic analysis...

BACKGROUND: Bone metastasis significantly impact the prognosis of non-small cell lung cancer (NSCLC) patients, reducing their quality of life and shortening their survival. Currently, there are no effective tools for the diagnosis and risk assessment of early bone metastasis in NSCLC patients. This study employed machine learning to analyze serum indicators that are closely associated with bone metastasis, aiming to construct a model for the timely detection and prognostic evaluation of bone metastasis in NSCLC patients...

Nowadays, effective prognostic models for esophageal cancer (ESCA) are still lacking. Long noncoding RNAs (lncRNAs) are commonly utilized as indicators for diagnosing cancer and forecasting patient outcomes. Cuproptosis is regulated by multiple genes and is crucial to the progression of ESCA. However, it is not yet clear what role the cuproptosis-associated lncRNAs (CuALs) play in ESCA. To tackle this problem, a prognostic signature incorporating three CuALs was created. This signature was constructed by the use of the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression...

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent liver disease worldwide and lack of research on the diagnostic utility of mitochondrial regulators in NAFLD. Mitochondrial dysfunction plays a pivotal role in the development and progression of NAFLD, especially oxidative stress and acidity β-oxidative overload. Thus, we aimed to identify and validate a panel of mitochondrial gene expression biomarkers for detection of NAFLD. METHODS: We selected the GSE89632 dataset and identified key mitochondrial regulators by intersecting DEGs, WGCNA modules, and MRGs...

BACKGROUND: Gliomas stand out as highly predominant malignant nervous tumors and are linked to adverse treatment outcomes and short survival periods. Current treatment options are limited, emphasizing the need to identify effective therapeutic targets. The heterogeneity of tumors necessitates a personalized treatment approach with an effective grouping system. Meox1 has been implicated in promoting tumor progression in diverse cancers; nonetheless, its role in gliomas remains unelucidated...

BACKGROUND: Radiotherapy is an effective treatment for hepatocellular carcinoma (HCC). Recent studies indicated that N7-methylguanosine (m7G)-associated genes are involved in radioresistance and prognosis of HCC. However, the prognostic value and underlying mechanism of m7G-and radiosensitivity-associated genes are still lacking. METHODS: The related statistics of HCC were downloaded from The Cancer Genome Atlas (TCGA). M7G- and radiosensitivity-associated genes were screened and evaluated using correlation, differential, univariate, and multivariate analysis...

OBJECTIVE: In this study, we aimed to utilize computed tomography (CT)-derived radiomics and various machine learning approaches to differentiate between invasive mucinous adenocarcinoma (IMA) and invasive non-mucinous adenocarcinoma (INMA) preoperatively in solitary pulmonary nodules (SPN) ≤3 cm. METHODS: A total of 538 patients with SPNs measuring ≤3 cm were enrolled, categorized into either the IMA group (n = 50) or INMA group (n = 488) based on postoperative pathology...

OBJECTIVE: To utilize radiomics analysis on dual-energy CT images of the pancreas to establish a quantitative imaging biomarker for type 2 diabetes mellitus. MATERIALS AND METHODS: In this retrospective study, 78 participants (45 with type 2 diabetes mellitus, 33 without) underwent a dual energy CT exam. Pancreas regions were segmented automatically using a deep learning algorithm. From these regions, radiomics features were extracted. Additionally, 24 clinical features were collected for each patient...

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is a common gynecologic tumor and patients with advanced and recurrent disease usually have a poor clinical outcome. Angiogenesis is involved in the biological processes of tumors and can promote tumor growth and invasion. In this paper, we created a signature for predicting prognosis based on angiogenesis-related lncRNAs (ARLs). This provides a prospective direction for enhancing the efficacy of immunotherapy in CESC patients. We screened seven OS-related ARLs by univariate and multivariate regression analyses and Lasso analysis and developed a prognostic signature at the same time...

Backgrounds: Colorectal cancer (CRC) is a highly malignant gastrointestinal malignancy with a poor prognosis, which imposes a significant burden on patients and healthcare providers globally. Previous studies have established that genes related to glutamine metabolism play a crucial role in the development of CRC. However, no studies have yet explored the prognostic significance of these genes in CRC. Methods: CRC patient data were downloaded from The Cancer Genome Atlas (TCGA), while glutamine metabolism-related genes were obtained from the Molecular Signatures Database (MSigDB) database...

OBJECTIVE: Approximately 50% of ST-segment elevation myocardial infarction (STEMI) patients have multivessel coronary artery disease (MVD). The management strategy for these patients remains controversial. This study aimed to develop predictive models and nomogram of outcomes in STEMI patients with MVD for better identification and classification. METHODS: The least absolute shrinkage and selection operator (LASSO) method was used to select the features most significantly associated with the outcomes...

BACKGROUND AND OBJECTIVE: Type 2 Diabetes Mellitus (T2DM) with insulin resistance (IR) is prone to damage the vascular endothelial, leading to the formation of vulnerable carotid plaques and increasing ischemic stroke (IS) risk. The purpose of this study is to develop a nomogram model based on carotid ultrasound radiomics for predicting IS risk in T2DM patients. METHODS: 198 T2DM patients were enrolled and separated into study and control groups based on IS history...

Deep vein thrombosis (DVT) is one of the common complications after joint replacement, which seriously affects the quality of life of patients. We systematically searched nine databases, a total of eleven studies on prediction models to predict DVT after knee/hip arthroplasty were included, eight prediction models for DVT after knee/hip arthroplasty were chosen and compared. The results of network meta-analysis showed the XGBoost model (SUCRA 100.0%), LASSO (SUCRA 84.8%), ANN (SUCRA 72.1%), SVM (SUCRA 53.0%), ensemble model (SUCRA 40...

Cyanobacteria have developed acclimation strategies to adapt to harsh environments, making them a model organism. Understanding the molecular mechanisms of tolerance to abiotic stresses can help elucidate how cells change their gene expression patterns in response to stress. Recent advances in sequencing techniques and bioinformatics analysis methods have led to the discovery of many genes involved in stress response in organisms. The Synechocystis sp. PCC 6803 is a suitable microorganism for studying transcriptome response under environmental stress...

BACKGROUND: Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. METHODS: Utilizing RNA sequencing data and corresponding clinical information from the TCGA database, and employing Weighted Gene Co-expression Network Analysis (WGCNA) on TNBC mRNAsi sourced from an online database, stemness-related genes (SRGs) and SRlncRNAs were identified...

Multidrug-resistant (MDR) pathogens are a rising global health worry that imposes an urgent need for the discovery of novel antibiotics particularly those of natural origin. In this context, we aimed to use the metagenomic nanopore sequence analysis of soil microbiota coupled with the conventional phenotypic screening and genomic analysis for identifying the antimicrobial metabolites produced by promising soil isolate(s). In this study, whole metagenome analysis of the soil sample(s) was performed using MinION™ (Oxford Nanopore Technologies)...

OBJECTIVE: To understand the association between chronic inflammation, cellular senescence, and immunological infiltration in endometriosis. METHODS: Datasets from GEO comprising 108 endometriosis and 97 healthy human samples and the human endometrial stromal cell. Differentially expressed genes were identified using Limma and WGCNA. Inflammatory response-related subtypes were constructed using consensus clustering analysis. The CIBERSORT algorithm and correlation analyses assessed immune cell infiltration...