Lasso

Severe asthma is characterized by a poor level of control that severely affects the patient's life and prognosis. However, the underlying pathogenic mechanisms remain unknown. Here, we identified differentially expressed genes from the microarray datasets(GSE130499 and GSE63142) of severe asthma, and then constructed models to screen the most relevant biomarkers to severe asthma by machine learning algorithms(LASSO and SVM-RFE), with further validation of the results by GSE43696. Three genes ( BCL3 , DDIT4 and S100A14 ) are considered as biomarkers of severe asthma and had good diagnostic effect...

Thrombocythemia (ET), polycythemia vera (PV), primary myelofibrosis (PMF), prefibrotic/early (pre-PMF), and overt fibrotic PMF (overt PMF) are classical Philadelphia-Negative (Ph-negative) myeloproliferative neoplasms (MPNs). Differentiating between these types based on morphology and molecular markers is challenging. This study aims to clarify the application of flow cytometry in the diagnosis and differential diagnosis of classical MPNs. This study retrospectively analyzed the immunophenotypes, clinical characteristics, and laboratory findings of 211 Ph-negative MPN patients, including ET, PV, pre-PMF, overt PMF, and 47 controls...

Granger causality is among the widely used data-driven approaches for causal analysis of time series data with applications in various areas including economics, molecular biology, and neuroscience. Two of the main challenges of this methodology are: 1) over-fitting as a result of limited data duration, and 2) correlated process noise as a confounding factor, both leading to errors in identifying the causal influences. Sparse estimation via the LASSO has successfully addressed these challenges for parameter estimation...

Neuroblastoma (NB) is the most prevalent extracranial solid tumor in pediatric patients, and its treatment failure often associated with metastasis. In this study, LASSO, SVM-RFE, and random forest tree algorithms, was used to identify the pivotal gene involved in NB metastasis. NB cell lines (SK-N-AS and SK-N-BE2), in conjunction with NB tissue were used for further study. ABLIM3 was identified as the hub gene and can be an independent prognostic factor for patients with NB. The immunohistochemical analysis revealed that ABLIM3 is negatively correlated with the metastasis of NB...

BACKGROUND: Sex differences are related to both biological factors and the gendered environment. To untangle sex-related effects on health and disease it is important to model sex-related differences better. METHODS: Data came from the baseline visit of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a longitudinal cohort study following 16,415 individuals recruited at baseline from four study sites: Bronx NY, Miami FL, San Diego CA, and Chicago IL...

OBJECTIVE: To establish a predictive modeling for the risk of bloodstream infection associated with peripherally inserted central catheter (PICC). METHODS: Patients receiving PICC treatment in Shenzhen People's Hospital from June 2020 to December 2020 were retrospectively enrolled and divided into the infection group and the non-infection group according to the presence and absence of PICC-related infections. Then, relevant clinical information of patients was collected and the predictors of PICC-related infection were screened by the least absolute shrinkage and selection operator regression (LASSO) model...

BACKGROUND: The role of glycosyltransferase (GT) genes in lung adenocarcinoma (LUAD) needs further elucidation. Thus, our study aims to identify the prognostic gene signature of LUAD and explore its molecular functions. METHODS: We initially extracted GT gene sets from the database, and obtained mRNA expression levels and clinical data from The Cancer Genome Atlas (TCGA) database. For constructing a prognostic model for GT genes, we utilized univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses...

PURPOSE: Concrete epidemiological evidence has suggested the mutually-contributing effect respectively between nonalcoholic fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM), and periodontitis (PD); however, their shared crosstalk mechanism remains an open issue. METHOD: The NAFLD, PD, and T2DM-related datasets were obtained from the NCBI GEO repository. Their common differentially expressed genes (DEGs) were identified and the functional enrichment analysis performed by the DAVID platform determined relevant biological processes and pathways...

AIM: Our aim was to explore the feasibility of using radiomics data derived from intratumoral and peritumoral edema on fat-suppressed T2-weighted imaging (T2 FS) to distinguish triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (non-TNBC). METHODS: This retrospective study enrolled 174 breast cancer patients. According to the MRI examination time, patients before 2021 were divided into training (n = 119) or internal test (n = 30) cohorts at a ratio of 8:2...

OBJECTIVES: We aimed to establish a diagnostic model of endometriosis (EM) based on disulfidptosis-related genes (DRGs). MATERIALS AND METHODS: The mRNA expression data of EM were downloaded from the gene expression omnibus database and subjected to differential analysis, and co-expression analysis was performed based on 10 disulfidptosis genes to acquire DRGs. The differentially expressed DRGs were subjected to biofunctional analysis. Lasso analysis and support vector machine-recursive feature elimination (SVM-RFE) analysis were employed to extract the intersection of feature genes as biomarkers, and the diagnostic values of biomarkers for EM were evaluated based on receiver operating characteristic curves...

OBJECTIVE: The aim of this study was to develop a web-based dynamic prediction model for postoperative nausea and vomiting (PONV) in patients undergoing gynecologic laparoscopic surgery. METHODS: The patients (N = 647) undergoing gynecologic laparoscopic surgery were included in this observational study. The candidate risk-factors related to PONV were included through literature search. Lasso regression was utilized to screen candidate risk-factors, and the variables with statistical significance were selected in multivariable logistic model building...

Recently, resuscitative endovascular balloon occlusion of the aorta (REBOA) had been introduced as an innovative procedure for severe hemorrhage in the abdomen or pelvis. We aimed to investigate risk factors associated with mortality after REBOA and construct a model for predicting mortality. This multicenter retrospective study collected data from 251 patients admitted at five regional trauma centers across South Korea from 2015 to 2022. The indications for REBOA included patients experiencing hypovolemic shock due to hemorrhage in the abdomen, pelvis, or lower extremities, and those who were non-responders (systolic blood pressure (SBP) < 90 mmHg) to initial fluid treatment...

BACKGROUND: The metastasis and aggressive nature of prostate cancer (PCa) has become a major malignancy related threat that concerns men's health. The efficacy of immune monotherapy against PCa is questionable due to its lymphocyte-suppressive nature. METHOD: Endoplasmic reticulum stress- (ERS-) and PCa-prognosis-related genes were obtained from the Molecular Signatures Database and the Cancer Genome Atlas database. The expression, prognosis and immune infiltration values of key genes were explored by "survival R package", "rms", "xCELL algorithm", and univariate-multivariate Cox and LASSO regression analyses...

BACKGROUND: The objective of this research was to create and validate an interpretable prediction model for drug-induced liver injury (DILI) during tuberculosis (TB) treatment. METHODS: A dataset of TB patients from Ningbo City was used to develop models employing the eXtreme Gradient Boosting (XGBoost), random forest (RF), and the least absolute shrinkage and selection operator (LASSO) logistic algorithms. The model's performance was evaluated through various metrics, including the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPR) alongside the decision curve...

BACKGROUND: Colorectal cancer (CRC) is a highly heterogeneous malignancy, and patients often have different responses to treatment. In this study, the genetic characteristics related to exosome formation and secretion procedure were used to predict chemoresistance and guide the individualized treatment of patients. METHODS: Firstly, seven microarray datasets in Gene Expression Omnibus (GEO) and RNA-Seq dataset from the Cancer Genome Atlas (TCGA) were used to analysis the transcriptome profiles and associated characteristics of CRC patients...

BACKGROUND: Delayed graft function (DGF) is an important complication after kidney transplantation surgery. The present study aimed to develop and validate a nomogram for preoperative prediction of DGF on the basis of clinical and histological risk factors. METHODS: The prediction model was constructed in a development cohort comprising 492 kidney transplant recipients from May 2018 to December 2019. Data regarding donor and recipient characteristics, pre-transplantation biopsy results, and machine perfusion parameters were collected, and univariate analysis was performed...

OBJECTIVE: Prediction of lymph node metastasis (LNM) for intrahepatic cholangiocarcinoma (ICC) is critical for the treatment regimen and prognosis. We aim to develop and validate machine learning (ML)-based predictive models for LNM in patients with ICC. METHODS: A total of 345 patients with clinicopathological characteristics confirmed ICC from Jan 2007 to Jan 2019 were enrolled. The predictors of LNM were identified by the least absolute shrinkage and selection operator (LASSO) and logistic analysis...

Acute pancreatitis (AP) is a common systemic inflammatory disease resulting from the activation of trypsinogen by various incentives in ICU. The annual incidence rate is approximately 30 out of 100,000. Some patients may progress to severe acute pancreatitis, with a mortality rate of up to 40%. Therefore, the goal of this article is to explore the key genes for effective diagnosis and treatment of AP. The analysis data for this study were merged from two GEO datasets. 1357 DEGs were used for functional enrichment and cMAP analysis, aiming to reveal the pathogenic genes and potential mechanisms of AP, as well as potential drugs for treating AP...

PURPOSE: To develop a mortality risk score for COVID-19 patients admitted to intensive care units (ICU), and to compare it with other existing scores. MATERIALS AND METHODS: It is a retrospective observational study, including consecutive adult patients with laboratory-confirmed COVID-19 admitted to ICUs of 18 hospitals from nine Brazilian cities, from 09/2021 to 07/2022. Potential predictors were selected based on the literature review. Generalized Additive Models were used to examine outcomes and predictors...

OBJECTIVES: A reliable, user-friendly, and multidimensional prediction tool can help to identify children at high risk for ADHD and facilitate early recognition and family management of ADHD. We aimed to develop and validate a risk nomogram for ADHD in children aged 3-17 years in the United States based on clinical manifestations and complex environments. METHODS: A total of 141,356 cases were collected for the prediction model. Another 54,444 cases from a new data set were utilized for performing independent external validation...