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Oncolytic virus OVV-03 enhances CAR-T cell therapy against glioblastoma via immune modulation and specific HER2 upregulation.
Glioblastoma (GBM) remains therapeutically challenging due to treatment resistance and immunosuppression. Oncolytic virotherapy offers a promising strategy. This study engineered OVV-03, a novel HER2-armed oncolytic vesicular stomatitis vir…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Gene-level gut microbiome signatures as predictive biomarkers for response to immune checkpoint inhibitors across multiple cancer types.
Targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) with immune checkpoint inhibitors (ICIs) has improved survival across multiple cancer types, but the variability in patient response h…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Identification of the immune-related diagnostic biomarkers between Graves' disease and thyroid carcinoma based on comprehensive bioinformatics analysis and machine learning.
Increasing evidence suggests that Graves' disease (GD) may increase the risk of thyroid cancer (THCA), but diagnostic biomarkers associated with it remain underexplored. To address this issue, we analyzed the Gene Expression Omnibus (GEO) a…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Exploring the key functions of T cells and the regulation of the immune microenvironment in prostate cancer using single-cell RNA sequencing and bulk RNA sequencing.
The incidence of prostate cancer continues to increase, making it the second most common malignant tumor among men worldwide. Immunotherapy has emerged as a key therapeutic strategy for treating tumors. Numerous studies have established tha…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Genetic relationships between the gut microbiota and prostate cancer: Mendelian randomization combined with bioinformatics analysis.
[BACKGROUND] Prostate cancer (PCa) is a leading cause of male cancer-related death globally. While the gut microbiota is linked to PCa, its genetic association remains unclear. [METHODS] We screened genetic instruments related to the gut m…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases.
[OBJECTIVE] To construct and interpret a machine learning model for predicting overall survival in nonsurgical prostate cancer with bone metastases (PCBM). [METHODS] Data from 3,378 SEER database patients were utilized to develop machine l…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Multi-platform analysis of the tumor immune microenvironment associated with breast cancer subtypes.
Breast cancer is genetically and histologically heterogenous, and is influenced by a variety of factors, including the tumor microenvironment (TME). The PAM50 subtypes; Luminal A, Luminal B, Normal-like, Basal-like and Her2-enriched, are as…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Locus-specific transcriptional regulation of transposable elements by p53.
The tumor suppressor p53 protects genomic integrity in part by regulating transposable elements (TEs). Studies of p53-TE interactions rely on synthetic DNA and reporter assays, estimating expression only at the family or subfamily level and…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Prolonged progression-free survival with zanubrutinib in relapsed/refractory CLL: an indirect treatment comparison versus other BTK inhibitors using multilevel network meta-regression.
[BACKGROUND] Bruton tyrosine kinase inhibitors (BTKis) are therapeutic agents for relapsed/refractory chronic lymphocytic leukemia (R/R CLL). Previous indirect treatment comparisons are limited in simultaneously comparing multiple intervent…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
The surgery for the patients with intestinal non‑Hodgkin lymphomas: a nationwide study.
[BACKGROUND] The treatment strategy for intestinal non-Hodgkin lymphoma (NHL) and the role of surgery warrant reevaluation. [METHODS] This study analyzed clinical data from a cohort of 12,047 patients diagnosed with intestinal NHL, extract…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Neutrophil extracellular trap-related genes in PTCL: identification, prognosis and drug interaction prediction via bioinformatics-machine learning.
[OBJECTIVE] This study aimed to identify neutrophil extracellular trap-related genes (NET-RGs), explore their prognostic significance, and predict drug interactions in peripheral T-cell lymphoma (PTCL). [METHODS] Differentially expressed N…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
A Randomized Trial Evaluating Intraoperative Ischemic Preconditioning of Parathyroid Glands During Total Thyroidectomy: A Signal for Earlier Parathyroid Function Recovery.
[BACKGROUND] Ischemic preconditioning of parathyroid glands (IPCP) is biologically plausible but clinical evidence is limited. In this single-center randomized trial (ChiCTR2000039788), we compared IPCP versus control during total thyroidec…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Comparison of the effects of exercise-based interventions on cardiometabolic health and fatigue in men with prostate cancer receiving androgen deprivation therapy: A network meta-analysis.
[OBJECTIVE] To compare the effects of exercise-based interventions on cardiometabolic health and fatigue in men with prostate cancer receiving androgen deprivation therapy (ADT). [METHODS] A comprehensive search for Randomized controlled s…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Impact of offering blood-based testing alongside existing modalities for colorectal cancer screening among those who previously declined screening: an economic evaluation.
[AIM] Inadequate adherence to colorectal cancer screening reduces individual and population level health benefits. Blood-based tests offer a new modality that may help patients overcome barriers, but there are concerns about the impact of p…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
A vision-language model-based approach for lung cancer diagnosis using lossless 3D CT images: evaluation of GPT-4.1 and GPT-4o for patient-level malignancy assessment.
[PURPOSE] Large vision-language models (VLMs), such as GPT-4.1 and GPT-4o, have shown strong potential in medical tasks. However, their application in lossless 3D medical image analysis is still underexplored. This study proposes a GPT-base…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Predicting lung cancer survival with attention-based CT slices combination.
Accurate prognosis of Non-Small Cell Lung Cancer (NSCLC) is crucial for enhancing patient care and treatment outcomes. Despite the advancements in deep learning, the task of overall survival prediction in NSCLC has not fully leveraged these…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Patient-reported outcomes with a personalized follow-up program after lung cancer resection: A single-center randomized controlled trial.
[OBJECTIVE] This study aims to determine the impact of PROM with a personalized follow-up program on the evaluation of quality of life and self-management for patients after lung cancer resection. [METHODS] Given a formal power calculation…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Integrated machine learning risk model for predicting radiation pneumonitis in lung cancer patients with interstitial lung disease.
[BACKGROUND] Radiation pneumonitis (RP) is a serious complication in lung cancer patients with pre-existing interstitial lung disease (ILD) undergoing radiotherapy. Accurate risk stratification is crucial for individualized management. But …
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Cost-effectiveness of pembrolizumab plus chemotherapy for metastatic non-small cell lung cancer: a head-to-head trial vs. real-world comparison.
[OBJECTIVES] Real-world evidence (RWE) is increasingly used in health technology assessment (HTA) to address uncertainties surrounding the generalizability of randomized clinical trial (RCT) data. Pembrolizumab plus platinum-based chemother…
FULLTEXT: Boosting Machine Learning Algorithms randomized -
Managing psychological distress in women with breast cancer: A systematic review of intervention trends in the past decade.
[OBJECTIVE] The rising incidence and survival rates of breast cancer have increased the number of breast cancer survivors (BCSs) experiencing psychological distress that often overlaps with anxiety, depression, and fear of recurrence. Many …
FULLTEXT: Boosting Machine Learning Algorithms randomized