Aim This study aims to assess the efficacy of Virtual Reality (VR) during painful procedures and chemotherapy (CT) in reducing pain and anxiety for patients with hematologic malignancies.Materials and methods A crossover design with an external control group was carried out. Participants were assigned to two groups: an intervention group, with a crossover design (n patients/procedures = 112), where patients underwent the procedure with standard care only, followed by washout period, then underwent the same procedure with VR. An external control group (n patients = 94, n procedures = 101) was matched to the intervention group based on age and procedure type. Pain and anxiety were assessed subjectively before and after the procedure, with intra-individual and intergroups comparisons. Side effects were captured objectively.Results A total of 206 participants were included in this study, with a total of 213 invasive procedures. Anxiety and pain decreased more during VR period than the without VR period and external control group. VR was effective in anxiety and pain reduction during all procedure, except pain during CT (p > 0.05). Two side effects (1.8%) related to intervention were reported.Conclusion VR effectiveness was demonstrated in reducing pain and anxiety during painful procedures. It was effective in reducing anxiety during CT.Clinical trial registration [ClinicalTrials.gov] identifier is [NCT07085065]
Aims Translocase of Outer Mitochondrial Membrane 5 (TOMM5), a mitochondrial outer membrane translocase subunit implicated in tumorigenesis, remains unexplored in oral cancer. Herein, we aimed to decipher the role of TOMM5 in oral cancer.Methods This study comprehensively explored the expression profile, clinical significance, and functional roles of TOMM5 in oral carcinogenesis with global RNA-seq and microarray datasets. In vitro experiments were performed for evaluating the impact of TOMM5 knockdown on the biological functions of oral cancer cells. Distribution heterogeneity of TOMM5 expression and related cellular trajectory was analyzed through scRNA-seq. The therapeutic implications of TOMM5 for oral cancer were analyzed through drug sensitivity prediction and tumor immune dysfunction and exclusion (TIDE) scoring.Results TOMM5 was significantly overexpressed in oral cancer tissues and demonstrated moderate diagnostic accuracy. TOMM5 knockdown significantly suppressed aggressive biological behaviors of oral cancer cells. ScRNA-seq data revealed predominant TOMM5 expression in B cells, decreasing with differentiation, and linked distinct pathway activities to specific cellular compartments. High TOMM5 expression was linked to reduced immune cell infiltration and sensitivity to Paclitaxel/Vincristine.Conclusions Overexpressed TOMM5 shows potential as a biomarker in oral cancer, correlating with tumor progression and immune infiltration.
Background Patients with chronic kidney disease (CKD) may be vulnerable to thiamine insufficiency due to dietary restrictions, altered metabolism, and renal replacement therapy. We aimed to determine the prevalence of functional thiamine deficiency, its distribution across CKD stages, and the associated clinical factors in a Thai population.Areas covered Thiamine status was assessed in red blood cells using the erythrocyte transketolase activity coefficient (ETKAC) assay. Participants (n = 605) were categorized as having normal thiamine status (ETKAC ≤1.25) or functional thiamine deficiency (ETKAC >1.25). The prevalence of functional thiamine deficiency was 6.1% overall and 6.4% among participants with CKD. Univariate analyses of participants with CKD showed that higher systolic blood pressure (SBP), hypertension, and lower estimated glomerular filtration rate (eGFR) were associated with functional thiamine deficiency. In the multivariable analysis adjusted for age, sex, SBP, eGFR, and alcohol intake, hypertension remained independently associated with functional thiamine deficiency (β = 2.202; 95% confidence interval (CI) for the corresponding odds ratio (OR): 2.311–35.383; p = 0.002).Expert Opinion/Commentary Functional thiamine deficiency was observed in a subset of participants, particularly in patients with CKD and hypertension, supporting further investigation of thiamine status in CKD populations.
Aims To examine index-window carcinoembryonic antigen (CEA), C-reactive protein (CRP), and five-year recorded mortality by ethnicity in colorectal cancer.Patients and methods This retrospective University of California Health Data Warehouse cohort included Hispanic/Latino and non-Hispanic White adults indexed during 2012–2020 with both biomarkers measured within ±30 days and complete covariates. Linear regression modeled log(CEA + 0.1); Cox regression modeled recorded all-cause mortality.Results Among 345 patients, 143 deaths were recorded. Hispanic/Latino ethnicity was associated with higher log(CEA + 0.1) (β = 0.743; robust 95% confidence interval [CI], 0.202–1.285; P = 0.007). The mortality association was nonsignificant (hazard ratio [HR], 0.723; 95% CI, 0.483–1.084; P = 0.117). Higher log(CEA + 0.1) (HR, 1.266; 95% CI, 1.174–1.366; P < 0.001) and log(CRP + 0.1) (HR, 1.134; 95% CI, 1.037–1.239; P = 0.006) were associated with mortality.Conclusions In this biomarker-selected cohort, Hispanic/Latino patients had higher recorded CEA without a statistically significant ethnic-group mortality difference. Confirmation requires clinically characterized cohorts with stage, treatment, biomarker timing, verified assay comparability, and complete mortality ascertainment.
INTRODUCTION:This systematic review and meta-analysis evaluated artificial intelligence (AI) and radiomics applied to renal ultrasound for the diagnosis, staging, and prognosis of degenerative kidney disorders. METHODS:PubMed/MEDLINE, Embase, Scopus, Web of Science, the Cochrane Library, and gray-literature sources were searched without date or language restrictions. Eligible studies applied AI or radiomics to renal ultrasound and reported diagnostic, staging, or prognostic outcomes. Risk of bias and methodological quality were assessed using the Prediction model Risk Of Bias Assessment Tool (PROBAST), Checklist for Artificial Intelligence in Medical Imaging (CLAIM 2024), and Radiomics Quality Score 2.0 (RQS 2.0). Random-effects models were used for diagnostic accuracy synthesis. RESULTS:Thirty-one studies were included. Machine-learning models achieved pooled sensitivity of 0.86 (95% confidence interval 0.82-0.90) and specificity of 0.83 (0.79-0.87); deep-learning models achieved sensitivity of 0.89 (0.84-0.93) and specificity of 0.85 (0.81-0.91). Heterogeneity was substantial and external validation was uncommon. CONCLUSIONS:AI-augmented renal ultrasound shows promising diagnostic performance, but heterogeneous populations, limited calibration, and predominantly internal validation constrain clinical generalizability. Prospective multicenter external validation is required.
