Medicine
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Observational Study
Deciphering sepsis: An observational bioinformatic analysis of gene expression in granulocytes from GEO dataset GSE123731.
Sepsis triggers severe inflammatory responses leading to organ dysfunction and demands early diagnostic and therapeutic intervention. This study identifies differentially expressed genes (DEGs) in sepsis patients using the Gene Expression Omnibus database to find potential diagnostic and therapeutic markers. We analyzed the dataset GSE123731 via GEO2R to detect DEGs, constructed protein-protein interaction networks, and performed transcription factor analyses using Cytoscape. ⋯ Cytokine signaling pathways were highlighted in Kyoto Encyclopedia of Genes and Genomes analysis. Co-immunoprecipitation assays confirmed interactions involving matrix metallopeptidase 8, matrix metallopeptidase 9, and arginase 1, supporting their roles as biomarkers. The identified DEGs and validated interactions reveal crucial molecular mechanisms in sepsis, offering new avenues for diagnostic and therapeutic strategies, potentially enhancing patient outcomes.
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To explore distributed characteristics and identify research focus and emerging trends related to cancer-related fatigue (CRF) in the nursing field. ⋯ In the field of nursing, the focus of CRF research is still on risk factors, adverse outcomes and nursing management. Assessment tools will continue to be developed and additional risk factors will be studied in the future.
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Surgical resection is the cornerstone of treatment for locally advanced gastric cancer (LAGC). Hence, downstaging of the tumor with neoadjuvant therapy is critical for R0 resection and prolongs the overall survival. Data from related studies are lacking, and the literature is scarce. ⋯ All adverse events were relieved and disappeared after symptomatic treatment, and no grade 4 adverse events were noted. PD-1 inhibitor and apatinib plus S-1 and oxaliplatin are safe and effective as neoadjuvant treatment of LAGC. Gastric transcatheter chemoembolization is useful for tumor regression during neoadjuvant therapy.
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Observational Study
Triglyceride-glucose index and risk of all-cause and cardiovascular mortality in patients with cardiovascular disease: Analysis from 1999 to 2018 NHANES data.
This research seeks to examine the correlation between the triglyceride-glucose index and the hazard of all-cause and cardiovascular death in individuals with cardiovascular disease (CVD). By evaluating the index, we can better anticipate and assess the risk and prognosis of CVD patients, and provide precise and individualized guidance for clinical treatment and management. Demographic and clinical data of 2185 CVD patients from 10 cycles of the National Health and Nutrition Examination Survey database from 1999 to 2018 were extracted for analysis. ⋯ Studies conducted on CVD individuals in the US have revealed a U-shaped correlation between triglyceride-glucose index and hazard of both all-cause and CVD-related death. However, further investigations are required to examine the particular function of index in forecasting the prognosis of CVD individuals. This will be helpful in accurately evaluating the risk and prognosis of CVD patients, and ultimately in developing more precise and personalized treatment and management strategies.
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Observational Study
Nonlinear association of alkaline phosphatase-to-albumin ratio with all-cause and cancer mortality: Evidence from NHANES 2005 to 2016.
The relationship between the alkaline phosphatase-to-albumin ratio (APAR) and mortality remains unclear. This research looked into the association between APAR levels and cause-specific mortality in US adults. A cohort of 7561 participants from National Health and Nutrition Examination Survey (2005-2016) was analyzed, with mortality outcomes collected from National Death Index records. ⋯ Thresholds of 1.289 and 2.167 might serve as potential targets for APAR to reduce all-cause and cancer mortality, respectively. Our findings suggest that APAR can be a valuable prognostic tool for clinical mortality risk assessments, helping to identify individuals at higher risk. Nevertheless, these findings necessitate validation through large-scale clinical trials for further substantiation.