Machine learning risk prediction model for bloodstream infections related to totally implantable venous access ports in patients with cancer.

Objective: This study aimed to develop and validate a machine learning-based risk prediction model for catheter-related bloodstream infection (CRBSI) following implantation of totally implantable venous access ports (TIVAPs) in patients. Methods: A retrospective cohort study design was employed, utilizing the R software package mlr3. Various algorithms including logistic regression, naive Bayes, K nearest neighbor, classification tree, and random forest were applied. Addressing class imbalance, benchmarks were used, and model performance was assessed using the area under the curve (AUC). The final model, chosen for its superior performance, was interpreted using variable importance scores. Additionally, a nomogram was developed to calculate individualized risk probabilities, enhancing clinical utility. Results: The study involved 755 patients across both development and validation cohorts, with a TIVAP-CRBSI rate of 14.17%. The random forest model demonstrated the highest discrimination ability, achieving a validated AUC of 0.94, which was consistent in the validation cohort. Conclusions: This study successfully developed a robust predictive model for TIVAP-CRBSI risk post-implantation. Implementation of this model may aid healthcare providers in making informed decisions, thereby potentially improving patient outcomes.

Gut microbiota influence frailty syndrome in older adults: mechanisms and therapeutic strategies.

Frailty syndrome denotes a decreased capacity of the body to maintain the homeostasis and stress of the internal environment, which simultaneously increases the risk of adverse health outcomes in older adults, including disability, hospitalization, falls, and death. To promote healthy aging, we should find strategies to cope with frailty. However, the pathogenesis of frailty syndrome is not yet clear. Recent studies have shown that the diversity, composition, and metabolites of gut microbiota significantly changed in older adults with frailty. In addition, several frailty symptoms were alleviated by adjusting gut microbiota with prebiotics, probiotics, and symbiosis. Therefore, we attempt to explore the pathogenesis of frailty syndrome in older people from gut microbiota and summarize the existing interventions for frailty syndrome targeting gut microbiota, with the aim of providing timely and necessary interventions and assistance for older adults with frailty.

Ethyl Lithospermate Reduces Lipopolysaccharide-Induced Inflammation through Inhibiting NF-κB and STAT3 Pathways in RAW 264.7 Cells and Zebrafish.

OBJECTIVE: To explore the anti-inflammatory effects of ethyl lithospermate in lipopolysaccharide (LPS)-stimulated RAW 264.7 murine-derived macrophages and zebrafish, and its underlying mechanisms. METHODS: 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazoliumbromide (MTT) assays were performed to investigate the toxicity of ethyl lithospermate at different concentrations (12.5-100 µ mol/L) in RAW 264.7 cells. The cells were stimulated with LPS (100 ng/mL) for 12 h to establish an inflammation model in vitro, the production of pro-inflammatory cytokines interleukin (IL)-6 and tumor necrosis factor α (TNF-α) were assessed by enzyme linked immunosorbent assay (ELISA). Western blot was used to ascertain the protein expressions of signal transducer and activator of transcription 3 (STAT3), nuclear factor kappa B (NF-κB) p65, phospho-STAT3 (p-STAT3, Tyr705), inhibitor of NF-κB (IκB) α, and phospho-I κB α (p-IκB α, Ser32), and confocal imaging was used to identify the nuclear translocation of NF-κB p65 and p-STAT3 (Tyr705). Additionally, the yolk sacs of zebrafish (3 days post fertilization) were injected with 2 nL LPS (0.5 mg/mL) to induce an inflammation model in vivo. Survival analysis, hematoxylin-eosin (HE) staining, observation of neutrophil migration, and quantitative real-time polymerase chain reaction (qRT-PCR) were used to further study the anti-inflammatory effects of ethyl lithospermate and its probable mechanisms in vivo. RESULTS: The non-toxic concentrations of ethyl lithospermate have been found to range from 12.5 to 100 µ mol/L. Ethyl lithospermate inhibited the release of IL-6 and TNF-α(P<0.05 or P<0.01), decreased IκBα degradation and phosphorylation (P<0.05) as well as the nuclear translocation of NF-κB p65 and p-STAT3 (Tyr705) in LPS-induced RAW 264.7 cells (P<0.01). Ethyl lithospermate also decreased inflammatory cells infiltration and neutrophil migration while increasing the survival rate of LPS-stimulated zebrafish (P<0.05 or P<0.01). In addition, ethyl lithospermate also inhibited the mRNA expression levels of of IL-6, TNF-α, IκBα, STAT3, and NF-κB in LPS-stimulated zebrafish (P<0.01). CONCLUSION: Ethyl lithospermate exerts anti-Inflammatory effected by inhibiting the NF-κB and STAT3 signal pathways in RAW 264.7 macrophages and zebrafish.