PubMed HealthSearch

Biomedical subjects

Mengyao Liu

Publications and source records attributed to Mengyao Liu.

2 recordsLinked to original sources

Glucose-responsive probiotics for glycaemic modulation in mice and monkeys.

Sustained and controlled delivery of glucose-lowering agents using engineered designer cells is recognized as an effective strategy for diabetes therapy1. However, current technologies rely on external signal control or have been programmed into mammalian cells using synthetic gene networks, which pose safety concerns arising from transplantation2,3. Here we developed an engineered oral-deliverable glucose-sensing and functional response probiotic living drug for 'sense-and-respond'-based control of diabetic blood glucose. We created a glucose sensor based on a synthetic gene circuit that incorporates the glucose-responsive transcriptional regulator HexR, coupled with a synthetic promoter. Upon oral administration of the engineered probiotics carrying the sensor, the cells reside temporarily in the intestine and regulate the expression of therapeutic transgenes in response to glucose levels that exceed the normal threshold. We show efficacy from the engineered probiotics for glycaemic control in multiple diabetic mouse and non-human primate models, demonstrating that long-term oral administration drives clear improvements in lipid profiles, while also attenuating development of multiple diabetic complications. Our probiotics-based living drug enables therapeutic dosing in response to real-time blood glucose levels, providing a programmable, orally deliverable sense-and-respond platform for metabolic therapy without transplantation.

Animals

Risk prediction models for blood transfusion in patients undergoing total hip and knee arthroplasty: a systematic review and meta-analysis.

OBJECTIVE: To systematically review and evaluate published risk prediction models for perioperative blood transfusion in patients undergoing total hip or knee arthroplasty (THA/TKA). METHODS: We systematically searched PubMed, Web of Science, the Cochrane Library, and Embase from inception to May 31, 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability using the Prediction model Risk Of Bias Assessment Tool (PROBAST). The area under the receiver operating characteristic curve (AUC) values were pooled via a meta-analysis using Stata 18.0. RESULTS: d Fourteen studies containing 36 prediction models were included. The incidence of blood transfusion among THA/TKA patients ranged from 3.2% to 30.8%. Preoperative hemoglobin (Hb) level, tranexamic acid (TXA) use, operative duration, intraoperative blood loss, and age were the most frequently incorporated predictors. Model sensitivity ranged from 58% to 94.5%, and specificity ranged from 71.3% to 94%. Meta-analysis showed that the pooled AUC value of the 13 validated models was 0.87 (95% CI: 0.85-0.90), suggesting good discriminatory performance. All models were rated as having a high risk of bias. The applicability of four studies was rated as unclear. CONCLUSION: Although the included studies demonstrated promising discriminative ability of prediction models for blood transfusion in THA/TKA, all were assessed as having a high risk of bias using the PROBAST tool. Therefore, future research should prioritize the development of models with larger sample sizes, rigorous study designs, and multicenter external validation.

Humans