Objective:To explore the impact of diabetes mellitus on perioperative myocardial injury and cardiac function recovery in patients undergoing off-pump coronary artery bypass grafting (CABG).Methods:The clinical data of 40 patients with coronary heart disease who underwent off-pump CABG in Changsha Central Hospital from 2015 to 2025 were retrospectively included. They were divided into the diabetes group (20 cases) and the control group (20 cases) according to whether they had type 2 diabetes mellitus. Myocardial injury markers (creatine kinase isoenzyme, troponin I, lactate dehydrogenase) before surgery, on the 1st and 3rd days after surgery and before discharge, as well as cardiac function indicators (B-type natriuretic peptide, left ventricular ejection fraction) before surgery and before discharge were compared between the two groups. The postoperative recovery speed (mechanical ventilation time, intensive care unit stay, vasoactive drug use time, postoperative hospital stay) was also compared between the two groups.Results:Before surgery, there were no statistically significant differences in myocardial injury markers and cardiac function indicators between the two groups (all P>0.05). On the 3rd day after surgery, lactate dehydrogenase in the diabetes group was significantly higher than that in the control group ( P<0.05), while there were no statistically significant differences in creatine kinase isoenzyme and troponin I between the two groups (all P>0.05). Before discharge, the levels of creatine kinase isoenzyme and B-type natriuretic peptide in the diabetes group were significantly higher than those in the control group (all P<0.05), and the left ventricular ejection fraction was significantly lower than that in the control group ( P<0.05). Compared with the control group, the diabetes group had significantly longer mechanical ventilation time, intensive care unit stay, and postoperative hospital stay (all P<0.05), but there was no statistically significant difference in the use time of vasoactive drugs ( P>0.05). Conclusions:For patients with coronary heart disease complicated with diabetes mellitus, their preoperative cardiac status is comparable to that of patients without diabetes mellitus, but they show a characteristic dynamic injury pattern after surgery: early elevation of lactate dehydrogenase suggests susceptibility to subcellular injury, and long-term abnormalities of creatine kinase isoenzyme, B-type natriuretic peptide, and decrease in left ventricular ejection fraction indicate myocardial repair disorders. Compared with patients without diabetes mellitus, those with diabetes mellitus require a longer recovery time after off-pump CABG, and targeted perioperative management strategies are urgently needed.

Objective:To explore the impact of diabetes mellitus on perioperative myocardial injury and cardiac function recovery in patients undergoing off-pump coronary artery bypass grafting (CABG).Methods:The clinical data of 40 patients with coronary heart disease who underwent off-pump CABG in Changsha Central Hospital from 2015 to 2025 were retrospectively included. They were divided into the diabetes group (20 cases) and the control group (20 cases) according to whether they had type 2 diabetes mellitus. Myocardial injury markers (creatine kinase isoenzyme, troponin I, lactate dehydrogenase) before surgery, on the 1st and 3rd days after surgery and before discharge, as well as cardiac function indicators (B-type natriuretic peptide, left ventricular ejection fraction) before surgery and before discharge were compared between the two groups. The postoperative recovery speed (mechanical ventilation time, intensive care unit stay, vasoactive drug use time, postoperative hospital stay) was also compared between the two groups.Results:Before surgery, there were no statistically significant differences in myocardial injury markers and cardiac function indicators between the two groups (all P>0.05). On the 3rd day after surgery, lactate dehydrogenase in the diabetes group was significantly higher than that in the control group ( P<0.05), while there were no statistically significant differences in creatine kinase isoenzyme and troponin I between the two groups (all P>0.05). Before discharge, the levels of creatine kinase isoenzyme and B-type natriuretic peptide in the diabetes group were significantly higher than those in the control group (all P<0.05), and the left ventricular ejection fraction was significantly lower than that in the control group ( P<0.05). Compared with the control group, the diabetes group had significantly longer mechanical ventilation time, intensive care unit stay, and postoperative hospital stay (all P<0.05), but there was no statistically significant difference in the use time of vasoactive drugs ( P>0.05). Conclusions:For patients with coronary heart disease complicated with diabetes mellitus, their preoperative cardiac status is comparable to that of patients without diabetes mellitus, but they show a characteristic dynamic injury pattern after surgery: early elevation of lactate dehydrogenase suggests susceptibility to subcellular injury, and long-term abnormalities of creatine kinase isoenzyme, B-type natriuretic peptide, and decrease in left ventricular ejection fraction indicate myocardial repair disorders. Compared with patients without diabetes mellitus, those with diabetes mellitus require a longer recovery time after off-pump CABG, and targeted perioperative management strategies are urgently needed.

To reduce the dependency on high-carbon-load chromatographic columns,a new method has been established for the determination of the content of docusate sodium using ion-pair high-performance liquid chromatography (IP-HPLC). Tetrapropylammonium chloride was used as the ion-pair reagent with a mobile phase, composition of acetonitrile:10 mmol/L tetrapropylammonium chloride solution = 66∶34, adjusting pH to 6.5 with 0.1% phosphoric acid solution,flow rate of 1.5 mL/min, detection wavelength of 214 nm,column temperature of 35 °C, and an injection volume of 25 μL,and quantified by an external standard method. The main peak of docusate sodium exhibited a tailing factor of 1.34. The method showed good linearity within the range of 0.02 mg/mL to 0.40 mg/mL, with a correlation coefficient (r) of 0.999 9. It also demonstrated good repeatability, with recovery ranging from 97.0% to 98.2% (n=6). The quantification limit was 3.31 μg/mL, and the detection limit was 2.76 μg/mL.In summary,the new method shows good durability, a wide linear range, and high sensitivity, it is suitable for the determination of docusate sodium.

The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

OBJECTIVE: To assess the relationship between blood pressure reactivity index (BPRI) and in-hospital mortality risk in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A retrospective cohort study was conducted to collect data from patients admitted to the intensive care unit (ICU) and clinically diagnosed with SA-AKI between 2008 and 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database in the United States. The collected data included demographic characteristics, comorbidities, vital signs, laboratory parameters, sequential organ failure assessment (SOFA) and simplified acute physiology scoreII(SAPSII) within 48 hours of SA-AKI diagnosis, stages of AKI, treatment regimens, mean BPRI during the first and second 24 hours (BPRI_0_24, BPRI_24_48), and outcome measures including primary outcome (in-hospital mortality) and secondary outcomes (ICU length of stay and total hospital length of stay). Variables with statistical significance in univariate analysis were included in LASSO regression analysis for variable selection, and the selected variables were subsequently incorporated into multivariate Logistic regression analysis to identify independent predictors associated with in-hospital mortality in SA-AKI patients. Restricted cubic spline (RCS) analysis was employed to examine whether there was a linear relationship between BPRI within 48 hours and in-hospital mortality in SA-AKI patients. Basic prediction models were constructed based on the independent predictors identified through multivariate Logistic regression analysis, and receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive performance of each basic prediction model before and after incorporating BPRI. RESULTS: A total of 3 517 SA-AKI patients admitted to the ICU were included, of whom 826 died during hospitalization and 2 691 survived. The BPRI values within 48 hours of SA-AKI diagnosis were significantly lower in the death group compared with the survival group [BPRI_0_24: 4.53 (1.81, 8.11) vs. 17.39 (5.16, 52.43); BPRI_24_48: 4.76 (2.42, 12.44) vs. 32.23 (8.85, 85.52), all P < 0.05]. LASSO regression analysis identified 20 variables with non-zero coefficients that were included in the multivariate Logistic regression analysis. The results showed that respiratory rate, temperature, pulse oxygen saturation (SpO₂), white blood cell count (WBC), hematocrit (HCT), activated partial thromboplastin time (APTT), lactate, oxygenation index, SOFA score, fluid balance (FB), BPRI_0_24, and BPRI_24_48 were all independent predictors for in-hospital mortality in SA-AKI patients (all P < 0.05). RCS analysis revealed that both BPRI showed "L"-shaped non-linear relationships with the risk of in-hospital mortality in SA-AKI patients. When BPRI_0_24 ≤ 14.47 or BPRI_24_48 ≤ 24.21, the risk of in-hospital mortality in SA-AKI increased as BPRI values decreased. Three basic prediction models were constructed based on the identified independent predictors: Model 1 (physiological indicator model) included respiratory rate, temperature, SpO₂, and oxygenation index; Model 2 (laboratory indicator model) included WBC, HCT, APTT, and lactate; Model 3 (scoring indicator model) included SOFA score and FB. ROC curve analysis showed that the predictive performance of the basic models ranked from high to low as follows: Model 3, Model 2, and Model 1, with area under the curve (AUC) values of 0.755, 0.661, and 0.655, respectively. The incorporation of BPRI indicators resulted in significant improvement in the discriminative ability of each model (all P < 0.05), with AUC values increasing to 0.832 for Model 3+BPRI, 0.805 for Model 2+BPRI, and 0.808 for Model 1+BPRI. CONCLUSIONS BPRI is an independent predictor factor for in-hospital mortality in SA-AKI patients. Incorporating BPRI into the prediction model for in-hospital mortality risk in SA-AKI can significantly improve its predictive capability.
Humans ; Acute Kidney Injury/mortality* ; Sepsis/complications* ; Retrospective Studies ; Hospital Mortality ; Prognosis ; Blood Pressure ; Intensive Care Units ; Male ; Female ; Length of Stay ; Middle Aged ; Aged ; Adult ; Logistic Models

To reduce the dependency on high-carbon-load chromatographic columns,a new method has been established for the determination of the content of docusate sodium using ion-pair high-performance liquid chromatography(IP-HPLC).Tetrapropylammonium chloride was used as the ion-pair reagent with a mobile phase,composition of acetonitrile:10 mmol/L tetrapropylammonium chloride solution=66∶34,adjusting pH to 6.5 with 0.1%phosphoric acid solution,flow rate of 1.5 mL/min,detection wavelength of 214 nm,column temperature of 35℃,and an injection volume of 25 μL,and quantified by an external standard method.The main peak of docusate sodium exhibited a tailing factor of 1.34.The method showed good linearity within the range of 0.02 mg/mL to 0.40 mg/mL,with a correlation coefficient(r)of 0.999 9.It also demonstrated good repeatability,with recovery ranging from 97.0%to 98.2%(n=6).The quantification limit was 3.31 μg/mL,and the detection limit was 2.76 μg/mL.In summary,the new method shows good durability,a wide linear range,and high sensitivity,it is suitable for the determination of docusate sodium.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Iron metabolism plays a regulatory role in various metabolic diseases, and excessive iron accumulation can increase the risk of metabolic diseases, especially type 2 diabetes mellitus (T2DM). Pathological processes such as iron deposition, iron overload, and ferroptosis can activate oxidative stress, lipid peroxidation, autophagy, and other processes, promote the amplification of inflammatory reactions and the reduction of antioxidant capacity, gradually decline the function of pancreatic islet β-cells, thereby promoting the occurrence and development of T2DM. Glucagon-like peptide-1 (GLP-1) is a physiological hormone secreted by intestinal L cells. GLP-1 analogs or GLP-1 receptor agonists can regulate the body's iron metabolism process, inhibit iron deposition, iron overload, and ferroptosis-related inflammatory reactions, promote the proliferation and differentiation of pancreatic islet β-cells, thereby reducing insulin resistance, inhibiting endothelial cell damage, and playing an important role in the prevention and treatmentof T2DM and its complications.

Advance care planning(ACP)is designed to ensure that patients lacking autonomous decision-making capacity receive medical services in accordance with their expectations and preferences.Individuals with advanced cancer are a crucial target for ACP implementation.However,the current practice of ACP in this group in China is suboptimal,demanding high-quality implementation evidence to strengthen ACP in the clinical practice of patients with advanced cancer.The existing literature can be summarized into 27 pieces of evidence across 7 dimensions,including initiation time,intervention content,intervention providers,intervention modalities,communication skills,outcome indicators,and environmental support.The aforementioned evidence could provide crucial support for improving ACP implementation for patients with advanced cancer.Subsequent research efforts should integrate patient preferences and explore the most suitable implementation strategies for ACP in the Chinese population with advanced cancer,considering diverse aspects such as traditional culture,ACP education and training,legislative support,and healthcare system refinement.

Objective To explore the role of the PPARα/HOXA10 signaling pathway in mediating the effect of adiponectin(APN)for improving endometrial receptivity in a rat model of polycystic ovary syndrome(PCOS).Methods Forty female SD rat models with letrozole-induced PCOS were randomized,with 10 normal rats as the control,into 4 equal groups for treatment with APN alone,APN combined with GW6471(a specific PPARα inhibitor)or the vehicle for 20 days,or no further treatment(PCOS model group).GW6471 treatment(daily dose of 1 mg/kg)and vehicle treatment were initiated on the 11th day following the start of APN treatment,all administered via intraperitoneal injection.The rats were observed for changes in estrous cycle,body weight,ovarian index and morphology,uterine index and morphology,serum hormone levels and lipid metabolism parameters.Endometrial expressions of PPARα and HOXA10 were detected with immunohistochemistry and Western blotting.The development of endometrial pinopodes was observed under electron microscope,and pregnancies of the rats were recorded.Results The rat models of PCOS exhibited obvious estrous cycle disorders with significantly prolonged estrous interval,increased body weight and ovarian index,decreased uterine index,disordered serum hormones and lipid metabolism(P<0.05),and polycystic ovarian changes,and these changes were significantly improved by APN treatment.Endometrial expressions of PPARα and HOXA10 were significantly lowered in PCOS rats and effectively up-regulated after APN treatment,but GW6471 treatment obviously blocked the effect of APN(P<0.05).APN showed strong protective effect against PCOS-induced impairment of endometrial pinopode development,and this effect was obviously attenuated by GW6471.APN also significantly increased the pregnancy rate and embryo number in PCOS rats,while GW6471 obviously reduced the embryo number and caused developmental retardation of the embryos.Conclusion APN can improve endometrial receptivity in PCOS rats by upregulating the PARα/HOXA10 pathway.