Objective To explore the echocardiographic features of critically ill patients with infection, and to evaluate the predictive value of echocardiographic parameters for 28-day mortality and myocardial injury. Methods Using a single-center prospective cohort design, 120 critically ill patients with infection admitted to the Intensive Care Unit, Jinshan Hospital of Fudan University from January 2024 to January 2025 were enrolled consecutively. According to the severity of infection, patients were divided into the sepsis group (n＝75) and the non-sepsis group (n＝45). Cox proportional hazards models and modified Poisson regression were used to analyze risk factors of 28-day all-cause mortality and myocardial injury. Kaplan-Meier survival curve and log-rank test were used to assess prognosis differences among patients with different ultrasound parameters. ROC curve and area under the curve (AUC) were applied to evaluate the predictive performance of ultrasound parameters, and restricted cubic spline (RCS) model was used to explore nonlinear relationships. Results The E/e′ ratio was significantly higher in the sepsis group than in the non-sepsis group (P＜0.001), while left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) were lower in the sepsis group (P＜0.05). The Cox proportional hazards model found no association between ultrasound parameters and 28-day all-cause mortality. Modified Poisson regression showed that, after adjusting for confounding factors, elevated E/e′ was an independent risk factor of myocardial injury (RR＝1.12, 95% CI 1.07–1.17, P＜0.001). Survival analysis demonstrated that patients with E/e′ ＞10.9 had lower 28-day survival rates (P＝0.02), and the AUC for E/e′ predicting myocardial injury was 0.835. RCS analysis suggested a nonlinear relationship between E/e′ and myocardial injury risk (P＜0.001). Conclusions E/e′, LVEF, and LVFS have no significant predictive value for 28-day mortality risk in critically ill patients with infections. Elevated E/e′ is an independent risk factor of myocardial injury in such patients, with a nonlinear relationship.

Objective:To explore the correlation between bile acid profiles and early efficacy of biologics for Crohn's disease (CD) .Methods:Patients with active CD who were treated with induction therapy with biologics (ustekinumab, vedolizumab, or combination therapy) in outpatient and inpatient clinics from January 2021 to March 2024 in Jinhua Central Hospital were included. Clinical data and serum bile acid profile of patients before treatment were collected. At the end of induction therapy, CD patients were categorized into remission and non-remission groups based on the CD activity index (CDAI) scores. Compare the clinical data of the two groups of patients with CD before induction treatment with biological agents, retrospective analysis of bile acid profiles in relation to early efficacy of biologics.Results:A total of 100 patients with CD were included, including 74 patients in remission group and 26 patients in non-remission group. Univariate analysis showed that hemoglobin [137 (119, 147) g/L vs. 121 (109, 136) g/L, P = 0.027], erythrocyte pressure volume [ (0.40 ± 0.06) % vs. (0.38 ± 0.05) %, P = 0.030], total bile acids[3.8 (2.4, 6.1) μmol/L比2.0 (1.5, 2.7) μmol/L, P < 0.001], cholic acid [0.188 (0.059, 0.597) μmol/L vs. 0.055 (0.024, 0.111) μmol/L, P < 0.001], chenodeoxycholic acid [0.812 (0.268, 1.717) μmol/L vs. 0.308 (0.087, 0.552) μmol/L, P < 0.001], and deoxycholic acid [0.042 (0.001, 0.299) μmol/L vs. 0.002 (0.001, 0.159) μmol/L, P = 0.028] were signficantly higher in remission group than those in unremission group. In addition, the pretreatment endoscopic score (SES-CD) [4.0 (0, 6.0) vs. 6.0 (3.0, 10.5), P = 0.025], erythrocyte sedimentation rate (ESR) [9.0 (2.8, 20.0) mm/1 h vs. 28.0 (12.8, 40.8) mm/1 h, P < 0.001] and C reactive protein (CRP) [0.6 (0.2, 6.7) mg/L vs. 9.1 (1.5, 23.9) mg/L, P < 0.001] in the remission group were lower than those in the non-remission group. Multirariate logistic regression analysis showed that chenodeoxycholic acid ( OR = 3.317, 95% CI: 1.270-12.437; P = 0.041) and ESR ( OR =0.979, 95% CI: 0.957-0.997; P = 0.034) were the independent influencing affecting the efficacy of biologics for the treatment of Crohn's disease in early stage. Conclusion:Chenodeoxycholic acid is an independent influencing factor of early efficacy of biologics for Crohn's disease.

Lipoprotein(a)[Lp(a)]is a unique plasma lipoprotein particle with a distinct structure that has garnered significant research attention due to its strong association with various cerebrovascular diseases.Recent studies underscore elevated Lp(a)levels as a critical risk factor,with multiple Lp(a)-targeted therapies advancing through clinical trials.This review explores the structural,functional,and genetic features of Lp(a),its connection to cerebrovascular diseases,and the latest therapeutic strategies aimed at reducing its impact.By consolidating these advancements,we aim to provide new insights for Lp(a)-centered research and propose innovative approaches for cerebrovascular disease prevention and management.

Spinal cord injury(SCI)can result in varying degrees of spinal motor dysfunction,partial sensory loss and sphincter dysfunction.SCI is divided into two stages:primary injury and secondary injury.The spinal cord cell necrosis during the primary injury period and apoptosis,oxidative stress and autophagy during the secondary injury period lead a large number of cell injury and permanant neurodysfunction.The histone deacetylase(HDAC)plays a key role in regulating the cellular viability and gene transcription.Neuro-dysfunction induced by SCI is associated with transcriptional dysfunction associated with unbalanced levels of protein acetylation.Valproic acid(VPA)is a inhibitor of HDAC and is usually used as an antiepileptic drug in clinic.Studies show that VPA may have the potential to treat the central nervous system diseases.VPA inhib-its HDAC,and then regulates oxidative stress,cellular autophagy,ion imbalance,microglia differentiation and inflammatory response,and plays the neuroprotective effect.This paper reviewed the related molecular mecha-nism of VPA in treating SCI.

Objective To investigate the characteristics of changes in blood uric acid(UA)and detection rate of hyperuricemia(HUA)among officers and soldiers during long-term maritime missions,as well as their related influencing factors.Methods A total of 100 servicemen were randomly selected from 240 officers and soldiers who will participate in a long-distance voyage mission.Their general information,including age,education level,administrative position,years of service on board,and department,was surveyed.Their annual data of physical examination were retrospectively analyzed and compared with the results of another 335 shore-based servicemen during the same period.On mission day 10(D10)and day 50(D50),the venous blood samples were collected from the participants to synchronously measure blood UA level and body composition indicators(body fat mass,BMI,fat percentage,fat mass,muscle mass,and muscle percentage).Additionally,on D50,Self-Rating Scale of Sleep(SRSS)and Symptom Checklist-90(SCL-90)were employed to survey their conditions.Seventy service members were randomly selected from the 100 participants to engage in aerobic exercise.The changes in UA level and detection rate of HUA among the mission personnel were analyzed,along with their influencing factors.Results The UA level and HUA detection rate in long-term navigation personnel during concurrent annual physical examinations were significantly lower than those in shore-based personnel(P<0.01).Compared to pre-voyage physical examination results,the UA level and HUA detection rate in long-term navigation personnel were significantly increased from mission day D10(P<0.001).Compared to the values at D10,the UA level and HUA detection rate at D50 showed significant decreases(P<0.05),and then essentially returned to pre-mission examination levels(P>0.05).Aged<32 years was an independent risk factor for new-onset HUA at mission D10(P<0.05).<32 years old and aerobic exercise during the voyage were independent influencing factors for HUA outcome(P<0.05).Conclusion Serum UA level and HUA detection rate among officers and soldiers participating in long-term maritime missions are relatively low before departure,but in significant increases during the early stages of the mission,particularly among those aged<32 years.Scientific aerobic exercise during the mission period helps reduce UA level and HUA detection rate,playing a crucial role in guaranteeing physical and mental health.

Objective To investigate the value of machine learning models based on contrast-enhanced CT radiomics in differentia-ting renal oncocytoma(RO)from chromophobe renal cell carcinoma(chRCC).Methods A total of 65 patients with RO and chRCC confirmed by pathology with complete clinical and imaging data were analyzed retrospectively.The patients were randomly divided into training set(n=45)and test set(n=20)according to a ratio of 7︰3.The tumor boundaries were delineated on the preoperative CT images using 3D Slicer software,and radiomics features were extracted using the Radiomics plugin.Univariate analysis,recursive fea-ture elimination(RFE),least absolute shrinkage and selection operator(LASSO)algorithms were used to select the best radiomics features.Three machine learning models were constructed on the training set and the grid search method was used to select the best combination of hyperparameters.The receiver operating characteristic(ROC)curve,calibration curve and decision curve were used to evaluate the performance of each machine learning model on the training set and test set.Results Random forest model,logistic regres-sion model and support vector machine model can better identify RO and chRCC.In the training set,the area under the curve(AUC)of random forest model and support vector machine model were 0.950[95%confidence interval(CI)0.901-0.998]and 0.955(95%CI 0.908-1.000),respectively,which were higher than the AUC of logistic regression model 0.882(95%CI 0.806-0.956).Statistical differences were found by DeLong test(P<0.05);In the test set,the AUC of random forest model,logistic regression model and support vector machine model were 0.876(95%CI 0.758-0.993),0.883(95%CI 0.768-0.997)and 0.883(95%CI 0.768-0.997),respectively.There was no significant statistical difference in the AUC of each model by DeLong test(P>0.05).The decision curve showed that all three models had significant net clinical benefits.Conclusion The machine learning model based on contrast-enhanced CT radiomics can effectively distinguish RO from chRCC.

Objective:To explore the correlation between bile acid profiles and early efficacy of biologics for Crohn's disease (CD) .Methods:Patients with active CD who were treated with induction therapy with biologics (ustekinumab, vedolizumab, or combination therapy) in outpatient and inpatient clinics from January 2021 to March 2024 in Jinhua Central Hospital were included. Clinical data and serum bile acid profile of patients before treatment were collected. At the end of induction therapy, CD patients were categorized into remission and non-remission groups based on the CD activity index (CDAI) scores. Compare the clinical data of the two groups of patients with CD before induction treatment with biological agents, retrospective analysis of bile acid profiles in relation to early efficacy of biologics.Results:A total of 100 patients with CD were included, including 74 patients in remission group and 26 patients in non-remission group. Univariate analysis showed that hemoglobin [137 (119, 147) g/L vs. 121 (109, 136) g/L, P = 0.027], erythrocyte pressure volume [ (0.40 ± 0.06) % vs. (0.38 ± 0.05) %, P = 0.030], total bile acids[3.8 (2.4, 6.1) μmol/L比2.0 (1.5, 2.7) μmol/L, P < 0.001], cholic acid [0.188 (0.059, 0.597) μmol/L vs. 0.055 (0.024, 0.111) μmol/L, P < 0.001], chenodeoxycholic acid [0.812 (0.268, 1.717) μmol/L vs. 0.308 (0.087, 0.552) μmol/L, P < 0.001], and deoxycholic acid [0.042 (0.001, 0.299) μmol/L vs. 0.002 (0.001, 0.159) μmol/L, P = 0.028] were signficantly higher in remission group than those in unremission group. In addition, the pretreatment endoscopic score (SES-CD) [4.0 (0, 6.0) vs. 6.0 (3.0, 10.5), P = 0.025], erythrocyte sedimentation rate (ESR) [9.0 (2.8, 20.0) mm/1 h vs. 28.0 (12.8, 40.8) mm/1 h, P < 0.001] and C reactive protein (CRP) [0.6 (0.2, 6.7) mg/L vs. 9.1 (1.5, 23.9) mg/L, P < 0.001] in the remission group were lower than those in the non-remission group. Multirariate logistic regression analysis showed that chenodeoxycholic acid ( OR = 3.317, 95% CI: 1.270-12.437; P = 0.041) and ESR ( OR =0.979, 95% CI: 0.957-0.997; P = 0.034) were the independent influencing affecting the efficacy of biologics for the treatment of Crohn's disease in early stage. Conclusion:Chenodeoxycholic acid is an independent influencing factor of early efficacy of biologics for Crohn's disease.

Objective To investigate the value of machine learning models based on contrast-enhanced CT radiomics in differentia-ting renal oncocytoma(RO)from chromophobe renal cell carcinoma(chRCC).Methods A total of 65 patients with RO and chRCC confirmed by pathology with complete clinical and imaging data were analyzed retrospectively.The patients were randomly divided into training set(n=45)and test set(n=20)according to a ratio of 7︰3.The tumor boundaries were delineated on the preoperative CT images using 3D Slicer software,and radiomics features were extracted using the Radiomics plugin.Univariate analysis,recursive fea-ture elimination(RFE),least absolute shrinkage and selection operator(LASSO)algorithms were used to select the best radiomics features.Three machine learning models were constructed on the training set and the grid search method was used to select the best combination of hyperparameters.The receiver operating characteristic(ROC)curve,calibration curve and decision curve were used to evaluate the performance of each machine learning model on the training set and test set.Results Random forest model,logistic regres-sion model and support vector machine model can better identify RO and chRCC.In the training set,the area under the curve(AUC)of random forest model and support vector machine model were 0.950[95%confidence interval(CI)0.901-0.998]and 0.955(95%CI 0.908-1.000),respectively,which were higher than the AUC of logistic regression model 0.882(95%CI 0.806-0.956).Statistical differences were found by DeLong test(P<0.05);In the test set,the AUC of random forest model,logistic regression model and support vector machine model were 0.876(95%CI 0.758-0.993),0.883(95%CI 0.768-0.997)and 0.883(95%CI 0.768-0.997),respectively.There was no significant statistical difference in the AUC of each model by DeLong test(P>0.05).The decision curve showed that all three models had significant net clinical benefits.Conclusion The machine learning model based on contrast-enhanced CT radiomics can effectively distinguish RO from chRCC.

Lipoprotein(a)[Lp(a)]is a unique plasma lipoprotein particle with a distinct structure that has garnered significant research attention due to its strong association with various cerebrovascular diseases.Recent studies underscore elevated Lp(a)levels as a critical risk factor,with multiple Lp(a)-targeted therapies advancing through clinical trials.This review explores the structural,functional,and genetic features of Lp(a),its connection to cerebrovascular diseases,and the latest therapeutic strategies aimed at reducing its impact.By consolidating these advancements,we aim to provide new insights for Lp(a)-centered research and propose innovative approaches for cerebrovascular disease prevention and management.

BACKGROUND: Long-term remote ischemic conditioning (RIC) has been proven to be beneficial in multiple diseases, such as cerebral and cardiovascular diseases. However, the hyperacute and acute effects of a single RIC stimulus are still not clear. Quantitative proteomic analyses of plasma proteins following RIC application have been conducted in preclinical and clinical studies but exhibit high heterogeneity in results due to wide variations in experimental setups and sampling procedures. Hence, this study aimed to explore the immediate effects of RIC on plasma proteome in healthy young adults to exclude confounding factors of disease entity, such as medications and gender. METHODS: Young healthy male participants were enrolled after a systematic physical examination and 6-month lifestyle observation. Individual RIC sessions included five cycles of alternative ischemia and reperfusion, each lasting for 5 min in bilateral forearms. Blood samples were collected at baseline, 5 min after RIC, and 2 h after RIC, and then samples were processed for proteomic analysis using liquid chromatography-tandem mass spectrometry method. RESULTS: Proteins related to lipid metabolism (e.g., Apolipoprotein F), coagulation factors (hepatocyte growth factor activator preproprotein), members of complement cascades (mannan-binding lectin serine protease 1 isoform 2 precursor), and inflammatory responses (carboxypeptidase N catalytic chain precursor) were differentially altered at their serum levels following the RIC intervention. The most enriched pathways were protein glycosylation and complement/coagulation cascades. CONCLUSIONS One-time RIC stimulus may induce instant cellular responses like anti-inflammation, coagulation, and fibrinolysis balancing, and lipid metabolism regulation which are protective in different perspectives. Protective effects of single RIC in hyperacute and acute phases may be exploited in clinical emergency settings due to apparently beneficial alterations in plasma proteome profile. Furthermore, the beneficial effects of long-term (repeated) RIC interventions in preventing chronic cardiovascular diseases among general populations can also be expected based on our study findings.
Young Adult ; Humans ; Male ; Proteome ; Cardiovascular Diseases ; Proteomics ; Ischemia ; Blood Coagulation