Objective To explore the effects of different serum potassium levels on the 28-day prognosis of elderly patients with sepsis. Methods A retrospective analysis was conducted on the clinical data and laboratory indicators within 24 hours after the diagnosis in 204 elderly patients with sepsis admitted to the Department of Critical Care Medicine, Zhongshan Hospital, Fudan University from January 2018 to January 2022. According to the potassium concentrations in the blood of the patients within 24 hours after admission to intensive care unit (ICU), the patients were divided into the hyperkalemia group (K^＋≥5.3 mmol/L), normokalemia group (K^＋ 3.5–＜5.3 mmol/L), and hypokalemia group (K^＋＜3.5 mmol/L). According to 28-day outcomes, the patients were divided into the death group and survival group. The acute physiological and chronic health evaluation (APACHE) Ⅱ score, sequential organ failure assessment (SOFA) score and laboratory indicators were analyzed. Multivariate logistic regression analysis was used to analyze the risk factors for 28-day mortality in elderly patients with sepsis. Results Compared with the normokalemia group (n＝99), patients in both the hyperkalemia (n＝61) and hypokalemia (n＝44) groups had significantly higher levels of C-reactive protein (CRP) and procalcitonin (PCT), longer duration of mechanical ventilation, longer length of hospital stay and ICU stay, and higher mortality (P ＜ 0.05). The death group (n＝49) had significantly higher APACHE Ⅱ score, SOFA score, white blood cell (WBC) counts, CRP level, and PCT level than the survival group (n＝155, P＜0.05). Multivariate logistic regression analysis showed that increased or decreased serum potassium level, higher SOFA score, and increased WBC counts were independent risk factors for 28-day mortality in elderly patients with sepsis (P＜0.05). Quadratic fitted curve showed a U-shaped association between serum potassium levels and 28-day mortality risk in elderly patients with sepsis, with the lowest mortality risk observed within the intermediate (normal) range, and both hypokalemia and hyperkalemia were associated with an increased mortality risk (P＝0.182). Conclusion Both increased and decreased serum potassium levels are independent risk factors for 28-day mortality in elderly patients with sepsis, which should be given particular attention in clinical management.

Objective To investigate the neural basis of glucagon-like peptide-1(GLP-1)in regulating glucose homeostasis and elucidate the molecular mechanisms.Methods Male Glp1r-IRES-Cre,Glp1r-KO,and wild-type mice were used in this study.Fiber photometry was employed to record Ca2+signals of neurons in ventromedial hypothalamus(VMH)and patch-clamp was used to analyze electrophysiological properties of GLP-1 receptor-positive(GLP-1RVMH)neurons.Viral stereotaxic injections,chemogenetics,plasma hormone assays,and routine glucose metabolism assessments were combined to determine the regulatory role of GLP-1RVMH neurons in glucose homeostasis.Tissue and cell mitochondrial respiratory function assays,transmission electron microscopy,and conventional molecular biology methods were used to explore the mechanism by which GLP-1R agonists regulate glucose homeostasis.Results When the glucose concentration decreased from 5.0 mmol/L to 0.5 mmol/L,the action potential frequency of GLP-1RVMH neuron decreased significantly[(4.51±0.80)Hz vs.(1.43±0.51)Hz,P<0.01].Activation of GLP-1RVMH neuron significantly enhanced insulin secretion[(7.60±0.56)μU/mL vs.(11.34±0.93)μU/mL,P<0.01],while inhibition of these neuronal activities impaired the hypoglycemic efficiency of GLP-1 agonists[(32.03%±0.91%)vs.(25.77%±1.09%),P<0.001)].Mechanistically,GLP-1 regulated glucose homeostasis through Drp1 phosphorylation-mediated mitochondrial fission and improved mitochondrial energy metabolism.Conclusion GLP-1RVMH neurons are a class of glucose-excited neurons,and which activated directly promotes secretion of insulin.The hypoglycemic effect of GLP-1R agonists depend on the neuronal activity of GLP-1RVMH.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

Objective To explore the efficacy and action mechanism of a novel phenothiazine derivative,DA414,in rats with intracerebral hemorrhage(ICH).Methods Male Sprague-Dawley(SD)rats(aged 8～10 weeks,weighing 250～300 g)were randomly divided into sham operation,model,and low and high dose DA414 groups[5 and 10 mg/(kg·d)],with 20 animals per group.The size and extent of injury in the ICH area were measured by magnetic resonance imaging(MRI)and histopathological slices.Neurological function was evaluated with a behavioral grading system.Western blotting was used to detect the expression of ferroptosis-related factor,glutathione peroxidase 4(GPX4).Multiplex immunohistochemistry was employed to quantitatively evaluate microglial activation in perihematomal tissue.RT-qPCR was applied to measure the mRNA expression levels of NLRP3 inflammasome components(NLRP3,Caspase-1,IL-1β),pro-inflammatory(IL-18,TLR4,IL-6,TNF-α)and anti-inflammatory cytokines(IL-4,IL-10).The integrity of the blood-brain barrier(BBB)was assessed by Evans blue staining,and the biosafety of DA414 for the liver,kidneys and heart was assessed by HE staining and clinical biochemical tests.Results DA414 significantly promoted the absorption of hematoma,reduced neuronal injury,and improved neurological function scores.DA414 significantly up-regulated the ferroptosis regulatory factor GPX4(P<0.01),and also significantly inhibited the activation of microglia after ICH(P<0.001).RT-qPCR indicated that DA414 treatment resulted in down-regulation of mRNA expression in the inflammasome pathway(NLRP3,Caspase-1,IL-1β,all P<0.01)and pro-inflammatory cytokines(TLR4,IL-6,both P<0.05;IL-18,TNF-α,both P<0.01)and up-regulation of anti-inflammatory cytokines(IL-4,IL-10,both P<0.05),suggesting that DA414 exerts its neuroprotective effect probably by regulating ferroptosis and inflammation.Safety assessment revealed that DA414 had no significant effect on BBB integrity or damage to the liver,kidneys,and heart in rats.Conclusion DA414 exerts significant neuroprotective effects in ICH model by targeted inhibition for ferroptosis and modulating inflammatory response.Our study provides an experimental foundation for ICH treatment.

Endovascular treatment is currently the most targeted therapeutic approach for acute ischemic stroke, which can recanalize the occluded blood vessels, restore the perfusion of ischemic penumbra, and reduce the size of infarct area. At present, evaluation of the ischemic penumbra mainly relies on imaging examinations; however, these examinations are difficult to fully reflect the cellular pathophysiological changes of brain tissues and lack unified standards; therefore, a more accurate method is urgently needed for evaluating the ischemic penumbra. This article summarizes the current dilemmas faced by imaging examinations in evaluating the ischemic penumbra and research status of biological markers in assessing the ischemic penumbra, proposing that volume of brain tissues that can be salvaged and biological markers as shown by imaging should be simultaneously focused during stroke treatment, so as to accurately evaluate the ischemic penumbra and improve the clinical prognosis to the greatest extent.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective To investigate the neural basis of glucagon-like peptide-1(GLP-1)in regulating glucose homeostasis and elucidate the molecular mechanisms.Methods Male Glp1r-IRES-Cre,Glp1r-KO,and wild-type mice were used in this study.Fiber photometry was employed to record Ca2+signals of neurons in ventromedial hypothalamus(VMH)and patch-clamp was used to analyze electrophysiological properties of GLP-1 receptor-positive(GLP-1RVMH)neurons.Viral stereotaxic injections,chemogenetics,plasma hormone assays,and routine glucose metabolism assessments were combined to determine the regulatory role of GLP-1RVMH neurons in glucose homeostasis.Tissue and cell mitochondrial respiratory function assays,transmission electron microscopy,and conventional molecular biology methods were used to explore the mechanism by which GLP-1R agonists regulate glucose homeostasis.Results When the glucose concentration decreased from 5.0 mmol/L to 0.5 mmol/L,the action potential frequency of GLP-1RVMH neuron decreased significantly[(4.51±0.80)Hz vs.(1.43±0.51)Hz,P<0.01].Activation of GLP-1RVMH neuron significantly enhanced insulin secretion[(7.60±0.56)μU/mL vs.(11.34±0.93)μU/mL,P<0.01],while inhibition of these neuronal activities impaired the hypoglycemic efficiency of GLP-1 agonists[(32.03%±0.91%)vs.(25.77%±1.09%),P<0.001)].Mechanistically,GLP-1 regulated glucose homeostasis through Drp1 phosphorylation-mediated mitochondrial fission and improved mitochondrial energy metabolism.Conclusion GLP-1RVMH neurons are a class of glucose-excited neurons,and which activated directly promotes secretion of insulin.The hypoglycemic effect of GLP-1R agonists depend on the neuronal activity of GLP-1RVMH.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.