Type 2 diabetes (T2D) is an independent risk factor for cognitive impairment. The dysregulation of hypoxia inducible factor (HIF) signaling in T2D patients results in impaired adaptive responses to hypoxia, thereby accelerating the progression of complications. However, limited knowledge is available regarding its precise function in diabetes-associated cognitive impairment (DACI). Here, elevated HIF-1α levels were observed in brain endothelial cells (ECs) of db/db mice. Functionally, brain ECs-specific knockdown of H if1 a significantly ameliorated T2D-induced memory loss and neuronal damage. Glycolysis in brain ECs was inhibited in this process, as indicated by RNA-seq, leading to decreased hippocampal lactate production through reduced LDHA expression. Notably, T2D patients showed increased cerebrospinal fluid lactate levels, which were strongly associated with their cognitive dysfunction. Intrahippocampal injection of lactate accelerated cognitive dysfunction and impaired adult hippocampal neurogenesis (AHN) in db/db mice. Conversely, reducing hippocampal lactate levels through the intrahippocampal injection of oxamate delayed the onset of memory deficits. Furthermore, asiatic acid was discovered to protect db/db mice from cognitive impairment by decreasing brain endothelial HIF-1α expression and subsequently reducing hippocampal lactate-induced AHN damage. Overall, this study elucidates the inhibiting role played by endothelial HIF-1α-driven lactate in AHN and highlights a potential tactic of targeting HIF-1α in brain ECs for treating cognitive impairment.

Retinopathy of prematurity (ROP) is a vision-threatening disorder that leads to pathological growth of the retinal vasculature due to hypoxia. Here, we investigated the potential effects of alamandine, a novel heptapeptide in the renin-angiotensin system (RAS), on hypoxia-induced retinal neovascularization and its underlying mechanisms. In vivo, the C57BL/6J mice with oxygen-induced retinopathy (OIR) were injected intravitreally with alamandine (1.0 μmol/kg per eye). In vitro, human retinal microvascular endothelial cells (HRMECs) were utilized to investigate the effects of alamandine (10 μg/mL) on proliferation, apoptosis, migration, and tubular formation under vascular endothelial growth factor (VEGF) stimulation. Single-cell RNA sequencing (scRNA-seq) matrix data from the Gene Expression Omnibus (GEO) database and RAS-related genes from the Molecular Signatures Database (MSigDB) were sourced for subsequent analyses. By integrating scRNA-seq data across multiple species, we identified that RAS-associated endothelial cell populations were highly related to retinal neovascularization. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis revealed a significant decrease in alamandine levels in both the serum and retina of OIR mice compared to those in the control group. Next, alamandine ameliorated hypoxia-induced retinal pathological neovascularization and physiologic revascularization in OIR mice. In vitro, alamandine effectively mitigated VEGF-induced proliferation, scratch wound healing, and tube formation of HRMECs primarily by inhibiting the hypoxia-inducible factor-1α (HIF-1α)/VEGF pathway. Further, coincubation with D-Pro⁷ (Mas-related G protein-coupled receptor D (MrgD) antagonist) hindered the beneficial impacts of alamandine on hypoxia-induced pathological angiogenesis both in vivo and in vitro. Our findings suggested that alamandine could mitigate retinal neovascularization by targeting the MrgD-mediated HIF-1α/VEGF pathway, providing a potential therapeutic agent for OIR prevention and treatment.
Animals ; Retinal Neovascularization/prevention & control* ; Mice, Inbred C57BL ; Vascular Endothelial Growth Factor A/metabolism* ; Humans ; Mice ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Oligopeptides/therapeutic use* ; Signal Transduction/drug effects* ; Cell Proliferation/drug effects* ; Endothelial Cells/drug effects* ; Retinopathy of Prematurity/drug therapy* ; Apoptosis/drug effects* ; Cell Movement/drug effects* ; Renin-Angiotensin System/drug effects* ; Cells, Cultured

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

In recent years, the prevalence of obstructive coronary artery disease has continued to rise. Despite the widespread application of strategies such as intensive pharmacotherapy, coronary artery bypass grafting, or percutaneous coronary intervention, a subset of patients still experience recurrent angina symptoms, which severely impacts their quality of life. For such cases of refractory angina (RA), researchers domestically and internationally have explored therapeutic approaches such as spinal cord stimulation, transmyocardial laser revascularization, and sympathectomy. However, existing studies are largely limited to small-scale clinical trials, and their clinical translation still faces challenges due to insufficient validation of safety and efficacy. Injectable hydrogels, as functional materials with hydrophilic three-dimensional network structures, demonstrate unique advantages in the treatment of RA. They can not only provide mechanical support but also serve as controlled-release carriers for drugs and proteins, and synergize with gene therapy and stem cell therapy to promotemyocardial tissue repair. This article systematically reviews the application prospects of injectable hydrogels in the treatment of RA, aiming to provide insights for future therapeutic strategies.

Background::The Global Leadership Initiative on Malnutrition (GLIM) criteria were published to build a global consensus on nutritional diagnosis. Reduced muscle mass is a phenotypic criterion with strong evidence to support its inclusion in the GLIM consensus criteria. However, there is no consensus regarding how to accurately measure and define reduced muscle mass in clinical settings. This study aimed to investigate the optimal reference values of skeletal muscle mass index for diagnosing sarcopenia and GLIM-defined malnutrition, as well as the prevalence of GLIM-defined malnutrition in hospitalized cirrhotic patients.Methods::This retrospective study was conducted on 1002 adult patients with liver cirrhosis between January 1, 2018, and February 28, 2022, at Beijing You-An Hospital, Capital Medical University. Adult patients with a clinical diagnosis of liver cirrhosis and who underwent an abdominal computed tomography (CT) examination during hospitalization were included in the study. These patients were randomly divided into a modeling group (cohort 1, 667 patients) and a validation group (cohort 2, 335 patients). In cohort 1, optimal cut-off values of skeletal muscle index at the third lumbar skeletal muscle index (L3-SMI) were determined using receiver operating characteristic analyses against in-hospital mortality in different gender groups. Next, patients in cohort 2 were screened for nutritional risk using the Nutritional Risk Screening 2002 (NRS-2002), and malnutrition was diagnosed by GLIM criteria. Additionally, the reference values of reduced muscle mass in GLIM criteria were derived from the L3-SMI values from cohort 1. Multivariate logistic regression analysis was used to analyze the association between GLIM-defined malnutrition and clinical outcomes.Results::The optimal cut-off values of L3-SMI were 39.50 cm 2/m 2 for male patients and 33.06 cm 2/m 2 for female patients. Based on the cut-off values, 31.63% (68/215) of the male patients and 23.3% (28/120) of the female patients had CT-determined sarcopenia in cohort 2. The prevalence of GLIM-defined malnutrition in cirrhotic patients was 34.3% (115/335) and GLIM-defined malnutrition was an independent risk factor for in-hospital mortality in patients with liver cirrhosis ( Wald = 6.347, P = 0.012). Conclusions::This study provided reference values for skeletal muscle mass index and the prevalence of GLIM-defined malnutrition in hospitalized patients with liver cirrhosis. These reference values will contribute to applying the GLIM criteria in cirrhotic patients.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.