Objective To elucidate the mechanism by which the BANCR/miR-145-5p axis regulates the AKT-GLUT1/HK2 pathway through downstream targets Reg3A/DMBT1 to facilitate the Warburg effect in gastric cancer. Methods Expression levels of BANCR, miR-145-5p, Reg3A, and DMBT1 were detected by RT-qPCR and Western blot in gastric cancer tissues and cell lines. Dual-luciferase reporter assays confirmed targeted relationships. Glycolytic capacity was assessed via glucose uptake. Immunohistochemistry analyzed molecular expression in 60 paired clinical samples. The prognostic values of key molecules in the BANCR/miR-145-5p-Reg3A/DMBT1 axis were evaluated by Kaplan-Meier survival analysis and Cox proportional hazards regression model. Results BANCR was significantly upregulated, whereas miR-145-5p was downregulated in gastric cancer tissues, correlating with advanced TNM stage, lymph node metastasis, and poor differentiation. Reg3A and DMBT1 were identified as direct targets of miR-145-5p. Knockdown of BANCR or overexpression of miR-145-5p significantly suppressed Reg3A/DMBT1 expression, reduced AKT phosphorylation and GLUT1/HK2 levels, and inhibited glycolysis. Clinical analysis revealed positive correlations between Reg3A/DMBT1 expression and glycolytic markers, with both serving as independent risk factors for poor prognosis. Conclusion The BANCR/miR-145-5p axis activates the AKT pathway by targeting Reg3A/DMBT1, thereby promoting GLUT1/HK2/LDHA-mediated glycolysis and facilitating the Warburg effect in gastric cancer. This regulatory axis represents a potential therapeutic target and prognostic biomarker.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

OBJECTIVE: To evaluate the efficacy and safety of a hospital-made resuscitation pack, a Chinese medicinal herbal compound formula designed to enhance recovery in post-bronchoscopy patients. METHODS: In this randomized, single-blind, placebo-controlled clinical trial, eligible patients were randomly assigned 1:1 to either the treatment or control groups. The patients in the treatment group applied the resuscitation pack, which contained aromatic compounded Chinese herbs. The patients in the control group applied a hospital-made, single herb placebo pack. Packs were placed on the Tiantu (CV 22) acupuncture point for 4 h as soon as the bronchoscopy finished. Efficacy indicators, such as recovery time, patients' symptoms including nausea and dizziness, and adverse events (AEs) were observed and compared. The outcome indices were evaluated at baseline, 1 and 24 h after the bronchoscopy. Subgroup analysis was further performed by patients' age and depth of sedation. RESULTS: When applying generalized estimating equations (GEE) to evaluate the intensity of post-bronchoscopy nausea and vomiting, the intensity was lower in the treatment group (163 cases) compared with the control group (162 cases; 95% CI: 0.004, 0.099, P=0.03]. Also, significantly lower intensity of nausea was observed in the 60-70 years of age subgroup (95% CI: 0.029, 0.169, P=0.006) and deep sedation subgroup (95% CI: 0.002, 0.124; P=0.04). There was no significant difference in dizziness between two groups by GEE (95% CI: -0.134, 0.297; P=0.459). In addition, no serious AEs were observed in either group. CONCLUSIONS Our study found that the resuscitation pack markedly improved patients' symptoms by reducing nausea and vomiting after bronchoscopy without AEs, compared with placebo in the perioperative period. (Trial registration No. ChiCTR2000038299).
Humans ; Male ; Middle Aged ; Female ; Bronchoscopy/adverse effects* ; Single-Blind Method ; Aged ; Drugs, Chinese Herbal/adverse effects* ; Treatment Outcome ; Resuscitation ; Adult ; Medicine, Chinese Traditional

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Objective:To discuss the effect of angiotensin(1-7)[Ang(1-7)]on high-turnover bone disease in the uremic rats,and to clarify its possible mechanism.Methods:Thirty SD rats were randomly divided into sham operation group(n=6)and experimental group(n=24).The rats in experimental group underwent 5/6 nephrectomy(Platt method)+high-phosphorus(P)diet[1.2％P,1.0％calcium(Ca)]to establish the model of uremic high-turnover bone disease.The successfully modeled rats were then randomly divided into model group,Ang(1-7)group,angiotensin-converting enzyme 2(ACE2)activator dimethylacetamide amidoxime(DIZE)group,and Mas receptor antagonist group(A779 group),with 6 rats in each group.The levels of Ca,P,blood creatinine(Scr),blood urea nitrogen(BUN),and 24 h urinary protein(UP)in serum of the rats in various groups were detected by automatic biochemical analyzer at 12 and 18 weeks after operation;immunofluorescence staining was used to detect the levels of intact parathyroid hormone(iPTH)in the rats in various groups;ELISA method was used to detect the levels of osteocalcin(OC),type Ⅰ collagen N-terminal peptide(NTX),and tartrate-resistant acid phosphatase(TRAP)-5b in serum of the rats in various groups;high-resolution micro-CT scan was used to detect the bone density(BMD),tissue mineral density(TMD),trabecular thickness(Tb.Th),and trabecular separation(Tb.Sp)in femur tissue of the rats in various groups;Von Kossa staining and Giemsa staining were used to observe the pathomorphology of cortical bone and trabecular bone of the rats in various groups,and the trabecular bone volume(TBV)was calculated;fluorescence microscope was used to detect the mineral apposition rates(MAR)of the rats in vanious groups,and the osteoblast index(OBI)and osteoclast index(OCI)of the rats in various groups were calculated.Results:At 12 and 18 weeks after operation,compared with sham operation group,the weights of the rats in model group,Ang(1-7)group,DIZE group,and A779 group were decreased(P＜0.05).At 12 and 18 weeks after operation,compared with sham operation group,the levels of 24 h UP,Scr,and BUN in serum of the rats in model group,Ang(1-7)group,DIZE group,and A779 group were increased(P＜0.05);at 18 weeks after operation,compared with model group,the levels of 24 h UP and Scr in serum of the rats in Ang(1-7)group and DIZZ group were decreased(P＜0.05),and the levels of 24 h UP,Scr and BUN in serum of the rats in A779 group were increased(P＜0.05).The successful establishment of the uremic high-turnover bone disease model was confirmed.At 12 and 18 weeks after operation,compared with sham operation group,the serum iPTH,P,OC,NTX,and TRAP-5b levels ofthe rats in model group,Ang(1-7)group,DIZE group,and A779 group were all significantly increased(P＜0.05);at 18 weeks after operation,compared with model group,the serum NTX and TRAP-5b levels of the rats in Ang(1-7)group and DIZE group were decreased(P＜0.05),while the serum iPTH,P,NTX and TRAP-5b levels in A779 group were increased(P＜0.05).The high-resolution micro-CT scan results showed that compared with sham operation group,the values of femur BMD and TMD of the rats in model group,Ang(1-7)group,DIZE group,and A779 group were all significantly decreased(P＜0.05);compared with model group,the values of femur BMD and TMD of the rats in Ang(1-7)group and DIZE group were increased(P＜0.05),while the values of BMD and TMD of the rats in A779 group were decreased(P＜0.05).Compared with sham operation group,the femur Tb.Th of the rats in model group was decreased(P＜0.05),and the Tb.Sp was increased(P＜0.05);the femur Tb.Th of the rats in Ang(1-7)group and DIZE group were increased(P＜0.05),and the Tb.Sp was decreased(P＜0.05).Compared with model group,the femur Tb.Th of the rats in A779 group was decreased(P＜0.05),and the Tb.Sp was increased(P＜0.05).The bone pathological examination results showed that compared with sham operation group,the femur TBV of the rats in model group,Ang(1-7)group,DIZZ group and A779 group were decreased(P＜0.05),and MAR,OBI and OCI were increased(P＜0.05);compared with model group,the OBI and OCI of the rats in Ang(1-7)group and DIZE group were decreased(P＜0.05),and TBV was increased(P＜0.05),while the OBI and OCI of the rats in A779 group were increased(P＜0.05),and TBV was decreased(P＜0.05).Conclusion:The ACE2/Ang(1-7)/Mas axis improves high-turnover bone disease in the uremic rats.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.