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.

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.

Objective To compare clinical efficacy of robot-assisted(RA)and remote sensing navigation alignment(RSNA)system-assisted total knee arthroplasty(TKA).Methods From March 2023 to June 2023,60 patients who underwent the first unilateral TKA due to severe knee osteoarthritis(KOA)were admitted and divided into RSNA group and RA group according to different treatment methods,with 30 patients in each group.There were 5 males and 25 females in RSNA group,aged from 56 to 81 years old with an average of(66.33±7.16)years old;body mass index(BM1)ranged from 19.87 to 38.54 kg·m-2 with an average of(28.40±6.18)kg·m-2;the courses of disease ranged from 5 to 36 months with an average of(18.20±8.98)months;RSNA system was used to assist the positioning of osteotomy.There were 7 males and 23 females in RA group,aged from 55 to 82 years old with an average of(67.83±8.61)years old;BMI ranged from 19.67 to 37.25 kg·m-2 with an aver-age of(28.01±4.89)kg·m-2;the courses of disease ranged from 3 to 33 months with an average of(17.93±9.20)months;RA was performed.Operation time,incision length,latent blood loss at 2 weeks after operation and incidence of lower extremity thrombosis were compared between two groups.Hip-knee ankle angle(HKAA),HKAA deviation,lateral distal femoral angle(LDFA),medial proximal tibial angle(MPTA)and posterior tibial slope(PTS)were compared between two groups;Western Ontario McMaster Universities Osteoarthritis Index(WOMAC)and Knee Society score(KSS)were used to evaluate functional recovery before operation,3 and 6 months after operation.Results The operation was performed successfully in both groups,and there were no serious complications such as vascular and nerve injury during operation.The wound healed well at stage Ⅰafter operation,and the follow-up time was 6 months.The operation time,latent blood loss at 2 weeks after operation and inci-sion length in RSNA group were(94.35±5.75)min,(130.54±17.53)mland(14.73±2.14)cm,respectively;while(102.57±6.88)min,(146.33±19.47)ml and(16.78±2.32)cm in RA group,respectively.RSNA group was better than RA group(P＜0.05).No deep vein thrombosis occurred in both groups at 2 weeks after operation,5 patients occurred intermuscular vein throm-bosisin in RSNA group and 8 patients in RA group,the difference was not statistically significant(P＞0.05).In RSNA group,HKAA,LDFA and MPTA were(173.00±5.54)°,(86.96±3.45)°,(82.79±3.35)° before operation,and(178.34±1.85)°,(89.92±0.42)°,(89.84±0.73)° at 1 week after operation,respectively.In RA group,HKAA,LDFA and MPTA were(173.31±6.48)°,(87.15±3.40)° and(82.99±3.05)° before operation,and(178.52±1.79)°,(90.03±0.39)° and(90.15±0.47)° at 1 week after operation,respectively.HKAA,LDFA and MPTA were significantly improved in both groups at 1 week after oper-ation(P＜0.05).There were no significant difference in HKAA,LDFA,MPTA and PTS between two groups before operation and 1 week after operation(P＞0.05).There was no significant difference in deviation distribution of HKAA at 1 week after op-eration(x2=2.61 1,P=0.456).There were no significant difference in WOMAC and KSS between two groups before operation,3 and 6 months after operation(P＞0.05),and postoperative WOMAC and KSS at 3 and 6 months between two groups were im-proved compared with those before operation(P＜0.05).Conclusion Both RA and RSNA system assisted TKA could obtain ac-curate osteotomy,RA has higher surgical accuracy,RSNA system assisted operation has less trauma,and operation is simpler.

Objective To explore clinical accuracy of remote sensing navigation alignment(RSNA)system in total knee arthroplasty(TKA)and its influence on postoperative clinical efficacy.Methods From May 2021 to May 2022,60 knee os-teoarthritis(KOA)patients with Kellgren-Lawrence(K-L)grade Ⅲ to Ⅳ treated by unilateral primary TKA were selected and divided into RSNA group and traditional operation group according to treatment methods,and 30 patients in each group.There were 6 males and 24 females in RSNA group,aged from 55 to 86 years old with an average of(68.06±8.23)years old;body mass index(BMI)ranged from 22.15 to 34.58 kg·m-2 with an average of(28.20±3.01)kg·m-2;the courses of disease ranged from 2 to 60 months with an average of(18.80±14.80)months;13 patients with grade Ⅲ and 17 patients with grade Ⅳaccording to K-L grading.In traditional operation group,there were 8 males and 22 females,aged from 57 to 85 years old with an average of(67.26±6.32)years old;BMI ranged from 23.94 to 34.55 kg·m-2 with an average of(27.49±2.32)kg·m-2;the courses of disease ranged from 3 to 60 months with an average of(21.30±16.44)months;14 patients with grade Ⅲ and 16 pa-tients with grade Ⅳ according to K-L grading.Western Ontario and McMaster Universities(WOMAC)osteoarthritis index and Knee Society score(KSS)were used to evaluate functional recovery of patients.Hip-knee-ankle angle(HKAA),distal femoral valgus angle(FVA)and distal fermoral flexion angle(DFFA)were measured before operation.HKAA and HKAA deviation angle were measured at 1 week after operation,and defective rate of lower limb force line,femur prosthesis valgus angle(FP-VA)and femoral prosthesis flexion angle(FPFA),respectively,were calculated.Results There were no serious complications such as vascular and nerve injury during operation,and wound healed at stage Ⅰ.Both groups were followed up for 6 months.There were no significant difference in WOMAC index,KSS,HKAA,FVA and DFFA between two groups before operation(P＞0.05).The force line defect rate,HKAA,HKAA deviation angle,FPVA deviation angle and FPFA of RSNA group were 6.7％,(178.74±1.56)°,(1.25±1.56)°,(1.84±0.16)° and(4.85±2.46)°,respectively;while in traditional operation group were 20％,(176.73±3.46)°,(3.27±3.46)°,(2.44±0.26)°,(6.60±1.86)°;the difference between two groups were statistically sig-nificant(P＜0.05).There were no significant difference in WOMAC index and KSS between two groups at 3 and 6 months after operation(P＞0.05).Conclusion RSNA system could reduce defective rate of lower limb force line,FPVA deviation angle and FPFA after TKA,which is more accurate and easy to operate than traditional intramedullary localization surgery while ensuring postoperative efficacy.

The effect of porcine SIRT5 on replication of foot and mouth disease virus type O(FMDV-O)and the underlying regulatory mechanism were investigated.Western blot and RT-qPCR analyses were employed to monitor expression of endoge-nous SIRT5 in PK-15 cells infected with FMDV-O.Three pairs of SIRT5-specific siRNAs were synthesized.Changes to SIRT5 and FMDV-O protein and transcript levels,in addition to virus copy numbers,were measured by western blot and RT-qPCR analyses.PK-15 cells were transfected with a eukaryotic SIRT5 expression plasmid.Western blot and RT-qPCR analyses were used to explore the impact of SIRT5 overexpression on FMDV-O replication.Meanwhile,RT-qPCR analysis was used to detect the effect of SIRT5 overexpression on the mRNA expression levels of type I interferon-stimulated genes induced by SeV and FMDV-O.The results showed that expression of SIRT5 was up-regulated in PK-15 cells infected with FMDV-O and siRNA interfered with SIRT5 to inhibit FMDV-O replication.SIRT5 overexpression promoted FMDV-O replication.SIRT5 over-expression decreased mRNA expression levels of interferon-stimulated genes induced by SeV and FMDV-O.These results suggest that FMDV-O infection stimulated expression of SIRT5 in PK-15 cells,while SIRT5 promoted FMDV-O rep-lication by inhibiting production of type I interferon-stimula-ted genes.These findings provide a reference to further ex-plore the mechanism underlying the ability of porcine SIRT5 to promote FMDV-O replication.

Objective To establish a rapid screening method for 34 emerging contaminants in surface water by ultra-high performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS).Methods The pretreatment conditions of solid phase extraction(SPE)were op-timized by orthogonal experimental design and the surface water samples were concentrated and ex-tracted by Oasis? HLB and Oasis? MCX SPE columns in series.The extracts were separated by Kine-tex? EVO C18 column,with gradient elution of 0.1%formic acid aqueous solution and 0.1%formic acid methanol solution.Q-TOF-MS'fullscan'and'targeted MS/MS'modes were used to detect 34 emerging contaminants and to establish a database with 34 emerging contaminants precursor ion,prod-uct ion and retention times.Results The 34 emerging contaminants exhibited good linearity in the con-centration range respectively and the correlation coefficients(r)were higher than 0.97.The limit of de-tection was 0.2-10 ng/L and the recoveries were 81.2%-119.2%.The intra-day precision was 0.78%-18.70%.The method was applied to analyze multiple surface water samples and 6 emerging contaminants were detected,with a concentration range of 1.93-157.71 ng/L.Conclusion The method is simple and rapid for screening various emerging contaminants at the trace level in surface water.

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.

OBJECTIVE: This study investigated the effects of bis (2-butoxyethyl) phthalate (BBOP) on the onset of male puberty by affecting Leydig cell development in rats. METHODS: Thirty 35-day-old male Sprague-Dawley rats were randomly allocated to five groups mg/kg bw per day that were gavaged for 21 days with BBOP at 0, 10, 100, 250, or 500 mg/kg bw per day. The hormone profiles; Leydig cell morphological metrics; mRNA and protein levels; oxidative stress; and AKT, mTOR, ERK1/2, and GSK3β pathways were assessed. RESULTS: BBOP at 250 and/or 500 mg/kg bw per day decreased serum testosterone, luteinizing hormone, and follicle-stimulating hormone levels mg/kg bw per day (P < 0.05). BBOP at 500 mg/kg bw per day decreased Leydig cell number mg/kg bw per day and downregulated Cyp11a1, Insl3, Hsd11b1, and Dhh in the testes, and Lhb and Fshb mRNAs in the pituitary gland (P < 0.05). The malondialdehyde content in the testis significantly increased, while Sod1 and Sod2 mRNAs were markedly down-regulated, by BBOP treatment at 250-500 mg/kg bw per day (P < 0.05). Furthermore, BBOP at 500 mg/kg bw per day decreased AKT1/AKT2, mTOR, and ERK1/2 phosphorylation, and GSK3β and SIRT1 levels mg/kg bw per day (P < 0.05). Finally, BBOP at 100 or 500 μmol/L induced ROS and apoptosis in Leydig cells after 24 h of treatment in vitro (P < 0.05). CONCLUSION: BBOP delays puberty onset by increasing oxidative stress and apoptosis in Leydig cells in rats. UNLABELLED The graphical abstract is available on the website www.besjournal.com.
Rats ; Male ; Animals ; Leydig Cells/metabolism* ; Testosterone ; Glycogen Synthase Kinase 3 beta/pharmacology* ; Rats, Sprague-Dawley ; Sexual Maturation ; Testis ; Oxidative Stress ; TOR Serine-Threonine Kinases/metabolism* ; Apoptosis