Background Lead is a typical persistent environmental pollutant that can accumulate in bones for decades. During pregnancy, alterations in calcium metabolism promote the mobilization of bone lead, resulting in secondary exposure; however, the mechanisms by which pregnancy-associated bone lead mobilization affects maternal renal function remain unclear. Objective To investigate the role of mitochondrial dysfunction in pregnancy-related bone lead mobilization-induced renal injury. Methods Newly weaned female Wistar rats were randomly assigned to a control or a lead-exposed group administered either 0.05% sodium acetate or 0.05% lead acetate in drinking water. Following a 4-week lead exposure and a 4-week washout period, the females were co-housed with healthy age-matched males for mating. Rats were sacrificed at early (gestational day 3) and late (gestational day 17) pregnancystages, respectively. Renal histopathology was assessed using hematoxylin and eosin staining staining. Mitochondria-related indicators, including oxidative stress, inflammatory responses, and energy metabolism, were measured. Differential metabolites were identified using serum metabolomics. Results Renal injury in the lead-exposed pregnant rats progressed in a time-dependent manner, characterized by degeneration of proximal tubular epithelial cells, glomerular hyaline changes, and interstitial inflammatory cell infiltration. Repeated measures ANOVA indicated a significant interaction between the treatment factor (lead exposure) and the temporal factor (gestational stage) on renal injury (P<0.001). Further analysis of mitochondrial function-related indicators in late-pregnancy renal tissue revealed that the lead exposure group exhibited significantly increased levels of malondialdehyde (MDA) and reactive oxygen species (ROS) (P<0.05), accompanied by a reduction in superoxide dismutase (SOD) and reduced glutathione (GSH) activities (P<0.05); regarding inflammatory markers, levels of interleukin-18 (IL-18) and interleukin-1β (IL-1β) were elevated (P<0.01), whereas interleukin-33 (IL-33) was decreased in the lead-exposed group (P<0.05); energy metabolism-related indicators, including adenosine triphosphate (ATP) level, Na⁺-K⁺-ATPase and Ca²⁺-Mg²⁺-ATPase activities, and mitochondrial respiratory chain complexes I, III, and V activities, were significantly reduced (P<0.05) in the lead-exposed gorup. The typical differential metabolite N-methylisoleucine, identified through serum metabolomics analysis, was negatively correlated with blood lead levels, kidney injury scores, and IL-1β, while positively correlated with catalase (CAT) activity and Ca²⁺-Mg²⁺-ATPase. Conclusions Mitochondrial dysfunction may play a critical role in renal injury induced by bone lead mobilization during late gestation.

In recent years, remarkable advances have been made in lung transplantation regarding donor evaluation, perioperative support, and immune regulation, laying a foundation for improving the long-term survival of recipients. The rational application of extended criteria donor lungs and the popularization of ex vivo lung perfusion technology have enhanced the utilization efficiency and safety of marginal donor lungs. Refined assessment of risk factors such as donors’ smoking history and infectious status has reduced the incidence of primary graft dysfunction and postoperative infection. In terms of recipient management, individualized assessment systems have been gradually optimized. The standardized application of intraoperative extracorporeal membrane oxygenation and the development of minimally invasive surgical techniques have effectively alleviated perioperative injuries. The optimization of postoperative immunosuppressive regimens and advances in rejection monitoring technologies have further improved the long-term survival of grafts. Nevertheless, chronic graft dysfunction and recurrent or refractory infections remain the major bottlenecks restricting long-term prognosis. Future research should focus on expanding donor sources, improving the repair quality of marginal donor lungs, promoting precise immunosuppression and anti-infection strategies, and comprehensively enhancing the long-term survival rate and quality of life of lung transplant recipients.

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.

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

Objective To investigate the classification capability of a deep learning classification model based on biparametric mag-netic resonance imaging(bpMRI)for clinically significant prostate cancer(csPCa)and clinically insignificant prostate cancer(cisPCa).Methods A retrospective analysis was conducted on the data of 565 prostate bpMRI patients.A deep learning classification model was established for csPCa.The patients were randomly divided into training set(452 cases)and internal test set(113 cases)at a ratio of 8︰2.Internal validation was performed,followed by external validation(external validation set)using data from 120 patients across four different hospitals.The area under the curve(AUC)of the receiver operating characteristic(ROC)curve,F1 score,precision,sensi-tivity,specificity,accuracy,and calibration curves were used to evaluate the model.Decision curve analysis(DCA)was also applied to assess the clinical benefit of the model.Results The deep learn-ing classification model for csPCa classification demonstrated the following performance across the training set,internaltest set,and external validation set:sensitivity of 0.986,0.887,and 0.750;specificity of 0.967,0.850,and 0.976;precision of 0.963,0.839,and 0.818;accuracy of 0.974,0.862,and 0.792;F1 score of 0.974,0.862,and 0.783;and AUC of 0.998,0.896,and 0.883,respec-tively.The calibration curves for all three datasets showed high consistency between predicted and actual probabilities.DCA indicated that the highest net benefit threshold probabilities for the training set,internal test set,and external validation set were 0.2-0.7,0.2-0.6,and 0.2-0.5,respectively.Conclusion The deep learning classification model demonstrated excellent performance in classifying csPCa and exhibited good generalizability,which is worhty of clinical application.

Objective To evaluate the effect of donor gender on short-term survival rate of lung transplant recipients. Methods A retrospective analysis was conducted on the data of 1 066 lung transplant recipients. The log-rank test was used to evaluate the differences in short-term fatality among different donor gender groups and donor-recipient gender combination groups. Multivariate Cox regression, propensity score (PS) regression, and propensity score matching (PSM) were employed to control for confounding factors and further assess the differences in fatality. Subgroup analyses were also performed based on donor gender. Results Multivariate Cox regression analysis showed no statistically significant differences in fatality at 30 days, 1 year, 2 years and 3 years postoperatively between male and female donor groups (all P>0.05). After PS regression and PSM, univariate Cox regression analysis indicated that recipients from female donors had a higher fatality at 2 years postoperatively compared to those from male donors, with hazard ratios (95% confidence intervals) of 1.29 (1.01-1.65) and 1.36 (1.03-1.80) respectively. Multivariate Cox regression analysis also revealed no statistically significant differences in fatality at various follow-up time points among different donor-recipient gender combination groups (all P>0.05). Subgroup analyses based on donor sex showed no statistically significant differences in fatality among recipients of different gender within either male or female donor groups (all P>0.05). Conclusions Female donors may reduce the short-term postoperative survival rate of lung transplant recipients, but this negative impact is not sustainable in the long term. At present, there is no evidence to support the inclusion of sex as a factor in lung allocation rules.

Tumor cell-intrinsic programmed death-ligand 1 (PD-L1) signals mediate tumor initiation, progression and metastasis, but their effects in ameloblastoma (AM) have not been reported. In this comprehensive study, we observed marked upregulation of PD-L1 in AM tissues and revealed the robust correlation between elevated PD-L1 expression and increased tumor growth and recurrence rates. Notably, we found that PD-L1 overexpression markedly increased self-renewal capacity and promoted tumorigenic processes and invasion in hTERT⁺-AM cells, whereas genetic ablation of PD-L1 exerted opposing inhibitory effects. By performing high-resolution single-cell profiling and thorough immunohistochemical analyses in AM patients, we delineated the intricate cellular landscape and elucidated the mechanisms underlying the aggressive phenotype and unfavorable prognosis of these tumors. Our findings revealed that hTERT⁺-AM cells with upregulated PD-L1 expression exhibit increased proliferative potential and stem-like attributes and undergo partial epithelial‒mesenchymal transition. This phenotypic shift is induced by the activation of the PI3K-AKT-mTOR signaling axis; thus, this study revealed a crucial regulatory mechanism that fuels tumor growth and recurrence. Importantly, targeted inhibition of the PD-L1-PI3K-AKT-mTOR signaling axis significantly suppressed the growth of AM patient-derived tumor organoids, highlighting the potential of PD-L1 blockade as a promising therapeutic approach for AM.
Ameloblastoma/metabolism* ; Humans ; B7-H1 Antigen/metabolism* ; Neoplasm Recurrence, Local/pathology* ; Signal Transduction ; Cell Proliferation ; Up-Regulation ; TOR Serine-Threonine Kinases/metabolism* ; Proto-Oncogene Proteins c-akt/metabolism* ; Telomerase/metabolism* ; Jaw Neoplasms/metabolism* ; Epithelial-Mesenchymal Transition ; Animals ; Cell Line, Tumor ; Female ; Male

BACKGROUND: Pre-transplant exposure to immune checkpoint inhibitors (ICIs) significantly increases the risk of allograft rejection after liver transplantation (LT); however, whether ICI-related rejection leads to increased graft loss remains controversial. Therefore, this study aimed to investigate the association between ICI-related allograft rejection and perioperative graft loss. METHODS: This was a retrospective analysis of adult liver transplant recipients with early biopsy-proven T-cell-mediated rejection (TCMR) at Liver Transplantation Center of Sun Yat-sen Memorial Hospital from June 2019 to September 2024. The pathological features, clinical characteristics, and perioperative graft survival were analyzed. RESULTS: Twenty-eight patients who underwent early TCMR between June 2019 and September 2024 were included. Based on pre-LT ICI exposure, recipients were categorized into ICI-related TCMR (irTCMR, n = 12) and conventional TCMR (cTCMR, n = 16) groups. Recipients with irTCMR had a higher median Banff rejection activity index (RAI) (6 vs . 5, P = 0.012) and more aggressive tissue damage and inflammation. Recipients with irTCMR showed higher proportion of treatment resistance, achieving a complete resolution rate of only 8/12 compared to 16/16 for cTCMR. Graft loss occurred in 5/12 of irTCMR recipients within 90 days after LT, with no graft loss in cTCMRs recipients. Cox analysis demonstrated that irTCMR with an ICI washout period of <30 days was an independent risk factor for perioperative graft loss (hazard ratio [HR], 6.540; 95% confidence interval [CI], 1.067-40.067, P = 0.042). CONCLUSION IrTCMR is associated with severe pathological features, increased resistance to treatment, and higher graft loss in adult liver transplant recipients.
Humans ; Liver Transplantation/adverse effects* ; Male ; Female ; Middle Aged ; Retrospective Studies ; Graft Rejection/immunology* ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; T-Lymphocytes/drug effects* ; Graft Survival/immunology* ; Aged

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.