Background: and Purpose Accurately predicting long-term functional outcomes of basilar artery occlusion (BAO) remains challenging. We compared the predictive performance of the baseline, 24-hour, and 72-hour National Institutes of Health Stroke Scale (NIHSS) scores for 90-day BAO functional outcomes using the Acute Basilar Artery Occlusion: Endovascular Thrombectomy versus Standard Medical Treatment (ATTENTION) trial data. We identified the optimal assessment time point, determined treatment-specific NIHSS cutoff values, and explored the role of early neurological function in treatment effects. Methods: This retrospective post hoc analysis included 324 patients with acute BAO with baseline NIHSS scores ≥10 and complete NIHSS assessments at each time point. The primary outcome was a favorable 90-day functional outcome (modified Rankin Scale score, 0–3). Receiver operating characteristic curve analysis was used to assess the predictive ability of NIHSS scores. The optimal 72-hour NIHSS predictive cutoff values were determined for the endovascular treatment (EVT) and best medical management (BMM) subgroups. Results: The 72-hour NIHSS score showed the highest predictive accuracy for the primary outcome (area under the receiver operating characteristic curve [AUC]: 0.954), outperforming the 24-hour (AUC: 0.903) and baseline (AUC: 0.688) scores; its optimal predictive cut-off value was ≤11 in the EVT group (sensitivity: 85.6%, specificity: 92.9%, positive predictive value [PPV]: 91.8%, negative predictive value [NPV]: 87.4%) and ≤9 in the BMM group (sensitivity: 84.6%, specificity: 95.1%, PPV: 84.6%, NPV: 95.1%). Conclusions The 72-hour NIHSS score outperformed the baseline and 24-hour scores in predicting 90-day functional outcomes and mediating the effects of EVT. Treatment-specific 72-hour NIHSS cut-off values may guide early risk stratification and prognostic assessments.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

ObjectiveTo investigate the protective effect of magnolol ester derivative YW against cisplatin （Cis）-induced acute kidney injury （AKI） and to explore its effect and preliminary mechanisms on Cis-induced AKI. MethodsThe research group designed and synthesized the magnolol ester derivative YW using magnolol as the parent core. Molecular docking was employed to predict the binding interaction between YW and lysine acetyltransferase 7 （KAT7）. A Cis-induced AKI model was established in C57BL/6J mice. Mice were divided into the normal control group， model group， YW low/medium/high dose groups （17.5， 35， 70 mg/kg）， and the positive control amifostine group. Renal function was assessed by measuring serum creatinine （Scr） and blood urea nitrogen （BUN） levels. Pathological changes were evaluated via HE staining and scoring of kidney tissues. Protein expression levels of kidney injury molecule 1 （KIM-1）， lysine acetyltransferase 7 （KAT7）， and cyclin-dependent kinase inhibitor 1A （p21） in kidney tissues were detected by Western blot （WB）. HK-2 cells were treated with different concentrations of YW； cell viability was measured by CCK-8 assay. WB was used to detect the expression levels of the renal injury marker KIM-1， KAT7， and its downstream protein p21. Cellular senescence was assessed by senescence-associated β-galactosidase （SA-β-Gal） staining. ResultsYW could stably bind to KAT7. In vivo experiments showed that， compared with the model group， all YW dose groups， especially the medium and high doses， significantly reduced the elevated levels of Scr and BUN in AKI mice （P<0.001） and effectively ameliorated renal histopathological damage. YW significantly downregulated the protein expression levels of KIM-1， KAT7， and p21 in kidney tissues （P<0.05）. Concentrations of YW≤10 μmol/L had no significant effect on HK-2 cell viability. YW inhibited the Cis-induced decline in HK-2 cell viability （P<0.05）， suppressed the Cis-induced upregulation of KIM-1， KAT7， and p21 proteins （P<0.05）， and significantly decreased the percentage of SA-β-Gal-positive cells （P<0.01）. ConclusionYW suppresses the expression of KAT7 and p21 proteins and inhibits the decline in HK-2 cell viability in cisplatin-induced AKI， significantly mitigates HK-2 cell senescence， and improves renal function， providing preliminary experimental evidence for developing AKI treatment strategies based on structural optimization of natural products.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

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*

Objective To explore the application value of constructing Visually Accesable Rembrandt Images(VASARI)MRI feature model for the prediction of isocitrate dehydrogenase-1(IDH-1)mutations in high-grade glioma(HGG).Methods A total of 242 patients with HGG were randomly divided into training set and validation set according to the ratio of 7︰3,the VASARI features of the patients were extracted to evaluate the statistical difference between IDH-1 mutant and wild-type VASARI features of the HGG.The least abso-lute shrinkage and selection operator(LASSO)regression method was used to reduce the dimension of VASARI features and the logistic regres-sion(LR)machine learning model was used to construct the prediction model for single VASARI feature and combined features.The receiver operating characteristic(ROC)curve was used to evaluate the predictive performance of the model.Results A total of 11 VASARI fea-tures were associated with IDH-1 mutations in HGG,with statistically significant differences(P<0.05).Seven closely related fea-tures were finally screened out,and the area under the curve(AUC)of the prediction model established after the combination of the seven VASARI features was higher,and the AUC of training set was 0.908,and the AUC of validation set was 0.872.Conclusion The VASARI MRI feature model can better predict IDH-1 mutations of HGG with high predictive efficacy and has greater application value.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.