Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

It is very limited that the benefit of perioperative chemotherapy in early non-small cell lung cancer (NSCLC), and the 5-year survival rate is only 5% higher than surgery. Antibodies that block programmed cell death protein 1/programmed death-ligand 1 significantly improve the survival of advanced NSCLC. The value of immunotherapy in early NSCLC is also being explored. This paper firstly summarized and analyzed the progress of immunotherapy in the perioperative period of NSCLC. Secondly, the safety and feasibility of surgical resection after neoadjuvant immunotherapy were discussed. Finally, the clinical value of different therapeutic efficacy prediction indicators was summarized, in order to clarify the current status of immunotherapy in the perioperative period, so as to improve the clinical benefits of early NSCLC patients.

AIM: To conduct whole exome sequencing(WES)analysis on three pedigrees with blepharophimosis-ptosis-epicanthus inversus syndrome(BPES)to identify the pathogenic gene loci, uncover novel mutations, and expand the mutation spectrum of the disease-associated genes.METHODS:Retrospective study. A total of 3 pedigrees and 30 patients with BPES(with criteria of bilateral blepharophimosis, ptosis, epicanthus inversus and wider inner canthal distance at birth)treated in the Ophthalmology Department of the Second People's Hospital of Yunnan Province were collected from January 2021 to August 2021, including 8 patients and 22 unaffected family members. Peripheral blood samples were collected from patients and related family members, and genomic DNA was extracted for whole exome sequencing. The sequencing results were screened to identify potential pathogenic gene loci, and candidate mutations were validated using Sanger sequencing.RESULTS:WES analysis identified pathogenic gene mutations in 3 BPES pedigrees: pedigree 1(6 members, 3 affected individuals, with a history of disease across three generations)harbored a novel heterozygous mutation in the PIEZO2 gene(located 36 bp upstream of exon 11, G>C). Sanger sequencing confirmed that this mutation was present in all affected individuals and absent in normal family members, and it represents the first report of this mutation. Pedigree 2(14 members, 2 affected individuals)and pedigree 3(10 members, 3 affected individuals)carried known heterozygous mutations in the FOXL2 gene, namely the missense mutation c.313A>C(p.N105H)and the in-frame mutation c.672_701dupAGCGGCTGCAGCAGCTGCGGCTGCAGCCGC(p.A225_A234dupAAAAAAAAAA), respectively.CONCLUSION:WES successfully identified the pathogenesis of familial congenital BPES in two families, including a known FOXL2 gene mutation and a newly discovered PIEZO2 gene mutation. These findings provide a theoretical basis for genetic counseling and reproductive guidance. Notably, the PIEZO2 gene mutation(located 36 bp upstream of exon 11, G>C)discovered in the pedigree 1 is reported for the first time and plays a critical role in the onset of the disease in this family. Further investigation of this new mutation could not only expand the mutation spectrum of BPES, but also enhance our understanding of its pathogenic mechanisms.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not adequately capture the complex biochemical properties of interest. Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties, and this is particularly true for the real industrial application scenario. Therefore, the desired testing datasets, will be small-size (∼10-100) experimental data for each protein, and involve as many proteins as possible and as many properties as possible, which is, however, lacking. Here, we present VenusMutHub, a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases, spanning 527 proteins across diverse functional properties including stability, activity, binding affinity, and selectivity. These datasets feature direct biochemical measurements rather than surrogate readouts, providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions. We evaluate 23 computational models across various methodological paradigms, such as sequence-based, structure-informed and evolutionary approaches. This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.

Pulpitis is a common infective oral disease in clinical situations. The regulatory mechanisms of immune defense in pulpitis are still being investigated. Osteomodulin (OMD) is a small leucine-rich proteoglycan family member distributed in bones and teeth. It is a bioactive protein that promotes osteogenesis and suppresses the apoptosis of human dental pulp stem cells (hDPSCs). In this study, the role of OMD in pulpitis and the OMD-induced regulatory mechanism were investigated. The OMD expression in normal and inflamed human pulp tissues was detected via immunofluorescence staining. Intriguingly, the OMD expression decreased in the inflammatory infiltration area of pulpitis specimens. The cellular experiments demonstrated that recombined human OMD could resist the detrimental effects of lipopolysaccharide (LPS)-induced inflammation. A conditional Omd knockout mouse model with pulpal inflammation was established. LPS-induced inflammatory impairment significantly increased in conditional Omd knockout mice, whereas OMD administration exhibited a protective effect against pulpitis. Mechanistically, the transcriptome alterations of OMD overexpression showed significant enrichment in the nuclear factor-κB (NF-κB) signaling pathway. Interleukin-1 receptor 1 (IL1R1), a vital membrane receptor activating the NF-κB pathway, was significantly downregulated in OMD-overexpressing hDPSCs. Additionally, the interaction between OMD and IL1R1 was verified using co-immunoprecipitation and molecular docking. In vivo, excessive pulpal inflammation in Omd-deficient mice was rescued using an IL1R antagonist. Overall, OMD played a protective role in the inflammatory response via the IL1R1/NF-κB signaling pathway. OMD may optimize the immunomodulatory functions of hDPSCs and can be used for regenerative endodontics.
Pulpitis/metabolism* ; NF-kappa B/metabolism* ; Animals ; Signal Transduction ; Humans ; Mice ; Mice, Knockout ; Dental Pulp/metabolism* ; Disease Models, Animal ; Lipopolysaccharides

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

Numerous c-mesenchymal-epithelial transition (c-MET) inhibitors have been reported as potential anticancer agents. However, most fail to enter clinical trials owing to poor efficacy or drug resistance. To date, the scaffold-based chemical space of small-molecule c-MET inhibitors has not been analyzed. In this study, we constructed the largest c-MET dataset, which included 2,278 molecules with different structures, by inhibiting the half maximal inhibitory concentration (IC₅₀) of kinase activity. No significant differences in drug-like properties were observed between active molecules (1,228) and inactive molecules (1,050), including chemical space coverage, physicochemical properties, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles. The higher chemical diversity of the active molecules was downscaled using t-distributed stochastic neighbor embedding (t-SNE) high-dimensional data. Further clustering and chemical space networks (CSNs) analyses revealed commonly used scaffolds for c-MET inhibitors, such as M5, M7, and M8. Activity cliffs and structural alerts were used to reveal "dead ends" and "safe bets" for c-MET, as well as dominant structural fragments consisting of pyridazinones, triazoles, and pyrazines. Finally, the decision tree model precisely indicated the key structural features required to constitute active c-MET inhibitor molecules, including at least three aromatic heterocycles, five aromatic nitrogen atoms, and eight nitrogen-oxygen atoms. Overall, our analyses revealed potential structure-activity relationship (SAR) patterns for c-MET inhibitors, which can inform the screening of new compounds and guide future optimization efforts.