Objective To investigate the expression profile, prognostic value, gene co-expression network, and immunomodulatory role of BRF1 in a pan-cancer context, and to explore its biological functions and molecular regulatory mechanisms in esophageal squamous cell carcinoma (ESCC). Methods The pan-cancer dataset from The Cancer Genome Atlas (TCGA) was utilized to analyze the differential expression of BRF1 in tumor versus normal tissues, its association with patient survival, pathway enrichment for co-expressed genes, and immune features (including immune checkpoints, cytokines, and immune cell infiltration). The expression profile of BRF1 in ESCC was validated using the Gene Expression Omnibus (GEO) database. In vitro, BRF1 was knocked down in ESCC cells using siRNA. Cell proliferation and migration were assessed by MTT and Transwell assays, respectively. The expression levels of proliferation- and migration-related proteins were detected by Western blotting. The correlation between BRF1 and ferroptosis was analyzed using TCGA data. Results BRF1 was significantly upregulated in over 20 types of cancer, and its high expression was associated with poor prognosis in patients with adrenocortical carcinoma and prostate adenocarcinoma. BRF1 was found to positively regulate the T-cell-mediated cell death pathway in esophageal adenocarcinoma and was associated with the circadian rhythm regulation pathway in pancreatic adenocarcinoma. The correlation of BRF1 with immune checkpoints, cytokine networks, and immune cell infiltration was found to be cancer type-specific. In vitro experiments demonstrated that knocking down BRF1 significantly inhibited the proliferation of ESCC cells, accompanied by the downregulation of the proliferation marker PCNA. Cell migration was also significantly impaired, with decreased expression of Vimentin and MMPs and increased expression of E-cadherin. Furthermore, the expression of BRF1 was positively correlated with that of ferroptosis-antagonizing genes, such as GPX4, HSPA5, and SLC7A11. Conclusion BRF1 plays complex roles in pan-cancer, participating in the regulation of tumorigenesis, progression, and immune infiltration. BRF1 promotes the proliferation and migration of ESCC cells, a mechanism potentially associated with the regulation of ferroptosis resistance. These findings suggest that BRF1 could be a potential therapeutic target for ESCC.

Stroke is the leading cause of death and disability among adults in China， and its common complications include digestive system abnormalities， cognitive impairment， depression， stroke-associated pneumonia， and hemiplegia. The combination of traditional Chinese and Western medicine has great potential in treating post-stroke complications. Xinglou Chengqitang （XLCQT） is a representative prescription of alleviating the disease in the upper part by treating the lower part. It has definite therapeutic effect and high safety. Clinically， XLCQT is often used to treat stroke and its complications. However， the quantity and quality of clinical trials of XLCQT in treating post-stroke complications need to be improved. Additionally， since the basic research is weak， the material basis and multi-target mechanism for the efficacy of this prescription are unknown. This article reviews XLCQT in terms of the pharmacodynamic basis， medicinal properties， safety evaluation， and progress in clinical research and mechanisms in treating post-stroke complications. This article summarizes 22 key active ingredients of XLCQT in treating acute stroke complicated with syndrome of phlegm heat and fu-organ excess. Among these key active ingredients， resveratrol， kaempferol， luteolin， chrysoeriol， apigenin， （+）-catechin， and adenosine have good pharmacokinetic properties and high bioavailability. The mechanisms of XLCQT in treating post-stroke complications are complex， including inflammatory response， brain-gut axis， hypothalamic-pituitary-adrenal （HPA） axis， intestinal flora， neurotrophic factors， autophagy， oxidative stress， and free radical damage. This review helps to deeply understand the pharmacodynamic basis and mechanisms of XLCQT in treating post-stroke complications and provides a theoretical basis for the clinical application of XLCQT against post-stroke complications and the development of drugs.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To construct and evaluate a prognostic model for clear cell renal cell carcinoma(ccRCC)based on preoperative lipid ratios, cM0(i+)staging, and other clinical characteristics, so as to provide a precise tool for clinical prognosis assessment. Methods A retrospective analysis was conducted on the clinical data of 215 ccRCC patients treated in our hospital during May 2014 and May 2023. Lipid ratios were calculated using preoperative lipid data, and patients were divided into cM0(i+)stage or cM0 stage according to postoperative circulating tumor cells(CTCs)test results. The optimal lipid ratio and cutoff value were selected using receiver operating characteristic(ROC)curves and the X-tile method. Patients were subdivided into three groups based on the level of the low-density lipoprotein cholesterol to non-low-density lipoprotein cholesterol ratio(LNLR)and cM0(i+)staging:Group A [LNLR＞1.68 and diagnosed with cM0(i+)], Group B [LNLR＞1.68 or diagnosed with cM0(i+)], and Group C(LNLR ≤1.68 and diagnosed with cM0). Kaplan-Meier survival analysis was used to plot survival curves for patients in different groups. The log-rank test was employed to compare differences in recurrence-free survival(RFS)among the subgroups. Multivariate Cox regression analysis was conducted to identify the independent risk factors influencing RFS, and a nomogram prediction model was constructed based on these results. The predictive performance of the model was validated using ROC curves, calibration curves, and decision curves. Results ROC curves were plotted for lipid markers, and LNLR was identified as the most predictive for RFS. Its optimal cutoff point was 1. 68. Patients in Group A experienced a significantly shorter postoperative RFS. Multivariate Cox regression analysis identified preoperative LNLR, cM0(i+)staging, pathological grade, and stage as independent risk factors for RFS. A nomogram model was constructed based on these risk factors. The area under the ROC curve(AUC)for 1-, 3-, and 5-year RFS was 0.896(95% CI:0.8121-0.9627), 0.890(95%CI:0.7879-0.9641), and 0.870(95%CI:0.7697-0.9526), indicating good discriminatory ability and predictive performance. Calibration plots demonstrated good agreement between predicted and actual outcomes. Clinical decision curve analysis showed high clinical net benefit. Conclusion Preoperative LNLR level is an independent risk factor for RFS in ccRCC patients. The prognostic prediction model based on LNLR, cM0(i+)staging, patient pathological grade, and staging demonstrates good predictive performance for RFS and holds potential clinical application value.

OBJECTIVES: Tiletamine, a veterinary anesthetic, has emerged as a novel psychoactive substance and has been abused in many parts of the world, causing great harm to public health. However, the sensitivity of existing detection methods cannot meet the needs of forensic practice. This study aims to establish an ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the determination of tiletamine and its metabolite desethyltiletamine in human biological samples, and to verify its applicability in forensic practice. METHODS: SKF_525A was used as the internal standard. Biological samples were extracted with acetonitrile containing 1 ng/mL SKF_525A, vortexed for 10 min, ultrasonicated for 20 min, centrifuged at 10 000 r/min for 10 min, and 500 μL of the supernatant was filtered through a 0.22 μm membrane. Analyses were performed using an ACQUITY UPLC H-Class PLUS system and an XEVO TQ-S Micro triple quadrupole mass spectrometer. An ACQUITY UPLC^® BEH C18 (1.7 µm, 2.1 mm×100 mm) column at a flow rate of 0.3 mL/min was used, and four mobile phase systems were tested to optimize separation. Detection used positive electrospray ionization (ESI+) in multiple reaction monitoring (MRM) mode, with quantifier ion transitions of mass to charge 224.043→179.016 for tiletamine and mass to charge 196.08→151.06 for desethyltiletamine. Calibration curves were established over 0.1-200 ng/mL in spiked blood samples. The linear range, limit of detection (LOD), and limit of quantification (LOQ) were determined. Low (5 ng/mL), medium (20 ng/mL), and high (100 ng/mL) concentrations of tiletamine were spiked into blood, liver, and kidney to evaluate precision, accuracy, matrix effect, recovery, and stability. Finally, actual forensic case samples were tested to validate applicability. RESULTS: The established UPLC-MS/MS method achieved simultaneous detection of tiletamine and desethyltiletamine in human biological samples, with retention times of 3.42 min and 2.82 min, respectively. Using mobile phase A (20 mmol/L ammonium acetate and 0.1% formic acid in water) and mobile phase B (acetonitrile) produced the best separation. In blood, tiletamine showed good linearity from 0.1-200 ng/mL (r=0.992, R²=0.983), LOD 0.03 ng/mL, LOQ 0.1 ng/mL, recovery 92%-107%, and matrix effect 71%-99%. In liver and kidney, recoveries were 91%-98% and 93%-104%, and matrix effects were 69%-96% and 72%-100%, respectively. Intra- and inter-day precision [expressed as relative standard deviation (RSD)] and accuracy [expressed as relative error (RE)] were within 15%, and samples were stable at -20 ℃. Tiletamine was detected in actual case samples at 0.37 μg/mL (blood), 0.15 μg/g (liver), 0.11 μg/g (kidney) in case 1, and 8.75 ng/mL (blood) in case 2; desethyltiletamine was also detected in blood. CONCLUSIONS The UPLC-MS/MS method is efficient, accurate, and sensitive, and is suitable for detecting tiletamine and desethyltiletamine in human biological samples.
Tandem Mass Spectrometry/methods* ; Humans ; Chromatography, High Pressure Liquid/methods* ; Substance Abuse Detection/methods* ; Liquid Chromatography-Mass Spectrometry

Antibody (Ab) humanization is critical to reduce immunogenicity and enhance efficacy in the preclinical phase of the development of therapeutic Abs originated from animal models. Computational suggestions have long been desired, but available tools focused on immunogenicity calculation of whole Ab sequences and sequence segments, missing the individual residue sites. This study introduces Site-specific Immunogenicity for Therapeutic Antibody (SITA), a novel computational framework that predicts B-cell immunogenicity score for not only the overall antibody, but also individual residues, based on a comprehensive set of amino acid descriptors characterizing physicochemical and spatial features for antibody structures. A transfer-learning-inspired framework was purposely adopted to overcome the scarcity of Ab-Ab structural complexes. On an independent testing dataset derived from 13 Ab-Ab structural complexes, SITA successfully predicted the epitope sites for Ab-Ab structures with a receiver operating characteristic (ROC)-area unver the ROC curve (AUC) of 0.85 and a precision-recall (PR)-AUC of 0.305 at the residue level. Furthermore, the SITA score can significantly distinguish immunogenicity levels of whole human Abs, therapeutic Abs and non-human-derived Abs. More importantly, analysis of an additional 25 therapeutic Abs revealed that over 70% of them were detected with decreased immunogenicity after modification compared to their parent variants. Among these, nearly 66% Abs successfully identified actual modification sites from the top five sites with the highest SITA scores, suggesting the ability of SITA scores for guide the humanization of antibody. Overall, these findings highlight the potential of SITA in optimizing immunogenicity assessments during the process of therapeutic antibody design.

BACKGROUND: Neoadjuvant immunochemotherapy has emerged as an indispensable therapeutic modality for non-small cell lung cancer (NSCLC). However, its clinical application experience remains limited, and the associations between various clinical factors and treatment benefits remain undefined. This study aims to evaluate the efficacy and safety of neoadjuvant immunochemotherapy in patients with stage IB-IIIB NSCLC in a real-world setting, analyze survival outcomes among subgroups with diverse clinical characteristics, and identify potential clinical predictive factors for pathological response. METHODS: This study included patients with stage IB-IIIB NSCLC who underwent radical lung resection after 2-4 cycles of neoadjuvant immunochemotherapy at Peking University People's Hospital between August 2019 and March 2024. Medical records and follow-up information were collected to analyze therapeutic response, adverse events and survival outcomes. Logistic analysis was used to identify clinical predictors of pathological response. RESULTS: Among 183 enrolled patients, 116 (63.4%) were stage III. Grade 3-4 immune-related adverse events (irAEs) occurred in 39 (21.3%) patients. Radiographic complete response (CR) or partial response (PR) was achieved in 118 (64.5%) patients. R0 resection was achieved in 180 (98.4%) patients. Major pathologic response (MPR) was observed in 107 (58.5%) patients, with 78 (42.6%) achieving pathologic complete response (pCR). Squamous cell carcinoma and radiographic objective response were associated with pathological response (pCR/MPR). With a median follow-up of 22.1 [interquartile range (IQR): 18.3-32.2] months, the 2-year event-free survival (EFS) and overall survival (OS) rates were 82.5% and 90.4%, respectively. Achievement of pathological response (pCR/MPR) was correlated with prolonged survival outcomes. CONCLUSIONS Neoadjuvant immunochemotherapy is safe and effective for patients with stage IB-IIIB NSCLC. Patients achieving pCR or MPR exhibit significantly better survival benefits from neoadjuvant immunochemotherapy. Squamous cell carcinoma and radiographic objective response can serve as clinical predictors of pathological response.
Humans ; Carcinoma, Non-Small-Cell Lung/mortality* ; Male ; Lung Neoplasms/mortality* ; Female ; Middle Aged ; Neoadjuvant Therapy/adverse effects* ; Aged ; Neoplasm Staging ; Adult ; Immunotherapy/adverse effects* ; Treatment Outcome ; Retrospective Studies

Antibody humanization is critical to reduce immunogenicity and enhance efficacy in the preclinical phase of the development of therapeutic antibodies originated from animal models.Computational suggestions have long been desired,but available tools focused on immunogenicity calculation of whole antibody sequences and sequence segments,missing the individual residue sites.This study introduces Site-specific Immunogenicity for Therapeutic Antibody(SITA),a novel computational framework that predicts B-cell immunogenicity score for not only the overall antibody,but also individual residues,based on a comprehensive set of amino acid descriptors characterizing physicochemical and spatial features for antibody structures.A transfer-learning-inspired framework was purposely adopted to overcome the scarcity of Antibody-Antibody structural complexes.On an independent testing dataset derived from 13 Antibody-Antibody structural complexes,SITA successfully predicted the epitope sites for Antibody-Antibody structures with a receiver operating characteristic(ROC)-area unver the ROC curve(AUC)of 0.85 and a precision-recall(PR)-AUC of 0.305 at the residue level.Furthermore,the SITA score can significantly distinguish immunogenicity levels of whole human antibodies,therapeutic antibodies and non-human-derived antibodies.More importantly,analysis of an additional 25 thera-peutic antibodies revealed that over 70％of them were detected with decreased immunogenicity after modification compared to their parent variants.Among these,nearly 66％antibodies successfully iden-tified actual modification sites from the top five sites with the highest SITA scores,suggesting the ability of SITA scores for guide the humanization of antibody.Overall,these findings highlight the potential of SITA in optimizing immunogenicity assessments during the process of therapeutic antibody design.

OBJECTIVE: To explore the clinical phenotype and genetic characteristics of a child with hereditary Spastic paraplegia type 52 (SPG52) due to variant of AP4S1 gene. METHODS: A child diagnosed with SPG52 at the Department of Pediatrics of the First Affiliated Hospital of Anhui Medical University in May 2010 was selected as the study subject. Whole-exome sequencing (WES) was carried out for the child and his parents. Candidate variants were confirmed by Sanger sequencing. Pathogenicity of the candidate variant was interpreted according to the guidelines from the American College of Medical Genetics and Genomics (ACMG). The study protocol was approved by the Ethics Committee of the Hospital (Ethics No.: PJ2024-04-56). RESULTS: The child had presented with global developmental delay from infancy, and featured progressive lower limb spasticity, contractures, talipes equinovarus, and muscle weakness, but with no significant facial dysmorphism. His first febrile seizure occurred before one year of age, followed by several afebrile seizures. The seizures had remitted after 3 to 4 years of antiepileptic therapy, and electroencephalography was normal. However, he had severe intellectual disability, and MRI revealed reduced white matter. WES identified a homozygous AP4S1 c.289C>T (p.Arg97*) variant in the child, for which both of his parents were heterozygous carriers. The variant was rated as pathogenic based on the ACMG guidelines. Literature review has identified 8 publications on SPG52, involving 18 patients from 12 pedigrees. Combined with our case, 14 had carried homozygous variants of the AP4S1 gene, 3 had compound heterozygous variants, and 2 had heterozygous variants, involving 12 distinct variant sites. The cohort included 7 males and 12 females. All patients exhibited progressive lower limb spasticity and weakness as the primary feature, with certain loss of independent ambulation. Most patients had intellectual disability, some had distinctive facial features, though febrile seizures or epilepsy were common. Electroencephalography often showed increased slow-wave activity. Brain MRI frequently demonstrated ventriculomegaly, a thin corpus callosum, and reduced white matter. CONCLUSION The homozygous c.289C>T (p.Arg97*) variant of the AP4S1 gene probably underlay the pathogenesis of SPG52 in this child. Above discovery has expanded the mutational spectrum of AP4S1 and provided valuable insights for the genetic diagnosis, counseling, and clinical management of SPG52.
Humans ; Male ; Spastic Paraplegia, Hereditary/genetics* ; Child, Preschool ; Female ; Exome Sequencing ; Child ; Infant ; Adaptor Protein Complex 4/genetics* ; Phenotype ; Mutation