Organophosphate pesticide poisoning is an acute form of poisoning primarily found in underdeveloped regions. Its main clinical manifestations include muscarinic symptoms, nicotinic symptoms, and central nervous system disturbances. This report presents a case of a middle-aged female who developed extremely rare symptoms of optic nerve damage after ingesting a large amount of an organophosphate pesticide.

ObjectiveTo investigate the role of DEAD-box helicase 3 X-linked （DDX3X） in immune-mediated liver injury （ILI）， and to clarify its mechanism by regulating endoplasmic reticulum stress （ERS）-dependent apoptotic pathway and its association with the clinical progression of hepatitis B. MethodsMice were given injection of concanavalin A （ConA） via the caudal vein to establish a model of ILI， PBS （control group） and different concentrations of ConA were injected into the tail vein of hepatocyte-specific DDX3X-knockout mice （DDX3X^ΔHep and DDX3X-flox mice （DDX3X^fl/fl）， respectively.. The log-rank survival analysis， measurement of the serum levels of aspartate aminotransferase （AST） and alanine aminotransferase （ALT）， and HE staining of liver tissue were performed to assess liver injury， and qRT-PCR and Western Blot were used to measure the mRNA and protein expression levels of glucose-regulated protein 78 （GRP78）， CCAAT/enhancer-binding protein homologous protein （CHOP）， and DDX3X in liver tissue. Intraperitoneal injection of 4-phenylbutyric acid （4-PBA， 100 mg/kg） was performed to inhibit ERS. Serum samples （n=30） and liver tissue samples （n=6） were collected from healthy controls， chronic hepatitis B （CHB） patients， and hepatitis B virus-associated liver failure （HBV-LF） patients； ELISA was used to measure the serum level of DDX3X， and qRT-PCR/Western Blot was used to analyze the expression of targets in liver tissue. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the control group of mice， the expression of DDX3X in the liver of mice induced by ConA was significantly increased after liver injury （P<0.05）， and hepatocyte-specific DDX3X knockout increased the 72-hour survival rate of mice by 55% （compared with 20% in the DDX3X^fl/fl group）， with significant reductions in the serum levels of ALT and AST （P<0.000 1） and the expression levels of the ERS markers GRP78 and CHOP （P<0.05）. After ERS was inhibited by 4-PBA， there was alleviation of liver injury （with reductions in ALT and AST， P <0.001） and a reduction in DDX3X expression （P<0.01）. The analysis of clinical samples showed that the mRNA and protein expression levels of liver DDX3X in CHB patients and HBV-LF patients were significantly higher than those in healthy controls （all P<0.01）， and there was a significant increase in the serum level of DDX3X in HBV-LF patients （P<0.000 1）. ConclusionDDX3X exacerbates ILI by regulating the ERS-dependent apoptotic pathway （GRP78/CHOP）， and its expression is associated with the progression of hepatitis B. Therefore， it can be used as a potential therapeutic target.

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 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.

OBJECTIVE: To delineate the clinical and genetic features of a Chinese girl harboring a rare de novo variant of SYNGAP1 associated with Mental retardation, autosomal dominant 5 (MRD5), and to conduct a comprehensive genotype-phenotype correlation analysis within the Chinese population through an extensive literature review. METHODS: A 5-year-old girl presenting with seizures without an obvious cause was enrolled in September 2020. Genomic DNA was extracted from the patient and her parents. Whole exome sequencing (WES) was performed on the proband to identify suspected pathogenic variants based on her clinical phenotype. Sanger sequencing was used for validation, followed by bioinformatic analysis of the variant. Additionally, data from 54 previously reported Chinese cases with SYNGAP1 variants were integrated to summarize the distribution of variant types and clinical characteristics. Ethical approval was obtained from the Ethics Committee of Kunming Children's Hospital (Ethics No.: 2021-03-055-K01). RESULTS: WES identified a heterozygous nonsense variant, SYNGAP1 c.725G>A (p.Trp242*), in the proband. Sanger sequencing confirmed it was a de novo variant. According to the ACMG guidelines, this variant was classified as pathogenic (PVS1+PS2). Based on the clinical manifestations, the patient was diagnosed with MRD5. Bioinformatic analysis suggested that this variant introduces a premature stop codon at tryptophan 242, disrupting the PH domain and leading to the loss of the C2, Ras-GAP, and C-terminal domains. The pooled analysis of Chinese cases revealed that nonsense (38.2%) and frameshift (36.4%) variants were the predominant types. Intellectual disability/developmental delay was present in 100.0% of patients, epilepsy in 83.6%, and autism spectrum disorder in 41.3%. The incidence of epilepsy differed significantly among variant types (P = 0.045). Exons 8 and 15 were identified as mutation hotspots. CONCLUSION This study has identified a SYNGAP1 c.725G>A variant in the Chinese population and confirmed it as a potential cause of MRD5, which expanded the mutational spectrum of this disorder.
Humans ; Female ; Child, Preschool ; Intellectual Disability/genetics* ; ras GTPase-Activating Proteins/genetics* ; Phenotype ; Exome Sequencing ; Genetic Association Studies

Obesity and its related metabolic diseases have become a major global public health threat, and its rising incidence significantly increases the risk of cardiovascular and cerebrovascular diseases, diabetes and other complications. Pancreatic lipase is a key enzyme that converts food-borne lipids into triglycerides and fatty acids, and the effective inhibition of its activity has become an important strategy for the treatment of obesity. This paper discusses the screening methods of pancreatic lipase inhibitors, and summarizes and reviews the basic principles, advantages and disadvantages and application status of traditional screening methods, modern new screening methods and virtual screening methods. In view of the problems faced by the screening methods of pancreatic lipase inhibitors, future research urgently needs to move towards a collaborative innovation path of multi-technology integration, intelligent screening and complex systematization of traditional Chinese medicine, so as to open up new research paradigms.

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.

The morphological characteristics and pathological progression of vulnerable plaques in atherosclerosis （AS） exhibit a high degree of similarity to the concept of "abscesses and ulcers" in traditional Chinese medicine （TCM）. Therefore， vulnerable atherosclerotic plaques can be analogized as "abscesses and ulcers within the vessels"， for which deficiency， stasis and toxin constitute the core pathogenesis. The pathological evolution progresses through three sequential stages， deficiency leading to pathological substances， with phlegm and stasis accumulating into a mass； the mass transforming into putridity， with internal decay and external thinning； putridity brewing toxin， and toxin accumulation threatening rupture， ultimately resulting in plaque instability. Accordingly， a stage-specific treatment strategy is established. In the early stage， it is suggested to supplement deficiency， resolve the mass， dissipate stasis， and prevent putridity， using Liujunzi Decoction （六君子汤） combined with Danshen Decoction （丹参饮） with modifications. In the middle stage， the treatment should focus on transforming putridity to generate new tissue， and rectifying healthy qi to consolidate the body， with modified Tuoli Xiaodu Powder （托里消毒散）. In the late stage， the treatment principle is clearing and resolving putridity toxin， cooling the blood， and preventing ulcerative rupture， using modified Simiao Yong'an Decoction （四妙勇安汤） combined with Xijiao Dihuang Decoction （犀角地黄汤）.

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 By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.