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

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: To investigate the characteristics of allele frequencies for 9 red blood cell (RBC) blood group systems in the Hui ethnic voluntary blood donor population of Suzhou using real-time fluorescence PCR technology, so as to provide technical support for establishing a RBC blood group genetic database. Methods: PCR-TaqMan technology was employed to perform genotyping detection for 9 RBC blood group systems using 144 samples from Hui voluntary blood donors in Suzhou, collected between October 2023 and August 2024. Results: Blood group allele frequencies among Suzhou Hui voluntary blood donors were distributed as follows: MNS system (M=0.566 0, N=0.434 0; S=0.079 9, s=0.920 1); Lutheran system (Lu =0.003 5, Lu =0.996 5; Au =0.895 8, Au =0.104 2); Kell system (K=0.000 0, k=1.000 0; Kp =0.003 5, Kp =0.996 5; JS =0.000 0, JS =1.000 0); Duffy system (Fy =0.899 3, Fy =0.100 7); Kidd system (JK =0.451 4, JK =0.548 6); Diego system (Di =0.041 7, Di =0.958 3); Yt system (Yt =0.996 5, Yt =0.003 5); Dombrock system (Do =0.128 5, Do =0.871 5); Colton system (Co =1.000 0, Co =0.000 0). The PCR-TaqMan-based RBC blood group genotyping technology successfully completed testing for all samples. Conclusion: The MNS, Lutheran, Duffy, Kidd, Diego, and Dombrock blood group systems in the Suzhou Hui population exhibited polymorphic distribution patterns, whereas the Colton system was monomorphic. Standardized application of PCR-TaqMan technology facilitates the establishment of an RBC blood group genetic database.

Objective To understand and grasp the status quo of resistance of Culex pipiens pallens to four commonly used insecticides in Hefei City, and to provide a scientific basis for the chemical control of mosquito larvae. Methods From June to July 2023, Cx. pipiens pallens larvae were collected from 9 counties (cities and districts) in Hefei City. The LC50 of late third-instar to early fourth-instar larvae of Cx. pipiens pallens to commonly used insecticides was determined by larval immersion method (sensitive baseline method). Results Cx.pipiens pallens larvae in Hefei City exhibited different degrees of resistance to four insecticides: permethrin, beta-cypermethrin, temephos, and propoxur. The relative resistance coefficients to permethrin and beta-cypermethrin were 26.96 and 21.17, respectively, indicating the moderate resistance level. The relative resistance coefficients to propoxur were 6.70, indicating a low resistance level. The relative resistance coefficient to temephos was 2.43, indicating a sensitivity level. Culex pipiens pallens against pyrethroids such as 0.25% permethrin, 0.025% deltamethrin and 0.025% cypermethrin in 1 h knockout rate and 24 h mortality rates were 3.25% (4/123) and 46.34% (57/123), 3.60% (5/139) and 35.97% (50/139), 3.85% (6/156) and 40.38% (63/156), respectively. For 5% malathion and 0.1% propoxur, the 1 h knockdown rate and 24 h mortality rate were 97.69% (127/130) and 99.23% (129/130), 94.48% (137/145) and 100.00% (145/145), respectively. It showed resistance to 0.25% permethrin, 0.025% deltamethrin and 0.025% cypermethrin, and sensitivity to 5% malathion and 0.1% propoxur. Conclusions Culex pipiens pallens in Hefei City have developed varying degrees of resistance to parathyroid and carbamate insecticides. In the control of mosquito vectors, it is essential to strengthen the scientific and rational use of chemical control in combination with environmental and physical control measures to form an integrated control strategy. This approach will improve the control efficiency while delaying the occurrence and development of insecticide resistance.

OBJECTIVE: To develop an artificial intelligence-assisted system for the automatic detection of the features of common 21 auricular points based on the YOLOv8 neural network. METHODS: A total of 660 human auricular images from three research centers were collected from June 2019 to February 2024. The rectangle boxes and features of images were annotated using the LabelMe5.3.1 tool and converted them into a format compatible with the YOLO model. Using these data, transfer learning and fine-tuning training were conducted on different scales of pretrained YOLO neural network models. The model's performance was evaluated on validation and test sets, including the mean average precision (mAP) at various thresholds, recall rate (recall), frames per second (FPS) and confusion matrices. Finally, the model was deployed on a local computer, and the real-time detection of human auricular images was conducted using a camera. RESULTS: Five different versions of the YOLOv8 key-point detection model were developed, including YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x. On the validation set, YOLOv8n showed the best performance in terms of speed (225.736 frames per second) and precision (0.998). On the external test set, YOLOv8n achieved the accuracy of 0.991, the sensitivity of 1.0, and the F1 score of 0.995. The localization performance of auricular point features showed the average accuracy of 0.990, the precision of 0.995, and the recall of 0.997 under 50% intersection ration (mAP⁵⁰). CONCLUSION The key-point detection model of 21 common auricular points based on YOLOv8n exhibits the excellent predictive performance, which is capable of rapidly and automatically locating and classifying auricular points.
Humans ; Neural Networks, Computer ; Artificial Intelligence ; Acupuncture Points

OBJECTIVE: An intelligent moxibustion instrument based on electromyography was designed to evaluate the real-time therapeutic effect of moxibustion. METHODS: Taking Shenshu (BL23) as the subject, surface electromyography (sEMG) at the center and equidistant points of Shenshu (BL23) were collected. The characteristic parameters, integrated electromyography (iEMG) and root mean square (RMS) were calculated before and after moxibustion. After analyzing the effect of moxibustion, a function algorithm for the end-of-moxibustion was obtained. Using this algorithm and combined with STM32 technology, the control system of moxibustion instrument and the upper computer software were designed to achieve the precise control during moxibustion delivery. Finally, the function, stability and safety of the moxibustion instrument were verified through clinical trials to ensure its effectiveness in practical application. RESULTS: During one cycle of moxibustion at the center of Shenshu (BL23), the iEMG of sEMG decreased over time, meaning the decrease in muscle fatigue degree, and after one cycle of moxibustion, it elevated over time, showing the increase in muscle fatigue degree. RMS increased by 1.90% before and after moxibustion at the equidistant points of Shenshu (BL23), and the system indicated the end of moxibustion when RMS increased by 0.15%, and decreased by 0.13% at the center of Shenshu (BL23). The intelligent moxibustion instrument designed based on this algorithm can realize the function of mild moxibustion, and the effect of moxibustion can be evaluated by the real-time monitoring of RMS changes through the upper computer. During the operation of moxibustion instrument, moxa stick was fixed stably, remained a safe distance of 3 cm to 4 cm away from the skin surface. When the length of moxa stick was less than 5 cm left after ignited and the skin temperature exceeded the preset safety threshold of 48 ℃, the system was alarmed automatically. CONCLUSION The intelligent moxibustion instrument designed in the research can effectively evaluate the effect of moxibustion, and ensure the safety and stability during moxibustion delivery.
Humans ; Moxibustion/methods* ; Electromyography/instrumentation* ; Adult ; Male ; Female ; Young Adult ; Acupuncture Points ; Algorithms ; Middle Aged

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.