Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challenges related to data standardization,completeness,and accuracy,primarily due to the decen-tralized distribution of TCM resources.To address these issues,we developed a platform for TCM knowledge discovery(TCMKD,https://cbcb.cdutcm.edu.cn/TCMKD/).Seven types of data,including syndromes,formulas,Chinese patent drugs(CPDs),Chinese medicinal materials(CMMs),ingredients,targets,and diseases,were manually proofread and consolidated within TCMKD.To strengthen the integration of TCM with modern medicine,TCMKD employs analytical methods such as TCM data mining,enrichment analysis,and network localization and separation.These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights.In addition to its analytical capabilities,a quick question and answer(Q&A)system is also embedded within TCMKD to query the database efficiently,thereby improving the interactivity of the platform.The platform also provides a TCM text annotation tool,offering a simple and efficient method for TCM text mining.Overall,TCMKD not only has the potential to become a pivotal repository for TCM,delving into the pharmaco-logical foundations of TCM treatments,but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems,extending beyond just TCM.

OBJECTIVE: To analyze the clinical manifestations and genotype of a child with You-Hoover-Fong syndrome (YHFS) to enhance clinical understanding of this disease. METHODS: Clinical data of a child who visited the Department of Pediatric Neurorehabilitation of the Women's and Children's Hospital Affiliated to Xiamen University in March 2025 for global developmental delay was collected. Peripheral blood samples of the child and his parents were collected for chromosomal microarray analysis and whole exome sequencing (WES). Sanger sequencing was performed for parental validation, and candidate variant was assessed for pathogenicity. Clinical and genetic analyses were conducted based on the child's phenotype. A literature review was performed by retrieving previously reported cases of YHFS due to TELO2 gene variants. This study was approved by the Medical Ethics Committee of the Women's and Children's Hospital Affiliated to Xiamen University (Ethics No.: KY-2023-044-K02). RESULTS: The child was a 1-year-and-2-month-old male presenting with global developmental delay, encephalodysplasia, congenital heart disease and distinctive facial features. WES revealed that the child has harbored compound heterozygous variants of the TELO2 gene, namely c.1826G>A (p.Arg609His) and c.1514_1515delAG (p.Glu505Alafs21). Sanger sequencing confirmed that his mother carried a heterozygous c.1826G>A variant and his father carried a heterozygous c.1514_1515delAG variant. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), both variants were classified as likely pathogenic (PM2_Supproting+PM3_Strong+PP1+PP3; PVS1+PM2_Supproting). Literature review has identified 9 articles reporting 31 cases of YHFS due to TELO2 gene variants, with primary clinical manifestations including developmental delay, intellectual disability, distinctive facial features, and congenital heart disease. CONCLUSION The c.1826G>A (p.Arg609His) and c.1514_1515delAG (p.Glu505Alafs*21) compound heterozygous variants of the TELO2 gene probably underlay the pathogenesis of this child. Above finding has provided a basis for the clinical and genetic diagnosis of the child, which also enriched the mutational spectrum of the TELO2 gene, and improved understanding of YHFS.
Humans ; Male ; Infant ; Heterozygote ; Developmental Disabilities/genetics* ; Female ; Exome Sequencing ; Mutation ; Phenotype ; Abnormalities, Multiple/genetics* ; Child, Preschool

The PI3K/Akt signaling pathway,a critical intracellular regulatory network,plays a piv-otal role in diverse physiological processes,including cell survival,proliferation,metabolism,and immune regulation.Current research has transitioned from elucidating fundamental molecular mechanisms to exploring novel dimensions within the host-pathogen interaction regulatory net-work.This shift emphasizes uncovering molecular strategies employed by pathogens to evade host immune clearance by hijacking or inhibiting this pathway,as well as developing targeted anti-infec-tion therapies specific to this pathway.This article delineates the components and activation mecha-nisms of the PI3K/Akt pathway and reviews its specific roles in mediating immune defense,im-mune evasion,and host tissue damage during bacterial infections.Furthermore,it evaluates the po-tential of targeting this pathway as a therapeutic strategy for infectious diseases.By synthesizing existing research and providing future perspectives,this review aims to advance the understanding of bacterial infection pathogenesis and inform the development of non-antibiotic therapies targeting host signaling pathways.

The PI3K/Akt signaling pathway,a critical intracellular regulatory network,plays a piv-otal role in diverse physiological processes,including cell survival,proliferation,metabolism,and immune regulation.Current research has transitioned from elucidating fundamental molecular mechanisms to exploring novel dimensions within the host-pathogen interaction regulatory net-work.This shift emphasizes uncovering molecular strategies employed by pathogens to evade host immune clearance by hijacking or inhibiting this pathway,as well as developing targeted anti-infec-tion therapies specific to this pathway.This article delineates the components and activation mecha-nisms of the PI3K/Akt pathway and reviews its specific roles in mediating immune defense,im-mune evasion,and host tissue damage during bacterial infections.Furthermore,it evaluates the po-tential of targeting this pathway as a therapeutic strategy for infectious diseases.By synthesizing existing research and providing future perspectives,this review aims to advance the understanding of bacterial infection pathogenesis and inform the development of non-antibiotic therapies targeting host signaling pathways.

Objective:To develop a deep learning model based on super-resolution endorectal ultrasound（ERUS）images for the preoperative prediction of perineural invasion（PNI）in patients with rectal cancer，thereby providing a reference for risk stratification and individualized treatment planning.Methods:A retrospective analysis was conducted on 382 patients with rectal cancer who underwent total mesorectal excision at Fujian Medical University Union Hospital between June 2019 and February 2024. Patients were randomly divided into a training set（ n=305）and a test set（ n=77）at a ratio of 8∶2，and further grouped into PNI-negative group and PNI-positive group subgroups based on pathological results. Super-resolution ultrasound images were generated from original ERUS images using a generative adversarial network（GAN）. Deep convolutional neural networks were developed based on features from intratumoral and peritumoral regions to identify the optimal region of interest（ROI）. The dSR5_ResNet18 and dSR5_ResNet50 models were constructed using the super-resolution images with a 5-pixel peritumoral extension. Representative clinical features were selected for subgroup analysis based on sample size and intergroup statistical differences between PNI-positive and PNI-negative patients. Forest plots were used to evaluate model applicability and robustness across subgroups. Results:The dSR5_ResNet18 model，built using super-resolution images of the tumor combined with a 5-pixel peritumoral region，achieved the best predictive performance，with an AUC of 0.867（95% CI=0.782 - 0.952）in the test set. Decision curve analysis demonstrated that the dSR5_ResNet18 model provided the greatest net clinical benefit. Forest plot analysis indicated strong generalizability of the models across subgroups such as pathological N stage，maximum lesion length，and lymph node enlargement，though relatively weaker performance was observed in the carcinoembryonic antigen（CEA）subgroup. Among all models，dSR5_ResNet18 exhibited the most consistent performance across subgroups，with the narrowest confidence intervals and highest robustness. Conclusions:The deep learning model incorporating ERUS-based super-resolution reconstruction demonstrated excellent performance in the preoperative prediction of PNI in rectal cancer. It offers significant advantages in image quality and generalizability，and may serve as a valuable tool to assist clinicians in formulating personalized treatment strategies.

Traditional Chinese medicine (TCM) serves as a treasure trove of ancient knowledge, holding a crucial position in the medical field. However, the exploration of TCM's extensive information has been hindered by challenges related to data standardization, completeness, and accuracy, primarily due to the decentralized distribution of TCM resources. To address these issues, we developed a platform for TCM knowledge discovery (TCMKD, https://cbcb.cdutcm.edu.cn/TCMKD/). Seven types of data, including syndromes, formulas, Chinese patent drugs (CPDs), Chinese medicinal materials (CMMs), ingredients, targets, and diseases, were manually proofread and consolidated within TCMKD. To strengthen the integration of TCM with modern medicine, TCMKD employs analytical methods such as TCM data mining, enrichment analysis, and network localization and separation. These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights. In addition to its analytical capabilities, a quick question and answer (Q&A) system is also embedded within TCMKD to query the database efficiently, thereby improving the interactivity of the platform. The platform also provides a TCM text annotation tool, offering a simple and efficient method for TCM text mining. Overall, TCMKD not only has the potential to become a pivotal repository for TCM, delving into the pharmacological foundations of TCM treatments, but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems, extending beyond just TCM.

Objective:To develop a deep learning model based on super-resolution endorectal ultrasound（ERUS）images for the preoperative prediction of perineural invasion（PNI）in patients with rectal cancer，thereby providing a reference for risk stratification and individualized treatment planning.Methods:A retrospective analysis was conducted on 382 patients with rectal cancer who underwent total mesorectal excision at Fujian Medical University Union Hospital between June 2019 and February 2024. Patients were randomly divided into a training set（ n=305）and a test set（ n=77）at a ratio of 8∶2，and further grouped into PNI-negative group and PNI-positive group subgroups based on pathological results. Super-resolution ultrasound images were generated from original ERUS images using a generative adversarial network（GAN）. Deep convolutional neural networks were developed based on features from intratumoral and peritumoral regions to identify the optimal region of interest（ROI）. The dSR5_ResNet18 and dSR5_ResNet50 models were constructed using the super-resolution images with a 5-pixel peritumoral extension. Representative clinical features were selected for subgroup analysis based on sample size and intergroup statistical differences between PNI-positive and PNI-negative patients. Forest plots were used to evaluate model applicability and robustness across subgroups. Results:The dSR5_ResNet18 model，built using super-resolution images of the tumor combined with a 5-pixel peritumoral region，achieved the best predictive performance，with an AUC of 0.867（95% CI=0.782 - 0.952）in the test set. Decision curve analysis demonstrated that the dSR5_ResNet18 model provided the greatest net clinical benefit. Forest plot analysis indicated strong generalizability of the models across subgroups such as pathological N stage，maximum lesion length，and lymph node enlargement，though relatively weaker performance was observed in the carcinoembryonic antigen（CEA）subgroup. Among all models，dSR5_ResNet18 exhibited the most consistent performance across subgroups，with the narrowest confidence intervals and highest robustness. Conclusions:The deep learning model incorporating ERUS-based super-resolution reconstruction demonstrated excellent performance in the preoperative prediction of PNI in rectal cancer. It offers significant advantages in image quality and generalizability，and may serve as a valuable tool to assist clinicians in formulating personalized treatment strategies.

OBJECTIVE: To assess the clinical application of single nucleotide polymorphism microarray (SNP array) in patients with intellectual disability/developmental delay(ID/DD). METHODS: SNP array was performed to detect genome-wide DNA copy number variants (CNVs) for 145 patients with ID/DD in Women's Hospital, Zhejiang University School of Medicine from January 2013 to June 2018. The CNVs were analyzed by CHAS software and related databases. RESULTS: Among 145 patients, pathogenic chromosomal abnormalities were detected in 32 cases, including 26 cases of pathogenic CNVs and 6 cases of likely pathogenic CNVs. Meanwhile, 18 cases of uncertain clinical significance and 14 cases of likely benign were identified, no significant abnormalities were found in 81 cases (including benign). CONCLUSIONS SNP array is effective for detecting chromosomal abnormalities in patients with ID/DD with high efficiency and resolution.
Chromosome Aberrations ; DNA Copy Number Variations ; Genome-Wide Association Study ; Humans ; Intellectual Disability ; diagnosis ; genetics ; Oligonucleotide Array Sequence Analysis ; standards ; Polymorphism, Single Nucleotide

OBJECTIVE: To assess the clinical application of single nucleotide polymorphism microarray (SNP array) in prenatal genetic diagnosis for fetuses with absent nasal bone. METHODS: Seventy four fetuses with absent nasal bone detected by prenatal ultrasound scanning were recruited from Women's Hospital, Zhejiang University School of Medicine during June 2015 and October 2018. The chromosome karyotypes analysis and SNP array were performed. The correlation between absent fetal nasal bone and chromosome copy number variants was analyzed. RESULTS: Among 74 fetuses, 19 were detected to have chromosomal abnormalities, including 16 cases of trisomy-21, 1 case of trisomy-18 and two cases of micro-deletion/duplication. Among 46 cases with isolated absence of nasal bone, 3 had trisomy-21, and 1 had a micro-duplication. Absence of nasal bone in association with nuchal translucency thickening had a higher rate of abnormal karyotypes compared with isolated absence of nasal bone (=32.27,<0.01). CONCLUSIONS Fetuses with absent nasal bone and nuchal translucency thickening are likely to have chromosome abnormalities, and SNP array testing is recommended to exclude the chromosome abnormalities.
Chromosome Aberrations ; Female ; Fetus ; Humans ; Nasal Bone ; abnormalities ; Oligonucleotide Array Sequence Analysis ; standards ; Polymorphism, Single Nucleotide ; genetics ; Pregnancy ; Pregnancy Trimester, First ; Prenatal Diagnosis ; methods

OBJECTIVE: To conduct genetic analysis in a fetus with complex translocation of four chromosomes. METHODS: G-banded chromosome karyotype analysis, single nucleotide polymorphism array (SNP array) and fluorescence hybridization (FISH) were performed in a fetus with multiple malformations. Peripheral blood chromosome karyotype and FISH were also carried out for the parents. RESULTS: The fetal amniotic fluid karyotype was 46, XY, t(12; 13)(q22; q32). SNP array analysis showed that there were 20 192 kb duplication at 1q42.13q44 and 13 293 kb deletion at 15q26.1q26.3 in the fetus. The results of karyotype and SNP array were inconsistent. FISH analyses on the parental peripheral blood samples demonstrated that the mother was a cryptic 46, XX, t(1; 15)(q42.1; q26.1) translocation. The fetus had inherited 46, XY, t(12; 13)(q22; q32) from his father and der(15)t(1; 15)(q42.1; q26.1) from his mother. CONCLUSIONS The 1q42.13q44 duplication and 15q26.1q26.3 deletion may have contributed to the abnormal sonographic features of the fetus. The combination of cytogenetic, SNP array and FISH techniques was beneficial for providing an accurate genetic counseling.
Chromosome Aberrations ; Female ; Fetus ; abnormalities ; Humans ; In Situ Hybridization, Fluorescence ; Karyotyping ; Male ; Polymorphism, Single Nucleotide ; Translocation, Genetic