The success of"New Medical Sciences"in higher education requires effective tools in evalua-ting students'performance in courses.Previously,we reported a teamwork(T),critique(C)and ap-preciation(A)(TCA)ideological and political model,a teaching model widely applied in Basic Medical courses.TCA is an abbreviation derived from Tricarboxylic Acid Cycle in Biochemistry as an analogy for nurturing the abilities of thinking and teamwork(T),critique(C)and appreciation(A),which hope-fully could provide students with moral norms for cognition,science and life.This paper further explores the tools to assess the educational outcomes of the TCA model,by which teachers can collect feedback and reflect on teaching quality and effectiveness.Addressing the challenges of individual differences in large classes,fragmented learning feedback,and the difficulty of measuring meta-cognition in educational evaluation,this study employs strategies of value-added assessment,matrix assessment and norm-transfer-able assessment to evaluate the TCA abilities from the aspects of thinking quality,thinking creativity,co-operation ability,iterative thinking,dialectical thinking and job responsibility.By modifying/using 18 e-valuation tools in Education and Psychology,we have established a rubric system composed of 30 primary indicators(with 11 newly designed,10 partly modified and 9 directly adopted),along with 49 secondary indicators and 98 tertiary indicators to enhance the feasibility of the evaluation process.This rubric sys-tem was applied to Biochemistry teaching among the five-year-program undergraduates at Air Force Medi-cal University.Specifically,thinking and teamwork are evaluated by creative works from"the magic bio-chemical-circle",while critiques are assessed in large classes under the guidance of basic and clinical teachers,coupled with appreciation measured by job responsibility in a task-driven virtual reality(VR)project.The results indicate that Biochemistry teaching not only accumulates knowledge in students,but also achieves the goals in nurturing values and cognition.The inclusion of creative performance evalua-tion,cooperative learning and clinical case studies,can enhance students'interpersonal skills,coopera-tion,quality of thinking,creative thinking,iterative thinking and dialectical thinking to varying degrees.TCA-based Biochemistry teaching has a long-lasting impact on character education,and is capable of in-ducing positive long-term changes in students'cognition and lifestyle.Taken together,with the help of this rubric system,teachers can promptly acknowledge the effectiveness of their teaching,thereby facilita-ting their teaching strategies.

OBJECTIVE: To investigate the clinical features and pathogenesis of a child with Stargardt disease caused by variants of ABCA4 gene. METHODS: A child presented at Shenzhen Eye Hospital between September 5, 2020, and April 3, 2023 was selected as the study subject. Clinical data of the child were collected. Whole exome sequencing was performed on peripheral blood samples from the child and his parents. Candidate variants were validated by Sanger sequencing and bioinformatic analysis. This study was approved by the Medical Ethics Committee of Shenzhen Eye Hospital (Ethics No.: 2022KYPJ072). RESULTS: The child was a 10-year-old male presenting with uncorrected visual acuity of 0.1 in both eyes without improvement with refractive correction. Fundus photography showed diffusely distributed yellow-white flecks in the macular region. FAF revealing central hypofluorescence surrounded by a hyperfluorescent ring, and OCT demonstrating significant foveal thinning (right eye: 45 μm; left eye: 50 μm) with ellipsoid zone disruption. Whole exome sequencing and Sanger sequencing revealed that the child has harbored compound heterozygous variants of the ABCA4 gene, namely c.2384G>T (p.Gly795Val) and c.2903G>A (p.Arg968Glu), which were inherited from his phenotypically normal parents and consistent with an autosomal recessive inheritance. This specific combination of the variants was previously unreported. According to the guidelines from the American College of Medical Genetics and Genomics (ACMG) guidelines, both variants were classified as likely pathogenic (PM2_Supporting+PM3+PP3+PP4; PM1+PM2_Supporting+PP3+PP4). CONCLUSION The novel compound heterozygous variants of the ABCA4 gene probably underlay the genetic etiology of Stargardt disease type 1 in this child. Above finding has expanded the mutational spectrum of the ABCA4 gene among the Chinese population and provided further evidence for understanding the genetic heterogeneity and genotype-phenotype correlation of the Stargardt disease.
Humans ; Male ; Child ; ATP-Binding Cassette Transporters/genetics* ; Stargardt Disease/genetics* ; Heterozygote ; Mutation ; Exome Sequencing ; Macular Degeneration/congenital*

Objective:To investigate the clinical features and pathogenesis of a child with Stargardt disease caused by variants of ABCA4 gene. Methods:A child presented at Shenzhen Eye Hospital between September 5, 2020, and April 3, 2023 was selected as the study subject. Clinical data of the child were collected. Whole exome sequencing was performed on peripheral blood samples from the child and his parents. Candidate variants were validated by Sanger sequencing and bioinformatic analysis. This study was approved by the Medical Ethics Committee of Shenzhen Eye Hospital (Ethics No.: 2022KYPJ072).Results:The child was a 10-year-old male presenting with uncorrected visual acuity of 0.1 in both eyes without improvement with refractive correction. Fundus photography showed diffusely distributed yellow-white flecks in the macular region. FAF revealing central hypofluorescence surrounded by a hyperfluorescent ring, and OCT demonstrating significant foveal thinning (right eye: 45 μm; left eye: 50 μm) with ellipsoid zone disruption. Whole exome sequencing and Sanger sequencing revealed that the child has harbored compound heterozygous variants of the ABCA4 gene, namely c. 2384G>T (p.Gly795Val) and c. 2903G>A (p.Arg968Glu), which were inherited from his phenotypically normal parents and consistent with an autosomal recessive inheritance. This specific combination of the variants was previously unreported. According to the guidelines from the American College of Medical Genetics and Genomics (ACMG) guidelines, both variants were classified as likely pathogenic (PM2_Supporting+ PM3+ PP3+ PP4; PM1+ PM2_Supporting+ PP3+ PP4). Conclusion:The novel compound heterozygous variants of the ABCA4 gene probably underlay the genetic etiology of Stargardt disease type 1 in this child. Above finding has expanded the mutational spectrum of the ABCA4 gene among the Chinese population and provided further evidence for understanding the genetic heterogeneity and genotype-phenotype correlation of the Stargardt disease.

BACKGROUND: Diabetic foot is a complex condition with high incidence, recurrence, mortality, and disability rates. Current treatments for diabetic foot ulcers are often insufficient. This study was conducted to identify potential therapeutic targets for diabetic foot. METHODS: Datasets related to diabetic foot and diabetic skin were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software. Enrichment analysis was conducted to screen for critical gene functions and pathways. A protein interaction network was constructed to identify node genes corresponding to key proteins. The DEGs and node genes were overlapped to pinpoint target genes. Plasma and chronic ulcer samples from diabetic and non-diabetic individuals were collected. Western blotting, immunohistochemistry, and enzyme-linked immunosorbent assays were performed to verify the S100 calcium binding protein A9 (S100A9), inflammatory cytokine, and related pathway protein levels. Hematoxylin and eosin staining was used to measure epidermal layer thickness. RESULTS: In total, 283 common DEGs and 42 node genes in diabetic foot ulcers were identified. Forty-three genes were differentially expressed in the skin of diabetic and non-diabetic individuals. The overlapping of the most significant DEGs and node genes led to the identification of S100A9 as a target gene. The S100A9 level was significantly higher in diabetic than in non-diabetic plasma (178.40 ± 44.65 ng/mL vs. 40.84 ± 18.86 ng/mL) and in chronic ulcers, and the wound healing time correlated positively with the plasma S100A9 level. The levels of inflammatory cytokines (tumor necrosis factor-α, interleukin [IL]-1, and IL-6) and related pathway proteins (phospho-extracellular signal regulated kinase [ERK], phospho-p38, phospho-p65, and p-protein kinase B [Akt]) were also elevated. The epidermal layer was notably thinner in chronic diabetic ulcers than in non-diabetic skin (24.17 ± 25.60 μm vs. 412.00 ± 181.60 μm). CONCLUSIONS S100A9 was significantly upregulated in diabetic foot and was associated with prolonged wound healing. S100A9 may impair diabetic wound healing by disrupting local inflammatory responses and skin re-epithelialization.
Calgranulin B/therapeutic use* ; Diabetic Foot/metabolism* ; Humans ; Datasets as Topic ; Computational Biology ; Mice, Inbred C57BL ; Animals ; Mice ; Protein Interaction Maps ; Immunohistochemistry

Sini Decoction (SNT) is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold. However, elucidating the mechanism of action of SNT remains challenging due to its complex multiple components. This study utilized a synergistic approach combining two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE)-based drug affinity responsive target stability (DARTS) with label-free quantitative proteomics techniques to identify the direct and indirect protein targets of SNT in myocardial infarction. The analysis identified 590 proteins, with 30 proteins showing significant upregulation and 51 proteins showing downregulation when comparing the SNT group with the model group. Through the integration of 2D-DIGE DARTS with proteomics data and pharmacological assessments, the findings indicate that protein disulfide-isomerase A3 (PDIA3) may serve as a potential protein target through which SNT provides protective effects on myocardial cells during myocardial infarction.
Myocardial Infarction/genetics* ; Proteomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Animals ; Protein Disulfide-Isomerases/genetics* ; Male ; Two-Dimensional Difference Gel Electrophoresis/methods* ; Humans ; Rats ; Rats, Sprague-Dawley ; Electrophoresis, Gel, Two-Dimensional

BACKGROUND: Double-stranded RNA-specific adenosine deaminase 1 (ADAR1) binds to double-stranded RNA and catalyzes the deamination of adenosine (A) to inosine (I). The functional mechanism of ADAR1 in non-small cell lung cancer (NSCLC) remains incompletely understood. This study aimed to investigate the prognostic significance of ADAR1 in NSCLC and to elucidate its potential role in regulating tumor cell proliferation and migration. METHODS: Data from The Cancer Genome Atlas (TCGA) and cBioPortal were analyzed to assess the correlation between high ADAR1 expression and clinicopathological features as well as prognosis in lung cancer. We performed Western blot (WB), cell proliferation assays, Transwell invasion/migration assays, and nude mouse xenograft modeling to examine the phenotypic changes and molecular mechanisms induced by ADAR1 knockdown. Furthermore, the ADAR1 p150 overexpression model was utilized to validate the proposed mechanism. RESULTS: ADAR1 expression was significantly elevated in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissues compared with adjacent non-tumor tissues (LUAD: P=3.70×10-15, LUSC: P=0.016). High ADAR1 expression was associated with poor prognosis (LUAD: P=2.03×10-2, LUSC: P=2.81×10-2) and distant metastasis (P=0.003). Gene Set Enrichment Analysis (GSEA) indicated that elevated ADAR1 was associated with mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathway activation, matrix metalloproteinase-9 (MMP-9) expression, and cell adhesion. ADAR1 and MMP-9 levels showed a strongly positive correlation (P=6.45×10-34) in 10 lung cancer cell lines, highest in H1581. Knockdown of ADAR1 in H1581 cells induced a rounded cellular morphology with reduced pseudopodia. Concomitantly, it suppressed cell proliferation, invasion, migration, and in vivo tumorigenesis. It also suppressed ERK phosphorylation and downregulated cellular Finkel-Biskis-Jinkins murine osteosarcoma viral oncogene homolog (c-FOS), MMP-9, N-cadherin, and Vimentin. Conversely, ADAR1 p150 overexpression in PC9 cells enhanced ERK phosphorylation and increased c-FOS and MMP-9 expression. CONCLUSIONS High ADAR1 expression is closely associated with poor prognosis and distant metastasis in NSCLC patients. Mechanistically, ADAR1 may promote proliferation, invasion, migration, and tumorigenesis in lung cancer cells via the ERK/c-FOS/MMP-9 axis.
Humans ; Lung Neoplasms/physiopathology* ; Adenosine Deaminase/genetics* ; Matrix Metalloproteinase 9/genetics* ; Cell Proliferation ; Carcinoma, Non-Small-Cell Lung/physiopathology* ; Cell Movement ; Animals ; Mice ; RNA-Binding Proteins/genetics* ; Female ; Male ; Cell Line, Tumor ; Proto-Oncogene Proteins c-fos/genetics* ; Middle Aged ; MAP Kinase Signaling System ; Gene Expression Regulation, Neoplastic ; Mice, Nude ; Extracellular Signal-Regulated MAP Kinases/genetics*

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks