OBJECTIVE: To investigate the genetic etiology of a fetus diagnosed with Mandibulofacial dysostosis with microcephaly (MFDM). METHODS: A fetus that underwent prenatal diagnosis at Beijing Obstetrics and Gynecology Hospital, Capital Medical University, on May 19, 2025 was selected for analysis. Results of fetal ultrasound findings, chromosomal karyotyping, copy number variation sequencing (CNV-seq), and whole-exome sequencing (WES) were collected. Sanger sequencing was performed for familial validation of the pathogenic variant. The Human Protein Atlas (HPA), STRING, and Simple ClinVar databases were queried to characterize the biological features of the candidate gene. Three-dimensional structures of the wild-type and variant proteins were modeled and analyzed, and the evolutionary conservation of the affected amino acid was assessed using UGENE. Prenatal phenotypes associated with EFTUD2 variants were summarized through a review of the literature. This study was approved by the Ethics Committee of Beijing Obstetrics and Gynecology Hospital, Capital Medical University (Ethics No.: 2025-KY-029-01). RESULTS: At 23⁺² weeks of gestation, ultrasound examination revealed bilateral microtia with low-set ears, mild micrognathia with a reduced mandibular-facial angle, a single umbilical artery, a slightly narrow aortic diameter, and trivial mitral regurgitation. Amniotic fluid karyotyping and CNV-seq showed no abnormalities. WES identified a de novo, previously unreported EFTUD2 variant, c.698dupA (p.V235Gfs*27), in the fetus. This frameshift variant is predicted to alter the structural integrity of the EFTUD2 protein. Literature review indicated that micrognathia and microtia or low-set ears are the most common sonographic features in fetuses with EFTUD2 variants, while secondary findings may include abnormal stomach bubble, cleft palate, single umbilical artery, gastrointestinal atresia, polyhydramnios, and reduced aortic diameter. CONCLUSION The EFTUD2: c.698dupA (p.V235Gfs*27) variant is likely the genetic cause underlying MFDM in this fetus.
Humans ; Mandibulofacial Dysostosis/diagnostic imaging* ; Microcephaly/diagnostic imaging* ; Female ; Pregnancy ; Ribonucleoprotein, U5 Small Nuclear/chemistry* ; Peptide Elongation Factors/chemistry* ; Fetus ; DNA Copy Number Variations/genetics* ; Adult ; Ultrasonography, Prenatal

OBJECTIVE: To identify the role of gene silencing or overexpression of Nemo-like kinase (NLK) during the process of neural differentiation of human mesenchymal stem cells (hBMSCs), and to explore the effect of NLK downregulation by transfection of small interfering RNA (siRNA) on promoting neuralized tissue engineered bone regeneration. METHODS: NLK-knockdown hBMSCs were established by transfection of siRNA (the experimental group was transfected with siRNA silencing the NLK gene, the control group was transfected with control siRNA and labeled as negative control group), and NLK-overexpression hBMSCs were established using lentivirus vector transfection technique (the experimental group was infected with lentivirus overexpressing the NLK gene, the control group was infected with an empty vector lentivirus and labeled as the empty vector group). After neurogenic induction, quantitative real-time polymerase chain reaction (qPCR) was used to detect the expression of neural-related gene, and Western blot as well as immunofluorescence staining about several specific neural markers were used to evaluate the neural differentiation ability of hBMSCs.6-week-old male nude mice were divided into 4 groups: ① β-tricalcium phosphate (β-TCP) group, ② β-TCP+ osteogenic induced hBMSCs group, ③ β-TCP+ siRNA-negative control (siRNA-NC) transfection hBMSCs group, ④ β-TCP+ siRNA-NLK transfection hBMSCs group. Four weeks after the subcutaneous ectopic osteogenesis models were established, the osteogenesis and neurogenesis were detected by hematoxylin-eosin (HE) staining, Masson staining and tissue immunofluorescence assay. Statistical analysis was conducted by independent sample t test. RESULTS: After gene silencing of NLK by siRNA in hBMSCs, neural-related genes, including the class Ⅲ β-tubulin (TUBB3), microtubule association protein-2 (MAP2), soluble protein-100 (S100), nestin (NES), NG2 proteoglycan (NG2) and calcitonin gene-related peptide (CGRP), were increased significantly in NLK-knockdown hBMSCs compared with the negative control group(P < 0.05), and the expression levels of TUBB3 and MAP2 of the NLK silencing group were also increased. Oppositely, after NLK was overexpressed using lentivirus vector transfection technique, TUBB3, MAP2, S100 and NG2 were significantly decreased in NLK-overexpression hBMSCs compared with the empty vector group (P < 0.05), and the expression level of TUBB3 was also decreased. 4 weeks after the subcutaneous ectopic osteogenesis model was established, more mineralized tissues were formed in the β-TCP+ siRNA-NLK transfection hBMSCs group compared with the other three groups, and the expression of BMP2 and S100 was higher in the β-TCP+ siRNA-NLK transfection hBMSCs group than in the other groups. CONCLUSION Gene silencing of NLK by siRNA promoted the ability of neural differentiation of hBMSCs in vitro and promoted neuralized tissue engineered bone formation in subcutaneous ectopic osteogenic models in vivo in nude mice.
Bone Regeneration/genetics* ; Animals ; Mesenchymal Stem Cells/cytology* ; Humans ; RNA, Small Interfering/genetics* ; Tissue Engineering/methods* ; Cell Differentiation ; Mice, Nude ; Gene Silencing ; Mice ; Male ; Protein Serine-Threonine Kinases/genetics* ; Intracellular Signaling Peptides and Proteins/genetics* ; Transfection ; Cells, Cultured ; Lentivirus/genetics*

OBJECTIVE: To explore the key target molecules and potential mechanisms of oridonin against non-small cell lung cancer (NSCLC). METHODS: The target molecules of oridonin were retrieved from SEA, STITCH, SuperPred and TargetPred databases; target genes associated with the treatment of NSCLC were retrieved from GeneCards, DisGeNET and TTD databases. Then, the overlapping target molecules between the drug and the disease were identified. The protein-protein interaction (PPI) was constructed using the STRING database according to overlapping targets, and Cytoscape was used to screen for key targets. Molecular docking verification were performed using AutoDockTools and PyMOL software. Using the DAVID database, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted. The impact of oridonin on the proliferation and apoptosis of NSCLC cells was assessed using cell counting kit-8, cell proliferation EdU image kit, and Annexin V-FITC/PI apoptosis kit respectively. Moreover, real-time quantitative PCR and Western blot were used to verify the potential mechanisms. RESULTS: Fifty-six target molecules and 12 key target molecules of oridonin involved in NSCLC treatment were identified, including tumor protein 53 (TP53), Caspase-3, signal transducer and activator of transcription 3 (STAT3), mitogen-activated protein kinase kinase 8 (MAPK8), and mammalian target of rapamycin (mTOR). Molecular docking showed that oridonin and its key target molecules bind spontaneously. GO and KEGG enrichment analyses revealed cancer, apoptosis, phosphoinositide-3 kinase/protein kinase B (PI3K/Akt), and other signaling pathways. In vitro experiments showed that oridonin inhibited the proliferation, induced apoptosis, downregulated the expression of Bcl-2 and Akt, and upregulated the expression of Caspase-3. CONCLUSION Oridonin can act on multiple targets and pathways to exert its inhibitory effects on NSCLC, and its mechanism may be related to upregulating the expression of Caspase-3 and downregulating the expressions of Akt and Bcl-2.
Diterpenes, Kaurane/chemistry* ; Carcinoma, Non-Small-Cell Lung/pathology* ; Humans ; Network Pharmacology ; Lung Neoplasms/pathology* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Molecular Docking Simulation ; Protein Interaction Maps/drug effects* ; Cell Line, Tumor ; Signal Transduction/drug effects* ; Gene Expression Regulation, Neoplastic/drug effects* ; Reproducibility of Results ; Gene Ontology

OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is characterized by complex pathogenesis and poor prognosis. In recent years, epithelial-mesenchymal transition (EMT) in tumor initiation and progression has attracted increasing attention. Enhancer of zeste homolog 2 (EZH2), which is aberrantly expressed in various tumors, may be closely related to the EMT process. This study aims to examine the expression and correlation of EZH2 and EMT markers in ESCC cells and tissues, evaluate the effects of EZH2 knockdown on ESCC cell proliferation, invasion, and migration, and explore how EZH2 contributes to the malignant biological behavior of ESCC. METHODS: Bioinformatics analyses were used to assess EZH2 expression levels in ESCC. Small interfering RNA was used to knock down EZH2 in ESCC cell lines EC109 and EC9706. Cell proliferation, invasion, and migration were evaluated using cell counting kit-8 (CCK-8), wound healing, and Transwell assays. Protein and mRNA expression levels of EZH2, E-cadherin (E-cad), and vimentin (Vim) were detected by Western blotting and real time fluorogenic quantitative PCR (RT-qPCR), respectively. Immunohistochemical (IHC) staining was performed on 70 ESCC tissue samples and 40 paired adjacent normal tissues collected from the First Affiliated Hospital of Shihezi University between 2010 and 2016 to assess the expression of EZH2, E-cad, and Vim, and to analyze their associations with clinicopathological feature and patient prognosis. RESULTS: Bioinformatics analysis showed that EZH2 was highly expressed in ESCC (P<0.001), and high EZH2 expression was associated with worse prognosis (P<0.001). CCK-8, wound healing, and Transwell assays demonstrated that EZH2 knockdown significantly suppressed the proliferation, invasion, and migration of ESCC cells (P<0.001). In addition, Vim expression was significantly reduced, while E-cad expression was significantly increased at both protein and mRNA levels in EZH2-silenced cells (all P<0.05). IHC staining analysis revealed higher expression of EZH2 and Vim and lower expression of E-cad in ESCC tissues compared to adjacent normal tissues. Kaplan-Meier survival analysis showed that low expression of EZH2 and Vim and high expression of E-cad were associated with longer survival (all P<0.05). CONCLUSIONS EZH2 promotes malignant biological behavior in ESCC by mediating EMT. Elevated EZH2 expression is associated with poor prognosis in ESCC patients.
Humans ; Enhancer of Zeste Homolog 2 Protein/physiology* ; Esophageal Squamous Cell Carcinoma/pathology* ; Epithelial-Mesenchymal Transition/genetics* ; Esophageal Neoplasms/metabolism* ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement ; Cadherins/genetics* ; Vimentin/genetics* ; Male ; Female ; Middle Aged ; Neoplasm Invasiveness ; Prognosis ; RNA, Small Interfering/genetics* ; Gene Expression Regulation, Neoplastic

OBJECTIVES: Non-small cell lung cancer (NSCLC) is associated with poor prognosis, with 30% of patients diagnosed at an advanced stage. Mutations in the EGFR and KRAS genes are important prognostic factors for NSCLC, and targeted therapies can significantly improve survival in these patients. Although tissue biopsy remains the gold standard for detecting gene mutations, it has limitations, including invasiveness, sampling errors due to tumor heterogeneity, and poor reproducibility. This study aims to develop machine learning models based on radiomic features to predict EGFR and KRAS gene mutation status in NSCLC patients, thereby providing a reference for precision oncology. METHODS: Imaging and mutation data from eligible NSCLC patients were obtained from the publicly available Lung-PET-CT-Dx dataset in The Cancer Imaging Archive (TCIA). A three-dimensional-convolutional neural network (3D-CNN) was used to extract imaging features from the regions of interest (ROI). The LightGBM algorithm was employed to build classification models for predicting EGFR and KRAS gene mutation status. Model performance was evaluated using 5-fold cross-validation, with receiver operator characteristic (ROC) curves, area under the curve (AUC), accuracy, sensitivity, and specificity used for validation. RESULTS: The models effectively predicted EGFR and KRAS mutations in NSCLC patients, achieving an AUC of 0.95 for EGFR mutations and 0.90 for KRAS. The models also demonstrated high accuracy (EGFR 89.66%; KRAS 87.10%), sensitivity (EGFR 93.33%; KRAS 87.50%), and specificity (EGFR 85.71%; KRAS 86.67%). CONCLUSIONS A radiogenomics-machine learning predictive model can serve as a non-invasive tool for anticipating EGFR and KRAS gene mutation status in NSCLC patients.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Lung Neoplasms/diagnostic imaging* ; Mutation ; Proto-Oncogene Proteins p21(ras)/genetics* ; ErbB Receptors/genetics* ; Machine Learning ; Positron Emission Tomography Computed Tomography ; Female ; Male ; Neural Networks, Computer ; Middle Aged ; Aged

Artificial intelligence (AI) researchers and cheminformatics specialists strive to identify effective drug precursors while optimizing costs and accelerating development processes. Digital molecular representation plays a crucial role in achieving this objective by making molecules machine-readable, thereby enhancing the accuracy of molecular prediction tasks and facilitating evidence-based decision making. This study presents a comprehensive review of small molecular representations and AI-driven drug discovery downstream tasks utilizing these representations. The research methodology begins with the compilation of small molecule databases, followed by an analysis of fundamental molecular representations and the models that learn these representations from initial forms, capturing patterns and salient features across extensive chemical spaces. The study then examines various drug discovery downstream tasks, including drug-target interaction (DTI) prediction, drug-target affinity (DTA) prediction, drug property (DP) prediction, and drug generation, all based on learned representations. The analysis concludes by highlighting challenges and opportunities associated with machine learning (ML) methods for molecular representation and improving downstream task performance. Additionally, the representation of small molecules and AI-based downstream tasks demonstrates significant potential in identifying traditional Chinese medicine (TCM) medicinal substances and facilitating TCM target discovery.
Artificial Intelligence ; Drug Discovery/methods* ; Humans ; Machine Learning ; Medicine, Chinese Traditional ; Small Molecule Libraries/chemistry*

OBJECTIVES: To investigate the effect of high glucose on macrophage polarization and the role of immune-responsive gene 1 (IRG1) in mediating its effect. METHODS: RAW264.7 cells were transfected with IRG1-overexpressing plasmid or IRG1 siRNA via electroporation and cultured in either normal or high glucose for 72 h to observe the changes in cell viability and morphology using CCK-8 assay and phase contrast microscopy. The protein levels of IRG1, iNOS, Arg-1, IL-1β and IL-10 in the treated cells were detected with Western blotting, and the fluorescence intensities of iNOS and Arg-1 were detected using immunofluorescence assay. The protein levels of IL-1β and IL-10 in the culture medium were determined with ELISA. RESULTS: High glucose exposure significantly reduced IRG1 and Arg-1 expressions, increased iNOS and IL-1β expressions and IL-1β secretion, and decreased IL-10 level in RAW264.7 cells. Transfection with the IRG1-overexpressing plasmid provided the cells with obvious resistance to high glucose-induced changes in iNOS, Arg-1, IL-1β and IL-10, whereas IRG1 knockdown further enhanced the effects of high glucose exposure on Arg-1 expression and the expression and secretion of IL-10. CONCLUSIONS High glucose promotes M1 polarization of the macrophages possibly through a mechanism to inhibit the expression of IRG1 protein, thus leading to chronic inflammatory response.
Animals ; Mice ; Macrophages/drug effects* ; Glucose/pharmacology* ; Interleukin-10/metabolism* ; Nitric Oxide Synthase Type II/metabolism* ; RAW 264.7 Cells ; Interleukin-1beta/metabolism* ; Arginase/metabolism* ; RNA, Small Interfering/genetics* ; Transfection ; Inflammation

OBJECTIVES: To propose a new method for optimizing radiotherapy planning for lung cancer by incorporating prognostic models that take into account individual patient information and assess the feasibility of treatment planning optimization directly guided by minimizing the predicted prognostic risk. METHODS: A mixed fluence map optimization objective was constructed, incorporating the outcome-based objective and the physical dose constraints. The outcome-based objective function was constructed as an equally weighted summation of prognostic prediction models for local control failure, radiation-induced cardiac toxicity, and radiation pneumonitis considering clinical risk factors. These models were derived using Cox regression analysis or Logistic regression. The primary goal was to minimize the outcome-based objective with the physical dose constraints recommended by the clinical guidelines. The efficacy of the proposed method for optimizing treatment plans was tested in 15 cases of non-small cell lung cancer in comparison with the conventional dose-based optimization method (clinical plan), and the dosimetric indicators and predicted prognostic outcomes were compared between different plans. RESULTS: In terms of the dosemetric indicators, D_95% of the planning target volume obtained using the proposed method was basically consistent with that of the clinical plan (100.33% vs 102.57%, P=0.056), and the average dose of the heart and lungs was significantly decreased from 9.83 Gy and 9.50 Gy to 7.02 Gy (t=4.537, P<0.05) and 8.40 Gy (t=4.104, P<0.05), respectively. The predicted probability of local control failure was similar between the proposed plan and the clinical plan (60.05% vs 59.66%), while the probability of radiation-induced cardiac toxicity was reduced by 1.41% in the proposed plan. CONCLUSIONS The proposed optimization method based on a mixed objective function of outcome prediction and physical dose provides effective protection against normal tissue exposure to improve the outcomes of lung cancer patients following radiotherapy.
Humans ; Lung Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods* ; Prognosis ; Radiotherapy, Intensity-Modulated/methods* ; Carcinoma, Non-Small-Cell Lung/radiotherapy* ; Radiotherapy Dosage ; Female ; Male ; Middle Aged

OBJECTIVES: To investigate the effect of curcumin on lipid metabolism in non-small cell lung cancer (NSCLC) and its molecular mechanism. METHODS: The inhibitory effect of curcumin (0-70 μmol/L) on proliferation of A549 and H1299 cells was assessed using MTT assay, and 20 and 40 μmol/L curcumin was used in the subsequent experiments. The effect of curcumin on lipid metabolism was evaluated using cellular uptake assay, wound healing assay, triglyceride (TG)/free fatty acid (NEFA) measurements, and Oil Red O staining. Western blotting was performed to detect the expressions of PGC-1α, PPAR-α, and HIF-1α in curcumin-treated cells. Network pharmacology was used to predict the metabolic pathways, and the results were validated by Western blotting. In a nude mouse model bearing A549 cell xenograft, the effects of curcumin (20 mg/kg) on tumor growth and lipid metabolism were assessed by measuring tumor weight and observing the changes in intracellular lipid droplets. RESULTS: Curcumin concentration-dependently inhibited the proliferation of A549 and H1299 cells and significantly reduced TG and NEFA levels and intracellular lipid droplets. Western blotting revealed that curcumin significantly upregulated PGC-1α and PPAR‑α expressions in the cells. KEGG pathway enrichment analysis predicted significant involvement of the HIF-1 signaling pathway in curcumin-treated NSCLC, suggesting a potential interaction between HIF-1α and PPAR‑α. Western blotting confirmed that curcumin downregulated the expression of HIF-1α. In the tumor-bearing mice, curcumin treatment caused significant reduction of the tumor weight and the number of lipid droplets in the tumor cells. CONCLUSIONS Curcumin inhibits NSCLC cell proliferation and lipid metabolism by downregulating the HIF-1α pathway.
Curcumin/pharmacology* ; Humans ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Animals ; Lipid Metabolism/drug effects* ; Carcinoma, Non-Small-Cell Lung/pathology* ; Lung Neoplasms/pathology* ; Mice, Nude ; Down-Regulation ; Mice ; Cell Proliferation/drug effects* ; Cell Line, Tumor ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha ; PPAR alpha/metabolism* ; Signal Transduction/drug effects* ; A549 Cells

OBJECTIVES: To investigate the inhibitory effect of Fuzheng Huaji Decoction against non-small cell lung cancer (NSCLC) cells in vitro and explore the underlying mechanism. METHODS: The active ingredients and targets of Fuzheng Huaji Decoction were identified using TCMSP and SwissTargetPrediction databases. NSCLC-related targets from GeneCards and PharmGKB were intersected with the targets of the Decoction, and a protein-protein interaction (PPI) network was constructed to identify the core targets, which were analyzed with GO and KEGG pathway enrichment analysis. Cultured A549 cells were treated with different concentrations of Fuzheng Huaji Decoction-medicated serum, and the changes in cell proliferation, apoptosis, and protein expressions were examined using CCK-8 assay, annexin V-FITC/PI staining and Western blotting. RESULTS: Fuzheng Huaji Decoction contained 140 active ingredients, and 707 drug-disease intersecting targets were identified. Among these targets, TP53, AKT1, HIF1A, GAPDH, ALB, EGFR, CTNNB1, and TNF were identified as the core targets which were involved in the biological processes related to kinases and receptors and the PI3K-AKT, Ras, calcium, and MAPK pathways. Molecular docking studies indicated strong binding affinity of the active ingredients with TP53, AKT1, and HIF1A. In cultured A549 cells, treatment with 2.5%, 5%, and 10% Fuzheng Huaji Decoction-medicated serum significantly inhibited cell proliferation, promoted cell apoptosis, and downregulated the expression levels of HIF1A, p-AKT (Thr308), and TP53 proteins. CONCLUSIONS Fuzheng Huaji Decoction inhibits proliferation of NSCLC cells possibly by downregulating the expressions of HIF1A, p-AKT (Thr308), and TP53.
Humans ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Drugs, Chinese Herbal/pharmacology* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Lung Neoplasms/metabolism* ; A549 Cells ; Proto-Oncogene Proteins c-akt/metabolism* ; Protein Interaction Maps ; Signal Transduction/drug effects* ; Cell Line, Tumor