BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

Objective: To construct prediction models of female stress urinary incontinence (SUI), and evaluate the efficacy of each model, so as to provide reference for the early diagnosis of SUI. Methods: Female SUI patients treated in our hospital during Oct. 2019 and Oct. 2023 and healthy women undergoing physical examination during the same period were involved. Women 42 days after delivery were included in the postpartum group (n=611), and perimenopausal and postmenopausal women were included in the non-postpartum group (n=409). The number of random seeds was set and the participants were divided into the training and verification sets in a ratio of 7∶3. Relevant clinical data were collected, and meaningful variables were screened using single factor and Lasso regression, which were then incorporated into the K-nearest neighbor method (KNN), support vector machine (SVM)，decision tree (DT) and random forest (RF) algorithms. The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC) of the models were calculated to screen out the optimal model. Results: There were 352 SUI patients (57.6%) in the postpartum group. According to single factor and Lasso regression, significant variables included age, body mass index (BMI), maximum rapid muscle stage, parity, bladder neck mobility (BND), urethral rotation angle (URA), lateral perineal incision, past incontinence, and constipation. In the verification set, the AUC of KNN，SVM，DT and RF models were 0.881，0.878，0.750 and 0.905,respectively; the AUC, accuracy, F1 index and Kappa value of RF model were the largest. In the non-postpartum group, there were 260 SUI patients, accounting for 63.6%. The significant variables were age，BMI, maximum value and recovery time of fast muscle stage, mean value of slow muscle stage, post-resting stage variability, vaginal delivery, past incontinence, and constipation. In the verification set, the AUC of KNN,SVM，DT and RF models were 0.819,0.805，0.603 and 0.830, respectively; the AUC, accuracy, Kappa value of the RF model were the largest. Conclusion: This study successfully established 4 prediction models for the incidence of SUI in women at 42 days postpartum, perimenopausal and postmenopausal women based on machine learning. Among them, the model adopting the RF algorithm had the best prediction efficiency.

Bufalin(BF)has a significant anti-tumor effect, but its clinical application is severely restricted by its high toxicity and poor water solubility. In this study, Scrophularia ningpoensis polysaccharide(SNP)and ursodeoxycholic acid(UDCA) were synthesized into an SNP-UDCA conjugate. BF was encapsulated to prepare BF/SNP-UDCA nanoparticles(NPs). The amphiphilic compound SNP-UDCA was synthesized via the one-step method, and its structure was characterized by Fourier-transform infrared spectroscopy(FT-IR)and proton nuclear magnetic resonance(~1H-NMR). The preparation process of BF/SNP-UDCA NPs was optimized through single-factor investigations. The encapsulation efficiency and drug-loading capacity of BF/SNP-UDCA NPs were determined by high-performance liquid chromatography(HPLC). The molecular form of BF/SNP-UDCA NPs was characterized by using a transmission electron microscope, X-ray diffraction(XRD), and differential scanning calorimeter(DSC). Additionally, the stability of BF/SNP-UDCA NPs was evaluated. The release behavior of BF/SNP-UDCA NPs at different pH values was determined by dialysis. The in vitro anti-tumor effect of BF/SNP-UDCA NPs was evaluated by MTT cytotoxicity assay, flow cytometry for apoptosis, and cellular uptake. The in vitro liver targeting was evaluated by measuring cellular uptake by laser confocal microscopy. The results demonstrated that the SNP-UDCA conjugate was successfully synthesized through an esterification reaction between SNP and UDCA. The preparation process of BF/SNP-UDCA NPs was as follows: the feed ratio of SNP-UDCA to BF was 2∶1, the ultrasonic time was 30 minutes, and the stirring time was two hours. The prepared BF/SNP-UDCA NPs were spherical in shape, with a particle size of(252.74±6.05)nm, an encapsulation efficiency of 65.00%±2.51%, and a drug-loading capacity of 6.80%±0.44%. The XRD and DSC results indicated that BF was encapsulated within the NPs and existed in a molecular or amorphous state. The short-term stability of BF/SNP-UDCA NPs and stability in DMEM medium are good, and their in vitro release behavior followed the first-order equation and was pH-dependent according to the in vitro experiment. Compared with BF, BF/SNP-UDCA NPs at the same concentration showed significantly stronger cytotoxicity and apoptotic effects on HepG2 cells(P<0.05, P<0.01). The uptake of coumarin 6(C6)/SNP-UDCA NPs in HepG2 cells was time-dependent and higher than that in HeLa cells at the same concentration of C6/SNP-UDCA NPs. Moreover, after treatment with SNP, the uptake of C6/SNP-UDCA NPs in HepG2 cells decreased. In conclusion, the preparation process of BF/SNP-UDCA NPs was simple and feasible. BF/SNP-UDCA NPs could enhance the targeting ability and inhibitory effect of BF on liver cancer cells. This study will provide a foundation for liver-targeting nanoformulations of BF.
Bufanolides/pharmacology* ; Nanoparticles/chemistry* ; Humans ; Drug Carriers/chemistry* ; Ursodeoxycholic Acid/chemistry* ; Antineoplastic Agents/pharmacology* ; Polysaccharides/chemistry* ; Scrophularia/chemistry* ; Liver Neoplasms/physiopathology* ; Hep G2 Cells

The AP2/ERF transcription factor family is a class of transcription factors widely present in plants, playing a crucial role in regulating flowering, flower development, flower opening, and flower senescence. Based on transcriptome data from flower, leaf, and stem samples of two Lonicera macranthoides varieties, 117 L. macranthoides AP2/ERF family members were identified, including 14 AP2 subfamily members, 61 ERF subfamily members, 40 DREB subfamily members, and 2 RAV subfamily members. Bioinformatics and differential gene expression analyses were performed using NCBI, ExPASy, SOMPA, and other platforms, and the expression patterns of L. macranthoides AP2/ERF transcription factors were validated via qRT-PCR. The results indicated that the 117 LmAP2/ERF members exhibited both similarities and variations in protein physicochemical properties, AP2 domains, family evolution, and protein functions. Differential gene expression analysis revealed that AP2/ERF transcription factors were primarily differentially expressed in the flowers of the two L. macranthoides varieties, with the differentially expressed genes mainly belonging to the ERF and DREB subfamilies. Further analysis identified three AP2 subfamily genes and two ERF subfamily genes as potential regulators of flower development, two ERF subfamily genes involved in flower opening, and two ERF subfamily genes along with one DREB subfamily gene involved in flower senescence. Based on family evolution and expression analyses, it is speculated that AP2/ERF transcription factors can regulate flower development, opening, and senescence in L. macranthoides, with ERF subfamily genes potentially serving as key regulators of flowering duration. These findings provide a theoretical foundation for further research into the specific functions of the AP2/ERF transcription factor family in L. macranthoides and offer important theoretical insights into the molecular mechanisms underlying floral phenotypic differences among its varieties.
Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Transcription Factors/chemistry* ; Lonicera/classification* ; Flowers/metabolism* ; Phylogeny ; Gene Expression Profiling ; Multigene Family

OBJECTIVE: To investigate the molecular alterations of splenocytes associated with anti-factor Ⅷ (FⅧ) immune response and the underlying mechanisms based on hemophilia A (HA) murine model via RNA sequencing (RNA-seq) technology. METHODS: Severe HA mice were immunized with recombinant human factor Ⅷ (rhF8) weekly for 4 weeks to establish an FⅧ inhibitor model. High quality raw data were obtained by using bulk RNA-seq and CASAVA base identification technology, and the differentially expressed genes (DEGs) were identified. The DEGs were statistically classified by gene ontology (GO) annotation to obtain information on the major signaling pathways and biological processes involved in anti-FⅧ immune response in HA mouse splenocytes. The cell clusters, genes, and signaling pathway datasets were comprehensively analyzed by GO, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and single cell RNA-seq (ScRNA-seq) analysis, respectively. Flow cytometry analysis was used to verify the changes in T follicular helper cells (Tfh) and regulatory T cells (Treg). RESULTS: A total of 3731 DEGs was identified, including 2275 genes with up-regulated expression and 1456 genes with down-regulated expression. The DEGs were enriched in helper T cell differentiation, cytokine receptor, T cell receptor signaling pathway, ferroptosis, etc. Uniform Manifold Approximation and Project (UMAP) downscaling and visualization analysis yielded a total number of 11 T/NK cell subsets, visualizing the overall expression distribution of C-X-C chemokine-specific receptor gene cxcr5 among these T/NK cell subsets. Higher expression of cxcr5 was found in activated Tfh from FⅧ inhibitor mice, in comparison to the control group. The visualization using Upset plot R language showed a close interaction between Tfh and Treg. Moreover, the increased frequencies of Tfh and the decreased frequencies of Treg in inhibitor mouse splenocytes were further verified by flow cytometry analysis. CONCLUSION Multiple immune cell subsets, signaling pathways, and characteristic genes may be involved in the process of anti-FⅧ immune response in HA mouse splenocytes. The molecules involved in the regulation of Tfh/Treg may play key roles, which provide potential biological targets and therapeutic strategies for HA patients with inhibitors in the future.
Animals ; Hemophilia A/genetics* ; Mice ; Sequence Analysis, RNA ; Disease Models, Animal ; Spleen/cytology* ; T-Lymphocytes, Regulatory/immunology* ; Humans ; Signal Transduction ; Factor VIII/immunology* ; T-Lymphocytes, Helper-Inducer/immunology*

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Objective:To investigate the change and clinical significance of serum Cathepsin K (Cathe K), 25 hydroxyvitamin D (25 (OH) D) and matrix gla protein (MGP) in postmenopausal patients with osteoporosis.Methods:Sixty postmenopausal patients with osteoporosis admitted to the hospital from May. 2020 to May. 2023 were selected as the study group, and 75 simple menopausal women were selected to the control group at the same period. Serum Cathe K, 25 (OH) D and MGP levels of the subjects were determined by enzyme-linked immunosorbent assay (ELISA). Bone metabolism indexes [N-terminal propeptide of typeⅠprecollagen (PINP), β isomer of the C-terminal telopep-tide of typeⅠcollagen ( β-CTX), bone alkaline phosphatase, (BALP) and osteocalcin (OC) ] were detected. The levels of Cathe K, 25 (OH) D and MGP and bone metabolism indexes were compared and their correlation was analyzed by Pearson correlation. The predictive value of Cathe K, 25 (OH) D and MGP levels in osteoporosis were analyzed and their effects on osteoporosis were analyzed by multiple Logistic regression. Results:Serum Cathe K in the study group was higher [ (27.27±4.82) μg/L vs. (20.84±4.17) μg/L], 25 (OH) D and MGP were lower [ (25.81±5.33) ng/mL, (7.26±1.53) ng/mL vs. (31.62±5.92) ng/mL, (10.75±2.31) ng/mL] ( t=5.22, P<0.001; t=4.88, P<0.05; t=7.58, P<0.05) ; The bone metabolism indexes PINP, β-CTX and OC in the study group were higher, while BALP was lower; Pearson correlation analysis showed that Cathe K was positively correlated with PINP, β-CTX and OC, and negatively correlated with BALP ( r=0.53, 0.45, 0.61, -0.75, P<0.05) ; 25 (OH) D was negatively correlated with PINP, β-CTX, OC, and positively correlated with BALP ( r=-0.41, -0.63, -0.43, 0.38, P<0.05) ; MGP was positively correlated with PINP, β-CTX and OC, and negatively correlated with BALP ( r=-0.77, -0.59, -0.61, 0.52, P<0.05) ; The area under the curve of serum Cathe K, 25 (OH) D and MGP for predicting osteoporosis were 0.715, 0.694 and 0.789, respectively. Conclusion:The abnormal levels of serum Cathe K, 25 (OH) D and MGP in postmenopausal patients with osteoporosis can be used to predict the occurrence of osteoporosis, and are closely related to the bone metabolism indexes of patients, which can provide a reference for the treatment of patients.

Objective To achieve automatic segmentation of cell nuclei in gastrointestinal cancer pathological images by using a deep learning algorithm,so as to assist in the quantitative analysis of subsequent pathological images.Methods A total of 59 patients with gastrointestinal cancer treated in Ruijin Hospital,Shanghai Jiao Tong University School of Medicine from Jan 2022 to Feb 2022,were selected as the research objects.Python and LabelMe were used for data anonymization,image segmentation,and region of interest annotation of patients'pathological images.A total of 944 pathological images were included,and 9 703 nuclei were annotated.Then,a new semantic segmentation model based on deep learning was constructed.The model introduced deformable attention transformer(DAT)to realize automatic,accurate and efficient segmentation of pathological image nuclei.Finally,multiple segmentation evaluation criteria are used to evaluate the model's performance.Results The mean absolute error of the segmentation results of the model proposed in this paper was 0.112 6,and the dice coefficient(Dice)was 0.721 5.Its effect was significantly better than the U-net baseline model,and it was ahead of models such as ResU-net++,R2Unet and R2AttUnet.Moreover,the segmentation results were relatively stable with good generalization.Conclusion The segmentation model established in this study can accurately identify and segment the nuclei in the pathological images,with good robustness and generalization,which is helpful to play an auxiliary diagnostic role in practical applications.