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.

OBJECTIVE: To investigate the clinical effect of minimally invasive technique in the treatment of moderate and severe gluteal muscle contracture. METHODS: A retrospective study was conducted on 85 patients (170 sides) with bilateral gluteal muscle contracture admitted from January 2016 to December 2019. All patients were treated with minimally invasive release of tendon knife. There were 32 males and 53 females, ranging in age from 15 to 37 years old, with an average age of (22.3±6.3) years old. Operation time, intraoperative blood loss, incision length, first postoperative ambulation time, complication rate, recurrence rate, and Harris hip score (HHS) were analyzed and evaluated. RESULTS: The average follow-up time was (16.2±4.6) months, ranging from 12 to 30 months. The operation time ranged from 7 to 15 min, with an average of (10.2±3.1) min. Intraoperative blood loss ranged from 2 to 20 ml, with an average of (8.4±2.2) ml. The incision length ranged from 0.6 to 2.0 cm, with an average of (0.8±0.3) cm. The time to postoperative ambulation ranged from 12 to 28 h, with an average of (20.0±3.2) h. All patients achieved primary wound healing without sciatic nerve injury or recurrence. HHS hip function scores ranged from 90 to 98, with an average score of (96.2±1.4). Complications included intraoperative tendon blade tip fracture in two cases (removed under fluoroscopic guidance) and subcutaneous hematoma in three cases-two resolved with compression and one with open evacuation.. Twenty-nine patients exhibited transient swaying gait postoperatively, of which 24 patients returned to normal after 4 weeks and 5 patients returned to normal after 6 weeks. CONCLUSION Minimally invasive tendon blade release is a safe and effective technique for treating gluteal muscle contracture, offering minimal trauma, rapid recovery, and excellent cosmetic and functional outcomes. However, it exhibits a low risk of blade tip fracture and sciatic nerve injury, warranting experienced surgical handling.
Humans ; Male ; Female ; Adult ; Minimally Invasive Surgical Procedures/methods* ; Adolescent ; Retrospective Studies ; Buttocks/surgery* ; Young Adult ; Contracture/surgery* ; Tendons/surgery* ; Muscle, Skeletal/surgery*

OBJECTIVE: To analyze the changes in coagulation during the treatment of acute promyelocytic leukemia (APL) and explore the influencing factors of coagulation in patients with APL. METHODS: Data of 166 APL patients admitted to our hospital from November 2018 to May 2023 were retrospectively analyzed, and the changes of various clinical indicators before and during treatment were compared. 166 APL patients were divided into abnormal coagulation group (n =115) and normal coagulation group (n =51) according to whether they experienced coagulation dysfunction. The basic information, clinical data and laboratory indicators of the two groups were compared. Multivariate logistic regression analysis was used to screen risk factors for coagulation dysfunction and established logistic regression model. Then we developed a neural network model and ranked the importance of the influencing factors, and used receiver operating characteristic (ROC) curves to evaluate the predictive performance of the two models. RESULTS: The comparative results of various clinical indicators in 166 APL patients before and during treatment showed that systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), estimated glomerular filtration rate (eGFR), platelet (PLT) and fibrinogen (FIB) were significantly increased during the treatment (P < 0.05), while glycosylated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), blood urea nitrogen (BUN), serum creatinine (SCr), high-sensitivity C reactive protein (hs-CRP), IL-6, TNF-α, TGF-β, white blood cells (WBC), absolute neutrophil count (ANC), prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer (D-D), fibrinogen degradation products (FDP) and lactate dehydrogenase (LDH) were significantly decreased during the treatment (P < 0.05). The proportion of patients with hemorrhage and high-risk APL in the abnormal coagulation group was significantly higher than that in the normal coagulation group (P < 0.05). The levels of IL-6, TNF-α, WBC, ANC, D-D, FDP and LDH in the abnormal coagulation group were significantly higher than those in the normal coagulation group (P < 0.05). The influencing factors selected by univariate analysis were incorporated into logistic regression analysis and neural network model to predict the risk of coagulation dysfunction in APL patients. ROC curves showed that the AUC of the two models were 096 and 0.908, the sensitivity were 0.824 and 0.892, the specificity were 0.940 and 0.904, the Youden index were 064 and 0.796, and the accuracy were 0.882 and 0.898, respectively. CONCLUSION High risk stratification, hemorrhage, elevated WBC, LDH, ANC and FDP levels are independent risk factors for coagulation dysfunction in APL patients. The logistic regression model and neural network model based on these risk factors demonstrate good predictive performance for coagulation dysfunction in APL patients.
Humans ; Leukemia, Promyelocytic, Acute/therapy* ; Blood Coagulation ; Retrospective Studies ; Male ; Female ; Risk Factors ; Logistic Models ; Middle Aged ; Adult ; ROC Curve

Drug resistance is one of the key factors affecting the effectiveness of cancer treatment methods, including chemotherapy, radiotherapy, and immunotherapy. Its occurrence is related to factors such as mRNA expression and methylation within cancer cells. If drug resistance in patients can be accurately identified early, doctors can devise more effective treatment plans, which is of great significance for improving patients' survival rates and quality of life. Cancer drug resistance prediction based on artificial intelligence (AI) technology has emerged as a current research hotspot, demonstrating promising application prospects in guiding clinical individualized and precise medication for cancer patients. This review aims to comprehensively summarize the research progress in utilizing AI algorithms to analyze multi-omics data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology, for predicting cancer drug resistance. It provides a detailed exposition of the processes involved in data processing and model construction, examines the current challenges faced in this field and future development directions, with the aim of better advancing the progress of precision medicine.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health concern in northwest China; however, the impact of particulate matter (PM) exposure during sand-dust storms (SDS) remains poorly understood. Therefore, this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions. METHODS: Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022, along with the corresponding air pollutant and meteorological data for each city in Gansu Province. Employing a space-time-stratified case-crossover design and conditional Poisson regression, we analyzed 265,379 COPD hospitalizations. RESULTS: PM exposure during SDS days significantly increased COPD hospitalization risk [relative risk ( RR) for PM _2.5, lag 3:1.028, 95% confidence interval ( CI): 1.021-1.034], particularly among men and the elderly, and during the cold season. The burden of PM exposure on COPD hospitalization was substantially high in Northwest China, especially in the arid and semi-arid regions. CONCLUSION Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China. This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.
Humans ; China/epidemiology* ; Pulmonary Disease, Chronic Obstructive/chemically induced* ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Male ; Female ; Middle Aged ; Aged ; Air Pollutants/analysis* ; Environmental Exposure/adverse effects* ; Spatio-Temporal Analysis ; Adult ; Sand ; Air Pollution

Neck dissection(ND)is one of the main treatment methods for oral and maxillofacial malignancies.Although ND type is in con-stant improvement,but intraoperative peal-pull-push injury of the accessory nerve,muscle,muscle membrane,fascia and ligament induced shoulder syndrome(SS)is still a common postoperative complication,combined with the influence of radiochemotherapy,not only can cause pain,stiffness,numbness,limited dysfunction of shoulder neck and arm,but also may have serious impact on patient's life quality and phys-ical and mental health.At present,there is still a lack of a systematic evaluation and rehabilitation management program for postoperative SS of oral and maxillofacial malignant tumors.Based on the previous clinical practice and the current available evidence,refer to the relevant lit-erature at home and abroad,the experts in the field of maxillofacial tumor surgery and rehabilitation were invited to discuss,modify and reach a consenusus on the etiology,assessment diagnosis,differential diagnosis,rehabilitation strategy and prevention of SS,in order to provide clinical reference.

Monosodium urate (MSU)-induced the gouty arthritis (GA) model was used to investigate the effect of Nod-like receptor protein 3 (NLRP3) inhibitor N14 in alleviating GA. Firstly, the effect of NLRP3 inhibitor N14 on the viability of mouse monocyte macrophage J774A.1 was examined by the cell counting kit-8 (CCK-8) assay. The expression of mature interleukin 1β (IL-1β) and cysteinyl aspartate specific proteinase-1 (caspase-1) p20 in the cell supernatant and the expression of NLRP3, caspase-1 and pro-IL-1β proteins in the cell lysates was detected by Western blot for the inhibitory effect of N14 on the MSU-induced NLRP3 inflammasome activation in J774A.1 cells. Animal behavioral tests were used to detect redness, swelling, heat and pain in mice with gouty arthritis. Hematoxylin-eosin (H&E) staining revealed pathologic changes and inflammatory infiltration in foot sections. Protein expression of NLRP3, caspase-1, and pro-IL-1β in mouse hind paw tissues were assessed by Western blot. The effect of N14 on the plasma levels of alanine transaminase (ALT), aspartate transaminase (AST), creatinine (CRE), urea, and uric acid (UA) was investigated by the MSU-induced gouty arthritis model in mice. All animal experiments in this paper were approved by the Scientific Ethics Review Board of Qingdao Marine Biomedical Research Institute (grant No. E-MBWNL-2024-20). The experimental results showed that N14 did not exhibit cytotoxicity in mouse monocyte macrophage J774A.1 cells at concentrations up to 100 μmol·L^-1, and N14 effectively prevented MSU-induced activation of NLRP3 inflammasome. In the mouse gouty arthritis model, N14 significantly ameliorated the redness, swelling, heat and pain caused by GA, and down-regulated the levels of NLRP3 inflammasome-associated proteins in mouse hind paw tissues. Meanwhile, N14 appeared to be well tolerated, as it did not significantly affect various biochemical indices in mouse plasma. In conclusion, N14 effectively alleviated GA in mice by inhibiting the NLRP3 inflammasome pathway, which is important for both prevention and treatment of related diseases.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective By screening key genes and related pathways for hepatic fibrosis treatment through bioinformatics analysis,the differentially expressed genes of hepatic fibrosis patients were mined to predict potential therapeutic targets for liver fibrosis.Methods Gene expression profiles GSE197112 were obtained from GEO database.Differentially expressed genes were screened by Limma.DAVID online database was used to conduct GO enrichment analysis and KEGG signaling pathway enrichment analysis of differentially expressed genes.The protein-protein interaction(PPI)network diagram of differentially expressed genes were obtained from STRING database and visualize by Cytoscape software.At the same time,the plug-in CytoHubba in Cytoscape software was used to screen the target genes of hepatic fibrosis.Results A total of 399 differentially expressed genes were screened(P<0.01,∣log2FC∣>1.5),including 300 down-regulated genes and 99 up-regulated genes.These genes were mainly involved in GO biological processes such as mitosis checkpoint,DNA replication,chromosome segregation,cell division,apoptosis,adaptive immune response and so on,and mainly regulated the intestinal immune network for IgA production,progesterone-mediated oocyte maturation,human T-cell leukemia virus 1 infection,cell cycle,antigen processing and presentation,p53 signaling pathway,cancer transcription disorder,cell adhesion molecules and so on.Five target genes were screened by Cytoscape software:TTK,KIF2C,ASPM,DLGAP5,PBK.Conclusion In this study,399 differentially expressed genes and 5 target genes in hepatic fibrosis were screened by bioinformatics methods,which play key roles in the biological processes related to hepatic fibrosis,and provide a new direction for the pharmacological treatment of liver fibrosis.