BACKGROUND:Gradient artificial bone repair scaffolds can mimic unique anatomical features in musculoskeletal tissues,showing great potential for repairing injured musculoskeletal tissues. OBJECTIVE:To review the latest research advances in gradient artificial bone repair scaffolds for tissue engineering in the musculoskeletal system and describe their advantages and fabrication strategies. METHODS:The first author of the article searched the Web of Science and PubMed databases for articles published from 2000 to 2023 with search terms"gradient,bone regeneration,scaffold".Finally,76 papers were analyzed and summarized after the screening. RESULTS AND CONCLUSION:(1)As an important means of efficient and high-quality repair of skeletal system tissues,gradient artificial bone repair scaffolds are currently designed bionically for the natural gradient characteristics of bone tissue,bone-cartilage,and tendon-bone tissue.These scaffolds can mimic the extracellular matrix of native tissues to a certain extent in terms of structure and composition,thus promoting cell adhesion,migration,proliferation,differentiation,and regenerative recovery of damaged tissues to their native state.(2)Advanced manufacturing technology provides more possibilities for gradient artificial bone repair scaffold preparation:Gradient electrospun fiber scaffolds constructed by spatially differentiated fiber arrangement and loading of biologically active substances have been developed;gradient 3D printed scaffolds fabricated by layered stacking,graded porosity,and bio-3D printing technology;gradient hydrogel scaffolds fabricated by in-situ layered injections,simple layer-by-layer stacking,and freeze-drying method;and in addition,there are also scaffolds made by other modalities or multi-method coupling.These scaffolds have demonstrated good biocompatibility in vitro experiments,were able to accelerate tissue regeneration in small animal tests,and were observed to have significantly improved histological structure.(3)The currently developed gradient artificial bone repair scaffolds have problems such as mismatch of gradient scales,unclear material-tissue interactions,and side effects caused by degradation products,which need to be further optimized by combining the strengths of related disciplines and clinical needs in the future.

Objective: To find a viable alternative to reduce the number of doses required for the patients with post-traumatic stress disorder (PTSD), and to improve efficacy and patient compliance. Methods: In this study, we used ginger oil, a phytochemical with potential therapeutic properties, to prepare ginger oil patches. High-performance liquid chromatography (HPLC) was used to quantify the main active component of ginger oil, 6-gingerol. Transdermal absorption experiments were conducted to optimize the various pressure-sensitive adhesives and permeation enhancers, including their type and concentration. Subsequently, the ginger oil patches were optimized and subjected to content determination and property evaluations. A PTSD mouse model was established using the foot-shock method. The therapeutic effect of ginger oil patches on PTSD was assessed through pathological sections, behavioral tests, and the evaluation of biomarkers such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), brain-derived neurotrophic factor (BDNF), and melatonin (MT). Results: The results demonstrated that ginger oil patches exerted therapeutic effects against PTSD by inhibiting inflammatory responses and modulating MT and BDNF levels. Pharmacokinetic experiments revealed that ginger oil patches maintained a stable blood drug concentration for at least one day, addressing the rapid metabolism drawback of 6-gingerol and enhancing its therapeutic efficacy. Conclusions Ginger oil can be prepared as a transdermal drug patch that meets these requirements, and the bioavailability of the prepared patch is better than that of oral administration. It can improve PTSD with good patient compliance and ease of administration. Therefore, it is a promising therapeutic formulation for the treatment of PTSD.

Objective To investigate the feasibility and clinical experience of kidney transplantation from donors with Marfan syndrome (MFS). Methods Clinical data of 2 recipients undergoing kidney transplantation from the same MFS patient were retrospectively analyzed and literature review of 2 cases was conducted. Characteristics and clinical diagnosis and treatment of kidney transplantation from MFS patients were summarized. Results The Remuzzi scores of the left and right donor kidneys of the MFS patient during time-zero biopsy were 1 and 2. No significant difference was observed in the renal arteriole wall compared with other donors of brain death and cardiac death. Two recipients who received kidney transplantation from the MFS patient suffered from postoperative delayed graft function. After short-term hemodialysis, the graft function of the recipients received the left and right kidney began to gradually recover at postoperative 10 d and 20 d. After discharge, serum creatinine level of the recipient received the left kidney was ranged from 80 to 90 μmol/L, whereas that of the recipient received the right kidney kept declining, and the lowest serum creatinine level was 232 μmol/L before the submission date (at postoperative 43 d). Through literature review, two cases successfully undergoing kidney transplantation from the same MFS donor were reported. Both two recipients experienced delayed graft function, and then renal function was restored to normal. Until the publication date, 1 recipient has survived for 6 years, and the other recipient died of de novo cerebrovascular disease at postoperative 2 years. Conclusions MFS patients may serve as an acceptable source of kidney donors. However, the willingness and general conditions of the recipients should be carefully evaluated before kidney transplantation. Intraoperatively, potential risk of tear of renal arterial media should be properly treated. Extensive attention should be paid to the incidence of postoperative complications.

Objective To construct a precise model for identifying traditional Chinese medicine(TCM)constitutions,thereby offering optimized guidance for clinical diagnosis and treatment plan-ning,and ultimately enhancing medical efficiency and treatment outcomes. Methods First,TCM full-body inspection data acquisition equipment was employed to col-lect full-body standing images of healthy people,from which the constitutions were labelled and defined in accordance with the Constitution in Chinese Medicine Questionnaire(CCMQ),and a dataset encompassing labelled constitutions was constructed.Second,heat-suppres-sion valve(HSV)color space and improved local binary patterns(LBP)algorithm were lever-aged for the extraction of features such as facial complexion and body shape.In addition,a dual-branch deep network was employed to collect deep features from the full-body standing images.Last,the random forest(RF)algorithm was utilized to learn the extracted multifea-tures,which were subsequently employed to establish a TCM constitution identification mod-el.Accuracy,precision,and F1 score were the three measures selected to assess the perfor-mance of the model. Results It was found that the accuracy,precision,and F1 score of the proposed model based on multifeatures for identifying TCM constitutions were 0.842,0.868,and 0.790,respectively.In comparison with the identification models that encompass a single feature,either a single facial complexion feature,a body shape feature,or deep features,the accuracy of the model that incorporating all the aforementioned features was elevated by 0.105,0.105,and 0.079,the precision increased by 0.164,0.164,and 0.211,and the F1 score rose by 0.071,0.071,and 0.084,respectively. Conclusion The research findings affirmed the viability of the proposed model,which incor-porated multifeatures,including the facial complexion feature,the body shape feature,and the deep feature.In addition,by employing the proposed model,the objectification and intel-ligence of identifying constitutions in TCM practices could be optimized.

Background::Few evidence is available in the early prediction models of behavioral and psychological symptoms of dementia (BPSD) in Alzheimer’s disease (AD). This study aimed to develop and validate a novel genetic-clinical-radiological nomogram for evaluating BPSD in patients with AD and explore its underlying nutritional mechanism.Methods::This retrospective study included 165 patients with AD from the Chinese Imaging, Biomarkers, and Lifestyle (CIBL) cohort between June 1, 2021, and March 31, 2022. Data on demographics, neuropsychological assessments, single-nucleotide polymorphisms of AD risk genes, and regional brain volumes were collected. A multivariate logistic regression model identified BPSD-associated factors, for subsequently constructing a diagnostic nomogram. This nomogram was internally validated through 1000-bootstrap resampling and externally validated using a time-series split based on the CIBL cohort data between June 1, 2022, and February 1, 2023. Area under receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to assess the discrimination, calibration, and clinical applicability of the nomogram.Results::Factors independently associated with BPSD were: CETP rs1800775 (odds ratio [OR] = 4.137, 95% confidence interval [CI]: 1.276-13.415, P = 0.018), decreased Mini Nutritional Assessment score (OR = 0.187, 95% CI: 0.086-0.405, P <0.001), increased caregiver burden inventory score (OR = 8.993, 95% CI: 3.830-21.119, P <0.001), and decreased brain stem volume (OR = 0.006, 95% CI: 0.001-0.191, P = 0.004). These variables were incorporated into the nomogram. The area under the ROC curve was 0.925 (95% CI: 0.884-0.967, P <0.001) in the internal validation and 0.791 (95% CI: 0.686-0.895, P <0.001) in the external validation. The calibration plots showed favorable consistency between the prediction of nomogram and actual observations, and the DCA showed that the model was clinically useful in both validations. Conclusion::A novel nomogram was established and validated based on lipid metabolism-related genes, nutritional status, and brain stem volumes, which may allow patients with AD to benefit from early triage and more intensive monitoring of BPSD.Registration::Chictr.org.cn, ChiCTR2100049131.

Objective:To understand the learning interest of college students majoring in Bioinformatics in Shenyang Medical College and its influencing factors,so as to provide a strong basis for future teaching reform and curriculum setting.Method:After the actual teaching,a self-made questionnaire was used to conduct a quantitative survey on the first-year students majoring in Bioinformatics of Shenyang Medical College to understand their learning interest and analyze its influencing factors.Results:The questionnaire survey found that students majoring in Bioinformatics had different interest points for all 9 courses,different teaching links and different teaching methods in the second semester of freshman.Students had a general high interest in Introduction to Bioinformatics and Introduction to Biometrics.In the Introduction to Bioinformatics course,students were more interested in the history of bioinformatics,but less interested in algorithm-related knowledge points.In the Introduction to Biometrics course,students were more interested in the application cases of biometric recognition,but less interested in laws and regulations of biometrics.The interest of students in learning mainly lied in whether it is conducive to the postgraduate entrance examination.Conclusion:Through strengthen the education of bioinformatics related courses,enhance students'understanding of bioinformatics knowledge and improve their interest in Bioinformatics by analyzing the results of students'questionnaire.

Background: In the Chinese coal industry, widespread blame avoidance behavior (BAB) greatly impacts coal mine accidents. Therefore, it is necessary to stop the BAB of coal mine managers and raise the management level of coal mine enterprises for the safe development of Chinese coal industry. Methods: Based on the semi-structured interviews and questionnaire surveys (20 middle-level managers in coal mines), this paper used the Grounded Theory and Nvivo Software qualitative research methodology to open, spindle, and selectively encode the interview data. Then, an index system of factors influencing BAB of coal mine managers was constructed. The influence degree, affected degree, centrality degree, cause degree of each influencing factor were calculated and the hierarchical model of influencing factors of BAB of coal mine managers was established by the DEMATEL-ISM method which is a decision support tool used to evaluate and analyze the interdependencies between influencing factors. Results: Index system of factors influencing BAB of coal mine managers included four levels and 12 influencing factors: individual, organizational, institutional environmental, and situational factors. The hierarchical model identified eight causal factors and four consequential factors, of which safety management (15.355), work attitude (14.380), and work group performance (14.281) in the top three of the centrality rankings are the key factors affecting the avoidance behavior of coal mine managers; A 3-level multilevel structure was constructed to reflect the interactions among the factors influencing the BAB of coal mine managers in terms of direct, indirect, and root causes, and corresponding improvement measures were proposed. Conclusion This study offers a theoretical complement and practical guidance for stopping BAB of coal mine managers.

Background: In the Chinese coal industry, widespread blame avoidance behavior (BAB) greatly impacts coal mine accidents. Therefore, it is necessary to stop the BAB of coal mine managers and raise the management level of coal mine enterprises for the safe development of Chinese coal industry. Methods: Based on the semi-structured interviews and questionnaire surveys (20 middle-level managers in coal mines), this paper used the Grounded Theory and Nvivo Software qualitative research methodology to open, spindle, and selectively encode the interview data. Then, an index system of factors influencing BAB of coal mine managers was constructed. The influence degree, affected degree, centrality degree, cause degree of each influencing factor were calculated and the hierarchical model of influencing factors of BAB of coal mine managers was established by the DEMATEL-ISM method which is a decision support tool used to evaluate and analyze the interdependencies between influencing factors. Results: Index system of factors influencing BAB of coal mine managers included four levels and 12 influencing factors: individual, organizational, institutional environmental, and situational factors. The hierarchical model identified eight causal factors and four consequential factors, of which safety management (15.355), work attitude (14.380), and work group performance (14.281) in the top three of the centrality rankings are the key factors affecting the avoidance behavior of coal mine managers; A 3-level multilevel structure was constructed to reflect the interactions among the factors influencing the BAB of coal mine managers in terms of direct, indirect, and root causes, and corresponding improvement measures were proposed. Conclusion This study offers a theoretical complement and practical guidance for stopping BAB of coal mine managers.

Background: In the Chinese coal industry, widespread blame avoidance behavior (BAB) greatly impacts coal mine accidents. Therefore, it is necessary to stop the BAB of coal mine managers and raise the management level of coal mine enterprises for the safe development of Chinese coal industry. Methods: Based on the semi-structured interviews and questionnaire surveys (20 middle-level managers in coal mines), this paper used the Grounded Theory and Nvivo Software qualitative research methodology to open, spindle, and selectively encode the interview data. Then, an index system of factors influencing BAB of coal mine managers was constructed. The influence degree, affected degree, centrality degree, cause degree of each influencing factor were calculated and the hierarchical model of influencing factors of BAB of coal mine managers was established by the DEMATEL-ISM method which is a decision support tool used to evaluate and analyze the interdependencies between influencing factors. Results: Index system of factors influencing BAB of coal mine managers included four levels and 12 influencing factors: individual, organizational, institutional environmental, and situational factors. The hierarchical model identified eight causal factors and four consequential factors, of which safety management (15.355), work attitude (14.380), and work group performance (14.281) in the top three of the centrality rankings are the key factors affecting the avoidance behavior of coal mine managers; A 3-level multilevel structure was constructed to reflect the interactions among the factors influencing the BAB of coal mine managers in terms of direct, indirect, and root causes, and corresponding improvement measures were proposed. Conclusion This study offers a theoretical complement and practical guidance for stopping BAB of coal mine managers.

Background: In the Chinese coal industry, widespread blame avoidance behavior (BAB) greatly impacts coal mine accidents. Therefore, it is necessary to stop the BAB of coal mine managers and raise the management level of coal mine enterprises for the safe development of Chinese coal industry. Methods: Based on the semi-structured interviews and questionnaire surveys (20 middle-level managers in coal mines), this paper used the Grounded Theory and Nvivo Software qualitative research methodology to open, spindle, and selectively encode the interview data. Then, an index system of factors influencing BAB of coal mine managers was constructed. The influence degree, affected degree, centrality degree, cause degree of each influencing factor were calculated and the hierarchical model of influencing factors of BAB of coal mine managers was established by the DEMATEL-ISM method which is a decision support tool used to evaluate and analyze the interdependencies between influencing factors. Results: Index system of factors influencing BAB of coal mine managers included four levels and 12 influencing factors: individual, organizational, institutional environmental, and situational factors. The hierarchical model identified eight causal factors and four consequential factors, of which safety management (15.355), work attitude (14.380), and work group performance (14.281) in the top three of the centrality rankings are the key factors affecting the avoidance behavior of coal mine managers; A 3-level multilevel structure was constructed to reflect the interactions among the factors influencing the BAB of coal mine managers in terms of direct, indirect, and root causes, and corresponding improvement measures were proposed. Conclusion This study offers a theoretical complement and practical guidance for stopping BAB of coal mine managers.