Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

OBJECTIVE To investigate the transcriptomal charactersistics of the striatum in the chronic social defeat stress(CSDS)model mice by using spatial transcriptome analysis and to address the underlying mechanism of the striatum in regulating depressive states.METHODS The CSDS para-digm was employed to establish a depression-like mouse model.The depressive indicators of behavioral despair,anhedonia,and social disorders were assessed through a battery of tests,including the tail suspension test,forced swim test,sucrose preference test,and social interaction experiments.The control mice and the mice exhibiting CSDS-sensitive depression-like behaviors were selected for spatial tran-scriptome sequencing of the striatal region.This sequencing aimed to identify highly expressed genes,followed by KEGG and GO enrichment analyses using the DAVID database.RESULTS The CSDS mouse model effectively induced behavioral despair,anhedonia and social avoidance(P<0.05,P<0.01).Spatial transcriptome analysis revealed 193 differentially expressed genes in the striatum of normal mice.KEGG and GO analyses indicated that these genes were primarily associated with striatal devel-opment,locomotor behaviors,and drug addiction.They were strongly implicated in signaling pathways such as cyclic adenosine monophosphate,cyclic guanosine monophosphate-protein kinase G,calcium signaling,Ras-related protein 1,and mitogen-activated protein kinase,and synaptic linked to GABAergic and dopaminergic neurons.In contrast,CSDS modeling mice led to the identification of 298 differentially expressed genes in the striatum compared with the normal control mice.These genes were significantly enriched in pathways related to neurodegenerative diseases,including Huntington disease,Alzheimer disease,and Parkinson disease.CONCLUSION Depressive states induced by CSDS are associated with the pathological processes underlying neurodegenerative diseases in the striatum.

Cognitive frailty is a reversible neurodegeneration, and its early identification and prevention are crucial. This paper summarizes the current situation, risk factors, and risk prediction models of cognitive frailty in elderly patients with chronic diseases, aiming to provide a reference for clinical medical and nursing staff to identify the risk of cognitive frailty in elderly patients with chronic diseases as early as possible and formulate intervention measures.

Venous thromboembolism is a common complication in cancer patients and a common cause of death in cancer patients. Machine learning algorithms provide a new approach for assessing the risk of cancer-associated thrombosis (CAT). This paper reviews the machine learning based risk prediction model for CAT from summarizing, analyzing, and comparing the construction methods, basic information, and predictive performance of the models, so as to provide reference for the construction and application of CAT risk prediction models.

Objective This study aimed to investigate the levels of non-enzymatic antioxidants among patients with depression at different age stages.Methods One hundred thirty five patients with depression(including 63 elderly patients aged 60 years and older,and 72 young and middle-aged patients under 60 years old)and 98 healthy controls(including 46 elderly controls aged 60 years and older,and 52 young and middle-aged controls aged under 60 years old)were enrolled.Serum levels of non-enzymatic antioxidants(uric acid,total bilirubin,albumin)were assessed.Results Multiple analysis of variance showed the main effects of depression factors on uric acid and total bilirubin were significant(P<0.05).Uric acid[(314.30±85.18)μmol/L vs.(339.68±85.27)μmol/L],total bilirubin[(12.81±6.16)μmol/L vs.(15.09±5.97)μmol/L]levels were lower in patients with depression than in controls(P<0.05).There was an interactive effect between age and depression factors on the levels of albumin(P<0.001),and the levels of albumin[(41.05±3.97)g/L vs.(46.01±4.49)g/L]were lower in group of the elderly patients with depression than those in group of the young and middle-aged patients with depression(P<0.01).Conclusion Patients with depression have abnormalities in levels of non-enzymatic antioxidants which are more severe in elderly patients.

Objective:To explore the clinical features and prognosis of patients with primary central nervous system lymphoma(PCNSL).Methods:A retrospective analysis was performed on the relationship between clinical features,treatment regimen and prognosis in 46 newly diagnosed patients with primary central nervous system lymphoma who were diagnosed and treated in The Second Hospital of Lanzhou University from January 2015 to September 2022.Fisher's exact probability method was used to analyze the differences in clinical data of different subgroups.Kaplan-Meier survival curve was used to analyze the overall survival rate and progression-free survival rate of patients with different treatments,and the factors influencing survival were analyzed.Results:Among 46 patients with PCNSL,which pathological type were diffuse large B-cell lymphoma(DLBCL).There were 26(56.5％)cases of male and 20(43.5％)of female,with a median age of 54(17-71)years.In Hans subtypes,14 cases(30.4％)of GCB subtype,32 cases(69.6％)of non-GCB subtype.32 cases(69.6％)of Ki-67 ≥80％.Among 36 patients who completed at least 2 cycles of treatment with follow-up data,the efficacy evaluation was as follows:overall response rate(ORR)was 63.9％,complete response(CR)rate was 47.2％,17 cases of CR,6 cases of PR.The 1-year progression-free survival rate and 1-year overall survival rate was 73.6％and 84.9％,respectively.The 2-year progression-free survival rate and 2-year overall survival rate was 52.2％and 68.9％,respectively.The ORR and CR rate of 17 patients treated with RMT regimen was 76.5％and 52.9％(9 cases CR and 4 cases PR),respectively.Univariate analysis of 3 groups of patients treated with RMT regimen,RM-BTKi regimen,and RM-TT regimen as first-line treament showed that deep brain infiltration was associated with adverse PFS(P=0.032),and treatment regimen was associated with adverse OS in PCNSL patients(P=0.025).Conclusion:Different treatment modalities were independent prognosis predictors for OS,the deep brain infiltration of PCNSL is a poor predictive factor for PFS.Patients with relapse/refractory(R/R)PCNSL have a longer overall survival time because to the novel medication BTKi.They have strong toleration and therapeutic potential as a first-line therapy for high-risk patients.

Objective:To observe the clinical effect of initiating continuous blood purification (CBP) treatment at different times for patients with severe acute pancreatitis (SAP), and to explore the optimal timing for starting CBP treatment for SAP, so as to provide evidence for clinicians to start CBP treatment.Methods:A retrospective cohort study was used to select patients with SAP who received CBP treatment in People's Hospital of Hunan Province from January 2020 to December 2023. According to the timing of CBP initiation, the patients were divided into early initiation group (diagnosis of SAP to the first CBP treatment time < 24 hours) and late initiation group (diagnosis of SAP to the first CBP treatment time of 24-48 hours). The general data, acute physiology and chronic health evaluationⅡ(APACHEⅡ), bedside index for severity in acute pancreatitis (BISAP) score and laboratory indicators, local complications and systemic complications, intensive care unit (ICU) treatment time, hospital stay, treatment cost, and clinical outcome of the two groups were collected and compared.Results:A total of 130 patients with SAP who received CBP treatment were enrolled, including 90 patients in the early initiation group and 40 patients in the late initiation group. Before treatment, there were no significant differences in gender, age, APACHEⅡscore, BISAP score, etiology and laboratory examination indexes between the early initiation group and late initiation group. At 48, 72, 96 hours after treatment, the blood calcium level of the two groups was significantly higher than that before treatment, and the levels of white blood cell count (WBC), C-reactive protein (CRP), lactic acid, interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), APACHEⅡscore and BISAP score were significantly lower than those before treatment. The WBC level, APACHEⅡscore and BISAP score of the late initiation group were significantly lower than those of the early initiation group at 72 hours and 96 hours after treatment [WBC (×10 9/L): 10.96 (8.68, 13.04) vs. 12.45 (8.93, 16.30) at 72 hours after treatment, and 10.18 (8.68, 12.42) vs. 11.96 (8.81, 16.87) at 96 hours after treatment; APACHEⅡscore: 9.50 (5.75, 12.00) vs. 11.00 (6.25, 14.00) at 72 hours after treatment, and 10.00 (4.00, 12.00) vs. 12.00 (7.00, 14.75) at 96 hours after treatment; BISAP score: 2.35±1.03 vs. 2.76±1.10 at 72 hours after treatment, and 2.08±1.21 vs. 2.70±1.11 at 96 hours after treatment], the differences were statistically significant (all P < 0.05). In terms of complications, the incidence of pancreatic abscess in the late initiation group was significantly lower than that in the early initiation group [5.00% (2/40) vs. 20.00% (18/90)], but the incidence of abdominal compartment syndrome was significantly higher than that in the early initiation group [42.50% (17/40) vs. 13.33% (12/90)], the differences were statistically significant (all P < 0.05). In addition, the ICU treatment time in the early initiation group was significantly shorter than that in the late initiation group [days: 11.00 (6.00, 20.00) vs. 15.00 (9.75, 25.00), P < 0.05], and there were no statistically significant differences in hospitalization costs, length of stay and mortality between the two groups. Conclusions:CBP can effectively increase the level of blood calcium and decrease the level of lactic acid and inflammatory factors. Starting CBP within 24-48 hours after diagnosis of SAP can reduce WBC level and disease severity score faster, and reduce the occurrence of pancreatic abscess. Initiation of CBP within 24 hours after diagnosis of SAP can reduce the incidence of abdominal compartment syndrome and shorten the duration of ICU treatment.

Objective To systematically evaluate the self-management behavior transformation experience of cancer patients,providing a basis for the subsequent development of targeted self-management intervention measures.Methods Qualitative studies related to self-management behavior transformation experience of cancer patients from Cochrane Library,CINAHL,Embase,PubMed,Web of science,PsycINFO,and China National Knowledge Infras-tructure,VIP Database,Wanfang Database,and China Biomedical Literature Database were searched by computer,with a search deadline of July 2023.The literature quality evaluation was conducted using the qualitative research quality evaluation standards of the Evidence Based Health Care Center at the Joanna Briggs Institute in Australia,and the results were integrated using a pooled integration method.Results A total of 12 articles were included,and 50 research results were extracted and summarized into 14 new categories.4 integrated results were synthesized,including the forms of self-management behavior transformation,the characteristics of self-management behavior transformation,the driving factors of self-management behavior transformation,and the obstacles to self-management behavior transformation.Conclusion Medical staff should pay attention to the real experience of cancer patients'self-management behavior transformation.Targeted ability cultivation and psychological intervention can be carried out based on the characteristics and influencing factors of cancer patients'self-management behavior transformation,promoting their smooth transformation of self-management behavior.