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.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective To analyze the practical value of spiral CT three-dimensional reconstruction techniquein evaluating triplane fractures of the distal tibia.Methods A retrospective analysis was conducted on183 patients with triplane fractures of the distal tibia admitted to Sichuan Orthopedic Hospital from January 2021 to March 2023.All patients underwent both X-ray and spiral CT examinations.Taking surgical reduction results as the gold standard for diagnosis,the diagnostic accuracies of X-ray examination and spiral CT three-dimensional reconstruction technique for triplane fractures of the distal tibia were analyzed.Results Fracture classification according to the number of fracture fragments showed that among the 183 patients with triplane fractures of the distal tibial,there were 44 cases of four-part fractures,62 cases of three-part fractures,and 77 cases of two-part fractures.The classification by the location of epiphyseal injury in the distal tibia showed 175 cases of lateral type and 8 cases of medial type.According to whether the fracture line involved the articular surface,they were categorized into 94 cases of type I,60 cases of type II,and 29 cases of type III.For the classification of the number of fracture fragments,X-ray misdiagnosed 9 cases of four-part fractures as three-part or two-part fractures,and 21 cases of three-part fractures as two-part fractures,resulting in a diagnostic accuracy of 83.60%.For theclassification of fracture line and articular surface position,X-ray led to misdiagnosis or inaccurate diagnosis in 39 cases,with a diagnostic accuracy of 78.69%.When spiral CT three-dimensional reconstruction technique was used to classify the number of fracture fragments,only 1 case of four-part fracture was misdiagnosed as three-part fracture,and 2 cases of three-part fractures were misdiagnosed as four-part fractures or two-part fractures,yielding a diagnostic accuracy of 98.36%.For the diagnosis of the positional relationship of the fracture line to the articular surface,spiral CT three-dimensional reconstruction technique had 8 misdiagnoses,with a corresponding diagnostic accuracy of 95.63%.Conclusion Spiral CT three-dimensional reconstruction technique can stereoscopically display the spatial information of the triplane fractures of the distal tibia,such as the location,shape,type,and articular surface,exhibiting high accuracy for classification diagnosis and significant application value in the reduction and treatment of triplane fractures of the distal tibia.

The CDH23 gene is a pathogenic mutant gene of the USH1D subtype in Usher syndrome.In this study,two wild-type Cdh23 full-length plasmids(～16 kb)with different promoters were construc-ted,and fluorinated polyethylene imine(FPEI)was used as a delivery vector to transfect the house ear institute-organ of corti 1(HEI-OC1)and the optimal expression plasmid was obtained by evaluating the transfection efficiency in vitro.Firstly,the results of the synthesis of FPEI were analyzed using Fourier transform infrared absorption spectroscopy to prove the successful synthesis of FPEI.After that,the plas-mid encapsulation ability of FPEI and the surface potential and hydration diameter of the formed comple-xes were characterized by agarose gel blocking assay,Zeta potential assay,and dynamic light scattering assay.It was found that FPEI had good plasmid encapsulation ability,and the FPEI plasmid complexes were all positively charged at high mass ratio,with the distribution of particle sizes in the range of 100-300 nm.The low cytotoxicity and high transfection efficiency of FPEI in HEI-OC1 cells were verified by Cell Counting Kit-8(CCK-8)and flow cytometry.Comparing FPEI with Lipofectamine 3000 and differ-ent quality PEI(25K,40K)transfection reagents,the transfection efficiency of FPEI was found to be significantly better than that of the traditional transfection reagents.Quantitative real-time polymerase chain reaction(qRT-PCR)and Western blot results showed that the CAG promoter was better than the CMV promoter,which could be used as the optimal expression plasmid for the subsequent in vivo experi-ments.In addition,it was verified by cellular immunofluorescence that CDH23 was mainly distributed in the cytoplasm after overexpression.The above results demonstrated that FPEI can be used as an efficient delivery vector for in vitro overexpression of large genes represented by Cdh23,which provides an impor-tant experimental basis for subsequent in vivo gene therapy of USH1D syndrome.

Constipation is a common functional gastrointestinal disorder with a global prevalence of approximately 10％to 20％.Its causes include functional disorders,organic diseases,and drug factors,with the majority being functional constipation.In recent years,driven by advancements in biomedicine,artificial intelligence(AI),and microbiome research,significant progress has been made in the diagnosis and treatment of constipation.This review systematically explores the latest developments in constipation treatment,including the role of the gut microbiota in constipation,the metabolic regulatory effects of short-chain fatty acids(SCFAs),the impact of mental factors on intestinal motility.Additionally,it discusses future development directions such as AI-assisted diagnosis,AI-based consultation systems,personalized microbiota transplantation,and minimally invasive neuromodulation,providing new insights for precision medicine in constipation.

Objective To construct radiomics-semantic models to predict the treatment resistance of chemoradiotherapy in brain gliomas based on MRI and clinical data of multicenter patients.Methods Among 2 108 brain gliomas patients from five medical institutions,132 patients had residual gliomas after surgery.The clinical risk factors and multimodal MRI were collected.All patients were divided into training set(n=95)and validation set(n=37).The treatment response of gliomas after standardized chemoradiotherapy were divided into resistant and non-resistant types.The semantic features of MRI were evaluated by two radiologists.Three different segmentation regions of interest(ROI)were delineated to extract radiomics features.And that three groups of radiomics models were con-structed based on different sequence MRIs.The radiomics model with the best predictive efficacy in each group was selected and combined with MRI semantic features,three radiomics-semantic models(combined models)were established.Finally,a MRI semantic model,three groups of radiomics models and three combined models were developed.Results Comparisons between the different models showed that the radiomics-semantic model based on pre-operative T2-fluid attenuated inversion recovery(FLAIR)sequence,had the best predictive efficacy,the area under the curve(AUC)in the training and validation sets were 0.866[95％confidence interval(CI)0.790-0.942]and 0.810(95％CI 0.667-0.952),respectively.The radiomics-semantic model based on postoperative T1 WI sequence performed the second best,with the AUC of the training and validation sets being 0.812(95％CI 0.726-0.898)and 0.711(95％CI 0.541-0.881),respectively.Conclusion The combined models based on MRI radiomics and semantic features are able to predict the treatment resistance of chemoradiotherapy in brain gliomas patients,and may be used as an important basis for optimizing treatment.

Objective:To construct a nursing quality evaluation indicator system for pulse indicator continuous cardiac output (PiCCO) monitoring and provide a basis for evaluating the nursing quality of PiCCO monitoring.Methods:Using Donabedian′s "structure-process-result" three-dimensional quality evaluation model as the theoretical framework, the nursing quality evaluation indicator system for PiCCO was established through literature search, Delphi expert correspondence, and hierarchical analysis during the period May to August 2023.Results:Of the 22 experts, 6 were male and 16 were female, aged (46.59 ± 4.34) years. The return rates of the questionnaires of the 2 rounds of expert correspondence were both 100%, the coefficients of expert authority were both 0.945, and the Kendall coordination coefficients were 0.045-0.186 ( χ2 values were 2.00-221.46, all P<0.05) and 0.045-0.132 ( χ2 values were 2.00-82.16, all P<0.05), respectively. The finalized nursing quality evaluation indicator system for PiCCO included 3 primary indicators, 7 secondary indicators, and 36 tertiary indicators. Conclusions:The nursing quality evaluation indicator system for PiCCO is practical and scientific, which can provide reference for PiCCO monitoring nursing quality evaluation.

As a globally prevalent malignancy with high morbidity and mortality rates,hepatocellular carcinoma has demonstrated significant potential in prognostic prediction and therapeutic evaluation through its imaging manifestations.This article focuses on the potential correlations between current imaging characteristics of hepatocellular carcinoma and its prognosis,emphasizing the importance of adopting and promoting a standardized imaging terminology system.It illustrates specific examples of imaging features associated with prognosis,reviews recent research hotspots and advancements in hepatocellular carcinoma prognosis.The aim is to offer precise prognostication,diagnosis and treatment strategies for patients with hepatocellular carcinoma.

In clinical practice,the diagnosis of hepatocellular carcinoma primarily relies on imaging findings.For cases with atypical imaging features or insufficient diagnostic specificity,pathological analysis remains essential.With the advancement of precision medicine,research focus has expanded from pure diagnostic evaluation to therapeutic efficacy prediction.Imaging-based prognostic biomarkers have emerged as a key research frontier in hepatocellular carcinoma management.Although accurate diagnosis remains paramount,current investigations increasingly prioritize the identification of biomarkers for treatment response prediction and outcome stratification.Recent studies demonstrate that radiological characteristics not only reflect tumor heterogeneity but also carry prognostic implications for hepatocellular carcinoma.These imaging biomarkers enable non-invasive outcome prediction and provide objective evidence to optimize therapeutic decision-making.This comprehensive review summarizes MRI-derived imaging features associated with hepatocellular carcinoma prognosis,aiming to guide personalized treatment strategies and ultimately improve survival outcomes for hepatocellular carcinoma patients.