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.

ObjectiveThe primary objective of this study was to investigate the effects of carbohydrate intake order on post-exercise recovery and metabolic regulation under heat stress, particularly in models of exercise induced fatigue. Given the increasing significance of optimizing nutritional strategies to support performance in extreme environmental conditions, this study aimed to provide experimental evidence that contributes to a better understanding of how the sequence in which carbohydrates are consumed impacts exercise recovery, metabolic homeostasis, and fatigue alleviation in a high-temperature environment. MethodsA mouse model of exercise-induced fatigue was established under high-temperature (35°C) to simulate heat stress. The subjects were divided into 3 distinct groups based on their carbohydrate intake order: the “mixed intake” group (HOT_MIX), where all macronutrients (carbohydrates, proteins, and fats) were consumed in a balanced ratio; the “carbohydrate-first intake” group (HOT_CHO), where carbohydrates were consumed first followed by other macronutrients; the “carbohydrate-later intake” group (HOT_PRO), where proteins and fats were consumed prior to carbohydrates. Each group underwent a 7 d intervention period with daily intake according to their designated group. Exercise performance was assessed using rotarod retention time test, and biomarkers of muscle damage, such as lactate dehydrogenase (LDH), creatine kinase (CK), lactate (LD), alanine aminotransferase (ALT), and non-esterified fatty acids (NEFA), were measured. Furthermore, targeted metabolomics analyses were conducted to investigate metabolic shifts in response to different dietary strategies, and KEGG pathway enrichment analysis was employed to explore the biological mechanisms underlying these changes. ResultsThe findings demonstrated that the HOT_PRO group exhibited a significantly improved performance in the rotarod test, with a longer retention time compared to both the HOT_MIX and HOT_CHO groups (P<0.05). Additionally, this group showed significantly reduced levels of muscle damage markers such as LDH and CK, indicating that the carbohydrate-later intake strategy helped alleviate exercise-induced muscle injury. Metabolomic profiling of the HOT_PRO group showed marked increases in alanine, creatine, and flavin adenine dinucleotide (FAD), indicating shifts in amino acid metabolism and oxidative metabolism. Conversely, metabolites such as spermidine, cholesterol sulfate, cholesterol, and serine were significantly reduced in the HOT_PRO group, pointing to alterations in lipid and sterol metabolism. Further analysis of the differential metabolites revealed that these changes were primarily associated with key metabolic pathways, including glycine-serine-threonine metabolism, primary bile acid biosynthesis, taurine and hypotaurine metabolism, and steroid hormone biosynthesis. These pathways are essential for energy production, antioxidant defense, and muscle recovery, suggesting that the carbohydrate-later feeding strategy may promote metabolic homeostasis and improve exercise recovery by enhancing these critical metabolic processes. ConclusionThe results of this study support the hypothesis that consuming carbohydrates after proteins and fats during exercise recovery enhances metabolic homeostasis and accelerates recovery under heat stress. This strategy effectively modulates energy, amino acid, and lipid-related pathways, which are crucial for improving endurance performance and mitigating fatigue in high-temperature environments. The findings suggest that carbohydrate-later intake could be a promising nutritional strategy for athletes and individuals exposed to heat during physical activity. Furthermore, the study provides valuable insights into how different nutrient timing strategies can impact exercise recovery and metabolic regulation, paving the way for more personalized and effective nutritional interventions in extreme environmental conditions.

Colorectal cancer(CRC) is one of the most common malignant tumors worldwide, primarily originating from recurrent inflammatory bowel disease(IBD). Therefore, blocking the inflammation-cancer transformation in the colon has become a focus in the early prevention and treatment of CRC. The inflammation-cancer transformation in the colon involves multiple types of cells and complex pathological processes, including inflammatory responses and tumorigenesis. In this complex pathological process, immune cells(including non-specific and specific immune cells) and non-immune cells(such as tumor cells and fibroblasts) interact with each other, collectively promoting the progression of the disease. In traditional Chinese medicine(TCM), inflammation-cancer transformation in the colon belongs to the categories of dysentery and diarrhea, with the main pathogenesis being cold and heat in complexity. This paper first elaborates on the complex molecular mechanisms involved in the inflammation-cancer transformation process in the colon from the perspectives of inflammation, cancer, and their mutual influences. Subsequently, by comparing the pathogenic characteristics and clinical manifestations between inflammation-cancer transformation and the TCM pathogenesis of cold and heat in complexity, this paper explores the intrinsic connections between the two. Furthermore, based on the correlation between inflammation-cancer transformation in the colon and the TCM pathogenesis, this paper delves into the importance of the interaction between inflammation and cancer. Finally, it summarizes and discusses the clinical and basic research progress in the TCM intervention in the inflammation-cancer transformation process, providing a theoretical basis and treatment strategy for the treatment of CRC with integrated traditional Chinese and Western medicine.
Humans ; Colon/pathology* ; Integrative Medicine ; Animals ; Cold Temperature ; Cell Transformation, Neoplastic/drug effects* ; Medicine, Chinese Traditional ; Hot Temperature ; Inflammation ; Drugs, Chinese Herbal/therapeutic use* ; Colonic Neoplasms/drug therapy*

OBJECTIVE: To explore the effect of simvastatin monotherapy or in combination with doxorubicin on diffuse large B-cell lymphoma (DLBCL) cells and its possible molecular mechanisms. METHODS: The differences in the expression levels of genes and proteins related to the mevalonate (MVA) pathway between DLBCL tissues and reactive lymph node hyperplasia tissues were compared via database analysis, as well as their effects on the prognosis. CCK-8 assay was used to detect the effect of simvastatin and doxorubicin on the viability of different subtypes of DLBCL cells, EdU was used to detect cell proliferation, flow cytometry was used to detect apoptosis, and Western blot was used to detect related protein and signaling pathway proteins. RESULTS: The expression levels of MVA pathway-related genes were increased in tumor tissues of DLBCL patients through the TCGA database, and the median overall survival time of DLBCL patients in HMGCR high expression group was shorter (all P < 0.05). Meanwhile, according to The Human Protein Atlas database, HMGCR protein was significantly high expressed in DLBCL tumor tissue compared with normal tissue. The viability of DLBCL cell lines treated with simvastatin or doxorubicin monotherapy was decreased in time- and concentration-dependent manner, and could be further inhibited by simvastatin combined with doxorubicin especially in GCB subtype cell lines. Both simvastatin and doxorubicin could inhibit the proliferation of DLBCL cell lines, and their combination further suppressed dramatically. Both the two drugs promoted apoptosis in DLBCL cell lines, and the apoptosis was further increased after their combination. Compared with monotherapy, the expression of HMGCR protein and apoptosis-related protein Bcl-2 was further decreased but cleaved-caspase3 and Bax increased after combination therapy. Meanwhile, the expression level of phosphorylated proteins in PI3K-Akt pro-survival signaling pathway were decreased especially in GCB subtype cell lines. CONCLUSION HMGCR, the protein associated with cholesterol synthesis pathway, is highly expressed in DLBCL tumor tissues and indicates poor prognosis. Simvastatin, a lipid-lowering drug, combined with doxorubicin can further affect the survival of DLBCL tumor cells at the cellular level.
Humans ; Lymphoma, Large B-Cell, Diffuse/metabolism* ; Doxorubicin/pharmacology* ; Simvastatin/pharmacology* ; Apoptosis/drug effects* ; Cell Proliferation/drug effects* ; Signal Transduction ; Cell Line, Tumor ; Hydroxymethylglutaryl CoA Reductases/metabolism*

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OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

Objective To investigate the impact of positive antinuclear antibody(ANA)and subsequent interven-tion therapy on the assisted reproductive technology outcomes among the patients experiencing recurrent implanta-tion failure(RIF).Methods A retrospective study was conducted on 344 RIF patients.Based on ANA test re-sults,the patients were divided into ANA-positive group(294 cases)and negative control group(50 cases).The ANA-positive group was further divided into a low titer group(214 cases)and a high titer group(80 cases).Com-parative statistical analyses such as the Wilcoxon rank-sum test,Mann-Whitney U test,Kruskal-Wallis test and chi-square test,etc.were employed to evaluate differences in general clinical data,embryo-related parameters,and pregnancy outcomes between the positive and negative groups.The impact of ANA on the assisted reproductive out-comes of patients with recurrent implantation failure was analyzed,and the outcomes of ANA-positive patients after intervention therapy were also analyzed.Results Notably,the clinical pregnancy rates of patients in the ANA-pos-itive low titer group and high titer group were significantly lower than those in the negative control group(P＜0.001).Similarly,the rates of fertilization and cleavage of oocytes in ANA-positive patients were also significantly lower than those in the negative control group(P＜0.05).For patients who did not achieve pregnancy after embryo transfer due to ANA positivity,immunomodulatory therapy significantly improved both the clinical pregnancy rate and cumulative clinical pregnancy rate(P＜0.05).Conclusion Compared with the negative control group,the clinical pregnancy rates decrease in both ANA-positive low titer subgroup and high titer subgroup.However,clini-cal intervention therapy enhances the single-cycle clinical pregnancy and cumulative pregnancy rates among ANA-positive patients,indicating that ANA positivity is an important factor in RIF.Immunomodulatory therapy is an ef-fective measure to improve recurrent implantation failure among ANA-positive patients.

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.

Based on the literature study,the thoughts and possible therapeutic mechanism in treating male infertility from the perspective of spleen and kidney by regulating intestinal flora were explored.Disturbance of intestinal flora is one of the important factors leading to the development of male infertility,and the spleen and kidney have certain similarities to intestinal flora in the physiological function and pathological changes.Moreover,tonifying the kidney and strengthening the spleen can regulate the intestinal flora by fostering the growth of beneficial bacteria,inhibiting the reproduction of pathogenic bacteria,and protecting the barrier of the intestinal mucosa.Therefore,the possible therapeutic mechanisms in treating male infertility with the prescriptions for tonifying the kidney and strengthening the spleen to regulate intestinal flora are as follows:inhibiting the expression of inflammatory factors to reduce the inflammatory reaction of testicular tissues;improving the antioxidant capacity to alleviate the damage of spermatozoa caused by oxidative stress,and improving the bad mood to alleviate the impact of psychological stress on the reproductive system.The exploration of the thoughts for treating male infertility from the perspective of spleen and kidney by regulating intestinal flora may provide a new entry point for modern Chinese medicine clinical treatment of male infertility.

Near infrared spectroscopy(NIRS)technology combined with chemometrics algorithms has been widely used in quantitative and qualitative analysis of food and medicine.However,traditional chemometrics methods,especially linear classification methods,often yield unsatisfactory results when addressing multi-class classification problems.Convolutional neural network(CNN)is adept at extracting deep-level features from data and suitable for handling non-linear relationships.The modeling performance of CNN depends on the size and diversity of sample,while the collection and preprocessing of NIRS sample data is often time-consuming and labor-intensive.This study proposed a NIRS qualitative analysis method based on data augmentation strategies and CNN.The data augmentation strategy included two steps.Firstly,applying Bootstrap resampling and generative adversarial network(GAN)methods to augment three NIRS datasets(Medicine,coffee and grape).Secondly,combining the original samples(Y)with the Bootstrap augmented samples(B)and GAN augmented samples(G)to obtain three augmented datasets(Y-B,Y-G and Y-B-G).Based on this,a CNN model structure suitable for these datasets was designed,consisting of 2 one-dimensional convolutional layers,1 max-pooling layer,and 1 fully connected layer.The results showed that compared to the optimal models of partial least squares discriminant analysis(PLS-DA),support vector machine(SVM),and back propagation neural network(BP),the CNN model based on Y-B dataset achieved average accuracy improvements of 3.998%,9.364%,and 4.689%for medicine(Binary classification);the CNN model based on the Y-B-G dataset achieved average accuracy improvements of 6.001%,2.004%,and 7.523%for coffee(7-class classification);and the CNN model based on the Y-B dataset achieved average accuracy improvements of 33.408%,51.994%,and 34.378%for grapes(20-class classification).It was evident that the models established based on data augmentation strategies and CNN demonstrated better classification accuracy and generalization performance with different datasets and classification categories.