Food-derived bioactive peptides (FBPs), particularly those with ten or fewer amino acid residues and a molecular weight below 1300 Da, have gained increasing attention for their safe, diverse structures and specific biological activities. The development of FBP-based functional foods and potential medications depends on understanding their structure‒activity relationships (SARs), stability, and bioavailability properties. In this review, we provide an in-depth overview of the roles of FBPs in treating various diseases, including Alzheimer's disease, hypertension, type 2 diabetes mellitus, liver diseases, and inflammatory bowel diseases, based on the literature from July 2017 to Mar. 2023. Subsequently, attention is directed toward elucidating the associations between the bioactivities and structural characteristics (e.g., molecular weight and the presence of specific amino acids within sequences and compositions) of FBPs. We also discuss in silico approaches for FBP screening and their limitations. Finally, we summarize recent advancements in formulation techniques to improve the bioavailability of FBPs in the food industry, thereby contributing to healthcare applications.
Humans ; Peptides/therapeutic use* ; Structure-Activity Relationship ; Functional Food ; Diabetes Mellitus, Type 2/drug therapy* ; Biological Availability ; Alzheimer Disease/drug therapy* ; Inflammatory Bowel Diseases/drug therapy* ; Hypertension/drug therapy* ; Liver Diseases/drug therapy* ; Bioactive Peptides, Dietary

Objective To investigate the interaction between a novel antimicrobial compound,HL-J6,and penicillin-binding protein 1(PBP1)of Staphylococcus aureus.Methods With MRSA252 genomic DNA as the template and PBP1F and PBP1R as primers,the expression plasmid pET30a-pbp1-39-608 was constructed by amplifying the target gene fragment followed by cloning into the Nde I/Xho I restriction sites of the pET30a vector.Then the obtained plasmids were transformed into Escherichia coli for the expression of PBP1-39-608 protein,and the product was purified by affinity chromatography.The inhibitory effect of HL-J6 on the transpeptidase activity of PBP1-39-608 was measured using peptidoglycan side chain backbone peptide,with thiol ester analog S2d as the substrate.The affinity between HL-J6 and PBP1-39-608 was detected using microscale thermophoresis(MST),and the binding interaction was confirmed by cellular thermal shift assay(CETSA).Molecular docking and dynamics simulation were performed using AutoDock Vina and Desmond software,respectively,to elucidate the binding mode of HL-J6 with the PBP1-39-608 protein and the key amino acid residues involved.Results The recombinant plasmid pET30a-pbp1-39-608 was successfully constructed,and PBP1-39-608 protein was produced after induction and purified,yielding a protein with an approximate molecular mass of 65×103.HL-J6 inhibited the transpeptidase activity of PBP1-39-608 in a time-dependent manner(P<0.001).The dissociation constant Kd of the binding between HL-J6 and PBP1-39-608 was 64.92 μmol/L.Molecular docking results showed that HL-J6 bound to the active pocket of PBP1-39-608 by interacting with key residues such as ILE-348,ASN-370,THR-516 and PHE-423,with a binding score of-8.38 kcal/mol(<-5.00 kcal/mol).Dynamics simulation results indicated that the complex became stable after 50 ns.Conclusion HL-J6 effectively inhibits the transpeptidase activity of Staphylococcus aureus PBP1,and shows stable interaction with the protein.

Objective: To construct a Family with sequence similarity 50 member A(FAM50A) gene knockout mouse insulinoma pancreatic β-cell line Beta-TC-6 using CRISPR/Cas9 gene editing technology and to prepare polyclonal antibodies specifically recognizing FAM50A. Methods: Two guide RNAs(sgRNAs) targeting the FAM50A gene were designed,and a recombinant plasmid expressing blue fluorescent protein(BFP) was constructed for gene knockout.The successfully constructed plasmid was transfected into Beta-TC-6 cells,and BFP-positive single cells were isolated for clonal expansion.The expanded monoclonal cell lines were genotyped by Sanger sequencing,and FAM50A protein expression was assessed by Western blot.Purified human recombinant FAM50A protein was used to immunize New Zealand rabbits for the preparation of a polyclonal antibody.The specificity of the prepared antibody was then validated using the successfully established FAM50A knockout cell line. Results: A monoclonal cell line with a successful knockout of the FAM50A gene was identified.Sanger sequencing confirmed base deletions at the target site.Western blot analysis showed a complete absence of FAM50A protein expression in this cell line.The prepared polyclonal antibody successfully recognized endogenous murine FAM50A protein in wild-type Beta-TC-6 cells and in hTERT-RPE1 cells overexpressing human FAM50A-GFP fusion protein,while no signal was detected in the FAM50A knockout cells. Conclusion This study successfully established a FAM50A gene knockout Beta-TC-6 cell model and generated a FAM50A polyclonal antibody,providing powerful tools for future research.

Objective:To investigate the correlation between immune function and age-related pulmonary fibrosis, as well as the potential impact of bacterial lysates on this condition.Methods:Twenty-four healthy male C57BL/6 mice, aged 24, were randomly divided into three groups: a control group(Group N), a pulmonary fibrosis group(Group M), and a pulmonary fibrosis+ bacterial lysis product intervention group(Group P). Mice in Groups M and P were intratracheally injected with bleomycin(5 mg/kg)to induce a mouse pulmonary fibrosis model, while mice in Group N were injected with saline.After modeling, mice in Group P were orally administered 0.4 ml of a bacterial lysis product once a day.After 28 days, lung tissue and blood samples were collected for analysis.Pathological changes in lung tissue were assessed using hematoxylin and tosin staining(HE)and Masson staining and the Ashcroft score.The expression of CD4+ and CD8+ in lung tissue was evaluated using immunohistochemistry.The levels of serum interferon-γ(INF-γ), interleukin-3(IL-13), and immunoglobulin A(IgA)protein were measured using Enzyme-linked Immuno Sorbent Assay(ELISA). The levels of INF-γ and IL-13 mRNA in lung tissue were determined using Real-Time Quantitative Transcription PCR(RT-qPCR). Additionally, the protein expression levels of matrix metalloprotein-9(MMP-9)and tissue inhibitor of metalloproteincise 1(TIMP-1)in lung tissue were assessed using blot analysis.Results:The degree of lung fibrosis was significantly reduced in mice in group P compared with group M when treated with bacterial lysis products.Group M showed a significant decrease in the expression of CD4+ T cells and an increase in the expression of CD8+ T cells( P<0.05)compared to group N. Additionally, the content of IgA was decreased( P<0.05)in group M. On the other hand, group P showed a significant increase in the expression of CD4+ T cells and a decrease in the expression of CD8+ T cells( P<0.05)compared to group M. Furthermore, the content of IgA was elevated( P<0.05)in group P. After bacterial lysis product intervention, mRNA and protein expression levels of IFN-γ were elevated( P<0.05), while mRNA and protein expression levels of IL-13 were reduced( P<0.05). Moreover, protein expression of MMP-9 and TIMP-1 was significantly up-regulated in group M compared with group N( P<0.05), and decreased after bacterial lysis product intervention( P<0.05). Conclusions:It is well-known that immune mechanisms play a crucial role in the development of pulmonary fibrosis.The use of bacterial lysates has been found to effectively regulate immune balance and mitigate the severity of pulmonary fibrosis in elderly mice.

BackgroundThe occurrence rate of dangerous behaviors in patients with severe mental disorders is higher than that of the general population. In China， there is limited research on the prediction of dangerous behaviors in community-dwelling patients with severe mental disorders， particularly in terms of predicting models using data mining techniques other than traditional methods. ObjectiveTo explore the influencing factors of dangerous behaviors in community-dwelling patients with severe mental disorders and testing whether the classification decision tree model is superior to the Logistic regression model. MethodsA total of 11 484 community-dwelling patients with severe mental disorders who had complete follow-up records from 2013 to 2022 were selected on December 2023. The data were divided into a training set （n=9 186） and a testing set （n=2 298） in an 8∶2 ratio. Logistic regression and classification decision trees were separately used to establish predictive models in the training set. Model discrimination and calibration were evaluated in the testing set. ResultsDuring the follow-up period， 1 115 cases （9.71%） exhibited dangerous behaviors. Logistic regression results showed that urban residence， poverty， guardianship， intellectual disability， history of dangerous behaviors， impaired insight and positive symptoms were risk factors for dangerous behaviors （OR=1.778， 1.459， 2.719， 1.483， 3.890， 1.423， 2.528， 2.124， P<0.01）. Being aged ≥60 years， educated， not requiring prescribed medication and having normal social functioning were protective factors for dangerous behaviors （OR=0.594， 0.824， 0.422， 0.719， P<0.05 or 0.01）. The predictive effect in the testing set showed an area under curve （AUC） of 0.729 （95% CI： 0.692~0.766）， accuracy of 70.97%， sensitivity of 59.71%， and specificity of 72.05%. The classification decision tree results showed that past dangerous situations， positive symptoms， overall social functioning score， economic status， insight， household registration， disability status and age were the influencing factors for dangerous behaviors. The predictive effect in the testing set showed an AUC of 0.721 （95% CI： 0.705~0.737）， accuracy of 68.28%， sensitivity of 64.46%， and specificity of 68.60%. ConclusionThe classification decision tree does not have a greater advantage over the logistic regression model in predicting the risk of dangerous behaviors in patients with severe mental disorders in the community. ［Funded by Chengdu Medical Research Project （number， 2020052）］

Objective:To study the role of special microbial communities in the development of periodontitis in type 2 diabetes melli-tus(T2DM)patients.Methods:40 subjects aged 20-70 years were included and divided into 3 groups:moderate to severe periodon-titis with T2DM(SP.T2DM,n=15),moderate to severe periodontitis group(SP,n=15)and normal healthy group(N,n=10).The basic information,periodontal clinical indicators and blood sugar of the subjects were recorded.Subgingival plaque samples were col-lected,DNA samples of the plaque were extracted,and sequenced by Illumina NovaSeq6000 platform.The microbial diversity,eco-logical characteristics and functions of the plaque were analyzed by Uparse,SPSS and other softwares.Results:481 species in 22 phyla,30 classes,73 orders,129 families and 265 genera were obtained from the samples.Beta polymorphism analysis showed that the species composition of CP.T2DM group and CP group was similar.Alpha polymorphism analysis showed that the species richness and evenness in CP.T2DM group and CP group were higher than those in N group(P＜0.01).Venn diagram analysis showed that the species richness of the plaque in CP.T2DM group was the highest,followed by CP group and the lowest in N group.At the genus lev-el,Klebsiella and Bifidobacterium in CP.T2DM group were larger than those in CP group and N group(P＜0.05),and between group CP and N,P＞0.05.At the species level,the Capnocytophaga leadbetteri in CP.T2DM group was higher than that in CP group and N group(P＜0.05),between group CP and N,P＞0.05;There were some differences in the microbial community structure of subgingival plaque among the 3 groups.The species richness of subgingival flora in patients with CP and T2DM was higher than that in patients with CP and healthy people.Conclusion:The increase of Klebsiella,Bifidobacterium and Capnocytophaga leadbetter in subgingival flora of patients with moderate and severe periodontitis may be related to the development of T2DM.

Aim To investigate the relationship between fibrinogen(FIB)and the progression of coronary plaque stenosis rate in patients with type 2 diabetes mellitus(T2DM).Methods Hospitalized T2DM patients who underwent two or more coronary CT angiography(CCTA)examinations in the First Affiliated Hospital of Xi'an Jiaotong U-niversity from January 2015 to December 2020 were included.The subjects were divided into high FIB and low FIB groups according to the median of FIB.The differences in the progression of coronary plaque stenosis rate and other clini-cal characteristics were compared between the two groups,and the relationship between FIB level and the progression of coronary plaque stenosis rate was analyzed by Spearman's correlation analysis and Logistic regression.Results A total of 145 patients were included,73 in the high FIB group and 72 in the low FIB group at baseline,with a median follow-up time of 25(18,40)months between CCTA.The age,proportion of women,and the progression of coronary plaque ste-nosis rate were higher in the high FIB group than those in the low FIB group,and the differences were statistically signifi-cant(P＜0.05).FIB level was positively correlated with the change in coronary plaque stenosis rate(r2=0.308,P＜0.001).Multivariate Logistic regression analysis showed that FIB level was a risk factor for the progression of coronary plaque stenosis rate in patients with T2DM(OR=5.25,95％CI:1.97～14.02,P＜0.001),after adjusting for age,sex and other clinical risk factors.Conclusion High baseline FIB level is an independent risk factor for the progression of coronary plaque stenosis rate in patients with T2DM,and monitoring FIB level is beneficial to cardiovascular risk stratifica-tion in patients with T2DM.

Objective To construct a model for predicting recidivism in violence in community-based schizophrenia spectrum disorder patients(SSDP)by adopting a joint modeling method.Methods Based on the basic data on severe mental illness in Southwest China between January 2017 and June 2018,4565 community-based SSDP with baseline violent behaviors were selected as the research subjects.We used a growth mixture model(GMM)to identify patterns of medication adherence and social functioning.We then fitted the joint model using a zero-inflated negative binomial regression model and compared it with traditional static models.Finally,we used a 10-fold training-test cross validation framework to evaluate the models'fitting and predictive performance.Results A total of 157 patients(3.44%)experienced recidivism in violence.Medication compliance and social functioning were fitted into four patterns.In the counting model,age,marital status,educational attainment,economic status,historical types of violence,and medication compliance patterns were predictive factors for the frequency of recidivism of violence(P＜0.05).In the zero-inflated model,age,adverse drug reactions,historical types of violence,medication compliance patterns,and social functioning patterns were predictive factors for the recidivism in violence(P＜0.05).For the joint model,the average value of Akaike information criterion(AIC)for the train set was 776.5±9.4,the average value of root mean squared error(RMSE)for the testing set was 0.168±0.013,and the average value of mean absolute error(MAE)for the testing set was 0.131±0.018,which were all lower than those of the traditional static models.Conclusion Joint modeling is an effective statistical strategy for identifying and processing dynamic variables,exhibiting better predictive performance than that of the traditional static models.It can provide new ideas for promoting the construction of comprehensive intervention systems.

Chinese medicine self-assembly nano-strategies（CSAN） is to utilize the self-assembly property of Chinese medicine components， so that the Chinese medicine components can self-assemble to form structurally stable nano-preparations through non-covalent interactions. The formation of Chinese medicine self-assembly nano-preparations is often a synergistic result of a variety of non-covalent interactions， and many Chinese medicine monomers are susceptible to self-assembly due to their structural characteristics， and the phenomenon of self-assembly of Chinese medicine is also common in the decoction of single or compound Chinese medicine， which has attracted the attention of researchers. It is found that CSAN can improve the solubility and bioavailability of active components in Chinese medicine， which is of positive significance for the development and application of insoluble components of Chinese medicine. The self-assembly phenomenon of Chinese medicine decoction is closely related to the therapeutic efficacy， and the study of self-assembly phenomenon of Chinese medicine will bring a new perspective for the explanation of the mechanism of Chinese medicine decoction. At the same time， traditional Chinese medicine（TCM） has unique advantages in the field of anti-tumor. The application of CSAN in the field of oncology can not only exert the anti-tumor effect of the active components of Chinese medicine directly， but also act as a natural nano-carrier to carry chemotherapy drugs for combination chemotherapy， improve the targeting of drugs， enhance the anti-tumor efficacy， and reduce the side effects of chemotherapy， which has excellent anti-tumor potential. The preparation method of Chinese medicine self-assembly nano-preparations is simple， low cost， and has better safety than traditional nano-preparations， which is conducive to the promotion of the clinical transformation of nano-preparations， and also helps to provide new strategies and perspectives for promoting the modernization of TCM. Therefore， based on a large number of researches in this field in recent years， this paper reviewed the formation mechanism， different assembly forms， formation conditions and stability of Chinese medicine self-assembly nano-preparations by searching databases such as China national knowledge infrastructure（CNKI）， PubMed， WanFang data and VIP， and summarized the application of CSAN in different tumor therapies， providing a reference for further research on CSAN.

Extended circulation of anticancer nanodrugs in blood stream is essential for their clinical applications. However, administered nanoparticles are rapidly sequestered and cleared by cells of the mononuclear phagocyte system (MPS). In this study, we developed a biomimetic nanosystem that is able to efficiently escape MPS and target tumor tissues. The fabricated nanoparticles (TM-CQ/NPs) were coated with fibroblast cell membrane expressing tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL). Coating with this functionalized membrane reduced the endocytosis of nanoparticles by macrophages, but increased the nanoparticle uptake in tumor cells. Importantly, this membrane coating specifically induced tumor cell apoptosis via the interaction of TRAIL and its cognate death receptors. Meanwhile, the encapsulated chloroquine (CQ) further suppressed the uptake of nanoparticles by macrophages, and synergized with TRAIL to induce tumor cell apoptosis. The vigorous antitumor efficacy in two mice tumor models confirmed our nanosystem was an effective approach to address the MPS challenge for cancer therapy. Together, our TM-CQ/NPs nanosystem provides a feasible approach to precisely target tumor tissues and improve anticancer efficacy.