Differences in proteomic profiles and immunomodulatory activity of goat and cow milk fat globule membrane.

This study aimed to clarify the composition and bioactivity differences between goat and cow milk fat globule membrane (MFGM) protein by proteomic, and the immunomodulatory activity of MFGM proteins was further evaluated by using mouse splenic lymphocytes in vitro. A total of 257 MFGM proteins showed significant differences between goat and cow milk. The upregulated and unique MFGM proteins in goat milk were significantly enriched in the positive regulation of immune response, negative regulation of Interleukin-5 (IL-5) secretion, and involved in nucleotide-binding oligomerization domain (NOD)-like receptor signaling. The contents of IL-2 and Interferon-γ in the supernatant of spleen lymphocytes treated with goat MFGM proteins were much higher than those of IL-4 and IL-5, suggesting a Th1-skewed immune response. These results revealed that goat MFGM proteins could possess better immunomodulatory effects as compared to cow milk. Our findings may provide new insights to elucidate the physiological functions and nutritional of goat milk.

CD4+T and CD8+T Cells in Uterus Exhibit Both Selective Dysfunction and Residency Signatures.

Unlike T cells in other tissues, uterine T cells must balance strong immune defense against pathogens with tolerance to semiallogeneic fetus. Our previous study fully elucidated the characteristics of γδT cells in nonpregnant uterus and the mechanism modulated by estrogen. However, comprehensive knowledge of the immunological properties of αßT (including CD4+T cells and CD8+T) cells in nonpregnancy uterus has not been acquired. In this study, we fully compared the immunological properties of αßT cells between uterus and blood using mouse and human sample. It showed that most of CD4+T cells and CD8+T cells in murine uterus and human endometrium were tissue resident memory T cells which highly expressed tissue residence markers CD69 and/or CD103. In addition, both CD4+T cells and CD8+T cells in uterus highly expressed inhibitory molecular PD-1 and cytokine IFN-γ. Uterine CD4+T cells highly expressed IL-17 and modulated by transcription factor pSTAT3. Moreover, we compared the similarities and differences between human and murine uterine T cell phenotype. Together, uterine CD4+T cells and CD8+ cells exhibited a unique mixed signature of T cell dysfunction, activation, and effector function which enabled them to balance strong immune defense against pathogens with tolerance to fetus. Our study fully elucidated the unique immunologic properties of uterine CD4+T and CD8+T cells and provided a base for further investigation of functions.

The enhanced affinity of moderately hydrolyzed whey protein to EGCG promotes the isoelectric separation and unlocks the protective effects on polyphenols.

The instability and discoloration of (-)-epigallocatechin-3-gallate (EGCG) constrain its application in functional dairy products. Concurrently, challenges persist in the separation and utilization of whey in the dairy industry. By harnessing the interactions between polyphenols and whey proteins or their hydrolysates, this study proposed a method that involved limited enzymatic hydrolysis followed by the addition of EGCG and pH adjustment around the isoelectric point to obtain whey protein hydrolysates (WPH)-EGCG. Over 92 % of protein-EGCG complexes recovered from whey while ensuring the preservation of α-lactalbumin. The combination between EGCG and WPH depended on hydrogen bonding and hydrophobic interactions, significantly enhanced the thermal stability and storage stability of EGCG. Besides, the intestinal phase retention rate of EGCG in WPH-EGCG complex was significantly increased by 23.67 % compared to free EGCG. This work represents an exploratory endeavor in the improvement of EGCG stability and expanding the utilization approaches of whey.

Digestive properties and peptide profiles exhibited significant differences between skim camel milk and bovine milk powder after static in vitro simulated infant gastrointestinal digestion.

This study aims to analyze the differences in digestion properties and peptide profiles between the skim camel and bovine milk powder after static in vitro simulated infant gastrointestinal digestion. The hydrolysis degree of camel milk proteins exceeded by 13.18% that of bovine milk. The concentration and release rate of free amino groups in the camel milk digesta was higher than that of bovine milk powder, which was likely due to the higher ß-/αs-casein ratio and larger casein micelle size in camel milk. Camel milk powder presented higher ß-CN coverage and comparatively shorter bioactive peptides compared to bovine milk powder. The anti-inflammatory peptide KVLPVPQ displayed the highest abundance in camel milk powder. Outcomes of this study showed that camel milk proteins possessed superior digestibility and unique peptides, which outlined the potential nutritional implications of camel milk for infants.

TEPCAM: Prediction of T-cell receptor-epitope binding specificity via interpretable deep learning.

The recognition of T-cell receptor (TCR) on the surface of T cell to specific epitope presented by the major histocompatibility complex is the key to trigger the immune response. Identifying the binding rules of TCR-epitope pair is crucial for developing immunotherapies, including neoantigen vaccine and drugs. Accurate prediction of TCR-epitope binding specificity via deep learning remains challenging, especially in test cases which are unseen in the training set. Here, we propose TEPCAM (TCR-EPitope identification based on Cross-Attention and Multi-channel convolution), a deep learning model that incorporates self-attention, cross-attention mechanism, and multi-channel convolution to improve the generalizability and enhance the model interpretability. Experimental results demonstrate that our model outperformed several state-of-the-art models on two challenging tasks including a strictly split dataset and an external dataset. Furthermore, the model can learn some interaction patterns between TCR and epitope by extracting the interpretable matrix from cross-attention layer and mapping them to the three-dimensional structures. The source code and data are freely available at https://github.com/Chenjw99/TEPCAM.

Antihyperuricemic activity and inhibition mechanism of xanthine oxidase inhibitory peptides derived from whey protein by virtual screening.

Xanthine oxidase (XO), a rate-limiting enzyme in uric acid production, is the pivotal therapeutic target for gout and hyperuricemia. In this study, 57 peptides from α-lactalbumin and ß-lactoglobulin were obtained via virtual enzymatic hydrolysis, and 10 XO inhibitory peptides were virtually screened using molecular docking. Then toxicity, allergenicity, solubility, and isoelectric point of the obtained 10 novel peptides were evaluated by in silico tools. The XO activity of these synthetic peptides was tested using an in vitro assay by high-performance liquid chromatography. Their inhibitory mechanism was further explored by molecular docking. The results showed that 4 peptides GL, PM, AL, and AM exhibited higher inhibitory activity, and their half maximal inhibitory concentration in vitro was 10.20 ± 0.89, 23.82 ± 0.94, 34.49 ± 0.89, and 40.45 ± 0.92 mM, respectively. The peptides fitted well with XO through hydrogen bond, hydrophobic interaction, and van der Waals forces, and amino acid residues Glu802, Leu873, Arg880, and Pro1076 played an important role in this process. Overall, this study indicated 4 novel peptides GL, PM, AL, and AM from whey protein exhibited XO inhibitory activity, and they might be useful and safe XO inhibitors for hyperuricemia prevention and treatment.

Bovine milk osteopontin improved intestinal health of pregnant rats fed a high-fat diet through improving bile acid metabolism.

The main purpose of the current study was to investigate the ameliorative effects of bovine milk osteopontin (bmOPN) on the gut dysfunction of pregnant rats fed a high-fat diet (HFD). Bovine milk osteopontin was supplemented at a dose of 6 mg/kg body weight. Bovine milk osteopontin supplementation during pregnancy reduced colonic inflammation of HFD dams, and it also increased the colonic expression of ZO-1 and claudin-4 of HFD dams. Bovine milk osteopontin significantly enriched the relative abundance of Bacteroidetes, whereas it decreased Proteobacteria, Helicobacteraceae, and Desulfovibrionaceae in feces of HFD dams. The levels of isobutyric acid and pentanoic acid in the HFD + bmOPN group were higher than that of the HFD group. Functional predication analysis of microbial genomes revealed that bmOPN supplementation to HFD pregnancies changed 4 Kyoto Encyclopedia of Genes and Genomes pathways including bile acid biosynthesis. Further, bmOPN enriched hepatic taurochenodeoxycholic acid and tauroursodeoxycholic acid plus taurohyodeoxycholic acid in the gut of HFD maternal rats. Our findings suggested that bmOPN improved the gut health of HFD pregnant rats partially through modulating bile acid biosynthesis.

Polar lipid-enriched milk fat globule membrane supplementation in maternal high-fat diet promotes intestinal barrier function and modulates gut microbiota in male offspring.

Intestinal development plays a critical role in physiology and disease in early life and has long-term effects on the health status throughout the lifespan. Maternal high-fat diet (HFD) fuels the inflammatory reaction and metabolic syndrome, disrupts intestinal barrier function, and alters gut microbiota in offspring. The aim of this study was to evaluate whether polar lipid-enriched milk fat globule membrane (MFGM-PL) supplementation in maternal HFD could promote intestinal barrier function and modulate gut microbiota in male offspring. Obese female rats induced by HFD were supplemented with MFGM-PL during pregnancy and lactation. The offspring were fed HFD for 11 weeks after weaning. MFGM-PL supplementation to dams fed HFD decreased the body weight gain and ameliorated abnormalities of serum insulin, lipids, and inflammatory cytokines in offspring at weaning. Maternal MFGM-PL supplementation promoted the intestinal barrier by increasing the expression of Ki-67, lysozyme, mucin 2, zonula occludens-1, claudin-3, and occludin. Additionally, MFGM-PL supplementation to HFD dams improved gut dysbiosis in offspring. MFGM-PL increased the relative abundance of Akkermansiaceae, Ruminococcaceae, and Blautia. Concomitantly, maternal MFGM-PL treatment increased short-chain fatty acids of colonic contents and G-protein-coupled receptor (GPR) 41 and GPR 43 expressions in the colon of offspring. Importantly, the beneficial effects of maternal MFGM-PL intervention persisted to offspring's adulthood, as evidenced by increased relative abundance of norank_f_Muribaculaceae, Peptostreptococcaceae and Romboutsia and modulated the taxonomic diversity of gut microbiota in adult offspring. In summary, maternal MFGM-PL supplementation improved intestinal development in the offspring of dams fed with HFD, which exerted long-term beneficial effects on offspring intestinal health.

MATT-DDI: Predicting multi-type drug-drug interactions via heterogeneous attention mechanisms.

The joint use of multiple drugs can result in adverse drug-drug interactions (DDIs) and side effects that harm the body. Accurate identification of DDIs is crucial for avoiding accidental drug side effects and understanding potential mechanisms underlying DDIs. Several computational methods have been proposed for multi-type DDI prediction, but most rely on the similarity profiles of drugs as the drug feature vectors, which may result in information leakage and overoptimistic performance when predicting interactions between new drugs. To address this issue, we propose a novel method, MATT-DDI, for predicting multi-type DDIs based on the original feature vectors of drugs and multiple attention mechanisms. MATT-DDI consists of three main modules: the top k most similar drug pair selection module, heterogeneous attention mechanism module and multi­type DDI prediction module. Firstly, based on the feature vector of the input drug pair (IDP), k drug pairs that are most similar to the input drug pair from the training dataset are selected according to cosine similarity between drug pairs. Then, the vectors of k selected drug pairs are averaged to obtain a new drug pair (NDP). Next, IDP and NDP are fed into heterogeneous attention modules, including scaled dot product attention and bilinear attention, to extract latent feature vectors. Finally, these latent feature vectors are taken as input of the classification module to predict DDI types. We evaluated MATT-DDI on three different tasks. The experimental results show that MATT-DDI provides better or comparable performance compared to several state-of-the-art methods, and its feasibility is supported by case studies. MATT-DDI is a robust model for predicting multi-type DDIs with excellent performance and no information leakage.

Inhibitory Mechanism of Quercimeritrin as a Novel α-Glucosidase Selective Inhibitor.

In this study, 12 flavonoid glycosides were selected based on virtual screening and the literature, and Quercimeritrin was selected as the best selective inhibitor of α-glucosidase through in vitro enzyme activity inhibition experiments. Its IC50 value for α-glucosidase was 79.88 µM, and its IC50 value for α-amylase >250 µM. As such, it could be used as a new selective inhibitor of α-glucosidase. The selective inhibition mechanism of Quercimeritrin on the two starch-digesting enzymes was further explored, and it was confirmed that Quercimeritrin had a strong binding affinity for α-glucosidase and occupied the binding pocket of α-glucosidase through non-covalent binding. Subsequently, animal experiments demonstrated that Quercimeritrin can effectively control postprandial blood glucose in vivo, with the same inhibitory effect as acarbose but without side effects. Our results, therefore, provide insights into how flavone aglycones can be used to effectively control the rate of digestion to improve postprandial blood glucose levels.

Influence of Post-Heating Treatment on the Sensory and Textural Properties of Stirred Fermented Milk.

The purpose of this study was to investigate the post-heating induced changes in the textural and sensory characteristics of stirred fermented milk. The textural and rheological properties of post-heating fermented milk (55-85 °C, 25 s) with respect to viscoelastic behaviors, viscosity, textural parameters, etc., were monitored, and the friction behaviors and sensory attributes were assessed. Treatments below 65 °C/25 s increased the textural properties of fermented milk such as gel strength, firmness, and viscosity, due to the moderate aggregation and increased linkages of microgels. In this case, despite the size and amount their aggregates increased (~15-~21 µm), they exhibited similar frictional behaviors and sensory attributes. However, treatments above 65 °C/25 s degraded textural properties due to excessive aggregation (~46-~63 µm), accompanied by unacceptable grainy attributes, which could be characterized by their good correlations with tribological coefficients and particle size parameters. These findings could provide an understanding of the quality formation of post-heating fermented milk and a perspective to improve the textural defects of ambient fermented milk products.

A Self-attention Graph Convolutional Network for Precision Multi-tumor Early Diagnostics with DNA Methylation Data.

DNA methylation-based precision tumor early diagnostics is emerging as state-of-the-art technology that could capture early cancer signs 3 ~ 5 years in advance, even for clinically homogenous groups. Presently, the sensitivity of early detection for many tumors is ~ 30%, which needs significant improvement. Nevertheless, based on the genome-wide DNA methylation data, one could comprehensively characterize tumors' entire molecular genetic landscape and their subtle differences. Therefore, novel high-performance methods must be modeled by considering unbiased information using excessively available DNA methylation data. To fill this gap, we have designed a computational model involving a self-attention graph convolutional network and multi-class classification support vector machine to identify the 11 most common cancers using DNA methylation data. The self-attention graph convolutional network automatically learns key methylation sites in a data-driven way. Then, multi-tumor early diagnostics is realized by training a multi-class classification support vector machine based on the selected methylation sites. We evaluated our model's performance through several data sets of experiments, and our results demonstrate the effectiveness of the selected key methylation sites, which are highly relevant for blood diagnosis. The pipeline of the self-attention graph convolutional network based computational framework.

Tissue resident memory T cells are enriched and dysfunctional in effusion of patients with malignant tumor.

Purpose Most malignant effusion is secondary to metastases to the pleura or peritoneum and portend poor oncological outcomes. Malignant effusion has different tumor microenvironment from primary tumor, containing a variety of cytokines and immune cells and directly contacting with tumor cells. However, the characteristic of CD4+ T cells and CD8+ T cells in malignant effusion remains unclear. Methods Malignant effusion including peritoneal ascites and pleural fluid from thirty-five patients with malignant tumor were collected and compared with matched blood. A detailed characterization of CD4+ T cells and CD8+ T cells in malignant effusion were conducted using flow cytometry and multiple cytokines assay. Results The concentration of IL-6 in malignant effusion was significantly higher than in blood. A substantial portion of T cells in malignant effusion were CD69+ and/ or CD103+ Trm cells. Most CD4+T and CD8+T cells in malignant effusion were exhausted T cells which expressed lower levels of cytokines, cytotoxic molecules and markedly higher levels of inhibitory receptor PD-1 compared with in blood. Conclusion Our study is the first to identify the presence of Trm cells in malignant effusion and will lay the foundation for future research on anti-tumor immunity of Trm cells in malignant effusion.

Machine learning of flow cytometry data reveals the delayed innate immune responses correlate with the severity of COVID-19.

Introduction: The COVID-19 pandemic has posed a major burden on healthcare and economic systems across the globe for over 3 years. Even though vaccines are available, the pathogenesis is still unclear. Multiple studies have indicated heterogeneity of immune responses to SARS-CoV-2, and potentially distinct patient immune types that might be related to disease features. However, those conclusions are mainly inferred by comparing the differences of pathological features between moderate and severe patients, some immunological features may be subjectively overlooked. Methods: In this study, the relevance scores(RS), reflecting which features play a more critical role in the decision-making process, between immunological features and the COVID-19 severity are objectively calculated through neural network, where the input features include the immune cell counts and the activation marker concentrations of particular cell, and these quantified characteristic data are robustly generated by processing flow cytometry data sets containing the peripheral blood information of COVID-19 patients through PhenoGraph algorithm. Results: Specifically, the RS between immune cell counts and COVID-19 severity with time indicated that the innate immune responses in severe patients are delayed at the early stage, and the continuous decrease of classical monocytes in peripherial blood is significantly associated with the severity of disease. The RS between activation marker concentrations and COVID-19 severity suggested that the down-regulation of IFN-γ in classical monocytes, Treg, CD8 T cells, and the not down-regulation of IL_17a in classical monocytes, Tregs are highly correlated with the occurrence of severe disease. Finally, a concise dynamic model of immune responses in COVID-19 patients was generalized. Discussion: These results suggest that the delayed innate immune responses in the early stage, and the abnormal expression of IL-17a and IFN-γ in classical monocytes, Tregs, and CD8 T cells are primarily responsible for the severity of COVID-19.

Validation of nonalcoholic fatty liver disease (NAFLD) related steatosis indices in metabolic associated fatty liver disease (MAFLD) and comparison of the diagnostic accuracy between NAFLD and MAFLD.

BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is a new term of nonalcoholic fatty liver disease (NAFLD), with newly proposed diagnostic criteria. The applicability of common noninvasive testing for screening NAFLD is unclear for the detection of MAFLD and requires reevaluation. We aimed to validate the effectiveness of traditional NAFLD-related steatosis indices for diagnosing MAFLD and to determine the optimal cutoff values as well as compare their accuracy between NAFLD and MAFLD diagnosis. METHODS: This study enrolled 1866 participants from the National Health and Nutrition Examination Survey (NHANES) database (2017-2018). The diagnostic performances of fatty liver index (FLI), Framingham Steatosis Index (FSI), Zhejiang University index (ZJU), lipid accumulation product (LAP), hepatitis steatosis index (HSI) and visceral adiposity index (VAI) were evaluated using the area under the receiver operator characteristic (AUROC) curve and the optimal cutoff points were calculated according to maximum Youden's index. RESULTS: FLI had the highest AUROC (0.840) for predicting MAFLD in the whole population, with a cutoff value of 56.93. The AUROCs of FLI, FSI, ZJU, LAP, HSI and VAI for predicting MAFLD/NAFLD were 0.840/0.812, 0.833/0.811, 0.826/0.811, 0.826/0.799, 0.814/0.803 and 0.747/0.729, respectively. The AUROC values of all indices decreased in the subgroup of the population with overweight or diabetes. CONCLUSION: The NAFLD-related scores would be equally useful to screen MAFLD and seemed to be more compatible with MAFLD. The FLI was optimal in both MAFLD and NAFLD diagnoses. However, a new predictive indicator suitable for various characteristics of the population is worth further development in the future.

Limited hydrolysis as a strategy to improve the non-covalent interaction of epigallocatechin-3-gallate (EGCG) with whey protein isolate near the isoelectric point.

This study was aimed to investigate the interaction mechanisms and structural changes of whey protein isolate (WPI) and whey protein isolate hydrolysates (WPIHs) with epigallocatechin-3-gallate (EGCG) near the isoelectric point through multiple spectroscopic techniques and field emission scanning electron microscopy. Fluorescence spectra results indicated that limited hydrolysis endowed WPIHs with higher affinity for the EGCG but the increased degree of hydrolysis led to an opposite result. Thermodynamic analysis revealed that EGCG bound WPI primarily through hydrogen bonds and van der waals forces, while the hydrophobic force was the main driving force in the interaction of EGCG with WPIHs. Synchronous fluorescence and three-dimensional spectra confirmed that EGCG induced conformational alterations of WPI and WPIHs, which was further supported by Ultraviolet-Visible spectra. Raman spectra indicated that binding to EGCG resulted in changes in the microenvironment of tryptophan residues, CH bending vibration and the secondary structure arrangements of WPI and WPIHs. Furthermore, compared with a sheet-like structure of WPI-EGCG complexes, the morphology of WPIHs with limited hydrolysis presented an uneven blocky structure after complexing with EGCG. Our findings might be helpful to better understand the interactions of milk protein hydrolysates-EGCG and suggest the potential application of the formed complexes as bioactive ingredients in food industry.

Milk fat globule membrane supplementation to obese rats during pregnancy and lactation promotes neurodevelopment in offspring via modulating gut microbiota.

Pre-pregnancy obesity and high-fat diet (HFD) during pregnancy and lactation are associated with neurodevelopmental delay in offspring. This study aimed to investigate whether milk fat globule membrane (MFGM) supplementation in obese dams could promote neurodevelopment in offspring. Obese female rats induced by HFD were supplemented with MFGM during pregnancy and lactation. Maternal HFD exposure significantly delayed the maturation of neurological reflexes and inhibited neurogenesis in offspring, which were significantly recovered by maternal MFGM supplementation. Gut microbiota analysis revealed that MFGM supplementation modulated the diversity and composition of gut microbiota in offspring. The abundance of pro-inflammatory bacteria such as Escherichia shigella and Enterococcus were down-regulated, and the abundance of bacteria with anti-inflammatory and anti-obesity functions, such as Akkermansia and Lactobacillus were up-regulated. Furthermore, MFGM alleviated neuroinflammation by decreasing the levels of lipopolysaccharides (LPS) and pro-inflammatory cytokines in the circulation and brain, as well as inhibiting the activation of microglia. Spearman's correlation analysis suggested that there existed a correlation between gut microbiota and inflammation-related indexes. In conclusion, maternal MFGM supplementation promotes neurodevelopment partly via modulating gut microbiota in offspring.

Preparation and identification of anti-breast cancer cells peptides released from yak milk casein.

Yak milk casein (YMC) is the main protein in the yak milk. Peptides released from Yak milk casein (YMC) have multiple bioactivities, including anti-inflammation and immune-regulation, suggesting that these peptides might be able to inhibit cancer theoretically. However, the anti-cancer peptides from YMC have only been sparsely studied. Breast carcinoma is the most common carcinoma in women worldwide. Thus, the paper herein was to identify yak milk casein (YMC)-derived anti-breast cancer peptides via gel filtration, reversed phase high-performance liquid chromatography (RP-HPLC) and liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI MS/MS) for the first time. The inhibitory effects of the hydrolysates on the cell viabilities, cell cycles and apoptosis of breast cancer cells were evaluated with a cck8 kit and a flow cytometry. The result showed that YMC hydrolysates (YMCH) obtained by united hydrolyzation with trypsin (3 h) and alkaline protease (3 h) displayed the highest cell viability inhibition rate for MCF7 (20.74 ± 1.39%) and MDA-MB-231 (26.73 ± 2.87%) cells. Three peptides were identified in the RP-HPLC subfraction F3-4, and a nonapeptide (TPVVVPPFL) showed the most potent inhibitory effects on both cancer cells and displayed good gastrointestinal stability. TPVVVPPFL could induce G2-M cell cycle arrest in MCF7 cells and S cell arrest in MDA-MB-231 cells and induce apoptosis in both cancer cells. Moreover, in silico analysis indicated that the peptide had non-toxic and no inhibitory roles on P4502D6-enzyme. Together, this study shows that YMC is a good source of anti-breast cancer cells peptides.

Conditioned medium from the bone marrow mesenchymal stem cells modulates immune response via signal transduction and activator of transcription 6 signaling pathway in an allergic rhinitis mouse model.

BACKGROUND: Allergic rhinitis (AR) is a common immune disease of the nasal mucosa characterized with immunoglobulin E (IgE)-mediated allergic inflammation after exposure to allergens in susceptible population. Previous reports have demonstrated that the bone marrow mesenchymal stem cells (BMSCs) could reduce allergic inflammation. However, there is little knowledge about whether the culture supernatant of BMSCs (conditioned medium, CM) has similar anti- inflammatory potential in treating AR. OBJECTIVE: The study aimed to evaluate the immunoregulatory effects of conditioned medium derived from BMSCs (BMSC-CM) on allergic inflammation in an AR mouse model. MATERIAL AND METHODS: The AR murine model was induced by repeated sensitization and challenges with ovalbumin (OVA). Subsequently the allergic symptoms of AR mice, cytokine levels, the histopathological features of the nasal mucosa and T helper 1 (Th1) : T helper 2 (Th2) cells ratio were evaluated. RESULTS: Treatment with BMSC-CM was found as effective as BMSCs in reducing allergic symptoms and inhibiting eosinophilic infiltration in the nasal mucosa. After BMSC-CM or BMSCs administration, the OVA-specific IgE and interleukin 4 levels in serum decreased and interferon gamma level increased compared with AR mice treated with uncultured fresh medium. Flow cytometry analysis revealed a decrease in Th1:Th2 cells ratio after OVA-sensitization and the ratio was reversed by BMSC-CM and BMSCs treatments. Furthermore, the data revealed that BMSC-CM suppressed the production of signal transduction and activator of transcription 6 (STAT6) at messenger RNA and protein levels in the nasal mucosa. CONCLUSION: BMSC-CM could ameliorate allergic inflammation and regulate the balance of Th cells, and the underlying mechanism was closely related to STAT6 signaling pathway. The immunoregulatory effects of BMSCs could be achieved through paracrine function, and nasal dripping of BMSC-CM might be a novel approach for the treatment of AR.

Bovine α-lactalbumin-derived peptides attenuate TNF-α-induced insulin resistance and inflammation in 3T3-L1 adipocytes through inhibiting JNK and NF-κB signaling.

Bioactive peptides in bovine α-lactalbumin were isolated and identified, and the effects and mechanisms of peptide KILDK on insulin resistance in 3T3-L1 adipocytes were investigated. Mature 3T3-L1 adipocytes were stimulated with TNF-α to induce insulin resistance. Bovine α-lactalbumin hydrolysates (α-LAH) were subjected to stimulated gastrointestinal digestion and Caco-2 absorption, and GD-α-LAH and CA-α-LAH were obtained. Our results demonstrated that α-LAH, GD-α-LAH, and CA-α-LAH increased glucose uptake, enhanced Akt phosphorylation (Ser473), and decreased IRS-1 phosphorylation (Ser307) in insulin resistant 3T3-L1 adipocytes. Gel filtration chromatography and liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI MS/MS) were used to separate and identify bioactive peptides. The identified peptide KILDK attenuated insulin resistance in 3T3-L1 adipocytes, which was attributed to the suppression of JNK phosphorylation (Thr183/Tyr185). Moreover, KILDK downregulated pro-inflammatory genes through blocking NF-κB signaling. Our findings suggested that bovine α-LAH might be a potential ingredient against insulin resistance.