Novel ethylenediamine-ß-cyclodextrin grafted membranes for the chiral separation of mandelic acid and its derivatives.

In the present study, flat cellulose acetate ultrafiltration membranes were prepared first by nonsolvent induced phase separation method. Then chiral membranes for separating the enantiomers were prepared by grafting the ultrafiltration membranes using ethylenediamine-ß-cyclodextrin as the chiral selector and epichlorohydrin as the spacer arm. The pure water permeability of the ultrafiltration membrane was around 115 L·m-2·h-1·bar-1. The properties of the chiral membranes were characterized using infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). The chiral membrane performance in enantiomer separation was evaluated with racemates, such as mandelic acid (MA), 2-chloromandelic acid (2-ClMA), 4-chloromandelic acid (4-ClMA), and methyl mandelate (MM). The influence of feed concentration on the separation efficiency was also investigated. The results indicated that the enantiomeric excess percentages (e.e%) of the racemic mixtures for these four chiral compounds were up to 31.8%, 25.4%, 17.8%, and 32.6%, respectively. The binding free energy of the chiral selector with the (S)-enantiomer calculated by molecular dynamics simulations was stronger than that with the (R)-enantiomer, which was consistent with the experimental results (higher concentration of (R)-enantiomer in the permeate). This supports the affinity absorption-separation mechanism.

Reaction Process of Solid Waste Composite-Based Cementitious Materials for Immobilizing and Characterizing Heavy Metals in Lead and Zinc Tailings: Based on XRD, SEM-EDS and Compressive Strength Characterization.

This study investigates the synergistic effect and mechanism of gelling materials with blast furnace slag (BFS), steel slag (SS) and desulphurization gypsum (DG) as the main components on the hardening of heavy metal ions by lead and zinc tailings. It is found that lead and zinc tailing (LZT) is mainly composed of dolomite and quartz and contain small amounts of calcium, aluminum, iron, magnesium and other elements as well as heavy metals such as lead and zinc. By the mechanical activation method, it is found that the lead and zinc tailings powder has the largest specific surface area and the highest activity index when the ball milling time is 2 h. At a hardening timepoint of 28 d, the calcite crystals in the samples are intertwined with the amorphous C-S-H gel (C-S-H gels are mainly composed of 3CaO∙SiO2 and 2CaO∙SiO2), which enhances the structural strength of the samples. The chemical reaction analysis confirmed that the formation of calcite is a major driver for the hydration reaction of the steel slag-desulphurization gypsum (SSSDG) system. Overall, the slag, steel slag and desulphurization gypsum solid waste-based gelling materials have synergistic effects in hardening heavy metals by limiting the leaching of metal ions, adsorbing metal ions and hardening heavy metals, and facilitating the hydration process through the formation of compound salt precipitates.

Substitutions of physical activity and sedentary behavior with negative emotions and sex difference among college students.

BACKGROUND: A growing number of studies have found that physical activity (PA) benefits mental health, and sedentary behavior (SB) increases the risk of psychological symptoms, but it remains unclear whether substituting the duration of different activities may affect the association, and whether sex difference exists among college students. METHODS: A longitudinal survey was conducted in three colleges in Anhui province, China. A total of 8049 participants validly answered the questionnaire, which included demographic variables, PA, SB and negative emotions (depressive, anxiety, and stress symptoms). RESULTS: Substituting 30 min per day of SB with equivalent walking was associated with lower scores of depressive symptoms. Stress symptoms were reduced when SB was substituted by moderate intensity PA (MPA) and walking. Substituting 30 min per day of MPA in place of walking and SB was associated with an amelioration of depressive and stress symptoms in females, and a reallocation of 30 min walking was associated with lower depressive and stress symptom scores when SB was replaced in males. CONCLUSIONS: Replacing SB with walking and MPA ameliorates the depressive and stress symptoms in young adults. The results suggest a reallocation of time from SB or walking to MPA in females while from SB to walking in males may markedly reduce the depressive and stress symptoms in college population.

Engineered Bacterial Biomimetic Vesicles Reprogram Tumor-Associated Macrophages and Remodel Tumor Microenvironment to Promote Innate and Adaptive Antitumor Immune Responses.

Tumor-associated macrophages (TAMs) are among the most abundant infiltrating leukocytes in the tumor microenvironment (TME). Reprogramming TAMs from protumor M2 to antitumor M1 phenotype is a promising strategy for remodeling the TME and promoting antitumor immunity; however, the development of an efficient strategy remains challenging. Here, a genetically modified bacterial biomimetic vesicle (BBV) with IFN-γ exposed on the surface in a nanoassembling membrane pore structure was constructed. The engineered IFN-γ BBV featured a nanoscale structure of protein and lipid vesicle, the existence of rich pattern-associated molecular patterns (PAMPs), and the costimulation of introduced IFN-γ molecules. In vitro, IFN-γ BBV reprogrammed M2 macrophages to M1, possibly through NF-κB and JAK-STAT signaling pathways, releasing nitric oxide (NO) and inflammatory cytokines IL-1ß, IL-6, and TNF-α and increasing the expression of IL-12 and iNOS. In tumor-bearing mice, IFN-γ BBV demonstrated a targeted enrichment in tumors and successfully reprogrammed TAMs into the M1 phenotype; notably, the response of antigen-specific cytotoxic T lymphocyte (CTL) in TME was promoted while the immunosuppressive myeloid-derived suppressor cell (MDSC) was suppressed. The tumor growth was found to be significantly inhibited in both a TC-1 tumor and a CT26 tumor. It was indicated that the antitumor effects of IFN-γ BBV were macrophage-dependent. Further, the modulation of TME by IFN-γ BBV produced synergistic effects against tumor growth and metastasis with an immune checkpoint inhibitor in an orthotopic 4T1 breast cancer model which was insensitive to anti-PD-1 mAb alone. In conclusion, IFN-γ-modified BBV demonstrated a strong capability of efficiently targeting tumor and tuning a cold tumor hot through reprogramming TAMs, providing a potent approach for tumor immunotherapy.

De-Epithelialized Viable Tracheal Allotransplantation Without Immunosuppressants: 5-Year Follow-Up.

OBJECTIVE: Tracheal transplantation could be a better option for patients with long segmental laryngotracheal stenosis or defects, but the need for immunosuppressants limits its widespread use due to the antigenicity of the tracheal epithelium. Chemically treated or cryopreserved nonviable tracheal allografts have no immunogenicity but lead to necrosis and stenosis in long-term outcomes. The present report describes the 5-year outcomes of de-epithelialized viable tracheal allotransplantation without immunosuppressants in a patient with severe laryngotracheal stenosis. METHODS: The recipient was a 47-year-old female with relapsing polychondritis affecting the larynx and cervical trachea and producing a 5 cm long stenosis that could not be repaired using resection and anastomosis. A tracheal allograft was obtained from a 45-year-old male donor and treated with a combination of 3% sodium dodecyl sulfate (SDS) and organ preservation solution for 138 hours. The allograft was revascularized by heterotopical implantation in the infrahyoid muscles of the recipient for 3 months and then transplantation to the laryngotracheal defect with a split-thickness skin graft sutured to the lumen and a silicon T-tube. No immunosuppressants were used postoperatively. RESULTS: The allograft was de-epithelialized, and most of the cartilage rings remained viable after the treatment. The allograft was revascularized, viable, and mechanically stable after 3 months of heterotopic implantation. No apparent signs of rejection or destruction were observed. The T-tube was removed, and the internal lining of the allograft was repopulated 4 months after orthotopic transplantation, despite the skin graft necrotizing at 2 weeks. Endoscopy and computed tomography showed a patent airway 5 years after orthotopic transplantation. The patient was able to resume her usual quality of life. CONCLUSION: The present study demonstrates that transplantation of the de-epithelialized viable tracheal allograft without immunosuppressants is safe and promising for patients with long laryngotracheal stenosis or defects, especially for those with malignant tumor resections.

Physical properties, phenolic profile and antioxidant capacity of Java tea (Clerodendranthus spicatus) stems as affected by steam explosion treatment.

Java tea (Clerodendranthus spicatus) has been favored for its various health benefits and abundance of phenolic substances. Steam explosion (SE) treatment was performed in the pretreatment of Java tea stems and the physical properties, phenolic profile and antioxidant capacity were investigated. Extraction kinetics study showed that the phenolics yields of Java tea stems treated at 2.4 MPa for 10 min reached the maximum in 40 min, which was approximately 3 times the yields of raw stems in 180 min. The antioxidant activities of the extracts of Java tea stems were also significantly increased after SE treatment (P < 0.05). In addition, 19 phenolics were detected in Java tea stems by HPLC/QTOF-MS/MS, and rosmarinic acid was found to be hydrolyzed to danshensu during the SE process. SE could be an efficient pretreatment technology to improve the extraction rates of phenolics and conversions of their high-value hydrolyzed products, which could facilitate further research of Java tea products.

Role of polygenic risk scores in the association between chronotype and health risk behaviors.

BACKGROUND: This study explores the association between chronotypes and adolescent health risk behaviors (HRBs) by testing how genetic background moderates these associations and clarifies the influence of chronotypes and polygenic risk score (PRS) on adolescent HRBs. METHODS: Using VOS-viewer software to select the corresponding data, this study used knowledge domain mapping to identify and develop the research direction with respect to adolescent risk factor type. Next, DNA samples from 264 students were collected for low-depth whole-genome sequencing. The sequencing detected HRB risk loci, 49 single nucleotide polymorphisms based to significant SNP. Subsequently, PRSs were assessed and divided into low, moderate, and high genetic risk according to the tertiles and chronotypes and interaction models were constructed to evaluate the association of interaction effect and clustering of adolescent HRBs. The chronotypes and the association between CLOCK-PRS and HRBs were examined to explore the association between chronotypes and mental health and circadian CLOCK-PRS and HRBs. RESULTS: Four prominent areas were displayed by clustering information fields in network and density visualization modes in VOS-viewer. The total score of evening chronotypes correlated with high-level clustering of HRBs in adolescents, co-occurrence, and mental health, and the difference was statistically significant. After controlling covariates, the results remained consistent. Three-way interactions between chronotype, age, and mental health were observed, and the differences were statistically significant. CLOCK-PRS was constructed to identify genetic susceptibility to the clustering of HRBs. The interaction of evening chronotypes and high genetic risk CLOCK-PRS was positively correlated with high-level clustering of HRBs and HRB co-occurrence in adolescents, and the difference was statistically significant. The interaction between the sub-dimensions of evening chronotypes and the high genetic CLOCK-PRS risk correlated with the outcome of the clustering of HRBs and HRB co-occurrence. CONCLUSIONS: The interaction of PRS and chronotype and the HRBs in adolescents appear to have an association, and the three-way interaction between the CLOCK-PRS, chronotype, and mental health plays important roles for HRBs in adolescents.

X3DFast model for classifying dairy cow behaviors based on a two-pathway architecture.

Behavior is one of the important factors reflecting the health status of dairy cows, and when dairy cows encounter health problems, they exhibit different behavioral characteristics. Therefore, identifying dairy cow behavior not only helps in assessing their physiological health and disease treatment but also improves cow welfare, which is very important for the development of animal husbandry. The method of relying on human eyes to observe the behavior of dairy cows has problems such as high labor costs, high labor intensity, and high fatigue rates. Therefore, it is necessary to explore more effective technical means to identify cow behaviors more quickly and accurately and improve the intelligence level of dairy cow farming. Automatic recognition of dairy cow behavior has become a key technology for diagnosing dairy cow diseases, improving farm economic benefits and reducing animal elimination rates. Recently, deep learning for automated dairy cow behavior identification has become a research focus. However, in complex farming environments, dairy cow behaviors are characterized by multiscale features due to large scenes and long data collection distances. Traditional behavior recognition models cannot accurately recognize similar behavior features of dairy cows, such as those with similar visual characteristics, i.e., standing and walking. The behavior recognition method based on 3D convolution solves the problem of small visual feature differences in behavior recognition. However, due to the large number of model parameters, long inference time, and simple data background, it cannot meet the demand for real-time recognition of dairy cow behaviors in complex breeding environments. To address this, we developed an effective yet lightweight model for fast and accurate dairy cow behavior feature learning from video data. We focused on four common behaviors: standing, walking, lying, and mounting. We recorded videos of dairy cow behaviors at a dairy farm containing over one hundred cows using surveillance cameras. A robust model was built using a complex background dataset. We proposed a two-pathway X3DFast model based on spatiotemporal behavior features. The X3D and fast pathways were laterally connected to integrate spatial and temporal features. The X3D pathway extracted spatial features. The fast pathway with R(2 + 1)D convolution decomposed spatiotemporal features and transferred effective spatial features to the X3D pathway. An action model further enhanced X3D spatial modeling. Experiments showed that X3DFast achieved 98.49% top-1 accuracy, outperforming similar methods in identifying the four behaviors. The method we proposed can effectively identify similar dairy cow behaviors while improving inference speed, providing technical support for subsequent dairy cow behavior recognition and daily behavior statistics.

Fabrication and characterization of a novel zein/pectin/pumpkin seed oil Pickering emulsion and the effects of myricetin on oxidation stability.

In this study, zein/pectin/pumpkin seed oil (PSO) Pickering emulsions (ZPPEs) were fabricated loading with myricetin (MYT), and the quality control methods of oxidation stability were innovatively investigated. The microstructure and particle properties of zein-pectin particles were determined. The zein to pectin ratio of 5:3 and oil phase fraction (φ = 50 %) turned out as the most optimal conditions for the stabilization of myricetin-loaded ZPPEs. The expected oil-in-water emulsion-type structure was confirmed by confocal laser scanning microscopy (CLSM). The internal 3D structure of Pickering emulsions (Lugol's solution improved the water-phase contrast) was imaged by micro-computed tomography (Micro-CT) for the first time. Results showed a sponge like structure of water phase in emulsion with 42 µm as mean droplet size. Light-induced oxidation was evaluated with the PetroOxy method and malondialdehyde (MDA) assays. Encapsuling ZPPEs with MYT could prevent the light induced oxidation, especially, loading of MYT at the core of the emulsion. The analysis of Electronic nose (E-nose) was used to analyze the odor before and after UV-induced oxidation, and showed a good discrimination. This study provided a new approach to prepare ZPPEs with high oxidation stability. Micro-CT, PetroOxy and E-nose could be new methods for characterization and quality assessment of Pickering emulsions.

Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer.

Male breast cancer (MBC) is a rare but aggressive malignancy with cellular and immunological characteristics that remain unclear. Here, we perform transcriptomic analysis for 111,038 single cells from tumor tissues of six MBC and thirteen female breast cancer (FBC) patients. We find that that MBC has significantly lower infiltration of T cells relative to FBC. Metastasis-related programs are more active in cancer cells from MBC. The activated fatty acid metabolism involved with FASN is related to cancer cell metastasis and low immune infiltration of MBC. T cells in MBC show activation of p38 MAPK and lipid oxidation pathways, indicating a dysfunctional state. In contrast, T cells in FBC exhibit higher expression of cytotoxic markers and immune activation pathways mediated by immune-modulatory cytokines. Moreover, we identify the inhibitory interactions between cancer cells and T cells in MBC. Our study provides important information for understanding the tumor immunology and metabolism of MBC.

Learning how to detect: A deep reinforcement learning method for whole-slide melanoma histopathology images.

Cutaneous melanoma represents one of the most life-threatening malignancies. Histopathological image analysis serves as a vital tool for early melanoma detection. Deep neural network (DNN) models are frequently employed to aid pathologists in enhancing the efficiency and accuracy of diagnoses. However, due to the paucity of well-annotated, high-resolution, whole-slide histopathology image (WSI) datasets, WSIs are typically fragmented into numerous patches during the model training and testing stages. This process disregards the inherent interconnectedness among patches, potentially impeding the models' performance. Additionally, the presence of excess, non-contributing patches extends processing times and introduces substantial computational burdens. To mitigate these issues, we draw inspiration from the clinical decision-making processes of dermatopathologists to propose an innovative, weakly supervised deep reinforcement learning framework, titled Fast medical decision-making in melanoma histopathology images (FastMDP-RL). This framework expedites model inference by reducing the number of irrelevant patches identified within WSIs. FastMDP-RL integrates two DNN-based agents: the search agent (SeAgent) and the decision agent (DeAgent). The SeAgent initiates actions, steered by the image features observed in the current viewing field at various magnifications. Simultaneously, the DeAgent provides labeling probabilities for each patch. We utilize multi-instance learning (MIL) to construct a teacher-guided model (MILTG), serving a dual purpose: rewarding the SeAgent and guiding the DeAgent. Our evaluations were conducted using two melanoma datasets: the publicly accessible TCIA-CM dataset and the proprietary MELSC dataset. Our experimental findings affirm FastMDP-RL's ability to expedite inference and accurately predict WSIs, even in the absence of pixel-level annotations. Moreover, our research investigates the WSI-based interactive environment, encompassing the design of agents, state and reward functions, and feature extractors suitable for melanoma tissue images. This investigation offers valuable insights and references for researchers engaged in related studies. The code is available at: https://github.com/titizheng/FastMDP-RL.

Relationship between chronotype and mental behavioural health among adolescents: a cross-sectional study based on the social ecological system.

BACKGROUND: Health risk behaviors (HRBs) is a kind of phenomenon behavior that often occurs in adolescence, and also often appears in clusters. Previous studies suggested an association between social ecological risk factors (SERFs) and HRBs. This study explored 1) whether chronotype moderates the risk of HRBs associated with SERFs and 2) whether mental health is a mediator in this relationship. METHODS: Adolescents were recruited from 39 junior or senior schools (three cities, 13 schools per city) using a multistage cluster sampling method conducted between October, 2020 and June, 2021. The Social Ecological System, Morningness-Eveningness Questionnaire, Brief Instrument on Psychological Health Youths, and Youth Risk Behavior Surveillance questionnaires were used to measure the SERFs, chronotype, mental health and HRBs. Latent category analysis was used to explore the clustering mode of HRBs. The primary exposure was SERFs, and the primary outcome was HRBs; chronotype was a moderator, and mental health was a mediator. The multivariable logistic regression model was used to determine the relationship between SERFs and chronotype and mental behavioral health status. Mediation moderate analysis using the PROCESS method was used to explore the relationship between these variables. Sensitivity analysis was conducted to evaluate the robustness of the model. RESULTS: In total, 17,800 individuals were initially enrolled. After excluding 947 individuals with invalid questionnaires, 16,853 participants were finally included in the analysis. The mean age of participants was 15.33 ± 1.08 years. After adjusting for covariates, multivariable logistic regression found that high levels of SERFs (odds ratio [OR] = 10.10, 95% confidence interval [CI]: 8.88-11.43, P < 0.01), intermediate chronotype (OR = 5.24, 95% CI: 4.57-6.01, P < 0.01), and eveningness (OR = 1.83, 95% CI: 1.64-2.05, P < 0.01) were associated with higher HRBs frequency. This study also assessed the interaction between chronotype, SERFs and HRBs (OR = 27.84, 95% CI: 22.03-35.19, P < 0.01) and mental health (OR = 18.46, 95% CI: 13.16-25.88, P < 0.01). The moderated mediation analyses examined the relationship between chronotype, SERFs, mental health and HRBs. CONCLUSIONS: SERFs may be important variables in measuring the effect of the adolescent psychosocial environment on HRBs; this effect is mediated by mental health and moderated by chronotype.

The impact of COVID-19 on the value of coastal recreational resource from the perspective of recreational behaviour change: Evident from China.

The Corona Virus Disease 2019 (COVID-19) outbreak took a heavy toll on the global tourism industry in 2020, and affected the value realization of coastal recreational ecosystem service. From the micro perspective, this paper combines travel cost method with contingent behaviour method to obtain residents' actual behaviour and contingent behaviour data, and discusses the impact of the outbreak of COVID-19 on the value realization of coastal recreational resources from the perspective of the change in residents' recreational behaviour in Qingdao, China. Residents are observed to significantly reduce their outdoor activities in response to the COVID-19. The number of visits to the beach decreases by 25.2% when there is an outbreak, and decreases by 0.064% for every 1% increase in the number of confirmed cases, which is used to represent the severity of the epidemic. The asymmetries effects of epidemic situation on residents' recreational behaviour show that the improvements lead to larger and more significant impacts than the deteriorations. The disappearance of the pandemic crisis will provide considerable welfare for the citizens in Qingdao, which reaches to 1.9323 billion CNY/year. If the number of confirmed cases deteriorates to 900, the environmental welfare loss will be 0.3366 billion CNY/year. Additionally, we test the effects of residents' cognitive variables, and find that risk perception can strengthen the negative impacts of COVID-19 cases. Furthermore, the deteriorations in the environmental attributes are found to have stronger impacts on the number of visits than the improvements. This paper provides empirical-support results about the change of coastal recreational value through the evaluation of recreational behaviours in the post-epidemic period, which will give important implications for government's marine ecosystem restoration and coastal management work.

Digerati - A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins.

The genome of Mycobacterium tuberculosis contains a relatively high percentage (10%) of genes that are poorly characterised because of their highly repetitive nature and high GC content. Some of these genes encode proteins of the PE/PPE family, which are thought to be involved in host-pathogen interactions, virulence, and disease pathogenicity. Members of this family are genetically divergent and challenging to both identify and classify using conventional computational tools. Thus, advanced in silico methods are needed to identify proteins of this family for subsequent functional annotation efficiently. In this study, we developed the first deep learning-based approach, termed Digerati, for the rapid and accurate identification of PE and PPE family proteins. Digerati was built upon a multipath parallel hybrid deep learning framework, which equips multi-layer convolutional neural networks with bidirectional, long short-term memory, equipped with a self-attention module to effectively learn the higher-order feature representations of PE/PPE proteins. Empirical studies demonstrated that Digerati achieved a significantly better performance (∼18-20%) than alignment-based approaches, including BLASTP, PHMMER, and HHsuite, in both prediction accuracy and speed. Digerati is anticipated to facilitate community-wide efforts to conduct high-throughput identification and analysis of PE/PPE family members. The webserver and source codes of Digerati are publicly available at http://web.unimelb-bioinfortools.cloud.edu.au/Digerati/.

SheepFaceNet: A Speed-Accuracy Balanced Model for Sheep Face Recognition.

The recognition of sheep faces based on computer vision has improved the efficiency and effectiveness of individual sheep identification, providing technical support for the development of smart farming. However, current recognition models have problems such as large parameter sizes, slow recognition speed, and difficult deployment. Therefore, this paper proposes an efficient and fast basic module called Eblock and uses it to build a lightweight sheep face recognition model called SheepFaceNet, which achieves the best balance between speed and accuracy. SheepFaceNet includes two modules: SheepFaceNetDet for detection and SheepFaceNetRec for recognition. SheepFaceNetDet uses Eblock to construct the backbone network to enhance feature extraction capability and efficiency, designs a bidirectional FPN layer (BiFPN) to enhance geometric location ability, and optimizes the network structure, which affects inference speed, to achieve fast and accurate sheep face detection. SheepFaceNetRec uses Eblock to construct the feature extraction network, uses ECA channel attention to improve the effectiveness of feature extraction, and uses multi-scale feature fusion to achieve fast and accurate sheep face recognition. On our self-built sheep face dataset, SheepFaceNet recognized 387 sheep face images per second with an accuracy rate of 97.75%, achieving an advanced balance between speed and accuracy. This research is expected to further promote the application of deep-learning-based sheep face recognition methods in production.

Drug-Free Antimicrobial Nanomotor for Precise Treatment of Multidrug-Resistant Bacterial Infections.

Manufacturing heteronanostructures with specific physicochemical characteristics and tightly controllable designs is very appealing. Herein, we reported NIR-II light-driven dual plasmonic (AuNR-SiO2-Cu7S4) antimicrobial nanomotors with an intended Janus configuration through the overgrowth of copper-rich Cu7S4 nanocrystals at only one high-curvature site of Au nanorods (Au NRs). These nanomotors were applied for photoacoustic imaging (PAI)-guided synergistic photothermal and photocatalytic treatment of bacterial infections. Both the photothermal performance and photocatalytic activity of the nanomotors are dramatically improved owing to the strong plasmon coupling between Au NRs and the Cu7S4 component and enhanced energy transfer. The motion behavior of nanomotors promotes transdermal penetration and enhances the matter-bacteria interaction. More importantly, the directional navigation and synergistic antimicrobial activity of the nanomotors could be synchronously driven by NIR-II light. The marriage of active motion and enhanced antibacterial activity resulted in the expected good antibacterial effects in an abscess infection mouse model.

Population attributable fractions of adverse childhood experiences for emotional problems and self-harming behaviors among middle school students in China.

The population attributable fractions of health outcomes attributed to adverse childhood experiences (ACEs) among Chinese middle school students is unknown. Of all the 22,868 middle school students, 29.8 % had exposure to four or more ACEs. Findings showed a graded relationship between ACE scores and those adverse outcomes. The PAFs of six outcomes attributed to experiencing ≥ 4 ACEs ranged from 23.1 % to 44.2 %. The results emphasized the significance of preventive interventions to alleviate the negative legacies of ACEs.

Structural Characterization of the Staphylococcus aureus Targeting Lectin Peptides from Garlic (Allium sativum L) by Liquid Nitrogen Grinding Coupled with the Proteomic and Antimicrobial Mechanism Analysis.

Garlic has long been used as an antimicrobial spice and herbal remedy. The aim of this study was to isolate the antimicrobial agent in garlic water extract against Staphylococcus aureus (S. aureus) and investigate its antimicrobial mechanism. By an activity-guided separation, garlic lectin-derived peptides (GLDPs) with main molecular weight of around 12 kDa were extracted by liquid nitrogen grinding and identified with high bactericidal activity toward S. aureus, and the MIC was determined as 24.38 µg/mL. In-gel digestion-based proteomic analysis indicated that the peptide sequences were highly identical to the B strain of garlic protein lectin II. Structure analysis suggested that the secondary structure was strongly affected by lyophilization and thus resulted in the inactivation of GLDPs (P < 0.05). Mechanism study revealed that treatment of GLDPs resulted in cell membrane depolarization in a dose-dependent manner, and the disruptions of the cell wall and membrane integrities were observed under electric microscopies. GLDPs could successfully dock with cell wall component lipoteichoic acid (LTA) via van der Waals and conventional bonds in molecular docking analysis. These results suggested that GLDPs were responsible for the S. aureus targeting activity and might be promising candidates for antibiotic development against bacterial infection.

Gut microbiome-mediated glucose and lipid metabolism mechanism of star apple leaf polyphenol-enriched fraction on metabolic syndrome in diabetic mice.

BACKGROUND: Diabetes is a kind of metabolic syndrome (MetS) that seriously threatens human health globally. The leaf of star apple (Chrysophyllum cainito L.) is an incompletely explored folk medicine on diabetes. And, the effects and mechanisms on diabetes complicated glycolipid metabolism disorders are unknown till now. PURPOSE: This study aimed to investigate the constituents of star apple leaf polyphenol enriched-fraction (SAP), and elucidate their treatment effects and mechanism on diabetes and accompanied other MetS. METHODS: The components of SAP were tentatively identified by HPLC-Q-TOF-MS/MS. The antioxidant activity was determined by the scavenging of free radicals and hypoglycemic activities by inhibition of α-glucosidase in vitro. HepG2 cells were used for evaluating the alleviation effects of SAP on lipid accumulation. Streptozotocin and high-fat diet induced diabetic mice were grouped to evaluate the effects of different dosages of SAP. 16S rRNA was conducted to analysis gut microbiome-mediated glucose and lipid metabolism mechanism. RESULTS: It showed that myricitrin was one of the main active constituents of SAP. SAP not only showed low IC50 on -glucosidase (24.427± 0.626 µg/mL), OH·(3.680± 0.054 µg/mL) and ABTS· (9.155±0.234 µg/mL), but significantly induced the lipid accumulation in HepG2 cells (p < 0.05). SAP at 200 mg/kg·day significantly decreased the blood glucose, insulin and oral glucose tolerance test value (p < 0.05). The insulin resistance indexes and oxidative stress were alleviated after administration. SAP not only attenuated hepatic lipid deposition, but also reversed the hepatic glycogen storage. 16S rRNA sequencing results revealed that the interaction between SAP and gut microbiota led to the positive regulation of beneficial bacteria including Akkermansia, Unspecified S24_7, Alistipes and Unspecified_Ruminococcaceae, which might be one of the mechanisms of SAP on MetS. CONCLUSION: For the first time, this study explored the regulation effect of star apple leaf polyphenols on the hepatic glycolipid metabolism and studied the underlying mechanism from the view of gut microbiota. These findings indicated that SAP possesses great potential to serve as a complementary medicine for diabetes and associated MetS. It provided scientific evidence for folk complementary medicine on the treatment of diabetes-complicated multiple metabolic disorders.

A novel visualization method for the composition analysis of processed garlic by MALDI-TOF imaging mass spectrometry (MSI) and Q-TOF LC-MS/MS.

Laba garlic is a kind of vinegar processed garlic (Allium sativum L.) product with multiple health effects. This study applied matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-TOF MSI) and Q-TOF LC-MS/MS for the first time to investigate the garlic tissue spatial distribution changes of low molecular weight compounds during the Laba garlic processing. The distribution characteristics of the compounds were observed in processed and unprocessed garlic including amino acids and derivatives, organosulfur compounds, pigment precursors, polysaccharides and saponins. During Laba garlic processing, some bioactive compounds such as alliin and saponins were lost because they were transformed into other compounds or leached into the acetic acid solution, and some new compounds including pigments-related compounds occurred. This study provided a basis for the spatial distributions and changes of compounds in garlic tissue during Laba garlic processing, which suggested that the bioactivities of garlic might be changed after processing owing to the transformation and change of the constituents.