Syntheses of heterometallic organic frameworks catalysts via multicomponent postmodification: For improving CO2 photoreduction efficiency.

To enhance the economic viability of photocatalytic materials for carbon capture and conversion, the challenge of employing expensive photosensitizer must be overcome. This study aims to improve the visible light utilization with zirconium-based metal-organic frameworks (Zr-MOFs) by employing a multi-component post-synthetic modification (PSM) strategy. An economical photosensitiser and copper ions are introduced into MOF 808 to enhance its photoreduction properties. Notably, the PSM of MOF 808 shows the highest CO yield up to 236.5 µmol g-1 h-1 with aHCOOH production of 993.6 µmol g-1 h-1 under non-noble metal, and its mechanistic insight for CO2 reaction is discussed in detail. The research results have important reference value for the potential application of photocatalytic metal-organic frameworks.

Self-Assembly Method for Synthesizing High-Dimensional EMOFs with High Stability and Laser Response.

Dimension and solvent molecules affect the performance of energetic metal-organic frameworks (EMOFs). High-dimensional EMOFs are usually characterized by high stability and low sensitivity due to their complex network structure. However, solvent molecules affect the detonation performance of EMOFs, and these molecules may be removed at low temperatures, resulting in structural collapse and affecting the stability of EMOFs. In this work, zero-dimensional (0D) Co(AFTO)2·(H2O)2 (EMOF 1) and Ni(AFTO)2·(H2O)2 (EMOF 2) with coordinated water molecules and [Co(AFTO)2]n·EtOH (EMOF 3) and [Ni(AFTO)2]n (EMOF 4) (AFTO = 5-(4-amino-furazan-3-yl)-1-hydroxytetrazole) with high-dimensional structure were synthesized using hydrothermal and self-assembly methods in ethanol, respectively. Structural and performance tests show that EMOF 3 and 4 exhibit remarkable thermal stability and low mechanical sensitivity. This method is a simple, effective, and green technique for synthesizing high-dimensional EMOFs with high stability through self-assembly in ethanol solution. In addition, EMOF 3 and 4 can be used as primary green laser explosives.

Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation.

Despite the success of antiretroviral therapy, human immunodeficiency virus (HIV) cannot be cured because of a reservoir of latently infected cells that evades therapy. To understand the mechanisms of HIV latency, we employed an integrated single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) approach to simultaneously profile the transcriptomic and epigenomic characteristics of ∼ 125,000 latently infected primary CD4+ T cells after reactivation using three different latency reversing agents. Differentially expressed genes and differentially accessible motifs were used to examine transcriptional pathways and transcription factor (TF) activities across the cell population. We identified cellular transcripts and TFs whose expression/activity was correlated with viral reactivation and demonstrated that a machine learning model trained on these data was 75%-79% accurate at predicting viral reactivation. Finally, we validated the role of two candidate HIV-regulating factors, FOXP1 and GATA3, in viral transcription. These data demonstrate the power of integrated multimodal single-cell analysis to uncover novel relationships between host cell factors and HIV latency.

Improving Clinician Performance in Classifying EEG Patterns on the Ictal-Interictal Injury Continuum Using Interpretable Machine Learning.

BACKGROUND: In intensive care units (ICUs), critically ill patients are monitored with electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is constrained by clinician availability, and EEG interpretation can be subjective and prone to interobserver variability. Automated deep-learning systems for EEG could reduce human bias and accelerate the diagnostic process. However, existing uninterpretable (black-box) deep-learning models are untrustworthy, difficult to troubleshoot, and lack accountability in real-world applications, leading to a lack of both trust and adoption by clinicians. METHODS: We developed an interpretable deep-learning system that accurately classifies six patterns of potentially harmful EEG activity - seizure, lateralized periodic discharges (LPDs), generalized periodic discharges (GPDs), lateralized rhythmic delta activity (LRDA), generalized rhythmic delta activity (GRDA), and other patterns - while providing faithful case-based explanations of its predictions. The model was trained on 50,697 total 50-second continuous EEG samples collected from 2711 patients in the ICU between July 2006 and March 2020 at Massachusetts General Hospital. EEG samples were labeled as one of the six EEG patterns by 124 domain experts and trained annotators. To evaluate the model, we asked eight medical professionals with relevant backgrounds to classify 100 EEG samples into the six pattern categories - once with and once without artificial intelligence (AI) assistance - and we assessed the assistive power of this interpretable system by comparing the diagnostic accuracy of the two methods. The model's discriminatory performance was evaluated with area under the receiver-operating characteristic curve (AUROC) and area under the precision-recall curve. The model's interpretability was measured with task-specific neighborhood agreement statistics that interrogated the similarities of samples and features. In a separate analysis, the latent space of the neural network was visualized by using dimension reduction techniques to examine whether the ictal-interictal injury continuum hypothesis, which asserts that seizures and seizure-like patterns of brain activity lie along a spectrum, is supported by data. RESULTS: The performance of all users significantly improved when provided with AI assistance. Mean user diagnostic accuracy improved from 47 to 71% (P<0.04). The model achieved AUROCs of 0.87, 0.93, 0.96, 0.92, 0.93, and 0.80 for the classes seizure, LPD, GPD, LRDA, GRDA, and other patterns, respectively. This performance was significantly higher than that of a corresponding uninterpretable black-box model (with P<0.0001). Videos traversing the ictal-interictal injury manifold from dimension reduction (a two-dimensional representation of the original high-dimensional feature space) give insight into the layout of EEG patterns within the network's latent space and illuminate relationships between EEG patterns that were previously hypothesized but had not yet been shown explicitly. These results indicate that the ictal-interictal injury continuum hypothesis is supported by data. CONCLUSIONS: Users showed significant pattern classification accuracy improvement with the assistance of this interpretable deep-learning model. The interpretable design facilitates effective human-AI collaboration; this system may improve diagnosis and patient care in clinical settings. The model may also provide a better understanding of how EEG patterns relate to each other along the ictal-interictal injury continuum. (Funded by the National Science Foundation, National Institutes of Health, and others.).

The effect of physical fitness on psychological health: evidence from Chinese university students.

BACKGROUND: Despite frequent discussions on the link between physical and mental health, the specific impact of physical fitness on mental well-being is yet to be fully established. METHOD: This study, carried out between January 2022 and August 2023, involved 4,484 Chinese University students from eight universities located in various regions of China. It aimed to examine the association between physical fitness on psychological well-being. Descriptive statistics, t-tests, and logistic regression were used to analyze the association between physical fitness indicators (e.g., Body Mass Index (BMI), vital capacity, and endurance running) and mental health, assessed using Symptom Checklist-90 (SCL-90). All procedures were ethically approved, and participants consented to take part in. RESULTS: Our analysis revealed that BMI, vital capacity, and endurance running scores significantly influence mental health indicators. Specifically, a 1-point increase in BMI increases the likelihood of an abnormal psychological state by 10.9%, while a similar increase in vital capacity and endurance running decreases the risk by 2.1% and 4.1%, respectively. In contrast, reaction time, lower limb explosiveness, flexibility, and muscle strength showed no significant effects on psychological states (p > 0.05). CONCLUSION: Improvements in BMI, vital capacity, and endurance running capabilities are associated with better mental health outcomes, highlighting their potential importance in enhancing overall well-being.

Accumulation mechanism of metabolite markers identified by machine learning between Qingyuan and Xiushui counties in Polygonatum cyrtonema Hua.

Polygonatum cyrtonema Hua is a traditional Chinese medicinal plant acclaimed for its therapeutic potential in diabetes and various chronic diseases. Its rhizomes are the main functional parts rich in secondary metabolites, such as flavonoids and saponins. But their quality varies by region, posing challenges for industrial and medicinal application of P. cyrtonema. In this study, 482 metabolites were identified in P. cyrtonema rhizome from Qingyuan and Xiushui counties. Cluster analysis showed that samples between these two regions had distinct secondary metabolite profiles. Machine learning methods, specifically support vector machine-recursive feature elimination and random forest, were utilized to further identify metabolite markers including flavonoids, phenolic acids, and lignans. Comparative transcriptomics and weighted gene co-expression analysis were performed to uncover potential candidate genes including CHI, UGT1, and PcOMT10/11/12/13 associated with these compounds. Functional assays using tobacco transient expression system revealed that PcOMT10/11/12/13 indeed impacted metabolic fluxes of the phenylpropanoid pathway and phenylpropanoid-related metabolites such as chrysoeriol-6,8-di-C-glucoside, syringaresinol-4'-O-glucopyranosid, and 1-O-Sinapoyl-D-glucose. These findings identified metabolite markers between these two regions and provided valuable genetic insights for engineering the biosynthesis of these compounds.

Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection Using Eight Million Samples Labeled With Imprecise Arrhythmia Alarms.

Atrial fibrillation (AF) is a common cardiac arrhythmia with serious health consequences if not detected and treated early. Detecting AF using wearable devices with photoplethysmography (PPG) sensors and deep neural networks has demonstrated some success using proprietary algorithms in commercial solutions. However, to improve continuous AF detection in ambulatory settings towards a population-wide screening use case, we face several challenges, one of which is the lack of large-scale labeled training data. To address this challenge, we propose to leverage AF alarms from bedside patient monitors to label concurrent PPG signals, resulting in the largest PPG-AF dataset so far (8.5 M 30-second records from 24,100 patients) and demonstrating a practical approach to build large labeled PPG datasets. Furthermore, we recognize that the AF labels thus obtained contain errors because of false AF alarms generated from imperfect built-in algorithms from bedside monitors. Dealing with label noise with unknown distribution characteristics in this case requires advanced algorithms. We, therefore, introduce and open-source a novel loss design, the cluster membership consistency (CMC) loss, to mitigate label errors. By comparing CMC with state-of-the-art methods selected from a noisy label competition, we demonstrate its superiority in handling label noise in PPG data, resilience to poor-quality signals, and computational efficiency.

Is dancing an effective intervention for fat loss? A systematic review and meta-analysis of dance interventions on body composition.

OBJECTIVE: The systematic review aimed to review the research on the effects of dance interventions, relative to normal lifestyles, on body composition in people with overweight and obesity. METHODS: 7 databases were searched from their inception to 3 July 2023 for studies with dance interventions and normal lifestyles groups. Only studies investigating dance interventions in people with overweight and obesity(body mass index (BMI)>24kg/m2 and percent fat mass (Fat(%)) abnormal(male>20%, female>25%)) were included in the meta-analysis. There were no restrictions on dance forms. RESULTS: 654 studies were identified from the databases, and 10 studies were evaluated to be eligible. The meta-analysis revealed that compared to normal lifestyles dance had meaningful improvements in body mass(BM), BMI, waist circumference(WC), Fat(%), and fat mass(Fat(kg)). No significant differences were found in the waist-to-hip ratio(WHR). CONCLUSIONS: Dance is effective on fat loss in people with overweight and obesity, and has a significant improvement on body composition and morphology. For its high efficiency and greater sense of enjoyment, dance can be a beneficial exercise intervention for fat loss.

Entanglement generation by strong coupling between surface lattice resonance and exciton in an Al nanoarray-coated WS2 quantum emitter.

Strong light-matter interaction plays a central role in realizing quantum photonic technologies. The entanglement state, which results from the hybridization of excitons and cavity photons, forms the foundation of quantum information science. In this work, an entanglement state is achieved by manipulating the mode coupling between surface lattice resonance and quantum emitter into the strong coupling regime. At the same time, a Rabi splitting of 40 meV is observed. A full quantum model based on the Heisenberg picture is used to describe this unclassical phenomenon, and it perfectly explains the interaction and dissipation process. In addition, the observed concurrency degree of the entanglement state is 0.5, presenting the quantum nonlocality. This work effectively contributes to the understanding of nonclassical quantum effects arising from strong coupling and will intrigue more interesting potential applications in quantum optics.

Effect of High-Intensity Interval Training vs. Moderate-Intensity Continuous Training on Fat Loss and Cardiorespiratory Fitness in the Young and Middle-Aged a Systematic Review and Meta-Analysis.

OBJECTIVES: This systematic review is conducted to evaluate the effect of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on body composition and cardiorespiratory fitness (CRF) in the young and middle-aged. METHODS: Seven databases were searched from their inception to 22 October 2022 for studies (randomized controlled trials only) with HIIT and MICT intervention. Meta-analysis was carried out for within-group (pre-intervention vs. post-intervention) and between-group (HIIT vs. MICT) comparisons for change in body mass (BM), body mass index (BMI), waist circumference (WC), percent fat mass (PFM), fat mass (FM), fat-free mass (FFM), and CRF. RESULTS: A total of 1738 studies were retrieved from the database, and 29 studies were included in the meta-analysis. Within-group analyses indicated that both HIIT and MICT can bring significant improvement in body composition and CRF, except for FFM. Between-group analyses found that compared to MICT, HIIT brings significant benefits to WC, PFM, and VO2peak. CONCLUSIONS: The effect of HIIT on fat loss and CRF in the young and middle-aged is similar to or better than MICT, which might be influenced by age (18-45 years), complications (obesity), duration (>6 weeks), frequency, and HIIT interval. Despite the clinical significance of the improvement being limited, HIIT appears to be more time-saving and enjoyable than MICT.

Screening of lncRNA profiles during intramuscular adipogenic differentiation in longissimus dorsi and semitendinosus muscles in pigs.

Intramuscular fat content is an important factor that determines meat quality in pigs. In recent years, epigenetic regulation has increasingly studied the physiological model of intramuscular fat. Although long noncoding RNAs (lncRNAs) play essential roles in various biological processes, their role in intramuscular fat deposition in pigs remains largely unknown. In this study, intramuscular preadipocytes in the longissimus dorsi and semitendinosus of Large White pigs were isolated and induced into adipogenic differentiation in vitro. High-throughput RNA-seq was carried out to estimate the expression of lncRNAs at 0, 2 and 8 days post-differentiation. At this stage, 2135 lncRNAs were identified. KEGG analysis showed that the differentially expressed lncRNAs were common in pathways involved with adipogenesis and lipid metabolism. lnc_000368 was found to gradually increase during the adipogenic process. Reverse-transcription quantitative polymerase chain reaction and a western blot revealed that the knockdown of lnc_000368 significantly repressed the expression of adipogenic genes and lipolytic genes. As a result, lipid accumulation in porcine intramuscular adipocytes was impaired by the silencing of lnc_000368. Overall, our study identified a genome-wide lncRNA profile related to porcine intramuscular fat deposition, and the results suggest that lnc_000368 is a potential target gene that might be targeted in pig breeding in the future.

The ferroptosis in haemocytes of Pacific oyster Crassostrea gigas upon erastin treatment.

Ferroptosis is an iron and oxidative dependent form of cell death usually mediated by redox related molecules in vertebrates. In the present study, a glutathione peroxidase 4 (GPX4) and a solute carrier family 7 member 11 (SLC7A11, xCT) homologues were identified from the oyster Crassostrea gigas (designed as CgGPX4 and CgxCT), which contained a GSHPx domain and an AA_permease domain, respectively. The mRNA transcripts of CgGPX4 and CgxCT were expressed in all the examined tissues, including gill, gonad, adductor muscle, labial palp, mantle, hepatopancreas and haemocytes, with the highest expression in haemocytes. After erastin treatment, the rate of cell malformation and cell death increased significantly in haemocytes, and the mitochondrial atrophy, crest loss and fracture were observed in haemocytes. While the amount of Fe2+ and Malondialdehyde (MDA) increased significantly, the mRNA expressions of CgGPX4, CgxCT and voltage-dependent anion channel 2 (CgVDAC2) in haemocytes decreased significantly after erastin treatment. These results indicated that erastin was able to induce the ferroptosis of oyster haemocytes.

Extracellular vesicles, a novel model linking bacteria to ferroptosis in the future?

Ferroptosis is a recently discovered modulated cell death mechanism caused by the accumulation of iron-dependent lipid peroxides to toxic levels and plays an important role in tumor immunology and neurology. Recent studies have shown that ferroptosis may play a crucial role in bacterial infection pathogenesis, which may be useful in anti-infection therapies. However, how bacteria enter cells to induce ferroptosis after invading the host immune system remains largely unknown. In addition, the current studies only focus on the relationship between a single bacterial species or genus and host cell ferroptosis, and there is no systematic summary of its regulatory mechanism. Therefore, our review firstly sums up the role of ferroptosis in bacterial infection and its regulatory mechanism, and innovatively speculates on the function and potential mechanism of extracellular vesicles (EVs) in bacterial-induced ferroptosis, in order to provide possible novel directions and ideas for future anti-infection research. KEY POINTS: • Ferroptosis presents a novel mechanism for bacterial host interaction • EVs provide the potential mechanism for bacterial-induced ferroptosis • The relationship of EVs with ferroptosis provides possible directions for future treatment of bacterial infection.

Controllable Structural Modulation: Assembling Variable Dimension Energetic Metal-Organic Frameworks via Free Protons.

Herein, we provide an efficient strategy for constructing three-dimensional (3D) energetic coordination polymers (ECPs), namely, metal-organic frameworks (EMOFs), avoiding solvent coordination without changing the organic ligands or metal nodes. Three ECPs with the same ligand and metal center, namely, two-dimensional (2D) layer ECP [Pb(HOBTT)(H2O)2]n (1), 3D solvent-free EMOFs [Pb(HOBTT)]n (2), and dense [Pb3(OBTT)2]n (3) (H3OBTT = 4,5-bis(1-hydroxytetrazol-5-yl)-2H-1,2,3-triazole), were rationally designed and synthesized via free protons. As expected, the theoretical density of 3 (4.080 g·cm-3) is greater than those of 2 (3.299 g·cm-3) and 1 (3.055 g·cm-3). Thermal stabilities indicate that their decomposition temperature exceeds 300 °C. Theoretical calculations show that the detonation performance of 3 is better than that of 1 and 2. The detonation performance of 1-3 was further proven by laser irradiation.

Microgel reinforced zwitterionic hydrogel coating for blood-contacting biomedical devices.

Zwitterionic hydrogels exhibit eminent nonfouling and hemocompatibility. Several key challenges hinder their application as coating materials for blood-contacting biomedical devices, including weak mechanical strength and low adhesion to the substrate. Here, we report a poly(carboxybetaine) microgel reinforced poly(sulfobetaine) (pCBM/pSB) pure zwitterionic hydrogel with excellent mechanical robustness and anti-swelling properties. The pCBM/pSB hydrogel coating was bonded to the PVC substrate via the entanglement network between the pSB and PVC chain. Moreover, the pCBM/pSB hydrogel coating can maintain favorable stability even after 21 d PBS shearing, 0.5 h strong water flushing, 1000 underwater bends, and 100 sandpaper abrasions. Notably, the pCBM/pSB hydrogel coated PVC tubing can not only mitigate the foreign body response but also prevent thrombus formation ex vivo in rats and rabbits blood circulation without anticoagulants. This work provides new insights to guide the design of pure zwitterionic hydrogel coatings for biomedical devices.

Bioinspired zwitterionic microgel-based coating: Controllable microstructure, high stability, and anticoagulant properties.

Zwitterionic polymers have shown promising results in non-fouling and preventing thrombosis. However, the lack of controlled surface coverage hinders their application for biomedical devices. Inspired by the natural biological surfaces, a facile zwitterionic microgel-based coating strategy is developed by the co-deposition of poly (sulfobetaine methacrylate-co-2-aminoethyl methacrylate) microgel (SAM), polydopamine (PDA), and sulfobetaine-modified polyethyleneimine (PES). The SAMs were used to construct controllable morphology by using the PDA combined with PES (PDAS) as the intermediate layer, which can be easily modulated via adjusting the crosslinking degree and contents of SAMs. The obtained SAM/PDAS coatings exhibit high anti-protein adhesive properties and can effectively inhibit the adhesion of cells, bacteria, and platelet through the synergy of high deposition density and controllable morphology. In addition, the stability of SAM/PDAS coating is improved owing to the anchoring effects of PDAS to substrate and SAMs. Importantly, the ex vivo blood circulation test in rabbits suggests that the SAM/PDAS coating can effectively decrease thrombosis without anticoagulants. This study provides a versatile coating method to address the integration of zwitterionic microgel-based coatings with high deposition density and controllable morphology onto various substrates for wide biomedical device applications. STATEMENT OF SIGNIFICANCE: Thrombosis is a major cause of medical device implantation failure, which results in significant morbidity and mortality. In this study, inspired by natural biological surfaces (fish skin and vascular endothelial layer) and the anchoring ability of mussels, we report a convenient and efficient method to firmly anchor zwitterionic microgels using an oxidative co-deposition strategy. The prepared coating has excellent antifouling and antithrombotic properties through the synergistic effect of physical morphology and chemical composition. This biomimetic surface engineering strategy is expected to provide new insights into the clinical problems of blood-contacting devices related to thrombosis.

Disruption of sncRNA Improves the Protective Efficacy of Outer Membrane Vesicles against Helicobacter pylori Infection in a Mouse Model.

The outer membrane vesicles (OMVs) secreted by Helicobacter pylori contain various bacterial components, such as proteins, phospholipids, toxins, and nucleic acids, including small noncoding RNA (sncRNA), which have regulatory functions in cell envelope structure, metabolism, bacterial communication, biofilm formation, and virulence. We previously showed that knocking out sncRNAs sR-989262 and sR-2509025 at the cellular level increased interleukin 8 (IL-8) levels in mice exposed to OMVs. In this study, we show that immunization with ΔsR-989262 and ΔsR-2509025 OMVs intragastrically significantly increased immunoglobulin G (IgG) and secreted IgA levels in mice compared to wild-type OMVs and without weight changes, which indicated that sncRNA-deficient OMVs are relatively safe to immunize mice. The detection of IgG subtypes IgG1 and IgG2c showed that the sncRNA-deficient OMVs primarily stimulate the T helper 2 (Th2)-mediated immune response. Moreover, levels of the cytokines IL-4, IL-13, gamma interferon (IFN-γ), IL-12 (p40), IL-8, and IL-17 indicate that ΔsR-989262 and ΔsR-2509025 OMVs trigger the Th2-type immune response but primarily trigger a Th1-mediated and Th17-mediated immune response. These findings show that OMV-encapsulated sncRNA plays an important role in regulating the immune response in hosts infected by H. pylori at the animal level. Moreover, they show that knocking out of sR-989262 and sR-2509025 improves the immunogenicity and protective efficacy of OMVs, and this may be beneficial to the design of OMV-based H. pylori vaccines.

CgHMGB1 functions as a broad-spectrum recognition molecule to induce the expressions of CgIL17-5 and Cgdefh2 via MAPK or NF-κB signaling pathway in Crassostrea gigas.

High-mobility group box 1 (HMGB1), a highly conserved nucleoprotein, functions in immune recognition, inflammation and antibacterial immunization in vertebrates. In the present study, the mediation mechanism of CgHMGB1 in activating MAPK and NF-κB/Rel signaling pathways to induce the expressions of immune effectors was investigated. CgHMGB1 mRNA was detected in all tested developmental stages from fertilized egg to D-larvae, with the higher expressions in 4 cells and 8 cells stages. CgHMGB1 proteins were mainly distributed in haemocyte granulocytes. The expressions of CgHMGB1 mRNA in haemocytes increased significantly after Vibrio splendidus stimulation, and CgHMGB1 protein translocated into the haemocyte cytoplasm and release into cell-free haemolymph. The phosphorylation of CgERK and CgP38 were induced, the nuclear translocation of CgRel were promoted, and the mRNA expressions of CgIL17-5 and Cgdefh2 increased significantly after rCgHMGB1 treatment. Obvious branchial swelling and cilium shedding were observed after rCgHMGB1 treatment. rCgHMGB1 exhibited binding activity to different polysaccharides, bacteria, and fungi. rCgHMGB1 also displayed obvious antibacterial activity to V. splendidus and E. coli. These results indicated that CgHMGB1 functioned as an immune recognition molecule to recognize various PAMPs and bacteria to induce the mRNA expressions of CgIL17-5 and Cgdefh2 via the activation of MAPK and NF-κB signaling pathways in oysters.

Cell pyroptosis in picornavirus and its potential for treating viral infection.

Cell pyroptosis has received increased attention due to the associations between innate immunity and disease, and it has become a major focal point recently due to in-depth studies of cancer. With increased research on pyroptosis, scientists have discovered that it has an essential role in viral infections, especially in the occurrence and development of some picornavirus infections. Many picornaviruses, including Coxsackievirus, a71 enterovirus, human rhinovirus, encephalomyocarditis virus, and foot-and-mouth disease virus induce pyroptosis to varying degrees. This review summarized the mechanisms by which these viruses induce cell pyroptosis, which can be an effective defense against pathogen infection. However, excessive inflammasome activation or pyroptosis also can damage the host's health or aggravate disease progression. Careful approaches that acknowledge this dual effect will aid in the exploration of picornavirus infections and the mechanisms that produce the inflammatory response. This information will promote the development of drugs that can inhibit cell pyroptosis and provide new avenues for future clinical treatment.

Effect of High-Intensity Interval Training Combined with Fasting in the Treatment of Overweight and Obese Adults: A Systematic Review and Meta-Analysis.

OBJECTIVES: A systematic review and meta-analysis is conducted to compare the effects of high-intensity interval training (HIIT) combined with fasting (HIIT + fasting) and other interventions (HIIT alone, fasting alone, or normal intervention) in adults with overweight and obesity on body composition (body mass, body mass index (BMI), waist circumference (WC), percent fat mass (PFM), fat mass (FM), fat-free mass (FFM)), maximal oxygen uptake (VO2peak), and glucose metabolism (fasting plasma glucose (FPG)), fasting plasma insulin (FPI)). METHODS: The databases of PubMed, the Cochrane Library, Embace, Web of Science, CNKI, Wangfang Data, and CBM were searched from their inception to February 2022. Randomized controlled trials comparing the effects of HIIT + fasting and other interventions on adults with overweight and obesity were included in this meta-analysis. The risk of bias was assessed by the Cochrane risk of bias tool. The effect size was completed by using mean difference (MD) and standard deviation. If there were varying units or large differences among the included studies, the standardized mean difference (SMD) would be used. The certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). RESULTS: Nine randomized controlled trials with 230 overweight and obese adults were conducted in accordance with our inclusion criteria. The results of the meta-analysis revealed that compared to the control group HIIT + fasting had better effects on the body mass, WC, FM, and VO2peak, while there were no significant differences in PFM, FFM, FPG, and FPI. CONCLUSIONS: Despite the number of included trials being small and the GRADE of all outcomes being very low, HIIT + fasting has a positive effect on the body composition of overweight and obese adults, and significantly improves VO2peak. For adults with overweight and obesity who have long-term comorbidity, HIIT + fasting was a better way to improve FPG than HIIT alone or fasting alone. More studies are required to investigate different combinations of HIIT + fasting; and the safety of HIIT + fasting intervention on overweight and obese adults.