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Ischemic stroke is a cerebrovascular disease associated with high mortality and disability rates. Since the inflammation and immune response play a central role in driving ischemic damage, it becomes essential to modulate excessive inflammatory reactions to promote cell survival and facilitate tissue repair around the injury site. Various cell types are involved in the inflammatory response, including microglia, astrocytes, and neutrophils, each exhibiting distinct phenotypic profiles upon stimulation. They display either proinflammatory or anti-inflammatory states, a phenomenon known as 'cell polarization.' There are two cell polarization therapy strategies. The first involves inducing cells into a neuroprotective phenotype in vitro, then reintroducing them autologously. The second approach utilizes small molecular substances to directly affect cells in vivo. In this review, we elucidate the polarization dynamics of the three reactive cell populations (microglia, astrocytes, and neutrophils) in the context of ischemic stroke, and provide a comprehensive summary of the molecular mechanisms involved in their phenotypic switching. By unraveling the complexity of cell polarization, we hope to offer insights for future research on neuroinflammation and novel therapeutic strategies for ischemic stroke.

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Importance: Understanding treatment expectations of patients and their clinicians is of great importance in improving personalized medical services and enhancing patient safety systems. Objective: To investigate treatment expectations of patients and their clinicians and compare differences between both, by using a pair of validated structured assessment tools covering three key aspects/dimensions of clinical interests. Design setting and participants: This single-center cross-sectional study was conducted at Peking Union Medical College Hospital in China. The study enrolled patients aged 16 years and older receiving inpatient care and their clinicians. Patient recruitment was conducted from March 2023 to November 2023. Assessments: In addition to demographic and clinical characteristics, this study employed two validated structured assessment tools to evaluate treatment expectations among patients and their clinicians: the Hospitalized Patients' Expectations for Treatment Scale-Patient version (HOPE-P) and its counterpart, the Hospitalized Patients' Expectations for Treatment Scale-Clinician version (HOPE-C). Results: A total of 233 patients (mean [SD] age, 52.3 [15.1] years; 108 [46.4%] female) along with their clinicians, who numbered 75 in total were enrolled in this study. The distribution of total scores for HOPE-P and HOPE-C displayed similar patterns, with most scores concentrated in the higher range (above 50% of the full score). The mean HOPE-P total score was higher than that of HOPE-C (mean [SD] score, 38.78 [4.86] vs 37.49 [4.32]; t = 3.12, P = 0.002). In Dimension 2, the HOPE-P score was higher than HOPE-C (23.67 [3.20] vs 21.72 [3.03]; t = 6.98, P < 0.001). However, in Dimensions 1 and 3, HOPE-P scored lower than HOPE-C (13.37 [2.44] vs 13.84 [1.73]; t = -2.384, P < 0.018; 1.74 [1.14] vs 1.94 [1.00]; t = -2.00, P = 0.047). Certain demographic and clinical characteristics led to variations in patients' treatment expectations, including marital status, monthly family income, and smoking history. Conclusions and relevance: This cross-sectional study revealed significant differences between patients' and doctors' treatment expectations. Notably, it highlighted the need for clinicians to focus on rationalizing patients' expectations concerning treatment outcomes. Trial Registration Chinese Clinical Trial Registry Identifier: ChiCTR2300075262.

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Objectives: To comprehensively analyze the randomized controlled clinical trials of integrated traditional Chinese medicine (TCM) and western medicine in the treatment of metabolic syndrome (MetS), and to explore the clinical efficacy and safety of different TCM combined with western medicine for MetS. The purpose of this study is to provide specific suggestions for clinical guidance in the treatment of MetS. Methods: A comprehensive literature review was conducted across several databases, including China Knowledge Network, Wanfang Data, VIP Information, China Biomedical Literature Service System, Embase, PubMed, and Web of Science, up to October 2023. The scope of this review was confined to RCTs focusing on the treatment of metabolic syndrome through an integrated approach of TCM and Western medicine. The primary efficacy endpoints analyzed were clinical efficacy, fasting blood glucose (FBG), triglyceride (TG), and high-density lipoprotein (HDL). Data synthesis and analysis were performed using Stata 16 and RevMan 5.4 for both traditional and network meta-analyses. Results: The findings from both traditional and network meta-analyses reveal that the combination of JiangZhiHuoXue pills (JZHX) + Conventional Western Medicine (CWM) significantly reduces FBG levels. Similarly, the AnShenNingXin capsules (ASNX) + CWM combination markedly lowers TG levels, while the FuFangQiMa capsules (FFQM) + CWM combination shows enhanced efficacy in elevating HDL levels. Notably, the combination of KangNing capsules (KNJN) + CWM demonstrates a more pronounced clinical effect compared to CWM/placebo alone. Conclusions: The study concludes that the synergistic combination of TCM and Western medicine exhibits superior therapeutic benefits in treating MetS compared to CWM/Placebo treatments alone. The combinations of JZHX, AXNX, FFQM, and KNJN with CWM emerge as potentially effective treatments.

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Background: Laparoscopic common bile duct exploration (LCBDE) proves a safe and effective treatment for choledochal stones. After LCBDE, preferred choledochal closure is favored for short- and long-term outcomes compared with t-tube drainage. However, there are no relevant studies on the technique of layered closure of the common bile duct with double-needle bidirectional barbed suture at home and abroad. Materials and Methods: A retrospective study of 37 patients who underwent laparoscopic choledochotomy from January 2021 to October 2023 in our hospital was performed. A continuous layered one-stage suture using two-needle bidirectional barb wire. The primary outcomes were stone clearance, operative time, blood loss, and complications. Secondary outcomes were complications, length of hospitalization, and time to drain removal. Results: During the study period, laparoscopic surgery was successful in all cases, and the initial stones were removed without complications. Conclusion: The treatment of choledocholithiasis with continuous layered one-stage suture with double-needle bidirectional barbed wire after LCBDE is a new convenient and effective treatment in selected patients.

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Groundwater is an essential source of drinking water and agricultural irrigation water, and its protection has become a global goal for public health. However, knowledge about heavy metal(loid) resistance genes (MRGs) in groundwater and the potential co-selection of antibiotic resistance genes (ARGs) have seldom been developed. Here, during the wet and dry seasons, we collected 66 groundwater samples (total dissolved solids = 93.9-9530 mg/L) adjacent to Baiyangdian Lake in Northern China, which presented the few metal(loid) and antibiotic contamination. We identified 160 MRGs whose composition exhibited significant seasonal variation, and dissolved metal(loid)s (particularly Ba) played a determinative role in promoting the MRGs proliferation though with relatively low concentrations, suggesting the relatively vulnerable groundwater ecosystems. Moreover, 27.4% of MRG-carrying metagenome-assembled genomes (MAGs) simultaneously carried ARGs, with the most frequently detected MRG types of Cu, Hg, and As, and ARG types of multidrug and bacitracin. Physicochemical variables, variables related to total dissolved solids, metal(loid)s, and antibiotics synthetically shaped the variation of MRG-ARG hosts in groundwater. We found that the increase of MRG-ARG hosts was critically responsible for the spread of MRGs and ARGs in groundwater. Our findings revealed the widespread co-occurrence of MRGs and ARGs in few-contaminated groundwater and highlighted the crucial roles of salinity in their propagation and transmission.

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BACKGROUND: Cognitive impairment is a core symptom of schizophrenia. Metabolic abnormalities impact cognition, and although the influence of blood lipids on cognition has been documented, it remains unclear. We conducted a small cross-sectional study to investigate the relationship between blood lipids and cognition in patients with stable-phase schizophrenia. Using Olink proteomics, we explored the potential mechanisms through which blood lipids might affect cognition from an inflammatory perspective. METHODS: A total of 107 patients with stable-phase schizophrenia and cognitive impairment were strictly included. Comprehensive data collection included basic patient information, blood glucose, blood lipids, and body mass index. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and the MATRICS Consensus Cognitive Battery (MCCB). After controlling for confounding factors, we identified differential metabolic indicators between patients with mild and severe cognitive impairment and conducted correlation and regression analyses. Furthermore, we matched two small sample groups of patients with lipid metabolism abnormalities and used Olink proteomics to analyze inflammation-related differential proteins, aiming to further explore the association between lipid metabolism abnormalities and cognition. RESULTS: The proportion of patients with severe cognitive impairment (SCI) was 34.58%. Compared to patients with mild cognitive impairment (MCI), those with SCI performed worse in the Attention/Alertness (t = 2.668, p = 0.009) and Working Memory (t = 2.496, p = 0.014) cognitive dimensions. Blood lipid metabolism indicators were correlated with cognitive function, specifically showing that higher levels of TG (r = -0.447, p < 0.001), TC (r = -0.307, p = 0.002), and LDL-C (r = -0.607, p < 0.001) were associated with poorer overall cognitive function. Further regression analysis indicated that TG (OR = 5.578, P = 0.003) and LDL-C (OR = 5.425, P = 0.001) may be risk factors for exacerbating cognitive impairment in individuals with stable-phase schizophrenia. Proteomics analysis revealed that, compared to individuals with stable-phase schizophrenia and normal lipid metabolism, those with hyperlipidemia had elevated levels of 10 inflammatory proteins and decreased levels of 2 inflammatory proteins in plasma, with these changes correlating with cognitive function. The differential proteins were primarily involved in pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, and IL-17 signaling pathway. CONCLUSION: Blood lipids are associated with cognitive function in individuals with stable-phase schizophrenia, with higher levels of TG, TC, and LDL-C correlating with poorer overall cognitive performance. TG and LDL-C may be risk factors for exacerbating cognitive impairment in these patients. From an inflammatory perspective, lipid metabolism abnormalities might influence cognition by activating or downregulating related proteins, or through pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, and IL-17 signaling pathway.

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The phenomenon wherein innate immune cells adopt long-term inflammatory phenotypes following the first stimuli is named trained immunity and can improve host defense against infections. Transcriptional and epigenetic reprogramming are critical mechanisms of trained immunity; however, the regulatory networks are not entirely clear at present. The human endogenous retroviruses (HERVs) provide large amounts of transcriptional regulators in the regulatory pathways. In this study, we analyzed published large omics data to explore the roles of such "dark matter" of the human genome in trained and tolerant macrophages. We collected 80 RNA sequencing data and 62 sequencing data to detect histone modifications and active regulatory regions from nine published studies on trained and tolerant macrophages. By analyzing the characteristics of transcription and epigenetic modification of HERVs, as well as their association with gene expression, we found that 15.3% of HERVs were transcribed nonrandomly from noncoding regions and enriched in specific HERV families and specific chromosomes, such as chromosomes 11, 15, 17, and 19, and they were highly related with the expression of adjacent genes. We found that 295 differentially expressed HERVs are located in 50-kbp flanking regions of 142 differentially expressed genes. We found epigenetic changes of these HERVs and that overlap with predicted enhancers and identified 35 enhancer-like HERVs. The related genes were highly involved in the activation and inflammatory responses, such as the TLR pathway. Other pathways including phosphoinositide signaling and transport of folate and K+ might be also related with trained immunity, which require further study. These results demonstrated that HERVs might play important roles in trained immunity.

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AIMS: Hypervirulent Klebsiella pneumoniae (hvKp) causes invasive community-acquired infections in healthy individuals, and hypermucoviscosity (HMV) is the main phenotype associated with hvKp. This study investigates the impact of microaerobic environment availability on the mucoviscosity of K. pneumoniae. METHODS AND RESULTS: By culturing 25 clinical strains under microaerobic and aerobic environments, we observed a notable reduction in mucoviscosity in microaerobic environments. RNA sequencing and qRT-PCR revealed downregulated expressions of capsule synthesis genes (galf, orf2, wzi, wza, wzb, wzc, wcaj, manC, manB, and ugd) and regulatory genes (rmpA, rmpD, and rmpC) under microaerobic conditions. Transmission electron microscopy and Indian ink staining analysis were performed, revealing that the capsular thickness of K. pneumoniae decreased by half in microaerobic conditions compared to aerobic conditions. Deletion of rmpD and rmpC caused the loss of the HMV phenotype in both aerobic and microaerobic conditions. However, compared to wild-type strain in microaerobic condition, only rmpD overexpression strain, and not rmpC overexpression strain, displayed a significant increase in capsule thickness in microaerobic conditions. CONCLUSIONS: Microaerobic conditions can suppress the mucoviscosity of K. pneumoniae, but this suppression can be overcome by altering the expression of rmpD, indicating a specific function for rmpD in the oxygen environmental adaptation of K. pneumoniae.

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OBJECTIVES: Cardiometabolic Index (CMI) is a surrogate marker for metabolic disorders. It is associated with various chronic diseases. This study aims to investigate the relationship between CMI and asthma. METHODS: Data from seven consecutive National Health and Nutrition Examination Survey cycles between 2005 and 2018 were used. The study included adults with self-reported asthma diagnoses and complete information for CMI calculation. The formula for CMI is CMI = [WC (cm)/height (cm)] × [TG (mg/dL)/HDL-C (mg/dL)]. A multivariate logistic regression model was employed to examine the linear relationship between CMI and asthma. Subgroup analyses were conducted to explore potential influencing factors. Additionally, smooth curve fitting and threshold effect analysis were used to describe the non-linear relationship. RESULTS: A higher CMI was possibly associated with an increased prevalence of asthma. After adjusting for various covariates including marital status, Poverty Income Ratio, Body Mass Index, hypertension, diabetes, smoking, alcohol consumption, heart attack, and stroke, the results remained significant (OR = 1.03; 95%CI, 1.00-1.05, p = 0.0178, R2 = 0.52). Participants with the highest CMI had a 38% increased risk of asthma prevalence compared to those with the lowest CMI (OR = 1.38; 95%CI, 1.19-1.60, p < 0.0001). CONCLUSION: The findings reveal that elevated CMI levels correlate with an increased risk of asthma, highlighting CMI's potential as a predictive marker for asthma, particularly in populations with a CMI below 1.97. These results suggest that interventions aimed at improving metabolic health may prove effective in managing or preventing asthma.

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In rare earth nickelates (RENiO3), electron-lattice coupling drives a concurrent metal-to-insulator and bond disproportionation phase transition whose microscopic origin has long been the subject of active debate. Of several proposed mechanisms, here we test the hypothesis that pairs of self-doped ligand holes spatially condense to provide local spin moments that are antiferromagnetically coupled to Ni spins. These singlet-like states provide a basis for long-range bond and spiral spin order. Using magnetic resonant X-ray scattering on NdNiO3 thin films, we observe the chiral nature of the spin-disproportionated state, with spin spirals propagating along the crystallographic (101)ortho direction. These spin spirals are found to preferentially couple to X-ray helicity, establishing the presence of a hitherto-unobserved macroscopic chirality. The presence of this chiral magnetic configuration suggests a potential multiferroic coupling between the noncollinear magnetic arrangement and improper ferroelectric behavior as observed in prior studies on NdNiO3 (101)ortho films and RENiO3 single crystals. Experimentally-constrained theoretical double-cluster calculations confirm the presence of an energetically stable spin-disproportionated state with Zhang-Rice singlet-like combinations of Ni and ligand moments.

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Extracellular membrane proteins are crucial for mediating cell attachment, recognition, and signal transduction in the testicular microenvironment, particularly germline stem cells. Cadherin 18 (CDH18), a type II classical cadherin, is primarily expressed in the nervous and reproductive systems. Here, we investigated the expression of CDH18 in neonatal porcine prospermatogonia (ProSGs) and murine spermatogonial stem cells (SSCs). Disruption of CDH18 expression did not adversely affect cell morphology, proliferation, self-renewal, or differentiation in cultured porcine ProSGs, but enhanced cell adhesion and prolonged cell maintenance. Transcriptomic analysis indicated that the down-regulation of CDH18 in ProSGs significantly up-regulated genes and signaling pathways associated with cell adhesion. To further elucidate the function of CDH18 in germ cells, Cdh18 knockout mice were generated, which exhibited normal testicular morphology, histology, and spermatogenesis. Transcriptomic analysis showed increased expression of genes associated with adhesion, consistent with the observations in porcine ProSGs. The interaction of CDH18 with ß-catenin and JAK2 in both porcine ProSGs and murine SSCs suggested an inhibitory effect on the canonical Wnt and JAK-STAT signaling pathways during CDH18 deficiency. Collectively, these findings highlight the crucial role of CDH18 in regulating cell adhesion in porcine ProSGs and mouse SSCs. Understanding this regulatory mechanism provides significant insights into the testicular niche.

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Plant-based protein supplements are increasingly popular, yet their efficacy in enhancing athletic performance compared to animal protein, insect protein, or other protein types remains under investigation. This study aimed to assess the effectiveness of plant-based protein on athletic abilities such as muscle strength, endurance performance, and muscle protein synthesis (MPS) rate and compare it to no- or low-protein ingestion and non-plant protein sources. Randomized controlled trials (RCTs) evaluating the beneficial and harmful effects of plant-based protein ingestion on athletic ability in healthy individuals were considered. A systematic search of six databases yielded 2152 studies, which were screened using the Covidence systematic review tool. Thirty-one studies were included for meta-analysis after independent selection, data extraction, and risk of bias assessment by two reviewers. The meta-analysis employed a Bayesian approach using the Markov chain Monte Carlo (MCMC) method through a random-effects model. The results demonstrated that plant-based protein supplements provided greater benefits for athletic performance in healthy individuals compared to the no- or low-protein ingestion group [µ(SMD): 0.281, 95% CI: 0.159 to 0.412; heterogeneity τ: 0.18, 95% CI: 0.017 to 0.362]. However, when compared to other types of protein, plant-based protein ingestion was less effective in enhancing athletic ability [µ(SMD): -0.119, 95% CI: -0.209 to -0.028; heterogeneity τ: 0.076, 95% CI: 0.003 to 0.192]. A subgroup analysis indicated significant improvements in muscle strength and endurance performance in both young and older individuals consuming plant-based protein compared to those with no- or low-protein ingestion. Nonetheless, other protein types showed greater benefits in muscle strength compared to plant-based protein [µ(SMD): -0.133, 95% CI: -0.235 to -0.034; heterogeneity τ: 0.086, 95% CI: 0.004 to 0.214]. In conclusion, while plant-based protein ingestion demonstrates superior efficacy compared to low- or no-protein ingestion, it is not as effective as other protein types such as whey, beef, or milk protein in enhancing athletic performance in healthy individuals. Registration: Registered at the International Prospective Register of Systematic Reviews (PROSPERO) (identification code CRD42024555804).

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Landfill leachate treatment plants (LLTPs) harbor a vast reservoir of uncultured microbes, yet limited studies have systematically unraveled their functional potentials within LLTPs. Combining 36 metagenomic and 18 metatranscriptomic datasets from a full-scale LLTP, we unveiled a double-edged sword role of unknown species in leachate biotreatment and environmental implication. We identified 655 species-level genome bins (SGBs) spanning 47 bacterial and 3 archaeal phyla, with 75.9 % unassigned to any known species. Over 90 % of up-regulated functional genes in biotreatment units, compared to the leachate influent, were carried by unknown species and actively participated in carbon, nitrogen, and sulfur cycles. Approximately 79 % of the 37,366 carbohydrate active enzymes (CAZymes), with ∼90 % novelty and high expression, were encoded by unknown species, exhibiting great potential in biodegrading carbohydrate compounds linked to human meat-rich diets. Unknown species offered a valuable genetic resource of thousands of versatile, abundant, and actively expressed metabolic gene clusters (MGCs) and biosynthetic gene clusters (BGCs) for enhancing leachate treatment. However, unknown species may contribute to the emission of hazardous N2O/H2S and represented significant reservoirs for antibiotic-resistant pathogens that posed environmental safety risks. This study highlighted the significance of considering both positive and adverse effects of LLTP microbes to optimize LLTP performance.

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Background: Ethylene oxide (EO) is a common organic compound associated with many adverse health outcomes. However, studies exploring the association between EO exposure and cognitive function are limited. Objective: This study aims to examine this relationship between EO exposure and cognition in older adults. Methods: This study enrolled 438 older adults from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 cycle. EO exposure was quantified by the measurements of blood hemoglobin adducts of ethylene oxide (HbEO) concentrations. Cognitive function was measured by the Consortium to Establish a Registry for Alzheimer's Disease battery (CREAD), the Animal Fluency test (AFT), and the Digit Symbol Substitution Test (DSST). Linear regression model, generalized additive model, and smooth curve fitting were applied to examine the linear and nonlinear relationship between EO exposure and cognitive function. We used a two-piecewise linear regression model to detect the threshold effect of EO exposure on cognitive function. Results: Participants with higher HbEO levels had lower AFT and DSST scores than those with lower HbEO levels. After adjusting for all confounding factors, log2-transformed HbEO levels were negatively associated with AFT score. The smooth curve fitting demonstrated the nonlinear relationship between EO exposure and DSST scores. When log-2 transformed HbEO levels >4.34 pmol/g Hb, EO exposure was negatively associated with DSST score. Conclusions: This study indicated that high levels of HbEO were associated with cognitive decline in US older adults. Future cohort studies are needed to verify our findings.

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Mobile colistin resistance (mcr) genes are pivotal contributors to last-line of antimicrobial resistance in human infections. Shewanella, historically recognized as a natural environmental bacterium with metal reduction capabilities, recently has been observed in clinical settings. However, limited knowledge has been explored on genetic differences between strains from non-clinical and clinical strains. In this study, we conducted the whole genome sequencing on six Arctic strains, illustrated the phylogenetic relationships on published 393 Shewanella strains that categorized the genus into four lineages (L1 to L4). Over 86.4% of clinical strain group (CG) strains belonged to L1 and L4, carrying mcr-4 genes and a complete metal-reduction pathways gene cluster. Remarkably, a novel Arctic Shewanella strain in L3, exhibits similar genetic characteristics with CG strains that carried both mcr-4 genes and a complete metal reduction pathway gene cluster. It raised concerns about the transmission ability from environment to clinic setting causing in the potential infections, and emphasized the need for monitoring the emerging strains with human infections.

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Facial morphology, a complex trait influenced by genetics, holds great significance in evolutionary research. However, due to limited fossil evidence, the facial characteristics of Neanderthals and Denisovans have remained largely unknown. In this study, we conducted a large-scale multi-ethnic meta-analysis of the genome-wide association study (GWAS), including 9674 East Asians and 10,115 Europeans, quantitatively assessing 78 facial traits using 3D facial images. We identified 71 genomic loci associated with facial features, including 21 novel loci. We developed a facial polygenic score (FPS) that enables the prediction of facial features based on genetic information. Interestingly, the distribution of FPSs among populations from diverse continental groups exhibited relevant correlations with observed facial features. Furthermore, we applied the FPS to predict the facial traits of seven Neanderthals and one Denisovan using ancient DNA and aligned predictions with the fossil records. Our results suggested that Neanderthals and Denisovans likely shared similar facial features, such as a wider but shorter nose and a wider endocanthion distance. The decreased mouth width was characterized specifically in Denisovans. The integration of genomic data and facial trait analysis provides valuable insights into the evolutionary history and adaptive changes in human facial morphology.

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The doping of porous carbon materials with nitrogen is an effective approach to enhance the electrochemical performance of electrode materials. In this study, nitrogen-doped porous carbon derived from peanut shells was prepared as an electrode for supercapacitors. Melamine, urea, urea phosphate, and ammonium dihydrogen phosphate were employed as different nitrogen dopants. The optimized electrode material PA-1-1 prepared by peanut shells, with ammonium dihydrogen phosphate as a nitrogen dopant, exhibited a N content of 3.11% and a specific surface area of 602.7 m2/g. In 6 M KOH, the PA-1-1 electrode delivered a high specific capacitance of 208.3 F/g at a current density of 1 A/g. Furthermore, the PA-1-1 electrode demonstrated an excellent rate performance with a specific capacitance of 170.0 F/g (retention rate of 81.6%) maintained at 20 A/g. It delivered a capacitance of PA-1-1 with a specific capacitance retention of 98.8% at 20 A/g after 5000 cycles, indicating excellent cycling stability. The PA-1-1//PA-1-1 symmetric supercapacitor exhibited an energy density of 17.7 Wh/kg at a power density of 2467.0 W/kg. This work not only presents attractive N-doped porous carbon materials for supercapacitors but also offers a novel insight into the rational design of biochar carbon derived from waste peelings.

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BACKGROUND: Natural compounds can positively impact health, and various studies suggest that they regulate glucose‒lipid metabolism by influencing short-chain fatty acids (SCFAs). This metabolism is key to maintaining energy balance and normal physiological functions in the body. This review explores how SCFAs regulate glucose and lipid metabolism and the natural compounds that can modulate these processes through SCFAs. This provides a healthier approach to treating glucose and lipid metabolism disorders in the future. METHODS: This article reviews relevant literature on SCFAs and glycolipid metabolism from PubMed and the Web of Science Core Collection (WoSCC). It also highlights a range of natural compounds, including polysaccharides, anthocyanins, quercetins, resveratrols, carotenoids, and betaines, that can regulate glycolipid metabolism through modulation of the SCFA pathway. RESULTS: Natural compounds enrich SCFA-producing bacteria, inhibit harmful bacteria, and regulate operational taxonomic unit (OTU) abundance and the intestinal transport rate in the gut microbiota to affect SCFA content in the intestine. However, most studies have been conducted in animals, lack clinical trials, and involve fewer natural compounds that target SCFAs. More research is needed to support the conclusions and to develop healthier interventions. CONCLUSIONS: SCFAs are crucial for human health and are produced mainly by the gut microbiota via dietary fiber fermentation. Eating foods rich in natural compounds, including fruits, vegetables, tea, and coarse fiber foods, can hinder harmful intestinal bacterial growth and promote beneficial bacterial proliferation, thus increasing SCFA levels and regulating glucose and lipid metabolism. By investigating how these compounds impact glycolipid metabolism via the SCFA pathway, novel insights and directions for treating glucolipid metabolism disorders can be provided.

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Hepatitis E virus (HEV), responsible for widespread viral hepatitis, infects approximately 2.3 billion individuals globally, with a significant mortality burden in Asia. The virus, primarily transmitted through contaminated water and undercooked meat, is often underdiagnosed, particularly in immunocompromised patients. Current HEV treatments, while effective, are limited by adverse effects, necessitating research into safer alternatives. Moreover, HEV's extrahepatic manifestations, impacting the nervous and renal systems, remain poorly understood. This study underscores the imperative for enhanced HEV research, improved diagnostic methods, and more effective treatments, coupled with increased public health awareness and preventive strategies.

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BACKGROUND: Human health is a complex, dynamic concept encompassing a spectrum of states influenced by genetic, environmental, physiological, and psychological factors. Traditional Chinese Medicine categorizes health into nine body constitutional types, each reflecting unique balances or imbalances in vital energies, influencing physical, mental, and emotional states. Advances in machine learning models offer promising avenues for diagnosing conditions like Alzheimer's, dementia, and respiratory diseases by analyzing speech patterns, enabling complementary non-invasive disease diagnosis. The study aims to use speech audio to identify subhealth populations characterized by unbalanced constitution types. METHODS: Participants, aged 18-45, were selected from the Acoustic Study of Health. Audio recordings were collected using ATR2500X-USB microphones and Praat software. Exclusion criteria included recent illness, dental issues, and specific medical histories. The audio data were preprocessed to Mel-frequency cepstral coefficients (MFCCs) for model training. Three deep learning models-1-Dimensional Convolution Network (Conv1D), 2-Dimensional Convolution Network (Conv2D), and Long Short-Term Memory (LSTM)-were implemented using Python to classify health status. Saliency maps were generated to provide model explainability. RESULTS: The study used 1,378 recordings from balanced (healthy) and 1,413 from unbalanced (subhealth) types. The Conv1D model achieved a training accuracy of 91.91% and validation accuracy of 84.19%. The Conv2D model had 96.19% training accuracy and 84.93% validation accuracy. The LSTM model showed 92.79% training accuracy and 87.13% validation accuracy, with early signs of overfitting. AUC scores were 0.92 and 0.94 (Conv1D), 0.99 (Conv2D), and 0.97 (LSTM). All models demonstrated robust performance, with Conv2D excelling in discrimination accuracy. CONCLUSIONS: The deep learning classification of human speech audio for health status using body constitution types showed promising results with Conv1D, Conv2D, and LSTM models. Analysis of ROC curves, training accuracy, and validation accuracy showed all models robustly distinguished between balanced and unbalanced constitution types. Conv2D excelled with good accuracy, while Conv1D and LSTM also performed well, affirming their reliability. The study integrates constitution theory and deep learning technologies to classify subhealth populations using noninvasive approach, thereby promoting personalized medicine and early intervention strategies.