Crenobacter oryzisoli sp. nov., a novel phosphate-solubilizing bacterium isolated from the paddy soil.

Two Gram-staining-negative, facultative anaerobic, rod-shaped and phosphate-solubilizing strains designated SG2303T and SG2305, were isolated from paddy soil in China. Phylogenetic analysis based on 16 S rRNA gene sequences indicated that SG2303T and SG2305 represented a member of the genus Crenobacter within the family Neisseriaceae of the phylum Pseudomonadota. Strain SG2303T displayed higher 16 S rRNA gene sequence similarities with members of the genus Crenobacter ranging from 93.5 to 94.0%. Strains C. luteus YIM 78141T and C. cavernae K1W11S-77T were closest related to the isolated strains and were considered as type strains. Growth of strain SG2303T occurred at 10-55 °C (optimum 37 °C), pH 5.0-9.0 (optimum pH 6.0-7.0) and 0-1% (w/v) NaCl (optimum 0%). The average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values between strain SG2303T and its closely related taxa were 76.1-78.2% and 20.5-22.1%, respectively. The genomic DNA G + C content was 62.2%. The quinone of strain SG2303T was Q-8. The major fatty acids (> 10%) of strain SG2303T were C16:0 (30.6%), summed feature 3 (C16:1ω7c and/or C16:1ω6c) (26.0%) and C12:0 3OH (12.1%). The polar lipids were phosphatidylglycerol (PG), diphosphatidylglycerol (DPG), phosphatidylethanolamine (PE), phospholipids (PL), glycolipid (GL) and unidentified lipids (UL). Based on the results of the phylogenetic, physiological, biochemical, and morphological analysis, strain SG2303T is recognized as a novel species of the genus Crenobacter, for which the name Crenobacter oryzisoli sp. nov. is proposed. The type strain is SG2303T (= GDMCC 1.3970T = JCM 36468T). In addition, SG2303T was also able of phosphorus solubilization and promoting the growth of rice seeds. Strain SG2303T exhibited a relatively high dissolvable phosphorus content of 2.52 µg·mL- 1.

VISTA: A promising target for overcoming immune evasion in gynecologic cancers.

Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment but has shown limited efficacy in gynecologic cancers. VISTA (V-domain Ig suppressor of T-cell activation), a member of the B7 family, is emerging as another checkpoint that regulates the anti-tumor immune responses within the tumor microenvironment. This paper reviews the structure, expression, and mechanism of action of VISTA. Furthermore, it highlights recent advances in VISTA-blocking therapies and their potential in improving outcomes for patients with gynecologic cancers. By understanding the role of VISTA in mediating the immune evasion of gynecologic tumors, we can develop more effective combinatory treatment strategies that could overcome resistance to current ICB therapies.

Identification of key genes and pathways in duck fatty liver syndrome using gene set enrichment analysis.

High-laying ducks are often fed high-energy, nutritious feeds to maintain high productivity, which predisposes them to lipid metabolism disorders and the development of fatty liver syndrome (FLS), which seriously affects production performance and has a substantial economic impact on the poultry industry. Therefore, it is necessary to elucidate the mechanisms underlying the development of fatty liver syndrome. In this study, seven Shan Partridge ducks, each with fatty liver syndrome and normal laying ducks, were selected, and Hematoxylin Eosin staining (HE staining), Masson staining, and transcriptome sequencing were performed on liver tissue. In addition to exploring key genes and pathways using conventional analysis methods, we constructed the first Kyoto Encyclopedia of Genes and Genomes (KEGG) database-based predefined gene set containing 12,764 pathways and 16,836 genes and further performed gene set enrichment analysis (GSEA) on the liver transcriptome data. Finally, key nodes and biological processes were identified via the protein-protein interaction (PPI) network. The results showed that the liver in the FL group exhibited steatosis and fibrosis, and a total of 3,663 genes with upregulated expression versus 2,296 downregulated genes were screened by conventional analysis. GSEA analysis and PPI network analysis revealed that the liver in the FL group exhibited disruption of the mitochondrial electron transport chain, leading to decreased oxidative phosphorylation and the secretion of excessive proinflammatory factors amid the continuous accumulation of lipids. Under continuous chronic inflammation, cell cycle arrest triggers apoptosis, while fibrosis becomes more severe, and procarcinogenic genes are activated, leading to the continuous development and deterioration of the liver. In conclusion, the predefined gene set constructed in this study can be used for GSEA, and the identified hub genes provide useful reference data and a solid foundation for the study of the genetic regulatory mechanism of fatty liver syndrome in ducks.

Evolving treatment paradigms for platinum-resistant ovarian cancer: An update narrative review.

Platinum-resistant ovarian cancer (PROC) refers to disease progression within 6 months after the completion of platinum-based chemotherapy. Historically, treatment options for PROC were limited with a poor prognosis and non-platinum single agent plus bevacizumab has been the mainstay of treatment. Fortunately, there have been notable advancements in recent years, leading to an advance in treatment paradigms for this challenging disease. Various combinations of chemotherapy, targeted agents such as poly (ADP-ribose) polymerase (PARP) inhibitors, and immunotherapy are being explored for an improved treatment outcome. Antibody-drug conjugates targeting folate receptor alpha, which deliver a cytotoxic payload directly to cancer cells, have emerged as a promising therapeutic approach for PROC. WEE1 inhibitors, such as adavosertib, function by inhibiting the WEE1 kinase activity, leading to premature entry of a cell into mitosis phase and thus increased DNA damage. It has been observed that cancer cells with TP53 mutations may be more sensitive to WEE1 inhibitors. Biomarker testing such as analysis of the expression level of folate receptor alpha or mutation in TP53 may be applicable for identifying patients who are more likely to respond to the specific therapy, enabling a more personalized treatment approach. This overview summarizes key clinical findings on the efficacy and safety of theses novel biomarker-driven therapeutic approaches.

Identification of DNase I hypersensitive sites in the human genome by multiple sequence descriptors.

DNase I hypersensitive sites (DHSs) are chromatin regions highly sensitive to DNase I enzymes. Studying DHSs is crucial for understanding complex transcriptional regulation mechanisms and localizing cis-regulatory elements (CREs). Numerous studies have indicated that disease-related loci are often enriched in DHSs regions, underscoring the importance of identifying DHSs. Although wet experiments exist for DHSs identification, they are often labor-intensive. Therefore, there is a strong need to develop computational methods for this purpose. In this study, we used experimental data to construct a benchmark dataset. Seven feature extraction methods were employed to capture information about human DHSs. The F-score was applied to filter the features. By comparing the prediction performance of various classification algorithms through five-fold cross-validation, random forest was proposed to perform the final model construction. The model could produce an overall prediction accuracy of 0.859 with an AUC value of 0.837. We hope that this model can assist scholars conducting DNase research in identifying these sites.

Chromosome-level genome assembly of Helwingia omeiensis: the first genome in the family Helwingiaceae.

Helwingia, a shrub of the monotypic cosmopolitan family Helwingiaceae, is distinguished by its inflorescence, in which flowers are borne on the midrib of the leaf-a trait not commonly observed in related plant families. Previous studies have investigated the development of this unusual structure using comparative anatomical methods. However, the scarcity of genomic data has hindered our understanding of the origins and evolutionary history of this uncommon trait at the molecular level. Here, we report the first high-quality genome of the family Helwingiaceae. Assembled using HiFi sequencing and Hi-C technologies, the genome of H. omeiensis is anchored to 19 chromosomes, with a total length of 2.75 Gb and a contig N50 length of 6.78 Mb. The BUSCO completeness score of the assembled genome was 98.2%. 53,951 genes were identified, of which 99.7% were annotated in at least one protein database. The high-quality reference genome of H. omeiensis provides an essential genetic resource and sheds light on the phylogeny and evolution of specific traits in the family Helwingiaceae.

Single Atom Ag Bonding Between PF3T Nanocluster and TiO2 Leads the Ultra-Stable Visible-Light-Driven Photocatalytic H2 Production.

Atomic Ag cluster bonding is employed to reinforce the interface between PF3T nano-cluster and TiO2 nanoparticle. With an optimized Ag loading (Ag/TiO2 = 0.5 wt%), the Ag atoms will uniformly disperse on TiO2 thus generating a high density of intermediate states in the band gap to form the electron channel between the terthiophene group of PF3T and the TiO2 in the hybrid composite (denoted as T@Ag05-P). The former expands the photon absorption band width and the latter facilitates the core-hole splitting by injecting the photon excited electron (from the excitons in PF3T) into the conduction band (CB) of TiO2. These characteristics enable the high efficiency of H2 production to 16 580 µmol h-1 g-1 and photocatalysis stability without degradation under visible light exposure for 96 h. Compared to that of hybrid material without Ag bonding (TiO2@PF3T), the H2 production yield and stability are improved by 4.1 and 18.2-fold which shows the best performance among existing materials in similar component combination and interfacial reinforcement. The unique bonding method offers a new prospect to accelerate the development of photocatalytic hydrogen production technologies.

Discovery of Fluorescent Naturally-occurring Inhibitor of SARS-CoV-2 Main Protease By AIE Fluorescent Probe.

Target-based high-throughput screening (HTS) is an efficient way to identify potent drugs. However, the accuracy of HTS could be affected by Pan-Assay Interference Compounds (PAINS). One reason for the generation of PAINS is that the inherent photophysical property of screened compounds could interfere with typically used assay signals including absorption and fluorescence. Our previous studies indicate that the fluorescent probe based on the fluorophore with characteristics of aggregation-induced emission (AIE) could provide high accuracy of HTS, especially for the fluorescent natural products. Herein, we report an AIE-based fluorescent probe for the main protease (Mpro) of SARS-CoV-2. We designed and synthesized an AIE fluorescent probe ZLHG5, which has a site that can be specifically cleaved by Mpro to produce a light-up fluorescence. Thanks to the large Stokes shift of AIE fluorophore (~300 nm), the probe could be effectively used for HTS of Mpro inhibitors. After screening a library of fluorescent natural products with ZLHG5, we obtained two coumarin-originated natural compounds with potent inhibitory activity towards Mpro protease. This study provides both useful fluorescent HTS probe and potent inhibitors for Mpro protease.

Quantitative and qualitative detection of target heavy metals using anti-interference colorimetric sensor Array combined with near-infrared spectroscopy.

An anti-interference colorimetric sensor array (CSA) technique was developed for the qualitative and quantitative detection of target heavy metals in corn oil. This method involves a binding mechanism that triggers changes in atomic energy levels and visible color changes. A custom-built olfactory visualization device was employed to gather spectral data, revealing distinct CSA color difference patterns. Subsequently, three pattern recognition algorithms were used to create an identification model for the target heavy metals. The results showed that the ACO-KNN (Ant Colony Optimization-K-Nearest Neighbor) model outperformed the other models, achieving accuracy rates of 90.28% and 89.58% for the calibration and prediction sets, respectively. The ACO-PLS (Partial Least Square) model was more stable with the lowest root mean square error of prediction (RMSEP), which were 0.1730 and 0.1180, respectively. The limit of detection (LOD) and quantification (LOQ) of Pb and Hg were (0.3, 0.6, 1.1 and 2.2) x 10-3 mg/L, respectively.

Identification of RNA­dependent liquid­liquid phase separation proteins using an artificial intelligence strategy.

RNA-dependent liquid-liquid phase separation (LLPS) proteins play critical roles in cellular processes such as stress granule formation, DNA repair, RNA metabolism, germ cell development, and protein translation regulation. The abnormal behavior of these proteins is associated with various diseases, particularly neurodegenerative disorders like amyotrophic lateral sclerosis and frontotemporal dementia, making their identification crucial. However, conventional biochemistry-based methods for identifying these proteins are time-consuming and costly. Addressing this challenge, our study developed a robust computational model for their identification. We constructed a comprehensive dataset containing 137 RNA-dependent and 606 non-RNA-dependent LLPS protein sequences, which were then encoded using amino acid composition, composition of K-spaced amino acid pairs, Geary autocorrelation, and conjoined triad methods. Through a combination of correlation analysis, mutual information scoring, and incremental feature selection, we identified an optimal feature subset. This subset was used to train a random forest model, which achieved an accuracy of 90% when tested against an independent dataset. This study demonstrates the potential of computational methods as efficient alternatives for the identification of RNA-dependent LLPS proteins. To enhance the accessibility of the model, a user-centric web server has been established and can be accessed via the link: http://rpp.lin-group.cn.

Targeting Rab7-Rilp Mediated Microlipophagy Alleviates Lipid Toxicity in Diabetic Cardiomyopathy.

Diabetic cardiomyopathy (DbCM) is characterized by diastolic dysfunction, which progresses into heart failure and aberrant electrophysiology in diabetic patients. Dyslipidemia in type 2 diabetic patients leads to the accumulation of lipid droplets (LDs) in cardiomyocytes and results in lipid toxicity which has been suggested to drive DbCM. It is aimed to explore potential pathways that may boost LDs degradation in DbCM and restore cardiac function. LDs accumulation resulted in an increase in lipid toxicity in DbCM hearts is confirmed. Microlipophagy pathway, rather than traditional macrolipophagy, is activated in DbCM hearts. RNA-Seq data and Rab7-CKO mice implicate that Rab7 is a major modulator of the microlipophagy pathway. Mechanistically, Rab7 is phosphorylated at Tyrosine 183, which allows the recruitment of Rab-interacting lysosome protein (Rilp) to proceed LDs degradation by lysosome. Treating DbCM mice with Rab7 activator ML-098 enhanced Rilp level and rescued the observed cardiac dysfunction. Overall, Rab7-Rilp-mediated microlipophagy may be a promising target in the treatment of lipid toxicity in DbCM is suggested.

How big five personality traits influence information sharing on social media: A meta analysis.

Research interest in information sharing behavior on social media has significantly increased over the past decade. However, empirical studies on the relationship between Big Five personality traits and information sharing behavior have yielded contradictory conclusions. We aimed to investigate how Big Five personality influences information sharing behavior on social media. This meta-analysis systematically reviewed high-quality studies indexed by web of science and CNKI from the past decade (n = 27, with 31969 samples) and performed a meta-analysis to examine the association between Big Five personality traits and information sharing behavior. The literature search was performed in September 2023. The meta-analysis results showed that extraversion (ß = 0.05**) had a positive relationship with information sharing behavior on social media. Agreeableness (ß = -0.06**), conscientiousness (ß = -0.03**), and neuroticism (ß = -0.03**) had negative relationships with information sharing behavior on social media. However, the relationship between openness and information sharing behavior was not clearly observed due to insufficient research. The meta-analysis results are made available to the scientific community to enhance research, comprehension, and utilization of social media.

Exploring Factors Affecting Acceptance of Fecal Microbiota Transplantation for Patients with Recurrent Urinary Tract Infections: a Descriptive Qualitative Study.

Purpose: Patients with recurrent urinary tract infections face complex management challenges. Fecal microbiota transplantation is a superior treatment for chronic infectious diseases, but limited patient knowledge affects treatment decisions. This study aims to identify factors associated with hesitancy towards fecal microbiota transplantation among patients with recurrent urinary tract infections, to help physicians and nurses in providing accurate and useful information to patients. Patients and Methods: A descriptive qualitative approach was employed, utilizing semi-structured interviews conducted with patients experiencing recurrent urinary tract infections who expressed hesitancy towards fecal microbiota transplantation. The interviews took place between September 2021 and December 2022. Thematic analysis was conducted on the semi-structured interviews to identify perceived facilitators and barriers associated with fecal microbiota transplantation. Results: The analysis included interviews with thirty adult female patients with recurrent urinary tract infections. Four facilitators influencing patients' decision-making regarding fecal microbiota transplantation were identified: (1) the motivating role of hope and expectations for active patient participation; (2) the influence of healthcare providers, as well as family members and friends on patients' decisions to pursue fecal microbiota transplantation; (3) the patients' perception of fecal microbiota transplantation as a low-risk treatment option; and (4) the dedication to the advancement of medical treatments. In contrast, two primary barriers to accepting fecal microbiota transplantation were identified: (1) that conventional treatment controls disease activity, while fecal microbiota transplantation effects remain uncertain; and (2) that safety concerns surrounding fecal microbiota transplantation. Conclusion: Comprehensive information about fecal microbiota transplantation, including donor selection, sample processing, the procedure, and potential discomfort, is essential for patients and families to make informed treatment decisions. Registration: CHiCTR2100048970.

Optical, Structural, and Synchrotron X-ray Absorption Studies for GaN Thin Films Grown on Si by Molecular Beam Epitaxy.

GaN on Si plays an important role in the integration and promotion of GaN-based wide-gap materials with Si-based integrated circuits (IC) technology. A series of GaN film materials were grown on Si (111) substrate using a unique plasma assistant molecular beam epitaxy (PA-MBE) technology and investigated using multiple characterization techniques of Nomarski microscopy (NM), high-resolution X-ray diffraction (HR-XRD), variable angular spectroscopic ellipsometry (VASE), Raman scattering, photoluminescence (PL), and synchrotron radiation (SR) near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. NM confirmed crack-free wurtzite (w-) GaN thin films in a large range of 180-1500 nm. XRD identified the w- single crystalline structure for these GaN films with the orientation along the c-axis in the normal growth direction. An optimized 700 °C growth temperature, plus other corresponding parameters, was obtained for the PA-MBE growth of GaN on Si, exhibiting strong PL emission, narrow/strong Raman phonon modes, XRD w-GaN peaks, and high crystalline perfection. VASE studies identified this set of MBE-grown GaN/Si as having very low Urbach energy of about 18 meV. UV (325 nm)-excited Raman spectra of GaN/Si samples exhibited the GaN E2(low) and E2(high) phonon modes clearly without Raman features from the Si substrate, overcoming the difficulties from visible (532 nm) Raman measurements with strong Si Raman features overwhelming the GaN signals. The combined UV excitation Raman-PL spectra revealed multiple LO phonons spread over the GaN fundamental band edge emission PL band due to the outgoing resonance effect. Calculation of the UV Raman spectra determined the carrier concentrations with excellent values. Angular-dependent NEXAFS on Ga K-edge revealed the significant anisotropy of the conduction band of w-GaN and identified the NEXAFS resonances corresponding to different final states in the hexagonal GaN films on Si. Comparative GaN material properties are investigated in depth.

Diagnosis and management of inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic and relapsing immune-mediated disease of the gastrointestinal tract with a gradually increasing global incidence and prevalence. A prolonged course of IBD leads to a decline in patient quality of life and the creation of a substantial economic burden on society. Owing to the lack of specific diagnostic markers, the diagnosis of IBD still needs a gold standard based on a combination of clinical manifestations, imaging, laboratory, and endoscopic results. Accordingly, the current goals of IBD treatment are to alleviate clinical symptoms and reduce recurrence rates. Therefore, it is imperative to develop a standard set of procedures to diagnose and treat IBD. In this review, we summarize prominent and emerging studies, outline classical and contemporary approaches to diagnosing and managing IBD, and integrate multiple guidelines. Furthermore, we propose the possibility of establishing an early and comprehensive diagnostic workflow and personalized management strategy in the future. We aim to enhance the quality and standardization of diagnostic and treatment procedures for IBD.

The role of small dense LDL-C/large buoyant LDL-C ratio as an independent risk factor in patients with type 2 diabetes mellitus and metabolic syndrome

Dyslipidemia plays a key role in metabolic syndrome (MS), intricately linked to type 2 diabetes mellitus (T2DM). This study aimed to investigate the differences in low-density lipoprotein cholesterol (LDL-C) subfraction levels between T2DM and T2DM with MS, and identify the risk factors associated with the disease. A total of 246 individuals diagnosed with T2DM, including 144 T2DM patients with MS, and 147 healthy subjects were recruited. All participants underwent a comprehensive clinical evaluation. Lipoprotein subfraction analysis was performed using the Lipoprint LDL system. Multivariate logistic regression analysis revealed that several lipid markers, including triglyceride (TG), LDL-C, large buoyant LDL-C (lbLDL-C), small dense LDL-C (sdLDL-C), LDLC2-5, and sdLDL-C/lbLDL-C ratio, were identified as independent risk factors for T2DM. Additionally, TG, sdLDL-C, LDLC-4, LDLC-5, and sdLDL-C/lbLDL-C ratio were found to be independent risk factors for T2DM with MS. Furthermore, the results of the receiver operating characteristic (ROC) curves demonstrated that sdLDL-C, LDLC-4, LDLC-3, and sdLDL-C/lbLDL-C ratio exhibited excellent predictive performance for the risk of T2DM (AUC > 0.9). The sdLDL-C/lbLDL-C ratio emerges as a shared independent risk factor for T2DM and MS complications. Furthermore, sdLDL-C/lbLDL-C ratio, along with LDL-4 and LDL-3, exhibits noteworthy predictive capabilities for T2DM.

The mediating role of sleep disturbance in the relationship between depression and cardiovascular disease.

Background: Studies suggest that both depression and disrupted sleep disturbance are linked to cardiovascular disease (CVD). However, the precise role of sleep disturbance in the connection between depression and CVD is poorly understood. Therefore, we sought to examine the associations among these factors and further explore the mediating role of sleep disturbance in the association between depression and CVD. Methods: This study included data from 29,831 adults (≥20 years old). Multifactorial logistic regression analyses were conducted to examine the relationships among depression, sleep disturbance, and CVD. Additionally, bootstrap tests were used to investigate whether the association between depression and CVD was mediated by sleep disturbance. Results: Our research showed that individuals who experienced depression or sleep disturbance had a notably greater likelihood of developing CVD than those who did not have these issues (depression: OR: 2.21, 95% CI=1.96-2.49; sleep disturbance: OR: 1.74, 95% CI=1.6-1.9). Even after adjusting for potential confounders, depression was still positively associated with the risk of sleep disturbance (OR: 4.07, 95% CI=3.73-4.44). Furthermore, sleep disturbance significantly mediated the association between depression and CVD, with a mediating effect of 18.1%. Conclusion: Our study demonstrated that depression, sleep disturbance, and CVD are interrelated. The increased risk of CVD among patients with depression may be attributed to the mediating role of sleep disturbance. This finding underscores the importance of interventions focused on sleep disturbances as a means to address the connection between depression and CVD.

The microbiota in patients with interstitial cystitis/bladder pain syndrome: a systematic review.

OBJECTIVE: To comprehensively review and critically assess the literature on microbiota differences between patients with interstitial cystitis (IC)/bladder pain syndrome (BPS) and normal controls and to provide clinical practice guidelines. MATERIALS AND METHODS: In this systematic review, we evaluated previous research on microbiota disparities between IC/BPS and normal controls, as well as distinctions among IC/BPS subgroups. A comprehensive literature search was conducted across PubMed/MEDLINE, EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials. Relevant studies were shortlisted based on predetermined inclusion and exclusion criteria, followed by quality assessment. The primary focus was identifying specific taxonomic variations among these cohorts. RESULTS: A total of 12 studies met the selection criteria. Discrepancies were adjudicated by a third reviewer. The Newcastle-Ottawa Scale was used to assess study quality. Predominantly, the studies focused on disparities in urine microbiota between IC/BPS patients and normal controls, with one study examining gut microbiota differences between the groups, and two studies exploring vaginal microbiota distinctions. Unfortunately, analyses of discrepancies in other microbiota were limited. Our findings revealed evidence of distinct bacterial abundance variations, particularly involving Lactobacillus, alongside variations in specific metabolites among IC/BPS patients compared to controls. CONCLUSIONS: Currently, there is evidence suggesting significant variations in the diversity and species composition of the urinary microbiota between individuals diagnosed with IC/BPS and control groups. In the foreseeable future, urologists should consider urine microbiota dysbiosis as a potential aetiology for IC, with potential clinical implications for diagnosis and treatment.

Online System for Monitoring the Degree of Fermentation of Oolong Tea Using Integrated Visible-Near-Infrared Spectroscopy and Image-Processing Technologies.

During the fermentation process of Oolong tea, significant changes occur in both its external characteristics and its internal components. This study aims to determine the fermentation degree of Oolong tea using visible-near-infrared spectroscopy (vis-VIS-NIR) and image processing. The preprocessed vis-VIS-NIR spectral data are fused with image features after sequential projection algorithm (SPA) feature selection. Subsequently, traditional machine learning and deep learning classification models are compared, with the support vector machine (SVM) and convolutional neural network (CNN) models yielding the highest prediction rates among traditional machine learning models and deep learning models with 97.14% and 95.15% in the prediction set, respectively. The results indicate that VIS-NIR combined with image processing possesses the capability for rapid non-destructive online determination of the fermentation degree of Oolong tea. Additionally, the predictive rate of traditional machine learning models exceeds that of deep learning models in this study. This study provides a theoretical basis for the fermentation of Oolong tea.

Humidity-Responsive Liquid Metal Core-Shell Materials for Enduring Heat Retention and Insulation.

High humidity in extremely cold weather can undermine the insulation capability of the clothing, imposing serious life risks. Current clothing insulation technologies have inherent deficiencies in terms of insulation efficiency and humidity adaptability. Here, we report humidity-stimulated self-heating clothing using aluminum core-liquid metal shell microparticles (Al@LM-MPs) as the filler. Al@LM-MPs exhibit a distinctive capability to react to water molecules in the air to generate heat, exhibiting remarkable sensitivity across a broad temperature range. This ability leads to the creation of intelligent clothing capable of autonomously responding to extreme cold and wet weather conditions, providing both enduring heat retention and insulation capabilities. This article is protected by copyright. All rights reserved.