On using an aerosol thermodynamic model to calculate aerosol acidity of coarse particles.

Thermodynamic modeling is still the most widely used method to characterize aerosol acidity, a critical physicochemical property of atmospheric aerosols. However, it remains unclear whether gas-aerosol partitioning should be incorporated when thermodynamic models are employed to estimate the acidity of coarse particles. In this work, field measurements were conducted at a coastal city in northern China across three seasons, and covered wide ranges of temperature, relative humidity and NH3 concentrations. We examined the performance of different modes of ISORROPIA-II (a widely used aerosol thermodynamic model) in estimating aerosol acidity of coarse and fine particles. The M0 mode, which incorporates gas-phase data and runs the model in the forward mode, provided reasonable estimation of aerosol acidity for coarse and fine particles. Compared to M0, the M1 mode, which runs the model in the forward mode but does not include gas-phase data, may capture the general trend of aerosol acidity but underestimates pH for both coarse and fine particles; M2, which runs the model in the reverse mode, results in large errors in estimated aerosol pH for both coarse and fine particles and should not be used for aerosol acidity calculations. However, M1 significantly underestimates liquid water contents for both fine and coarse particles, while M2 provides reliable estimation of liquid water contents. In summary, our work highlights the importance of incorporating gas-aerosol partitioning when estimating coarse particle acidity, and thus may help improve our understanding of acidity of coarse particles.

Research on the Behavior Recognition of Beef Cattle Based on the Improved Lightweight CBR-YOLO Model Based on YOLOv8 in Multi-Scene Weather.

In modern animal husbandry, intelligent digital farming has become the key to improve production efficiency. This paper introduces a model based on improved YOLOv8, Cattle Behavior Recognition-YOLO (CBR-YOLO), which aims to accurately identify the behavior of cattle. We not only generate a variety of weather conditions, but also introduce multi-target detection technology to achieve comprehensive monitoring of cattle and their status. We introduce Inner-MPDIoU Loss and we have innovatively designed the Multi-Convolutional Focused Pyramid module to explore and learn in depth the detailed features of cattle in different states. Meanwhile, the Lightweight Multi-Scale Feature Fusion Detection Head module is proposed to take advantage of deep convolution, achieving a lightweight network architecture and effectively reducing redundant information. Experimental results prove that our method achieves an average accuracy of 90.2% with a reduction of 3.9 G floating-point numbers, an increase of 7.4%, significantly better than 12 kinds of SOTA object detection models. By deploying our approach on monitoring computers on farms, we expect to advance the development of automated cattle monitoring systems to improve animal welfare and farm management.

GFI-YOLOv8: Sika Deer Posture Recognition Target Detection Method Based on YOLOv8.

As the sika deer breeding industry flourishes on a large scale, accurately assessing the health of these animals is of paramount importance. Implementing posture recognition through target detection serves as a vital method for monitoring the well-being of sika deer. This approach allows for a more nuanced understanding of their physical condition, ensuring the industry can maintain high standards of animal welfare and productivity. In order to achieve remote monitoring of sika deer without interfering with the natural behavior of the animals, and to enhance animal welfare, this paper proposes a sika deer individual posture recognition detection algorithm GFI-YOLOv8 based on YOLOv8. Firstly, this paper proposes to add the iAFF iterative attention feature fusion module to the C2f of the backbone network module, replace the original SPPF module with AIFI module, and use the attention mechanism to adjust the feature channel adaptively. This aims to enhance granularity, improve the model's recognition, and enhance understanding of sika deer behavior in complex scenes. Secondly, a novel convolutional neural network module is introduced to improve the efficiency and accuracy of feature extraction, while preserving the model's depth and diversity. In addition, a new attention mechanism module is proposed to expand the receptive field and simplify the model. Furthermore, a new pyramid network and an optimized detection head module are presented to improve the recognition and interpretation of sika deer postures in intricate environments. The experimental results demonstrate that the model achieves 91.6% accuracy in recognizing the posture of sika deer, with a 6% improvement in accuracy and a 4.6% increase in mAP50 compared to YOLOv8n. Compared to other models in the YOLO series, such as YOLOv5n, YOLOv7-tiny, YOLOv8n, YOLOv8s, YOLOv9, and YOLOv10, this model exhibits higher accuracy, and improved mAP50 and mAP50-95 values. The overall performance is commendable, meeting the requirements for accurate and rapid identification of the posture of sika deer. This model proves beneficial for the precise and real-time monitoring of sika deer posture in complex breeding environments and under all-weather conditions.

Bionic sulfated glycosaminoglycan-based hydrogel inspired by snail mucus promotes diabetic chronic wound healing via regulating macrophage polarization.

The treatment of diabetic foot ulcers remains a significant challenge, as their morbidity is increasing while current therapies are expensive and often ineffective. The dried mucus from the snail Achatina fulica promotes diabetic wound healing. Herein, to develop a more controllable and stable wound dressing for diabetic wound treatment, the AFG/StarPEG hydrogel mimicking snail mucus was prepared by covalently coupling of sulfated glycosaminoglycan from A. fulica (AFG) with star-shaped polyethylene glycol (StarPEG) amine. The AFG/StarPEG hydrogel reduced excessive inflammation in wound tissues by decreasing pro-inflammatory cytokines (IL-6, IL-1ß, and TNF-α) and increasing anti-inflammatory cytokines (IL-4 and IL-10). Moreover, it promoted the polarization of macrophages to M2 anti-inflammatory type in diabetic wound. By improving transition of diabetic chronic wound from inflammatory phase to proliferative phase, it promoted angiogenesis, collagen deposition and re-epithelialization, and thus tissue regeneration for wound healing. This work provides a convenient and effective dressing for treating chronic diabetic wound.

Dominant Contribution of Non-dust Primary Emissions and Secondary Processes to Dissolved Aerosol Iron.

Solubility largely determines the impacts of aerosol Fe on marine ecosystems and human health. Currently, modeling studies have large uncertainties in aerosol Fe solubility due to inadequate understanding of the sources of dissolved Fe. This work investigated seasonal variations of Fe solubility in coarse and fine aerosols in Qingdao, a coastal city in the Northwest Pacific, and utilized a receptor model for source apportionment of total and dissolved aerosol Fe. Desert dust was found to be the main source of total Fe, contributing 65 and 81% annually to total Fe in coarse and fine particles, respectively; in contrast, dissolved aerosol Fe originated primarily from combustion, industrial, and secondary sources. The annual average contributions to dissolved Fe in coarse and fine particles were 68 and 47% for the secondary source and 32 and 33% for the combustion source, respectively. Aerosol Fe solubility was found to be highest in summer and lowest in spring, showing seasonal patterns similar to those of aerosol acidity. Increase in Fe solubility in atmospheric particles, when compared to desert dust, was mainly caused by secondary processing and combustion emission, and the effect of secondary processes was dictated by aerosol acidity and liquid water content.

Integrated analysis of the lncRNA-miRNA-mRNA ceRNA network in nasopharyngeal carcinoma.

Background: Nasopharyngeal carcinoma (NPC) is particularly prevalent in East and Southeast Asia. Competing endogenous RNA (ceRNA) networks are known to play an essential role in the emergence of various diseases, including cancer. Building a network of protein-protein interactions (PPIs) and ceRNAs can facilitate the detection of potential connections between messenger RNAs (mRNAs) and various non-coding RNAs. However, the precise role of ceRNA networks in NPC has not been examined in detail. Therefore, the primary aim of the present study was to characterize a ceRNA network for NPC. Methods: Datasets of microRNA (miRNA), long non-coding RNA (lncRNA), and mRNA microarrays were downloaded from the Gene Expression Omnibus (GEO) database. Data were standardized and differentially expressed genes (DEGs) were screened using the limma package. The ClusterProfiler software suite was used to perform enrichment analysis of differentially expressed mRNAs using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) techniques. Results: A total of 160 lncRNAs, 8 miRNAs, and 147 mRNAs were differentially expressed in NPC samples. A ceRNA network was constructed using four lncRNAs, five miRNAs, and one mRNA that were dysregulated in NPC. Cellular functions of the abnormally expressed mRNAs were mainly associated with tumor cell movement, cell growth and proliferation, cell cycle, invasion, and metastasis. Conclusions: The ceRNA network constructed herein clarified the regulatory mechanisms through which lncRNAs act as ceRNAs and participate in NPC development. Notably, lncRNAs, miRNAs, and mRNAs identified in this ceRNA network can serve as therapeutic targets and prognostic biomarkers for NPC.

Relationship between four visceral obesity indices and prediabetes and diabetes: a cross-sectional study in Dalian, China.

BACKGROUND: In recent times, a number of new indices for measuring visceral obesity have been developed. This research sought to investigate the relationship between four visceral obesity indices and prediabetes and diabetes. METHODS: Conducted in 2011 as a cross-sectional analysis in Dalian, China, this study utilized logistic regression models to explore the relationships between four visceral obesity indices and prediabetes and diabetes. It also assessed the dose-response relationships using restricted cubic splines (RCS), performed subgroup analyses, and conducted interaction tests. The predictive values of four visceral obesity indices were evaluated using receiver operating characteristic (ROC) curves. RESULTS: The study enrolled 10,090 participants, with prediabetes and diabetes prevalence at 80.53%. Multifactorial logistic regression revealed positive relationships between the four visceral obesity indices and prediabetes and diabetes. The results of the RCS analysis revealed a linear relationship between the body roundness index (BRI), cardiometabolic index (CMI) and prediabetes and diabetes. Conversely, a non-linear relationship was observed between Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP) and prediabetes and diabetes. Subgroup analyses demonstrated stronger relationships of CMI, CVAI, and LAP with prediabetes and diabetes among females. ROC curves suggested that LAP could be an effective predictor of these conditions. CONCLUSION: This research confirmed that four visceral obesity indices are linked with a higher risk of prediabetes and diabetes in middle-aged and elderly individuals in Dalian. Importantly, LAP could be an effective predictor of prediabetes and diabetes. Effective weight management significantly reduces the risk of both prediabetes and diabetes.

Enhanced CO2 conversion through confinement of cross-linked ionic polymer within the pores of porous carbon materials.

It is crucial to employ an integrated catalyst to avoid the complications of the recovery process. This work reports the fabrication of porous carbon@ionic liquid (PC@IL) composites with readily accessible active ion sites, achieved by confining cross-linked ionic liquid (IL) within the channels of porous carbon (PC). The incorporation of porous carbon not only confines the IL within its framework, creating microsites for CO2 adsorption and conversion, but also simplifies catalyst recovery. The results indicate that PC@IL composites exhibit excellent cycloaddition activity towards CO2 in a co-catalyst- and solvent-free environment. Notably, PC@IL(C)-24 demonstrates remarkable catalytic performance across various epoxides under 1 bar of CO2, with yields above 90 % at 90 °C for 12 h, and achieving a remarkable styrene carbonate yield of up to 92.8 % under a CO2 pressure of 1 bar (at 100 °C for 12 h). Control experiments confirm that the confinement effect exerted by N,S co-doped carbon on cross-linked IL plays a pivotal role in enhancing both stability and activity of PC@IL composites, thereby providing novel insights for designing functionalized porous carbon catalysts for CO2 cycloaddition conversion.

Nanosilicates facilitate periodontal regeneration potential by activating the PI3K-AKT signaling pathway in periodontal ligament cells.

The recent development of nanobiomaterials has shed some light on the field of periodontal tissue regeneration. Laponite (LAP), an artificially synthesized two-dimensional (2D) disk-shaped nanosilicate, has garnered substantial attention in regenerative biomedical applications owing to its distinctive structure, exceptional biocompatibility and bioactivity. This study endeavors to comprehensively evaluate the influence of LAP on periodontal regeneration. The effects of LAP on periodontal ligament cells (PDLCs) on osteogenesis, cementogenesis and angiogenesis were systematically assessed, and the potential mechanism was explored through RNA sequencing. The results indicated that LAP improved osteogenic and cementogenic differentiation of PDLCs, the regulatory effects of LAP on PDLCs were closely correlated with activation of PI3K-AKT signaling pathway. Moreover, LAP enhanced angiogenesis indirectly via manipulating paracrine of PDLCs. Then, LAP was implanted into rat periodontal defect to confirm its regenerative potential. Both micro-CT and histological analysis indicated that LAP could facilitate periodontal tissue regeneration in vivo. These findings provide insights into the bioactivity and underlying mechanism of LAP on PDLCs, highlighting it might be a potential therapeutic option in periodontal therapy.

Identifying reliable obesity indices for hyperuricemia among middle-aged and elderly populations: a longitudinal study.

BACKGROUND: Given the established link between obesity and hyperuricemia (HUA), the research want to investigate the relationship between different obesity indices and HUA, and further analyze which obesity index can better predict HUA. METHODS: The data were obtained from a longitudinal study involving middle-aged and elderly populations in Dalian, China. The research encompassed individuals who exhibited typical uric acid levels initially and tracked their progress over a three-year period. 8 obesity indices were evaluated retrospectively. Subgroup analyses were conducted to identify susceptible populations. Restricted cubic splines (RCS) were utilized to model the dose-response relationships between obesity indices and HUA. Receiver operating characteristic (ROC) curves were applied to visualize and compare the predictive value of both traditional and new obesity indices for HUA. RESULTS: Among 4,112 individuals with normal baseline uric acid levels, 950 developed HUA. Significant associations with HUA were observed for body mass index (BMI), waist circumference (WC), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), and abdominal volume index (AVI). Subgroup analysis indicated that all obesity indices proved more effective in assessing the onset of HUA in women without Metabolic Syndrome (MetS). Further analysis using RCS revealed non-linear dose-response relationships between LAP, CMI, VAI, and HUA in males, with similar non-linear relationships observed for all indices in females. The results from the ROC curves indicate that LAP may serve as a better predictor of HUA in males, and CVAI may serve as a better predictor in females. CONCLUSION: HUA is closely associated with obesity indices. Among females, CVAI emerges as the preferred predictive index for HUA. In males, LAP emerges as the preferred predictive index for HUA.

CB1 Promotes Osteogenic Differentiation Potential of Periodontal Ligament Stem Cells by Enhancing Mitochondrial Transfer of Bone Marrow Mesenchymal Stem Cells.

OBJECTIVE: To reveal the role and mechanism of cannabinoid receptor 1 (CB1) and mitochondria in promoting osteogenic differentiation of periodontal ligament stem cells (PDLSCs) in the inflammatory microenvironment. METHODS: Bidirectional mitochondrial transfer was performed in bone mesenchymal stem cells (BMSCs) and PDLSCs. Laser confocal microscopy and quantitative flow cytometry were used to observe the mitochondrial transfer and quantitative mitochondrial transfer efficiency. Realtime reverse transcription polymerase chain reaction (RT-PCR) was employed to detect gene expression. Alkaline phosphatase (ALP) activity, alizarin red staining (ARS) and quantitative calcium ion analysis were used to evaluate the degree of osteogenic differentiation of PDLSCs. RESULTS: Bidirectional mitochondrial transfer was observed between BMSCs and PDLSCs. The indirect co-culture system could simulate intercellular mitochondrial transfer. Compared with the conditioned medium (CM) for BMSCs, that for HA-CB1 BMSCs could significantly enhance the mineralisation ability of PDLSCs. The mineralisation ability of PDLSCs could not be enhanced after removing the mitochondria in CM for HA-CB1 BMSCs. The expression level of HO-1, PGC-1α, NRF-1, ND1 and HK2 was significantly increased in HA-CB1 BMSCs. CONCLUSION: CM for HA-CB1 BMSCs could significantly enhance the damaged osteogenic differentiation ability of PDLSCs in the inflammatory microenvironment, and the mitochondria of CM played an important role. CB1 was related to the activation of the HO-1/PGC-1α/NRF-1 mitochondrial biogenesis pathway, and significantly increased the mitochondrial content in BMSCs.

The effect of perioperative dexmedetomidine on postoperative delirium in adult patients undergoing cardiac surgery with cardiopulmonary bypass: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Dexmedetomidine is considered to have neuroprotective effects and may reduce postoperative delirium in both cardiac and major non-cardiac surgeries. Compared with non-cardiac surgery, the delirium incidence is extremely high after cardiac surgery, which could be caused by neuroinflammation induced by surgical stress and CPB. Thus, it is essential to explore the potential benefits of dexmedetomidine on the incidence of delirium in cardiac surgery under CPB. METHODS: Randomized controlled trials studying the effect of perioperative dexmedetomidine on the delirium incidence in adult patients undergoing cardiac surgery with CPB were considered to be eligible. Data collection was conducted by two reviewers independently. The pre-specified outcome of interest is delirium incidence. RoB 2 was used to perform risk of bias assessment by two reviewers independently. The random effects model and Mantel-Haenszel statistical method were selected to pool effect sizes for each study. RESULTS: PubMed, Embase, Cochrane Library, and Web of Science were systematically searched from inception to June 28, 2023. Sixteen studies including 3381 participants were included in our systematic review and meta-analysis. Perioperative dexmedetomidine reduced the incidence of postoperative delirium in patients undergoing cardiac surgery with CPB compared with the other sedatives, placebo, or normal saline (RR 0.57; 95% CI 0.41-0.79; P = 0.0009; I2 = 61%). CONCLUSIONS: Perioperative administration of dexmedetomidine could reduce the postoperative delirium occurrence in adult patients undergoing cardiac surgery with CPB. However, there is relatively significant heterogeneity among the studies. And the included studies comprise many early-stage small sample trials, which may lead to an overestimation of the beneficial effects. It is necessary to design the large-scale RCTs to further confirm the potential benefits of dexmedetomidine in cardiac surgery with CPB. REGISTRATION NUMBER: CRD42023452410.

Effect of primary tumor volume on survival of concurrent chemoradiotherapy in stage IV non-small cell lung cancer.

OBJECTIVE: To explore the survival effect of thoracic gross tumor volume (GTV) in three-dimensional (3D) radiotherapy for stage IV non-small cell lung cancer (NSCLC). METHODS: The data cases were obtained from a single-center retrospective analysis. From May. From 2008 to August 2018, 377 treatment criteria were enrolled. GTV was defined as the volume of the primary lesion and the hilus as well as the mediastinal metastatic lymph node. Chemotherapy was a platinum-based combined regimen of two drugs. The number of median chemotherapy cycles was 4 (2-6), and the cut-off value of the planning target volume (PTV) dose of the primary tumor was 63 Gy (30-76.5 Gy). The cut-off value of GTV volume was 150 cm3 (5.83-3535.20 cm3). RESULTS: The survival rate of patients with GTV <150 cm3 is better than patients with GTV ≥150 cm3. Multivariate Cox regression analyses suggested that peripheral lung cancer, radiation dose ≥63 Gy, GTV <150 cm3, 4-6 cycles of chemotherapy, and CR + PR are good prognostic factors for patients with stage IV non-small cell lung cancer. The survival rate of patients with GTV <150 cm3 was longer than patients with ≥150 cm3 when they underwent 2 to 3 cycles of chemotherapy concurrent 3D radiotherapy (p < 0.05). When performing 4 to 6 cycles of chemotherapy concurrent 3D radiotherapy, there was no significant difference between <150 cm3 and ≥150 cm3. CONCLUSIONS: The volume of stage IV NSCLC primary tumor can affect the survival of patients. Appropriate treatment methods can be opted by considering the volume of tumors to extend patients' lifetime to the utmost.

Safety analysis of fluoroquinolone drugs in elderly patients over 65 based on FAERS.

OBJECTIVE: This study investigates adverse drug event (ADE) reports from the FAERS related to FQs drugs in patients aged 65 and older. The findings aim to guide the rational clinical use of these drugs in elderly patients. METHODS: We employed Reporting Odds Ratio (ROR) and Proportional Reporting Ratio (PRR) methods to analyze ADE reports for the representative FQ drugs from Q1 2015 to Q4 2023, covering 36 quarters. RESULTS: The analysis identified 6883 ADE cases for ciprofloxacin, 5866 for levofloxacin, 1498 for moxifloxacin, and 317 for ofloxacin. Moxifloxacin showed higher incidences of Cardiac disorders and Psychiatric disorders ADEs (4.01%, 23.11%). Ciprofloxacin and levofloxacin showed higher ADE rates in musculoskeletal and connective tissue diseases (20.18% and 26.97%) compared to moxifloxacin (3.62%) and ofloxacin (9.25%). Additionally, moxifloxacin and ofloxacin showed higher ADE rates for eye disorders (10.61% and 15.03%). CONCLUSION: Different FQs exhibit varying ADE profiles across cardiovascular, vascular and lymphatic, renal and urinary, psychiatric, musculoskeletal and connective tissue, and ocular systems. Patients with underlying systemic diseases should avoid FQs with higher ADE risks for their conditions. Personalized medication plans for elderly patients should also be strengthened.

A Green and Efficient Electrocatalytic Route for the Highly-Selective Oxidation of C-H Bonds in Aromatics over 1D Co3O4-Based Nanoarrays.

Electrocatalytic oxidation of C-H bonds in hydrocarbons represents an efficient and sustainable strategy for the synthesis of value-added chemicals. Herein, a highly selective and continuous-flow electrochemical oxidation process of toluene to various oxygenated products (benzyl alcohol, benzaldehyde, and benzyl acetate) is developed with the electrocatalytic membrane electrodes (ECMEs). The selectivity of target products can be manipulated via surface and interface engineering of Co3O4-based electrocatalysts. We achieved a high benzaldehyde selectivity of 90% at a toluene conversion of 47.6% using 1D-Co3O4 nanoneedles (NNs) loaded on a microfiltration (MF) titanium (Ti) membrane, i.e, Co3O4 NNs/Ti. In contrast, the main product shifted to benzyl alcohol with a selectivity of 90.1% at conversion of 32.1% after modifying MnO2 nanosheets (NSs) on Co3O4 NNs/Ti (Co3O4@MnO2/Ti) catalyst. Moreover, benzyl acetate product can be obtained with selectivity of 92% at a conversion of 58.5% at high current density (> 1.5mA cm-2), demonstrating that the pathway of toluene oxidation is readily maneuvered. DFT results reveal that modifying MnO2 on Co3O4 optimizes the electron structure of Co3O4@MnO2/Ti and modulates the adsorption behavior of intermediate species. This work demonstrates a sustainable, and continuous-flow process for precise control over production selectivity of value-added oxygenated derivatives in electrochemical oxidation of aromatic hydrocarbons.

Uncertainty quantification in epigenetic clocks via conformalized quantile regression.

DNA methylation (DNAm) is a chemical modification of DNA that can be influenced by various factors, including age, environment, and lifestyle. An epigenetic clock is a predictive tool that measures biological age based on DNAm levels. It can provide insights into an individual's biological age, which may differ from their chronological age. This difference, known as the epigenetic age acceleration, may indicate the state of one's health and risk for age-related diseases. Moreover, epigenetic clocks are used in studies of aging to assess the effectiveness of anti-aging interventions and to understand the underlying mechanisms of aging and disease. Various epigenetic clocks have been developed using samples from different populations, tissues, and cell types, typically by training high-dimensional linear regression models with an elastic net penalty. While these models can predict mean biological age with high precision, there is a lack of uncertainty quantification which is important for interpreting the precision of age estimations and for clinical decision-making. To understand the distribution of a biological age clock beyond its mean, we propose a general pipeline for training epigenetic clocks, based on an integration of high-dimensional quantile regression and conformal prediction, to effectively reveal population heterogeneity and construct prediction intervals. Our approach produces adaptive prediction intervals not only achieving nominal coverage but also accounting for the inherent variability across individuals. By using the data collected from 728 blood samples in 11 DNAm datasets from children, we find that our quantile regression-based prediction intervals are narrower than those derived from conventional mean regression-based epigenetic clocks. This observation demonstrates an improved statistical efficiency over the existing pipeline for training epigenetic clocks. In addition, the resulting intervals have a synchronized varying pattern to age acceleration, effectively revealing cellular evolutionary heterogeneity in age patterns in different developmental stages during individual childhoods and adolescent cohort. Our findings suggest that conformalized high-dimensional quantile regression can produce valid prediction intervals and uncover underlying population heterogeneity. Although our methodology focuses on the distribution of aging in children, it is applicable to a broader range of populations to improve understanding of epigenetic age beyond the mean. This inference-based toolbox could provide valuable insights for future applications of epigenetic interventions for age-related diseases.

Momordica charantia L.-derived exosome-like nanovesicles stabilize p62 expression to ameliorate doxorubicin cardiotoxicity.

BACKGROUND: Doxorubicin (DOX) is a first-line chemotherapeutic drug for various malignancies that causes cardiotoxicity. Plant-derived exosome-like nanovesicles (P-ELNs) are growing as novel therapeutic agents. Here, we investigated the protective effects in DOX cardiotoxicity of ELNs from Momordica charantia L. (MC-ELNs), a medicinal plant with antioxidant activity. RESULTS: We isolated MC-ELNs using ultracentrifugation and characterized them with canonical mammalian extracellular vesicles features. In vivo studies proved that MC-ELNs ameliorated DOX cardiotoxicity with enhanced cardiac function and myocardial structure. In vitro assays revealed that MC-ELNs promoted cell survival, diminished reactive oxygen species, and protected mitochondrial integrity in DOX-treated H9c2 cells. We found that DOX treatment decreased the protein level of p62 through ubiquitin-dependent degradation pathway in H9c2 and NRVM cells. However, MC-ELNs suppressed DOX-induced p62 ubiquitination degradation, and the recovered p62 bound with Keap1 promoting Nrf2 nuclear translocation and the expressions of downstream gene HO-1. Furthermore, both the knockdown of Nrf2 and the inhibition of p62-Keap1 interaction abrogated the cardioprotective effect of MC-ELNs. CONCLUSIONS: Our findings demonstrated the therapeutic beneficials of MC-ELNs via increasing p62 protein stability, shedding light on preventive approaches for DOX cardiotoxicity.

Genome sequencing and CAZymes repertoire analysis of Diaporthe eres P3-1W causing postharvest fruit rot of 'Hongyang' kiwifruit in China.

Postharvest rot caused by various fungal pathogens is a damaging disease affecting kiwifruit production and quality, resulting in significant annual economic losses. This study focused on isolating the strain P3-1W, identified as Diaporthe eres, as the causal agent of 'Hongyang' postharvest rot disease in China. The investigation highlighted cell wall degrading enzymes (CWDEs) as crucial pathogenic factors. Specially, the enzymatic activities of cellulase, ß-galactosidase, polygalacturonase, and pectin methylesterases peaked significantly on the second day after infection of D. eres P3-1W. To gain a comprehensive understanding of these CWDEs, the genome of this strain was sequenced using PacBio and Illumina sequencing technologies. The analysis revealed that the genome of D. eres P3-1W spans 58,489,835 bp, with an N50 of 5,939,879 bp and a GC content of 50.7%. A total of 15,407 total protein-coding genes (PCGs) were predicted and functionally annotated. Notably, 857 carbohydrate-active enzymes (CAZymes) were identified in D. eres P3-1W, with 521 CWDEs consisting of 374 glycoside hydrolases (GHs), 108 carbohydrate esterase (CEs) and 91 polysaccharide lyases (PLs). Additionally, 221 auxiliary activities (AAs), 91 glycosyltransferases (GTs), and 108 carbohydrate binding modules (CBMs) were detected. These findings offer valuable insights into the CAZymes of D. eres P3-1W.

Clinical Evaluation of a New Chemiluminescence Assay for the Detection of Treponema Pallidum Antibodies.

BACKGROUND: A new chemiluminescence assay, the Anti-TP-Ⅱ assay, is going to be commercially available in clinical laboratories in China and other countries. This study examined the performance of the new assay for the detection of TP infection and compared it with that of the Anti-TP assay by using large amounts of clinical samples. METHODS: The precision, accuracy, anti-interference ability, and the clinical sensitivity and specificity of the Anti-TP-Ⅱ assay were evaluated. In addition, compared with those of the Anti-TP assay, the false positive and false negative rates of the Anti-TP-Ⅱ assay were evaluated for 2,436 clinical routine samples and 711 preselected Anti-TP assay reactive samples. Discrepancy of the samples was investigated with the recomLinec Treponema IgM/IgG kit or the Elecsys syphilis assay. RESULTS: The precision, accuracy, and anti-interference ability of the Anti-TP-Ⅱ assay met the national standard of China, and there was an overall agreement of 96.75% (Kappa = 0.91) between the two assays. The sensitivity and specificity of the Anti-TP-Ⅱ assay were 100% (95% CI: 94.13% to 100%) and 99.92% (95% CI: 99.70% to 99.99%), respectively. Compared with the Anti-TP assay, the Anti-TP-Ⅱ assay significantly reduced the number of borderline samples and the false positive rate. CONCLUSIONS: Considering its excellent performance, the Anti-TP-Ⅱ assay is a good screening test for high-throughput laboratories and can replace the previous generation of reagents, the Anti-TP assay, with a superior specificity.

J-shaped relationship between Chinese visceral adiposity index and hyperuricemia: a cross-sectional study.

BACKGROUND: Recent years have seen the emergence of numerous novel indicators for visceral obesity. This study investigates the potential correlation between the Chinese visceral adiposity index (CVAI) and hyperuricemia (HUA). METHODS: This research, derived from a 2011 cross-sectional analysis in Dalian, China, employed restricted cubic spline (RCS) plots to identify inflection points. Subsequently, one-way and multifactorial logistic regression models were utilized, with HUA as the outcome variable. Additionally, subgroup analyses and interaction tests were conducted. Eventually, receiver operating characteristic (ROC) curves were calculated to assess the effectiveness of CVAI and other body composition indices in predicting HUA. RESULTS: The study included 10,061 individuals, with a HUA prevalence of 14.25%. Significant relationships with HUA were observed for CVAI. RCS analysis revealed a J-shaped relationship between CVAI and HUA. Compared to those in the low CVAI category, HUA was notably associated with individuals in the high CVAI category in multifactorial logistic regression (OR = 2.661, 95% CI: 2.323, 3.047). Subgroup analyses demonstrated stronger relationships in women, participants without hypertension, and participants without diabetes. Additional modeling via ROC curves suggested that the CVAI may offer effective predictive value for HUA. CONCLUSION: This study confirmed that an elevated CVAI elevates the risk of HUA in middle-aged and elderly populations in the Dalian community. The findings advance obesity prevention strategies that mitigate HUA risk and support healthcare initiatives for China's aging population.