Development and validation of a novel sleep health score in the sleep heart health study.

BACKGROUND: There is a lack of consensus in evaluating multidimensional sleep health, especially concerning its implication for mortality. A validated multidimensional sleep health score is the foundation of effective interventions. METHODS: We obtained data from 5706 participants in the Sleep Heart Health Study. First, random forest-recursive feature elimination algorithm was used to select potential predictive variables. Second, a sleep composite score was developed based on the regression coefficients from a Cox proportional hazards model evaluating the associations between selected sleep-related variables and mortality. Last, we validated the score by constructing Cox proportional hazards models to assess its association with mortality. RESULTS: The mean age of participants was 63.2 years old, and 47.6% (2715/5706) were male. Six sleep variables, including average oxygen saturation (%), spindle density (C3), sleep efficiency (%), spindle density (C4), percentage of fast spindles (%) and percentage of rapid eye movement (%) were selected to construct this multidimensional sleep health score. The average sleep composite score in participants was 6.8 of 22 (lower is better). Participants with a one-point increase in sleep composite score had an 10% higher risk of death (hazard ratio = 1.10, 95% confidence interval: 1.08-1.12). CONCLUSIONS: This study constructed and validated a novel multidimensional sleep health score to better predict death based on sleep, with significant associations between sleep composite score and all-cause mortality. Integrating questionnaire information and sleep microstructures, our sleep composite score is more appropriately applied for mortality risk stratification.

Practice of standardization of CLSI M45 A3 antimicrobial susceptibility testing of Infrequently Isolated or Fastidious Bacteria strains isolated from blood specimens in Guangdong Province 2017-2021.

The concentration of antimicrobial agents in environments like water and food has increased rapidly, which led to a rapid increase in antimicrobial resistance levels in the environment. Monitoring of bacterial resistance levels is considered as a necessary means to control the bacterial resistance. Reference standards are critical for antimicrobial susceptibility testing. CLSI M45 A3 standard defines pathogenic microorganisms that cause infections less frequently than those covered by CLSI M02, M07, and M100 as Infrequently Isolated or Fastidious Bacteria and specifies antimicrobial susceptibility testing methods. Our study investigated the epidemiology and antimicrobial susceptibility testing data of Infrequently Isolated or Fastidious Bacteria strains isolated from blood specimens in 70 hospitals in Guangdong Province between 2017 and 2021. We defined testing methods other than those specified in CLSI M45 A3 as "Non-Standardized." The proportion of standardized antimicrobial susceptibility testing for penicillin increased significantly (Corynebacterium spp. 17.4% vs. 50.0% p < 0.05; Micrococcus spp. 50.0% vs. 77.8% p < 0.05; Abiotrophia spp. and Granulicatella spp. 21.4% vs. 90.9% p < 0.001), while for cefotaxime (Corynebacterium spp. 0.0% vs. 45.2% p < 0.05; Abiotrophia spp. and Granulicatella spp. 0.0% vs. 14.3% p = 0.515) and vancomycin increased finitely. Non-standardized methods were used for all other antimicrobials. Due to limitations in the economic and medical environment, some clinical laboratories are unable to fully comply with CLSI M45 A3 standard. We recommend that CLSI should add breakpoints for disk diffusion method to improve the standardization of antimicrobial susceptibility testing.

CNOT7 regulates lipid deposition in nonalcoholic fatty liver disease.

BACKGROUND: In recent years, the incidence rate of nonalcoholic fatty liver disease (NAFLD) has ascended with the increasing number of metabolic diseases such as obesity and diabetes, which will bring great medical burden to society. At present, multiple scientific experiments have found that the CCR4-NOT complex can participate in regulating obesity and energy metabolism. This study is designed to explore the role and mechanism of CCR4-NOT transcription complex subunit 7 (CNOT7), a subunit of the CCR4-NOT complex in liver lipid deposition. METHODS: To establish the NAFLD cell model, palmitic acid (PA) was utilized to stimulate HepG2 cells and LO2 cells, promoting intracellular lipid deposition. CNOT7 was knockdown by siRNA and lentivirus to evaluate the effect of CNOT7 in NAFLD. RESULTS: Our results demonstrated that the expression of CNOT7 was increased in the NAFLD cell model. After knocking down CNOT7, the lipid deposition declined in HepG2 or LO2 cells treated by PA reduced. We found the lipid synthesis genes and the lipid uptake and transport factors in the CNOT7 knockdown group were significantly downregulated compared to the non-knockdown group. Furthermore, knockdown of CNOT7 might promote fatty acid oxidation. CONCLUSION: Knocking down CNOT7 can improve lipid deposition and CNOT7 may be a potential therapeutic target for NAFLD.

Salivary metabolites are promising noninvasive biomarkers of drug-induced liver injury.

BACKGROUND: Drug-induced liver injury (DILI) is one of the most common adverse events of medication use, and its incidence is increasing. However, early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests. AIM: To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools. METHODS: Saliva samples from 31 DILI patients and 35 healthy controls (HCs) were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry. Subsequent analyses, including partial least squares-discriminant analysis modeling, t tests and weighted metabolite coexpression network analysis (WMCNA), were conducted to identify key differentially expressed metabolites (DEMs) and metabolite sets. Furthermore, we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction. The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves. RESULTS: We found 247 differentially expressed salivary metabolites between the DILI group and the HC group. Using WMCNA, we identified a set of 8 DEMs closely related to liver injury for further prediction testing. Interestingly, the distinct separation of DILI patients and HCs was achieved with five metabolites, namely, 12-hydroxydodecanoic acid, 3-hydroxydecanoic acid, tetradecanedioic acid, hypoxanthine, and inosine (area under the curve: 0.733-1). CONCLUSION: Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients. Our study may provide a potentially feasible and noninvasive diagnostic method for DILI, but further validation is needed.

Metagenomic and transcriptomic analysis revealing the impact of oxytetracycline and ciprofloxacin on gut microbiota and gene expression in the Chinese giant salamander (Andrias davidianus).

Excessive antibiotic use has led to the spread of antibiotic resistance genes (ARGs), impacting gut microbiota and host health. However, the effects of antibiotics on amphibian populations remain unclear. We investigated the impact of oxytetracycline (OTC) and ciprofloxacin (CIP) on Chinese giant salamanders (Andrias davidianus), focusing on gut microbiota, ARGs, and gene expression by performing metagenome and transcriptome sequencing. A. davidianus were given OTC (20 or 40 mg/kg) or CIP (50 or 100 mg/kg) orally for 7 days. The results revealed that oral administration of OTC and CIP led to distinct changes in microbial composition and functional potential, with CIP treatment having a greater impact than OTC. Antibiotic treatment also influenced the abundance of ARGs, with an increase in fluoroquinolone and multi-drug resistance genes observed post-treatment. The construction of metagenome-assembled genomes (MAGs) accurately validated that CIP intervention enriched fish-associated potential pathogens Aeromonas hydrophila carrying an increased number of ARGs. Additionally, mobile genetic elements (MGEs), such as phages and plasmids, were implicated in the dissemination of ARGs. Transcriptomic analysis of the gut revealed significant alterations in gene expression, particularly in immune-related pathways, with differential effects observed between OTC and CIP treatments. Integration of metagenomic and transcriptomic data highlighted potential correlations between gut gene expression and microbial composition, suggesting complex interactions between the host gut and its gut microbiota in response to antibiotic exposure. These findings underscore the importance of understanding the impact of antibiotic intervention on the gut microbiome and host health in amphibians, particularly in the context of antibiotic resistance and immune function.

Deep learning-based model for difficult transfemoral access prediction compared with human assessment in stroke thrombectomy.

BACKGROUND: In mechanical thrombectomy (MT), extracranial vascular tortuosity is among the main determinants of procedure duration and success. Currently, no rapid and reliable method exists to identify the anatomical features precluding fast and stable access to the cervical vessels. METHODS: A retrospective sample of 513 patients were included in this study. Patients underwent first-line transfemoral MT following anterior circulation large vessel occlusion stroke. Difficult transfemoral access (DTFA) was defined as impossible common carotid catheterization or time from groin puncture to first carotid angiogram >30 min. A machine learning model based on 29 anatomical features automatically extracted from head-and-neck computed tomography angiography (CTA) was developed to predict DTFA. Three experienced raters independently assessed the likelihood of DTFA on a reduced cohort of 116 cases using a Likert scale as benchmark for the model, using preprocedural CTA as well as automatic 3D vascular segmentation separately. RESULTS: Among the study population, 11.5% of procedures (59/513) presented DTFA. Six different features from the aortic, supra-aortic, and cervical regions were included in the model. Cross-validation resulted in an area under the receiver operating characteristic (AUROC) curve of 0.76 (95% CI 0.75 to 0.76) for DTFA prediction, with high sensitivity for impossible access identification (0.90, 95% CI 0.81 to 0.94). The model outperformed human assessment in the reduced cohort [F1-score (95% CI) by experts with CTA: 0.43 (0.37 to 0.50); experts with 3D segmentation: 0.50 (0.46 to 0.54); and model: 0.70 (0.65 to 0.75)]. CONCLUSIONS: A fully automatic model for DTFA prediction was developed and validated. The presented method improved expert assessment of difficult access prediction in stroke MT. Derived information could be used to guide decisions regarding arterial access for MT.

Cobalt telluride regulated by nickel for efficient electrooxidation of 5-hydroxymethylfurfural.

Replacing the anodic oxygen evolution reaction (OER) in water splitting with 5-hydroxymethylfurfural oxidation reaction (HMFOR) can not only reduce the energy required for hydrogen production but also yield the valuable chemical 2,5-furandicarboxylic acid (FDCA). Co-based catalysts are known to be efficient for HMFOR, with high-valent Co being recognized as the main active component. However, efficiently promoting the oxidation of Co2+ to produce high-valent reactive species remains a challenge. In this study, Ni-doped CoTe (CoNiTe) nanorods were prepared as efficient catalysts for HMFOR, achieving a high HMFOR current density of 65.3 mA cm-2 at 1.50 V. Even after undergoing five successive electrolysis processes, the Faradaic efficiency (FE) remained at approximately 90.7 %, showing robust electrochemical durability. Mechanistic studies indicated that Ni doping changes the electronic configuration of Co, enhancing its charge transfer rate and facilitating the oxidation of Co2+ to high-valent CoO2 species. This work reveals the effect of Ni doping on the reconfiguration of the active phase during HMFOR.

Luteolin alleviates cadmium-induced metabolism disorder through antioxidant and anti-inflammatory mechanisms in chicken kidney.

Cadmium (Cd) is a common environmental pollutant associated with an increased incidence of renal metabolic diseases. Luteolin (Lut), a natural flavonoid, is widely used for its multifaceted therapeutic properties in inflammatory diseases. However, whether Lut protects against Cd-induced nephrotoxicity is still equivocal. The present study investigated the effects of Lut supplementation on renal oxidative stress, inflammation and metabolism and their related mechanisms. Therefore, 40 chickens were treated with Cd and/or Lut with automatic water and free food intake for 1 mo and then the kidney tissues were collected to explore this issue. In this study, Cd exposure induced renal glycolipid metabolism disorders and resultant kidney damage by periodic acid Schiff (PAS) staining, Oil Red O staining, total cholesterol (TC), triglyceride (TG), and glucose (Glu) levels in kidney, which were significantly ameliorated by Lut. Moreover, Lut also normalized the expression levels of factors related to Cd-disturbed glycolipid metabolism, improving metabolic homeostasis, and contributing to alleviating kidney damage. Furthermore, Lut demonstrated therapeutic potential against Cd-induced renal oxidative stress and inflammation by enhancing antioxidant capacity and inhibiting cytokine production in the kidney tissues. Mechanistically, Lut activated the AMPK/SIRT1/FOXO1 signaling pathway, attenuating oxidative stress and inflammatory responses, ameliorating the metabolic disturbance. In conclusion, these observations demonstrate that Lut treatment activates AMPK/SIRT1/FOXO1 signaling pathway, decreases oxidative stress and inflammation response, which may contribute to prevent Cd-induced metabolism disorder and consequent kidney damage.

Association of gastrointestinal microbiome and obesity with gestational diabetes mellitus-an updated globally based review of the high-quality literatures.

OBJECTIVES: The purpose of this review is to investigate the relationship between gastrointestinal microbiome, obesity, and gestational diabetes mellitus (GDM) in an objective manner. METHODS: We conducted a thorough and comprehensive search of the English language literatures published in PubMed, Web of Science, and the Cochrane Library from the establishment of the library until 12 December 2023. Our search strategy included both keywords and free words searches, and we strictly applied inclusion and exclusion criteria. Meta-analyses and systematic reviews were prepared. RESULTS: Six high-quality literature sources were identified for meta-analysis. However, after detailed study and analysis, a certain degree of heterogeneity was found, and the credibility of the combined analysis results was limited. Therefore, descriptive analyses were conducted. The dysbiosis of intestinal microbiome, specifically the ratio of Firmicutes/Bacteroides, is a significant factor in the development of metabolic diseases such as obesity and gestational diabetes. Patients with intestinal dysbiosis and obesity are at a higher risk of developing GDM. CONCLUSIONS: During pregnancy, gastrointestinal microbiome disorders and obesity may contribute to the development of GDM, with all three factors influencing each other. This finding could aid in the diagnosis and management of patients with GDM through further research on their gastrointestinal microbiome.

Reducing Overpotential of Lithium-Oxygen Batteries by Diatomic Metal Catalyst Orbital Matching Strategy.

Aprotic Li-O2 batteries have sparked attention in recent years due to their ultrahigh theoretical energy density. Nevertheless, their practical implementation is impeded by the sluggish reaction kinetics at the cathode. Comprehending the catalytic mechanisms is pivotal to developing efficient cathode catalysts for high-performance Li-O2 batteries. Herein, the intrinsic activity map of Li-O2 batteries is established based on the specific adsorption mode of O2 induced by diatomic catalyst orbital matching and the transfer-acceptance-backdonation mechanism, and the four-step screening strategy based on the intrinsic activity map is proposed. Guided by the strategy, FeNi@NC and FeCu@NC promising durable stability with a low overpotential are screened out from 27 Fe-Metal diatomic catalysts. Our research not only provides insights into the fundamental understanding of the reaction mechanism of Li-O2 batteries but also accelerates the rational design of efficient Li-O2 batteries based on the structure-activity relationship.

Reactive Oxygen Species-Responsive Delivery of a Notch Inhibitor to Alleviate Nonalcoholic Steatohepatitis by Inhibiting Hepatic de Novo Lipogenesis and Inflammation.

With the increased prevalence of nonalcoholic steatohepatitis (NASH) in the world, effective pharmacotherapy in clinical practice is still lacking. Previous studies have shown that dibenzazepine (DBZ), a Notch inhibitor, could alleviate NASH development in a mouse model. However, low bioavailability, poor water solubility, and extrahepatic side effects restrict its clinical application. To overcome these barriers, we developed a reactive oxygen species (ROS)-sensitive nanoparticle based on the conjugation of bilirubin to poly(ethylene glycol) (PEG) chains, taking into account the overaccumulation of hepatic ROS in the pathologic state of nonalcoholic steatohepatitis (NASH). The PEGylated bilirubin can self-assemble into nanoparticles in an aqueous solution and encapsulate insoluble DBZ into its hydrophobic cavity. DBZ nanoparticles (DBZ Nps) had good stability, rapidly released DBZ in response to H2O2, and effectively scavenged intracellular ROS of hepatocytes. After systemic administration, DBZ Nps could accumulate in the liver of the NASH mice, extend persistence in circulation, and improve the bioavailability of DBZ. Furthermore, DBZ Nps significantly improved glucose intolerance, relieved hepatic lipid accumulation and inflammation, and ameliorated NASH-induced liver fibrosis. Additionally, DBZ Nps had no significant extrahepatic side effects. Taken together, our results highlight the potential of the ROS-sensitive DBZ nanoparticle as a promising therapeutic strategy for NASH.

Accurate prediction of myopic progression and high myopia by machine learning.

Background: Myopia is a leading cause of visual impairment in Asia and worldwide. However, accurately predicting the progression of myopia and the high risk of myopia remains a challenge. This study aims to develop a predictive model for the development of myopia. Methods: We first retrospectively gathered 612 530 medical records from five independent cohorts, encompassing 227 543 patients ranging from infants to young adults. Subsequently, we developed a multivariate linear regression algorithm model to predict the progression of myopia and the risk of high myopia. Result: The model to predict the progression of myopia achieved an R2 value of 0.964 vs a mean absolute error (MAE) of 0.119D [95% confidence interval (CI): 0.119, 1.146] in the internal validation set. It demonstrated strong generalizability, maintaining consistent performance across external validation sets: R2 = 0.950 vs MAE = 0.119D (95% CI: 0.119, 1.136) in validation study 1, R2 = 0.950 vs MAE = 0.121D (95% CI: 0.121, 1.144) in validation study 2, and R2 = 0.806 vs MAE = -0.066D (95% CI: -0.066, 0.569) in the Shanghai Children Myopia Study. In the Beijing Children Eye Study, the model achieved an R2 of 0.749 vs a MAE of 0.178D (95% CI: 0.178, 1.557). The model to predict the risk of high myopia achieved an area under the curve (AUC) of 0.99 in the internal validation set and consistently high area under the curve values of 0.99, 0.99, 0.96 and 0.99 in the respective external validation sets. Conclusion: Our study demonstrates accurate prediction of myopia progression and risk of high myopia providing valuable insights for tailoring strategies to personalize and optimize the clinical management of myopia in children.

Discovery of the Highly Selective and Potent STAT3 Inhibitor for Pancreatic Cancer Treatment.

Signal transducer and activator of transcription 3 (STAT3) is an attractive cancer therapeutic target. Unfortunately, targeting STAT3 with small molecules has proven to be very challenging, and for full activation of STAT3, the cooperative phosphorylation of both tyrosine 705 (Tyr705) and serine 727 (Ser727) is needed. Further, a selective inhibitor of STAT3 dual phosphorylation has not been developed. Here, we identified a low nanomolar potency and highly selective small-molecule STAT3 inhibitor that simultaneously inhibits both STAT3 Tyr705 and Ser727 phosphorylation. YY002 potently inhibited STAT3-dependent tumor cell growth in vitro and achieved potent suppression of tumor growth and metastasis in vivo. More importantly, YY002 exhibited favorable pharmacokinetics, an acceptable safety profile, and superior antitumor efficacy compared to BBI608 (STAT3 inhibitor that has advanced into phase III trials). For the mechanism, YY002 is selectively bound to the STAT3 Src Homology 2 (SH2) domain over other STAT members, which strongly suppressed STAT3 nuclear and mitochondrial functions in STAT3-dependent cells. Collectively, this study suggests the potential of small-molecule STAT3 inhibitors as possible anticancer therapeutic agents.

Analysis of the causes of primary revision after unicompartmental knee arthroplasty: A case series.

BACKGROUND: Unicompartmental knee arthroplasty (UKA) has great advantages in the treatment of unicompartmental knee osteoarthritis, but its revision rate is higher than that of total knee arthroplasty. AIM: To summarize and analyse the causes of revision after UKA. METHODS: This is a retrospective case series study in which the reasons for the first revision after UKA are summarized. We analysed the clinical symptoms, medical histories, laboratory test results, imaging examination results and treatment processes of the patients who underwent revision and summarized the reasons for primary revision after UKA. RESULTS: A total of 13 patients, including 3 males and 10 females, underwent revision surgery after UKA. The average age of the included patients was 67.62 years. The prosthesis was used for 3 d to 72 months. The main reasons for revision after UKA were improper suturing of the surgical opening (1 patient), osteophytes (2 patients), intra-articular loose bodies (2 patients), tibial prosthesis loosening (2 patients), rheumatoid arthritis (1 patient), gasket dislocation (3 patients), anterior cruciate ligament injury (1 patient), and medial collateral ligament injury with residual bone cement (1 patient). CONCLUSION: The causes of primary revision after UKA were gasket dislocation, osteophytes, intra-articular loose bodies and tibial prosthesis loosening. Avoidance of these factors may greatly reduce the rate of revision after UKA, improve patient satisfaction and reduce medical burden.

IRF4 Knockdown Inhibits the Chronic Rhinosinusitis Without Nasal Polyps Development by Regulating NLRP3/Caspase-1/GSDMD-Mediated Pyroptosis.

Chronic rhinosinusitis without nasal polyps (CRSsNP) is a CRS phenotype. However, the mechanisms of CRSsNP remains unclear. Differentially expressed genes (DEGs) were obtained from the GSE36830 and GSE198950 datasets through the GEO2R tool. The six hub genes were screened by the protein-protein interaction (PPI) network analysis and Cytoscape software. Then we constructed the mouse models of CRS and verified the expression levels of hub genes by reverse transcription quantitative PCR (RT-qPCR). Hematoxylin-eosin (HE) staining was employed to observe pathological alterations in mouse tissues. Casepase-3 expression was detected by immunohistochemistry (IHC). The levels of TNF-α, IL-12, IL-6, IL-1ß, LDH, and IL-18 were evaluated using enzyme-linked immunosorbent assay (ELISA). Pyroptosis-related protein expressions were measured by western blotting. Cell counting kit-8 (CCK-8) and flow cytometry were performed to assess the proliferation and apoptosis of lipopolysaccharide (LPS)-induced NP69 cells. Six hub DEGs were identified. The expression levels of IRF4, IKZF1, and CD79A were obviously increased in CRSsNP, while those of ADH6, ADH1A, and LDHC were significantly decreased. IRF4 knockdown attenuated the pathologic features of CRSsNP. IRF4 knockdown reduced levels of the TNF-α, IL-12, IL-6 IL-1ß, LDH, and IL-18 as well as the proteins expression of Casepase-1, GSDMD, and NLRP3 both in vivo and in vitro, implying that inflammation and pyroptosis were inhibited. IRF4 knockdown hinders the development of CRSsNP by inhibiting the inflammatory response and NLRP3/Caspase-1/GSDMD-mediated pyroptosis, which offers novel promising treatment strategies for clinical intervention.

Parameters optimization for decontamination and fine physical regeneration pathways of polypropylene plastics from waste lunchboxes.

Due to the development of the food delivery industry, a large amount of waste lunchboxes made of homo polypropylene (PP) plastic have been generated. This study developed a new technological strategy to effectively regenerate PP from waste lunchboxes. Through response surface curve analysis, it was found that under the optimal process conditions of hot alkali washing at 80 â„ƒ, 30 min, and pH 13, the optimal contact angle was 65.55°, indicating a good oil stain removal effect. By identifying and analyzing the characteristics of impurities in waste lunchboxes, a physical sorting and granulation regeneration process was constructed. And through large-scale statistical analysis and data collection, it was further verified that recycled PP plastics maintained their physical stability and excellent processing performance. The quality stability of recycled PP plastics in terms of impurities content was also verified. By designing different formulations specifically, recycled PP was mixed with different virgin PP and antioxidants in appropriate proportions, and extruded into particles under 150-300 mesh filtration conditions to obtain modified recycled PP. Modified recycled PP was applied in textiles, clothing, and injection molded products. In conclusion, we achieve the up-cylcing of waste PP lunchboxes instead of down-cylcing.

Co-formulation of the rF1V plague vaccine with depot-formulated cytokines enhances immunogenicity and efficacy to elicit protective responses against aerosol challenge in mice.

This study evaluated a depot-formulated cytokine-based adjuvant to improve the efficacy of the recombinant F1V (rF1V) plague vaccine and examined the protective response following aerosol challenge in a murine model. The results of this study showed that co-formulation of the Alhydrogel-adsorbed rF1V plague fusion vaccine with the depot-formulated cytokines recombinant human interleukin 2 (rhuIL-2) and/or recombinant murine granulocyte macrophage colony-stimulating factor (rmGM-CSF) significantly enhances immunogenicity and significant protection at lower antigen doses against a lethal aerosol challenge. These results provide additional support for the co-application of the depot-formulated IL-2 and/or GM-CSF cytokines to enhance vaccine efficacy.

Empowering precise advertising with Fed-GANCC: A novel federated learning approach leveraging Generative Adversarial Networks and group clustering.

In the realm of targeted advertising, the demand for precision is paramount, and the traditional centralized machine learning paradigm fails to address this necessity effectively. Two critical challenges persist in the current advertising ecosystem: the data privacy concerns leading to isolated data islands and the complexity in handling non-Independent and Identically Distributed (non-IID) data and concept drift due to the specificity and diversity in user behavior data. Current federated learning frameworks struggle to overcome these hurdles satisfactorily. This paper introduces Fed-GANCC, an innovative federated learning framework that synergizes Generative Adversarial Networks (GANs) and Group Clustering. The framework incorporates a user data augmentation algorithm predicated on adversarial generative networks to enrich user behavior data, curtail the impact of non-uniform data distribution, and enhance the applicability of the global machine learning model. Unlike traditional approaches, our framework offers user data augmentation algorithms based on adversarial generative networks, which not only enriches user behavior data but also reduces the challenges posed by non-uniform data distribution, thereby enhancing the applicability of the global machine learning (ML) model. The effectiveness of Fed-GANCC is distinctly showcased through experimental results, outperforming contemporary methods like FED-AVG and FED-SGD in terms of accuracy, loss value, and receiver operating characteristic (ROC) indicators within the same computing time. Experimental results vindicate the effectiveness of Fed-GANCC, revealing substantial enhancements in accuracy, loss value, and receiver operating characteristic (ROC) metrics compared to FED-AVG and FED-SGD given the same computational time. These outcomes underline Fed-GANCC's exceptional prowess in mitigating issues such as isolated data islands, non-IID data, and concept drift. With its novel approach to addressing the prevailing challenges in targeted advertising such as isolated data islands, non-IID data, and concept drift, the Fed-GANCC framework stands as a benchmark, paving the way for future advancements in federated learning solutions tailored for the advertising domain. The Fed-GANCC framework promises to offer pivotal insights for the future development of efficient and advanced federated learning solutions for targeted advertising.

Obacunone, a Promising Phytochemical Triterpenoid: Research Progress on Its Pharmacological Activity and Mechanism.

Obacunone, a natural triterpenoid, is an active component of the herbs Dictamnus dasycarpus Turcz. and Phellodendron amurense Rupr, and an indicator of the herbs' quality. Owing to its multiple health benefits, several studies have investigated the multi-targeting potential action mechanisms of obacunone. To summarize recent developments on the pharmacological actions of obacunone and focus on the underlying molecular mechanisms and signaling networks, we searched PubMed, Europe PMC, Wiley Online Library, Web of Science, Google Scholar, Wanfang Medical Network, and China National Knowledge Infrastructure for articles published prior to March 2024. Existing research indicates obacunone has great potential to become a promising therapeutic option against tumors, fibrotic diseases, bone and cholesterol metabolism diseases, and infections of pathogenic microorganisms, among others. The paper contributes to providing up-to-date references for further research and clinical applications of obacunone.