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Background Cell division cycle 6 (CDC6) is a key licensing factor for DNA replication in the G1 and S phases. Besides initiating replication, CDC6 also helps establish and maintain the S-M checkpoint, ensuring genomic stability. Emerging evidence highlights its dysregulation in various cancers, implicating CDC6 in tumor progression and therapy resistance. However, a comprehensive pan-cancer analysis evaluating its diagnostic, prognostic and immunomodulatory potential remains lacking, underscoring the need for further investigation. Methods By integrating multi-omics datasets from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), cBioPortal, Human Protein Atlas (HPA), UALCAN and SangerBox, we employed systematic bioinformatics approaches to investigate the oncogenic role of CDC6 across multiple cancer types. Our analysis encompassed prognostic associations, mutational landscapes, tumor immune microenvironment (TIME) infiltration patterns and epigenetic regulation via DNA methylation, providing a pan-cancer perspective on CDC6’s potential role in tumorigenesis. In addition, CDC6’s role in melanoma cell proliferation, invasion and migration was experimentally assessed. Results Pan-cancer analysis demonstrated CDC6 as a consistently upregulated oncogene across multiple malignancies, exhibiting significantly elevated expression compared to normal tissues. Notably, CDC6 is closely associated with prognosis across various cancer types. Our investigation further revealed robust correlations between CDC6 expression and immune cell infiltration patterns. Epigenetic profiling identified significant associations between CDC6 expression and DNA methylation alterations in nine cancer types. Functional studies validated CDC6’s oncogenic role, where its overexpression significantly promoted cellular proliferation, migration and invasion in melanoma. Conclusions Our study demonstrates that CDC6 serves as a crucial oncogenic driver across diverse tumor types, establishing its dual utility as a diagnostic biomarker and independent prognostic indicator. Importantly, we identified a significant correlation between elevated CDC6 expression and specific immune microenvironment alterations, suggesting its potential as a predictive biomarker for immunotherapy response. These findings demonstrate CDC6’s dual role in cancer development and immune regulation, warranting further investigation into its mechanisms and therapeutic potential.

Along with the popularity of intelligent services and mobile services, service recommendation has become a key task, especially the task based on quality-of-service (QoS) in edge computing environment. Most existing service recommendation methods have some serious defects, and cannot be directly adopted in edge computing environment. For example, most of existing methods cannot learn deep features of users or services, but in edge computing environment, there are a variety of devices with different configurations and different functions, and it is necessary to learn deep features behind those complex devices. In order to fully utilize hidden features, this paper proposes a new matrix factorization (MF) model with deep features learning, which integrates a convolutional neural network (CNN). The proposed mode is named Joint CNN-MF (JCM). JCM is capable of using the learned deep latent features of neighbors to infer the features of a user or a service. Meanwhile, to improve the accuracy of neighbors selection, the proposed model contains a novel similarity computation method. CNN learns the neighbors features, forms a feature matrix and infers the features of the target user or target service. We conducted experiments on a real-world service dataset under a batch of cases of data densities, to reflect the complex invocation cases in edge computing environment. The experimental results verify that compared to counterpart methods, our method can consistently achieve higher QoS prediction results.

Leukocyte esterase test (LET) detection is a simple and inexpensive test performed by urinalysis. This study investigated the predictive value of LET for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) infection among men attending HIV and sexually transmitted infection (HIV/STI) clinics in Guangdong Province, China. A total of 5,509 urine samples were collected from HIV and sexually transmitted infection clinics in Guangdong Province between 2017 and 2019. Specimens from 5,464 males were tested by both LET and nucleic acid amplification test (NAAT). Of 5,464 males, 497 (9.1%) tested positive for CT or NG by NAAT, with respective prevalence rates of 6.4% (95% confidence interval [95% CI]: 5.8–7.1%) and 3.8% (95% CI: 3.3–4.3%), including 1.2% (95% CI: 0.9–1.4%) co-infected. Compared to the HIV-negative individuals, individuals living with HIV tend to have a higher prevalence of CT, NG and co-infection with CT and NG. The LET sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for CT were 46.4% (95% CI: 41.2–51.7%), 92.0% (95% CI: 91.2–92.7%), 28.4% (95% CI: 24.8–32.1%), and 96.1% (95% CI: 95.6–96.7%), respectively. The LET sensitivity, specificity, PPV, and NPV for NG were 68.4% (95% CI: 62.1–74.7%), 91.8% (95% CI: 91.1–92.6%), 25.0% (95% CI: 21.4–28.5%), and 98.7% (95% CI: 98.3–99%), respectively. Compared to the HIV-negative individuals, higher sensitivity and specificity were observed for HIV-positive individuals, but there was no statistical difference. The incremental cost-effectiveness ratio (ICER) using economic costs per additional person CT positive and NG positive was – $238.74 and –$ 145.60 compared with LET positive, respectively. LET is a cost-effective test and will be valuable for predicting CT and NG infection, which is highly prevalent in low- and middle-income countries.

Abstract Single-dose azithromycin is recommended for treating Chlamydia trachomatis infections. Here, we established an in vitro cell model of azithromycin-induced persistent infection. Azithromycin inhibited the replication of C. trachomatis in a dose–time-dependent manner. Electron microscopy indicated that small inclusions in the induced model contained enlarged, aberrant and non-infectious reticulate bodies. RT-PCR showed that C. trachomatis still has the ability to express the unprocessed 16S rRNA gene in the model and that C. trachomatis recovered after the removal of azithromycin with a peak recovery time of 24 h. The mutations in 23S rRNA, L4 and L22 genes were not found in persistent infection, and qRT-PCR analysis showed that the relative expression level of euo in azithromycin treated infection was upregulated while omcB was downregulated. In summary, this study provides a novel in vitro cell model to examine the characteristics of azithromycin-induced persistent infection and contribute to the development of treatments for C. trachomatis infection. This study provides a novel in vitro cell model to examine the characteristics of azithromycin-induced persistent infection and contribute to the development of treatments for Chlamydia trachomatis infection.

IntroductionChlamydia is the most common sexually transmitted disease worldwide. Many studies have been evaluated the prevalence of Chlamydia trachomatis (CT) infection while very rare studies assessed the genotype distribution in urine among males attending sexually transmitted diseases (STD) clinics (MSCs)in China. This study aimed to investigate the prevalence and molecular epidemiology of CT infection by urine samples among MSCs from different geographic areas of Guangdong province, China.MethodsA cross-sectional study was performed among MSCs from ten HIV surveillance sites of Guangdong province, China. CT DNA in male urines were extracted and detected by using the Roche cobas 4800 CT/NG. The ompA genes were amplified by nested polymerase chain reaction and sequenced. Urine leukocyte esterase test were performed.ResultsOf the 1926 urine specimens, 1903 urines were successfully validated for detection of CT. Of the 1903 samples, one hundred and sixty-three (8.6%, 95% CI 8.2% to 9.0%) were found to be positive for CT. One hundred and thirty CT positive specimens were successfully genotyped by nested PCR, resulting in eight genotypes. The most prevalent genotypes were D, E, F, and J with proportions of 20.8%, 20.0%, 17.7%, 16.9%, respectively. There was no significant difference between age, geographic area, leukocyte esterase test and genotype distribution.ConclusionThere was a high prevalence of CT infection among males attending STD clinics in eastern area of Guangdong province, China. Promoting detection and molecular epidemiology research are needed for effective and comprehensive prevention and control programs.

Gonorrhea caused by Neisseria gonorrhoeae has spread world-wide. Antimicrobial-resistant strains have emerged to an alarming level to most antibiotics, including to the ceftriaxone-azithromycin combination, currently recommended as first-line dual therapy. Rapid testing for antimicrobial resistance will contribute to clinical decision-making for rational drug use and will slow this trend. Herein, we developed a Cas13a-based assay for N. gonorrhoeae detection (porA target) and azithromycin resistance identification (A2059G and C2611T point mutations). We evaluated the sensitivity and specificity of this method, and 10 copies per reaction can be achieved in porA detection and C2611T identification, with no cross-reactions. Comparison of the Cas13a-based assay (porA target) with Roche Cobas 4800 assay (n=23 urine samples) revealed 100% concordance. Isolated N. gonorrhoeae strains were used to validate the identification of A2059G and C2611T resistance mutations. All tested strains (8 A2059G strains, 8 C2611T strains, and 8 wild-type strains) were successfully distinguished by our assay and verified by testing MIC for azithromycin and sequencing the 23S rRNA gene. We adopted lateral flow for the SHERLOCK assay readout, which showed a visible difference between test group and NC group results. To further evaluate the capability of our assay, we tested 27 urethral swabs from patients with urethritis for N. gonorrhoeae detection and azithromycin-resistance identification. Of these, 62.96% (17/27) strains were detected with no mutant strains and confirmed by sequencing. In conclusion, the novel Cas13a-based assay for rapid and accurate N. gonorrhoeae detection combined with azithromycin drug resistance testing is a promising assay for application in clinical practice.

In this work, PtCo nanoparticles (NPs) on hierarchically ordered mesoporous carbon (PtCo/OMC) are synthesized for polymer electrolyte membrane fuel cells (PEMFCs) aiming to improve the activity and durability of the Pt-based catalyst towards oxygen reduction reaction (ORR). Specifically, the OMC is prepared through a solvent evaporation-induced self-assembly (EISA) method by using a triblock copolymer PEO-PPO-PEO as the structure agent, followed by annealing in the nitrogen atmosphere to decompose the structure agent and to carbonize the carbon precursor. PtCo nanoparticles (NPs) are fabricated with an average diameter of 3.3 nm by H 2 reduction and galvanic replacement in an acid solution, and then are uniformly dispersed onto the OMC via impregnation. The typical mesoporous structure of the OMC enhances the uniformly distribution and thermal stability of the small-sized PtCo NPs. The activity and the durability of the as-prepared PtCo/OMC catalyst are investigated by cyclic voltammetry (CV) and single-cell test. In the electrochemical tests, PtCo/OMC exhibits a high ECSA value of 88.56 m 2 g −1 , and a ECSA retention of 77.5% after 5000 CV cycles. The results show that the PtCo/OMC catalyst is more active and more stable than the commercial-carbon-supported PtCo catalyst (PtCo/XC-72). Graphical abstract PtCo nanoparticles (NPs) on hierarchically ordered mesoporous carbon (PtCo/OMC) are synthesized aiming to improve the activity and stability of the Pt-based catalyst for the oxygen reduction reaction (ORR). Due to the natural mesoporous and graphite-carbon nanostructure of the OMC, the as-prepared PtCo/OMC catalyst is more active and more stable than the PtCo NPs on the commercial Vulcan @ XC-72 support (PtCo/XC-72), showing great potential in proton exchange membrane fuel cells (PEMFCs).