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Abstract Background Tuberculous meningitis (TBM) is a severe central nervous system (CNS) infection with a challenging diagnosis due to inadequate detection methods. This study evaluated current clinical detection methods and their applicability. Methods A cohort of 514 CNS infection patients from 2018 to 2020 was studied. Data on general demographics, Cerebrospinal Fluid (CSF) analysis, epidemiology, and clinical outcomes were collected. TBM patients were identified, and the sensitivities of mmetagenomic next-generation sequencing (NGS), GeneXpert, and microbial culture were compared. Kappa statistic assessed the consistency between methods. Results Among the patients involved, TBM (29%) and neurosyphilis (25%) were the two most prevalent CNS infections. CSF analysis indicated that 76% of patients had leukocytosis, suggesting a potential CNS inflammation. In TBM cases, 92.5% had elevated CSF protein and leukocyte counts. Moreover, the percentage of positive mNGS results was 55.6%. GeneXpert and MTB cultures alone had lower sensitivity, but combined use resulted in a 53.4% positive rate. Conclusions This study highlights the high sensitivity of mNGS, comparable to GeneXpert and MTB culture. The combined methods are cost-effective and straightforward, and can partially substitute for mNGS, offering valuable alternatives for TBM diagnosis and providing insights into multiple diagnostic strategies in clinical practice.

Objectives: Recent mpox outbreaks highlight diverse transmission modes, with sexual behavior prominent in China's IIb strain. Nevertheless, despite HPV being a common sexually transmitted pathogen, there is a paucity of research into its coexistence and genotype distribution within this patients population. Methods: We conducted a study at the Third People's Hospital of Shenzhen from May to September 2023. We collected information on mpox patients, including their sociodemographic and clinical characteristics. Anal swabs were collected for HPV genotyping. Results: Among 73 MSM mpox cases, HIV positivity was 56.2 % (41/73) and HPV positivity 80.4 % (41/51). Multiple HPV infections were prevalent (56.9 %, 29/51), especially among HIV-positive (93 %, 27/29). HPV16 (29.3 %, 12/41) was the most common high-risk genotype, followed by HPV59 (26.8 %, 10/41), HPV42 (19.5 %, 8/41), HPV6 (14.6 %, 6/41), and HPV54 (14.6 %, 6/41). HPV infection was significantly associated with HIV infection (p = 0.001). Additionally, HIV infection (p = 0.001) and PCR-detected positive sites for mpox (p = 0.047) were associated with high-risk HPV infection. Conclusions: In this study, most of the mpox patients were found to be infected with HPV, mostly with high-risk types and multiple infections. Therefore, it is strongly recommended that mpox-infected individuals intensify HPV-related screening, prevention, and treatment measures.

Triple-negative breast cancer (TNBC) is the most aggressive molecular subtype of breast cancer. Curcumol, as a natural small molecule compound, has potential anti-breast cancer activity. In this study, we chemically synthesized a derivative of curcumol, named HCL-23, by structural modification and explored its effect on and underlying mechanism regarding TNBC progression. MTT and colony formation assays demonstrated that HCL-23 significantly inhibited TNBC cells proliferation. HCL-23 induced G2/M phase cell cycle arrest and repressed the capability of migration, invasion, and adhesion in MDA-MB-231 cells. RNA-seq results identified 990 differentially expressed genes including 366 upregulated and 624 downregulated genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) revealed that these differentially expressed genes were obviously enriched in adhesion, cell migration, apoptosis, and ferroptosis. Furthermore, HCL-23 induced apoptosis via the loss of mitochondrial membrane potential and the activation of the caspase family in TNBC cells. In addition, HCL-23 was verified to trigger ferroptosis through increasing cellular reactive oxygen species (ROS), labile iron pool (LIP), and lipid peroxidation levels. Mechanistically, HCL-23 markedly upregulated the expression of heme oxygenase 1 (HO-1), and the knockdown of HO-1 could attenuate ferroptosis induced by HCL-23. In animal experiments, we found that HCL-23 inhibited tumor growth and weight. Consistently, the upregulation of Cleaved Caspase-3, Cleaved PARP, and HO-1 expression was also observed in tumor tissues treated with HCL-23. In summary, the above results suggest that HCL-23 can promote cell death through activating caspases-mediated apoptosis and HO-1-dependent ferroptosis in TNBC. Therefore, our findings provide a new potential agent against TNBC.

Improving the efficiency and safety of highway traffic relies heavily on accurately modeling the complex dynamics of traffic flow. This study aims to develop a novel method for modeling highway traffic flows by integrating data from multiple sources, such as roadside cameras, gantry cameras, and communication devices. The method leverages heterogeneous sensor data characteristics, temporal information, and spatial structures to achieve deep fusion of latent features at the sensor level. To minimize human intervention, a multistage training approach is employed, combining large-scale self-supervised learning with supervised fine-tuning, leveraging abundant unlabeled unstructured data such as monitoring videos recorded by roadside cameras and snapshots captured by gantry cameras, alongside limited accurate structured traffic flow data aggregated by communication devices from gantries and toll stations. We demonstrate the effectiveness and stability of the proposed method on a case study, the G92 ring highway around the Hangzhou Bay in Zhejiang Province, China, achieving the mean absolute percentage error of traffic flow within 7.5% and 8.3% for fixed and variable highway sensor networks, respectively. Ablation studies further demonstrate the significant improvement in predictive accuracy achieved by the designed self-supervised pretraining task. To summarize, our approach provides a promising solution for efficient and safe management of highway traffic flow, with potential applicability to real-world scenarios. [ABSTRACT FROM AUTHOR]