Gonorrhoea, caused by Neisseria gonorrhoeae, is a common sexually transmitted infection. Increasing multi-drug resistance and the impact of asymptomatic infections on sexual and reproductive health underline the need for an effective gonococcal vaccine. Outer membrane vesicles (OMVs) from Neisseria meningitidis induce modest cross-protection against gonococcal infection.
View Article and Find Full Text PDFBackground: Cephalometric landmark annotation is a key challenge in radiographic analysis, requiring automation due to its time-consuming process and inherent subjectivity. This study investigates the application of advanced transfer learning techniques to enhance the accuracy of anatomical landmarks in cephalometric images, which is a vital aspect of orthodontic diagnosis and treatment planning.
Methods: We assess the suitability of transfer learning methods by employing state-of-the-art pose estimation models.
The convenience and cost-effectiveness offered by cloud computing have attracted a large customer base. In a cloud environment, the inclusion of the concept of virtualization requires careful management of resource utilization and energy consumption. With a rapidly increasing consumer base of cloud data centers, it faces an overwhelming influx of Virtual Machine (VM) requests.
View Article and Find Full Text PDFDevelopment of a vaccine against gonorrhoea is a global priority, driven by the rise in antibiotic resistance. Although Neisseria gonorrhoeae (Ng) infection does not induce substantial protective immunity, highly exposed individuals may develop immunity against re-infection with the same strain. Retrospective epidemiological studies have shown that vaccines containing Neisseria meningitidis (Nm) outer membrane vesicles (OMVs) provide a degree of cross-protection against Ng infection.
View Article and Find Full Text PDFDespite the wealth of publicly available single-cell datasets, our understanding of distinct resident immune cells and their unique features in diverse human organs remains limited. To address this, we compiled a meta-analysis dataset of 114,275 CD45+ immune cells sourced from 14 organs in healthy donors. While the transcriptome of immune cells remains relatively consistent across organs, our analysis has unveiled organ-specific gene expression differences (GTPX3 in kidney, DNTT and ACVR2B in thymus).
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