The control of African animal trypanosomosis (AAT) relies on accurate diagnostic tools. Serological diagnosis using ELISA is well-suited for surveillance due to its high-throughput capacity, low cost, and adaptability to rapid formats. However, the WOAH-recommended antibody ELISA for AAT, based on trypanosome lysates purified from rodent blood, can lack specificity and presents standardization challenges as well as ethical concerns. Recombinant proteins offer a solution to standardization, often improving specificity, though potentially at the expense of sensitivity. Combining multiple recombinant proteins can enhance sensitivity while maintaining specificity. Therefore, this study developed chimeric proteins for serological diagnosis of AAT, composed of highly immunoreactive regions from multiple known antigens using genetic engineering. Following an inventory of immunodominant antigens, we selected candidates and, using bioinformatics, designed five chimeric constructs in silico: three species-specific and two pan-trypanosome. The coding sequences for these chimeras were synthesized, cloned into expression vectors, and expressed in Escherichia coli. Purification was achieved through a series of chromatographic steps, including Ni-NTA affinity chromatography, Q Sepharose ion-exchange chromatography, and Sephadex 200 size-exclusion chromatography. Preliminary assessment of their reactivity with sera from cattle experimentally infected with Trypanosoma vivax, T. congolense or T. brucei yielded promising results. Longitudinal analysis comparing their reactivity with trypanosome lysates revealed that those specific to T. congolense, and T. vivax, as well as one pan-trypanosome, can discriminate pre- and post-infection sera. These observations confirm the potential of our chimeric constructs. Future work will involve evaluating these chimeras against a broader panel of sera.

Human babesiosis is a disease transmitted by the bite of an infected tick or via blood transfusions involving contaminated blood products; in humans, it can lead to severe complications and even death, depending on the clinical history, age and health status of the affected patient. Babesiosis is caused by members of the Babesia spp., protozoan parasites whose life cycle includes sexual reproduction in the arthropod vector and asexual reproduction in the mainly mammalian host. Cases of human babesiosis have been rare, but there are increasing reports of human babesiosis associated with climatic changes affecting the geographical distribution of the parasite and tick vector, enhanced vector–human interactions and improved awareness of the disease in humans. Diagnostics and treatment options for humans are based around discoveries in veterinary research, such as point-of-care testing in cases of bovine babesiosis, and include direct diagnosis by blood smears, polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) technologies, and indirect diagnosis by ELISA, immunofluorescence tests (IFAT) and fluorescent in situ hybridisation. Treatment involves a combination of drugs such as azithromycin and atovaquone, or clindamycin and quinine, but more effective options are being investigated, including, but not limited to, trans-chalcones and tafenoquine. Improved surveillance, awareness and diagnosis, as well as advanced technologies to interrupt vector–host interactions, are crucial in managing the increased threat posed by this once-neglected disease in humans.

Objectives: Periprosthetic joint infection (PJI) is one of the most serious and debilitating complications that can occur after total joint arthroplasty. Therefore, early diagnosis and appropriate treatment are important for a good prognosis. Recently, molecular diagnostic methods have been widely used to detect the causative microorganisms of PJI sensitively and rapidly. The Multiplex Loop- Mediated Isothermal Amplification (LAMP) method is faster and easier to perform compared to polymerase chain reaction (PCR)-based assays. Therefore, this study developed a multiplex LAMP assay for diagnosing bacterial PJI using LAMP technology and evaluated its analytical and clinical performance. Methods: We developed a multiplex LAMP assay for the detection of five bacteria: Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus agalactiae, Pseudomonas aeruginosa, and Escherichia coli, frequently observed to be the causative agents of PJI. The method limit of detection (LOD) and cross-reactivity were determined by spiking standard strains into the joint synovial fluid. The LOD of the multiplex LAMP assay was compared with that of a quantitative real-time PCR (qPCR) assay. Clinical performance was evaluated using 20 joint synovial fluid samples collected from patients suspected of having bacterial PJI. Results: The LOD of the gram-positive bacterial multiplex LAMP assay and qPCR were 105/104 CFU/mL, 103/103 CFU/mL, and 105/104 CFU/mL against S. agalactiae, S. epidermidis, and S. aureus, respectively. For P. aeruginosa and E. coli, the LOD of the multiplex LAMP and qPCR assays were 105/104 and 106/104 CFU/mL, respectively. The multiplex LAMP assay detects target bacteria without cross-reacting with other bacteria, and exhibited 100% sensitivity and specificity in clinical performance evaluation. Conclusions: This multiplex LAMP assay can rapidly detect five high-prevalence bacterial species causing bacterial PJI, with excellent sensitivity and specificity, in less than 1 h, and it may be useful for the early diagnosis of PJI.

Dengue is an arboviral infection that poses a substantial public health concern, with early diagnosis being a critical factor in effective management. However, limited diagnostic expertise in developing countries contributes to the under-reporting of dengue cases. This review compares the accuracy of rapid diagnostic tests (RDTs) and the tourniquet test (TT) in diagnosing dengue fever (DF) in non-laboratory-based settings. Relevant original articles on the use of RDTs and TT for dengue diagnosis were retrieved from PubMed, Scopus, and ScienceDirect. The STARD and QUADAS-2 tools were employed to evaluate the methodological quality of the included studies. Search terms included combinations of ‘fever’, ‘dengue’, and ‘“diagnosis’. In total, 23 articles were eligible for inclusion. The RDTs demonstrated mean sensitivities and specificities of 76.2% (SD = 13.8) and 91.5% (SD = 10.3), respectively, while the TT showed mean sensitivity and specificity values of 48.6% (SD = 24.9) and 79.5% (SD = 14.9), respectively. Overall, RDTs exhibited superior diagnostic performance compared to the TT. Our findings suggest that the TT is an inadequate stand-alone diagnostic tool for dengue. RDTs should be prioritized for dengue diagnosis in resource-limited settings. However, in situations where RDTs are unavailable, the TT may serve as a supplementary option.

The objective was to identify the predictive markers and develop a diagnostic model with predictive markers for Parkinson’s disease (PD) and investigate the roles of immune cells in the disease pathology. Microarray datasets of PD and control samples were obtained from the Gene Expression Omnibus (GEO) database. We then performed a comprehensive analysis of differentially expressed genes (DEGs), functional enrichment, and protein-protein interactions to pinpoint a set of promising candidate genes. To establish a diagnosis model for PD, we utilized machine learning algorithms and evaluated the corresponding diagnostic performance using the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). Additionally, the differential abundance of immune cell subsets between PD and control samples was evaluated using the single-sample Gene Set Enrichment Analysis (ssGSEA) method. A total of 264 DEGs were identified in GSE72267. The PPI network ultimately identified 30 hub genes for model construction. Seven genes, namely CD79B, CD40, CCR9, ADRA2A, SIGLEC1, FLT3LG, and THBD, were identified as diagnostic markers for PD, with an AUC of 0.870. This seven-gene signature model was subsequently validated in an independent cohort (GSE22491), demonstrating an AUC of 0.825. Ultimately, the infiltration of 28 immune cells showed that activated B cells, natural killer T cells, and regulatory T cells may contribute to the occurrence and progression of PD. We also found complex associations between these genes and immune cells. CD79B, CD40, CCR9, ADRA2A, SIGLEC1, FLT3LG, and THBD were identified as diagnostic markers for PD, and the infiltration of immune cells may contribute to the pathogenesis of the disease.

Biomarkers alone cannot resolve psychiatry’s diagnostic challenges, particularly the boundary between normal variation and pathology. Diagnosis should prioritise the subjective, phenomenological experiences of patients rather than solely relying on biological evidence, emphasising a framework centred on suffering, debilitation and societal impact.

The ‘overview effect’ was described by astronauts who saw the earth from space and found this gave them a very different perspective. This effect is a shift in worldview, and it has been suggested that politicians be sent to space to change their narrow perspectives. In a similar vein, it is crucial that psychiatrists have an overview of their patients so that their perspectives on patient care enable them to deal with the patient from different angles. In this editorial, the overview effect is described in the context of clinical care.