BackgroundAs malaria endemic countries shift from control to elimination, the proportion of low density Plasmodium falciparum infections increases. Current field diagnostic tools, such as microscopy and rapid diagnostic tests (RDT), with detection limits of approximately 100–200 parasites/µL (p/µL) and 800–1000 pg/mL histidine-rich protein 2 (HRP2), respectively, are unable to detect these infections. A novel ultra-sensitive HRP2-based Alere™ Malaria Ag P.f RDT (uRDT) was evaluated in laboratory conditions to define the test’s performance against recombinant HRP2 and native cultured parasites.ResultsThe uRDT detected dilutions of P. falciparum recombinant GST-W2 and FliS-W2, as well as cultured W2 and ITG, diluted in whole blood down to 10–40 pg/mL HRP2, depending on the protein tested. uRDT specificity was 100% against 123 archived frozen whole blood samples. Rapid test cross-reactivity with HRP3 was investigated using pfhrp2 gene deletion strains D10 and Dd2, pfhrp3 gene deletion strain HB3, and controls pfhrp2 and pfhrp3 double deletion strain 3BD5 and pfhrp2 and pfhrp3 competent strain ITG. The commercial Standard Diagnostics, Inc. BIOLINE Malaria Ag P.f RDT (SD-RDT) and uRDT detected pfhrp2 positive strains down to 49 and 3.13 p/µL, respectively. The pfhrp2 deletion strains were detected down to 98 p/µL by both tests.ConclusionThe performance of the uRDT was variable depending on the protein, but overall showed a greater than 10-fold improvement over the SD-RDT. The uRDT also exhibited excellent specificity and showed the same cross-reactivity with HRP3 as the SD-RDT. Together, the results support the uRDT as a more sensitive HRP2 test that could be a potentially effective tool in elimination campaigns. Further clinical evaluations for this purpose are merited.

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PurposeSweat is a relatively unexplored biofluid for diagnosis and monitoring of disease states. In this study, the proteomic profiling of immune‐related biomarkers from healthy individuals are presented.Experimental DesignEccrine sweat samples are collected from 50 healthy individuals. LC‐MS/MS is performed on two pools of sweat samples from five male and female participants. Individual sweat samples are analyzed by antibody isotyping microarrays (n = 49), human cytokine arrays (n = 30), and quantitative ELISAs for interleukin‐1α (n = 16), epidermal growth factor (n = 6), and angiogenin (n = 7).ResultsIn sweat, 220 unique proteins are identified by shotgun analysis. Detectable antibody isotypes include IgA (100% positive; median 1230 ± 28 700 pg mL−1), IgD (18%; 22.0 ± 119 pg mL−1), IgG1 (96%; 1640 ± 6750 pg mL−1), IgG2 (37%; 292 ± 6810 pg mL−1), IgG3 (71%; 74.0 ± 119 pg mL−1), IgG4 (69%; 43.0 ± 42.0 pg mL−1), and IgM (41%; 69.0 ± 1630 pg mL−1). Of 42 cytokines, three are readily detected in all sweat samples (p < 0.01). The median concentration for interleukin‐1α is 352 ± 521 pg mL−1, epidermal growth factor is 86.5 ± 147 pg mL−1, and angiogenin is 38.3 ± 96.3 pg mL−1. Multiple other cytokines are detected at lower levels.Conclusions and Clinical RelevanceSweat can be used for profiling antibodies and innate immune biomarkers.

Antibiotic resistance is a worldwide and growing clinical problem. With limited drug development in the antibacterial space, combination therapy has emerged as a promising strategy to combat multidrug‐resistant bacteria. Antibacterial combinations can improve antibiotic efficacy and suppress antibacterial resistance through independent, synergistic, or even antagonistic activities. Combination therapies are famously used to treat viral and mycobacterial infections and cancer. However, antibacterial combinations are only now emerging as a common treatment strategy for other bacterial infections owing to challenges in their discovery, development, regulatory approval, and commercial/clinical deployment. Here, we focus on discovery—where the sheer scale of combinatorial chemical spaces represents a significant challenge—and discuss how combination therapy can impact the treatment of bacterial infections. Despite these challenges, recent advancements, including new in silico methods, theoretical frameworks, and microfluidic platforms, are poised to identify the new and efficacious antibacterial combinations needed to revitalize the antibacterial drug pipeline.

BackgroundA significant relationship has been reported in which Ki-67/MIB-1 expression is correlated with survival in cervical cancer patients. However, the prognostic value of Ki-67/MIB-1 in cervical cancer is still not well understood.Material/MethodA meta-analysis was carried out to explore the prognostic value of Ki-67/MIB-1 on overall survival (OS) and/or disease-free survival (DFS) in cervical cancer. The databases of PubMed, ISI Web of Science, EMBASE, Cochrane Central Register of Controlled Trials, ScienceDirect, and Wiley Online Library were used to identify relevant literature.ResultsWe included 18 studies covering 1344 patients in the meta-analysis. The effect of Ki-67/MIB-1 on OS for pooled random effects HR estimate was 1.63 (95% confidence intervals (CI) 1.09–2.45; P<0.05). Subgroup analysis by ethnicity suggested that high expression of Ki-67/MIB-1 had association with Asians (1.84, 95% CI 1.04–3.23), but not with Africans (HR=1.53, 95% CI 0.34–6.86) or Europeans (HR=1.29, 95% CI 0.74–2.23). Furthermore, subgroup analysis of diverse treatments revealed no difference in surgery (HR=1.97, 95% CI 0.78–4.99) and radiation therapy (RT) (HR=1.56, 95% CI 0.93–2.63). The pooled HR for DFS was 1.26 (95% CI 0.58–2.73; P>0.05) and the subgroup analysis indicated Ki-67/MIB1 was associated with DFS (HR=3.67, 95% CI 2.65–5.09) in Asians. In the treatment subgroup analysis, no direct value was found among surgery (HR=1.13, 95% CI 0.10–13.53) and RT (HR=1.26, 95% CI 0.71–2.24).ConclusionsOur meta-analysis concludes that Ki-67/MIB-1 had a prognostic value for OS in cervical cancer patients. To further evaluate the prognostic role of Ki-67/MIB-1 on DFS, studies with larger numbers of patients are needed to validate our findings.

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An effective method of combating infectious diseases is the deployment of hand-held devices at the point-of-care (POC) for screening or self-monitoring applications. There is a need for very sensitive, low-cost and quantitative diagnostic devices. In this study, we present a low-cost, multiplexed fluorescence detection platform that has a high sensitivity and wide dynamic range. Our system features inexpensive 3×3 mm interference filter with a high stopband rejection, sharp transition edges, and greater than 90% transmission in the passband. In addition to the filters we improve signal-to-noise ratio by leveraging time for accuracy using a charge-integration-based readout. The fluorescence sensing platform provides a sensitivity to photon flux of ∼1×104 photons/mm2sec and has the potential for 2 to 3 orders of magnitude improvement in sensitivity over standard colorimetric detection that uses colored latex microspheres. We also detail the design, development, and characterization of our low-cost fluorescence detection platform and demonstrate 100% and 97.96% reduction in crosstalk probability and filter cost, respectively. This is achieved by reducing fi r dimensions and ensuring appropriate channel isolation in a 2×2 array configuration. Practical considerations with low-cost interference fi system design, analysis, and system performance are also discussed. The performance of our platform is compared to that of a standard laboratory array scanner. We also demonstrate the detection of antibodies to human papillomavirus (HPV16) E7 protein, as a potential biomarker for early cervical cancer detection in human plasma.

The COVID-19 pandemic has demonstrated a clear need for high-throughput, multiplexed, and sensitive assays for detecting SARS-CoV-2 and other respiratory viruses as well as their emerging variants. Here, we present microfluidic CARMEN (mCARMEN), a cost-effective virus and variant detection platform that combines CRISPR-based diagnostics and microfluidics with a streamlined workflow for clinical use. We developed the mCARMEN respiratory virus panel (RVP) and demonstrated its diagnostic-grade performance on 533 patient specimens in an academic setting and then 166 specimens in a clinical setting. We further developed a panel to distinguish 6 SARS-CoV-2 variant lineages, including Delta and Omicron, and evaluated it on 106 patient specimens, with near-perfect concordance to sequencing-based variant classification. Lastly, we implemented a combined Cas13 and Cas12 approach that enables quantitative measurement of viral copies in samples. mCARMEN enables high-throughput surveillance of multiple viruses and variants simultaneously.