The optimization of loop-mediated isothermal amplification (LAMP) as a diagnostic tool for low-density, asymptomatic malaria infections

Current diagnostic tools for malaria lack the sensitivity to identify individuals with low-density infections. Asymptomatic low-density infections are common in malaria endemic regions and these individuals provide an important reservoir of infection that enables transmission to mosquitoes. Failure to detect these individuals threatens the global health goal of malaria elimination. Loop-mediated isothermal amplification (LAMP) is a technique to amplify DNA and has the potential to diagnose these individuals. The LAMP assay was assessed in a field study in rural Vietnam. 5421 samples were collected and tested with a commercially available LAMP assay in Commune Health Care Centres in Binh Phuoc and Dak Nong Provinces. 101 positive LAMP cases (asymptomatic, smear, and RDT negative) were identified, with the proportion of positives ranging from 0.18% and 3.25% across five communes. In order for LAMP to be used as a screening tool, it must be cost effective and have a workflow suitable for minimally trained end users. To achieve this, an in-house LAMP assay was developed and compared to PCR. The assay was combined with instrument detection to simplify decision making for the end user and improve sensitivity. The in-house assay was as sensitive as the PCR assay and cost US$0.60 per reaction compared to US$3.57 for PCR and US$8.23 for the commercial LAMP. An integrated single cartridge, called T1, was assessed to further simplify this workflow of sample preparation, LAMP amplification and detection. Further development of the cartridge and the assay will be required for future deployment. The LAMP assay is suitable for detection of low density infections in asymptomatically infected individuals in field settings and has the potential for cost effective population based screening.Doctor of Philosoph

Enhancing Measurements of the CMB Blackbody Temperature Power Spectrum by Removing CIB and Thermal Sunyaev-Zel'dovich Contamination Using External Galaxy Catalogs

Extracting the CMB blackbody temperature power spectrum -- which is dominated by the primary CMB signal and the kinematic Sunyaev-Zel'dovich (kSZ) effect -- from mm-wave sky maps requires cleaning other sky components. In this work, we develop new methods to use large-scale structure (LSS) tracers to remove cosmic infrared background (CIB) and thermal Sunyaev-Zel'dovich (tSZ) contamination in such measurements. Our methods rely on the fact that LSS tracers are correlated with the CIB and tSZ signals, but their two-point correlations with the CMB and kSZ signals vanish on small scales, thus leaving the CMB blackbody power spectrum unbiased after cleaning. We develop methods analogous to delensing ($\textit{de-CIB}$ or $\textit{de-(CIB+tSZ)}$) to clean CIB and tSZ contaminants using these tracers. We compare these methods to internal linear combination (ILC) methods, including novel approaches that incorporate the tracer maps in the ILC procedure itself, without requiring exact assumptions about the CIB SED. As a concrete example, we use the $\textit{unWISE}$ galaxy samples as tracers. We provide calculations for a combined Simons Observatory and $\textit{Planck}$-like experiment, with our simulated sky model comprising eight frequencies from 93 to 353 GHz. Using $\textit{unWISE}$ tracers, improvements with our methods over current approaches are already non-negligible: we find improvements up to 20% in the kSZ power spectrum signal-to-noise ratio (SNR) when applying the de-CIB method to a tSZ-deprojected ILC map. These gains could be more significant when using additional LSS tracers from current surveys, and will become even larger with future LSS surveys, with improvements in the kSZ power spectrum SNR up to 50%. For the total CMB blackbody power spectrum, these improvements stand at 4% and 7%, respectively. Our code is publicly available at https://github.com/olakusiak/deCIBing.Comment: 35+21 pages, 20+11 figures; code is available at https://github.com/olakusiak/deCIBin

Accurate estimation of angular power spectra for maps with correlated masks

The widely used MASTER approach for angular power spectrum estimation was developed as a fast $C_{\ell}$ estimator on limited regions of the sky. This method expresses the power spectrum of a masked map ("pseudo-$C_\ell$") in terms of the power spectrum of the unmasked map (the true $C_\ell$) and that of the mask or weight map. However, it is often the case that the map and mask are correlated in some way, such as point source masks used in cosmic microwave background (CMB) analyses, which have nonzero correlation with CMB secondary anisotropy fields and other mm-wave sky signals. In such situations, the MASTER approach gives biased results, as it assumes that the unmasked map and mask have zero correlation. While such effects have been discussed before with regard to specific physical models, here we derive a completely general formalism for any case where the map and mask are correlated. We show that our result ("reMASTERed") reconstructs ensemble-averaged pseudo-$C_\ell$ to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. In particular, we obtain an improvement in the mean absolute percent error from 30% with the MASTER result to essentially no error with the reMASTERed result for an integrated Sachs-Wolfe (ISW) field map with a mask built from the thresholded ISW field, and 10% to effectively zero for a Compton-$y$ map combined with an infrared source mask (the latter being directly relevant to actual data analysis). An important consequence of our result is that for maps with correlated masks it is no longer possible to invert a simple equation to obtain the true $C_\ell$ from the pseudo-$C_\ell$. Instead, our result necessitates the use of forward modeling from theory space into the observable domain of the pseudo-$C_\ell$. Our code is publicly available at https://github.com/kmsurrao/reMASTERed.Comment: 14+9 pages, 6+6 figures; matches the version accepted for publication in PRD (https://journals.aps.org/prd/abstract/10.1103/PhysRevD.107.083521); code available at at https://github.com/kmsurrao/reMASTERe

Dorsal-Ventral Differences in Retinal Structure in the Pigmented Royal College of Surgeons Model of Retinal Degeneration: Retinal Changes in the RCS With Age

Retinitis pigmentosa is a family of inherited retinal degenerations associated with gradual loss of photoreceptors, that ultimately leads to irreversible vision loss. The Royal College of Surgeon's (RCS) rat carries a recessive mutation affecting mer proto-oncogene tyrosine kinase (merTK), that models autosomal recessive disease. The aim of this study was to understand the glial, microglial, and photoreceptor changes that occur in different retinal locations with advancing disease. Pigmented RCS rats (RCS-p+/LAV) and age-matched isogenic control rdy (RCS-rdy +p+/LAV) rats aged postnatal day 18 to 6 months were evaluated for in vivo retinal structure and function using optical coherence tomography and electroretinography. Retinal tissues were assessed using high resolution immunohistochemistry to evaluate changes in photoreceptors, glia and microglia in the dorsal, and ventral retina. Photoreceptor dysfunction and death occurred from 1 month of age. There was a striking difference in loss of photoreceptors between the dorsal and ventral retina, with a greater number of photoreceptors surviving in the dorsal retina, despite being adjacent a layer of photoreceptor debris within the subretinal space. Loss of photoreceptors in the ventral retina was associated with fragmentation of the outer limiting membrane, extension of glial processes into the subretinal space that was accompanied by possible adhesion and migration of mononuclear phagocytes in the subretinal space. Overall, these findings highlight that breakdown of the outer limiting membrane could play an important role in exacerbating photoreceptor loss in the ventral retina. Our results also highlight the value of using the RCS rat to model sectorial retinitis pigmentosa, a disease known to predominantly effect the inferior retina

class_sz I: Overview

class_sz is a versatile and robust code in C and Python that can compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks (https://github.com/CLASS-SZ/notebooks). It will be presented in full detail in paper II. Here we give a brief overview of key features and usage.Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Science

Physician ability to assess rheumatoid arthritis disease activity using an electronic medical record-based disease activity calculator

OBJECTIVE: To assess physicians\u27 concordance with Disease Activity Score in 28 joints (DAS28) categories calculated by an electronic medical record (EMR)-embedded disease activity calculator, as well as attitudes toward this application. METHODS: Fifteen rheumatologists used the EMR-embedded disease activity calculator to predict a rheumatoid arthritis (RA) DAS28 disease activity category at the time of each clinical encounter. RESULTS: Physician-predicted DAS28 disease activity categories ranged from high ( \u3e 5.1, 15% of cohort, 66 of 429 patient visits) to moderate ( \u3e 3.2-5.1, 21% of cohort, 90 of 429 patient visits) to low (2.6-3.2, 29% of cohort, 123 of 429 patient visits) to remission ( \u3c 2.6, 35% of cohort, 150 of 429 patient visits). Overall concordance between calculated DAS28 results and physician-predicted RA disease activity was 64%. Using either the physician-predicted or the calculated DAS28 category as the gold standard, accuracy was greatest for patients in remission (75% and 88% accuracy, respectively) and those with high disease activity (68% and 79% accuracy, respectively), and less for patients with moderate (48% and 62% accuracy, respectively) or low disease activity (62% and 31% accuracy, respectively). CONCLUSION: Accurate physician prediction of DAS28 remission and high disease activity categories, even without immediate availability of the erythrocyte sedimentation rate or the C-reactive protein level at the time of the visit, may be used to guide quantitatively driven outpatient RA management

Going beyond RGD: Screening of a cell-adhesion peptide library in 3D cell culture

In tissue engineering, cell-adhesion peptides (CAPs) such as the ubiquitous arginine-glycine-aspartic acid (RGD) sequence have allowed the functionalization of synthetic materials to mimic macromolecules of the extracellular matrix (ECM). However, the variety of ECM macromolecules makes it challenging to reproduce all of the native tissue functions with only a limited variety of CAPs. Screening of libraries of CAPs, analogous to high-throughput drug discovery assays, can help to identify new sequences directing cell organization. However, challenges to this approach include the automation of cell seeding in three dimensions and characterization methods. Here, we report a method for robotically generating a library of 16 CAPs to identify a microenvironment capable of directing a chain-like morphology in olfactory ensheathing cells (OECs), a cell type of particular interest for guiding axon growth in spinal cord injury repair. This approach resulted in the identification of one CAP not previously reported to interact with OECs to direct their morphology into structures suitable for potential axon guidance. The same screening approach should be applicable to any range of cell types to discover new CAPs to direct cell fate or function.</p