Fluidic Control with Wax Valves for Paper-based Diagnostics

Paper-fluidic devices are a common platform for point-of-care disease detection in under-resourced areas because of their low cost and minimal instrumentation requirements. Limited fluidic control in paper-fluidic devices has hindered the incorporation of multistep reactions that are necessary for more sensitive disease detection. One potential fluidic control mechanism is the incorporation of thermally actuated wax valves to separate assay stages. Such valving would expand the detection capabilities of these devices by permitting fluid obstruction for sustained reactions and facilitating controlled volume release within a fully-automated, self-contained device. Despite the potential to exploit wax valves for innovative paper-fluidic diagnostics, a thorough, quantitative analysis of how they can best be used has not been performed. Here, in parallel macroscopic and microscopic analyses, we show that wax valves’ geometry and surface area in paper test strips influence flow behavior when thermally actuated. Macroscopic analysis evaluated the flow rate past the valves of the visible fluid front across the width of the membrane; microscopic analysis used particle image velocimetry to evaluate trends in particle flow before and after valve actuation. Preliminary results indicate that geometry and size influence valve opening times and the rate of fluid flow past the valves. Future analyses will compare the macroscopic and microscopic velocity profiles in various assay spaces and times to provide quantitative insight to the inner workings of paper-fluidic devices. This information will facilitate intelligent and efficient design of multistep paper-fluidic detection technologies with potential applications in lateral flow immunoassays, two-dimensional paper networks, and other point-of-care diagnostics

Smartphone-Based Microscope for Pathogen Detection

Vibrio cholerae is a water and food borne bacteria that causes cholera, a severe acute diarrheal disease, when ingested and when left untreated, can cause patient death within hours. Currently there is a lack of both sensitive and rapid portable detection technologies of V. cholerae for testing water and food samples. Combining nucleic acid amplification and particle diffusometry present an alternative detection method for V. cholerae in under 30 minutes, but the process requires an expensive laboratory microscope. In this work, we develop a smartphone-based microscope to detect V. cholerae DNA in environmental water samples using particle diffusometry. A modular iPhone case is designed with a detachable cartridge and an integrated ball lens to image a microfluidic sample slide. This sample slide is essential for performing the DNA amplification assay and contains the microparticles necessary for imaging and particle diffusometry measurements. The ball lenses to image these particles have diameters of 1.0, 0.79, and 0.5 millimeters and are tested in conjunction with the iPhone 6 camera to determine optimal magnification and focal length. We demonstrate the ability to detect the Brownian motion of 1.0 micrometer particles using a 0.5 millimeter ball lens with brightfield imaging. This field-portable imaging platform provides the capability to perform rapid detection of V. cholerae in the field, and in the future, can be applied toward detecting other diseases at the point of care

Dark Stars and Boosted Dark Matter Annihilation Rates

Dark Stars (DS) may constitute the first phase of stellar evolution, powered by dark matter (DM) annihilation. We will investigate here the properties of DS assuming the DM particle has the required properties to explain the excess positron and elec- tron signals in the cosmic rays detected by the PAMELA and FERMI satellites. Any possible DM interpretation of these signals requires exotic DM candidates, with an- nihilation cross sections a few orders of magnitude higher than the canonical value required for correct thermal relic abundance for Weakly Interacting Dark Matter can- didates; additionally in most models the annihilation must be preferentially to lep- tons. Secondly, we study the dependence of DS properties on the concentration pa- rameter of the initial DM density profile of the halos where the first stars are formed. We restrict our study to the DM in the star due to simple (vs. extended) adiabatic contraction and minimal (vs. extended) capture; this simple study is sufficient to illustrate dependence on the cross section and concentration parameter. Our basic results are that the final stellar properties, once the star enters the main sequence, are always roughly the same, regardless of the value of boosted annihilation or concentration parameter in the range between c=2 and c=5: stellar mass ~ 1000M\odot, luminosity ~ 10^7 L\odot, lifetime ~ 10^6 yrs (for the minimal DM models considered here; additional DM would lead to more massive dark stars). However, the lifetime, final mass, and final luminosity of the DS show some dependence on boost factor and concentration parameter as discussed in the paper.Comment: 37 pages, 11 figure

Towards the use of a smartphone imaging-based tool for point-of-care detection of asymptomatic low-density malaria parasitaemia

Background: Globally, there are over 200 million cases of malaria annually and over 400,000 deaths. Early and accurate detection of low-density parasitaemia and asymptomatic individuals is key to achieving the World Health Organization (WHO) 2030 sustainable development goals of reducing malaria-related deaths by 90% and eradication in 35 countries. Current rapid diagnostic tests are neither sensitive nor specific enough to detect the low parasite concentrations in the blood of asymptomatic individuals. Methods: Here, an imaging-based sensing technique, particle diffusometry (PD), is combined with loop mediated isothermal amplification (LAMP) on a smartphone-enabled device to detect low levels of parasitaemia often associated with asymptomatic malaria. After amplification, PD quantifies the Brownian motion of fluorescent nanoparticles in the solution during a 30 s video taken on the phone. The resulting diffusion coefficient is used to detect the presence of Plasmodium DNA amplicons. The coefficients of known negative samples are compared to positive samples using a one-way ANOVA post-hoc Dunnett's test for confirmation of amplification. Results: As few as 3 parasite/µL of blood was detectable in 45 min without DNA extraction. Plasmodium falciparum parasites were detected from asymptomatic individuals' whole blood samples with 89% sensitivity and 100% specificity when compared to quantitative polymerase chain reaction (qPCR). Conclusions: PD-LAMP is of value for the detection of low density parasitaemia especially in areas where trained personnel may be scarce. The demonstration of this smartphone biosensor paired with the sensitivity of LAMP provides a proof of concept to achieve widespread asymptomatic malaria testing at the point of care

Monotherapy treatment of epilepsy in pregnancy: congenital malformation outcomes in the child.

BackgroundPrenatal exposure to certain anti-seizure medications (ASMs) is associated with an increased risk of major congenital malformations (MCM). The majority of women with epilepsy continue taking ASMs throughout pregnancy and, therefore, information on the potential risks associated with ASM treatment is required.ObjectivesTo assess the effects of prenatal exposure to ASMs on the prevalence of MCM in the child.Search methodsFor the latest update of this review, we searched the following databases on 17 February 2022: Cochrane Register of Studies (CRS Web), MEDLINE (Ovid, 1946 to February 16, 2022), SCOPUS (1823 onwards), and ClinicalTrials.gov, WHO International Clinical Trials Registry Platform (ICTRP). No language restrictions were imposed.Selection criteriaWe included prospective cohort controlled studies, cohort studies set within pregnancy registries, randomised controlled trials and epidemiological studies using routine health record data. Participants were women with epilepsy taking ASMs; the two control groups were women without epilepsy and untreated women with epilepsy.Data collection and analysisFive authors independently selected studies for inclusion. Eight authors completed data extraction and/or risk of bias assessments. The primary outcome was the presence of an MCM. Secondary outcomes included specific types of MCM. Where meta-analysis was not possible, we reviewed included studies narratively.Main resultsFrom 12,296 abstracts, we reviewed 283 full-text publications which identified 49 studies with 128 publications between them. Data from ASM-exposed pregnancies were more numerous for prospective cohort studies (n = 17,963), than data currently available for epidemiological health record studies (n = 7913). The MCM risk for children of women without epilepsy was 2.1% (95% CI 1.5 to 3.0) in cohort studies and 3.3% (95% CI 1.5 to 7.1) in health record studies. The known risk associated with sodium valproate exposure was clear across comparisons with a pooled prevalence of 9.8% (95% CI 8.1 to 11.9) from cohort data and 9.7% (95% CI 7.1 to 13.4) from routine health record studies. This was elevated across almost all comparisons to other monotherapy ASMs, with the absolute risk differences ranging from 5% to 9%. Multiple studies found that the MCM risk is dose-dependent. Children exposed to carbamazepine had an increased MCM prevalence in both cohort studies (4.7%, 95% CI 3.7 to 5.9) and routine health record studies (4.0%, 95% CI 2.9 to 5.4) which was significantly higher than that for the children born to women without epilepsy for both cohort (RR 2.30, 95% CI 1.47 to 3.59) and routine health record studies (RR 1.14, 95% CI 0.80 to 1.64); with similar significant results in comparison to the children of women with untreated epilepsy for both cohort studies (RR 1.44, 95% CI 1.05 to 1.96) and routine health record studies (RR 1.42, 95% CI 1.10 to 1.83). For phenobarbital exposure, the prevalence was 6.3% (95% CI 4.8 to 8.3) and 8.8% (95% CI 0.0 to 9277.0) from cohort and routine health record data, respectively. This increased risk was significant in comparison to the children of women without epilepsy (RR 3.22, 95% CI 1.84 to 5.65) and those born to women with untreated epilepsy (RR 1.64, 95% CI 0.94 to 2.83) in cohort studies; data from routine health record studies was limited. For phenytoin exposure, the prevalence of MCM was elevated for cohort study data (5.4%, 95% CI 3.6 to 8.1) and routine health record data (6.8%, 95% CI 0.1 to 701.2). The prevalence of MCM was higher for phenytoin-exposed children in comparison to children of women without epilepsy (RR 3.81, 95% CI 1.91 to 7.57) and the children of women with untreated epilepsy (RR 2.01. 95% CI 1.29 to 3.12); there were no data from routine health record studies. Pooled data from cohort studies indicated a significantly increased MCM risk for children exposed to lamotrigine in comparison to children born to women without epilepsy (RR 1.99, 95% CI 1.16 to 3.39); with a risk difference (RD) indicating a 1% increased risk of MCM (RD 0.01. 95% CI 0.00 to 0.03). This was not replicated in the comparison to the children of women with untreated epilepsy (RR 1.04, 95% CI 0.66 to 1.63), which contained the largest group of lamotrigine-exposed children (> 2700). Further, a non-significant difference was also found both in comparison to the children of women without epilepsy (RR 1.19, 95% CI 0.86 to 1.64) and children born to women with untreated epilepsy (RR 1.00, 95% CI 0.79 to 1.28) from routine data studies. For levetiracetam exposure, pooled data provided similar risk ratios to women without epilepsy in cohort (RR 2.20, 95% CI 0.98 to 4.93) and routine health record studies (RR 0.67, 95% CI 0.17 to 2.66). This was supported by the pooled results from both cohort (RR 0.71, 95% CI 0.39 to 1.28) and routine health record studies (RR 0.82, 95% CI 0.39 to 1.71) when comparisons were made to the offspring of women with untreated epilepsy. For topiramate, the prevalence of MCM was 3.9% (95% CI 2.3 to 6.5) from cohort study data and 4.1% (0.0 to 27,050.1) from routine health record studies. Risk ratios were significantly higher for children exposed to topiramate in comparison to the children of women without epilepsy in cohort studies (RR 4.07, 95% CI 1.64 to 10.14) but not in a smaller comparison to the children of women with untreated epilepsy (RR 1.37, 95% CI 0.57 to 3.27); few data are currently available from routine health record studies. Exposure in utero to topiramate was also associated with significantly higher RRs in comparison to other ASMs for oro-facial clefts. Data for all other ASMs were extremely limited. Given the observational designs, all studies were at high risk of certain biases, but the biases observed across primary data collection studies and secondary use of routine health records were different and were, in part, complementary. Biases were balanced across the ASMs investigated, and it is unlikely that the differential results observed across the ASMs are solely explained by these biases.Authors' conclusionsExposure in the womb to certain ASMs was associated with an increased risk of certain MCMs which, for many, is dose-dependent

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Prevalence and architecture of de novo mutations in developmental disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year

The First Post-Kepler Brightness Dips of KIC 8462852

We present a photometric detection of the first brightness dips of the unique variable star KIC 8462852 since the end of the Kepler space mission in 2013 May. Our regular photometric surveillance started in October 2015, and a sequence of dipping began in 2017 May continuing on through the end of 2017, when the star was no longer visible from Earth. We distinguish four main 1-2.5% dips, named "Elsie," "Celeste," "Skara Brae," and "Angkor", which persist on timescales from several days to weeks. Our main results so far are: (i) there are no apparent changes of the stellar spectrum or polarization during the dips; (ii) the multiband photometry of the dips shows differential reddening favoring non-grey extinction. Therefore, our data are inconsistent with dip models that invoke optically thick material, but rather they are in-line with predictions for an occulter consisting primarily of ordinary dust, where much of the material must be optically thin with a size scale <<1um, and may also be consistent with models invoking variations intrinsic to the stellar photosphere. Notably, our data do not place constraints on the color of the longer-term "secular" dimming, which may be caused by independent processes, or probe different regimes of a single process