Factor V Leiden and thrombosis in patients with systemic lupus erythematosus: a meta-analysis.

The aim of this study was to perform a meta-analysis of the association between the factor V Leiden polymorphism (FVL) and thrombosis among patients with systemic lupus erythematosus (SLE) and/or antiphospholipid antibody (aPL) positivity. Included studies recruited patients based on SLE or aPL-positive status, confirmed subjects' SLE diagnosis as defined by the American College of Rheumatology, and documented thrombotic events. Excluded studies were non-English or considered only arterial thrombosis. Individual patient data, available from 5 studies, together with unpublished data from 1210 European-American SLE patients from the UCSF Lupus Genetics Collection genotyped for FVL, were further analyzed. Seventeen studies (n=2090 subjects) were included in the initial meta-analysis. Unadjusted odds ratios (OR) were calculated to assess association of FVL with thrombosis. The OR for association of thrombosis with FVL was 2.88 (95% confidence interval (CI) 1.98-4.20). In the secondary analysis with our individual patient dataset (n=1447 European-derived individuals), SLE subjects with the FVL polymorphism still had more than two times the odds of thrombosis compared to subjects without this polymorphism, even when adjusting for covariates such as gender, age and aPL status. SLE and/or aPL-positive patients with the FVL variant have more than two times the odds of thrombosis compared to those without this polymorphism

Neural development features: Spatio-temporal development of the Caenorhabditis elegans neuronal network

The nematode Caenorhabditis elegans, with information on neural connectivity, three-dimensional position and cell linage provides a unique system for understanding the development of neural networks. Although C. elegans has been widely studied in the past, we present the first statistical study from a developmental perspective, with findings that raise interesting suggestions on the establishment of long-distance connections and network hubs. Here, we analyze the neuro-development for temporal and spatial features, using birth times of neurons and their three-dimensional positions. Comparisons of growth in C. elegans with random spatial network growth highlight two findings relevant to neural network development. First, most neurons which are linked by long-distance connections are born around the same time and early on, suggesting the possibility of early contact or interaction between connected neurons during development. Second, early-born neurons are more highly connected (tendency to form hubs) than later born neurons. This indicates that the longer time frame available to them might underlie high connectivity. Both outcomes are not observed for random connection formation. The study finds that around one-third of electrically coupled long-range connections are late forming, raising the question of what mechanisms are involved in ensuring their accuracy, particularly in light of the extremely invariant connectivity observed in C. elegans. In conclusion, the sequence of neural network development highlights the possibility of early contact or interaction in securing long-distance and high-degree connectivity

Lessons from a year of COVID-19 in Zambia: reported attendance and mask wearing at large gatherings in rural communities

Zambia instituted prevention behavior guidelines for social gatherings before the first case of COVID-19 was confirmed on March 18, 2020. Guidelines included nonpharmaceutical interventions (NPIs) including mask wearing, social distancing, and reducing sizes of gatherings. Within a larger cluster randomized trial of community-based parenting groups in four rural districts (three in Southern Province, one in Eastern Province), we collected 5,711 questionnaires from intervention participants between August 2020 and September 2021, during which the country saw two COVID-19 waves. Questionnaires asked about participation and behaviors at community gatherings. Generally, perception of risk of contracting COVID-19 was low for respondents in districts in Southern Province but higher for those in Eastern Province. The highest compliance to mask wearing was reported at clinics (84%) and church services (81%), which were the most frequently attended gatherings. Many funerals were attended by 200 to 300 people, but individuals were 30% less likely to report wearing masks (odds ratio [OR] = 0.71, 95% confidence ratio [CI]: 0.6-0.8) than those attending a clinic visit. After controlling for other variables, the odds of self-reported mask wearing at events were higher in January to March 2021 (adjusted OR = 1.5, 95% CI: 1.3, 1.7) and July and September of 2021 (adjusted OR = 3.0, 95% CI: 2.5-3.5), timepoints that broadly overlay with two COVID-19 peaks observed in Zambia. Results suggest guideline dissemination penetrated the rural areas. However, there is need to optimize the messaging to increase compliance to NPIs at high-risk gatherings, including funerals. The findings from this analysis should be considered as the COVID-19 pandemic continues to evolve

Unsupervised feature selection for noisy data

Feature selection techniques are enormously applied in a variety of data analysis tasks in order to reduce the dimensionality. According to the type of learning, feature selection algorithms are categorized to: supervised or unsupervised. In unsupervised learning scenarios, selecting features is a much harder problem, due to the lack of class labels that would facilitate the search for relevant features. The selecting feature difficulty is amplified when the data is corrupted by different noises. Almost all traditional unsupervised feature selection methods are not robust against the noise in samples. These approaches do not have any explicit mechanism for detaching and isolating the noise thus they can not produce an optimal feature subset. In this article, we propose an unsupervised approach for feature selection on noisy data, called Robust Independent Feature Selection (RIFS). Specifically, we choose feature subset that contains most of the underlying information, using the same criteria as the Independent component analysis (ICA). Simultaneously, the noise is separated as an independent component. The isolation of representative noise samples is achieved using factor oblique rotation whereas noise identification is performed using factor pattern loadings. Extensive experimental results over divers real-life data sets have showed the efficiency and advantage of the proposed algorithm.We thankfully acknowledge the support of the Comision Interministerial de Ciencia y Tecnologa (CICYT) under contract No. TIN2015-65316-P which has partially funded this work.Peer ReviewedPostprint (author's final draft

The White Dwarf Luminosity Functions from the Pan-STARRS 1 3π Steradian Survey

A large sample of white dwarfs is selected by both proper motion and colours from the Pan-STARRS 1 3{\pi} Steradian Survey Processing Version 2 to construct the White Dwarf Luminosity Functions of the discs and halo in the solar neighbourhood. Four-parameter astrometric solutions were recomputed from the epoch data. The generalised maximum volume method is then used to calculate the density of the populations. After removal of crowded areas near the Galactic plane and centre, the final sky area used by this work is 7.833 sr, which is 83% of the 3{\pi} sky and 62% of the whole sky. By dividing the sky using Voronoi tessellation, photometric and astrometric uncertainties are recomputed at each step of the integration to improve the accuracy of the maximum volume. Interstellar reddening is considered throughout the work. We find a disc-to-halo white dwarf ratio of about 100

Current–Voltage Characteristics in Individual Polypyrrole Nanotube, Poly(3,4-ethylenedioxythiophene) Nanowire, Polyaniline Nanotube, and CdS Nanorope

In this paper, we focus on current–voltage (I–V) characteristics in several kinds of quasi-one-dimensional (quasi-1D) nanofibers to investigate their electronic transport properties covering a wide temperature range from 300 down to 2 K. Since the complex structures composed of ordered conductive regions in series with disordered barriers in conducting polymer nanotubes/wires and CdS nanowires, all measured nonlinearI–Vcharacteristics show temperature and field-dependent features and are well fitted to the extended fluctuation-induced tunneling and thermal excitation model (Kaiser expression). However, we find that there are surprisingly similar deviations emerged between theI–Vdata and fitting curves at the low bias voltages and low temperatures, which can be possibly ascribed to the electron–electron interaction in such quasi-1D systems with inhomogeneous nanostructures

Adherence to Tuberculosis Therapy among Patients Receiving Home-Based Directly Observed Treatment: Evidence from the United Republic of Tanzania.

\ud \ud Non-adherence to tuberculosis (TB) treatment is the leading contributor to the selection of drug-resistant strains of Mycobacterium tuberculosis and subsequent treatment failure. Tanzania introduced a TB Patient Centred Treatment (PCT) approach which gives new TB patients the choice between home-based treatment supervised by a treatment supporter of their own choice, and health facility-based treatment observed by a medical professional. The aim of this study was to assess the extent and determinants of adherence to anti-TB therapy in patients opting for home-based treatment under the novel PCT approach. In this cross-sectional study, the primary outcome was the percentage of patients adherent to TB therapy as detected by the presence of isoniazid in urine (IsoScreen assay). The primary analysis followed a non-inferiority approach in which adherence could not be lower than 75%. Logistic regression was used to examine the influence of potentially predictive factors. A total of 651 new TB patients were included. Of these, 645 (99.1%) provided urine for testing and 617 patients (95.7%; 90%CI 94.3-96.9) showed a positive result. This result was statistically non-inferior to the postulated adherence level of 75% (p<0.001). Adherence to TB therapy under home-based Directly Observed Treatment can be ensured in programmatic settings. A reliable supply of medication and the careful selection of treatment supporters, who preferably live very close to the patient, are crucial success factors. Finally, we recommend a cohort study to assess the rate of adherence throughout the full course of TB treatment

Block of death-receptor apoptosis protects mouse cytomegalovirus from macrophages and is a determinant of virulence in immunodeficient hosts.

The inhibition of death-receptor apoptosis is a conserved viral function. The murine cytomegalovirus (MCMV) gene M36 is a sequence and functional homologue of the human cytomegalovirus gene UL36, and it encodes an inhibitor of apoptosis that binds to caspase-8, blocks downstream signaling and thus contributes to viral fitness in macrophages and in vivo. Here we show a direct link between the inability of mutants lacking the M36 gene (ΔM36) to inhibit apoptosis, poor viral growth in macrophage cell cultures and viral in vivo fitness and virulence. ΔM36 grew poorly in RAG1 knockout mice and in RAG/IL-2-receptor common gamma chain double knockout mice (RAGγC(-/-)), but the depletion of macrophages in either mouse strain rescued the growth of ΔM36 to almost wild-type levels. This was consistent with the observation that activated macrophages were sufficient to impair ΔM36 growth in vitro. Namely, spiking fibroblast cell cultures with activated macrophages had a suppressive effect on ΔM36 growth, which could be reverted by z-VAD-fmk, a chemical apoptosis inhibitor. TNFα from activated macrophages synergized with IFNγ in target cells to inhibit ΔM36 growth. Hence, our data show that poor ΔM36 growth in macrophages does not reflect a defect in tropism, but rather a defect in the suppression of antiviral mediators secreted by macrophages. To the best of our knowledge, this shows for the first time an immune evasion mechanism that protects MCMV selectively from the antiviral activity of macrophages, and thus critically contributes to viral pathogenicity in the immunocompromised host devoid of the adaptive immune system