Quantitative Real-Time Pcr Assays For The Detection Of Leptospira

Leptospirosis is an infectious zoonotic disease caused by bacteria of the genus Leptospira. The genus is comprised of 40 pathogenic species divided among P1 (19) and P2 (21). Leptospirosis incurs a disproportionately large burden of disease in urban slum regions of developing countries that lack adequate sewage disposal, water treatment, and sanitation infrastructure. While P1 species have been identified in cases of human infection, it is unclear if all Leptospira species are capable of infecting humans, especially P2 species. Among P1 species, L. interrogans has been described as the most frequent specie to cause disease in both animals and humans, and varying pathogenicity has been identified in other pathogenic species. Real-time qPCR assays have been shown to identify Leptospira with high sensitivity and specificity; however, there is a lack of assays capable of targeting relevant species of Leptospira of specific clinical and environmental importance among both humans and animals. Thus, the purpose of this study was three-fold: (1) design a multiplex assay for the simultaneous detection of and discrimination between P1 and P2 species; (2) optimize a previous assay for the detection of all currently-named P1 species; and (3) create an assay for the specific detection of L. interrogans. Primers and probes were designed in silico utilizing the BioEdit software to evaluate sequences of all 68 species with available genomic sequences. In vitro sensitivity and specificity analyses were conducted on 28 reference species. Given the specificity and sensitivity of the developed assays, real-time qPCR assays may be useful in future epidemiological and clinical studies for the identification and quantification of various Leptospira species

Timed Fault Tree Models of the China Yongwen Railway Accident

Safety is an essential requirement for railway transportation. There are many methods that have been developed to predict, prevent and mitigate accidents in this context. All of these methods have their own purpose and limitations. This paper presents a new useful analysis technique: timed fault tree analysis. This method extends traditional fault tree analysis with temporal events and fault characteristics. Timed Fault Trees (TFTs) can determine which faults need to be eliminated urgently, and it can also provide a safe time window to repair them. They can also be used to determine the time taken for railway maintenance requirements, and thereby improve maintenance efficiency, and reduce risks. In this paper, we present the features and functionality of a railway transportation system based on timed fault tree models. We demonstrate the applicability of our framework via a case study of the China Yongwen line railway accident

Transiently Transfected Purine Biosynthetic Enzymes Form Stress Bodies

It has been hypothesized that components of enzymatic pathways might organize into intracellular assemblies to improve their catalytic efficiency or lead to coordinate regulation. Accordingly, de novo purine biosynthesis enzymes may form a purinosome in the absence of purines, and a punctate intracellular body has been identified as the purinosome. We investigated the mechanism by which human de novo purine biosynthetic enzymes might be organized into purinosomes, especially under differing cellular conditions. Irregardless of the activity of bodies formed by endogenous enzymes, we demonstrate that intracellular bodies formed by transiently transfected, fluorescently tagged human purine biosynthesis proteins are best explained as protein aggregation.This work was supported by grants from the United States National Institutes of Health, National Science Foundation, and Welch (F1515) and Packard Foundations to EMM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Cellular and Molecular Biolog

Men Also Do Laundry: Multi-Attribute Bias Amplification

As computer vision systems become more widely deployed, there is increasing concern from both the research community and the public that these systems are not only reproducing but amplifying harmful social biases. The phenomenon of bias amplification, which is the focus of this work, refers to models amplifying inherent training set biases at test time. Existing metrics measure bias amplification with respect to single annotated attributes (e.g., $\texttt{computer}$). However, several visual datasets consist of images with multiple attribute annotations. We show models can learn to exploit correlations with respect to multiple attributes (e.g., {$\texttt{computer}$, $\texttt{keyboard}$}), which are not accounted for by current metrics. In addition, we show current metrics can give the erroneous impression that minimal or no bias amplification has occurred as they involve aggregating over positive and negative values. Further, these metrics lack a clear desired value, making them difficult to interpret. To address these shortcomings, we propose a new metric: Multi-Attribute Bias Amplification. We validate our proposed metric through an analysis of gender bias amplification on the COCO and imSitu datasets. Finally, we benchmark bias mitigation methods using our proposed metric, suggesting possible avenues for future bias mitigationComment: Accepted at ICML 202

Cytoplasmic foci at the crossroads of artifactual science and biological function

Deciphering protein interaction and compartmentalization is crucial to understanding the molecular mechanisms that drive biological processes. Using various high throughput approaches, we have managed to score subcellular dynamic protein re-organization into supramolecular structures and map physical association networks to discover protein complexes on a proteome-wide level. However, the case by case studies of some of these novel structures and interactions reveal difficulties in interpreting their biological basis. This study offers insights into limits inherent in the molecular techniques used to investigate subcellular structures and protein interactions, describing a set of cautionary tales and critical analysis for deciphering cases of confounding data from orthogonal approaches. This study also offers a new experimental technique for high-throughput imaging assays with mammalian cell lines.Cellular and Molecular Biolog

Generating and protecting against adversarial attacks for deep speech-based emotion recognition models

A paper in ICASSP 202

Overpartitions and Bressoud's conjecture, II

The main objective of this paper is to prove Bressoud's conjecture for $j=0$. The case for $j=1$ has been recently proved by Kim. We first obtain an overpartition analogue of Bressoud's conjecture for $j=1$ by using a bijective method. We then show that Bressoud's conjecture for $j=0$ can be derived from the overpartition analogue of Bressoud's conjecture for $j=1$ with the aid of the relation between the partition function $B_0$ in Bressoud's conjecture and the partition function $\bar{B}_1$ established in our previous paper