Using Discrete Event Simulation to Design and Assess an AI-aided Workflow for Same-day Diagnostic Testing of Women Undergoing Breast Screening.

The process of patients waiting for diagnostic examinations after an abnormal screening mammogram is inefficient and anxiety-inducing. Artificial intelligence (AI)-aided interpretation of screening mammography could reduce the number of recalls after screening. We proposed a same-day diagnostic workup to alleviate patient anxiety by employing an AI-aided interpretation to reduce unnecessary diagnostic testing after an abnormal screening mammogram. However, the potential unintended consequences of introducing this workflow in a high-volume breast imaging center are unknown. Using discrete event simulation, we observed that implementing the AI-aided screening mammogram interpretation and same-day diagnostic workflow would reduce daily patient volume by 4%, increase the time a patient would be at the clinic by 24%, and increase waiting times by 13-31%. We discuss how changing the hours of operation and introducing new imaging equipment and personnel may alleviate these negative impacts

Sulfide Generation by Dominant Halanaerobium Microorganisms in Hydraulically Fractured Shales

Hydraulic fracturing of black shale formations has greatly increased United States oil and natural gas recovery. However, the accumulation of biomass in subsurface reservoirs and pipelines is detrimental because of possible well souring, microbially induced corrosion, and pore clogging. Temporal sampling of produced fluids from a well in the Utica Shale revealed the dominance of Halanaerobium strains within the in situ microbial community and the potential for these microorganisms to catalyze thiosulfate-dependent sulfidogenesis. From these field data, we investigated biogenic sulfide production catalyzed by a Halanaerobium strain isolated from the produced fluids using proteogenomics and laboratory growth experiments. Analysis of Halanaerobium isolate genomes and reconstructed genomes from metagenomic data sets revealed the conserved presence of rhodanese-like proteins and anaerobic sulfite reductase complexes capable of converting thiosulfate to sulfide. Shotgun proteomics measurements using a Halanaerobium isolate verified that these proteins were more abundant when thiosulfate was present in the growth medium, and culture-based assays identified thiosulfate-dependent sulfide production by the same isolate. Increased production of sulfide and organic acids during the stationary growth phase suggests that fermentative Halanaerobium uses thiosulfate to remove excess reductant. These findings emphasize the potential detrimental effects that could arise from thiosulfate-reducing microorganisms in hydraulically fractured shales, which are undetected by current industry-wide corrosion diagnostics. IMPORTANCE Although thousands of wells in deep shale formations across the United States have been hydraulically fractured for oil and gas recovery, the impact of microbial metabolism within these environments is poorly understood. Our research demonstrates that dominant microbial populations in these subsurface ecosystems contain the conserved capacity for the reduction of thiosulfate to sulfide and that this process is likely occurring in the environment. Sulfide generation (also known as “souring”) is considered deleterious in the oil and gas industry because of both toxicity issues and impacts on corrosion of the subsurface infrastructure. Critically, the capacity for sulfide generation via reduction of sulfate was not detected in our data sets. Given that current industry wellhead tests for sulfidogenesis target canonical sulfate-reducing microorganisms, these data suggest that new approaches to the detection of sulfide-producing microorganisms may be necessary

A Simple Standard for Sharing Ontological Mappings (SSSOM).

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

ADP Ribosylation Factor Like 2 (Arl2) Regulates Breast Tumor Aggressivity in Immunodeficient Mice

We have previously reported that ADP ribosylation factor like 2 (Arl2), a small GTPase, content influences microtubule dynamics and cell cycle distribution in breast tumor cells, as well as the degree and distribution of phosphorylated P53. Here we show, in two different human breast adenocarcinoma models, that Arl2 content has a major impact on breast tumor cell aggressivity both in vitro and in vivo. Cells with reduced content of Arl2 displayed reduced contact inhibition, increased clonogenic or cluster formation as well as a proliferative advantage over control cells in an in vitro competition assay. These cells also caused larger tumors in SCID mice, a phenotype which was mimicked by the in vivo administration of siRNA directed against Arl2. Cells with increased Arl2 content displayed reduced aggressivity, both in vitro and in vivo, with enhanced necrosis and were also found to contain increased PP2A phosphatase activity. A rt-PCR analysis of fresh human tumor breast samples suggested that low Arl2 expression was associated with larger tumor size and greater risk of lymph node involvement at diagnosis. These data underline the role of Arl2, a small GTPase, as an important regulator of breast tumor cell aggressivity, both in vitro and in vivo

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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Breast Tubular Adenoma in a Man with Alcoholic Cirrhosis: A Case Report

Tubular adenomas are rare, benign breast tumors primarily found in postmenarchal, premenopausal women. We report a case of tubular adenoma in a 56-year-old man with a history of alcoholic cirrhosis. The breast mass was incidentally discovered on computed tomography imaging performed as part of a patient liver transplant evaluation. Dedicated breast imaging and ultrasound-guided biopsy confirmed the diagnosis of tubular adenoma