Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Cardiac Magnetic Resonance Imaging for Nonischemic Cardiac Disease in Out-of-Hospital Cardiac Arrest Survivors Treated with Targeted Temperature Management: A Multicenter Retrospective Analysis

(1) Background: Cardiac magnetic resonance (CMR) imaging is an emerging tool for investigating nonischemic cardiomyopathies and cardiac systemic disease. However, data on the cardiac arrest population are limited. This study aimed to evaluate the usefulness of CMR imaging in out-of-hospital cardiac arrest (OHCA) survivors treated with targeted temperature management (TTM). (2) Methods: We conducted the retrospective observational study using a multicenter registry of adult non-traumatic comatose OHCA survivors who underwent TTM between January 2010 and December 2019. Of the 949 patients, 389 with OHCA of non-cardiac cause, 145 with significant lesions in the coronary artery, 151 who died during TTM, 81 without further evaluation due to anticipated poor neurological outcome, and 51 whose etiology is underlying disease were excluded. In 36 of the 132 remaining patients, the etiologies included variant angina, long QT syndrome, and complete atrioventricular block in ancillary studies. Fifty-six patients were diagnosed idiopathic ventricular fibrillation without CMR. (3) Results: CMR imaging was performed in the remaining 40 patients with cardiac arrest of unknown cause. The median time from cardiac arrest to CMR imaging was 10.1 days. The CMR finding was normal in 23 patients, non-diagnostic in 12, and abnormal in 5, which suggested non-ischemic cardiomyopathy but did not support the final diagnosis. (4) Conclusions: CMR imaging may not be useful for identifying unknown causes of cardiac arrest in OHCA survivors treated with targeted temperature management without definitive diagnosis even after coronary angiography, echocardiography, and electrophysiology studies. However, further large-scale studies will be needed to confirm these findings

Effect of Urethane Crosslinking by Blocked Isocyanates with Pyrazole-Based Blocking Agents on Rheological and Mechanical Performance of Clearcoats

A novel blocked isocyanate crosslinker was synthesized, and its applicability was investigated for the low-temperature curing of automotive clearcoats. Various pyrazole derivatives were prepared as blocking agents in isocyanate crosslinkers, which strongly affect the deblocking and curing properties of the urethane-bonded coating systems. The thermal curing properties of clearcoat samples containing a pyrazole-based blocked isocyanate crosslinker and polyol resin were characterized under two different temperature conditions (120 and 150 &deg;C). The decrease in the amount of hydroxyl groups in the polyol before and after curing was expressed by the change in OH stretching frequency in the Fourier transform infrared (FT-IR) spectra. The real-time rheological storage moduli of the bulk clearcoat mixtures were measured via a rotational rheometer to determine the effect of pyrazole-based blocking agents on the curing dynamics. In addition, a rigid-body pendulum tester (RPT) was employed to investigate the curing behavior in the thin film form. The nano-indentation and the nano-scratch tests were conducted to examine the surface hardness and scratch resistance characteristics of the cured clearcoat films. The results show that a low-temperature curing system of clearcoats can be realized by tuning the curing temperature and reactivity of isocyanate crosslinkers blocked with pyrazole-based substituents

Effect of isocyanate crosslinkers blocked with amine derivatives on rheological and crosslinking characteristics of automotive clearcoats

Isocyanate crosslinkers with blocking agents based on various amine derivatives were newly synthesized for automotive clearcoat applications. Amine-based blocking agents were prepared by varying the alkyl substituent attached on both sides of the main nitrogen atom (named DEA, DiPA, NtBEA, and NtBiA) to modify their deblocking feature in blocked isocyanates (BIs) and curing reaction under thermal curing conditions. Curing properties of clearcoats containing amine-based BIs were characterized at the normal curing temperature of 150 degrees C and were compared with those by the commercialized BI, Desmodur (R) PL350. The dissociation ability of the amine-based BIs was interpreted using the density functional theory (DFT) simulation under their optimized geometric configurations. The urethane reaction between isocyanate group in BIs and hydroxyl group in a hydroxyl-functionalized polyol binder within clearcoats was confirmed from the OH stretching absorbance data via Fourier-transform infrared (FT-IR) spectrometer. The real-time cross-linking dynamics of various clearcoats with amine-based BIs were comprehensively investigated using rotational rheometer and rigid-body pendulum tester. The surface mechanical properties of fully-cured clearcoat films were measured by nano-indentation and nano-scratch testers to address the crosslinked network formation caused by amine-based BIs. It is demonstrated that the amine-based BIs could be favorably applied to thermal curing process of clearcoats, based on their reactivity and curing performance

A Study on the Design Procedure of Re-Configurable Convolutional Neural Network Engine for FPGA-Based Applications

Convolutional neural networks (CNNs) have become a primary approach in the field of artificial intelligence (AI), with wide range of applications. The two computational phases for every neural network are; the training phase and the testing phase. Usually, testing is performed on high-processing hardware engines, however, the training part is still a challenge for low-power devices. There are several neural accelerators; such as graphics processing units and field-programmable-gate-arrays (FPGAs). From the design perspective, an efficient hardware engine at the register-transfer level and efficient CNN modeling at the TensorFlow level are mandatory for any type of application. Hence, we propose a comprehensive, and step-by-step design procedure for a re-configurable CNN engine. We used TensorFlow and Keras libraries for modeling in Python, whereas the register-transfer-level part was performed using Verilog. The proposed idea was synthesized, placed, and routed for 180 nm complementary metal-oxide semiconductor technology using synopsis design compiler tools. The proposed design layout occupies an area of 3.16 × 3.16 mm2. A competitive accuracy of approximately 96% was achieved for the Modified National Institute of Standards and Technology (MNIST) and Canadian Institute for Advanced Research (CIFAR-10) datasets

Expression of <i>SLC5A5</i> in Circulating Tumor Cells May Distinguish Follicular Thyroid Carcinomas from Adenomas: Implications for Blood-Based Preoperative Diagnosis

Preoperative diagnosis of thyroid nodules reduces unnecessary surgery. Circulating tumor cells (CTCs) may contain information of primary tumor(s). We asked whether the peripheral blood expression of genes specific for circulating tumor cells (CTCs) differentiates benign thyroid nodules from malignant nodules. Peripheral blood mononuclear cells from thyroid nodule patients (n = 20) were isolated preoperatively and the expression of seven CTC-associated genes was measured in patients with thyroid nodule(s) (n = 20). Among the tested genes, the expression of SLC5A5 and LGALS3 were validated in a larger number of patients (n = 64) and our results show that SLC5A5 expression differentiated follicular adenomas from follicular carcinomas (area under the curve (AUC) = 0.831). The expression of SLC5A5 in CTCs may preoperatively distinguish thyroid follicular adenomas from follicular carcinomas

A Low-Power Analog Processor-in-Memory-Based Convolutional Neural Network for Biosensor Applications

This paper presents an on-chip implementation of an analog processor-in-memory (PIM)-based convolutional neural network (CNN) in a biosensor. The operator was designed with low power to implement CNN as an on-chip device on the biosensor, which consists of plates of 32 × 32 material. In this paper, 10T SRAM-based analog PIM, which performs multiple and average (MAV) operations with multiplication and accumulation (MAC), is used as a filter to implement CNN at low power. PIM proceeds with MAV operations, with feature extraction as a filter, using an analog method. To prepare the input feature, an input matrix is formed by scanning a 32 × 32 biosensor based on a digital controller operating at 32 MHz frequency. Memory reuse techniques were applied to the analog SRAM filter, which is the core of low power implementation, and in order to accurately grasp the MAC operational efficiency and classification, we modeled and trained numerous input features based on biosignal data, confirming the classification. When the learned weight data was input, 19 mW of power was consumed during analog-based MAC operation. The implementation showed an energy efficiency of 5.38 TOPS/W and was differentiated through the implementation of 8 bits of high resolution in the 180 nm CMOS process