Noise and thermal stability of vibrating micro-gyrometers preamplifiers

The preamplifier is a critical component of gyrometer's electronics. Indeed the resolution of the sensor is limited by its signal to noise ratio, and the gyrometer's thermal stability is limited by its gain drift. In this paper, five different kinds of preamplifiers are presented and compared. Finally, the design of an integrated preamplifier is shown in order to increase the gain stability while reducing its noise and size.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/EDA-Publishing

Architecture for Integrated Mems Resonators Quality Factor Measurement

In this paper, an architecture designed for electrical measurement of the quality factor of MEMS resonators is proposed. An estimation of the measurement performance is made using PSPICE simulations taking into account the component's non-idealities. An error on the measured Q value of only several percent is achievable, at a small integration cost, for sufficiently high quality factor values (Q > 100).Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/EDA-Publishing

A Low-Cost, Built-In Self-Test Method for Resistive MEMS sensors

This paper illustrates the experimental application of the LIMBO method, an identification method based on binary observations dedicated to the (self-) test of integrated electronic and electromechanical systems, such as MEMS. The tested MEMS device is a micro-wire used as a heating resistor, inserted in a Wheatstone bridge. We show how the impulse response and the offset of the micro device are estimated only using binary inputs and outputs and straightforward calculations, which can easily be implemented on an FPGA. This approach only requires a 1-bit ADC and a 1-bit DAC, which makes it very amenable to integration and highlights its suitability for the test of systems based on resistive sensor and/or actuator

Exposure to androstenes influences processing of emotional words

There is evidence that human-produced androstenes affect attitudinal, emotional, and physiological states in a context-dependent manner, suggesting that they could be involved in modulating social interactions. For instance, androstadienone appears to increase attention specifically to emotional information. Most of the previous work focused on one or two androstenes. Here, we tested whether androstenes affect linguistic processing, using three different androstene compounds. Participants (90 women and 77 men) performed a lexical decision task after being exposed to an androstene or to a control treatment (all compounds were applied on the philtrum). We tested effects on three categories of target words, varying in emotional valence: positive, competitive, and neutral words (e.g., hope, war, and century, respectively). Results show that response times were modulated by androstene treatment and by emotional valence of words. Androstenone, but not androstadienone and androstenol, significantly slowed down the reaction time to words with competitive valence. Moreover, men exposed to androstenol showed a significantly reduced error rate, although men tended to make more errors than women in general. This suggests that these androstenes modulate the processing of emotional words, namely some particular lexical emotional content may become more salient under the effect of androstenes

Cerebral infarction in diabetes: Clinical pattern, stroke subtypes, and predictors of in-hospital mortality

BACKGROUND: To compare the characteristics and prognostic features of ischemic stroke in patients with diabetes and without diabetes, and to determine the independent predictors of in-hospital mortality in people with diabetes and ischemic stroke. METHODS: Diabetes was diagnosed in 393 (21.3%) of 1,840 consecutive patients with cerebral infarction included in a prospective stroke registry over a 12-year period. Demographic characteristics, cardiovascular risk factors, clinical events, stroke subtypes, neuroimaging data, and outcome in ischemic stroke patients with and without diabetes were compared. Predictors of in-hospital mortality in diabetic patients with ischemic stroke were assessed by multivariate analysis. RESULTS: People with diabetes compared to people without diabetes presented more frequently atherothrombotic stroke (41.2% vs 27%) and lacunar infarction (35.1% vs 23.9%) (P < 0.01). The in-hospital mortality in ischemic stroke patients with diabetes was 12.5% and 14.6% in those without (P = NS). Ischemic heart disease, hyperlipidemia, subacute onset, 85 years old or more, atherothrombotic and lacunar infarcts, and thalamic topography were independently associated with ischemic stroke in patients with diabetes, whereas predictors of in-hospital mortality included the patient's age, decreased consciousness, chronic nephropathy, congestive heart failure and atrial fibrillation CONCLUSION: Ischemic stroke in people with diabetes showed a different clinical pattern from those without diabetes, with atherothrombotic stroke and lacunar infarcts being more frequent. Clinical factors indicative of the severity of ischemic stroke available at onset have a predominant influence upon in-hospital mortality and may help clinicians to assess prognosis more accurately

Cerebral infarction in diabetes: Clinical pattern, stroke subtypes, and predictors of in-hospital mortality

BACKGROUND: To compare the characteristics and prognostic features of ischemic stroke in patients with diabetes and without diabetes, and to determine the independent predictors of in-hospital mortality in people with diabetes and ischemic stroke. METHODS: Diabetes was diagnosed in 393 (21.3%) of 1,840 consecutive patients with cerebral infarction included in a prospective stroke registry over a 12-year period. Demographic characteristics, cardiovascular risk factors, clinical events, stroke subtypes, neuroimaging data, and outcome in ischemic stroke patients with and without diabetes were compared. Predictors of in-hospital mortality in diabetic patients with ischemic stroke were assessed by multivariate analysis. RESULTS: People with diabetes compared to people without diabetes presented more frequently atherothrombotic stroke (41.2% vs 27%) and lacunar infarction (35.1% vs 23.9%) (P < 0.01). The in-hospital mortality in ischemic stroke patients with diabetes was 12.5% and 14.6% in those without (P = NS). Ischemic heart disease, hyperlipidemia, subacute onset, 85 years old or more, atherothrombotic and lacunar infarcts, and thalamic topography were independently associated with ischemic stroke in patients with diabetes, whereas predictors of in-hospital mortality included the patient's age, decreased consciousness, chronic nephropathy, congestive heart failure and atrial fibrillation CONCLUSION: Ischemic stroke in people with diabetes showed a different clinical pattern from those without diabetes, with atherothrombotic stroke and lacunar infarcts being more frequent. Clinical factors indicative of the severity of ischemic stroke available at onset have a predominant influence upon in-hospital mortality and may help clinicians to assess prognosis more accurately

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mainly on the development of methods for effective batch effects removal. However, their impact on cross-batch prediction performance, which is one of the most important goals in microarray-based applications, has not been addressed. This paper uses a broad selection of data sets from the Microarray Quality Control Phase II (MAQC-II) effort, generated on three microarray platforms with different causes of batch effects to assess the efficacy of their removal. Two data sets from cross-tissue and cross-platform experiments are also included. Of the 120 cases studied using Support vector machines (SVM) and K nearest neighbors (KNN) as classifiers and Matthews correlation coefficient (MCC) as performance metric, we find that Ratio-G, Ratio-A, EJLR, mean-centering and standardization methods perform better or equivalent to no batch effect removal in 89, 85, 83, 79 and 75% of the cases, respectively, suggesting that the application of these methods is generally advisable and ratio-based methods are preferred

Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions

BackgroundTargeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing.ResultsAll panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden.ConclusionThis comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.Peer reviewe

The SEQC2 Epigenomics Quality Control (EpiQC) Study: comprehensive characterization of epigenetic methods, reproducibility, and quantification

Detection of DNA cytosine modifications such as 5-methylcytosine (5mC) and 5-hydroxy-methylcytosine (5hmC) is essential for understanding the epigenetic changes that guide development, cellular lineage specification, and disease. The wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. We present a multi-platform assessment and a global resource for epigenetics research from the FDA's Epigenomics Quality Control (EpiQC) Group. The study design leverages seven human cell lines that are publicly available from the National Institute of Standards and Technology (NIST) and Genome in a Bottle (GIAB) consortium. These genomes were subject to a variety of genome-wide methylation interrogation approaches across six independent laboratories. Our primary focus was on cytosine modifications found in mammalian genomes (5mC, 5hmC). Each sample was processed in two or more technical replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS, SPLAT), oxidative bisulfite sequencing (oxBS), Enzymatic Methyl-seq (EM-seq), Illumina EPIC targeted-methylation sequencing, and ATAC-seq. Each library was sequenced to high coverage on an Illumina NovaSeq 6000. The data were subject to rigorous quality assessment and subsequently compared to Illumina EPIC methylation microarrays. We provide a wide range of sequence data for commonly used genomics reference materials, as well as best practices for epigenomics research. These findings can serve as a guide for researchers to enable epigenomic analysis of cellular identity in development, health, and disease