Cut-off Set Research Articles

SIGNAL: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from genome-scale assays.

Hit selection from high-throughput assays remains a critical bottleneck in realizing the potential of omic-scale studies in biology. Widely used methods such as setting of cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions offer divergent solutions yet are associated with critical analytical trade-offs. The specific limitations of these individual approaches and the lack of a systematic way by which to integrate their rankings have contributed to limited overlap in the reported results from comparable genome-wide studies and costly inefficiencies in secondary validation efforts. Using comparative analysis of parallel independent studies as a benchmark, we characterize the specific complementary contributions of each approach and demonstrate an optimal framework to integrate these methods. We describe selection by iterative pathway group and network analysis looping (SIGNAL), an integrated, iterative approach that uses both pathway and network methods to optimize gene prioritization. SIGNAL is accessible as a rapid user-friendly web-based application (https://signal.niaid.nih.gov). A record of this paper's transparent peer review is included in the Supplemental information.

Light therapy for seasonal affective disorder in visual impairment and blindness – a pilot study

Seasonal and non-seasonal depression are prevalent conditions in visual impairment (VI). We assessed the effects and side effects of light therapy in persons with severe VI/blindness who experienced recurrent depressive symptoms in winter corresponding to seasonal affective disorder (SAD) or subsyndromal SAD (sSAD). We included 18 persons (11 with severe VI, 3 with light perception and 4 with no light perception) who met screening criteria for sSAD/SAD in a single-arm, assessor-blinded trial of 6 weeks light therapy. In the 12 persons who completed the 6 weeks of treatment, the post-treatment depression score was reduced (p < 0.001), and subjective wellbeing (p = 0.01) and sleep quality were improved (p = 0.03). In 6/12 participants (50%), the post-treatment depression score was below the cut-off set for remission. In four participants with VI, side effects (glare or transiently altered visual function) led to dropout or exclusion. Light therapy was associated with a reduction in depressive symptoms in persons with severe VI/blindness. Eye safety remains a concern in persons with residual sight.

Effectiveness of mid-regional pro-adrenomedullin (MR-proADM) as prognostic marker in COVID-19 critically ill patients: An observational prospective study.

ObjectiveTo test the effectiveness of mid-regional pro-adrenomedullin (MR-proADM) in comparison to C-reactive protein (CRP), procalcitonin (PCT), D-dimer, lactate dehydrogenase (LDH) in predicting mortality in COVID-19-ICU-patients.MethodsAll consecutive COVID-19 adult patients admitted between March and June 2020 to the ICU of a referral, university hospital in Northern-Italy were enrolled. MR-proADM and routine laboratory test were measured within 48 hours from ICU admission, on day 3, 7 and 14. Survival curves difference with MR-proADM cut-off set to 1.8 nmol/L were tested using log-rank test. Predictive ability was compared using area under the curve and 95% confidence interval of different receiver-operating characteristics curves.Results57 patients were enrolled. ICU and overall mortality were 54.4%. At admission, lymphocytopenia was present in 86% of patients; increased D-dimer and CRP levels were found in 84.2% and 87.7% of patients respectively, while PCT values > 0.5 μg/L were observed in 47.4% of patients. MR-proADM, CRP and LDH were significantly different between surviving and non-surviving patients and over time, while PCT, D-dimer and NT-pro-BNP did not show any difference between the groups and over time; lymphocytes were different between surviving and non-surviving patients only. MR-proADM was higher in dying patients (2.65±2.33vs1.18±0.47, p<0.001) and a higher mortality characterized patients with MR-proADM >1.8 nmol/L (p = 0.016). The logistic regression model adjusted for age, gender, cardiovascular disease, diabetes mellitus and PCT values confirmed an odds ratio = 10.3 [95%CI:1.9–53.6] (p = 0.006) for MR-proADM >1.8 nmol/L and = 22.2 [95%CI:1.6–316.9] (p = 0.022) for cardiovascular disease. Overall, MR-proADM had the best predictive ability (AUC = 0.85 [95%CI:0.78–0.90]).ConclusionsIn COVID-19 ICU-patients, MR-proADM seems to have constantly higher values in non-survivor patients and predict mortality more precisely than other biomarkers. Repeated MR-proADM measurement may support a rapid and effective decision-making. Further studies are needed to better explain the mechanisms responsible of the increase in MR-proADM in COVID-19 patients.

Prevalence of Metabolic Syndrome and Factors Associated With It Among Adults of West Gojjam: A Community-Based Cross-Sectional Study.

BackgroundMetabolic syndrome is a cluster of risk factors for cardiovascular diseases, indicating great clinical attention. However, much less attention has been given to metabolic syndrome in the study area.ObjectiveThe objective of this study is to determine the prevalence of metabolic syndrome and its associated factors in the adult population of West Gojjam zone, Ethiopia.MethodsA community-based cross-sectional study was conducted in West Gojjam from September 15 to October 20, 2018. A total of 627 participants were randomly selected. The data were collected using the WHO STEP-wise approach for non-communicable diseases by contextualizing the instrument based on the study questions. The collected data were entered into and analyzed in SPSS version 20. Binary logistic regression was used to identify predictors of the dependent variable. The odds ratio was used to measure the strength of association between variables. For all statistical significance tests, the cut-off value set was p < 0.05 with CI of 95%.ResultsIn the studied region, high prevalence of metabolic syndrome at 17.3% is documented. In the final model, age (adjusted odds ratio [AOR] = 1.02, CI: 1.01–1. 05), occupation (AOR = 2.97, CI: 1.25–7.04), a moderate or high level of physical activity (AOR = 0.28, CI: 0.14–0.56 and AOR = 0.42, CI: 0.18–0.97) and type of oil used for cooking (AOR = 2.62, CI: 1.87–7.86) are significantly associated with metabolic syndrome.ConclusionThe prevalence of metabolic syndrome in this study is high, and it is determined by age, occupation, physical activity and type of oil used for cooking. Designing an intervention which focuses on promoting a healthy lifestyle like physical activity and using oils which are liquid at room temperature to prevent the risk of major non-communicable diseases is needed.

High-pass filtering artifacts in multivariate classification of neural time series data

BackgroundTraditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown. New methodTo prevent potential displacement effects, we extend an alternative method of removing slow drift noise – robust detrending – with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending. ResultsIn both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements. Comparison with existing method(s)Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial. ConclusionsDecoding analyses benefit from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

U-TEST, a simple decision support tool for the diagnosis of sarcopenia in orthopaedic patients: the Screening for People Suffering Sarcopenia in Orthopedic cohort of Kobe study (SPSS-OK).

We aimed to develop and validate a new simple decision support tool (U-TEST) for diagnosis of sarcopenia in orthopaedic patients. We created seventeen candidate original questions to detect sarcopenia in orthopaedic patients with sarcopenia through expert opinions and a semi-structured interview. To derive a decision support tool, a logistic regression model with backward elimination was applied to select variables from the seventeen questions, age and underweight (BMI < 18·5 kg/m2). Sarcopenia was defined by Asian Working Group for Sarcopenia 2019 criteria. After assigning a score to each selected variable, the sum of scores was calculated. We evaluated the diagnostic performance of the new tool using a logistic regression model. A bootstrap technique was used for internal validation. Among a total of 1334 orthopaedic patients, sixty-five (4·9 %) patients were diagnosed with sarcopenia. We succeeded in developing a 'U-TEST' with scores ranging from 0 to 11 consisting of values for BMI (Underweight), age (Elderly) and two original questions ('I can't stand up from a chair without supporting myself with my arms' (Strength) and 'I feel that my arms and legs are thinner than they were in the past' (Thin)). The AUC was 0·77 (95 % CI 0·71, 0·83). With the optimal cut-off set at 3 or greater based on Youden's index, the sensitivity and the specificity were 76·1 and 63·6 %, respectively. In orthopaedic patients, our U-TEST scoring with two questions and two simple clinical variables can help to screen for sarcopenia.

Hormonal Receptor Immunochemistry Heterogeneity and 18F-FDG Metabolic Heterogeneity: Preliminary Results of Their Relationship and Prognostic Value in Luminal Non-Metastatic Breast Cancers.

IntroductionWe aimed to investigate whether 18F-FDG PET metabolic heterogeneity reflects the heterogeneity of estrogen receptor (ER) and progesterone receptor (PR) expressions within luminal non-metastatic breast tumors and if it could help in identifying patients with worst event-free survival (EFS).Materials and methodsOn 38 PET high-resolution breast bed positions, a single physician drew volumes of interest encompassing the breast tumors to extract SUVmax, histogram parameters and textural features. High-resolution immunochemistry (IHC) scans were analyzed to extract Haralick parameters and descriptors of the distribution shape. Correlation between IHC and PET parameters were explored using Spearman tests. Variables of interest to predict the EFS status at 8 years (EFS-8y) were sought by means of a random forest classification. EFS-8y analyses were then performed using univariable Kaplan-Meier analyses and Cox regression analysis. When appropriate, Mann-Whitney tests and Spearman correlations were used to explore the relationship between clinical data and tumoral PET heterogeneity variables.ResultsFor ER expression, correlations were mainly observed with 18F-FDG histogram parameters, whereas for PR expression correlations were mainly observed with gray-level co-occurrence matrix (GLCM) parameters. The strongest correlations were observed between skewness_ER and uniformity_HISTO (ρ = −0.386, p = 0.017) and correlation_PR and entropy_GLCM (ρ = 0.540, p = 0.001), respectively. The median follow-up was 6.5 years and the 8y-EFS was 71.0%. Random forest classification found age, clinical stage, SUVmax, skewness_ER, kurtosis_ER, entropy_HISTO, and uniformity_HISTO to be variables of importance to predict the 8y-EFS. Univariable Kaplan-Meier survival analyses showed that skewness_ER was a predictor of 8y-EFS (66.7 ± 27.2 versus 19.1 ± 15.2, p = 0.018 with a cut-off value set to 0.163) whereas other IHC and PET parameters were not. On multivariable analysis including age, clinical stage and skewness_ER, none of the parameters were independent predictors. Indeed, skewness_ER was significantly higher in youngest patients (ρ = −0.351, p = 0.031) and in clinical stage III tumors (p = 0.023).ConclusionA heterogeneous distribution of ER within the tumor in IHC appeared as an EFS-8y prognosticator in luminal non-metastatic breast cancers. Interestingly, it appeared to be correlated with PET histogram parameters which could therefore become potential non-invasive prognosticator tools, provided these results are confirmed by further larger and prospective studies.

Characterization of CRLF2 Expression in Pediatric B-Cell Precursor Acute Lymphoblastic Leukemia.

Acute lymphoblastic leukemia (ALL) is a heterogeneous disease with several underlying genetic ab-normalities. Several studies have tried to elucidate the prognostic significance of cytokine receptor-like factor 2 (CRLF2) overexpression in pediatric B-cell precursor (BCP)-ALL; however, it is still controversial. CRLF2 expression was assessed by flow cytometry in 87 newly diagnosed BCP-ALL pediatric patients, and 80 age and gender-matched control group. Janus Kinase2 (JAK2) (R683) mutation analysis was also performed in those identified to have CRLF2 overexpression with adequate DNA samples by direct sequencing. CRLF2 overexpression was identified in 26/87 (29.9%) of our patients with cutoff set at mean fluorescence intensity (MFI = 3.8) using the Receiver Operating Characteristic (ROC) curve. There were no significant differences in the clinical and laboratory features between patients with high and low-CRLF2 expression, apart from thrombocytopenia which showed statistically significant association with the low-expression group (p = 0.041). Sequence analysis of samples with high CRLF2 expression (n = 23) revealed that 2/23 (8.7%) cases harbored the mutation JAK2 (R683). CRLF2 levels did not have a significant impact on either overall survival (OS) or disease free survival (DFS) (p = 0.601; p = 0.212, respectively). CRLF2 overexpression was not an adverse parameter in pediatric BCP-ALL patients. However, patients with CRLF2 overexpression may harbor the JAK2 mutation presenting a group that can benefit from targeted therapy by kinase inhibitors. The usage of CRLF2 expression to monitor minimal residual disease of BCP-ALL would be an area of interest for further evaluation.

The Significance of Apolipoprotein E Measurement in the Screening of Fetal Down Syndrome.

Prenatal screening for Down syndrome (DS) is based on both noninvasive and invasive methods. Noninvasive, cell-free fetal DNA genetic tests are expensive, whereas biochemical methods remain imprecise. Amniocentesis is the most frequently used invasive diagnosis procedure, characterized by 99.8% diagnostic efficiency and less than 1% risk of miscarriage. The aim of this study was to evaluate the screening value of apolipoprotein E (ApoE) as a potential noninvasive biomarker for prenatal DS assessment. This study was conducted on a group of female patients who decided to undergo routine amniocentesis between the 15th and 18th week of pregnancy at the Department of Reproduction and Gynecological Endocrinology of the Medical University of Bialystok, Poland. For the purpose of this study, 20 women with DS fetuses were selected as the study group, and 20 healthy pregnant women with euploid fetus karyotypes as the control group. The plasma levels of ApoE were significantly higher in the study group compared to healthy subjects (p < 0.05). The area under the receiver operating characteristic (ROC) curve was 0.978 (p < 0.001), with the cut-off set to 1.37 mg/mL, which was characterized by 80% of sensitivity and 100% of specificity. The high sensitivity and specificity demonstrate the screening utility of maternal ApoE concentration in prenatal fetal DS screening.

Quantitative Proteomic Analysis of Duck Embryo Fibroblasts Infected With Novel Duck Reovirus.

The novel duck reovirus (NDRV) can cause hemorrhage and necrosis on the spleen of Pekin ducks; this disease has resulted in great economic losses to the duck industry. However, the molecular pathogenesis of NDRV remains poorly understood. In the current study, the quantitative proteomic analysis of NDRV-infected duck embryo fibroblasts was performed to explore the cellular protein changes in response to viral infection through iTRAQ coupled with the liquid chromatography (LC)–tandem mass spectrometry (MS/MS) method. A total of 6,137 proteins were obtained in cell samples at 24 h post-infection. Of these, 179 differentially expressed proteins (DEPs) were identified (cutoff set to 1.5-fold change), including 89 upregulated and 90 downregulated proteins. Bioinformatics analysis showed that DEPs can be divided into the cellular component, molecular function, and biological process; they were mainly involved in signal transduction, infectious diseases, cell growth and death, and the immune system. The subcellular localization of most proteins was in the cytoplasm. Importantly, the expressions of signal transducer and activator of transcription 1 (STAT1) and various interferon-stimulated genes (ISGs) were upregulated after NDRV infection. The mRNA transcripts of some ISGs were consistent with proteomic data, showing an increased trend. Results of our study suggested that NDRV infection can elicit strong expression changes of cellular proteins and activate the expression of ISGs from the point of quantitative proteomic analysis. The study provides a new insight into the understanding of NDRV pathogenesis.

Zinc deficiency may play a crucial role in dialysis-associated bacterial infections

Introduction: Systemic bacterial infections are a common cause of mortality and morbidity in hemodialysis patients. Zinc has a critical role in several immune system functions. Patients who have enough amounts of zinc are able to better face infections caused by various pathogens in comparison to those with zinc insufficiency Objective We sought to assess the role of zinc deficiency in dialysis-associated bacterial infections. Patients and Methods: Eighty-Three adult patients with end-stage renal disease (ESRD) on hemodialysis including 43 patients with bacterial infectious complications and 40 non-infected patients as well as 41 healthy individuals were enrolled. Clinical data, laboratory values including serum zinc level and imaging findings were collected. SPSS was utilized to analyze the data with a significance cutoff set at P &lt; 0.05. Results: Out of 124 participants, 80 (64.51%) were males and 44 (35.49%) were females. The mean age of infected hemodialysis group, non-infected hemodialysis group, and healthy controls were 50.8 ± 16.25, 49.1 ± 18.1, and 56.3 ± 18.2 years, respectively. Catheter site infection (37.3%) and urinary tract infection (30.2%) were the most common infections. The mean serum zinc concentration was significantly lower in the infected patients, compared to non-infected patients and healthy individuals (P &lt; 0.001). Conclusion: The ESRD patients on hemodialysis have lower serum zinc levels which are associated with increased risk of bacterial infection. The role of screening for zinc deficiency and use of supplemental zinc in these patients need to be studied.

Prevalence of maternal antenatal and postnatal depression and their association with sociodemographic and socioeconomic factors: A multicentre study in Italy

Background: Perinatal depression is a widespread and burdensome mental disorder. The objectives of this study were to assess the prevalence of both antenatal and postnatal depression in a large sample of women in Italy and to analyse their association with sociodemographic and socioeconomic factors.Methods: Cross-sectional data from eleven healthcare centres located throughout Italy (2017–2018) were analysed (n = 1471). Depressive disorder was assessed with the Edinburgh Postnatal Depression Scale (EPDS), and sociodemographic and socioeconomic factors were also measured. Prevalences by perinatal period and by sociodemographic and socioeconomic factors were estimated, and their associations were evaluated using logistic regression models. All analyses were stratified by perinatal period: antenatal (i.e., from conception to delivery) vs. postnatal (i.e., the nine months after delivery).Results: With a cut-off score set at 12 points, the prevalence of perinatal depression was 6.4% during pregnancy and 19.9% in the postnatal period, and the odds ratio for postpartum vs. antepartum depression was 3.65 (2.56–5.39). High economic status was associated with an approximate fivefold reduction in odds of depression in the antenatal period (ORa: 0.23, 95%CI: 0.10-0.54) and about a sixfold reduction in the postnatal period (ORa: 0.15, 95%CI: 0.05-0.45).Limitations: The data were cross-sectional. The EPDS has a sensitivity of 55.6%.Conclusion: The prevalence of perinatal depression in Italy is strongly associated with socioeconomic disadvantages. Early procedures to evaluate socioeconomic status and the provision of economical support for mothers might reduce the prevalence of perinatal depression and its direct and indirect costs.

Olorofim Susceptibility Testing of 1,423 Danish Mold Isolates Obtained in 2018-2019 Confirms Uniform and Broad-Spectrum Activity

Olorofim is a novel antifungal drug in phase 2 trials. It has shown promising in vitro activity against various molds, except for Mucorales. Initially, we observed a broad range of EUCAST MICs for Aspergillus fumigatus Here, we explored the MIC variability in more detail and prospectively investigated the susceptibility of contemporary clinical mold isolates, as population data are needed for future epidemiological cutoff (ECOFF) settings. Fifteen A. fumigatus isolates previously found with low/medium/high MICs (≤0.002 to 0.25 mg/liter) were tested repeatedly and EUCAST MICs read in a blinded fashion by three observers. pyrE, encoding the olorofim target enzyme dihydroorotate dehydrogenase (DHODH), was sequenced. A total of 1,423 mold isolates (10 Aspergillus species complexes [including 1,032 A. fumigatus isolates] and 105 other mold/dermatophyte isolates) were examined. Olorofim susceptibility (modal MIC, MIC50, MIC90, and wild-type upper limits [WT-ULs] [species complexes with ≥15 isolates]) was determined and compared to that of four comparators. MICs (mg/liter) were within two 2-fold dilutions (0.016 to 0.03) for 473/476 determinations. The MIC range spanned four dilutions (0.008 to 0.06). No significant pyrE mutations were found. Modal MIC/WT-UL97.5 (mg/liter) values were 0.03/0.06 (A. terreus and A. flavus), 0.06/0.125 (A. fumigatus and Trichophyton rubrum), and 0.06/0.25 (A. niger and A. nidulans). The MIC range for Scedosporium spp. was 0.008 to 0.25. Olorofim susceptibility was similar for azole-resistant and -susceptible isolates of A. fumigatus but reduced for A. montevidensis and A. chevalieri (MICs of >1). With experience, olorofim susceptibility testing is robust. The testing of isolates from our center showed uniform and broad-spectrum activity. Single-center WT-ULs are suggested.

Methodological Issues and the Impact of Age Stratification on the Proportion of Participants with Low Appendicular Lean Mass When Adjusting for Height and Fat Mass Using Linear Regression: Results from the Canadian Longitudinal Study on Aging

Using residual values calculated from models regressing appendicular lean mass on fat mass and height is one of several suggested strategies for adjusting appendicular lean mass for body size when measuring sarcopenia. However, special consideration is required when using this technique in different subgroups in order to capture the correct individuals as sarcopenic. To provide guidance about how to conduct stratified analyses for the regression adjustment technique using age groups as an example. Cross-sectional study. Data collected at baseline (2012–2015) for the Canadian Longitudinal Study on Aging. Community dwelling participants of European descent aged 45 to 85 years (n=25,399). Appendicular lean mass, height, and weight were measured. Sex-specific residuals were calculated in participants before and after stratifying participants by age group (45–54, 55–64, 65–74, 75–85 years). Cut offs corresponding to the sex-specific 20th percentile residual values in participants ≥65 years were determined first in the residuals calculated in all participants and residuals calculated in only those aged ≥65 years. For each set of cut offs, the percentage of age and sex-stratified participants with low appendicular lean mass were compared for the residuals calculated in all participants and the residuals calculated after stratifying by age. In 12,622 males and 12, 737 females, regardless of the cut off used, the percentage of participants with low appendicular lean mass decreased with age when residuals were calculated after age stratification. When the residuals were calculated in all participants, the percentage of participants with sarcopenia increased from the youngest to the oldest age groups. Sex-specific residuals in all participants should be calculated prior to stratifying the sample by age group, or other stratification variables, for the purposes of developing appendicular lean mass cut offs or subgroup analyses.

Evaluation of dried blood spot testing using the Abbott Alinity i.

The West of Scotland Specialist Virology Centre currently uses the Abbott Architect for DBS serology. The new Abbott Alinity i will replace the Architect in our laboratory. In this study, mock and stored patient DBS samples were tested on both platforms and results compared. Mock DBS were made from whole blood where patient results were known (38 negative samples and 141 positive samples; 39 HIV Antigen/Antibody (Ag/Ab), 35 HCV IgG antibody (HCVG), 34 HBV core IgG (HBCG) and 33 HBsAg). Mock DBS were tested on both Abbott platforms. Stored patient DBS samples (132 negative and 263 positive: 9 HIVAg/Ab, 10 HBsAg, 52 HBCG and 60 HCVG) previously tested on the Architect were retested on the Alinity i. Mock DBS showed good correlation between the Architect and Alinity i for the HIV Ag/Ab,HBCG and HCVG assays. A poorer correlation occurred with HBsAg, the Alinity i reported HBsAg positives at a lower value compared to the Architect. The coefficient of variation for intra-assay variation was 1.69 % (HIVAg/Ab), 3.25 % (HCVG), 1.68 % (HBsAg) and 1.95 % (HBCG). The sensitivity and specificity was determined based on results from the mock and patient samples. At S/Co cut-off 1.0 both HIV and HBsAg had a sensitivity of 100 %. A cut-off 0.8 gave a sensitivity of 95.83 % (95 % CI 89.67%-98.85%) for HCVG and 0.3 gave a sensitivity of 98.8 % (CI 93.69%-99.97%) for HBCG. The alinity i compared well against the architect and can be used to test DBS samples.

Evaluating the reliability of attention bias and attention bias variability measures in the dot-probe task among people with social anxiety disorder.

The dot-probe task is a widely used experimental paradigm that evaluates attention biases within anxiety disorders. Considerable research has focused on improving the reliability of dot-probe scores because the task's original attention bias index has shown very low test-retest reliability. The current study serves as a replication and extension of Price et al. (2015), who systematically examined the effects of methodological choices on reliability of dot-probe task results. Fifty-six adults diagnosed with social anxiety disorder were asked to complete a facial dot-probe task twice, approximately 1 week apart. Test-retest reliability and internal consistency were examined for 10 dot-probe attention bias indices across 55 sets of outlier cutoffs. Both Pearson's r and intraclass correlation coefficients were used. Trial-level bias score indices of mean bias toward threat and attention bias variability, which measure attention bias dynamically using individual pairs of trials, demonstrated the highest reliability and were less sensitive to changes in outlier cutoffs as compared with the dot probe's classic attention bias index and others. Results demonstrate the potential for post hoc outlier cutoff selection to artificially inflate reliability, particularly for unreliable indices. A priori cutoff selection is recommended for future research. Intraclass correlation coefficients are also recommended for assessment of reliability because Pearson's r does not account for poor agreement between scores. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Biological correlates of the Toronto Alexithymia Scale (TAS-20) in cardiovascular disease and healthy community subjects

This research studies the relationship between Alexithymia, behavioural, biometric, biochemical and cardiovascular risk in clinical and healthy samples. There were 602 participants (mean age of 52.82 ± 10.59) divided into two groups. The first was made up of 202 patients (165 males and 37 females) who had suffered a cardiovascular disease (CVD), while the second was composed of 400 (285 males and 115 females) healthy volunteers without CVD diagnosis. A cardiovascular risk index (CRI) was developed with the high factorial loading of the following variables: systolic and diastolic blood pressure, total cholesterol/HDL, triglycerides, body mass index, glucose and alcohol and tobacco consumption. The results showed a significant correlation between Alexithymia and the CRI. After controlling for age, sex, occupation, alcohol and tobacco consumption, this correlation decreased, but remained significant for most values. Alexithymia predicted 6% of CRI in the entire sample, once age and sex effect were discounted. Alexithymic subjects with scores above a cut-off point set at higher than 60 had higher levels of glucose, systolic, diastolic, cholesterol/HDL and cardiovascular risk. We discuss that Alexithymia scores contribute to cardiovascular risk, supporting previous findings.

Abstract 5899: Development and characterization an NGS multi-cancer panel plus CNV detection; a single-tube, multiplex-PCR based NGS Assay with 309 tiled amplicons

Abstract Introduction: SLIMamp technology allows multiplex-PCR of tiled amplicons in a single tube, which enables targeting of large exons for NGS analysis with a streamlined process. Copy number variants (CNVs) are DNA segments that are present with variation in the number of copies compared to a normal genome. CNVs have a high prevalence in the pathogenesis of cancer and their characterization is important to acquire a more comprehensive picture of the mutations present in a patient sample. Pillar developed a proprietary CNV algorithm and combined it with SLIMamp to develop an integrated multi-cancer plus CNV detection NGS panel which identifies CNVs in the ERBB2, EGFR, MET, and MYC genes. Methods: To assess the ability of the ONCO/Reveal Multi-Cancer with CNV Panel to detect ERBB2 CNV compared to DISH (dual in situ hybridization), libraries were created from 44 well-characterized FFPE breast cancer samples plus 3 Genome in a Bottle (GIAB) samples. 23 tumor samples had known ERBB2 amplification (20 with matched normal tissue), 21 were known non-amplified tumors, and 3 GIAB samples were used as negative controls. Libraries were sequenced on an Illumina MiSeq and data was analyzed by the Pillar Variant Analysis Toolkit (PiVAT). The previous DISH results were not known to Pillar. Results were provided to an independent collaborator who unblinded the study and compared the NGS results to DISH. Results: Overall the assay performed well with a mapping rate of 99.4% ± 2.1%, on-target rate of 99.1% ± 0.4%, and coverage uniformity &amp;gt;0.2x mean coverage of 93.5% ± 4.1%. With respect to CNV calling, the assay and software detected 100% (21/21) of ERBB2 amplification negative samples as confirmed by DISH. For amplification positive samples, the NGS assay detected 100% (23/23) of positive samples. The software correctly identified 91% (21/23) of amplification positive samples. The two samples that were not called by PiVAT had normalized genes counts of 1.2 and 1.4, and also had the lowest DISH scores. All samples with a normalized gene count &amp;gt;1.5 were correctly called by PiVAT. The NGS assay was able to accurately call CNV independent of tumor cellularity with tumor content of 20%-90% not impacting the CNV call. Conclusions: The ONCO/Reveal Multi-Cancer with CNV Panel is a robust assay for the detection of CNVs, SNVs, and Indels of interest across multiple solid tumor cancer types. The workflow is streamlined, with same day loading of finished libraries when starting from as little as 5ng of isolated input DNA. The assay and software demonstrate detection of low CNV with the recommended cutoff set at 1.5. With further optimization of the calling algorithm accurate calling of even lower CNVs may be possible. The detection and identification of CNVs along with other mutations gives a more comprehensive overview of the mutations present in a sample, supporting better clinical management of patients. Citation Format: Nicholas Lodato, Zonghan Liu, Akuah Kontor, Xiaoxi Wu, Lukas Hillmer, Sean Polvino, Yue Ke, Erin Petrilli, Adam Labonte, Geoffrey Richman, Zhaohui Wang. Development and characterization an NGS multi-cancer panel plus CNV detection; a single-tube, multiplex-PCR based NGS Assay with 309 tiled amplicons [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5899.

An optimal cut-off algorithm for parameterised refinement checking

• The cut-off set problem of a parameterised system is expressed in first-order logic. • An SMT-based semi-algorithm for computing a cut-off set is presented. • The algorithm terminates for topologies expressed in the E*A* fragment of FOL. • Upon termination, the algorithm produces the optimal cut-off set. • The algorithm is applied to the leader election phase of (Byzantine) Raft. The verification of contemporary distributed software systems is challenging, because they are heavily parameterised, containing components whose number and connections cannot be a priori fixed. In this work, we consider the multi-parameterised verification of safety properties by refinement checking in the context of labelled transition systems (LTSs). The LTSs are parameterised by using first-order constructs, sorts, variables, and predicates, while preserving compositionality. This allows us to parameterise not only the number of replicated components but also the communication topology of the system. Our approach to solving a verification task in the parameterised LTS formalism is to determine a finite cut-off set of parameter values such that in order to prove a parameterised system implementation correct with respect to its specification, it is sufficient to consider only finitely many instances of the parameterised system generated by the parameter values in the cut-off set. In the conference version of this work, we converted the problem of determining a finite cut-off set into the unsatisfiability of a first-order formula and provided a satisfiability modulo theories (SMT)-based semi-algorithm for dynamically, i.e., iteratively, computing a cut-off set. In this article, we present a new version of the algorithm and prove that the cut-off sets computed by this new algorithm are optimal. Hence, we call the new version the optimal cut-off algorithm. The algorithm will always terminate for system topologies expressible in the ∃ ⁎ ∀ ⁎ fragment of first-order logic. It also enables us to consider systems with topologies beyond this fragment, but for these systems, the algorithm is not guaranteed to terminate. We have implemented the approach on top of the Z3 SMT solver and successfully applied it to several system models. As a running example, we consider the leader election phase of the generalised (Byzantine) Raft consensus algorithm and prove the optimal cut-off set of six (respectively, thirteen) parameter values corresponding to instances up to three (respectively, four) servers. To the best of our knowledge, this is the first time a Byzantine variant of the parameterised Raft leader election is automatically verified.

Elevated plasma phenylalanine predicts mortality in critical patients with heart failure.

AimsPrevious studies found a relationship between elevated phenylalanine levels and poor cardiovascular outcomes. Potential strategies are available to manipulate phenylalanine metabolism. This study investigated whether increased phenylalanine predicted mortality in critical patients with either acute heart failure (HF) or acute on chronic HF, and its correlation with inflammation and immune cytokines.Methods and resultsThis study recruited 152 subjects, including 115 patients with HF admitted for critical conditions and 37 normal controls. We measured left ventricular ejection fraction (LVEF), plasma concentrations of phenylalanine, C‐reactive protein, albumin, pre‐albumin, transferrin, and pro‐inflammatory and immune cytokines. Acute Physiology and Chronic Health Evaluation (APACHE II), Sequential Organ Failure Assessment (SOFA), and maximal vasoactive–inotropic scores (VISmax) were calculated. Patients were followed up until death or a maximum of 1 year. The primary endpoint was all‐cause death. Of the 115 patients, 37 (32.2%) were admitted owing to acute HF, and 78 (67.8%) were admitted owing to acute on chronic HF; 64 (55.7%) had ST elevation/non‐ST elevation myocardial infarction. An LVEF measured during the hospitalization of <40%, 40–50%, and ≥50% was noted in 51 (44.3%), 15 (13.1%), and 49 (42.6%) patients, respectively. During 1 year follow‐up, 51 (44.3%) patients died. Death was associated with higher APACHE II, SOFA, and VISmax scores; higher levels of C‐reactive protein and phenylalanine; higher incidence of atrial fibrillation and use of inotropic agents; lower cholesterol, albumin, pre‐albumin, and transferrin levels; and significant changes in pro‐inflammatory and immune cytokines. Phenylalanine levels demonstrated an area under the receiver operating characteristic curve of 0.80 for mortality, with an optimal cut‐off value set at 112 μM. Phenylalanine ≥ 112 μM was associated with a higher mortality rate than was phenylalanine < 112 μM (80.5% vs. 24.3%, P < 0.001) [hazard ratio = 5.07 (2.83–9.05), P < 0.001]. The Kaplan–Meier curves revealed that phenylalanine ≥ 112 μM was associated with a lower accumulative survival rate (log rank = 36.9, P < 0.001). Higher phenylalanine levels were correlated with higher APACHE II and SOFA scores, higher C‐reactive protein levels and incidence of using inotropic agents, and changes in cytokines suggestive of immunosuppression, but lower levels of pre‐albumin and transferrin. Further multivariable analysis showed that phenylalanine ≥ 112 μM predicted death over 1 year independently of age, APACHE II and SOFA scores, atrial fibrillation, C‐reactive protein, cholesterol, pre‐albumin, transferrin, and interleukin‐8 and interleukin‐10.ConclusionsElevated phenylalanine levels predicted mortality in critical patients, phenotypically predominantly presenting with HF, independently of traditional prognostic factors and cytokines associated with inflammation and immunity.