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Nevin Manimala Statistics

Auditory Processing Disorder Test Battery in European Portuguese-Development and Normative Data for Pediatric Population

Audiol Res. 2021 Sep 17;11(3):474-490. doi: 10.3390/audiolres11030044.

ABSTRACT

There is an increasing need for state-of-the-art Central Auditory Processing assessment for Portuguese native speakers, applicable as early as possible. As a contribution to answering this need, this paper presents a new battery for Central Auditory Processing assessment for European Portuguese applicable to children aged 5 and above, named BAPA-PE, providing information regarding test selection and development. The battery consists of six behavioral tests: Staggered Spondaic Words (SSW) for European Portuguese, Filtered Speech, Speech in Noise, Detection Interval in Noise, Duration, and Frequency Pattern. The normative data for children aged 5 to 12 are also reported. A sample was obtained of 217 subjects without ear pathology and with typical development. Each age group was composed of at least 30 children. All children were evaluated using pure tone audiometry, speech audiometry, impedance, and otoacoustic emissions. Normative scores are reported for each of the six auditory processing tests. The assessment is applicable to young children (aged 5 and 6). The statistical analyses showed significant effects in scores of Age for all tests and of Ear for several tests. The main result from the work presented, the Auditory Processing Assessment Battery-European Portuguese (BAPA-PE), is available for clinical use with normative data. This battery is a new tool for behaviorism assessment of European Portuguese speakers with suspected central auditory pathology and for monitoring the results of auditory training.

PMID:34562882 | DOI:10.3390/audiolres11030044

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Nevin Manimala Statistics

Application of a solid-phase microextraction-gas chromatography-mass spectrometry/metal oxide sensor system for detection of antibiotic susceptibility in urinary tract infection-causing Escherichia coli – A proof of principle study

Adv Med Sci. 2021 Sep 22;67(1):1-9. doi: 10.1016/j.advms.2021.09.001. Online ahead of print.

ABSTRACT

PURPOSE: Antibiotic resistance is widespread throughout the world and represents a serious health concern. There is an urgent need for the development of novel tools for rapidly distinguishing antibiotic resistant bacteria from susceptible strains. Previous work has demonstrated that differences in antimicrobial susceptibility can be reflected in differences in the profile of volatile organic compounds (VOCs) produced by dissimilar strains. The aim of this study was to investigate the effect of the presence of cephalosporin antibiotics on the VOC profile of extended spectrum beta-lactamase (ESBL) and non-ESBL producing strains of Escherichia coli.

MATERIAL AND METHODS: In this study, VOCs from strains of Escherichia coli positive and negative for the most commonly encountered ESBL, CTX-M in the presence of cephalosporin antibiotics were assessed using solid-phase microextraction (SPME) coupled with a combined gas chromatography-mass spectrometry/metal oxide sensor (GC-MS/MOS) system.

RESULTS: Our proof-of-concept study allowed for distinguishing CTX-M positive and negative bacteria within 2 ​h after the addition of antibiotics. One MOS signal (RT: 22.6) showed a statistically significant three-way interaction (p ​= ​0.033) in addition to significant two-way interactions for culture and additive (p ​= ​0.046) plus time and additive (p ​= ​0.020). There were also significant effects observed for time (p ​= ​0.009), culture (p ​= ​0.030) and additive (p ​= ​0.028). No effects were observed in the MS data.

CONCLUSIONS: The results of our study showed the potential of VOC analysis using SPME combined with a GC-MS/MOS system for the early detection of CTX-M-producing, antibiotic-resistant E. coli, responsible for urinary tract infections (UTIs).

PMID:34562855 | DOI:10.1016/j.advms.2021.09.001

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Nevin Manimala Statistics

Triglyceride/Glucose Index (TyG Index) as a marker of glucose status conversion among reproductive-aged women in Jakarta, Indonesia: The Bogor cohort study (2011-2016)

Diabetes Metab Syndr. 2021 Sep 11;15(6):102280. doi: 10.1016/j.dsx.2021.102280. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Reproductive-aged women are prone to type 2 diabetes mellitus. This study aims to evaluate the optimal cut off point of Triglyceride/Glucose Index for predicting glucose status conversion among women of reproductive age.

METHODS: This study involved normoglycemic and prediabetes women aged 20-49 years from the Bogor Non-Communicable Diseases Cohort Study (West Java, Indonesia) conducted from 2011 to 2016. Statistical analysis was performed using Receiver Operating Characteristics curve analysis with STATA version 15.

RESULTS: Among prediabetes subjects (n = 371), the cut-off point of TyG index for regression from prediabetes to normoglycemic subjects was <4.51 [sensitivity, specificity, AUC (95%CI) 83.9%, 80.1%, 0.913 (0.875-0.943), respectively] and the cut-off point for progression from prediabetes to diabetes was >4.54 [80.0%, 73.1%, 0.858 (0.807-0.900)]. Among normoglycemic subjects (n = 1300), the cut-off point of TyG index for progression to prediabetes and diabetes were >4.44 [80.1%, 71.1%, 0.834 (0.812-0.854)] and >4.47 [80.6%, 80.8%, 0.909 (0.890-0.926)] respectively.

CONCLUSION: Based on sample of subjects evaluated between 2011 and 2016, TyG index appears to be a promising marker for glucose status conversion among reproductive-aged women in Jakarta, Indonesia.

PMID:34562866 | DOI:10.1016/j.dsx.2021.102280

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Nevin Manimala Statistics

Which measurement method should be used for prostate volume for PI-RADS? A comparison of ellipsoid and segmentation methods

Clin Imaging. 2021 Sep 21;80:454-458. doi: 10.1016/j.clinimag.2021.09.003. Online ahead of print.

ABSTRACT

PURPOSE: Prostate volume and PSA density (PSAd) are important in the risk stratification of suspected prostate cancer (Pca). PI-RADS v2.1 allows for determining volume via segmentation or ellipsoid calculation. The purpose of our study was to compare ellipsoid and segmentation volume calculation methods and evaluate if PSAd diagnostic performance is altered.

METHODS: We retrospectively assessed 397 patients (mean age/standard deviation: 63.7/7.4 years) who underwent MRI and prostate biopsy or prostatectomy, with Pca classified by Gleason ≥3 + 4 and ≥4 + 4 disease. Prostate total volumes were determined with ellipsoid calculations (TVe) and with semi-automated segmentation (TVs), along with inter-rater reliability with intraclass correlation coefficient (ICC). PSAd was calculated for TVe and TVs and ROC curves were created to compare performance for Gleason ≥3 + 4 and ≥4 + 4 disease.

RESULTS: TVe was significantly higher than TVs (p < 0.0001), with mean TVe = 55.4 mL and TVs = 51.0 mL. ROC area under the curve for PSAd derived with TVe (0.63, 95%CI:0.59-0.68) and TVs (0.64, 95%CI:0.59-0.68) showed no significant difference for Gleason ≥3 + 4 disease (p = 0.45), but PSAd derived with TVs (0.63, 95%CI: 0.58-0.68) significantly outperformed TVe (0.61, 95%CI: 0.57-0.67) for Gleason ≥4 + 4 disease (p = 0.02). Both methods demonstrated excellent inter-rater reliability with TVe with ICC of 0.93(95%CI: 0.92-0.94) and TVs with ICC of 0.98(95%CI: 0.98-0.99).

CONCLUSION: Traditional ellipsoid measurements tend to overestimate total prostate volume compared to segmentation, but both methods demonstrate similar diagnostic performance of derived PSA density for PI-RADS clinically significant disease. For higher grade disease, PSAd derived from segmentation volumes demonstrates statistically significant superior performance. Both methods are viable, but segmentation volume is potentially better.

PMID:34562834 | DOI:10.1016/j.clinimag.2021.09.003

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Nevin Manimala Statistics

QSAR-guided pharmacophoric modeling reveals important structural requirements for Polo kinase 1 (Plk1) inhibitors

J Mol Graph Model. 2021 Sep 18;109:108022. doi: 10.1016/j.jmgm.2021.108022. Online ahead of print.

ABSTRACT

Targeting Polo-like kinase 1 (Plk1) by molecular inhibitors is being a promising approach for tumor therapy. Nevertheless, insufficient methodical analyses have been done to characterize the interactions inside the Plk1 binding pocket. In this study, an extensive combined ligand and structure-based drug design workflow was conducted to data-mine the structural requirements for Plk1 inhibition. Consequently, the binding modes of 368 previously known Plk1 inhibitors were investigated by pharmacophore generation technique. The resulted pharmacophores were engaged in the context of Genetic function algorithm (GFA) and Multiple linear regression (MLR) analyses to search for a prognostic QSAR model. The most successful QSAR model was with statistical criteria of (r2277 = 0.76, r2adj = 0.76, r2pred = 0.75, Q2 = 0.73). Our QSAR-selected pharmacophores were validated by Receiver Operating Characteristic (ROC) curve analysis. Later on, the best QSAR model and its associated pharmacophoric hypotheses (HypoB-T4-5, HypoI-T2-7, HypoD-T4-3, and HypoC-T3-3) were used to identify new Plk1 inhibitory hits retrieved from the National Cancer Institute (NCI) database. The most potent hits exhibited experimental anti-Plk1 IC50 of 1.49, 3.79. 5.26 and 6.35 μM. Noticeably, our hits, were found to interact with the Plk1 kinase domain through some important amino acid residues namely, Cys67, Lys82, Cys133, Phe183, and Asp194.

PMID:34562852 | DOI:10.1016/j.jmgm.2021.108022

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Nevin Manimala Statistics

Alteration of power law scaling of spontaneous brain activity in schizophrenia

Schizophr Res. 2021 Sep 22;238:10-19. doi: 10.1016/j.schres.2021.08.026. Online ahead of print.

ABSTRACT

Nonlinear dynamical analysis has been used to quantify the complexity of brain signal at temporal scales. Power law scaling is a well-validated method in physics that has been used to describe the dynamics of a system in the frequency domain, ranging from noisy oscillation to complex fluctuations. In this research, we investigated the power-law characteristics in a large-scale resting-state fMRI data of schizophrenia and healthy participants derived from Taiwan Aging and Mental Illness cohort. We extracted the power spectral density (PSD) of resting signal by Fourier transform. Power law scaling of PSD was estimated by determining the slope of the regression line fitting to the logarithm of PSD. t-Test was used to assess the statistical difference in power law scaling between schizophrenia and healthy participants. The significant differences in power law scaling were found in six brain regions. Schizophrenia patients have significantly more positive power law scaling (i.e., more homogenous frequency components) at four brain regions: left precuneus, left medial dorsal nucleus, right inferior frontal gyrus, and right middle temporal gyrus and less positive power law scaling (i.e., more dominant at lower frequency range) in bilateral putamen compared with healthy participants. Moreover, significant correlations of power law scaling with the severity of psychosis were found. These findings suggest that schizophrenia has abnormal brain signal complexity linked to psychotic symptoms. The power law scaling represents the dynamical properties of resting-state fMRI signal may serve as a novel functional brain imaging marker for evaluating patients with mental illness.

PMID:34562833 | DOI:10.1016/j.schres.2021.08.026

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Nevin Manimala Statistics

Uncertainty propagation for dropout-based Bayesian neural networks

Neural Netw. 2021 Sep 9;144:394-406. doi: 10.1016/j.neunet.2021.09.005. Online ahead of print.

ABSTRACT

Uncertainty evaluation is a core technique when deep neural networks (DNNs) are used in real-world problems. In practical applications, we often encounter unexpected samples that have not seen in the training process. Not only achieving the high-prediction accuracy but also detecting uncertain data is significant for safety-critical systems. In statistics and machine learning, Bayesian inference has been exploited for uncertainty evaluation. The Bayesian neural networks (BNNs) have recently attracted considerable attention in this context, as the DNN trained using dropout is interpreted as a Bayesian method. Based on this interpretation, several methods to calculate the Bayes predictive distribution for DNNs have been developed. Though the Monte-Carlo method called MC dropout is a popular method for uncertainty evaluation, it requires a number of repeated feed-forward calculations of DNNs with randomly sampled weight parameters. To overcome the computational issue, we propose a sampling-free method to evaluate uncertainty. Our method converts a neural network trained using dropout to the corresponding Bayesian neural network with variance propagation. Our method is available not only to feed-forward NNs but also to recurrent NNs such as LSTM. We report the computational efficiency and statistical reliability of our method in numerical experiments of language modeling using RNNs, and the out-of-distribution detection with DNNs.

PMID:34562813 | DOI:10.1016/j.neunet.2021.09.005

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Nevin Manimala Statistics

Functional Social Support and Perceived Stress of Nurses Working in Secular and Religious Hospitals

J Natl Black Nurses Assoc. 2021 Sep;32(1):35-40.

ABSTRACT

Nurses experience high levels of stress. In this study, functional social support and perceived stress of nurses working in secular and religious hospitals were examined. The social support model, the job demands-resources theory, and the transactional model of stress guided this study. The population that was examined was comprised of a convenience and snowballing sample of 84 registered nurses from across the United States. The data collected using the Expanded Nursing Stress Scale, the Inventory of Socially Supportive Behavior survey, and a demographic questionnaire were statistically analyzed using Pearson’s correlation and Fisher’s Test. Results showed no significant relationship between support and nurses’ stress in secular hospitals and no significant relationship between the same variables for nurses’ in religious hospitals. Findings also revealed that there was no significant difference in the compared correlations for nurses’ support and stress between the two groups. The outcomes will inform healthcare professionals about the association between nurses’ support and stress in hospitals with unique missions.

PMID:34562351

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Nevin Manimala Statistics

Influenza vaccination among caregivers and household contacts of children with congenital heart disease before and during COVID-19 pandemic

J Paediatr Child Health. 2021 Sep 25. doi: 10.1111/jpc.15748. Online ahead of print.

ABSTRACT

AIM: We aimed to investigate the influenza immunisation status of caregivers and household contacts of children with congenital heart disease (CHD) and potential barriers to vaccine uptake.

METHODS: Prospective questionnaire-based survey over two influenza seasons (2019-2020 and 2020-2021) on 161 children with CHD attending a tertiary paediatric cardiology clinic and their families. Logistic regression and factor analysis were performed to identify factors associated with influenza vaccine uptake.

RESULTS: Influenza vaccination coverage of children was 65%, whereas that of their fathers and mothers was 34% and 26%, respectively. Children with unvaccinated siblings represented 43% and those with unvaccinated adults in the household 79% of our study population. No statistically significant differences were found before and during COVID-19 pandemic on vaccine uptake. Logistic regression analysis showed that higher education level, understanding the risk of contracting the disease and vaccination status of the child determined the vaccination status of parents, regardless of their age, age of their child, severity of CHD, beliefs about vaccine safety and efficacy and risk of transmission if not vaccinated. Factor analysis revealed distinct groups among unvaccinated parents (76.3% of the variation in the responses).

CONCLUSIONS: Vaccination coverage of caregivers and household contacts of children with CHD is suboptimal. Influenza vaccination campaigns should take into consideration the specific characteristics of parental groups and target interventions accordingly to increase their vaccine uptake and indirectly protect children with CHD.

PMID:34562323 | DOI:10.1111/jpc.15748

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Nevin Manimala Statistics

Metaheuristics for Pharmacometrics

CPT Pharmacometrics Syst Pharmacol. 2021 Sep 25. doi: 10.1002/psp4.12714. Online ahead of print.

ABSTRACT

Metaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature-inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be particularly flexible and useful in solving complicated optimization problems in computer science and engineering. A common practice with metaheuristics is to hybridize it with another suitably chosen algorithm for enhanced performance. This paper reviews metaheruristic algorithms and demonstrates some of its utility in tackling pharmacometric problems. Specifically, we provide three applications using one of its most celebrated members, particle swarm optimization (PSO), and show that PSO can effectively estimate parameters in complicated nonlinear mixed-effects models and to gain insights into statistical identifiability issues in a complex compartment model. In the third application, we demonstrate how to hybridize PSO with sparse grid, which is an often used technique to evaluate high dimensional integrals, to search for D-efficient designs for estimating parameters in nonlinear mixed-effects models with a count outcome. We also show the proposed hybrid algorithm outperforms its competitors when sparse grid is replaced by its competitor, adaptive gaussian quadrature to approximate the integral, or when PSO is replaced by three notable nature-inspired metaheuristic algorithms.

PMID:34562342 | DOI:10.1002/psp4.12714