Tag: nevin manimala

PLoS One. 2021 Jul 29;16(7):e0255422. doi: 10.1371/journal.pone.0255422. eCollection 2021.

ABSTRACT

In this study, a network autoregressive model with GARCH effects, denoted by NAR-GARCH, is proposed to depict the return dynamics of stock market indices. A GARCH filter is employed to marginally remove the GARCH effects of each index, and the NAR model with the Granger causality test and Pearson’s correlation test with sharp price movements is used to capture the joint effects caused by other indices with the most updated market information. The NAR-GARCH model is designed to depict the joint effects of nonsynchronous multiple time series in an easy-to-implement and effective way. The returns of 20 global stock indices from 2006 to 2020 are employed for our empirical investigation. The numerical results reveal that the NAR-GARCH model has satisfactory performance in both fitting and prediction for the 20 stock indices, especially when a market index has strong upward or downward movements.

PMID:34324604 | DOI:10.1371/journal.pone.0255422

PLoS One. 2021 Jul 29;16(7):e0255384. doi: 10.1371/journal.pone.0255384. eCollection 2021.

ABSTRACT

We aimed to investigate whether antibiotic administration is necessary for patients with uncomplicated right colonic diverticulitis. Data from patients diagnosed with uncomplicated right colonic diverticulitis, who received inpatient treatment at a single center between January 2019 and January 2021, were retrospectively examined. The patients were divided into two groups according to whether antibiotics were administered. The patients were matched between groups using propensity score matching in a 1:1 ratio using logistic regression with the nearest-neighbor method. The primary study outcome was the length of hospital stay, and the secondary outcomes were time to the introduction of sips of water and a soft diet. The study included 138 patients who received antibiotics and 59 who did not. After propensity score matching, 55 patients were assigned to each treatment group. There was no significant difference between the two groups in terms of age (p = 0.772), sex (p>0.999), body mass index (p = 0.121), prehospital symptom duration (p = 0.727), initial body temperature (p = 0.661), white blood cell count (p = 0.688), or C-reactive protein level (p = 0.337). There was also no statistically significant difference in the length of hospital stay between the no antibiotic and antibiotic groups (3.1±0.7 days vs. 3.0±1.0 days, p = 0.584). Additionally, no significant difference was observed between the no antibiotic and antibiotic groups with respect to time to sips of water (2.1±0.7 days vs. 1.8±0.9 days, p = 0.100) and time to the introduction of a soft diet (2.4±0.8 days vs. 2.1±0.9 days, p = 0.125). The findings suggest that routine antibiotics may be not required for treating patients with uncomplicated right colonic diverticulitis.

PMID:34324608 | DOI:10.1371/journal.pone.0255384

PLoS One. 2021 Jul 29;16(7):e0255221. doi: 10.1371/journal.pone.0255221. eCollection 2021.

ABSTRACT

Tendons are responsive to mechanical loading and their properties are often the target of intervention programs. The tendon’s mechanical properties, particularly stiffness, also govern its function, therefore changes to these properties could have substantial influence on energy-saving mechanisms during activities utilizing the stretch-shortening cycle. We investigated Achilles tendon (AT) function in vivo during walking with respect to a training intervention that elicited significant increases in AT stiffness. 14 men and women completed 12-weeks of isometric plantarflexor strength training that increased AT stiffness, measured during isometric MVC, by ~31%. Before and after the intervention, participants walked shod at their preferred velocity on a fully-instrumented treadmill. Movement kinematics, kinetics and displacement of the gastrocnemius medialis muscle-tendon junction were captured synchronously using 3D motion capture and ultrasound imaging, respectively. A MANOVA test was used to examine changes in AT force, stress, strain, stiffness, Young’s modulus, hysteresis and strain energy, measured during walking, before and following strength training. All were non-significant for a main effect of time, therefore no follow-up statistical tests were conducted. Changes in joint kinematics, tendon strain, velocity, work and power and muscle activity during the stance phase were assessed with 1D statistical parametric mapping, all of which also demonstrated a lack of change in response to the intervention. This in vivo examination of tendon function in walking provides an important foundation for investigating the functional consequences of training adaptations. We found substantial increases in AT stiffness did not impact on tendon function during walking. AT stiffness measured during walking, however, was unchanged with training, which suggests that increases in stiffness may not be evident across the whole force-elongation relation, a finding which may help explain previously mixed intervention results and guide future investigations in the functional implications of tendon adaptation.

PMID:34324575 | DOI:10.1371/journal.pone.0255221

PLoS One. 2021 Jul 29;16(7):e0255317. doi: 10.1371/journal.pone.0255317. eCollection 2021.

ABSTRACT

BACKGROUND: The assessment of self-reported outcomes in neuromyelitis optica spectrum disorder (NMOSD) is limited by the lack of validated disease-specific measures. The SymptoMScreen (SyMS) is a patient-reported questionnaire for measuring symptom severity in different domains affected by multiple sclerosis (MS), but has not been thoroughly evaluated in NMOSD. The aim of this study was to assess the psychometric properties of the SyMS in a sample of patients with NMOSD.

METHODS: A non-interventional, cross-sectional study in adult subjects with NMOSD (Wingerchuk 2015 criteria) was conducted at 13 neuroimmunology clinics applying the SyMS. A non-parametric item response theory procedure, Mokken analysis, was performed to assess the underlying dimensional structure and scalability of items and overall questionnaire. All analyses were performed with R (v4.0.3) using the mokken library.

RESULTS: A total of 70 patients were studied (mean age: 47.5 ± 15 years, 80% female, mean Expanded Disability Status Scale score: 3.0 [interquartile range 1.5, 4.5]). Symptom severity was low (median SyMS score: 19.0 [interquartile range 10.0, 32.0]). The SyMS showed a robust internal reliability (Cronbach’s alpha: 0.90 [95% confidence interval 0.86, 0.93]) and behaved as a unidimensional scale with all items showing scalability coefficients > 0.30. The overall SyMS scalability was 0.45 conforming to a medium scale according to Mokken’s criteria. Fatigue and body pain were the domains with the highest scalability coefficients. The SyMS was associated with disability (rho: 0.586), and physical and psychological quality of life (rho: 0.856 and 0.696, respectively).

CONCLUSIONS: The SyMS shows appropriate psychometric characteristics and may constitute a valuable and easy-to-implement option to measure symptom severity in patients with NMOSD.

PMID:34324586 | DOI:10.1371/journal.pone.0255317

PLoS One. 2021 Jul 29;16(7):e0255389. doi: 10.1371/journal.pone.0255389. eCollection 2021.

ABSTRACT

In a cluster-randomized trial (CRT), the number of participants enrolled often varies across clusters. This variation should be considered during both trial design and data analysis to ensure statistical performance goals are achieved. Most methodological literature on the CRT design has assumed equal cluster sizes. This scoping review focuses on methodology for unequal cluster size CRTs. EMBASE, Medline, Google Scholar, MathSciNet and Web of Science databases were searched to identify English-language articles reporting on methodology for unequal cluster size CRTs published until March 2021. We extracted data on the focus of the paper (power calculation, Type I error etc.), the type of CRT, the type and the range of parameter values investigated (number of clusters, mean cluster size, cluster size coefficient of variation, intra-cluster correlation coefficient, etc.), and the main conclusions. Seventy-nine of 5032 identified papers met the inclusion criteria. Papers primarily focused on the parallel-arm CRT (p-CRT, n = 60, 76%) and the stepped-wedge CRT (n = 14, 18%). Roughly 75% of the papers addressed trial design issues (sample size/power calculation) while 25% focused on analysis considerations (Type I error, bias, etc.). The ranges of parameter values explored varied substantially across different studies. Methods for accounting for unequal cluster sizes in the p-CRT have been investigated extensively for Gaussian and binary outcomes. Synthesizing the findings of these works is difficult as the magnitude of impact of the unequal cluster sizes varies substantially across the combinations and ranges of input parameters. Limited investigations have been done for other combinations of a CRT design by outcome type, particularly methodology involving binary outcomes-the most commonly used type of primary outcome in trials. The paucity of methodological papers outside of the p-CRT with Gaussian or binary outcomes highlights the need for further methodological development to fill the gaps.

PMID:34324593 | DOI:10.1371/journal.pone.0255389

PLoS One. 2021 Jul 29;16(7):e0255370. doi: 10.1371/journal.pone.0255370. eCollection 2021.

ABSTRACT

The aim of this study was to evaluate the potential of diatom (microalgae) biomass as a lice-reducing ingredient in salmon feed. The original hypothesis was based on the fact that polyunsaturated aldehydes (PUAs), e.g. 2-trans, 4-trans decadenial (A3) produced by diatoms can function as grazing deterrents and harm copepod development. Salmon lice (Lepeophtheirus salmonis) is a copepod, and we intended to test if inclusion of diatom biomass in the feed could reduce the infestation of lice on salmon. We performed experiments where salmon kept in tanks were offered four different diets, i.e. basic feed with diatoms, fish oil, Calanus sp. oil or rapeseed oil added. After a feeding period of 67 days a statistically representative group of fishes, tagged with diet group origin, were pooled in a 4000L tank and exposed to salmon lice copepodites whereafter lice infestation was enumerated. Salmon from all four diet groups had good growth with SGR values from 1.29 to 1.44% day-1 (increase from ca. 130 g to 350 g). At the termination of the experiment the number of lice on salmon offered diatom feed were statistically significantly lower than on salmon fed the other diets. Mean lice infestation values increased from diatom feed through Calanus and fish oil to standard feed with terrestrial plant ingredients. Analysis of the chemical composition of the different diets (fatty acids, amino acids) failed to explain the differences in lice infestation. The only notable result was that diatom and Calanus feed contained more FFA (free fatty acids) than feed with fish oil and the control feed. None of the potential deleterious targeted polyunsaturated aldehydes could be detected in skin samples of the salmon. What was exclusive for salmon that experienced reduced lice was diatom inclusion in the feed. This therefore still indicates the presence of some lice deterring ingredient, either in the feed, or an ingredient can have triggered production of an deterrent in the fish. An obvious follow up of this will be to perform experiments with different degrees of diatom inclusion in the feeds, i.e. dose response experiments combined with targeted PUA analyses, as well as to perform large scale experiments under natural conditions in aquaculture pens.

PMID:34324572 | DOI:10.1371/journal.pone.0255370

PLoS One. 2021 Jul 29;16(7):e0255377. doi: 10.1371/journal.pone.0255377. eCollection 2021.

ABSTRACT

OBJECTIVES: To describe the relationship between reported serious operational problems (SOPs), and mortality for patients with COVID-19 admitted to intensive care units (ICUs).

DESIGN: English national retrospective cohort study.

SETTING: 89 English hospital trusts (i.e. small groups of hospitals functioning as single operational units).

PATIENTS: All adults with COVID-19 admitted to ICU between 2nd April and 1st December, 2020 (n = 6,737).

INTERVENTIONS: N/A.

MAIN OUTCOMES AND MEASURES: Hospital trusts routinely submit declarations of whether they have experienced ‘serious operational problems’ in the last 24 hours (e.g. due to staffing issues, adverse weather conditions, etc.). Bayesian hierarchical models were used to estimate the association between in-hospital mortality (binary outcome) and: 1) an indicator for whether a SOP occurred on the date of a patient’s admission, and; 2) the proportion of the days in a patient’s stay that had a SOP occur within their trust. These models were adjusted for individual demographic characteristics (age, sex, ethnicity), and recorded comorbidities.

RESULTS: Serious operational problems (SOPs) were common; reported in 47 trusts (52.8%) and were present for 2,701 (of 21,716; 12.4%) trust days. Overall mortality was 37.7% (2,539 deaths). Admission during a period of SOPs was associated with a substantially increased mortality; adjusted odds ratio (OR) 1.34 (95% posterior credible interval (PCI): 1.07 to 1.68). Mortality was also associated with the proportion of a patient’s admission duration that had concurrent SOPs; OR 1.47 (95% PCI: 1.10 to 1.96) for mortality where SOPs were present for 100% compared to 0% of the stay.

CONCLUSION AND RELEVANCE: Serious operational problems at the trust-level are associated with a significant increase in mortality in patients with COVID-19 admitted to critical care. The link isn’t necessarily causal, but this observation justifies further research to determine if a binary indicator might be a valid prognostic marker for deteriorating quality of care.

PMID:34324569 | DOI:10.1371/journal.pone.0255377

PLoS One. 2021 Jul 29;16(7):e0255270. doi: 10.1371/journal.pone.0255270. eCollection 2021.

ABSTRACT

The COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has become the current health concern and threat to the entire world. Thus, the world needs the fast recognition of appropriate drugs to restrict the spread of this disease. The global effort started to identify the best drug compounds to treat COVID-19, but going through a series of clinical trials and our lack of information about the details of the virus’s performance has slowed down the time to reach this goal. In this work, we try to select the subset of human proteins as candidate sets that can bind to approved drugs. Our method is based on the information on human-virus protein interaction and their effect on the biological processes of the host cells. We also define some informative topological and statistical features for proteins in the protein-protein interaction network. We evaluate our selected sets with two groups of drugs. The first group contains the experimental unapproved treatments for COVID-19, and we show that from 17 drugs in this group, 15 drugs are approved by our selected sets. The second group contains the external clinical trials for COVID-19, and we show that 85% of drugs in this group, target at least one protein of our selected sets. We also study COVID-19 associated protein sets and identify proteins that are essential to disease pathology. For this analysis, we use DAVID tools to show and compare disease-associated genes that are contributed between the COVID-19 comorbidities. Our results for shared genes show significant enrichment for cardiovascular-related, hypertension, diabetes type 2, kidney-related and lung-related diseases. In the last part of this work, we recommend 56 potential effective drugs for further research and investigation for COVID-19 treatment. Materials and implementations are available at: https://github.com/MahnazHabibi/Drug-repurposing.

PMID:34324563 | DOI:10.1371/journal.pone.0255270

PLoS One. 2021 Jul 29;16(7):e0255146. doi: 10.1371/journal.pone.0255146. eCollection 2021.

ABSTRACT

BACKGROUND: The comparatively straightforward and cheaper light-emitting diode fluorescent microscope (LEDFM) was suggested by WHO to replace conventional microscope in tuberculosis (TB) laboratories. However, the comparable efficacy of each of those techniques differs from laboratory to laboratory. We investigated the efficacy of LEDFM for the diagnosis of tuberculous lymphadenitis (TBLN) patients.

METHODS: A cross-sectional study was conducted on 211 samples from clinically suspected tuberculous lymphadenitis patients. Three smears were prepared from FNA on microscope slides for cytomorphology study, Auramine O (AO), and for Ziehl-Neelsen (ZN) staining. The left-over samples were inoculated onto Lowenstein-Jensen (LJ) media. Statistical analysis was done using STATA version 11. The sensitivity, specificity, positive and negative predictive values were calculated by considering the culture results as the gold standard using a 95% confidence interval.

RESULTS: Among 211 samples 49.7% (105) were positive by cytomorphology, 32.7% (69) by LEDFM, 23.69% (50) by LJ culture, and 13.7% (29) by ZN. Compared to the gold standard sensitivity of ZN, LEDFM, and cytomorphology were 30% [95% CI: 17.9-44.6], 66% [95% CI: 51.2-78.8] 78% [95% CI: 64-88.5], respectively. The specificity of ZN, LEDFM, and cytomorphology was 91.3% [95% CI: 85.8-95.2], 77.6% [95% CI: 70.4-83.8], 58.8% [95% CI: 50.7-66.5], respectively.

CONCLUSION: LED fluorescence microscopy gives a legitimate option in contrast to conventional ZN techniques in terms of its higher sensitivity, a bit lower specificity, time-saving, and minimal effort.

PMID:34324565 | DOI:10.1371/journal.pone.0255146

PLoS One. 2021 Jul 29;16(7):e0255240. doi: 10.1371/journal.pone.0255240. eCollection 2021.

ABSTRACT

Metabolomic data processing pipelines have been improving in recent years, allowing for greater feature extraction and identification. Lately, machine learning and robust statistical techniques to control false discoveries are being incorporated into metabolomic data analysis. In this paper, we introduce one such recently developed technique called aggregate knockoff filtering to untargeted metabolomic analysis. When applied to a publicly available dataset, aggregate knockoff filtering combined with typical p-value filtering improves the number of significantly changing metabolites by 25% when compared to conventional untargeted metabolomic data processing. By using this method, features that would normally not be extracted under standard processing would be brought to researchers’ attention for further analysis.

PMID:34324558 | DOI:10.1371/journal.pone.0255240