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Nevin Manimala Statistics

The relay for human longevity: country-specific contributions to the increase of the best-practice life expectancy

Qual Quant. 2022 Jan 13:1-13. doi: 10.1007/s11135-021-01298-1. Online ahead of print.

ABSTRACT

This study investigates the long-term dynamics of longevity by taking into account the specific contribution of each country, and how this has changed over time, thus highlighting different timing and speeds of the evolution of life expectancy among the low-lowest mortality countries. Leveraging on quantile regression, we analyze the specific position of countries that have recorded the maximum (BPLE) and second-best life expectancy value at least once in the period 1960-2014, both at ages 0 and 65. Moving in this direction, the purpose of our contribution is to provide new perspectives on the untracked behavior that may be overshadowed by the maximum longevity levels. Our results provide a comprehensive picture of the different phases and transitions experienced by developed countries in the evolution of life expectancy that has led to a continuous increase in the BPLE. This study is a prominent practice in detecting untracked behaviors, providing imminent onsets on the maximum and sub-maximum values, thus contributing to new clues for future longevity.

PMID:35039691 | PMC:PMC8754529 | DOI:10.1007/s11135-021-01298-1

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Nevin Manimala Statistics

Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis

NPJ Digit Med. 2022 Jan 17;5(1):6. doi: 10.1038/s41746-021-00551-z.

ABSTRACT

To seek new signatures of illness in heart rate and oxygen saturation vital signs from Neonatal Intensive Care Unit (NICU) patients, we implemented highly comparative time-series analysis to discover features of all-cause mortality in the next 7 days. We collected 0.5 Hz heart rate and oxygen saturation vital signs of infants in the University of Virginia NICU from 2009 to 2019. We applied 4998 algorithmic operations from 11 mathematical families to random daily 10 min segments from 5957 NICU infants, 205 of whom died. We clustered the results and selected a representative from each, and examined multivariable logistic regression models. 3555 operations were usable; 20 cluster medoids held more than 81% of the information, and a multivariable model had AUC 0.83. New algorithms outperformed others: moving threshold, successive increases, surprise, and random walk. We computed provenance of the computations and constructed a software library with links to the data. We conclude that highly comparative time-series analysis revealed new vital sign measures to identify NICU patients at the highest risk of death in the next week.

PMID:35039624 | DOI:10.1038/s41746-021-00551-z

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Nevin Manimala Statistics

Effect of the toothbrush tuft arrangement and bristle stiffness on the abrasive dentin wear

Sci Rep. 2022 Jan 17;12(1):840. doi: 10.1038/s41598-022-04884-x.

ABSTRACT

The geometrical properties of toothbrushes play a role in developing abrasive tooth wear and non-carious cervical lesions. This study investigated the interplay between the toothbrush tuft arrangement (crossed vs. parallel) and bristle stiffness (soft vs. medium) on the abrasive dentin wear using three slurries with different levels of abrasivity (RDA: 67, 121 and 174). Twelve groups of bovine dentin samples (n = 20) were brushed with a combination of the aforementioned variables. Abrasive dentin wear was recorded with a profilometer and the resulting abrasive wear of each group was calculated and compared with each other using two-way ANOVA and pairwise tests. Toothbrushes with parallel tuft arrangement caused statistically significantly higher dentin wear compared to crossed tuft arrangement, regardless of the abrasivity level of the used slurry and the bristle stiffness. Soft crossed tuft toothbrushes caused statistically significantly higher abrasive dentin wear than medium crossed tuft toothbrushes, while soft and medium parallel tuft toothbrushes caused the same amounts of dentin wear, regardless of the RDA value of the used slurry. These results could be helpful for dentists and dental hygienists when advising patients. Crossed tuft toothbrushes could be a less-abrasive choice in comparison to parallel tuft toothbrushes.

PMID:35039599 | DOI:10.1038/s41598-022-04884-x

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Nevin Manimala Statistics

Objective evaluation of deep uncertainty predictions for COVID-19 detection

Sci Rep. 2022 Jan 17;12(1):815. doi: 10.1038/s41598-022-05052-x.

ABSTRACT

Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their predictive confidence. Quantifying uncertainties associated with DNN predictions is a prerequisite for their trusted deployment in medical settings. Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced. Through comprehensive experiments, it is shown that networks pertained on CXR images outperform networks pretrained on natural image datasets such as ImageNet. Qualitatively and quantitatively evaluations also reveal that the predictive uncertainty estimates are statistically higher for erroneous predictions than correct predictions. Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates. We also observe that ensemble methods more reliably capture uncertainties during the inference. DNN-based solutions for COVID-19 detection have been mainly proposed without any principled mechanism for risk mitigation. Previous studies have mainly focused on on generating single-valued predictions using pretrained DNNs. In this paper, we comprehensively apply and comparatively evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced for the first time. Using these new uncertainty performance metrics, we quantitatively demonstrate when we could trust DNN predictions for COVID-19 detection from chest X-rays. It is important to note the proposed novel uncertainty evaluation metrics are generic and could be applied for evaluation of probabilistic forecasts in all classification problems.

PMID:35039620 | DOI:10.1038/s41598-022-05052-x

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Nevin Manimala Statistics

Joint analysis of the intention to vaccinate and to use contact tracing app during the COVID-19 pandemic

Sci Rep. 2022 Jan 17;12(1):793. doi: 10.1038/s41598-021-04765-9.

ABSTRACT

Pharmacological and non-pharmacological measures will overlap for a period after the onset of the pandemic, playing a strong role in virus containment. We explored which factors influence the likelihood to adopt two different preventive measures against the COVID-19 pandemic. An online snowball sampling (May-June 2020) collected a total of 448 questionnaires in Italy. A Bayesian bivariate Gaussian regression model jointly investigated the willingness to get vaccinated against COVID-19 and to download the national contact tracing app. A mixed-effects cumulative logistic model explored which factors affected the motivation to adopt one of the two preventive measures. Despite both COVID-19 vaccines and tracing apps being indispensable tools to contain the spread of SARS-CoV-2, our results suggest that adherence to the vaccine or to the national contact tracing app is not predicted by the same factors. Therefore, public communication on these measures needs to take in consideration not only the perceived risk associated with COVID-19, but also the trust people place in politics and science, their concerns and doubts about vaccinations, and their employment status. Further, the results suggest that the motivation to comply with these measurements was predominantly to protect others rather than self-protection.

PMID:35039550 | DOI:10.1038/s41598-021-04765-9

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Nevin Manimala Statistics

Long-term metal fume exposure assessment of workers in a shipbuilding factory

Sci Rep. 2022 Jan 17;12(1):790. doi: 10.1038/s41598-021-04761-z.

ABSTRACT

This study aims to assess the metal fume exposure of welders and to determine exposure rates for similar exposure groups in a shipyard through the use of Near-field/Far-field (NF/FF) mathematical model and Bayesian decision analysis (BDA) technique. Emission rates of various metal fumes (i.e., total chromium (Cr), iron (Fe), lead (Pb), manganese (Mn), and nickel (Ni)) were experimentally determined for the gas metal arc welding and flux cored arc welding processes, which are commonly used in shipyards. Then the NF/FF field model which used the emission rates were further validated by welding simulation experiment, and together with long-term operation condition data obtained from the investigated shipyard, the predicted long-term exposure concentrations of workers was established and used as the prior distribution in the BDA. Along with the field monitoring metal fume concentrations which served as the likelihood distribution, the posterior decision distributions in the BDA were determined and used to assess workers’ long-term metal exposures. Results show that the predicted exposure concentrations (Cp) and the field worker’s exposure concentrations (Cm) were statistically correlated, and the high R2 (= 0.81-0.94) indicates that the proposed surrogate predicting method by the NF and FF model was adequate for predicting metal fume concentrations. The consistency in both prior and likelihood distributions suggests the resultant posterior would be more feasible to assess workers’ long-term exposures. Welders’ Fe, Mn and Pb exposures were found to exceed their corresponding action levels with a high probability (= 54%), indicating preventive measures should be taken immediately. The proposed approach provides a universal solution for conducting exposure assessment with usual limited number of personal exposure data.

PMID:35039543 | DOI:10.1038/s41598-021-04761-z

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Nevin Manimala Statistics

The impairment of speech perception in noise following pure tone hearing recovery in patients with sudden sensorineural hearing loss

Sci Rep. 2022 Jan 17;12(1):866. doi: 10.1038/s41598-021-03847-y.

ABSTRACT

To explore whether patients with unilateral idiopathic sudden sensorineural hearing loss (uISSNHL) have normal speech in noise (SIN) perception under different masking conditions after complete recovery of pure tone audiometry. Eight completely recovered uISSNHL patients were enrolled in ISSNHL group, while 8 normal-hearing adults matched with age, gender, and education experience were selected as the control group. Each group was tested SIN under four masking conditions, including noise and speech maskings with and without spatial separation cues. For both ISSNHL and control groups a two-way ANOVA showed a statistically significant effect of masking type (p = 0.007 vs p = 0.012). A significant effect of perceived spatial separation (p < 0.001 vs p < 0.001). A significant interaction between masking type and perceived spatial separation was found (p < 0.001 vs p < 0.001). A paired sample T-test showed that the SIN perception of the control group was statistically significant lower than that of ISSNHL patients only under speech masking without spatial separation cues (p = 0.011). There were still abnormalities in the auditory center shortly after complete recovery in the ISSNHL group (within 2 weeks). However, the auditory periphery and higher-level ability to use spatial cues was normal.

PMID:35039548 | DOI:10.1038/s41598-021-03847-y

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Nevin Manimala Statistics

A randomized controlled trial of stem cell injection for tendon tear

Sci Rep. 2022 Jan 17;12(1):818. doi: 10.1038/s41598-021-04656-z.

ABSTRACT

Tendons have limited reparative ability and perform a relatively simple mechanical function via the extracellular matrix. Thus, the injured tendon might be treated successfully by stem cell transplantation. We performed a randomized, controlled study to investigate the effects of mesenchymal stem cell injection for treating partial tears in the supraspinatus tendon. We enrolled 24 patients with shoulder pain lasting more than 3 months and partial tears in the supraspinatus tendon. Participants were assigned to three groups: stem cells in fibrin glue, normal saline/fibrin glue mixture, and normal saline only, with which intra-lesional injection was performed. Pain at activity and rest, shoulder function and tear size were evaluated. For safety measures, laboratory tests were taken and adverse events were recorded at every visit. Participants were followed up at 6, 12 weeks, 6, 12 months and 2 years after injection. The primary outcome measure was the improvement in pain at activity at 3 months after injection. Twenty-three patients were included in the final analysis. Primary outcome did not differ among groups (p = 0.35). A mixed effect model revealed no statistically significant interactions. Only time significantly predicted the outcome measure. All participants reported transient pain at the injection site. There were no differences in post-injection pain duration or severity. Safety measures did not differ between groups, and there were no persistent adverse events. Stem cell injection into supraspinatus partial tears in patients with shoulder pain lasting more than 3 months was not more effective than control injections.ClinicalTrials.gov Identifier: NCT02298023.

PMID:35039529 | DOI:10.1038/s41598-021-04656-z

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Nevin Manimala Statistics

Extracting phylogenetic dimensions of coevolution reveals hidden functional signals

Sci Rep. 2022 Jan 17;12(1):820. doi: 10.1038/s41598-021-04260-1.

ABSTRACT

Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein’s phylogenetic history and gives rise to concurrent variation between protein sequences that is not driven by selection for function. Here, we introduce a background model for phylogenetic contributions of statistical coupling that separates the coevolution signal due to inter-clade and intra-clade sequence comparisons and demonstrate that coevolution can be measured on multiple phylogenetic timescales within a single protein. Our method, nested coevolution (NC), can be applied as an extension to any coevolution metric. We use NC to demonstrate that poorly conserved residues can nonetheless have important roles in protein function. Moreover, NC improved the structural-contact predictions of several coevolution-based methods, particularly in subsampled alignments with fewer sequences. NC also lowered the noise in detecting functional sectors of collectively coevolving residues. Sectors of coevolving residues identified after application of NC were more spatially compact and phylogenetically distinct from the rest of the protein, and strongly enriched for mutations that disrupt protein activity. Thus, our conceptualization of the phylogenetic separation of coevolution provides the potential to further elucidate relationships among protein evolution, function, and genetic diseases.

PMID:35039514 | DOI:10.1038/s41598-021-04260-1

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Nevin Manimala Statistics

Microbiome differential abundance methods produce different results across 38 datasets

Nat Commun. 2022 Jan 17;13(1):342. doi: 10.1038/s41467-022-28034-z.

ABSTRACT

Identifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods are used interchangeably for this purpose in the literature. Yet, there are few large-scale studies systematically exploring the appropriateness of using these tools interchangeably, and the scale and significance of the differences between them. Here, we compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups. We test for differences in amplicon sequence variants and operational taxonomic units (ASVs) between these groups. Our findings confirm that these tools identified drastically different numbers and sets of significant ASVs, and that results depend on data pre-processing. For many tools the number of features identified correlate with aspects of the data, such as sample size, sequencing depth, and effect size of community differences. ALDEx2 and ANCOM-II produce the most consistent results across studies and agree best with the intersect of results from different approaches. Nevertheless, we recommend that researchers should use a consensus approach based on multiple differential abundance methods to help ensure robust biological interpretations.

PMID:35039521 | DOI:10.1038/s41467-022-28034-z