Nevin Manimala

PLoS One. 2022 Jul 22;17(7):e0272007. doi: 10.1371/journal.pone.0272007. eCollection 2022.

ABSTRACT

Interval estimation with accurate coverage for risk difference (RD) in a correlated 2 × 2 table with structural zero is a fundamental and important problem in biostatistics. The score test-based and Bayesian tail-based confidence intervals (CIs) have good coverage performance among the existing methods. However, as approximation approaches, they have coverage probabilities lower than the nominal confidence level for finite and moderate sample sizes. In this paper, we propose three new CIs for RD based on the fiducial, inferential model (IM) and modified IM (MIM) methods. The IM interval is proven to be valid. Moreover, simulation studies show that the CIs of fiducial and MIM methods can guarantee the preset coverage rate even for small sample sizes. More importantly, in terms of coverage probability and expected length, the MIM interval outperforms other intervals. Finally, a real example illustrates the application of the proposed methods.

PMID:35867721 | DOI:10.1371/journal.pone.0272007

Clin Infect Dis. 2022 Jul 22:ciac577. doi: 10.1093/cid/ciac577. Online ahead of print.

ABSTRACT

BACKGROUND: Adult studies have demonstrated within-season declines in influenza vaccine effectiveness (VE); data in children are limited.

METHODS: We conducted a prospective, test-negative study of children 6 months-17 years hospitalized with acute respiratory illness at 7 pediatric medical centers during the 2015-2016 through 2019-2020 influenza seasons. Case-patients were children with an influenza-positive molecular test matched by illness onset to influenza-negative control-patients. We estimated VE [100% x (1 – odds ratio)] by comparing the odds of receipt of ≥1 dose of influenza vaccine ≥14 days before illness onset among influenza-positive children to influenza-negative children. Changes in VE over time between vaccination date and illness onset date were estimated using multivariable logistic regression.

RESULTS: Of 8,430 children, 4,653 (55%) received ≥1 dose of influenza vaccine. On average, 48% were vaccinated through October and 85% through December each season. Influenza vaccine receipt was lower in case-patients than control-patients (39% vs. 57%, p < 0.001); overall VE against hospitalization was 53% (95% CI: 46%-60%). Pooling data across 5 seasons, the odds of influenza-associated hospitalization increased 4.2% (-3.2%-12.2%) per month since vaccination, with an average VE decrease of 1.9% per month (n = 4,000, p = 0.275). Odds of hospitalization increased 2.9% (95% CI: -5.4%-11.8%) and 9.6% (95% CI: -7.0%-29.1%) per month in children ≤8 years (n = 3,084) and 9-17 years (n = 916), respectively. These findings were not statistically significant.

CONCLUSIONS: We observed minimal, not statistically significant within-season declines in VE. Vaccination following current ACIP guidelines for timing of vaccine receipt remains the best strategy for preventing influenza-associated hospitalizations in children.

PMID:35867698 | DOI:10.1093/cid/ciac577

JMIR Res Protoc. 2022 Jul 22;11(7):e35565. doi: 10.2196/35565.

ABSTRACT

BACKGROUND: Following radioiodine (¹³¹I) therapy of differentiated thyroid cancer, the salivary glands may become inflamed, leading to dysfunctions and decreases in patients’ nutritional status and quality of life. The incidence of these dysfunctions after ¹³¹I-therapy is poorly known, and no clinical or genetic factors have been identified to date to define at-risk patients, which would allow the delivered activity to be adapted to the expected risk of salivary dysfunctions.

OBJECTIVE: The aims of this study are to estimate the incidence of salivary dysfunctions, and consequences on the quality of life and nutritional status for patients after ¹³¹I-therapy; to characterize at-risk patients of developing posttreatment dysfunctions using clinical, biomolecular, and biochemical factors; and to validate a dosimetric method to calculate the dose received at the salivary gland level for analyzing the dose-response relationship between absorbed doses to salivary glands and salivary dysfunctions.

METHODS: This prospective study aims to include patients for whom ¹³¹I-therapy is indicated as part of the treatment for differentiated thyroid cancer in a Paris hospital (40 and 80 patients in the 1.1 GBq and 3.7 GBq groups, respectively). The follow-up is based on three scheduled visits: at inclusion (T0, immediately before ¹³¹I-therapy), and at 6 months (T6) and 18 months (T18) posttreatment. For each visit, questionnaires on salivary dysfunctions (validated French tool), quality of life (Hospital Anxiety and Depression scale, Medical Outcomes Study 36-Item Short Form Survey), and nutritional status (visual analog scale) are administered by a trained clinical research associate. At T0 and T6, saliva samples and individual measurements of the salivary flow, without and with salivary glands stimulation, are performed. External thermoluminescent dosimeters are positioned on the skin opposite the salivary glands and at the sternal fork immediately before ¹³¹I administration and removed after 5 days. From the doses recorded by the dosimeters, an estimation of the dose received at the salivary glands will be carried out using physical and computational phantoms. Genetic and epigenetic analyses will be performed to search for potential biomarkers of the predisposition to develop salivary dysfunctions after ¹³¹I-therapy.

RESULTS: A total of 139 patients (99 women, 71.2%; mean age 47.4, SD 14.3 years) were enrolled in the study between September 2020 and April 2021 (45 and 94 patients in the 1.1 GBq and 3.7G Bq groups, respectively). T6 follow-up is complete and T18 follow-up is currently underway. Statistical analyses will assess the links between salivary dysfunctions and absorbed doses to the salivary glands, accounting for associated factors. Moreover, impacts on the patients’ quality of life will be analyzed.

CONCLUSIONS: To our knowledge, this study is the first to investigate the risk of salivary dysfunctions (using both objective and subjective indicators) in relation to organ (salivary glands) doses, based on individual dosimeter records and dose reconstructions. The results will allow the identification of patients at risk of salivary dysfunctions and will permit clinicians to propose a more adapted follow-up and/or countermeasures to adverse effects.

TRIAL REGISTRATION: ClinicalTrials.gov NCT04876287; https://clinicaltrials.gov/ct2/show/NCT04876287.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35565.

PMID:35867385 | DOI:10.2196/35565

JMIR Serious Games. 2022 Jul 22;10(3):e38433. doi: 10.2196/38433.

ABSTRACT

BACKGROUND: Recently, the demand for mechanical ventilation (MV) has increased with the COVID-19 pandemic; however, the conventional approaches to MV training are resource intensive and require on-site training. Consequently, the need for independent learning platforms with remote assistance in institutions without resources has surged.

OBJECTIVE: This study aimed to determine the feasibility and effectiveness of an augmented reality (AR)-based self-learning platform for novices to set up a ventilator without on-site assistance.

METHODS: This prospective randomized controlled pilot study was conducted at Samsung Medical Center, Korea, from January to February 2022. Nurses with no prior experience of MV or AR were enrolled. We randomized the participants into 2 groups: manual and AR groups. Participants in the manual group used a printed manual and made a phone call for assistance, whereas participants in the AR group were guided by AR-based instructions and requested assistance with the head-mounted display. We compared the overall score of the procedure, required level of assistance, and user experience between the groups.

RESULTS: In total, 30 participants completed the entire procedure with or without remote assistance. Fewer participants requested assistance in the AR group compared to the manual group (7/15, 47.7% vs 14/15, 93.3%; P=.02). The number of steps that required assistance was also lower in the AR group compared to the manual group (n=13 vs n=33; P=.004). The AR group had a higher rating in predeveloped questions for confidence (median 3, IQR 2.50-4.00 vs median 2, IQR 2.00-3.00; P=.01), suitability of method (median 4, IQR 4.00-5.00 vs median 3, IQR 3.00-3.50; P=.01), and whether they intended to recommend AR systems to others (median 4, IQR 3.00-5.00 vs median 3, IQR 2.00-3.00; P=.002).

CONCLUSIONS: AR-based instructions to set up a mechanical ventilator were feasible for novices who had no prior experience with MV or AR. Additionally, participants in the AR group required less assistance compared with those in the manual group, resulting in higher confidence after training.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05446896; https://beta.clinicaltrials.gov/study/NCT05446896.

PMID:35867382 | DOI:10.2196/38433

J Am Chem Soc. 2022 Jul 22. doi: 10.1021/jacs.2c04990. Online ahead of print.

ABSTRACT

The ability to directly observe chemical reactions at the single-molecule and single-particle level has enabled the discovery of behaviors otherwise obscured by ensemble averaging in bulk measurements. However powerful, a common restriction of these studies to date has been the absolute requirement to surface tether or otherwise immobilize the chemical reagent/reaction of interest. This constraint arose from a fundamental limitation of conventional microscopy techniques, which could not track molecules or particles rapidly diffusing in three dimensions, as occurs in solution. However, many chemical processes occur entirely in the solution phase, leaving single-particle/-molecule analysis of this critical area of science beyond the scope of available technology. Here, we report the first kinetics studies of freely diffusing and actively growing single polymer-particles at the single-particle level freely diffusing in solution. Active-feedback single-particle tracking was used to capture three-dimensional (3D) trajectories and real-time volumetric images of freely diffusing polymer particles (D ≈ 10^-12 m²/s) and extract the growth rates of individual particles in the solution phase. The observed growth rates show that the average growth rate is a poor representation of the true underlying variability in polymer-particle growth behavior. These data revealed statistically significant populations of faster- and slower-growing particles at different depths in the sample, showing emergent heterogeneity while particles are still freely diffusing in solution. These results go against the prevailing premise that chemical processes in freely diffusing solution will exhibit uniform kinetics. We anticipate that these studies will launch new directions of solution-phase, nonensemble-averaged measurements of chemical processes.

PMID:35867381 | DOI:10.1021/jacs.2c04990

IEEE Trans Neural Netw Learn Syst. 2022 Jul 22;PP. doi: 10.1109/TNNLS.2022.3190448. Online ahead of print.

ABSTRACT

Decades of research have shown machine learning superiority in discovering highly nonlinear patterns embedded in electroencephalography (EEG) records compared with conventional statistical techniques. However, even the most advanced machine learning techniques require relatively large, labeled EEG repositories. EEG data collection and labeling are costly. Moreover, combining available datasets to achieve a large data volume is usually infeasible due to inconsistent experimental paradigms across trials. Self-supervised learning (SSL) solves these challenges because it enables learning from EEG records across trials with variable experimental paradigms, even when the trials explore different phenomena. It aggregates multiple EEG repositories to increase accuracy, reduce bias, and mitigate overfitting in machine learning training. In addition, SSL could be employed in situations where there is limited labeled training data, and manual labeling is costly. This article: 1) provides a brief introduction to SSL; 2) describes some SSL techniques employed in recent studies, including EEG; 3) proposes current and potential SSL techniques for future investigations in EEG studies; 4) discusses the cons and pros of different SSL techniques; and 5) proposes holistic implementation tips and potential future directions for EEG SSL practices.

PMID:35867362 | DOI:10.1109/TNNLS.2022.3190448

ACS Nano. 2022 Jul 22. doi: 10.1021/acsnano.2c02307. Online ahead of print.

ABSTRACT

Nanoparticles are an important class of materials that exhibit special properties arising from their high surface area-to-volume ratio. Scanning transmission electron microscopy (STEM) has played an important role in nanoparticle characterization, owing to its high spatial resolution, which allows direct visualization of composition and morphology with atomic precision. This typically comes at the cost of sample size, potentially limiting the accuracy and relevance of STEM results, as well as the ability to meaningfully track changes in properties that vary spatially. In this work, automated STEM data acquisition and analysis techniques are employed that enable physical and compositional properties of nanoparticles to be obtained at high resolution over length scales on the order of microns. This is demonstrated by studying the localized effects of potential cycling on electrocatalyst degradation across proton exchange membrane fuel cell cathodes. In contrast to conventional, manual STEM measurements, which produce particle size distributions representing hundreds of particles, these high-throughput automated methods capture tens of thousands of particles and enable nanoparticle size, number density, and composition to be measured as a function of position within the cathode. Comparing the properties of pristine and degraded fuel cells provides statistically robust evidence for the inhomogeneous nature of catalyst degradation across electrodes. These results demonstrate how high-throughput automated STEM techniques can be utilized to investigate local phenomena occurring in nanoparticle systems employed in practical devices.

PMID:35867353 | DOI:10.1021/acsnano.2c02307

Genome Biol Evol. 2022 Jul 22:evac112. doi: 10.1093/gbe/evac112. Online ahead of print.

ABSTRACT

Polypodium hydriforme is an enigmatic parasite that belongs to the phylum Cnidaria. Its taxonomic position has been debated: while it was previously suggested to be part of Medusozoa, recent phylogenomic analyses based on nuclear genes support the view that P. hydriforme and Myxozoa form a clade called Endocnidozoa. Medusozoans have linear mitochondrial (mt) chromosomes while myxozoans, as most metazoan species, have circular chromosomes. In this work, we determined the structure of the mt genome of P. hydriforme, using Illumina and Oxford Nanopore Technologies reads, and showed that it is circular. This suggests that P. hydriforme is not nested within Medusozoa, as this would entail linearization followed by re-circulation. Instead, our results support the view that P. hydriforme is a sister clade to Myxozoa, and mt linearization in the lineage leading to medusozoans occurred after the divergence of Myxozoa + P. hydriforme. Detailed analyses of the assembled P. hydriforme mt genome show that: (1) It is encoded on a single circular chromosome with an estimated size of ∼93,000 base pairs, making it one of the largest metazoan mt genomes; (2) Around 78% of the genome encompasses a non-coding region composed of several repeat types; (3) Similar to Myxozoa, no mt tRNAs were identified; (4) The codon TGA is a stop codon and does not encode for tryptophan as in other cnidarians; (5) Similar to other myxozoan mt genomes, it is extremely fast-evolving.

PMID:35867352 | DOI:10.1093/gbe/evac112

Eur J Health Econ. 2022 Jul 22. doi: 10.1007/s10198-022-01493-3. Online ahead of print.

ABSTRACT

This paper investigates the effects of obesity, socio-economic variables, and individual-specific factors on work productivity across Italian regions. A dynamic panel data with correlated random effects is used to jointly deal with incidental parameters, endogeneity issues, and functional forms of misspecification. Methodologically, a hierarchical semiparametric Bayesian approach is involved in shrinking high dimensional model classes, and then obtaining a subset of potential predictors affecting outcomes. Monte Carlo designs are addressed to construct exact posterior distributions and then perform accurate forecasts. Cross-sectional Heterogeneity is modelled nonparametrically allowing for correlation between heterogeneous parameters and initial conditions as well as individual-specific regressors. Prevention policies and strategies to handle health and labour market prospects are also discussed.

PMID:35867310 | DOI:10.1007/s10198-022-01493-3

Environ Sci Pollut Res Int. 2022 Jul 22. doi: 10.1007/s11356-022-22006-y. Online ahead of print.

ABSTRACT

As industry is the world’s leading carbon emitter, promoting industrial carbon reduction is of key significance to carbon peak and carbon neutrality. Using a data-driven method, based on the collection and processing of relevant data from statistical yearbooks and others, we analyze the efficiency and amount of carbon emission of each industrial sector after processing multi-dimensional data by the improved IPCC EF method of calculating carbon emissions. In addition, we adopt the LMDI decomposition method for data modeling to measure the contribution of energy efficiency, industrial structure, GDP per capita, and population size to carbon emission changes, to identify targets for industrial carbon reduction, and to propose a targeted optimization path for carbon emission. We show how the method is implemented by taking the statistics of Anhui Province from 2010 to 2019 as an example and advises on an optimization path for carbon emission in Anhui Province. This study is of both theoretical and practical significance as it provides theoretical and methodological support for the low-carbon development of the regional industry, and provides a reference for other countries and regions to explore the path of low-carbon and environment-friendly green transformation and upgrading.

PMID:35867299 | DOI:10.1007/s11356-022-22006-y