Tag: pubmed

PLoS One. 2021 Jun 18;16(6):e0252977. doi: 10.1371/journal.pone.0252977. eCollection 2021.

ABSTRACT

INTRODUCTION: Evidence from sub-Saharan Africa, including Kenya, shows that negative beliefs about contraceptive methods are associated with non-use. However, little is known about the relationship between contraceptive beliefs and subsequent method choice.

METHODOLOGY: We used data from a two-year longitudinal survey of married women aged 15-39 years at enrollment from one urban site (Nairobi) and one rural site (Homa Bay) in Kenya. Analysis entails descriptive statistics and estimation of a conditional logit analysis to examine associations between method-specific beliefs and choice of injectables, implants or pills among women who were not using any method or were pregnant at baseline (round 1) but adopted these methods at 12-month follow-up (Nairobi, n = 221; Homa Bay n = 197).

RESULTS: Beliefs about pills, injectables and implants among non-users were generally negative. With the partial exception of the pill in Nairobi, the majority thought that each method was likely to cause serious health problems, unpleasant side effects, menstrual disruption, and would be unsafe for long-term use. In both sites, satisfied past use of a method and the perception that a method is easy to use had a major influence on method choice. Concerns about menstrual disruption and safety for long-term use were unimportant in both sites. There were some marked differences between the two sites. Beliefs about long-term fertility impairment and perceived husband approval had strong influences on choice of injectables, implants or pills in the urban site but not in the rural site.

CONCLUSION: The relative importance of beliefs, some erroneous, in predisposing women to choose one method over another appears to be conditioned by the social context. There is need for family planning counseling programmes to pay attention to erroneous beliefs and misconceptions about contraceptives.

PMID:34143804 | DOI:10.1371/journal.pone.0252977

PLoS One. 2021 Jun 18;16(6):e0250991. doi: 10.1371/journal.pone.0250991. eCollection 2021.

ABSTRACT

Long-term predictions of forest dynamics, including forecasts of tree growth and mortality, are central to sustainable forest-management planning. Although often difficult to evaluate, tree mortality rates under different abiotic and biotic conditions are vital in defining the long-term dynamics of forest ecosystems. In this study, we have modeled tree mortality rates using conditional inference trees (CTREE) and multi-year permanent sample plot data sourced from an inventory with coverage of New Brunswick (NB), Canada. The final CTREE mortality model was based on four tree- and three stand-level terms together with two climatic terms. The correlation coefficient (R2) between observed and predicted mortality rates was 0.67. High cumulative annual growing degree-days (GDD) was found to lead to increased mortality in 18 tree species, including Betula papyrifera, Picea mariana, Acer saccharum, and Larix laricina. In another ten species, including Abies balsamea, Tsuga canadensis, Fraxinus americana, and Fagus grandifolia, mortality rates tended to be higher in areas with high incident solar radiation. High amounts of precipitation in NB’s humid maritime climate were also found to contribute to heightened tree mortality. The relationship between high GDD, solar radiation, and high mortality rates was particularly strong when precipitation was also low. This would suggest that although excessive soil water can contribute to heightened tree mortality by reducing the supply of air to the roots, occasional drought in NB can also contribute to increased mortality events. These results would have significant implications when considered alongside regional climate projections which generally entail both components of warming and increased precipitation.

PMID:34143806 | DOI:10.1371/journal.pone.0250991

PLoS One. 2021 Jun 18;16(6):e0252505. doi: 10.1371/journal.pone.0252505. eCollection 2021.

ABSTRACT

Statistical image analysis of an ensemble of digital images of histological samples is performed as an auxiliary investigation a result of the recently proposed method of articular cartilage repair utilizing growth plate chondrocytes in a skeleton animal model. A fixed-shift model of maximal likelihood estimates of image histograms applied for monochromatic (grayscale) images or their RGB components confirms the statistically significant effect of the previously proposed medical treatment. The type of staining used to prepare images of histological samples is related to the visibility of the effectiveness of medical treatment. Hellinger distance of escort distributions for maximal likelihood estimates of image histograms of medically treated and control samples is investigated to identify grayscale (or RGB) intensities responsible for statistically significant difference of the estimates. A difference of Shannon entropy quantifying informational content of the histograms allows one to identify staining and image colors which are most suitable to visualize cluster formation typical for articular cartilage repair processes.

PMID:34143793 | DOI:10.1371/journal.pone.0252505

PLoS One. 2021 Jun 18;16(6):e0251815. doi: 10.1371/journal.pone.0251815. eCollection 2021.

ABSTRACT

BACKGROUND: Blood/body fluid splash are hazards to health care professionals in their working area. Around twenty bloodborne pathogens are known to be transmitted through these occupational injuries. This problem alters the health status of health care professionals in different ways, including physically, mentally, and psychologically. Even though health professionals especially midwives who are working in delivery rooms are highly affected, little is known about the exposure. So, this study was aimed to assess the prevalence of exposure to blood/body fluid splash and its predictors among midwives working in public health institutions of Addis Ababa city.

METHODS: Institution based cross-sectional study was conducted among 438 study participants in public health institutions in Addis Ababa. Data was collected from March 1-20, 2020 by a self-administered questionnaire. The data were entered into Epi data version 3.1 and then exported to SPSS version 24 for analysis. All variables with P<0.25 in the bivariate analysis were included in a final model and statistical significance was declared at P< 0.05.

RESULTS: In this study, a total of 424 respondents respond yielding a response rate of 97%. The prevalence of blood and body fluid splashes (BBFs) was 198 (46.7%). Not training on infection prevention, working in two shifts (> 12 hours), not regularly apply universal precautions, job-related stress, an average monthly salary of 5001-8000 were independent predictors of blood and body fluid splashes.

CONCLUSION: The study revealed that nearly half of midwives were exposed to BBFS. This highlights the need for key stakeholders such as policymakers and service providers to design appropriate policies to avert this magnitude and making the environment enabling to comply with standard precautions. We recommend that this study may be done by including rural setting institutions and by including other health professionals that are susceptible to BBFS at work. Formal training on infection prevention and safety practice to apply universal precautions will be needed from the concerned bodies to prevent exposures to blood/body fluid splash.

PMID:34143794 | DOI:10.1371/journal.pone.0251815

PLoS One. 2021 Jun 18;16(6):e0250025. doi: 10.1371/journal.pone.0250025. eCollection 2021.

ABSTRACT

OBJECTIVE: Takayasu arteritis (TAK) is a rare immune-mediated vasculitis of the aorta and its branches. Aims were to calculate prevalence and incidence in Switzerland, to assess disease activity and performance of MR-Angiography (MRA).

METHODS: 31 patients were recorded in a database, 27 were followed prospectively up to 3 years. Prevalence was calculated based on data of the national statistical bureau. Disease activity was defined using the revised EULAR criteria. MRA depicted stenotic changes and aortic wall enhancement.

RESULTS: A disease prevalence of 14.5/1.000.000 inhabitants and an incidence of 0.3/1.000.000 per year was calculated. Aortic wall enhancement was found in 10 patients while in clinical and serological remission. EULAR criteria missed 5 patients with disease activity with isolated elevations of ESR/CRP. Arterial stenosis did not change over time in 5 cases, it improved in 2 and increased in 7. At follow-up 16 patients were treated with tocilizumab, 11/16 in monotherapy, 5 patients were treatment-free, 25/27 stayed in remission.

CONCLUSION: In addition to prevalence and incidence, our data show that MRA qualifies to detect subclinical disease activity, but, on the other hand, that EULAR criteria may miss disease activity in case of isolated elevation of ESR/CRP.

PMID:34143786 | DOI:10.1371/journal.pone.0250025

PLoS One. 2021 Jun 18;16(6):e0248350. doi: 10.1371/journal.pone.0248350. eCollection 2021.

ABSTRACT

PURPOSE: To investigate the repeatability in corneal thickness (CT) and epithelial thickness (ET) measurements using spectral domain anterior segment optical coherence tomography (AS-OCT, REVO NX, Optopol) in keratoconus, and examine the effect of corneal crosslinking (CXL) on repeatability.

METHODS: A cross-sectional study of 259 eyes of 212 patients with keratoconus attending the corneal disease clinic at a university hospital tertiary referral center were enrolled. Two groups were analysed: eyes with no prior history of CXL (Group A) and eyes with prior CXL (Group B). Repeatability of measurements was assessed using the intraclass correlation coefficient (ICC) and coefficient of variation (CV).

RESULTS: In Group A, central corneal thickness (CCT) was 472.18 ± 45.41μm, and the ET was found to be the thinnest in the inferior-temporal aspect at 51.79 ± 5.97μm and thickest at the superior-nasal aspect at 56.07 ± 5.70μm. In Group B, CCT was 465.11± 42.28μm, and the ET was the thinnest at the inferior-temporal aspect at 50.63 ± 5.52μm and thickest at the superior aspect at 56.80 ± 6.39μm. When evaluating CT measurements, ICC was above 0.86 and 0.83 for Group A and Group B respectively. When evaluating ET measurements, ICC was above 0.82 for both groups. CXL had no statistically significant impact on the repeatability of measurements.

CONCLUSIONS: AS-OCT provides repeatable CT and ET measurements in the central and peripheral cornea in patients with keratoconus. Repeatability is not affected by a history of CXL.

PMID:34143790 | DOI:10.1371/journal.pone.0248350

PLoS Negl Trop Dis. 2021 Jun 18;15(6):e0009410. doi: 10.1371/journal.pntd.0009410. eCollection 2021 Jun.

ABSTRACT

BACKGROUND: Leptospirosis has been described as a biphasic disease consisting of hematogenous dissemination to major organs in the acute phase and asymptomatic renal colonization in the chronic phase. Several observational studies have suggested an association between leptospirosis and chronic kidney disease (CKD). We investigated the dynamics of leptospires and histopathological changes in the kidney to understand the relationship between them, and also investigated the extent of renal dysfunction in the acute and chronic phases of leptospirosis using a hamster model.

FINDINGS: Hamsters (n = 68) were subcutaneously infected with 1 × 104 cells of the Leptospira interrogans serovar Manilae strain UP-MMC-SM. A total of 53 infected hamsters developed fatal acute leptospirosis, and the remaining 15 hamsters recovered from the acute phase, 13 of which showed Leptospira colonization in the kidneys in the chronic phase. Five asymptomatic hamsters also had renal colonization in the chronic phase. Immunofluorescence staining showed that leptospires were locally distributed in the renal interstitium in the early acute phase and then spread continuously into the surrounding interstitium. The kidneys of the surviving hamsters in the chronic phase showed patchy lesions of atrophic tubules, a finding of chronic tubulointerstitial nephritis, which were substantially consistent with the distribution of leptospires in the renal interstitium. The degree of atrophic tubules in kidney sections correlated statistically with the serum creatinine level in the chronic phase (rs = 0.78, p = 0.01).

CONCLUSION: Subcutaneous infection with pathogenic leptospires could cause acute death or chronic leptospirosis in hamsters after surviving the acute phase. We suggest that the renal distribution of leptospires during the acute phase probably affected the extent of tubular atrophy, leading to CKD.

PMID:34143778 | DOI:10.1371/journal.pntd.0009410

IEEE Trans Neural Netw Learn Syst. 2021 Jun 18;PP. doi: 10.1109/TNNLS.2021.3086570. Online ahead of print.

ABSTRACT

The novel 2019 Coronavirus (COVID-19) infection has spread worldwide and is currently a major healthcare challenge around the world. Chest computed tomography (CT) and X-ray images have been well recognized to be two effective techniques for clinical COVID-19 disease diagnoses. Due to faster imaging time and considerably lower cost than CT, detecting COVID-19 in chest X-ray (CXR) images is preferred for efficient diagnosis, assessment, and treatment. However, considering the similarity between COVID-19 and pneumonia, CXR samples with deep features distributed near category boundaries are easily misclassified by the hyperplanes learned from limited training data. Moreover, most existing approaches for COVID-19 detection focus on the accuracy of prediction and overlook uncertainty estimation, which is particularly important when dealing with noisy datasets. To alleviate these concerns, we propose a novel deep network named RCoNetks for robust COVID-19 detection which employs Deformable Mutual Information Maximization (DeIM), Mixed High-order Moment Feature (MHMF), and Multiexpert Uncertainty-aware Learning (MUL). With DeIM, the mutual information (MI) between input data and the corresponding latent representations can be well estimated and maximized to capture compact and disentangled representational characteristics. Meanwhile, MHMF can fully explore the benefits of using high-order statistics and extract discriminative features of complex distributions in medical imaging. Finally, MUL creates multiple parallel dropout networks for each CXR image to evaluate uncertainty and thus prevent performance degradation caused by the noise in the data. The experimental results show that RCoNetks achieves the state-of-the-art performance on an open-source COVIDx dataset of 15,134 original CXR images across several metrics. Crucially, our method is shown to be more effective than existing methods with the presence of noise in the data.

PMID:34143745 | DOI:10.1109/TNNLS.2021.3086570

PLoS Comput Biol. 2021 Jun 18;17(6):e1009089. doi: 10.1371/journal.pcbi.1009089. Online ahead of print.

ABSTRACT

The advent of high-throughput metagenomic sequencing has prompted the development of efficient taxonomic profiling methods allowing to measure the presence, abundance and phylogeny of organisms in a wide range of environmental samples. Multivariate sequence-derived abundance data further has the potential to enable inference of ecological associations between microbial populations, but several technical issues need to be accounted for, like the compositional nature of the data, its extreme sparsity and overdispersion, as well as the frequent need to operate in under-determined regimes. The ecological network reconstruction problem is frequently cast into the paradigm of Gaussian Graphical Models (GGMs) for which efficient structure inference algorithms are available, like the graphical lasso and neighborhood selection. Unfortunately, GGMs or variants thereof can not properly account for the extremely sparse patterns occurring in real-world metagenomic taxonomic profiles. In particular, structural zeros (as opposed to sampling zeros) corresponding to true absences of biological signals fail to be properly handled by most statistical methods. We present here a zero-inflated log-normal graphical model (available at https://github.com/vincentprost/Zi-LN) specifically aimed at handling such “biological” zeros, and demonstrate significant performance gains over state-of-the-art statistical methods for the inference of microbial association networks, with most notable gains obtained when analyzing taxonomic profiles displaying sparsity levels on par with real-world metagenomic datasets.

PMID:34143768 | DOI:10.1371/journal.pcbi.1009089

PLoS One. 2021 Jun 18;16(6):e0246913. doi: 10.1371/journal.pone.0246913. eCollection 2021.

ABSTRACT

Video games have become a ubiquitous part of demographically diverse cultures. Numerous studies have focused on analyzing the cognitive aspects involved in game playing that could help in providing an optimal gaming experience by improving video game design. To this end, we present a framework for classifying the game player’s expertise level using wearable electroencephalography (EEG) headset. We hypothesize that expert and novice players’ brain activity is different, which can be classified using frequency domain features extracted from EEG signals of the game player. A systematic channel reduction approach is presented using a correlation-based attribute evaluation method. This approach lead us in identifying two significant EEG channels, i.e., AF3 and P7, among fourteen channels available in Emotiv EPOC headset. In particular, features extracted from these two EEG channels contributed the most to the video game player’s expertise level classification. This finding is validated by performing statistical analysis (t-test) over the extracted features. Moreover, among multiple classifiers used, K-nearest neighbor is the best classifier in classifying game player’s expertise level with a classification accuracy of up to 98.04% (without data balancing) and 98.33% (with data balancing).

PMID:34143774 | DOI:10.1371/journal.pone.0246913