Category: Nevin Manimala

Pol J Microbiol. 2024 Mar 4;73(1):49-57. doi: 10.33073/pjm-2024-006. eCollection 2024 Mar 1.

ABSTRACT

Gut microbiota (GM) is a crucial underlying player during sepsis pathogenesis. However, the causal relationship is unclear and remains to be determined. A two-sample Mendelian randomization study was implemented. The statistical data about sepsis together with GM summarized from genome-wide association studies were evaluated. Instrumental variables were defined as single-nucleotide polymorphisms with prominent correlations with exposure. The inverse-variance-weighted test was employed as a major approach of Mendelian randomization analysis to estimate of causal relationships. The inverse-variance-weighted analysis results demonstrated that at different taxa levels, Actinobacteria and Bifidobacteriaceae influence sepsis. Actinobacteria had negative relationships to sepsis risk at the phylum (β = -0.34, SE = 0.10, p = 0.0008) and class (β = -0.23, SE = 0.07, p = 0.0011) levels in outcome coded ieu-b-69. Actinobacteria at the phylum level (β = -0.22, SE = 0.10, p = 0.027) was also negatively associated with sepsis in outcome coded ieu-b-4980. Bifidobacteriaceae at the order (β = -0.20, SE = 0.06, p = 0.0021), family (β = -0.20, SE = 0.06, p = 0.0021), and genus (β = -0.20, SE = 0.06, p = 0.0007) levels were all negatively correlated with the risk of sepsis in outcome coded ieu-b-69. The results of the Wald ratio model showed that Tyzzerella genus (OR (95%CI) = 0.6902[0.4907,0.9708], p = 0.0331) and Gastranaerophilales order (OR (95%CI) = 0.5907[0.3516,0.9926], p = 0.0468) were negatively connected with sepsis. This study implied at different taxa levels Actinobacteria and Bifidobacteriaceae, Tyzzerella genus, and Gastranaerophilales order have a causal relationship with sepsis, indicating that they are protective factors for the incidence of sepsis.

PMID:38437468 | DOI:10.33073/pjm-2024-006

J Opt Soc Am A Opt Image Sci Vis. 2024 Mar 1;41(3):476-488. doi: 10.1364/JOSAA.506999.

ABSTRACT

Color constancy is a basic step for achieving stable color perception in both biological visual systems and the image signal processing (ISP) pipeline of cameras. So far, there have been numerous computational models of color constancy that focus on scenes under normal light conditions but are less concerned with nighttime scenes. Compared with daytime scenes, nighttime scenes usually suffer from relatively higher-level noise and insufficient lighting, which usually degrade the performance of color constancy methods designed for scenes under normal light. In addition, there is a lack of nighttime color constancy datasets, limiting the development of relevant methods. In this paper, based on the gray-pixel-based color constancy methods, we propose a robust gray pixel (RGP) detection method by carefully designing the computation of illuminant-invariant measures (IIMs) from a given color-biased nighttime image. In addition, to evaluate the proposed method, a new dataset that contains 513 nighttime images and corresponding ground-truth illuminants was collected. We believe this dataset is a useful supplement to the field of color constancy. Finally, experimental results show that the proposed method achieves superior performance to statistics-based methods. In addition, the proposed method was also compared with recent deep-learning methods for nighttime color constancy, and the results show the method’s advantages in cross-validation among different datasets.

PMID:38437439 | DOI:10.1364/JOSAA.506999

J Opt Soc Am A Opt Image Sci Vis. 2024 Mar 1;41(3):A63-A72. doi: 10.1364/JOSAA.507308.

ABSTRACT

In this paper, a multiuser medical image encryption algorithm is proposed. The proposed algorithm utilizes polar decomposition, which enables multiuser features in the proposed algorithm. A computer-generated hologram (CGH) improves the security of the proposed algorithm in the gyrator domain. The phase-only CGH-based multiuser algorithm offers advantages such as storing a large amount of information in a compact space, resistance to counterfeiting, and enhanced security. The proposed method is validated with various statistical metrics, such as information entropy, mean squared error, correlation coefficient, histogram, and mesh plots. Results confirm that the proposed algorithm is secure and robust against potential attacks, such as plaintext attacks, iterative attacks, and contamination attacks. The proposed method has a large keyspace, which makes it very difficult to be breached in real-time with existing computational power.

PMID:38437431 | DOI:10.1364/JOSAA.507308

J Opt Soc Am A Opt Image Sci Vis. 2024 Feb 1;41(2):261-271. doi: 10.1364/JOSAA.513833.

ABSTRACT

As a continuation of a previous investigation on the temporal integration of partially polarized thermal light and/or the spatial integration of polarization speckle, we calculate more accurate probability density functions for integrated Stokes parameters. With the aid of the unitary linear transformation and the Karhunen-Loève expansion of the stochastic electric field, the light of interest has been decomposed into an infinite number of statistically independent modes and the integrated Stokes parameters have been expressed as the sums of infinite numbers of random variables known as the polarization-related mode shape. A mathematical formalism of the exact solutions for the distributions of the integrated Stokes parameters has been derived. Through some approximations to the exact solutions, we also make a comparison of the “exact” and approximate solutions to understand the entire statistics of the integrated stochastic phenomena in optics.

PMID:38437338 | DOI:10.1364/JOSAA.513833

J Opt Soc Am A Opt Image Sci Vis. 2024 Feb 1;41(2):157-164. doi: 10.1364/JOSAA.501371.

ABSTRACT

Feature point matching is one of the fundamental tasks in binocular vision. It directly affects the accuracy and quality of 3D reconstruction. This study proposes a directional region-based feature point matching algorithm based on the SURF algorithm to improve the accuracy of feature point matching. First, same-name points are selected as the matching reference points in the left and right images. Then, the SURF algorithm is used to extract feature points and construct the SURF feature point descriptors. During the matching process, the location relationship between the query feature point and the reference point in the left image is directed to determine the corresponding matching region in the right image. Then, the matching is completed within this region based on Euclidean distance. Finally, the grid-based motion statistics algorithm is used to eliminate mismatches. Experimental results show that the proposed algorithm can substantially improve the matching accuracy and the number of valid matched points, particularly in the presence of a large amount of noise and interference. It also exhibits good robustness and stability.

PMID:38437328 | DOI:10.1364/JOSAA.501371

PLoS One. 2024 Mar 4;19(3):e0298977. doi: 10.1371/journal.pone.0298977. eCollection 2024.

ABSTRACT

OBJECTIVE: To analyse the relationship between health app quality with user ratings and the number of downloads of corresponding health apps.

MATERIALS AND METHODS: Utilising a dataset of 881 Android-based health apps, assessed via the 300-point objective Organisation for the Review of Care and Health Applications (ORCHA) assessment tool, we explored whether subjective user-level indicators of quality (user ratings and downloads) correlate with objective quality scores in the domains of user experience, data privacy and professional/clinical assurance. For this purpose, we applied spearman correlation and multiple linear regression models.

RESULTS: For user experience, professional/clinical assurance and data privacy scores, all models had very low adjusted R squared values (< .02). Suggesting that there is no meaningful link between subjective user ratings or the number of health app downloads and objective quality measures. Spearman correlations suggested that prior downloads only had a very weak positive correlation with user experience scores (Spearman = .084, p = .012) and data privacy scores (Spearman = .088, p = .009). There was a very weak negative correlation between downloads and professional/clinical assurance score (Spearman = -.081, p = .016). Additionally, user ratings demonstrated a very weak correlation with no statistically significant correlations observed between user ratings and the scores (all p > 0.05). For ORCHA scores multiple linear regression had adjusted R-squared = -.002.

CONCLUSION: This study highlights that widely available proxies which users may perceive to signify the quality of health apps, namely user ratings and downloads, are inaccurate predictors for estimating quality. This indicates the need for wider use of quality assurance methodologies which can accurately determine the quality, safety, and compliance of health apps. Findings suggest more should be done to enable users to recognise high-quality health apps, including digital health literacy training and the provision of nationally endorsed “libraries”.

PMID:38437233 | DOI:10.1371/journal.pone.0298977

PLoS One. 2024 Mar 4;19(3):e0298144. doi: 10.1371/journal.pone.0298144. eCollection 2024.

ABSTRACT

Evaluation of high value patents is essential for the enterprise’s technical layout and innovative product design. The existing research on the patent value needs the support of a large number of professional statistical information and is difficult to directly reflect the technical value. Since technological innovation is the fundamental means to enhance the sustainable competitiveness of enterprises. Therefore, a high-tech value patent evaluation and cultivation method for engineering designers need to be proposed. Firstly, the patent samples based on design methodology are retrieved and the indicators for evaluating technical value are summarized and the rationality of the evaluation indicators is verifier through empirical study based on improved evidence theory. Secondly, based on principal component analysis and factor analysis, a high-tech value patent evaluation and cultivation method is proposed. Finally, the proposed method is applied to identify the high-tech value patents in the cutting machine industry, and structural improvement is made based on this patent to demonstrate the cultivation process of high-tech value patents. The proposed method provides a clear guiding direction for the cultivation of high novelty patents and enterprise innovative product design. The method can effectively assist the product R&D activities of engineering designers and enhance the sustainable competitiveness of enterprises from a technological perspective.

PMID:38437218 | DOI:10.1371/journal.pone.0298144

PLOS Glob Public Health. 2024 Mar 4;4(3):e0001751. doi: 10.1371/journal.pgph.0001751. eCollection 2024.

ABSTRACT

The Network for Improving Quality of Care for Maternal, Newborn and Child Health (QCN) aims to work through learning, action, leadership and accountability. We aimed to evaluate the effectiveness of QCN in these four areas at the global level and in four QCN countries: Bangladesh, Ethiopia, Malawi and Uganda. This mixed method evaluation comprised 2-4 iterative rounds of data collection between 2019-2022, involving stakeholder interviews, hospital observations, QCN members survey, and document review. Qualitative data was analysed using a coding framework developed from underlying theories on network effectiveness, behaviour change, and QCN proposed theory of change. Survey data capturing respondents’ perception of QCN was analysed with descriptive statistics. The QCN global level, led by the WHO secretariat, was effective in bringing together network countries’ governments and global actors via providing online and in-person platforms for communication and learning. In-country, various interventions were delivered in ‘learning districts’, however often separately by different partners in different locations, and pandemic-disrupted. Governance structures for quality of care were set-up, some preceding QCN, and were found to be stronger and better (though often externally) resourced at national than local levels. Awareness of operational plans and network activities differed between countries, was lower at local than national levels, but increased from 2019 to 2022. Engagement with, and value of, QCN was perceived to be higher in Uganda and Bangladesh than in Malawi or Ethiopia. Capacity building efforts were implemented in all countries-yet often dependent on implementing partners and donors. QCN stakeholders agreed 15 core monitoring indicators though data collection was challenging, especially for indicators requiring new or parallel systems. Accountability initiatives remained nascent in 2022. Global and national leadership elements of QCN have been most effective to date, with action, learning and accountability more challenging, partner or donor dependent, remaining to be scaled-up, and pandemic-disrupted.

PMID:38437217 | DOI:10.1371/journal.pgph.0001751

PLoS One. 2024 Mar 4;19(3):e0299192. doi: 10.1371/journal.pone.0299192. eCollection 2024.

ABSTRACT

BACKGROUND: Previous studies have indicated a heightened susceptibility to cataract and glaucoma among rheumatoid arthritis (RA) patients, while it remains uncertain whether RA is causally associated with cataract and glaucoma. A two-sample mendelian randomization (MR) analysis was used to investigate the causal associations between RA, cataract and glaucoma in European and East Asian populations.

METHODS: In the European population, genome-wide association study (GWAS) summary statistics for cataract (372,386 individuals) and glaucoma (377,277 individuals) were obtained from the FinnGen consortium (R9), while RA summary data were derived from a meta-analysis of GWAS encompassing 97173 samples. In the East Asian population, summary data for cataract (212453 individuals), glaucoma (212453 individuals), and RA (22515 individuals) were sourced from the IEU Open GWAS project. Inverse-variance weighted (IVW, random-effects) method served as the primary analysis, complemented by MR‒Egger regression, weighted median, weighted mode and simple mode methods. Additionally, various sensitivity tests, including Cochran’s Q test, MR‒Egger intercept, MR pleiotropy Residual Sum and Outlier test and leave-one-out test were performed to detect the heterogeneity, horizontal pleiotropy and stability of the analysis results.

RESULTS: Following stringent screening, the number of selected instrumental variables ranged from 8 to 56. The IVW results revealed that RA had an increased risk of cataract (OR = 1.041, 95% CI = 1.019-1.064; P = 2.08×10-4) and glaucoma (OR = 1.029, 95% CI = 1.003-1.057; P = 2.94×10-2) in European populations, and RA displayed a positive association with cataract (OR = 1.021, 95% CI = 1.004-1.039; P = 1.64×10-2) in East Asian populations. Other methods also supported those results by IVW, and sensitivity tests showed that our analysis results were credible and stable.

CONCLUSIONS: This study revealed a positive causality between RA and the increased risk of cataract and glaucoma, which provides guidance for the early prevention of cataracts and glaucoma in patients with RA and furnishes evidence for the impact of RA-induced inflammation on ophthalmic diseases.

PMID:38437213 | DOI:10.1371/journal.pone.0299192

PLoS One. 2024 Mar 4;19(3):e0294116. doi: 10.1371/journal.pone.0294116. eCollection 2024.

ABSTRACT

The 5-item Medication Adherence Report Scale (MARS-5) is a reliable and valid questionnaire for evaluating adherence in patients with asthma, hypertension, and diabetes. Validity has not been determined in multiple sclerosis (MS). We aimed to establish criterion validity and reliability of the MARS-5 in persons with MS (PwMS). Our prospective study included PwMS on dimethyl fumarate (DMF). PwMS self-completed the MARS-5 on the same day before baseline and follow-up brain magnetic resonance imaging (MRI) 3 and 9 months after treatment initiation and were graded as highly and medium adherent upon the 24-cut-off score, established by receiver operator curve analysis. Health outcomes were represented by relapse occurrence from the 1st DMF dispense till follow-up brain MRI and radiological progression (new T2 MRI lesions and quantitative analysis) between baseline and follow-up MRI. Criterion validity was established by association with the Proportion of Days Covered (PDC), new T2 MRI lesions, and Beliefs in Medicines questionnaire (BMQ). The reliability evaluation included internal consistency and the test-retest method. We included 40 PwMS (age 37.6 ± 9.9 years, 75% women), 34 were treatment-naive. No relapses were seen during the follow-up period but quantitative MRI analysis showed new T2 lesions in 6 PwMS. The mean (SD) MARS-5 score was 23.1 (2.5), with 24 PwMS graded as highly adherent. The higher MARS-5 score was associated with higher PDC (b = 0.027, P<0.001, 95% CI: (0.0134-0.0403)) and lower medication concerns (b = -1.25, P<0.001, 95% CI: (-1.93-(-0,579)). Lower adherence was associated with increased number (P = 0.00148) and total volume of new T2 MRI lesions (P = 0.00149). The questionnaire showed acceptable internal consistency (Cronbach α = 0.72) and moderate test-retest reliability (r = 0.62, P < 0.0001, 95% CI: 0.33-0.79). The MARS-5 was found to be valid and reliable for estimating medication adherence and predicting medication concerns in persons with MS.

PMID:38437197 | DOI:10.1371/journal.pone.0294116