Category: Nevin Manimala

PLoS One. 2021 Oct 13;16(10):e0258556. doi: 10.1371/journal.pone.0258556. eCollection 2021.

ABSTRACT

BACKGROUND: Trichomonas vaginalis infection is underreported due to nonspecific clinical presentation and the nonavailability of sensitive laboratory diagnostic tests at the clinical setup. Hence, this study was designed to compare the sensitivity and specificity of microscopy and culture methods with polymerase chain reaction (PCR). The socio-demographic factors associated with the infection were explored.

METHODS: The study was carried out at the National Sexually Transmitted Diseases and Acquired Immuno Deficiency Syndrome Control Programme in Colombo and Sexually Transmitted Diseases and Acquired Immuno Deficiency Syndrome Control Programme in Kandy. Samples were collected from a total of 385 patients including, 272 females (70.7%) and 113 males (29.3%), and tested using microscopy (wet mount and Giemsa staining), culture, and PCR. Genus-specific primer set (TFR1/TFR2) that amplifies 5.8S rRNA and species-specific primer sets (TV16Sf-2/TV16Sr-2 and TVK3/7) that amplifies 18S rRNA and repetitive DNA, respectively, were used. Patient’s socio-demographic and sexual behaviour data were obtained using a standard interviewer-administered questionnaire. Data were analyzed with R statistical software Version 3.6.3.

RESULTS: The overall prevalence of trichomoniasis was 4.4% (17/385). Of these, six (1.6%) were positive for microscopic examination, 7 (1.8%) were positive for culture, and 13 (3.4%) for TVK3/7, 15 (3.9%) for TV16Sf/r, and TFR1/2 17 (4.4%) were positive for PCR. Sensitivities of PCR using TFR1/2, TV16Sf/r, and TVK3/7 primer sets were 100%, 88.20%, and 76.50%, respectively, against the expanded gold standard. Trichomoniasis was associated with age above 36 (p = 0.033), not using condoms in last three months (p = 0.016), multiple sex partners (p = 0.001), reason for attendance (p = 0.027), symptomatic nature (p = 0.015), and the presence of other sexually transmitted diseases (p = 0.001).

CONCLUSIONS: The study highlighted that age over 36 years, multiple sex partners, not using condoms, reason for attendance, symptomatic nature, and having other sexually transmitted diseases can increase the risk of acquiring trichomoniasis. Furthermore, this study confirmed PCR as highly sensitive and specific diagnostic test for the diagnosis of trichomoniasis in comparison to microscopy and culture methods.

PMID:34644344 | DOI:10.1371/journal.pone.0258556

PLoS One. 2021 Oct 13;16(10):e0258399. doi: 10.1371/journal.pone.0258399. eCollection 2021.

ABSTRACT

This study analysed the business sustainability of remanufacturing waste steel sheet from the shells of end-of-life vehicles into mesh steel sheet for manufacturing sheet-metal products. Hybrid statistical, fuzzy, and overall sustainability-index curve-fitting models were used to analyse the technical, economic, environmental, management, and social feasibility of remanufacturing, where the sales price, eco-cost savings, and CO2 emission reductions were used as typical statistical indicators. The remanufacturing process was optimised to allocate hardware for a plant recovering 480 m2/shift of waste sheet steel and producing 2851-5520 m2/shift of mesh sheet steel. Six scenarios were used to model the sustainability parameters to normalise the sustainability index values. The sustainability index of each parameter was calculated by multiplying its weight of importance by its weight of satisfaction. The highest sustainability index of 0.95 was calculated for the economic feasibility index, while the lowest sustainability index of 0.4 was calculated for the management feasibility. Remanufacturing of waste sheet steel into mesh sheet steel can be applied with an estimated overall sustainability index of 0.88.

PMID:34644340 | DOI:10.1371/journal.pone.0258399

PLoS One. 2021 Oct 13;16(10):e0258537. doi: 10.1371/journal.pone.0258537. eCollection 2021.

ABSTRACT

BACKGROUND: Real-world big data studies using health insurance claims databases require extraction algorithms to accurately identify target population and outcome. However, no algorithm for Crohn’s disease (CD) has yet been validated. In this study we aim to develop an algorithm for identifying CD using the claims data of the insurance system.

METHODS: A single-center retrospective study to develop a CD extraction algorithm from insurance claims data was conducted. Patients visiting the Kitasato University Kitasato Institute Hospital between January 2015-February 2019 were enrolled, and data were extracted according to inclusion criteria combining the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) diagnosis codes with or without prescription or surgical codes. Hundred cases that met each inclusion criterion were randomly sampled and positive predictive values (PPVs) were calculated according to the diagnosis in the medical chart. Of all cases, 20% were reviewed in duplicate, and the inter-observer agreement (Kappa) was also calculated.

RESULTS: From the 82,898 enrolled, 255 cases were extracted by diagnosis code alone, 197 by the combination of diagnosis and prescription codes, and 197 by the combination of diagnosis codes and prescription or surgical codes. The PPV for confirmed CD cases was 83% by diagnosis codes alone, but improved to 97% by combining with prescription codes. The inter-observer agreement was 0.9903.

CONCLUSIONS: Single ICD-code alone was insufficient to define CD; however, the algorithm that combined diagnosis codes with prescription codes indicated a sufficiently high PPV and will enable outcome-based research on CD using the Japanese claims database.

PMID:34644342 | DOI:10.1371/journal.pone.0258537

PLoS One. 2021 Oct 13;16(10):e0258326. doi: 10.1371/journal.pone.0258326. eCollection 2021.

ABSTRACT

Gene expression data has the characteristics of high dimensionality and a small sample size and contains a large number of redundant genes unrelated to a disease. The direct application of machine learning to classify this type of data will not only incur a great time cost but will also sometimes fail to improved classification performance. To counter this problem, this paper proposes a dimension-reduction algorithm based on weighted kernel principal component analysis (WKPCA), constructs kernel function weights according to kernel matrix eigenvalues, and combines multiple kernel functions to reduce the feature dimensions. To further improve the dimensional reduction efficiency of WKPCA, t-class kernel functions are constructed, and corresponding theoretical proofs are given. Moreover, the cumulative optimal performance rate is constructed to measure the overall performance of WKPCA combined with machine learning algorithms. Naive Bayes, K-nearest neighbour, random forest, iterative random forest and support vector machine approaches are used in classifiers to analyse 6 real gene expression dataset. Compared with the all-variable model, linear principal component dimension reduction and single kernel function dimension reduction, the results show that the classification performance of the 5 machine learning methods mentioned above can be improved effectively by WKPCA dimension reduction.

PMID:34644329 | DOI:10.1371/journal.pone.0258326

PLoS One. 2021 Oct 13;16(10):e0257421. doi: 10.1371/journal.pone.0257421. eCollection 2021.

ABSTRACT

Coronavirus Disease-2019 (COVID-19) quickly surged the whole world and affected people’s physical, mental, and social health thereby upsetting their quality of life. Therefore, we aimed to investigate the quality of life (QoL) of COVID-19 positive patients after recovery in Bangladesh. This was a study of adult (aged ≥18 years) COVID-19 individuals from eight divisions of Bangladesh diagnosed and confirmed by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) from June 2020 to November 2020. Given a response rate of 60% in a pilot study, a random list of 6400 COVID-19 patients was generated to recruit approximately 3200 patients from eight divisions of Bangladesh and finally a total of 3244 participants could be recruited for the current study. The validated Bangla version of the World Health Organization Quality of Life Brief (WHOQOL-BREF) questionnaire was used to assess the QoL. Data were analyzed by STATA (Version 16.1) and R (Version 4.0.0). All the procedures were conducted following ethical approval and in accordance with the Declaration of Helsinki. The mean scores of QoL were highest for the physical domain (68.25±14.45) followed by social (65.10±15.78), psychological (63.28±15.48), and environmental domain (62.77±13.07). Psychological and physical domain scores among females were significantly lower than the males (p<0.001). The overall quality of life was lower in persons having a chronic disease. Participants over 45 years of age were 52% less likely to enjoy good physical health than the participants aged below 26 years (AOR: 0.48, CI: 0.28-0.82). The quality of life of employed participants was found 1.8 times higher than the unemployed (AOR: 1.80, CI: 1.11-2.91). Those who were admitted to hospitals during infection had a low QoL score in physical, psychological, and socials domains. However, QoL improved in all aspect except the psychological domain for each day passed after the diagnosis. These findings call for a focus on the quality of life of the COVID-19 affected population, with special emphasis given to females, older adults, unemployed, and people with comorbidities.

PMID:34644332 | DOI:10.1371/journal.pone.0257421

PLoS One. 2021 Oct 13;16(10):e0258321. doi: 10.1371/journal.pone.0258321. eCollection 2021.

ABSTRACT

Point process generalized linear models (GLMs) provide a powerful tool for characterizing the coding properties of neural populations. Spline basis functions are often used in point process GLMs, when the relationship between the spiking and driving signals are nonlinear, but common choices for the structure of these spline bases often lead to loss of statistical power and numerical instability when the signals that influence spiking are bounded above or below. In particular, history dependent spike train models often suffer these issues at times immediately following a previous spike. This can make inferences related to refractoriness and bursting activity more challenging. Here, we propose a modified set of spline basis functions that assumes a flat derivative at the endpoints and show that this limits the uncertainty and numerical issues associated with cardinal splines. We illustrate the application of this modified basis to the problem of simultaneously estimating the place field and history dependent properties of a set of neurons from the CA1 region of rat hippocampus, and compare it with the other commonly used basis functions. We have made code available in MATLAB to implement spike train regression using these modified basis functions.

PMID:34644315 | DOI:10.1371/journal.pone.0258321

PLoS One. 2021 Oct 13;16(10):e0258243. doi: 10.1371/journal.pone.0258243. eCollection 2021.

ABSTRACT

Millions of Americans have been infected with COVID-19 and communities of color have been disproportionately burdened. We investigated the relationship between demographic characteristics and COVID-19 positivity, and comorbidities and severe COVID-19 illness (use of mechanical ventilation and length of stay) within a racial/ethnic minority population. Patients tested for COVID-19 between March 2020 and January 2021 (N = 14171) were 49.9% (n = 7072) female; 50.1% (n = 7104) non-Hispanic Black; 33.2% (n = 4698) Hispanic; and 23.6% (n = 3348) aged 65+. Overall COVID-19 positivity was 16.1% (n = 2286). Compared to females, males were 1.1 times more likely to test positive (p = 0.014). Compared to non-Hispanic Whites, non-Hispanic Black and Hispanic persons were 1.4 (p = 0.003) and 2.4 (p<0.001) times more likely, respectively, to test positive. Compared to persons ages 18-24, the odds of testing positive were statistically significantly higher for every age group except 25-34, and those aged 65+ were 2.8 times more likely to test positive (p<0.001). Adjusted for race, sex, and age, COVID-positive patients with chronic obstructive pulmonary disease were 1.9 times more likely to require a ventilator compared to those without chronic obstructive pulmonary disease (p = 0.001). Length of stay was not statistically significantly associated with any of the comorbidity variables. Our findings emphasize the importance of documenting COVID-19 disparities in marginalized populations.

PMID:34644327 | DOI:10.1371/journal.pone.0258243

PLoS Comput Biol. 2021 Oct 13;17(10):e1009513. doi: 10.1371/journal.pcbi.1009513. Online ahead of print.

ABSTRACT

It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and physics-based modelling. In this paper, we argue that bond graphs are compatible with recent developments in modularity and abstraction in systems biology, and are thus a desirable framework for constructing large-scale models. We use two examples to illustrate the utility of bond graphs in this context: a model of a mitogen-activated protein kinase (MAPK) cascade to illustrate the reusability of modules and a model of glycolysis to illustrate the ability to modify the model granularity.

PMID:34644304 | DOI:10.1371/journal.pcbi.1009513

PLoS One. 2021 Oct 13;16(10):e0258274. doi: 10.1371/journal.pone.0258274. eCollection 2021.

ABSTRACT

OBJECTIVE: We aim to estimate the total factor productivity and analyze factors related to the Chinese government’s health care expenditure in each of its provinces after its implementation of new health care reform in the period after 2009.

MATERIALS AND METHODS: We use the Malmquist DEA model to measure efficiency and apply the Tobit regression to explore factors that influence the efficiency of government health care expenditure. Data are taken from the China statistics yearbook (2004-2020).

RESULTS: We find that the average TFP of China’s 31 provincial health care expenditure was lower than 1 in the period 2009-2019. We note that the average TFP was much higher after new health care reform was implemented, and note this in the eastern, central and western regions. But per capita GDP, population density and new health care reform implementation are found to have a statistically significant impact on the technical efficiency of the provincial government’s health care expenditure (P<0.05); meanwhile, region, education, urbanization and per capita provincial government health care expenditure are not found to have a statistically significant impact.

CONCLUSION: Although the implementation of the new medical reform has improved the efficiency of the government’s health expenditure, it is remains low in 31 provinces in China. In addition, the government should consider per capita GDP, population density and other factors when coordinating the allocation of health care input.

SIGNIFICANCE: This study systematically analyzes the efficiency and influencing factors of the Chinese government’s health expenditure after it introduced new health care reforms. The results show that China’s new medical reform will help to improve the government’s health expenditure. The Chinese government can continue to adhere to the new medical reform policy, and should pay attention to demographic and economic factors when implementing the policy.

PMID:34644313 | DOI:10.1371/journal.pone.0258274

PLoS One. 2021 Oct 13;16(10):e0256542. doi: 10.1371/journal.pone.0256542. eCollection 2021.

ABSTRACT

This paper utilizes spatial econometric reenactments to examine the geographic effects of different types of environmentally friendly power on corban discharges. The example covers 31 nations in the Asia-Pacific district during the time frame 2000 to 2018. The spatial connection in the model was affirmed by symptomatic testing, and the spatial Durbin model was picked as the last model. Results show that Gross domestic product per capita, receptiveness to business sectors, unfamiliar direct venture, energy force, and urbanization critically affect CO2 emanations. In correlation, just wind and sunlight-based energy have added to a generous abatement in ozone harming substance emanations in nations over the long run. In contrast, hydropower, bioenergy, and geothermal energy discoveries have been irrelevant. A cross-sectional examination worldview delineated that nations with more elevated sunlight-based energy yield have higher CO2 outflows, while nations with lower levels have lower CO2 emanations. The presence of spatial impacts in the model gave off an impression of the negative consequences for homegrown CO2 outflows of Gross domestic product per capita and exchange transparency of adjoining nations. Furthermore, energy power and higher creation of sustainable power in adjoining nations will prompt lower homegrown CO2 outflows.

PMID:34644297 | DOI:10.1371/journal.pone.0256542