Tag: nevin manimala

PLoS One. 2022 Jun 22;17(6):e0270102. doi: 10.1371/journal.pone.0270102. eCollection 2022.

ABSTRACT

BACKGROUND: Polycystic ovary syndrome (PCOS) is a common female reproductive endocrine problem worldwide. The prevalence of mental disorder is increasing among PCOS patients due to various physical, psychological, and social issues. Here we aimed to evaluate the mental health and associated factors among women suffering from PCOS in Bangladesh.

METHODS: We performed an online cross-sectional survey among 409 participants with PCOS using Google Forms. We used structured questionnaires to collect socio-demographic information and lifestyle-related factors. Also, we applied patient health questionnaire (PHQ-9), generalized anxiety disorder (GAD-7) scale, and UCLA loneliness (UCLA-3) scale for psychometric assessment of the participants. Finally, we applied several statistical tools and performed data interpretations to evaluate the prevalence of mental health disorders and associated factors among patients with PCOS in Bangladesh.

RESULTS: Prevalence of loneliness, generalized anxiety disorder and depressive illness among the women with PCOS were 71%, 88%, and 60%, respectively. Among the mental illness, mild, moderate, and severe cases were 39%, 18%, and 14% for loneliness; 39%, 23% and 26% for generalized anxiety disorder; and 35%, 18%, and 7% for depressive disorder. According to the present findings, obesity, financial condition, physical exercise, mealtime, food habit, daily water consumption, birth control method, and long-term oral contraceptive pills contribute to developing mental health disorders among females with PCOS in Bangladesh.

CONCLUSION: According to present study results, high proportion of women suffering from PCOS experience several mental disorders in Bangladesh. Although several socio-demographic and lifestyle-related factors were found to be associated with the poor mental health of women with PCOS; however, PCOS itself is a condition that favors poor physical and psychological health. Therefore, we recommend proper treatment, public awareness, and a healthy lifestyle to promote the good mental health of women suffering from PCOS.

PMID:35731829 | DOI:10.1371/journal.pone.0270102

PLoS Comput Biol. 2022 Jun 22;18(6):e1010182. doi: 10.1371/journal.pcbi.1010182. Online ahead of print.

ABSTRACT

Internal models capture the regularities of the environment and are central to understanding how humans adapt to environmental statistics. In general, the correct internal model is unknown to observers, instead they rely on an approximate model that is continually adapted throughout learning. However, experimenters assume an ideal observer model, which captures stimulus structure but ignores the diverging hypotheses that humans form during learning. We combine non-parametric Bayesian methods and probabilistic programming to infer rich and dynamic individualised internal models from response times. We demonstrate that the approach is capable of characterizing the discrepancy between the internal model maintained by individuals and the ideal observer model and to track the evolution of the contribution of the ideal observer model to the internal model throughout training. In particular, in an implicit visuomotor sequence learning task the identified discrepancy revealed an inductive bias that was consistent across individuals but varied in strength and persistence.

PMID:35731822 | DOI:10.1371/journal.pcbi.1010182

PLoS One. 2022 Jun 22;17(6):e0269790. doi: 10.1371/journal.pone.0269790. eCollection 2022.

ABSTRACT

Tourism and outdoor leisure is an important economic sector for many countries, and has a substantial reliance on natural capital. Natural capital may be the primary purpose for tourism, or it may be a secondary factor, where the choice of location for a leisure activity is influenced by natural capital. Typically, when valuing tourism and outdoor leisure, all expenditure associated with the activity is assigned to the ecosystem it occurs in. However, this value illustrates the dependency on natural capital, rather than the contribution of natural capital. In natural capital accounting, a major challenge is to separately identify the contribution of natural capital from that of other forms of capital. In this study we develop a transparent and repeatable method that is able to attribute the contribution of natural capital (here defined as ecosystems) to the output of multiple tourism and outdoor leisure activities. Using national statistics from Great Britain, we calculate the natural capital contribution to tourism spend by activity at a national and regional scale, and for a case study map and value the contributing ecosystems. We estimated that, out of a total £36 billion spent on tourism and leisure activities in 2017, £22.5 billion was attributable to natural capital. This equates to 0.9% of the UK GDP. The Gross Value Added component of this attributable was £10.5 billion, equivalent to 0.4% of the UK GDP. Regions with the highest natural capital contribution in Great Britain were Scotland and Wales, with the lowest being Greater London and the West Midlands in England. For the case study, the ecosystems with the greatest contribution to terrestrial activities were marine and enclosed farmland. These methods can be applied worldwide for anywhere with aggregate economic statistics on expenditure associated with tourism and outdoor leisure, with the aid of open source GIS datasets.

PMID:35731823 | DOI:10.1371/journal.pone.0269790

PLoS Comput Biol. 2022 Jun 22;18(6):e1009414. doi: 10.1371/journal.pcbi.1009414. Online ahead of print.

ABSTRACT

Gene expression is controlled by pathways of regulatory factors often involving the activity of protein kinases on transcription factor proteins. Despite this well established mechanism, the number of well described pathways that include the regulatory role of protein kinases on transcription factors is surprisingly scarce in eukaryotes. To address this, PhosTF was developed to infer functional regulatory interactions and pathways in both simulated and real biological networks, based on linear cyclic causal models with latent variables. GeneNetWeaverPhos, an extension of GeneNetWeaver, was developed to allow the simulation of perturbations in known networks that included the activity of protein kinases and phosphatases on gene regulation. Over 2000 genome-wide gene expression profiles, where the loss or gain of regulatory genes could be observed to perturb gene regulation, were then used to infer the existence of regulatory interactions, and their mode of regulation in the budding yeast Saccharomyces cerevisiae. Despite the additional complexity, our inference performed comparably to the best methods that inferred transcription factor regulation assessed in the DREAM4 challenge on similar simulated networks. Inference on integrated genome-scale data sets for yeast identified ∼ 8800 protein kinase/phosphatase-transcription factor interactions and ∼ 6500 interactions among protein kinases and/or phosphatases. Both types of regulatory predictions captured statistically significant numbers of known interactions of their type. Surprisingly, kinases and phosphatases regulated transcription factors by a negative mode or regulation (deactivation) in over 70% of the predictions.

PMID:35731801 | DOI:10.1371/journal.pcbi.1009414

PLoS One. 2022 Jun 22;17(6):e0270254. doi: 10.1371/journal.pone.0270254. eCollection 2022.

ABSTRACT

This study aims to investigate the supply chain challenges of public sector agriculture development projects in Bangladesh using the modified Delphi, Best Worst Method (BWM), and Interpretive Structural Modelling (ISM) methods. Based on these three widely acclaimed statistical techniques, the study identified, ranked, and identified interrelationships among the challenges. The study is unique not only in terms of research findings, but also in terms of methodology, as it is the first to use the three MCDM (Multicriteria Decision Making) tools to examine supply chain issues in public sector agriculture development projects in a developing country context. A literature review and two modified Delphi rounds with 15 industry experts’ opinions were applied to identify and validate a list of 11 key supply chain challenges. To determine the priority of the challenges, a panel of eight industry experts was consulted, and their responses were analysed using the BWM. Then, another group of 10 experts was consulted using ISM to investigate the contextual relationships among the challenges, resulting in a five-layered Interpretive Structural Model (ISM) and MICMAC (cross-impact matrix multiplication applied to classification) analysis of the challenges. According to relative importance (global weights), “improper procurement planning (0.213), “delay in project initiation (0.177), “demand forecasting error (0.146)”, “lack of contract monitoring mechanism (0.097)”, and “lack of competent staff (0.095)” are the top five ranked key challenges that have a significant impact on the project supply chain. Regarding contextual relationships, the ISM model and ISM-MICMAC analysis identified the “political influence” challenge as the most influential, and also independent of the other challenges. The findings are critical for project managers in managing challenges because understanding both relative importance and contextual relationships are required to address the challenges holistically. Additionally, these findings will benefit policymakers, academics, and future researchers.

PMID:35731792 | DOI:10.1371/journal.pone.0270254

PLoS One. 2022 Jun 22;17(6):e0269569. doi: 10.1371/journal.pone.0269569. eCollection 2022.

ABSTRACT

BACKGROUND: The prevalence of obstructive sleep apnea is higher in women after menopause. This is suggested to be a result of an altered sex hormone balance but has so far not been confirmed in a population-based study.

OBJECTIVE: To investigate whether serum concentration of estrogens and progesterone are associated with the prevalence of sleep apnea symptoms in middle-aged women of the general population.

METHODS: We analyzed data from 774 women (40-67 years) from 15 study centers in seven countries participating in the second follow-up of the European Community Respiratory Health Survey (2010-2012). Multiple logistic regression models were fitted with self-reported symptoms of sleep apnea as outcomes and serum concentrations of various estrogens and progesterone as predictors. All analyses were adjusted for relevant covariates including age, BMI, education, study center, smoking habits, and reproductive age.

RESULTS: Among all included women, a doubling of serum concentrations of estrone and progesterone was associated with 19% respectively 9% decreased odds of snoring. Among snorers, a doubling of the concentrations of 17β-estradiol, estrone and estrone 3-sulfate was associated with 18%, 23% and 17% decreased odds of breathing irregularly, and a doubling of the progesterone concentration was further associated with 12% decreased odds of waking up suddenly with a chocking sensation. Other evaluated associations were not statistically significant.

CONCLUSIONS: Middle-aged women with low serum estrogen and progesterone levels are more likely to snore and report symptoms of obstructive sleep apnea.

PMID:35731786 | DOI:10.1371/journal.pone.0269569

PLoS One. 2022 Jun 22;17(6):e0268409. doi: 10.1371/journal.pone.0268409. eCollection 2022.

ABSTRACT

INTRODUCTION: The use of social media during the COVID-19 pandemic has led to an “infodemic” of mis- and disinformation with potentially grave consequences. To explore means of counteracting disinformation, we analyzed tweets containing the hashtags #Scamdemic and #Plandemic.

METHODS: Using a Twitter scraping tool called twint, we collected 419,269 English-language tweets that contained “#Scamdemic” or “#Plandemic” posted in 2020. Using the Twitter application-programming interface, we extracted the same tweets (by tweet ID) with additional user metadata. We explored descriptive statistics of tweets including their content and user profiles, analyzed sentiments and emotions, performed topic modeling, and determined tweet availability in both datasets.

RESULTS: After removal of retweets, replies, non-English tweets, or duplicate tweets, 40,081 users tweeted 227,067 times using our selected hashtags. The mean weekly sentiment was overall negative for both hashtags. One in five users who used these hashtags were suspended by Twitter by January 2021. Suspended accounts had an average of 610 followers and an average of 6.7 tweets per user, while active users had an average of 472 followers and an average of 5.4 tweets per user. The most frequent tweet topic was “Complaints against mandates introduced during the pandemic” (79,670 tweets), which included complaints against masks, social distancing, and closures.

DISCUSSION: While social media has democratized speech, it also permits users to disseminate potentially unverified or misleading information that endangers people’s lives and public health interventions. Characterizing tweets and users that use hashtags associated with COVID-19 pandemic denial allowed us to understand the extent of misinformation. With the preponderance of inaccessible original tweets, we concluded that posters were in denial of the COVID-19 pandemic and sought to disperse related mis- or disinformation resulting in suspension.

CONCLUSION: Leveraging 227,067 tweets with the hashtags #scamdemic and #plandemic in 2020, we were able to elucidate important trends in public disinformation about the COVID-19 vaccine.

PMID:35731785 | DOI:10.1371/journal.pone.0268409

IEEE Trans Ultrason Ferroelectr Freq Control. 2022 Jun 22;PP. doi: 10.1109/TUFFC.2022.3185528. Online ahead of print.

ABSTRACT

This article addresses the measurement of the power spectrum of red noise processes at the lowest frequencies, where the minimum acquisition time is so long that it is impossible to average on a sequence of data record. Therefore, averaging is possible only on simultaneous observation of multiple instruments. This is the case of radio astronomy, which we take as the paradigm, but examples may be found in other fields such as climatology and geodesy. We compare the Bayesian confidence interval of the red noise parameter using two estimators, the spectrum average and the cross-spectrum. While the spectrum average is widely used, the cross-spectrum using multiple instruments is rather uncommon. With two instruments, the cross-spectrum estimator leads to the Variance-Gamma distribution. A generalization to q devices based on the Fourier transform of characteristic functions is provided, with the example of the observation of millisecond pulsars with 5 radio telescopes. The simulations show that the spectrum average is by a small amount more efficient than the cross-spectrum, chiefly when the background exceeds the signal. However some notable differences between their upper limit indicate that it should be wiser to compute both estimators.

PMID:35731776 | DOI:10.1109/TUFFC.2022.3185528

Pediatr Blood Cancer. 2022 Jun 22:e29867. doi: 10.1002/pbc.29867. Online ahead of print.

ABSTRACT

BACKGROUND: Burkitt lymphoma (BL) accounts for 90% of pediatric lymphomas in sub-saharan Africa. Plasmodium falciparum (Pf) malaria is considered an etiological factor of BL. We describe the geographic distribution of pediatric BL in Malawi and association with malaria prevalence (PfPR).

METHODS: We enrolled 220 pathologically confirmed incident pediatric BL cases (2013-2018) into an observational clinical cohort at Kamuzu Central Hospital (KCH) in Lilongwe district. KCH is the main tertiary cancer referral center serving the central and northern region of Malawi. Using an ecological study design, we calculated district-level annual BL incidence rate using census population estimates. District-level PfPR was extracted from the National Malaria Control Program 2010 report. BL incidence and PfPR maps were constructed in QGIS. Moran’s I was used to identify BL spatial clusters. Pearson’s correlation and multiple linear regression was used to statistically examine the relationship between PfPR and BL.

RESULTS: BL incidence was higher in central region districts (8.2 cases per million) than northern districts (2.9 cases per million) and was elevated in lakeshore districts. Districts with elevated PfPR tended to have elevated BL incidence. A low-risk BL cluster was detected in the north. Statistically, BL incidence was positively correlated with PfPR (r = 0.77, p<0.01). A 1% increase in PfPR predicted an increase in BL incidence of 0.2 cases per million (p = 0.03) when controlling for travel time from referral district hospital to KCH.

CONCLUSION: Our study supports evidence for an association between Pf and BL and highlights a need to improve geographic accessibility to tertiary cancer services in Malawi’s northern region. This article is protected by copyright. All rights reserved.

PMID:35731580 | DOI:10.1002/pbc.29867

JMIR Form Res. 2022 Jun 22;6(6):e28013. doi: 10.2196/28013.

ABSTRACT

BACKGROUND: Clinical decision support systems often adopt and operationalize existing clinical practice guidelines leading to higher guideline availability, increased guideline adherence, and data integration. Most of these systems use an internal state-based model of a clinical practice guideline to derive recommendations but do not provide the user with comprehensive insight into the model.

OBJECTIVE: Here we present a novel approach based on dynamic guideline visualization that incorporates the individual patient’s current treatment context.

METHODS: We derived multiple requirements to be fulfilled by such an enhanced guideline visualization. Using business process and model notation as the representation format for computer-interpretable guidelines, a combination of graph-based representation and logical inferences is adopted for guideline processing. A context-specific guideline visualization is inferred using a business rules engine.

RESULTS: We implemented and piloted an algorithmic approach for guideline interpretation and processing. As a result of this interpretation, a context-specific guideline is derived and visualized. Our implementation can be used as a software library but also provides a representational state transfer interface. Spring, Camunda, and Drools served as the main frameworks for implementation. A formative usability evaluation of a demonstrator tool that uses the visualization yielded high acceptance among clinicians.

CONCLUSIONS: The novel guideline processing and visualization concept proved to be technically feasible. The approach addresses known problems of guideline-based clinical decision support systems. Further research is necessary to evaluate the applicability of the approach in specific medical use cases.

PMID:35731571 | DOI:10.2196/28013