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Nevin Manimala Statistics

Nurse Spiritual Care Therapeutics Scale: Validation Among Nurses Who Care for Patients With Life-Threatening Illnesses in South Korea

J Hosp Palliat Nurs. 2022 Jun 18. doi: 10.1097/NJH.0000000000000895. Online ahead of print.

ABSTRACT

Although clinical and empirical literature documents the variety of spiritual care interventions available to palliative care clinicians, the frequency with which they are provided is rarely and inadequately measured. Given the growing interest in implementing spiritual care across Asia, including South Korea, this study sought to cross-culturally validate the Korean version of the Nurse Spiritual Care Therapeutics Scale (NSCTS-K), a scale initially developed in the United States. The World Health Organization process for cross-cultural adaptation of scales and Polit and Yang’s process for evaluating validation were implemented. With data from a sample of 252 Korean nurses providing care to patients with life-threatening illnesses, various statistical procedures for evaluating validity and reliability were applied during this cross-sectional, observational study. Exploratory factor analysis for the structural validity of the Korean scale generated 3 factors that accounted for 69.40% of the variance. The Cronbach α was 0.95. The NSCTS-K is one of the few scales available to determine the impact of nurse-provided spiritual care frequency on patient outcomes. Thus, this tool can quantify the frequency of spiritual care better and be used in quality improvement initiatives or palliative care research.

PMID:35713883 | DOI:10.1097/NJH.0000000000000895

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Nevin Manimala Statistics

Maternal autonomy and childhood undernutrition: Analysis of 2018 Nigeria demographic and health survey

J Child Health Care. 2022 Jun 17:13674935221108011. doi: 10.1177/13674935221108011. Online ahead of print.

ABSTRACT

Existing knowledge of how maternal autonomy relates to child undernutrition in Nigeria is few and limited to children under 24 months old. Nothing is known about how it affects older children. Therefore, this study investigated whether mothers’ household autonomy affects children 24-59 months, as do children under 24 months old. We used data from 2018 Nigerian Demographic and Health Survey, which is a nationally representative survey. Samples include 3502 and 5463 children under 24 months and between 24 and 59 months old, respectively. Three anthropometry indexes were used to determine child undernutrition: weight-for-height, height-for-age, and weight-for-age, which indicate wasting, stunting, and underweight, respectively. Three domains of maternal autonomy: decision-making, financial-control, and mobility, were operationalized using responses from mothers. Results from logistic regression analysis show that in unadjusted models, maternal decision-making autonomy and mobility were associated with undernutrition in both samples. After adding covariates, only associations between maternal decision-making autonomy and underweight in children 24-59 months old retained statistical significance. Findings show that gendered social inequalities are linked to differences in child nutritional outcomes. Future studies could investigate how feeding practices mediate associations between maternal autonomy and childhood undernutrition.

PMID:35713878 | DOI:10.1177/13674935221108011

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Nevin Manimala Statistics

Combining Literature Mining and Machine Learning for Predicting Biomedical Discoveries

Methods Mol Biol. 2022;2496:123-140. doi: 10.1007/978-1-0716-2305-3_7.

ABSTRACT

The major outcomes and insights of scientific research and clinical study end up in the form of publication or clinical record in an unstructured text format. Due to advancements in biomedical research, the growth of published literature is getting tremendous large in recent years. The scientists and clinical researchers are facing a big challenge to stay current with the knowledge and to extract hidden information from this sheer quantity of millions of published biomedical literature. The potential one-stop automated solution to this problem is biomedical literature mining. One of the long-standing goals in biology is to discover the disease-causing genes and their specific roles in personalized precision medicine and drug repurposing. However, the empirical approaches and clinical affirmation are expensive and time-consuming. In silico approach using text mining to identify the disease causing genes can contribute towards biomarker discovery. This chapter presents a protocol on combining literature mining and machine learning for predicting biomedical discoveries with a special emphasis on gene-disease relation based discovery. The protocol is presented as a literature based discovery (LBD) pipeline for gene-disease based discovery. The protocol includes our web based tools: (1) DNER (Disease Named Entity Recognizer) for disease entity recognition, (2) BCCNER (Bidirectional, Contextual clues Named Entity Tagger) for gene/protein entity recognition, (3) DisGeReExT (Disease-Gene Relation Extractor) for statistically validated results and visualization, and (4) a newly introduced deep learning based method for association discovery. Our proposed deep learning based method can be generalized and applied to other important biomedical discoveries focusing on entities such as drug/chemical, or miRNA.

PMID:35713862 | DOI:10.1007/978-1-0716-2305-3_7

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Nevin Manimala Statistics

Biomedical Literature Mining for Repurposing Laboratory Tests

Methods Mol Biol. 2022;2496:91-109. doi: 10.1007/978-1-0716-2305-3_5.

ABSTRACT

Epidemiological studies identifying biological markers of disease state are valuable, but can be time-consuming, expensive, and require extensive intuition and expertise. Furthermore, not all hypothesized markers will be borne out in a study, suggesting that high-quality initial hypotheses are crucial. In this chapter, we describe a high-throughput pipeline to produce a ranked list of high-quality hypothesized biomarkers for diseases. We review an example use of this approach to generate a large number of candidate disease biomarker hypotheses derived from machine learning models, filter and rank them according to their potential novelty using text mining, and corroborate the most promising hypotheses with further statistical modeling. The example use of the pipeline uses a large electronic health record dataset and the PubMed corpus, to find several promising hypothesized laboratory tests with previously undocumented correlations to particular diseases.

PMID:35713860 | DOI:10.1007/978-1-0716-2305-3_5

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Nevin Manimala Statistics

Spatial variability and source analysis of typical soil trace elements at permafrost section along national highway 214 in the eastern Qinghai-Tibet Plateau

Environ Geochem Health. 2022 Jun 17. doi: 10.1007/s10653-022-01299-5. Online ahead of print.

ABSTRACT

This paper attempts to reveal the enrichment status, spatial characteristics and material sources of typical soil trace elements at permafrost section along National Highway 214 on the Qinghai-Tibet Plateau. Therefore, the samples of typical trace elements in surface soil, being located at the northern slope of Bayan Kara Mountains, were collected and tested. The concentrations of typical trace elements in soil were analysed by mathematical statistics, spatial analysis and ecological assessment. The results show that: (1) the concentrations of As, Cd and Hg in the soil are higher than the local background values, and their degrees of variation were high. There was a certain degree of accumulation. Soil As and Hg elements constitute “slight pollution”, indicating there is a none-to-slight ecological hazard. (2) The distributions of soil As, Cd, Pb and Zn concentrations are lower near the highway and increase with distance from it and then become relatively low further away. The distributions of Cr, Cu, Hg and Ni concentrations show no obvious trends in any direction. (3) The spatial heterogeneity of typical trace elements in soil is affected by soil organic matter (SOM), cation exchange capacity (CEC), pH, slope curvature and aspect. At the local scale, soil texture and topography were the main affecting factors. Concentrations of Cd, Cr, Cu, Ni, Pb and Zn were mainly affected by natural factors, while those of As and Hg were affected by both natural and human factors.

PMID:35713839 | DOI:10.1007/s10653-022-01299-5

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Nevin Manimala Statistics

Associations of organophosphate metabolites with thyroid hormone and antibody levels: findings from U.S. National Health and Nutrition Examination Survey (NHANES)

Environ Sci Pollut Res Int. 2022 Jun 17. doi: 10.1007/s11356-022-21385-6. Online ahead of print.

ABSTRACT

Studies have shown that organophosphate pesticides (OPs) exposure may disrupt thyroid endocrine functions in animal models, agricultural population, occupational workers, and work-related population. However, the relationships between OPs exposure and thyroid hormone levels in the general population are unclear. This study aimed to explore the relationships of OPs exposure with thyroid hormone and antibody levels in the general population. We analyzed a sample of 1089 US adults from the National Health and Nutrition Examination Survey (NHANES) 2001-2002. OPs exposure was estimated using measures of six non-specific dialkyl phosphate metabolites (DAPs), e.g., dimethylphosphate (DMP). Multiple linear regression models were used to examine the associations of OPs exposure with thyroid hormone and antibody levels. The medians of urinary ∑DAPs detected in males and females were 32.98 nmol/g creatinine and 40.77 nmol/g creatinine, with statistical significance (p = 0.001). After controlling for sociodemographic factors, we found that concentrations of urinary OPs metabolites were positively associated with the serum thyroid stimulating hormone (TSH) in the general US population, particularly in males; OPs metabolites were associated with the serum TgAb, tT3, fT3, and TSH. These findings showed that thyroid hormone and antibody disruption are probably associated with OPs exposure in the general population; more studies are needed to confirm our findings.

PMID:35713824 | DOI:10.1007/s11356-022-21385-6

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Nevin Manimala Statistics

Generation of hemipelvis surface geometry based on statistical shape modelling and contralateral mirroring

Biomech Model Mechanobiol. 2022 Jun 17. doi: 10.1007/s10237-022-01594-1. Online ahead of print.

ABSTRACT

Personalised fracture plates manufactured using 3D printing offer an improved treatment option for unstable pelvic ring fractures that may not be adequately secured using off-the-shelf components. To design fracture plates that secure the bone fragments in their pre-fracture positions, the fractures must be reduced virtually using medical imaging-based reconstructions, a time-consuming process involving segmentation and repositioning of fragments until surface congruency is achieved. This study compared statistical shape models (SSMs) and contralateral mirroring as automated methods to reconstruct the hemipelvis using varying amounts of bone surface geometry. The training set for the geometries was obtained from pelvis CT scans of 33 females. The root-mean-squared error (RMSE) was quantified across the entire surface of the hemipelvis and within specific regions, and deviations of pelvic landmarks were computed from their positions in the intact hemipelvis. The reconstruction of the entire hemipelvis surfaced based on contralateral mirroring had an RMSE of 1.21 ± 0.29 mm, whereas for SSMs based on the entire hemipelvis surface, the RMSE was 1.11 ± 0.29 mm, a difference that was not significant (p = 0.32). Moreover, all hemipelvis reconstructions based on the full or partial bone geometries had RMSEs and landmark deviations from contralateral mirroring that were significantly lower (p < 0.05) or statistically equivalent to the SSMs. These results indicate that contralateral mirroring tends to be more accurate than SSMs for reconstructing unilateral pelvic fractures. SSMs may still be a viable method for hemipelvis fracture reconstruction in situations where contralateral geometries are not available, such as bilateral pelvic factures, or for highly asymmetric pelvic anatomies.

PMID:35713823 | DOI:10.1007/s10237-022-01594-1

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Nevin Manimala Statistics

Habit-like attentional bias is unlike goal-driven attentional bias against spatial updating

Cogn Res Princ Implic. 2022 Jun 17;7(1):50. doi: 10.1186/s41235-022-00404-7.

ABSTRACT

Statistical knowledge of a target’s location may benefit visual search, and rapidly understanding the changes in regularity would increase the adaptability in visual search situations where fast and accurate performance is required. The current study tested the sources of statistical knowledge-explicitly-given instruction or experience-driven learning-and whether they affect the speed and location spatial attention is guided. Participants performed a visual search task with a statistical regularity to bias one quadrant (“old-rich” condition) in the training phase, followed by another quadrant (“new-rich” condition) in the switching phase. The “instruction” group was explicitly instructed on the regularity, whereas the “no-instruction” group was not. It was expected that the instruction group would rely on goal-driven attention (using regularities with explicit top-down knowledge), and the no-instruction group would rely on habit-like attention (learning regularities through repetitive experiences) in visual search. Compared with the no-instruction group, the instruction group readjusted spatial attention following the regularity switch more rapidly. The instruction group showed greater attentional bias toward the new-rich quadrant than the old-rich quadrant; however, the no-instruction group showed a similar extent of attentional bias to two rich quadrants. The current study suggests that the source of statistical knowledge can affect attentional allocation. Moreover, habit-like attention, a different type of attentional source than goal-driven attention, is relatively implicit and inflexible.

PMID:35713814 | DOI:10.1186/s41235-022-00404-7

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Nevin Manimala Statistics

Vitamin D deficiency and cardiometabolic risk factors in adolescents: systematic review and meta-analysis

Rev Endocr Metab Disord. 2022 Jun 17. doi: 10.1007/s11154-022-09736-7. Online ahead of print.

ABSTRACT

Vitamin D deficiency is associated with an increase in the occurrence of cardiometabolic events, but the evidence of this relationship in adolescence is still limited. Thus, we analyzed the association between vitamin D deficiency and cardiometabolic risk factors in adolescents. Observational studies were searching in PubMed/Medline, Embase, Scopus, Web of Science, Science Direct, Lilacs, and Google Scholar database. Random effects models were used to summarize standardized mean differences for as a summary measure. The certainty of the evidence was verified using the Cochrane recommendations. A total of 7537 studies were identified, of which 32 were included in the systematic review and 24 in the meta-analysis.Vitamin D deficiency was associated with increased systolic pressure (SMD = 0.22; 95%CI = 0.10; 0.34), diastolic pressure (SMD = 0.23; 95%CI = 0.10; 0.35), glycemia (SMD = 0.13; 95%CI = 0.05; 0.12), and insulin (SMD = 0.50; 95%CI = 0.15; 0.84), an increase in the HOMA index (SMD = 0.48; 95%CI = 0.36; 0.60), high triglyceride values (SMD = 0.30; 95%CI = 0.11; 0.49), and reduced HDL concentrations (SMD= -0.25; 95%CI = -0.46; -0.04). No statistically significant association was observed for glycated hemoglobin, LDL cholesterol, and total cholesterol. Most of the studies presented low and moderate risks of bias, respectively. The certainty of the evidence was very low for all the outcomes analyzed. Vitamin D deficiency was associated with increased exposure to the factors linked to the occurrence of cardiometabolic diseases in adolescents. Systematic Review Registration: PROSPERO (record number 42,018,086,298).

PMID:35713809 | DOI:10.1007/s11154-022-09736-7

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Nevin Manimala Statistics

Immunological characterization of chitosan adjuvanted outer membrane proteins of Salmonella enterica serovar Typhi as multi-epitope typhoid vaccine candidate

Mol Biol Rep. 2022 Jun 17. doi: 10.1007/s11033-022-07531-w. Online ahead of print.

ABSTRACT

BACKGROUND: Outer membrane proteins (OMPs) of Gram-negative bacteria have been known as potential vaccine targets due to their antigenic properties and host specificity. Here, we focused on the exploration of the immunogenic potential and protective efficacy of total OMPs of Salmonella enterica serovar Typhi due to their multi epitope properties, adjuvanted with nanoporous chitosan particles (NPCPs). The study was designed to extrapolate an effective, low cost prophylactic approach for typhoid fever being getting uncontrolled in Pakistan due to emergence of extensively drug resistant (XDR) strains.

METHODS & RESULTS: The OMPs of two S. Typhi variants (with and without Vi capsule) alone and with nanoporous chitosan particles as adjuvant were comparatively analyzed for immunogenic potential in mice. Adaptive immunity was evaluated by ELISA and relative quantification of cytokine gene expression (IL4, IL6, IL9, IL17, IL10, TNF, INF and PPIA as house keeping gene) using RT-qPCR. Statistical analysis was done using Welch’s test. The protection was recorded by challenging the immunized mice with 50% ×LD50 of S. Typhi. The Vi + ve-OMPs of S. Typhi showed the most promising results by ELISA and significantly high expression of IL-6, IL-10 and IL-17 and 92.5% protective efficacy with no detectable side effects.

CONCLUSION: We can conclude that the OMPs of Vi + ve S. Typhi are the most promising candidates for future typhoid vaccines because of cost effective preparation without expensive purification steps and multi-epitope properties. Chitosan adjuvant may have applications for oral protein based vaccines but found less effective in injectable preparations.

PMID:35713798 | DOI:10.1007/s11033-022-07531-w