Biological research for nursing最新文献

Irritable bowel syndrome (IBS) is a common disorder of gut-brain interaction with multifaceted pathophysiology. Prior studies have demonstrated higher rates of vitamin D deficiency in individuals with IBS compared to healthy controls (HC), as well as associations of vitamin D concentration with IBS symptoms. A systematic review of 10 mouse and 14 human studies reported a positive association between vitamin D (serum levels and supplementation) and beta diversity of gut microbiome in a variety of conditions. The present retrospective case-control study aimed to compare vitamin D (25(OH)D) plasma concentrations and gut microbiome composition in adult women with IBS (n=99) and HC (n=62). Plasma concentrations of 25(OH)D were assessed using the Endocrine Society Guidelines definition of vitamin D deficiency (25(OH)D <20 ng/ml) and insufficiency (25(OH)D >20-<30 ng/ml). 16S rRNA microbiome gene sequencing data was available for 39 HC and 62 participants with IBS. Genus-level Bifidobacterium and Lactobacillus and phylum-level Firmicutes and Bacteroidetes relative abundances were extracted from microbiome profiles. Results showed vitamin D deficiency in 40.3% (n=25) vs. 41.4% (n=41), and insufficiency 33.9% (n=21) vs. 34.3% (n=34) in the HCs vs. IBS groups, respectively. The odds of IBS did not differ depending on 25(OH)D status (p=0.75 for deficient, p=0.78 for insufficient), and the average plasma vitamin D concentration did not differ between IBS (mean 24.8 ng/ml) and HCs (mean 25.1 ng/ml; p=0.57). We did not find evidence of an association between plasma 25(OH)D concentration and richness, Shannon index, Simpson index or specific bacterial abundances in either HCs or the IBS group.

Background: Accurate prediction of risk for chronic diseases like type 2 diabetes (T2D) is challenging due to the complex underlying etiology. Integration of more complex data types from sensors and leveraging technologies for collection of -omics datasets may provide greater insights into the specific risk profile for complex diseases.Methods: We performed a literature review to identify feature selection methods and machine learning models for prediction of weight loss in a previously completed clinical trial (NCT02278939) of a behavioral intervention for weight loss in Filipinos at risk for T2D. Features included demographic and clinical characteristics, dietary factors, physical activity, and transcriptomics.Results: We identified four feature selection methods: Correlation-based Feature Subset Selection (CfsSubsetEval) with BestFirst, Kolmogorov-Smirnov (KS) test with correlation featureselection (CFS), DESeq2, and max-relevance-min-relevance (MRMR) with linear forward search and mutual information (MI) and four machine learning algorithms: support vector machine, decision tree, random forest, and extra trees that are applicable to prediction of weight loss using the specified feature types.Conclusion: More accurate prediction of risk for T2D and other complex conditions may be possible by leveraging complex data types from sensors and -omics datasets. Emerging methods for feature selection and machine learning algorithms make this type of modeling feasible.

Electronic cigarette use is highest among adults of child-bearing age. Many parents that use electronic cigarettes believe that secondhand exposure of electronic cigarette vapors for their children is not dangerous and is less harmful than secondhand exposure to traditional cigarette smoke. These beliefs may prompt excessive secondhand exposure to electronic cigarette vapors for their children. Little research has been done to document exposure in children. The traditional biological method of exposure detection is through a blood draw, which is difficult and undesirable in children. The purpose of this study was to assess the feasibility of using saliva and exhaled breath condensate as non-invasive biomatrices for detecting secondhand electronic cigarette vapor exposure in children. In this cross-sectionally designed study, we recruited 22 children exposed to electronic cigarette vapors and 26 non-exposed between the ages of 4-12 years. We compared metabolic features across three biomatrices, blood, saliva, and exhaled breath condensate. We noted moderate to strong pairwise, sample-specific, and feature-specific adjusted correlations. Annotated features associated with direct and secondhand electronic cigarette exposure were noted. These results demonstrate that less invasive biomatrices may be used to detect features associated with secondhand electronic cigarette vapor exposure in children.

Food restriction (FR) enhances sensitivity to cardiopulmonary reflexes and α1-adrenoreceptors in females in the presence of hypotension. However, the effect of FR on cardiopulmonary and vascular function in males is not well-understood. This study examines the effects of FR on cardiopulmonary, isolated arterial function, and potential underlying mechanisms. Male Sprague-Dawley (SD) rats were randomly divided into 3 groups and monitored for 5 weeks: (1) control (n = 30), (2) 20% food reduction (FR20, n = 30), and (3) 40% food reduction (FR40, n = 30). Non-invasive blood pressure was measured twice a week. Pulmonary arterial pressure (PAP) was measured using isolated/perfused lungs. The isolated vascular reactivity was assessed using double-wire myographs. FR rats exhibited a lower mean arterial pressure and heart rate; however, only the FR40 group exhibited statistically significant differences. We observed that FR enhanced sensitivity (EC₅₀) to vasoconstriction induced by the α1-adrenoreceptor phenylephrine (PhE) but not to serotonin, U46619, or high K⁺ in the mesenteric arteries. PhE-mediated vasoconstriction in the mesenteric arteries was eliminated in the presence of the eNOS inhibitor (L-NAME). In addition, incubation with NOX2/4 inhibitors (apocynin, GKT137831, and VAS2870) and the reactive oxygen species (ROS) scavenger inhibitor (Tiron) eliminated the differences in PhE-mediated vasoconstriction, but the cyclooxygenase inhibitor (indomethacin) in the mesenteric arteries did not. Augmentation of α1-adrenergic-mediated contraction via the inhibition of the eNOS-NO pathway increased the activation of ROS through NOX2/4 in response to FR. Reduced eNOS-NO signaling may be a pathophysiological counterbalance to prevent hypovolemic shock in response to FR.

Background: Blood cancers may be potentially cured with hematopoietic stem cell transplantation (HCT); however, standard pre-assessments for transplant eligibility do not capture all contributing factors for transplant outcomes. Epigenetic biomarkers predict outcomes in various diseases. This pilot study aims to explore epigenetic changes (epigenetic age and differentially methylated genes) in patients before and after autologous HCT, that can serve as potential biomarkers to better predict HCT outcomes.

Methods: This study used a prospective longitudinal study design to compare genome wide DNA methylation changes in 36 autologous HCT eligible patients recruited from the Cellular Immunotherapies and Transplant clinic at a designated National Cancer Center.

Results: Genome-wide DNA methylation, measured by the Illumina Infinium Human Methylation 850K BeadChip, showed a significant difference in DNA methylation patterns post-HCT compared to pre-HCT. Compared to baseline levels of DNA methylation pre-HCT, 3358 CpG sites were hypo-methylated and 3687 were hyper-methylated. Identified differentially methylated positions overlapped with genes involved in hematopoiesis, blood cancers, inflammation and immune responses. Enrichment analyses showed significant alterations in biological processes such as immune response and cell structure organization, however no significant pathways were noted. Though participants had an advanced epigenetic age compared to chronologic age before and after HCT, both epigenetic age and accelerated age decreased post-HCT.

Conclusion: Epigenetic changes, both in epigenetic age and differentially methylated genes were observed in autologous HCT recipients, and should be explored as biomarkers to predict transplant outcomes after autologous HCT in larger, longitudinal studies.

Objectives: Palpitations are common and have a negative impact on women's quality of life. While evidence suggests that inflammatory mechanisms may play a role in the development of palpitations, no studies have evaluated for this association in patients with breast cancer who report palpitations prior to surgery. The purpose of this pilot study was to evaluate for associations between the occurrence of palpitations and single nucleotide polymorphisms (SNPs) in genes for pro- and anti-inflammatory cytokines, their receptors, and transcriptional regulators.

Methods: Patients were recruited prior to surgery and completed a self-report questionnaire on the occurrence of palpitations. Genotyping of SNPs in cytokine genes was performed using a custom array. Multiple logistic regression analyses were done to identify associations between the occurrence of palpitations and SNPs in fifteen candidate genes.

Results: Of the 82 SNPs evaluated in the bivariate analyses, eleven SNPs in 6 genes were associated with the occurrence of palpitations. After controlling for functional status, the occurrence of back pain, and self-reported and genomic estimates of race/ethnicity, 3 SNPs in 3 different genes (i.e., interleukin (IL) 1-beta (IL1B) rs1143643, IL10 rs3024505, IL13 rs1295686) were associated with the occurrence of palpitations prior to surgery (all p ≤ .038).

Conclusions: While these preliminary findings warrant replication, they suggest that inflammatory mechanisms may contribute to the subjective sensation of palpitations in women prior to breast cancer surgery.

Background: There is a need to detect and prevent fluid overload and malnutrition in heart failure. Bioelectrical impedance analysis and bioelectrical impedance vector analysis are medical instruments that can advance heart failure management by generating values of body composition and body water, assisting clinicians to detect fluid and nutritional status. However, there is a lack of evidence to summarise how they have been used among heart failure patients.

Method: A systematic search was conducted.

Result: Two hundred and four papers were screened. Forty-eight papers were reviewed, and 46 papers were included in this review. The literature shows that bioelectrical impedance analysis and bioelectrical impedance vector analysis were mostly used to assess fluid and nutritional status, together with diagnostic and prognostic values. Contraindication of using BIA and implications for practice are also demonstrated.

Conclusion: The findings suggest that bioelectrical impedance vector analysis is superior to bioelectrical impedance analysis when assessing hydration/nutritional status in heart failure. Assessing a patient using bioelectrical impedance analysis /bioelectrical impedance vector analysis, together with natriuretic peptide -heart failure biomarkers, increases the diagnostic accuracy of heart failure. Further studies are required to examine the cost effectiveness of using these instruments in clinical practice.

Background: Gout is triggered by high urate levels and causes inflammation, pain, and an impaired quality of life. Immersion in water at 20-30°C reduces inflammation and pain in arthritis. Yet, relationships of immersion in water at 20-30°C with urate levels and the nucleotide-binding domain (NOD)-like receptor protein 1 (NLRP1) inflammasome have never been clarified.

Objectives: We aimed to investigate the effects of immersion in water at 20-30°C on urate levels, the NLRP1 inflammasome, pain, and quality of life among acute gout patients.

Methods: A community-based randomized control trial design was used with 2 parallel-intervention groups: immersion in water at 20-30°C (20 min/day for 4 weeks) group and a control group. In total, 76 eligible participants in Tomohon City, Indonesia, were assigned using block randomization. We analyze the results (coef. β) and 95% confidence intervals (CIs) using a generalized estimating equation model. We analyzed mediating effects using a path analysis.

Results: Significant pain alleviation (β = -2.06 [95% CI = -2.67∼-1.45]; β = -2.42 [95% CI = -2.97∼-1.87]) and improved quality of life (β = 5.34 [95% CI = 3.12-7.57]; β = 9.93 [95% CI = 7.02-12.83]) were detected at 2 and 4 weeks of follow-up compared to the pre-test and control group. Urate levels (β = -0.34 [95% CI = -0.52∼-0.16]) were reduced at the 2-week follow-up, but there was no significant change in the NLRP1 inflammasome compared to the pre-test and control group after immersion in water at 20-30°C. Both the NLRP1 inflammasome (β = -0.48 [95% CI = -0.63∼-0.34]); water 0.01) and urate levels (β = -0.11 [95% CI = -0.24∼-0.03]; p < 0.01) had partial indirect (mediating) effects on the link between immersion in water at 20-30°C and pain at the 4-week follow-up.

Conclusions: Immersion in water at 20-30°C significantly decreased pain and increased the quality of life. Immersion in water at 20-30°C mediated NLRP1 and urate levels to decrease pain, although it had no significant effect on the NLRP1 inflammasome concentration after 4 weeks of follow-up and reduced urate levels only at 2 weeks after immersion in water at 20-30°C.

Background: Gestational diabetes mellitus (GDM) is a common pregnancy complication that negatively impacts the health of both the mother and child. Early prediction of the risk of GDM may permit prompt and effective interventions. This systematic review and meta-analysis aimed to summarize the study characteristics, methodological quality, and model performance of first-trimester prediction model studies for GDM.

Methods: Five electronic databases, one clinical trial register, and gray literature were searched from the inception date to March 19, 2022. Studies developing or validating a first-trimester prediction model for GDM were included. Two reviewers independently extracted data according to an established checklist and assessed the risk of bias by the Prediction Model Risk of Bias Assessment Tool (PROBAST). We used a random-effects model to perform a quantitative meta-analysis of the predictive power of models that were externally validated at least three times.

Results: We identified 43 model development studies, six model development and external validation studies, and five external validation-only studies. Body mass index, maternal age, and fasting plasma glucose were the most commonly included predictors across all models. Multiple estimates of performance measures were available for eight of the models. Summary estimates range from 0.68 to 0.78 (I² ranged from 0% to 97%).

Conclusion: Most studies were assessed as having a high overall risk of bias. Only eight prediction models for GDM have been externally validated at least three times. Future research needs to focus on updating and externally validating existing models.

Background: The interaction between type 2 diabetes mellitus (T2DM) and cardiometabolic morbidity and mortality stems from the progressive nature of inflammation underpinning both diseases. Exercise training is considered an effective treatment strategy for T2DM and cardiometabolic diseases.

Objective: The current systematic review and meta-analysis investigated the effects of exercise training on inflammatory and cardiometabolic risk biomarkers in patients with T2DM.

Data sources: Electronic databases (PubMed/Medline, Embase, Cochrane Library, CINAHL, Google Scholar, Scopus, and Web of Science) were searched for randomized controlled trials (RCTs) from inception to January 2022. We used random effects models to estimate weighted mean differences with 95% confidence intervals.

Study selection: Twenty-five RCTs were included (N = 1257 participants; mean age = 52 years). Included studies had moderate to good overall methodological quality (TESTEX = 9 (range 7-13).

Results: Meta-analysis indicated that exercise training significantly increased adiponectin and decreased fasting insulin, homeostatic model assessment for insulin resistance, tumor necrosis factor-α, interleukin-6, and C-reactive protein (ps ≤ 0.05). Subgroup analysis by type of training indicated that aerobic exercise had the most consistent beneficial effects as compared to other types of exercise training; however, there was high heterogeneity among studies.

Conclusion: Different types of exercise training increase adiponectin levels and decrease pro-inflammatory cytokines such as TNF-α, IL-6, and CRP, as well as fasting insulin and insulin resistance markers in patients with T2DM. However, these effects were not beneficial for more commonly measured cardiometabolic risk factors (i.e., lipid profiles). Additional relevant clinical trials are required to confirm these results.

Trial registration: This systematic review and meta-analysis was prospectively registered in the PROSPERO database (CRD42022307396).