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Nevin Manimala Statistics

Consumption of Olive Oil and Diet Quality and Risk of Dementia-Related Death

JAMA Netw Open. 2024 May 1;7(5):e2410021. doi: 10.1001/jamanetworkopen.2024.10021.

ABSTRACT

IMPORTANCE: Age-standardized dementia mortality rates are on the rise. Whether long-term consumption of olive oil and diet quality are associated with dementia-related death is unknown.

OBJECTIVE: To examine the association of olive oil intake with the subsequent risk of dementia-related death and assess the joint association with diet quality and substitution for other fats.

DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study examined data from the Nurses’ Health Study (NHS; 1990-2018) and Health Professionals Follow-Up Study (HPFS; 1990-2018). The population included women from the NHS and men from the HPFS who were free of cardiovascular disease and cancer at baseline. Data were analyzed from May 2022 to July 2023.

EXPOSURES: Olive oil intake was assessed every 4 years using a food frequency questionnaire and categorized as (1) never or less than once per month, (2) greater than 0 to less than or equal to 4.5 g/d, (3) greater than 4.5 g/d to less than or equal to 7 g/d, and (4) greater than 7 g/d. Diet quality was based on the Alternative Healthy Eating Index and Mediterranean Diet score.

MAIN OUTCOME AND MEASURE: Dementia death was ascertained from death records. Multivariable Cox proportional hazards regressions were used to estimate hazard ratios (HRs) and 95% CIs adjusted for confounders including genetic, sociodemographic, and lifestyle factors.

RESULTS: Of 92 383 participants, 60 582 (65.6%) were women and the mean (SD) age was 56.4 (8.0) years. During 28 years of follow-up (2 183 095 person-years), 4751 dementia-related deaths occurred. Individuals who were homozygous for the apolipoprotein ε4 (APOE ε4) allele were 5 to 9 times more likely to die with dementia. Consuming at least 7 g/d of olive oil was associated with a 28% lower risk of dementia-related death (adjusted pooled HR, 0.72 [95% CI, 0.64-0.81]) compared with never or rarely consuming olive oil (P for trend < .001); results were consistent after further adjustment for APOE ε4. No interaction by diet quality scores was found. In modeled substitution analyses, replacing 5 g/d of margarine and mayonnaise with the equivalent amount of olive oil was associated with an 8% (95% CI, 4%-12%) to 14% (95% CI, 7%-20%) lower risk of dementia mortality. Substitutions for other vegetable oils or butter were not significant.

CONCLUSIONS AND RELEVANCE: In US adults, higher olive oil intake was associated with a lower risk of dementia-related mortality, irrespective of diet quality. Beyond heart health, the findings extend the current dietary recommendations of choosing olive oil and other vegetable oils for cognitive-related health.

PMID:38709531 | DOI:10.1001/jamanetworkopen.2024.10021

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Nevin Manimala Statistics

Doubly Robust Causal Modeling to Evaluate Device Implantation

JAMA Intern Med. 2024 May 6. doi: 10.1001/jamainternmed.2024.1181. Online ahead of print.

NO ABSTRACT

PMID:38709499 | DOI:10.1001/jamainternmed.2024.1181

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Nevin Manimala Statistics

Learning Morphological, Spatial, and Dynamic Models of Cellular Components

Methods Mol Biol. 2024;2800:231-244. doi: 10.1007/978-1-0716-3834-7_16.

ABSTRACT

In this chapter, we describe protocols for using the CellOrganizer software on the Jupyter Notebook platform to analyze and model cell and organelle shape and spatial arrangement. CellOrganizer is an open-source system for using microscope images to learn statistical models of the structure of cell components and how those components are organized relative to each other. Such models capture the statistical variation in the organization of cellular components by jointly modeling the distributions of their number, shape, and spatial distributions. These models can be created for different cell types or conditions and compared to reflect differences in their spatial organizations. The models are also generative, in that they can be used to synthesize new cell instances reflecting what a model learned and to provide well-structured cell geometries that can be used for biochemical simulations.

PMID:38709488 | DOI:10.1007/978-1-0716-3834-7_16

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Nevin Manimala Statistics

Author Correction: Discovering trends of social interaction behavior over time: An introduction to relational event modeling

Behav Res Methods. 2024 May 6. doi: 10.3758/s13428-024-02423-2. Online ahead of print.

NO ABSTRACT

PMID:38709453 | DOI:10.3758/s13428-024-02423-2

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Nevin Manimala Statistics

Influence of UGT2B7, UGT1A4 and ABCG2 Polymorphisms on the Pharmacokinetics and Therapeutic Efficacy of Lamotrigine in Patients with Epilepsy

Eur J Drug Metab Pharmacokinet. 2024 May 6. doi: 10.1007/s13318-024-00894-4. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: A substantial inter-individual variability has been observed in the pharmacokinetics of lamotrigine. The aim of the study was to investigate the impact of genetic polymorphism of the metabolizing enzymes (UGT2B7, UGT1A4) and transporter (ABCG2) on the pharmacokinetics and therapeutic efficacy of lamotrigine in patients with epilepsy.

METHODS: The genetic analysis of single-nucleotide polymorphisms was conducted using polymerase chain reaction sequence. High-performance liquid chromatography/tandem mass spectrometry was employed to measure the plasma concentrations of lamotrigine. The efficacy of lamotrigine was assessed by evaluating the reduction rate of epileptic seizure frequency.

RESULTS: This study included a cohort of 331 patients who were treated with lamotrigine as monotherapy. A linear correlation was observed between the lamotrigine concentration and daily dose taken (r = 0.58, p < 2.2e-16). Statistically significant differences were found in both the median plasma concentration and dose-adjusted concentration (C/D ratio) when comparing the ineffective to the effective group (p < 0.05). Multivariate analysis showed that UGT1A4 rs2011425, ABCG2 rs2231142 polymorphisms and age had a significant relationship with the lamotrigine concentrations (p < 0.05). Age was a predictive factor for C/D ratio (p < 0.001). Lamotrigine concentration and weight were good predictive factors for effective seizure outcomes (odds ratio [OR] = 0.715, 95% CI 0.658-0.776, p < 0.001; OR = 0.926, 95% CI 0.901-0.951, p < 0.001, respectively). The cut-off values of lamotrigine trough concentrations for clinical outcomes in the age-related groups were determined as 2.49 μg/ml (area under the receiver-operating characteristic curve [AUC]: 0.828, 95% CI 0.690-0.966), 2.70 μg/ml (AUC: 0.805, 95% CI 0.745-0.866) and 3.25 μg/ml (AUC: 0.807, 95% CI 0.686-0.928) for the adult group, adolescent group, and toddler and school-age group, respectively.

CONCLUSIONS: UGT1A4 rs2011425 and ABCG2 rs2231142 were correlated with lamotrigine concentrations. Lower lamotrigine trough concentration was found in the ineffective group and the troughs were associated with seizure outcomes.

PMID:38709450 | DOI:10.1007/s13318-024-00894-4

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Nevin Manimala Statistics

Real-World Clinical Burden of Newly Diagnosed Heart failure in Thai Patients

Cardiol Ther. 2024 May 6. doi: 10.1007/s40119-024-00366-5. Online ahead of print.

ABSTRACT

INTRODUCTION: There are limited data on the burden of newly diagnosed patients with heart failure (HF) in Thailand. Thus, this study aimed to fully understand the hospitalization, rehospitalization, mortality rates, demographics and characteristics, and quality of care in these patients.

METHOD: A retrospective review of all eligible adult patients’ medical records from 2018 and 2019 was conducted at five hospitals. The patients were newly diagnosed with HF, as indicated by the International Classification of Diseases (ICD)-10 code “I50.” Descriptive statistics was used to investigate patients’ hospital burden and clinical outcome data.

RESULTS: There were 1134 patients newly diagnosed with HF, classified as HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF), and HF with mildly reduced ejection fraction (HFmrEF) (44.0, 40.0, and 16.0%, respectively). The male-to-female ratios in HFmrEF and HFpEF were similar. In contrast, the proportion of men with HFrEF was greater. The mean age of all patients was 66.0 years. The hospitalization rate was 1.3. Rehospitalization rates for HF-related issues were 0.1, 0.2, 0.4, and 0.5 at 30 days, 60 days, 180 days, and 1 year, respectively. The percentage of deaths from all causes among these patients was 9.8%, while the percentage of deaths from cardiovascular-related causes was 8.5%. Only a small proportion of patients received a target dose of guideline-directed medical therapy (GDMT).

CONCLUSIONS: The study revealed that the characteristics, hospitalization rate for HF, and in-hospital mortality rate among newly diagnosed patients with HF were higher compared to similar studies conducted in Thailand and other countries. Moreover, a high quality of care is needed to improve the morbidity and mortality associated with HF in Thailand.

PMID:38709436 | DOI:10.1007/s40119-024-00366-5

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Nevin Manimala Statistics

Efficacy and Safety of Monoclonal Antibodies for the Treatment of Eosinophilic Esophagitis: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Dig Dis Sci. 2024 May 6. doi: 10.1007/s10620-024-08413-w. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Monoclonal antibodies (MAbs) have clinical benefits for treating several atopic diseases. However, consensus on its use for eosinophilic esophagitis (EoE) is lacking. The present meta-analysis aimed to compare the efficacy and safety of MAbs versus placebo for treating EoE.

METHODS: We searched PubMed, Embase, and Cochrane Library for randomized controlled trials (RCTs). The primary outcomes were changes in peak esophageal eosinophils count/high power field (HPF) and mean esophageal eosinophils count/HPF. The secondary outcomes were changes in the EoE-Histology Scoring System (EoE-HSS), Endoscopic Reference Score (EREFS), dysphagia score, and adverse events (AEs). We compared binary outcomes using risk ratio (RR) and continuous outcomes using mean difference (MD) or standardized mean difference (SMD), with 95% confidence interval (CI). Considering the diversity of mechanistic properties of MAbs, a pre-specified subgroup analysis by MAb mechanism of action was performed for all outcomes, provided that at least two studies were in each subgroup. Heterogeneity was assessed using Cochran’s Q test and I2 statistics.

RESULTS: 6 RCTs were included (533 patients). Compared to placebo, MAbs led to a significant reduction in peak esophageal eosinophils count/HPF (MD -0.78; CI 95% -0.87, -0.6801) and mean esophageal eosinophils count/HPF (SMD -0.79; CI 95% -1.5, -0.08). Moreover, MAbs significantly reduced EoE-HSS scores (grade score: SMD -9.31; 95% CI -13.95, -4.6701; stage score: SMD -10.18; 95% CI -15.06, -5.31), EREFS (SMD -5.95; CI 95% -9.19, -2.71) and dysphagia score (SMD -1.79; CI 95% -3.36, -0.23) without increasing AEs compared to placebo. Among those MAbs whose mechanism of action includes the blockage of the receptor for IL-13 (Dupilumab, QAX576, and RPC4046), the scores of EoE-HSS grade, EoE-HSS stage, EREFS, and dysphagia were significantly reduced, and they presented a similar risk of overall and serious AEs compared to placebo.

CONCLUSION: MAbs seem effective and safe in reducing esophageal eosinophil infiltrate, EoE-HSS score, EREFS score, and dysphagia symptoms in patients with EoE. However, further evidence is needed to establish its place in EoE management.

PMID:38709421 | DOI:10.1007/s10620-024-08413-w

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Nevin Manimala Statistics

Moss as a passive biomonitoring tool for the atmospheric deposition and spatial distribution pattern of toxic metals in an industrial city

Environ Monit Assess. 2024 May 6;196(6):513. doi: 10.1007/s10661-024-12696-x.

ABSTRACT

Anthropogenic pollution impacts human and environmental health, climate change, and air quality. Karabük, an industrial area from the Black Sea Region in northern Türkiye, is vulnerable to environmental pollution, particularly soil and air. In this research on methodological aspects, we analyzed the concentrations of six potential toxic metals in the atmospheric deposition of the city using the passive method of moss biomonitoring. The ground-growing terrestrial moss, Hypnum cupressiforme Hedw., was collected during the dry season of August 2023 at 20 urban points. The concentrations of Cr, Cu, Cd, Ni, Pb, and Co were determined in mosses by the ICP-MS method. Descriptive statistical analysis was employed to evaluate the status and variance in the spatial distribution of the studied metals, and multivariate analysis, Pearson correlation, and cluster analysis were used to investigate the associations of elements and discuss the most probable sources of these elements in the study area. Cd and Co showed positive and significant inter-element correlations (r > 0.938), representing an anthropogenic association mostly present in the air particles emitted from several metal plants. The results showed substantial impacts from local industry, manufactured activity, and soil dust emissions. Steel and iron smelter plants and cement factories are the biggest emitters of trace metals in the Karabük area and the primary sources of Cr, Cd, Ni, and Co deposition.

PMID:38709416 | DOI:10.1007/s10661-024-12696-x

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Nevin Manimala Statistics

Enhancing biomethanation performance through co-digestion of diverse organic wastes: a comprehensive study on substrate optimization, inoculum selection, and microbial community analysis

Environ Sci Pollut Res Int. 2024 May 6. doi: 10.1007/s11356-024-33557-7. Online ahead of print.

ABSTRACT

A blend of organic municipal solid waste, slaughterhouse waste, fecal sludge, and landfill leachate was selected in different mixing ratios to formulate the best substrate mixture for biomethanation. Individual substrates were characterized, and the mixing ratio was optimized with the help of a response surface methodology tool to a value of 1:1:1:1 (with a C/N ratio of 28±0.769 and total volatile fatty acid (VFA) concentration of 2500±10.53 mg/L) to improve the overall biomethanation. The optimized blend (C/N ratio: 28.6, VFA: 2538 mg/L) was characterized for physicochemical, biological, and microbial properties and subjected to anaerobic digestion in lab-scale reactors of 1000 mL capacity with and without the addition of inoculum. The biogas yield of individual substrates and blends was ascertained separately. The observed cumulative biogas yield over 21 days from the non-inoculated substrates varied between 142±1.95 mL (24.6±0.3 ml/gVS) and 1974.5±21.72 mL (270.4±3.1 ml/gVS). In comparison, the addition of external inoculation at a 5% rate (w/w) of the substrate uplifted the minimum and maximum cumulative gas yield values to 203±9.9 mL (35.0±1.6 mL/gVS) and 3394±13.4 mL (315.3±1.2 mL/gVS), respectively. The inoculum procured from the Defence Research and Development Organisation (DRDO) was screened in advance, considering factors such as maximizing VFA production and consumption rate, biogas yield, and digestate quality. A similar outcome regarding biogas yield and digestate quality was observed for the equivalent blend. The cumulative gas yield increased from 2673±14.5 mL (373.7±2.2 mL/gVS) to 4284±111.02 mL (391.47±20.02 mL/gVS) over 21 days post-application of a similar dosage of DRDO inoculum. The 16S rRNA genomic analysis revealed that the predominant bacterial population belonged to the phylum Firmicutes, with the majority falling within the orders Clostridiales and Lactobacillales. Ultimately, the study advocates the potential of the blend mentioned above for biomethanation and concomitant enrichment of both biogas yield and digestate quality.

PMID:38709410 | DOI:10.1007/s11356-024-33557-7

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Nevin Manimala Statistics

Can geomorphic flood descriptors coupled with machine learning models enhance in quantifying flood risks over data-scarce catchments? Development of a hybrid framework for Ganga basin (India)

Environ Sci Pollut Res Int. 2024 May 6. doi: 10.1007/s11356-024-33507-3. Online ahead of print.

ABSTRACT

Quantifying flood risks through a cascade of hydraulic-cum-hydrodynamic modelling is data-intensive and computationally demanding- a major constraint for economically struggling and data-scarce low and middle-income nations. Under such circumstances, geomorphic flood descriptors (GFDs), that encompass the hidden characteristics of flood propensity may assist in developing a nuanced understanding of flood risk management. In line with this, the present study proposes a novel framework for estimating flood hazard and population exposure by leveraging GFDs and Machine Learning (ML) models over severely flood-prone Ganga basin. The study incorporates SHapley Additive exPlanations (SHAP) values in flood hazard modeling to justify the degree of influence of each GFD on the simulated floodplain maps. A set of 15 relevant GFDs derived from high-resolution CartoDEM are forced to five state-of-the-art ML models; AdaBoost, Random Forest, GBDT, XGBoost, and CatBoost, for predicting flood extents and depths. To enumerate the performance of ML models, a set of twelve statistical metrics are considered. Our result indicates a superior performance of XGBoost (κ = 0.72 and KGE = 82%) over other ML models in flood extent and flood depth prediction, resulting in about 47% of the population exposure to high-flood risks. The SHAP summary plots reveal a pre-dominance of Height Above Nearest Drainage during flood depth prediction. The study contributes significantly in comprehending our understanding of catchment characteristics and its influence in the process of sustainable disaster risk reduction. The results obtained from the study provide valuable recommendations for efficient flood management and mitigation strategies, especially over global data-scarce flood-prone basins.

PMID:38709408 | DOI:10.1007/s11356-024-33507-3