Nevin Manimala

PLoS One. 2021 Aug 2;16(8):e0253294. doi: 10.1371/journal.pone.0253294. eCollection 2021.

ABSTRACT

Due to various human activities, soil quality under different land use patterns is deteriorating all over the world. This deterioration is very complex in the river irrigation area and is caused by multi-point and non-point source pollution and seasonal variation. Therefore, the characteristics and sources of soil metal pollution in river irrigation area of Baoji city were analyzed. The contents of 8 metals were given by ICP-MS, in the soil samples. Statistical methods, geo-accumulation index (Igeo) and potential ecological risk index (RI) were conducted to evaluate the spatial distribution features, sources and ecological risks of metal contamination from the study area soil. Principal component analysis and cluster analysis were used to analyze the pollution sources of metal. The analysis showed that Cd is the most polluted, and human activities represented a great impact on the contents of Zn, Ni, Cu and Cd in soil, Cd post moderate-strong pollution and strong risk, Cd has a maximum Igeo value of 3.17. All rivers were at risk of moderate pollution levels in study. Among them, some rivers had even reached strong pollution level. Pollution caused by human activities was the most significant pollution source of metal in the research area soil.

PMID:34339446 | DOI:10.1371/journal.pone.0253294

PLoS One. 2021 Aug 2;16(8):e0255261. doi: 10.1371/journal.pone.0255261. eCollection 2021.

ABSTRACT

RATIONALE: Clinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials.

OBJECTIVES: To assess the effectiveness and efficiency of Asthma-Guidance and Prediction System (A-GPS), an Artificial Intelligence (AI)-assisted CDS tool, in optimizing asthma management through a randomized clinical trial (RCT).

METHODS: This was a single-center pragmatic RCT with a stratified randomization design conducted for one year in the primary care pediatric practice of the Mayo Clinic, MN. Children (<18 years) diagnosed with asthma receiving care at the study site were enrolled along with their 42 primary care providers. Study subjects were stratified into three strata (based on asthma severity, asthma care status, and asthma diagnosis) and were blinded to the assigned groups.

MEASUREMENTS: Intervention was a quarterly A-GPS report to clinicians including relevant clinical information for asthma management from EHRs and machine learning-based prediction for risk of asthma exacerbation (AE). Primary endpoint was the occurrence of AE within 1 year and secondary outcomes included time required for clinicians to review EHRs for asthma management.

MAIN RESULTS: Out of 555 participants invited to the study, 184 consented for the study and were randomized (90 in intervention and 94 in control group). Median age of 184 participants was 8.5 years. While the proportion of children with AE in both groups decreased from the baseline (P = 0.042), there was no difference in AE frequency between the two groups (12% for the intervention group vs. 15% for the control group, Odds Ratio: 0.82; 95%CI 0.374-1.96; P = 0.626) during the study period. For the secondary end points, A-GPS intervention, however, significantly reduced time for reviewing EHRs for asthma management of each participant (median: 3.5 min, IQR: 2-5), compared to usual care without A-GPS (median: 11.3 min, IQR: 6.3-15); p<0.001). Mean health care costs with 95%CI of children during the trial (compared to before the trial) in the intervention group were lower than those in the control group (-$1,036 [-$2177, $44] for the intervention group vs. +$80 [-$841, $1000] for the control group), though there was no significant difference (p = 0.12). Among those who experienced the first AE during the study period (n = 25), those in the intervention group had timelier follow up by the clinical care team compared to those in the control group but no significant difference was found (HR = 1.93; 95% CI: 0.82-1.45, P = 0.10). There was no difference in the proportion of duration when patients had well-controlled asthma during the study period between the intervention and the control groups.

CONCLUSIONS: While A-GPS-based intervention showed similar reduction in AE events to usual care, it might reduce clinicians’ burden for EHRs review resulting in efficient asthma management. A larger RCT is needed for further studying the findings.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02865967.

PMID:34339438 | DOI:10.1371/journal.pone.0255261

PLoS One. 2021 Aug 2;16(8):e0253873. doi: 10.1371/journal.pone.0253873. eCollection 2021.

ABSTRACT

Online social networks like Twitter and Facebook are among the most popular sites on the Internet. Most online social networks involve some specific features, including reciprocity, transitivity and degree heterogeneity. Such networks are so called scale-free networks and have drawn lots of attention in research. The aim of this paper is to develop a novel methodology for directed network embedding within the latent space model (LSM) framework. It is known, the link probability between two individuals may increase as the features of each become similar, which is referred to as homophily attributes. To this end, penalized pair-specific attributes, acting as a distance measure, are introduced to provide with more powerful interpretation and improve link prediction accuracy, named penalized homophily latent space models (PHLSM). The proposed models also involve in-degree heterogeneity of directed scale-free networks by embedding with the popularity scales. We also introduce LASSO-based PHLSM to produce an accurate and sparse model for high-dimensional covariates. We make Bayesian inference using MCMC algorithms. The finite sample performance of the proposed models is evaluated by three benchmark simulation datasets and two real data examples. Our methods are competitive and interpretable, they outperform existing approaches for fitting directed networks.

PMID:34339437 | DOI:10.1371/journal.pone.0253873

PLoS One. 2021 Aug 2;16(8):e0255128. doi: 10.1371/journal.pone.0255128. eCollection 2021.

ABSTRACT

OBJECTIVE: To assess the effectiveness of mindfulness-based interventions on people with dementia and mild cognitive impairment.

METHODS: We searched several electronic databases, namely Cochrane Library, EMBASE, and MEDLINE with no limitations for language or document type (last search: 1 February 2020). Randomized controlled trials of mindfulness-based interventions for people with dementia and mild cognitive impairment compared to active-control interventions, waiting lists, or treatment as usual were included. Predefined outcomes were anxiety symptoms, depressive symptoms, cognitive function, quality of life, mindfulness, ADL and attrition. We used the random effects model (DerSimonian-Laird method) for meta-analysis, reporting effect sizes as Standardized Mean Difference. Heterogeneity was assessed with the I2 statistics.

RESULTS: Eight randomized controlled trials, involving 276 patients, met the eligibility criteria and were included in the meta-analysis. We found no significant effects for mindfulness-based interventions in either the short-term or the medium- to long-term on any outcomes, when compared with control conditions. The number of included studies and sample sizes were too small. Additionally, the quality of evidence was low for each randomized controlled trial included in the analysis. This is primarily due to lack of intent-to-treat analysis, high risk of bias, and imprecise study results. The limited statistical power and weak body of evidence prevented us from reaching firm conclusions.

CONCLUSIONS: We found no significant effects of mindfulness-based interventions on any of the outcomes when compared with control conditions. The evidence concerning the efficacy of mindfulness-based interventions in this population is scarce in terms of both quality and quantity. More well-designed, rigorous, and large-scale randomized controlled trials are needed.

PMID:34339428 | DOI:10.1371/journal.pone.0255128

PLoS Comput Biol. 2021 Aug 2;17(8):e1009266. doi: 10.1371/journal.pcbi.1009266. Online ahead of print.

ABSTRACT

It is of great interest and potential to discover causal relationships between pairs of exposures and outcomes using genetic variants as instrumental variables (IVs) to deal with hidden confounding in observational studies. Two most popular approaches are Mendelian randomization (MR), which usually use independent genetic variants/SNPs across the genome, and transcriptome-wide association studies (TWAS) (or their generalizations) using cis-SNPs local to a gene (or some genome-wide and likely dependent SNPs), as IVs. In spite of their many promising applications, both approaches face a major challenge: the validity of their causal conclusions depends on three critical assumptions on valid IVs, and more generally on other modeling assumptions, which however may not hold in practice. The most likely as well as challenging situation is due to the wide-spread horizontal pleiotropy, leading to two of the three IV assumptions being violated and thus to biased statistical inference. More generally, we’d like to conduct a goodness-of-fit (GOF) test to check the model being used. Although some methods have been proposed as being robust to various degrees to the violation of some modeling assumptions, they often give different and even conflicting results due to their own modeling assumptions and possibly lower statistical efficiency, imposing difficulties to the practitioner in choosing and interpreting varying results across different methods. Hence, it would help to directly test whether any assumption is violated or not. In particular, there is a lack of such tests for TWAS. We propose a new and general GOF test, called TEDE (TEsting Direct Effects), applicable to both correlated and independent SNPs/IVs (as commonly used in TWAS and MR respectively). Through simulation studies and real data examples, we demonstrate high statistical power and advantages of our new method, while confirming the frequent violation of modeling (including valid IV) assumptions in practice and thus the importance of model checking by applying such a test in MR/TWAS analysis.

PMID:34339418 | DOI:10.1371/journal.pcbi.1009266

Aging (Albany NY). 2021 Aug 2;13(undefined). doi: 10.18632/aging.203361. Online ahead of print.

ABSTRACT

Parkinson’s disease (PD), the typical neurodegenerative disease, is characterized by the progressive loss of dopaminergic neurons in the substantia nigra (SN). However, no therapeutic agent used currently could slow down neuronal cell loss so as to decelerate or halt the progression of PD. Traditional Chinese medicine (TCM) has been utilized to treat the dysfunction of the autonomic nervous system. Wen-Shen-Yang-Gan decoction (WSYGD) has a good effect on the clinical treatment of PD with constipation. However, it is not clear which ingredients and what mechanism are responsible for the therapeutic effect. In this study, the pharmacodynamic study of WSYGD in PD mice was applied. Concurrently, a novel method for the identification of metabolic profiles of WSYGD has been developed. Finally, we found that WSYGD could protect the PD mice induced by rotenone. The underlying mechanism of the protective effect may be related to the reduction of the DA neurons apoptosis via reducing inflammatory reaction. By virtue of UPLC-MS and chemoinformatics method, 35 prototype compounds and 27 metabolites were filtered out and tentatively characterized. In conclusion, this study provides an insight into the metabolism of WSYGD in vivo to enable understanding of the metabolic process and therapeutic mechanism of PD.

PMID:34339394 | DOI:10.18632/aging.203361

Am J Trop Med Hyg. 2021 Aug 2:tpmd210377. doi: 10.4269/ajtmh.21-0377. Online ahead of print.

ABSTRACT

Ivermectin (IVM) is a widely used anthelmintic. However, with widespread use comes the risk of the emergence of IVM resistance, particularly in strongyloidiasis. Adenosine triphosphate (ATP)-binding cassette (ABC) transporter genes play an important role in the IVM-resistance mechanism. Here, we aimed to establish an animal experimental model of IVM resistance by frequent treatment of Strongyloides ratti with subtherapeutic doses of IVM, resistance being evaluated by the expression levels of ABC transporter genes. Rats infected with S. ratti were placed in experimental groups as follows: 1) untreated control (control); 2) treated with the mutagen ethyl methanesulfonate (EMS); 3) injected with 100 µg/kg body weight of IVM (IVM); 4) treated with a combination of EMS and IVM (IVM+EMS). Parasites were evaluated after four generations. Extent of IVM resistance was assessed using IVM sensitivity, larval development, and expression of ABC genes. By the F4 generation, S. ratti in the IVM group exhibited significantly higher levels of IVM resistance than did other groups according to in vitro drug-sensitivity tests and inhibition of larval development (IC50 = 36.60 ng/mL; 95% CI: 31.6, 42.01). Expression levels of ABC isoform genes (ABCA, ABCF, and ABCG) were statistically significantly higher in the IVM-resistant line compared with the susceptible line. In conclusion, IVM subtherapeutic doses induced IVM resistance in S. ratti by the F4 generation with corresponding upregulation of some ABC isoform genes. The study provides a model for inducing and assessing drug resistance in Strongyloides.

PMID:34339389 | DOI:10.4269/ajtmh.21-0377

J Cardiovasc Surg (Torino). 2021 Aug 2. doi: 10.23736/S0021-9509.21.11945-7. Online ahead of print.

ABSTRACT

BACKGROUND: Aortic and mitral valve replacement are commonly performed by cardiovascular surgeons, but little data quantitatively analyzes the etiology and prevalence of medical malpractice litigations involving these operations. This study aims to analyze incidence, cause, and resolution of medical malpractice lawsuits involving aortic and mitral valve replacements, alone and in combination with coronary artery bypass and/or aortic procedures.

METHODS: The Westlaw legal database was utilized to compile relevant litigations across the United States from 1994-2019. Clinical data, verdict data, demographic data, and litigation attributes were compiled. Fisher-exact tests and Mann-Whitney tests were performed for statistical analyses.

RESULTS: One hundred four malpractice litigations involving aortic valve replacement and 55 litigations involving mitral valve replacement were included in this analysis. The mean age of patients was 55.2 years and proportion of female patients was 32.7% in aortic valve replacements litigations, compared to a mean age of 54.1 years and female patients in 61.8% of mitral valve replacements litigations. Significant relationships exist between an alleged failure to monitor the patient and defendant verdicts (p=0.01), delayed treatment and defendant verdicts (p=0.04), and incidence of infective endocarditis and plaintiff verdicts (p=0.04) in aortic valve replacement litigations. Similarly, significant relationships exist between an alleged failure to diagnose and settlement verdicts (p=0.047), and stroke incidence and defendant verdicts (p=0.03) in mitral valve replacement litigations.

CONCLUSIONS: In addition to excellent surgeon patient/family communication, administering surgical treatment in a timely manner, diagnosing and acting on concomitant medical conditions, and close patient monitoring may diminish medical malpractice litigation involving aortic and mitral valve replacement operations.

PMID:34338496 | DOI:10.23736/S0021-9509.21.11945-7

Minerva Cardiol Angiol. 2021 Aug 2. doi: 10.23736/S2724-5683.21.05709-4. Online ahead of print.

ABSTRACT

This paper reviews recent cardiology literature and reports how Artificial Intelligence Tools (specifically, Machine Learning techniques) are being used by physicians in the field. Each technique is introduced with enough details to allow the understanding of how it works and its intent, but without delving into details that do not add immediate benefits and require expertise in the field. We specifically focus on the principal Machine Learning based risk scores used in cardiovascular research. After introducing them and summarizing their assumptions and biases, we discuss their merits and shortcomings. We report on how frequently they are adopted in the field and suggest why this is the case based on our expertise in Machine Learning. We complete the analysis by reviewing how corresponding statistical approaches compare with them. Finally, we discuss the main open issues in applying Machine Learning tools to cardiology tasks, also drafting possible future directions. Despite the growing interest in these tools, we argue that there are many still underutilized techniques: while Neural Networks are slowly being incorporated in cardiovascular research, other important techniques such as Semi-Supervised Learning and Federated Learning are still underutilized. The former would allow practitioners to harness the information contained in large datasets that are only partially labeled, while the latter would foster collaboration between institutions allowing building larger and better models.

PMID:34338485 | DOI:10.23736/S2724-5683.21.05709-4

JBRA Assist Reprod. 2021 Aug 2;0(0):0. doi: 10.5935/1518-0557.20210033. Online ahead of print.

ABSTRACT

OBJECTIVE: To determine the length of exposure to high doses of phthalate that might affect sperm quality in adult male Wistar rats.

METHODS: Forty-two (42) adult male Wistar rats (weighing 150-200 g) were randomly assigned into six groups (n=7): Group A received 0.5 mL of distilled water – placebo – and served as controls; groups B, C, D, E and F received Phthalate (750 mg/kgbw) for 1, 3, 5, 7 and 9 weeks, respectively. The data obtained from the study was expressed as Mean ± SEM with a p-value <0.05 considered significant. The data was analyzed with one-way analysis of variance (ANOVA) followed by Tukey’s post-hoc test using GraphPad Prism, version 8.

RESULTS: The results showed a statistically significant (p<0.05) decrease in testicular weight in the rats exposed to 750 mg/kg of phthalate for 3, 5, 7 and 9 weeks when compared with the controls. Sperm count, motility and viability were also significantly (p<0.05) reduced, while sperm cells with abnormal morphology had increased counts in the groups exposed for 3, 5, 7 and 9 weeks when compared with controls. Serum zinc and magnesium were also significantly reduced (p<0.05) in the subjects treated for 1, 3, 5, 7 and 9 weeks when compared with controls.

CONCLUSIONS: The dosage of phthalate adopted in this study was deleterious to testicular function when rats were exposed to it for as short a period as three weeks.

PMID:34338483 | DOI:10.5935/1518-0557.20210033