Tag: pubmed

J Environ Manage. 2022 Sep 1;317:115464. doi: 10.1016/j.jenvman.2022.115464. Epub 2022 Jun 5.

ABSTRACT

Based on the panel data of 20 countries in EU during the period of 2007-2019, this paper study the effect of energy market integration (EMI) on renewable energy development (RED). We develop a general equilibrium model to explain how EMI affect the RED and the role of different mechanisms. The empirical results reports that the European EMI increased both the consumption and power generation of renewable energy, which proves a significant positive effect of EMI on the RED. In line with our expectations of theoretical model, our estimates show that the increase of renewable energy consumption is mainly due to the fossil energy cost increased, technology advancement and regional environmental regulation strengthening. And the fossil energy cost is the main driven force which plays a completely mediating role between EMI and RED. Furthermore, we also observe a negative effect of FDI and industry structure on RED.

PMID:35751265 | DOI:10.1016/j.jenvman.2022.115464

J Environ Manage. 2022 Sep 1;317:115484. doi: 10.1016/j.jenvman.2022.115484. Epub 2022 Jun 9.

ABSTRACT

Water conservation is vital to safeguard future water availability when natural resources like water become extremely scarce. It is fundamental to understand the significant determinants of water conservation activities which can also facilitate the implementation of appropriate policies for water demand management. Thus, the goal of this study was to determine the important social, psychological, and behavioral factors of water conservation behavior. A questionnaire survey was used to collect the data from 625 international students and employees from different universities in Japan. The structural equation modeling demonstrated that the proposed model explained 46% of the variation in water conservation behavior. Awareness of water issues was highly related to attitude, responsibility, and culture. Except for culture, attitude and responsibility were significantly connected with emotion. Finally, emotion, habit, culture and involvement were significantly and positively associated with water conservation behavior. These factors are incorporated for the first time in this study into a single model to better understand individual water conservation behavior. The sequential regression model showed that all determinants including demographic factors raised the variation’s proportion by 53% in water conservation. Female participants had a significantly higher positive attitude, emotion, and water conservation behavior than male participants. Older participants exhibited higher levels of awareness, habit, culture, and water conservation behavior when compared to younger people. Lastly, participants believed that the most dominant component in water conservation behavior was the awareness of water issues. These findings could assist policymakers in raising household awareness, accountability, and involvement towards water conservation efforts.

PMID:35751281 | DOI:10.1016/j.jenvman.2022.115484

J Environ Manage. 2022 Sep 1;317:115402. doi: 10.1016/j.jenvman.2022.115402. Epub 2022 Jun 14.

ABSTRACT

The process of extracting information from data generated in environmental monitoring programs is often carried out using statistical tools, with Statistical Process Control (SPC) showing great potential for application in environmental monitoring. In November 2015, millions of cubic metres of tailings were dumped into the basin of the River Doce with the collapse of the Fundão dam. A study of the impact of this incident requires new approaches in data monitoring and processing, so it was sought to evaluate, using SPC tools, changes in water quality in the basin of the River Doce following the collapse of the dam. Using process charts and the process capability index (PCI), water quality parameters in the Doce and Carmo rivers were evaluated between 2009 and 2020. There, turbidity has improved since 2018, and Mn since 2016. Control charts showed that by December 2020 dissolved Fe was still not within normal pre-event fluctuation patterns. The PCI value showed that the situation worsened after the event for each of the parameters, with the lowest values for Mn and E. coli. By using a reference period, SPC makes it possible to infer the permanence of the impact of extreme pollution on the waterbody, which can be used in the routine monitoring of water quality in such events.

PMID:35751244 | DOI:10.1016/j.jenvman.2022.115402

Comput Biol Med. 2022 Jul;146:105623. doi: 10.1016/j.compbiomed.2022.105623. Epub 2022 May 17.

ABSTRACT

The COVID-19 pandemic has changed the way we practice medicine. Cancer patient and obstetric care landscapes have been distorted. Delaying cancer diagnosis or maternal-fetal monitoring increased the number of preventable deaths or pregnancy complications. One solution is using Artificial Intelligence to help the medical personnel establish the diagnosis in a faster and more accurate manner. Deep learning is the state-of-the-art solution for image classification. Researchers manually design the structure of fix deep learning neural networks structures and afterwards verify their performance. The goal of this paper is to propose a potential method for learning deep network architectures automatically. As the number of networks architectures increases exponentially with the number of convolutional layers in the network, we propose a differential evolution algorithm to traverse the search space. At first, we propose a way to encode the network structure as a candidate solution of fixed-length integer array, followed by the initialization of differential evolution method. A set of random individuals is generated, followed by mutation, recombination, and selection. At each generation the individuals with the poorest loss values are eliminated and replaced with more competitive individuals. The model has been tested on three cancer datasets containing MRI scans and histopathological images and two maternal-fetal screening ultrasound images. The novel proposed method has been compared and statistically benchmarked to four state-of-the-art deep learning networks: VGG16, ResNet50, Inception V3, and DenseNet169. The experimental results showed that the model is competitive to other state-of-the-art models, obtaining accuracies between 78.73% and 99.50% depending on the dataset it had been applied on.

PMID:35751202 | DOI:10.1016/j.compbiomed.2022.105623

Comput Biol Med. 2022 Jul;146:105601. doi: 10.1016/j.compbiomed.2022.105601. Epub 2022 May 19.

ABSTRACT

BACKGROUND: The 2019 novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently a major challenge threatening the global healthcare system. Respiratory virus infection is the most common cause of asthma attacks, and thus COVID-19 may contribute to an increase in asthma exacerbations. However, the mechanisms of COVID-19/asthma comorbidity remain unclear.

METHODS: The “Limma” package or “DESeq2” package was used to screen differentially expressed genes (DEGs). Alveolar lavage fluid datasets of COVID-19 and asthma were obtained from the GEO and GSV database. A series of analyses of common host factors for COVID-19 and asthma were conducted, including PPI network construction, module analysis, enrichment analysis, inference of the upstream pathway activity of host factors, tissue-specific analysis and drug candidate prediction. Finally, the key host factors were verified in the GSE152418 and GSE164805 datasets.

RESULTS: 192 overlapping host factors were obtained by analyzing the intersection of asthma and COVID-19. FN1, UBA52, EEF1A1, ITGB1, XPO1, NPM1, EGR1, EIF4E, SRSF1, CCR5, PXN, IRF8 and DDX5 as host factors were tightly connected in the PPI network. Module analysis identified five modules with different biological functions and pathways. According to the degree values ranking in the PPI network, EEF1A1, EGR1, UBA52, DDX5 and IRF8 were considered as the key cohost factors for COVID-19 and asthma. The H₂O₂, VEGF, IL-1 and Wnt signaling pathways had the strongest activities in the upstream pathways. Tissue-specific enrichment analysis revealed the different expression levels of the five critical host factors. LY294002, wortmannin, PD98059 and heparin might have great potential to evolve into therapeutic drugs for COVID-19 and asthma comorbidity. Finally, the validation dataset confirmed that the expression of five key host factors were statistically significant among COVID-19 groups with different severity and healthy control subjects.

CONCLUSIONS: This study constructed a network of common host factors between asthma and COVID-19 and predicted several drugs with therapeutic potential. Therefore, this study is likely to provide a reference for the management and treatment for COVID-19/asthma comorbidity.

PMID:35751199 | DOI:10.1016/j.compbiomed.2022.105601

Comput Biol Med. 2022 Jul;146:105571. doi: 10.1016/j.compbiomed.2022.105571. Epub 2022 May 21.

ABSTRACT

BACKGROUND: COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wiliest high performance on lung segmentation and lesion localization.

METHOD: ology: The proposed study uses multicenter ∼9,000 CT slices from two different nations, namely, CroMed from Croatia (80 patients, experimental data), and NovMed from Italy (72 patients, validation data). We hypothesize that by using pruning and evolutionary optimization algorithms, the size of the AI models can be reduced significantly, ensuring optimal performance. Eight different pruning techniques (i) differential evolution (DE), (ii) genetic algorithm (GA), (iii) particle swarm optimization algorithm (PSO), and (iv) whale optimization algorithm (WO) in two deep learning frameworks (i) Fully connected network (FCN) and (ii) SegNet were designed. COVLIAS 2.0 was validated using “Unseen NovMed” and benchmarked against MedSeg. Statistical tests for stability and reliability were also conducted.

RESULTS: Pruning algorithms (i) FCN-DE, (ii) FCN-GA, (iii) FCN-PSO, and (iv) FCN-WO showed improvement in storage by 92.4%, 95.3%, 98.7%, and 99.8% respectively when compared against solo FCN, and (v) SegNet-DE, (vi) SegNet-GA, (vii) SegNet-PSO, and (viii) SegNet-WO showed improvement by 97.1%, 97.9%, 98.8%, and 99.2% respectively when compared against solo SegNet. AUC > 0.94 (p < 0.0001) on CroMed and > 0.86 (p < 0.0001) on NovMed data set for all eight EA model. PAI <0.25 s per image. DenseNet-121-based Grad-CAM heatmaps showed validation on glass ground opacity lesions.

CONCLUSIONS: Eight PAI networks that were successfully validated are five times faster, storage efficient, and could be used in clinical settings.

PMID:35751196 | DOI:10.1016/j.compbiomed.2022.105571

Nicotine Tob Res. 2022 Jun 24:ntac152. doi: 10.1093/ntr/ntac152. Online ahead of print.

ABSTRACT

INTRODUCTION: Anti-tobacco media campaigns can prevent youth smoking, but there is little research on how adult-targeted campaigns affect youth. We investigated the association between the Tips From Former Smokers (Tips) campaign and youth smoking behaviors and anti-tobacco attitudes, and variation by sex, race/ethnicity, or socioeconomic status (SES).

METHODS: We used data from the Monitoring the Future (MTF) study, a nationally representative survey on 8th, 10th, and 12th graders, from 2013-2015. Quartiles of Tips gross rating points (GRPs) were used to estimate exposure. Youth smoking behavior outcomes included smoking prevalence, initiation, and susceptibility. The anti-tobacco attitude outcomes included the extent that anti-tobacco ads made participants (a) less favorable towards smoking or (b) less likely to smoke cigarettes. Modified Poisson regression models estimated average marginal effects; separate additive interactions between Tips GRP exposure and sex, race/ethnicity, parents’ highest education, and college plans (12th graders only) were used to test for effect modification.

RESULTS: Tips GRPs were not associated with smoking behaviors within any grade. However, 12 th graders in the highest quartile of Tips had a 7.0 percentage point higher probability (95%CI=0.023-0.116) of responding that anti-tobacco ads made them less likely to smoke. Tips GRPs were associated with a lower probability of past 30-day smoking prevalence among 10 th grade females, but not males (joint p-value=0.002). No additional statistically significant interactions were found for any other outcomes for any grade.

CONCLUSIONS: This study revealed the potential for adult-targeted campaigns to increase youth’s anti-smoking attitudes, but campaign exposure was not associated with smoking behaviors.

IMPLICATIONS: Few studies have examined the potential for anti-smoking media campaigns to influence audiences outside their targeted audience. In this study, we show the potential for adult-targeted campaigns to impact youth and suggests that Tips exposure may promote anti-smoking attitudes among youth.

PMID:35749779 | DOI:10.1093/ntr/ntac152

ASAIO J. 2022 Jun 24. doi: 10.1097/MAT.0000000000001785. Online ahead of print.

ABSTRACT

This systematic review summarizes the major developments in extracorporeal membrane oxygenation (ECMO) circuitry in pediatrics over the past 20 years and demonstrates the impacts of those developments on clinical outcomes. This systematic review followed structured Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 1987 studies were retrieved, of which 82 were included in the final analysis. Over the past 20 years, ECMO pumps have shifted from roller pumps to centrifugal pumps. Silicone and polypropylene hollow fiber membrane oxygenators were initially used but have been replaced by polymethylpentene hollow fiber membrane oxygenators, with other ECMO components poorly reported. Considerable variability in mortality was found across studies and there was no statistical difference in mortality rates across different periods. The duration of ECMO and other outcome measures were inconsistently reported across studies. This systematic review demonstrated technological developments in pumps and oxygenators over the last two decades, although patient mortality rates remained unchanged. This could be because of ECMO support applied to patients in more critical conditions over the years. We also highlighted the limitations of methodology information disclosure and outcome measures in current ECMO studies, showing the need of reporting standardization for future ECMO studies.

PMID:35749749 | DOI:10.1097/MAT.0000000000001785

Psychiatr Genet. 2022 Jun 27. doi: 10.1097/YPG.0000000000000318. Online ahead of print.

ABSTRACT

OBJECTIVE: The SCHEMA consortium has identified 10 genes in which protein-truncating variants (PTVs) confer a substantial risk of schizophrenia. This study aimed to determine whether carrying these PTVs was associated with neuropsychiatric impairment in the general population.

METHODS: Phenotype fields of exome-sequenced participants in the UK Biobank who carried PTVs in these genes were studied to determine to what extent they demonstrated features of schizophrenia or had neuropsychiatric impairment.

RESULTS: Following automated quality control and visual inspection of reads, 251 subjects were identified as having well-supported PTVs in one of these genes. The frequency of PTVs in CACNA1G was higher than that had been observed in SCHEMA cases, casting doubt on its role in schizophrenia pathogenesis, but otherwise rates were similar to those observed in SCHEMA controls. Numbers were too small to allow formal statistical analysis but in general carriers of PTVs did not appear to have high rates of psychiatric illness or reduced educational or occupational functioning. One subject with a PTV in SETD1A had a diagnosis of schizophrenia, one with a PTV in HERC1 had psychotic depression and two subjects seemed to have developmental disorders, one with a PTV in GRIN2A and one with a PTV in RBCC1. There seemed to be somewhat increased rates of affective disorders among carriers of PTVs in HERC1 and RB1CC1.

CONCLUSION: Carriers of PTVs did not appear to have subclinical manifestations of schizophrenia. Although PTVs in these genes can substantially increase schizophrenia risk, their effect seems to be dichotomous and most carriers appear psychiatrically well. This research has been conducted using the UK Biobank Resource.

PMID:35749744 | DOI:10.1097/YPG.0000000000000318

Am J Hosp Palliat Care. 2022 Jun 24:10499091221110217. doi: 10.1177/10499091221110217. Online ahead of print.

ABSTRACT

OBJECTIVES: Our study sought to further characterize patterns of medical cannabis use in elderly cancer patients. Furthermore, we sought to assess efficacy of medical cannabis for the treatment of pain, nausea, anorexia, insomnia and anxiety in elderly cancer patients.

BACKGROUND: Medical cannabis use is growing for symptom management in cancer patients, but limited data exists on the safety or efficacy of use in elderly patients.

METHODS: A retrospective chart review assessing changes in numerical symptom scores reported at clinic visits before and after medical cannabis initiation.

RESULTS: There was no statistically significant difference in pain, nausea, appetite, insomnia or anxiety scores reported before and after initiation of medical cannabis. Oil was the most common form used, followed by vape, and the most common ratios used were high tetrahydrocannabinol (THC) to cannabidiol (CBD) and equal parts THC/CBD products.

CONCLUSION: This study did not find a statistically significant change in symptom scores with medical cannabis use, although further study is warranted given the limitations of the present study. Elderly patients most commonly are using equal parts THC/CBD or high THC ratio products initially.

PMID:35749740 | DOI:10.1177/10499091221110217