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  1. Observations on malnutrition and anti-TB drugs in Ghana
    Muyou AJ, Kunasagran PD, Syed Abdul Rahim SS, Avoi R, Hayati F
    Int J Tuberc Lung Dis, 2021 Sep 01;25(9):778-779.
    PMID: 34802506 DOI: 10.5588/ijtld.21.0258
    Matched MeSH terms: Humans
  2. Fulltext Metformin in COVID-19: clinical trials are needed to prove its benefits
    Kow CS, Ramachandram DS, Hasan SS
    Ir J Med Sci, 2022 Dec;191(6):2641-2642.
    PMID: 34997410 DOI: 10.1007/s11845-021-02869-9
    Matched MeSH terms: Humans
  3. Parametric and non-parametric convergence analysis of electricity intensity in developed and developing countries
    Solarin SA
    Environ Sci Pollut Res Int, 2019 Mar;26(9):8552-8574.
    PMID: 30706273 DOI: 10.1007/s11356-019-04225-y
    This paper examines the pattern of convergence in electricity intensity in a sample of 79 countries. We apply the residual augmented least squares regression to the convergence of energy intensity. This method has been used in the convergence of per capita energy consumption but not convergence of energy intensity. Furthermore, in contrast to the previous studies which mainly used the conventional beta convergence approach to examine conditional convergence, we use a beta convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma and gamma convergences of electricity intensity are also examined. In addition to the full sample of countries, we also examine convergence in African countries, Asian and Oceanic countries, American countries and European countries, separately. Convergences in OECD and non-OECD countries are also examined, separately. In the full sample, the results show convergence exists in 54% of the countries in the total sample. There is convergence in 65% of the African countries, 61% of the American countries, 43% of the Asian and Oceanic countries and 33% of the European countries. In terms of the regional classification, it is also observed that convergence exists for 58% of the non-OECD countries and 31% of the OECD countries. There is evidence for sigma convergence in all the blocs with the exception of European and non-OECD countries. With the exception of African countries, there is evidence for gamma convergence in all the countries and the various blocs. The policy implications of the results are discussed.
    Matched MeSH terms: Humans
  4. Occurrence and health risk assessment of arsenic and heavy metals in groundwater of three industrial areas in Delhi, India
    Alsubih M, El Morabet R, Khan RA, Khan NA, Ul Haq Khan M, Ahmed S, et al.
    Environ Sci Pollut Res Int, 2021 Nov;28(44):63017-63031.
    PMID: 34218378 DOI: 10.1007/s11356-021-15062-3
    Groundwater is a primary natural water source in the absence of surface water bodies. Groundwater in urban environments experiences unprecedented stress from urban growth, population increase, and industrial activities. This study assessed groundwater quality in terms of arsenic and heavy metal contamination in three industrial areas (Shahdara, Jhilmil, and Patparganj), Delhi, India. The water quality was assessed over a 3-year time interval (i.e., 2015 and 2018). The groundwater constituents investigated were As, Fe, Cr, Cd, Ni, Zn, Mn, Cu, and Pb. Metal index and heavy metal pollution indexes were estimated to assess groundwater pollution. The health risk was evaluated in terms of non-carcinogenic and carcinogenic risk assessment. Patparganj industrial area saw increment in concentration for Cu 0.23 mg/L (2015)-0.85 mg/L (2018), Zn 0.51 mg/L (2015)-7.2 mg/L (2018), Fe 0.32 mg/L (2015)-0.9 mg/L (2018), Cr 0.21 mg/L (2015)-0.26 mg/L (2018), Mn 0.14 mg/L (2015)-0.25 mg/L (2018), Ni 0.04 mg/L (2015)-0.34 mg/L (2018), and As 0.01 mg/L (2015)-0.18 mg/L (2018). Cd and Pb concentrations were observed to decrease by 40-90 % and 85-99% for all the three industrial areas. Metal index and heavy metal index values were found to be >1 for all locations. The risk quotient value > 1 was observed for all locations in the year 2015 but was found to increase further to a range of RQ 10-62 in the year 2018, inferring increased non-carcinogenic risk to consumers. The carcinogenic risk was significant with respect to Fe (0.2-0.7), Zn (0.001-0.007), and As (0.002-0.003) for all locations in the year 2015. This study concludes that groundwater in the three industrial areas is highly polluted and is not fit for human consumption. Further studies are required to explore possible control measures and develop methods to mitigate groundwater pollution, sustainable management, and optimized use to conserve it for future generations.
    Matched MeSH terms: Humans
  5. Global trends of textile waste research from 2005 to 2020 using bibliometric analysis
    Kasavan S, Yusoff S, Guan NC, Zaman NSK, Fakri MFR
    Environ Sci Pollut Res Int, 2021 Sep;28(33):44780-44794.
    PMID: 34235692 DOI: 10.1007/s11356-021-15303-5
    Researchers have broadly studied textile waste, but the research topics development and performance trends in this study area are still unclear. A bibliometric analysis was conducted to explore the global scientific literature to determine state of the art on textile waste over the past 16 years. Data of publications output are identified based on the Web of Science (from 2015 to 2020). This study used VOSviewer to analyse collaboration networks among authors, countries, institutions, and author's keywords in identifying five main clusters. A total of 3296 papers in textile waste research were identified. In this study, a total of 10451 authors were involved in textile waste research, and 36 authors among them published more than ten research publications in the period of this study. China has been in a top position in textile waste research moving from 3 output publications in 2005 to 91 output publications in 2020. Indian Institute of Technology System IIT System was ranked first in terms of the total publication number (85 publications, 2.45%). Textile wastewater and adsorption are the most commonly used keywords that reflect the current main research direction in this field and received more attention in recent years. Based on keyword cluster analysis outputs, textile waste research can be categorized into five types of clusters, namely (1) pollutant compositions, (2) component of textile wastewater, (3) treatment methods for textile wastewater, (4) effect mechanism of textile wastewater, and (5) recyclability of textile waste.
    Matched MeSH terms: Humans
  6. Towards achieving environmental sustainability: environmental quality versus economic growth in a developing economy on ecological footprint via dynamic simulations of ARDL
    Solarin SA, Nathaniel SP, Bekun FV, Okunola AM, Alhassan A
    Environ Sci Pollut Res Int, 2021 Apr;28(14):17942-17959.
    PMID: 33410031 DOI: 10.1007/s11356-020-11637-8
    Studies have shown that factors like trade, urbanization, and economic growth may increase the ecological footprint (EFP) since ecological distortions are mainly human-induced. Therefore, this study explores the effect of economic growth and urbanization on the EFP, accounting for foreign direct investment and trade in Nigeria, using data from 1977 to 2016. This study used the EFP variable as against the CO2 emissions used in the previous studies since the former is a more comprehensive and extensive measure of environmental quality. We apply the novel dynamic autoregressive distributed lag (ARDL) simulations for model estimation, the Bayer and Hanck J Time Ser Anal 34: 83-95, (2013) combined cointegration, and the ARDL bounds test for cointegration. Although the results affirmed the presence of long-run relationship among the variables, economic growth deteriorates the environment in the short run, while urbanization exacts no harmful impact. In the long run, FDI and trade deteriorate the environment while economic growth adds to environmental quality. It is recommended that policymakers strengthen the existing environmental regulations to curtail harmful trade and provide rural infrastructures to abate urban anomaly.
    Matched MeSH terms: Humans
  7. Does tradeoff between financial and social indicators matters in environmental consideration: evidence from G7 region
    Van Song N, Phuong NTM, Oanh TTK, Chien DH, Phuc VQ, Mohsin M
    Environ Sci Pollut Res Int, 2021 Apr;28(16):19911-19925.
    PMID: 33410000 DOI: 10.1007/s11356-020-12041-y
    The study tries to discover the impact of financial and social indicators' growth towards environmental considerations to understand the drivers of economic growth and carbon dioxide emissions change in G7 countries. The DEA-like composite index has been used to examine the tradeoff between financial and social indicator matters in environmental consideration by using a multi-objective goal programming approach. The data from 2008 to 2018 is collected from G-7 countries. The results from the DEA-like composite index reveals that there is a mixed condition of environmental sustainability in G-7 countries where the USA is performing better and Japan is performing worse among the set of other countries. The further result shows that the energy and fiscal indicators help to decrease the dangerous gas emissions. Divergent to that, the human and financial index positively contributes to greenhouse gas emissions. Fostering sustainable development is essential to successfully reduce emissions, meet established objectives, and ensure steady development. The study provides valuable information for policymakers.
    Matched MeSH terms: Humans
  8. Response to "Refer to the investigation of toxic elements in Carassius gibelio and Sinanodonta woodiana and its health risk to humans by Arumugam et al. (2020)" by Fakhri and Mousavi Khaneghah (2020) : Fakhri, Y., Mousavi Khaneghah, A. Refer to the investigation of toxic elements in Carassius gibelio and Sinanodonta woodiana and its health risk to humans by Arumugam et al. (2020). Environ Sci Pollut Res 27, 30901-30902 (2020)
    Arumugam A, Li J, Krishnamurthy P, Jia ZX, Leng Z, Ramasamy N, et al.
    Environ Sci Pollut Res Int, 2021 01;28(4):4883-4884.
    PMID: 32889655 DOI: 10.1007/s11356-020-10695-2
    Matched MeSH terms: Humans
  9. Sustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysia
    Mohd Azlan NNI, Abdul Malek M, Zolkepli M, Mohd Salim J, Ahmed AN
    Environ Sci Pollut Res Int, 2021 Apr;28(16):20261-20272.
    PMID: 33405154 DOI: 10.1007/s11356-020-11908-4
    Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at Kenyir Lake, Terengganu, using a fuzzy inference system (FIS). The analysis is widened by comparing FIS with the multiple linear regression (MLR) method. FIS applied as an analysis tool provides good generalization capability for optimum solutions and utilizes human behavior influenced by expert knowledge in water resources management for fuzzy rules specified in the system, whereas MLR can simultaneously adjust and compare several variables as per the needs of the study. The water demand dataset of Kenyir Lake was analyzed using FIS and MLR, resulting in total forecasted water consumptions at Kenyir Lake of 2314.38 m3 and 1358.22 m3, respectively. It is confirmed that both techniques converge close to the actual water consumption of 1249.98 m3. MLR showed the accuracy of the water demand values with smaller forecasted errors to be higher than FIS did. To attain sustainable water demand management, the techniques used can be examined extensively by researchers, educators, and learners by adding more variables, which will provide more anticipated outcomes.
    Matched MeSH terms: Humans
  10. Microplastic pollution in freshwater systems in Southeast Asia: contamination levels, sources, and ecological impacts
    Chen HL, Selvam SB, Ting KN, Gibbins CN
    Environ Sci Pollut Res Int, 2021 Oct;28(39):54222-54237.
    PMID: 34386926 DOI: 10.1007/s11356-021-15826-x
    Plastics are synthetic polymers known for their outstanding durability and versatility, and have replaced traditional materials in many applications. Unfortunately, their unique traits ensure that they pose a major threat to the environment. While literature on freshwater microplastic contamination has grown over the recent years, research undertaken in rapidly developing countries, where plastic production and use are increasing dramatically, has lagged behind that in other parts of the world. In the South East Asia (SEA) region, basic information on levels of contamination is very limited and, as a consequence, the risk to human and ecological health remains hard to assess. This review synthesises what is currently known about microplastic contamination of freshwater ecosystems in SEA, with a particular focus on Malaysia. The review 1) summarises published studies that have assessed levels of contamination in freshwater systems in SEA, 2) discusses key sources and transport pathways of microplastic in freshwaters, 3) outlines what is known of the impacts of microplastic on freshwater organisms, and 4) identifies key knowledge gaps related to our understanding of the transport, fate and effects of microplastic.
    Matched MeSH terms: Humans
  11. Fulltext Deciphering the role of nanoparticles for management of bacterial meningitis: an update on recent studies
    Sharma N, Zahoor I, Sachdeva M, Subramaniyan V, Fuloria S, Fuloria NK, et al.
    Environ Sci Pollut Res Int, 2021 Nov;28(43):60459-60476.
    PMID: 34545518 DOI: 10.1007/s11356-021-16570-y
    Meningitis is an inflammation of the protective membranes called meninges and fluid adjacent the brain and spinal cord. The inflammatory progression expands all through subarachnoid space of the brain and spinal cord and occupies the ventricles. The pathogens like bacteria, fungi, viruses, or parasites are main sources of infection causing meningitis. Bacterial meningitis is a life-threatening health problem that which needs instantaneous apprehension and treatment. Nesseria meningitidis, Streptococcus pneumoniae, and Haemophilus flu are major widespread factors causing bacterial meningitis. The conventional drug delivery approaches encounter difficulty in crossing this blood-brain barrier (BBB) and therefore are insufficient to elicit the desired pharmacological effect as required for treatment of meningitis. Therefore, application of nanoparticle-based drug delivery systems has become imperative for successful dealing with this deadly disease. The nanoparticles have ability to across BBB via four important transport mechanisms, i.e., paracellular transport, transcellular (transcytosis), endocytosis (adsorptive transcytosis), and receptor-mediated transcytosis. In this review, we reminisce distinctive symptoms of meningitis, and provide an overview of various types of bacterial meningitis, with a focus on its epidemiology, pathogenesis, and pathophysiology. This review describes conventional therapeutic approaches for treatment of meningitis and the problems encountered by them while transmitting across tight junctions of BBB. The nanotechnology approaches like functionalized polymeric nanoparticles, solid lipid nanoparticles, nanostructured lipid carrier, nanoemulsion, liposomes, transferosomes, and carbon nanotubes which have been recently evaluated for treatment or detection of bacterial meningitis have been focused. This review has also briefly summarized the recent patents and clinical status of therapeutic modalities for meningitis.
    Matched MeSH terms: Humans
  12. Bibliometric analysis of the research landscape on rice husks gasification (1995-2019)
    Nyakuma BB, Wong S, Mong GR, Utume LN, Oladokun O, Wong KY, et al.
    Environ Sci Pollut Res Int, 2021 Sep;28(36):49467-49490.
    PMID: 34355317 DOI: 10.1007/s11356-021-15761-x
    The processing of rice (Oryza sativa L.) generates large quantities of lignocellulosic wastes termed rice husks (RH). Numerous researchers have proposed biomass gasification as the panacea to the waste disposal and management challenges posed by RH. However, a comprehensive analysis of RH gasification is required to examine the research landscape and future directions on the area. The research landscape and global developments on RH gasification from 1995 to 2019 are examined through bibliometric analysis of 228 publications extracted from the Web of Science. Bioresource Technology is considered the most influential journal on the topic, whereas China is the most productive nation due to government policies and research funding. The most productive organization is the Harbin Institute of Technology, which is due to the significant contributions of Zhao YiJun and co-workers. Keyword analysis revealed three crucial research themes: gasification, biomass, and rice husks. The literature revealed that the syngas yield, distribution, and performance of RH gasification are significantly influenced by temperature, equivalence ratio, selected reactor, and gasifying medium. The techno-economic analysis of RH gasification revealed that government interventions such as high sales rates and low investment costs could enhance the commercial viability of the technology. Furthermore, the integration of RH gasification with carbon capture utilization and storage could promote the decarbonization of power plants, negative emissions, and net-zero climate goals. Overall, the paper provides valuable information for future researchers to identify strategic collaborators, journal publications, and research frontiers yet unexplored.
    Matched MeSH terms: Humans
  13. Fulltext When dysbiosis meets dystrophy: an unwanted gut-muscle connection
    Jayaraman A, Pettersson S
    EMBO Mol Med, 2023 Mar 08;15(3):e17324.
    PMID: 36843560 DOI: 10.15252/emmm.202217324
    Duchenne muscular dystrophy (DMD) is a devastating neuromuscular degenerative disease with no known cure to date. In recent years, the hypothesis of a "gut-muscle axis" has emerged suggesting that bidirectional communication between the gut microbiota and the muscular system regulates the muscular function and may be perturbed in several muscular disorders. In addition, the excessive consumption of sugar and of lipid-rich processed food products are factors that further aggravate the phenotype for such diseases and accelerate biological aging. However, these unhealthy microbiota profiles can be reversed by individualized dietary changes to not only alter the microbiota composition but also to reset the production of microbial metabolites known to trigger beneficial effects typically associated with prolonged health span. Two recent studies (in this issue of EMBO Mol Med) highlight the interesting potential of microbiota-informed next-generation dietary intervention programs to be considered in genetically linked muscle disorders like DMD.
    Matched MeSH terms: Humans
  14. Fulltext Diet Gut Microbiota Axis in Pregnancy: A Systematic Review of Recent Evidence
    Kunasegaran T, Balasubramaniam VRMT, Arasoo VJT, Palanisamy UD, Ramadas A
    Curr Nutr Rep, 2023 Mar;12(1):203-214.
    PMID: 36810808 DOI: 10.1007/s13668-023-00453-4
    PURPOSE OF REVIEW: Although gut microbiota have been associated with the etiology of some diseases, the influence of foods on gut microbiota, especially among pregnant women, remains unclear. Hence, a systematic review was performed to investigate the association between diet and gut microbiota and their influence on metabolic health in pregnant women.

    RECENT FINDINGS: We performed the systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 protocol to investigate the association between diet and gut microbiota and their influence on metabolic role in pregnant women. Five databases were searched for relevant peer-reviewed articles published in English since 2011. Two-staged screening of 659 retrieved records resulted in the inclusion of 10 studies. The collated findings suggested associations between nutrient intakes and four key microbes: Collinsella, Lachnospira, Sutterella, Faecalibacterium, and the Firmicutes/Bacteroidetes ratio in pregnant women. Dietary intakes in pregnancy were found to modify the gut microbiota and positively influence the cell metabolism in pregnant women. This review, however, emphasizes the importance of conducting well-designed prospective cohorts to investigate the role of changes in dietary intakes within the pregnancy and the influence of such changes on gut microbiota.

    Matched MeSH terms: Humans
  15. Fulltext Predicting the natural history of artificial intelligence in travel medicine
    Flaherty GT, Piyaphanee W
    J Travel Med, 2023 Feb 18;30(1).
    PMID: 36208173 DOI: 10.1093/jtm/taac113
    Matched MeSH terms: Humans
  16. Fulltext Evidence-based public policy making for medicines across countries: findings and implications for the future
    Godman B, Fadare J, Kwon HY, Dias CZ, Kurdi A, Dias Godói IP, et al.
    J Comp Eff Res, 2021 Aug;10(12):1019-1052.
    PMID: 34241546 DOI: 10.2217/cer-2020-0273
    Aim: Global expenditure on medicines is rising up to 6% per year driven by increasing prevalence of non-communicable diseases (NCDs) and new premium priced medicines for cancer, orphan diseases and other complex areas. This is difficult to sustain without reforms. Methods: Extensive narrative review of published papers and contextualizing the findings to provide future guidance. Results: New models are being introduced to improve the managed entry of new medicines including managed entry agreements, fair pricing approaches and monitoring prescribing against agreed guidance. Multiple measures have also successfully been introduced to improve the prescribing of established medicines. This includes encouraging greater prescribing of generics and biosimilars versus originators and patented medicines in a class to conserve resources without compromising care. In addition, reducing inappropriate antibiotic utilization. Typically, multiple measures are the most effective. Conclusion: Multiple measures will be needed to attain and retain universal healthcare.
    Matched MeSH terms: Humans
  17. Ensuring Global Access to Cancer Medicines: A Generational Call to Action
    Dare AJ, Bayle A, Hatoqai A, Mungo C, Velilla DG, Soto-Perez-de-Celis E, et al.
    Cancer Discov, 2023 Feb 06;13(2):269-274.
    PMID: 36734325 DOI: 10.1158/2159-8290.CD-22-1372
    Essential cancer treatments are not accessible, affordable, or available to patients who need them in many parts of the world. A new Access to Oncology Medicines (ATOM) Coalition, using public-private partnerships, aims to bring essential cancer medicines and diagnostics to patients in low- and lower middle-income countries.
    Matched MeSH terms: Humans
  18. A systematic literature review of deep learning neural network for time series air quality forecasting
    Zaini N, Ean LW, Ahmed AN, Malek MA
    Environ Sci Pollut Res Int, 2022 Jan;29(4):4958-4990.
    PMID: 34807385 DOI: 10.1007/s11356-021-17442-1
    Rapid progress of industrial development, urbanization and traffic has caused air quality reduction that negatively affects human health and environmental sustainability, especially among developed countries. Numerous studies on the development of air quality forecasting model using machine learning have been conducted to control air pollution. As such, there are significant numbers of reviews on the application of machine learning in air quality forecasting. Shallow architectures of machine learning exhibit several limitations and yield lower forecasting accuracy than deep learning architecture. Deep learning is a new technology in computational intelligence; thus, its application in air quality forecasting is still limited. This study aims to investigate the deep learning applications in time series air quality forecasting. Owing to this, literature search is conducted thoroughly from all scientific databases to avoid unnecessary clutter. This study summarizes and discusses different types of deep learning algorithms applied in air quality forecasting, including the theoretical backgrounds, hyperparameters, applications and limitations. Hybrid deep learning with data decomposition, optimization algorithm and spatiotemporal models are also presented to highlight those techniques' effectiveness in tackling the drawbacks of individual deep learning models. It is clearly stated that hybrid deep learning was able to forecast future air quality with higher accuracy than individual models. At the end of the study, some possible research directions are suggested for future model development. The main objective of this review study is to provide a comprehensive literature summary of deep learning applications in time series air quality forecasting that may benefit interested researchers for subsequent research.
    Matched MeSH terms: Humans
  19. Occurrence of heavy metals and their removal in Perna viridis mussels using chemical methods: a review
    Ali TG, Abdul Keyon AS, Mahat NA
    Environ Sci Pollut Res Int, 2022 Jan;29(4):4803-4821.
    PMID: 34775561 DOI: 10.1007/s11356-021-17343-3
    Despite the nutritional benefits, bivalves like mussels are also an excellent aquatic heavy metal biomonitoring agent due to their high tolerance to varying levels of temperature, salinity and oxygen, as well as pollutants. Although the accumulated toxic heavy metals may not exert direct negative impacts on the mussels, such toxicants in mussel tissues can give harmful effects on human body when consumed in toxic quantities and/or over prolonged period. The booming of urban and industrial activities, and consequently the increment of runoffs, as well as wastewater effluents and leaching, further exacerbated the magnitude of this issue. Hence, continuous monitoring of heavy metal contents in mussels is vital to ensure its compliance with food safety regulations, protecting consumers at large. This review paper discusses the occurrence of heavy metals in mussels especially that of Perna viridis in Malaysia and other parts of the world since year 2000 until 2021. Heavy metal concentration data and patterns from various coastal and/or estuaries were compared. Where applicable, statistical data that indicate variations between sampling sites, sampling months or years and chemical treatments for heavy metal removal were critically reviewed. Health risk assessment findings were also discussed. More importantly, related chemical-based interventions to minimize and/or eliminate toxic heavy metals from mussels are also reviewed.
    Matched MeSH terms: Humans
  20. Fulltext How COVID-19 induced panic on stock price and green finance markets: global economic recovery nexus from volatility dynamics
    Tan LP, Sadiq M, Aldeehani TM, Ehsanullah S, Mutira P, Vu HM
    Environ Sci Pollut Res Int, 2022 Apr;29(18):26322-26335.
    PMID: 34853996 DOI: 10.1007/s11356-021-17774-y
    This paper investigates the effect of different categories of essential COVID-19 data from 2020 to 2021 towards stock price dynamics and options markets. It applied the hypothetical method in which investors develop depression based on the understanding suggested by various green finance divisions. Furthermore, additional elements like panic, sentiment, and social networking sites may impact the attitude, size, and direction of green finance, subsequently impacting the security prices. We created new emotion proxies based on five groups of information, namely COVID-19, marketplace, lockdown, banking sector, and government relief using Google search data. The results show that (1) if the proportional number of traders' conduct exceeds the stock market, the effect of sentimentality indexes on jump volatility is expected to change; (2) the volatility index component jump radically increases with the COVID-19 index, city and market lockdown index, and banking index; and (3) expanding the COVID-19 index gives rise to the stock market index. Moreover, all indexes decreased in jump volatility but only after 5 days. These findings comply with the hypotheses proposed by our model.
    Matched MeSH terms: Humans
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