| 1. |
- Malik, Yashpal Singh, et al.
(författare)
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Coronavirus Disease Pandemic (COVID-19) : Challenges and a Global Perspective
- 2020
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Ingår i: Pathogens. - : MDPI AG. - 2076-0817. ; 9:7
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Forskningsöversikt (refereegranskat)abstract
- The technology-driven world of the 21st century is currently confronted with a major threat to humankind, represented by the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome, coronavirus-2 (SARS-CoV-2). As of now, COVID-19 has affected more than 6 million confirmed cases and took 0.39 million human lives. SARS-CoV-2 spreads much faster than its two ancestors, SARS-CoV and Middle East respiratory syndrome-CoV (MERS-CoV), but has low fatality rates. Our analyses speculate that the efficient replication and transmission of SARS-CoV-2 might be due to the high-density basic amino acid residues, preferably positioned in close proximity at both the furin-like cleavage sites (S1/S2 and S2 ') within the spike protein. Given the high genomic similarities of SARS-CoV-2 to bat SARS-like CoVs, it is likely that bats serve as a reservoir host for its progenitor. Women and children are less susceptible to SARS-CoV-2 infection, while the elderly and people with comorbidities are more prone to serious clinical outcomes, which may be associated with acute respiratory distress syndrome (ARDS) and cytokine storm. The cohesive approach amongst researchers across the globe has delivered high-end viral diagnostics. However, home-based point-of-care diagnostics are still under development, which may prove transformative in current COVID-19 pandemic containment. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. In this review, we discuss the noteworthy advancements, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology and diagnosis, animal reservoirs, laboratory animal models, disease transmission, therapeutics, vaccine challenges, and disease mitigation measures.
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| 2. |
- Kumar Singh, Abhinav, et al.
(författare)
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An Integrated Statistical-Machine Learning Approach for Runoff Prediction
- 2022
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 14:3
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Tidskriftsartikel (refereegranskat)abstract
- Nowadays, great attention has been attributed to the study of runoff and its fluctuation over space and time. There is a crucial need for a good soil and water management system to overcome the challenges of water scarcity and other natural adverse events like floods and landslides, among others. Rainfall–runoff (R-R) modeling is an appropriate approach for runoff prediction, making it possible to take preventive measures to avoid damage caused by natural hazards such as floods. In the present study, several data-driven models, namely, multiple linear regression (MLR), multiple adaptive regression splines (MARS), support vector machine (SVM), and random forest (RF), were used for rainfall–runoff prediction of the Gola watershed, located in the south-eastern part of the Uttarakhand. The rainfall–runoff model analysis was conducted using daily rainfall and runoff data for 12 years (2009 to 2020) of the Gola watershed. The first 80% of the complete data was used to train the model, and the remaining 20% was used for the testing period. The performance of the models was evaluated based on the coefficient of determination (R2), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and percent bias (PBAIS) indices. In addition to the numerical comparison, the models were evaluated. Their performances were evaluated based on graphical plotting, i.e., time-series line diagram, scatter plot, violin plot, relative error plot, and Taylor diagram (TD). The comparison results revealed that the four heuristic methods gave higher accuracy than the MLR model. Among the machine learning models, the RF (RMSE (m3/s), R2, NSE, and PBIAS (%) = 6.31, 0.96, 0.94, and −0.20 during the training period, respectively, and 5.53, 0.95, 0.92, and −0.20 during the testing period, respectively) surpassed the MARS, SVM, and the MLR models in forecasting daily runoff for all cases studied. The RF model outperformed in all four models’ training and testing periods. It can be summarized that the RF model is best-in-class and delivers a strong potential for the runoff prediction of the Gola watershed.
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| 3. |
- Marichelvam, M.K., et al.
(författare)
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Investigation on mechanical properties of novel natural fiber-epoxy resin hybrid composites for engineering structural applications
- 2023
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Polymers and fibers are the main components of cementitious composite materials to reinforce concrete. The synthetic fibers used in concrete composites typically weigh and also, and they are easily subjected to thermal degradation. To tackle the above issues, researchers developed various natural fiber-based composites. In the paper, the mechanical characteristics of hybrid composites were examined. The hybrid composites were developed using Madar, Gongura, and Hibiscus cannabinus fibers. The polyester resin was the matrix. The fibers were treated chemically using a 5% sodium hydroxide (NaOH) solution. The fibers were then carefully cleaned with distilled water twice and baked for 70 min at 60 °C. For the evaluation of the tensile, flexural, and impact properties of the hybrid composites, specimens were made in accordance with ASTM standards. The treated composite sample (S3) specimen exhibits a tensile strength (TS) of approximately 34.720 N/mm2, flexural strength (FS) of 77.957 MPa, and flexural modulus (FM) of 1548.588 GPa. The average water absorption of the sample is only 2.45%. The hardness and impact strength (IS) of the samples are also superior to those of several other composites studied in the literature. Hence, the proposed hybrid composites could be a potential material for reinforcing the concrete composites to provide a higher service rate and greater durability to the structures.
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| 4. |
- Ahmed, Sirwan Khalid, et al.
(författare)
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Knowledge, Attitude and Worry in the Kurdistan Region of Iraq during the Mpox (Monkeypox) Outbreak in 2022 : An Online Cross-Sectional Study
- 2023
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Ingår i: Vaccines. - : MDPI AG. - 2076-393X. ; 11:3
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Tidskriftsartikel (refereegranskat)abstract
- The rapid spread of monkeypox (mpox) has been declared as a public health emergency of international concern (PHEIC). The present study aimed to assess the knowledge, attitude, and worry levels of the general population in the Kurdistan region of Iraq regarding the ongoing mpox multi-country outbreak. An online cross-sectional survey was conducted between 27–30 July 2022, using a convenience sampling method. The questionnaire was adapted from previous studies addressing the same topic. The independent Student’s t-test, one-way ANOVA, and logistic regression were used to assess possible factors associated with knowledge, attitude, and worry toward mpox. A total of 510 respondents were included in the final analysis. The participants showed a moderate level of mpox knowledge, a neutral attitude towards mpox, and a relatively moderate worry level. The logistic regression analysis showed that age, gender, marital status, religion, level of education, and place of residence were associated with mpox knowledge; however, the significant variables in the multivariate regression analysis were gender, religion, level of education, and residential area. Gender and residential area were associated with attitudes toward mpox; however, the significant variables in the multivariate regression analysis were gender and residential areas. The worry toward mpox was influenced by gender, marital status, religion, and place of residence, yet the significant variables in the multivariate regression analysis were gender, religion, educational level, and residential area. In conclusion, the Kurdish population had moderate knowledge, a neutral attitude, and a moderate level of worry about mpox. Considering the continuous rapid rise in mpox cases in several countries, and its possible risk as pandemic amid the ongoing COVID-19 pandemic, proactive control measures, adequate disease prevention strategies, and preparedness plans need to be formulated and immediately implemented to tackle the appearance of fears among people, and to safeguard the mental health of the public.
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| 5. |
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| 6. |
- Boen, Rune, et al.
(författare)
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Beyond the global brain differences : intraindividual variability differences in 1q21.1 distal and 15q11.2 bp1-bp2 deletion carriers
- 2024
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Ingår i: Biological Psychiatry. - 0006-3223 .- 1873-2402. ; 95:2, s. 147-160
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Tidskriftsartikel (refereegranskat)abstract
- Background: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure.Methods: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference.Results: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness.Conclusions: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
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| 7. |
- Dhama, Kuldeep, et al.
(författare)
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SARS-CoV-2 emerging Omicron subvariants with a special focus on BF.7 and XBB.1.5 recently posing fears of rising cases amid ongoing COVID-19 pandemic
- 2022
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Ingår i: Journal of Experimental Biology and Agricultural Sciences. - : JEBAS. - 2320-8694. ; 10:6, s. 1215-1221
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Tidskriftsartikel (refereegranskat)abstract
- The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron versions have been the sole one circulating for quite some time. Subvariants BA.1, BA.2, BA.3, BA.4, and BA.5 of the Omicron emerged over time and through mutation, with BA.1 responsible for the most severe global pandemic between December 2021 and January 2022. Other Omicron subvariants such as BQ.1, BQ.1.1, BA.4.6, BF.7, BA.2.75.2, XBB.1 appeared recently and could cause a new wave of increased cases amid the ongoing COVID-19 pandemic. There is evidence that certain Omicron subvariants have increased transmissibility, extra spike mutations, and ability to overcome protective effects of COVID-19 neutralizing antibodies through immunological evasion. In recent months, the Omicron BF.7 subvariant has been in the news due to its spread in China and a small number of other countries, raising concerns about a possible rebound in COVID-19 cases. More recently, the Omicron XBB.1.5 subvariant has captured international attention due to an increase in cases in the United States. As a highly transmissible sublineage of Omicron BA.5, as well as having a shorter incubation time and the potential to reinfect or infect immune population, BF.7 has stronger infection ability. It appears that the regional immunological landscape is affected by the amount and timing of previous Omicron waves, as well as the COVID-19 vaccination coverage, which in turn determines whether the increased immune escape of BF.7 and XBB.1.5 subvariants is sufficient to drive new infection waves. Expanding our understanding of the transmission and efficacy of vaccines, immunotherapeutics, and antiviral drugs against newly emerging Omicron subvariants and lineages, as well as bolstering genomic facilities for tracking their spread and maintaining a constant vigilance, and shedding more light on their evolution and mutational events, would help in the development of effective mitigation strategies. Importantly, reducing the occurrence of mutations and recombination in the virus can be aided by bolstering One health approach and emphasizing its significance in combating zoonosis and reversal zoonosis linked with COVID-19. This article provides a brief overview on Omicron variant, its recently emerging lineages and subvairants with a special focus on BF.7 and XBB.1.5 as much more infectious and highly transmissible variations that may once again threaten a sharp increase in COVID-19 cases globally amid the currently ongoing pandemic, along with presenting salient mitigation measures.
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| 8. |
- Islam, Md. Aminul, et al.
(författare)
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A 30-day follow-up study on the prevalence of SARS-COV-2 genetic markers in wastewater from the residence of COVID-19 patient and comparison with clinical positivity
- 2023
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 858, s. 159350-
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Tidskriftsartikel (refereegranskat)abstract
- Wastewater based epidemiology (WBE) is an important tool to fight against COVID-19 as it provides insights into the health status of the targeted population from a small single house to a large municipality in a cost-effective, rapid, and non-invasive way. The implementation of wastewater based surveillance (WBS) could reduce the burden on the public health system, management of pandemics, help to make informed decisions, and protect public health. In this study, a house with COVID-19 patients was targeted for monitoring the prevalence of SARS-CoV-2 genetic markers in wastewa-ter samples (WS) with clinical specimens (CS) for a period of 30 days. RT-qPCR technique was employed to target non-structural (ORF1ab) and structural-nucleocapsid (N) protein genes of SARS-CoV-2, according to a validated experimental protocol. Physiological, environmental, and biological parameters were also measured following the American Public Health Association (APHA) standard protocols. SARS-CoV-2 viral shedding in wastewater peaked when the highest number of COVID-19 cases were clinically diagnosed. Throughout the study period, 7450 to 23,000 gene copies/1000 mL were detected, where we identified 47 % (57/120) positive samples from WS and 35 % (128/360) from CS. When the COVID-19 patient number was the lowest (2), the highest CT value (39.4; i.e., lowest copy number) was identified from WS. On the other hand, when the COVID-19 patients were the highest (6), the lowest CT value (25.2 i.e., highest copy numbers) was obtained from WS. An advance signal of increased SARS-CoV-2 viral load from the COVID-19 patient was found in WS earlier than in the CS. Using customized primer sets in a traditional PCR approach, we confirmed that all SARS-CoV-2 variants identified in both CS and WS were Delta variants (B.1.617.2). To our knowledge, this is the first follow-up study to determine a temporal relationship be-tween COVID-19 patients and their discharge of SARS-CoV-2 RNA genetic markers in wastewater from a single house including all family members for clinical sampling from a developing country (Bangladesh), where a proper sewage system is lacking. The salient findings of the study indicate that monitoring the genetic markers of the SARS-CoV-2 virus in wastewater could identify COVID-19 cases, which reduces the burden on the public health system during COVID-19 pandemics.
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| 9. |
- Islam, Md. Aminul, et al.
(författare)
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Association of household fuel with acute respiratory infection (ARI) under-five years children in Bangladesh
- 2022
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Ingår i: Frontiers In Public Health. - : Frontiers Media SA. - 2296-2565. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- In developing countries, acute respiratory infections (ARIs) cause a significant number of deaths among children. According to Bangladesh Demographic and Health Survey (BDHS), about 25% of the deaths in children under-five years are caused by ARI in Bangladesh every year. Low-income families frequently rely on wood, coal, and animal excrement for cooking. However, it is unclear whether using alternative fuels offers a health benefit over solid fuels. To clear this doubt, we conducted a study to investigate the effects of fuel usage on ARI in children. In this study, we used the latest BDHS 2017-18 survey data collected by the Government of Bangladesh (GoB) and estimated the effects of fuel use on ARI by constructing multivariable logistic regression models. From the analysis, we found that the crude (the only type of fuel in the model) odds ratio (OR) for ARI is 1.69 [95% confidence interval (CI): 1.06-2.71]. This suggests that children in families using contaminated fuels are 69.3% more likely to experience an ARI episode than children in households using clean fuels. After adjusting for cooking fuel, type of roof material, child's age (months), and sex of the child-the effect of solid fuels is similar to the adjusted odds ratio (AOR) for ARI (OR: 1.69, 95% CI: 1.05-2.72). This implies that an ARI occurrence is 69.2% more likely when compared to the effect of clean fuel. This study found a statistically significant association between solid fuel consumption and the occurrence of ARI in children in households. The correlation between indoor air pollution and clinical parameters of ARI requires further investigation. Our findings will also help other researchers and policymakers to take comprehensive actions by considering fuel type as a risk factor as well as taking proper steps to solve this issue.
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| 10. |
- Malik, Yashpal Singh, et al.
(författare)
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Pitfalls and lessons for the future : Pitfalls and lessons for the future
- 2021
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Ingår i: Reviews in Medical Virology. - : John Wiley & Sons. - 1052-9276 .- 1099-1654. ; 31:5
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Forskningsöversikt (refereegranskat)abstract
- The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI-based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid-19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI-based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better responses against Covid-19 cases. AI-based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid-19 pandemic.
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