Remdesivir is one of the most widely recommended and used medications for COVID-19 treatment. However, different outcomes have been reported for hospitalized patients with COVID-19 treated with ...remdesivir. Specifically, the effect of the timing of remdesivir initiation (from patient's symptom onset) on clinical outcomes in COVID-19 patients has not been investigated. This is a retrospective cohort study of patients hospitalized with COVID-19 and treated with or without remdisivir. The primary outcome was patient's recovery rate, defined as clinical improvement and patient's discharge by day 14 of symptom onset. The secondary outcome was the need for intensive care unit (ICU) admission, mechanical ventilation, and mortality within 28 days of patient's symptom onset. Out of 323 hospitalized adults with COVID-19, 107 (33.1%) received no remdesivir during their hospital stay, 107 (33.1%) received remdesivir early within 7 days of the symptom onset, and 109 (33.7%) received it at 8 days or later of symptom onset. At day 14 following symptom onset, higher proportion of patients recovered in the early remdesivir compared to the late remdesivir cohort, or patients who did not receive remdesivir (adjusted odds ratio, aOR, 2.65; 95% confidence interval CI, 1.31 to 5.35). Moreover, early administration of remdesivir was associated with lower admission to intensive care unit (adjusted hazard ratio aHR, 0.31; 95% CI, 0.15 to 0.64), less need for mechanical ventilation (aHR, 0.22; 95% CI, 0.10 to 0.51), and lower mortality at 28 days (aHR, 0.15; 95% CI, 0.04 to 0.53), as compared to the late remdesivir cohort or patients who did not receive remdesivir. Early administration of remdesivir within 7 days of symptom onset is associated with less need for mechanical ventilation and lower 28-days mortality.
Closing the gap between economy activity and environmental quality is one of the solutions for reaching “sustainable development” in Malaysia. To do so, the cubic polynomial functional form of EKC is ...utilized by accommodating renewable energy into the base of the EKC model and validating its hypothesis between CO2 emissions and GDP growth for the 1971–2015 period. The F-bounds, VECM Granger causality, CUSUM, and CUSUMSQ tests are utilized. The estimated results consistently show that the inverted N-shaped EKC hypothesis holds in Malaysia. Ceteris paribus, the CO2 emissions will be declined when the GDP reach RM2841.9 billion in 2030, which is beyond the sample period. The renewable energy has a negative significant effect on CO2 emissions, and the direction of causality is running from CO2 emissions to renewable energy. Also, the GDP growth will be the remedy for environmental pollution problems and that renewable energy is one of important elements to be considered for improving environmental quality. A tighter and concentrated environmental policy is needed to direct the environment–economic growth nexus toward a downward trend. Consequently, these results may help Malaysian policymakers to establish an energy policy that guarantees a balance between economic growth and environmental prosperity.
•Literature results on the EKC hypothesis for Malaysian cases are still limited.•Role of renewable energy in the cubic polynomial functional form of EKC is tested.•The inverted N-shaped EKC hypothesis is confirmed.•The renewable energy diminishes the CO2 emissions in the long run.•GDP soon will be remedy for environmental pollution problems.
Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation ...efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan's mountain ungulates.
Hitting the limits on propene synthesis
The greater abundance of propane from shale gas has spurred efforts to use it as a propylene feedstock. Direct dehydrogenation catalysts consisting of ...platinum–tin alloy nanoparticles supported on alumina often must run with hydrogen dilution to avoid carbon buildup and excess tin to avoid alloy segregation. Motagamwala
et al.
report that platinum–tin nanoparticles interact more weakly with a silica support and the metals thus do not segregate. The use of undiluted reactants allowed the reaction to run near the thermodynamically limit of about 67% conversion with a selectivity to propylene of more than 99%. This catalyst also does not build up carbon and could run up to 30 hours without deactivation.
Science
, abg7894, this issue p.
217
Nanoparticles of a Pt-Sn alloy on silica enable high conversion and resist carbon formation in propane dehydrogenation.
Intentional (“on-purpose”) propylene production through nonoxidative propane dehydrogenation (PDH) holds great promise for meeting the increasing global demand for propylene. For stable performance, traditional alumina-supported platinum-based catalysts require excess tin and feed dilution with hydrogen; however, this reduces per-pass propylene conversion and thus lowers catalyst productivity. We report that silica-supported platinum-tin (Pt
1
Sn
1
) nanoparticles (<2 nanometers in diameter) can operate as a PDH catalyst at thermodynamically limited conversion levels, with excellent stability and selectivity to propylene (>99%). Atomic mixing of Pt and Sn in the precursor is preserved upon reduction and during catalytic operation. The benign interaction of these nanoparticles with the silicon dioxide support does not lead to Pt-Sn segregation and formation of a tin oxide phase that can occur over traditional catalyst supports.
Habitat suitability models are useful to understand species distribution and to guide management and conservation strategies. The grey wolf (Canis lupus) has been extirpated from most of its historic ...range in Pakistan primarily due to its impact on livestock and livelihoods. We used non-invasive survey data from camera traps and genetic sampling to develop a habitat suitability model for C. lupus in northern Pakistan and to explore the extent of connectivity among populations. We detected suitable habitat of grey wolf using a maximum entropy approach (Maxent ver. 3.4.0) and identified suitable movement corridors using the Circuitscape 4.0 tool. Our model showed high levels of predictive performances, as seen from the values of area under curve (0.971±0.002) and true skill statistics (0.886±0.021). The main predictors for habitat suitability for C. lupus were distances to road, mean temperature of the wettest quarter and distance to river. The model predicted ca. 23,129 km2 of suitable areas for wolf in Pakistan, with much of suitable habitat in remote and inaccessible areas that appeared to be well connected through vulnerable movement corridors. These movement corridors suggest that potentially the wolf range can expand in Pakistan's Northern Areas. However, managing protected areas with stringent restrictions is challenging in northern Pakistan, in part due to heavy dependence of people on natural resources. The habitat suitability map provided by this study can inform future management strategies by helping authorities to identify key conservation areas.
This work aims to distill the findings of a wide variety of scholarly disciplines into a coherent narrative of the Qur'an's history, from the first oral recitation to the four published Variants in ...active circulation today. In the process of unraveling the complicated relationships between the oral Qur'an and the written Qur'an, it becomes clear that there are, in fact, two histories of the Qur'an and that the overall history of the Qur'an cannot be appreciated without understanding the interactions between these two occasionally intertwined but often independent component histories. Discrepancies between the four qur'anic Variants that are in active use today are indexed and analyzed. While most scholarship views the Qur'an either in relation to its past and its possible origins, or in relation to its contemporary status as a static, fixed text, this work adopts an organic, developmental approach recognizing that the Qur'an is a living text that continues to evolve.
BackgroundIschemic heart disease (IHD) is a leading cause of death worldwide. Also referred to as coronary artery disease (CAD) and atherosclerotic cardiovascular disease (ACD), it manifests ...clinically as myocardial infarction and ischemic cardiomyopathy. This study aims to evaluate the epidemiological trends of IHD globally.MethodsThe most up-to-date epidemiological data from the Global Burden of Disease (GBD) dataset were analyzed. GBD collates data from a large number of sources, including research studies, hospital registries, and government reports. This dataset includes annual figures from 1990 to 2017 for IHD in all countries and regions. We analyzed the incidence, prevalence, and disability-adjusted life years (DALY) for IHD. Forecasting for the next two decades was conducted using the Statistical Package for the Social Sciences (SPSS) Time Series Modeler (IBM Corp., Armonk, NY).ResultsOur study estimated that globally, IHD affects around 126 million individuals (1,655 per 100,000), which is approximately 1.72% of the world’s population. Nine million deaths were caused by IHD globally. Men were more commonly affected than women, and incidence typically started in the fourth decade and increased with age. The global prevalence of IHD is rising. We estimated that the current prevalence rate of 1,655 per 100,000 population is expected to exceed 1,845 by the year 2030. Eastern European countries are sustaining the highest prevalence. Age-standardized rates, which remove the effect of population changes over time, have decreased in many regions.ConclusionsIHD is the number one cause of death, disability, and human suffering globally. Age-adjusted rates show a promising decrease. However, health systems have to manage an increasing number of cases due to population aging.
Digitization and automation have always had an immense impact on healthcare. It embraces every new and advanced technology. Recently the world has witnessed the prominence of the metaverse which is ...an emerging technology in digital space. The metaverse has huge potential to provide a plethora of health services seamlessly to patients and medical professionals with an immersive experience. This paper proposes the amalgamation of artificial intelligence and blockchain in the metaverse to provide better, faster, and more secure healthcare facilities in digital space with a realistic experience. Our proposed architecture can be summarized as follows. It consists of three environments, namely the doctor's environment, the patient's environment, and the metaverse environment. The doctors and patients interact in a metaverse environment assisted by blockchain technology which ensures the safety, security, and privacy of data. The metaverse environment is the main part of our proposed architecture. The doctors, patients, and nurses enter this environment by registering on the blockchain and they are represented by avatars in the metaverse environment. All the consultation activities between the doctor and the patient will be recorded and the data, i.e., images, speech, text, videos, clinical data, etc., will be gathered, transferred, and stored on the blockchain. These data are used for disease prediction and diagnosis by explainable artificial intelligence (XAI) models. The GradCAM and LIME approaches of XAI provide logical reasoning for the prediction of diseases and ensure trust, explainability, interpretability, and transparency regarding the diagnosis and prediction of diseases. Blockchain technology provides data security for patients while enabling transparency, traceability, and immutability regarding their data. These features of blockchain ensure trust among the patients regarding their data. Consequently, this proposed architecture ensures transparency and trust regarding both the diagnosis of diseases and the data security of the patient. We also explored the building block technologies of the metaverse. Furthermore, we also investigated the advantages and challenges of a metaverse in healthcare.
Bacterial co‐infections with SARS‐CoV‐2 Mirzaei, Rasoul; Goodarzi, Pedram; Asadi, Muhammad ...
IUBMB life,
October 2020, Volume:
72, Issue:
10
Journal Article
Peer reviewed
Open access
The pandemic coronavirus disease 2019 (COVID‐19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2), has affected millions of people worldwide. To date, there are no proven ...effective therapies for this virus. Efforts made to develop antiviral strategies for the treatment of COVID‐19 are underway. Respiratory viral infections, such as influenza, predispose patients to co‐infections and these lead to increased disease severity and mortality. Numerous types of antibiotics such as azithromycin have been employed for the prevention and treatment of bacterial co‐infection and secondary bacterial infections in patients with a viral respiratory infection (e.g., SARS‐CoV‐2). Although antibiotics do not directly affect SARS‐CoV‐2, viral respiratory infections often result in bacterial pneumonia. It is possible that some patients die from bacterial co‐infection rather than virus itself. To date, a considerable number of bacterial strains have been resistant to various antibiotics such as azithromycin, and the overuse could render those or other antibiotics even less effective. Therefore, bacterial co‐infection and secondary bacterial infection are considered critical risk factors for the severity and mortality rates of COVID‐19. Also, the antibiotic‐resistant as a result of overusing must be considered. In this review, we will summarize the bacterial co‐infection and secondary bacterial infection in some featured respiratory viral infections, especially COVID‐19.
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