Dynamic linkages between renewable energy, carbon emissions and economic growth through nonlinear ARDL approach: Evidence from Iran

This study examines the relationship between economic growth, renewable energy consumption, and carbon emissions in Iran between 1975–2017, and the bounds testing approach to cointegration and the asymmetric method was used in this study. The results reveal that in the long run increase in renewable energy consumption and CO₂ emissions causes an increase in real GDP per capita. Meanwhile, the decrease in renewable energy has the same effect, but GDP per capita reacts more strongly to the rise in renewable energy than the decline. Besides, in the long run, a reduction of CO₂ emissions has an insignificant impact on GDP per capita. Furthermore, the results from asymmetric tests suggest that reducing CO₂ emissions and renewable energy consumption do not have an essential role in decreasing growth in the short run. In contrast, an increase in renewable energy consumption and CO₂ emissions do contribute to boosting the growth. These results may be attributable to the less renewable energy in the energy portfolio of Iran. Additionally, the coefficients on capital and labor are statistically significant, and we discuss the economic implications of the results and propose specific policy recommendations.

A multi-feature hybrid classification data mining technique for human-emotion

BACKGROUND AND OBJECTIVES

The ideal treatment of illnesses is the interest of every era. Data innovation in medical care has become extremely quick to analyze diverse diseases from the most recent twenty years. In such a finding, past and current information assume an essential job is utilizing and information mining strategies. We are inadequate in diagnosing the enthusiastic mental unsettling influence precisely in the beginning phases. In this manner, the underlying conclusion of misery expressively positions an extraordinary clinical and Scientific research issue. This work is dedicated to tackling the same issue utilizing the AI strategy. Individuals' dependence on passionate stages has been successfully characterized into various gatherings in the data innovation climate.

METHODS

A notable AI multi-include cross breed classifier is utilized to execute half and half order by having the passionate incitement as pessimistic or positive individuals. A troupe learning calculation helps to pick the more appropriate highlights from the accessible classes feeling information on online media to improve order. We split the Dataset into preparing and testing sets for the best proactive model.

RESULTS

The execution assessment is applied to check the proposed framework through measurements of execution assessment. This exploration is done on the Class Labels MovieLens dataset. The exploratory outcomes show that the used group technique gives ideal order execution by picking the highlights' greatest separation. The supposed results demonstrated the projected framework's distinction, which originates from the picking-related highlights chosen by the incorporated learning calculation.

CONCLUSION

The proposed approach is utilized to precisely and successfully analyze the downturn in its beginning phase. It will assist in the recovery and action of discouraged individuals. We presume that the future strategy's utilization is exceptionally appropriate in all data innovation-based E-medical services for discouraging incitement.

Reflection of government performance from foreign exchange market through engineered mechanism using conditional copula model

This paper investigates governments’ performance in the country. We achieved this objective differently. We employed an inverse method of assessment, with the utilization of factor copula modeling technique, to study the dependence relationship of exchange rates returns as auxiliary variables, the performance of political and army government tenures in the country in the last two decades are evaluated. Through factor analysis, common factors for the exchange rate are obtained. The analysis shows that conditioned on the common factors, the dependence amongst the elected currencies are strongly asymmetric in most of the tenures except the term of Pakistan Muslim League-Nawaz, and condition on common factor Clayton copula demonstrating hypothesis is more suitable. However, we perceive high left tail reliance among foreign currency returns during Pakistan Muslim League-Nawaz tenure, and the condition on common factor Gumbel copula molding assumption is more appropriate. We are signifying the foulest government performance in the country among all occupancies under consideration.

Machine learning-based mortality rate prediction using optimized hyper-parameter

OBJECTIVE AND BACKGROUND

The current scenario of the Pandemic of COVID-19 demands multi-channel investigations and predictions. A variety of prediction models are available in the literature. The majority of these models are based on extrapolating by the parameters related to the diseases, which are history-oriented. Instead, the current research is designed to predict the mortality rate of COVID-19 by Regression techniques in comparison to the models followed by five countries.

METHODS

The Regression method with an optimized hyper-parameter is used to develop these models under training data by Machine Learning Technique.

RESULTS

The validity of the proposed model is endorsed by considering the case study on the data for Pakistan. Five distinct models for mortality rate prediction are built using Confirmed cases data as a predictor variable for France, Spain, Turkey, Sweden, and Pakistan, respectively. The results evidenced that Sweden has a fewer death case over 20,000 confirmed cases without observing lockdown. Hence, by following the strategy adopted by Sweden, the chosen entity will control the death rate despite the increase of the confirmed cases.

CONCLUSION

The evaluated results notice the high mortality rate and low RMSE for Pakistan by the GPR method based Mortality model. Therefore, the morality rate based MRP model is selected for the COVID-19 death rate in Pakistan. Hence, the best-fit is the Sweden model to control the mortality rate.

Leishmania amazonensis ferric iron reductase (LFR1) is a bifunctional enzyme: Unveiling a NADPH oxidase activity

Leishmania amazonensis is one of leishmaniasis' causative agents, a disease that has no cure and leads to the appearance of cutaneous lesions. Recently, our group showed that heme activates a Na⁺/K⁺ ATPase in these parasites through a signaling cascade involving hydrogen peroxide (H₂O₂) generation. Heme has a pro-oxidant activity and signaling capacity, but the mechanism by which this molecule increases H₂O₂ levels in L. amazonensis has not been elucidated. Here we investigated the source of H₂O₂ stimulated by heme, ruling out the participation of mitochondria and raising the possibility of a role for a NADPH oxidase (Nox) activity. Despite the absence of a classical Nox sequence in trypanosomatid genomes, L. amazonensis expresses a surface ferric iron reductase (LFR1). Interestingly, Nox enzymes are thought to have evolved from ferric iron reductases because they share same core domain and are very similar in structure. The main difference is that Nox catalyses electron flow from NADPH to oxygen, generating reactive oxygen species (ROS), while ferric iron reductase promotes electron flow to ferric iron, generating ferrous iron. Using L. amazonensis overexpressing or knockout for LFR1 and heterologous expression of LFR1 in mammalian embryonic kidney (HEK 293) cells, we show that this enzyme is bifunctional, being able to generate both ferrous iron and H₂O₂. It was previously described that protozoans knockout for LFR1 have their differentiation to virulent forms (amastigote and metacyclic promastigote) impaired. In this work, we observed that LFR1 overexpression stimulates protozoan differentiation to amastigote forms, reinforcing the importance of this enzyme in L. amazonensis life cycle regulation. Thus, we not only identified a new source of ROS production in Leishmania, but also described, for the first time, an enzyme with both ferric iron reductase and Nox activities.

Role of Serum Osteoprotegerin as a Diagnostic Indicator of Primary Osteoporosis in Perimenopausal and Postmenopausal Women: An Indian Perspective

Introduction: Osteoporosis (OP) is a major health problem in the older population. The aim of the study was to assess the role of serum osteoprotegerin (OPG) as a diagnostic indicator of primary osteoporosis in peri- and post-menopausal women in an Indian population.

Materials and Methods: After ethical approval, 90 cases (45 cases and 45 controls) of peri- and post-menopausal females above 40 years of age presenting to our outpatient department were included in the study. It was a case controlled study conducted between July 2014 to July 2015. Based on the clinical features, t-score and radiological evidence from the DEXA scan, they were equally divided into two groups (cases and controls). Serum osteoprotegerin (OPG) levels were measured amongst cases and controls.

Results: The total calcium (mg/dl) level was lower among the cases and the difference was significant (p-Value= <0.001). Similarly, alkaline phosphatase (u/l), osteoprotegerin (u/ml) levels were higher in the cases as compared to controls and the difference was significant (p-Value= <0.001). The mean osteoprotegerin level showed a slight increase with increase in severity of the grading of BMD of spine. The results suggested a cut-off value of ≥10.5 u/ml (86.7% sensitive and 80% specific with accuracy of 84.5%) between normal and osteoporosis.

Conclusion: From the present study, we conclude that osteoprotegerin is a valid biomarker to diagnose postmenopausal women with low bone mineral density.

Hypoxia preconditioning by cobalt chloride enhances endurance performance and protects skeletal muscles from exercise-induced oxidative damage in rats

AIM

Training under hypoxia has several advantages over normoxic training in terms of enhancing the physical performance. Therefore, we tested the protective effect of hypoxia preconditioning by hypoxia mimetic cobalt chloride against exercise-induced oxidative damage in the skeletal muscles and improvement of physical performance.

METHOD

Male Sprague-Dawley rats were randomly divided into four groups (n=8), namely control, cobalt-supplemented, training and cobalt with training. The red gastrocnemius muscle was examined for all measurements, viz. free radical generation, lipid peroxidation, muscle damage and antioxidative capacity.

RESULTS

Hypoxic preconditioning with cobalt along with training significantly increased physical performance (33%, P<0.01) in rats compared with training-only rats. Cobalt supplementation activated cellular oxygen sensing system in rat skeletal muscle. It also protected against training-induced oxidative damage as observed by an increase in the GSH/GSSG ratio (36%, P<0.001; 28%, P<0.01 respectively) and reduced lipid peroxidation (15%, P<0.01; 31%, P<0.01 respectively) in both trained and untrained rats compared with their respective controls. Cobalt supplementation along with training enhanced the expression of antioxidant proteins haem oxygenase-1 (HO-1; 1.2-fold, P<0.05) and metallothionein (MT; 4.8-fold, P<0.001) compared with training only. A marked reduction was observed in exercise-induced muscle fibre damage as indicated by decreased necrotic muscle fibre, decreased lipofuscin content of muscle and plasma creatine kinase level (16%, P<0.01) in rats preconditioned with cobalt.

CONCLUSION

Our study provides strong evidence that hypoxic preconditioning with cobalt chloride enhances physical performance and protects muscle from exercise-induced oxidative damage via GSH, HO-1 and MT-mediated antioxidative capacity.

Chemotherapy-induced suppression of serum holotranscobalamin

e20639

Purpose: Chemotherapy-induced damage to the stomach and small intestine may inhibit the absorption of vitamin B12. To assess the risk of chemotherapy causing acute vitamin B12 deficiency, we primarily measured the active form of vitamin B12, holotranscobalamin, but also total serum B12, methylmalonic acid, and total homocysteine. Experimental Design: We studied 21 patients that were actively on chemotherapy and recorded values for holotranscobalamin, total serum B12, methylmalonic acid, total homocysteine, and cystatin-c. Measurements were taken both before and after four doses of chemotherapy. T-tests were employed to determine statistical significance. Results: There was a statistically significant drop in holotranscobalamin after chemotherapy in eighteen out of twenty-one patients (p = 2.64x10–3). Three patients were vitamin B12 deficient as defined by total B12 < 300 pg/ml. Neither methylmalonic acid (p = 3.95x10–1), nor total homocysteine (p = 4.34x10–1), showed any significant changes. Conclusions: Chemotherapy caused an acute deficiency of the only metabolically active form of vitamin B12, holotranscobalamin, despite B12 supplementation. We suggest monitoring patients for changes in holotranscobalamin to ensure that prolonged deficiency does not occur. The clinical implications of acute lowering of holotranscobalamin remain unknown.

No significant financial relationships to disclose.

Uveitis-glaucoma-hyphema syndrome after handmade, anterior chamber lens implantation

Two patients developed uveitis-glaucoma-hyphema syndrome secondary to implantation of handmade anterior chamber intraocular lenses (IOLs). The IOLs were designed and made by the patients' ophthalmologists in their native Ukraine. The cases illustrate innovative and unusual solutions to the shortage of quality IOLs in the developing world and the challenging management of patients who present with complications arising from these IOLs.