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Ecofriendly spectrophotometric methods for simultaneous determination of remdesivir and moxifloxacin hydrochloride as co administered drugs in corona virus treatment
AbstractRemdesivir and moxifloxacin hydrochloride are among the most frequently co-administered drugs used for COVID-19 treatment. The current work aims to evaluate green spectrophotometric methodologies for estimating remdesivir and moxifloxacin hydrochloride in different matrices for the first time. The proposed approaches were absorbance subtraction, extended ratio subtraction and amplitude modulation methods. In order to determine the absorbance of the investigated medications in combination at the isoabsorptive point, the pure moxifloxacin hydrochloride absorbance factor is applied using the absorbance subtraction method, which modifies the zero absorption spectra of the drugs under investigation at the isoabsorptive point (229 nm). The spectrum of moxifloxacin hydrochloride is more extended in the plateau area between 340 and 400 nm, where remdesivir exhibits no absorption. So, also, the ratio spectra were successfully manipulated for quantification of the two drugs. Regarding the pharmacokinetic profile of remdesivir (Cmax 4420 ng/mL) and moxifloxacin hydrochloride (Cmax 3.56 µg/mL), the proposed methods were effectively used to spectrophotometrically determine remdesivir and moxifloxacin hydrochloride in plasma matrix. The new approach was validated using the ICH guidelines for specificity, linearity, precision, and accuracy. The greenness of the reported methodologies was evaluated using two metrics: the analytical eco-scale and the green analytical procedure index.
Predicting coefficient of volume compressibility of fine-grained soils using appropriate soil type and soil state parameters
AbstractPredicting the coefficient of volume compressibility (mv) would help a field engineer to make a quick estimate of the soil compressibility. The multiple correlations suggested by various researchers as available in the literature indicate the importance of predicting the mv of soil. The existing correlations as available in literature either use soil state (in the form of SPT N-value or unconfined compressive strength or natural water content) or soil type (in the form of plasticity properties). However, using both soil type and soil state parameters in developing any prediction equation would be more reliable. To overcome this limitation of existing correlation equations to predict mv, a simple and reliable method that can be universally applied with appropriate soil type parameter represented by the Shrinkage Index (Liquid Limit-Shrinkage Limit) and soil state parameter represented by standardized SPT N60 has been proposed. This model is designed to be universally applicable, serving as a valuable tool for practicing engineers and researchers to predict mv.
The nonlinear association between lipoprotein(a) and major adverse cardiovascular events in acute coronary syndrome patients with three-vessel disease
Using an inferior decoy alternative to nudge COVID-19 vaccination
Improved dynamic programming method for solving multi-objective and multi-stage decision-making problems
The mechanistical principles and engineering application of roof- cutting for roadway protection in advance of the working face
The integration of optimizing train timetables with EMU route plans
Neurological post-COVID syndrome is associated with substantial impairment of verbal short-term and working memory
AbstractA substantial proportion of patients suffer from Post-COVID Syndrome (PCS) with fatigue and impairment of memory and concentration being the most important symptoms. We here set out to perform in-depth neuropsychological assessment of PCS patients referred to the Neurologic PCS clinic compared to patients without sequelae after COVID-19 (non-PCS) and healthy controls (HC) to decipher the most prevalent cognitive deficits. We included n = 60 PCS patients with neurologic symptoms, n = 15 non-PCS patients and n = 15 healthy controls. Basic socioeconomic data and subjective complaints were recorded. This was followed by a detailed neuropsychological test battery, including assessments of general orientation, motor and cognitive fatigue, screening of depressive and anxiety symptoms, information processing speed, concentration, visuomotor processing speed, attention, verbal short-term and working memory, cognitive flexibility, semantic and phonematic word fluency, as well as verbal and visual memory functions. Neurologic PCS patients had more complaints with significantly higher fatigue scores as well as higher levels of depressive and anxiety symptoms compared to Non-PCS and HC. Deep neuropsychological assessment showed that neurologic PCS patients performed worse in a general screening of cognitive deficits compared to HC. Neurologic PCS patients showed impaired mental flexibility as an executive subfunction, verbal short-term memory, working memory and general reactivity (prolonged reaction time). Multiple regression showed fatigue affected processing speed; depression did not. Self-reported cognitive deficits of patients with neurologic PCS including fatigue, concentration, and memory deficits, are well mirrored in impaired performance of cognitive domains of concentration and working memory. The present results should be considered to optimize treatment algorithms for therapy and rehabilitation programs of PCS patients with neurologic symptoms.
Hydrogen gas inhalation ameliorates glomerular enlargement after hypoxic-ischemic insult in asphyxiated piglet model
Use of data mining algorithms in prediction of eggshell thickness from egg quality traits of Potchefstroom Koekoek layers
Abstract Egg quality is affected by lot of factors. Study was conducted to compare performance of data mining algorithms; Classification and regression tree (CART), Chi-square automatic interaction detection (CHAID), Exhaustive chi-square automatic interaction detection (Ex-CHAID) and Multivariate adaptive regression spline (MARS) in prediction of Potchefstroom Koekoek’s eggshell thickness from egg quality traits. 350 eggs were collected at 31st to 39th week to examine the egg quality traits. MARS with R2(0.86) revealed yolk ratio, shell weight, egg shape index, yolk ratio, shell ratio, albumen weight and albumen ratio as explanatory variables predicting eggshell thickness. CART with R2 (0.37), yolk/albumen ratio was noted to be influential predictor of eggshell thickness. CHAID and Ex-CHAID (R2= 0.35) discovered egg weight as the best predictor of eggshell thickness. MARS with R2(0.86) revealed yolk ratio, shell weight, egg shape index, yolk ratio, shell ratio, albumen weight and albumen ratio as explanatory variables predicting eggshell thickness. MARS had high r (0.925), R2 (0.856) and lower RMSE (0.129) and AIC (-975.331) compared to CHAID, Ex-CHAID and CART leading MARS to be the best data mining algorithm when predicting the eggshell thickness using egg quality traits.
Nationwide cervical precancer screening in Ghana: concurrent HPV DNA testing and visual inspection under an expanded hub-and-spoke model
Widespread anticoagulant resistance in house mice (Mus musculus musculus) linked to the Tyr139Phe mutation in the Czech Republic
Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems
Evaluating climate-related financial policies’ impact on decarbonization with machine learning methods
Abstract This study examines how Climate-Related Financial Policies (CRFPs) support decarbonization and renewable energy transitions across 87 countries from 2000 to 2023. Using the Policy Sequencing Score (PSS) and a bindingness-weighted adoption indicator, it explores the relationships between CRFPs, CO2 emissions, and Renewable Energy Production (REP) across diverse economic and institutional contexts. Findings reveal significant variation in outcomes. Advanced economies and OECD countries leverage structured policies and robust institutions to achieve steady emissions reductions and REP growth, with diminishing returns at higher policy intensities. Emerging Markets and Developing Economies (EMDEs) face institutional and structural constraints but show strong responsiveness to targeted policies, particularly in Sub-Saharan Africa and South Asia, where renewable energy growth potential is notable. Regions such as Latin America and East Asia display mixed trends, reflecting unique challenges and opportunities. Binding policies prove essential for environmental outcomes, particularly in institutionalized settings, while EMDEs require capacity building and international cooperation to address barriers. This study highlights the importance of tailoring CRFPs to specific contexts, emphasizing policy sequencing, enforcement, and capacity building. By identifying global and regional variations, the findings provide actionable insights for aligning financial systems with climate goals, fostering a sustainable low-carbon transition, and addressing equity challenges.
Supportive care needs of the family caregivers of urostomy patients: a qualitative study
The role of fat-soluble vitamins for graft-versus host disease after myeloablative conditioning in allogeneic stem cell transplanted patients
Harnessing advanced hybrid deep learning model for real-time detection and prevention of man-in-the-middle cyber attacks
Radiation-assisted tailoring of swelling behavior and water retention of Na-CMC/PAAm hydrogels for enhancing Beta Vulgaris under drought stress
AbstractThis study investigates the negative impact of climate change on water resources, specifically water for agricultural irrigation. It describes how to optimize swelling, gel properties and long-term water retention capacities of Na-CMC/PAAm hydrogels for managing drought stress of Sugar beet plants through techniques such as changing the composition, synthetic conditions and chemical modification. Gamma radiation-induced free radical copolymerization was used to synthesize superabsorbent hydrogels using sodium carboxymethyl cellulose (Na-CMC) and acrylamide (AAm). The study also explored how varying Na-CMC/AAm ratio and radiation dose influence their swelling behaviour, gel fraction, and water retention. FTIR showed that CMC and PAAm components are part of the hydrogel structure. The equilibrium swelling reached a maximum value of ~ 500 g/g at a Na-CMC/AAm ratio of 60/40. High content of AAm reduced swelling because it caused increased hydrophobicity while high radiation doses up to 50 kGy increased crosslinking resulting in improved but limited swelling from 65 to 85 (g/g). After the second cycle, KOH modification reached maximum swelling capacity by introducing anionic carboxylate groups up to 415 (g/g). SEM images revealed uniform pores in an unmodified scaffold while larger cavities were formed upon modification facilitating Water absorption. Surprisingly, the improved hydrogels retained more water: about 75% even after 16 days as opposed to a 50% drop within five days in the case of unmodified ones. This hydrogel significantly enhanced shoot length by 18%, root length by 32%, fresh weight shoot by 15%, and dry weight shoot by 15% under severe drought conditions. As a result, yield increased by 22%, proteins went up by 19%, and carbohydrates rose by 13%. Leaf chlorophyll content increased with a corresponding decline in stress enzymes indicating decreased oxidative damage. This eco-friendly Na-CMC/PAAm-based hydrogel seems to have potential use for addressing water scarcity and agricultural challenges.