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Objective: In the present research work, we examined the dietary Moringa oleifera effect on gut health and growth traits in chickens. Materials and Methods: There were 280 chicks (day old) that were weighted and allotted uniformly in seven groupings, each containing eight replicates (n = 5). Birds were supplemented with M. oleifera leaf extract (MLE) and seed extract (MSE) for 35 days. Group I was the control (fed merely basal diets), while Group II received 0.8% MLE, Group III was given 0.8% MSE, Group IV was given 1.2% MLE, Group V was given 1.2% MSE, Group VI was given 0.8% MLE + 0.8% MSE, and Group VII was given 1.2% MLE + 1.2% MSE. At the end of the fifth week, two chickens were selected from each replica, and samples (small intestine and ileal ingesta) were collected. Results: The chicken diet with MLE and MSE supplements saw significant improvement (p < 0.05) in both feed conversion ratio (FCR) and body weight gain (BWG). In the small intestine (duodenal, jejunal, and ileal), dietary MLE and MSE supplements significantly increased (p < 0.05) the surface area of the villus and the ratio of their height/crypt depth in comparison to the control group. The MLE and MSE supplements significantly increased (p < 0.05) the total goblet cell counts in the small intestine. The Lactobacillus spp. count was significantly improved (p < 0.05) and reduced (p < 0.05) in Escherichia coli counts when the bird diet was supplemented with MLE (0.8%) and MSE (0.8%). Conclusion: Results indicated that M. oleifera leaf and seed extract diet improved the growth trait and gut health in chickens.
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Plants have evolved intricate signaling pathways, which operate as networks governed by feedback to deal with stressors. Nevertheless, the sophisticated molecular mechanisms underlying these routes still need to be comprehended, and experimental validation poses significant challenges and expenses. Consequently, computational hypothesis evaluation gains prominence in understanding plant signaling dynamics. Biosensors are genetically modified to emit light when exposed to a particular hormone, such as abscisic acid (ABA), enabling quantification. We developed computational models to simulate the relationship between ABA concentrations and bioluminescent sensors utilizing the Hill equation and ordinary differential equations (ODEs), aiding better hypothesis development regarding plant signaling. Based on simulation results, the luminescence intensity was recorded for a concentration of 47.646 RLUs for 1.5 µmol, given the specified parameters and model assumptions. This method enhances our understanding of plant signaling pathways at the cellular level, offering significant benefits to the scientific community in a cost-effective manner. The alignment of these computational predictions with experimental results emphasizes the robustness of our approach, providing a cost-effective means to validate mathematical models empirically. The research intended to correlate the bioluminescence of biosensors with plant signaling and its mathematical models for quantified detection of specific plant hormone ABA.
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Ácido Abscísico , Técnicas Biosensibles , Modelos Teóricos , Transducción de Señal , Ácido Abscísico/metabolismo , Luminiscencia , Plantas/metabolismo , Mediciones Luminiscentes , Reguladores del Crecimiento de las Plantas/metabolismoRESUMEN
High concentrations of metals and sulfates in acid mine drainage (AMD) are the cause of the severe environmental hazard that mining operations pose to the surrounding ecosystem. Little study has been conducted on the cost-effective biological process for treating high AMD. The current research investigated the potential of the proposed carbon source and sulfate reduction bacteria (SRB) culture in achieving the bioremediation of sulfate and heavy metals. This work uses individual and combinatorial bioaugmentation and bio-stimulation methods to bioremediate acid-mine-influenced groundwater in batch microcosm experiments. Bioaugmentation and bio-stimulation methods included pure culture SRB (Desulfovibrio vulgaris) and microsized oil droplet (MOD) by emulsifying corn oil. The research tested natural attenuation (T 1), bioaugmentation (T2), biostimulation (T3), and bioaugmentation plus biostimulation (T4) for AM-contaminated groundwater remediation. Bioaugmentation and bio-stimulation showed the greatest sulfate reduction (75.3%) and metal removal (95-99%). Due to carbon supply scarcity, T1 and T2 demonstrated 15.7% and 27.8% sulfate reduction activities. Acetate concentrations in T3 and T4 increased bacterial activity by providing carbon sources. Metal bio-precipitation was substantially linked with sulfate reduction and cell growth. SEM-EDS study of precipitates in T3 and T4 microcosm spectra indicated peaks for S, Cd, Mn, Cu, Zn, and Fe, indicating metal-sulfide association for metal removal precipitates. The MOD provided a constant carbon source for indigenous bacteria, while Desulfovibrio vulgaris increased biogenic sulfide synthesis for heavy metal removal.
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Desulfovibrio vulgaris , Desulfovibrio , Metales Pesados , Biodegradación Ambiental , Aceite de Maíz , Zea mays , Ecosistema , Bacterias , Ácidos , Sulfatos , Carbono , SulfurosRESUMEN
The coronavirus disease 2019 (COVID-19) pandemic, which emerged in late 2019, has caused millions of infections and fatalities globally, disrupting various aspects of human society, including socioeconomic, political, and educational systems. One of the key challenges during the COVID-19 pandemic is accurately predicting the clinical development and outcome of the infected patients. In response, scientists and medical professionals globally have mobilized to develop prognostic strategies such as risk scores, biomarkers, and machine learning models to predict the clinical course and outcomes of COVID-19 patients. In this contribution, we deployed a mathematical approach called matrix factorization feature selection to select the most relevant features from the anonymized laboratory biomarkers and demographic data of COVID-19 patients. Based on these features, developed a model that leverages the deep stacking neural network (DSNN) to aid in clinical care by predicting patients' mortality risk. To gauge the performance of our suggested model, performed a comparative analysis with principal component analysis plus support vector machine, deep learning, and random forest, achieving outstanding performances. The DSNN model outperformed all the other models in terms of area under the curve (96.0%), F1-score (98.1%), recall (98.5%), accuracy (99.0%), precision (97.7%), specificity (97.0%), and maximum probability of correction decision (93.4%). Our model outperforms the clinical predictive models regarding patient mortality risk and classification in the literature. Therefore, we conclude that our robust model can help healthcare professionals to manage COVID-19 patients more effectively. We expect that early prediction of COVID-19 patients and preventive interventions can reduce the mortality risk of patients.
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COVID-19 , Médicos , Humanos , Pandemias , Redes Neurales de la Computación , BiomarcadoresRESUMEN
Diabetes mellitus (DM) is a metabolic complication and can pose a serious challenge to human health. DM is the main cause of many life-threatening diseases. Researchers of natural products have been continuously engaged in treating vital diseases in an economical and efficient way. In this research, we extensively used phytosteroids from Notholirion thomsonianum (Royle) Stapf for the treatment of DM. The structures of phytosteroids NtSt01 and NtSt02 were confirmed with gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR) analyses. Through in vitro studies including α-glucosidase, α-amylase, and DPPH assays, compound NtSt01 was found to be comparatively potent. An elevated dose of compound NtSt01 was also found to be safe in an experimental study on rats. With a dose of 1.0 mg/kg of NtSt01, the effect on blood glucose levels in rats was observed to be 519 ± 3.98, 413 ± 1.87, 325 ± 1.62, 219 ± 2.87, and 116 ± 1.33 mg/dL on the 1st, 7th, 14th, 21st, and 28th, days, respectively. The in vivo results were compared with those of glibenclamide, which reduced the blood glucose level to 107 ± 2.33 mg/dL on the 28th day. On the 28th day of NtSt01 administration, the average weights of the rats and vital organs (liver, kidney, pancreas, and heart) remained healthy, with a slight increase. The biochemical parameters of the blood, i.e., serum creatinine, blood urea, serum bilirubin, SGPT (or ALT), and serum alkaline phosphatase, of rats treated with NtSt01 remained in the normal ranges. Similarly, the serum cholesterol, triglycerides, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels also remained within the standard ranges. It is obvious from our overall results that the phytosteroids (specifically NtSt01) had an efficient therapeutic effect on the blood glucose level, protection of vital organs, and blood biochemistry.
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There is now widespread agreement that global warming is the source of climate variability and is a global danger that poses a significant challenge for the 21st century. Climate crisis has exacerbated water deficit stress and restricts plant's growth and output by limiting nutrient absorption and raising osmotic strains. Worldwide, Sweet pepper is among the most important vegetable crops due to its medicinal and nutritional benefits. Drought stress poses negative impacts on sweet pepper (Capsicum annuum L.) growth and production. Although, γ aminobutyric acid (GABA) being an endogenous signaling molecule and metabolite has high physio-molecular activity in plant's cells and could induce tolerance to water stress regimes, but little is known about its influence on sweet pepper development when applied exogenously. The current study sought to comprehend the effects of foliar GABA application on vegetative development, as well as physiological and biochemical constituents of Capsicum annuum L. A Field experiment was carried out during the 2021 pepper growing season and GABA (0, 2, and 4mM) concentrated solutions were sprayed on two Capsicum annuum L. genotypes including Scope F1 and Mercury, under drought stress of 50% and 30% field capacity. Results of the study showed that exogenous GABA supplementation significantly improved vegetative growth attributes such as, shoot and root length, fresh and dry weight, as well as root shoot ratio (RSR), and relative water content (RWC) while decreasing electrolyte leakage (EL). Furthermore, a positive and significant effect on chlorophyll a, b, a/b ratio and total chlorophyll content (TCC), carotenoids content (CC), soluble protein content (SPC), soluble sugars content (SSC), total proline content (TPC), catalase (CAT), and ascorbate peroxidase (APX) activity was observed. The application of GABA at 2mM yielded the highest values for these variables. In both genotypes, peroxidase (POD) and superoxide dismutase (SOD) content increased with growing activity of those antioxidant enzymes in treated plants compared to non-treated plants. In comparison with the rest of GABA treatments, 2mM GABA solution had the highest improvement in morphological traits, and biochemical composition. In conclusion, GABA application can improve development and productivity of Capsicum annuum L. under drought stress regimes. In addition, foliar applied GABA ameliorated the levels of osmolytes and the activities of antioxidant enzymes involved in defense mechanism.
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Capsicum , Antioxidantes , Clorofila A , Sequías , Productos Agrícolas , DeshidrataciónRESUMEN
The pursuit of environmentally friendly solvents has become an essential research topic in sustainable chemistry and nanomaterial science. With the need to substitute toxic solvents in nanofabrication processes becoming more pressing, the search for alternative solvents has taken on a crucial role in this field. Additionally, the use of toxic, non-economical organic solvents, such as N-methyl-2 pyrrolidone and dimethylformamide, is not suitable for all biomedical applications, even though these solvents are often considered as the best exfoliating agents for nanomaterial fabrication. In this context, the success of producing two-dimensional transition metal dichalcogenides (2D TMDs), such as MoS2 and WS2, with excellent captivating properties is due to the ease of synthesis based on environment-friendly, benign methods with fewer toxic chemicals involved. Herein, we report for the first time on the use of cyrene as an exfoliating agent to fabricate monolayer and few-layered 2D TMDs with a versatile, less time-consuming liquid-phase exfoliation technique. This bio-derived, aprotic, green and eco-friendly solvent produced a stable, surfactant-free, concentrated 2D TMD dispersion with very interesting features, as characterized by UV-visible and Raman spectroscopies. The surface charge and morphology of the fabricated nanoflakes were analyzed using ς-potential and scanning electron microscopy. The study demonstrates that cyrene is a promising green solvent for the exfoliation of 2D TMD nanosheets with potential advantages over traditional organic solvents. The ability to produce smaller-sized-especially in the case of WS2 as compared to MoS2-and mono/few-layered nanostructures with higher negative surface charge values makes cyrene a promising candidate for various biomedical and electronic applications. Overall, the study contributes to the development of sustainable and environmentally friendly methods for the production of 2D nanomaterials for various applications.
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Nanoestructuras , Elementos de Transición , Solventes , Molibdeno/química , Elementos de Transición/química , Nanoestructuras/químicaRESUMEN
Microbial fuel cells (MFCs) seem to have emerged in recent years to degrade the organic pollutants from wastewater. The current research also focused on phenol biodegradation using MFCs. According to the US Environmental Protection Agency (EPA), phenol is a priority pollutant to remediate due to its potential adverse effects on human health. At the same time, the present study focused on the weakness of MFCs, which is the low generation of electrons due to the organic substrate. The present study used rotten rice as an organic substrate to empower the MFC's functional capacity to degrade the phenol while simultaneously generating bioenergy. In 19 days of operation, the phenol degradation efficiency was 70% at a current density of 17.10 mA/m2 and a voltage of 199 mV. The electrochemical analysis showed that the internal resistance was 312.58 Ω and the maximum specific capacitance value was 0.00020 F/g on day 30, which demonstrated mature biofilm production and its stability throughout the operation. The biofilm study and bacterial identification process revealed that the presence of conductive pili species (Bacillus genus) are the most dominant on the anode electrode. However, the present study also explained well the oxidation mechanism of rotten rice with phenol degradation. The most critical challenges for future recommendations are also enclosed in a separate section for the research community with concluding remarks.
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Fuentes de Energía Bioeléctrica , Humanos , Fuentes de Energía Bioeléctrica/microbiología , Aguas Residuales , Oxidación-Reducción , Fenol , Fenoles , Electrodos , ElectricidadRESUMEN
Herein we report the fabrication of cationic functionalized cellulose nanofibers (c-CNF) having 0.13 mmol.g-1 ammonium content and its ionic crosslinking via the pad-batch process. The overall chemical modifications were justified through infrared spectroscopy. It is revealed that the tensile strength of ionic crosslinked c-CNF (zc-CNF) improved from 3.8 MPa to 5.4 MPa over c-CNF. The adsorption capacity of zc--CNF was found to be 158 mg.g-1 followed by the Thomas model. Further, the experimental data were used to train and test a series of machine learning (ML) models. A total of 23 various classical ML models (as a benchmark) were compared simultaneously using Pycaret which helped reduce the programming complexity. However, shallow, and deep neural networks are used that outperformed the classic machine learning models. The best classical-tuned ML model using Random Forests regression had an accuracy of 92.6 %. The deep neural network made effective by early stopping and dropout regularization techniques, with 20 × 6 (Neurons x Layers) configuration, showed an appreciable prediction accuracy of 96 %.
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Celulosa , Nanofibras , Celulosa/química , Nanofibras/química , Adsorción , Resistencia a la Tracción , Espectrofotometría Infrarroja , IonesRESUMEN
The present study used a bioassay of immobilized microalgae (Chlorella vulgaris) via direct contact to assess the toxicity of eleven uncontaminated (reference) and five field contaminated soils with various physicochemical properties and contamination. Photosynthetic oxygen concentration in the headspace of the test kit by Chlorella vulgaris in the reference soils ranged between 12.93% and 14.80% and only 2.54%-7.14% in the contaminated soils, respectively. Inherent test variability (CVi) values ranged between 2.90% and 9.04%; variation due to soil natural properties (CVrs) ranged between 0.33% and 13.0%; and minimal detectable difference (MDD) values ranged from 4.69% to 11.6%. A computed toxicity threshold of 15% was established for microalgae soil toxicity tests based on calculations of the maximal tolerable inhibition (MTI). All contaminated soils were considered toxic to microalgae because their levels of inhibition ranged between 39.5% and 82.9%, exceeding the 15% toxicity threshold. It can be concluded that the elevated concentrations of heavy metals and organic contaminants in the contaminated soils induced the higher inhibitory levels. Overall, direct contact soil toxicity tests using immobilized microalgae provided coherent and repeatable data and can be utilized as a simple and suitable tool for the toxicity testing of contaminated field soils.
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Chlorella vulgaris , Metales Pesados , Microalgas , Contaminantes del Suelo , Bioensayo , Metales Pesados/análisis , Suelo/química , Contaminantes del Suelo/análisis , Contaminantes del Suelo/toxicidadRESUMEN
The objective of the current study was to evaluate the phytochemical and pharmacological potential of the Cornus macrophylla. C. macrophylla belongs to the family Cornaceae. It is locally known as khadang and is used for the treatment of different diseases such as analgesic, tonic, diuretic, malaria, inflammation, allergy, infections, cancer, diabetes, and lipid peroxidative. The crude extract and different fractions of C. macrophyll were evaluated by gas chromatography and mass spectroscopy (GC-MS), which identified the most potent bioactive phytochemicals. The antioxidant ability of C. macrophylla was studied by 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid (ABTS) and 1,1 diphenyl-2-picryl-hydrazyl (DPPH) methods. The crude and subsequent fractions of the C. macrophylla were also tested against anti-inflammatory enzymes using COX-2 (Cyclooxygenase-2) and 5-LOX (5-lipoxygenase) assays. The molecular docking was carried out using molecular operating environment (MOE) software. The GC-MS study of C. macrophylla confirmed forty-eight compounds in ethyl acetate (Et.AC) fraction and revealed that the Et.AC fraction was the most active fraction. The antioxidant ability of the Et.AC fraction showed an IC50 values of 09.54 µg/mL and 7.8 µg/mL against ABTS and DPPH assay respectively. Among all the fractions of C. macrophylla, Et.AC showed excellent activity against COX-2 and 5-LOX enzyme. The observed IC50 values were 93.35 µg/mL against COX-2 and 75.64 µg/mL for 5-LOX respectively. Molecular docking studies supported these in vitro results and confirmed the anti-inflammatory potential of C. macrophylla. C. macrophylla has promising potential as a source for the development of new drugs against inflammation in the future.
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Antioxidantes , Cornus , Antiinflamatorios/química , Antiinflamatorios/farmacología , Antioxidantes/química , Antioxidantes/farmacología , Ciclooxigenasa 2 , Humanos , Inflamación , Simulación del Acoplamiento Molecular , Fitoquímicos/farmacología , Corteza de la Planta , Extractos Vegetales/química , Extractos Vegetales/farmacologíaRESUMEN
AIM: The study was planned to investigate the phytochemicals, antidiabetic and antioxidant studies of A. consanguineum. METHODS: The preliminary studies were performed on crude extract and different solvent fractions. Based on the potency, the chloroform fraction was semi-purified to phyto-fractions CHF-1 - 5. Furthermore, CHF-3 was subjected to isolation of pure compounds using column chromatography. The α-glucosidase, α-amylase and antioxidant assays (DPPH, ABTS, H2O2) were performed on all samples. The in-vivo experiments on compounds 1 and 2 were also performed using oral glucose tolerance test. Docking studies were performed on α-glucosidase and α-amylase targets. RESULTS: Among all fractions, the chloroform fraction exhibited excellent activities profile giving IC50 values of 824, 55, 117, 58 and 85 µg/ml against α-glucosidase, α-amylase, DPPH, ABTS and H2O2 targets respectively. Among the five semi-purified chloroform phyto-fractions (CHF-1-5), CHF-3 was the leading fraction in activities giving IC50 values of 85.54, 61.19 and 26.58 µg/ml against α-glucosidase, α-amylase and DPPH respectively. Based on the overall potency and physical amount of CHF-3, it was subjected to purification to get compounds 1 and 2. The two compounds were also found potent in in-vitro activities. The observed IC50 values for compound 1 were 7.93, 28.01 and 6.19 µg/ml against α-glucosidase, α-amylase and DPPH respectively. Similarly, the compound 2 exhibited IC50 of 14.63, 24.82 and 7.654 µg/ml against α-glucosidase, α-amylase and DPPH respectively. Compounds 1 and 2 were potent in decreasing the blood glucose levels in experimental animals. Compounds 1 and 2 also showed interactions with the respective enzymes with molecular docking. CONCLUSIONS: We can conclude that A. Consanguineum is a rich source of natural antidiabetic agents. Bioguided isolation of compound 1 and 2 showed potential inhibitions in all tested in-vitro antidiabetic targets. Further, both the compounds were also able to decrease the blood glucose levels in experimental animals.
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Allium , Antioxidantes , Animales , Antioxidantes/química , Glucemia , Cloroformo , Peróxido de Hidrógeno , Hipoglucemiantes/química , Hipoglucemiantes/farmacología , Simulación del Acoplamiento Molecular , Extractos Vegetales/química , alfa-Amilasas , alfa-GlucosidasasRESUMEN
This research was planned to synthesize cyano-acetate derivatives of succinimide and evaluate its comparative biological efficacy as anti-inflammatory, anti-cholinesterase and anti-diabetic, which was further validated by molecular docking studies. The three cyano-acetate derivatives of succinimide including compound 23 Methyl 2-cyano-2-(2,5-dioxopyrrolidin-3-yl)acetate, compound 31 Methyl 2-cyano-2-(1-methyl-2,5-dioxopyrrolidin-3-yl)acetate and compound 44 Methyl 2-cyano-2-(1-ethyl-2,5-dioxopyrrolidin-3-yl) acetate were synthesized. The mentioned compounds were checked for in vitro anti-inflammatory, anti-cholinesterase and anti-diabetic (α-amylase inhibition) activity. To validate the in vitro results, computational studies were carried out using molecular operating environment to analyse the BE, i.e. binding energies of all synthesized compounds against the respective enzymes. The Compounds 23, 31, 44 exhibited anti-inflammatory via inhibiting COX-2 (IC50 value of 204.08, 68.60 and 50.93 µM, respectively), COX-1 (IC50 value of 287, 185, and 143 µM, respectively) and 5-LOX (IC50 value of 138, 50.76 and 20, 87 µM respectively). They exhibited choline-mimetic potential, such as compound 23, 31 and 44 inhibited AChE enzyme (IC50 value of 240, 174, and 134 µM, respectively) and BChE enzyme (IC50 value of 203, 134 and 97 µM, respectively). The Compounds 23, 31, 44 exhibited anti-diabetic effect via inhibiting α-amylase enzyme (IC50 values of 250, 106 and 60 µM, respectively). Molecular docking studies revealed that the synthesized compounds have good binding affinity in the binding pockets of AChE, BChE, COX-2, 5-LOX and α-amylase enzyme and showed high binding energies. The synthesized succinimide derivatives, i.e. compound 23, 31, 44 showed marked inhibitory activities against cyclooxygenase, lipoxygenase, α-amylase and cholinesterase enzymes. Among these three, compound 44 and 31 showed strong anti-inflammatory and anti-diabetic activity while they displayed moderate anti-cholinesterase activity supported by molecular docking results.Communicated by Ramaswamy H. Sarma.
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Prostrate knotweed also called Polygonum aviculare is an important edible plant. The polygonum is majorly known for the phenolics and antioxidants. The antioxidants combat the excessive free radicals within the body. The excessive free radicals are implicated in various other diseases like diabetes, Alzheimer's, and inflammation. This study was aimed at exploring the antioxidant bioactives and their derivatizations to produce new molecules with advanced pharmacological features. We have isolated six compounds (1-6) from Polygonum aviculare. Furthermore, rational-based chemical derivatives for compound 5 have been formed for the management of diabetes, Alzheimer's, and inflammation. In preliminary antioxidant studies, all the isolated compounds (1-6) showed potential results against DPPH and ABTS free radicals. Based on the IC50 and chemical nature of the compounds, compound 5 was subjected to derivatization. Keeping the phenolic part of compound 5 unaffected, hydroxy succinimide (5A) and thiazolidinedione (5B) were synthesized. The compound 5A was found to be a potent inhibitor of AChE, BChE, COX-1, COX-2, 5-LOX, and DPPH giving IC50 values of 10.60, 15.10, 13.91, 1.08, 0.71, and 1.05 µM, respectively. The COX-2 selectivity of compound 5A was found at 12.9. The compound 5B was found to be a potent multitarget antidiabetic agent giving IC50 values of 15.34, 21.83, 53.28, and 1.94 µM against α-glucosidase, α-amylase, protein tyrosine phosphatase 1B, and DPPH. Docking studies were performed to manipulate the binding interactions. The docking pose of all the tested compounds was found to have increased binding affinity against all tested targets that supported the in vitro results. Our results showed that Polygonum aviculare is a rich source of antioxidant compounds. The two new derivatives have enhanced pharmacological features to treat diabetes, inflammation, and Alzheimer's disease.
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Enfermedad de Alzheimer , Diabetes Mellitus , Polygonum , Antioxidantes/química , Antioxidantes/farmacología , Ciclooxigenasa 2 , Hipoglucemiantes/farmacología , Inflamación , Simulación del Acoplamiento MolecularRESUMEN
The prevalence of diabetes mellitus is persistently increasing globally creating a serious public health affliction. Diabetes mellitus is categorized into two major types designated as type I and Type II. Type I diabetes mellitus is characterized by complete lack of secretion of insulin, while Type II diabetes mellitus is the resistance of peripheral tissues to the action of insulin and inadequate compensatory secretion of insulin. Chronic hyperglycemia associated with diabetes causes failure of cardiovascular system, nervous system, kidneys, and eyes. At present, different types of drugs are used for the management of diabetes, but each of them is associated with more or less serious side effects. Therefore, we need to develop new therapeutic agents that have better efficacy and safety profile. In this study, three ketone derivatives of succinimides were synthesized based on Michael addition and characterized using NMR. All the synthesized compounds were checked for their in vitro α-amylase and α-glucosidase inhibitory activities. Further the synthesized compounds were also explored for their antioxidant activities, i.e, DPPH and ABTS assays. Based on the in vitro results, the synthesized compounds were further evaluated for in vivo antidiabetic activity. The synthesized compounds were (2-oxocyclohexyl)-1-phenylpyrrolidine-2,5-dione (BW1), benzyl-3-(2-oxocyclohexyl) pyrrolidine-2,5-dione (BW2), and (4-bromophenyl)-3-(2-oxocyclohexyl) pyrrolidine-2,5-dione (BW3). BW1 showed the highest inhibitory activity for DPPH causing 83.03 ± 0.48 at 500 µg/ml with IC50 value of 10.84 µg/ml and highest inhibitory activity for ABTS causing 78.35 ± 0.23 at 500 µg/ml with IC50 value of 9.40 µg/ml against ascorbic acid used as standard. BW1 also exhibited the highest activity against α-amylase and α-glucosidase inhibition causing 81.60 ± 0.00 at concentrations of 500 µg/ml with IC50 value of 13.90 µg/ml and 89.08 ± 1.04 at concentrations of 500 µg/ml with IC50 value of 10.49 µg/ml, respectively, against the standard drug acarbose.
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BACKGROUND: The coronavirus (COVID-19) is a novel pandemic and recently we do not have enough knowledge about the virus behaviour and key performance indicators (KPIs) to assess the mortality risk forecast. However, using a lot of complex and expensive biomarkers could be impossible for many low budget hospitals. Timely identification of the risk of mortality of COVID-19 patients (RMCPs) is essential to improve hospitals' management systems and resource allocation standards. METHODS: For the mortality risk prediction, this research work proposes a COVID-19 mortality risk calculator based on a deep learning (DL) model and based on a dataset provided by the HM Hospitals Madrid, Spain. A pre-processing strategy for unbalanced classes and feature selection is proposed. To evaluate the proposed methods, an over-sampling Synthetic Minority TEchnique (SMOTE) and data imputation approaches are introduced which is based on the K-nearest neighbour. RESULTS: A total of 1,503 seriously ill COVID-19 patients having a median age of 70 years old are comprised in the research work, with 927 (61.7%) males and 576 (38.3%) females. A total of 48 features are considered to evaluate the proposed method, and the following results are achieved. It includes the following values i.e., area under the curve (AUC) 0.93, F2 score 0.93, recall 1.00, accuracy, 0.95, precision 0.91, specificity 0.9279 and maximum probability of correct decision (MPCD) 0.93. CONCLUSION: The results show that the proposed method is significantly best for the mortality risk prediction of patients with COVID-19 infection. The MPCD score shows that the proposed DL outperforms on every dataset when evaluating even with an over-sampling technique. The benefits of the data imputation algorithm for unavailable biomarker data are also evaluated. Based on the results, the proposed scheme could be an appropriate tool for critically ill Covid-19 patients to assess the risk of mortality and prognosis.
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COVID-19 , Aprendizaje Profundo , Anciano , Algoritmos , Área Bajo la Curva , Femenino , Humanos , Masculino , PronósticoRESUMEN
Herbal medicines are gaining popularity worldwide for human healthcare because of their therapeutic potential. However, adulteration and use of unauthentic raw herbals as substitutes have become a major issue for the local communities and industry for reasons of safety and efficacy. Therefore, the authentication of medicinal plants before their use in herbal medicines is a need of time. Hence, the present study was designed with an aim, to authenticate the therapeutic Lamiaceous taxa by using pollen traits observed under scanning electron microscopy. Pollen micro-morphological studies solve the problem through discrimination and correct identification of the Lamiaceae species from the adulterants. Based on pollen features, Lamiaceae were further divided into two sub-families Lamioideae (tricolpate) and Nepetoideae (hexa-colpate). The pollen grains of Lamioideae were found as small to medium-sized, tricolpate, radially/bilateral symmetrical, sub-spheroidal and oblate shape. Besides, exine patterns bireticulate, reticulate and micro-reticulate, colpus surface sculpturing as psilate, gemmate, scabrate, and verrucate have also been reported. A significant variation was found in the pattern of the reticulum, thickness, and the number of secondary lumina per primary lumen. Similarly, Nepetoideae has a hexa zono-colpate pollen but tri and tetra zono-colpate pollen have also been observed. Hence, this study contributes to the authentication and correct identification of medicinally important Lamiaceae taxa by using scanning electron microscopic techniques and can help to solve the adulteration problem. Highlights Authentication of medicinally important Lamiceous taxa was carried out through scanning electron microscopic techniques. Chemotaxonomic characterization was used for the accurate identification of the therapeutic taxa. The medicinal, palynological and phytochemical significance of Lamiaceae taxa were evaluated. A significant variation was seen in the palynological traits that help in the determination and authentication of the therapeutic Lamiaceous species. Based on the chemotaxonomic characterization, our study can help to solve the adulteration problem for the reason of safety and efficacy.
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Lamiaceae , Humanos , Lamiaceae/anatomía & histología , Microscopía Electrónica de Rastreo , Polen/ultraestructuraRESUMEN
Bioremediation and phytoremediation have demonstrated potential for decontamination of petroleum hydrocarbon-impacted soils. The total petroleum hydrocarbons (TPHs) are known to induce phytotoxicity, reduce water retention in soil, associate hydrophobic nature and contaminants' in situ heterogeneous distribution, limit soil nutrient release and reduce soil aeration and compaction. The ageing of TPHs in contaminated soils further hinders the degradation process. Soil amendments can promote plant growth and enhance the TPH removal from contaminated aged soil. In the present experiment, remediation of TPH-contaminated aged soil was performed by Italian ryegrass, with compost (COM, 5%), biochar (BC, 5%) and immobilized microorganisms' technique (IMT). Results revealed that significantly highest hydrocarbon removal (40%) was noted in mixed amendments (MAA) which contained BC + COM + IMT, followed by COM (36%), compared to vegetative control and other treatments. The higher TPH removal in aged soil corresponds with the stimulated rhizospheric effects, as evidenced by higher root biomass (85-159% increase), and bacterial count compared to NA control. Phyto-stimulants actions of biochar and IMT improved seed germination of Italian ryegrass. The compost co-amendment with other treatments showed improvement in plant physiological status. These results suggested that plant growth and TPH removal from aged, contaminated soils using BC, COM and IMT can improve bioremediation efficiency.
Asunto(s)
Lolium , Petróleo , Contaminantes del Suelo , Hidrocarburos , Suelo , Contaminantes del Suelo/análisisRESUMEN
The current study reports the effect of different wt. ratios of copper oxide nanoparticle (CuO-NPs) and reduced graphene oxide (rGO) as fillers on mechanical, electrical, and thermal properties of waste polystyrene (WPS) matrix. Firstly, thin sheets of WPS-rGO-CuO composites were prepared through solution casting method with different ratios, i.e., 2, 8, 10, 15 and 20 wt.% of CuO-NPs and rGO in WPS matrix. The synthesized composite sheets were characterized by Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray (EDX), X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM) and thermal gravimetric analysis (TGA). The electrical conductance and mechanical strength of the prepared composites were determined by using LCR meter and universal testing machine (UTM). These properties were dependent on the concentrations of CuO-NPs and rGO. Results display that the addition of both fillers, i.e., rGO and CuO-NPs, collectively led to remarkable increase in the mechanical properties of the composite. The incorporation of rGO-CuO: 15% WPS sample, i.e., WPS-rGO-CuO: 15%, has shown high mechanical strength with tensile strength of 25.282 MPa and Young modulus of 1951.0 MPa, respectively. Similarly, the electrical conductance of the same composite is also enhanced from 6.7 × 10-14 to 4 × 10-7 S/m in contrast to WPS at 2.0 × 106 Hz. The fabricated composites exhibited high thermal stability through TGA analysis in terms of 3.52% and 6.055% wt. loss at 250 °C as compared to WPS.
RESUMEN
The primary purpose of this study was to extract ß-conglycinin (7S) and glycinin (11S) from soybean seed, soybean meals and soybean protein isolate and compare their yield and purity. The previous methods were modified for the extraction and isolation of 7S and 11S globulins. The adjustment mainly included sample to solution ratio of 1:10 (previously 1:15). Comparing the yield of 11S fraction in Tris-HCl and water as extractable solutions, it was almost doubled in soybean seed (16.97% to 32.41%) with purity from 96 to 98% respectively. In case of soybean meal, samples yield increased from 45.46 to 61.86% with purity from 94 to 98%. On contrary, 7S yield was significantly improved in soybean protein isolate sample from 30.33 to 53.81% along with no contamination in its purity while soybean seed and soybean meal samples had less increase in both yield and purity in Tris-HCl and water as extractable solutions. Results of this study will bring new insights into soybean 7S and 11S separation and purification techniques as well as pave the way for their application in food industry.