The Effectiveness of Cyrene as a Solvent in Exfoliating 2D TMDs Nanosheets.

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.

Bioenergy Generation and Phenol Degradation through Microbial Fuel Cells Energized by Domestic Organic Waste.

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.

Prognosis patients with COVID-19 using deep learning.

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.

A direct contact bioassay using immobilized microalgal balls to evaluate the toxicity of contaminated field soils.

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.

Phytochemical Profiling, Anti-Inflammatory, Anti-Oxidant and In-Silico Approach of Cornus macrophylla Bioss (Bark).

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.

Optimization of Fenton process for removing TOC and color from swine wastewater using response surface method (RSM).

The Fenton oxidation process was applied to biologically treated swine wastewater (BSWW) for the removal of TOC and color constituents after coagulation with FeCl3. Optimizing of operational variables such as FeSO4 and H2O2 doses was achieved by the response surface method (RSM). Statistical analysis led to the conclusion that FeSO4 is the more important than H2O2 in the removal of TOC. However, H2O2 plays a more significant role than FeSO4 in color removal. The optimal conditions for effective removal of TOC and color from swine wastewater were derived by using process optimization. The experimental results show that overall removal of TOC and color is 76.7% and 98%, respectively, when optimal conditions of 800 mg/L (FeSO4) and 5207 mg/L (H2O2) at 120 min were used. Furthermore, the optimization model produces a desirability value of 0.980 that verifies the optimal conditions. Finally, it is observed that removal of undesirable compounds follows a pseudo-first order and pseudo-second order kinetics model with high R2 values of 0.99 for both TOC and color removal, respectively. Statistical analysis and process optimization show that the employed model may determine conditions conducive to the effective removal of TOC and color from swine wastewater.

Real-time biomonitoring of oxygen uptake rate and biochemical oxygen demand using a novel optical biogas respirometric system.

In response to the ever-increasing need for monitoring-based process control of wastewater treatment plants, an online applicable respirometer shows great promise for real-time measurement of oxygen uptake rate (OUR) and biochemical oxygen demand (BOD) measurements as a surrogate of the biodegradability of wastewater. Here, we have developed a photosensor-assisted real-time respirometric system equipped with bubble counting sensors for accurate measurement of microbial oxygen consumption in a bottle. This system can measure OUR and BOD in a bottle equipped with a tube containing NaOH solution to absorb carbon dioxide and supplied with continuous atmospheric oxygen to the bottle, which reliably supplies non-limiting dissolved oxygen (DO) for aerobic biodegradation even at high organic loads. These technical improvements allow a sensitive and rapid analytical tool offering real-time profiles of oxygen uptake rate as well as BOD measurements with an extended measurable range (0-420 mg O2/L), enabling significant reduction or elimination of dilution steps. The respirometric system was used to elucidate the biodegradable kinetics of domestic and swine wastewaters as a function of the type and concentration of organic matters, depending on source characteristics including rapidly or slowly oxidizable organic substances by bacteria. Compared with conventional and manometric BOD methods, our method is reliable and accurate.

Synthesis, in-vitro α-glucosidase inhibition, antioxidant, in-vivo antidiabetic and molecular docking studies of pyrrolidine-2,5-dione and thiazolidine-2,4-dione derivatives.

α-Glucosidase is considered as a therapeutic target for the treatment of type 2 diabetes mellitus (DM2). In current study, we synthesized pyrrolidine-2,5-dione (succinimide) and thiazolidine-2,4-dione derivatives and evaluated for their ability to inhibit α-Glucosidase. Pyrrolidine-2,5-dione derivatives (11a-o) showed moderate to poor α-glucosidase inhibition. Compound 11o with the IC50 value of 28.3 ±â€¯0.28 µM emerged as a good inhibitor of α-glucosidase. Thiazolidine-2,4-dione and dihydropyrimidine (TZD-DHPM) hybrids (22a-c) showed excellent inhibitory activities. The most active compound 22a displayed IC50 value of 0.98 ±â€¯0.008 µM. Other two compounds of this series also showed activity in low micromolar range. The in-vivo antidiabetic study of three compounds 11n, 11o and 22a were also determined using alloxan induced diabetes mice model. Compounds 11o and 22a showed significant hypoglycemic effect compared to the reference drug. In-vivo acute toxicity study showed the safety of these selected compounds. In-silico docking studies were carried out to rationalize the in-vitro results. The binding modes and bioassay results of TZD-DHPM hybrids showed that interactions with important residues appeared significant for high potency.

Gastric emptying scintigraphy in postprandial distress syndrome.

OBJECTIVE: To find out the pattern of gastric emptying scintigraphy (GES) in patients with post prandial distress syndrome (PDS). METHODS: This study was carried out from January 2015 to July 2016 at Combined Military Hospital (CMH) Kharian and Nuclear Medical Centre (NMC) of Armed Forces Institute of Pathology (AFIP) Rawalpindi. Patient's inclusion criteria were dyspepsia of post prandial distress type for more than six months duration. Patients with dyspepsia due to epigastric pain syndrome and other organic disorder were excluded. Upper gastrointestinal endoscopy was performed in all patients to rules out organic causes. Four-hour Gastric emptying scintigraphy was carried out at NMC, AFIP. Results were compiled and statistical assessment was done by utilizing SPSS IBM 22 version. RESULTS: Thirty-eight patients were included in the study with age range from 15-72 years with mean age of 37.05±13.5 years. Males were 28(73.7%) and 10(26.7%) were female. Mean gastric retention with SD at one, two, three and four hours were 63 ± 19.04, 37± 20.62, 19±16.66 and 10±12.73 percent respectively. Early gastric emptying was in 3(7.89%) and delayed gastric emptying at two and four hours was seen in 4(10.52%) and 12(32%) respectively. Seventeen (44%) of the patients had normal gastric emptying despite the classical symptoms of PDS. CONCLUSION: Gastric dysmotility in GES seen in half of the patients points some additional mechanism as well like gastric accommodation or visceral hypersensitivity in the patients with PDS.

Nickel adsorption onto polyurethane ethylene and vinyl acetate sorbents.

The present study was conducted to appraise the efficiencies of polyurethane ethylene sorbent (PES) and vinyl acetate sorbent (VAS) for nickel (Ni) adsorption. Process variables, i.e. Ni(II) ions initial concentration, pH, contact time and adsorbent dosage were optimized by response surface methodology (RSM) approach. The Ni(II) adsorption was fitted to the kinetic models (pseudo-first-order and pseudo-second-order) and adsorption isotherms (Freundlich and Langmuir). At optimum conditions of process variables, 171.99 mg/g (64.7%) and 388.08 mg/g (92.7%) Ni(II) was adsorbed onto PES and VAS, respectively. The RSM analysis revealed that maximum Ni(II) adsorption can be achieved at 299 mg/L Ni(II) ions initial concentration, 4.5 pH, 934 min contact time and 1.3 g adsorbent dosage levels for PES, whereas the optimum values for VAS were found to be 402 mg/L Ni(II) ions initial concentration, 4.6 pH, 881 min contact time and 1.2 g adsorbent dosage, respectively. The -OH and -C = O- were involved in the Ni(II) adsorption onto PES and VAS adsorbents. At optimum levels, up to 53.67% and 80.0% Ni(II) was removed from chemical industry wastewater using PES and VAS, respectively, which suggest that PES and VAS could possibly be used for Ni(II) adsorption from industrial wastewater.

Explicit formula of finite difference method to estimate human peripheral tissue temperatures during exposure to severe cold stress.

During cold exposure, peripheral tissues undergo vasoconstriction to minimize heat loss to preserve the maintenance of a normal core temperature. However, vasoconstricted tissues exposed to cold temperatures are susceptible to freezing and frostbite-related tissue damage. Therefore, it is imperative to establish a mathematical model for the estimation of tissue necrosis due to cold stress. To this end, an explicit formula of finite difference method has been used to obtain the solution of Pennes' bio-heat equation with appropriate boundary conditions to estimate the temperature profiles of dermal and subdermal layers when exposed to severe cold temperatures. The discrete values of nodal temperature were calculated at the interfaces of skin and subcutaneous tissues with respect to the atmospheric temperatures of 25 °C, 20 °C, 15 °C, 5 °C, -5 °C and -10 °C. The results obtained were used to identify the scenarios under which various degrees of frostbite occur on the surface of skin as well as the dermal and subdermal areas. The explicit formula of finite difference method proposed in this model provides more accurate predictions as compared to other numerical methods. This model of predicting tissue temperatures provides researchers with a more accurate prediction of peripheral tissue temperature and, hence, the susceptibility to frostbite during severe cold exposure.

FLUOROSCOPY TIME DURING CARDIAC CATHETERIZATION PROCEDURES USING THE RADIAL AND FEMORAL ROUTES.

BACKGROUND: Use of trans-radial route for cardiac catheterization is on the rise but is associated with increased radiation exposure to the operator. Our aim was to compare the radiation exposure, by taking fluoroscopy time (FT) as a surrogate of radiation exposure, to the operator with femoral and radial routes. METHODS: This prospective observational study was carried out at Army Cardiac Center Lahore from lst Jan to 1st June 2013. Mean fluoroscopy times via trans-radia (TR) and trans-femoral (TF) routes were compared. Procedure time was considered as time from sheath insertion to the finish of the diagnostic and interventional procedure. Descriptive statistics were used to explain the data. Chi square test was applied to compare qualitative variables between them. RESULTS: A total of 1,110 diagnostic & PCI cases were performed out of which there were 850 diagnostic CA and 260 PCI cases. The mean procedure time & mean fluoroscopy time for TF-CA was 15.5±5.5 minutes and 4.3±3.2 minutes respectively in the current study while for TR-CA was 6.6±4.1. For TF-PCI, mean procedure time was 42.3±16.7 minutes, mean fluoroscopy time was 11.6±7.7 minutes & for TR-PCI it was 55.3±19.2 and 15.4±12.1. CONCLUSION: Radial route for cardiac catheterization procedures is associated with longer fluoroscopy time leading to increased radiation exposure to the operator along with an increased use of contrast.

EVALUATION OF TOXIC HEAVY METALS IN AYURVEDIC SYRUPS SOLD IN LOCAL MARKETS OF HAZARA, PAKISTAN.

BACKGROUND: Herbal and Ayurvedic preparations, widely used in Pakistan and the developing world, present serious risk of heavy metal toxicity related to their medicinal content and prolonged use by patients. The objective of this study was to find out the concentration of heavy metals in Herbal & Ayurvedic liquid preparations commonly used for treatment of different diseases, from local markets of Hazara. METHODS: The cross sectional survey of traditional herbal & Ayurvedic medicine shops included ten liquid preparations selected from local shops of Mansehra and Abbottabad after interviewing the shopkeepers; so as to select the most commonly sold preparations along with their indications. All samples were analysed on standard Atomic Absorption Spectroscopy for qualitative and quantitative study of toxic heavy metals (Mercury, Iron, Zinc, Lead, Manganese and Arsenic). RESULTS: Toxic levels of Mercury were present in seven syrups, i.e., (Kashneeze, Akseer e Pachas, Tankar, Sharbat e folad, Urosinal, Akseer e Jigar and Amrat dhara) while Arsenic was present only in Urosinal. Iron, Zinc, Manganese and Lead were present in permissible limits in all syrups. CONCLUSION: Mercury and Arsenic are present in local Herbal & Ayurvedic liquid preparations far beyond the permissible limits as proposed by the International Regulatory Authorities for health drugs while the rest of metals, i.e., Zinc, Manganese, and Iron are within the therapeutic limits.

Clinical predictions of COVID-19 patients using deep stacking neural networks.

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.

Enhanced bioremediation of acid mine-influenced groundwater with micro-sized emulsified corn oil droplets (MOD) and sulfate-reducing bacteria (Desulfovibrio vulgaris) in a microcosm assay.

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.

Physiology of gamma-aminobutyric acid treated Capsicum annuum L. (Sweet pepper) under induced drought stress.

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.

Enhanced cellulose nanofiber mechanical stability through ionic crosslinking and interpretation of adsorption data using machine learning.

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 %.

Antidiabetic, Antihyperlipidemic, and Antioxidant Evaluation of Phytosteroids from Notholirion thomsonianum (Royle) Stapf.

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.

Synthesis, Antioxidant, and Antidiabetic Activities of Ketone Derivatives of Succinimide.

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.

Soil conditioners improve rhizodegradation of aged petroleum hydrocarbons and enhance the growth of Lolium multiflorum.

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.