From nature to cancer therapy: Evaluating the Streptomyces clavuligerus secondary metabolites for potential protein kinase inhibitors.

The study aimed to evaluate the antioxidant, protein kinase inhibitory (PKIs) potential, cytotoxicity activity of Streptomyces clavuligerus extract. DPPH assay revealed a robust free radical scavenging capacity (IC50 28.90 ± 0.24 µg/mL) of organic extract with a maximum inhibition percentage of 61 ± 1.04%. PKIs assay revealed the formation of a whitish bald zone by S. clavuligerus extracts which indicates the presence of PKIs. The cytotoxicity activity of organic fraction of extract through Sulforhodamine B assay on MCF-7, Hop-62, SiHa, and PC-3 cell lines demonstrated the lowest GI50 value against the MCF-7 cell line followed by the PC-3 cell line, showing potent growth inhibitory potential against human breast cancer and human prostate cancer cell line. HR-LCMS analysis identified multiple secondary metabolites from the organic and aqueous extracts of S. clavuligerus when incubated at 30°C under 200 rpm for 3 days. All the secondary metabolites were elucidated for their potential to inhibit RTKs by molecular docking, molecular dynamic simulation, MM/GBSA calculations, and free energy approach. It revealed the superior inhibitory potential of epirubicin (Epi) and dodecaprenyl phosphate-galacturonic acid (DPGA) against fibroblast growth factors receptor (FGFR). Epi also exhibited excellent inhibitory activity against the platelet-derived growth factor receptor (PDGFR), while DPGA effectively inhibited the vascular endothelial growth factor receptor. Additionally, the presence Epi in S. clavuligerus extract was validated through the HPLC technique. Thus, our findings highlight a superior inhibitory potential of Epi against FGFR and PDGFR RTKs than the FDA-approved drug.

Enantioselective Distal Functionalization of 3-Cyano-4-methylcoumarins through Direct Vinylogous Conjugate Addition to Maleimides.

An unprecedented organocatalyzed asymmetric vinylogous Michael reaction between 3-cyano-4-methylcoumarins and maleimides with an excellent enantiomeric ratio (up to 99.5:0.5) and yield (up to 95%) is reported. This remarkable selectivity is attributed to the hydrogen bonding ability of l-tert-leucine-derived amine thiourea catalyst. The versatility, practical applicability, and scalability are demonstrated by the generation of γ-functionalized coumarin derivatives.

EGFRisopred: a machine learning-based classification model for identifying isoform-specific inhibitors against EGFR and HER2.

The EGFR kinase pathway is one of the most frequently activated signaling pathways in human cancers. EGFR and HER2 are the two significant members of this pathway, which are attractive drug targets of clinical relevance in lung and breast cancer. Therefore, identifying EGFR- and HER2-specific inhibitors is one of the important challenges in cancer drug discovery. To address this issue, a dataset of 519 compounds having inhibitory activity against both the isoforms, i.e., EGFR and HER2, was collected from the literature and developed a knowledge-based computational classification model for predicting the specificity of a molecule for an isoform (EGFR/HER2) with precision. A total of seventy-two classification models using nine fingerprint types, four classifiers (IBK, NB, SMO and RF) and two different datasets (EGFR and HER2 isoform specific) were developed. It was observed that the models developed using random forest and IBK performed better for EGFR- and HER2-specific datasets, respectively. Scaffold and functional group analysis led to the identification of prevalent core and fragments in each of the datasets. The accuracy of the selected best performing models was also evaluated using the decoy dataset. We have also developed an application EGFRisopred, which integrates the best performing models and permits the user to predict the specificity of a compound as an EGFR-/HER2-specific anticancer agent. It is expected that the tool's availability as a free utility will allow researchers to identify new inhibitors against these targets important in cancer.

First report of Curvularia penniseti causing leaf blight of Bajra Napier hybrid grass in India.

Bajra Napier hybrid (Pennisetum glaucum x Pennisetum purpureum) is a perennial, high yielding grass and is widely grown for fodder in India. During August-2021, Bajra Napier hybrid germplasm line (NBN 15-2) showed severe leaf blight symptoms at ICAR-Indian Grassland and fodder research institute, Jhansi (25.527890 N, 78.5451400 E). Symptoms were initial irregular yellow spots on the leaf lamina, which later became brownish, coalesced and gave blighted appearance to the leaf surface. Disease severity recorded was 55 to 60 percent. To isolate the pathogen, 10 symptomatic leaf samples were cut into small pieces (~4 mm2), surface-sterilized with 70% ethanol for 30 seconds and rinsed with sterile water. Sterilized leaf pieces were transferred to potato dextrose agar (PDA) and incubated at 28°C for 7 days. Four similar fungal isolates (BNHCP-1 to BNHCP-4) were obtained from the affected portions. The colonies were grayish-brown with dark brown margins. Conidia were mostly clavate, elongated, straight or bent at the terminal cell, with 2-3 septa with dimensions of 17.5 to 30 µm × 10 to 12.5 µm (avg. 24 µm × 12 µm; n=40). The third cell from the base was broader and darker. These morphological characteristics were consistent with previous descriptions of Curvularia penniseti (Mitra) Boedijn (Ellis, 1971). To confirm the species, BNHCP-1 was chosen as representative isolate for further studies. Internal transcribed spacer (ITS) region and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene of isolate BNHCP-1 was amplified with primers ITS1F/ITS4R (White et al. 1990) and GDF/GDR (Templeton et al. 1992), and sequenced. The sequences were deposited in GenBank (ITS: OM073980; GAPDH: OM103702.2). BLASTn analysis showed 99.6% and 98% similarity of ITS and GAPDH gene respectively with GenBank accession numbers MH859833.1 (548 bp/550 bp) and MN688838.1 (130 bp/133 bp) of C. penniseti. A maximum-likelihood phylogenetic analysis based on concatenated sequences of ITS and GAPDH gene using MEGA X placed the isolate BNHCP-1 within a clade comprising C. penniseti. Pure culture of BNHCP-1 was deposited in National Agriculturally Important Microbial Culture Collection (NAIMCC), Maunath Bhanjan (Uttar Pradesh) with accession number NAIMCC-F-04251. For pathogenicity, root slips of Bajra Napier hybrid germplasm line NBN 15-2 were transplanted in pots (6 pots; 2 root slips per pot) and kept for fresh growth in a growth chamber at 25 0C for 21 days. Bajra-Napier hybrid plants were sprayed until runoff with conidial suspension (5 × 105 conidia/ml) made from 2-week old fungal colony grown on PDA petri dish. The pots were covered with plastic bag for 48 h to maintain humidity. Inoculated plants displayed small, brown, oval-shaped lesions within seven days on the lamina and edges of the leaf which later enlarged and gave blighted appearance to the leaf. Control plants were asymptomatic. The pathogen was re-isolated from the inoculated leaves and confirmed morphologically, fulfilling Koch's postulates. C. penniseti has been reported earlier from Pennisetum americanum, P. clandestinum, Sorghum and Triticum sp. from different parts of the world (Sivanesan, 1987). However, there is no report of C. penniseti in Bajra Napier hybrid. Thus, to the best of our knowledge, this is the first report of C. penniseti from Bajra-Napier hybrid grass in India. Further studies on economic impact of this disease on Bajra-Napier hybrid production and its presence on commercial cultivars are needed.

Three-dimensional DenseNet self-attention neural network for automatic detection of student's engagement.

Today, due to the widespread outbreak of the deadly coronavirus, popularly known as COVID-19, the traditional classroom education has been shifted to computer-based learning. Students of various cognitive and psychological abilities participate in the learning process. However, most students are hesitant to provide regular and honest feedback on the comprehensiveness of the course, making it difficult for the instructor to ensure that all students are grasping the information at the same rate. The students' understanding of the course and their emotional engagement, as indicated via facial expressions, are intertwined. This paper attempts to present a three-dimensional DenseNet self-attention neural network (DenseAttNet) used to identify and evaluate student participation in modern and traditional educational programs. With the Dataset for Affective States in E-Environments (DAiSEE), the proposed DenseAttNet model outperformed all other existing methods, achieving baseline accuracy of 63.59% for engagement classification and 54.27% for boredom classification, respectively. Besides, DenseAttNet trained on all four multi-labels, namely boredom, engagement, confusion, and frustration has registered an accuracy of 81.17%, 94.85%, 90.96%, and 95.85%, respectively. In addition, we performed a regression experiment on DAiSEE and obtained the lowest Mean Square Error (MSE) value of 0.0347. Finally, the proposed approach achieves a competitive MSE of 0.0877 when validated on the Emotion Recognition in the Wild Engagement Prediction (EmotiW-EP) dataset.

Floodplains landforms, clay deposition and irrigation return flow govern arsenic occurrence, prevalence and mobilization: A geochemical and isotopic study of the mid-Gangetic floodplains.

This article attempts to understand the evolution of groundwater chemistry in the mid Gangetic floodplain through the identification of hydrogeochemical processes including the impact of surface recharge and geological features. Isotopic investigations identified that irrigation return flow is partly responsible for arsenic (As) enrichment through preferential vertical recharge. Further, the floodplain geomorphological attributes and associated As hydrogeochemical behaviour traced through isotopes tracers highlighted that meandering and ox-bow like geomorphological features owing to clay deposition leads to the anoxic condition induced reductive microbial dissolution of As-bearing minerals causing the arsenic contamination in the investigated aquifer of the mid-Gangetic plain (MGP). To achieve the objectives, 146 water samples for water chemistry and 62 samples for the isotopic study were collected from Bhojpur district, Bihar (district bounded by the river Ganges in the north and Son in the east) located in MGP during the pre-monsoon season of 2018. The chemical results revealed high arsenic concentration (BDL to 206 µg.L-1, 32% samples are exceeding the 10 µg.L-1 limit) in the Holocene recent alluviums which are characterized by various geomorphological features such as meander scars and oxbow lake (northern part of the district). Arsenic is more concentrated in the depth range of 15-40 m below ground surface. All other trace metals viz. Ni, Pb, Zn, Cd and Al were found in low concentration except Fe and Mn. The geochemical analyses suggest that rock-water interaction is controlling the hydro-geochemistry while the chemical constituent of the groundwater is mainly controlled by carbonate weathering with limited contribution from silicate weathering. The isotopic signatures revealed that the Son river is recharging groundwater while the groundwater is contributing to the Ganges river. A clear pattern of fast vertical recharge in the arsenic contaminated area is observed in the proximity to the river Ganges with an elevated nitrate concentration resulted from the reduced As dissolution. The origin of groundwater is local precipitation with low to high evaporation enrichment effect which is further indicating the vertical mixing of groundwater from the irrigation return flow and/or recharge from domestic discharge causing enhanced As mobilization through microbial assisted reductive dissolution of As-bearing minerals.

Pharmacokinetic profiling of anticancer phytocompounds using computational approach.

INTRODUCTION: Natural products exhibit diverse scaffolds and are considered as suitable candidates for development of leads. However, poor pharmacokinetics often acts as a hindrance during the drug discovery process. OBJECTIVE: With a view of exploring the absorption, distribution, metabolism, excretion and toxicity (ADMET) profile of plant-based anticancer compounds, open-access databases (NPACT, CancerHSP and TaxKB) were analysed to identify molecules having properties favourable for drug ability. METHODOLOGY: Our workflow involved identification of molecules capable of passing each of the ADMET barriers based on physicochemical properties of molecules, and physiological barriers and factors. RESULTS: The results revealed that out of 5086 phytomolecules, 63% were orally absorbable and 52% distributable. Also, an appreciable proportion of these compounds (45%) could be metabolised and excreted. Furthermore, 28% were found to be non-toxic for cardio toxicity and central nervous system (CNS) activity. Additionally, comparison against known anticancer drugs (reference dataset) revealed that the three libraries exhibit similar trends, thus providing additional confidence to the predictions. Overall, 28% of the molecular dataset was found to have suitable pharmacokinetic properties. We have also discussed a few natural products which exhibit favourable ADMET as well as low nano-micromolar in vitro anticancer activity. CONCLUSION: We have created an interactive database (ADMETCan), which provides access to predicted ADMET of these anticancer phytomolecules. The ease of availability of this dataset is expected to minimise failure rate of these compounds and thus is expected to be beneficial to the scientific community involved in anticancer identification and development.

Proteomic analysis of the endometrium during early pregnancy in the domestic pig.

Reproductive processes in domestic pigs have been studied extensively. Pigs are one of the main sources of meat for human consumption and are an established model for investigations into mammalian, including human, reproductive physiology. Studies of the uterus during early pregnancy will lead to a better understanding of mechanisms governing pregnancy. Proteomics provides the possibility to explore endometrial functions in an unbiased way. The aim of the study was to compare endometrium harvested from Days 12-13 and 15-16 of pregnancy with the corresponding days of the oestrous cycle. We identified endometrial proteins that are unique to the early stages of pregnancy (Days 12-13 and 15-16). Twenty-one proteins were identified that were uniquely expressed on the selected days of pregnancy or the oestrous cycle. Out of 21 identified proteins, 14 referred to the pregnancy periods. Systemic analysis of the identified proteins revealed cell adhesion and cytoskeletal organisation as two of the major functions, both of which are important for the establishment and maintenance of pregnancy. Thrombospondin 1 expression was validated using western blotting analysis and the results suggest its involvement in the adhesiveness of the embryo during the peri-implantation period in pigs.

Proteomics of dedifferentiation of SK-N-BE2 neuroblastoma cells.

Neuroblastoma develops through processes which include cellular dedifferentiation. Ability of tumors to form spheroids is one of the manifestations of dedifferentiation and carcinogenic transformation. To study mechanisms of dedifferentiation of neuroblastoma cells, we generated spheroids and performed a proteomics study to compare the spheroids with parental SK-N-BE2 cells. We observed that dedifferentiation induced extensive changes in the proteome profiles of the cells, which affected more than 30% of detected cellular proteins. Using mass spectrometry, we identified 239 proteins affected by dedifferentiation into spheroids as compared to the parental cells. These proteins represented such regulatory processes as transcription, cell cycle regulation, apoptosis, cell adhesion, metabolism, intracellular transport, stress response, and angiogenesis. A number of potent regulators of stemness, differentiation and cancer were detected as subnetworks formed by the identified proteins. Our validation tissue microarray study of 30 neuroblastoma cases confirmed that two of the identified proteins, DISC1 and DNA-PKcs, had their expression increased in advanced malignancies. Thus, our report unveiled extensive changes of the cellular proteome upon dedifferentiation of neuroblastoma cells, indicated top subnetworks and clusters of molecular mechanisms involved in dedifferentiation, and provided candidate biomarkers for clinical studies.

Green Synthesis of Reduced Graphene Oxide Using the Tinospora cordifolia Plant Extract: Exploring Its Potential for Methylene Blue Dye Degradation and Antibacterial Activity.

Graphene has attracted significant attention recently due to its unique mechanical, electrical, thermal, and optical properties. The present study focuses on synthesizing green rGO using the Tinospora cordifolia plant extract by mixing it in a suspension of graphene oxide. The plant extract of T. cordifolia acts as a reducing agent and is cost-effective, renewable, and eco-friendly. Green-synthesized rGO (G-rGO) was characterized using FTIR, HR-SEM, EDX, and HR-XRD analyses. G-rGO consists of nanosheets with an average width of approximately 30 nm. G-rGO has a range of hydrodynamic radius (270-470) nm and an average ζ potential of -29.9 mV. Further, G-rGO was used as a nanoadsorbent for optimal exclusion of methylene blue (MB) dye using the response surface methodology (RSM). Adsorption results confirmed 94.85% MB dye removal with 58.81 mg g-1 adsorption capacity at optimum conditions. The G-rGO's antibacterial activity was also tested against Staphylococcus aureus (Gram-positive) and Escherichia coli (Gram-negative) bacteria, finding the exhibited zone of inhibition of 10, 11, and 15 mm and 10, 13, and 17 mm at 20, 40, and 80 µg mL-1 concentrations of G-rGO, respectively.

Desymmetric homologating annulation to access chiral pentafulvenes and their application in bioimaging.

The architectural design of polycyclic/multisubstituted pentafulvenes has demonstrated great potential for the development of electrochromic materials and biologically active motifs. Unfortunately, the enantioselective construction of such distinctive cores with all carbon quaternary chiral centers has remained untouched to date. Herein, we disclose an enantioselective homologating annulation of cyclopent-4-ene-dione with 3-cyano-4-methylcoumarins through L-tert-leucine derived thiourea catalysis, affording a wide range of enantioenriched polycyclic multisubstituted embedded aminopentafulvenes with excellent stereocontrol (up to 99:1 er) and chemical yields up to 87%. A detailed photophysical and cytotoxicity analysis of racemic and chiral homologated adducts unveils the exceptional behavior of chiral adducts over their racemic analogs, highlighting the importance of stereoselectivity of the developed scaffolds. A cellular uptake experiment in a mammalian fibroblast cell line confirmed the potential of developed polycyclic aminopentafulvene cores as a highly promising labeling dye that can be utilized for bioimaging without any adverse effects.

Advancing orthopaedic trauma care through WhatsApp: An analysis of clinical and non-clinical applications, challenges, and future directions.

The integration of WhatsApp, a widely-used instant messaging application (IMA), into the realm of orthopaedics and trauma surgery has emerged as a significant development in recent years. This paper explores the multifaceted role of WhatsApp in orthopaedics, focusing on its clinical and non-clinical applications, advantages, disadvantages, and future prospects. The study synthesizes findings from various research papers, emphasizing the growing reliance on mobile technology in healthcare. WhatsApp's role in orthopaedics is notable for its ease of use, real-time communication, and accessibility. Clinically, it facilitates triage, teleconsultation, diagnosis, treatment, patient advice, and post-operative monitoring. Non-clinically, it supports telemedicine, teleradiology, virtual fracture clinics, research, and education in orthopaedic surgery. The application has proven beneficial in enhancing communication among healthcare teams, providing quick responses, and motivating junior physicians. Its use in educational settings has been shown to improve learner's understanding and patient care. However, the use of WhatsApp in orthopaedics is not without challenges. Risks include the potential spread of misleading information, privacy concerns, and issues with image quality affecting diagnosis and treatment decisions. The paper acknowledges the importance of maintaining professional boundaries and the need for oversight measures to ensure content accuracy. Looking forward, the potential of WhatsApp and similar IMAs in orthopaedics lies in their ability to streamline data collection and retrieval, improve doctor-patient communication, and address challenges like bureaucratic red tape and limited resources. The paper suggests that future orthopaedic practice, particularly in emergency departments, will increasingly rely on such technologies for efficient patient management. This shift, however, must be approached with an understanding of the ethical, legal, and practical implications of integrating social media and mobile technology in healthcare.

Improvement of qualitative and quantitative traits in cotton under normal and stressed environments using genomics and biotechnological tools: A review.

Due to the increasing demand for high-quality and high fiber-yielding cotton (Gossypium spp.), research into the development of stress-resilient cotton cultivars has acquired greater significance. Various biotic and abiotic stressors greatly affect cotton production and productivity, posing challenges to the future of the textile industry. Moreover, the content and quality of cottonseed oil can also potentially be influenced by future environmental conditions. Apart from conventional methods, genetic engineering has emerged as a potential tool to improve cotton fiber quality and productivity. Identification and modification of genome sequences and the expression levels of yield-related genes using genetic engineering approaches have enabled to increase both the quality and yields of cotton fiber and cottonseed oil. Herein, we evaluate the significance and molecular mechanisms associated with the regulation of cotton agronomic traits under both normal and stressful environmental conditions. In addition, the importance of gossypol, a toxic phenolic compound in cottonseed that can limit consumption by animals and humans, is reviewed and discussed.

Natural phytocompounds physalin D, withaferin a and withanone target L-asparaginase of Mycobacterium tuberculosis: a molecular dynamics study.

Tuberculosis is a major infectious disease that is responsible for high mortality in humans. The reason for the global burden is the emergence of new antibiotic resistant strains of Mycobacteria that showed resistance against the currently given therapy. It is identified that the pathogen utilizes the L-asparaginase enzyme as a virulence factor for survival benefits inside the host. Therefore, L-asparaginase of Mycobacterium tuberculosis is a promising therapeutic drug target. In view of the light, the present study explores thirty phytocompounds from medicinal plants to determine the binding affinity in the catalytic site of L-asparaginase. The studies initiated with the construction of the 3 D structure of L-asparaginase using homology modeling. Using the robustness of molecular docking with binding energy cut-off value < -9.0 kcal/mol and 100 ns molecular dynamics simulations, three phytocompounds viz., Physalin D (-9.11 kcal/mol), Withanone (-9.45 kcal/mol) and Withaferin A (-9. 67 kcal/mol) showed strong binding potential compared to the product, L-aspartate (-5.87 kcal/mol). The active site residues identified are Thr 12, Asp 51, Ser 53, Thr 84, Asp 85, and Lys 157. Upon MD simulations, the phytocompounds and the product L-aspartate remain present in the same catalytic pocket of the enzyme. The RMSD, RMSF, radius of gyration and H-bond analysis of enzyme ligand complexes efficiently showed the stability of ligands at the docked site. Further, ADME studies distinctly demonstrate the potential of selected phytoconstituents as therapeutics. Thus, serve as safe and low-cost alternatives to chemical compounds to be used in combination therapy for treatment of tuberculosis.Communicated by Ramaswamy H. Sarma.

Phytochemical profiling and evaluation of the antidiabetic potential of Ichnocarpus frutescens (Krishna Sariva): kinetic study, molecular modelling, and free energy approach.

This research explored novel antidiabetic drugs from natural sources using the Ayurvedic Rasayana herb Ichnocarpus frutescens through invitro enzyme assay, kinetics study, and computational approaches. Invitro enzyme inhibition assay demonstrated the promising inhibitory activity of root extract against alpha-amylase (α-A) and alpha-glucosidase (α-G) enzyme with IC50 value 7.34 ± 0.22 mg/ml and 4.40 ± 0.25 mg/ml respectively. Enzyme kinetic study revealed the competitive inhibition of both proteins by Ichnocarpus frutescens extract. High-Resolution Liquid Chromatography Mass Spectrometer and Docking study revealed the better binding energy of phytoconstituents 23-Acetoxysoladulcidine, Atrovirinone, Bismurrayaquinone A, Lamprolobine, Zygadenine, and Gambiriin A3 than standard drug acarbose. Molecular modelling showed stable protein-ligands binding interaction during the 100 ns simulation. It revealed comparable Root Mean Square Deviation, Radius of Gyration, and Solvent Accessible Surface Area of these compounds with acarbose. The active site residues of both proteins remained stable and showed significantly less Root Mean Square Fluctuation. Molecular Mechanics with Generalised Bonn Surface Area analysis has illustrated the similar inhibitory activity of Zygadenine for α-A, 23-Acetoxysoladulcidine, and Gambiriin A3 for α-G protein, compared to the FDA-approved drug acarbose. Thus, the study suggested that the root of Ichnocarpus frutescens can be used as α-A and α-G inhibitors and be considered a compelling lead for the medication of type 2 diabetes.Communicated by Ramaswamy H. Sarma.

Atrovirinone, 23-Acetoxysoladulcidine, Bismurrayaquinone A, Gambiriin A3, Zygadenine, and Lamprolobine are the major phytoconstituents identified from Ichnocarpus frutescens.The computational study suggested that this compound possesses α-A and α-G inhibition potential.Invitro study confirmed the competitive mode of inhibition of both enzymes by root extract of Ichnocarpus frutescens.The antidiabetic potential of Ichnocarpus frutescens was investigated for the first time by kinetic study and insilico approach.

Molecular modelling and in vitro studies of Daruharidra as a potent alpha-amylase inhibitor.

The present study aims at exploring the potential of the Daruharidra plant (stem and bark) for inhibition of alpha-amylase. Aqueous and ethanolic extraction yielded the highest total phenolic content (TPC) of 101.4 and 111.8 mcg of gallic acid equivalent. Methanol and ethanol extract had Total flavonoid content (TFC) of 319.6 and 288.3 mcg of quercetin equivalent, respectively. In contrast, petroleum ether extraction resulted in the lowest TPC of 23.6 and TFC of 8.33 mcg, respectively. Methanol (5.554 mg/ml), acetone (6.576 mg/ml), and ethanol (7.321 mg/ml) extract had the lowest IC50 values in alpha-amylase inhibition with the mode of inhibition being non-competitive inhibition. HR-LCMS was used for comprehension of phytoconstituents present in the extract. Amongst hundreds of hits observed 10 ligands of alkaloid nature were used for docking studies. Berbamine, alloxanthine, protopine and benazepril along with reference molecule (Acarbose) were subjected to Molecular dynamics (MD) simulation to analyze the stability of the docked protein-ligand complex. The values of RMSD, RMSF, RG, H-Bond and SASA, the interaction energy of all protein-ligand complexes were calculated after 150 ns of MD simulation. The results of screened complexes revealed good stability as compared to reference Acarbose. These screened ligands used for simulation have the most negative binding energies that interacted with alpha amylase enzyme having -9.28 kcal/mol, -7.51 kcal/mol, -7.73 kcal/mol and -8.00 kcal/mol, energies respectively. The results show significant alpha-amylase inhibitory activity and interaction of ligands targeting this enzyme, which can be used for cross-validation, in vitroCommunicated by Ramaswamy H. Sarma.

HR-LCMS and evaluation of anti-diabetic activity of Hemidesmus indicus (anantmool): Kinetic study, and molecular modelling approach.

This study delved into the exploration of novel antidiabetic medications acquired from natural resources, utilizing the Ayurvedic Rasayana herb Hemidesmus indicus through cutting-edge chemoprofiling and molecular modelling techniques. The methanolic extract of Hemidesmus indicus root exhibited the highest extractive yield (24.70 ± 0.08 %) and contained substantial levels of total phenolic and flavonoid content as 154.15 ± 1.24 mg Gallic Acid Equivalent/g extract and 70.61 ± 0.35 Quercetin Equivalent/g extract respectively. Invitro study revealed the potent inhibitory potential of methanolic extract of the herb against essential carbohydrate hydrolytic enzymes α-amylase (IC50 = 4.19 ± 0.04 mg/ml) and α-glucosidase (IC50 = 5.78 ± 0.10 mg/ml). Further, the enzyme kinetic study demonstrated the competitive mode of inhibition of both enzymes. HR-LCMS analysis identified the major phytoconstituents present in the extracts, including Solanocapsine, Cyclovirobuxine C, Lucidine B, Zygadenine, Aspidospermidine, silychristin, 3beta-3-Hydroxy-18-lupen-21-one, Manglupenone, and 19-Noretiocholanolone. Molecular docking, molecular dynamic simulation, and MM/GBSA analysis have proved stable, rigid, compact, and folded form of complexes during the entire 100 ns simulation, illustrating Zygadenine, Solanocapsine, and Cyclovirobuxine C as the superior inhibitors of α-A protein, while Zygadenine, Plumieride, and Phlegmarine exhibited greater inhibitory behaviour towards α-G protein than the FDA-approved drug acarbose. Collectively, our findings indicate that the Hemidesmus indicus could be a promising source of α-A and α-G inhibitors, potentially serving as a lead in order to develop medications for type-2 diabetes.

Exploring plant-based alpha-glucosidase inhibitors: promising contenders for combatting type-2 diabetes.

Objective: This systematic review aimed to provide comprehensive details on the α-G inhibitory potential of various bioactive compounds derived from natural sources.Methods: A comprehensive literature search was conducted using various databases and search engines, including Science Direct, Google Scholar, SciFinder, Web of Science, and PubMed until May, 2023.Results and conclusions: The enzyme alpha-glucosidase (α-G) is found in the brush border epithelium of the small intestine and consists of duplicated glycoside hydrolase (GH31) domain. It involves the conversion of disaccharides and oligosaccharides into monosaccharides by acting on alpha (1 → 4) and (1 → 6) linked glucose residue. Once absorbed, glucose enters the bloodstream and elevates postprandial glucose, which is associated with the development of type 2 Diabetes (T2D). Epidemic obesity, cardiovascular disease, and nephropathy are linked to T2D. Traditional medicinal plants with α-G inhibitory potential are commonly used to treat T2D due to the adverse effects of currently used α-G inhibitors miglitol, acarbose, and voglibose. Various bioactive compounds derived from natural sources, including lupenone, Wilforlide A, Baicalein, Betulinic acid, Ursolic acid, Oleanolic acid, Katononic acid, Carnosol, Hypericin, Astilbin, lupeol, betulonic acid, Fagomine, Lactucaxanthin, Erythritol, GP90-1B, Procyanidins, Galangin, and vomifoliol retain α-G inhibitory potential for regulating hyperglycaemia.

A comprehensive review on ayurvedic herb Leptadenia reticulata (Jeevanti): a phytochemistry and pharmacological perspective.

Leptadenia reticulata is a vital Ayurvedic medicinal herb, commonly known as Jivanti or Jiv, and contains revitalising, rejuvenating, and lactogenic activities. It has been used in traditional medicine for treating respiratory disorders, wounds, inflammation, cough, dehydration, tuberculosis, colitis, chickenpox, dysentery, eye diseases, night blindness, fever, and snake bites. It is a perennial herb of Indian origin belonging to the Asclepiadaceae family and has been utilised for its therapeutic properties since ancient times. It is a key ingredient in several marketed herbal drugs, including chyawanprash, speman, and leptaden. Several potent compounds, including ß-sitosterol, γ-sitosterol, phytol, α-amyrin, ß-amyrin, apigenin, reticulin, deniculatin, leptaculatin, diosmetin, and rutin are present in this herb and attributed various pharmacological activities, including antidiabetic, antimicrobial, antioxidant, anti-abortifacient, anticancer, antipyretic, analgesic, anti-inflammatory, and antiulcer properties. This review provides an in-depth analysis of the distribution, ethnobotanical use, botanical description, phytocompounds, and pharmacological activities of Leptadenia reticulata.

Leptadenia reticulata is a vital Ayurvedic herb containing revitalising, rejuvenating, and lactogenic activities.It is present in polyherbal formulations chyawanprash, speman, and leptaden.Its secondary metabolites have anticancer, anticholesterol, antidiabetic, antiabortifacient, and anti-inflammatory potential.This review shows the distribution, morphology, and therapeutic potential of Leptadenia reticulata.A summary of the phytochemicals present in Leptadenia reticulata will also be provided.

Facial expression recognition in videos using hybrid CNN & ConvLSTM.

The three-dimensional convolutional neural network (3D-CNN) and long short-term memory (LSTM) have consistently outperformed many approaches in video-based facial expression recognition (VFER). The image is unrolled to a one-dimensional vector by the vanilla version of the fully-connected LSTM (FC-LSTM), which leads to the loss of crucial spatial information. Convolutional LSTM (ConvLSTM) overcomes this limitation by performing LSTM operations in convolutions without unrolling, thus retaining useful spatial information. Motivated by this, in this paper, we propose a neural network architecture that consists of a blend of 3D-CNN and ConvLSTM for VFER. The proposed hybrid architecture captures spatiotemporal information from the video sequences of emotions and attains competitive accuracy on three FER datasets open to the public, namely the SAVEE, CK + , and AFEW. The experimental results demonstrate excellent performance without external emotional data with the added advantage of having a simple model with fewer parameters. Moreover, unlike the state-of-the-art deep learning models, our designed FER pipeline improves execution speed by many factors while achieving competitive recognition accuracy. Hence, the proposed FER pipeline is an appropriate candidate for recognizing facial expressions on resource-limited embedded platforms for real-time applications.