Prevalence and factors associated with digital addiction among students taking university entrance tests: a GIS-based study.

BACKGROUND: The surge in digital media consumption, coupled with the ensuing consequences of digital addiction, has witnessed a rapid increase, particularly after the initiation of the COVID-19 pandemic. Despite some studies exploring specific technological addictions, such as internet or social media addiction, in Bangladesh, there is a noticeable gap in research focusing on digital addiction in a broader context. Thus, this study aims to investigate digital addiction among students taking the university entrance test, examining its prevalence, contributing factors, and geographical distribution using GIS techniques. METHODS: Data from a cross-sectional survey were collected from a total of 2,157 students who were taking the university entrance test at Jahangirnagar University, Bangladesh. A convenience sampling method was applied for data collection using a structured questionnaire. Statistical analyses were performed with SPSS 25 Version and AMOS 23 Version, whereas ArcGIS 10.8 Version was used for the geographical distribution of digital addiction. RESULTS: The prevalence of digital addiction was 33.1% (mean score: 16.05 ± 5.58). Those students who are attempting the test for a second time were more likely to be addicted (42.7% vs. 39.1%), but the difference was not statistically significant. Besides, the potential factors predicted for digital addiction were student status, satisfaction with previous mock tests, average monthly expenditure during the admission test preparation, and depression. No significant difference was found between digital addiction and districts. However, digital addiction was higher in the districts of Manikganj, Rajbari, Shariatpur, and Chittagong Hill Tract areas, including Rangamati, and Bandarban. CONCLUSIONS: The study emphasizes the pressing need for collaborative efforts involving educational policymakers, institutions, and parents to address the growing digital addiction among university-bound students. The recommendations focus on promoting alternative activities, enhancing digital literacy, and imposing restrictions on digital device use, which are crucial steps toward fostering a healthier digital environment and balanced relationship with technology for students.

Determinants of anxiety and depression among type 2 diabetes mellitus patients: A hospital-based study in Bangladesh amid the COVID-19 pandemic.

Anxiety and depression are common psychological disorders in patients with type 2 diabetes mellitus (T2DM), which was upsurging worldwide amid the COVID-19 pandemic. This study aimed to explore factors associated with anxiety and depression among T2DM patients in Bangladesh during the COVID-19 pandemic. A cross-sectional study was conducted among T2DM patients using face-to-face interviews. Anxiety and depressive symptoms were measured using the CAS and PHQ-9 scales. Outcomes were assessed including sociodemographic, lifestyle, anthropometric, and challenges of getting routine medical and healthcare access-related questions. The prevalence of anxiety and depressive symptoms were 29.8% and 22.7%, respectively. Regression analysis reported that males older than 50 years, illiterate, unemployed or retired, urban residents, below the recommended level of moderate to vigorous physical activity (MVPA), low dietary diversity score (DDS) and obese respondents were associated with higher odds of anxiety and depressive symptoms. Moreover, respondents with transport difficulties, unaffordable medicine, medicine shortages, close friends or family members diagnosed with COVID-19 and financial problems during COVID-19 had higher odds of anxiety and depressive symptoms than their counterparts, respectively. Our study suggests providing psychological support, such as home-based psychological interventions, and highlighting policy implications to ensure the well-being of T2DM patients in Bangladesh during the pandemic.

Optimization and Characterization of Phenolic Extraction Conditions and Antioxidant Activity Evaluation of Adenanthera pavonina L. Bark.

The presence of high levels of secondary metabolites in medicinal plants can significantly influence the progress of drug development. Here, we aimed to maximize phenolic extraction from Adenanthera pavonina L. stem bark using various solvents such as ethyl acetate, methanol, petroleum ether, and chloroform. A response surface method (RSM) with a central composite design (CCD) statistical technique was applied to optimize the extraction process, employing three important extracting parameters such as extraction time (h), temperature (°C), and solvent composition (% v/v of methanol/water) to obtain the highest phenolic content. Total phenolic content (TPC) and antioxidant activity (IC50 of extract's DPPH radical scavenging activity) were used as response variables to find the influence of these extracting parameters. Among the various solvents used, methanol extract showed the highest contents of phenolics and the maximum level of antioxidant activity with a lower IC50 value. The notable TPC and IC50 value of the extract's DPPH radical scavenging capacity were found to be 181.69 ± 0.20 mg GAE/g dry tissue and 60.13 ± 0.11 mg/mL, respectively, under the optimal conditions with a solvent composition of 71.61% (v/v) of methanol/water, extraction temperature of 42.52 °C, and extraction time of 24 h. The optimized extract of A. pavonina stem bark was further subjected to HPLC analysis, where six phenolic compounds, including coumarin, p-coumaric acid, chlorogenic acid, sinapic acid, gallic acid, and caffeic acid, were identified along with their respective quantities. Overall, the findings of this study uncover a low-cost analytical model for maximizing phenolic extraction from A. pavonina bark with enhanced antioxidant activity.

Paddynet: An organized dataset of paddy leaves for a smart fertilizer recommendation system.

The dataset of Leaf Color Chart (PaddyNet) is publicly unavailable. As far as the author's knowledge, this is the first dataset about paddy leaves based on LCC. This dataset has been generated by collecting images from a particular location such as Sajiali, Dogachia and Shyamnagar at Jashore, Bangladesh. This dataset contains 4 categories of Aman paddy leaves. The leaf images were captured by smart phones. There are 560 images of Aman paddy leaves. The data collection procedure was carried out according to the guidelines of Bangladesh Agricultural Research Institute (BARI). We meticulously categorized the entire dataset with regard to the LCC level and validated the data with the assistance of domain specialists. Hence, the images are analyzed and categorized with standards. The dataset is utilized for recognizing Leaf Color Chart level which will help of farmers recommending nitrogen fertilizer in their paddy fields.

SARS-CoV-2 prevalence in domestic and wildlife animals: A genomic and docking based structural comprehensive review.

The SARS-CoV-2 virus has been identified as the infectious agent that led to the COVID-19 pandemic, which the world has seen very recently. Researchers have linked the SARS-CoV-2 outbreak to bats for the zoonotic spread of the virus to humans. Coronaviruses have a crown-like shape and positive-sense RNA nucleic acid. It attaches its spike glycoprotein to the host angiotensin-converting enzyme 2 (ACE2) receptor. Coronavirus genome comprises 14 ORFs and 27 proteins, spike glycoprotein being one of the most critical proteins for viral pathogenesis. Many mammals and reptiles, including bats, pangolins, ferrets, snakes, and turtles, serve as the principal reservoirs for this virus. But many experimental investigations have shown that certain domestic animals, including pigs, chickens, dogs, cats, and others, may also be able to harbor this virus, whether they exhibit any symptoms. These animals act as reservoirs for SARS-CoV, facilitating its zoonotic cross-species transmission to other species, including humans. In this review, we performed a phylogenetic analysis with multiple sequence alignment and pairwise evolutionary distance analysis, which revealed the similarity of ACE2 receptors in humans, chimpanzees, domestic rabbits, house mice, and golden hamsters. Pairwise RMSD analysis of the spike protein from some commonly reported SARS-CoV revealed that bat and pangolin coronavirus shared the highest structural similarity with human coronavirus. In a further experiment, molecular docking confirmed a higher affinity of pig, bat, and pangolin coronavirus spike proteins' affinity to the human ACE2 receptor. Such comprehensive structural and genomic analysis can help us to forecast the next likely animal source of these coronaviruses that may infect humans. To combat these zoonotic illnesses, we need a one health strategy that considers the well-being of people and animals and the local ecosystem.

Chemico-biological interaction unraveled the potential mechanistic pathway of Ixeridium dentatum compounds against atopic dermatitis.

This study aims to investigate the potential therapeutic application of Ixeridium dentatum (ID) in treating atopic dermatitis (AD) through network pharmacology, molecular docking, and molecular dynamic simulation. We employed GC-MS techniques and identified 40 bioactive compounds present in the ID and determined their targets by accessing public databases. The convergence of compounds and dermatitis related targets led to the identification of 32 common genes. Among them, IL1B, PTGS2, IL6, IL2, and RELA, were found to be significant targets which were analyzed using Cytoscape network topology. The KEGG pathway evaluation revealed that these targets were significantly enriched in the C-type lectin receptor signaling pathway. The therapeutic efficacy of Stigmasta-5,22-dien-3-ol, Urea, n-Heptyl-, and 3-Epimoretenol was demonstrated in molecular docking assay, as evidenced by their presence in the core compounds of the compound-target network. Furthermore, these compounds exhibited significant kinetic stability and chemical reactivity in DFT quantum analysis when compared to their co-crystallized ligands and reference drug, indicating their potential as key targets for future research. Among the top three docking complexes, namely IL6-3-Epimoretenol, and IL2- Stigmasta-5,22-dien-3-ol, both demonstrated exceptional dynamic characteristics in molecular dynamics simulations at 100 ns. The feasibility of these compounds could be attributed to the prior traditional interrelationship between ID and AD. Overall, this research elucidates the interplay between AD-associated signaling pathways and target receptors with the bioactive ID. The proposal posits the utilization of antecedent compounds as a substitute for the customary pharmaceutical intervention that obstructs the discharge of cytokines, which incite dermal inflammation in the C-type lectin receptor signaling pathway of atopic dermatitis.

Bioactive Compounds and Signaling Pathways of Wolfiporia extensa in Suppressing Inflammatory Response by Network Pharmacology.

Wolfiporia extensa (WE) is a medicinal mushroom and an excellent source of naturally occurring anti-inflammatory substances. However, the particular bioactive compound(s) and mechanism(s) of action against inflammation have yet to be determined. Here, we studied anti-inflammatory bioactive compounds and their molecular mechanisms through network pharmacology. Methanol (ME) extract of WE (MEWE) was used for GC-MS analysis to identify the bioactives, which were screened by following Lipinski's rules. Public databases were used to extract selected bioactives and inflammation-related targets, and Venn diagrams exposed the common targets. Then, STRING and Cytoscape tools were used to construct protein-protein (PPI) network and mushroom-bioactives-target (M-C-T) networks. Gene Ontology and KEGG pathway analysis were performed by accessing the DAVID database and molecular docking was conducted to validate the findings. The chemical reactivity of key compounds and standard drugs was explored by the computational quantum mechanical modelling method (DFT study). Results from GC-MS revealed 27 bioactives, and all obeyed Lipinski's rules. The public databases uncovered 284 compound-related targets and 7283 inflammation targets. A Venn diagram pointed to 42 common targets which were manifested in the PPI and M-C-T networks. KEGG analysis pointed to the HIF-1 signaling pathway and, hence, the suggested strategy for preventing the onset of inflammatory response was inhibition of downstream NFKB, MAPK, mTOR, and PI3K-Akt signaling cascades. Molecular docking revealed the strongest binding affinity for "N-(3-chlorophenyl) naphthyl carboxamide" on five target proteins associated with the HIF-1 signaling pathway. Compared to the standard drug utilized in the DFT (Density Functional Theory) analysis, the proposed bioactive showed a good electron donor component and a reduced chemical hardness energy. Our research pinpoints the therapeutic efficiency of MEWE and this work suggests a key bioactive compound and its action mechanism against inflammation.

Revealing Potential Bioactive Compounds and Mechanisms of Lithospermum erythrorhizon against COVID-19 via Network Pharmacology Study.

Lithospermum erythrorhizon (LE) is known in Korean traditional medicine for its potent therapeutic effect and antiviral activity. Currently, coronavirus (COVID-19) disease is a developing global pandemic that can cause pneumonia. A precise study of the infection and molecular pathway of COVID-19 is therefore obviously important. The compounds of LE were identified from the Natural Product Activity and Species Source (NPASS) database and screened by SwissADME. The targets interacted with the compounds and were selected using the Similarity Ensemble Approach (SEA) and Swiss Target Prediction (STP) methods. PubChem was used to classify targets linked to COVID-19. The protein-protein interaction (PPI) networks and signaling pathways-targets-bioactive compounds (STB) networks were constructed by RPackage. Lastly, we performed the molecular docking test (MDT) to verify the binding affinity between significant complexes through AutoDock 1.5.6. The Natural Product Activity and Species Source (NPASS) revealed a total of 82 compounds from LE, which interacted with 1262 targets (SEA and STP), and 249 overlapping targets were identified. The 19 final overlapping targets from the 249 targets and 356 COVID-19 targets were ultimately selected. A bubble chart exhibited that inhibition of the MAPK signaling pathway could be a key mechanism of LE on COVID-19. The three key targets (RELA, TNF, and VEGFA) directly related to the MAPK signaling pathway, and methyl 4-prenyloxycinnamate, tormentic acid, and eugenol were related to each target and had the most stable binding affinity. The three bioactive effects on the three key targets might be synergistic effects to alleviate symptoms of COVID-19 infection. Overall, this study shows that LE can play a role in alleviating COVID-19 symptoms, revealing that the three components (bioactive compounds, targets, and mechanism) are the most significant elements of LE against COVID-19. However, the promising mechanism of LE on COVID-19 is only predicted on the basis of mining data; the efficacy of the chemical compounds and the affinity between compounds and the targets in experiment was ignored, which should be further substantiated through clinical trials.

New Insight into Drugs to Alleviate Atopic March via Network Pharmacology-Based Analysis.

In the present study, a subject of atopic dermatitis (AD) is exposed progressively to allergic rhinitis (AR) and asthma (AS), which is defined as atopic march (AM). However, both the targets and compounds against AM are still largely unknown. Hence, we investigated the overlapping targets related directly to the occurrence and development of AD, AR, and AS through public databases (DisGeNET, and OMIM). The final overlapping targets were considered as key targets of AM, which were visualized by a Venn diagram. The protein-protein interaction (PPI) network was constructed using R package software. We retrieved the association between targets and ligands via scientific journals, and the ligands were filtered by physicochemical properties. Lastly, we performed a molecular docking test (MDT) to identify the significant ligand on each target. A total of 229 overlapping targets were considered as AM causal elements, and 210 out of them were interconnected with each other. We adopted 65 targets representing the top 30% highest in degree centrality among 210 targets. Then, we obtained 20 targets representing the top 30% greatest in betweenness centrality among 65 targets. The network analysis unveiled key targets against AM, and the MDT confirmed the affinity between significant compounds and targets. In this study, we described the significance of the eight uppermost targets (CCL2, CTLA4, CXCL8, ICAM1, IL10, IL17A, IL1B, and IL2) and eight ligands (Bindarit, CTLA-4 inhibitor, Danirixin, A-205804, AX-24 HCl, Y-320, T-5224, and Apilimod) against AM, providing a scientific basis for further experiments.

Drug Investigation to Dampen the Comorbidity of Rheumatoid Arthritis and Osteoporosis via Molecular Docking Test.

At present, most rheumatoid arthritis (RA) patients are at risk of osteoporosis (OP), which is increased by 1.5 times compared to non-RA individuals. Hence, we investigated overlapping targets related directly to the occurrence and development of RA and OP through public databases (DisGeNET, and OMIM) and literature. A total of 678 overlapping targets were considered as comorbid factors, and 604 out of 678 were correlated with one another. Interleukin 6 (IL-6), with the highest degree of value in terms of protein−protein interaction (PPI), was considered to be a core target against comorbidity. We identified 31 existing small molecules (< 1000 g/mol) as IL-6 inhibitors, and 19 ligands were selected by the 3 primary criteria (Lipinski's rule, TPSA, and binding energy). We postulated that MD2-TLR4-IN-1 (PubChem ID: 138454798), as confirmed by the three criteria, was the key ligand to alleviate comorbidity between RA and OP. In conclusion, we described a promising active ligand (MD2-TLR4-IN-1), and a potential target (IL-6) against comorbidity of RA and OP, providing scientific evidence for a further clinical trial.

Network Pharmacology Study to Elucidate the Key Targets of Underlying Antihistamines against COVID-19.

Antihistamines have potent efficacy to alleviate COVID-19 (Coronavirus disease 2019) symptoms such as anti-inflammation and as a pain reliever. However, the pharmacological mechanism(s), key target(s), and drug(s) are not documented well against COVID-19. Thus, we investigated to decipher the most significant components and how its research methodology was utilized by network pharmacology. The list of 32 common antihistamines on the market were retrieved via drug browsing databases. The targets associated with the selected antihistamines and the targets that responded to COVID-19 infection were identified by the Similarity Ensemble Approach (SEA), SwissTargetPrediction (STP), and PubChem, respectively. We described bubble charts, the Pathways-Targets-Antihistamines (PTA) network, and the protein-protein interaction (PPI) network on the RPackage via STRING database. Furthermore, we utilized the AutoDock Tools software to perform molecular docking tests (MDT) on the key targets and drugs to evaluate the network pharmacological perspective. The final 15 targets were identified as core targets, indicating that Neuroactive ligand-receptor interaction might be the hub-signaling pathway of antihistamines on COVID-19 via bubble chart. The PTA network was constructed by the RPackage, which identified 7 pathways, 11 targets, and 30 drugs. In addition, GRIN2B, a key target, was identified via topological analysis of the PPI network. Finally, we observed that the GRIN2B-Loratidine complex was the most stable docking score with -7.3 kcal/mol through molecular docking test. Our results showed that Loratadine might exert as an antagonist on GRIN2B via the neuroactive ligand-receptor interaction pathway. To sum up, we elucidated the most potential antihistamine, a key target, and a key pharmacological pathway as alleviating components against COVID-19, supporting scientific evidence for further research.

Network pharmacology-based study to identify the significant pathways of Lentinula edodes against cancer.

Lentinula edodes (LE) is known as a good food source with potent anticancer efficacy, but its active chemical compounds and pathways against cancer have not been revealed. This study was to uncover the active chemical constituents and pathways of LE against cancer through network pharmacology. The chemical compositions were recognized by gas chromatography-mass spectrometry (GC-MS) and filtered drug-like compounds (DLCs) by SwissADME. Targets related to filtered compounds were recognized by two public databases and the final overlapping targets were identified by Venn diagram. Then, protein-protein interaction (PPI) and pathway-target-compound (PTC) networks were built by RStudio. Ultimately, we recognized the key compounds and targets via molecular docking test (MDT). A total of 33 compounds from LE were accepted by Lipinski's rule were selected as DLCs. The 33 compounds were associated with 108 targets and a key target (cyclooxygenase2 [COX2]) was identified through PPI networks. Most significantly, inactivation of pathways in cancer and activation of peroxisome proliferator activated receptor signaling pathway were significant pathways of LE. On MDT, we identified a key compound (Indole, 2-methyl-3-phenyl) on COX2 related to inactivation of athways in cancer, additionally, the number of 6 ergostane steroids was associated with the two pathways might be dual efficacy to alleviate inflammation against cancer. Overall, 13 targets, 11 compounds, and 2 key pathways of LE were identified as the significant elements to treat cancer. Hence, this study shows therapeutic evidence to verify the promising clinical effect of LE on cancer, suggesting that LE might be an important mushroom against cancer. PRACTICAL APPLICATIONS: Lentinula edodes (LE) has been used widely in cuisine as well as alternative medicines, especially, for anticancer. The LE has rich nutritional compounds including proteins, vitamins, polyphenols, and glucans, however, most of which have a critical hurdle as poor bioavailability not to be applicable for pharmaceuticals. Its main cause is very hydrophilic property. Thus, we adopted GC-MS analysis to identify lipophilic compounds to enhance cell permeability involved in bioavailability. The compounds selected from LE were confirmed by Lipinski's rule for drug-like-compounds (DLCs). Then, we retrieved targets associated with DLCs, and multiple pathways, multiple targets, and multiple compounds against cancer on network-based analysis. In summary, our study reveals the medicinal value of LE on cancer based on the multicomponents. Overall, the aim of this work is to represent the pharmacological evidence to reveal the therapeutic efficacy of AC on cancer, suggesting that DLCs from AC might be alleviators to dampen cancer.

Microwave-Assisted Synchronous Nanogold Synthesis Reinforced by Kenaf Seed and Decoding Their Biocompatibility and Anticancer Activity.

The combination of green-nanotechnology and biology may contribute to anticancer therapy. In this regard, using gold nanoparticles (GNPs) as therapeutic molecules can be a promising strategy. Herein, we proposed a novel biocompatible nanogold constructed by simply microwave-heating (MWI) Au3+ ions and kenaf seed (KS) extract within a minute. The phytoconstituents of KS extract have been utilized for safe synthesis of gold nanoparticles (KS@GNPs). The biogenic KS@GNPs were characterized by UV-vis Spectra, TEM, HR-TEM, XRD, FTIR, DLS, EDX, and SEAD techniques. The legitimacy and toxicity concern of KS@GNPs were tested against RAW 264.7 and NIH3T3 cell lines. The anticancer efficacy was verified using LN-229 cells. The pathways of KS@GNPs synthesis were optimized by varying the KS concentration (λmax 528 nm), gold salt amount (λmax 524 nm), and MWI times (λmax 522 nm). TEM displayed spherical shape and narrow size distribution (5-19.5 nm) of KS@GNPs, whereas DLS recorded Z-average size of 121.7 d·nm with a zeta potential of -33.7 mV. XRD and SAED ring patterns confirmed the high crystallinity and crystalline face centered cubic structure of gold. FTIR explored OH functional group involved in Au3+ ions reduction followed by GNPs stabilization. KS@GNPs exposure to RAW 264.7 and NIH3T3 cell lines did not induce toxicity while dose-dependent overt cell toxicity and reduced cell viability (26.6%) was observed in LN-229 cells. Moreover, the IC50 (18.79 µg/mL) treatment to cancer cell triggered cellular damages, excessive ROS generation, and apoptosis. Overall, this research exploits a sustainable method of KS@GNPs synthesis and their anticancer therapy.

Network Pharmacology Study to Reveal the Potentiality of a Methanol Extract of Caesalpinia sappan L. Wood against Type-2 Diabetes Mellitus.

Caesalpinia sappan L. (CS) is widely used to treat diabetic complications in south-east Asia, specifically in traditional Chinese medicine. This study intends to explain the molecular mechanism of how chemical constituents of CS interrelate with different signaling pathways and receptors involved in T2DM. GC-MS was employed to identify the chemical compounds from the methanol extract of CS wood (MECSW). Lipinski's rule of five was applied, and 33 bioactive constituents have been screened from the CS extract. After that, 124 common targets and 26 compounds associated with T2DM were identified by mining several public databases. Protein-protein interactions and compound-target network were constructed using the STRING database and Cytoscape tool. Protein-protein interactions were identified in 121 interconnected nodes active in T2DM and peroxisome proliferator-activated receptor gamma (PPARG) as key target receptors. Furthermore, pathway compound target (PCT) analysis using the merger algorithm plugin of Cytoscape revealed 121 nodes from common T2DM targets, 33 nodes from MECSW compounds and 9 nodes of the KEGG pathway. Moreover, network topology analysis determined "Fisetin tetramethyl ether" as the key chemical compound. The DAVID online tool determined seven signaling receptors, among which PPARG was found most significant in T2DM progression. Gene ontology and KEGG pathway analysis implied the involvement of nine pathways, and the peroxisome proliferator-activated receptor (PPAR) pathway was selected as the hub signaling pathway. Finally, molecular docking and quantum chemistry analysis confirmed the strong binding affinity and reactive chemical nature of fisetin tetramethyl ether with target receptors exceeding that of the conventional drug (metformin), PPARs agonist (rosiglitazone) and co-crystallized ligands, indicating that fisetin could be a potential drug of choice in T2DM management. This study depicts the interrelationship of the bioactive compounds of MECSW with the T2DM-associated signaling pathways and target receptors. It also proposes a more pharmaceutically effective substance, fisetin tetramethyl ether, over the standard drug that activates PPARG protein in the PPAR signaling pathway of T2DM.

Exploring the impact of daily food habit and modification of lifestyle for boosting immunity against COVID-19.

The lockdown crisis due to novel coronavirus (COVID-19) mainly affected people who live under economic despair. Since boosting the immune system against the virus depends on a variety of food intake and lifestyle approaches; hence, it is crucial to know how daily food habits and lifestyle modification protect from pathogenic viral infections. This study focused on the benefit of plant-based foods, functional foods and the modified lifestyle which enhance the immunity of all aged groups against COVID-19 in Bangladesh. An online close-ended randomly selected structured multiple-choice questionnaire survey was conducted for people of different parts of Bangladesh (n = 161; male 51.55%, female 48.45%). The total percentage was counted for all variables. We found that plant-based foods, functional foods, and physical exercise played a vital role in enhancing people's immunity to control COVID-19. Plant-based micronutrients, nutraceuticals and antioxidants mainly took part to boost the immune system against the virus. Furthermore, physical activity had a vital role in improving people's immunity to manage COVID-19. Literature suggested that food habits, body immunity, awareness, stress and weight variation were affected by the COVID-19 pandemic. The vaccine or proper medication of COVID-19 still remains in an enigma. In this situation, boosting immunity to combat Coronavirus is the only way to survive.

Uncovering a Hub Signaling Pathway of Antimicrobial-Antifungal-Anticancer Peptides' Axis on Short Cationic Peptides via Network Pharmacology Study.

Short cationic peptides (SCPs) with therapeutic efficacy of antimicrobial peptides (AMPs), antifungal peptides (AFPs), and anticancer peptides (ACPs) are known as an enhancement of the host defense system. Here, we investigated the uppermost peptide(s), hub signaling pathway(s), and their associated target(s) through network pharmacology. Firstly, we selected SCPs with positive amino acid residues on N- and C- terminals under 500 Dalton via RStudio. Secondly, the overlapping targets between the bacteria-responsive targets (TTD and OMIM) and AMPs' targets were visualized by VENNY 2.1. Thirdly, the overlapping targets between AFPs' targets and fungal-responsive targets were exhibited by VENNY 2.1. Fourthly, the overlapping targets between cancer-related targets (TTD and OMIM) and fungal-responsive targets were displayed by VENNY 2.1. Finally, a molecular docking study (MDS) was carried out to discover the most potent peptides on a hub signaling pathway. A total of 1833 SCPs were identified, and AMPs', AFPs', and ACPs' filtration suggested that 197 peptides (30 targets), 81 peptides (6 targets), and 59 peptides (4 targets) were connected, respectively. The AMPs-AFPs-ACPs' axis indicated that 27 peptides (2 targets) were associated. Each hub signaling pathway for the enhancement of the host defense system was "Inactivation of Rap1 signaling pathway on AMPs", "Activation of Notch signaling pathway on AMPs-AFPs' axis", and "Inactivation of HIF-1 signaling pathway on AMPs-AFPs-ACPs' axis". The most potent peptides were assessed via MDS; finally, HPIK on STAT3 and HVTK on NOS2 and on HIF-1 signaling pathway were the most stable complexes. Furthermore, the two peptides had better affinity scores than standard inhibitors (Stattic, 1400 W). Overall, the most potent SCPs for the human defense system were HPIK on STAT3 and HVTK on NOS2, which might inactivate the HIF-1 signaling pathway.

Elucidating Drug-Like Compounds and Potential Mechanisms of Corn Silk (Stigma Maydis) against Obesity: A Network Pharmacology Study.

Corn silk (Stigma Maydis) has been utilized as an important herb against obesity by Chinese, Korean, and Native Americans, but its phytochemicals and mechanisms(s) against obesity have not been deciphered completely. This study aimed to identify promising bioactive constituents and mechanism of action(s) of corn silk (CS) against obesity via network pharmacology. The compounds from CS were identified using Gas Chromatography Mass Spectrometry (GC-MS) and were confirmed ultimately by Lipinski's rule via SwissADME. The relationships of the compound-targets or obesity-related targets were confirmed by public bioinformatics. The signaling pathways related to obesity, protein-protein interaction (PPI), and signaling pathways-targets-bioactives (STB) were constructed, visualized, and analyzed by RPackage. Lastly, Molecular Docking Test (MDT) was performed to validate affinity between ligand(s) and protein(s) on key signaling pathway(s). We identified a total of 36 compounds from CS via GC-MS, all accepted by Lipinski's rule. The number of 36 compounds linked to 154 targets, 85 among 154 targets related directly to obesity-targets (3028 targets). Of the final 85 targets, we showed that the PPI network (79 edges, 357 edges), 12 signaling pathways on a bubble chart, and STB network (67 edges, 239 edges) are considered as therapeutic components. The MDT confirmed that two key activators (ß-Amyrone, ß-Stigmasterol) bound most stably to PPARA, PPARD, PPARG, FABP3, FABP4, and NR1H3 on the PPAR signaling pathway, also, three key inhibitors (Neotocopherol, Xanthosine, and ß-Amyrone) bound most tightly to AKT1, IL6, FGF2, and PHLPP1 on the PI3K-Akt signaling pathway. Overall, we provided promising key signaling pathways, targets, and bioactives of CS against obesity, suggesting crucial pharmacological evidence for further clinical testing.

Development of value added drinks from date palm juice (Phoenix sylvestris).

The high decaying tendency of date palm juice limited its manifold application. Here, we developed a preservation technique for concentrated juice and formulated ready to serve (RTS) drinks. The collected date palm juice was heated at 85 °C for 5 min; scum was removed and preserved in the sterilized glass bottle. After that, this pasteurized juice was concentrated to 9%, 12%, 15%, 18% and 21% total soluble solids (TSS) levels and treated with 200 ppm of potassium metabisulfite (KMS) and stored at refrigerated temperature (4 °C). Among them, 18% TSS showed overall acceptability to sensory evaluations for colour, flavour, sweetness, TSS, acidity and microbial load. In contrast, heat treated date palm juice (9% TSS) was used to formulate RTS drinks containing 10%, 20%, 30% and 40% date palm juice, were preserved in sterilized bottles and stored at 30 °C. Results showed that RTS drinks containing 30% date palm juice secured the best colour, flavour, sweetness, TSS, acidity, microbial load and overall acceptability. Furthermore, no significant change was observed in TSS, acidity, microbial load up to three and six months for concentrated juice and RTS drinks, respectively.

Network Pharmacology-Based Study to Uncover Potential Pharmacological Mechanisms of Korean Thistle (Cirsium japonicum var. maackii (Maxim.) Matsum.) Flower against Cancer.

Cirsium japonicum var. maackii (Maxim.) Matsum. or Korean thistle flower is a herbal plant used to treat tumors in Korean folk remedies, but its essential bioactives and pharmacological mechanisms against cancer have remained unexplored. This study identified the main compounds(s) and mechanism(s) of the C. maackii flower against cancer via network pharmacology. The bioactives from the C. maackii flower were revealed by gas chromatography-mass spectrum (GC-MS), and SwissADME evaluated their physicochemical properties. Next, target(s) associated with the obtained bioactives or cancer-related targets were retrieved by public databases, and the Venn diagram selected the overlapping targets. The networks between overlapping targets and bioactives were visualized, constructed, and analyzed by RPackage. Finally, we implemented a molecular docking test (MDT) to explore key target(s) and compound(s) on AutoDockVina and LigPlot+. GC-MS detected a total of 34 bioactives and all were accepted by Lipinski's rules and therefore classified as drug-like compounds (DLCs). A total of 597 bioactive-related targets and 4245 cancer-related targets were identified from public databases. The final 51 overlapping targets were selected between the bioactive targets network and cancer-related targets. With Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, a total of 20 signaling pathways were manifested, and a hub signaling pathway (PI3K-Akt signaling pathway), a key target (Akt1), and a key compound (Urs-12-en-24-oic acid, 3-oxo, methyl ester) were selected among the 20 signaling pathways via MDT. Overall, Urs-12-en-24-oic acid, 3-oxo, methyl ester from the C. maackii flower has potent anti-cancer efficacy by inactivating Akt1 on the PI3K-Akt signaling pathway.

Network Pharmacology Study on Morus alba L. Leaves: Pivotal Functions of Bioactives on RAS Signaling Pathway and Its Associated Target Proteins against Gout.

M. alba L. is a valuable nutraceutical plant rich in potential bioactive compounds with promising anti-gouty arthritis. Here, we have explored bioactives, signaling pathways, and key proteins underlying the anti-gout activity of M. alba L. leaves for the first-time utilizing network pharmacology. Bioactives in M. alba L. leaves were detected through GC-MS (Gas Chromatography-Mass Spectrum) analysis and filtered by Lipinski's rule. Target proteins connected to the filtered compounds and gout were selected from public databases. The overlapping target proteins between bioactives-interacted target proteins and gout-targeted proteins were identified using a Venn diagram. Bioactives-Proteins interactive networking for gout was analyzed to identify potential ligand-target and visualized the rich factor on the R package via the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on STRING. Finally, a molecular docking test (MDT) between bioactives and target proteins was analyzed via AutoDock Vina. Gene Set Enrichment Analysis (GSEA) demonstrated that mechanisms of M. alba L. leaves against gout were connected to 17 signaling pathways on 26 compounds. AKT1 (AKT Serine/Threonine Kinase 1), γ-Tocopherol, and RAS signaling pathway were selected as a hub target, a key bioactive, and a hub signaling pathway, respectively. Furthermore, three main compounds (γ-Tocopherol, 4-Dehydroxy-N-(4,5-methylenedioxy-2-nitrobenzylidene) tyramine, and Lanosterol acetate) and three key target proteins-AKT1, PRKCA, and PLA2G2A associated with the RAS signaling pathway were noted for their highest affinity on MDT. The identified three key bioactives in M. alba L. leaves might contribute to recovering gouty condition by inactivating the RAS signaling pathway.