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.

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.

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.

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.

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.

Simple and cleaner system of silver nanoparticle synthesis using kenaf seed and revealing its anticancer and antimicrobial potential.

The clean and eco-friendly synthesis of silver nanoparticles (AgNPs) has provided promising characteristics with impressive biomedical related potential. Here, we have employed a green process for the synthesis of AgNPs using kenaf seed (KS) extract as a bilateral mediator for reducing and capping of Ag+ ions under hydrothermal condition. The synthesis pathways, such as varying amounts of KS, Ag ion concentration and autoclaving time were optimized. The manifestation of a strong absorption peak from 420-430 nm in UV-vis spectroscopy indicated the successful synthesis of KS@AgNPs. Fourier transform infrared spectroscopy confirmed the presence of hydroxyl and carbonyl functionalities involved in the reduction and stabilization of Ag+ ions. Furthermore, transmission electron microscopy revealed that the KS@AgNPs are spherical in shape having a size around 7-11 nm, whereas high-quality crystals were evidenced by x-ray diffraction analysis. Moreover, inductively coupled plasma-optical emission spectrometry revealed that 19.6 µg l-1 of Ag+ ions were released from the KS@AgNPs. In cell line studies, KS@AgNPs at a higher dose were shown to be non-toxic to the healthy (NIH3T3) cells, while strong anti-proliferative response was found in the case of lung cancer (A549) cells. Furthermore, a significant zone of inhibition was observed for both Gram-positive and Gram-negative microorganisms, and a combination of KS@AgNPs with ampicillin revealed a notable synergistic anti-pathogenic effect. Overall, our study proved the potentiality of KS as an efficient bio-resource for the synthesis of AgNPs and also its original feature as an anti-cancer and antimicrobial agent.

Human bone and amniotic membrane banking in Bangladesh for grafting: the impact of the international atomic energy agency (IAEA) programme.

The idea of establishing a human tissue bank in Bangladesh was started in 1985. However, in 2003, with the active cooperation of international atomic energy agency (IAEA) and Bangladesh Atomic Energy Commission, a tissue bank laboratory was upgraded as a unit for tissue banking and research. Due to increasing demand of allograft, this unit was transformed as an independent institute "Institute of Tissue Banking and Biomaterial Research (ITBBR)" in 2016. This is the only human tissue bank in Bangladesh, which processes human bone and amniotic membrane to provide safe and cost-effective allografts for transplantation. Importantly, banking of human cranial bone as autograft has also started at ITBBR. These processed grafts are sterilized using gamma radiation according to the IAEA Code of Practice for the radiation sterilization of tissues allografts. The amount of grafts produced by the ITBBR from 2007 to 2018 were 120,800 cc of bone chips, 45,420 cm2 of amniotic membranes, 277 vials of de-mineralized bone granules (DMB), 95 pieces of massive bones, and 134 pieces of cranial bones. Overall, 112,748 cc of bone chips, 40,339 cm2 of amniotic membranes, 174 vials of DMB, 44 pieces of massive bones, and 64 pieces of cranial bones were transplanted successfully. Nevertheless, to cope up with the modern advanced concepts of cell and tissue banking for therapeutic purpose, ITBBR is working to set up facilities for skin banking, stem cells banking including amniotic and cord blood derived stem cells and scaffold designing. To ensure the quality, safety, ethical and regulatory issues are sustainable in cell and tissue banking practices, ITBBR always works with the Government of Bangladesh for enhancing the national tissue transplantation programme within the contemporary facilities.

Evaluation of Various Solvent Extracts of Tetrastigma leucostaphylum (Dennst.) Alston Leaves, a Bangladeshi Traditional Medicine Used for the Treatment of Diarrhea.

Tetrastigma leucostaphylum (TL) is an important ethnic medicine of Bangladesh used to treat diarrhea and dysentery. Hence, current study has been designed to characterize the antidiarrheal (in vivo) and cytotoxic (in vitro) effects of T. leucostaphylum. A crude extract was prepared with methanol (MTL) and further partitioned into n-hexane (NTL), dichloromethane (DTL), and n-butanol (BTL) fractions. Antidiarrheal activity was investigated using castor oil induced diarrhea, enteropooling, and gastrointestinal transit models, while cytotoxicity was evaluated using the brine shrimp lethality bioassay. In antidiarrheal experiments, all doses (100, 200, and 400 mg/kg) of the DTL extract significantly reduced diarrheal stool frequency, volume and weight of intestinal contents, and gastrointestinal motility in mice. Similarly, in the cytotoxicity assay, all extracts exhibited activity, with the DTL extract the most potent (LC50 67.23 µg/mL). GC-MS analysis of the DTL extract identified 10 compounds, which showed good binding affinity toward M3 muscarinic acetylcholine, 5-HT3, Gut inhibitory phosphodiesterase, DNA polymerase III subunit alpha, and UDP-N-acetylglucosamine-1 carboxyvinyltransferase enzyme targets upon molecular docking analysis. Although ADME/T analyses predicted the drug-likeness and likely safety upon consumption of these bioactive compounds, significant toxicity concerns are evident due to the presence of the known phytotoxin, 2,4-di-tert-butylphenol. In summary, T. leucostaphylum showed promising activity, helping to rationalize the ethnomedicinal use and importance of this plant, its safety profile following both acute and chronic exposure warrants further investigation.

Unravelling the Biological Activities of the Byttneria pilosa Leaves Using Experimental and Computational Approaches.

Byttneria pilosa is locally known as Harijora, and used by the native hill-tract people of Bangladesh for the treatment of rheumatalgia, snake bite, syphilis, fractured bones, elephantiasis and an antidote for poisoning. The present study was carried out to determine the possible anti-inflammatory, analgesic, neuropharmacological and anti-diarrhoeal activity of the methanol extract of B. pilosa leaves (MEBPL) through in vitro, in vivo and in silico approaches. In the anti-inflammatory study, evaluated by membrane stabilizing and protein denaturation methods, MEBPL showed a significant and dose dependent inhibition. The analgesic effect of MEBPL tested by inducing acetic acid and formalin revealed significant inhibition of pain in both tests. During the anxiolytic evaluation, the extract exhibited a significant and dose-dependent reduction of anxiety-like behaviour in mice. Similarly, mice treated with MEBPL demonstrated dose-dependent reduction in locomotion effect in the open field test and increased sedative effect in the thiopental sodium induced sleeping test. MEBPL also showed good anti-diarrheal activity in both castor oil induced diarrheal and intestinal motility tests. Besides, a previously isolated compound (beta-sitosterol) exhibited good binding affinity in docking and drug-likeliness properties in ADME/T studies. Overall, B. pilosa is a biologically active plant and could be a potential source of drug leads, which warrants further advanced study.

Investigation of the Biological Activities and Characterization of Bioactive Constituents of Ophiorrhiza rugosa var. prostrata (D.Don) & Mondal Leaves through In Vivo, In Vitro, and In Silico Approaches.

Ophiorrhiza rugosa var. prostrata is one of the most frequently used ethnomedicinal plants by the indigenous communities of Bangladesh. This study was designed to investigate the antidiarrheal, anti-inflammatory, anthelmintic and antibacterial activities of the ethanol extract of O. rugosa leaves (EEOR). The leaves were extracted with ethanol and subjected to in vivo antidiarrheal screening using the castor oil-induced diarrhea, enteropooling, and gastrointestinal transit models. Anti-inflammatory efficacy was evaluated using the histamine-induced paw edema test. In parallel, in vitro anthelmintic and antibacterial activities were evaluated using the aquatic worm and disc diffusion assays respectively. In all three diarrheal models, EEOR (100, 200 and 400 mg/kg) showed obvious inhibition of diarrheal stool frequency, reduction of the volume and weight of the intestinal contents, and significant inhibition of intestinal motility. Also, EEOR manifested dose-dependent anti-inflammatory activity. Anthelmintic action was deemed significant (P < 0.001) with respect to the onset of paralysis and helminth death. EEOR also resulted in strong zones of inhibition when tested against both Gram-positive and Gram-negative bacteria. GC-MS analysis identified 30 compounds within EEOR, and of these, 13 compounds documented as bioactive showed good binding affinities to M3 muscarinic acetylcholine, 5-HT3, tubulin and GlcN-6-P synthase protein targets in molecular docking experiments. Additionally, ADME/T and PASS analyses revealed their drug-likeness, likely safety upon consumption and possible pharmacological activities. In conclusion, our findings scientifically support the ethnomedicinal use and value of this plant, which may provide a potential source for future development of medicines.

Attributes of Videos on YouTube Related to Cupping Therapy.

CONTEXT: Cupping is a complementary and alternative therapy that attracts much attention on social media. OBJECTIVET: The study intended to examine the types of user-generated content found on YouTube on the practice of cupping therapy as a form of pain management. DESIGNT: The current research team searched YouTube for videos on cupping therapy on August 14, 2016. SETTINGT: The Internet was accessed from Wayne, NJ, USA. OUTCOME MEASUREST: The research team manually coded the 100 most widely viewed, cupping videos for content and sources. Logistic regression was applied to obtain the association of video source-consumer, news, or professional-to each of the 21 content categories. RESULTST: In total, the 100 videos were viewed more than 36.80 million times. Among them, 52 were consumer videos; 16 were professional videos; and 32 were news videos. Compared to news videos, (1) the odds of consumer videos mentioning what cupping is were 85.90% lower-odds ratio (OR) = 0.14, 95% confidence interval (CI) (0.04 to 0.52), P < .01; (2) the odds of consumer videos and professional videos mentioning an increase in blood flow as a benefit were 93.50% lower-OR = 0.07, 95% CI (0.02 to 0.24), P < .01-and 82.80% lower-OR = 0.17, 95% CI (0.04 to 0.82), P = .03, respectively; and (3) the odds of consumer videos mentioning a decrease in inflammation as a benefit were 92.9% lower-OR = 0.07, 95% CI (0.02 to 0.21), P < .01. CONCLUSIONST: The current study found that, despite the large presence of consumer-based videos in YouTube regarding cupping therapy, news sources were more widely viewed. Health professionals could engage more with YouTube by providing clear and authentic information about a popular alternative therapy.

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.

Bio-mimic optimization strategies in wireless sensor networks: a survey.

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

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.

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.

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.