Subtractive proteomics-based vaccine targets annotation and reverse vaccinology approaches to identify multiepitope vaccine against Plesiomonas shigelloides.

Plesiomonas shigelloides, an aquatic bacterium belonging to the Enterobacteriaceae family, is a frequent cause of gastroenteritis with diarrhea and gastrointestinal severe disease. Despite decades of research, discovering a licensed and globally accessible vaccine is still years away. Developing a putative vaccine that can combat the Plesiomonas shigelloides infection by boosting population immunity against P. shigelloides is direly needed. In the framework of the current study, the entire proteome of P. shigelloides was explored using subtractive genomics integrated with the immunoinformatics approach for designing an effective vaccine construct against P. shigelloides. The overall stability of the vaccine construct was evaluated using molecular docking, which demonstrated that MEV showed higher binding affinities with toll-like receptors (TLR4: 51.5 ± 10.3, TLR2: 60.5 ± 9.2) and MHC receptors(MHCI: 79.7 ± 11.2 kcal/mol, MHCII: 70.4 ± 23.7). Further, the therapeutic efficacy of the vaccine construct for generating an efficient immune response was evaluated by computational immunological simulation. Finally, computer-based cloning and improvement in codon composition without altering amino acid sequence led to the development of a proposed vaccine. In a nutshell, the findings of this study add to the existing knowledge about the pathogenesis of this infection. The schemed MEV can be a possible prophylactic agent for individuals infected with P. shigelloides. Nevertheless, further authentication is required to guarantee its safeness and immunogenic potential.

The antihyperglycemic potential of pyrazolobenzothiazine 1, 1-dioxide novel derivative in mice using integrated molecular pharmacological approach.

Diabetes Mellitus is a metabolic disease characterized by elevated blood sugar levels caused by inadequate insulin production, which subsequently leads to hyperglycemia. This study was aimed to investigate the antidiabetic potential of pyrazolobenzothiazine derivatives in silico, in vitro, and in vivo. Molecular docking of pyrazolobenzothiazine derivatives was performed against α-glucosidase and α-amylase and compounds were selected based on docking score, bonding interactions and low root mean square deviation (RMSD). Enzyme inhibition assay against α-glucosidase and α-amylase was performed in vitro using p-nitrophenyl-α-D-glucopyranoside (PNPG) and starch substrate. Synthetic compound pyrazolobenzothiazine (S1) exhibited minimal conformational changes during the 100 ns MD simulation run. S1 also revealed effective IC50 values for α-glucosidase (3.91 µM) and α-amylase (8.89 µM) and an enzyme kinetic study showed low ki (- 0.186 µM, - 1.267 µM) and ki' (- 0.691 µM, - 1.78 µM) values with the competitive type of inhibition for both enzymes α-glucosidase and α-amylase, respectively. Moreover, studies were conducted to check the effect of the synthetic compound in a mouse model. A low necrosis rate was observed in the liver, kidney, and pancreas through histology analysis performed on mice. Compound S1 also exhibited a good biochemical profile with lower sugar level (110-115 mg/dL), increased insulin level (25-30 µM/L), and low level of cholesterol (85 mg/dL) and creatinine (0.6 mg/dL) in blood. The treated mice group also exhibited a low % of glycated haemoglobin (3%). This study concludes that S1 is a new antidiabetic-agent that helps lower blood glucose levels and minimizes the complications associated with type-II diabetes.

Risk of infection with arboviruses in a healthy population in Pakistan based on seroprevalence.

Infectious diseases caused by arboviruses are a public health concern in Pakistan. However, the studies on data prevalence and threats posed by arboviruses are limited. This study investigated the seroprevalence of arboviruses in a healthy population in Pakistan, including severe fever with thrombocytopenia syndrome virus (SFTSV), Crimean-Congo hemorrhagic fever virus (CCHFV), Tamdy virus (TAMV), and Karshi virus (KSIV) based on a newly established luciferase immunoprecipitation system (LIPS) assays, and Zika virus (ZIKV) by enzyme-linked immunosorbent assays (ELISA). Neutralizing activities against these arboviruses were further examined from the antibody positive samples. The results showed that the seroprevalence of SFTSV, CCHFV, TAMV, KSIV, and ZIKV was 17.37%, 7.58%, 4.41%, 1.10%, and 6.48%, respectively, and neutralizing to SFTSV (1.79%), CCHFV (2.62%), and ZIKV (0.69%) were identified, as well as to the SFTSV-related Guertu virus (GTV, 0.83%). Risk factors associated with the incidence of exposure and levels of antibody response were analyzed. Moreover, co-exposure to different arboviruses was demonstrated, as thirty-seven individuals were having antibodies against multiple viruses and thirteen showed neutralizing activity. Males, individuals aged ≤40 years, and outdoor workers had high risk of exposure to arboviruses. All these results reveal the substantial risks of infection with arboviruses in Pakistan, and indicate the threat from co-exposure to multiple arboviruses. The findings raise the need for further epidemiologic investigation in expanded regions and populations and the necessity to improve health surveillance in Pakistan.

Multitarget Mechanisms of Monocarbonyl Curcuminoid Analogues against HL-60 Cancer Cells: In Vitro and Network Pharmacology-Based Approach.

This study addressed the cytotoxic potential of four compounds: monocarbonyl curcuminoid, ethyl (2E)-2-benzylidene-3-oxobutanoate 1, 1,2-dimethoxy-12-methyl-13H- [1,3] benzodioxolo[5,6-c] phenanthridine 2, 3,5-dibenzyloxybenzyl bromide 3, and (E)-4-(4-chlorobenzylidene)-1-(4-nitrophenyl)hexan-3-one 4. In vitro cytotoxic assays were carried out in HL-60 and BJ cells using the MTT assay along with analysis of apoptosis with the annexin V detection kit. Additional network pharmacology and docking analyses were carried out. In the in vitro assays, compounds 2 and 4 displayed significant antiproliferative effects in HL-60 cells, exhibiting IC50 values of 5.02 and 9.50 µM, respectively. Compound 1 showed no activity, and compound 3 displayed toxicity in BJ cells. In addition, both compounds 2 and 4 induced apoptosis in HL-60 cells. Network pharmacology and docking analyses indicated that compounds 2 and 4 had synergistic effects targeting the CASP3 and PARP1 proteins. Notably, these proteins play pivotal roles in cancer-related pathways. Thus, by modulating these proteins, monocarbonyl curcuminoid has the potential to influence various cancer-related pathways. In summary, our novel findings provide valuable insights into the potential of these compounds to serve as novel anticancer therapeutic agents, warranting further mechanistic studies and clinical exploration.

Regenerative Medicine and Nanotechnology approaches against Cardiovascular Diseases: Recent Advances and Future Prospective.

Regenerative medicine refers to medical research focusing on repairing, replacing, or regenerating damaged or diseased tissues or organs. Cardiovascular disease (CVDs) is a significant health issue globally and is the leading cause of death in many countries. According to the Centers for Disease Control and Prevention (CDC), one person dies every 34 seconds in the United States from cardiovascular diseases, and according to a World Health Organization (WHO) report, cardiovascular diseases are the leading cause of death globally, taking an estimated 17.9 million lives each year. Many conventional treatments are available using different drugs for cardiovascular diseases, but these treatments are inadequate. Stem cells and nanotechnology are promising research areas for regenerative medicine treating CVDs. Regenerative medicines are a revolutionary strategy for advancing and successfully treating various diseases, intending to control cardiovascular disorders. This review is a comprehensive study of different treatment methods for cardiovascular diseases using different types of biomaterials as regenerative medicines, the importance of different stem cells in therapeutics, the expanded role of nanotechnology in treatment, the administration of several types of stem cells, their tracking, imaging, and the final observation of clinical trials on many different levels as well as it aims to keep readers up to pace on emerging therapeutic applications of some specific organs and disorders that may improve from regenerative medicine shortly.

Deciphering Multi-target Pharmacological Mechanism of Cucurbita pepo Seeds against Kidney Stones: Network Pharmacology and Molecular Docking Approach.

BACKGROUND: Urolithiasis is a prevalent condition with significant morbidity and economic implications. The economic burden associated with urolithiasis primarily stems from medical expenses. Previous literature suggests that herbal plants, including Cucurbita pepo, have lithotriptic capabilities. C. pepo is an annual, herbaceous, widely grown, and monoecious vegetative plant known for its antioxidants, fibers, and fatty acids. Recent studies on C. pepo seeds have shown therapeutic potential in reducing bladder stones and urodynamic illnesses, like kidney stones. However, the precise molecular and pharmacological mechanisms are unclear. OBJECTIVE: In this research, we employed network pharmacology and molecular docking to examine the active compounds and biological mechanisms of Cucurbita pepo against kidney stones. METHODS: Active constituents were obtained from previous studies and the IMPPAT database, with their targets predicted using Swiss target prediction. Kidney stone-associated genes were collected from DisGeNET and GeneCards. The active constituent-target-pathway network was constructed using Cytoscape, and the target protein-protein interaction network was generated using the STRING database. Gene enrichment analysis of C. pepo core targets was conducted using DAVID. Molecular docking was performed to identify potential kidney stone-fighting agents. RESULTS: The findings revealed that Cucurbita pepo contains 18 active components and has 192 potential gene targets, including AR, EGFR, ESR1, AKT1, MAPK3, SRC, and MTOR. Network analysis demonstrated that C. pepo seeds may prevent kidney stones by influencing disease-related signaling pathways. Molecular docking indicated that key kidney stone targets (mTOR, EGFR, AR, and ESR1) effectively bind with active constituents of C. pepo. CONCLUSION: These findings provide insight into the anti-kidney stone effects of Cucurbita pepo at a molecular level. In conclusion, this study contributes to understanding the potential of Cucurbita pepo in combating kidney stones and lays the foundation for further research.

Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective.

Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases, such as skin, breast, and lung cancer. AI is an advanced form of technology that uses mathematical-based algorithmic principles similar to those of the human mind for cognizing complex challenges of the healthcare unit. Cancer is a lethal disease with many etiologies, including numerous genetic and epigenetic mutations. Cancer being a multifactorial disease is difficult to be diagnosed at an early stage. Therefore, genetic variations and other leading factors could be identified in due time through AI and machine learning (ML). AI is the synergetic approach for mining the drug targets, their mechanism of action, and drug-organism interaction from massive raw data. This synergetic approach is also facing several challenges in data mining but computational algorithms from different scientific communities for multi-target drug discovery are highly helpful to overcome the bottlenecks in AI for drug-target discovery. AI and ML could be the epicenter in the medical world for the diagnosis, treatment, and evaluation of almost any disease in the near future. In this comprehensive review, we explore the immense potential of AI and ML when integrated with the biological sciences, specifically in the context of cancer research. Our goal is to illuminate the many ways in which AI and ML are being applied to the study of cancer, from diagnosis to individualized treatment. We highlight the prospective role of AI in supporting oncologists and other medical professionals in making informed decisions and improving patient outcomes by examining the intersection of AI and cancer control. Although AI-based medical therapies show great potential, many challenges must be overcome before they can be implemented in clinical practice. We critically assess the current hurdles and provide insights into the future directions of AI-driven approaches, aiming to pave the way for enhanced cancer interventions and improved patient care.

Systematic elucidation of the multi-target pharmacological mechanism of Terminalia arjuna against congestive cardiac failure via network pharmacology and molecular modelling approaches.

Congestive cardiac failure (CCF) is a pathophysiologic state when the heart is not able to maintain its cardiac output to meet the demand of metabolising tissues. CCF is responsible for approximately 2.9 million deaths worldwide. The heterogeneous nature of CCF draws the attention of researchers to find more enthralling and promising diagnostic and treatment options. Terminalia arjuna (Arjuna) is an evergreen, deciduous tree exhibited various astringent, anti-bacterial, and anti-microbial properties. T. arjuna is being used in various regions for anginal pain, hypertension, congestive heart failure, and dyslipidemia. Although previous in vitro studies have demonstrated the therapeutic potential of T. arjuna, the exact molecular mechanism underlying its protective effect on the heart remains unclear. In this study, a network pharmacology technique was used to explore the active ingredients, potential targets in T. arjuna for the treatment of CCF. In the framework of this study, we explored the active ingredient-target-pathway network and figured out that oleanolic acid, arjunolic acid, luteolin, kaempferol, cholesterol, ellagic acid 4-O-xylopyranoside 3,3'-dimethyl ether, and cyclohexyl (2,4-dimethyl phenyl) methanone contributed significantly to the development of CCF by affecting AKT1, MAPK14, TNF, IL6, ESR1, and HSP90AA1 genes. Molecular docking analysis further validated the activities of these compounds against potential targets. To sum up, integrated network pharmacology and docking analysis revealed that T. arjuna exerts its cardioprotective effect by acting on various signalling pathways, including the thyroid hormone, VEGF signalling pathway, AGE-RAGE signalling pathway in diabetic complications, HIF signalling pathway, sphingolipid signalling pathway, and oestrogen signalling pathways. Overall, this study provides valuable insights into the molecular mechanism of T. arjuna in CCF and highlights its potential as a promising preventive treatment for this condition.

Impact of Nanotechnology on Differentiation and Augmentation of Stem Cells for Liver Therapy.

The liver is one of the crucial organs of the body that performs hundreds of chemical reactions needed by the body to survive. It is also the largest gland of the body. The liver has multiple functions, including the synthesis of chemicals, metabolism of nutrients, and removal of toxins. It also acts as a storage unit. The liver has a unique ability to regenerate itself, but it can lead to permanent damage if the injury is beyond recovery. The only possible treatment of severe liver damage is liver transplant which is a costly procedure and has several other drawbacks. Therefore, attention has been shifted towards the use of stem cells that have shown the ability to differentiate into hepatocytes. Among the numerous kinds of stem cells (SCs), the mesenchymal stem cells (MSCs) are the most famous. Various studies suggest that an MSC transplant can repair liver function, improve the signs and symptoms, and increase the chances of survival. This review discusses the impact of combining stem cell therapy with nanotechnology. By integrating stem cell science and nanotechnology, the information about stem cell differentiation and regulation will increase, resulting in a better comprehension of stem cell-based treatment strategies. The augmentation of SCs with nanoparticles has been shown to boost the effect of stem cell-based therapy. Also, the function of green nanoparticles in liver therapies is discussed.

Recent Updates on Peptide Molecules in Drug and Vaccine Development.

Peptides are of great importance in the areas of science because they can act as drug carriers and their therapeutic effect and their ability to generate an immune response. As culturing of viral agents for drugs and vaccine development is harmful, therefore, peptide-based drugs and vaccines have achieved great importance. Large immunoglobulins cannot pass the plasma membrane, so peptides are used to study this interaction because of their small size. Peptides with substituted amino acid sequences are also stable in blood serum, which makes them significant for drug development. Peptides with substituted amino acid sequences are stable in blood serum hence, their stability, small size, easy screening, cost-effectiveness, ease of administration and particularity (target specificity) make them effective to be used in pharmaceutical companies. Mostly branched peptides are used for the development of drugs because they are not prone to be degraded by proteolytic enzymes. In peptide-based vaccines, protein acts as the main constituent from which the main component that causes the infection is deleted by recombinant DNA technology, and these peptides act as antigens to stimulate the immune response. Self-assembled peptides have the main role in the delivery of drugs and vaccine molecules inside the living cells because they may also assemble into nano technological structures to improve their efficiency. This review focuses on the characteristics of peptides that make them effective to develop drugs and vaccines. Different peptides like synthetic peptides, antimicrobial peptides, signal peptides, carrier peptides, and their role against various viral, pathogenic, and microbial diseases and in cosmetics are described briefly.

Identification and characterization of codon usage pattern and influencing factors in HFRS-causing hantaviruses.

Hemorrhagic fever with renal syndrome (HFRS) is an acute viral zoonosis carried and transmitted by infected rodents through urine, droppings, or saliva. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors which hinder the development of potential therapeutic solutions for HFRS. Hantaan virus (HTNV), Dobrava-Belgrade virus (DOBV), Seoul virus (SEOV), and Puumala virus (PUUV) are predominantly found in hantaviral species that cause HFRS in patients. Despite ongoing prevention and control efforts, HFRS remains a serious economic burden worldwide. Furthermore, recent studies reported that the hantavirus nucleocapsid protein is a multi-functional protein and plays a major role in the replication cycle of the hantavirus. However, the precise mechanism of the nucleoproteins in viral pathogenesis is not completely understood. In the framework of the current study, various in silico approaches were employed to identify the factors influencing the codon usage pattern of hantaviral nucleoproteins. Based on the relative synonymous codon usage (RSCU) values, a comparative analysis was performed between HFRS-causing hantavirus and their hosts, suggesting that HTNV, DOBV, SEOV, and PUUV, were inclined to evolve their codon usage patterns that were comparable to those of their hosts. The results indicated that most of the overrepresented codons had AU-endings, which revealed that mutational pressure is the major force shaping codon usage patterns. However, the influence of natural selection and geographical factors cannot be ignored on viral codon usage bias. Further analysis also demonstrated that HFRS causing hantaviruses adapted host-specific codon usage patterns to sustain successful replication and transmission chains within hosts. To our knowledge, no study to date reported the factors influencing the codon usage pattern within hantaviral nucleoproteins. Thus, the proposed computational scheme can help in understanding the underlying mechanism of codon usage patterns in HFRS-causing hantaviruses which lend a helping hand in designing effective anti-HFRS treatments in future. This study, although comprehensive, relies on in silico methods and thus necessitates experimental validation for more solid outcomes. Beyond the identified factors influencing viral behavior, there could be other yet undiscovered influences. These potential factors should be targets for further research to improve HFRS therapeutic strategies.

Exploring the recent developments of alginate silk fibroin material for hydrogel wound dressing: A review.

Hydrogels, a type of polymeric material capable of retaining water within a three-dimensional network, have demonstrated their potential in wound healing, surpassing traditional wound dressings. These hydrogels possess remarkable mechanical, chemical, and biological properties, making them suitable scaffolds for tissue regeneration. This article aims to emphasize the advantages of alginate, silk fibroin, and hydrogel-based wound dressings, specifically highlighting their crucial functions that accelerate the healing process of skin wounds. Noteworthy functions include self-healing ability, water solubility, anti-inflammatory properties, adhesion, antimicrobial properties, drug delivery, conductivity, and responsiveness to stimuli. Moreover, recent advancements in hydrogel technology have resulted in the development of wound dressings with enhanced features for monitoring wound progression, further augmenting their effectiveness. This review emphasizes the utilization of hydrogel membranes for treating excisional and incisional wounds, while exploring recent breakthroughs in hydrogel wound dressings, including nanoparticle composite hydrogels, stem cell hydrogel composites, and curcumin-hydrogel composites. Additionally, the review focuses on diverse synthesis procedures, designs, and potential applications of hydrogels in wound healing dressings.

A Comprehensive Update of Various Attempts by Medicinal Chemists to Combat COVID-19 through Natural Products.

The ongoing COVID-19 pandemic has resulted in a global panic because of its continual evolution and recurring spikes. This serious malignancy is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the outbreak, millions of people have been affected from December 2019 till now, which has led to a great surge in finding treatments. Despite trying to handle the pandemic with the repurposing of some drugs, such as chloroquine, hydroxychloroquine, remdesivir, lopinavir, ivermectin, etc., against COVID-19, the SARS-CoV-2 virus continues its out-of-control spread. There is a dire need to identify a new regimen of natural products to combat the deadly viral disease. This article deals with the literature reports to date of natural products showing inhibitory activity towards SARS-CoV-2 through different approaches, such as in vivo, in vitro, and in silico studies. Natural compounds targeting the proteins of SARS-CoV-2-the main protease (Mpro), papain-like protease (PLpro), spike proteins, RNA-dependent RNA polymerase (RdRp), endoribonuclease, exoribonuclease, helicase, nucleocapsid, methyltransferase, adeno diphosphate (ADP) phosphatase, other nonstructural proteins, and envelope proteins-were extracted mainly from plants, and some were isolated from bacteria, algae, fungi, and a few marine organisms.

Discovering common pathogenic processes between COVID-19 and HFRS by integrating RNA-seq differential expression analysis with machine learning.

Zoonotic virus spillover in human hosts including outbreaks of Hantavirus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) imposes a serious impact on the quality of life of patients. Recent studies provide a shred of evidence that patients with Hantavirus-caused hemorrhagic fever with renal syndrome (HFRS) are at risk of contracting SARS-CoV-2. Both RNA viruses shared a higher degree of clinical features similarity including dry cough, high fever, shortness of breath, and certain reported cases with multiple organ failure. However, there is currently no validated treatment option to tackle this global concern. This study is attributed to the identification of common genes and perturbed pathways by combining differential expression analysis with bioinformatics and machine learning approaches. Initially, the transcriptomic data of hantavirus-infected peripheral blood mononuclear cells (PBMCs) and SARS-CoV-2 infected PBMCs were analyzed through differential gene expression analysis for identification of common differentially expressed genes (DEGs). The functional annotation by enrichment analysis of common genes demonstrated immune and inflammatory response biological processes enriched by DEGs. The protein-protein interaction (PPI) network of DEGs was then constructed and six genes named RAD51, ALDH1A1, UBA52, CUL3, GADD45B, and CDKN1A were identified as the commonly dysregulated hub genes among HFRS and COVID-19. Later, the classification performance of these hub genes were evaluated using Random Forest (RF), Poisson Linear Discriminant Analysis (PLDA), Voom-based Nearest Shrunken Centroids (voomNSC), and Support Vector Machine (SVM) classifiers which demonstrated accuracy >70%, suggesting the biomarker potential of the hub genes. To our knowledge, this is the first study that unveiled biological processes and pathways commonly dysregulated in HFRS and COVID-19, which could be in the next future used for the design of personalized treatment to prevent the linked attacks of COVID-19 and HFRS.

Advanced network pharmacology study reveals multi-pathway and multi-gene regulatory molecular mechanism of Bacopa monnieri in liver cancer based on data mining, molecular modeling, and microarray data analysis.

Liver cancer is a malignant tumor that grows on the surface or inside the liver. The leading cause is a viral infection with hepatitis B or C virus. Natural products and their structural analogues have historically made a major contribution to pharmacotherapy, especially for cancer. A list of studies evidences the therapeutic efficacy of Bacopa monnieri against liver cancer, but the precise molecular mechanism is yet to be discovered. This study combines data mining, network pharmacology, and molecular docking analysis to potentially revolutionize liver cancer treatment by identifying effective phytochemicals. Initially, the information on active constituents of B. monnieri and target genes of both liver cancer and B. monnieri were retrieved from literature as well as from publicly available databases. Based on the matching results between B. monnieri potential targets and liver cancer targets, the protein-protein interaction (PPI) network was constructed using the STRING database and imported into Cytoscape for screening of hub genes based on their degree of connectivity. Later, the interactions network between compounds and overlapping genes was constructed using Cytoscape software to analyze the network pharmacological prospective effects of B. monnieri on liver cancer. Gene Ontology (GO) and KEGG pathway analysis of hub genes revealed that these genes are involved in the cancer-related pathway. Lastly, the expression level of core targets was analyzed using microarray data (GSE39791, GSE76427, GSE22058, GSE87630, and GSE112790). Further, the GEPIA server and PyRx software were used for survival and molecular docking analysis, respectively. In summary, we proposed that quercetin, luteolin, apigenin, catechin, epicatechin, stigmasterol, beta-sitosterol, celastrol, and betulic acid inhibit tumor growth by affecting tumor protein 53 (TP53), interleukin 6 (IL6), RAC-alpha serine/threonine protein kinases 1 (AKT1), caspase-3 (CASP3), tumor necrosis factor (TNF), jun proto-oncogene (JUN), heat shot protein 90 AA1 (HSP90AA1), vascular endothelial growth factor A (VEGFA), epidermal growth factor receptor (EGFR), and SRC proto-oncogene (SRC). Through, microarray data analysis, the expression level of JUN and IL6 were found to be upregulated while the expression level of HSP90AA1 was found to be downregulated. Kaplan-Meier survival analysis indicated that HSP90AA1 and JUN are promising candidate genes that can serve as diagnostic and prognostic biomarkers for liver cancer. Moreover, the molecular docking and molecular dynamic simulation of 60ns well complemented the binding affinity of the compound and revealed strong stability of predicted compounds at the docked site. Calculation of binding free energies using MMPBSA and MMGBSA validated the strong binding affinity between the compound and binding pockets of HSP90AA1 and JUN. Despite that, in vivo and in vitro studies are mandatory to unveil pharmacokinetics and biosafety profiles to completely track the candidature status of B. monnieri in liver cancer.

Antidiabetic activity of Berberis brandisiana is possibly mediated through modulation of insulin signaling pathway, inflammatory cytokines and adipocytokines in high fat diet and streptozotocin-administered rats.

Medicinal plants play a key role in protection of chronic non-communicable ailments like diabetes, hypertension and dyslipidemia. Berberis brandisiana Ahrendt (Berberidaceae) is traditionally used to treat diabetes, liver problems, wounds, arthritis, infections, swelling and tumors. It is also known to be enriched with multiple phytoconstituents including berbamine, berberine, quercetin, gallic acid, caffeic acid, vanillic acid, benzoic acid, chlorogenic acid, syringic acid, p-coumaric acid, m-coumaric acid and ferulic acid. The efficacy of B. brandisiana has not been established yet in diabetes. This study has been planned to assess the antidiabetic activity of B. brandisiana in high fat diet and streptozotocin (HFD/STZ)-induced diabetes using animals. Administration of aqueous methanolic extract of B. brandisiana (AMEBB) and berbamine (Berb) for 8 weeks caused a dose dependent marked (p < 0.01) rise in serum insulin and HDL levels with a significant decline (p < 0.01) in glucose, triglycerides, glycosylated hemoglobin (HbA1c), cholesterol, LDL, LFTs and RFTs levels when compared with only HFD/STZ-administered rats. AMEBB and Berb also modulated inflammatory biomarkers (TNF-α, IL-6) and adipocytokines (leptin, adiponectin and chemerin). AMEBB (150 mg/kg and 300 mg/kg) and Berb (80 mg/kg and 160 mg/kg) treated rats showed a marked increase (p < 0.001) in catalase levels (Units/mg) in pancreas (42.4 ± 0.24, 47.4 ± 0.51), (38.2 ± 0.583, 48.6 ± 1.03) and liver (52 ± 1.41, 63.2 ± 0.51), (57.2 ± 0.58, 61.6 ± 1.24) and superoxide dismutase levels (Units/mg) in pancreas (34.8 ± 1.46, 38.2 ± 0.58), (33.2 ± 0.80, 40.4 ± 1.96) and liver (31.8 ± 1.52, 36.8 ± 0.96), (30 ± 0.70, 38.4 ± 0.81),respectively while a significant (p < 0.01) decrease in serum melondialdehyde levels (nmol/g) in pancreas (7.34 ± 0.17, 6.22 ± 0.22), (7.34 ± 0.20, 6.34 ± 0.11) and liver (9.08 ± 0.31,8.18 ± 0.29), (9.34 ± 0.10, 8.86 ± 0.24) compared to the data of only HFD/STZ-fed rats. Histopathological studies of pancreas, liver, kidney, heart and aorta revealed restoration of normal tissue architect in AMEBB and Berb treated rats. When mRNA expressions of candidate genes were assessed, AMEBB and Berb showed upregulation of IRS-1, SIRT1, GLUT-4 and downregulation of ADAM17. These findings suggest that AMEBB and Berb possess antidiabetic activity, possibly due to its effect on oxidative stress, glucose metabolism, inflammatory biomarkers and adipocytokines levels. Further upregulation of IRS-1, SIRT1, GLUT-4 and downregulation of ADAM17, demonstrated its potential impact on glucose homeostasis, insulin resistance and chronic inflammatory markers. Thus, this study provides support to the medicinal use of B. brandisiana and berbamine in diabetes.

Machine learning for synergistic network pharmacology: a comprehensive overview.

Network pharmacology is an emerging area of systematic drug research that attempts to understand drug actions and interactions with multiple targets. Network pharmacology has changed the paradigm from 'one-target one-drug' to highly potent 'multi-target drug'. Despite that, this synergistic approach is currently facing many challenges particularly mining effective information such as drug targets, mechanism of action, and drug and organism interaction from massive, heterogeneous data. To overcome bottlenecks in multi-target drug discovery, computational algorithms are highly welcomed by scientific community. Machine learning (ML) and especially its subfield deep learning (DL) have seen impressive advances. Techniques developed within these fields are now able to analyze and learn from huge amounts of data in disparate formats. In terms of network pharmacology, ML can improve discovery and decision making from big data. Opportunities to apply ML occur in all stages of network pharmacology research. Examples include screening of biologically active small molecules, target identification, metabolic pathways identification, protein-protein interaction network analysis, hub gene analysis and finding binding affinity between compounds and target proteins. This review summarizes the premier algorithmic concepts of ML in network pharmacology and forecasts future opportunities, potential applications as well as several remaining challenges of implementing ML in network pharmacology. To our knowledge, this study provides the first comprehensive assessment of ML approaches in network pharmacology, and we hope that it encourages additional efforts toward the development and acceptance of network pharmacology in the pharmaceutical industry.

Prospects of antimicrobial peptides as an alternative to chemical preservatives for food safety.

Antimicrobial peptides (AMPs) are a potential alternative to antimicrobial agents that have got considerable research interest owing to their significant role in the inhibition of bacterial pathogens. These AMPs can essentially inhibit the growth and multiplication of microbes through multiple mechanisms including disruption of cellular membranes, inhibition of cell wall biosynthesis, or affecting intracellular components and cell division. Moreover, AMPs are biocompatible and biodegradable therefore, they can be a good alternative to antimicrobial agents and chemical preservatives. A few of their features for example thermostability and high selectivity are quite appealing for their potential use in the food industry for food preservation to prevent the spoilage caused by microorganisms and foodborne pathogens. Despite these advantages, very few AMPs are being used at an industrial scale for food preservation as these peptides are quite vulnerable to external environmental factors which deter their practical applications and commercialization. The review aims to provide an outline of the mechanism of action of AMPs and their prospects as an alternative to chemical preservatives in the food industry. Further studies related to the structure-activity relationship of AMPs will help to expand the understanding of their mechanism of action and to determine specific conditions to increase their stability and applicability in food preservation.

Exploring the Antimicrobial and Pharmacological Potential of NF22 as a Potent Inhibitor of E. coli DNA Gyrase: An In Vitro and In Silico Study.

Toward the search for novel antimicrobial agents to control pathogenic E. coli-associated infections, a series of novel norfloxacin derivatives were screened for antimicrobial activities. The norfloxacin derivative, 1-ethyl-6-fluoro-7-(4-(2-(2-(3-hydroxybenzylidene)hydrazinyl)-2-oxoethyl)piperazin-1-yl)-4-oxo-1,4-dihydroquinoline-3-carboxylic acid (NF22) demonstrated excellent antibacterial activities against E. coli ATCC 25922 (MIC = 0.0625 µg/mL) and MDR E. coli 1-3 (MIC = 1, 2 and 1 µg/mL). The time-kill kinetic studies have demonstrated that the NF22 was advantageous over norfloxacin and ciprofloxacin in killing the control and MDR E. coli strains. The checkerboard assay showed that NF22 in combination with tetracycline had a synergistic effect against the E. coli strains. The experimental findings are supported by molecular modeling studies on DNA gyrase, explaining the interactions involved for compound NF22, compared to norfloxacin and ciprofloxacin. Further, the compound was also evaluated for various pharmacokinetics (absorption, metabolism, distribution, toxicity and excretion) as well as drug-likeness properties. Our data have highlighted the potential of norfloxacin by restoring its efficacy against E. coli which could lead to the development of new antimicrobial agents.

Personalized nutrition, microbiota, and metabolism: A triad for eudaimonia.

During the previous few years, the relationship between the gut microbiota, metabolic disorders, and diet has come to light, especially due to the understanding of the mechanisms that particularly link the gut microbiota with obesity in animal models and clinical trials. Research has led to the understanding that the responses of individuals to dietary inputs vary remarkably therefore no single diet can be suggested to every individual. The variations are attributed to differences in the microbiome and host characteristics. In general, it is believed that the immanent nature of host-derived factors makes them difficult to modulate. However, diet can more easily shape the microbiome, potentially influencing human physiology through modulation of digestion, absorption, mucosal immune response, and the availability of bioactive compounds. Thus, diet could be useful to influence the physiology of the host, as well as to ameliorate various disorders. In the present study, we have described recent developments in understanding the disparities of gut microbiota populations between individuals and the primary role of diet-microbiota interactions in modulating human physiology. A deeper understanding of these relationships can be useful for proposing personalized nutrition strategies and nutrition-based therapeutic interventions to improve human health.