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Plants generally secrete secondary metabolites in response to stress. These secondary metabolites are very useful for humankind as they possess a wide range of therapeutic activities. Secondary metabolites produced by plants include alkaloids, flavonoids, terpenoids, and steroids. Flavonoids are one of the classes of secondary metabolites of plants found mainly in edible plant parts such as fruits, vegetables, stems, grains, and bark. They are synthesized by the phenylpropanoid pathway. Flavonoids possess antibacterial, antiviral, antioxidant, anti-inflammatory, antimutagenic, and anticarcinogenic properties. Due to their various therapeutic applications, various pharmaceutical companies have exploited different plants for the production of flavonoids. To overcome this situation, various biotechnological strategies have been incorporated to improve the production of different types of flavonoids. In this review, we have highlighted the various types of flavonoids, their biosynthesis, properties, and different strategies to enhance the production of flavonoids.

Human struggle against the deadly disease conditions is continued since ages. The contribution of science and technology in fighting against these diseases cannot be ignored exclusively due to the invention of novel procedure and products, extending their size ranges from micro to nano. Recently nanotechnology has been gaining more consideration for its ability to diagnose and treat different cancers. Different nanoparticles have been used to evade the issues related with conservative anticancer delivery systems, including their nonspecificity, adverse effects and burst release. These nanocarriers including, solid lipid nanoparticles (SLNs), liposomes, nano lipid carriers (NLCs), nano micelles, nanocomposites, polymeric and magnetic nanocarriers, have brought revolutions in antitumor drug delivery. Nanocarriers improved the therapeutic efficacy of anticancer drugs with better accumulation at the specific site with sustained release, improved bioavailability and apoptosis of the cancer cells while bypassing the normal cells. In this review, the cancer targeting techniques and surface modification on nanoparticles are discussed briefly with possible challenges and opportunities. It can be concluded that understanding the role of nanomedicine in tumor treatment is significant, and therefore, the modern progressions in this arena is essential to be considered for a prosperous today and an affluent future of tumor patients.

Cancer is one of the leading causes of morbidity and mortality around the globe and is likely to become the major cause of global death in the coming years. As per World Health Organization (WHO) report, every year there are over 10 and 9 million new cases and deaths from this disease. Chemotherapy, radiotherapy, and surgery are the three basic approaches to treating cancer. These approaches are aiming at eradicating all cancer cells with minimum off-target effects on other cell types. Most drugs have serious adverse effects due to the lack of target selectivity. On the other hand, resistance to already available drugs has emerged as a major obstacle in cancer chemotherapy, allowing cancer to proliferate irrespective of the chemotherapeutic agent. Consequently, it leads to multidrug resistance (MDR), a growing concern in the scientific community. To overcome this problem, in recent years, nanotechnology-based drug therapies have been explored and have shown great promise in overcoming resistance, with most nano-based drugs being explored at the clinical level. Through this review, we try to explain various mechanisms involved in multidrug resistance in cancer and the role nanotechnology has played in overcoming or reversing this resistance.

Blockchain technology allows for the decentralized creation of a propagated record of digital events, in which third parties do not control information and associated transactions. This methodology was initially developed for value transmission. Still, it now has a broad array of utilization in various industries, including health, banking, the internet of things, and several others. With its numerous added benefits, a blockchain-based learning management system is a commonly utilized methodology at academic institutes, and more specifically during and after the COVID-19 period. It also presents several potentials for decentralized, interoperable record management in the academic system in education. Integrity, authenticity, and peer-executed smart contracts (SC) are some of the qualities of a blockchain that could introduce a new degree of safety, trustworthiness, and openness to e-learning. This research proposes a unique encryption technique for implementing a blockchain system in an e-learning (EL) environment to promote transparency in assessment procedures. Our methodology may automate evaluations and provide credentials. We built it to be analytical and content-neutral in order to demonstrate the advantages of a blockchain back-end to end-users, including student and faculty members particularly during this COVID-19 era. This article explains the employment of blockchain and SC in e-learning. To improve the trust in the assessment, we propose a novel improved elliptic curve cryptography algorithm (IECCA) for data encryption and decryption. The performance of the suggested method is examined by comparing it with various existing algorithms of encryption. The evaluation of the behaviour of the presented method demonstrates that the technique shall enhance trust in online educational systems, assessment processes, educational history, and credentials.

Acute myeloid leukemia (AML) is characterized by disruption of intracellular signaling due to aberration of extracellular signaling pathways, namely PI3K/AKT cascade, by dysregulating erythropoiesis and myelopoiesis. Therefore, inhibition of PI3K/AKT, either individually, or by dual inhibitors, is shown to be effective in suppression of tumorigenesis. To increase the therapeutic viability and decrease adverse effects, including cytotoxicity due to off-target kinase inhibitions, customized targeted pharmacological agents are needed that would have greater treatment potential. In this work, using an interdisciplinary approach, we have identified dual inhibitors targeted to PI3K and AKT to significantly repress the cell proliferation in AML cancers. Diversity-based high-throughput virtual screening (D-HTVS) technique followed by conventional docking approach identified small molecules from ChemBridge library, having high binding affinity for PI3KCG subunit. Further computational screening of top identified PI3K-specific lead molecules predicts dual inhibitors with high binding affinity for AKT. To rule out the possibility for cross-reaction/off-target effects of identified small molecules, lead compounds having nil or negligible binding to PI3KCA- and PI3KCB subunits were chosen. Computational screening, enzyme inhibition and cell proliferation assays show compound C16, 5-{[(1,3-dioxo-1H-benzo[de]isoquinolin-2(3H)-yl)amino]methylene}-1-phenyl-2,4,6(1H,3H,5H)-pyrimidinetrione has better affinity for PI3KCG, delta, and AKT kinases compared to their respective known/established inhibitors, and has significant anti-cell proliferation activity in AML cells with a GI 50 values of 77.25 nM and 49.65 nM in THP-1 and HL-60 cells, respectively. This work proposes a novel dual inhibitor that selectively targets PI3K/AKT and suppresses cell proliferation in AML cells as a potential lead molecule for treating AML cancers.

The emergence of antibiotic-resistant Elizabethkingia strains poses a significant challenge in clinical settings. This systematic review and meta-analysis provide a comprehensive assessment of the prevalence of antibiotic resistance among Elizabethkingia isolates across different regions worldwide. A systematic literature search was conducted across PubMed, Embase, Web of Science, and Scopus from 1998 to January 9, 2024, using predefined search strategies. Eligible studies reporting antibiotic resistance in Elizabethkingia were included. A random-effects model was applied to estimate resistance proportions and assess heterogeneity. Additional analyses, including meta-regression, subgroup evaluations, and assessments of outliers and influential studies, were performed to explore resistance trends and evaluate publication bias. Study quality was assessed using the Joanna Briggs Institute Checklist, and all statistical analyses were conducted using R with the metafor package. A total of 1,016 articles were identified, of which 34 studies (47 reports) met the inclusion criteria. The pooled analysis indicated high resistance to ceftazidime (88.5% of isolates, 95% CI: 21.1%-99.5%) with no significant heterogeneity. Resistance to rifampin was 12.5% (95% CI: 5.9%-24.7%), showing substantial heterogeneity, while ciprofloxacin resistance was 27.9% (95% CI: 13.8%-48.4%) with considerable heterogeneity. Among specific antibiotics, cefotaxime resistance was 96.1% (220 isolates), meropenem resistance was 92.4% (353 isolates), and gentamicin resistance was 77.7% (356 isolates). Additionally, sulfamethoxazole resistance was 46.1% (176 out of 360 isolates, 95% CI: 23.5%-70.4%), displaying significant heterogeneity. This study highlights the widespread antibiotic resistance in Elizabethkingia, underscoring the urgent need for targeted treatment strategies and enhanced surveillance programs. The findings emphasize the importance of monitoring local resistance patterns to guide clinical decision-making. Future research should focus on elucidating resistance mechanisms and genetic diversity to develop practical therapeutic approaches and mitigate the global health impact of Elizabethkingia infections.

Minichromosome maintenance complex component 7 (MCM7) is involved in replicative licensing and the synthesis of DNA, and its overexpression is a fascinating biomarker for various cancer types. There is currently no effective agent that can prevent the development of cancer caused by the MCM7 protein. However, on the molecular level, inhibiting MCM7 lowers cancer-related cellular growth. With this purpose, this study screened 452 biogenic compounds extracted from the UEFS Natural Products dataset against MCM protein by using the in silico art of technique. The hit compounds UEFS99, UEFS137, and UEFS428 showed good binding with the MCM7 protein with binding energy values of −9.95, −8.92, and −8.71 kcal/mol, which was comparatively higher than that of the control compound ciprofloxacin (−6.50). The hit (UEFS99) with the minimum binding energy was picked for molecular dynamics (MD) simulation investigation, and it demonstrated stability at 30 ns. Computational prediction of physicochemical property evaluation revealed that these hits are non-toxic and have good drug-likeness features. It is suggested that hit compounds UEFS99, UEFS137, and UEFS428 pave the way for further bench work validation in novel inhibitor development against MCM7 to fight the cancers.

In recent years, medicinal plants have gained significant attention in modern medicine due to their accessibility, affordability, widespread acceptance, and safety, making herbal remedies highly valued globally. Consequently, ensuring medicinal plants’ quality, efficacy, and safety has become a critical concern for developed and developing nations. The emergence of multidrug-resistant microorganisms poses a serious global health threat, particularly in low-income regions, despite significant advancements in antimicrobial drugs and medical research over the past century. The rapid spread of these multidrug-resistant infections is primarily attributed to improper prescriptions, overuse, and unregulated access to antibiotics. Addressing these challenges, the standardization of plant-derived pharmaceuticals could pave the way for a transformative era in healthcare. Preserving and leveraging the historical knowledge of medicinal plants is essential before such valuable information is lost. Recently, there has been growing interest among natural and pharmaceutical scientists in exploring medicinal plants as potential sources of antimicrobial agents. This current review aims to identify the most common pathogens threatening human health, analyze the factors contributing to the rise of drug-resistant microorganisms, and evaluate the widespread use of medicinal plants across various countries as alternative antibiotics, highlighting their unique mechanisms of antimicrobial resistance.

B-cell lymphoma 2 (Bcl-2) is a crucial regulatory protein involved in the control of apoptosis. Its overexpression in cancer cells facilitates evasion of programmed cell death, contributing to their survival and resistance to chemotherapy. Consequently, Bcl-2 has emerged as a promising drug target in cancer therapy. There is still ongoing research to find potential drug molecules that target Bcl-2 with higher potency, selectivity, and safety profile. This study was carried out by conducting a virtual screening of phytoconstituents from the IMPPAT database that could potentially inhibit the aberrant activity of Bcl-2. We first excluded compounds that did not abide by the Lipinski rule of five based on their physicochemical properties. We also calculated binding affinities, applied PAINS filters, and performed ADMET and PASS analyses, as well as interaction analyses, to identify compounds that were predicted to be safe and effective. Finally, two compounds, Daturilinol and Withametelin B, were selected because of their high binding and selective binding to Bcl-2. We analyzed these compounds in terms of time evolution by employing molecular dynamics simulation (MDS), principal component analysis (PCA), free energy landscape (FEL), and MM/PBSA. Consequently, we suggest that Daturilinol and Withametelin B could be further investigated in vitro and in vivo for therapeutic development against cancer.

The biological processes involved in diseases like human immunodeficiency virus (HIV) and tuberculosis (TB) require extensive research, particularly when both diseases occur together. This piece of research delves to explore a new fractional-order mathematical model that examines the co-dynamics of HIV and TB, taking into account the treatment effects. Although no definitive vaccine or cure for HIV exists, antiretroviral therapy (ART) can slow disease spread and prevent subsequent complications. The basic properties of the fractional model in the Caputo sense, including existence, uniqueness, positivity, and boundedness, are proved using crucial mathematical tools. The disease-free and endemic equilibria are determined for the co-infection model, along with the basic reproduction numbers for TB and for HIV, using the next-generation matrix technique. A comprehensive analysis is conducted to determine the local and global stability of the disease-free equilibrium point by applying the Routh–Hurwitz criteria and constructing a Lyapunov function, respectively. The stability of the disease-free state is also verified graphically by considering different initial conditions and observing the convergence of the curves to the disease-free equilibrium point. Furthermore, the model is examined under different scenarios by varying the reproduction numbers, specifically when and , and when and . Using actual data from the USA from 1999 to 2022, crucial parameters are estimated. The final fitting of the model with real data demonstrates how effectively the model framework aligns with the data. Finally, computational simulations are performed for different cases to illustrate the behavior of the model solutions by varying the fractional order derivative, as well as examining the solution’s behavior with respect to the stability points.