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Nanotechnology, contrary to its name, has massively revolutionized industries around the world. This paper predominantly deals with data regarding the applications of nanotechnology in the modernization of several industries. A comprehensive research strategy is adopted to incorporate the latest data driven from major science platforms. Resultantly, a broad-spectrum overview is presented which comprises the diverse applications of nanotechnology in modern industries. This study reveals that nanotechnology is not limited to research labs or small-scale manufacturing units of nanomedicine, but instead has taken a major share in different industries. Companies around the world are now trying to make their innovations more efficient in terms of structuring, working, and designing outlook and productivity by taking advantage of nanotechnology. From small-scale manufacturing and processing units such as those in agriculture, food, and medicine industries to larger-scale production units such as those operating in industries of automobiles, civil engineering, and environmental management, nanotechnology has manifested the modernization of almost every industrial domain on a global scale. With pronounced cooperation among researchers, industrialists, scientists, technologists, environmentalists, and educationists, the more sustainable development of nano-based industries can be predicted in the future.

Knowing the beneficial aspects of nanomedicine, scientists are trying to harness the applications of nanotechnology in diagnosis, treatment, and prevention of diseases. There are also potential uses in designing medical tools and processes for the new generation of medical scientists. The main objective for conducting this research review is to gather the widespread aspects of nanomedicine under one heading and to highlight standard research practices in the medical field. Comprehensive research has been conducted to incorporate the latest data related to nanotechnology in medicine and therapeutics derived from acknowledged scientific platforms. Nanotechnology is used to conduct sensitive medical procedures. Nanotechnology is showing successful and beneficial uses in the fields of diagnostics, disease treatment, regenerative medicine, gene therapy, dentistry, oncology, aesthetics industry, drug delivery, and therapeutics. A thorough association of and cooperation between physicians, clinicians, researchers, and technologies will bring forward a future where there is a more calculated, outlined, and technically programed field of nanomedicine. Advances are being made to overcome challenges associated with the application of nanotechnology in the medical field due to the pathophysiological basis of diseases. This review highlights the multipronged aspects of nanomedicine and how nanotechnology is proving beneficial for the health industry. There is a need to minimize the health, environmental, and ethical concerns linked to nanotechnology.

Dentistry is a branch of healthcare where nanobiotechnology is reverberating in multiple ways to produce beneficial outcomes. The purpose of this review is to bring into the awareness of the readers the various practical dimensions of the nano-dental complex (nanodentistry) in healthcare and how novelties linked with the field are revolutionizing dentistry. A methodological approach was adopted to collect the latest data on nanotechnology and dentistry from sources, including PubMed, Google Scholar, Scopus, and official websites like the WHO. Nanodentistry is an emerging field in dentistry that involves the use of nanomaterials, nanorobots, and nanotechnology to diagnose, treat, and prevent dental diseases. The results summarize the descriptive analyses of the uses of nanodentistry within orthodontics, preventive dentistry, prosthodontics, restorative dentistry, periodontics, dental surgeries, dental restoration technologies, and other areas of dentistry. The future directions of nano-industries and nano-healthcare have been included to link them with the oral healthcare sector, treatment plans, and improved medical services which could be explored in the future for advanced healthcare regulation. The major limitations to the use of dental nanoproducts are their cost-effectiveness and accessibility, especially in financially constrained countries. These data will help the readers to experience a detailed analysis and comprehensive covering of the diverse achievements of nanodentistry with past analyses, present scenarios, and future implications.

The interaction between SARS-CoV-2 Spike protein and angiotensin-converting enzyme 2 (ACE2) is essential to viral attachment and the subsequent fusion process. Interfering with this event represents an attractive avenue for the development of therapeutics and vaccine development. Here, a hybrid approach of ligand- and structure-based virtual screening techniques were employed to disclose similar analogues of a reported antiviral phytochemical, glycyrrhizin, targeting the blockade of ACE2 interaction with the SARS-CoV-2 Spike. A ligand-based similarity search using a stringent cut-off revealed 40 FDA-approved compounds in DrugBank. These filtered hits were screened against ACE2 using a blind docking approach to determine the natural binding tendency of the compounds with ACE2. Three compounds, deslanoside, digitoxin, and digoxin, were reported to show strong binding with ACE2. These compounds bind at the H1-H2 binding pocket, in a manner similar to that of glycyrrhizin which was used as a control. To achieve consistency in the docking results, docking calculations were performed via two sets of docking software that predicted binding energy as ACE2-Deslanoside (AutoDock, −10.3 kcal/mol and DockThor, −9.53 kcal/mol), ACE2-Digitoxin (AutoDock, −10.6 kcal/mol and DockThor, −8.84 kcal/mol), and ACE2-Digoxin (AutoDock, −10.6 kcal/mol and DockThor, −8.81 kcal/mol). The docking results were validated by running molecular simulations in aqueous solution that demonstrated the stability of ACE2 with no major conformational changes in the ligand original binding mode (~ 2 Å average RMSD). Binding interactions remained quite stable with an increased potential for getting stronger as the simulation proceeded. MMGB/PBSA binding free energies were also estimated and these supported the high stability of the complexes compared to the control (~ −50 kcal/mol net MMGB/PBSA binding energy versus ~ −30 kcal/mol). Collectively, the data demonstrated that the compounds shortlisted in this study might be subjected to experimental evaluation to uncover their real blockade capacity of SARS-CoV-2 host ACE2 receptor. Graphical abstract

Background The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students’ perceptions regarding the credibility and effectiveness of AI as a learning tool and to explore the dynamics of integrating AI in medical education. Methodology A cross-sectional study was carried out across medical colleges in Pakistan. A 26-question survey was developed using Google Forms from previously validated studies. The survey assessed demographics of participants, basic understanding of AI, AI as a learning tool in medical education and socio-ethical impacts of the use of AI. The data was analyzed using SPSS (v 26.0) to derive descriptive and inferential statistics. Result A total of 702 medical students aged 18 to 26 years (mean age 20.50 ± 1.6 years) participated in the study. The findings revealed a generally favorable attitude towards AI among medical students (80.3%), with the majority considering it an effective (60.8%) and credible (58.4%) learning tool in medical education. Students agreed that AI learning optimized their study time (60.3%) and provided up-to-date medical information (63.1%). Notably, 65.7% of students found AI more efficient in helping them grasp medical concepts compared to traditional tools like books and lectures, while 66.8% reported receiving more accurate answers to their medical inquiries through AI. The study highlighted that medical students view traditional tools as becoming increasingly outdated (59%), emphasizing the importance of integrating AI into medical education and creating dedicated AI tools (80%) for the medical education. Conclusion This study demonstrated that AI is an effective and credible tool in medical education, offering personalized learning experiences and improved educational outcomes. AI tools are helping students learn medical concepts by cutting down on study-time, providing accurate answers, and ultimately improving study outcomes. We recommend developing dedicated AI tools for medical education and their formal integration into medical curricula, along with appropriate regulatory oversight to ensure AI can enhance human abilities rather than acting as a replacement for humans.

Mycobacteroides abscessus (Previously Mycobacterium abscessus ) is an emerging microorganism of the newly defined genera Mycobacteroides that causes mainly skin and tissue diseases in humans. The recent availability of total 34 fully sequenced genomes of different strains belonging to this species has provided an opportunity to utilize this genomics data to gain novel insights and guide the development of specific antimicrobial therapies. In the present study, we collected collectively 34 complete genome sequences of M. abscessus from the NCBI GenBank database. Pangenome analysis was conducted on these genomes to understand the genetic diversity and to obtain proteins associated with its core genome. These core proteins were then subjected to various subtractive filters to identify potential antigenic targets that were subjected to multi-epitope vaccine design. Our analysis projected the open pangenome of M. abscessus containing 3443 core genes. After applying various stepwise filtration steps on the core proteins, a total of four potential antigenic targets were identified. Utilizing their constituent CD4 and CD8 T-cell epitopes, a multi-epitope based subunit vaccine was computationally designed. Sequence-based analysis as well as structural characterization revealed the immunological effectiveness of this designed vaccine. Further molecular docking, molecular dynamics simulation and binding free energy estimation with Toll-like receptor 2 indicated strong structural associations of the vaccine with the immune receptor. The promising results are encouraging and need to be validated by additional wet laboratory studies for confirmation.

According to the study findings, LDH levels play a crucial role in determining the severity and outlook of COVID-19 pneumonia. [...]fever and diarrhea were identified as risk factors for severe coronavirus disease, and high serum lactic dehydrogenase and neutrophil counts were associated with severe COVID-19 pneumonia. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Human papillomaviruses (HPVs) are high-risk causative factors for HPV infection. This infection does not come alone; it is often seen with co-infection with other viruses and acts as a causative agent for several malignancies. The major purpose of this comprehensive study was to highlight some recent advances in biotechnology associated with HPV infection, including understanding its host interactions and cancerous progression. A systematic research strategy was used to gather data from recent, and the most advanced published electronic sources. The compiled data explain the recent understanding of biology, host–viral interaction cycles, co-infection with other viral diseases, and cellular transformation toward malignancies associated with HPV. In recent years, some vaccination protocols have been introduced in the form of live attenuated, subunit, and DNA-based vaccines. Moreover, some strategies of nanotechnology are being employed to synthesize drugs and vaccines with a whole new approach of plant-based products. The data are immense for the proposed research question, yet the need is to implement modern follow-up screening and modern therapeutics at the clinical level and to conduct wide-scale public awareness to lessen the HPV-related disease burden.

SARS-CoV-2 (severe acute respiratory syndrome causing coronavirus 2) caused an epidemic that swept the globe and resulted in large number of casualties. It is still sporadically causing cases and has a long-term impact on the health of once infected individuals. Molnupiravir binds RNA dependent RNA polymerase (RdRp) of SARS-CoV-2 as well as spike protein. In this study, we assessed the mutated spike protein of BA.5 variant and BQ.1.1 subvariant of COVID-19 and tested their binding with it. Multiple sequence and structural alignment of homologous structures revealed highly conserved amino acid residues at the active site of the domain. The molecular docking of Molnupiravir with the active site of the domain, comprised conserved motifs (motif A-G), and exhibited considerable binding affinity against variant and subvariant protein targets. Molnupiravir exhibited stability in its interactions with the Omicron and BQ.1.1 spike proteins, preserving constant engagement within the active site. The protein and Ligand reached An equilibrium with An RMSD of 10.46 Å after 100 nanoseconds, whereas the Ligand measured 8.0 Å. Fluctuations were noted between 40 And 75 nanoseconds, stabilizing from 80 to 100 ns. In simulations including the BQ.1.1 subvariant, the RMSD values demonstrated considerable stability, exhibiting Little variations. The ligand demonstrated flexibility, altering its binding orientation over time, resulting in An average RMSD of 18.72 Å. Herein, investigation of molecular dynamics trajectories elucidated the conformational stability of Molnupiravir, emphasizing its interactions with active residues and the hydrogen bond acceptor and donor environments. The results highlighted the crucial function of protein loops in offering flexibility and enabling ligand binding within the active site. It is concluded that Molnupiravir has the potential to function as an inhibitor of both omicron and its subvariant BQ.1.1.

Insulin-producing β-cells are destroyed in type 1 diabetes mellitus (T1DM), a chronic autoimmune disease that results in complete insulin insufficiency and metabolic dysfunction. According to a survival study that used p values, some hub genes are important for predicting and diagnosing illness. Scientists have inferred medicines to identify possible therapies that interact with the identified hub genes. The GSE10586 gene expression dataset from the Gene Expression Omnibus (GEO) was used for this investigation, which included 27 samples from 15 healthy controls and 12 diabetic patients. Normalization methods such as variance stabilization normalization (VSN) were used as part of the data pretreatment. A protein‒protein interaction (PPI) network was constructed, principal component analysis (PCA) was performed, heatmaps were created, and the Limma algorithm was used to analyze differential gene expression. Using DAVID v6.8 and KEGG pathway annotations, the functional enrichment of differentially expressed genes (DEGs) was evaluated. Furthermore, a computational study revealed CERS6 to be one of the potential hub genes. Four drugs, methotrexate, eliglustat, myriocin and statin, were the focus of further studies on the basis of predictions made via ChemSpider and PubChem database analysis. To determine the optimal binding positions of these drugs with CERS6, we used molecular docking techniques. The binding affinity of methotrexate was 8.48 kcal/mol, that of myriocin was 7.85 kcal/mol, that of eliglustat was − 6.62 kcal/mol, and that of serine was − 4.90 kcal/mol against the binding pocket’s active residues. To determine how consistently each drug interacted with the CERS6 protein over time, molecular dynamics (MD) simulations were run. Throughout the simulation intervals, both medications were confirmed to be stable, with minor alterations in the CERS6 protein loop region. Therefore, the investigation of structure-based drug design has potential for identifying specific therapeutic targets. Ten hub genes were identified via network analysis of differentially expressed genes. These hub genes could serve as novel targets for T1DM detection, prognosis, and targeting. CERS6 exhibited the highest degree of interaction. Methotrexate, eliglustat, myriocin and statins were identified as potential drugs for CERS6. Overall, these findings provide valuable insights that could pave the way for new experimental strategies in T1DM therapy.