Cancer is one of the leading causes of death worldwide. Early detection of cancer can play a decisive role in cancer treatment and improving survival rates. Conventional cancer detection methods, such as biopsy, imaging and blood tests are generally invasive and time-consuming, and their results have accuracy issues. Biosensors with artificial intelligence integration play a significant and evolving role in cancer diagnostics, offering non-invasive, rapid, and highly sensitive methods for early detection, monitoring, and treatment of cancer. Biosensors detect specific biomarkers associated with cancerous cells or tumours, such as nucleic acid (DNA, RNA), small molecules, peptides, proteins and metabolites. In recent years, many predictive artificial intelligence models and bioinformatics tools have been developed to integrate biosensors, emerging as powerful tools for cancer diagnostics. This review explores the role of biosensors in cancer detection, the development and application of predictive AI models and bioinformatics tools in cancer detection through biosensor technologies, and the challenges associated with their clinical adoption.

Bacteriophages are viruses that infect bacteria, which are essential for controlling bacterial diversity. Among the novel aspects, phage display-based strategies are used for epitope mapping and the development of immunotherapy. A recent classification system has been developed based on the recent sequencing methods and bioinformatic tools. The unique specificity of phages is of increasing use in biocontrol, where bacteriophages are applied to target and reduce harmful bacterial populations in agriculture, food preservation and safety, offering a sustainable alternative to chemical exposure and a plausible solution to excessive misuse of antibiotics. Phage therapy has emerged as a complement to antibiotics for difficult-to-treat infectious diseases such as multi-drug resistant bacteria where other alternatives are lacking. The ability of bacteriophages to specifically target pathogenic bacteria while sparing the normal flora makes them attractive treatment options. Among the challenges are the slow uptake of phage therapy in the clinical setting, a lack of standardisation and regulatory issues. Nevertheless, phage-based strategies are likely to become a future cornerstone for biocontrol and treatment of infectious diseases.

Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge in modern medicine, characterized by its insidious progression, early systemic metastasis, and alarmingly low survival rates. Given its clinical challenges, improving detection strategies for PDAC remains a critical area of research. This study has used advanced computational approaches to predict pancreatic adenocarcinoma-associated target genes using transcriptomics datasets. Predictive machine learning models were trained using the identified gene signatures, highlighting their potential relevance for future research into diagnostic strategies for PDAC. A total of thirteen differentially expressed genes (DEGs) associated with PDAC were identified, of which twelve were upregulated (CEACAM5, CEACAM6, CTSE, GALNT5, LAMB3, LAMC2, SLC6A14, TMPRSS4, TSPAN1, ITGA2, ITGB6, and POSTN) and one was down regulated (IAPP). These DEGs are all linked to cancer-associated pathways and potentially play a role in the growth and development of cancer. Furthermore, virtual screening evaluated the upregulated SLC6A14 gene-encoded protein for therapeutic repurposing, revealing promising candidates for PDAC treatment. This study offers exploratory insights into gene expression patterns and molecular biomarkers that may inform future research to improve PDAC prognosis and therapeutic development and provide the repurposed drug candidate for further exploration.

Visceral leishmaniasis is a neglected tropical disease. Drug resistance and toxicity are the critical issues with the currently available antileishmanial drugs. Therefore, research efforts are underway to identify and validate new drug targets specific to Leishmania parasite. The enzyme homoserine dehydrogenase (HSD) functions in the third step of aspartate pathway. The present study focuses on the biophysical and biochemical characterization of HSD enzyme from Leishmania donovani (LdHSD) which is unique to the parasite with no homologous enzyme in the host. LdHSD gene was cloned in pET28c(+) vector and transformed in E. coli BL21 (DE3) strain. LdHSD recombinant enzyme of molecular weight 46.6 kDa with 6X-His tag at the C-terminal end was expressed, purified by nickel affinity chromatography and confirmed by western blot analysis using anti-His antibody. Effect of pH, temperature, salts, metal ions and amino acids on the recombinant enzyme were evaluated. Kinetic parameters of LdHSD were evaluated for substrates L-homoserine and NADP+. Biophysical analysis revealed that the enzyme is rich in β-sheets. Thermal denaturation study revealed that the protein is stable up to 45 °C. Furthermore, comprehensive comparative sequence analysis and structural modeling revealed the structural and functionally important residues, which are involved in the catalytic mechanisms. The putative binding mode of the natural substrate L-homoserine into the active site of LdHSD was also elucidated. These findings provide a foundation for the development of selective, target-based inhibitors against the HSD enzyme of the parasite.

The PWWP domain is a conserved motif unique to eukaryotes, playing a critical role in various cellular processes. Proteins containing the PWWP domain are typically found in chromatin, where they bind to DNA and histones in nucleosomes, facilitating chromatin-associated functions. Among these proteins, PWWP-domain containing proteins 2A and 2B (PWWP2A and PWWP2B), identified during the H2A interactome analysis, are DNA methyltransferase-related proteins, that are structurally disordered, except for their PWWP domain. While their precise functions remain to be fully elucidated, PWWP2A and PWWP2B have been implicated in essential processes such as embryonic development, mitotic regulation, adipose thermogenesis, transcriptional control, and DNA damage response. Their involvement in disease pathology is an emerging area of research, with PWWP2B downregulation linked to recurrent gastric cancer, promoting cell proliferation and migration. Literature reveals that the circular RNA, cPWWP2A sequesters miR-203, miR-223, and miR-27, to modulate TGF-β signalling by inhibiting key regulators like SMAD3 and SP3. Additionally, PWWP2A/B proteins may interact with P4HA3, a regulator of the TGF-β/SMAD signalling pathway that influences tumour invasiveness, though the precise nature of this interaction is not yet fully understood. The PWWP2-miRNA-TGF-β axis, particularly the PWWP2-P4HA3 association, provides valuable insights into therapeutic strategies, especially under adverse conditions where this pathway is differentially regulated. Overall, given their essential roles in fundamental cellular processes and their involvement in disease mechanisms, PWWP2A and PWWP2B proteins could be ideal targets for therapeutic intervention. Thus, these proteins occupy a prominent position in the human proteome and epigenetic landscape.

The authors regret an unintentional mistake in the single-letter code for Tryptophan in the legend of Fig. 5 and in Page 5 where the figure is cited. The authors would like to apologise for any inconvenience caused. The single-letter code for Tryptophan is mistakenly published as “Y”, instead of “W”. The corrected legend for Fig. 5 is provided below: Fig. 5. A) Different homologs of the PWWP domain superimposed on each other, showing histone methyl-lysine-binding aromatic cage. Dark blue and red represents the BRPF1:H3K36me3 peptide complex (PDB Id: 2X4W), light pink corresponds to the modelled PWWP domain structure of PWWP2A, and cyan denotes the PWWP domain structure of PWWP2B (PDB Id: 4LD6). In the BRPF1:H3K36me3 peptide complex, the aromatic cage residues Y1096, Y1099, and F1147, corresponds to F666, W669, and W695 in PWWP2A, and F501, W504, and W530 in PWWP2B. B) Images visualizing the distribution of electrostatic charges on the surface of PWWP2A and PWWP2B proteins. In these visualizations, red indicates negatively charged regions and blue represents positively charged areas. These surface maps confirm the presence of positively charged surfaces in both proteins, supporting their potential interaction with DNA. The corrected text in page 5 is provided below: Similarly, studies on the PWWP domain of the BRPF1 protein identified aromatic residues Y1096, Y1099, and F1147 as key contributors to H3K36me3 binding. Structural superimposition revealed that these residues correspond to F666, W669, and W695 in PWWP2A, and F501, W504, and W530 in PWWP2B

Vibrio species pose significant threats worldwide, causing mortalities in aquaculture and infections in humans. Global warming and the emergence of worldwide strains of Vibrio diseases are increasing day by day. Control of Vibrio species requires effective monitoring, diagnosis, and treatment strategies at the global scale. Despite current efforts based on chemical, biological, and mechanical means, Vibrio control management faces limitations due to complicated implementation processes. This review explores the intricacies and challenges of Vibrio-related diseases, including accurate and cost-effective diagnosis and effective control. The global burden due to emerging Vibrio species further complicates management strategies. We propose an innovative integrated technology model that harnesses cutting-edge technologies to address these obstacles. The proposed model incorporates advanced tools, such as biosensing technologies, the Internet of Things (IoT), remote sensing devices, cloud computing, and machine learning. This model offers invaluable insights and supports better decision-making by integrating real-time ecological data and biological phenotype signatures. A major advantage of our approach lies in leveraging cloud-based analytics programs, efficiently extracting meaningful information from vast and complex datasets. Collaborating with data and clinical professionals ensures logical and customized solutions tailored to each unique situation. Aquaculture biotechnology that prioritizes sustainability may have a large impact on human health and the seafood industry. Our review underscores the importance of adopting this model, revolutionizing the prognosis and management of Vibrio-related infections, even under complex circumstances. Furthermore, this model has promising implications for aquaculture and public health, addressing the United Nations Sustainable Development Goals and their development agenda.

Introduction. Sporotrichosis is a subcutaneous infection caused by dimorphic Sporothrix species embedded in the clinical clade. Fungi have virulence factors, such as biofilm and melanin production, which contribute to their survival and are related to the increase in the number of cases of therapeutic failure, making it necessary to search for new options.Gap statement. Proton pump inhibitors (PPIs) have already been shown to inhibit the growth and melanogenesis of other fungi.Aim. Therefore, this study aimed to evaluate the effect of the PPIs omeprazole (OMP), rabeprazole (RBP), esomeprazole, pantoprazole and lansoprazole on the susceptibility and melanogenesis of Sporothrix species, and their interactions with itraconazole, terbinafine and amphotericin B.Methodology. The antifungal activity of PPIs was evaluated using the microdilution method, and the combination of PPIs with itraconazole, terbinafine and amphotericin B was assessed using the checkerboard method. The assessment of melanogenesis inhibition was assessed using grey scale.Results. The OMP and RBP showed significant MIC results ranging from 32 to 256 µg ml-1 and 32 to 128 µg ml-1, respectively. Biofilms were sensitive, with a significant reduction (P<0.05) in metabolic activity of 52% for OMP and 50% for RBP at a concentration of 512 µg ml-1 and of biomass by 53% for OMP and 51% for RBP at concentrations of 512 µg ml-1. As for the inhibition of melanogenesis, only OMP showed inhibition, with a 54% reduction.Conclusion. It concludes that the PPIs OMP and RBP have antifungal activity in vitro against planktonic cells and biofilms of Sporothrix species and that, in addition, OMP can inhibit the melanization process in Sporothrix species.

Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine development in light of the recurrent pandemics and epidemics. Also, identifying vaccines against certain viruses is challenging due to various factors, notably the inability to culture certain viruses in cell cultures and the wide-ranging diversity of MHC profiles in humans. Fortunately, reverse vaccinology (RV) efficiently overcomes these limitations and has simplified the identification of epitopes from antigenic proteins across the entire proteome, streamlining the vaccine development process. Furthermore, it enables the creation of multiepitope vaccines that can effectively account for the variations in MHC profiles within the human population. The RV approach offers numerous advantages in developing precise and effective vaccines against viral pathogens, including extensive proteome coverage, accurate epitope identification, crossprotection capabilities, and MHC compatibility. With the introduction of RV, there is a growing emphasis among researchers on creating multiepitope-based vaccines aiming to stimulate the host's immune responses against multiple serotypes, as opposed to single-component monovalent alternatives. Regardless of how promising the RV-based vaccine candidates may appear, they must undergo experimental validation to probe their protection efficacy for real-world applications. The time, effort, and resources allocated to the laborious epitope identification process can now be redirected toward validating vaccine candidates identified through the RV approach. However, to overcome failures in the RV-based approach, efforts must be made to incorporate immunological principles and consider targeting the epitope regions involved in disease pathogenesis, immune responses, and neutralizing antibody maturation. Integrating multi-omics and incorporating artificial intelligence and machine learning-based tools and techniques in RV would increase the chances of developing an effective vaccine. This review thoroughly explains the RV approach, ideal RV-based vaccine construct components, RV-based vaccines designed to combat viral pathogens, its challenges, and future perspectives.

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme in the biosynthesis of essential amino acids in microorganisms and some plants. Inhibition of ASADHs can be a potential drug target for developing novel antimicrobial and herbicidal compounds. This review covers up-to-date information about sequence diversity, ligand/inhibitor-bound 3D structures, potential inhibitors, and key pharmacophoric features of ASADH useful in designing novel and target-specific inhibitors of ASADH. Most reported ASADH inhibitors have two highly electronegative functional groups that interact with two key arginyl residues present in the active site of ASADHs. The structural information, active site binding modes, and key interactions between the enzyme and inhibitors serve as the basis for designing new and potent inhibitors against the ASADH family.