Carbon nanodots (CNDs) have garnered significant attention as viable drug delivery vehicles in recent years, especially in the field of phytomedicine. Although there is much promise for therapeutic applications with phytomedicine, its effectiveness is frequently restricted by its low solubility, stability, and bioavailability. This paper offers a thorough synopsis of the developing field of phytomedicine drug delivery based on CND. It explores CND synthesis processes, surface functionalization strategies, and structural and optical characteristics. Additionally, the advantages and difficulties of phytomedicine are examined, with a focus on the contribution of drug delivery methods to the increased effectiveness of phytomedicine. The applications of CNDs in drug delivery are also included in the review, along with the mechanisms that underlie their improved drug delivery capabilities. Additionally, it looks at controlled release methods, stability augmentation, and phytomedicine loading tactics onto CNDs. The potential of polymeric carbon nanodots in drug delivery is also covered, along with difficulties and prospective directions going forward, such as resolving toxicity and biocompatibility issues. In summary, the present review highlights the encouraging contribution of CNDs to the field of drug delivery, specifically in enhancing the potential of phytomedicine for therapeutic purposes.

Molecularly imprinted polymers (MIPs) were synthesized and applied for the selective extraction of oblongifolin C (OC) from fruit extracts of Garcinia yunnanensis Hu. A series of experiments and computational approaches were employed to improve the efficiency of screening for optimal MIP systems in the study. The molar ratio (1:4) was chosen at last based on the comparison of the binding energy of the complexes between the template (OC) and functional monomers using density functional theory (DFT) at the RI-PBE-D3-gCP/def2-TZVP level of theory. The binding characterization and the molecular recognition mechanism of MIPs were further explained using the molecular modeling method and NMR and IR spectra data. The reusability of this approach was demonstrated in over 20 batch rebinding experiments. 140.5 mg of OC (>95% purity) was obtained from the 5 g extracts with 2 g of MIPs with the best binding properties through gradient elution program from 35% to 70% methanol-water solution. At the same time, another structural analog, 46.5 mg of guttiferone K (GK) (>88% purity), was also obtained by the gradient elution procedure. Our results showed that the structural analogs could be separated from the crude extracts by the molecularly imprinted solid-phase extraction (MISPE) using a gradient elution procedure for the first time.

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. Emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

Epilepsy is one of the most prevalent and serious brain disorders, affecting 70 million people worldwide. Antiseizure medications (ASMs) though relieve symptoms and prevent the occurrence of future seizures in epileptic patients have limited effect on epileptogenesis. Addressing the multifaceted nature of epileptogenesis and its association with Nod-like receptor family pyrin domain containing 3 (NLRP3) inflammasome-mediated neuroinflammation requires a comprehensive understanding of the underlying mechanisms for development of targeted therapeutic strategies beyond conventional antiseizure treatments. Several types of NLRP3 inhibitors have been developed and their effect has been validated both in vitro and in vivo models of epileptogenesis. In this review, we discuss the advances in understanding the regulatory mechanisms of NLRP3 activation as well as progress made and challenges facing in the development of NLRP3 inhibitors for the treatment of epilepsy.

Tyrosine kinase fibroblast growth factor receptor (FGFR), which is aberrant in various cancer types, is a promising target for cancer therapy. Here we reported the design, synthesis, and biological evaluation of a new series of 6-(2,6-dichloro-3,5-dimethoxyphenyl)-4-substituted-1H-indazoles derivatives as potent FGFR inhibitors. Compound 10a was first identified as a potent FGFR1 inhibitor, with good enzymatic inhibition. Further structure-based optimization revealed that compound 13a is the most potent FGFR1 inhibitor in this series with the enzyme inhibitory activity about 30.2 nM of IC50 value.

In the dynamic landscape of drug discovery, Computer-rAided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADD's historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADD's predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. The paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery.

The integration of bioinformatics in drug discovery has revolutionized the field of pharmaceutical research. The use of computational tools and techniques has enabled researchers to analyze vast amounts of data, identify potential drug targets, and design new drugs with greater precision and efficiency. The integration of bioinformatics has also facilitated the development of personalized medicine, where drugs can be tailored to individual patients based on their genetic makeup. However, there are still challenges that need to be addressed, such as the need for more accurate predictive models and the ethical considerations surrounding the use of patient data. Overall, the integration of bioinformatics in drug discovery holds great promise for improving human health and advancing our understanding of disease mechanisms. In this mini-review, we discuss how Bioinformatics plays a crucial role in each step of drug discovery by providing tools and techniques to analyze large amounts of data generated from various sources, as well as the challenges and the opportunities offered by bioinformatics.

The dopamine D3 receptor is an important CNS target for the treatment of a variety of neurological diseases. Selective dopamine D3 receptor antagonists modulate the improvement of psychostimulant addiction and relapse. In this study, five and six featured pharmacophore models of D3R antagonists were generated and evaluated with the post-hoc score combining two survival scores of active and inactive. Among Top 10 models, APRRR215 and AHPRRR104 were chosen based on the coefficient of determination (APRRR215: R2training = 0.80; AHPRRR104: R2training = 0.82) and predictability (APRRR215: Q2test = 0.73, R2predictive = 0.82; AHPRRR104: Q2test = 0.86, R2predictive = 0.74) of their 3D-quantitative structure–activity relationship models. Pharmacophore-based virtual screening of a large compound library from eMolecules (> 3 million compounds) using two optimal models expedited the search process 100-fold speed increase compared to the docking-based screening (HTVS scoring function in Glide) and identified a series of hit compounds having promising novel scaffolds. After the screening, docking scores, as an adjuvant predictor, were added to two fitness scores (from the pharmacophore models) and predicted Ki (from PLSs of the QSAR models) to improve accuracy. Final selection of the most promising hit compounds were also evaluated for CNS-like properties as well as expected D3R antagonism.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by >6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

Lead optimization in drug discovery is a crucial phase where initial hits are refined into compounds with improved pharmacological properties. While traditional methods rely on manual experimentation and modifications, AI-driven techniques have revolutionized this process by leveraging big data and predictive modeling. This review explores how AI-driven approaches accelerate lead optimization, showcasing examples like deep neural networks and reinforcement learning. Integration of multi-omic data and experimental validation further enhances AI-driven strategies. The future lies in refining these AI methods, democratizing tools, and interdisciplinary collaboration to streamline drug discovery and address medical needs efficiently.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

Background. Transferrin receptor 1 (TfR1), glucose transporter 1 (GLUT1), and CD98hc are candidates for targeted therapy at the blood-brain barrier (BBB). Our objective was to challenge the expression of TfR1, GLUT1, and CD98hc in brain capillaries by the histone deacetylase inhibitor (HDACi) valproic acid (VPA). Methods. Primary mouse brain capillary endothelial cells (BCECs) and brain capillaries isolated from mice injected intraperitoneally with VPA were examined using RT-qPCR and ELISA. Targeting to the BBB was performed by injecting monoclonal anti-TfR1 (Ri7217)-conjugated gold nanoparticles measured using ICP-MS. Results. In BCECs co-cultured with glial cells, Tfrc mRNA expression was significantly higher after 6 h VPA returning to baseline after 24 h. In vivo Glut1 mRNA expression was significantly higher in males, but not females', receiving VPA, whereas Cd98hc mRNA expression was unaffected by VPA. TfR1 increased significantly in vivo after VPA, whereas GLUT1 and CD98hc were unchanged. Uptake of anti-TfR1-conjugated nanoparticles was unaltered by VPA in spite upregulated TfR expression. Conclusions. VPA upregulates TfR1 in brain endothelium in vivo and in vitro. VPA does not increase GLUT1 and CD98hc proteins. The increase in TfR1 does not result in higher anti-TfR1 antibody targetability, suggesting targeting sufficiently occurs with available transferrin receptors without further contribution from accessory VPA-induced TfR1.

Hematological malignancies refer to a heterogeneous group of neoplastic conditions of lymphoid and hematopoietic tissues classified in leukemias, Hodgkin and non-Hodgkin lymphomas and multiple myeloma, according to their presumed cell of origin, genetic abnormalities, and clinical features. Metabolic adaptation and immune escape, which influence various cellular functions including proliferation and survival of hematological malignant tumor cells, are major aspects of these malignancies that lead to therapeutic drug resistance. Targeting specific metabolic pathways is emerging as novel therapeutic strategy in hematopoietic neoplasms, particularly in acute myeloid leukemia and multiple myeloma. In this context, CD147, also known as Extracellular Matrix Metalloproteinase Inducer (EMMPRIN) or Basigin, is one target-candidate involved in reprogramming metabolism in different cancer cells, including hematological malignant tumor cells. CD147 overexpression significantly contributes to the metabolic transformation of these cancer cells, by mediating signaling pathway, growth, metastasis and metabolic reprogramming, through its interaction, direct or not, with various membrane proteins related to metabolic, regulation including monocarboxylated transporters, integrins, P-glycoprotein and Glucose Transporter 1. This review explores the metabolic functions of CD147 and its impact on the tumor microenvironment, influencing the progression and neoplastic transformation in leukemias, myeloma and lymphomas. Furthermore, we highlight new opportunities for the development of targeted therapies against CD147, potentially improving the treatment of hematologic malignancies.

Artificial intelligence AI or machine learning has proven to be a potential activity in the health and biomedical sciences. Previous research it has found that AI can learn new data and transform it into the useful knowledge. In the field of pharmacology, the aim is to design more efficient and novel vaccines using this method which are also cost effective. The underlying fact is to predict the molecular mechanism and structure for increased likelihood of developing new drugs. Clinical, electronic and high resolution imaging datasets can be used as inputs to aid the drug development niche. Moreover, the use of comprehensive target activity has been performed for repurposing a drug molecule by extending target profiles of drugs which also include off targets with therapeutic potential providing a new indication.

Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis (TB), a disease that alt-hough preventable and curable, remains a global epidemic due to the emergence of resistance and a latent form responsible for a long period of treatment. Drug discovery in TB is a challenging task due to the heterogeneity of the disease, the emergence of resistance and an uncomplete knowledge of the pathophysiology of the disease. The limited permeability of the cell wall and the presence of multiple efflux pumps remain a major barrier to achieve effective intracellular drug accumulation. While the complete genome sequence of Mtb has been determined and several potential protein targets have been validated, the lack of adequate models for in vitro and in vivo studies is a limit-ing factor in TB drug discovery programs. In current therapeutic regimens, less than 0.5% of bac-terial proteins are targeted being the biosynthesis of the cell wall and the energetic metabolism two of the most important processes exploited for TB chemotherapeutics. This review provides an overview on the current challenges in TB drug discovery and emerging Mtb druggable proteins, and how chemical probes for protein profiling enabled the identification of new targets and bi-omarkers, paving the way to disruptive therapeutic regimens and diagnostic tools.

Mosquitoes conveying Plasmodium store parasites into the skin of the mammalian host. Parasites make a trip through the circulation system to the liver, where they cross a few hepatocytes prior to building up a disease. Inside the last hepatocyte the parasite goes through morphogenesis and afterward abiogenetically partitions to become more than 20,000 blood-infective parasites, called merozoites. On account of P. vivax, P. ovale, and P. cynomolgi, the parasites can stay lethargic in the liver in structures called hypnozoites. The merozoites are delivered once again into the circulation system, where they start the repetitive blood stage. Inside erythrocytes, a little division of parasites separate into male or female gametocytes. These gametocytes are ingested by the mosquito during blood taking care of, where they will duplicate explicitly, in the long run prompting the arrangement of sporozoites

Precision metagenomic approaches using Oxford Nanopore Technology (ONT) sequencing has been shown to allow recovery of complete genomes of Escherichia coli O157:H7 from overnight enrichments of agricultural waters. This study tests the applicability of a similar approach for Cronobacter genome recovery from powdered infant formula (PIF) overnight enrichments, where Cronobacter typically dominates the overall microbiome (>90%). In this study, we aimed to test whether using ONT sequencing of overnight PIF enrichments could recover a completely closed Cronobacter genome for further genomic characterization. Ten PIF samples, each inoculated with different Cronobacter strains, covering Cronobacter sakazakii, C. muytjensii, C. dublinensis, C. turicensis, and C. universalis, were processed according to the Bacteriological Analytical Manual (BAM) protocol. qPCR was used for initial screening (detection and quantification) of the overnight enrichments and confirmed that the spiked PIF samples after the overnight enrichment have high levels of Cronobacter (107 to 109 CFU/mL). DNA from overnight PIF enrichments was extracted from the enrichment broth and sequenced using ONT. Results showed that ONT sequencing could accurately identify, characterize, and close the genomes of Cronobacter strains from overnight PIF enrichments in 3 days, much faster than the nearly two weeks required by the current BAM method. Complete genome recovery and species differentiation were achieved. This suggests that combining qPCR with ONT sequencing provides a rapid, cost-effective alternative for detecting and characterizing Cronobacter in PIF, enabling timely corrective actions during outbreaks.

Non-systemic oral drugs, which do not get absorbed through the gastrointestinal membrane, are an important group of compounds for targeting diseases residing within the gastrointestinal lumen. However, they require a set of design principles not sufficiently covered by traditional druglikeness metrics, such as Lipinski’s Rule of 5. These druglikeness metrics fail to accurately identify true negative outcomes; such is the requirement for novel cheminformatic based approaches for the discovery of non-systemic small molecules. One such example of these newer metrics is the fraction of SP3-hybridised carbon atoms (fSP3) which has shown promising application as an identifier of poor oral-bioavailability. Herein, we discuss the application of fSP3 in the drug discovery process in a number of case studies, including our own work discovering non-systemic fructose scavengers for the treatment of fructose malabsorption.

Ebola Virus Disease (EVD) is one of the most lethal transmissible infections characterized by a high fatality rate, and caused by members of the Filoviridae family. The recent large outbreak of EVD in West Africa (2013-2016), highlighted the worldwide danger of this disease and its impact on global public health and economy. The development of highly needed anti-Filoviridae antivirals has been so far hampered by the shortage of tools to study their life cycle in vitro, and therefore screen for potential active compounds outside a biosafety level-4 (BSL-4) containment. Importantly, the development of surrogate models to in vitro study of Filoviridae entry in a BSL-2 setting, such as viral pseudotypes and Ebola virus like particles, tremendously boosted both our knowledge on viral life cycle and the identification of promising anti-Filoviridae compounds interfering with viral entry. In this context, the combination of such surrogate systems with large-scale small molecule compounds and haploid genetic screenings, as well as rational drug design and drug repurposing approaches will prove priceless in our quest for the development of a treatment for EVD.

Fuzzy Rule Interpolation (FRI) offers an innovative methodology for inferring outcomes from data points that match no established rules in a sparse fuzzy rule base. Generally, a traditional fuzzy rule-based system suffers from the inability to perform inference while facing an unmatched observation, given a sparse fuzzy rule base that is derived from insufficient data or inadequate human experience and that fails to cover parts of a specific problem domain. Fortunately, starting with a sparse rule base, Fuzzy Rule Interpolation (FRI) can help to formulate interpolated rules specifically in instances where observations fail to activate any existing rule. An interpolated rule gives a result called consequent, which is related to the unmatched observation so that the inference system will not fail to generate an outcome corresponding to the observation as the output. Conventionally, these interpolated rules will be discarded after obtaining outcomes. However, valuable information may be potentially embedded within those discarded rules addressing the limitation regarding the coverage of the original sparse knowledge space. Moreover, without exploiting the potential value of the interpolated rules, the fuzzy inference system based on a sparse rule base will never improve its efficiency and robustness in the long run. Therefore, this underscores the necessity for Dynamic Fuzzy Rule Interpolation (D-FRI), which aims to collate interpolated rules that cover particular knowledge spaces absent in the sparse rule base. Intuitively, those frequently appeared interpolated rules are considered valuable because future observations are more likely to hit the respective problem areas. Promoting selected interpolated rules to the sparse rule base can enhance the overall coverage of the knowledge space and increase the inference efficiency over time. This paper introduces a framework for Dynamic Fuzzy Rule Interpolation that integrates the widely used Transformation-based Fuzzy Rule Interpolation (T-FRI) with an effective form of clustering of interpolated results. Experimental findings validate the effectiveness of this approach.

Iron (Fe) is co-factor for enzymes of the developing brain necessitating sufficient supply. We investigated the effects of administering ferric derisomaltose/Fe isomaltoside (FDI) subcutaneously to Fe deficient (ID) pregnant rats on cerebral and hepatic concentrations of essential metals and gene expression of ferroportin and hepcidin. Pregnant rats subjected to ID were injected with FDI on the day of mating (E0), 14 days into pregnancy (E14), or the day of birth (Postnatal (P0)). The efficacy was evaluated by determination of cerebral and hepatic Fe in pups on P0 and as adults on P70, and the concentration of copper (Cu) and zinc (Zn). Females fed an ID diet (5.2 mg/kg Fe) had offspring with significantly lower cerebral and hepatic Fe compared to female controls fed a standard diet (158 mg/kg Fe). Cerebral Cu increased irrespective of supplying a standard diet or administering FDI combined with the standard diet. Hepatic hepcidin was significantly lower following ID, whereas cerebral hepcidin was virtually undetectable in all experimental groups. In conclusion, administering FDI subcutaneously to ID pregnant rats on EO normalizes cerebral Fe in the fetus, but when applied at later gestational ages, additional Fe to the offspring is needed to normalize cerebral and hepatic Fe.

Inhibition of amyloid fibril formation could benefit patients with systemic amyloidosis. In this group of diseases, deposition of amyloid fibrils derived from normally soluble proteins leads to progressive tissue damage and organ failure. Although many small molecules have been proposed as inhibitors of amyloid formation, few have been successful in clinical trials. Amyloid formation is complex and several individual steps could be targeted by small molecules. However, the exact mechanism of action for a molecule is often not known, which impedes medicinal chemistry efforts to develop more potent molecules. Furthermore, commonly used assays are prone to artifacts that must be controlled for. Here, potential mechanisms by which small molecules could inhibit aggregation of immunoglobulin light chain dimers, the precursor proteins for AL amyloidosis are studied in assays that recapitulate different aspects of amyloidogenesis in vitro. One molecule reduced unfolding-coupled proteolysis of light chains, but no molecules inhibited aggregation of light chains or disrupted pre-formed amyloid fibrils. This work demonstrates the challenges associated with drug development for amyloidosis, but also highlights the potential to combine therapies that target different aspects of amyloidogenesis.

The morbidity and mortality caused by invasive fungal infections is increasing across the globe due to developments in transplant surgery, the use of immunosuppressive agents, and the emergence of drug-resistant fungal strains, which has led to a challenge in terms of treatment due to the limitations of three classes of drugs. Hence, it is imperative to establish effective strategies to identify and design new antifungal drugs. Drug repurposing is an effective way of expanding the application of existing drugs. In the last years, various existing drugs have been shown to be useful in the prevention and treatment of the invasive fungi. In this review, we summarize the currently used antifungal agents. In addition, the most up to date information on the effectiveness of existing drugs with antifungal activity is discussed. Moreover, the antifungal mechanisms of existing drugs are highlighted. These data will provide valuable knowledge to stimulate further investigation and clinical application in this field.

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. There is evidence that some ligands that bind to the GPCRs activate different downstream signaling pathways. G protein activation or -arrestin biased signaling involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. Molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions between receptors and ligands. Here, we highlight recent simulation studies and methods used to study biased G protein-coupled receptor signaling and their conformational dynamics. We also highlight applications of MD simulations to drug discovery.

Induced pluripotent stem cells (iPSC) are derived from reprogrammed adult somatic cells. These adult cells are manipulated in vitro to express genes and factors essential for acquiring and maintaining embryonic stem cell (ESC) properties. This technology is widely applied in many fields, and there has been much attention to developing iPSC-based disease models to validate drug discovery platforms and study pathophysiological molecular processes underlying disease onset. Especially in neurological diseases, there is a great need for iPSC-based technological research, as these cells can be obtained from each patient and carry the individual’s bulk of genetic mutations and properties. Moreover, iPSC can differentiate into multiple cell types. These are essential characteristics since the study of neurological diseases is affected by limited access to injured sites, in vitro models composed of various cell types, the complexity of reproducing the brain’s anatomy, ethical issues, and the fact that post-mortem cell culture is challenging. Neurodegenerative diseases enormously impact global health due to their high incidence, symptoms severity, and usually lack of effective therapies. Recently, analyses using disease-specific iPSC-based models confirmed their efficacy for testing multiple drugs. This review summarizes the advances in iPSC technology used in disease modeling and drug testing with a primary focus on neurodegenerative diseases, including Parkinson’s and Alzheimer’s diseases.

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry and science related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, rational design of combination therapies and the global response to the Covid19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human focused, systems-based approach to drug discovery and research.

Introduction: The combination of Virtual Screening (VS) techniques with in vivo screening in the zebrafish model is currently being used in tandem for drug development in a faster and more efficient way. Areas covered: We review the different virtual screening techniques, the use of zebrafish as a vertebrate model for drug discovery and the synergy that exists between them. Expert opinion: We highlight the advantages of combining virtual and zebrafish larvae screening for drug discovery. On the one hand, VS is a faster and cheaper tool for searching active compounds and possible candidates for therapy than in vivo screening when processing large compound libraries. On the other hand, zebrafish larvae form a vertebrate model which allows in vivo screening of large amounts of the compounds. Importantly physiology and chemical response are mostly conserved between zebrafish and mammals. The availability of the transgenic and mutant zebrafish lines allows an analysis of a specific phenotype upon treatment along with toxicity, off-target effect, side effects, and dosage. Advantages of VS, in vivo whole animal approach screening, and the screening combinations are also reviewed.

The efficacy and safety of organic UV-filters could benefit from their incorporation into lipid nanoparticles because of the ability of such carriers to reflect solar radiations, thus acting synergically as physical sunscreens. In this work, bemotrizinol (BMTZ), a broad-spectrum UV-filter, was loaded into nanostructured lipid carriers (NLC) whose lipid matrix contained different oils to assess the effects of the lipid core composition on the properties of the resulting NLC. Subsequently, the effects of incorporating different concentrations of optimized BMTZ-loaded NLC on the technological properties of O/W emulsions (pH, viscosity, spreadability, occlusion factor, in vitro BMTZ release and skin permeation, in vitro sun protection factor) were assessed. Optimized BMTZ-loaded NLC showed mean size=190.6±9.8 nm, PDI=0.153±0.013, ζ-potential=-10.6±1.7 mV, loading capacity=8% w/w. The incorporation of increasing concentrations of optimized BMTZ-loaded into emulsions provided slight increase of spreadability, lower viscosity and no change of pH, occlusion factor and BMTZ release compared to the control. No BMTZ skin permeation was observed from all formulations. About 20% increase of sun protection factor values was obtained for vehicles containing BMTZ-loaded NLC. Therefore, BMTZ-loaded NLC incorporation into emulsions could be a promising strategy to develop safer and more effective sunscreen formulations.

Since the first published genome sequence of Trypanosoma cruzi in 2005, there has been tremendous technological advance in genomics, reverse genetics, and assay development for this elusive pathogen. However, there is still an unmet need for new and better drugs to treat Chagas disease. Here we introduce a T. cruzi assay strain that is useful for drug research as well as basic studies in host-pathogen interaction. Trypanosoma cruzi STIB980 is a strain of discrete typing unit TcI that grows well in culture as axenic epimastigotes or intracellular amastigotes. We have evaluated the optimal parameters for genetic transfection and constructed derivatives of T. cruzi STIB980 that express reporter genes for fluorescence- or bioluminescence-based drug efficacy testing, as well as a Cas9-expressing line for CRISPR/Cas9-mediated gene editing. The genome of T. cruzi STIB980 was sequenced by combining short-read Illumina with long-read Oxford Nanopore technologies. The latter served for the primary assembly, the former to correct mistakes and fill the gaps. This resulted in a high-quality nuclear haplotype assembly of 28 Mb in 400 contigs, containing 10,043 open-reading frames with a median length of 1077 bp. We believe that T. cruzi STIB980 is a useful addition to the antichagasic toolbox, and propose that it can serve as a DTU TcI reference strain for drug efficacy testing.

African swine fever virus (ASFV), a highly contagious pathogen characterized by a complex structure and a variety of immunosuppression proteins, causes hemorrhagic, acute, and aggressive infectious disease that severely injure the pork product and industry. However, there is no effective vaccine or treatment. The main reasons are not only the complex mechanisms that lead to immunosuppression, but also the unknown functions of various proteins. This review summarizes the interaction between ASFV and host immune system, along with the involvement of virulence related genes and proteins, as well as the corresponding molecular mechanism of immunosuppression of ASFV, encompassing pathways such as cGAS-STING, NF-κB, JAK/STAT, apoptosis, and other modulation. The aim is to summarize the dynamic process during the ASFV infection and entry into host cell, provide a rational insight into development of vaccine and a better clear knowledge of how ASFV impacts host.

Background: Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy. We determined the validity of a rare-cell detection platform and demonstrated the usefulness of a certain rare cell subset as a novel approach to characterize the breast cancer system. Methods: Linearity of the Rarmax® platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 non-cancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts and inflammation-associated cells, was performed using a phenotype and morphology-based classification system. Results: The platform performed linearly over a range of 5-950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 50% and 85.7%, respectively and the specificity was 100% and 96.6%, respectively. Conclusion: The present study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential for sustenance of life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context, to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were tested and implemented for mostly cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more complex systems (for instance, multi-protein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate and the development of a new kind of kinetic analysis to study these systems is required. The current review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

The drug discovery process is a rigorous and time-consuming endeavor, typically requiring several years of extensive research and development. Although classical machine learning (ML) has proven successful in this field, its computational demands in terms of speed and resources are significant. In recent years, researchers have sought to explore the potential benefits of quantum computing (QC) in the context of ML, leading to the emergence of Quantum Machine Learning (QML) as a distinct research field. The objective of the current study is twofold: first, to present a review of the proposed QML algorithms for application in the drug discovery pipeline, and second, to compare QML algorithms with their classical and hybrid counterparts in terms of their efficiency. A query-based search of various databases took place, and five different categories of algorithms were identified in which QML was implemented. The majority of QML applications in drug discovery are primarily focused on the initial stages of the drug discovery pipeline, particularly with regard to the identification of novel drug-like molecules. Comparison results revealed that QML algorithms are strong rivals against the classical ones and a hybrid solution is the recommended approach at present.

KLEPTOSE® CRYSMEB is a methylated cyclodextrin derivative displaying less methylated group substitution than randomly methylated cyclodextrin. It has demonstrated an impact on atherosclerosis and neurological diseases. linked in part to cholesterol complexation and immune response, but the impact on inflammatory cascade pathways was not clear. Thus, the impact of KLEPTOSE® CRYSMEB on various pharmacological targets was assessed using human umbilical vein endothelial cells in physiological and inflammatory conditions, followed by screening against twelve human primary cell-based systems designed to model complex human tissue and disease biology of the vasculature, skin, lung, and inflammatory tissues using the BioMAP® Diversity PLUS® Panel. Finally, the anti-inflammatory mechanism was investigated on peripheral blood mononuclear cells to evaluate anti-inflammatory or pro-resolving properties. The results showed that KLEPTOSE® CRYSMEB can modulate the immune system in vitro and potentially manage vascular issues by stimulating the expression of molecules involved in the crosstalk between immune cells and other cell types. It showed anti-inflammatory effects driven by pro-inflammatory cytokine secretion inhibition and could have different impacts on different tissue types. Moreover, this cyclodextrin showed no clear impact on pro-resolving lipid mediators. Finally, it appeared that the mechanism of action of KLEPTOSE® CRYSMEB seems to not be shared by well-known anti-inflammatory molecules.

The field of biobanking human biospecimens has evolved significantly, transitioning from the basic, often poorly documented collection of clinical leftovers kept privately to well-organized and extensively documented collections overseen by both commercial and non-profit platforms. The increasing demand for high-quality and clinically annotated biospecimens is propelled by unprecedented levels of health research activities. Meeting this growing demand presents both new opportunities and challenges, particularly in developing strategies to establish international biospecimen sourcing (IBS) platforms. These platforms aim to facilitate collaboration among biobanks to address future biospecimen needs. In this manuscript, we delve into the advantages and challenges of establishing IBS platforms to provide high-quality and cost-effective biospecimens to drive drug discovery research, ultimately leading to improved health and quality of life for everyone.

New furan, thiophene and triazole oximes were synthesized through several-step reaction paths to investigate their potential for development of central nervous systems (CNS)-active and cholinesterase-targeted therapeutics in organophosphorus compound (OP) poisonings. Acute OP poisoning is still a challenge in treating patients despite the development of a large number of oxime compounds that should have the capacity to reactivate acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). The activity of these two enzymes, crucial for neurotransmission, are blocked by the OP, which has the consequence of disturbing normal cholinergic nerve signal transduction in the peripheral and CNS, leading to cholinergic crisis. Oximes in use have one or two pyridinium rings and cross the brain–blood barrier poorly due to the quaternary nitrogen. Following our recent study on 2-thienostilbene oximes, in this paper we described the synthesis of 63 heterostilbene derivatives out of which 26 oximes were tested as inhibitors and reactivators of AChE and BChE inhibited by OP nerve agents – sarin and cyclosarin. While the majority of oximes were potent inhibitors of both enzymes in micromolar range, we identified several oximes as BChE or AChE selective inhibitors with a potential for drug development. Moreover, even oximes were poor reactivators of AChE, four heterocyclic derivatives reactivated the cyclosarin-inhibited BChE up to 70%, and cis,trans-5 [2-((Z)-2-(5-((E)-(hydroxyimino)methyl)thiophen-2-yl)vinyl)benzonitrile] had comparable reactivation efficacy to the standard oxime HI-6. In silico analysis and molecular docking studies connected the kinetic data to the structural features of these oximes, and confirmed their productive interactions with the active site of the cyclosarin-inhibited BChE. Based on inhibition and reactivation and their ADMET properties regarding lipophilicity, CNS activity, and hepatotoxicity, these compounds could be considered for further development of CNS-active reactivators in OP poisoning as well as cholinesterase-targeted therapeutics in neurodegenerative diseases like Alzheimer’s and Parkinson’s.

Intermolecular interactions are the fabrics underlying almost all processes in living organisms, where two cornerstone concepts, intermolecular binding affinity (K d ) and binding energy (ΔG), have long been established to physically describe the strengths of biomolecular interactions, e.g., drug-target K d and ΔG to describe the strength of drug-target interaction. The past two-three years saw a big step forward in the use of artificial intelligence (AI) in structural biology (e.g., AlphaFold for protein structure prediction) and drug discovery & design. In light of the roles of K d and ΔG in drug discovery & design, the speed of this AI progress raises a question of what’s next for its practical application in the pharmaceutical industry, in addition to a system-wide account of biomolecular structures and motions. Last August, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined and proposed in an MDPI-published preprint. Here, this article puts forward an updated conceptual and practical framework of GIBAC, including its inception, definition, construction, practical applications, technical challenges and limitations, and future directions. Moreover, this article argues that the time is now ripe for the construction of such an accurate, precise and efficient GIBAC to be on the agenda of the entire drug discovery & design community, to ensure its applicability & reliability, and to enhance its value in drug R&D in future.

Delivering nucleic acid therapeutics across cell membranes is a significant challenge. Cell-penetrating peptides (CPPs) containing arginine (R), tryptophan (W), and histidine (H) show promise for siRNA delivery. To improve siRNA delivery and silencing a model STAT3 gene, we hypothesized that oleyl acylation to CPPs, specifically (WRH)n, would enhance STAT3 silencing efficiency in breast and ovarian cancer cells. Using Fmoc/tBu solid-phase peptide chemistry, we synthesized, purified, and characterized the oleyl-conjugated (WRH)n (n = 1-4) peptides. The peptide:siRNA complexes were non-cytotoxic at N/P 40 (~20 μM) against MDA-MB-231, MCF-7, SK-OV-3, and HEK-293 cells after 72 h incubation. All peptide:siRNA complexes showed serum stability at N/P ≥40. The synthesized conjugates, with a diameter of <100 nm, formed nano complexes with siRNA and exhibited stable range of zeta potential values (13-18 mV at N/P 40). Confocal microscopy and flow cytometry analysis provided qualitative and quantitative evidence of successful cellular internalization of siRNA. Peptides oleyl-(WRH)3 and oleyl-(WRH)4 showed ~60% and ~75% cellular uptake of siRNA, respectively, in both MDA-MB-231 and SK-OV-3 cells. Western blot analysis of oleyl-(WRH)4 demonstrated effective silencing of the STAT-3 gene, with ~75% silencing in MDA-MB-231 cells and ~45% in SK-OV-3 cells.

Proteolysis Targeting Chimeras (PROTACs) describe compounds that bind to and induce degradation of a target by simultaneously binding to a ubiquitin ligase. More generally referred to as bifunctional degraders, PROTACs have led the way in the field of targeted protein degradation (TPD) with several compounds currently undergoing clinical testing. Alongside bifunctional degraders, single-moiety compounds, or molecular glue degraders (MGDs), are increasingly being considered as a viable approach for development of therapeutics, driven by advances in rational discovery approaches. This review focusses on drug discovery with respect to bifunctional and molecular glue degraders within the ubiquitin proteasome system, including analysis of mechanistic concepts and discovery approaches, with an overview of current clinical and pre-clinical degrader status in oncology, neurodegenerative and inflammatory disease.

Trypanosomatids are mainly responsible for leishmaniasis, sleeping sickness, and Chagas disease, which are the most challenging among the neglected tropical diseases due to the problem of drug resistance. Although problems of target deconvolution and polypharmacology are encountered, a target-based approach is a rational method for screening drug candidates targeting a biomolecule that causes diseases. The present study aims to summarize the latest information re-garding potential inhibitors of squalene synthase and farnesyl phosphate synthase with anti-Trypanosomatidae activity. The information was obtained by referencing textbooks and major scientific databases from their inception until April 2023. Based on in vitro experiments, more than seventy compounds were reported to inhibit squalene synthase and farnesyl diphosphate synthase. Among these compounds, more than 30 were found to be active in vitro against Trypanosomatidae, inferring that these compounds can be prospected as scaffolds for the development of new drugs against trypanosomatid-related infections. Over-all, natural and synthetic products can inhibit enzymes that are crucial for the survival and virulence of trypanosomatids. Moreover, in vitro experiments have confirmed the activity of more than half of these inhibitors using cell-based as-says. Nevertheless, additional studies on the cytotoxicity, pharmacokinetics, and lead optimization of potent anti-Trypanosomatid compounds should be investi-gated.

With the first case of human immunodeficiency virus (HIV) infection confirmed in US in 1981, the efforts of discovering anti-HIV therapeutics have been continued ever since. Ten years later, the first HIV drug zidovudine (AZT) was developed to inhibit HIV reverse transcriptase. At meantime, scientists were enlightened to discover new drugs of different targets acting on HIV integrase, protease, and host receptors. The advent of combination antiretroviral therapy (cART) is completely a game changer, with high efficiency in suppressing viremia for people with HIV (PWH) by controlling the viral load below the detectable level. On the bright side, the ART treatment has made HIV a chronic infection rather than a fatal disease. However, it cannot eradicate integrated HIV DNA from the host cells, thus the latent viral reservoir has become a lifelong threaten. In this review, we first discuss the scientific history of conventional HIV drug discovery, with more and more anti-HIV agents have been developed to solve drug resistant issue and relieve the side effect. As a complementary therapy, advanced gene editing technologies have been applied to excise HIV provirus from host genome. Within four decades, novel research conducted on HIV treatment and their contributions to eliminate HIV have been altogether summarized in our review.

Tuberculosis (TB) continues to pose a global health challenge, exacerbated by the rise of drug-resistant strains. The development of new TB therapies is an arduous and time-consuming process. To expedite the discovery of effective treatments, computational structure-based drug re-purposing has emerged as a promising strategy. From this perspective, conditionally essential targets present a valuable opportunity, and the mycobactin biosynthesis pathway stands out as a prime example highlighting the intricate response of Mycobacterium tuberculosis (Mtb) to changes in iron availability. This study focuses on the re-purposing and revival of FDA-approved drugs (library) as potential inhibitors of MbtA, a crucial enzyme in mycobactin biosynthesis in Mtb conserved among all species of mycobacteria. Literature suggests this pathway to be associated with drug efflux pumps, which potentially contribute to drug resistance. This makes it a potential target for antitubercular drug discovery. Herein we utilized cheminformatics and structure-based drug repurposing approaches, viz., molecular docking, dynamics, and PCA analysis, to decode the intermolecular interactions and binding affinity of the FDA-reported molecules against MbtA. The virtual screening revealed ten molecules with significant binding affinities and interactions with MbtA. These drugs, originally designed for different therapeutic indications (4: antiviral, 3: anticancer, 1: CYP450 inhibitor, 1: ACE inhibitor, and 1: leukotriene antagonist), are repurposed as potential MbtA inhibitors. Furthermore, our study explores the binding modes and interactions between these drugs and MbtA, shedding light on the structural basis of their inhibitory potential. Principal component analysis highlighted significant motions in MbtA-bound ligands, emphasizing the stability of the top Protein-Ligand Complexes (PLCs). This computational approach provides a swift and cost-effective method for identifying new MbtA inhibitors, which can subsequently undergo validation through experimental assays. This streamlined process is facilitated by the fact that these compounds are already FDA-approved and have established safety and efficacy profiles. This study has the potential to lay the groundwork for addressing the urgent global health challenge at hand, specifically in the context of combating Antimicrobial Resistance (AMR) and Tuberculosis (TB).

Tuberculosis (TB) remains a global healthcare crisis with an estimated 10 million new cases and 1.4 million deaths per year TB is caused by infection with the major human pathogen Mycobacte-rium tuberculosis, which is difficult to rapidly diagnose and treat. There is an urgent need for new methods of diagnosis, sufficient in vitro models which capably mimic all physiological condi-tions of the infection, and high-throughput drug screening platforms. Microfluidic-based tech-niques provide single-cell analysis which reduces experimental time, the cost of reagents, and have been extremely useful for gaining insight into monitoring microorganisms. This review out-lines the field of microfluidics and discusses the use of this novel technique so far in M. tuberculo-sis diagnostics, research methods, and drug discovery platforms. The practices of microfluidics have promising future applications for diagnosing and treating TB.

The c-Jun N-terminal Kinase (JNK) signalling pathway is a conserved response to a wide range of internal and external cellular stress signals. Besides the stress response, the JNK pathway is involved in a series of vital regulatory mechanisms during development and adulthood that are critical to maintain tissue homeostasis. These mechanisms include the regulation of apoptosis, growth, proliferation, differentiation, migration and invasion. The JNK pathway has such a diverse functionality and cell-tissue specificity, that it has emerged as a key player in regeneration, tumorigenesis and other pathologies such as neurodegenerative diseases. The JNK pathway is highly active in the central nervous system (CNS), and plays a central role for the cells to cope with pathophysiological insults during both development and adulthood. Among the many mechanisms described in the literature, in this review we focus on the JNK pathway functions in pathologies of the CNS. More specifically, we discuss some newly identified examples and mechanisms of JNK-driven tumor progression in glioblastoma, regeneration/repair after an injury in the CNS, neurodegeneration, and neuronal cell death. Recent studies have shown that the JNK pathway regulates matrix metalloproteinases (MMPs) production in response to cytoneme/tumor microtubes formation and Wingless (Wg)/WNT pathway activation in glioblastoma cells. Thus, JNK pathway is essential for glioblastoma progression, infiltration and non-autonomous induction of neurodegeneration. In regeneration, the JNK pathway controls Draper (Drpr) expression in glial cells that mediate engulfment and regeneration of the CNS upon injury.

Background: Chronic Hepatitis B Virus (HBV) infection is a global health concern, associated with severe liver diseases, necessitating ongoing research on novel drug candidates. This study aims to identify potential drug candidates targeting HBV core protein (HBcAg) and disrupting capsid assembly, a critical step in the virus's life cycle. Methods: HBcAg in complex with HBV inhibitors were obtained from the Protein Data Bank (PDB). CavityPlus server was used for analysis of druggable cavity. Structure-based pharmacophores were extracted from identified cavities, and potential allosteric ligand binding sites were assessed using CavPharmer, CorrSite, and CovCys. LigandScout was employed for ligand-based pharmacophore screening against an FDA-approved library. The ZINC database was screened with features extracted from CavPharmer. Molecular docking studies were conducted using Autodock Vina. Lead compounds were selected based on docking scores, binding modes, and interactions within the druggable cavity. Results: Strong druggable pockets were found for Ciclopirox, while Compound 24, NVR10-001E2, and others showed medium to weak pockets. Ligand-based pharmacophores varied in size and complexity. Screening revealed potential hits matching these pharmacophores, including Ciclopirox olamine, Voriconazole, Enasidenib, and Statins. A large compound database search yielded additional hits like ZINC86859997 and ZINC63280172. Docking analyses confirmed these hits' potential, highlighting their interactions with critical HBc protein residues, offering promising leads for hepatitis B drug development. Conclusions: Voriconazole, Enasidenib, and Lovastatin have shown promises. These hits displayed favorable interactions with crucial HBc protein residues, indicating their potential as lead compounds The mechanism of action of statins with anti-HBV activities also highlighted. This comprehensive approach offers valuable insights into targeting HBc protein for antiviral drug discovery.

To improve efficacy and safety of sunscreen emulsions, UV‐filter skin permeation could be kept as low as possible by reducing UV‐filter content or changing emulsion composition. In this work, different lipid phase ratio (12, 14 and 16% w/w) were assessed for their ability to affect the technological and sensory properties of O/W emulsions in which bemotrizinol (BMTZ), a broad spectrum sunscreen agent, was incorporated free or loaded into nanostructured lipid nanocarriers (NLC) to reduce its release from the vehicle and, hence, its skin permeation. The following technological properties were evaluated in vitro by suitable methodologies: spreadability, viscosity, pH, occlusion factor, BMTZ release, sun protection factor (SPF). Sensory attributes were assessed by trained panelists in three different phases: before/during pick‐up, rub‐in, after application. Raising the lipid phase ratio led to an increase of viscosity and to a corresponding drop of spreadability while the incorporation of BMTZ‐loaded NLC determined a decrease of occlusion factor and an increase of SPF. No BMTZ release was observed from all emulsions. Sensory attributes were mainly affected by lipid phase ratio. These results suggest that lipid phase ratio and BMTZ incorporation into NLC could contribute to determine technological and sensory properties of O/W emulsions.

Bladder cancer (BC) is one of the most lethal genitourinary malignancies owing to its propensity for recurrence and poor survival. The biochemical pathway, signal transducer and activator of transcription 3 (STAT3), has gained significance as a molecular pathway that promotes proliferation, invasion, and chemoresistance. In this study, we explored the targeting of STAT3 with TTI-101 and SH5-07 in bladder cancer (BCa) and elucidated the mechanisms in three-dimensional (3D) spheroid and tumoroid models. We optimized the growth of spheroids from human, rat, and mouse BCa cell lines (J82, NBT-II, and MB49, respectively), and tumoroids from BBN (N-butyl-N-(4-hydroxybutyl)-nitrosamine) induced rat bladder tumors. Cell viability was assessed using MTT and trypan blue assays. ATP production, ROS production, and calcium AM (CA)/EtBr staining were used to measure the spheroid and organoid inhibition and mitochondrial function. Western blot analysis was performed to evaluate the pharmacodynamic markers involved in cell proliferation, apoptosis, cancer stem cells (CSCs), and STAT3 signaling in BCa. We found that targeting STAT3 (using TTI-101 and SH5-07) significantly reduced the proliferation of BCa spheroids, and tumoroids, which was accompanied by decreased expression of pSTAT3, Cyclin D1, and PCNA. Our data also demonstrated that treatment with STAT3 inhibitors induced ROS production and cell death in BCa spheroids and organoids. STAT3 inhibition induced cell death was associated with the activation of caspase 3/7 and PARP cleavage. Moreover, TTI-101 and SH5-07 targets cancer stem cells by downregulating the expression of CD44 and CD133 in 3D models. This study provides the first evidence for the prevention of bladder cancer with small-molecule inhibitors TTI101 and SH5-07 via suppression of CSCs and STAT3 signaling.

Leukocyte migration is an essential function of innate and adaptive immune responses. Chemokines and their receptors control the migration system. The abundance of chemokines is controlled by atypical chemokine receptors (ACKRs), chemokine receptor-like molecules that do not couple to the G protein signaling pathways. Among them, ACKR4 regulates dendritic cell migration by controlling the ligands and is involved in tumor development in mouse models. Because no anti-mACKR4 mAb for flow cytometry has been reported, this study aimed to develop a novel monoclonal antibody (mAb) for mouse ACKR4 (mACKR4). Among the established anti-mACKR4 mAbs, A₄Mab-1 (rat IgG_2b, kappa), A₄Mab-2 (rat IgG_2b, kappa), and A₄Mab-3 (rat IgG_2b, kappa) recognized mACKR4-overexpressed Chinese hamster ovary-K1 (CHO/mACKR4) by flow cytometry. The dissociation constant (K_D) values of A₄Mab-1, A₄Mab-2, and A₄Mab-3 for CHO/mACKR4 were determined as 3.5 × 10⁻⁹ M, 6.0 × 10⁻⁹ M, and 1.6 × 10⁻⁹ M, respectively. Furthermore, A₄Mab-1 and A₄Mab-2 could detect mACKR4 by western blotting. These results indicated that A₄Mab-1, A₄Mab-2, and A₄Mab-3 help to detect mACKR4 by flow cytometry and western blotting and obtain the proof of concept in preclinical models.

Covid-19 is one of humanity’s biggest threat in the 21st century with WHO figures reporting 636 million cases and up to 6.6 million deaths globally. SARS-CoV-2, the virus that causes the Covid-19 disease, is characterized by high mutation which contributes to its rapid spread. While several vaccines have been produced to minimize the severity of the coronavirus and diverse treatment regimens have been approved by the US FDA under Emergency Use Authorization (EUA), SARS-CoV-2 viral mutations continue to derail the efforts of scientists as the emerging variants evade the recommended therapies. Nonetheless, diverse computational models exist that offer an opportunity to overcome the barriers involved in developing new drugs. In this review, the focus is on the use of various virtual screening techniques like molecular docking, molecular dynamics simulations, QSAR, pharmacophore modeling, and homology modeling in repurposing SARS-CoV-2 therapeutics. The results have been promising from the computer-aided drug design (CADD) studies in suggesting potential compounds for treatment of Covid-19 and helping in bringing the pandemic under control.

Despite being an abundant marine organism in Indonesia, black sea cucumber is still underutilised due to its slightly bitter taste. Previous studies have hinted at the potential of black sea cucumber as an anti-cancer agent. However, specific identification of bioactive compounds that can interact with cancer proteins is still lacking. In the same place, cancer ranks third as Indonesia's leading cause of death. Therefore, this study aims to identify potential anti-cancer compounds from black sea cucumbers using a comprehensive in silico drug discovery approach. This research uses machine learning, molecular docking, and ADMET analysis to identify bioactive compounds that specifically interact with cancer proteins. A combination of the Cascade Deep Forest algorithm and ECFP-AAIndex1 feature combination proved to be the most effective in predicting these interactions. Through molecular docking validation, four bioactive compounds with strong binding affinity were identified: Afimoxifene, Danazol, Taxifolin, and Terfenadine. ADMET analysis highlighted Taxifolin as the most promising candidate, as it passed most ADMET parameters. Further wet laboratory studies are required to confirm the effects and potential of these compounds as anti-cancer agents. This study builds a foundation for future investigations into alternative cancer treatments using abundant natural resources.

CD44 is a type I transmembrane glycoprotein, which is associated with poor prognosis in various solid tumors. Since CD44 plays critical roles in tumor development by regulating cell adhesion, survival, proliferation, and stemness, it has been considered a target for tumor therapy. Anti-CD44 monoclonal antibodies (mAbs) have been developed and applied to antibody-drug conjugates and chimeric antigen receptor-T cell therapy. We previously developed anti‐pan-CD44 mAbs, C₄₄Mab-5 and C₄₄Mab-46, which can recognize both CD44 standard (CD44s) and variant isoforms. In the present study, a defucosylated mouse IgG_2a version of the anti-pan-CD44 mAbs (5-mG_2a-f and C₄₄Mab-46-mG_2a-f) was generated to evaluate the antitumor activities against CD44-positive cells. Both 5-mG_2a-f and C₄₄Mab-46-mG_2a-f recognized CD44s-overexpressed CHO-K1 (CHO/CD44s) cells and esophageal tumor cell line (KYSE770) in flow cytometry. Furthermore, both 5-mG_2a-f and C₄₄Mab-46-mG_2a-f could activate effector cells in the presence of CHO/CD44s cells and exhibited the complement‐dependent cytotoxicity against both CHO/CD44s and KYSE770 cells. Furthermore, the administration of 5-mG_2a-f and C₄₄Mab-46-mG_2a-f significantly suppressed CHO/CD44s and KYSE770 xenograft tumor development compared with the control defucosylated mouse IgG_2a. These results indicate that 5-mG_2a-f and C₄₄Mab-46-mG_2a-f could exert antitumor activities against CD44-positive cancers and could be a promising therapeutic regimen for tumors.

One of the G protein-coupled receptors, C-C chemokine receptor 5 (CCR5), is an important regulator for the activation of T and B lymphocytes, dendritic cells, natural killer cells, and macrophages. Upon binding to the ligands, CCR5 activates downstream signaling, which plays critical roles in the innate and adaptive immune response through the promotion of lymphocyte migration and the secretion of pro-inflammatory cytokines. Anti-CCR5 monoclonal antibodies (mAbs) have been developed and evaluated in clinical trials for tumors and inflammatory diseases. In this study, we developed novel mAbs for mouse CCR5 (mCCR5) using the N-terminal peptide immunization. Among the established anti-mCCR5 mAbs, C₅Mab-4 (rat IgG_2a, kappa) and C₅Mab-8 (rat IgG₁, kappa), recognized mCCR5-overexpressed Chinese hamster ovary-K1 (CHO/mCCR5) and an endogenously mCCR5-expressing cell line (L1210) by flow cytometry. The dissociation constant (K_D) values of C₅Mab-4 and C₅Mab-8 for CHO/mCCR5 were determined as 3.5 × 10⁻⁸ M and 7.3 × 10⁻⁹ M, respectively. Furthermore, both C₅Mab-4 and C₅Mab-8 could detect mCCR5 by western blotting. These results indicated that C₅Mab-4 and C₅Mab-8 are useful for detecting mCCR5 by flow cytometry and western blotting and provide a possibility to obtain the proof of concept in preclinical studies.

The generation of forensic DNA profiles consisting of single nucleotide polymorphisms (SNPs) is now being facilitated by wider adoption of next-generation sequencing (NGS) methods in casework laboratories. At the same time, and in part because of this advance, there is an intense focus on the generation of SNP profiles from evidentiary specimens for so-called forensic or investigative genetic genealogy (FGG or IGG) applications. However, FGG methods are constrained by the algorithms for genealogical database searches, which were designed for use with single-source profiles, and the fact that many forensic samples are mixtures. To enable the use of two-person mixtures for FGG, we developed a workflow, MixDeR, for the deconvolution of mixed SNP profiles. MixDeR, a flexible and easy to use R package and Shiny app, processes ForenSeq Kintelligence® (QIAGEN, Inc.) SNP genotyping results and directs deconvolution of the profiles in EuroForMix (EFM). MixDeR then filters the EFM outputs to produce inferred single-source genotypes in reports formatted for use with GEDmatch® PRO. An optional MixDeR output includes metrics that assist with testing and validation of the workflow. As the Shiny app provides a graphical user interface and the software is designed to be run offline, MixDeR should be suitable for use by any laboratory developing FGG capabilities, no matter their bioinformatic resources or expertise.

Calcium signaling and lipid metabolism are crucial in the infection processes of Apicomplexans parasites. Thus, enzymes involved in these processes can be drug targets against Apicomplexans. For example, in malaria infection, in-depth research into lipid metabolic pathways is crucial in understanding the parasite's infection cycle, particularly during its erythrocytic infection cycle, which has been demonstrated to be a critical stage during the disease progression. Most enzymes that play critical roles in lipid synthesis and calcium signaling have been extensively studied; nonetheless, a vast knowledge gap still exists, especially on specific enzymes and their roles in the transmission and progression of the Apicomplexan parasites. Many types of infections caused by Apicomplexans are life-threatening and hard to treat. These intracellular parasites proliferate within parasitophorous vacuoles in their host cells. As the parasites multiply, they need to meet their high demand for nutrients such as amino acids and lipids. They can acquire nutrients through scavenging and biosynthesis. This review summarizes a few interesting, unique pathways in selected Apicomplexa and how such unique pathways can be targets for drugs.

C-C motif chemokine receptor-8 (CCR8) belongs to class A of G protein-coupled receptors (GPCRs). CCR8 interacts with the specific chemokine ligand CCL1/I-309 in humans, which is produced by various cells, including tumor-associated macrophages and regulatory T cells (Treg). CCR8 is highly expressed on Treg and T-helper 2 (T_H2) cells recruited to the inflammation site and is implicated in allergy, asthma, and cancer progression. The CCR8⁺Treg has been suggested to be an important regulator in the immunosuppressive tumor microenvironment (TME); therefore, it has been desired to develop sensitive monoclonal antibodies (mAbs) for CCR8. This study developed a specific mAb for human CCR8 (hCCR8), which is useful for flow cytometry by employing the Cell-Based Immunization and Screening (CBIS) method. The established anti-hCCR8 mAb, C₈Mab-21, (mouse IgM, kappa) reacted with hCCR8-overexpressed Chinese hamster ovary-K1 (CHO/hCCR8) cells, TALL-1 (acute T lymphoblastic leukemia), CCRF-HSB2 (human T-lymphoblastic leukemia), and natural killer cells, which express endogenous hCCR8 by flow cytometry. Furthermore, C₈Mab-21 demonstrated a moderate binding affinity for CHO/hCCR8 and TALL-1 with a dissociation constant of 6.5×10^-8 M and 2.0×10^-8 M, respectively. C₈Mab-21, which was established by the CBIS method, could be a useful tool for analyzing the hCCR8-related biological response using flow cytometry.

Triple negative breast cancer (TNBC) is associated with a generally poor prognosis due to its highly aggressive and metastatic nature, lack of targetable receptors, as well as the frequent development of resistance to chemotherapy. We previously reported that AU1, a small molecule developed as an inhibitor of BPTF (bromodomain PHD finger containing transcription factor), was capable of sensitizing preclinical models of triple negative breast cancer to chemotherapy, in part via the promotion of autophagy. In studies reported here, we identify an additional property of this compound, specifically that sensitization is associated with inhibition of the P-glycoprotein efflux pump. In silico molecular docking studies indicate that AU1 binds to active regions of the efflux pump, in a manner consistent with inhibition of pump function. This work identifies a novel chemical structure that can influence multidrug efflux, an established mechanism of drug resistance in triple negative breast cancer, that has not yet been successfully addressed by clinical efforts.

Onchocerciasis treatment and control relies mainly on the use of ivermectin which has high activity against the microfilarial stage of Onchocerca volvulus but limited activity against the long lived, tissue dwelling adult nematodes. As this neglected tropical disease has now been targeted for elimination there is an urgent need for new drugs to combat these parasites, ideally with macrofilaricidal activity. In this study we have examined the anti-Onchocerca activity of a range of existing FDA approved drugs with a view to repurposing, which can lead to rapid and relatively inexpensive development. From the Pharmakon-1600 library, 106 drugs were selected and tested against O. gutturosa adult male parasites using a concentration of 1.25 x 10-5 M in an in vitro 5-day standard assay to assess motility and viability (using MTT/formazan colorimetry). The findings revealed that 44 drugs produced marginal/moderate activity (50-99% motility and/or MTT reductions) including cefuroxime sodium, methenamine, primaquine phosphate, rivastigmine tartrate, while 23 drugs produced good activity (100% motility reductions and significant MTT reductions), including atovaquone, isradipine, losartan, rifaximin, cefaclor and pyrantel pamoate. Although this study represents only a first step, some of the identified hits indicate there are potential anti-Onchocerca drug candidates worthy of further investigation.

Public perception contrasts scientific findings on the depression-related effects of cannabis. However, earlier studies were performed when cannabis was predominantly illegal, its production was mostly uncontrolled, and the idea of medical cannabis was incipient only. We hypothesized that recent changes in attitudes and legislations may have favorably affected research. In addition, publication bias against cannabis may have also decreased. To investigate this hypothesis, we conducted a systematic review of research studies published over the last three years. We found 156 relevant studies. In most cross-sectional studies, depression was higher in those who consumed cannabis than in those who did not. An increase in cannabis consumption was typically followed by an increase in depression, whereas withdrawal from cannabis ameliorated depression in most cases. Albeit medical cannabis reduced depression in most studies, none of these were placebo controlled. In clinical studies published in the same period, placebo also ameliorated depression and in addition, the average effect size of placebo was larger than the average effect size of medical cannabis. We also investigated the plausibility of the antidepressant effects of cannabis by reviewing molecular and pharmacological studies. Taken together, the reviewed findings do not support the antidepressant effects of herbal cannabis.

The Severe acute respiratory syndrome-Corona virus-2 (SARS-CoV-2) which is responsible for recurring pandemics takes advantage of host-cell processes including the glycosylation pathway. The heavily glycosylated spike protein assists viruses in attachment and penetration. The N-glycans of N-terminal domain N165 and N234 play a significant role in conformational dynamics of the receptor-binding domain (RBD) with angiotensin-converting enzyme 2 (ACE2). In addition, the deletion of N-glycan sites N331 and N334 have been associated with reduced infectivity. This signifies the importance of targeting the N-glycans making them unavailable for interacting with the ACE2 receptor, ultimately leading to reduced infectivity. These glycans can be specifically targeted and can be used for designing SARS specific drugs or neutralizing molecules. In the current study, lectins Griffithsin, Cyanovirin-N, Cyanovirin homolog, and BanLec H84T were used to target the spike protein's N-glycans. Molecular docking programs AutoDock Vina and HADDOCK were used to study lectin-glycan interactions. The interactions look convincible in accordance with the lowest interaction energies best-fit approach but the characteristic feature (scoring functions) of the docking programs are questionable concerning Lectin-Glycan interactions exist in nature. There is a high need of the hour for developing specific algorithms for docking glycans with a preferential selection of terminal residues.

BackgroundThe present review summarizes the state-of-the-art of in silico methods and techniques that are the most useful in drug discovery, their relationship with data science, as well as the successful application of data science, machine learning (ML) and artificial intelligence (AI) applications. A meta-analysis of the various technologies available is furthermore proposed as a guideline for the non-expert, reader relative to the several subject areas is also discussed in this article. The scope of this meta-analysis is to rank the enlisted technologies by their field of applications and to depict the latter according to knowledge accessibility, from students to experts.Method The search strategy utilized for this review first produced a general collection of 900 papers without duplications, which were subsequently streamlined and divided into two independent collections: the top 300 most-cited papers of all time (since 2000) and the papers with the highest interest for a systematic review analysis (high-impact exciting papers). Results In Part 1, we discuss the most cited and quality 97 articles in these top 300 papers most relevant to the field of in silico drug discovery. The different disciplines are listed according to their industrial and economic incurred to society, independently from the “metric” results of how many new drug approvals (NDAs) each discipline has generated to date.ConclusionBig data, the ensemble of known items stored in publicly available databases, has improved our understanding of the many fates of a potential drug candidate during its development and even after its commercialization. Moreover, the combination of new screening techniques and “omics” with old drugs has led to a new paradigm in which the unknown knowledge of any biological molecule and its cellular structure, now plays an important role as a target for a series of yet-to-be-developed drugs: the chemical space. Furthermore, leveraging big data, data science, ML, and AI can revolutionize drug discovery by swiftly analyzing massive datasets, predicting efficacy and safety profiles, streamlining development, cutting costs, and boosting success rates for new drugs. AI also speeds up the search for promising drug candidates, advancing innovative therapies.

Porifera, commonly referred to as marine sponges, have stood out as major producers of marine natural products (MNPs). Sponges of the genus Phorbas have attracted much attention along years. They are widespread in all continents, and several structurally unique compounds have been identified from species of this genus. Terpenes, mainly sesterterpenoids, represent the great majority of secondary metabolites isolated from Phorbas species, even though several alkaloids and steroids have also been reported. Many of these compounds have shown a variety of biological activities. Particularly, Phorbas sponges have been demonstrated to be a source of cytotoxic metabolites. In addition, MNPs exhibiting cytostatic, antimicrobial and anti-inflammatory activities, have been isolated and structurally characterized. This work brings an overview of Phorbas secondary metabolites reported since the first study published in 1993 until 2020, and their biological activities.

In the domain of drug discovery and design, the acquisition of precise structural and intermolecular Kd data for biological molecules is paramount. However, conventional methods for obtaining such data are often beset by challenges including high costs, time intensiveness, and inherent limitations in scalability and diversity. This article puts forward a high-throughput approach for in silico generation of structural and intermolecular binding affinity (Kd) data, which keeps exploring the uncharted territories of drug discovery & design by harnessing computational methodologies to synthetically generate diverse datasets. Through a meticulously designed workflow encompassing molecular structural modeling, structural biophysics-based calculations of intermolecular binding affinity (Kd), this innovative methodology transcends the constraints of traditional experimentation, offering a cost-effective, scalable, and efficient alternative. By simulating molecular interactions and binding interfaces and predicting binding affinities with reasonable accuracy, this approach not only expedites the drug development process but also enables the exploration of vast molecular space, thereby facilitating the discovery of novel therapeutics beyond conventional drug modality as a form factor. Moreover, the versatility of synthetic data extends beyond virtual screening and lead optimization, encompassing applications such as dataset augmentation, model validation, and benchmarking against experimental data. This article elucidates the conceptual underpinnings, methodological intricacies, validation strategies, and potential ramifications of in silico generated data, heralding a paradigm shift in drug discovery paradigms. By fostering synergy between computational and experimental research domains, this innovative approach promises to accelerate the pace of drug discovery, enhance the robustness of predictive models, and pave the way for transformative advancements in the entire pharmaceutical industry.

Glioblastoma (GBM) is the most common primitive tumor in adult central nervous system (CNS), classified as grade IV according to WHO 2016 classification. GBM shows a poor prognosis with an average survival of approximately 15 months, representing an extreme therapeutic challenge. One of its distinctive and aggressive features is aberrant angiogenesis, which drives tumor neovascularization, representing a promising candidate for molecular target therapy. Although several pre-clinical studies and clinical trials have shown promising results, anti-angiogenic drugs have not led to a significant improvement in overall survival (OS), suggesting the necessity of identifying novel therapeutic strategies. Metformin, an anti-hyperglycemic drug of the Biguanides family, used as first line treatment in Type 2 Diabetes Mellitus (T2DM), demonstrated in vitro and in vivo antitumoral efficacy in many different tumors, including GBM. From this evidence, a process of repurposing of the drug has begun, leading to the demonstration of the inhibition of various oncopromoter mechanisms and, consequently, to the identification of the molecular pathways involved. Here, we review and discuss the potential metformin’s antitumoral effects on GBM, inspecting if it could properly act as an anti-angiogenic compound to be considered as a safely add-on therapy in the treatment and management of GBM patients.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

MRI shows in-vivo the three archetypal patterns of CNS volume loss underlying progressive ataxias, namely spinal atrophy (SA), cortical cerebellar atrophy (CCA) and olivopontocerebellar atrophy (OPCA). The MRI-based CNS atrophy pattern was reviewed in 128 progressive ataxias. A CNS atrophy pattern was identified in 91 conditions: SA in Freidreich’s ataxia, CCA in 5 acquired and 72 (24 dominant, 47 recessive,1 X-linked) inherited ataxias, OPCA in Multi-System Atrophy and 12 (9 dominant, 2 recessive,1 X-linked) inherited ataxias. The MRI-based CNS atrophy pattern may be useful for genetic assessment, identification of shared cellular targets, and repurposing therapies or enlargement of drugs indications in progressive ataxias.

Alzheimer’s disease (AD) is an age-associated neurodegenerative disorder. A wealth of evidence indicates that the amyloid β (Aβ) aggregates result from dyshomeostasis between Aβ production and clearance, which plays a pivotal role in the pathogenesis of AD. Consequently, therapies targeting Aβ reduction represent a promising strategy of AD intervention. Tetramethylpyrazine nitrone (TBN) is a novel tetramethylpyrazine derivative with the potential for the treatment of AD. Previously, we demonstrated that TBN markedly improved cognitive functions and reduced Aβ, APP, BACE 1 and hyperphosphorylated tau levels in 3 × Tg-AD mice. However, the mechanism by which TBN inhibits Aβ deposition still unclear. In this study, we employed the APP/PS1 mice treated with TBN (60 mg/kg, ig, bid) for six months and N2a/APP695swe cells treated with TBN (300 μM) to explore the mechanism of TBN on the Aβ reduction. Our results indicated that TBN significantly alleviated cognitive impairment and reduced Aβ depositions in APP/PS1 mice. Further investigation of the underlying mechanisms revealed that TBN decreased the expression of APP and BACE1, activated the AMPK/mTOR/ULK1 autophagy pathway and inhibited the PI3K/AKT/mTOR/ULK1 autophagy pathway, as well as decreased the phosphorylation levels of JNK and ERK in APP/PS1 mice. Moreover, TBN was found to significantly reduce the mRNA levels of APP and BACE1, as well as those of SP1, CTCF, TGF-β, and NF-κB, transcription factors involved in regulating gene expression. Additionally, TBN was observed to decrease the level of miR-346 and increase the levels of miR-147 and miR-106a in the N2a/APP695swe cells. These findings indicate that TBN may reduce Aβ levels likely via reducing APP expression by regulating APP gene transcriptional factors and miRNAs, reducing BACE1 expression, and promoting autophagy activities.

This study aimed to evaluate the safety and tolerability of STP1, a combination of ibudilast and bumetanide, tailored for the treatment of a specific subgroup of patients with Autism Spectrum Disorder (ASD), namely ASD Phenotype 1 (ASD-Phen1). We conducted a randomized, double-blind, placebo-controlled, parallel-group phase 1b study with two 14-day treatment phases (registered at clinicaltrials.gov as NCT04644003). Nine ASD-Phen1 patients were administered STP1, while three received a placebo. We assessed safety and tolerability, along with electrophysiological markers, such as EEG, Auditory Habituation, and Auditory Chirp Synchronization, to better understand STP1's mechanism of action. Additionally, we used several clinical scales to measure treatment outcomes. The results showed that STP1 was safe and well-tolerated, with electrophysiological markers indicating a significant and dose-related reduction of gamma power in the whole brain and in brain areas associated with executive function and memory. Treatment with STP1 also increased alpha 2 power in frontal and occipital regions and improved habituation and neural synchronization to auditory chirps. Although numerical improvements were observed in several clinical scales, they did not reach statistical significance. Overall, this study suggests that STP1 is safe and well-tolerated in ASD-Phen1 patients and shows indirect target engagement in ASD brain regions of interest.

Cancer-specific monoclonal antibodies (CasMabs) that recognize cancer-specific antigens with in vivo antitumor efficacy are innovative therapeutic strategies for minimizing the adverse effects. We previously established a cancer-specific anti-human epidermal growth factor receptor 2 (HER2)monoclonal antibody (mAb), H₂Mab-250/H₂CasMab-2. In flow cytometry and immunohistochemistry, H₂Mab-250 reacted with HER2-positive breast cancer cells but did not show the reactivity to normal epithelial cells. In contrast, a clinically approved anti-HER2 mAb, trastuzumab, strongly recognizes both breast cancer and normal epithelial cells in flow cytometry. The human IgG₁ version of H₂Mab-250 (H₂Mab-250-hG₁) possesses compatible in vivo antitumor effects against breast cancer xenografts with trastuzumab despite the lower affinity and effector activation than trastuzumab in vitro. This study compared the antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cellular cytotoxicity (CDC) between H₂Mab-250-hG₁ and trastuzumab. Both H₂Mab-250-hG₁ and trastuzumab showed ADCC activity against CHO/HER2 and breast cancer cell lines (BT-474 and SK-BR-3) in the presence of human natural killer cells. Some tendency was observed that trastuzumab showed a more significant ADCC effect compared to H₂Mab-250-hG₁. Importantly, H₂Mab-250-hG₁ exhibited superior CDC activity in these cells compared to trastuzumab. Similar results were obtained in mouse IgG_2a types of both H₂Mab-250 and trastuzumab. These results suggest the different contributions of ADCC and CDC activities to the antitumor effects of H₂Mab-250-hG₁ and trastuzumab and indicate the future direction for the clinical development of H₂Mab-250-hG₁ against HER2-positive tumors.

The clinical practice implies a research translation that helps the use of scientific data and thera-peutic evidence for patient benefits. This review critically summarizes the potential impact of cannabinoids in concomitance with other drugs in the following chronic diseases as Epilepsy, Au-tism Spectrum Disorders (ASD), Oncology, Multiple Sclerosis, and Chronic Pain. The potential in-teractions can change the predicted clinical outcomes of therapeutic protocols and need to be evaluated. Some of the effects would be additive, synergistic or antagonistic, but can also enroll changes in absorption, distribution, metabolism, particularly via cytochrome P450 (CYP) isoen-zymes (e.g CYP2C9 and CYP3A4) and excretion. For instance, the combination of canna-bis-derived compounds and the antifungal drug ketoconazole, a CYP3A4 inhibitor, increases plasma concentration of Δ-9-tetrahydrocannabinol (THC) and CBD (CBD). Opposable, rifampic-in, a CYP3A4 inducer, stands out for the approximately 20-40% reduction in plasma THC levels and 50% to 60% for CBD. Other CYP3A4 inhibitors and inducers are likely to have a similar effect on plasma concentrations if co-administered. Indeed, pharmacokinetic interactions have been also reported with antiseizure drugs. Moreover, pharmacodynamic interactions between cannabinoids and drugs with sympathomimetic effects (eg tachycardia, hypertension), central nervous system depressants (eg drowsiness, ataxia), and anticholinergics (eg tachycardia and drowsiness) are also expected. Even though pending further studies, there is currently clinical evidence supporting drug interaction with cannabinoids, demanding doctors evaluate the risk of drug combinations with cannabinoids. The tables herein provided were designed to facilitate the identification of bi-orelevant interactions that may compromise therapeutic efficacy and toxicity.

The main proteinase (Mpro), or 3CLpro, is a critical enzyme in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lifecycle and is responsible for breaking down and releasing vital functional viral proteins crucial for virus development and transmission. As a catalytically active dimer, its dimerization interface has become an attractive target for antiviral drug development. Recent research has extensively investigated the enzymatic activity of Mpro, focusing on its role in regulating the coronavirus replication complex and its significance in virus maturation and infectivity. Computational investigations have identified four druggable pockets, suggesting potential allosteric sites beyond the substrate-binding region. Empirical validation through site-directed alanine mutagenesis targeted residues in both the active and allosteric regions corroborated these predictions. Structural studies of drug target proteins can inform therapeutic approaches, with metadynamics simulations shedding light on the role of H163 in regulating Mpro function and providing insights into its dynamic equilibrium to the wild-type enzyme. Despite the efficacy of vaccines and drugs in mitigating SARS-CoV-2 spread, ongoing viral evolution, selective pressures, and continued transmission pose challenges, potentially leading to resistance mutations. Phylogenetic analyses indicated the existence of several resistance variations predating drug introduction to the human population, emphasizing the likelihood of drug spread. Hydrogen/deuterium-exchange mass spectrometry reveals the structural influence of the mutation, while clinical trials on 3CLPro inhibitors underscore the clinical significance of reduced enzymatic activity and offer avenues for future therapeutic exploration. Understanding the implications of 3CLPro mutations holds promise for shaping forthcoming therapeutic strategies against COVID-19. This review delves into factors influencing mutation rates and identifies areas warranting further investigation, providing a comprehensive overview of Mpro mutations, their categorization, and terminology. Moreover, we examined their associations with clinical outcomes, illness severity, unresolved issues, and future research prospects, including their impact on vaccine efficacy and potential therapeutic targeting.

With increasing numbers of older adults worldwide, multimorbidity and polypharmacy are on the rise, highlighting the risks of harmful drug-drug interactions (DDIs) to patients. As cardiovascular agents are among the most prescribed medications, we performed an observational cross-sectional study to determine the prevalence of DDIs in a cardiology department of a secondary hospital. Patient data was obtained from medical records and screened for DDIs using the Micromedex drug interaction software. Descriptive statistics, Chi-square (χ2) test, Student's t test and Pearson's correlation test were used to analyse the results. Out of 50 participants, 45 (90%) had at least one DDI. A total of 266 DDIs were identified, with more than half classified as major. At least one major DDI was found in 78% of patients. 42% of patients were at an increased risk of bleeding due to DDIs. A statistically significant relationship was found between the detection of DDIs and both patient age (p = 0.005) and the number of drugs used (p < 0.001). Our findings pose questions about the wider prevalence and risks of drug-drug interactions among patients with cardiovascular disease.

EphB2 is a member of the Eph family tyrosine kinase receptors. EphB2 binds to ephrin-B1, ephrin-B2, and ephrin-B3, which are critical regulators of vascular and nervous development through controlling cell migration and axon guidance. EphB2 is overexpressed in tumors, including glioma, breast cancer, hepatocellular carcinoma, and malignant mesothelioma, and it functions as a tumor promoter. Therefore, the development of monoclonal antibodies (mAbs) against EphB2 is essential for tumor diagnosis and therapy for EphB2-positive tumors. In this study, we developed novel mAbs for human EphB2 using the Cell-Based Immunization and Screening (CBIS) method. One of the established anti-EphB2 mAbs, Eb2Mab-3 (mouse IgG1, kappa), reacted with EphB2-overexpressed Chinese hamster ovary-K1 (CHO/EphB2) and an endogenously EphB2-expressing cancer cell line (LS174T) by flow cytometry. Using flow cytometry, the dissociation constant (KD) values of Eb2Mab-3 for CHO/EphB2 and LS174T were determined as 1.1 × 10−9 M and 3.6 × 10−10 M, respectively. These results indicated that Eb2Mab-3 possesses a high affinity for detecting EphB2 and could apply to tumor therapy.

Berberine (BER) is a natural alkaloid found in various Berberis species, used traditionally in herbal medicine and dietary supplements. BER exhibited various biological activities, including anti-inflammatory, antioxidant, antidiabetic, and anti-tumour properties by modulating cellular pathways and influencing gene expression. While BER shows promise in various health applications, its possible toxicity raises concerns. In 2023, EFSA issued a call for data on BER- and protoberberine (PROTBER)-containing products, to comprehensively assess its safety and potential health claims. With these premises, new data was collected by assessing: i) the phytochemical profile of BER- and PROTBER-containing preparations by newly developed HPLC-DAD method; ii) in silico and in vitro investigation of pharmacokinetics properties of BER; iii) in vitro cytotoxicity in different human cell lines and, iv) biological and molecular activities of extracts containing BER and PROTBER in in vitro human non-cancer cells. By testing 16 commercial Berberis extracts, the evidence collected showed a good qualitative reliability in terms of phytochemical profile and limited relapses on cytotoxicity even at 200 µg/ml after a 24h of exposure, while evidencing a good cellular bioavailability and cell migration inhibition. The potential for plant-drug interactions affecting CYP450 proved to be minimal. Overall, our work provides a useful overview to better elucidate potential concerns on botanicals containing BER and minor PROTBER commonly used in food supplement.

Diabetes is a major health concern that the next-generation of on-demand insulin releasing implants may overcome for personalized therapy. Therein, 3D-printed phenylboronic acid-containing subcutaneous implants with on-demand glucose-triggered drug release abilities are produced using high resolution stereolithography technology. To that end, the methacrylation of phenylboronic acid is targeted following a two-step reaction. The resulting photocurable phenylboronic acid derivative is accordingly incorporated within bioinert polyhydroxyethyl methacrylate-based hydrogels at varying loadings. The end result are sub-centimeter scaled 3D-printed bionert implants that can be remotely activated with 1,2-diols and 1,3-diols such as glucose for on-demand drug administration such as insulin. As a proof of concept, varying glucose concentration from hypoglycemia to hyperglycemia levels readily allow the release of pinacol, i.e. a model molecule with similar release properties than insulin, at respectively low and high rates. In addition, the results demonstrated that adjusting the geometry and size of the 3D-printed part is a simple and suitable method for tailoring the release behavior and dosage.

The rapid and accurate detection of viruses and the discovery of single nucleotide polymorphisms (SNPs) are crucial for disease management and understanding viral evolution. In this study, a pipeline for virus detection, validation, and SNP discovery from next-generation sequencing (NGS) data is presented. By integrating state-of-the-art bioinformatics tools with artificial intelligence, the pipeline processes raw sequencing data to identify viral sequences with high accuracy and sensitivity. Before aligning the reads to the reference genomes, quality control measures and adapter trimming are performed to ensure the integrity of the data. Unmapped reads are subjected to de novo assembly to reveal novel viral sequences and genetic elements. The effectiveness of the pipeline is demonstrated by the identification of virus sequences, illustrating its potential for the detection of known and emerging pathogens. SNP discovery is performed using a custom Python script that compares the entire population of sequenced viral reads to a reference genome. This approach provides a comprehensive overview of viral genetic diversity and identifies dominant variants and a spectrum of genetic variations. The robustness of the pipeline is confirmed by the recovery of complete viral sequences, which improves our understanding of viral genomics. This study highlights the synergy between traditional bioinformatics techniques and modern approaches, providing a robust tool for analyzing viral genomes and contributing to the broader field of viral genomics.

Pomegranate extract has potential benefits for women's reproductive health, including fertility enhancement, menstrual cycle regulation, pregnancy support, and polycystic ovary syndrome (PCOS) treatment. It possesses antioxidant properties, reducing oxidative stress and improving fertility. Phytoestrogens in pomegranate extract may help regulate hormonal imbalances and promote regular menstrual cycles. The extract's rich nutrient profile supports placental development and fetal growth and may reduce the risk of preterm birth. Additionally, pomegranate extract shows promise in improving insulin sensitivity and reducing inflammation and oxidative damage in PCOS. Some studies suggest its potential anticancer properties, particularly against breast cancer. However, further research, including human clinical trials, is necessary to establish its effectiveness and safety. The current evidence is limited and primarily based on in vitro studies, animal studies, and clinical trials. This review provides a comprehensive summary of the benefits of pomegranate extract for women's reproductive health and breast cancer, serving as a reference for future research.

In CNS drug discovery, estimation of brain exposure of lead compounds is critical for their optimization. Compounds need to cross the blood-brain barrier (BBB) to reach the pharmacological targets in the CNS. The BBB is a complex system involving passive and active mechanisms of transport and efflux transporters such as P-glycoproteins (P-gp) and breast cancer resistance protein (BCRP), which play an essential role in CNS penetration of small molecules. Several in vivo, in vitro and in silico methods are available to estimate human brain penetration. Preclinical species are used as in vivo models to understand the unbound brain exposure by deriving the Kp,uu parameter, the brain/plasma ratio of exposure corrected with the plasma and brain free fraction. MDCK-mdr1 (Madin Darby canine kidney cells transfected with the MDR1 gene encoding for the human P-gp) assay is the most commonly used in vitro assay to estimate compound permeability and human efflux. The in silico methods to predict brain exposure, such as CNS MPO, CNS BBB scores and various Machine Learning models, help save costs and speed up compound discovery and optimization at all stages. These methods enable the screening of virtual compounds and building of a CNS penetrable compounds library as well as optimization of lead molecules for CNS penetration. Therefore, it is crucial to understand these methods' reliability and ability to predict CNS penetration. We review the in silico, in vitro and in vivo data and their correlation with each other and assess published in silico approaches to predict the BBB penetrability of compounds.

Polyelectrolyte-drug complexes are interesting alternatives to improve unfavourable drugs properties. Vancomycin (VAN) is an antimicrobial used in the treatment of methicillin-resistant Staphylococcus aureus pulmonary infections in patients with cystic fibrosis. It is generally administered intravenously with high incidence of adverse side effects, which could be reduced by intrapulmonary administration. Currently, there are no commercially available inhalable formulations containing VAN. Thus, the present work focuses on the preparation and characterization of an ionic complex between hyaluronic acid (HA) and VAN with potential use as inhalable formulations. Particulate-solid HA-VAN25 complex by spray drying from an aqueous dispersion was obtained. FTIR spectroscopy and thermal analysis confirmed the ionic interaction between HA and VAN, while an amorphous diffraction pattern by X-ray was observed. The powder density, geometric size and morphology showed a suitable aerosolization and aerodynamic performance of the powder, indicating the capability of reaching the deep lung. An in vitro extended-release profile of VAN from the complex was obtained, exceeding 24 hours. Microbiological assays against methicillin-resistant and -sensitive reference strains of Staphylococcus aureus, showed that VAN preserves its antibacterial efficacy. In conclusion, HA-VAN25 exhibited interesting properties for the development of inhalable formulations with potential efficacy and safety advantages over conventional treatment.

Microglial cells, the resident macrophages of the CNS, exist in a process-bearing, ramified/surveying phenotype under resting conditions. Upon activation by cell damaging factors they get transformed to an amoeboid phenotype releasing various cell products including pro-inflammatory cytokines, chemokines, proteases, reactive oxygen/nitrogen species and the excytotoxic ATP and glutamate. In addition, they engulf pathogenic bacteria or cell debris and phagocytose them. However, already resting/surveying microglia has a number of important physiological functions in the CNS; they e.g. shield small disruptions of the blood-brain barrier by their processes, dynamically interact with synaptic structures and clear surplus synapses during development. In neurodegenerative illnesses they aggravate the original disease by a microglia-based compulsory neuroinflammatory reaction. Therefore, the blockade of this reaction improves the outcome of Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, amyotrophic lateral sclerosis, etc. The function of microglia is regulated by a whole array of purinergic receptors classified as P2Y12, P2Y6, P2Y4, P2X4, P2X7, A2A, A3, and being targets for endogenous ATP, ADP, or adenosine. ATP is sequentially degraded by the ecto-nucleotidases and 5’-nucleotidase enzymes to the weak adenosine agonist inosine as an end-product. The appropriate selective agonists/antagonists for purinergic receptors as well as the respective enzyme inhibitors may profoundly interfere with microglial functions and reconstitute the homeostasis of the CNS disturbed by neuroinflammation.

Accurately predicting drug-drug interactions (DDIs) is crucial for preventing adverse drug events in clinical settings. However, existing methodologies often rely on complex models built from diverse data sources, posing challenges in computational drug discovery. To address the need for precise computational methods in predicting unknown DDIs, this study introduces a novel Deep Neural Network (DNN)-based approach. By leveraging a wide range of drug-related information, including substructure, targets, side effects, pathways, and indications, our method calculates multiple drug similarities. These similarities are then synthesized using a nonlinear fusion method to extract high-level features. Subsequently, a tailored neural network is deployed for interaction prediction. Comparative evaluation against three prominent machine learning classifiers—Extreme Gradient Boosting (XGBoost), Adaptive Gradient Boosting (AdaBoost), and Light Gradient-Boosting Machine (LGBM)—using three benchmark datasets demonstrates the superior performance of DNN. It achieves outstanding accuracy, precision, recall, and F1-score metrics, all reaching 94.6% in cross-validation. Additionally, case studies involving numerous drug pairs confirm the reliability of DNN in accurately predicting unknown DDIs. These findings underscore DNN as a potent and reliable method for DDI prediction, with promising implications for drug discovery and healthcare applications.

Background: COVID-19 is a critical pandemic that has affected human communities worldwide, and there is an urgent need to develop effective drugs. Although there are a large number of candidate drug compounds that may be useful for treating COVID-19, the evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is necessary. Method: In this study, we applied the recently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of multiple lung cancer cell lines infected with severe acute respiratory syndrome coronavirus 2. We identified drug candidate compounds that significantly altered the expression of the 163 genes selected by TD-based unsupervised FE. Results: Numerous drugs were successfully screened, including many known antiviral drug compounds such as C646, chelerythrine chloride, canertinib, BX-795, sorafenib, sorafenib, QL-X-138, radicicol, A-443654, CGP-60474, alvocidib, mitoxantrone, QL-XII-47, geldanamycin, fluticasone, atorvastatin, quercetin, motexafin gadolinium, trovafloxacin, doxycycline, meloxicam, gentamicin, and dibromochloromethane. The screen also identified ivermectin, which was first identified as an anti-parasite drug and recently the drug was included in clinical trials for SARS-CoV-2. Conclusions: The drugs screened using our strategy may be effective candidates for treating patients with COVID-19.

To develop peptide drugs targeting integrin receptors, synthetic peptide ligands endowed with well-defined selective binding motifs are necessary. The snake venom KTS-containing disintegrins, that selectively block collagen α1β1 integrin, were used as lead compounds for the synthesis and structure-activity relationship of a series of linear peptides containing the KTS-pharmacophore and alternating natural amino acids and 3-aminobenzoic acid (MABA). To ensure a better stiffness and metabolic stability, one, two and three MABA residues, were introduced around the KTS pharmacophore motif. Molecular dynamics simulations have determined that the solution conformation of MABA peptide 4 is more compact, underwent larger conformational changes until convergence, and spent most of the time in a single cluster. The peptides’ binding affinity has been characterized by enzyme linked immunosorbent assay in which the most potent peptide 4 inhibited with IC50 of 324±8 µM and 550±45 µM the binding of GST-α1-A domain to collagen IV fragment CB3, and the cell adhesion to collagen IV using α1-overexpressor cells, respectively. Docking studies and MM-GBSA calculations confirmed that peptide 4 binds a smaller region of the integrin near the collagen- binding site and penetrated deeper into the binding site near Trp1. Peptide 4, inhibited tube formation by endothelial cell migration in the Matrigel angiogenesis in vitro assay. Peptide 4 was acutely tolerated by mice, showed stability in human serum, decreased tumor volume and angiogenesis, and significantly increased the survival of mice injected with B16 melanoma cells. These findings propose that MABA-peptide 4 can further serve as an α1β1-integrin antagonist lead compound for further drug-optimization in angiogenesis and cancer therapy.

Based on screening in computational biology and biological in vitro assays, five natural products isolated from extracts of the herbal medicine toad skin, such as cinobufagin (CBFi), bufalin (BFi), arenobufagin (ABFi), telocinobufagin (TBFi), bufotalin (BFTi), were subjected to molecular docking calculations with the use of SARS-CoV-2 main protease (PDB 6LU7 and 7BTF) and top-scoring ligand-receptor complexes were obtained. The results showed that the binding energy of ABFi to the 3CL protein was -17.044kcal/mol, which was higher than CBFi and TBFi. However, the binding energy of ABFi to the RdRp protease was -23.250 kcal/mol, which was much lower than that of CBFi and TBFi, EVEN lower than that of ABFi to the 3CL protein. ABFi also has polar interactions with amino acids such as Glu811, Ser814, Ser681 and Thr680 of RdRp enzyme. The results revealed that ABFi had a moderate inhibitory effect on the cell proliferation of SARS-CoV-2 in vitro, with an inhibition rate of 61.12%, even weaker than Remdesivir. This new discovery provides us with new ideas for in-depth studies on the development of natural products with this class of structural generalizations as inhibitors of SARS-CoV-2, and provides an experimental basis for the next step of mechanistic studies.

Neuropsychiatric manifestations of COVID-19 include delirium, general malaise, headache, and psychiatric symptoms. These manifestations are related to the neuroinflammatory response to viral antigens and proinflammatory mediators/immune cells. Tetracyclines, such as minocycline, have antibacterial and anti-inflammatory properties. Saiko-keishi-to, a traditional Japanese Kampo medicine, also has anti-inflammatory properties. Given the anti-inflammatory properties of minocycline and Saiko-keishi-to, we describe two cases of COVID-19 with prolonged headaches and general malaise successfully treated with these medications.

Nanoparticles have been used as a novel drug delivery system. Drug-incorporated nanoparticles for local delivery might optimize the efficacy and minimize the side effects of drugs. The efficacy and safety of intratracheal administration of prostacyclin analog (beraprost)-incorporated nanoparticles and imatinib, a PDGF-receptor tyrosine kinase inhibitor, -incorporated nanoparticles in Sugen-hypoxia-normoxia or monocrotaline rat models of PAH and in human PAH-pulmonary arterial smooth muscle cells have been reported. The use of inhaled drug-incorporated nanoparticles might be a novel approach for treatment of PAH.

The growing interest in Kv7.2/7.3 agonists originates from the involvement of these channels in several brain hyperexcitability disorders. In particular, Kv7.2/7.3 mutants have been clearly associated with epileptic encephalopathies (DEE) as well as with a spectrum of focal epilepsy disorders, often associated with developmental plateauing or regression. Nevertheless, there is a lack of available therapeutic options, considering that retigabine, the only molecule used in clinic as broad-spectrum Kv7 agonist, has been withdrawn from the market in the late 2016. This is why several efforts have been made both by both academia and industry in the search for suitable chemotypes acting as Kv7.2/7.3 agonists. In this context, in silico methods have played a major role, since the precise structures of different Kv7 homotetramers have been only recently disclosed. In the present review the computational methods used for the design of Kv.7.2/7.3 small molecule agonists and the underlying medicinal chemistry are discussed in the context of their biological and structure-function properties.

Neurodegenerative diseases (NDs) are a set of progressive, chronic, and incurable diseases characterized by the gradual loss of neurons, culminating in the decline of cognitive and/or motor functions. Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common NDs and represent an enormous burden both in terms of human suffering and economic cost. The available therapies for AD and PD only provide symptomatic and palliative relief for a limited period and are unable to modify the diseases’ progression. Over the last decades, research efforts have been focused on developing new pharmacological treatments for these NDs. However, to date, no breakthrough treatment has been discovered. Hence, the development of disease-modifying drugs able to halt or reverse the progression of NDs remains an unmet clinical need. This review summarizes the major hallmarks of AD and PD and the drugs available for pharmacological treatment. It also sheds light on potential directions that can be pursued to develop of new, disease-modifying drugs to treat AD and PD, thereby decreasing the social and economic burdens linked to these NDs.

Amitriptyline is a tricyclic antidepressant commonly used for depressive disorders and pre-scribed off-label for several neurological conditions like neuropathic pain, migraine and anxiety. Amitriptyline potentiates the monoaminergic transmission by blocking the reuptake of norepi-nephrine and serotonin. However, antidepressants also act on additional targets that contribute to either therapeutic or adverse effects and may suggest new indications for their repurposing. Furthermore, since depression is often a co-morbidity in patients with chronic conditions (i.e. cancer, neurodegenerative diseases) the use of antidepressants interfering with pathways in-volved in cell homeostasis may affect the progression and outcome of these pathologies. Here we investigate the effects of amitriptyline on proliferation and autophagy in human SH-SY5Y neuroblastoma cells. Dose and time-dependent upregulation of the autophagy markers LC3II and autophagy receptor p62, with accumulation of LAMP1 positive compartments, were observed in SH-SY5Y cells exposed to amitriptyline. Alteration of autophagy was accompanied by reduced cell viability and decreased clonogenic capacity, without a significant induction of apoptosis. Decrease viability and clonogenic activity were still observed in autophagy deficient Atg5 -/- MEF and following pre-treatment of SH-SY5Y culture with the autophagy inhibitor chloroquine suggesting that the amitriptyline’s effects on cell proliferation were not caused by the modulation of autophagy. Our findings demonstrate that amitriptyline acts on pathways that are crucial for cell and tissue homeostasis and pose the basis for further studies on the potential application of these effects and the consequences during long-term antidepressant treatment.

Knowing professionals’ attitudes is the basis for the development of skills for dealing with drug dependence. These attitudes may affect patients’ clinical safety and the cost-benefit ratio of the interventions. The goal of this study was to assess emergency and mental health nurses’ attitudes and perceptions towards alcoholics. A multicenter prospective descriptive study was conducted in six hospitals with 167 emergency and mental health nurses. Nurses classified alcoholics as sick individuals, although there was a tendency to feel comfortable working with them. Results indicated that these professionals had a rejecting attitude towards moderate alcohol consumption. We found a significant association between the attitude of the nurse and gender, with the degree of rejection towards the alcoholic being higher in men than in women and with less punitive attitudes in professionals from 0 to 11 years of professional experience.

Lactate, an important metabolic product, provides energy to neural cells during energy depletion or high demand and acts as a signaling molecule in the central nervous system. Recent studies revealed that lactate-mediated protein lactylation regulates gene transcription and influences cell fate, metabolic processes, inflammation, and immune responses. This review comprehensively examines the regulatory roles and mechanisms of lactylation in neurodevelopment, neuropsychiatric disorders, brain tumors, and cerebrovascular diseases. This analysis indicates that lactylation has multifaceted effects on central nervous system function and pathology, particularly in hypoxia-induced brain damage. Highlighting its potential as a novel therapeutic target, lactylation may play a significant role in treating neurological diseases. By summarizing current findings, this review aims to provide insights and guide future research and clinical strategies for central nervous system disorders.

In a rapidly evolving global landscape characterized by increased international travel, migration, and ecological shifts, this study sheds light on the emergence of protozoal and helminthic infections targeting the central nervous system (CNS) within Europe. Despite being traditionally associated with tropical regions, these infections are progressively becoming more prevalent in non-endemic areas. By scrutinizing the inherent risks, potential outcomes, and attendant challenges, this study underscores the intricate interplay between diagnostic limitations, susceptibility of specific population subsets, and the profound influence of climate fluctuations. The contemporary interconnectedness of societies serves as a conduit for the introduction and establishment of these infections, warranting comprehensive assessment. This study emphasizes the pivotal role of heightened clinician vigilance, judicious public health interventions, and synergistic research collaborations to mitigate the potential consequences of these infections. Though rare, their profound impact on morbidity and mortality underscores the collective urgency required to safeguard the neurological well-being of the European populace. Through this multifaceted approach, Europe can effectively navigate the complex terrain posed by these emergent infections.

Conclusions: Meningiomas with histopathological CNS invasion show a higher proliferative activity.

CD44 regulates cell adhesion, proliferation, survival, and stemness and has been considered a tumor therapy target. CD44 possesses the shortest CD44 standard (CD44s) and a variety of CD44 variant (CD44v) isoforms. Since the expression of CD44v is restricted in epithelial cells and carcinomas compared to CD44s, CD44v has been considered a promising target for monoclonal antibody (mAb) therapy. We previously developed an anti‐CD44v10 mAb, C44Mab-18 (IgM, kappa) to recognize the variant exon 10-encoded region. In the present study, a mouse IgG2a version of C44Mab-18 (C44Mab-18-mG2a) was generated to evaluate the antitumor activities against CD44-positive cells compared with previously established anti-pan CD44 mAb, C44Mab-46-mG2a. C44Mab-18-mG2a exhibited higher reactivity compared with C44Mab-46-mG2a to CD44v3–10-overexpressed CHO-K1 (CHO/CD44v3–10) and oral squamous cell carcinoma cell lines (HSC-2 and SAS) in flow cytometry. C44Mab-18-mG2a exerted a superior antibody‐dependent cellular cytotoxicity (ADCC) against CD44v3–10. In contrast, C44Mab-46-mG2a showed a superior complement‐dependent cytotoxicity (CDC) against CD44v3–10. A similar tendency was observed in ADCC and CDC against HSC-2 and SAS. Furthermore, administering C44Mab-18-mG2a or C44Mab-46-mG2a significantly suppressed CD44v3–10, HSC-2, and SAS xenograft tumor growth compared with the control mouse IgG2a. These results indicate that C44Mab-18-mG2a could be a promising therapeutic regimen for CD44v10-positive tumors.

Drug-induced liver injury (DILI) stands as a significant cause of drug attrition. To mitigate clinical DILI risks, assessing drugs using human liver models is crucial since animal studies may fall short due to species-specific liver pathway variations. Cell-based preclinical hepatotoxicity testing is often pertinent. In the present study, cells from a human liver cancer line (HepG2, HepaRG) were cultured in both formats of 2D and 3D spheroids to explore their responses to drugs. Liver-specific marker expressions across cell lines and culture formats were also examined to assess disparities in drug-induced liver injury marker expressions. In cytotoxicity assays, HepG2 cells exhibited heightened sensitivity to amiodarone HCl, while HepaRG cells showed greater sensitivity to acetaminophen. Generally, 2D cultures were more responsive to drugs than 3D cultures. Consistency was observed between cytotoxicity assays and liver injury markers AST and ALT. Variations were also noted in liver cell marker secretion, with albumin and urea concentrations declining post-drug treatment, particularly with higher baseline expression in HepaRG cells and 3D cultures. Additionally, mRNA expression levels of CYP enzymes involved in hepatocellular drug metabolism were compared following treatment with enzyme inducers. CYP1A2 and CYP2C9 were not expressed in HepG2 cells. On the other hand, CYP3A4 was expressed higher in 3D culture than in 2D culture. HepaRG cells exhibited significantly increased expression of all three enzymes post-treatment. Notably, enzyme expression was notably higher in 3D cultures than in 2D cultures. Collectively, these findings suggest that HepaRG cells and 3D cultures hold promise for evaluating DILI during early-stage drug development.

Cancer, characterized by abnormal cell proliferation driven by genetic mutations, remains a significant health challenge. Tailoring effective therapies depends on factors like tumor location, grade, and stage, alongside patient condition. Leveraging Nano-carrier encapsulated drugs offers a promising avenue, as they accumulate preferentially at tumor sites, enhancing therapeutic efficacy while mitigating side effects. Polymeric Nano-carriers, with their customizable properties, further optimize drug delivery efficiency and specificity. Incorporating active targeting ligands such as antibodies, carbohydrates, peptides, folates, and aptamers-onto polymeric nanoparticle surfaces through techniques like functionalization, adsorption, and conjugation plays a pivotal role in directing therapeutic agents to tumor cells. Consequently, polymeric nanoparticles emerge as the carrier of choice for delivering drugs to various tumor types, including breast, colon, lung, prostate, liver, and spleen tumors.

In a dynamic production processes, mechanical degradation poses a significant challenge, impacting product quality and process efficiency. This paper explores a novel approach for monitoring degradation in the context of viscose fiber production, a highly dynamic manufacturing process. Using causal discovery techniques, our method allows domain experts to incorporate background knowledge into the creation of causal graphs. Further, it enhances the interpretability and increases the ability to identify potential problems via changes in causal relations over time. The case study employs a comprehensive analysis of the viscose fiber production process within a prominent textile industry, emphasizing the advantages of causal discovery for monitoring degradation. The results are compared with state-of-the-art methods, which are not considered to be interpretable, specifically LSTM-based autoencoders, showcasing the alignment and validation of our approach. This paper provides valuable information on degradation monitoring strategies, demonstrating the efficacy of causal discovery in dynamic manufacturing environments. The findings contribute to the evolving landscape of process optimization and quality control.

Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modelling of gene expression networks that involve large amounts of data. The integration of data from DNA, RNA, and protein activities has resemblance to pharmacogenomics, which is of utmost importance in the development of cancer drugs. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Expanding the study and application of functional genomics has great promise to advance the process of discovering and repurposing drugs, especially in the field of oncology.

Glioblastoma (GBL) is one of the more malignant primary brain tumors, currently treated by a multimodality strategy including surgery, radio- and chemotherapy, mainly consisting of Temozolomide(TMZ)-based chemotherapy. Tumor relapse often occurs due to the establishment of TMZ resistance, with a patient median survival <2 years. The identification of natural molecules having strong anti-tumor activity, led to combine these compounds with conventional chemotherapeutic agents, developing protocols of integrated anticancer therapies. Curcumin (CUR), Resveratrol (RES), and its glucoside Polydatin (PLD) are widely employed in the pharmaceutical and nutraceutical fields, and several studies demonstrated that the combination of these natural products was more cytotoxic than the single compound alone in different cancers. Some of us recently demonstrated the synergistic efficacy of the sublingual administration of a new nutraceutical formulation of CUR+PLD in reducing tumor size and improving GBL patient survival. To deepen some mechanistic aspects of these results, we investigated if the pretreatment with a combination of CUR+PLD, can improve TMZ cytotoxicity on GBL cells, by analyzing the effects on cell cycle, viability and morphology, on proteins related to cell proliferation, differentiation, apoptosis or autophagy, and on actin network. Cell viability was assessed by MTT or by the cell counter CytoSmart. CalcuSyn software was used to study the CUR+PLD synergism. Morphology was evaluated by optical and scanning electron microscopy, and protein expression was analyzed by Western Blot. Flow cytometry was used for cell cycle, autophagic flux, and apoptosis analyses. The results obtained provide evidence that CUR and PLD, acting in synergy with each other, strongly improve the efficacy of alkylating antitumor agents such as TMZ, also in drug-resistant GBL cells, through their abilities to affect survival, differentiation, and tumor invasiveness.

In this review we aim to address the current status of phage therapy in the management of multidrug-resistant infections, from compassionate use cases to ongoing clinical trials, as well as the challenges this approach presents in the particular context of CF patients.

In the mammalian isocortex CD44, a cell surface receptor for extracellular matrix molecules, is present in pial-based and fibrous astrocytes of white matter, but not the protoplasmic astrocytes. In the hominid isocortex, CD44+ astrocytes comprise the subpial “interlaminar” astrocytes, sending long processes into the cortex. The hippocampus also contains similar astrocytes. We have examined all levels of the human CNS and found CD44+ astrocytes in every region. Astrocytes in white matter and astrocytes that interact with large blood vessels, but not capillaries in gray matter, are CD44+, the latter extending long processes into the parenchyma. Motor neurons in the brainstem and spinal cord, such as oculomotor, facial, hypoglossal, and in the anterior horn of the spinal cord, are surrounded by CD44+ processes, contrasting with neurons in the cortex, basal ganglia and thalamus. We found CD44+ processes that intercalate between ependymal cells to reach the ventricle and that show a location-specific presence. We also found a CD44+ astrocyte in the molecular layer of the cerebellar cortex. Protoplasmic astrocytes, which do not normally contain CD44, acquire it in pathologies like hypoxia and seizures.