Charge-switchable cell-penetrating peptides for rerouting nanoparticles to glioblastoma treatment.

Glioblastoma (GB) is one of the most lethal types of neoplasms with unique anatomic, physiologic, and pathologic features that usually persist after exposure to standard therapeutic modalities. It is biologically aggressive, and the existence of the blood-brain barrier (BBB) limits the efficacy of standard therapies. In this work, we hypothesize the potential of surface-functionalized ultra-small nanostructured lipid carriers (usNLCs) with charge-switchable cell-penetrating peptides (CPPs) to overcome this biological barrier and improve targeted delivery to brain tumor tissues.

A Stepwise Framework for the Systematic Development of Lipid Nanoparticles.

A properly designed nanosystem aims to deliver an optimized concentration of the active pharmaceutical ingredient (API) at the site of action, resulting in a therapeutic response with reduced adverse effects. Due to the vast availability of lipids and surfactants, producing stable lipid dispersions is a double-edged sword: on the one hand, the versatility of composition allows for a refined design and tuning of properties; on the other hand, the complexity of the materials and their physical interactions often result in laborious and time-consuming pre-formulation studies. However, how can they be tailored, and which premises are required for a "right at first time" development? Here, a stepwise framework encompassing the sequential stages of nanoparticle production for disulfiram delivery is presented.

Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors.

Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and development, providing advanced tools for promoting cost-effectiveness throughout drug life cycle. Specifically, AI brings together the potential to improve drug approval rates, reduce development costs, get medications to patients faster, and help patients complying with their treatments. Accelerated pharmaceutical development and drug product approval rates can further benefit from the quantum computing (QC) technology, which will ultimately enable larger profits from patent-protected market exclusivity.

Female Voice-Related Sexual Attractiveness to Males: Does it Vary With Different Degrees of Conception Likelihood?

Previous investigations have found that female voice-related attractiveness to males increases when both conception likelihood (CL) and voice fundamental frequency (f) are elevated. To test this hypothesis, we conducted a perceptual experiment where 78 heterosexual males rated sexual attractiveness of 9 female voice samples, recorded at menstrual, follicular and luteal phases of the menstrual cycle under two double-blinded randomly allocated conditions: a natural menstrual cycle (placebo condition) and when using an oral contraceptive pill (OCP condition). The voice samples yielded a total of 54 stimuli that were visually sorted and rated using Visor software.

Sorting hidden patterns in nanoparticle performance for glioblastoma using machine learning algorithms.

Cationic compounds have been described to readily penetrate cell membranes. Assigning positive charge to nanosystems, e.g.

Diving into Batch-to-Batch Variability of Topical Products-a Regulatory Bottleneck.

Purpose: Following the recent European Medicine Agency (EMA) draft guideline on quality and equivalence of topical products, a modular framework for bioequivalence assessment is proposed, wherein the qualitative, quantitative, microstructure and product performance sameness is demanded to support generic applications. Strict regulatory limits are now imposed, but, the suitability of these limits has been subject of intense debate. In this context, this paper aims to address these issues by characterizing a panel of 8 reference blockbuster semisolid topical products.

Peptide-lipid nanoconstructs act site-specifically towards glioblastoma growth impairment.

Ultra-small nanostructured lipid carriers (usNLCs) have been hypothesized to promote site-specific glioblastoma (GB) drug delivery. Envisioning a multitarget purpose towards tumor cells and microenvironment, a surface-bioconjugated usNLC prototype is herein presented. The comeback of co-delivery by repurposing atorvastatin and curcumin, as complementary therapy, was unveiled and characterized, considering colloidal properties, stability, and drug release behavior.

Biomimeting ultra-small lipid nanoconstructs for glioblastoma treatment: A computationally guided experimental approach.

Ultra-small nanostructured lipid carriers (usNLCs) are stable, biocompatible and biodegradable colloidal systems, claiming a broad set of advanced features suitable for cancer drug delivery. To unleash their potential in glioblastoma research and therapy, we have developed an usNLC prototype able to co-encapsulate atorvastatin calcium and curcumin, as repurposed drugs previously screened from molecular dynamics simulations. The novelty not only relies on the drug repositioning approach, but also on a robust computational methodology utilized for formulation optimization, under the umbrella of multivariate analysis and full factorial designs.

Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns.

Computational Chemistry is currently a synergistic assembly between calculations, simulation, machine learning (ML) and optimization strategies for describing, solving and predicting chemical data and related phenomena. These include accelerated literature searches, analysis and prediction of physical and quantum chemical properties, transition states, chemical structures, chemical reactions, and also new catalysts and drug candidates. The generalization of scalability to larger chemical problems, rather than specialization, is now the main principle for transforming chemical tasks in multiple fronts, for which systematic and cost-effective solutions have benefited from ML approaches, including those based on deep learning (e.

Aptamer-peptide conjugates as a new strategy to modulate human α-thrombin binding affinity.

Aptamers are single-stranded RNA or DNA molecules that specifically recognize their targets and have proven valuable for functionalizing sensitive biosensors. α-thrombin is a trypsin-like serine proteinase which plays a crucial role in haemostasis and thrombosis. An abnormal activity or overexpression of this protein is associated with a variety of diseases.

Computational Approaches in Theranostics: Mining and Predicting Cancer Data.

The ability to understand the complexity of cancer-related data has been prompted by the applications of (1) computer and data sciences, including data mining, predictive analytics, machine learning, and artificial intelligence, and (2) advances in imaging technology and probe development. Computational modelling and simulation are systematic and cost-effective tools able to identify important temporal/spatial patterns (and relationships), characterize distinct molecular features of cancer states, and address other relevant aspects, including tumor detection and heterogeneity, progression and metastasis, and drug resistance. These approaches have provided invaluable insights for improving the experimental design of therapeutic delivery systems and for increasing the translational value of the results obtained from early and preclinical studies.

Hydrogel-Based Drug Delivery Nanosystems for the Treatment of Brain Tumors.

Chemotherapy is commonly associated with limited effectiveness and unwanted side effects in normal cells and tissues, due to the lack of specificity of therapeutic agents to cancer cells when systemically administered. In brain tumors, the existence of both physiological barriers that protect tumor cells and complex resistance mechanisms to anticancer drugs are additional obstacles that hamper a successful course of chemotherapy, thus resulting in high treatment failure rates. Several potential surrogate therapies have been developed so far.

Host flexibility and space filling in supramolecular complexation of cyclodextrins: A free-energy-oriented approach.

Cyclodextrins (Cds) are versatile carbohydrate hosts for developing multifunctional nanostructures of pharmaceutical interest. Factors affecting the thermodynamic signatures and stability of β- and γ-Cd complexes are detailed at the atomic level. The MD/PMF-based method is combined with the description of the nature and strength of the inter-partner affinity.

Adsorption of charged macromolecules upon multicomponent responsive surfaces.

Adsorption of polyions onto charged surfaces has long been recognized as a crucial phenomenon in biological and technological applications. An intuitive model relating polyelectrolyte adsorption with the imposed features of polarizable surfaces of different compositions and charges is proposed based on Monte Carlo simulations using a coarse-grained approach. The excellent performance of the equation allows simultaneously describing a wide range of adsorption regimes and accounting for specific non-monotonic trends.

Combining Cellulose and Cyclodextrins: Fascinating Designs for Materials and Pharmaceutics.

Cellulose and cyclodextrins possess unique properties that can be tailored, combined, and used in a considerable number of applications, including textiles, coatings, sensors, and drug delivery systems. Successfully structuring and applying cellulose and cyclodextrins conjugates requires a deep understanding of the relation between structural, and soft matter behavior, materials, energy, and function. This review focuses on the key advances in developing materials based on these conjugates.

Unstructured Formulation Data Analysis for the Optimization of Lipid Nanoparticle Drug Delivery Vehicles.

Designing nanoparticle formulations with features tailored to their therapeutic targets in demanding timelines assumes increased importance. In this context, nanostructured lipid carriers (NLCs) offer an excellent example of a drug delivery nanosystem that has been broadly explored in the treatment of glioblastoma multiforme (GBM). Distinct fundamental NLC quality attributes can be harnessed to fit this purpose, namely particle size, size distribution, and zeta potential.

Exploring PAZ/3'-overhang interaction to improve siRNA specificity. A combined experimental and modeling study.

The understanding of the dynamical and mechanistic aspects that lie behind siRNA-based gene regulation is a requisite to boost the performance of siRNA therapeutics. A systematic experimental and computational study on the 3'-overhang structural requirements for the design of more specific and potent siRNA molecules was carried out using nucleotide analogues differing in structural parameters, such as sugar constraint, lack of nucleobase, distance between the phosphodiester backbone and nucleobase, enantioselectivity, and steric hindrance. The results established a set of rules governing the siRNA-mediated silencing, indicating that the thermodynamic stability of the 5'-end is a crucial determinant for antisense-mediated silencing but is not sufficient to avoid sense-mediated silencing.

Modeling of ultra-small lipid nanoparticle surface charge for targeting glioblastoma.

Surface modification of ultra-small nanostructured lipid carriers (usNLC) via introduction of a positive charge is hypothesized to prompt site-specific drug delivery for glioblastoma multiforme (GBM) treatment. A more effective interaction with negatively charged lipid bilayers, including the blood-brain barrier (BBB), will facilitate the nanoparticle access to the brain. For this purpose, usNLC with a particle size of 43.

Computational modeling in glioblastoma: from the prediction of blood-brain barrier permeability to the simulation of tumor behavior.

The integrated in silico-in vitro-in vivo approaches have fostered the development of new treatment strategies for glioblastoma patients and improved diagnosis, establishing the bridge between biochemical research and clinical practice. These approaches have provided new insights on the identification of bioactive compounds and on the complex mechanisms underlying the interactions among glioblastoma cells, and the tumor microenvironment. This review focuses on the key advances pertaining to computational modeling in glioblastoma, including predictive data on drug permeability across the blood-brain barrier, tumor growth and treatment responses.

Reconstructing the historical synthesis of mauveine from Perkin and Caro: procedure and details.

Mauveine, an iconic dye, first synthesised in 1856 still has secrets to unveil. If nowadays one wanted to prepare the original Perkin's mauveine, what would be the procedure? It will be described in this work and lies on the use of a 1:2:1 (mole) ratio of aniline, p-toluidine and o-toluidine. This was found from a comparison of a series of products synthesized from different proportions of these starting materials, with a set of historical samples of mauveine and further analysed with two unsupervised chemometrics methods.

Free-energy patterns in inclusion complexes: the relevance of non-included moieties in the stability constants.

Inclusion complexes play a definite role in a variety of applications, ranging from drug solubilization to smart materials. This work presents a series of studies based on molecular dynamics, including potential of mean force calculations, and aiming at understanding the factors that govern inclusion. Naphthalene and its derivatives are used as guests for a common host, β-cyclodextrin.

Novel serine-based gemini surfactants as chemical permeation enhancers of local anesthetics: A comprehensive study on structure-activity relationships, molecular dynamics and dermal delivery.

This work aims at studying the efficacy of a series of novel biocompatible, serine-based surfactants as chemical permeation enhancers for two different local anesthetics, tetracaine and ropivacaine, combining an experimental and computational approach. The surfactants consist of gemini molecules structurally related, but with variations in headgroup charge (nonionic vs. cationic) and in the hydrocarbon chain lengths (main and spacer chains).

Lysine-based surfactants as chemical permeation enhancers for dermal delivery of local anesthetics.

The aim of this study is to investigate the efficacy of new, biocompatible, lysine-based surfactants as chemical permeation enhancers for two different local anesthetics, tetracaine and ropivacaine hydrochloride, topically administered. Results show that this class of surfactants strongly influences permeation, especially in the case of the hydrophilic and ionized drug, ropivacaine hydrochloride, that is not easily administered through the stratum corneum. It is also seen that the selected permeation enhancers do not have significant deleterious effects on the skin structure.

Improving discrimination in the grading of rat mammary tumors using two-dimensional mapping of histopathological observations.

This work aims at characterizing rat mammary tumors induced by 7,12-dimethylbenz(a)anthracene (DMBA) and the respective malignancy potential, commonly graded with histopathology features grouped by intensity levels. Tumors were described over fourteen multiple ranged microscopic parameters and a comprehensive characterization of the histological patterns and their relation with tumor grade was carried out by principal component analysis (PCA). The number of histological patterns present on a tumor tends to correlate with malignant features.

A new perspective on correlated polyelectrolyte adsorption: positioning, conformation, and patterns.

This work focuses on multiple chain deposition, using a coarse-grained model. The phenomenon is assessed from a novel perspective which emphasizes the conformation and relative arrangement of the deposited chains. Variations in chain number and length are considered, and the surface charge in the different systems ranges from partially neutralized to reversed by backbone deposition.