The Hill equation: a review of its capabilities in pharmacological modelling

Entrance channels to coproheme in coproporphyrin ferrochelatase probed by exogenous imidazole binding

Iron insertion into porphyrins is an essential step in heme biosynthesis. In the coproporphyrin-dependent pathway, specific to monoderm bacteria, this reaction is catalyzed by the monomeric enzyme coproporphyrin ferrochelatase. In addition to the mechanistic details of the metalation of the porphyrin, the identification of the substrate access channel for ferrous iron to the active site is important to fully understand this enzymatic system. In fact, whether the iron reaches the active site from the distal or the proximal porphyrin side is still under debate. In this study we have thoroughly addressed this question in Listeria monocytogenes coproporphyrin ferrochelatase by X-ray crystallography, steady-state and pre-steady-state imidazole ligand binding studies, together with a detailed spectroscopic characterization using resonance Raman and UV-vis absorption spectroscopies in solution. Analysis of the X-ray structures of coproporphyrin ferrochelatase-coproporphyrin III crystals soaked with ferrous iron shows that iron is present on both sides of the porphyrin. The kinetic and spectroscopic study of imidazole binding to coproporphyrin ferrochelatase‑iron coproporphyrin III clearly indicates the presence of two possible binding sites in this monomeric enzyme that influence each other, which is confirmed by the observed cooperativity at steady-state and a biphasic behavior in the pre-steady-state experiments. The current results are discussed in the context of the entire heme biosynthetic pathway and pave the way for future studies focusing on protein-protein interactions.

Exploring Fe(III) coordination and membrane interaction of a siderophore-peptide conjugate: Enhancing synergistically the antimicrobial activity

Many microbes produce siderophores, which are extremely potent weapons capable of stealing iron ions from human tissues, fluids and cells and transferring them into bacteria through their appropriate porins. We have recently designed a multi-block molecule, each block having a dedicated role. The first component is an antimicrobial peptide, whose good effectiveness against some bacterial strains was gradually improved through interactive sequence modifications. Connected to this block is a flexible bio-band, also optimized in length, which terminates in a hydroxyamide unit, a strong metal binder. Thus, the whole molecule brings together two pieces that work synergistically to fight infection. To understand if the peptide unit, although modified with a long tail, preserves the structure and therefore the antimicrobial activity, and to characterize the mechanism of interaction with bio-membrane models mimicking Gram-negative membranes, we performed a set of fluorescence-based experiments and circular dichroism studies, which further supported our design of a combination of two different entities working synergistically. The chelating activity and iron(III) binding of the peptide was confirmed by iron(III) paramagnetic NMR analyses, and through a competitive assay with ethylenediamine-tetra acetic acid by ultraviolet-visible spectroscopy. The complexation parameters, the Michaelis constant K, and the number of sites n, evaluated with spectrophotometric techniques are confirmed by Fe(III) paramagnetic NMR analyses here reported. In conclusion, we showed that the coupling of antimicrobial capabilities with iron-trapping capabilities works well in the treatment of infectious diseases caused by Gram-negative pathogens.

Development towards a novel screening method for nipecotic acid bioisosteres using molecular imprinted polymers (MIPs) as alternative to in vitro cellular uptake assays

Impaired expression of GABA transporters (GATs) is closely related to the pathogenesis of among others Parkinson's disease and epilepsy. As such, lipophilic nipecotic acid analogs have been extensively studied as GAT1-addressing drugs and radioligands but suffer from limited brain uptake due to the zwitterionic properties of the nipecotic acid moiety. Bioisosteric replacement of the carboxylic acid group is a promising strategy to improve the brain uptake, though it requires knowledge on the binding of these isosteres to GAT1. To screen nipecotic acid isosteres for their affinity to GAT1 in a time- and cost-effective manner, this research aims to develop a molecular imprinted polymer (MIP) that mimics the natural binding site of GAT1 and can act as an alternative screening tool to the current radiometric and mass spectrometry cellular-based assays. To this end, a nipecotic acid MIP was created using the electropolymerization of ortho-phenylenediamine (oPD) by cyclic voltammetry (CV). The optimization of the generated receptor layer was achieved by varying the scan rate (50-250 mV/s) and number of CV cycles (5-12), yielding an optimized MIP with an average imprinting factor of 2.6, a linear range of 1-1000 nm, and a theoretical LOD of 0.05 nm, as analyzed by electrical impedance spectroscopy (EIS). Selectivity studies facilitated the investigation of major binding interactions between the MIP and the substrate, building an experimental model that compares characteristics of various analogs. Results from this model indicate that the substrate carboxylic acid group plays a more important role in binding than an amine group, after comparing the binding of cyclohexanecarboxylic acid (average IF of 1.7) and piperidine (average IF of 0.46). The research culminates in a discussion regarding the feasibility of the in vitro model, comparing the synthetic system against the biological performance of GAT1. Thus, evaluating if it is possible to generate a synthetic GAT1 mimic, and if so, provide directions for follow-up research.

Preparation of imidazolium ionic liquid functionalized paper membrane for selective extraction of caffeic acid and its structural and functional analogues from Taraxaci Herba

In the search for pharmaceutically active compounds from natural products, it is crucial and challenging to develop separation or purification methods that target not only structurally similar compounds but also those with specific pharmaceutical functions. The adsorption-based method is widely employed in this field and holds potential for this application, given the diverse range of functional monomers that can be chosen based on structural or functional selectivity. In this work, an imidazolium ionic liquid (IL) modified paper membrane was synthesized via microwave reaction. Caffeic acid (CA), with potential interactions with imidazolium IL and a representative component of phenolic acids in Taraxaci Herba, was chosen as a target compound. After optimization of synthesis and extraction parameters, the resulting extraction membrane could be used to quantitatively analyze CA at ng/ml level, and to extract CA's analogues from the sample matrix. Cheminformatics confirmed the presence of structural and functional similarity among these extracted compounds. This study offers a novel approach to preparing a readily synthesized extraction membrane capable of isolating compounds with structural and functional analogies, as well as developing a membrane solid-phase extraction-based analytical method for natural products.

Repurposing an antimicrobial peptide for the development of a dual ion channel/molecular receptor-like platform for metal ion detection

The presence of non-essential metals in the environment as contaminants is prone to cause hazardous health problems following accumulation in the human body and the ensuing toxic effects. This calls for continuous discovery and innovation in the realm of developing easy-to-operate, cheap and sensitive sensors. Herein, we describe the proof of concept approach for designing a molecular receptor-like, chimeric sensor based on the pore-forming peptide alamethicin (Alm), tethered via a linker with an ultrashort peptide nucleic acid (PNA) moiety, capable of generating functional ion channel oligomers in planar lipid membranes. The working principle of the sensor exploits the ability of Hg2+ ions to complex mismatching thymine-thymine sequences between the PNA receptor moiety on Alm oligomers and free, thymine-based, single-stranded DNAs (ssDNAs) in solution, thus creating a stable base pair at the oligomer entrance. This generates a transducing mechanism which converts the metal ion complexation into a specific electrical signature of the self-assembled Alm oligomers, enabling selective Hg2+ ion detection. The platform is programmable, whereby the simple exchange of the PNA sequence and its ssDNA counterpart in solution rendered the system selective for Cu2+ ion detection. With further optimization, the presented solution has the potential to translate into miniaturized, cost-effective biosensors suitable for the real-time, label-free and continuous detection of metal ions or other biomolecules.

Best Practices for Development and Validation of Enzymatic Activity Assays to Support Drug Development for Inborn Errors of Metabolism and Biomarker Assessment

Aberrant or dysfunctional cellular enzymes are responsible for a wide range of diseases including cancer, neurodegenerative conditions, and metabolic disorders. Deficiencies in enzyme level or biofunction may lead to intracellular accumulation of substrate to toxic levels and interfere with overall cellular function, ultimately leading to cell damage, disease, and death. Marketed therapeutic interventions for inherited monogenic enzyme deficiency disorders include enzyme replacement therapy and small molecule chaperones. Novel approaches of in vivo gene therapy and ex vivo cell therapy are under clinical evaluation and provide promising opportunities to expand the number of available disease-modifying treatments. To support the development of these different therapeutics, assays to quantify the functional activity of protein enzymes have gained importance in the diagnosis of disease, assessment of pharmacokinetics and pharmacodynamic response, and evaluation of drug efficacy. In this review, we discuss the technical aspects of enzyme activity assays in the bioanalytical context, including assay design and format as well as the unique challenges and considerations associated with assay development, validation, and life cycle management.

Spectroscopic and solution properties characterization of quaternary ammonium ion containing polycations complexed with fluorescent rhodamine sulfonic acid dyes

Based on the growing range of applications for polycations in research and commercial materials, a continuing need exists to advance the fundamental knowledge and understanding of this class of materials. Spectroscopic and solution properties characterizations of noncovalently labeled, fluorescent Alexa Fluor® dye complexes of two commercial polycations, poly(2-(trimethylamino) ethyl methacrylate) monocation and poly[bis[2-chloroethyl] ether-alt-1,3-bis[3-(dimethylamino) propyl] urea] dication are reported to help address this need. A variety of fluorescence spectroscopic methods are used with a special emphasis on fluorescence correlation spectroscopy (FCS) which is applied to characterize the Stokes radius (RS) and equilibrium dissociation constants (Kd) of dye-polycation complexes at nanomolar dye concentrations. Resulting RS values indicate dye binding to individual polycation chains. Measured Kd values in the sub-micromolar range are consistent with strong dye binding. Increasing solution ionic strength with sodium chloride addition inhibits dye binding and decreases the RS of dye-polycation complexes due to size collapse of polycation chains. The complexes differ in their solution stability to ionic strength changes suggesting that both electrostatic and hydrophobic binding interactions influence dye binding. This study establishes the viability of noncovalent dye-polycation complexation in concert with FCS characterization as a general approach for investigating the properties of quaternary ammonium ion containing polycations in aqueous solution.

Quantitative Effects of the Loop Region on Topology, Thermodynamics, and Cation Binding of DNA G-quadruplexes

The thermal stability of G-quadruplexes is important for their biological roles. G-quadruplexes are stable in the presence of cations such as K+ and Na+ because these cations coordinate in the G-quartet of four guanine bases. It is well known that the number of G-quartets and the configuration of the guanine bases affect the binding affinity of the cation. Recently, structures formed in the loop regions connecting the guanine stretches have attracted significant attention, because the loop region affects G-quadruplex properties, such as topology, thermal stability, and interactions with proteins and small molecules. Considering these effects, the loop region can also affect the binding affinity of the cations. Here, we designed a series of G-quadruplex-forming DNA sequences that contain a hairpin in a loop region and investigated the effects of the sequence and structure of the loop region on the cation binding affinity as well as the thermal stability of the G-quadruplex as a whole. First, structural analysis of the DNA sequences showed that the hairpin at the loop plays a key role in determining G4 topology (strand orientation). Second, in the case of the G-quadruplexes with the hairpin-forming loop region, it was found that a longer loop length led to a higher thermodynamic stability of the G-quadruplex as well as higher cation binding affinity. In contrast, an unstructured loop region did not lead to such effects. Interestingly, the cation binding affinity was correlated to the thermodynamic stability of the hairpin structure at the loop region. It was quantitatively demonstrated that the stable loop region stabilized the whole G-quadruplex structure, which induced higher cation binding affinity. These systematic and quantitative results showed that the loop region is one of the determinants of cation binding and expanded the possibilities of drug development targeting G4s by stabilizing the loop region.

Cytotoxicity and toxicoproteomics analysis of thiazolidinedione exposure in human-derived cardiomyocytes

Thiazolidinediones (TZDs) (e.g. pioglitazone and rosiglitazone), known insulin sensitiser agents for type II diabetes mellitus, exhibit controversial effects on cardiac tissue. Despite consensus on their association with increased heart failure risk, limiting TZD use in diabetes management, the underlying mechanisms remain uncharacterised. Herein, we report a comprehensive in vitro investigation utilising a novel toxicoproteomics pipeline coupled with cytotoxicity assays in human adult cardiomyocytes to elucidate mechanistic insights into TZD cardiotoxicity. The cytotoxicity assay findings showed a significant loss of mitochondrial adenosine triphosphate production upon exposure to either TZD agents, which may underpin TZD cardiotoxicity. Our toxicoproteomics analysis revealed that mitochondrial dysfunction primarily stems from oxidative phosphorylation impairment, with distinct signalling mechanisms observed for both agents. The type of cell death differed strikingly between the two agents, with rosiglitazone exhibiting features of caspase-dependent apoptosis and pioglitazone implicating mitochondrial-mediated necroptosis, as evidenced by the protein upregulation in the phosphoglycerate mutase family 5-dynamin-related protein 1 axis. Furthermore, our analysis revealed additional mechanistic aspects of cardiotoxicity, showcasing drug specificity. The downregulation of various proteins involved in protein machinery and protein processing in the endoplasmic reticulum was observed in rosiglitazone-treated cells, implicating proteostasis in the rosiglitazone cardiotoxicity. Regarding pioglitazone, the findings suggested the potential activation of the interplay between the complement and coagulation systems and the disruption of the cytoskeletal architecture, which was primarily mediated through the integrin-signalling pathways responsible for pioglitazone-induced myocardial contractile failure. Collectively, this study unlocks substantial mechanistic insight into TZD cardiotoxicity, providing the rationale for future optimisation of antidiabetic therapies.

Binaphthalene-Assisted Axial Chirality in Porphyrins: Toward Solid-State Circularly Polarized Luminescence from Self-Assembled Nanostructures

Circularly polarized luminescence (CPL) is emerging as an effective tool to study the excited-state optical activity in molecules and their self-assembled nanostructures. Chiral porphyrins are a class of optically active molecules wherein the ground-state chirality has been extensively studied in recent times using circular dichroism (CD) spectroscopy. However, obtaining CPL from porphyrin nanostructures, which would have vast implications in biological applications, has remained an uphill task. In this work, we design and synthesize a pair of chiral porphyrin enantiomers functionalized by axially chiral binaphthalene units at the four meso-positions. The molecule undergoes self-assembly following an isodesmic polymerization model, leading to the formation of a spherical nanostructure possessing opposite chirality. Favorable thermodynamic parameters achieved through the controlled experimental conditions helped drive the self-assembly in the forward direction. The limitations imposed by a large nonradiative decay constant arising due to the aggregation-induced quenching could be overcome by fabricating self-standing polymeric films of the nanostructures. The films exhibited relatively high radiative decay and, more interestingly, good CPL activity with clear mirror image spectra for the nanostructures with opposite chirality. The work on CPL-active solid-state materials opens avenue for the design and synthesis of a variety of porphyrin-based chromophoric systems and their nanoaggregates that can find potential application in the field of chiral biosensing and bioimaging, security tags, and display devices.

Drug-loaded nanoparticles for cancer therapy: a high-throughput multicellular agent-based modeling study

Interactions between biological systems and engineered nanomaterials have become an important area of study due to the application of nanomaterials in medicine. In particular, the application of nanomaterials for cancer diagnosis or treatment presents a challenging opportunity due to the complex biology of this disease spanning multiple time and spatial scales. A system-level analysis would benefit from mathematical modeling and computational simulation to explore the interactions between anticancer drug-loaded nanoparticles (NPs), cells, and tissues, and the associated parameters driving this system and a patient's overall response. Although a number of models have explored these interactions in the past, few have focused on simulating individual cell-NP interactions. This study develops a multicellular agent-based model of cancer nanotherapy that simulates NP internalization, drug release within the cell cytoplasm, "inheritance" of NPs by daughter cells at cell division, cell pharmacodynamic response to the intracellular drug, and overall drug effect on tumor dynamics. A large-scale parallel computational framework is used to investigate the impact of pharmacokinetic design parameters (NP internalization rate, NP decay rate, anticancer drug release rate) and therapeutic strategies (NP doses and injection frequency) on the tumor dynamics. In particular, through the exploration of NP "inheritance" at cell division, the results indicate that cancer treatment may be improved when NPs are inherited at cell division for cytotoxic chemotherapy. Moreover, smaller dosage of cytostatic chemotherapy may also improve inhibition of tumor growth when cell division is not completely inhibited. This work suggests that slow delivery by "heritable" NPs can drive new dimensions of nanotherapy design for more sustained therapeutic response.

Prediction of in-vitro dissolution and tablet hardness from optical porosity measurements

Advanced manufacturing technologies such as continuous processing require fast information on the quality of intermediates and products. Process analytical technologies (PAT) to monitor many critical quality attributes (CQAs) have been developed and successfully implemented in pharmaceutical industry. However, there are some CQAs, which still have to be measured off-line with significant effort due to the lack of suitable PAT sensors. Two prominent examples are the in-vitro dissolution and the tablet hardness. Both are obtained via destructive measurement, and the dissolution is tedious and time-consuming to determine. In this study, these two CQAs were predicted via correlation with the optical porosity of tablets. The optical porosity was measured via a novel combination of gas in scattering media absorption spectroscopy (GASMAS) and photon time of flight spectroscopy (pTOFS) with a SpectraPore instrument. The approach was tested in a continuous tableting line and showed promising results in predicting the amount of drug released after specific dissolution times as well as the tablet hardness. This indicates that the measurement of optical porosity can support control strategies within the real-time release testing (RTRT) concept.

Synthesis and characterization of 2-(anthracene-9-yl)-4,5-diphenyl-1H-imidazole derivatives as environmentally sensitive fluorophores

2-(Anthracene-9-yl)-4,5-diphenyl-1H-imidazole (ADPI) provides an intriguing molecular platform for developing organic fluorophores with diverse properties and fluorescence performances. However, derivatives of ADPI have not yet been well explored and extensive studies are warranted. To shed more light on this, we have synthesized a series of π-extended ADPIs through a concise synthetic route involving an efficient cross-condensation reaction followed by Pd-catalyzed Suzuki cross-coupling. The obtained compounds were subjected to X-ray single crystallographic analysis to understand their molecular conformational and solid-state packing properties. Furthermore, UV-Vis absorption and fluorescence spectroscopic analyses were conducted. Our experimental results have disclosed interesting solvatofluorochromic properties of these compounds which are useful for solvent polarity-sensitive applications. The presence of an amphoteric imidazolyl group in the ADPI derivatives also renders them sensitive fluorescence responses to strong protic acids (e.g., trifluoroacetic acid) as well as fluoride anion. It transpires that the fluorescence changes are dependent on the functional groups attached to the ADPI core, suggesting a bottom-up molecular tuning approach for development of fluorophores and chemosensors with diverse functions.

Graphene Multiplexed Sensor for Point-of-Need Viral Wastewater-Based Epidemiology

Wastewater-based epidemiology (WBE) can help mitigate the spread of respiratory infections through the early detection of viruses, pathogens, and other biomarkers in human waste. The need for sample collection, shipping, and testing facilities drives up the cost of WBE and hinders its use for rapid detection and isolation in environments with small populations and in low-resource settings. Given the ubiquitousness and regular outbreaks of respiratory syncytial virus, SARS-CoV-2, and various influenza strains, there is a rising need for a low-cost and easy-to-use biosensing platform to detect these viruses locally before outbreaks can occur and monitor their progression. To this end, we have developed an easy-to-use, cost-effective, multiplexed platform able to detect viral loads in wastewater with several orders of magnitude lower limit of detection than that of mass spectrometry. This is enabled by wafer-scale production and aptamers preattached with linker molecules, producing 44 chips at once. Each chip can simultaneously detect four target analytes using 20 transistors segregated into four sets of five for each analyte to allow for immediate statistical analysis. We show our platform's ability to rapidly detect three virus proteins (SARS-CoV-2, RSV, and Influenza A) and a population normalization molecule (caffeine) in wastewater. Going forward, turning these devices into hand-held systems would enable wastewater epidemiology in low-resource settings and be instrumental for rapid, local outbreak prevention.

Modelling Role of Protective and Nonprotective HLA Allele Inducing Different HIV Infection Outcomes

Human immunodeficiency virus (HIV) infects CD4+ cells and causes progressive immune function failure, and CD8+ cells lyse infected CD4+ cell via recognising peptide presented by human leukocyte antigens (HLA). Variations in HLA allele lead to observed different HIV infection outcomes. Within-host HIV dynamics involves virus replication within infected cells and lysing of infected cells by CD8+ cells, but how variations in HLA alleles determine different infection outcomes was far from clear. Here, we used mathematical modelling and parameter inference with a new analysis of published virus inhibition assay data to estimate CD8+ cell lysing efficiency, and found that lysing efficiency fall in the gap between low bound (0.1-0.2 day-1 (Elemans et al. in PLoS Comput Biol 8(2):e1002381, 2012)) and upper boundary (6.5-8.4 day-1 (Wick et al. in J Virol 79(21):13579-13586, 2005)). Our outcomes indicate that both lysing efficiency and viral inoculum size jointly determine observed different infection outcomes. Low lysing rate associated with non-protective HLA alleles leads to monostable viral kinetic to high viral titre and oscillatory viral kinetics. High lysing rate associated with protective HLA alleles leads monostable viral kinetic to low viral titre and bistable viral kinetics; at a specific interval of CD8+ cell counts, small viral inoculum sizes are inhibited but not large viral inoculum sizes remain infectious. Further, with CD8+ cell recruitment, HIV kinetics always exhibit oscillatory kinetics, but lysing rate is negatively correlated with range of CD8+ cell count. Our finding highlights role of HLA allele determining different infection outcomes, thereby providing a potential mechanistic explanation for observed good and bad HIV infection outcomes induced by protective HLA allele.

Precision Culture Scaling to Establish High-Throughput Vasculogenesis Models

Hydrogel-based 3D cell cultures can recapitulate (patho)physiological phenomena ex vivo. However, due to their complex multifactorial regulation, adapting these tissue and disease models for high-throughput screening workflows remains challenging. In this study, a new precision culture scaling (PCS-X) methodology combines statistical techniques (design of experiment and multiple linear regression) with automated, parallelized experiments and analyses to customize hydrogel-based vasculogenesis cultures using human umbilical vein endothelial cells and retinal microvascular endothelial cells. Variations of cell density, growth factor supplementation, and media composition are systematically explored to induce vasculogenesis in endothelial mono- and cocultures with mesenchymal stromal cells or retinal microvascular pericytes in 384-well plate formats. The developed cultures are shown to respond to vasculogenesis inhibitors in a compound- and dose-dependent manner, demonstrating the scope and power of PCS-X in creating parallelized tissue and disease models for drug discovery and individualized therapies.

How many patients do you need? Investigating trial designs for anti-seizure treatment in acute brain injury patients

BACKGROUND/OBJECTIVES

Epileptiform activity (EA), including seizures and periodic patterns, worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized control trials (RCTs) assessing anti-seizure interventions are needed. Due to scant drug efficacy data and ethical reservations with placebo utilization, and complex physiology of acute brain injury, RCTs are lacking or hindered by design constraints. We used a pharmacological model-guided simulator to design and determine the feasibility of RCTs evaluating EA treatment.

METHODS

In a single-center cohort of adults (age >18) with aSAH and EA, we employed a mechanistic pharmacokinetic-pharmacodynamic framework to model treatment response using observational data. We subsequently simulated RCTs for levetiracetam and propofol, each with three treatment arms mirroring clinical practice and an additional placebo arm. Using our framework, we simulated EA trajectories across treatment arms. We predicted discharge modified Rankin Scale as a function of baseline covariates, EA burden, and drug doses using a double machine learning model learned from observational data. Differences in outcomes across arms were used to estimate the required sample size.

RESULTS

Sample sizes ranged from 500 for levetiracetam 7 mg/kg versus placebo, to >4000 for levetiracetam 15 versus 7 mg/kg to achieve 80% power (5% type I error). For propofol 1 mg/kg/h versus placebo, 1200 participants were needed. Simulations comparing propofol at varying doses did not reach 80% power even at samples >1200.

CONCLUSIONS

Our simulations using drug efficacy show sample sizes are infeasible, even for potentially unethical placebo-control trials. We highlight the strength of simulations with observational data to inform the null hypotheses and propose use of this simulation-based RCT paradigm to assess the feasibility of future trials of anti-seizure treatment in acute brain injury.

Exploring the ability of the MD+FoldX method to predict SARS-CoV-2 antibody escape mutations using large-scale data

Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain. Our results show a positive correlation between predicted and experimental data, indicating that mutations with reduced predicted binding affinity correlate moderately with higher experimental escape fractions. We also demonstrate that better performance can be achieved using affinity cutoffs tailored to distinct antibody-antigen interactions rather than a one-size-fits-all approach. We find that 70% of the systems surpass the 50% precision mark, and demonstrate success in identifying mutations present in significant variants of concern and variants of interest. Despite promising results for some systems, our study highlights the challenges in comparing predicted and experimental values. It also emphasizes the need for new binding affinity methods with improved accuracy that are fast enough to estimate hundreds to thousands of antibody-antigen binding affinities.

Monomeric Esterase: Insights into Cooperative Behavior, Hysteresis/Allokairy

Herein, we present a novel esterase enzyme, Ade1, isolated from a metagenomic library of Amazonian dark earths soils, demonstrating its broad substrate promiscuity by hydrolyzing ester bonds linked to aliphatic groups. The three-dimensional structure of the enzyme was solved in the presence and absence of substrate (tributyrin), revealing its classification within the α/β-hydrolase superfamily. Despite being a monomeric enzyme, enzymatic assays reveal a cooperative behavior with a sigmoidal profile (initial velocities vs substrate concentrations). Our investigation brings to light the allokairy/hysteresis behavior of Ade1, as evidenced by a transient burst profile during the hydrolysis of substrates such as p-nitrophenyl butyrate and p-nitrophenyl octanoate. Crystal structures of Ade1, coupled with molecular dynamics simulations, unveil the existence of multiple conformational structures within a single molecular state (E̅1). Notably, substrate binding induces a loop closure that traps the substrate in the catalytic site. Upon product release, the cap domain opens simultaneously with structural changes, transitioning the enzyme to a new molecular state (E̅2). This study advances our understanding of hysteresis/allokairy mechanisms, a temporal regulation that appears more pervasive than previously acknowledged and extends its presence to metabolic enzymes. These findings also hold potential implications for addressing human diseases associated with metabolic dysregulation.

Fluorescence study of the interaction between albumin and layered double hydroxides

Layered double hydroxides nanoparticles (LDH-NP) are increasingly studied for biomedical applications. Nevertheless, their interaction with biomolecules such as proteins needs further exploration for an effective application. In this work, the adsorption of bovine serum albumin (BSA) on LDH-NP and the conformation changes of the protein upon adsorption were characterized using fluorescence spectroscopy. First, the quenching of tryptophan residues of BSA by chloride-intercalated LDH-NP was explored and the BSA adsorption capacity of LDH-NP were determined. Then, the structural conformation of the protein was analyzed by fluorescence spectroscopy (including synchronous, polarization and quenching studies) at different surface coverages. Finally, the proclivity of adsorbed BSA molecules to assemble as amyloid fibril was evaluated. Due to the positive charging and low curvature of LDH-NP, BSA molecules were strongly adsorbed, which produced a quenching of the protein fluorescence and a large adsorption capacity. The effect on BSA conformation was dependent on surface coverage (SC): at low values ,t he tryptophan residues were in more hydrophobic environments and more accessible to quenchers than al high ones. At low SC, there is space between the BSA molecules to spread on the surface, which led to a conformation change. Contrarily, the native conformation around tryptophan residues of BSA was preserved at high SC due to the tight packing of the adsorbed protein molecules. As a result, BSA molecules are stabilized against the formation of amyloid fibrils at high SC, while at low SC they present a similar fibrillation than free BSA.

Preparation of imidazole-modified paper membrane for selective extraction of gallic acid and its structural and functional analogues from Pomegranate Peel

In the search for pharmaceutically active compounds from natural products, it is crucial and challenging to develop separation methods that target not only structurally similar compounds but also a class of compounds with desired pharmaceutical functions. To achieve both structure-oriented and function-oriented selectivity, the choice of functional monomers with broad interactions or even biomimetic roles towards targeted compounds is essential. In this work, an imidazole (IM)-functionalized paper membrane was synthesized to realize selectivity. The IM was selected based on its capability to provide multiple interactions, participation in several bioprocesses, and experimental verification of adsorption performance. Using gallic acid as a representative component of Pomegranate Peel, the preparation conditions and extraction parameters were systematically investigated. The optimal membrane solid-phase extraction (MSPE) method allowed for enrichment of gallic acid from the complex matrix of Pomegranate Peel, enabling facile quantitative analysis with a limit of detection (LOD) of 0.1 ng mL-1. Furthermore, with the aid of cheminformatics, the extracted compounds were found to be similar in both their structures and pharmaceutical functions. This work offers a novel approach to preparing a readily synthesized extraction membrane capable of isolating compounds with similar structures and pharmaceutical effects, and provides an MSPE-based analytical method for natural products.

Cerium Oxide Catalyzed Disproportionation of Hydrogen Peroxide: A Closer Look at the Reaction Intermediate

Cerium oxide nanoparticles (CNPs) have recently gained increasing interest as redox enzyme-mimetics to scavenge the intracellular excess of reactive oxygen species, including hydrogen peroxide (H2 O2 ). Despite the extensive exploration, there remains a notable discrepancy regarding the interpretation of observed redshift of UV-Visible spectroscopy due to H2 O2 addition and the catalase-mimicking mechanism of CNPs. To address this question, we investigated the reaction mechanism by taking a closer look at the reaction intermediate during the catalase mimicking reaction. In this study, we present evidence demonstrating that in aqueous solutions, H2 O2 adsorption at CNP surface triggers the formation of stable intermediates known as cerium-peroxo (Ce-O2 2- ) and/or cerium-hydroperoxo (Ce-OOH- ) complexes as resolved by Raman scattering and UV-Visible spectroscopy. Polymer coating presents steric hinderance for H2 O2 accessibility to the solid-liquid interface limiting further intermediate formation. We demonstrate in depth that the catalytic reactivity of CNPs in the H2 O2 disproportionation reaction increases with the Ce(III)-fraction and decreases in the presence of polymer coatings. The developed approach using UV-Visible spectroscopy for the characterization of the surface peroxide species can potentially serve as a foundation for determining the catalytic reactivity of CNPs in the disproportionation of H2 O2 .

Design patterns of biological cells

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.

Establishment of a new cell-based assay to quantitatively evaluate the sweetness of sugar and sugar alcohol

Sweetness is a crucial indicator for identifying sweeteners used for flavor regulation and nutritional matching of foods. This study established a new quantitative sweetness evaluation method based on a combination of transiently transfected sweet taste receptor cells (STRs) and human sensory evaluation. Here, nine different sweeteners were evaluated and 10 sensory difference intensities and their corresponding concentrations were obtained through sensory evaluation. Using the same concentration solution as in the sensory evaluation, the dosage-response curve and EC50 of the nine sweeteners were obtained by analyzing the intracellular calcium signal fluctuation of STRs. Data analysis revealed that the calcium signal intensity and sweetness intensity under the same concentration of sweetener presented a strong linear correlation (R2 > 0.9). Additionally, we found a favorable correlation (R2 = 0.8746) between the relative sweetness and EC50. These findings indicate that the quantitative evaluation of sweetness based on STRs could be a potential alternative to human sensory evaluation.

Bayesian inference for prediction of survival probability in prime-boost vaccination regimes

We focus on Bayesian inference for survival probabilities in a prime-boost vaccination regime in the development of an Ebola vaccine. We are interested in the heterologous prime-boost regimen (unmatched vaccine deliverys using the same antigen) due to its demonstrated durable immunity, well-tolerated safety profile, and suitability as a population vaccination strategy. Our research is motivated by the need to estimate the survival probability given the administered dosage. To do so, we establish two key relationships. Firstly, we model the connection between the designed dose concentration and the induced antibody count using a Bayesian response surface model. Secondly, we model the association between the antibody count and the probability of survival when experimental subjects are exposed to the Ebola virus in a controlled setting using a Bayesian probability of survival model. Finally, we employ a combination of the two models with dose concentration as the predictor of the survival probability for a future vaccinated population. We implement our two-level Bayesian model in Stan, and illustrate its use with simulated and real-world data. Performance of this model is evaluated via simulation. Our work offers a new application of drug synergy models to examine prime-boost vaccine efficacy, and does so using a hierarchical Bayesian framework that allows us to use dose concentration to predict survival probability.

Power-law behavior of transcriptional bursting regulated by enhancer-promoter communication

Revealing how transcriptional bursting kinetics are genomically encoded is challenging because genome structures are stochastic at the organization level and are suggestively linked to gene transcription. To address this challenge, we develop a generic theoretical framework that integrates chromatin dynamics, enhancer-promoter (E-P) communication, and gene-state switching to study transcriptional bursting. The theory predicts that power law can be a general rule to quantitatively describe bursting modulations by E-P spatial communication. Specifically, burst frequency and burst size are up-regulated by E-P communication strength, following power laws with positive exponents. Analysis of the scaling exponents further reveals that burst frequency is preferentially regulated. Bursting kinetics are down-regulated by E-P genomic distance with negative power-law exponents, and this negative modulation desensitizes at large distances. The mutual information between burst frequency (or burst size) and E-P spatial distance further reveals essential characteristics of the information transfer from E-P communication to transcriptional bursting kinetics. These findings, which are in agreement with experimental observations, not only reveal fundamental principles of E-P communication in transcriptional bursting but also are essential for understanding cellular decision-making.

Radiofrequency driving antitumor effect of graphene oxide-based nanocomposites: a Hill model analysis

Aim: This report proposes using the Hill model to assess the benchmark dose, the 50% lethal dose, the cooperativity and the dissociation constant while analyzing cell viability data using nanomaterials to evaluate the antitumor potential while combined with radiofrequency therapy. Materials & methods: A nanocomposite was synthesized (graphene oxide-polyethyleneimine-gold) and the viability was evaluated using two tumor cell lines, namely LLC-WRC-256 and B16-F10. Results: Our findings demonstrated that while the nanocomposite is biocompatible against the LLC-WRC-256 and B16-F10 cancer cell lines in the absence of radiofrequency, the application of radiofrequency enhances the cell toxicity by orders of magnitude. Conclusion: This result points to prospective studies with the tested cell lines using tumor animal models.

A model of subcutaneous pramlintide pharmacokinetics and its effect on gastric emptying: Proof-of-concept based on populational data

Pramlintide, an amylin analog, has been coming up as an agent in type 1 diabetes dual-hormone therapies (insulin/pramlintide). Since pramlintide slows down gastric emptying, it allows for easing glucose control and reducing the burden of meal announcements. Pre-clinical in silico evaluations are a key step in the development of any closed-loop strategy. However, mathematical models are needed, and pramlintide models in the literature are scarce. This work proposes a proof-of-concept pramlintide model, describing its subcutaneous pharmacokinetics (PK) and its effect on gastric emptying (PD). The model is validated with published populational (clinical) data. The model development is divided into three stages: intravenous PK, subcutaneous PK, and PD modeling. In each stage, a set of model structures are proposed, and their performance is assessed using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). In order to evaluate the modulation of the rate of gastric emptying, a literature meal model was used. The final pramlintide model comprises four compartments and a function that modulates gastric emptying depending on plasma pramlintide. Results show an appropriate fit for the data. Some aspects are left as open questions due to the lack of specific data (e.g., the influence of meal composition on the pramlintide effect). Moreover, further validation with individual data is necessary to propose a virtual cohort of patients.

Protein sequence landscapes are not so simple: on reference-free versus reference-based inference

In a recent preprint, Park, Metzger, and Thornton reanalyze 20 empirical protein sequence-function landscapes using a "reference-free analysis" (RFA) method they recently developed. They argue that these empirical landscapes are simpler and less epistatic than earlier work suggested, and attribute the difference to limitations of the methods used in the original analyses of these landscapes, which they claim are more sensitive to measurement noise, missing data, and other artifacts. Here, we show that these claims are incorrect. Instead, we find that the RFA method introduced by Park et al. is exactly equivalent to the reference-based least-squares methods used in the original analysis of many of these empirical landscapes (and also equivalent to a Hadamard-based approach they implement). Because the reanalyzed and original landscapes are in fact identical, the different conclusions drawn by Park et al. instead reflect different interpretations of the parameters describing the inferred landscapes; we argue that these do not support the conclusion that epistasis plays only a small role in protein sequence-function landscapes.

Quantitative comparison of nuclear transport inhibition by SARS coronavirus ORF6 reveals the importance of oligomerization

Open Reading Frame 6 (ORF6) proteins, which are unique to severe acute respiratory syndrome-related (SARS) coronavirus, inhibit the classical nuclear import pathway to antagonize host antiviral responses. Several alternative models were proposed to explain the inhibitory function of ORF6 [H. Xia et al., Cell Rep. 33, 108234 (2020); L. Miorin et al., Proc. Natl. Acad. Sci. U.S.A. 117, 28344-28354 (2020); and M. Frieman et al., J. Virol. 81, 9812-9824 (2007)]. To distinguish these models and build quantitative understanding of ORF6 function, we developed a method for scoring both ORF6 concentration and functional effect in single living cells. We combined quantification of untagged ORF6 expression level in single cells with optogenetics-based measurement of nuclear transport kinetics, using methods that could be adapted to measure concentration-dependent effects of any untagged protein. We found that SARS-CoV-2 ORF6 is ~15 times more potent than SARS-CoV-1 ORF6 in inhibiting nuclear import and export, due to differences in the C-terminal region that is required for the NUP98-RAE1 binding. The N-terminal region was required for transport inhibition. This region binds membranes but could be replaced by synthetic constructs which forced oligomerization in solution, suggesting its primary function is oligomerization. We propose that the hydrophobic N-terminal region drives oligomerization of ORF6 to multivalently cross-link the NUP98-RAE1 complexes at the nuclear pore complex, and this multivalent binding inhibits bidirectional transport.

Investigation of the association between oxygen reserve index and arterial partial oxygen pressure in anesthetized dogs

OBJECTIVE

To evaluate the relationship between oxygen reserve index (ORI) and arterial partial pressure of oxygen (PaO2) in anesthetized dogs.

STUDY DESIGN

Prospective experimental study.

ANIMALS

A total of eight healthy adult Beagle dogs with a median age of 38 (range 20-87) months and a median body mass of 8.6 (range 7.0-13.8) kg.

METHODS

After induction of general anesthesia with propofol, dogs were mechanically ventilated and anesthesia maintained with isoflurane carried in oxygen. Arterial blood samples were collected from a catheter placed in the femoral artery. ORI was measured by placing a CO-oximeter sensor on the tongue. Inspired oxygen fraction (FiO2) was increased from 21% to > 95% in increments of 5%. PaO2 and ORI were recorded and compared at different times. The relationship between ORI and PaO2 was investigated using a nonlinear function, the Hill equation, and a linear regression analysis was performed, as appropriate.

RESULTS

A total of 128 pairs of values were compared for all dogs. Applying the Hill equation to the relationship between ORI and PaO2 resulted in R2 = 0.80 (p < 0.001) with a Hill coefficient of 3.7. It was predicted that ORI ranged 0.1-0.9 as PaO2 ranged 127.0-417.9 mmHg and that in the more linear portion of the range, PaO2 of 127.0-289.9 mmHg ORI ranged 0.1-0.7. Linear regression analysis in the more linear portion showed a weak correlation (R2 = 0.29, p = 0.006).

CONCLUSIONS AND CLINICAL RELEVANCE

In the present study, the Hill equation predicted the relationship between PaO2 and ORI for PaO2 ranging 127.0-417.9 mmHg in anesthetized dogs. However, in the linear portion of the PaO2, the coefficient of determination was low, indicating that ORI is not a surrogate for PaO2.

Mathematical modeling predicts pathways to successful implementation of combination TRAIL-producing oncolytic virus and PAC-1 to treat granulosa cell tumors of the ovary

The development of new cancer therapies requires multiple rounds of validation from in vitro and in vivo experiments before they can be considered for clinical trials. Mathematical models assist in this preclinical phase by combining experimental data with human parameters to provide guidance about potential therapeutic regimens to bring forward into trials. However, granulosa cell tumors of the ovary lack a relevant mouse model, complexifying preclinical drug development for this rare tumor. To bridge this gap, we established a mathematical model as a framework to explore the potential of using a tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-producing oncolytic vaccinia virus in combination with the chemotherapeutic agent first procaspase activating compound (PAC-1). We have previously shown that TRAIL and PAC-1 act synergistically on granulosa tumor cells. In line with our previous results, our current model predicts that, although it is unable to stop the tumor from growing in its current form, combination oral PAC-1 with oncolytic virus (OV) provides the best result compared to monotherapies. Encouragingly, our results suggest that increases to the OV infection rate can lead to the success of this combination therapy within a year. The model developed here can continue to be improved as more data become available, allowing for regimen-tailoring via virtual clinical trials, ultimately shepherding effective regimens into trials.

Modelling the impact of JNJ-1802, a first-in-class dengue inhibitor blocking the NS3-NS4B interaction, on in-vitro DENV-2 dynamics

Dengue virus (DENV) is a public health challenge across the tropics and subtropics. Currently, there is no licensed prophylactic or antiviral treatment for dengue. The novel DENV inhibitor JNJ-1802 can significantly reduce viral load in mice and non-human primates. Here, using a mechanistic viral kinetic model calibrated against viral RNA data from experimental in-vitro infection studies, we assess the in-vitro inhibitory effect of JNJ-1802 by characterising infection dynamics of two DENV-2 strains in the absence and presence of different JNJ-1802 concentrations. Viral RNA suppression to below the limit of detection was achieved at concentrations of >1.6 nM, with a median concentration exhibiting 50% of maximal inhibitory effect (IC50) of 1.23x10-02 nM and 1.28x10-02 nM for the DENV-2/RL and DENV-2/16681 strains, respectively. This work provides important insight into the in-vitro inhibitory effect of JNJ-1802 and presents a first step towards a modelling framework to support characterization of viral kinetics and drug effect across different host systems.

4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction

Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance. Interestingly, we find that long-range E-P interactions can induce bimodal and trimodal mRNA distributions. The 4D nucleome equation also allows for model selection and parameter inference. When this equation is applied to the mouse embryonic stem cell smRNA-FISH data and the E-P genomic-distance data, the predicted E-P contact probability and mRNA distribution are in good agreement with experimental results. Further statistical inference indicates that the E-P interactions prefer to modulate the mRNA level by controlling promoter activation and transcription initiation rates. Our model and results provide quantitative insights into both spatiotemporal gene-expression determinants (i.e., long-range E-P interactions) and cellular fates during development.

Experimental and computational methods to highlight behavioural variations in TonB-dependent transporter expression in Pseudomonas aeruginosa versus siderophore concentration

Iron is a key nutrient for bacterial growth. The source can be either heme or siderophore-Fe complexes. Siderophores are small molecules synthesized by bacteria to scavenge iron from the bacterial environment. The pathogen Pseudomonas aeruginosa can express at least 15 different iron uptake pathways and all but one involve a TonB-dependent transporter (TBDT) for the uptake of iron across the outer membrane. Little is known about how bacteria modulate and adapt the expression of their different iron import pathways according to their environment. Here, we have developed fluorescent reporters between the promoter region of genes encoding a TBDT and the fluorescent reporter mCherry. With these constructs, we can follow the expression of TBDTs under different growth conditions. Mathematical modelling of the data obtained showed the transcription and expression of the gene encoding the TBDT PfeA to have a sigmoidal shape, whereas it was logarithmic for the TBDT gene foxA. Maximum transcription for pfeA was reached in the presence of 3 µM enterobactin, the siderophore recognized by PfeA, whereas the maximum was not reached for foxA with 100 µM nocardamine, the siderophore of FoxA.

A modeling framework for adaptive collective defense: crisis response in social-insect colonies

Living systems, from cells to superorganismic insect colonies, have an organizational boundary between inside and outside and allocate resources to defend it. Whereas the micro-scale dynamics of cell walls can be difficult to study, the adaptive allocation of workers to defense in social-insect colonies is more conspicuous. This is particularly the case for Tetragonisca angustula stingless bees, which combine different defensive mechanisms found across other colonial animals: (1) morphological specialization (distinct soldiers (majors) are produced over weeks); (2) age-based polyethism (young majors transition to guarding tasks over days); and (3) task switching (small workers (minors) replace soldiers within minutes under crisis). To better understand how these timescales of reproduction, development, and behavior integrate to balance defensive demands with other colony needs, we developed a demographic Filippov ODE system to study the effect of these processes on task allocation and colony size. Our results show that colony size peaks at low proportions of majors, but colonies die if minors are too plastic or defensive demands are too high or if there is a high proportion of quickly developing majors. For fast maturation, increasing major production may decrease defenses. This model elucidates the demographic factors constraining collective defense regulation in social insects while also suggesting new explanations for variation in defensive allocation at smaller scales where the mechanisms underlying defensive processes are not easily observable. Moreover, our work helps to establish social insects as model organisms for understanding other systems where the transaction costs for component turnover are nontrivial, as in manufacturing systems and just-in-time supply chains.

Selective targeting and clustering of phosphatidylserine lipids by RSV M protein is critical for virus particle production

Human respiratory syncytial virus (RSV) is the leading cause of infantile bronchiolitis in the developed world and of childhood deaths in resource-poor settings. The elderly and the immunosuppressed are also affected. It is a major unmet target for vaccines and antiviral drugs. RSV assembles and buds from the host cell plasma membrane by forming infectious viral particles which are mostly filamentous. A key interaction during RSV assembly is the interaction of the matrix (M) protein with cell plasma membrane lipids forming a layer at assembly sites. Although the structure of RSV M protein dimer is known, it is unclear how the viral M proteins interact with cell membrane lipids, and with which one, to promote viral assembly. Here, we demonstrate that M proteins are able to cluster at the plasma membrane by selectively binding with phosphatidylserine (PS). Our in vitro studies suggest that M binds PS lipid as a dimer and upon M oligomerization, PS clustering is observed. In contrast, the presence of other negatively charged lipids like PI(4, 5)P2 does not enhance M binding beyond control zwitterionic lipids, while cholesterol negatively affects M interaction with membrane lipids. Moreover, we show that the initial binding of the RSV M protein with PS lipids is independent of the cytoplasmic tail of the fusion (F) glycoprotein (FCT). Here, we highlight that M binding on membranes occurs directly through PS lipids, this interaction is electrostatic in nature, and M oligomerization generates PS clusters.

Dynamic Metallosupramolecular Cages Containing 12 Adaptable Pockets for High-Order Guest Binding Beyond Biomimicry

Molecular recognition lies at the heart of biological functions, which inspires lasting research in artificial host syntheses to mimic biomolecules that can recognize, process, and transport molecules with the highest level of complexity; nonetheless, the design principle and quantifying methodology of artificial hosts for multiple guests (≥4) remain a formidable task. Herein, we report two rhombic dodecahedral cages [(Zn/Fe)8Pd6-MOC-16], which embrace 12 adaptive pockets for multiguest binding with distinct conformational dynamics inherent in metal-center lability and are able to capture 4-24 guests to manifest a surprising complexity of binding scenarios. The exceptional high-order and hierarchical encapsulation phenomena suggest a wide host-guest dynamic-fit, enabling conformational adjustment and adaptation beyond the duality of induced-fit and conformational selection in protein interactions. A critical inspection of the host-guest binding events in solution has been performed by NMR and ESI-MS spectra, highlighting the importance of acquiring a reliable binding repertoire from different techniques and the uncertainty of quantifying the binding affinities of multiplying guests by an oversimplified method.

Polysaccharide/Silica Microcapsules Prepared via Ionic Gelation Combined with Spray Drying: Application in the Release of Hydrophilic Substances and Catalysis

Polysaccharide/silica hybrid microcapsules were prepared using ionic gelation followed by spray-drying. Chitosan and alginate were used as biopolymer matrices, and in situ prepared silica was used as a structuring additive. The prepared microparticles were used in two very different applications: the encapsulation of hydrophilic molecules, and as a support for palladium nanoparticles used as catalysts for a model organic reaction, namely the reduction of p-nitrophenol by sodium borhydride. In the first application, erioglaucine disodium salt, taken as a model hydrophilic substance, was encapsulated in situ during the preparation of the microparticles. The results indicate that the presence of silica nanostructures, integrated within the polymer matrix, affect the morphology and the stability of the particles, retarding the release of the encapsulated substance. In the second application, chloropalladate was complexed on the surface of chitosan microparticles, and palladium(II) was subsequently reduced to palladium(0) to obtain heterogeneous catalysts with an excellent performance.

Cooperation in bioluminescence: understanding the role of autoinducers by a stochastic random resistor model

Quorum sensing is a communication mechanism adopted by different bacterial strains for the regulation of gene transcription. It takes place through the exchange of molecules called autoinducers. Bioluminescence is an emergent threshold phenomenon shown by some bacteria strains. Its precise relationship to quorum sensing is a debated topic, particularly regarding the role of the different autoinducers used by bacteria. In this paper, assuming a direct relationship between bioluminescence and quorum sensing, we investigate the role of multiple autoinducers in the bioluminescence response of Vibrio harveyi, considered as a model bioluminescent strain, due to its quorum sensing circuitry involving an array of three different autoinducers. Experiments on mutants of this bacterium, obtained by suppression of one or more autoinducers, reveal their relative non-trivial relevance and cooperative interaction patterns. The proposed analysis is implemented on a regular lattice, whose nodes represent microbial entities equipped with charges, which represent the ability to up/down regulate the gene expression. Quorum sensing results from a Coulomb-type field, produced by the charges. In analogy with random resistor network models, the lattice is permeated by an effective current which accounts for the amount and distribution of the charges. We propose that the presence of different autoinducers correspond to a different up/down regulation of gene expression, i.e., to a different way to account for the charges. Then, by introducing a modulation of the charge dependence into the current flowing within the network, we show that it is able to describe the bioluminescence exhibited by V. harveyi mutants. Furthermore, modulation of the charge dependence allows the interactions between the different autoinducers to be taken into account, providing a prediction regarding the data obtainable under specific growth conditions.

Robust Biosensor Based on Carbon Nanotubes/Protein Hybrid Electrolyte Gated Transistors

Semiconducting single walled carbon nanotubes (SWCNTs) are promising materials for biosensing applications with electrolyte-gated transistors (EGT). However, to be employed in EGT devices, SWCNTs often require lengthy solution-processing fabrication techniques. Here, we introduce a simple solution-based method that allows fabricating EGT devices from stable dispersions of SWCNTs/bovine serum albumin (BSA) hybrids in water. The dispersion is then deposited on a substrate allowing the formation of a SWCNTs random network as the semiconducting channel. We demonstrate that this methodology allows the fabrication of EGT devices with electric performances that allow their use in biosensing applications. We demonstrate their application for the detection of cortisol in solution, upon gate electrode functionalization with anti-cortisol antibodies. This is a robust and cost-effective methodology that sets the ground for a SWCNT/BSA-based biosensing platform that allows overcoming many limitations of standard SWCNTs biosensor fabrications.

The terminal oxidase cytochrome bd-I confers carbon monoxide resistance to Escherichia coli cells

Carbon monoxide (CO) plays a multifaceted role in the physiology of organisms, from poison to signaling molecule. Heme proteins, including terminal oxidases, are plausible CO targets. Three quinol oxidases terminate the branched aerobic respiratory chain of Escherichia coli. These are the heme‑copper cytochrome bo3 and two copper-lacking bd-type cytochromes, bd-I and bd-II. All three enzymes generate a proton motive force during the four-electron oxygen reduction reaction that is used for ATP production. The bd-type oxidases also contribute to mechanisms of bacterial defense against various types of stresses. Here we report that in E. coli cells, at the enzyme concentrations tested, cytochrome bd-I is much more resistant to inhibition by CO than cytochrome bd-II and cytochrome bo3. The apparent half-maximal inhibitory concentration values, IC50, for inhibition of O2 consumption of the membrane-bound bd-II and bo3 oxidases by CO at ~150 μM O2 were estimated to be 187.1 ± 11.1 and 183.3 ± 13.5 μM CO, respectively. Under the same conditions, the maximum inhibition observed with the membrane-bound cytochrome bd-I was 20 ± 10% at ~200 μM CO.

Mathematical models describing oxygen binding by hemoglobin

Despite the fact that the investigation of the structural and functional properties of hemoglobin dates back more than 150 years, the topic has not lost its relevance today. The most important component of these studies is the development of mathematical models that formalize and generalize the mechanisms determining the cooperative binding of ligands based on data on the structural and functional state of the protein. In this work, we review the mathematical relationships describing oxygen binding by hemoglobin, ranging from the classical Hüfner, Hill, and Adair equations to the Szabo-Karplus and tertiary two-state mathematical models based on the Monod-Wyman-Changeux and Koshland-Némethy-Filmer concepts. The generality of the considered equations as mathematical functions, bearing in their basis a power dependence, is demonstrated. The problems and possible solutions related to approximation of experimental data by the oxygenation equations with correlated fitting parameters are noted. Attention is paid to empirical equations, extended versions of the Hill equation, where the coefficient of cooperation is modulated by Gauss and Lorentz distributions as functions of partial oxygen pressure.

Clinical validation of an adapted Eleveld Model for high-dose propofol treatments for depression

Repeated administration of high doses of propofol to patients with treatment-resistant depression (TRD) has been shown to produce antidepressant effects in small clinical trials. These effects can be elicited when the patient's EEG burst-suppression ratio (BSR) is maintained at 70-90% for 15 min in repeated treatments. This deep anesthesia domain lies beyond the range of current propofol pharmacokinetic/pharmacodynamic (PK/PD) models. In this study, we adapt the Eleveld model for use at deep anesthesia levels with a BSR endpoint, with the goal of aiding the estimation of the dosage of propofol needed to achieve 70-90% BSR for 15 min. We test the ability of the adapted model to predict BSR for these treatments. Twenty participants underwent 6-9 treatments of high doses of propofol (5-9 of which were included in this analysis) for a total of 115 treatments. To adapt the Eleveld model for this endpoint, we optimized the model parameters Ke0, γ and Ce50. These parameters were then used in the adapted model to estimate second-by-second BSR for each treatment. Estimated BSR was compared with observed BSR for each treatment of each participant. Median absolute performance error (MdAPE) between the estimated and observed BSR (25th-75th percentile) was 6.63 (3.79-12.96) % points and 8.51 (4.32-16.74) % between the estimated and observed treatment duration. This predictive performance is statistically significantly better at predicting BSR compared with the standard Eleveld model at deep anesthesia levels. Our adapted Eleveld model provides a useful tool to aid dosing propofol for high-dose anesthetic treatments for depression.

Phospholipid headgroup composition modulates the molecular interactions and antimicrobial effects of sulfobetaine zwitterionic detergents against the "ESKAPE" pathogen Pseudomonas aeruginosa

We determine the efficacy for three known structurally related, membrane active detergents against multidrug resistant and wild type strains of Pseudomonas aeruginosa. Accessible solution state NMR experiments are used to quantify phospholipid headgroup composition of the microbial membranes and to gain molecular level insight into antimicrobial mode of action.

(R)evolution of the Standard Addition Procedure for Immunoassays

A new method to transfer the standard addition procedure for concentration determination to immunoassays with non-linear calibration curves was developed. The new method was successfully applied to simulated data and benchmarked against a state-of-the-art algorithm, showing a significantly improved performance with improvement factors between 2 and 192. The logit function was used to transform the immunoassay signal response of test samples spiked with known analyte concentrations. The relationship between logit(signal) and log-transformed estimated total analyte concentration is linear if the estimated total analyte concentration is correct. Finally, the new method was validated experimentally using different assays in varying, relevant complex matrices, such as serum, saliva, and milk. Different concentrations of testosterone and amitriptyline between 0.05 and 3.0 µg L-1 were quantified using a binding inhibition assay in combination with reflectometric interference spectroscopy (RIfS) as the transduction principle. The sample concentration was calculated using a numerical method. Samples could be quantified with recoveries between 70 and 118%. The standard addition method accounts for individual matrix interference on the immunoassay by spiking the test sample itself. Although the experiments were carried out using RIfS, the method can be applied to any immunoassay that meets the analytical requirements.

How Many Patients Do You Need? Investigating Trial Designs for Anti-Seizure Treatment in Acute Brain Injury Patients

Objectives

Epileptiform activity (EA) worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized trials (RCTs) assessing anti-seizure interventions are needed. Due to scant drug efficacy data and ethical reservations with placebo utilization, RCTs are lacking or hindered by design constraints. We used a pharmacological model-guided simulator to design and determine feasibility of RCTs evaluating EA treatment.

Methods

In a single-center cohort of adults (age >18) with aSAH and EA, we employed a mechanistic pharmacokinetic-pharmacodynamic framework to model treatment response using observational data. We subsequently simulated RCTs for levetiracetam and propofol, each with three treatment arms mirroring clinical practice and an additional placebo arm. Using our framework we simulated EA trajectories across treatment arms. We predicted discharge modified Rankin Scale as a function of baseline covariates, EA burden, and drug doses using a double machine learning model learned from observational data. Differences in outcomes across arms were used to estimate the required sample size.

Results

Sample sizes ranged from 500 for levetiracetam 7 mg/kg vs placebo, to >4000 for levetiracetam 15 vs. 7 mg/kg to achieve 80% power (5% type I error). For propofol 1mg/kg/hr vs. placebo 1200 participants were needed. Simulations comparing propofol at varying doses did not reach 80% power even at samples >1200.

Interpretation

Our simulations using drug efficacy show sample sizes are infeasible, even for potentially unethical placebo-control trials. We highlight the strength of simulations with observational data to inform the null hypotheses and assess feasibility of future trials of EA treatment.

Evaluation of DNA damage induced by acesulfame potassium: spectroscopic, molecular modeling simulations and toxicity studies

Acesulfame potassium (Ace-K) is a widely used artificial sweetener that has been reported to interact with DNA and cause important genetic damage. However, the type of interaction mechanism is unknown. This study provides an approach to understanding the in vitro mechanism of Ace-K interaction with Ct-DNA using spectroscopic methods combined with molecular simulations. The hypochromic effect as obtained from UV-Vis spectra indicated the formation of the DNA-Ace-K complex in the minor groove. Further evidence for groove binding mode comes from the decrease in Hoechst-DNA fluorescence caused by increasing Ace-K concentrations, alongside no detectable change in MB-DNA emission band intensity. A negative value of ΔH and ΔS represents the hydrogen bonds and van der Waals forces between Ace-K and DNA. Based on the molecular docking, Ace-K was located between the guanine10 and 16 in DNA minor groove and stabilized by two hydrogen bonds and one π-Sulfur interaction. In vitro cell culture results showed that about 5 mg/mL of Ace-K caused the death of 85% of HUVEC cells after 48 h. Communicated by Ramaswamy H. Sarma.

The artificial oxygen carrier erythrocruorin-characteristics and potential significance in medicine

The diminishing supply and increasing costs of donated blood have motivated research into novel hemoglobin-based oxygen carriers (HBOCs) that can serve as red blood cell (RBC) substitutes. HBOCs are versatile agents that can be used in the treatment of hemorrhagic shock. However, many of the RBC substitutes that are based on mammalian hemoglobins have presented key limitations such as instability and toxicity. In contrast, erythrocruorins (Ecs) are other types of HBOCs that may not suffer these disadvantages. Ecs are giant metalloproteins found in annelids, crustaceans, and some other invertebrates. Thus far, the Ecs of Lumbricus terrestris (LtEc) and Arenicola marina (AmEc) are the most thoroughly studied. Based on data from preclinical transfusion studies, it was found that these compounds not only efficiently transport oxygen and have anti-inflammatory properties, but also can be modified to further increase their effectiveness. This literature review focuses on the structure, properties, and application of Ecs, as well as their advantages over other HBOCs. Development of methods for both the stabilization and purification of erythrocruorin could confer to enhanced access to artificial blood resources.

Characterising the intensity of insecticide resistance: A novel framework for analysis of intensity bioassay data

Insecticide resistance is a growing problem that risks harming the progress made by vector control tools in reducing the malaria burden globally. New methods for quantifying the extent of resistance in wild populations are urgently needed to guide deployment of interventions to improve disease control. Intensity bioassays measure mosquito mortality at a range of insecticide doses and characterise phenotypic resistance in regions where resistance is already detected. These data are increasingly being collected but tend to exhibit high measurement error and there is a lack of formal guidelines on how they should be analysed or compared. This paper introduces a novel Bayesian framework for analysing intensity bioassay data, which uses a flexible statistical model able to capture a wide variety of relationships between mortality and insecticide dose. By accounting for background mortality of mosquitoes, our approach minimises the impact of this source of measurement noise resulting in more precise quantification of resistance. It outputs a range of metrics for describing the intensity and variability in resistance within the sample and quantifies the level of measurement error in the assay. The functionality is illustrated with data from laboratory-reared mosquitoes to show how the lethal dose varies within and between different strains. The framework can also be used to formally test hypotheses by explicitly considering the high heterogeneity seen in these types of data in field samples. Here we show that the intensity of resistance (as measured by the median lethal dose (LC50) of insecticide) increases over 7 years in mosquitoes from one village in Burkina Faso but remains constant in another. This work showcases the benefits of statistically rigorous analysis of insecticide bioassay data and highlights the additional information available from this and other dose-response data.