RSC Advances

The delivery of small-molecule therapeutics across cellular membranes remains a fundamental challenge in drug development, particularly for compounds whose physicochemical properties limit intracellular bioavailability. Inspired by the low toxicity, biodegradability, and synthetic accessibility of triethanolamine-derived lipids, we investigated a series of C18 aminotriester lipids as excipients for the codelivery of anticancer therapeutics. Four structurally related triester lipids bearing saturated, cis-monounsaturated, trans-monounsaturated, and di-unsaturated C18 tails were synthesized through straightforward esterification reactions with triethanolamine. These lipids were evaluated for their ability to enhance the antiproliferative activity of several anticancer agents, including paclitaxel, doxorubicin, amonafide, homoharringtonine, camptothecin, and SN-38. Across multiple drug classes, the aminotriester lipids exhibited minimal intrinsic cytotoxicity and generally produced limited enhancement of drug potency. However, the fully saturated tris-stearate aminotriester lipid selectively enhanced the antiproliferative activity of amonafide in HCT-116 colorectal cancer cells, particularly at lower concentrations. In contrast, unsaturated lipid analogues displayed negligible enhancement effects, and the activity of the tris-stearate lipid was substantially attenuated in A549 lung adenocarcinoma cells, weakly observed in HT-29 colorectal cancer cells, and absent in CT26 murine colorectal cancer cells. Lactate dehydrogenase release assays indicated that these effects were not associated with membrane lysis or nonspecific cytotoxicity. Further, fluorescence microscopy time course experiments suggest improved membrane trafficking of amonafide when codelivered stoichiometrically with fully saturated C18 aminotriester lipids. Collectively, these findings demonstrate that saturated triethanolamine-based aminotriester lipids may function as selective and biocompatible codelivery excipients for certain small-molecule therapeutics. The observed dependence on both lipid saturation state and cellular context suggests that membrane organization and lipid packing may play important roles in mediating these effects. These results establish a foundation for further mechanistic investigations into aminotriester lipid-assisted small-molecule delivery systems.

The development of NIR fluorescent dyes with favorable optical properties is of great importance especially for applications within the field of optical imaging. In this study, we report the design, synthesis and photophysical characterization of novel BODIPY-Xanthene hybrid dyes obtained via Knoevenagel condensation between an asymmetrical BODIPY core and the functionalized xanthene aldehydes intermediates. The synthesized dyes ex-hibit absorption (667 nm) and emission bands (720-722 nm) within the NIR region. Detailed UV-Vis and fluo-rescence studies were performed and molar extinction coefficients and stokes shifts also calculated. Moreover, findings highlighting the influence of structural modifications on the optical behavior of the hybrid dyes and their potential utility in optical imaging applications are reported.

In 1998 we predicted percent human intestinal absorption (HIA) for 86 drug and drug-like compounds from six molecular descriptors chosen by a genetic algorithm with a small neural network serving as the fitness function. That result rested on one division of the compounds into three sets: training, cross-validation and external prediction. Repeating the division shows it was a rather fortunate one. An extraction is one random draw from a wide distribution, so we repeat every experiment 250 times and report the result as a distribution. Across 250 stratified extractions, 14 match the published cross-validation error and only one matches the published external prediction error. Reconstructed this way, the published six descriptors give a mean extraction error roughly twice the external prediction value we reported in 1998 (Table 1). We then applied the same six descriptors to a larger set of 780 compounds from a public compilation. Under the 1998 network they give 22.50 %HIA units on training compounds against 25.77 on extracted compounds, whereas on the 86 they give 13.43 against 30.39. More compounds close the gap between fitting and prediction. Four datasets are modeled here: 780 small molecules with HIA measured in man, 3,771 small molecules and 1,281 cyclic peptides measured across Caco-2 cell monolayers, and 7,298 cyclic peptides measured across artificial membranes. Each is its own prediction problem, and one procedure is applied to all four. A genetic algorithm chooses which descriptors to use and how many, and a random forest grades each choice on compounds its own trees never saw. The descriptors chosen most often across the 250 extractions form one consensus set for each dataset. For absorption, 25 consensus descriptors under a random forest reach an extraction rms of 20.47 %HIA units at R 0.76. On the same compounds and the same extractions, the six 1998 descriptors under the 1998 network reach 25.77 at R 0.59. The four models are served at predicthia.ai, where a structure can be drawn or pasted, scored against its training set for similarity, and the training data with fitted models downloaded. Each model served is its fixed consensus set fitted on every compound in its dataset; the accuracy quoted beside a prediction comes from evaluating that same set across 250 extractions (Table 3). The fixed sets hold 25 descriptors for absorption, 55 for Caco-2 small-molecule permeability, 50 for Caco-2 peptide permeability and 25 for artificial-membrane permeability. Keywords: human intestinal absorption; QSPR; genetic algorithm; descriptor selection; cyclic peptides; membrane permeability; oral bioavailability; repeated extraction

Microplastic pollution from homopolymers such as polypropylene (PP), polystyrene (PS), and polyethylene (PE) poses growing health and environmental concerns, highlighting the need for robust polymer-degrading biocatalysts. We previously identified a naturally occurring cysteine-dependent hydrolase (CsdH) from Rhodococcus opacus, featuring a unique Cys160-Lys127-Asp39 catalytic triad and providing a novel mechanism for polyethylene terephthalate (PET) degradation. In this study, we have determined crystal structures of CsdH in complex with PP, PS, PE, and styrene and demonstrated the potential of the enzyme to directly degrade these homopolymers into their respective low molecular weight degradation products using LC-MS. Structural analysis reveals that the enzyme retains a conserved principal access tunnel while undergoing subtle substrate-dependent changes to accommodate different substrates. The enzyme exhibited broad plastic degradation activity with the highest weight loss observed for PE, followed by PP and PS. SEM analysis reveals surface roughness, cracks and grooves, confirming polymer degradation. Further, these results corroborate through FTIR and TGA analysis. These findings establish a strong foundation for enzyme engineering and aim at developing efficient microplastic degradation.

In the enzymatic toolbox of depollution, hydrolytic dehalogenases are of particular interest for the bioremediation of organohalogenated compounds. To better identify and characterize these enzymes, it is important to develop appropriate sensing methods. Fluorescent probes for dehalogenase detection have been developed in the past years, however, to this date none were available for application using the common FITC parameters (i.e. excitation laser at 488 nm). To address this limitation, we herein report a new fluorescent probe, COU4-Cl, excitable in the violet (405 nm) and blue (488 nm) wavelengths adapted for the detection and characterization of haloalkane dehalogenases. Its applicability is discussed and evaluated in comparison to the previously described COU2-Cl probe only excitable in the violet (405 nm). This study shows the advantages and complementarity of the two probes, and further demonstrate their application for the discrimination of dehalogenase activity in whole cell assays.

Electromicrobial production (EMP) technologies aim to combine renewable electricity, CO2, and engineered microbes to make energy-dense molecules at efficiencies exceeding photosynthesis. CO2 can be electrochemically reduced to formate, which is far easier to handle at the bench than H2 or an electrode, but formate carries only two electrons per carbon against the six in a biofuel. The remaining electrons must come from oxidizing additional formate, from H2 oxidation, or from extracellular electron uptake (EEU), and no rigorous comparison of these options coupled to the choice of carbon assimilation pathway currently exists. We calculate upper-limit efficiencies for butanol production by six carbon assimilation pathways, each paired with all three electron delivery mechanisms, using electrochemical parameters drawn from a survey of the recent literature. Electrical to butanol energy conversion efficiencies range from 35.5 to 51.7%, corresponding to solar-to-fuel efficiencies of 11.7 to 17%, so even the least efficient route exceeds the 8% theoretical ceiling of algal photosynthesis. The serine variant of the reductive glycine pathway reaches an electrical energy conversion efficiency of when using H2 oxidation, within 1.9 points of the most efficient pathway, and is the only high-efficiency option that tolerates O2. This makes an EMP system that combines electron delivery by formate coupled with the serine variant of reductive glycine pathway highly attractive, as it presents few barriers to rapid, iterative engineering in the lab, and a high theoretical ceiling. Drawing both carbon and electrons from formate costs 6.2 points against H2 at a state-of-the-art whole-cell voltage (2.2 V). However, this small penalty is amplified three-fold by any rise in the CO2-to-formate cell voltage, and reaches 13.5 points at the highest whole-cell voltages reported for scaled-up CO2-to-formate electrolyzers, where formate-only operation falls to 11.2 electrical-to-fuel and 3.7% solar-to-fuel efficiency, below the ceiling of photosynthesis, against 24.7 and 8.1% for H2 (only just above algal photosynthesis). Our choice between a formate-only system and one coupled to H2 oxidation or EEU therefore depends on our belief about the trajectory of CO2 reduction technology. If whole-cell voltages continue to fall at the rate of the past decade, formate alone is the right target, and the simplicity of its workflow is bought at low cost. However, if that improvement plateaus, the electron delivery mechanism must be swappable, and a system should be designed from the outset so that it can be. At the US Department of Energy SunShot target of 2 cents per kilowatt hour, the electricity to make a US gallon of butanol costs $1.40 for a formate-only system at the state of the art, rising to $5.45 at the highest scaled-up electrolyzer voltage reported, against $1.23 and $2.47 for formate and H2 system.

Computational safety evaluation of phytochemical libraries commonly relies on models trained on experimentally tested compounds and applied to much larger and chemically diverse collections. An important but often overlooked question is whether predicted compounds are adequately represented within the experimental chemical space underlying these models. Here, we examined this question for the Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT) database using experimentally characterized datasets for three anti-target endpoints: hERG blockade, cytochrome P450 (CYP) inhibition, and pregnane X receptor (PXR) induction. After structure standardization, 14,956 unique IMPPAT compounds were compared with 8,877 hERG, 4,905 CYP, and 4,138 PXR reference compounds using consensus nearest-neighbor similarity based on Morgan and atom-pair fingerprints. At a Tanimoto similarity threshold of 0.80, only 0.92%, 0.30%, and 0.46% of IMPPAT compounds had close measured analogs in the hERG, CYP, and PXR datasets, respectively. Relative to the internal nearest-neighbor distributions of the reference datasets, a typical IMPPAT compound lay near the 1st percentile, indicating substantial chemical-space separation. Compounds with close experimental analogs also showed distinct molecular characteristics, with descriptor-based logistic regression yielding cross-validated AUC values of 0.77-0.80. Plant-level enrichment was markedly reduced after excluding widely distributed metabolites and was further restricted when the nearest measured analog was required to have pIC50 or pEC50 [≥] 5. The remaining signals were concentrated in a limited number of taxa, including Rauvolfia, Sinopodophyllum/Dysosma, Cinchona, and Catharanthus roseus. Overall, most IMPPAT phytochemicals lack close structural representation among currently measured anti-target compounds. Computational safety predictions for these molecules should therefore be interpreted as extrapolations and accompanied by explicit measures of structural support. Absence of a close experimental analog should be regarded as a gap in available evidence rather than evidence of safety.

Animal-derived surface coatings present the gold standard in stem cell culture. However, they come with major drawbacks such as lot-to-lot inconsistency and an ethically problematic production. Approaches to develop synthetic coating alternatives have largely failed to recapitulate biological functions essential to PSC-self renewal and differentiation. In this study, we have investigated the suitability of a fully synthetic, chemically defined extracellular matrix-mimicking coating named BIOINSTRUCT for hiPSC culture. BIOINSTRUCT was employed during maintenance culture of IMR90-4 cells, as well as directed differentiation of HIHCNi008-A, ACTN2-GFP, and UKKI-011-A cells. BIOINSTRUCT preserved hiPSC characteristics over the experimental period of 10 passages similar to Matrigel. Spontaneous differentiation resulted in the formation of ectodermal, mesodermal and endodermal derivatives, confirming the retention of pluripotency. Directed differentiation on BIOINSTRUCT enabled the generation of neuronal, cardiac and pancreatic endocrine cells. Altogether, our data underscore BIOINSTRUCT as a promising alternative to animal-derived extracellular matrix coatings.

The enzymatic oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid (FDCA) is a key step in the sustainable production of polyethylene furanoate (PEF), yet the final oxidation of 5-formyl-2-furancarboxylic acid (FFCA) to FDCA remains the principal bottleneck for industrial application. Although hydroxymethylfurfural oxidases (HMFOs) can catalyze this transformation, naturally occurring enzymes with high FFCA-oxidizing activity remain largely unexplored. Here, we present an iterative computational bioprospecting campaign to identify natural HMFOs with improved activity toward this rate-limiting reaction. Across four successive rounds, the computational workflow evolved from conservative homology-based screening to large-scale sequence mining assisted by machine learning, with each iteration redesigned according to the principal limitations identified through molecular simulations and experimental characterization. This adaptive strategy led to the discovery of several natural HMFOs with substantially improved FFCA oxidation activity, including candidates whose performance under the tested conditions approached that of the engineered benchmark 8BxHMFO. Beyond the identification of promising biocatalysts, the study demonstrates the value of continuous integration of computational prediction and experimental feedback for refining enzyme discovery campaigns, and provides practical insights into balancing catalytic prioritization, sequence diversity, developability, and computational scalability in future simulation-guided bioprospecting efforts.

Polyhydroxyalkanoates (PHAs) are microbial polyesters that represent a sustainable alternative to fossil fuel-based plastics. These biodegradable polymers have properties similar to conventional plastics and can be produced from waste materials. The key enzyme in PHA synthesis is PHA synthase (PhaC) and despite its importance, only a few PhaCs from extremophilic microorganisms have been characterised in detail. Here we characterised PHA synthase enzyme from the thermophilic bacterium Caldimonas thermodepolymerans DSM15344, an attractive candidate for PHA production from lignocellulosic residues due to its unique properties such as utilisation of xylose-rich substrates and high PHA yields on this pentose sugar. PhaC was successfully expressed in the surrogate host E. coli BL21 (DE3) GOLD, purified to homogeneity and its enzymatic activity was confirmed in vitro. The optimal pH range and temperature were determined as 6.3-6.9 and 50 {degrees}C, respectively. The melting temperature of PhaC was detected at 57.83 {+/-} 0.04 {degrees}C and the enzyme storage stability was assessed. The tertiary structure, including the enzyme active site, was predicted using available bioinformatic tools and the predicted catalytic residues were supported by site-directed mutagenesis. This study represents the first biochemical characterisation of PHA synthase from C. thermodepolymerans, expanding the limited set of characterised thermophilic PhaC enzymes.

BACKGROUND Botanicals are widely consumed as herbal remedies and plant-derived products, but their complex and variable chemical composition presents major challenges for safety assessment. Although hepatotoxicity has been reported for several botanicals, the constituent compounds responsible and the underlying mechanisms often remain poorly characterised. OBJECTIVES We aimed to determine whether Cell Painting could identify candidate constituent drivers of botanical bioactivity and generate hypotheses about potential mechanisms of action in primary human hepatocytes. METHODS We profiled 13 botanical extracts and 85 known constituents across multiple concentrations using Cell Painting alongside assays of metabolic activity and membrane integrity. To interpret morphological phenotypes, we trained machine-learning models using a Cell Painting reference atlas of >1,000 chemicals linked to ToxCast/Tox21 molecular and cellular bioactivity annotations. RESULTS Cell Painting detected bioactivity in 11/13 botanical extracts and 46/85 constituents, compared with 9/13 extracts and 40/85 constituents in the cell-health assays, and generally detected activity at lower concentrations. For 9/13 extracts, at least one constituent was active at a lower concentration than the corresponding botanical extract, supporting the contribution of a subset of potent constituents to mixture-level responses. Aristolochia and goldenseal were the most potent extracts across Cell Painting and cell-health assays and contained highly active constituents. Reference-atlas models generated specific mechanistic hypotheses, including cytotoxicity-, endocrine-, and genotoxicity-associated responses for several botanicals and constituents. CONCLUSION These results support Cell Painting combined with machine learning as a sensitive approach for characterising cellular responses to botanicals, prioritising candidate constituent drivers of hepatotoxicity-associated phenotypes, and generating testable hypotheses about potential mechanisms of action.

G protein-coupled receptors (GPCRs) represent the largest membrane protein family in the human body and the major targets of FDA-approved medications. Unlike some other physiological proteins, GPCRs are highly plastic and often exist as collections of conformational ensembles in the environment to exert their function. Therefore, understanding how a GPCR adopts different conformational ensembles in response to ligands and signaling partners is essential for drug development. 19F-NMR has emerged as one of the most promising tools in this regard; however, a well-established 19F-labeling system is still lacking, including an effective 19F probe that meets both environmental susceptibility and NMR sensitivity requirements, even though progress has been made dramatically in recent years. Thus, this manuscript reports a novel conformational probe (4-(bromomethyl)-ethoxy-2-(trifluoromethyl)benzene, BTMB) that offers paramount benefits for future GPCR conformational dynamics studies. To rationalize the mechanism behind BTMB's superiority for future probe development, we performed MD simulations, referenced to the current state-of-the-art probe, BTFMA. Our study suggests that the spatial proximity of aromatic residues significantly influences the chemical shift dispersion and linewidths of related 19F-probe-profiled conformational states, as well as the rigidity and compactness of -CF3 in the target protein.

Characterizing the enzymatic accommodation of circular agricultural fertilizers is critical for informing strategies to remediate widespread soil sulfur hunger. Here, we present an exploratory in-silico investigation evaluating the active-site cleft of sulfate thiohydrolase (SoxB) across representative soil Proteobacteria. Following the crystallographic precedent of uncomplexed thiosulfate in PDB 2WDE, site-directed molecular docking indicated that the free thiosulfate polyanion binds favorably within the catalytic pocket (predicted affinity: -3.506 kcal/mol), yielding a substantially lower empirical energy barrier than hydrophobic elemental sulfur (S8, -1.409 kcal/mol). Comparative evaluation against the alkaline-adapted Thiobacillus denitrificans homolog revealed an elevated predicted binding affinity of -4.610 kcal/mol, suggesting a potential structural accommodation in high-pH calcareous soils (pH > 8.0). Unrestrained 5.0 ns all-atom molecular dynamics in explicit TIP3P solvent demonstrated initial structural stability of the unliganded host backbone (RMSD = 1.10 +/- 0.15 Angstrom). Energetic decomposition indicated that ligand association is governed predominantly by electrostatic interactions (delta-E_elec ~ -40 kcal/mol) with basic residues (His146, His269, Trp147; RMSF < 0.60 Angstrom), with a single-trajectory unbinding event observed at 3.2 ns. These computational observations provide an exploratory baseline characterizing the active-site electrostatic landscape of SoxB, generating working hypotheses for downstream empirical soil microcosm and in-planta trials.

An increasing number of researchers, educators, and at-home growers are turning to hydroponics as an alternative method of food production, diversifying and strengthening the food supply chain. This has led to a substantial increase in the amount of academic work involving hydroponic production of plants for a variety of purposes, including but not limited to a more controlled and customizable environment than conventional production methods, utilizing hydroponics as a method of wastewater treatment, and investigating the vertical production of plants on a much smaller footprint than traditional commercial-scale production. Because so many unique stakeholders are interested in hydroponics for a variety of reasons, academic studies use a wide variety of hydroponic systems with varying levels of technology and automation, making comparisons across studies and systems challenging. A few institutions have sophisticated plant growth and research facilities, like those used by commercial companies, but these systems are often prohibitively expensive, costing upwards of $10,000 USD for a very limited amount of growing space for experimental trials. To enable more researchers, educators, and citizen scientists to conduct experiments and easily compare their results, this study details three pilot-scale hydroponic production systems (Kratky, NFT, and DWC), utilizing entirely off-the-shelf components, for under $5,000 USD each, that are capable of maintaining the desired consistent temperature and relative humidity levels, and have space for 216, 108 (6 irrigation loops), and 64 (16 irrigation bins) plants, respectively. The material lists and prices are provided along with assembly instructions and general guidelines for each hydroponic system. The testing and optimization process of environmental conditions within each growth system is also detailed, with suggested customizations for potential experimental setups. The authors developed these systems during their Masters and Doctoral degree programs, enabling improved hydroponic research at the University of Illinois Urbana-Champaign. They hope that other aspiring hydroponic researchers can benefit from this work in the development and operation of their hydroponic systems, increasing research efficiency and collaboration opportunities in this field of study.

The cornea is the outermost layer of the eye, most vulnerable to injury including from chemical exposure, either environmental, industrial or chemical weapons. For example, exposure of the eye to sulfur mustard (SM) can cause mustard gas keratopathy, resulting in devastating consequences for vision. Available treatments for corneal mustard keratopathy are either ineffective, or if used for a prolonged time, have deleterious side effects. Here, we aimed to harness the anti-inflammatory and anti-angiogenic peptide angiotensin-(1-7), known as Ang-(1-7), that is derived from the renin-angiotensin system (RAS). We designed and developed a protein-like polymer (PLP) displaying a brush of norleucine modified Ang (1-7) peptides (NLE Ang (1-7) PLP), which is a more potent derivative of Ang-(1-7), for administration as an eye drop. In a mouse model of nitrogen mustard (NM)-induced corneal injury, topical treatment and intraperitoneal (i.p.) injection of NLE Ang (1-7) PLP persistently minimized: (i) corneal haze; (ii) edema; (iii), expression of pro-inflammatory and pro-angiogenic genes; and (iv) neovascularization and conjunctivalization as evidenced after a prolonged treatment and recovery period. Collectively, our observations have demonstrated the efficacy of this novel polymer proteomimetic based eye drop treatment in reducing chemical agent-induced corneal injury as well as indicating its potential application in other ocular surface diseases associated with inflammation and angiogenesis.

With the increase of recycled water to offset water demand, the potential possibility to spread contagious RNA viruses, such as Coxsackievirus B3, increases. However, detection of viral particles remains challenging because of low viral concentrations in wastewater and high mutation rates of the RNA virus. Robust monitoring is needed with low cost and low infrastructure technologies to increase accessibility of monitoring technologies worldwide. Novel viral detection methods have been developed, based on synthetic riboswitches that bind to the target virus and trigger a reporter gene, thus amplifying the detection signals. Such monitoring technologies can leverage machine learning to optimize the candidate nucleic acid sequences used for detection. To support the design of effective riboswitches, we present a machine learning model for classifying riboswitch performance, integrating RNA sequence data with secondary structural features based on free energy calculations and parameters that represent single strandedness. This model uses a sparsely gated Mixture of Experts (MoE) architecture to route sequence and thermodynamic features to specialized experts, achieving strong generalization performance across cross-validation and held-out testing. When evaluated against baseline Decision Tree, Random Forest, Gaussian Naive Bayes, and Dense Neural Network classifiers, the MoE model demonstrated near-zero classification errors. Furthermore, post-hoc feature importance and k-mer analyzes reveal that near-perfect predictive performance in silico is strongly driven by sequence constructs in addition to generalizable folding mechanics. An ablation study of numerical feature and sequence inputs showed that while the Dense Neural Network also achieved high accuracy across all ablation conditions, the MoE architecture was retained as the primary model because its specialized subnetworks do not require all model parameters to be activated offering a potential computational advantage.

Liquid-liquid phase separation (LLPS) of biomacromolecules has been shown to influence a large variety of biological processes via the formation of membraneless organelles. Aberrant LLPS, however, has been implicated in a number of oncological and neurodegenerative disorders. Proteins related to Alzheimer's, Parkinson's diseases and other major amyloidoses have all been shown to form these condensates. Interestingly, some amyloidogenic proteins were demonstrated to form heterotypic droplets, where both molecules coexisted within the same condensate and affected each other's aggregation. While such cross-interactions have been reported numerous times under non-LLPS conditions, the heterotypic droplet assemblies were only shown for a very limited number of amyloidogenic proteins. In this work, we examine heterotypic LLPS of prion proteins and the pro-inflammatory S100A9, whose cross-interaction under non-LLPS conditions we confirmed in a previous work. The results show that this interaction under condensation-promoting conditions enhances their aggregation, leading to the formation of a higher concentration of amyloid structures. These findings suggest that the pro-inflammatory S100A9 may have a critical role in promoting prion protein aggregation via the assembly of heterotypic condensates under high molecular crowding conditions.

Biofilm mechanics depend strongly on growth history, hydration, nutrient availability, and interfacial attachment, yet conventional rheology requires harvesting and transfer that can perturb the as-grown structure. Here, we introduce bioRheoFlow, a 3D-printed rheometer-mounted platform for cultivation and mechanical characterization without sample transfer. The platform combines evaporation compensation with static or axial nutrient flow, and benchmark measurements validate its rheometric performance. Applied to Pseudomonas putida and Pantoea sp., bioRheoFlow reveals that biofilms cultivated in situ under axial flow exhibit substantially higher elastic moduli than conventionally grown and scraped samples. Despite similar linear-viscoelastic stress ranges, the species show distinct nonlinear responses: P. putida exhibits a lower crossover stress and more abrupt failure, whereas Pantoea sp. sustains larger stresses and deformations. Creep suggests contributions from bulk deformation and biofilm-substrate interactions. bioRheoFlow provides a controlled framework for probing growth-conditioned mechanics in living biofilms.

Traumatic brain injury (TBI) is a leading cause of long-term neurological disability, affecting 50-60 million people annually. Cascading secondary injury mechanisms, including oxidative stress and neuroinflammation, impair motor and cognitive function, while current therapies often manage symptoms rather than restore lost neurological function. This study investigated an ultrasound-activated piezoelectric hydrogel scaffold composed of barium titanate nanoparticles (BTNPs), sodium alginate (SA), and polyethylene oxide (PEO). The hypothesis was that TBI flies receiving the scaffold and ultrasound would display a higher climbing assay pass rate than TBI flies receiving no treatment or BTNPs alone. TBI was induced in Drosophila melanogaster with a high-impact trauma (HIT) apparatus. Treatments were applied by opening and resealing the fly head cuticle, followed by ultrasound stimulation. Motor recovery was quantified with a climbing assay across four groups (N=10 flies per group), which measured the percentage of flies that could cross a 5 cm mark within 30 seconds. Assay validity was supported by a statistically significant difference between flies without TBI and those with TBI using Mann-Whitney U testing (p=0.0035). Although TBI treatment groups did not differ significantly (p>0.05), median pass rates increased from injury control (35%) to BTNPs (45%) to scaffold (50%). However, high inter-trial variation, a 45.2% procedural mortality rate, and small sample size limited statistical power. These results suggest that piezoelectric electrospun hydrogel scaffolds may be a pathway for safer and more biocompatible restoration after TBI, but provide insufficient evidence to conclude that the scaffold significantly improved motor recovery.

Influenza A virus (IAV) defective interfering particles (DIPs) are regarded as promising broad-spectrum antivirals due to their high efficacy demonstrated in animal trials. Previously, an OP7 chimera DIP was generated that showed markedly enhanced antiviral efficacy compared to conventional IAV DIPs. In addition, a high-yield cell culture-based production process for OP7 chimera DIPs was established in perfusion mode. However, due to the technical complexity of this technology, we aimed to combine the advantages of perfusion in terms of yield with that of a simple and less complex batch process. In the present work, we established a fed-batch production process for OP7 chimera DIPs that allows a more straightforward implementation into existing production facilities. Using a feeding regime that was able to overcome the cell density effect, we achieved productive virus infection in stirred tank reactors until a cell density of 10E+6 cells/mL. Furthermore, we obtained a high virus titer of 3.8 log10(HAU/100 uL), corresponding to a 3.4-fold increase compared to a reference batch production. Moreover, the produced material demonstrated a significantly increased interfering bioactivity shown by an in vitro potency assay. Interestingly, this efficacy was similarly high as compared to OP7 chimera DIP material previously produced in perfusion mode, despite twofold lower virus titers. Finally, we demonstrate robustness of OP7 chimera DIP seed virus trains, which is significant step towards later pharmaceutical production. Further, corresponding GMP MDCK-PB2(sus) cell and OP7 chimera virus banks are now available for later biomanufacturing further use. In conclusion, the established fed-batch process offers a valid n additional option for pharmaceutical grade OP7 chimera DIP GMP manufacturing production under GMP conditions required for subsequent clinical testing and for later large-scale manufacturing.