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In this article, we propose a versatile and modular camera system designed for a wide range of research applications, with a particular focus on multi-camera and camera array setups. Current camera setups-whether single, stereo, or array configurations-are rarely available off-the-shelf and typically require custom mechanical assemblies. The proposed system addresses this limitation by providing a building-block-style catalog of components that can be easily fabricated and assembled. It leverages modern consumer-grade hardware, which has significantly improved in recent years, offering affordable alternatives to industrial camera systems without sacrificing functionality. The modular design enhances reproducibility and flexibility and enables research into advanced imaging methods, including generic intrinsic and extrinsic camera calibration.
Transcription factors ( TFs ) cooperatively drive gene regulatory networks ( GRNs ) to establish transcriptional states. Forced induction of TFs in combination can reprogram cell state by supplanting existing GRNs. Thus, TFs and GRNs are the building blocks to engineering transcriptional state. However, one key challenge is that the relationship between TF combinations and GRNs remains largely uncharacterized and difficult to accurately predict. Here, we apply single-cell overexpression screens to map the combinatorial activities of ∼100 TFs to gene expression states. Our analysis identifies diverse TF combinations driving cell-type specific regulatory programs. Notably, different TF combinations induce shared gene sets with cell-type specific functions, suggesting a modular regulatory architecture of the transcriptome. Furthermore, we define pairwise TF interactions and show that cooperative interactions improve transcriptional reprogramming. Finally, we developed tools to predict combinatorial TF phenotypes. These findings improve our understanding of cell state and how to manipulate it for biomedical applications. Combinatorial over-expression screens for ∼100 transcription factors (TFs).Diverse TF combinations drive cell-type specific regulatory programs.TF regulatory networks reveal a modular regulatory architecture of the transcriptome.TF-TF interactions and predictive models enhance reprogramming cocktails.
High-performance cell-free protein synthesis has transformative potential for synthetic biology, yet the prohibitive costs of Protein synthesis Using Recombinant Elements kits and the labor intensity of in-house preparation have restricted accessibility and scalability. We developed Purified components Optimized for Flexible protein expression using in vitro-produced translation factors (i-POPFLEX), a modular cell-free protein synthesis system in which 34 translation factors and a split T7 RNA polymerase are individually synthesized in vitro and assembled using automated liquid handling. This workflow minimizes manual input and supports parallelized production, generating complete, ready-to-use systems within 2 days. i-POPFLEX achieves up to 8.4-fold higher protein yields and a 96% cost reduction (27-fold lower cost) compared with commercial kits. Its flexible architecture also enables selective component inclusion for genetic code reprogramming and site-specific incorporation of noncanonical amino acids. By coupling modular design with automation, i-POPFLEX provides an accessible, customizable, and economically viable platform for next-generation biomanufacturing workflows.
To create modular solutions for interactive real-time MRI using reconstruction algorithms implemented in BART. A new protocol for streaming of multidimensional arrays is presented and integrated into BART. The new functionality is demonstrated using examples for cardiac interactive real-time MRI based on radial FLASH, where iterative reconstruction is combined with advanced features such as dynamic coil compression and gradient-delay correction. We analyze the latency of the reconstruction and measure end-to-end latency of the full imaging process. Reconstruction pipelines with iterative reconstruction and advanced functionality were built in a modular way using scripting. Latency measurements demonstrate latency sufficient for interactive real-time MRI, on the order of 30 ms for BART processing and network transfer time, or 200 ms for end-to-end latency including acquisition, vendor processing, and display. With the new streaming capabilities, real-time reconstruction pipelines can be assembled using BART in a flexible way, enabling rapid prototyping of advanced applications such as interactive real-time MRI.
Radial neck osteolysis is frequently reported after press-fit pyrocarbon radial head arthroplasty (RHA) and has been proposed as a marker of impaired outcome beyond a 3 mm threshold. Whether this association holds at short-to-midterm follow-up with the MoPyC implant is debated. We retrospectively analysed 16 consecutive adults who underwent modular press-fit pyrocarbon RHA (MoPyC, FX Solutions) for unreconstructable radial head fractures between 2010 and 2023. Clinical evaluation comprised the Mayo Elbow Performance Score (MEPS), QuickDASH, visual analogue scale (VAS) for pain and goniometric range of motion. Anteroposterior and lateral radiographs and a systematic final follow-up CT scan were assessed by a single senior orthopaedic surgeon for radial neck osteolysis depth (mm), periprosthetic radiolucency, stress shielding, Delta sign, heterotopic ossification (Brooker grade) and humero-ulnar osteoarthritis. Associations between osteolysis depth and functional scores were analysed using Spearman rank correlation with exact permutation tests (10 000 permutations) and Fisher z 95% confidence intervals. All analyses were exploratory. Median follow-up was 36 months (range 12-110). Mean MEPS was 80.6 ± 11.7, QuickDASH 20.4 ± 7.5 and VAS 2.2 ± 2.3. Mean flexion was 140 ± 9°, extension deficit 16 ± 11°, pronation 74.5 ± 7.2° and supination 70.8 ± 16.9°. Any radial neck osteolysis (> 0 mm) was found in 12/16 patients (75.0%), reached 2 mm in 9 (56.2%) and reached the 3 mm threshold in only 1 patient (6.2%); mean depth was 1.68 ± 1.20 mm (range 0-3.16). Osteolysis depth was not correlated with MEPS (ρ =  + 0.31, 95% CI - 0.22 to + 0.70, p = 0.24), VAS pain (ρ =  - 0.17, 95% CI - 0.61 to + 0.36, p = 0.54) or any range-of-motion variable; a non-significant trend toward lower QuickDASH with deeper osteolysis was observed (ρ =  - 0.48, p = 0.07), opposite to the working hypothesis. Secondary radiographic findings (Brooker ≥ II 43.8%, humero-ulnar osteoarthritis 43.8%, stress shielding 31.2%, Delta sign 25.0%) were not associated with MEPS (all p > 0.15). One patient (6.2%) underwent ulnar nerve neurolysis; no implant was revised. In this small exploratory cohort of modular press-fit pyrocarbon RHA, radial neck osteolysis ≥ 3 mm was rare and no association was found between osteolysis depth and functional outcomes. These findings do not support the use of an isolated 3 mm osteolysis threshold as a clinical warning sign in this implant at short-to-midterm follow-up. Retrospective case series.
Mollusca, the second-largest animal phylum, includes many aquaculture species used as important food resources for humans. While DNA viruses that threaten molluscan aquaculture have received much attention, molluscan RNA viromes are still understudied. Here, using a multi-stage RdRP discovery pipeline combining six-frame translation, profile-based homology search, and phylogenetic validation, 203 RNA viruses spanning five viral phyla and fifteen viral orders were identified, based on 223 molluscan metatranscriptomes covering eight classes. Phylogenetic analysis, combined with structural modeling, revealed a significant increase in the number of Pisuviricota-related lineages. Extensive modular evolution in viral genomes was observed, including gene rearrangements and co-evolution of capsid and RdRP genes. Host prediction linked 76% of the RNA viruses to a range of eukaryotes. These findings expand the diversity of RNA viruses associated with molluscs and shed light on their phylogenetic relationships, highlighting that molluscs might serve as an important reservoir of diverse RNA viruses infecting a range of eukaryotic hosts.
The structure of phospholipid headgroups and chains are well-established drivers of membrane elastic properties, but functions for different chemistries that join these moieties together are poorly understood. While canonical phospholipids feature ester linkages, alkyl ether- and plasmenyl-linked species emerged in prokaryotes, are highly abundant in metazoans, and have been implicated in neurodegeneration and aging. Ether phospholipid chemistry, and plasmenyl linkages in particular, arose independently several times in evolution, suggesting conserved functions in the structure of cell membranes. Here we combine experiments and molecular simulations to determine how backbone linkage chemistry modulates membrane mechanics. We find that ether linkages additively promote negative intrinsic curvature, destabilizing bilayers and enhancing membrane fusion. They also decouple membrane stiffness from viscosity, softening membranes while maintaining packing in the hydrophobic core. The plasmenyl linkage uniquely stabilizes the inverted hexagonal phase by lowering the energetic cost of chain stretching, providing a rationale for the evolution of its biosynthesis. These results explain the fusogenicity of ether lipids and show how they regulate membrane topology through multiple physical mechanisms. We propose that phospholipid backbone linkage chemistry constitutes a modular control element for membrane mechanics and topology. The structure and dynamics of cell membranes can be sensitive to small chemical changes in their phospholipid building blocks. Phospholipids with ether bonds connecting their glycerol backbone and hydrocarbon chains have long been proposed to impart chemical stability to thermo- and acidophile microbial membranes, but have more recently been identified as major components of mammalian tissues. We show that ether linkages promote membrane dynamics through imposition of a canonical molecular geometry and by decoupling of bending stiffness from chain ordering. Plasmalogen lipids, in which the ether linkage is modified with a vicinal double bond, further promote non-lamellar topologies through a chain-stretching mechanism. These biophysical features suggest a basis for the repeated emergence of ether phospholipids in evolution and their observed functions in membrane trafficking. The thermodynamic and structural bases of plasmalogen function are especially notable as these lipids have been increasingly implicated in neurodegenerative and cardiovascular disease.
Nanoparticles are now central to many drug and vaccine delivery strategies, but most require reformulation for each application. Bacteriophage‑derived nanoparticles offer a genetically encoded, structurally defined, and modular alternative. This review organizes recent advances along three tunable axes - scaffold, surface, and cargo - and highlights hybrid phage-polymer/lipid/inorganic constructs that expand stability, targeting, and loading. We survey applications from multivalent vaccines and oversized gene transfer to precision microbiome editing, and outline translational hurdles. Phage-derived products are approaching translation, with virus-like particle-based vaccines and CRISPR-enhanced antimicrobial phages in clinical trials. Finally, we preview emerging opportunities, including AI‑guided capsid and receptor‑binding protein design, cell‑free phage synthesis, and standardized 'reference' phage chassis that can be combined with traditional nanoparticles, positioning phage nanoparticles as reusable, plug-and-play nanomedicines.
Although veterinary vaccines against West Nile virus (WNV) have been developed, no approved human vaccine is currently available, highlighting the need for scalable and safer WNV vaccine candidates. In this study, a recombinant WNV subunit nanoparticle vaccine was developed by displaying the envelope protein domain III (ED3) on a cholera toxin B subunit (CTB) pentameric scaffold. The resulting recombinant protein comprising CTB-ED3 was expressed predominantly as soluble nanoparticles in Escherichia coli. Immunized mice produced strong humoral responses with balanced IgG1/IgG2a ratios, and some constructs achieved neutralizing titres comparable to those elicited by formalin-inactivated WNV. Importantly, no cross-reactivity with other flaviviruses was observed, alleviating potential concerns about ADE. These findings demonstrate that CTB-ED3 is assembled into multimeric nanoparticles in bacteria, offering a cost-effective, scalable, and biosafe platform for developing subunit nanoparticle vaccines against WNV and potentially other flaviviruses.
Currently, in vitro models of microvascular biology rely on self-assembly of vascular cells in compatible gels. However, the stochastic nature of this process results in large variations in lumen sizes, perfusion continuity, and shear stresses, making systematic and reproducible analysis challenging. Here, we report a new technology to generate artificial capillaries on a chip with custom control over lumen sizes and architectures using a combination of femtosecond laser cavitation and collagen casting within multi-chambered microfluidic chips. The design allows seeding of endothelial cells within capillary-sized microchannels and seeding of stromal cells within top-open silos, with independent control over seeding sequence and media compositions. Results show that endothelialized microchannels, coined as artificial capillaries, exhibit excellent barrier function with reproducible control over lumen sizes (ϕ=8-40µm) and their architectures (straight, curvatures, tapered, branched). The physical flow parameters measured across the lumen (namely, flow shear) and at the channel outlets (flow velocities) have been validated against high-fidelity numerical assessments from the Large Eddy Simulation scheme within the digitized versions of microchannels. The experiment-computation compatibility enabled us to predict changes in regional velocity and wall shear stresses within artificial capillaries for various capillary architectures. We also show that in situ editing of artificial capillaries in the form of adding new branches or adding occlusions is possible. Lastly, we developed a co-culture model that enables the study of stromal cells with artificial capillaries using conventional imaging methods. We envision that acellular chips with two seeding ports can be readily shipped worldwide and could potentially be adopted as a new technology to study microvascular biology in a reproducible manner.
The properties of functional brain networks are an important determinant of cognitive function in aging and dementia. Despite this, few studies have comprehensively examined demographic and biopsychosocial predictors of functional brain networks, and none have attempted to do so across the adult lifespan while accounting for collinearity among these predictors. The current study used data from 525 individuals between the ages of 35 and 100 years from the Human Connectome Project 2.0 Lifespan Release, which includes task-based functional neuroimaging, physical and emotional health, and demographic information. Two functional brain network properties previously identified as moderators of cognitive functioning across the lifespan, entropy (regional specialization) and modularity (network segregation)-were used as outcome metrics in elastic net regression models that identified and ranked predictors of these metrics as well as their age-interaction terms. Our models ranked and established generalizability of key biopsychosocial health determinants of brain network properties across the lifespan using methodology allowing for high collinearity among predictors, differing notably from correlational findings. Derived models ranked biological sex, sleep duration, instrumental support, visual acuity, education, social isolation, diastolic blood pressure, and vigorous physical activity as the strongest generalizable factors. Biological sex exhibited a significant moderation effect such that males demonstrated greater age-related differences in entropy and modularity compared to females. Given that these brain network properties have previously been linked to cognitive functioning, understanding the complex interplay between these biopsychosocial determinants is crucial for informing intervention targets with the greatest potential for maintaining or improving cognitive functioning in aging.
The Amazon Arc of Deforestation is facing a silent decline in ecological functionality. Using four decades of high-resolution land cover data, we reveal a dramatic decline in functional connectivity across deforested areas in the Brazilian Amazon. Analyzing 40 targeted large-scale forest landscapes across Pará, Mato Grosso, and Rondônia, we quantified connectivity for key ecological processes-seed dispersal, pollen dispersal, and gap-crossing capacity of animals-using graph theory metrics. Between 1990 and 2020, the connectivity dropped by up to 50% in highly deforested regions, even when accounting for stepping-stones. Simultaneously, spatial modularity increased in nearly all study regions, in some by more than 25%, reflecting a more compartmentalized landscape structure. Forest fragment distances rose, and mean patch area fell sharply, compromising dispersal and potentially gene flow. Our results suggest a potential breakdown of spatial connectivity within the targeted zones of the Amazonian forests, except in the Western Pará region, where higher connectivity and lower modularity still prevail. Without urgent connectivity-enhancing strategies, even remaining forest patches may become functionally isolated, threatening the maintenance of biodiversity.
To develop and illustrate the potential of a new, flexible, open-source software engine for task-based optimisation of exposure parameter settings in x-ray projection imaging.

Approach: The engine was built with several modules scripted in Python, to automate the different processes of optimisation of exposure parameters. Input is taken from a set of pre-calculated data containing image quality and dose metrics, and system parameters defined by the user. Modular code is employed, with classes responsible for image quality and dose calculations. For this study, the image quality (IQ) module
incorporated the standard signal-to-noise ratio (SNR) and a version of SNR (SNRw) that is weighted for the influence of the x-ray focus size and finite x-ray pulse width on the task. Optimal x-ray factors for a specified task are established by the Optimizer class that maximizes an FOM defined as SNR2 or SNRw2 divided by dose. A set of six experiments with different degrees of complexity was performed to illustrate the
engine and the influence of x-ray factor selection for a cardiac imaging task.

Main Results: A full parameter search covering 2400 different combinations of tube potential, additional copper filtration and focal spot size for 11 distinct patient thicknesses took approximately 30 minutes. The six experiments demonstrated that it is essential to consider x-ray tube power limitations and, when applicable, object motion and dose limits when determining the optimal exposure parameters.

Significance: The proposed engine automates optimal exposure parameter selection for user-defined image quality metrics and dose estimates. The influence of x-ray system parameters on system performance can be explored systematically. The engine is provided as an open-source resource with a modular structure that can be extended to include different figures of merit, image quality and dose metrics. The repository containing the engine is available at https://gitlab.kuleuven.be/medphysqa/deploy/flexpose/flexpose.
Targeted microbubbles (MBs) have emerged as pivotal dual-functional agents for molecular ultrasound (US) imaging and US-triggered targeted drug delivery. However, the efficacy of traditional ligand-directed MBs is often compromised by the inherent heterogeneity of tumor receptor expression and physiological barriers. Herein, we report a robust targeting platform based on dibenzocyclooctyne-functionalized MBs (MB-DBCO) that leverages metabolic glycoengineering and bioorthogonal strain-promoted azide-alkyne cycloaddition (SPAAC). This strategy decoupled targeting efficiency from genetic receptor expression by pre-installing azide chemical handles onto the tumor cell surface. Our results demonstrate that MB-DBCO provides a stable "chemical anchor" in both 4T1 tumor cells and vascular endothelial cells, significantly enhancing contrast-enhanced ultrasound (CEUS) sensitivity and tumor cell specificity. Crucially, the synergistic combination of SPAAC-mediated covalent tethering and US cavitation-induced sonoporation breaches the endothelial cell barrier and tumor stromal barriers, driving the deep penetration of the paclitaxel (PTX) payload. In vivo studies showed that the MB-DBCO + US treatment leads to profound tumor regression, extensive vascular depletion, and a 100% survival rate in aggressive 4T1 tumor models. This study establishes a modular, chemically-defined, and scalable targeting platform that overcomes the critical biological barriers of solid tumors, offering a promising paradigm for CEUS imaging and US-triggered chemotherapy. STATEMENT OF SIGNIFICANCE: Contrast-enhanced ultrasound (CEUS) imaging and US-triggered targeted chemotherapy efficacy of dual functional microbubbles (MBs) is often compromised by heterogeneous receptor expression and the endothelial cell barrier of solid tumors. This study introduces a modular bioorthogonal platform that decouples tumor targeting from genetic markers by converting metabolic flux into a robust chemical interface for MBs anchoring. We demonstrate that this stable chemical-mechanical coupling enables localized cavitation to physically breach the tumor stroma, providing a scalable and universal framework for CEUS imaging and US-triggered targeted chemotherapy.
Peptide amphiphiles (PAs) offer modular control over biomineralization, yet the mechanisms by which they guide nanoparticle growth at the water-metal interface remain poorly understood. We employ molecular dynamics coupled with enhanced sampling methods to dissect residue-level interactions, component contributions, and full PA adsorption on Au(111) and Au(100). Using a modular PA incorporating the Au-binding Flg peptide (DYKDDDDK), we show that tyrosine dominates Au(111) adsorption, while charged residues largely remain in the adsorbed water layers. For individual amino acids and the beta-sheet forming region, orientation-resolved free energy landscapes reveal prominent backbone participation in adsorption to Au(111). In contrast, adsorption of the full Flg peptide and Flg-PA is dominated by the tyrosine side chain, with the peptide backbone remaining in solution. Cooperative effects among neighboring residues rationalize Flg's mineralizing capacity: the presence of at least one adjacent lysine enhances Tyr-mediated Au(111) adsorption, while a purely acidic local environment diminishes facet selectivity. The results provide the first atomically detailed framework for PA-Au interactions, providing guiding principles for future PA-based nanomaterial engineering.
Rare disease research and diagnosis rely on the integration of genomic and phenotypic data generated across diverse clinical sites; however, the absence of widely adopted standards for representing genomic data and associated metadata has limited data interoperability, reuse, and cross-study analysis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was established to investigate challenging rare disease cases and evaluate emerging multi-omic technologies for clinical translation. To support coordinated data integration across distributed research sites, we developed a common Consortium Data Model in partnership with domain experts to standardize the capture of participant-, family-, phenotype- and assay-level metadata, with a particular emphasis on using a modular architecture to support linking of multiple data versions from multiple omic technologies to a single individual and attribution of a genetic finding to the specific technology used for its initial discovery. Adoption of the GREGoR Data Model has enabled continued generation and public release of a harmonized, analysis-ready Consortium Dataset. The most recent release includes phenotypic, family and multi-omic data from 12,292 participants in 5,029 families. Other rare disease data sharing efforts are beginning to adopt this data model which will facilitate cross consortium analyses and empower rare disease research. This work demonstrates that a collaborative, flexible, and scalable data model can enable large-scale rare disease research, facilitate cross-center data harmonization, and enable data interoperability.
Recent advances in tissue clearing protocols such as DISCO, CUBIC, Clarity, FUnGI, and PEGASOS have revolutionized our ability to label and image intact 3-dimensional (3D) biological structures using fluorescence microscopy. The lactating mammary gland particularly benefits from clearing due to its high degree of tissue opacity. Cleared mammary gland images are strikingly beautiful and complicated but are difficult to fully interpret without developing a series of quantitative techniques and assays to analyze and compare them. These approaches will ultimately be as varied as the biology each scientist wishes to study. Here, we present one strategy based on a modular, hybrid, deep-learning approach and classical image processing that can segment and measure alveoli, cell nuclei and myoepithelial cells in intact mammary tissue. We have developed two original, three-dimensional (3D) U-shaped encoder-decoder networks (U-Nets), AlveoliNet and MyoNet, and combined these with CellPose3 nuclear instance segmentation and SlideBook/SlideBook Synergy binary mask operations. This approach can be used to easily score 100,000s of cells in intact tissue and differentiated glands at different developmental stages, genetic backgrounds, or treatments. We demonstrate the utility of this approach for quantifying the change in proportion of myoepithelial cells over the pregnancy-lactation transition, driven by endoreplication in the gland postpartum. We present a complete methods pipeline for other laboratories to utilize our approach in their own studies using standard desktop computers. Colin Monks is co-founder and co-President of Intelligent Imaging Innovations, Inc. (3i) and receives a salary from it.
Estuarine ecosystems exhibit strong environmental gradients and complex ecological processes. Here, we investigated the spatial patterns, ecological drivers and assembly processes of fungi across China's estuarine intertidal zones along a latitudinal gradient spanning the northern (NCS), eastern (ECS) and southern (SCS) coastal regions. The community α-diversity was higher in NCS and SCS than in ECS, whereas species richness was higher in ECS than in NCS and SCS. Community β-diversity increased significantly with geographic distance, with nitrate, organic carbon and ferric iron identified as the key environmental drivers. Niche analysis based on niche breadth (Levins' index) and species classification revealed a significant difference between the proportions of generalist species (32.92%) and specialist species (45.55%), and the mean niche breadth of fungal communities in NCS was significantly higher than that in ECS and SCS, reflecting the lowest environmental sensitivity. Neutral model analysis suggested that dispersal limitation was the predominant process shaping fungal community assembly, with its influence increasing from high- to low-latitude regions. Moreover, all fungal co-occurrence networks displayed weak modularity, highlighting a dispersed, non-modular interaction pattern among fungal taxa. These findings provide important insights into the macroecological patterns of intertidal fungal communities and their implications for ecosystem stability.
The incorporation of heteroatom-linked trifluoromethyl groups, such as N-trifluoromethyl (NCF3) and trifluoromethylthio (SCF3) motifs, remains challenging, particularly in the context of late-stage aryl functionalization. Herein, we report a flow-enabled platform that allows for the late-stage installation of NCF3 and SCF3 groups onto aryl frameworks through the coupling of flow-generated nucleophilic heteroatom-CF3 anions with aryl thianthrenium salts. In this strategy, readily available organic precursors are converted on demand into NCF3 and SCF3 anions using a CsF-packed bed reactor, allowing safe handling of highly reactive fluorinated intermediates while minimizing fluorinated waste. The resulting anions are subsequently engaged in a copper-mediated, photocatalytic cross-coupling, enabling efficient formation of aryl-NCF3 and aryl-SCF3 bonds under mild conditions. The method exhibits broad substrate scope and functional group tolerance, and is applicable to the late-stage diversification of medicinally and agrochemically relevant molecules. Overall, this work expands the scope of nucleophilic CF3X anions as viable partners in late-stage aryl functionalization and provides a modular platform for the discovery-oriented synthesis of fluorinated molecules.
We developed a gold-catalyzed (n + 4) (n = 5, 6) high-order dipolar annulation between imidazolidines or hexahydropyrimidines and alkynylcyclopropane ketones. This method provides a modular, atom-efficient strategy for accessing two libraries of synthetically challenging medium-sized diazaheterocycles in moderate to good yields under mild conditions. Control experiments on chirality transfer support a dominant stereospecific SN2 pathway that proceeds via a cyclopropyl oxonium-containing vinyl gold intermediate. Moreover, asymmetric catalysis, including kinetic resolution and dynamic kinetic asymmetric transformation, to enantioenriched products has been realized, highlighting the synthetic potential of this methodology.