Biology subjects

Sun, C.

Publications and source records attributed to Sun, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Balancing performance and complexity of dual-wedge prism-based spectroscopic single-molecule localization microscopy

Spectroscopic single-molecule localization microscopy (sSMLM) enables multiplexed super-resolution imaging by simultaneously acquiring the spatial position and spectral information of individual fluorophores. Dual-wedge prism (DWP)-based implementations provide a compact, alignment-stable approach to spectral dispersion, but trade-offs between localization precision, spectral precision, and experimental complexity remain. We systematically compare five DWP-based sSMLM configurations, including two-dimensional (2D) and three-dimensional (3D) implementations using single DWP (DWP-sSMLM) and symmetrically-dispersed DWP (SDDWP-sSMLM). We evaluate lateral precision, spectral precision, and ease of use. SDDWP configurations acquire spectral images in both channels and utilize both for spatial localization, yielding the highest lateral and spectral precision. However, for applications that do not require axial information, 2D-DWP provides a simple, plug-and-play solution with robust performance. This work offers a guideline for selecting DWP configurations based on experimental needs.

bioengineering↗

bioRxiv2026

A missing PEPC1 exaptation restricts C₄ evolution in palms (Arecaceae)

O_LIC4 and CAM photosynthesis evolved repeatedly across angiosperms, yet the four palm species examined here -- representing three of five Arecaceae subfamilies ([~]2,600 species total) -- all lack both. We hypothesized that this reflects the absence of PEPC1, a phosphoenolpyruvate carboxylase isoform required for C4 carbon fixation initiation and present in commelinids (Poaceae + Bromeliaceae) but whose distribution across monocots is unknown. C_LIO_LIWe surveyed six core C4 enzyme families by HMMER profiling across nine plant genomes -- four palms (Cocos nucifera, Elaeis guineensis, Phoenix dactylifera, Nypa fruticans), two grasses, one bromeliad, one basal monocot, and one fern. We constructed maximum-likelihood PEPC phylogenies and performed codon-based branch-site likelihood ratio tests using PAML. C_LIO_LIAll six enzyme families were present in palms. PEPC1 was detected in all commelinids (rice, maize, pineapple) but absent from all four palm species and outgroups. No palm PEPC sequence fell within the PPC-1 clade. Molecular dating indicates the Arecaceae-commelinid divergence ([~]120 Mya) predates PEPC1 origin ([~]105 Mya). Branch-site tests on the maize C4-PEPC1 branch were marginally significant (2{Delta}l = 3.03, p {approx} 0.082). C_LIO_LIThe absence of PEPC1 represents an ancestral molecular barrier that likely precluded C4 evolution in palms. This identifies a lineage-specific gene duplication as a constraint on photosynthetic pathway evolution in a major tropical plant lineage. C_LI

plant biology↗

bioRxiv2026

Dronedarone hydrochloride reverses obesity-related metabolic syndrome while preserving skeletal muscle mass

Obesity-driven metabolic syndrome poses a critical global threat, yet standard therapies like GLP-1 receptor agonists trigger substantial lean mass wasting, with muscle loss accounting for up to 40% of reduced weight. Here we identify a non-canonical metabolic application for dronedarone hydrochloride, an anti-arrhythmic benzofuran derivative. In diet-induced and ob/ob obese mice, short-term dronedarone hydrochloride administration dose-dependently reduces food intake, clears visceral and subcutaneous adiposity, and reverses steatohepatitis. Head-to-head trials show that dronedarone hydrochloride achieves glycemic control and fat clearance non-inferior to semaglutide, tirzepatide, and empagliflozin, but uniquely and completely preserves skeletal muscle mass. Mechanistically, dronedarone hydrochloride operates independently of central hypothalamic appetite-regulating neuropeptides and the peripheral leptin pathway. By decoupling fat reduction from sarcopenia, our findings establish dronedarone hydrochloride as a muscle-sparing therapeutic candidate for metabolic syndrome.

pharmacology and toxicology↗

bioRxiv2026

PEPC Gene Family Evolution Across Arecaceae: Complete Five-Subfamily Evidence for a Two-Lock Model of Irreversible C4 Exclusion

BackgroundC4 photosynthesis has evolved more than sixty times across flowering plants, but never in palms. Over 2,500 palm species have spent more than 100 million years in high-light, water-stressed habitats where C4 physiology would be advantageous, yet none have taken this path. Phosphoenolpyruvate carboxylase (PEPC) is the enzyme that gates entry into the C4 pathway. In every C4 grass, a commelinid-specific paralog called PEPC1 drives the CO2-concentrating mechanism that defines the syndrome. Until this study, one of the five palm subfamilies -- Ceroxyloideae -- had never been examined for PEPC gene content. ResultsWe present a complete PEPC census across 13 palm species spanning all five subfamilies (Calamoideae, Nypoideae, Coryphoideae, Ceroxyloideae, Arecoideae). Ceroxyloideae was characterized for the first time, using deep tBLASTn screening of ten million whole-genome shotgun reads. PEPC1 is absent from every palm species examined. Copy numbers are tightly constrained to 5-7 per genome, in stark contrast with the 6-25 copies found in grasses. A phylogenetic analysis of 337 PEPC sequences places all 55 palm loci at basal positions relative to the PEPC1 clade, consistent with the palm lineage having diverged approximately 120 million years ago -- roughly 15 million years before the PEPC1 duplication that occurred within the commelinids. Birth-death modeling reveals long-term gene family stasis in palms. Codon substitution analyses yield a genome-wide {omega} of 0.0582, indicating pervasive purifying selection and no signature of C4-specific adaptation. Coconut PEPC promoters uniformly lack the mesophyll-specific MESP-1/GT-1/DOF regulatory module that is required for C4-type gene expression. ConclusionsWe propose a Two-Lock Model of irreversible C4 exclusion in palms. The first is a Gene Lock: PEPC1 is phylogenetically absent from all five subfamilies. The second is a Regulatory Lock: the ancestral promoter architecture of palm PEPC genes lacks the cis-elements needed for mesophyll-specific expression. Together, these two locks -- one phylogenetic, one regulatory -- explain why C4 photosynthesis has never arisen in one of the largest C4-absent plant families. The model provides a testable framework for investigating other lineages that have remained closed to the C4 path.

evolutionary biology↗

bioRxiv2026

Super-Resolution Visual ProteomEx for Hard Tissues and Clinical Samples

Correlating nanoscale tissue architecture with unbiased molecular composition within the same specimen remains a fundamental challenge in spatial biology. Current spatial proteomics methods either lack the imaging resolution required to resolve nanoscale tissue architecture or achieve only limited proteome coverage, and untargeted approaches capable of deep protein identification have yet to be integrated with super-resolution imaging within a single workflow. Here, we present microProteomEx, an integrated platform that combines hydrogel-assisted tissue expansion with mass spectrometry-compatible fluorescence imaging, laser capture microdissection, and bottom-up proteomics to achieve simultaneous three-dimensional super-resolution imaging (effective lateral resolution down to [~]47 nm on conventional diffraction-limited microscopes) and spatially resolved proteomics at a scalable lateral resolution of 29-100 {micro}m (0.02-0.28 nL volumetric resolution). By optimizing fixation, protein anchoring, and a secondary re-embedding strategy, we extend the method to mechanically resilient tissues, including mouse kidney and heart, as well as to formalin-fixed, paraffin-embedded clinical specimens. We demonstrate single-glomerulus and single-plaque proteomics (450-1,000 proteins per structure), resolve proteomic differences between malignant melanoma and giant congenital melanocytic nevus in a rare pediatric case, and characterize the morphology-resolved molecular heterogeneity of cored versus diffuse amyloid-beta plaques in a mouse model of Alzheimers disease across two disease stages. microProteomEx establishes a broadly accessible framework for correlating tissue ultrastructure with deep spatial proteomics, with direct implications for disease biology, biomarker discovery, and precision medicine.

biochemistry↗

bioRxiv2026

Gaming Addiction Transmission: Interpersonal Neural Pathways Revealed by HYPER-NESS

Gaming addiction may be contagious through social interaction. In team competitive video games, individuals of varying addiction levels are often paired. This raises the question of whether, and through what mechanisms, one individuals addiction level is affected by other players. Methodologically, addressing this question requires understanding both what happens between brains and within individual brains during a gaming session. To this end, we used HYPER-NESS (Hyper Brain Network Estimation via Source Separation), a novel analytical framework to decompose and weight the distinct contributions of inter-brain and intra-brain processes to social brain networks. We applied this framework to a hyperscanning fNIRS dataset where dyads were scanned while playing a video game together against experimenters. We found that inter-brain and intra-brain contributions to the social brain networks were differentially associated with changes in game reward and social reward sensitivity, depending on the addiction level of ones partner. Granger causality analysis of both social and individual brain networks revealed influences from the high-addiction partner to low-addiction partner. Furthermore, significant cross-frequency coupling was found selectively between low-addiction players, supporting the idea that this form of inter-brain interactions underpins the joint processing of task-relevant rewards. To our knowledge, these findings provide the first neural-level account for the hypothesis that gaming addiction propagates though dyadic social interaction.

neuroscience↗

bioRxiv2026

Simultaneous regeneration of skin and bone in full-thickness cranial composite defects

Traumatic cranial defects often involve concurrent loss of soft and hard tissues and can progress to chronic defects due to delayed healing associated with infection or other co-morbidities. Despite autologous reconstruction remaining the clinical standard, it requires staged procedures using heterogeneous tissues, increasing operative time, costs, and surgical risks. Moreover, current tissue engineering approaches focus on single tissues or acute tissue defect models, limiting their clinical applications. Herein, we describe an acellular, material-driven 3D-printed composite scaffold designed to regenerate both bone and skin within composite cranial defects. The scaffold integrates controlled copper ion release from both organic and inorganic components with 3D-printed citrate polymer and citrate polymer-ceramic composites. Integrated thermoresponsive citrate-based hydrogels further enable spatially defined dermoconductive and osteoconductive properties, supporting a one-step surgical approach. At 12 weeks post-implantation, our scaffold enhanced keratinocyte organization, collagen deposition, and defect coverage with mature bone, achieving histological outcomes comparable to autografts. Furthermore, the system suppressed bacterial burden. Thus, this acellular platform represents a clinically promising synchronized strategy to address the complex demands of traumatic craniofacial composite defects.

bioengineering↗

bioRxiv2026

PertDiffBench: Benchmarking Diffusion Models for Single-Cell Perturbation Response Prediction

Diffusion models are increasingly used to predict transcriptional responses to perturbations, but whether they improve on simpler generative and representation-based baselines remains unclear. Existing evaluations often do not separate the effects of model architecture, input representation, biological context and metric choice, making it difficult to determine where diffusion-based methods are useful. Here we introduce PertDiffBench, a standardized benchmark for diffusion-based transcriptomic perturbation prediction across single-cell and bulk RNA-seq datasets. PertDiffBench evaluates diffusion-based models across three complementary evaluation settings: standard prediction in known single-cell contexts and bulk perturbation conditions, generalization to unseen cell types, species, drugs and intermediate time points, and stress tests of feature dimensionality, input representation, noise type and gene ordering. Across these settings, diffusion models did not show a consistent advantage. scGen remained a strong baseline in common prediction tasks, whereas scDiffusion was the most competitive diffusion-based method in several generalization settings. Temporal imputation showed a different pattern, with a simple DDPM operating directly in expression space outperforming more specialized models. Stress tests showed that performance was model dependent and sensitive to feature dimensionality, encoder choice, noise type and gene ordering. Pretrained encoders did not consistently improve performance, with the classical scVI representation slightly exceeding STATE in seen-condition and unseen-cell-type settings. These results indicate that diffusion-model performance in perturbation response prediction depends strongly on task design and representation choice. PertDiffBench provides a practical framework for evaluating these models under biologically varied and stress-tested conditions.

bioinformatics↗

bioRxiv2026

Differentiation of Bacterial, Fungal, and Algal Communities on Coastal Concrete Versus Drainage Pipes and the Coexistence of Corrosion and Healing Potentials

Coastal concrete structures and drainage pipes are prone to microbially influenced deterioration. However, differences in microbial communities and their corrosion/healing potentials between these habitats remain unclear. Here, we compared bacterial(16S), fungal (ITS) and algal(18S) communities on coastal concrete(C) and drainage pipe(P) surfaces. Fungal and algal -diversity were significantly higher in P than in C, while bacterial diversity did not differ. {beta}-Diversity strongly separated bacterial and algal communities between habitats, but not fungi. A shared core "seed bank" of 575 bacterial, 520 fungal and 40 algal ASVs was identified. Students t-test revealed that P enriched oligotrophic degraders (Sphingomonas) and acid-producing fungi (Arxiella, Bisifusarium), whereas C selected for halotolerant EPS-producing bacteria (Tunicatimonas, Muricauda) and the extremotolerant alga Coelastrella. db-RDA linked these differences to salinity, NH4+-N, NO3--N, and COD. Functional prediction indicated a shift from metabolism pathways in C to signaling in P. Co-occurrence networks revealed cross-kingdom competition and within-kingdom cooperation, especially among algae. Importantly, both habitats harbored microorganisms with documented corrosion and healing potentials, but under natural conditions, net deterioration dominated, microbial healing is hardly to counteract the negative effects. This study provides a functional taxonomic framework for understanding and managing concrete microbiomes in coastal and sewer infrastructure. ImportanceConcrete is the most widely used construction material, and its deterioration in coastal and sewer environments poses significant economic and safety challenges. Microorganisms play a dual role in concrete durability -- they can both corrode and heal concrete, but the net outcome under natural conditions is poorly understood. Most studies have focused on bacteria alone, overlooking the contributions of fungi and algae, and few reports on the of coastal concrete which also exist the microbially influenced concrete corrosion (MICC) similar to sewer. Here, we simultaneously analyzed all three microbial kingdoms on coastal concrete and drainage pipes. We found that while concrete surfaces harbor a diverse "seed bank" of microorganisms potentially involved in both corrosion and healing, under natural conditions, net deterioration dominated, indicating microbial healing is hard to counteract the negative effects from the environment and microbial. Our work provides a functional framework to guide the development of microbiome-based strategies for enhancing concrete durability, such as activating rare healing taxa in drainage pipes or selecting for endogenous healers in marine environments.

microbiology↗

bioRxiv2026

TEX15 safeguards neuronal diversity in the mouse olfactory system

Animals detect diverse chemicals using hundreds of chemoreceptor proteins. In many organisms, sensory chemoreceptors obey a one-receptor-type-per-cell rule, which organizes information gathered by sensory neurons. A key question remains how receptor expression gets diversified so that hundreds of chemoreceptors get expressed across the population of sensory neurons. Here we show that diverse odorant receptor (OR) expression in mice requires testis expressed gene 15 (Tex15). We find that Tex15 regulates OR expression in neuronal precursor cells. In Tex15 deficient (Tex15-/-) mice, OR transcript levels are increased in precursors, a handful of early-transcribed OR genes get expressed at abnormally high levels, and these ORs come to dominate the olfactory sensory neuron population. This results in a profound reduction in the diversity of OR gene choice as well as disrupted spatial patterning of the olfactory epithelium, without disrupting the one-receptor-type-per-cell rule. Tex15 encodes a transcriptional repressor, and we show that Tex15-/- mice have reduced heterochromatin-associated H3K9me3 on OR genes. Thus, we propose that Tex15 directs a heterochromatin-based transcriptional repression mechanism that prevents uneven transcriptional onset from skewing OR choice. This mechanism safeguards the cellular diversity that is essential for broadly tuned chemosensation.

genomics↗

bioRxiv2026

AMPK senses cellular levels of nicotinamide adenine dinucleotide

The electron shuttle and coenzyme nicotinamide adenine nucleotide (NAD) is essential for cellular metabolism and homeostasis. NAD levels significantly fluctuate in cells, whilst several age-related diseases are associated with depletion of this metabolite. However, how NAD changes are monitored by nutrient/energy sensing signalling pathways remains poorly understood. We found that at physiological concentrations NAD controls the activity of the AMP-activated protein kinase (AMPK) in vitro and in human cells. Mechanistically, NAD binds gamma subunit of AMPK, and mutagenesis of the putative binding site renders the holoenzyme insensitive to NAD inhibition. Hyperactivation of AMPK in response to NAD depletion suppresses metabolic pathways including mammalian Target of Rapamycin Complex I (mTORC1) and autophagy. These results demonstrate that in addition to monitoring cellular energy levels AMPK functions as a NAD sensor, providing novel insight into how cells and tissues detect and respond to metabolic fluctuations with implications for stress resistance and ageing.

molecular biology↗

bioRxiv2026

Liver-to-Atria Inflammatory Axis Driving Arrhythmia

BackgroundMetabolic dysfunction-associated steatohepatitis (MASH) is emerging as a risk factor of cardiometabolic diseases, including the atrial fibrillation (AF) - the most common sustained arrhythmia. Given that the liver is a major source of inflammatory mediators, lipids, and hepatokines under metabolic stress, we hypothesized that hepatocyte-derived factors in MASH may accelerate atrial remodeling and arrhythmogenesis. MethodsAnalysis of the Atherosclerosis Risk in Communities (ARIC) visit 5 cohort was performed to determine the association between the FIB-4 index - a classic indicator of liver fibrosis, and AF risk, with multivariable adjustment for common comorbidities. A murine model of MASH was induced using the GAN (Gubra-Amylin NASH) diet. Programmed intracardiac stimulation and echocardiography were performed to assess AF susceptibility and cardiac function. Calcium imaging, histology, flow cytometry, plasma proteomics, and single-nucleus RNA sequencing (snRNA-seq) analyses were employed to elucidate the role of recruited inflammatory macrophages via hepatocyte-derived osteopontin (OPN) in MASH-induced atrial remodeling. ResultsAnalysis of the ARIC cohort confirmed a higher cumulative incidence of AF and an elevated adjusted hazard ratio (HR) in patients with intermediate and high FIB-4 indices compared to individuals with low FIB-4 scores. MASH mice exhibited increased susceptibility to pacing-induced AF, accompanied by enhanced proarrhythmic calcium release events, atrial enlargement, and fibrosis, independent of ventricular dysfunction. Proteomics and snRNA-seq revealed that the hepatocyte-secreted OPN under MASH conditions promoted the differentiation and recruitment of TGFBR1+ inflammatory macrophages to the atria, leading to gasdermin D (GSDMD) activation - an effector of inflammasome signaling and consequent proarrhythmic atrial remodeling. Activation of the monocyte-derived pro-inflammatory TGFBR1+ macrophages was dependent on the OPN receptor CD44. Furthermore, the MASH-induced atrial fibroinflammatory milieu and enhanced AF susceptibility were mitigated through several strategies, including hepatocyte-specific Spp1 (encoding OPN) deletion, neutralization of circulating OPN, ablation of CD44 or GSDMD. ConclusionsThese findings establish a pathogenic role of the hepatokine osteopontin in driving activation and recruitment of TGFBR1+ inflammatory macrophages into the atria, leading to proarrhythmic atrial remodeling under MASH. Osteopontin-targeted therapy or GSDMD inhibition prevents AF, indicating a novel therapeutic strategy for liver disease-related atrial arrhythmogenesis. Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIIn the ARIC cohort, metabolic dysfunction-associated steatohepatitis (MASH) is associated with increased risk of atrial fibrillation (AF) after adjusting for common comorbidities. Elevated levels of circulating osteopontin (encoded by SPP1) predict an increased risk of AF in patients with MASH-induced liver fibrosis. C_LIO_LIMASH enhances hepatocyte secretion of osteopontin, leading to expansion of myeloid cells and recruitment of inflammatory macrophages into atria. This liver-to-atrial inflammatory circuit promotes the development of a substrate conducive to AF, which can be attenuated by hepatocyte-specific Spp1 deletion or neutralizing anti-anti-osteopontin antibody treatment to eliminate the mediator, or ablation of inflammasome effector gasdermin D to correct the atrial response. C_LI What are the clinical implications?O_LIOsteopontin may serve as a biomarker for AF in MASH cohorts. C_LIO_LIAnti-osteopontin therapy through neutralizing antibodies may serve as a novel therapeutic strategy for liver disease-related atrial arrhythmia. C_LI

systems biology↗

bioRxiv2026

Geissoschizine scaffolding enzymes shape monoterpene indole alkaloid biosynthesis

For decades, medicinal plants have been an invaluable source of therapeutics for human health. Among plant specialized metabolites, monoterpene indole alkaloids (MIAs) display remarkable chemical diversity and potent bioactivities, including anticancer properties. While the biosynthetic pathways leading to major MIAs such as vincristine, vinblastine, and camptothecin have been extensively studied, the mechanisms regulating metabolic flux within these pathways remain poorly understood. Here, we uncover an unexpected regulatory layer in MIA biosynthesis involving medium-chain dehydrogenase/reductase (MDR) proteins. Using a combination of in vitro biochemical assays, pathway reconstitution in planta, protein-protein interaction analyses, and metabolic engineering in yeast, we show that specific MDRs do not function as classical catalysts but instead enhance both the activity and diversify the stereochemical outputs of geissoschizine synthase (GS). These proteins physically interact with GS and strictosidine {beta}-glucosidase (SGD), forming ternary complexes that likely facilitate substrate channeling of reactive intermediates. Importantly, introduction of these MDRs into engineered yeast strains leads to a dramatic increase in the production of geissoschizine, a central MIA precursor. Collectively, our findings reveal a previously unrecognized role for MDR proteins as regulators of metabolic flux and highlight their potential as powerful tools for metabolic engineering of valuable plant natural products.

plant biology↗

bioRxiv2026

mChIP-seq for Multiplex and Multifactorial Epigenomic Profiling Uncovers Cancer-specific Histone Features in Cellular and Circulating Nucleosomes

Epigenomic profiling facilitates access to investigate regulatory roles of histone marks in a type-specific cell, and serves as a critical path for discovering noninvasive epigenetic models in cell-free nucleosomes. Here, we present mChIP-seq, an epigenomic profiling technology that is compatible with both cell and cell-free samples for synchronously profiling multifactorial epigenetic landscapes on multiple samples. Combining sample indexing in a single reaction with a pool-and-split strategy for immunoprecipitation, mChIP-seq enhances efficiency and reduces cost. Using mChIP-seq, we profiled H2A.Z and 10 histone modifications in cell lines representing 9 cancer types. Integrative analyses further revealed an atypical association of H2A.Z and H3K4me3 at promoter regions in cancer. Based on mChIP-seq, we developed cf-mChIP-seq for circulating nucleosomes, which requires as little as 25 l of plasma per profile. Profiling 38 plasma samples for H2A.Z, H3K4me3, H3K27ac, and H3K9me3 with cf-mChIP-seq revealed distinct histone mark-associated cfDNA fragment patterns in breast cancer versus healthy control, highlighting the potential of cf-mChIP-seq to expand liquid biopsy methodologies. These results demonstrate that mChIP-seq is a widely applicable technology for large-scale epigenomic profiling of nucleosomes in cellular or cell-free forms.

genomics↗

bioRxiv2026

Extracellular Vesicles Enable CircRNA Delivery via in situ Biogenesis and Sorting

Extracellular vesicles (EVs) are promising vehicles for nucleic acid delivery, yet efficient delivery of circular RNA (circRNA) remains challenging due to inefficient loading and limited intracellular expression. Here, we establish an EV-based platform that enables efficient circRNA delivery via in situ biogenesis and sorting. By optimizing intracellular circularization and translation through vector design, we markedly enhance circRNA expression. By combining this with Snu13-mediated EV sorting and enhanced vesicle biogenesis, we achieve efficient packaging of circRNA without compromising vesicle integrity. This integrated strategy enables robust and sustained protein expression following EV-based circRNA delivery. By leveraging this platform, we demonstrate a dendritic cell-targeting circRNA vaccine that elicits strong antigen-specific CD8+ T cell responses and antitumor efficacy. We further show that systemic delivery of BNP-encoding circRNA attenuates doxorubicin-induced myocardial fibrosis. Together, this work establishes a generalizable platform for circRNA therapeutics by overcoming key barriers in circRNA expression and EV-mediated delivery. TeaserEngineered EVs enable efficient circRNA delivery for sustained protein expression and therapy.

bioengineering↗

bioRxiv2026

An Expert-Informed Synthetic Animal Data Generator: A Physiology-Consistent Generative Framework for High-Fidelity Animal Digital Twins

Digital twins are increasingly recognized as a transformative technology for precision livestock farming; however, a major bottleneck in their development remains the scarcity of high-quality, high-granularity physiological data. This study introduces the expert-informed conditional diffusion (EICD) framework, a novel approach to synthesizing high-fidelity metabolic time-series trajectories by embedding mechanistic biological principles directly into the generative process. While traditional generative models often prioritize statistical pattern-matching over biological reality, frequently resulting in physiological hallucinations, the EICD framework utilizes a physiology loss function (PhLF) to act as a form of mechanistic regularization. This guardrail penalizes samples that contradict expert-defined constraints, such as the laws of porcine bioenergetics, effectively steering the model toward a realistic physiological manifold. The framework was validated using an empirical dataset of growing pigs under varying thermal conditions. Quantitative results demonstrate near-perfect statistical distributional fidelity, with the model achieving an average Jensen-Shannon divergence (JSD) of 0.062 and a Kullback-Leibler divergence (KLD) of 0.19. The full EICD model produced a mean energy expenditure (EE) of 284.94 {+/-} 38.70 kJ/kg/day, mirroring the empirical average of 281.33 {+/-} 41.58 kJ/kg/day. In contrast, the standard generative diffusion model (i.e., with no physiology guardrail) exhibited significant distributional drift, yielding a mean EE of 334.41 kJ/kg/day. The biological integrity of the model was further assessed using the biological violation rate (BVR), a novel metric defined as the percentage of generated samples that fall outside the physically possible metabolic boundaries established by species-specific laws. While the standard diffusion model produced frequent biological artifacts, the EICD framework successfully suppressed these hallucinations, ensuring that synthetic trajectories remain strictly grounded in mechanistic laws. Despite these advancements, limitations remain at physiological extremes where individual stochasticity is high. By providing a reliable method for generating physiology-consistent synthetic data, this framework provides a robust foundation for the next generation of animal digital twins. HighlightsO_LIA novel expert-informed conditional diffusion (EICD) framework is proposed for physiology-consistent synthetic data generation in precision livestock farming. C_LIO_LIA physiology loss function (PhLF) embeds species-specific bioenergetic laws directly into the generative process as a mechanistic guardrail. C_LIO_LIThe framework achieves near-perfect distributional fidelity (JSD = 0.062) while suppressing physiological hallucinations (BVR = 0.93%). C_LIO_LIAn ablation study confirms that biological consistency is not an emergent property of standard diffusion models but requires explicit mechanistic constraints. C_LIO_LIThe framework provides a scalable solution for synthetic data augmentation in precision livestock farming, supporting the 3Rs and enabling high-throughput in silico experimentation. C_LI

bioengineering↗

bioRxiv2026

CellChem: Cellular transcriptional responses reshape molecular representation space for efficient and multi-scale drug discovery

Despite decades of progress in computational drug discovery, deep learning-based molecular representation models remain largely structure-centric, assuming that chemical similarity approximates functional similarity. However, drug effects in cells are shaped not only by chemical similarity but also by molecular interactions in the cellular context. To capture this complexity, we introduce CellChem, a cellular-chemical representation-learning framework that learns cell-guided molecular representations of small-molecule actions within cells. By incorporating large-scale cellular transcriptional profiles during pretraining, CellChem reshapes molecular representation space from structure-centric to a balanced integration of structure and function. The learned CellChem molecular representations exhibit biologically meaningful geometric organization, such that distances between molecules encode not only structural similarity but also similarity in the cellular responses they elicit, independent of downstream tasks. Using downstream derivative models such as cell-guided compound-protein interaction prediction and drug-induced transcriptional response profile generation, CellChem supports highly efficient, multi-scale drug discovery, achieving significantly better performance than traditional models.

molecular biology↗

bioRxiv2026

Epigenetically constrained astrocyte states underlie prefrontal cortex vulnerability in Down syndrome associated Alzheimer disease

Down syndrome (DS), caused by trisomy 21, confers a near-universal risk for Alzheimers disease (AD), yet individuals exhibit marked variability in cognitive decline, suggesting the presence of cellular mechanisms that modulate vulnerability and resilience. However, these mechanisms remain poorly defined in the human brain. Here, we integrate matched single-nucleus RNA-seq and ATAC-seq profiles from the prefrontal cortex (PFC) and amygdala (AMY) of age-matched individuals with DS with and without AD (DSAD), enabling direct comparison within a shared genetic background. We identify basal astrocytes in the PFC as a selectively vulnerable cell state in DSAD, characterized by both reduced abundance and coordinated transcriptional and regulatory reprogramming. This state exhibits a shift away from homeostatic support functions, with decreased cytokine signaling and lipid-handling programs, alongside increased steroid- and nuclear receptor-associated activity. Concomitantly, chromatin accessibility profiling reveals reduced engagement of immune- and stress-responsive transcription factor programs, including AP-1, STAT, and BACH families, with linked regulatory perturbations at loci such as ABCA1, DAB2IP, and IL1RAP. Together, these findings define a previously unrecognized astrocyte state marked by epigenetic constraint and diminished responsiveness to stress and inflammatory signals, distinguishing it from classical reactive astrocyte phenotypes. Our results nominate PFC basal astrocytes as a key locus of vulnerability in DSAD and suggest that failure to mount appropriate astrocyte responses, rather than overt activation alone, may contribute to neurodegenerative progression.

bioinformatics↗