Biology subjects

Saha, D.

Publications and source records attributed to Saha, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Parental B-MYB/FOXM1 controls mitotic E2F to determine daughter cell fate

Mitogens trigger cell-cycle entry by activating E2F at the restriction point, which is followed by B-MYB/FOXM1 activation and progression to mitosis. How mitogens control continued cycling and cell-cycle exit after the restriction point is not well-understood. By developing an E2F and B-MYB/FOXM1 dual transcriptional biosensor system, we show that S/G2 phase duration is set by timed mitogen-regulated B-MYB/FOXM1 activation, while E2F activity gradually declines before mitosis. As a striking consequence, rapid B-MYB/FOXM1 activation shortens S/G2, delivering high mitotic E2F activity to daughter cells which keeps them cycling. Delayed B-MYB/FOXM1 activation prolongs S/G2, depleting mitotic E2F which drives daughters to quiescence. When S/G2 is further prolonged, partially activated B-MYB/FOXM1 frequently reverts, triggering mitotic bypass and polyploid quiescence. Thus, B-MYB/FOXM1 governs a tri-directional (G2 restriction point) where cells commit to continued cycling through early B-MYB/FOXM1 activation; cell-cycle exit through delayed B-MYB/FOXM1 activation; or mitotic bypass by B-MYB/FOXM1 inactivation.

cell biology↗

bioRxiv2026

Morphogenesis of the muscular ventricular septum of the mouse heart is driven by retinoic acid signalling to myocardium

The mammalian heart is divided into four chambers by septa that isolate systemic and pulmonary circulation and are hotspots of congenital heart defects (CHD). The muscular ventricular septum develops between left and right ventricular cardiomyocytes derived from the first and second heart fields. Despite its clinical importance, mechanisms underlying development of the ventricular septum are poorly understood. Here we show that myocardial reception of retinoic acid (RA) signalling regulates formation of the compact septal core. Activation of a dominant negative RA receptor in second heart field-derived myocardium during septal morphogenesis results in a deep interventricular cleft and bifid cardiac apex. This phenotype is preceded by ectopic trabecular contributions to a RA-independent septal primordium. Molecular analysis implicates defective cardiomyocyte maturation and impaired RAC1 activation in mutant hearts. These results support an infolding and RA-dependent fusion model of septal morphogenesis, providing new insights into ventricular development and the origins of CHD.

developmental biology↗

bioRxiv2026

Uncovering High-Order Epistatic Interactions in GWAS via a Machine Learning-Based Feature Engineering Framework

BackgroundGenome-wide association studies (GWAS) often fail to identify higher-order epistatic interactions that contribute to complex inheritance patterns of traits and diseases. While machine learning (ML) can capture non-linear relationships, extracting interpretable insights from these models remains a challenge. We propose a novel tree-based feature engineering framework that uses Classification and Regression Trees (CART) to explicitly encode high-order interaction decision paths as dummy variables. We investigate three path-based encoding strategies: (i) all decision paths, (ii) leaf-node paths only, and (iii) internal-node paths only. This approach aims to transform complex decision boundaries into discrete features that capture nonlinear interactions that are not readily captured by traditional association models. ResultsThe framework was evaluated using genetic data for ANCA-associated vasculitis (AAV). To manage the high dimensionality of the engineered feature space, we applied a comprehensive suite of ML methods across three tasks: (1) Ensemble Learning (Random Forest, XGBoost, and Gradient Boosting Machine); (2) Decision Tree Analysis (CART); and (3) Regression and Classification Tasks (Regularized Linear Regression/LASSO, Support Vector Machine, and Logistic Regression). Stepwise feature selection and regularization were employed to isolate the most informative interaction patterns. Results indicate that incorporating CART-derived interaction paths--particularly those from high-impact regions of the tree--significantly improves classification accuracy and model interpretability compared to using the original feature space alone. ConclusionsThe proposed framework provides a robust, scalable methodology for identifying high-order genetic interactions. By bridging the gap between the predictive power of ensemble ML and the necessity for mechanistic insight, this approach offers a clearer mapping of the combinatorial genetic processes underlying complex diseases. While applied here to AAV, the method is highly adaptable for exploring the genetic architecture of diverse populations and complex traits.

genomics↗

bioRxiv2026

Genetic encoding of 3-cyano-tyrosine and its use in controlling the chromophore isomeric state of the fluorescent protein mKate

Switchable {beta}-barrel-type fluorescent proteins are essential genetically encoded probes for super-resolution imaging. The space required for chromophore cis-trans isomerisation can also provide an opportunity to introduce bulkier chemistry at the 3-position of the phenolic ring. Here, we report, to our knowledge, the first successful genetic encoding of 3-cyano-L-tyrosine (3CNY) into a protein. Using genetic code expansion, the cyano-containing amino acid was incorporated directly into the chromophore of mKate, a pH-dependent switchable red fluorescent protein. In mKate, the chromophore adopts a fluorescent phenolate cis state at physiological pH, transitioning to a phenolic trans state under acidic conditions. Substitution of the native tyrosine with 3CNY yields a functional protein exhibiting hypsochromically shifted spectral properties. Time-dependent density functional theory (TD-DFT) calculations indicate that 3CNY incorporation results in a trans state at pH 8. Unlike mKate, the trans state is fluorescent. In contrast, incorporation of 3-chloro-L-tyrosine (3ClY) preserves the preference for the cis phenolate state. Molecular modelling suggests that the cyano group can form stabilising hydrogen bonds with residues S143 and S158, promoting the trans configuration. DFT analysis further indicates that the electron-withdrawing cyano group perturbs conjugation across the chromophore, potentially lowering the barrier to cis-trans isomerisation. Conversely, wild-type and 3ClY variants maintain polarised HOMO and LUMO distributions in the cis state, supporting stronger conjugation and a reduced HOMO-LUMO gap. Overall, the introduction of a genetically encoded 3-CNY tyrosine analogue into a fluorescent protein chromophore expands our mechanistic understanding and enables incorporation of a new chemical tag directly into the chromophore.

biochemistry↗

bioRxiv2026

Data-Constrained Recurrent Network Neural Model Uncovers the Circuit Mechanism of Olfactory OFF Responses

Sensory neural circuits must encode both the presence and termination of a stimulus. Following odor offset, projection neurons (PNs) in the insect antennal lobe (AL) exhibit transient increases in firing rate, termed OFF responses, yet the circuit mechanisms that generate them in recurrent excitatory-inhibitory networks remain poorly understood. Here, we constructed a biologically-constrained firing rate-based recurrent neural network (RNN) model of the locust AL and trained it on electrophysiological recordings from 110 in vivo PNs to reconstruct their odor-evoked temporal dynamics across five odorants. The trained model faithfully reproduced the firing rates of constrained neurons, while unconstrained PNs and LNs developed biologically plausible temporal response patterns and response-type diversity. Using targeted input and connectivity perturbations, we found that OFF responses arise through two mechanistically distinct pathways. A feedforward pathway transmits offset-type olfactory receptor neuron (ORN) input directly to downstream PNs, while a recurrent pathway generates post-stimulus excitation independently of offset input. Selective perturbation of individual recurrent connections identified LN-LN mutual inhibition as the dominant recurrent pathway, and decomposition of excitatory and inhibitory inputs revealed that it produces net excitation through the transient release of inhibition rather than through increased drive. The two pathways recruit largely non-overlapping PN populations, indicating that OFF response identity is an emergent property of the network state rather than a cell-intrinsic feature. These findings provide a circuit-level account of OFF response generation and demonstrate how data-constrained RNNs can dissect circuit mechanisms directly from in vivo recordings.

neuroscience↗

bioRxiv2026

Small-molecule modulators of HIPK4 activity and proteostasis

Homeodomain-interacting protein kinase 4 (HIPK4) is a dual-specificity kinase that is predominantly expressed in differentiating spermatids, required for sperm development, and a promising target for nonhormonal male contraception. Genetic and functional studies have established an essential role for HIPK4 in spermiogenesis, where it acts at least in part through regulation of the F-actin-scaffolded acroplaxome during spermatid head shaping. The direct molecular targets of HIPK4 and their downstream effectors remain poorly defined, and small-molecule probes would be versatile tools for further investigating HIPK4 functions. Synthetic HIPK4 ligands could also be valuable leads for the development of nonhormonal male contraceptives. Here, we report the discovery of a cyanoquinoline-based series of HIPK4 inhibitors with nanomolar potency. Our lead compounds are selective for HIPK4, both within the HIPK family and across the broader kinome, establishing this scaffold as a useful starting point for probe and lead development. Unexpectedly, we found that a subset of these cyanoquinolines also perturbs HIPK4 proteostasis in a cell type-specific manner. In spermatids, these compounds induce the formation of detergent-insoluble HIPK4 aggregates and promote interactions between this kinase and the autophagy receptor Tax1-binding protein 1 (TAX1BP1). Together, our findings establish cyanoquinoline ligands as a new chemotype for probing HIPK4 biology and advancing male contraceptive discovery.

biochemistry↗

bioRxiv2026

Integrative Transcriptomic and Machine Learning Analysis of ecDNA-Associated Features for Studying Chemotherapy Resistance in TNBC

Extrachromosomal DNA (ecDNA) has emerged as a critical mediator of oncogene amplification and transcriptional dynamics in aggressive cancers, yet its contribution to chemotherapy resistance in vivo remains incompletely understood. This study investigates the contribution of ecDNA-associated molecular features to predictive chemotherapy resistance in TNBC. We analyzed RNA-seq data from 4T1 TNBC cells and 4T1 bulk tumors at different growth stages (1-, 3-, and 6-week) to identify differentially expressed ecDNA alterations. We then utilized molecular docking tools to predict ecDNA protein-drug interactions and employed machine learning (ML) models to predict ecDNA-associated therapeutic resistance. Our results revealed changes in global gene expression, including expression of ecDNA-associated genes, that continued over time, with significant molecular remodeling observed at six weeks. Additionally, we found gradual accumulation of mutations in ecDNA genes, which may have contributed to reduced drug binding affinity, indicating potential resistance. ML models generated stable, high-confidence classifications of resistant phenotypes, consistently identifying ecDNA burden and prevalence as dominant predictive features of drug resistance. Drug specific predictions further highlighted elevated resistance probabilities for paclitaxel and doxorubicin, whereas hydroxyurea, which depletes ecDNA, showed reduced resistance probabilities, indicating potential roles of ecDNA in chemoresistance. This study provides new insights into temporal remodeling of ecDNA within TNBC tumors over time and their potential association with drug resistance.

cancer biology↗

bioRxiv2026

Topological Entanglement in Intrinsically Disordered Proteins: Sequence, Structural, and Functional Determinants

Intrinsically disordered proteins (IDPs) populate heterogeneous conformational ensembles that are difficult to characterize using conventional structural descriptors. As a result, it remains unclear which ensemble features meaningfully connect sequence composition to biological function. Here, we employ entanglement-based measures derived from knot theory to provide complementary insight into IDP organization. Using the human IDRome database, we analyze two continuous entanglement descriptors, the writhe and the second Vassiliev invariant (V2), across more than 28,000 simulated disordered sequences. We show that these entanglement measures exhibit structured, low-dimensional variation across the database and display distinct relationships with sequence composition and ensemble geometry. Writhe primarily reflects compaction-dependent coiling tendencies that are largely recoverable from coarse sequence and structural features, whereas V2 captures higher-order topological organization that is less predictable from simple metrics. Embedding the resulting distribution features reveals functionally enriched regions of entanglement space, and ortholog simulations demonstrate that these signatures are evolutionarily conserved. Together, these results establish entanglement as a biologically relevant dimension of IDP organization and provide a rigorous, complementary framework for linking its sequence, ensemble structure, and molecular function.

biophysics↗

bioRxiv2026

Restoring Shugoshin 1 reduces chromosome errors in human eggs

Aneuploidy in human eggs, which rises sharply with age, is a leading cause of infertility, IVF failure, and miscarriage. This age-related aneuploidy is primarily driven by premature sister chromatid separation (PSSC), resulting from loss of the cohesin complex that holds chromatids together. How cohesin is destabilized in the long-lived mammalian oocyte is poorly understood. Here, we show that in mouse oocytes, pericentromeric transcription is essential for maintaining the cohesion protector Shugoshin 1 (SGO1) and PP2A at centromeres, which together safeguard the cohesin subunit REC8. With age, mouse oocytes lose pericentromeric transcription, SGO1, and PP2A, leading to destabilized cohesion and increased PSSC. Supplementing aged mouse oocytes with Sgo1 restores centromeric protection, and reduces PSSC to youthful levels. Aged human oocytes also show reduced SGO1, and SGO1 supplementation reduces the fraction of human eggs with PSSC by approximately half. These findings establish SGO1 supplementation as a potential strategy to preserve chromatid cohesion in aging oocytes.

cell biology↗

bioRxiv2026

p62/SQSTM1 selectively supports starvation-induced autophagy in N2a neuroblastoma cells

Autophagy is a critical cellular process that maintains homeostasis and enables adaptation to metabolic stress. The selective autophagy receptor p62/SQSTM1 has been implicated in multiple aspects of autophagy regulation; however, its specific contribution to basal versus stress-induced autophagic flux remains incompletely defined, particularly in neuronal cells. In this study, we investigated the role of p62 in regulating basal and starvation-induced autophagy using a CRISPR-Cas9-generated p62 knockout (p62-/-) neuroblastoma (N2a) cell model. Autophagic flux was quantified by measuring LC3-II accumulation in the presence and absence of the lysosomal inhibitor bafilomycin A1. Under nutrient-replete conditions, basal autophagic flux was comparable between wild-type and p62-deficient cells, indicating that p62 is dispensable for constitutive autophagy. In contrast, starvation robustly increased autophagic flux in wild-type cells but failed to do so in p62-/- cells, demonstrating a requirement for p62 in starvation-induced autophagy. Consistent with a stress-responsive role, p62 protein levels increased during starvation in wild-type cells under lysosomal inhibition, reflecting enhanced p62 expression rather than impaired degradation. Together, these findings reveal a context-dependent function for p62 in neuronal autophagy, whereby p62 is essential for mounting an effective autophagic response to nutrient deprivation but is not required for basal autophagic turnover.

cell biology↗

bioRxiv2025

Structural Divergence without Functional Impact: Comparative Characterization of SARS-CoV-2 3CL-Mpro Variants Using Cleavage Site Substrates

The SARS-CoV-2 main protease (3CLpro) is essential for viral replication and a leading antiviral target. Circulating variants accumulate substitutions on this enzyme, distant from the catalytic site. Surprisingly, mutant enzymes retain full proteolytic activity, though preserved overall activity does not exclude subtler effects on substrate recognition or selectivity, arising from distal structural perturbations. In this study, we compared the steady-state kinetics of wild-type (Wuhan) 3CLpro with enzymes from the Beta (K90R), Lambda (G15S), and Omicron (P132H) variants, using two peptide substrates representing distinct viral polyprotein cleavage sites. All four proteases displayed comparable catalytic efficiencies, similar pH-rate profiles, suggesting conservation of the catalytic mechanism despite sequence variation. The crystal structure of Omicron 3CLpro bound to an Nsp8-Nsp9 peptide revealed a conserved fold and active-site geometry, with the P132H side chain adopting a substrate-dependent conformation that rebuilt its local contacts, indicating towards how a distal substitution is accommodated without perturbing catalysis. Thermal stability measurements identified the sole distinguishing effect of P132H, with Omicron showing altered stability at elevated temperature. A screen of 31 tanshinones against 3CLpro identified T06 with Ki values of 5 uM, as 3CL pro inhibitor. Thus, 3CLpro may tolerate distal substitutions through local structural adaptation, supporting its durability as an antiviral target.

biochemistry↗

bioRxiv2025

Residue-Specific Modulation of Aggregation-Associated Interactions bySpermine in Tau, α-Synuclein, and Aβ40

Preventing neurodegenerative diseases associated with intrinsically disordered proteins (IDPs) remains a major challenge due to the lack of a detailed, sequence-level picture of disease-relevant structures formation and the influence of cellular factors that modulate these transitions. Here, we probe spermine (Spm), a +4 charged polyamine abundant in cells, to determine how it reshapes the conformational ensembles and fibril-associated contact propensities of three disease-linked IDPs: the K18 domain of Tau, -synuclein (S) and amyloid-{beta}40 (A{beta}40). Using long all-atom molecular dynamics simulations across a range of Spm concentrations, we quantify residue-level changes in intra-chain contacts relative to native contacts observed in fibrils, and corroborate computational predictions with ThT fluorescence assays for Tau constructs. Spm acts in a sequence-and region-specific manner, not simply through overall net charge. In K18, Spm binds near the fourth microtubule binding repeat, disrupting intra-chain contacts associated with Alzheimers fibril structures and thereby inhibiting aggregation. In S, Spm binds mainly to acidic residues in the C-terminal half of the sequence and redistributes intramolecular contacts in a way that increases contact propensity in the central aggregation-prone region and therefore aggregation, in line with previous studies showing Spm-enhanced S aggregation. For A{beta}40, Spm neutralizes acidic residues near positions 22-24 and shifts the balance of intra-chain interactions toward its aggregation-prone core, resulting in a net promotion of fibril-like conformations. These divergent effects show that net charge alone cannot predict polyamine influence on IDPs. Instead, residue-specific binding hotspots and local reweighting of aggregation-linked contacts determine whether Spm promotes or suppresses fibril-like conformations. This combined simulation-experimental framework provides a mechanistic basis for how small molecules reprogram IDP conformational ensembles and suggests principles for designing ligands that exploit similar residue-level modulation.

biophysics↗

bioRxiv2025

Deep-Pose-Tracker: a unified model for behavioural studies of Caenorhabditis elegans

Tracking and analyzing animal behaviour is a crucial step in fields such as neuroscience and developmental biology. Behavioural studies in the nematode C. elegans, for example, help in understanding how organisms respond to external cues and how the specific physiological responses link to either instantaneous or learned behaviours. Although tracking behaviour through locomotion patterns and postural dynamics is routine, it becomes laborious and time-consuming when performed manually. Automation of this process is therefore crucial for accurate and fast detection and analysis. To this end, we report Deep-Pose-Tracker (DPT), a YOLO (You Only Look Once)-based model for automated pose detection of C. elegans from videos and images. The module is further utilized for several downstream analysis algorithms to quantify essential behavioural features, including locomotion speed, orientation, forward or reverse locomotion, and complex body bends such as omega turns. In addition, it includes eigenworms decomposition to represent complex posture dynamics in a low-dimensional space. The model shows reliable performance on the validation and test datasets, with high inference speed, while being user-friendly. DPT, therefore, can be a valuable toolkit for automated behavioural quantification of C. elegans under varying experimental stimuli.

animal behavior and cognition↗

bioRxiv2025

Molecular Plasticity of T Cells Informs Their Possible Adaptation in 4T1 Tumors

BackgroundThe triple-negative breast cancer (TNBC) microenvironment (TME) undergoes progressive reprogramming, transitioning from an early immune-active state to a late immune-suppressed state. While tumor cell plasticity has been extensively studied, the molecular plasticity of T cells in vivo remains poorly defined. ObjectivesTo characterize transcriptional changes in T cells during TNBC progression and identify stage-specific shifts in T cell function, polarization, and antigen-presenting cell (APC)-T cell interactions. ResultsTranscriptional analysis of T cells from BALB/c mice bearing 4T1 tumors at 1, 3, and 6 weeks revealed a decline in T cell-associated genes from 194 at 1 week to 156 at 6 weeks, with a significant late-stage loss of TCR diversity and contraction of natural killer T (NKT)- and {gamma}{delta} T cell-related transcripts. Cytokine and transcription factor dynamics reflected temporal T cell polarization: early (1 week) IL-12/{beta}-STAT4 signaling supports CD4+ type 1 T helper cell (Th1) and type 1 CD8+ cytotoxic T cell (Tc1) responses; intermediate (3 weeks) IL-21 and BCL6 expression suggest transient CD8+ cytotoxic follicular T cell (Tfc) skewing; and late (6 weeks) AhR and IL-1{beta} induction reflect interleukin 17/22 producing CD8+ T cell (Tc17/Tc22) transition. Pro-inflammatory cytokines and chemokines increased over time, while immunosuppressive mediators (e.g., IL-10) declined significantly. Antigen-presenting cell (APC)-T cell crosstalk deteriorated at 6 weeks, characterized by a reduction in the expression of co-stimulatory and APC genes. Despite an early dominance of M1-like macrophage signals (e.g., IL-12/{beta}), persistent expression of arginase 1 (ARG1) and other M2-associated genes indicated a stable tolerogenic niche. ConclusionsTNBC progression is characterized by progressive T cell functional decline, narrowing of TCR diversity, impaired APC-T cell interactions, and sustained macrophage-driven immunosuppression. These temporally coordinated immune shifts suggest tumor-driven adaptation toward immune evasion and identify potential windows for stage-specific immunotherapeutic intervention.

cancer biology↗

bioRxiv2025

Cathepsin K as a Key SARS-CoV-2 Cell Entry Protease and Dual-Inhibition Target

SARS-CoV-2 relies on host proteases to prime its spike protein for cell entry through either the endosomal or plasma membrane pathway. Although cysteine cathepsins are known to mediate the endosomal route, the identity of the dominant enzyme has remained unclear. Here, we identify human Cathepsin K (hCatK), a lysosomal cysteine protease, as a previously unrecognized yet functionally important mediator of spike activation. While human Cathepsin L (hCatL) has long been regarded as the principal endosomal protease for spike processing, inhibition of hCatK with the selective inhibitor Odanacatib suppressed viral infection in endothelial cells as effectively as the broad-spectrum cysteine protease inhibitor E-64d, implicating hCatK as a key driver of spike processing during the endosomal viral entry. Comprehensive enzymatic profiling demonstrated that hCatK exhibits 24- to 63-fold higher catalytic efficiency toward the Furin-cleavage site (FCS) sequence than hCatL and displays a distinct substrate-recognition pattern at the Omicron FCS relative to the Wuhan variant. We further demonstrate that hCatK is an off-target of Nirmatrelvir, a clinically approved 3CL-Mpro inhibitor, with a sub-micromolar potency (IC50 = 0.6 {+/-} 0.1 {micro}M). A 1.9 [A] crystal structure of the hCatK-Nirmatrelvir complex delineates the molecular basis of inhibitor binding and supports the rational design of dual-acting antivirals. Collectively, these findings redefine the landscape of host proteases involved in SARS-CoV-2 spike activation and establish hCatK as a previously overlooked but strategic target for antiviral intervention.

biochemistry↗

bioRxiv2025

Detection of multiple per- and polyfluoroalkyl substances (PFAS) using a biological brain-based gas sensor

Per- and polyfluoroalkyl substances (PFAS) are man-made compounds that bioaccumulate in environments. Current PFAS detection technologies encounter difficulty in detecting trace concentrations and require complex data processing, limiting their on-site applicability. By leveraging biological chemical sensing systems (insect olfaction) we can detect broad ranges of PFAS. Insects advanced combinatorial coding mechanism at the level of olfactory sensory neurons enables highly sensitive and specific odor detection. Here, we harness the locust olfactory system to differentiate several PFAS. In-vivo extracellular neural recordings displayed unique odor-evoked responses for multiple PFAS at environmental concentrations. Using population neuronal response, we classified multiple PFAS with an average 87% accuracy. Machine learning algorithms incorporated separate training and testing datasets, reaching a 61% accuracy. Overall, our study demonstrates the first biological olfaction based broad PFAS detection system. Structured AbstractO_ST_ABSIntroductionC_ST_ABSPer- and polyfluoroalkyl substances (PFAS) pose a significant environmental threat due to their widespread presence in consumer waste and resistance to degradation. These "forever chemicals" persist in various ecosystems and exhibit bio accumulative behavior. Increased human exposure to PFAS has been linked to numerous health issues. Despite their growing relevance, current detection methods often lack the sensitivity and efficiency needed for comprehensive environmental monitoring and are unable to simultaneously detect multiple PFAS at environmental concentrations. RationaleThe locust (Schistocerca americana) possesses a highly developed olfactory system that has been extensively studied and is accessible for physiological recordings across multiple brain regions. Utilizing olfactory receptor neurons and combinatorial coding strategies, locusts can generate distinct neural fingerprints for trillions of odorants across a wide range of concentrations. Through spatiotemporal neural coding at the antennal lobe (AL) neurons, they can detect chemicals at parts per trillion levels, functioning as a biological chemical sensor with exceptional sensitivity and broad specificity. In this study, we aimed to directly harness the locusts olfactory neural circuitry to develop a next-generation, brain-based cyborg sensor capable of (1) simultaneously identifying multiple PFAS and (2) determining their concentration ranges, addressing key limitations of existing detection technologies with the integration of machine learning algorithms. ResultsIn-vivo extracellular neural recordings from the locust AL revealed that individual neurons exhibited distinct response profiles to different PFAS and their varying concentrations, indicating that neuronal activity if modulated by both chemical identity and concentration. By incorporating both spatial and temporal dimensions of neural activity, the recorded neuronal populations produced unique and reproducible response patterns corresponding to specific PFAS and concentration levels. Using this approach, the cyborg sensor demonstrated an overall detection accuracy of 87% across a panel of seven PFAS, with high sensitivity and specificity for both individual analytes and broader chemical groupings. Notably, classification of PFAS concentration ranges down to parts per trillion achieved 84% accuracy, with PFOS concentrations reaching 100% detection rate. A machine learning algorithm trained on high concentration data and tested on low concentration data achieved a 61% accuracy. These results underscore the potential of biologically integrated cyborg sensors for real-time, high-resolution environmental monitoring of several PFAS. ConclusionThis study demonstrates, for the first time, the locust olfactory neural network harnessed as a highly effective cyborg sensor for detecting and classifying various PFAS across concentration ranges. This sensor can accurately distinguish between multiple PFAS and controls with high sensitivity and specificity. Through combinatorial coding and spatiotemporal neural dynamics, the locust neural computation encodes distinct activity patterns in response to PFAS and their concentrations. These neural signatures serve as unique "fingerprints" for individual PFAS and concentrations, enabling precise identification. In-vivo electrophysiological recordings revealed clear, compound-specific differences in neural activity, with high classification accuracy. Real-time and machine learning analysis further addressed key limitations of conventional PFAS sensors. This novel approach represents a significant step toward the development of compact, real-time, brain-based PFAS detection sensor capable of discriminating multiple compounds and concentrations simultaneously.

bioengineering↗

bioRxiv2025

Avasopasem Manganese acts as both a Radioprotector and a Radiomitigator of Radiation-Induced Acute or Late Effects.

The pentaazamacrocyclic superoxide dismutase mimetic, Avasopasem Manganese (AVA), has been shown in clinical trials to reduce the severity and duration of acute oral mucositis (OM) and acute esophagitis in patients treated for head and neck and lung cancers, respectively, by radiotherapy using conventional fractionation protocols. Here, the radioprotective effects of AVA were tested in normal tissues after high dose per fraction radiation exposures to determine whether: radioprotective effects of AVA were still present after doses like those used with stereotactic ablative radiotherapy (SAbR); AVA protected against late normal tissue responses; and, whether AVA could act as a radiomitigator of adverse normal tissue events. With AVA, residual DNA lesions and micronuclei were reduced in HBEC3 KT but increased in H1299 cells 24h post-irradiation. Furthermore, radiation-induced mutations and chromosome aberrations were reduced in WTK-1 lymphoblast cells. The radioprotective effects of AVA at high dose per fraction were then tested against both acute and late normal tissue effects. When provided prior to radiation, AVA reduced the extent of epithelial cell layer degradation of mouse tongue irradiated with a single dose of 17 Gy and reduced radiation recall when a second dose of radiation of 12 or 17 Gy was given two weeks following the initial 17 Gy dose. In addition, when provided after radiation, there was a modest but significant reduction in adverse epithelial layer response. Radiation-induced lung fibrosis, determined at 24 weeks post-irradiation, was also reduced when AVA was delivered 1 hour prior to irradiation after a single dose of 54 Gy. When AVA was provided 24h after 54 Gy and given daily (Monday-Friday) for increasing numbers of weeks, fibrosis was progressively reduced as the length of AVA treatment increased. However, AVAs effect on fibrosis decreased as the time between irradiation and post-irradiation AVA application increased. These studies confirm the efficacy of AVA as a radioprotector and mitigator of both radiation-induced acute and late effects after high dose per fraction exposures while not protecting tumor cells to radiation exposure.

cancer biology↗

bioRxiv2025

Noninvasive detection of bacterial biofilms using an insect olfactory brain-based gas sensor

Bacteria emit volatile organic compounds (VOCs) that can be targeted for disease detection. Biological olfactory systems have keen senses of smell, can detect VOCs at low concentrations, and are naturally adapted to classifying mixtures of VOCs as odors. Here, we employed locust (Schistocerca americana) olfactory neural circuitry to differentiate biofilm and planktonic cultures of Pseudomonas aeruginosa and Staphylococcus aureus using their odors. In vivo extracellular neural recordings were taken from the second-order olfactory processing center (antennal lobe) of locusts. The VOCs from biofilm cultures evoked distinct spiking responses compared to the planktonic cultures for both bacterial species. By analyzing the population neuronal responses, we classified individual bacterial biofilm vs. planktonic odors with up to 96% accuracy. The neural responses were highly discriminatory within the first couple of seconds of odor presentation and our analysis was conducted on less than five seconds of data, highlighting the potential of our biological sensor for real-time biofilm detection.

neuroscience↗