Biology subjects

Gao, Y.

Publications and source records attributed to Gao, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

LorMe: a streamlined and interoperable R framework for end-to-end microbiome analysis

Microbiome research is rapidly evolving accompanied by increasingly diverse analytical strategies and visualization formats. However, existing R-based tools remain fragmented, differ in data structures, and often require extensive package-specific pre-processing. This increases command-line complexity and limits both interoperability and reproducibility across packages. Here, we present LorMe (Lightweight One-line Resolving Microbial Ecology), an R package that provides a unified, interoperable, and user-friendly framework for microbiome data analysis. LorMe incorporates a standardized S4 object system with fully bidirectional compatibility with phyloseq and microeco, which enables seamless data exchange across major microbial analysis packages. A global configuration system ensures consistent parameter control and visualization standards, and a modular architecture supports both complete end-to-end workflows and flexible execution of individual analytical components. Based on these, LorMe further offers an one-command pipeline that conducts the full spectrum of microbial community analyses, including alpha and beta diversity, differential abundance testing, co-occurrence network inference, and meta-network construction, while archiving all intermediate objects and source data to ensure complete reproducibility. Demonstrations using sample datasets show that LorMe performs comprehensive analyses within minute, produces publication-ready outputs, and maintains methodological transparency. Application to a real rhizosphere dataset revealed biologically coherent patterns across diversity metrics, differential taxa, and network modules, highlighting the capacity of LorMe to support robust ecological interpretation. Collectively, LorMe provides a lightweight, extensible, and flexible solution that reduces technical barriers and enhances reproducibility in microbiome research. LorMe package is freely accessible from both CRAN (https://cran.r-project.org/web/packages/LorMe) and github (https://github.com/wangnq111/LorMe)

bioinformatics↗

bioRxiv2025

EGFR suppression and drug-induced potentiation are widespread features of oncogenic RTK fusions

Regulation of cancer cells by their environment contributes to tumorigenesis and drug response, though the extent to which the oncogenic state can alter a cells perception of its environment is not clear. Prior studies found that EML4-ALK, a receptor tyrosine kinase (RTK) fusion oncoprotein, suppresses transmembrane receptor signaling through EGFR. Moreover, suppression was reversed with targeted ALK inhibition, thereby promoting survival and drug tolerance. Here we tested whether such modulation of EGFR was common among other RTK fusions, which collectively are found in [~]5% of all cancers. Using live- and fixed-cell microscopy in isogenic and patient-derived cell lines, we found that a wide variety of RTK fusions suppress transmembrane EGFR and sequester essential adaptor proteins in the cytoplasm, as evidenced by the localization of endogenous Grb2. Targeted therapies rapidly released Grb2 from sequestration and potentiated EGFR. Synthetic optogenetic analogs of RTK fusions confirmed that cytoplasmic sequestration of Grb2 was sufficient to suppress perception of extracellular EGF and could do so without driving signaling from the synthetic fusion itself, demonstrating that fusion signaling and suppression of EGFR could be functionally decoupled. Our study uncovers that a large number of RTK fusions simultaneously act as both activators and suppressors of signaling, the mechanisms of which could be exploited for new biomimetic therapies that enhance cell killing and suppress drug tolerance.

cancer biology↗

bioRxiv2025

Extracting task-relevant preserved dynamics from contrastive aligned neural recordings

Recent work indicates that low-dimensional dynamics of neural and behavioral data are often preserved across days and subjects. However, extracting these preserved dynamics remains challenging: high-dimensional neural population activity and the recorded neuron populations vary across recording sessions. While existing modeling tools can improve alignment between neural and behavioral data, they often operate on a per-subject basis or discretize behavior into categories, disrupting its natural continuity and failing to capture the underlying dynamics. We introduce Contrastive Aligned Neural DYnamics (CANDY), an end-to-end framework that aligns neural and behavioral data using rank-based contrastive learning, adapted for continuous behavioral variables, to project neural activity from different sessions onto a shared low-dimensional embedding space. CANDY fits a shared linear dynamical system to the aligned embeddings, enabling an interpretable model of the conserved temporal structure in the latent space. We validate CANDY on synthetic and real-world datasets spanning multiple species, behaviors, and recording modalities. Our results show that CANDY is able to learn aligned latent embeddings and preserved dynamics across neural recording sessions and subjects, and it achieves improved cross-session behavior decoding performance. We further show that the latent linear dynamical system generalizes to new sessions and subjects, achieving comparable or even superior behavior decoding performance to models trained from scratch. These advances enable robust cross-session behavioral decoding and offer a path towards identifying shared neural dynamics that underlie behavior across individuals and recording conditions. The code and two-photon imaging data of striatal neural activity that we acquired here are available at https://github.com/schnitzer-lab/CANDY-public.git.

neuroscience↗

bioRxiv2025

Structural and Functional Insights into HBx-Smc6 Targeting for HBV Inhibition

The hepatitis B virus (HBV) X protein (HBx) is a multifunctional regulator essential for HBV replication and HBV-associated hepatocarcinogenesis. Despite its central role, the molecular basis of HBx function has remained elusive. Here, we present the first cryo-electron microscopy structure of the human HBx-CRL4-Smc5/6 complex at 3.1 [A] resolution. In this reconstituted ten-subunit assembly, HBx adopts a Zn2 {square}-stabilized Y-shaped architecture that simultaneously engages the DDB1 and the Smc6 subunit. A composite helix-turn-helix (HTH) pocket in HBx accommodates a conserved "Leucine Key" motif (LRCKL) on Smc6, forming a critical interface essential for complex stability and function. Molecular docking and biochemical validation reveal that the compound Tranilast binds this HTH pocket, disrupts the HBx-Smc6 interaction, and suppresses HBV replication. These findings define the structural mechanism by which HBx counteracts host restriction and establish the HBx-Smc6 interface as a previously unrecognized and druggable target for antiviral intervention.

cell biology↗

bioRxiv2025

Language may be all omics needs: Harmonizing multimodal data for omics understanding with CellHermes

Decoding cellular systems requires integrating diverse omics data, yet most models are trained from scratch on a single modality, restricting generalization. Here we present CellHermes, a biological language model that leverages pretrained large language models (LLMs) to integrate multimodal forms of omics data, such as transcriptomic profile and PPI network, through natural language for better omics understanding. By reformulating these datasets into question-answer pairs, CellHermes emulates multiple self-supervised learning paradigms within a single, universal, language-based framework with LORA fine-tuning on existing natural language-LLM, achieving comparable or even better performance compared to current single-cell foundation models. Within this framework, CellHermes functions as an encoder, a predictor and an explainer for supporting a range of downstream tasks. For encoder, CellHermes encodes biological entities with embeddings that enable accurate network discovery and cross-dataset generalization; For predictor, CellHermes unifies heterogeneous downstream tasks by translating them into natural language question-answers pairs, allowing a single model to perform multi-task prediction by instruction fine-tuning; For explainer, CellHermes explains molecular mechanisms by combining attention analysis with text-based reasoning, leveraging the interpretability and reasoning capabilities of LLMs. We evaluated the ability of CellHermes as an encoder on representing genes and cells using 5 gene-level downstream tasks and 5 diverse single-cell datasets across different tissues compared with other single cell foundation models. We also evaluated CellHermes as a predictor on BioUniBench, a new benchmark of 10 tasks across 7 databases for LLMs, including perturbation response, cell fitness estimation, gene-disease association, and cell type identification. All benchmarks suggest CellHermes can unify multiple biological tasks within one model without compromising performance. By applying CellHermes as an explainer for a melanoma patients dataset, it can uncover potential key genes on tumor-reactive T cells. Together, CellHermes establishes natural language as a unifying medium for omics, offering a foundation that, in the future, potentially enables a more integrated and interpretable research loop of biological representation, prediction, and interpretability.

bioinformatics↗

bioRxiv2025

Two routes to land: Genomic underpinnings of parallel aerial egg deposition in aquatic Old-World Pila and New-World Pomacea (Ampullariidae)

The parallel evolution of aerial oviposition in Old-World Pila and New-World Pomacea apple snails--diverged since the Gondwanan breakup yet convergently transitioning from aquatic to terrestrial egg deposition--offers a powerful model for probing genomic adaptations underpinning key evolutionary innovations. We generated chromosomal-level genomes of Pila celebensis and Pila pesmei, revealing a genus-specific doubling in genome size driven by transposable element expansions. Parallel chromosomal rearrangements linked to environmental sensing, stress responses, and metabolism were identified in both lineages. Gene family analyses uncovered parallel expansions in cellulases, immune genes, and environmental sensors, alongside convergent positive selection in aquaporins critical for aerial osmoregulation. Strikingly, proteomics of egg perivitelline fluid (PVF) highlighted parallel adaptations in the PV1 protein family, where increased hydrophobicity enhances desiccation resistance in aerially deposited eggs. Phylogenetic and structural evidence traced PV1s likely origin to horizontal gene transfer (HGT) from a virus in the Ampullariidae ancestor, with subsequent duplications enabling lineage-specific aerial adaptations. Despite distinct genomic trajectories, Pila and Pomacea demonstrate that parallel molecular evolution and HGT-driven innovation facilitated their convergent transition to terrestrial reproduction, providing unprecedented insights into the genomic architecture of adaptive convergence.

evolutionary biology↗

bioRxiv2025

A novel 18F-labeled brain penetrant PET ligand for imaging poly(ADP-ribose) polymerase-1

Poly(ADP-ribose) polymerase-1 (PARP-1) is a key mediator of DNA repair, and its inhibition has become a validated therapeutic strategy in homologous recombination-deficient cancers. However, tools for non-invasive assessment of PARP-1-specific expression remain limited. Here, we evaluated [18F]AZD9574, a next-generation PARP-1-selective PET radiotracer. [18F]AZD9574 was tested in a panel of breast, glioblastoma, prostate, and pancreatic cancer cell lines. Uptake correlated with PARP-1 expression and was dose-dependently blocked by a variety of clinically relevant PARP inhibitors, confirming its binding specificity. In 22Rv1 xenograft mouse models, the tracer demonstrated significant tumor accumulation that was specific to PARP-1, and ex vivo biodistribution confirmed organ uptake consistent with specific tumor binding and PARP-1 expression. Together, these findings establish [18F]AZD9574 as a promising PARP-1-targeted imaging agent with strong potential for advancing cancer research and therapeutic monitoring.

cancer biology↗

bioRxiv2025

LRP8 is a Receptor for Yellow Fever Virus

Yellow fever virus (YFV), an arbovirus causing substantial human morbidity and mortality, was the first human virus discovered over a century ago. The live-attenuated 17D vaccine is among the most successful vaccines in medicine. Despite the importance of YFV, its receptor has remained unknown. Here, we performed a barcoded, genome-wide human ORF library screen and identified LRP8 (also named APOER2) as a receptor for YFV. We show that LRP8 expression specifically boosts YFV infection in cell lines by promoting entry. AAV-mediated expression of human LRP8 in mouse liver aggravates infection and pathology. LRP8 knockdown abolishes YFV infection in brain cells, primary human hepatocytes, and notably in mosquitoes. Biochemically, LRP8 directly interacts with YFV particles via the viral envelope protein. This function of LRP8 is conserved across species, particularly in mosquitoes and primates. A soluble LRP8 decoy protein can block YFV infection in vitro and in mice, providing a potential therapeutic or prophylactic strategy. Our findings provide groundwork for understanding YFV entry, tropism, and pathogenesis, and may enable development of novel therapeutics to treat YFV infection.

microbiology↗

bioRxiv2025

Targeting homologous recombination repair to potentiate fluoroquinolone efficacy in Mycobacterium abscessus

Synthetic antibiotics, fluoroquinolones (FQs), are extensively important treatment options for fast growing mycobacterial infections. However, their widespread use has led to decreased efficacy due to intrinsic or acquired resistance. FQs exhibit antimicrobial activity by stabilizing type II topoisomerases-generated DNA breaks, thereby inducing lethal double-strand breaks (DSBs) and leading to bacterial death. Escalating resistance among mycobacterial pathogens highlights the need to elucidate resistance mechanisms and identify novel strategies to restore or enhance the drug activity. Here, we revealed homologous recombination (HR) as a key determinant of FQ tolerance in Mycobacterium abscessus, a notoriously drug-resistant pathogen. Through a transposon mutagenesis screen, we identified that disruption of adnB - an HR-associated gene, markedly sensitized M. abscessus to FQs. This finding prompted a systematic dissection of DSB repair pathways in M. abscessus. Targeted deletion of HR core components (adnB, recO, recA, recR, ruvB) significantly increased FQ susceptibility in vitro, while inactivation of alternative DSB repair pathways - single-strand annealing (SSA) and non-homologous end joining (NHEJ) - had no effect, revealing a unique reliance on HR for FQ tolerance. Furthermore, the complementation of gene knock-out M. abscessus strains {Delta}adnB, {Delta}recO, {Delta}recA, {Delta}recR or {Delta}ruvB with the corresponding genes from M. abscessus, as well as homologous genes from Mycobacterium tuberculosis restored the resistance phenotype, indicating a conserved HR-dependent tolerance mechanism in M. abscessuss. In a murine infection model, genetic abrogation of HR significantly improved the therapeutic efficacy of FQs against M. abscessus, demonstrating translational relevance. Collectively, our findings position HR as a conserved and actionable vulnerability in M. abscessus, and provide a compelling rationale for developing HR-targeted adjuvant therapies to resensitize drug-refractory strains to FQ treatment. Impact statementFluoroquinolone (FQ) resistance poses a major challenge in the treatment of Mycobacterium abscessus infections. This study identifies homologous recombination (HR) as a key defense mechanism that limits FQ efficacy across multiple mycobacterial species. Genetic inhibition of HR not only sensitizes M. abscessus to FQs in vitro but also enhances antibiotic activity in vivo. These results highlight HR repair as a promising therapeutic target to potentiate FQ activity and combat drug resistance in M. abscessus infections.

molecular biology↗

bioRxiv2025

Elevated Temperatures Representing Heatwave Conditions Shift Active Nitrifying Communities and Their Viruses in Tidal Flats and Agricultural Soils

Global heatwave intensification associated with climate change will impact the nitrogen cycle, yet its effect on specific nitrifier groups or their interactions with viruses remains unclear. Using 13CO2-DNA-based stable isotope probing (SIP) coupled with metagenomics, we show that elevated temperatures associated with heatwave conditions restructure active nitrifying communities and their viruses in Yangtze River estuary tidal flats and adjacent agricultural soils. In tidal flats, high temperatures shifted active ammonia-oxidizing archaea and bacteria (AOA and AOB), and nitrite-oxidizing bacteria (NOB) from marine to terrestrial ecotypes. In contrast, heatwave conditions stimulated terrestrial ecotypes of AOA but suppressed AOB in agricultural soils. 13C-labeled nitrifier-infecting viruses also showed temperature-driven shifts in activity, lifestyle, and auxiliary metabolic genes in concert with hosts. Notably, AOA viruses carried the plastocyanin gene, potentially augmenting host metabolism. These findings demonstrate heatwaves drive complex shifts in nitrifier communities and their interactions with viruses, impacting global nutrient cycling under climate extremes.

microbiology↗

bioRxiv2025

AAV11 mediates efficient retrograde trans-neuronal transduction of astrocytes

Understanding the mechanisms by which astrocytes regulate neural circuits is crucial for elucidating the mechanisms underlying cognitive and behavioral abnormalities in psychiatric disorders and for exploring potential therapeutic or intervention strategies. Viral tracers are powerful vehicles for comprehending the complex relationship between neurons and astrocytes. Despite adeno-associated virus 1 (AAV1) based anterograde trans-neuronal tools have been successfully applied for identifying astrocytes connected with presynaptic neurons, analogous retrograde trans-neuronal tools for labeling astrocytes connected to postsynaptic neurons remain under development. Here, we first demonstrate that GfaABC1D promoter embedding AAV11 can transfer retrogradely from axons of postsynaptic neurons to astrocytes. Furthermore, we established an AAV11-based dual-viral recombination strategy for labeling astrocytes connected to specific postsynaptic neurons. Finally, by employing targeted neuronal ablation technology to ablate neurons in a specific brain region, we observed that injection of AAV11 into the downstream brain region of this targeted area exhibited minimal labeling of astrocytes functionally associated with the ablated neurons. This finding indicates that AAV11 holds utility for deciphering pathological alterations in disease-related astrocyte-neuron connectivity networks. This work fills a key gap in tools used for studying astrocyte-neuron connectivity networks.

neuroscience↗

bioRxiv2025

Common-specific edge-centric connectome across Four Episodes in Bipolar Disorder

BackgroundBipolar disorder (BD) is a heterogeneous psychiatric illness marked by dynamic mood states, including manic (BipM), depressive (BipD), mixed (mBD), and euthymic/remitted (rBD) episodes. These clinical fluctuations are accompanied by widespread functional disruptions in the brain. However, the shared and individual-specific neural mechanisms across distinct episodes of BD remain poorly understood. MethodsWe analyzed resting-state fMRI data from 190 participants (BD patients in four episodes and healthy controls) using edge-centric functional connectomes (eFC), which capture time-resolved co-fluctuations between brain regions. A common-orthogonal-basis extraction (COBE) algorithm was applied to decompose individual eFC matrices into shared and individual-specific subspaces. We characterized the spatial topology, genetic relevance, and circuit-level correlates of the shared component. Dynamic properties (entropy, identifiability) and symptom prediction models were assessed using entropy metrics, intraclass correlation coefficients, and support vector regression. ResultsThe shared eFC pattern was stable across participants, aligned with the sensory-association gradient (p < 0.0001), and exhibited significant heritability and test-retest reliability (p < 0.05). Entropy of individual loadings increased with illness duration and was significantly elevated in BD, particularly in mBD. Microcircuit modeling revealed that this shared pattern was inversely related to external input strength (r = - 0.34, pspin< 0.05), indicating intrinsic network dominance. mBD was associated with globally elevated eFC entropy and markedly reduced fingerprint stability. Symptom severity (HDRS, YMRS, HAMA) was significantly predicted from individual network topographies across BD phases, highlighting clinically meaningful dynamic signatures. ConclusionOur findings demonstrate that BD episodes are underpinned by a conserved functional scaffold and distinct individual-specific neural fingerprints. Edge-centric dynamics--especially those derived from individual-specific decompositions--offer robust biomarkers for mood state characterization and symptom severity, and may facilitate future personalized interventions in BD.

neuroscience↗

bioRxiv2025

Development of a High-Throughput Screening Method for Anti-NNV Drugs

Nervous necrosis virus (NNV) is an infectious pathogen, characterized by rapid infection and high mortality, commonly encountered in the aquaculture industry. Therefore, there is an urgent need to develop effective antiviral drugs against NNV, which is crucial for targeted treatment strategies, pathogen control, and loss reduction. Screening of effective antiviral active compounds, namely drug precursors, is key to developing highly efficient drugs against NNV. Reverse transcription-quantitative real-time PCR (RT-qPCR) is widely applied to screen and evaluate various substances to prevent and control virus infection. However, RT-qPCR is a cumbersome procedure and not suitable for high-throughput rapid screening. The aptamer TNA1c, which specifically binds to NNV-infected cells, was used to construct a target-driven activatable aptamer probe (TAA). Then, the TAA probe was applied to establish a high-throughput screening (TAA-HTS) method for efficient evaluation of substances against NNV infection. TAA-HTS technology achieved rapid, sensitive, and specific screening of bioactive substances with significant anti-NNV effects. As compared to commonly used analytical methods, such as RT-qPCR, TAA-HTS has the advantages of easy operation and high sensitivity and specificity. The findings of this study provide data support and a theoretical basis for the development of effective antivirus preparations. IMPORTANCEIn this study, a target-driven activatable aptamer probe was employed to establish a high-throughput screening method for anti-NNV drugs. This method enables rapid, sensitive, and specific screening of anti-NNV compounds while reducing background interference. Although RT-qPCR is currently the most widely used technique for antiviral drug screening and validation, the screening approach developed in this study significantly shortens screening time while achieving results consistent with those of RT-qPCR. This demonstrates that the screening method presented here has the potential to become a universal strategy for future drug screening against viral diseases. Moreover, this study not only provides a novel technical solution for NNV control but also demonstrates the potential of aptamer-based probes in high-throughput antiviral screening, serving as a model for combating viral pathogens in aquaculture and other fields.

pathology↗

bioRxiv2025

Reactivation-coupled brain stimulation enables complete learning generalization

Generalization of learned knowledge to new contexts is essential for adaptive behavior. Despite extensive research on the brain plasticity mechanisms underlying learning specificity, the mechanisms that facilitate generalization remain poorly understood. Here, we investigate whether using brain stimulation to disrupt offline consolidation in visual cortex promotes learning generalization. Separate groups of participants (N = 144) were trained on visual detection tasks using either a reactivation-based protocol or conventional full-practice, combined with anodal or sham transcranial direct current stimulation (tDCS) over the visual cortex. Strikingly, only combination of reactivation-based learning with anodal tDCS produced complete generalization from trained to untrained stimuli, an effect consistently replicated across features (orientation, motion direction). In contrast, reactivation-based learning alone and conventional full-practice - whether with or without brain stimulation - yielded stimulus-specific learning. Importantly, reactivation-coupled brain stimulation achieved generalization with an 80% reduction in training trials while maintaining learning gains comparable to full-practice. These findings demonstrate that reactivation and neuromodulation interact to unlock learning generalization, revealing a key brain plasticity mechanism and offering a rapid, translatable strategy for sensory rehabilitation.

neuroscience↗

bioRxiv2025

Synthesis and In Vitro Characterization of OGA-2506 as a High Affinity Radioligand for O-GlcNAcase

O-GlcNAcase (OGA) is a glycoside hydrolase that regulates protein O-GlcNAcylation, a dynamic post-translational modification implicated in numerous cellular processes. Dysregulation of OGA alters cellular O-GlcNAc homeostasis and has been linked to neurodegenerative and other chronic diseases. The development of radioligands targeting OGA, particularly those derived from well-characterized tool compounds, could substantially advance drug discovery in this area. Herein, we report the radiosynthesis of a novel tritium (3H)-labeled radioligand 7 (code name [3H]OGA-2506) derived from a chiral piperidine scaffold, and its preliminary in vitro binding evaluation. Starting from iodine precursor 8, palladium-catalyzed tritiation afforded [3H]7 with excellent molar activity (1822 GBq/mmol) and high radiochemical purity (>99%). Saturation binding studies revealed that [3H]7 binds OGA with high affinity to rat striatum homogenates (Kd = 3.56 nM; Bmax = 42.62 nM). Competition assays yielded an IC50 of 5.55 nM, and preliminary autoradiography demonstrated heterogeneous regional distribution in the brain with specific binding. These findings highlight [3H]7 as a valuable tool for OGA binding studies and provide a foundation for the future development of novel positron emission tomography (PET) ligands to probe O-GlcNAc signaling in the brain.

pharmacology and toxicology↗

bioRxiv2025

Genome-wide Identification, Structural Features and Single-Cell Expression Atlas of the Carbonic Anhydrase Gene Family in Maize (Zea mays L.)

Maize is a cornerstone C{square} crop underpinning food, feed and bioenergy. Carbonic anhydrases (CAs) are zinc metalloenzymes that catalyze the interconversion of CO{square} and HCO{square}{square}, underpinning photosynthesis, pH homeostasis and stress acclimation. Despite extensive work on plant CA families, a maize-focused synthesis integrating genome-wide cataloging, structural divergence, regulatory logic, and cell-type specificity is still lacking.Here we present a genome-wide census and a single-cell-resolved expression atlas of the maize CA family. We identified 18 CA genes partitioning into (8), {beta} (5) and {gamma} (5) subfamilies. Proteins span 206-452 aa, pI 6.09-10.58 and 22.67-49.36 kDa, with predominantly hydrophilic profiles. Phylogeny resolved three robust clades (UFboot >90%) and indicated closer affinity to rice than to Arabidopsis; synteny recovered 15 maize-rice and 3 maize-Arabidopsis orthologs. Promoters are enriched for ABRE, TCA-element and ARE, suggesting ABA, SA and redox regulation. Bulk RNA-seq across 21 tissues revealed strong tissue specificity ({tau} >0.7 for 12 genes), with {beta}-CAs elevated in leaves and -CAs in roots. Single-cell analyses further showed Zm{beta}CA3 enriched in mesophyll cells and ZmCA2 enriched in vascular/root-cap cells. Together, these data position {beta}-CAs as chloroplast-centered hubs for C4 photosynthesis, while /{gamma}-Cas support ion/pH buffering and mitochondrial metabolism. We nominate cell-type-specific CA members as candidates for genetic improvement toward stress resilience in maize.

plant biology↗

bioRxiv2025

Changes in Urinary Proteome Post-Translational Modifications Following Short-Term Intake of Specific Magnesium, Calcium, Zinc, and Iron Supplements in Rats

Magnesium, calcium, zinc, and iron are essential mineral elements indispensable for maintaining physiological functions in mammals. This study investigated changes in post-translational modifications (PTMs) of the urinary proteome in Sprague-Dawley (SD) rats of different ages following short-term intragastric administration of magnesium L-threonate (MgT), calcium gluconate, zinc gluconate, and polysaccharide-iron complex. The results revealed PTM alterations in the urinary proteins of rats in all mineral supplement groups, with the most pronounced changes observed in the polysaccharide-iron complex group. Notably, rats of different ages exhibited distinct responses to the same mineral supplement. The proteins carrying differential PTMs were involved in a wide range of biological functions, and several of them, including serotransferrin and beta-2-microglobulin, are closely associated with mineral metabolism. This study explores the functional changes in urinary proteins from a PTM perspective following short-term mineral supplementation in rats, providing a novel viewpoint for investigating the physiological functions of mineral elements.

biochemistry↗

bioRxiv2025

Frequency-Aware Interpretable Deep Learning Framework for Alzheimer's Disease Classification Using rs-fMRI

Gaining insight into the spectral and temporal alterations in brain connectivity associated with Alzheimers disease (AD) may offer pathways toward more informative biomarkers and a deeper understanding of disease mechanisms. We propose FINE (Frequency-aware Interpretable Neural Encoder), a novel deep learning model designed to capture multi-scale temporal and frequency-specific patterns in dynamic functional network connectivity (dFNC) derived from resting-state fMRI. FINE integrates multiple expert branches, including convolutional layers, learnable wavelet layers, transformers, and static encoders, enabling the joint modeling of temporal evolution and spectral content of brain networks in an end-to-end framework. Beyond classification, FINE supports frequency-wise interpretability by aligning gradient-based saliency maps with statistical group differences, revealing potential robust, biologically meaningful biomarkers of AD. Evaluated on the large OASIS-3 dataset (856 subjects), FINE achieves AD classification performance (ROC-AUC 0.769) and provides insights into frequency-specific connectivity disruptions, particularly within subcortical, sensorimotor, and cerebellar networks. Our results demonstrate that incorporating frequency-aware modeling and interpretable architectures can advance both disease classification and underlying functional disruption of AD-related brain dynamics.

neuroscience↗