Biology subjects

Yang, H.

Publications and source records attributed to Yang, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

A cross-tissue POSTN+ fibroblast atlas links periodontal, tumor, and fibrotic stromal niches

Cross-tissue single-cell atlases have re-framed fibroblasts as a continuum of activation states, with universal Pi16+ progenitors giving rise to tissue-restricted activated populations[1] and shared pathological states recurring across inflammatory diseases[2]. Periostin (POSTN), a matricellular protein of injured, fibrotic, and tumor stroma, has been independently linked to activated fibroblasts in liver fibrosis[3], colorectal cancer[4], head-and-neck cancer[5], and dental contexts[6, 7], but cross-tissue conservation of a single POSTN+ program is untested. Here we built a Harmony-integrated atlas of 56,713 human and mouse fibroblasts from eight single-cell datasets spanning six organ contexts (periodontal ligament, periodontitis, oral squamous-cell carcinoma, colorectal cancer, temporomandibular-joint osteoarthritis, and bile-duct-ligation liver fibrosis). A conservative cluster-consensus definition (Wilcoxon padj < 0.05 and log2FC > 0.5 within an atlas-integrated leiden cluster, combined with per-cell POSTN > 0) identified 11,451 POSTN+ cells (20.2% of the atlas) recurring across all six contexts at frequencies from 6.2% (periodontal ligament) to 55.1% (liver fibrosis). Within-fibroblast differential expression yielded a 102-gene shared core program -- collagen biosynthesis, ECM crosslinkers, and matricellular markers including POSTN, SPARC, BGN, FN1, MMP2, and CTHRC1 -- interpreted as POSTN-specific transcriptional amplification of an activated ECM-remodelling module. KLF4, hypothesized a priori as a POSTN+ co-marker, was upregulated in only one of six contexts, consistent with its role as a quiescence brake released during activation[3]. Three pre-registered sensitivity analyses (Harmony parameter, three definitions, dataset exclusion) and an independent Puram-2017 OSCC cohort (1,422 fibroblasts; 101/102 core genes recovered; primary vs lymph-node-met Mann-Whitney p = 0.005) support robustness across integration parameters, definitions, dataset inclusion, and platform.

bioinformatics↗

bioRxiv2026

Synthetic-data augmented calibration for expert-informed rare disease models

Clinical data for rare diseases are sparse, noisy, and heterogeneous, complicating calibration of ordinary differential equation (ODE) models. Thus, we introduce a noise-robust calibration in latent space that combines expertderived ODEs with learned latent representations. Our approach leverages synthetic ODE trajectories, augmenting our scarce observations to train a model-specific autoencoder representation and imputer. During calibration, observed and ODE-generated trajectories are compared in latent space, and ODE parameters are updated by minimizing their latent distance. In a controlled ABCDE simulation model, the imputer outperformed a carry-forward baseline for moderate parameter shifts, parameter recovery remained stable under random missingness, calibration remained robust to additional noise variables despite reduced downstream identifiability, and distinct dynamics formed visually separable latent trajectories. On a custom developed ODE model for real Epidermolysis Bullosa patients, the calibrated phenomenological model reproduced patient-level trajectories from sparse observations. Thus, we conclude that our latent-space calibration approach supports rare-disease modeling.

bioinformatics↗

bioRxiv2026

BiomniBench: Process-level Evaluation of LLM Agents for Real-world Biomedical Research

LLM agents now perform real biomedical research, but evaluating them rigorously is hard. Outcome-only benchmarks fail in two ways. First, a correct final answer can come from memorization, reward hacking, or wrong reasoning that produces the right number by chance. Second, valid alternative analyses are marked wrong simply because they differ from the reference. We introduce BiomniBench, a process-level evaluation framework that scores the full agent trajectory against expert-designed, task-specific rubrics. Our first release, BiomniBench-DA, contains 100 data-analysis tasks across 17 task types, 5 disease areas, and a general-biology category, each based on a paper from journals such as Nature, Cell, and Science and co-developed with an original author or a domain expert. Benchmarking frontier and open-weight models across four agent harnesses reveals three findings. Frontier and open-weight bases cluster within a few points of each other, with substantial headroom for all models. The agent harness shifts scores by more than the gap between successive model generations. Agents reliably ground claims in real sources yet consistently fall short on method selection, biological interpretation, and scientific reasoning. BiomniBench is the first process-level benchmark for LLM agents in biomedical research, providing the dimension-level diagnostics that outcome scoring cannot. Datasethuggingface.co/datasets/phylobio/BiomniBench-DA

bioinformatics↗

bioRxiv2026

DOMINO: Learning Domain Co-occurrence for Multidomain Protein Design

Multidomain proteins arise through the reuse and recombination of structural domains, yet natural architectures represent a sparse, structured sample of the possible domain-combination space. Here, we introduce DOMINO, a two-stage framework that learns domain co-occurrence from TED-annotated multidomain proteins and uses the learned patterns to generate new multidomain sequences. DOMIN, a contrastive retrieval model, embeds domains into a latent compatibility space and retrieves candidate partners for a query domain from a TED-derived domain pool, including pairings not observed in the TED-derived co-occurrence set. DOMO, a conditional autoregressive sequence model, converts each retrieved domain pair into a full-length protein sequence by jointly generating the specified domain regions and the non-domain sequence context between and around them. DOMIN recovers hierarchical patterns of natural domain co-occurrence and expands the observed CATH homologous-superfamily co-occurrence network with candidate novel pairings. DOMO realizes both held-out natural pairs and DOMIN-retrieved pairs as proteins with high domain recovery and high AlphaFold-predicted structural confidence. Applied at scale, DOMINO generated 5 million retrieval-derived multidomain proteins, with sampled designs showing recovery of the specified domains, diverse CATH annotations, and sequence novelty relative to UniRef100. Together, these results support domain co-occurrence as a predictive design prior and demonstrate a scalable strategy for exploring multidomain protein architectures through new combinations of existing structural modules.

bioinformatics↗

bioRxiv2026

Automated Multimodal Correlative Registration for Organelle-Specific Molecular Imaging

Mapping subcellular drug distribution is essential for understanding trafficking and off-target effects. NanoSIMS enables chemical imaging of labeled therapeutics, but signal interpretation requires ultrastructural correlation with electron microscopy, a manual and laborious process. We present an automated AI-driven pipeline for correlating chemical and ultrastructural images, enabling multiscale, organelle-precise imaging of molecules in cells and tissues. The method integrates bidirectional optical flow, confidence-guided affine transformation, and automated template matching for cross-scale EM alignment. Morphology-rich ion channels (e.g., 32S) estimate transformations that propagate to sparse therapeutic signals (e.g., 79Br, 15N), overcoming low signal-to-noise challenges. We validate this framework across diverse cell and tissue types, tracking oligonucleotide and antibody therapeutics in vitro and in vivo to reveal cell-type- and organelle-specific distribution patterns. This work establishes a generalizable platform for automated multimodal registration and organelle-resolved subcellular pharmacology.

bioinformatics↗

bioRxiv2026

A Deep Learning-Based Scoring Framework for Large-Scale Multi-Donor Cardiotoxicity Screening

Cardiotoxicity remains a major cause of drug attrition and post-market withdrawal, yet the vast majority of environmental chemicals to which humans may be exposed remain uncharacterized for cardiotoxicity risk. Human induced pluripotent stem cell (hiPSC)-based testing has been proposed to address this gap. Here we present an unsupervised deep learning framework for multi-donor cardiotoxicity screening using high-throughput calcium transient recordings from hiPSC-derived cardiomyocytes (hiPSC-CMs). We used data from a library of 1,029 compounds that were tested in hiPSC-CM from five donors in concentration-response. An autoencoder trained exclusively on baseline signals quantified chemical-induced functional perturbations through reconstruction error, bypassing the need for labeled training data while capturing the full spectrum of calcium handling disruptions. Using this framework, we generated effect levels. Aggregation of donor-specific scores revealed substantial inter-individual variability in potential cardiotoxicity, underscoring the value of this approach for population-level risk prediction. We found that microbiocides, dyes, and pesticides to have potential concern, characterized by high toxicity scores and low inter-donor variability. This framework establishes a scalable, human-relevant, and genetically diverse platform for cardiotoxicity surveillance across both pharmacological and environmental chemical spaces, with direct implications for drug and chemical safety evaluation and prioritization for additional studies.

bioengineering↗

bioRxiv2026

A Generative AI Framework to Predict Cardiomyocyte Contraction Function from Single Static Images.

Understanding how cardiomyocyte structure governs contractile function is fundamental to cardiac biology and disease modeling, yet current approaches rely on time-resolved imaging and computationally intensive analysis. Here, we present a generative artificial intelligence (AI) framework that directly predicts contractile behavior of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from single static images. Our approach integrates a U-Net-based generator with a patch-based generative adversarial network (GAN) discriminator to translate morphological and sarcomere structural features into pixel-resolved contraction heatmaps. This U-Net-GAN model achieved high predictive accuracy, with structural similarity index (SSIM) values up to 0.84 using combined morphological and structural inputs. To further enhance performance and generalizability, we incorporated synthetic cell-function pairs generated via a generative AI StyleGAN2 framework, improving prediction accuracy and perceptual similarity. Importantly, region-specific and whole-cell analyses revealed that AI predictions capture biologically meaningful structure-function relationships, with sarcomere organization strongly associated with both contractile output and prediction fidelity. Reconstruction error emerged as an interpretable metric reflecting localized inefficiencies in sarcomere-to-contraction coupling. Together, this framework establishes a scalable and interpretable strategy for inferring cardiomyocyte function from static morphology, eliminating the need for time-lapse imaging. More broadly, this work positions generative AI as a powerful tool for bridging cellular structure and function, enabling high-throughput functional phenotyping and advancing in vitro cardiac modeling.

bioengineering↗

bioRxiv2026

A recurrent neural network model of chronic pain development and recovery

Chronic pain presents a leading challenge in the world today for both clinicians and researchers. Because chronic pain is difficult to explain and treat, it is often managed with opioids despite providing limited relief and contributing to dependence and misuse. Persistent pain can be maintained by altered central nervous system processing even in the absence of distinct tissue damage or disease, which may limit the efficacy of conventional pharmacological therapies that target nociceptive signal transmission rather than maladaptive central nervous system dynamics often present in those with chronic pain. Although neuroimaging studies have identified this shift from nociceptive to emotional circuits during pain chronification, a quantitative framework linking these neural changes to longitudinal pain trajectories or recovery is lacking. We present a parsimonious firing-rate model that can account for the development of and recovery from chronic pain, which is based on the theoretical framework established by Wilson and Cowan. The model provides a quantitative explanation of how sensitization, anxiety, and fear maintain pain even after an injury has healed, and how calming stimulus downregulates these processes to facilitate recovery. A study applying the same principles as the model produced an average pain decrease of 3.5 on the Visual Analog Scale (VAS), with all subjects experiencing a reduction in pain. These results, coupled with our model and findings in prior studies, suggest that increasing calming stimulus can reduce pain without necessitating pharmacological or invasive, resource-intensive interventions.

neuroscience↗

bioRxiv2026

Integration of proteogenomic analyses in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is still lack of clinically molecular subtyping and effective therapeutic strategies. Herein, a total of 46 paired tissue samples of esophageal squamous cell carcinoma (ESCC) were collected and subjected to a systematic proteogenomic evaluation. Consensus assessment of the ESCC-related transcriptomes and TCGA dataset revealed several consensual modes of gene expression related to ESCC specificity, with 8 plasma-detectable hub proteins that could discriminate ESCC from others. Three ESCC molecular subtypes were defined and validated based on proteome data, including pCC1 with activated immune response and best survival outcome, pCC2 as cell cycle subtype with relative worse outcome, and pCC3 with worst outcome that expressed more cell adhesion related proteins. Furthermore, we proposed potential therapeutic strategies for improving survival outcomes in patients with different ESCC molecular subtypes. This integrative proteogenomic analysis provided a novel view of ESCC-dependent molecular information.

cancer biology↗

bioRxiv2026

Combination of engineered cell type-specific promoters and a high-efficiency AAV capsid restores hearing in adult DFNB1 mice model with demonstrated safety in nonhuman primate

A major challenge in gene therapy for GJB2-related hearing loss (DFNB1)--the most common form of hereditary deafness--is achieving efficient and precise connexin 26 delivery. Herein, we engineered two cell type-specific promoters (GJB2-1 and WFS1-2274) and developed an AAV capsid, AAV-MAS012, with enhanced transduction efficiency in mature cochlear cells. Our AAV-mediated gene therapy systems restored hearing of low-to-mid-frequencies in newborn Gjb2 cKO mice to wild-type levels and maintained for 45 weeks. Additionally, our therapeutic systems restored low-to-mid-frequencies hearing function to wild-type levels in adult Gjb2 cKO mice. A humanized version of the therapy, AAV-MAS012-WFS1-2274-hGJB2, rescued hearing function in two distinct Gjb2-deficient mouse models, and demonstrated a favorable safety profile in nonhuman primates. This study represents the first successful hearing restoration in adult Gjb2-deficient mice. The significant therapeutic efficacy of the humanized gene therapy system shows great potential for clinical translation in DFNB1 patients.

genetics↗

bioRxiv2026

Catalase 2-dependent regulation of autophagy in response to carbon starvation in Arabidopsis

Reactive oxygen species (ROS) are fundamental regulators of plant development and stress acclimation. However, their roles in carbon starvation tolerance remain largely unresolved. We therefore dissected the dynamics of redox regulation in carbon-starved Arabidopsis leaves. We present data showing the presence of an early ROS wave that activates autophagy, followed by a sustained, accumulation of hydrogen peroxide (H2O2) that leads to programmed cell death. We show that catalase 2 (CAT2) constitutively binds and sequesters the autophagy initiators ATG1a and ATG13a, a process that prevents the activation of autophagy under carbon-replete conditions. The accumulation of H2O2 in response to carbon starvation leads to oxidation of the Cys-370 and Cys-413 residues on the CAT2 protein and dissociation from ATG1a/13a, thereby allowing ATG1-kinase complex assembly and autophagosome formation. The expression of CAT2-C370S or CAT2-C413S variants in the cat2-1 mutant significantly enhanced carbon starvation tolerance, because both variants retain catalase activity but fail to bind ATG1a/13a. We conclude that CAT2 functions as a redox-sensitive regulator of autophagy.

plant biology↗

bioRxiv2026

Structure-based similarity network accelerates the discovery of lysins as oral microbiome modulators targeting periodontal pathogens

Microorganisms significantly influence human health, and dysbiosis of the oral microbiome plays a critical role in the development and progression of both oral and systemic diseases. This highlights the urgent need for novel therapeutics targeting specific pathogens. Here, we presented a structure-based pipeline to efficiently identify potential phage-derived periodontal lysins (LysPds) from nearly one million proteins. We predicted the structures of candidate lysins using AlphaFold2 and developed an innovative structure-based similarity network to classify them into distinct clusters, each with unique functional properties. A systematic characterization of 16 representative LysPds from 11 superfamilies revealed that over 90% demonstrated potent antibacterial activity against key periodontal pathogens. Among these, LysPd078 was identified as a promising preclinical drug candidate, effectively reconfiguring microbiome communities while demonstrating significant efficacy and safety in mouse models of periodontitis and calvarial infection. Our findings highlight the effectiveness of structure-based similarity networks in exploring vast protein spaces and underscore the potential of LysPd078 as a targeted modulating agent for the oral microbiome.

microbiology↗

bioRxiv2026

Nucleoid-associated proteins sense phage-induced genome damage to elicit abortive infection

Bacteria have evolved diverse immune strategies to detect and neutralize bacteriophage infection. Here, we describe an unprecedented paradigm in which a chromosome-architecting nucleoid-associated protein (NAP) is repurposed as a viral infection sensor. When phage attack leads to genome degradation, the NAP sensor is released from the nucleoid to the cytoplasm, where it binds and activates diverse immune effectors. One such effector is a nucleotide-modifying toxin normally existing as an inactive homotetramer. NAP binding converts it into a catalytically active heterotrimer that halts both transcription and translation. Phylogenetic analyses unveiled the high modularity, polyphyletic origin, and wide distribution of NAP-mediated defenses. Collectively, we define a distinct class of defense systems in which bacteria sense phage-induced genome damage through NAP relocation, highlighting an unexpected but essential role for these proteins as sentinels of genome integrity.

microbiology↗

bioRxiv2026

Box H/ACA snoRNP regulates lipid storage through insulin signaling pathway in Drosophila melanogaster

Text abstractsLipid homeostasis is essential for organismal physiology, and its disruption contributes to metabolic disorders. Using an unbiased genetic modifier screen in Drosophila, we identified GAR1, a core component of the box H/ACA small nucleolar ribonucleoprotein complex, as a pivotal regulator of systemic lipid storage. We show that the H/ACA snoRNP complex is essential for maintaining lipid droplet morphology in adipose tissue and preventing ectopic fat accumulation. Moreover, null mutants of Gar1 or Dkc1 exhibit severe developmental defects, including reduced body size and larval lethality. RNA-seq analysis revealed that Gar1 dysfunction triggered widespread alternative splicing defects, specifically targeting key transcripts within the insulin signaling cascade, including chico, Pi3K92E, sgg, and Lip4. Furthermore, knockdown of Gar1 impaired insulin signaling, as evidenced by the reduced membrane localization of the tGPH fluorescence. Genetic epistasis further positions GAR1 upstream of the lin-28/foxo axis, as knocking down lin-28 or foxo fully rescues the lipometabolic defects in GAR1-deficient animals. These findings reveal a previously unrecognized link between the snoRNP machinery and metabolic process, establishing the box H/ACA complex as an important coordinator that integrates RNA processing with insulin-mediated nutrient sensing to ensure developmental and lipid homeostasis. Article summaryLipid metabolism is tightly controlled by multiple factors. To find new regulators, the authors performed a genetic screen and identified a small nucleolar protein GAR1 participate in fat storage and larval development. They demonstrated a critical role of box H/ACA snoRNP complex in modulating alternative splicing and balancing insulin cascade. Blocking two insulin-related genes reversed the lipid defects caused by Gar1 loss. These findings revealed the box H/ACA complex integrates RNA processing with insulin-mediated nutrient sensing to ensure developmental and lipid homeostasis, offering a perspective for understanding the metabolic regulation network.

genetics↗

bioRxiv2026

A Conserved Metabolic Oxidative Axis Underlies Immune Cell Cryo-vulnerability

Immunotherapy has emerged as a transformative approach for treating cancer and other diseases, yet its widespread deployment requires effective cryopreservation strategies to enable scalable global distribution. However, many immune cell types remain acutely vulnerable to freeze-thaw stress, and the underlying mechanisms of this cryo-vulnerability are not well defined. In this study, we combined metabolic flux analysis, ROS quantification, lipidomics, and preclinical xenograft models to investigate how metabolic state influences cryopreservation outcomes. We found that immune cell activation induces a metabolic shift characterized by elevated glucose utilization and excessive ROS production, leading to profound post-thaw loss of viability and function, as demonstrated by a [~]25% survival rate in natural killer (NK) cells. Targeted pretreatments--including inhibitors of glucose metabolism, antioxidants, and suppression of lipid peroxidation--restored post-thaw recovery to nearly 90% while preserving effector activity and antitumor efficacy. Similar protective effects were observed across {beta} T cells, {gamma}{delta} T cells, and macrophages, defining a conserved metabolic-oxidative pathway of cryo-vulnerability and offering applicable strategies to enhance immune cell preservation.

immunology↗

bioRxiv2026

A novel fracture lattice in spiny mouse skin facilitates tissue autotomy and regeneration

Autotomy is a unique phenotype whereby an animal sheds a body part to escape predation1-3. The timing and location of autotomy are tightly regulated by preformed planes of weakness (aka fracture planes) which facilitate tissue loss. While autotomy is often followed by regeneration, these phenotypes are rarely reported in mammals4-9. A notable exception are spiny mice (Acomys) which exhibit skin autotomy and more remarkably, complete tissue regeneration10-14. Presently, mechanisms underlying autotomy and complete regeneration in Acomys skin remain elusive. Here, we report the discovery of a honeycomb-like fracture lattice in Acomys skin whose design directs tissue destruction but also facilitates regenerative healing. Unlike the single continuous surface of a fracture plane, this fracture lattice consists of a three-dimensional array of hexagonal units whose boundaries guide tissue breakage. Moreover, we identify collagen VI as the main constituent of the fracture lattice and find that it is distinctly arranged to initiate fracturing and propagation of skin tearing. By preconditioning the tissue for autotomy, the fracture lattice dampens the damage-induced inflammatory response but also upregulates a pro-regenerative gene signature, accelerating skin appendage regeneration. Lastly, we discovered the key role of spiny hairs in fracture lattice formation, as inhibiting their development leads to abnormal pattern formation and changes in skin fracture mechanics. Our results present a novel example of a uniquely evolved structural adaptation in mammalian skin that links tissue patterning, autotomy and regeneration. We expect that the application of a modular compartment structure to artificial skin and other organ engineering may enhance resilience to injury and facilitate efficient regeneration.

developmental biology↗

bioRxiv2026

Patchouli alcohol suppresses gastric cancer growth and immune evasion via inhibition of the NF-κB/PD-L1 axis

ObjectiveThis study aimed to investigate the anti-gastric cancer effect of Patchouli alcohol (PA), especially its influence on PD-L1-mediated immune evasion, and to elucidate the underlying molecular mechanisms. MethodsA CCK-8 assay was used to evaluate the effects of PA on the viability of the gastric cancer cell lines HGC-27 and MKN-45. RT-qPCR and western blotting were performed to analyze the mRNA and protein levels of NF-{kappa}B and PD-L1, respectively. In a coculture system of gastric cancer cells and peripheral blood mononuclear cells (PBMCs), the effect of PA pretreatment on the PBMC-induced apoptosis of cancer cells was analyzed by flow cytometry, and the cytotoxic activity of the PBMCs was assessed by a lactate dehydrogenase (LDH) release assay. Flow cytometry was also used to determine the proportions of CD3CD8 T cells and IFN-{gamma}CD8 T cells. ELISA was used to measure the levels of IFN-{gamma}, TNF-, and granzyme B in the coculture supernatants. Immunofluorescence staining was conducted to assess NF-{kappa}B nuclear translocation. In a mouse xenograft model, tumor volume and weight were measured after 14 days of PA treatment. Histopathological changes and apoptosis were analyzed by HE and TUNEL staining. A luciferase reporter assay was used to examine the transcriptional regulation of PD-L1 by NF-{kappa}B. ResultsPA inhibited the viability of HGC-27 and MKN-45 cells in a dose- and time-dependent manner and significantly downregulated the expression of NF-{kappa}B and PD-L1 at both the mRNA and protein levels. In a PBMC coculture model, PA pretreatment enhanced the ability of PBMCs to induce apoptosis and directly kill gastric cancer cells. Furthermore, PA pretreatment increased the proportions of CD3CD8 T cells and IFN-{gamma}CD8 T cells in a dose-dependent manner. Consistent with this immunostimulatory effect, PA increased the levels of IFN-{gamma}, TNF-, and granzyme B in the coculture supernatants. Mechanistically, western blotting analysis demonstrated that PA significantly reduced the protein levels of AKT, NF-{kappa}B, and PD-L1 in gastric cancer cells. Immunofluorescence staining further indicated that PA suppressed the nuclear translocation of NF-{kappa}B. In a mouse xenograft model, PA treatment significantly inhibited tumor growth, induced apoptosis, and downregulated NF-{kappa}B and PD-L1 protein expression in tumor tissues. Flow cytometry of tumor-infiltrating lymphocytes revealed increased proportions of CD3CD8 and IFN-{gamma}CD8 T cells following PA treatment. Finally, luciferase reporter assays demonstrated that NF-{kappa}B directly regulates PD-L1 transcription by binding to its promoter region. ConclusionPA exerts antitumor effects in gastric cancer by suppressing the NF-{kappa}B/PD-L1 axis, thereby enhancing CD8 T-cell-mediated cytotoxicity and inhibiting immune evasion.

pharmacology and toxicology↗

bioRxiv2026

Zhi-Shi-Huang-Wu slows Parkinson's disease progression in transgenic C. elegans models

Parkinsons disease (PD) is the second most progressive degenerative disorder of the brain due to dopaminergic (DA) neuron degenerations and alpha-synuclein (-Syn) accumulations. At present, the disease has no effective treatment. Therefore, the current study objective is to identify a novel anti-PD formula (Zhi-Shi-Huang-Wu Formula, F-2) computed at 8:4:2:1 ratio from HSP 70 promoter activators Valeriana jatamansi (V), Acori talarinowii (A), Scutellaria baicalensis (S), Fructus Schisandrae (F). Traditionally, V is used to cure memory impairments, A treats mental disorders, and chronic mild stress, S for neuroprotection, and F showed multiple therapeutic actions to treat insomnia. This study investigated the neuroprotective potential of the V, A, S, F, formula F-2 and its underlying molecular mechanisms in transgenic Caenorhabditis elegans models. A, S, F, and F-2 successfully restored 6-hydroxydopamine intoxicated DA neuron degenerations, reduced food-sensing behavior disabilities, and attenuated -Syn aggregations. Moreover, activates the lipid deposition and proteasome expressions to confirm -Syn degradations at the cellular level. Reactive oxygen species (ROS) cause oxidative stress, and A, S, F, and F-2 repressed ROS and raised SOD-3 expressions. Overall, these data indicate that V, A, S, F combined into F-2 (22.3%) are more effective against PD progression-like symptom than individual drugs V (0.7%), A (11.4%), S (9.6%), and F (12.6%). These improved neuroprotective actions of F-2 possibly due to following the antioxidative pathway. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/709540v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1a6f1f7org.highwire.dtl.DTLVardef@157a270org.highwire.dtl.DTLVardef@69a238org.highwire.dtl.DTLVardef@1194b5e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗