Biology subjects

Yang, H.

Publications and source records attributed to Yang, H..

At least 163 records · Page 9Linked to original sources

bioRxiv2025

The growth and pathogenesis of Citrobacter rodentium is compromised by disrupted mucin sugar pathways that accumulate N-acetylglucosamine 6-phosphate

Many enteric bacterial pathogens, including the attaching/effacing (A/E) Escherichia coli strains, cause acute gastroenteritis in humans. Considering the highly competitive nature of the mammalian gastrointestinal (GI) tract, these pathogens must rely on specific metabolic adaptations to establish successful infections. We hypothesized that A/E pathogens exploit host-derived nutrients within GI mucus, including the monosaccharides N-acetylglucosamine (GlcNAc) and N-acetylneuraminic acid (NeuNAc) to fuel their pathogenesis. Using Citrobacter rodentium, a murine-specific A/E pathogen, we disrupted both GlcNAc and NeuNAc catabolism by deleting nagA, which encodes the GlcNAc-6-phosphate (GlcNAc-6P) deacetylase that converts GlcNAc-6P into glucosamine-6-phosphate (GlcN-6P). The {Delta}nagA mutant displayed dramatically impaired colonization in C57BL/6J mice and accumulated significant levels of GlcNAc-6P, unlike the {Delta}mana strain, a mutant lacking all GlcNAc and NeuNAc transporters, suggesting that the attenuation was due to sugar-phosphate stress rather than nutrient deprivation alone. Supplementation with glucosamine (GlcN) restored growth, indicating that dysregulated GlcN-6P synthesis, rather than GlcNAc-6P toxicity, underlies the defect. Furthermore, {Delta}nagA exhibited increased susceptibility to several cell wall-dependent stress conditions, in concert with compromised peptidoglycan biosynthesis due to reduced UDP-GlcNAc synthesis. These findings reveal a previously unrecognized metabolic vulnerability in C. rodentium and suggest that targeting sugar-phosphate stress responses may provide a new therapeutic strategy against GI bacterial pathogens. ImportanceEnteric pathogens like Citrobacter rodentium can exploit sugars, including N-acetylglucosamine and N-acetylneuraminic acid, derived from intestinal mucus to grow and infect their hosts. This study shows that disruption of mucin-derived sugar catabolism impairs the fitness of C. rodentium in infecting the murine intestine by causing the accumulation of a toxic intermediate of mucin sugar metabolism. Rather than impaired nutrient acquisition, the bacteria are impaired due to the buildup of N-acetylglucosamine-6-phosphate, which depletes substrates for peptidoglycan synthesis. This metabolic bottleneck weakens the bacterial cell wall, making the pathogen more sensitive to environmental stress. These findings identify a conserved metabolic stress response that could be targeted to combat enteric pathogen infections.

microbiology↗

bioRxiv2025

Quantifying spatiotemporal decoupling of GDGT-temperature relationships in a deep alpine lake

Glycerol dialkyl glycerol tetraethers (GDGTs), membrane lipids produced by archaea and some bacteria, are widely used in paleoclimate reconstructions due to their empirical relationship with temperature. However, their application in lakes is complicated by uncertainties in source attribution and environmental controls on their distribution. To address these constraints, we analyzed both branched and isoprenoid GDGTs (brGDGTs and isoGDGTs) in settling particles collected over 19 months using sediment traps at four depths (10, 15, 25 and 35 m) in Lake Lugu, a deep, stratified alpine lake in southwestern China. GDGT fluxes showed synchronous spatiotemporal variations across depths, with higher values during winter mixing than summer stratification, suggesting in situ production enhanced by nutrient upwelling during lake overturn. Correlations between GDGT distributions and high-resolution water temperature profiles revealed strong temperature sensitivity in isoGDGTs, particularly the Ring Index (RI), with peak correlations linked to mean temperatures [~]20 days prior to trap recovery, indicating a clear temporal lag in GDGT-temperature relationship. Moreover, stronger correlations with temperatures at overlying depths, implying vertical transport of isoGDGTs and a dominant autochthonous origin from the upper water column. In contrast, brGDGTs displayed weak or non-significant temperature dependence, likely reflecting distinct microbial sources or other controlling factors. These findings underscore the utility of isoGDGT-based proxies, particularly RI, while highlighting the importance of accounting for spatiotemporal offsets in GDGTs production when reconstructing paleotemperatures in deep, stratified lakes.

ecology↗

bioRxiv2025

scRNA + TCR + BCR-seq Reveals the proportion and characteristics of dual TCR T cells and dual BCR B cells in mice infected with Echinococcus granulosus

Cystic echinococcosis (CE) is a zoonotic parasitic disease caused by Echinococcus granulosus, and the T and B cell responses and regulatory mechanisms in CE remain unclear. In this study, we analyzed the data of peripheral blood and spleen of mice infected with Echinococcus granulosus(EG) by scRNA+TCR+BCR-seq, and made the following novel findings: (1) Peripheral blood of Echinococcus granulosus (EG)-infected mice contained a higher proportion of dual TCR(T cell receptor) T cells with higher clonality than uninfected mice; (2) There was a bias in V gene usage between single TCR T and dual TCR T cells, as well as between single BCR(B cell receptor) B cells and dual BCR B cells in EG-infected mice; (3) Dual TCR Tregs, dual TCR effector CD8 T cells, dual BCR Bregs, and dual BCR memory/dividing B cells exhibited relatively high clonal expansion in EG-infected mice; (4) Shared CDR3 sequences and consistently highly expressed mRNA molecules exist between single receptor T/B and dual receptor T/B cells in EG-infected mice. KEGG enrichment analysis revealed that dual BCR B cells are closely related to the expression of factors associated with pathways such as "Th1/Th2 differentiation" and "antigen processing and presentation". These results suggest that dual TCR T and dual BCR B cells may be involved in the specific responses and regulation of EG-infected mice, providing a novel perspective for the adaptive immune response mechanisms and targeted therapy of parasitic infections. Author summaryEchinococcosis is a zoonotic disease currently prevalent mainly in various parts of Africa. At present, it cannot be completely cured; treatment relies solely on medication to alleviate symptoms. The immunoregulatory mechanisms underlying the disease remain unclear. Using single-cell RNA sequencing, we have identified a novel T- and B-cell subpopulation that may play a role in the immune response to the parasite. This finding opens a new avenue for researchers investigating parasitic diseases.

immunology↗

bioRxiv2025

De Novo design of a potent Wnt Surrogate specific for the frizzled7 subtype members

In humans, 19 Wnt ligands interact with 10 Frizzled (Fzd) receptors and the co-receptors LRP5/6 to initiate signaling. Wnts and Fzds are highly promiscuous, making it challenging to dissect the specific outcomes of individual Wnt-Fzd interactions. Developing Wnt surrogates with specificity for individual Fzd subtypes could be pivotal. We present a modular, potent, and Fzd7-specific Wnt surrogate that consists of three de novo designed modules, a Fzd7 binder, an LRP6 binder and a homodimeric protein. The Fzd7-specific module was designed by targeting two less conserved surface patches on the cysteine-rich domain (CRD) of Fzds to achieve both selectivity and affinity. It exhibits a strong binding affinity (KD < 2.3 nM) for the very closely related Fzd7 subtype members (Fzd7, Fzd1, Fzd2) with no measurable binding to the CRDs of the other seven Fzd receptors. This Wnt surrogate induced spheroid organoid formation from intestinal stem cells at subnanomolar concentration, and promoted full hair follicle regeneration and robust hair growth in mice. These results suggest that our strategy could be extended to design modular Wnt surrogates capable of selectively activating individual Fzd receptors, providing a valuable tool kit for development and differentiation, organoid cultures and targeted regeneration.

bioengineering↗

bioRxiv2025

FLEXTAG: A Small and Self-renewable Protein Labeling System for Anti-fading Multi-color Super-resolution Imaging

Super-resolution fluorescence imaging enables visualization of subcellular structures and molecular interactions at the nanoscale, but its broader application has been hindered by long-standing limitations in current protein tagging systems, including rapid photobleaching, tag-induced artifacts, poor post-fixation labeling efficiency, and restricted multiplexing capability. Here, we present FLEXTAG (Fluorescent Labeling for Exchangeable, X-resilient Tagging in Advanced Generic Nanoscopy), a comprehensive protein labeling system comprising three orthogonal, ultrasmall (12-18 kDa), and self-renewable protein tags that collectively overcome these major limitations of existing tagging systems, enabling optimized multi-color super-resolution imaging. Through continuous exchange of organic fluorophores, FLEXTAG supports unprecedented durations of high-resolution imaging in both live and fixed cells with minimal photobleaching. It is compatible with major super-resolution modalities, such as SIM, STED, STORM, and PAINT, and is applicable to a wide range of subcellular targets. To further address fixation-induced labeling inefficiency and background fluorescence, we developed a novel protection-based fixation method and chemical blocking strategies that significantly preserve tag accessibility and enhance signal-to-noise ratio, improvements that are broadly applicable to other protein tagging systems. Altogether, FLEXTAG enables long-term tracking of dynamic behaviors and interactions of subcellular targets, as well as mapping of nanoscale protein organizations and cellular architecture, advancing both basic research and translational applications in cell biology.

bioengineering↗

bioRxiv2025

NTM-DB: A Comprehensive Non-Tuberculosis Mycobacteria Genomic Database

Non-tuberculous mycobacteria (NTM) are a major group of environmental bacteria, with approximately one-third of them causing serious human infections, particularly respiratory diseases. The global rise in the prevalence and severity of NTM infections has posed a major public health challenge. While high-throughput sequencing has generated vast genomic data on NTM, there remains a lack of comprehensive resources for cross-species genomic analysis. To address these limitations, we have developed a specialized database called NTM-DB (https://ngdc.cncb.ac.cn/ntmdb) tailored for NTM researchers and clinicians. NTM-DB offers the most comprehensive collection of NTM genomic and bioinformatic resources, including 16,469 genome assemblies (13,134 newly assembled genomes), 189 type/standard strain genomes representing 177 species and 12 subspecies, 705 MLST types, 33,240 resistance genes, and 74,315 virulence genes. A user-friendly interactive website has been constructed to enable efficient browsing, MLST profiling, searching, online analysis, and downloading of the aforementioned data. Notably, with online analysis tools, users can perform customized genotyping, cross-species phylogeny, pan-genome, and virulence and drug resistance gene annotation analyses using our data and/or their uploaded data. Overall, with its comprehensive data, intuitive interface, and powerful analysis tools, NTM-DB serves as an important resource and reference for NTM researchers and clinicians, improving diagnosis and treatment for various NTM-related diseases, and supporting both scientific discovery and clinical practice.

microbiology↗

bioRxiv2025

Genetically encoded assembly recorder temporally resolves cellular histories in cellulo and in vivo

Mapping cellular activity with high spatiotemporal precision in complex tissues is essential for understanding organ physiology, pathology, and regenerative processes. Here, we introduce Granularly Expanding Memory for Intracellular Narrative Integration (GEMINI), an in cellulo recording platform that leverages a computationally designed protein assembly as an intracellular memory device to record individual cells activity histories. GEMINI grows predictably within live cells with minimal interference to cellular functions, capturing cellular activities as tree-ring-like fluorescent patterns in the expanding scaffolds for imaging-based retrospective readout. Absolute chronological information of activity histories was attainable with hour-level accuracy through the integration of fiducial timestamps. GEMINI effectively resolved differential NF{kappa}B-mediated transcriptional changes, distinguishing fast dynamics of 15 minutes, and providing quantifiable signal amplitudes. In a xenograft model, GEMINI recorded inflammation-induced signaling dynamics across tissue with cellular resolution, revealing spatial heterogeneity linked to vascular density. When expressed in the mouse brain, GEMINI exhibited negligible impact on neuronal survival, with animals maintaining normal motor and cognitive behaviors. In physiological contexts, GEMINI successfully resolved both transcriptional changes and activity patterns of neurons in the brain. Together, GEMINI provides a robust and generalizable means for spatiotemporal mapping of cell dynamics underlying physiological and pathological processes in both culture and intact tissues.

bioengineering↗

bioRxiv2025

Formulation and Characterization of Primary Tissue-Derived Microfluidic Droplet-Engineered Organoids

Organoid technology offers a powerful platform for modeling human tissues, studying disease mechanisms, and developing personalized therapies. However, widespread clinical application is hindered by challenges in scalability, reproducibility, and the handling of ultra-small tissue samples typical of clinical biopsies. Here, we present a comprehensive and automated protocol for the formulation and characterization of microfluidic droplet-engineered organoids (DEOs) derived from primary tissue samples. This protocol integrates 3 key stages: (1) Extraction and purification of viable primary cells from ultra-small tissue specimens using the small-Tissue Extraction Device (sTED); (2) High-throughput fabrication of uniform cell-laden microspheres using an integrated microfluidic bioprinter (OrgFab), capable of generating over 100 organoids from just 10 L of bioink; and (3) Rapid organoid characterization using lamination-based processing for single-cell analysis while preserving spatial context. The automated workflow minimizes manual intervention, reducing variability and enhancing reproducibility, making it suitable for high-throughput applications such as drug screening and disease modeling. Our method allows for the generation of patient-derived organoids that closely mimic the native tissue microenvironment, including diverse cell types and structural features, within a significantly reduced timeframe. This 3 stage protocol enhances the use of organoids in personalized medicine by enabling the rapid assessment of drug efficacy in patient-specific models. Here, the integration of advanced techniques supports existing organoid protocols, providing a valuable resource for researchers and clinicians seeking to improve patient outcomes through more efficient and precise organoid-based applications.

bioengineering↗

bioRxiv2025

Modular Assembly of Biohybrid Machines Using Force-Enhanced Skeletal Muscle Actuators

Muscle-based biohybrid systems integrate living muscle with engineered structures to create soft robots, biological models, and regenerative platforms. However, current actuators often lack strength and are difficult to assemble into complex devices. This study presents a suspended compliant skeleton that enhances muscle maturation by providing passive resistance, enabling high-stroke self-exercise without external stimulation. Using immortalized C2C12 cells, the resulting actuators achieved millimeter-scale strokes and millinewton-scale forces, surpassing previous benchmarks. Magnetic interfaces embedded in the skeleton allowed modular assembly into multi-degree-of-freedom devices such as grippers, arms, and positioning stages. These interfaces also support actuator replacement and repair, improving resilience and scalability. This approach significantly boosts engineered muscle performance and offers a robust, modular platform for building high-functioning, repairable biohybrid machines.

bioengineering↗

bioRxiv2025

Clinical and molecular characterisation of primary refractoriness to atezolizumab plus bevacizumab in patients with unresectable hepatocellular carcinoma.

BackgroundDespite improved outcomes with atezolizumab plus bevacizumab (A+B) in hepatocellular carcinoma (HCC), primary refractoriness (PRef), characterised by early progression or short-lived disease stabilisation following treatment, remains a significant and poorly understood clinical challenge. MethodsWe analysed 1296 patients with HCC and Child-Pugh A liver cirrhosis treated with frontline A+B (AB-real) and validated findings in 645 trial participants recruited to IMbrave150 and GO30140. PRef was defined by Society for the Immunotherapy of Cancer (SITC) criteria as progressive disease in the first 6 months after treatment initiation. Patients who achieved complete response, partial response or stable disease for [≥] 6 months were classified as responders. We performed a multi-parametric analysis of pre-treatment tumour tissue including machine learning-based quantification of tumour-infiltrating lymphocytes, imaging mass cytometry and RNA sequencing (RNAseq) to evaluate differences in the tumour microenvironment (TME) of PRef versus responding patients. We employed conditional inference tree analyses to provide a hierarchical organisation of determinants of PRef. ResultsAmong 677 AB-real and 378 trial patients evaluable by SITC criteria, PRef identified inferior median OS in comparison with responding patients (AB-real: 7.3 vs. 31.5 months, HR 3.7, 95%CI 2.8-8.5, p<0.001; Trials: 10.8 vs. NR, HR 4.6, 95%CI 3.3-6.3, p<0.001). PRef patients exhibited higher baseline systemic inflammation (neutrophil-to-lymphocyte ratio, NLR [≥]3), a distinctively immunosuppressive TME enriched in CD163+ tumour-associated macrophages and a higher Treg/Teff ratio. RNAseq of tumour tissue demonstrated lower intrinsic immunogenicity in PRef samples, characterised by repressed IFN-{gamma} and Teff signatures, with elevated myeloid infiltration. Conditional inference tree analysis identified IFN-{gamma} signature downregulation combined with NLR [≥]3 as the strongest contributor of PRef. ConclusionsPRef to A+B identifies a distinct biological entity characterised by unopposed systemic inflammation, myeloid cell infiltration and T-cell depletion. Targeting myeloid-mediated immunosuppression, particularly in patients with low IFN-{gamma} signature expression and elevated NLR might enhance responsiveness to A+B. HighlightsO_LIPrimary refractoriness to atezolizumab plus bevacizumab in hepatocellular carcinoma, as defined by SITC criteria, is associated with poor clinical outcomes. C_LIO_LITumour microenvironment profiling reveals an immunosuppressive phenotype characterized by high myeloid infiltration, reduced interferon-{gamma} signalling, and T-cell depletion. C_LIO_LIThe combination of systemic inflammation and low IFN-{gamma} signature expression strongly predicts primary refractoriness and may inform therapeutic decision-making. C_LI

cancer biology↗

bioRxiv2025

Multi-omics characterization of the skin microbiota reveals the anti-aging roles of Stenotrophomonas maltophilia

Shifts in the skin microbiome have shown a close link to chronological age. However, the contribution of skin microbiome in skin aging phenotypes remains unclear. To explore this, we performed phenotypic, metabolomic, metagenomic, and functional analyses on a cohort with divergent skin aging phenotypes. Genome-scale metabolic models (GEMs) integrated with metabolomic analysis revealed that Stenotrophomonas maltophilia, enriched in the younger group (categorized by AI-predicted age and skin elasticity), utilizes the glutathione cycle to maintain redox homeostasis. Cellular experiments showed its metabolites enhanced GSH synthesis and alleviated oxidative stress-induced skin aging by upregulating key genes in fibroblasts, including GCLM, PGD, SOD2, and NQO1. Additionally, GEMs highlighted its potential anti-aging roles in regulating host metabolic pathways involving betaine, lysolecithin, and porphyrin. In parallel, Acinetobacter guillouiae was found to influence host melanin metabolism by degrading dopamine (DA) and 3-methoxytyramine (3-MT), offering potential therapeutic strategies for mitigating pigmentation. Our findings highlight the dynamic interplay between skin microbiota and the host in aging, offering new insights for designing targeted anti-aging interventions.

microbiology↗

bioRxiv2025

Application of machine learning in the discovery of antimicrobial peptides: Exploring their potential for ulcerative colitis therapy

Ulcerative colitis (UC) is a chronic inflammatory bowel disease with rising global prevalence, yet existing treatments are not universally effective. Antimicrobial peptides (AMPs), produced by the immune system, have diverse antimicrobial and immune-regulatory functions, making them promising candidates for UC therapy. Using machine learning, we developed a machine learning-based prediction model to identify novel AMPs. The predicted peptides demonstrated significant biological activity in vitro and in vivo. In a dextran sulfate sodium-induced UC mouse model, engineered AMPs notably improved UC-related parameters, such as body weight, disease activity index (DAI), and colon length. These effects were likely mediated by modulation of Akkermansia muciniphila. This study highlights the potential of machine learning-identified AMPs as future therapeutic candidates for UC. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/660148v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@187dc6borg.highwire.dtl.DTLVardef@9800deorg.highwire.dtl.DTLVardef@1611c42org.highwire.dtl.DTLVardef@866406_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2025

Co-transcriptional splicing changes combine with reduced productive transcription initiation for cold-induced repression of FLC

The Arabidopsis floral repressor locus FLC is epigenetically silenced during winter cold to align flowering with spring. During weeks of cold exposure, FLC transcription is progressively reduced both by transcriptional repression mediated by FLC antisense transcription, and epigenetic silencing implemented through a Polycomb-mediated epigenetic switch. In the warm, FLC is transcriptionally repressed by coordinated changes in transcription initiation and RNA PolII speed in a mechanism involving proximal termination. Whether similar mechanisms contribute to the cold-induced FLC transcriptional repression is unknown. Here, we combine mathematical modelling and transcription profiling to investigate FLC transcriptional changes during the cold. We find different dynamics of spliced and unspliced transcripts during cold exposure with only a small change in PolII speed. We also show that, unlike short-term cold, long-term cold temperatures drive an increase in splicing rates while simultaneously reducing productive transcription at FLC. This process is influenced by antisense COOLAIR transcription but does not rely on proximal COOLAIR termination. Cold-induced transcriptional repression of FLC thus involves a decoupling of changes in productive transcription initiation from PolII speed and rates of co-transcriptional splicing, a different mechanism to that repressing FLC in the warm.

molecular biology↗

bioRxiv2025

Patch deconvolution for Fourier light-field microscopy

Imaging flow cytometry using Fourier light-field microscopy enables high-throughput three-dimensional cellular imaging, capable of capturing thousands of events per second. However, volumetric reconstruction speed remains orders of magnitude slower than the acquisition speed. The current state of art uses Richardson-Lucy algorithm, restricted to just 5-10 reconstructed per second with GPU acceleration. This limitation hinders real-time applications such as cell sorting and thus has bottlenecked the widespread adoption of 3D imaging flow cytometry. We introduce patch deconvolution, an optimisation compatible with the Richardson-Lucy framework that significantly accelerates convergence, achieving over 100-200 reconstructions per second on standard GPUs, a 20-40 fold improvement over Richardson-Lucy. Validated on both simulated and experimental datasets, patch deconvolution achieves reconstruction quality comparable to Richardson-Lucy in both static and flow data. This supports rapid cell sorting based on spatial features and enables advanced applications, such as detecting rare spatial events in large cell populations, which would otherwise be indistinguishable in traditional flow cytometry.

biophysics↗

bioRxiv2025

Regularized Deep Neural Networks for Combining Heterogeneous Features of Peptides in Data Independent Acquisition Mass Spectrometry

AbstractData-independent acquisition (DIA) has gained much attention in mass spectrometry (MS)-based proteomics for its improved reproducibility and unbiased data acquisition. In DIA-MS, the spectral library is crucial in peptide identification. However, this method is limited to peptides previously identified via data-dependent acquisition (DDA) MS experiments. This study proposes a deep learning approach for generating spectral libraries, even for previously unseen peptides. While most deep learning-based methods rely on one-hot encoding representation for peptides, the proposed method incorporates physicochemical features, including atomic composition, hydrophobicity, flexibility, fractional surface probability, and aromaticity. We introduce sparsity regu-larized neural network layers to facilitate the selection and combination of important high-dimensional physicochemical features and improve prediction performance. Fur-thermore, we suggest a transfer learning strategy for training the proposed deep neural networks having multiple heterogeneous input channels. Numerical experiments using benchmark DDA-MS data demonstrated that the proposed deep learning model out-performed existing benchmark models, such as Prosit and DeepDIA, particularly in predicting retention times. And it was demonstrated that the proposed models with sparsity regularization identified more peptides from HeLa cell DIA data compared to the other deep learning models.

bioinformatics↗

bioRxiv2025

Effects of diffusion MRI spatial resolution on human brain short-range association fiber reconstruction and structural connectivity estimation

Short-range association fibers (SAFs) are critical for cortical communications but are often underestimated in conventional resolution diffusion magnetic resonance imaging (dMRI) since they locate within a [~]1.5mm thin layer of superficial white matter. With the emergence of high-resolution diffusion imaging techniques, this study timely evaluated the effects of image spatial resolution on SAF reconstruction using simulation data and multi-resolution (2, 1.5, and 0.96 mm iso.) empirical data acquired on the same 20 healthy subjects using the gSlider sequence and 20 widely used tractography approaches. Resolution effects were qualitatively assessed through model fitting and tractography results and quantitatively evaluated using global and regional short-range connectivity strength (SCS). It is found that lower resolution systematically reduces SCS across all methods in a spatially varying manner. Moreover, tractography methods exhibit significant differences in resolution sensitivity, with diffusion tensor imaging (DTI) based single-tissue single-fiber tractography showing greater vulnerability than constrained spherical deconvolution (CSD)-based multi-tissue multi-fiber tractography. Probabilistic tracking with anatomical constraints (ACT) and filtering (SIFT) improves robustness. Finally, up-sampling data to nominally higher resolution partially mitigates resolution-induced degradation and improves SAF reconstruction accuracy, particularly for DTI tractography. Based on these findings, higher resolution and multi-shell imaging is recommended if possible. For a given dataset, data up-sampling and DTI-based probabilistic tracking with ACT is recommended for single-shell low b-value data. CSD-based probabilistic tracking with ACT and SIFT is recommended for single-shell higher b-value data and multi-shell data. In summary, this study systematically and quantitatively evaluated resolution effects on SAF reconstruction and structural connectivity estimation and provided practical guidelines for more accurate mapping of SAFs. These advances hold promises to improve the characterization of healthy and diseased human brains in a wide range of neuroscientific and clinical applications.

neuroscience↗

bioRxiv2025

GPX4 Promotes Optic Nerve Regeneration and RGC Neuroprotection

Preventing retinal ganglion cells (RGCs)s soma and axon degeneration and promoting optic nerve (ON) regeneration holds great promise for effective glaucoma treatment. To explore potential neural repair strategies, we focused on glutathione peroxidase 4 (GPX4), a key regulator of lipid peroxidation. GPX4 is upregulated in surviving RGCs after acute ON crush or chronic ocular hypertension insult, and also in regenerating RGCs. AAV-mediated RGC-specific overexpression of GPX4 promotes significant ON regeneration and RGC survival, along with visual functional preservation, demonstrating the detrimental role of lipid peroxidation in glaucoma and the therapeutic potential of modulating lipid peroxidation through GPX4 in optic neuropathies.

neuroscience↗

bioRxiv2025

Enhancing protective efficacy and immunogenicity of hemagglutinin-based influenza vaccine utilizing adjuvants developed by BECC

Seasonal influenza viruses continue to pose a significant threat, causing substantial morbidity and mortality in the US and worldwide despite the availability of vaccines and antivirals. These challenges may be addressed by improving vaccine immunogenicity through the inclusion of adjuvants that enhance immune responses against key antigens including influenza hemagglutinin (HA). BECC (Bacterial Enzymatic Combinatorial Chemistry) adjuvants are novel Toll-like Receptor 4 (TLR4) ligands created by modifying enzymes from lipid A synthesis pathways in Gram-negative bacteria. This study compares the ability of the biological and synthetic versions of these adjuvants to enhance the efficacy of recombinant HA (rHA) antigens in mouse influenza virus challenge. Mice immunized with rHA adjuvanted with BECCs stimulate the humoral and cell-mediated arms of the immune system without exhibiting cytotoxicity/pyrogenicity. A robust HA-specific immunoglobulin subtype, especially IgG2a, response was observed in mice adjuvanted with BECCs as compared to control adjuvants, MPL, and PHAD Further, animals adjuvanted with BECC470 cleared infection seven days post-infection, demonstrating their potential for further translational development. Vaccination adjuvanted with BECCs were also able to increase immune recognition of linear B and T cell epitopes when compared to control adjuvants, as well as induce durable immune response eighteen months post-vaccination. Together, these findings indicate that BECCs may serve as highly effective adjuvants in influenza vaccination. One Sentence Summary: Efficacy of engineered lipid A molecules as adjuvants for HA-based influenza vaccine

immunology↗