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Zhang, T.

Publications and source records attributed to Zhang, T..

At least 55 records · Page 3Linked to original sources

Hologenomics of xylotrophic bivalves reveals a minimalist, remote-acting evolutionary strategy of wood digestion

Wood constitutes the largest reservoir of biogenic carbon on Earth, yet remarkably few animals can exploit it. While terrestrial wood-feeders like termites rely on highly diverse gut microbiomes, xylotrophic marine bivalves have evolved a fundamentally different approach: a spatially segregated system where intracellular gill symbionts produce enzymes that act remotely within a nearly sterile cecum. However, the genetic and evolutionary basis of this unique symbiosis remains largely elusive. Here, we integrate hologenomics, transcriptomics, and biochemistry of a shallow-water shipworm (Teredo navalis) and a deep-sea borer (Xyloredo sp.). We find that despite diverging approximately 147 million years ago and occupying drastically different habitats, these bivalves maintain a strictly conserved ancestral karyotype and a shared genomic architecture for wood digestion. Our models reveal a clear host-symbiont division of labor. The host genome is specialized for lignin modification and targeted enzyme transport, whereas a highly streamlined symbiont community is responsible for core polysaccharide degradation. Central to this minimalist strategy is a lineage-specific GH5-GH6 dual-catalytic enzyme. By sharing amino acids across proximal binding pockets, this fusion protein unites endo- and exo-cellulase activities, enabling highly synergistic cellulose cleavage without the need for complex microbial communities. Ultimately, our comparative analysis with terrestrial models demonstrates that these marine invertebrates achieve efficient biomass degradation not through microbial expansion, but through extreme functional streamlining and molecular innovation, offering a distinct evolutionary paradigm for marine carbon cycling.

evolutionary biology↗

Computational evolutionary approach to generate antimicrobial peptides

As a consequence of the overuse of conventional antibiotics, there is currently an unprecedented increase in antibiotic resistance in newer generations of pathogenic bacteria. This growing problem has led scientists to discover novel medications that could potentially reduce the usage of antibiotics, such as antimicrobial peptides (AMPs). Recent study has demonstrated that pardaxin could bind deeply into the surface of a lipid model membrane and inhibit the growth of pathogenic bacteria, including Staphylococcus aureus and Escherichia coli. In this work, the antibacterial efficacy of pardaxin was extended further by performing selective in silico substitution, driven by deep learning, Evolutionary-Scale Cambrian (ESMC) combined with conventional AMP design principles. Principal component analyses of the ESMC embeddings combined with conventional design models produced a set of single- and multiple-mutant analogues of pardaxin, which were predicted and validated with experimental data to exhibit selective antimicrobial properties against either E. coli or S. aureus, respectively. Atomistic molecular dynamics simulations further supported the notion that alpha-helical stability is a critical predictor of inner membrane activity, strongly correlated with their selective antimicrobial action tested in the lab. Overall, the findings highlighted a promising application of deep evolutionary machine learning techniques for screening a range of novel AMPs for selective antimicrobial agents.

biochemistry↗

Inhibition of Pseudomonas aeruginosa-secreted protease IV reduces lung

The opportunistic pathogen Pseudomonas aeruginosa secretes numerous proteases that disrupt host defenses. Among them, the lysyl endopeptidase PrpL has been implicated in virulence, but its role in inflammatory responses has remained unclear. This study shows that purified PrpL activates the AP-1 transcription factors following instillation into mouse lungs, and drives robust production of IL-1{beta}, IL-6, and TNF, as well as clinical symptoms. A proteolytically inactive mutant of PrpL fails to elicit these responses. Structural analysis of the complex of PrpL and its natural inhibitory propeptide (PrpLPP) using X-ray crystallography revealed the inhibitory mechanism of PrpLPP, which guided the identification of a pre-existing dipeptide inhibitor (LasBi) that blocked PrpL activity and restricted AP-1-driven cytokine induction and clinical symptoms in vivo. This study shows that the alkaline protease AprA degrades PrpLPP and functions redundantly with LasB to liberate mature, active PrpL. Our findings: 1) establish PrpL as a key virulence factor that triggers AP-1-mediated inflammatory signaling, 2) provide structural and functional insights into PrpL inhibition, and 3) identify AprA as a novel upstream PrpL activator. Together, these results highlight PrpL as a promising anti-virulence therapeutic target. Given the functional redundancy of inflammatory effectors produced by P. aeruginosa, strategies aimed at mitigating P. aeruginosa-induced lung inflammation through PrpL inhibition would likely need to be combined with approaches targeting additional pro-inflammatory bacterial factors. Author SummaryWe identify PrpL as a critical Pseudomonas aeruginosa protease that activates the inflammatory transcription factor AP-1 and drives potent lung inflammation. Structural analysis of a natural PrpL inhibitor guided development of an existing dipeptide inhibitor that significantly reduced the production of proinflammatory cytokines and clinical responses in vivo. Moreover, discovery of the AprA protease as an additional PrpL activator refines the activation model and suggests potential upstream therapeutic strategies. These findings highlight PrpL as both a driver of pathogenesis and a promising therapeutic target for treating P. aeruginosa infections.

microbiology↗

Photo-thermal Bidirectional Coupling Model for Transcranial Photobiomodulation

BackgroundAccurate optical-field simulation is critical for precise dosage delivery in transcranial photobiomodulation (tPBM). Current simulations neglect photon absorption-induced tissue heating which leads to temperature-dependent alterations of the optical field, thus fails to account for the bidirectional photo-thermal coupling effect. ObjectiveThis paper aims to establish a dynamic photo-thermal couple model that rigorously quantifies the bidirectional interaction between tissue heating and light propagation, and improves the optical dose prediction. ModelWe propose a Photo-Thermal bidirectional coupling Model (PTM). First, the Pennes Bioheat Equation (PBE) is employed to model the thermal response induced by photon absorption. Second, a Real-time temperature-dependent Absorption coefficient Model (RAM) is newly developed to quantify the thermal effect. Third, the PBE and RAM are integrated into the photon diffusion equation, forming the PTM. Finally, this coupled framework is solved temporally by an unconditionally stable Crank-Nicolson scheme. SimulationsBenchmarking against an analytical solution (two-layer cylindrical domain) demonstrates that PTM reduces the temperature prediction error by over 2.35% compared to the uncoupled baseline. Simulations using a realistic head model reveal that, compared to PTM, uncoupled modeling underestimates energy deposition by 150 J/m3 and overestimates photon fluence by 3 J/m2 within just one minute, and such discrepancies will be amplified with increasing exposure duration and power. Furthermore, the PTM identifies a 1.43-mm advantage in penetration depth for pulsed-wave over continuous-wave modality under iso-energy conditions, a key insight enabled by the coupled modeling approach. ConclusionThe PTM provides a high-fidelity simulation framework that captures the dynamic, bidirectional photo-thermal coupling in tPBM, explicitly quantifying the thermal feedback ignored by current models and thereby enabling more reliable treatment optimization and safer clinical translation.

neuroscience↗

Driver-independent lexAop-tdTomato.nls reporter signal in the adult Drosophila proventriculus

Reporters are widely used in Drosophila genetics to visualize gene expression and cell lineages. However, uncharacterized limitations in specific reporter lines can lead to data misinterpretation. Here, we identify a consistent, driver-independent tdTomato signal in the adult proventriculus from the widely used lexAop-tdTomato.nls reporter line. This signal was observed across multiple lexA driver combinations and was directly detectable in lexAop-tdTomato.nls responder-alone adult proventriculi lacking any lexA driver and without antibody staining. In contrast, no comparable native red fluorescence was detected in larval proventriculi under the same no-antibody imaging condition. Mouse and rabbit anti-RFP immunostaining further supported the presence of proventriculus-associated tdTomato/RFP antigen in adult responder-alone animals. In larval responder-alone proventriculi, antibody-amplified staining was antibody-source-dependent: a detectable signal was observed only with rabbit anti-RFP, whereas mouse and rat anti-RFP produced no reliable detectable signal under the same staining condition. A driver-matched comparison using lexAop-RFP.nls did not reproduce the proventricular signal, arguing against detectable ectopic activity of the tested lexA driver in this tissue. However, because lexAop-tdTomato.nls and lexAop-RFP.nls differ in reporter/transgene architecture and possibly genomic insertion context, the underlying cause cannot be assigned specifically to the lexAop sequence. Our findings highlight the necessity of including driver-negative and no-antibody controls when using this reporter line in adult Drosophila proventriculus and gut studies.

genetics↗

Discrete depolarisations of chordotonal organ neurons propagate toward the soma and are independent of the sensory TRP channels NompC and Nanchung-Inactive.

The electrophysiological process of auditory transduction in insects remains largely conjecture due to the unknown role of ion channels localised to the cilia, but experimental evidence supports either NompC or Nan-Iav as the auditory mechanotransduction ion channel. Here, we knocked down two key genes that code for the two candidate sound-activated ion channels using dsRNA-mediated RNA interference. We measured sound-evoked activity of the auditory nerve and intracellular electrical currents from the ciliated ending of individual auditory receptors. We found that the sound-evoked nerve activity was reduced in nompC, nan and ift88 knockdown. Using whole-cell patch clamp recordings we found that nompC and nan knockdown resulted in reduced sound-evoked transduction current. Stochastic depolarisations hypothesised to be mediated from one of the candidate mechanotransduction ion channels, either NompC or Nan-Iav, where not affected by knockdown of either channel. The discrete depolarisations are therefore mediated through another unidentified ion channel. We test the hypothesis that discrete depolarisations are graded action potentials that travel toward the soma through noise analysis of the transduction current and analysis of discrete depolarisations to voltage-steps. As a positive control we also knocked down ift88, a protein essential for transporting proteins, including ion channels, along the cilium and found both the transduction current and the discrete depolarisations decreased. Key pointsO_LIInjection of dsRNA decreased RNA of nompC and nan C_LIO_LISound-evoked nerve activity is reduced for RNAi-mediated knockdown of nompC and nan C_LIO_LINompC and Nan both contribute to the transduction current C_LIO_LIThe stochastic discrete depolarisations are not due to NompC or Nan-Iav ion channel but to a third unidentified ion channel. C_LIO_LINoise analysis of the transduction current and the discrete depolarisations suggests they are graded action potentials that travel in the direction of the soma. C_LIO_LIKnockdown of ift88 reduced both the transduction current and discrete depolarisations. C_LI Significance StatementInsects are important to understand, economically, agriculturally and medically. However, we still do not understand fundamental aspects of how insects detect their own body movements, vibrations and sound. These senses are detected by insect chordotonal organs, specialised miniaturised mechanoreceptors that convert movements into electrical signals through specialised ion channels. Previous experimental work has advocated either NompC or Nan-Iav as the mechanosensitive ion channel. Here, for the first time, we reduced the expression of both nompC and nan and measured the sound-evoked transduction current directly from neurons in a specialised auditory chordotonal organ. In contradiction to previous studies, we show that both ion channels contribute to the transduction current and find that electrical signals termed "discrete depolarisations" travel toward the soma.

neuroscience↗

Transfer learning reveals species-specific olfactory preferences in Diptera and informs pest management strategies

The interaction between volatile organic compounds (VOCs) and odorant receptors (ORs), termed VOI, constitutes the molecular basis for species to recognize chemical information in the environment. Characterization of subtle differences in VOI relationships among closely related species is crucial for understanding the rapid evolution of ORs and for identifying species-specific chemical cues relevant to pest management. However, progress in this field has been constrained by both the scarcity of experimental data and limitations in computational prediction accuracy. To address this, we developed a virtual screening-enhanced transfer learning strategy that integrates large-scale molecular docking data with sparse functional experimental data. The resulting VOI prediction model was validated through functional experiments on the pest species Bactrocera dorsalis, demonstrating its cross-species predictive capacity. Using this model, we investigated the relationship between ecological niches and olfactory sensitivity in Diptera insects from multiple perspectives, with an emphasis on patterns that may inform pest behavioral research. The models predictive reliability was further supported by its consistency with known olfactory trends: it recapitulated the preferential responses of fruit flies and mosquitoes to esters and aromatics, respectively, and reproduced the previously reported negative correlation between olfactory and visual capacities in Drosophila. As a proof-of-concept application, we compared hematophagous and non-hematophagous mosquitoes, revealing overlapping chemical spaces but distinct patterns in their specifically recognized compounds. This study provides a reliable VOI prediction framework that reveals species-level olfactory preference patterns in Diptera, offering a computational pipeline to accelerate the discovery of behaviorally active compounds for species-specific pest monitoring and control.

bioinformatics↗

Much stronger coarse-to-fine visual processing in primate superior colliculus than primary visual cortex neurons

The visual system optimizes its signal processing properties to efficiently encode natural scenes. The superior colliculus (SC) and primary visual cortex (V1) both play important roles in visual-motor processing, and they both exhibit qualitatively similar visual responses. However, it is not clear whether the SC simply inherits V1s efficient coding image processing optimizations or not, especially given that the SC receives a substantial amount of direct anatomical inputs from V1. Here, by performing matched experiments in the two brain areas, as well as with the same visual stimuli and in the same experimental animals, we show that the dynamics of coarse-to-fine visual image processing in the SC are much stronger than those in V1. In the SC, visual response latencies, being fastest for coarse patterns, are dictated by image spatial frequency, independently of the spatial frequency tuning curves of the neurons. On the other hand, V1 visual response latencies are largely dominated by visual response sensitivity, which is itself much more broadband than in the SC. These observations remain fundamentally unchanged in active vision gaze-shift scenarios eliciting visual reafferent responses in both brain areas. Our results suggest that coarse-to-fine visual image processing dynamics are most observable, and thus most relevant, in visually-responsive neurons driving foveating eye movements, like in the SC. Besides explaining behavioral evidence for saccadic facilitation by images that are consistent with the statistics of natural scenes, these results indicate that coarse-to-fine visual processing dynamics are much more of a collicular than a cortical visual phenomenon.

neuroscience↗

Brain Structure Shapes Function through higher-order Functional Interactions

Brain function is deeply embedded within multiscale structural architecture. Conventional studies predominantly utilize pairwise connectivity networks to investigate structure-function relationships. However, this low-dimensional perspective overlooks multi-region collaborations for complex cognition. Consequently, whether and how anatomy constrains such higher-order functional networks remains unresolved. To address this pivotal question, we utilize an information-theoretic O-information approach to characterize higher-order functional interactions (HOIs). By reconstructing individual-level HOIs from multimodal structural networks, we directly validate the structural constraint on HOIs. The resulting reconstruction coefficients are defined as structural-functional constraint strength (SFCS), serving as a quantitative vehicle to decipher how anatomy shapes these higher-order networks. SFCS uncovers a highly heterogeneous structural constraint landscape across data modalities, spatial regions, and informational interaction modes. Crucially, individualized SFCS robustly predicts multi-domain cognitive phenotypes, showing higher sensitivity for informant-reported than patient-reported assessments. Finally, we show that this landscape undergoes pathological, mode-specific reorganization in Alzheimers disease. Cross-scale alignment with spatial transcriptomics further demonstrates that this macroscale network remodeling is coupled with microscale metabolic and regulatory gene pathways. Collectively, our findings not only validate the structural constraint on higher-order functional networks but also decipher its precise underlying mechanisms. This constraint paradigm plays a pivotal role in shaping diverse cognitive capabilities, while its pathological disruption in Alzheimers disease highlights the potential of SFCS as a biomarker for tracking neurodegenerative network impairments.

neuroscience↗

Complete elucidation and heterologous reconstruction of the biosynthetic pathway of camptothecin

Camptothecin derivatives are first-line anticancer drugs used worldwide for the treatment of diverse malignant tumors. However, the biosynthetic pathway of camptothecin has remained elusive for five decades. Here, we fully map its entire biosynthetic route. We discovered five key missing enzymes (OpCAR, OpSDR11, OpCS, OpGH1, and OpSTR) via the combination of MALDI mass spectrometry imaging, single-cell RNA sequencing and co-expression analysis. Meanwhile, we demonstrated a free flavin mononucleotide triggered the non-enzymatic 6-5-6 to 6-6-5 fused-ring skeleton rearrangement, filling the last gap in camptothecin biosynthesis. Finally, we validated this identified pathway and achieved the de novo biosynthesis of camptothecin in Saccharomyces cerevisiae. These discoveries uncover the long-standing mystery underlying camptothecin and pave the way for manufacturing camptothecin and its derivatives through synthetic biology approaches.

synthetic biology↗

Incorporation of single-neuron projectome-based connectivity motifs enhances the cortex-specific performance of artificial neural networks

The organizational principles of natural neural networks could inspire the new architecture design of artificial neural networks (ANNs). Analysis of single-neuron connectomes of mouse brains revealed distinct profiles of three-node connectivity motifs in various cortical areas and hippocampal formation. A connectome-informed neural network algorithm ("CINA") was developed to incorporate natural connectivity motifs into ANN algorithms represented by recurrent neural network (RNN) and transformer-based large language model (LLM). We found that incorporation of the average profile of cortical motifs improved the RNNs performance in noise-resistant categorization and motor learning benchmark tasks, as compared with RNNs with random connectivity. Notably, incorporating cortex-specific motifs further elevated the RNNs performance in tasks related to the cortical function, and this effect was enhanced by artificially increasing the bias in the motif profile. Similar experimental results were verified on an LLM using Motif-Transformer for natural language question answering and brain-signal decoding tasks. Graph-theoretic analyses showed that incorporating natural motifs drove the emergence of modular and small-world properties in ANNs. Together, we demonstrated not only connectome-inspired optimization of ANN architecture but also functional significance of specific motif profiles in various cortices.

neuroscience↗

DigiMus: a connectome-informed spiking framework for multi-region mouse neural-behavior modeling

Computational models are increasingly used to relate mouse brain structure, neural activity and behavior, but most models still learn from task data with limited constraints from biological circuit organization. Here we present DigiMus, a connectome-informed spiking framework for multi-region-capable mouse neural-behavior modeling. DigiMus combines leaky integrate-and-fire spiking dynamics with brain-region-specific motif regularization in a trainable sequence-modeling architecture, allowing directed three-node circuit motifs derived from 38,481 reconstructed neuronal morphologies across approximately 50 brain regions to guide recurrent coupling during learning. We evaluate DigiMus on 18 rule-based cognitive tasks spanning sensorimotor mapping and perceptual decision-making, and on three mouse neural decoding datasets involving auditory discrimination, fixed-interval licking and visual decoding. Across synthetic tasks, DigiMus showed stable performance relative to TCN, LSTM and Transformer baselines, with stronger advantages in more complex decision-making settings. In real neural datasets, single-region instantiations of DigiMus produced small, consistent and dataset-dependent improvements over a structure-free sequence baseline, while retaining motif-prior signatures in trained connectivity. Internal state analyses further linked task-dependent state dynamics to behavioral error patterns. These results suggest that connectome-derived structural priors can shape neural sequence models, and establish DigiMus as a modular, connectome-informed workflow for mouse neural-behavior modeling and hypothesis generation, rather than a complete digital reconstruction.

neuroscience↗

Sequence-encoded H2A.Z nucleosome dynamics control DNA unwrapping and SUV420H1 recognition

H2A.Z and canonical H2A adopt nearly identical nucleosomal folds, yet their distinct chromatin functions are not captured by static structural analysis. Using fast magic-angle spinning 1H-detected solid-state NMR, we show that H2A.Z possesses enhanced backbone flexibility in the L1 loop and the 2-L2 region (M2) relative to H2A. Chimeric segment-swapping demonstrates that these dynamic signatures are locally sequence-encoded and functionally transplantable. The inherent mobility of the M2 region promotes nucleosomal DNA-end unwrapping and persists when DNA ends are stabilized by linker histone H1 or opened by SUV420H1, indicating that this mobility is intrinsic rather than a passive consequence of DNA detachment. Chemical shift perturbation mapping and catalytic assays further show that SUV420H1 reads this H2A.Z-specific conformational landscape: the M2 region, together with the H2A.Z DS motif, supports variant-selective methyltransferase activity. These findings establish an axis of sequence-dynamics-accessibility-recognition along which local backbone fluctuations serve as physical determinants of epigenetic enzyme specificity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/731474v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@a50ceforg.highwire.dtl.DTLVardef@1f43af0org.highwire.dtl.DTLVardef@14969b8org.highwire.dtl.DTLVardef@bbbe0d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Differences in microbial community structure and soil nutrients between healthy and diseased soils of Zingiber officinale

To investigate the differences in soil nutrients and microbial community structure in the rhizosphere between healthy and diseased Zingiber officinale plants, soil samples were collected from healthy root-zone soil (ZSH), healthy rhizosphere soil (RSH), diseased root-zone soil (ZSD), and diseased rhizosphere soil (RSD). Diseased soils had significantly higher pH values, whereas RSH showed the strongest acidity. Moreover, pH, AN, and AK contents in diseased soils were significantly higher than those in healthy soils, while SOM and AP were significantly lower. The -diversity of microbial communities in diseased soils was significantly reduced, and the community structure was distinctly differentiated from that of healthy soils. In diseased soils, the abundance of potential pathogenic taxa such as Ralstonia solanacearum increased significantly, while beneficial genera such as Bradyrhizobium decreased. Redundancy analysis and correlation analysis indicated that soil pH, AN, SOM, and AP were the major environmental factors driving changes in microbial community structure. The occurrence of soil-borne diseases in Zingiber officinale is closely associated with soil nutrient imbalance and disruption of microbial community structure. The study identified candidate microbial taxa (e.g., beneficial Sphingomonas, Streptomyces) and key soil properties (pH, available nitrogen) that differentiate healthy from diseased ginger soils. Together, these findings provide a theoretical basis for improving diseased soils through microecological regulation strategies, and also serve as a foundation for generating testable hypotheses in future hypothesis-driven research on ginger soil-borne disease suppression.

microbiology↗

Circadian misalignment underlies immune escape in breast cancer

Circadian regulation shapes tissue physiology, yet how it organizes cellular and molecular dynamics within the tumor microenvironment (TME) and influences tumor immunity remains unclear. Using temporal single-nucleus multiomic profiling of mouse breast tumors, we uncovered extensive circadian programs that are both cell-type-specific and shared across the TME, governing proliferation and immune responses. Notably, cancer epithelial cells exhibited global acrophase misalignment relative to immune populations. This intercellular desynchrony manifests as temporal decoupling between tumor proliferation and immune activation, discordant antigen presentation and T cell recognition with intrinsic activation-exhaustion overlap in T cells, and asynchronous PD-1/PD-L1 oscillations that sustain checkpoint-mediated suppression. Similar patterns were observed in human triple-negative breast cancer (TNBC). Together, these findings establish intercellular circadian misalignment as a mechanism of tumor immune evasion and position the circadian architecture of the tumor-immune ecosystem as a previously underappreciated determinant of tumor development and therapeutic response. HIGHLIGHTSO_LISingle-cell multiomics maps circadian regulation of tumor-immune programs. C_LIO_LICircadian regulation in cancer epithelial cells is misaligned with immune cell populations. C_LIO_LITumor-immune temporal misalignment undermines antitumor immunity. C_LIO_LICircadian misalignment in human TNBC suggests relevance for immunotherapy timing. C_LI

cancer biology↗

Sex differences in vaccine-induced neuraminidase cross-recognition and protection against H5N1 in mice

H5N1 vaccines have been poorly immunogenic in humans, creating a challenge for vaccine development. Seasonal influenza vaccines offer some cross-protection against H5N1, but there has been no consideration of whether protection differs between the sexes. We investigated sex differences in antibody responses following receipt of either beta-propiolactone inactivated whole virus H1N1 or H5N1 (LAIV backbone) vaccines in C57BL/6 mice. Using systems serology assays, vaccination induced strong homologous and heterologous antibody responses, with females generating greater IgG titers than males against whole virus H1N1 and H5N1, which was primarily mediated by greater IgG responses to neuraminidase (NA) than hemagglutinin (HA) protein. Cross-reactive H5N1 IgG titers were greater among H1N1-vaccinated females, and primarily mediated by greater N1-specific IgG titers. IgG2b and IgG2c were the primary antibody isotypes generated in response to these vaccines, with females having greater IgG2b titers and enhanced binding to Fc{gamma}RIV for avian and human NA than males following either homologous or heterologous vaccination. Antibody-dependent complement deposition was measured as an FcR-mediated non-neutralizing response against HA and NA and was more robust among H1N1 and H5N1 vaccinated females than their male counterparts in response to homologous HA only. Vaccinated females tended to have greater neutralizing antibody titers than males against the homologous vaccine strain, with limited cross-neutralizing antibodies detected in either sexes. Neuraminidase inhibition titers were greater in vaccinated females than males against the heterologous virus following H1N1 vaccination and against both the vaccine and heterologous viruses following H5N1 vaccination. When H1N1 and H5N1 vaccinated mice were challenged with a lethal dose of A/Texas/37/2024 H5N1, all H5N1 vaccinated mice were protected, regardless of sex. Among H1N1 vaccinated mice, while both sexes were protected against disease, H1N1 vaccinated females restricted virus to the upper respiratory tract and had lower pulmonary virus titers than males at 3 days post challenge. These findings highlight that sex differences in vaccine-induced NA-specific antibody responses are associated with differential respiratory dissemination of H5N1 and that sex should be considered in studies of vaccine-induced cross-reactive influenza immunity.

immunology↗

A Cross-tissue Temporal Multi-omics Atlas Reveals the Molecular Architecture of Pressure Injury

Pressure injury induces progressive necrosis of skin and deep muscle, yet how mechanical loading reshapes molecular programs across tissues and time remains poorly defined. To address this gap, we established a rat pressure-injury model and performed longitudinal integrated profiling of skin and deep muscle across four stages, combining transcriptomics, proteomics and untargeted metabolomics with histological assessment. This multi-layered atlas revealed a staged injury program dominated by early transcriptional activation of innate immunity and complement-coagulation crosstalk, accompanied by neutrophil-associated responses and engagement of upstream regulatory networks. As injury advanced, a second axis of remodeling emerged, characterized by sustained suppression of mitochondrial energy metabolism and oxidative phosphorylation, particularly in muscle, together with extracellular matrix and adhesion rewiring. In parallel, skin preferentially activated barrier-repair and protein-homeostasis programs, including keratinization and autophagy-linked processes, indicating tissue-specific adaptation to the same mechanical insult. Temporal clustering and pathway-network analysis further showed that immune activation and metabolic collapse are not independent events but are dynamically coupled across stages, with muscle exhibiting broader molecular reprogramming and a stronger shift toward irreversible structural failure. Together, these data define a cross-tissue, stage-resolved molecular framework for pressure injury progression and identify pathway-level windows that may inform tissue-targeted and stage-specific intervention strategies.

systems biology↗

miR-6818-5p Drives Ovarian Granulosa Cell Dysfunction in PCOS via Targeting HSD17B2 and Modulating PI3K/Caspase-9 Axis

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovaries, with granulosa cell dysfunction being a key pathological feature. This study aimed to investigate the role of microRNA-6818-5p in PCOS pathogenesis. Quantitative PCR revealed a significant upregulation of circulating miR-6818-5p in PCOS patients compared to healthy controls. In vitro, functional assays in the human granulosa cell line KGN demonstrated that miR-6818-5p overexpression markedly inhibited cell proliferation (assessed by CCK-8 assay) and promoted apoptosis (measured by Annexin V/PI flow cytometry). Mechanistically, dual-luciferase reporter assay and Western blotting identified HSD17B2 as a direct target of miR-6818-5p, with miR-6818-5p mimics significantly suppressing HSD17B2 protein expression. In conclusion, our findings reveal that elevated miR-6818-5p in PCOS may contribute to follicular development dysfunction by targeting HSD17B2 to disrupt granulosa cell proliferation and apoptosis balance, offering novel insights into PCOS pathology and highlighting miR-6818-5p as a potential diagnostic biomarker and therapeutic target.

molecular biology↗