Biology subjects

Han, Z.

Publications and source records attributed to Han, Z..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Structural connectome architecture and biological vulnerability shape cortical atrophy in cocaine use disorder

Cocaine use disorder (CUD) is prevalent and characterized by widespread gray matter atrophy across the cerebral cortex. However, it remains unclear whether and how connectome-based circuits and biological features shape these structural abnormalities. Here, we show that CUD-associated regional atrophy is constrained by the white matter (WM) structural connectome. Along these WM pathways, regions that share similar haemodynamic activity and molecular profiles are more likely to exhibit analogous atrophy patterns. By integrating the structural connectome with these multiple connectivity blueprints, we subsequently identify CUD epicenters and reveal that the prefrontal and visual cortices serve as core systems. Furthermore, we link these epicenters to cortical gene expression patterns and delineate CUD-related transcriptomic enrichment in biological processes, including inter-neuronal communication, synaptic function and neural homeostasis. Finally, we demonstrate that the spatial distribution of these epicenters correlates with cocaine craving-response maps derived from repeated transcranial magnetic stimulation and can track individual variations in clinical behavioural representations, suggesting their potential as key targets for therapeutic intervention. Together, our findings establish a structurally constrained framework for the spread of pathology underlying cortical atrophy in CUD, where initial perturbations propagate via structural connectome pathways to vulnerable regions shaped by neural activity and molecular landscapes.

neuroscience↗

bioRxiv2025

Group size and social interactions' strength determine collective response to perturbation in a model of burst-and-coast swimming fish

Collective responses to localized perturbations are essential for the adaptability of animal groups. Using a biologically grounded computational model of burst-and-coast swimming in Hemigrammus rhodostomus, we investigate how group size and the strength of social interactions shape collective dynamics under perturbation. The model integrates experimentally derived attraction and alignment rules, behavioral heterogeneity, and boundary effects within a circular tank. We identify four collective states (schooling, milling, turning, and swarming) and characterize a critical regime in which groups exhibit multistable dynamics. At this critical point, small subsets of perturbing individuals, defined by altered social interaction strengths, can induce sharp transitions to new collective states. In particular, such transitions occur in large groups (N = 100) but not in smaller ones (N = 25 or 50), highlighting a size-dependent sensitivity to disturbance. We show that both the nature of the perturbing individuals and the initial state of the group modulate the systems responsiveness. Our findings suggest that large groups may exploit criticality to remain both robust, flexible, and that individual variability can serve as a catalyst for adaptive reconfiguration. This work provides new insights into how the internal group structure and perturbation design influence collective behavior in animal groups.

animal behavior and cognition↗

bioRxiv2025

DCX Enhances Glioblastoma Metabolism Through Synergistic Regulation of Glutamine Synthesis and Metabolism-Related Genes for Cellular Homeostasis

Gliomas are the most common primary intracranial tumors, comprising 81% of malignant brain tumors, and currently lack effective therapies. Recent advances in molecular biology have shown that cancer cells exploit microtubule-associated proteins (MAPs) under stress to activate various signaling pathways. This study investigates the role of Doublecortin (DCX) in glioma metabolism and its impact on tumor proliferation. In this study, CRISPR-engineered glioma models with DCX overexpression or knockdown were analyzed using integrated genomic, transcriptomic, and metabolomic approaches. Metabolic activity was assessed via RNA sequencing, Seahorse assays, and targeted mass spectrometry. Pharmacological inhibition of key pathways validated functional dependencies. We demonstrate that gliomas enriched with DCX exhibit elevated glycolytic activity while also relying on cellular respiration and oxidative phosphorylation (OXPHOS) for energy to support the abnormal proliferation of glioma cells. Upon integrative analysis of enriched genes and proteins, we observed genetic and metabolome-level signatures associated with differences in central carbon and energy metabolism in CRISPR-modified glioma cells expressing high DCX. Whole-genome transcriptome analysis revealed enriched metabolic entities promoting hydrolysis of glutamine and glutaminolysis in glioma cells and inhibition of selected differentially enriched genes with small molecule inhibitors abrogated metabolic enrichment and resulted in reduced energy levels and protein translation required for aberrant growth. Finally, we establish that DCX stimulates glutaminolysis to regulate homeostasis for energy supplements in glioma cells. Targeting DCX-mediated metabolic pathways may provide a novel therapeutic approach for glioblastoma, highlighting the potential for innovative treatments in this challenging disease.

cancer biology↗

bioRxiv2025

Improved Anisotropic Network Models for Membrane Protein Dynamics and Mechanosensitive Ion Channels

Mechanosensitive (MS) ion channels are crucial for translating mechanical stimuli into cellular responses; however, their dynamic properties pose significant challenges for experimental investigations. This study introduces two enhanced Anisotropic Network Models (ANMs) that incorporate Membrane Contact Probability (MCP) to more effectively capture the influence of the cell membrane on protein dynamics. MCP-ANM and MCP-mANM (multiscale ANM) outperform traditional ANM models that do not explicitly consider membranes when predicting the flexibility of various types of membrane proteins. Furthermore, by integrating MCP-mANM with Perturbation Response Scanning (PRS), we are able to effciently simulate the conformational changes of MS proteins subjected to different mechanical forces. This methodology allows for the examination of various gating mechanisms, including force-from-lipids and force-from-tether, across multiple MS ion channels such as NOMPC, MscS, and PIEZO. The calculated mechanosensitivity of the MS channels aligns well with the experimental findings. These results demonstrate the effectiveness of MCP-incorporated ANM in linking mechanical stimuli to protein dynamics, providing a reliable and effcient framework for understanding the mechanotransduction and gating mechanisms of MS ion channels.

biophysics↗

bioRxiv2025

Inhibitors of membrane associated serine proteases block replication of coronavirus SARS-CoV-2 and influenza virus H1N1

TMPRSS2 is a membrane associated serine protease which is important in the viral pathogenesis of coronaviruses and influenza viruses. We developed mechanism-based covalent -ketobenzothiazole (kbt) inhibitors using substrate specificity PS-SCL screening of TMPRSS2 as a rational guide for inhibitor design. Three distinct focused libraries of tetrapeptide kbts were synthesized and evaluated for their inhibition of TMPRSS2, matriptase and other serine proteases. We also investigated different capping groups for the previously reported tripeptide inhibitor Ac-QFR-kbt (MM3144) to increase its selectivity over the blood coagulation protease factor Xa. The most potent compounds were tested for their ability to inhibit viral replication of SARS-CoV-2 coronavirus and the H1N1 influenza virus. The most active compounds were profiled for their pharmacokinetics (PK) in mice. Several promising new compounds were identified with improved potency, selectivity, and drug-like properties including Bz-QFR-kbt (CA1043) and Cbz-QFR-kbt (ZFH9141) with an IC50 of 150 nM and 60 nM for H1N1, respectively.

microbiology↗

bioRxiv2025

Topoisomerase IIα orchestrates secretion of IL-6 and IL-8 with human papillomavirus replication

High-risk human papillomavirus (HPV) replication requires deregulation of host DNA damage response (DDR) and inflammatory pathways. DNA topoisomerase 2{beta} (Top2{beta}) was previously shown to promote HPV replication, while the function of its paralog Top2 in the viral life cycle remains unknown. Elevated levels of Top2 are consistently observed in cervical intraepithelial lesions and the related carcinomas, as well as in HPV-positive cell lines. Silencing Top2 with shRNA severely suppresses HPV genome maintenance and amplification, but in a DDR-independent manner. Instead, Top2 facilitates secretion of interleukin (IL)-6 and IL-8, which are necessary for HPV replication. Mechanistically, this manipulation is regulated by toll-like receptor 4 (TLR4). Top2 binds to the TLR4 promoter to transcriptionally induce TLR4 expression. Blockade of TLR4 signaling by the specific inhibitor TAK-242 significantly reduces the secreted IL-6/IL-8 levels and HPV replication. Overall, our results reveal a novel role of Top2 to shape the inflammatory microenvironment that benefits HPV replication, making it a promising therapeutic target for HPV-associated diseases. IMPORTANCEHuman papillomaviruses (HPVs) are oncogenic pathogens responsible for many HPV-related diseases such as cervical cancer. HPV replication depends on the subversion of host cellular machineries, particularly pathways governing DNA damage response (DDR) and inflammation. However, the roles of enzymes that directly introduce DNA nicks or mediate strand rejoining remain poorly characterized. Here we highlight a novel role of DNA topoisomerase 2 (Top2) in promoting HPV genome maintenance and amplification but in a DDR-independent manner. Unlike its previously studied paralog Top2{beta}, Top2 supports HPV replication by driving the secretion of inflammatory molecules interleukin (IL)-6 and IL-8, which are critical for the viral genome persistence and copy number expansion. To our knowledge, this is the first evidence that a DDR-associated protein manipulates cytokine secretion, rather than expression, to support HPV replication. Furthermore, blocking toll-like receptor 4 (TLR4) activities significantly reduced Top2-dependent IL-6/IL-8 secretion and impaired HPV replication. These findings establish Top2 as a crucial player in HPV pathogenesis, with a therapeutic potential for treating HPV-associated malignancies.

microbiology↗

bioRxiv2025

Magnetically Labeled iPSC-Derived Extracellular Vesicles Enable MRI/MPI-Guided Regenerative Therapy for Myocardial Infarction

Stem cell-derived extracellular vesicles (EVs) offer a promising cell-free approach for cardiovascular regenerative medicine. In this study, we developed magnetically labeled induced pluripotent stem cell-derived EVs (magneto-iPSC-EVs) encapsulated with superparamagnetic iron oxide (SPIO) nanoparticles for image-guided regenerative treatment of myocardial infarction, in which EVs that can be detected by both magnetic resonance imaging (MRI) and magnetic particle imaging (MPI). iPSC-EVs were isolated, characterized per MISEV2023 guidelines, and loaded with SuperSPIO20 nanoparticles using optimized electroporation conditions (300 V, 2 x 10 ms pulses), achieving a high loading efficiency of 1.77 ng Fe/106 EVs. In vitro results show that magneto-iPSC-EVs can be sensitively detected by MPI and MRI, with a detectability of approximately 107 EVs. In a mouse myocardial ischemia-reperfusion model, intramyocardially injected magneto-iPSC-EVs (2 x 109) were imaged non-invasively by in vivo MPI for 7 days and ex vivo MRI, with the presence of magneto-iPSC-EVs confirmed by Prussian blue staining. Therapeutically, both native and magneto-iPSC-EVs significantly improved cardiac function, with a 37.3% increase in left ventricular ejection fraction and 61.0% reduction in scar size. This study highlights the potential of magneto-iPSC-EVs as a cell-free approach for cardiovascular regenerative medicine, offering both non-invasive imaging capabilities and therapeutic benefits for myocardial repair.

bioengineering↗

bioRxiv2025

Experimental evidence of stress-induced critical state in schooling fish

How do animal groups dynamically adjust their collective behavior in response to environmental changes is an open and challenging question. Here, we investigate the mechanisms that allow fish schools to tune their collective state under stress, testing the hypothesis that these systems operate near criticality, a state maximizing sensitivity, responsiveness, and adaptability. We combine experiments and data-driven computational modeling to study how group size and stress influence the collective behavior of rummy-nose tetras (Hemigrammus rhodostomus). We quantify the collective state of fish schools using polarization, milling, and cohesion metrics and use a burst-and-coast model to infer the social interaction parameters that drive these behaviors. Our results indicate that group size modulates stress levels, with smaller groups experiencing higher baseline stress, likely due to a reduced social buffering effect. Under stress, fish adjust the strength of their social interactions in a way that leads the group into a critical state, thus enhancing its sensitivity to perturbations and facilitating rapid adaptation. However, large groups require an external stressor to enter the critical regime, whereas small groups are already near this state. Unlike previous studies suggesting that fish adjust their interaction network structure under risk, our results suggest that the intensity of social interactions, rather than network structure, governs collective state transitions. This simpler mechanism reduces cognitive demands while enabling dynamic adaptation. By revealing how stress and group size drive self-organization toward criticality, our study provides fundamental insights into the adaptability of collective biological systems and the emergent properties in animal groups.

animal behavior and cognition↗

bioRxiv2025

Emergent modularity in large language models: Insights from aphasia simulations

Recent large language models (LLMs) have demonstrated remarkable proficiency in complex linguistic tasks and have been shown to share certain computational principles with human language processing. However, whether LLMs internal components perform distinct functions, like semantic and syntactic processing in human language systems, remains unclear. Here, we systematically disrupted components of LLMs to simulate the behavioral profiles of aphasia--a disorder characterized by specific language deficits resulting from brain injury. Our findings showed that lesioning specific components of LLMs could replicate behaviors characteristic of different aphasia subtypes. Notably, while semantic deficits as those observed in Wernickes and Conduction aphasia, were relatively straightforward to simulate, reproducing syntactic and lexical impairments, as seen in Brocas and Anomic aphasia, proved more challenging. Together, these results highlight both parallels and discrepancies between emergent modularity in LLMs and the human language system, providing new insights into how information is represented and processed in artificial and biological intelligence.

neuroscience↗

bioRxiv2024

Exploring the druggability of the UEV domain of human TSG101 in search for broad-spectrum antivirals

The ubiquitin E2 variant domain of TSG101 (TSG101-UEV) plays a pivotal role in protein sorting and virus budding by recognizing PTAP motifs within ubiquitinated proteins. Disruption of TSG101-UEV/PTAP interactions has emerged as a promising strategy for the development of host-oriented broad-spectrum antivirals with low susceptibility to resistance. TSG101 is a challenging target characterized by an extended and flat binding interface, low affinity for PTAP ligands, and complex binding energetics. Here, we assess the druggability of the TSG101-UEV/PTAP binding interface by searching for drug-like inhibitors and evaluating their ability to block PTAP recognition, impair budding, and inhibit viral proliferation. A discovery workflow was established combining in vitro miniaturized HTS assays and a set of cell-based activity assays including high-content bimolecular complementation, virus-like particle release measurement, and antiviral testing in live virus infection. This approach has allowed us to identify a set of chemically diverse molecules that block TSG101-UEV/PTAP binding with IC50s in the low M range, and able to disrupt the interaction between full-length TSG101 and viral proteins in human cells and inhibit viral replication. State-of-the-art molecular docking studies reveal that the active compounds exploit binding hotspots at the PTAP binding site, unlocking the full binding potential of the TSG101-UEV binding pockets. These inhibitors represent promising hits for the development of novel broad-spectrum antivirals through targeted optimization and are also valuable tools for investigating the involvement of ESCRT in the proliferation of different virus families and study the secondary effects induced by the disruption of ESCRT/virus interactions. ImportanceMany viruses rely on the interaction between TSG101 and viral proteins containing PTAP motifs for their proliferation. Here we show that these interactions can be efficiently blocked by drug-like compounds that impair budding and replication of viruses from different families. We have also provided valuable insights into the determinants of high affinity for these small molecule inhibitors that open new avenues for developing the identified candidates into broad-spectrum antivirals with low susceptibility to resistance.

molecular biology↗

bioRxiv2024

Older is Order: Entropy reduction in cortical spontaneous activity marks healthy aging

Entropy trajectories remain unclear for the aging process of human brain system due to the lacking of longitudinal neuroimaging resource. We used open data from an accelerated longitudinal cohort (PREVENT-AD) that included 24 healthy aging participants followed by 4 years with 5 visits per participant to establish cortical entropy aging curves and distinguish with the effects of age and cohort. This reveals that global cortical entropy decreased with aging, while a significant cohort effect was detectable that people who were born earlier showed higher cortical entropy. Such entropy reductions were also evident for large-scale cortical networks, although with different rates of reduction for different networks. Specifically, the primary and intermediate networks reduce their entropy faster than the higher-order association networks. We conclude two specific characteristics of the entropy of the human cortex with aging: the shift of the complexity hierarchy and the diversity of complexity strengthen.

neuroscience↗

bioRxiv2024

Physical vitrification and nanowarming at human organ scale to enable cryopreservation

Organ banking by vitrification could revolutionize transplant medicine. However, vitrification and rewarming have never been demonstrated at the human organ scale. Using modeling and experimentation, we tested the ability to vitrify and rewarm 0.5 - 3 L volumes of three common cryoprotective agent (CPA) solutions: M22, VS55, and 40% EG+0.6M Sucrose. We first demonstrated our ability to avoid ice formation by convectively cooling faster than the critical cooling rates of these CPAs while also maintaining adequate uniformity to avoid cracking. Vitrification success was then verified by visual, thermometry, and x-ray CT inspection. M22 and EG+sucrose were successfully vitrified in 0.5 L bags, but only M22 was vitrified at 3 L. VS55 did not vitrify at any tested volumes. As additional proof of principle, we successfully vitrified a porcine liver ([~]1L) after perfusion loading with 40% EG+0.6M Sucrose. Uniform volumetric rewarming was then achieved in up to 2 L volumes (M22 with [~]5 mgFe/mL iron-oxide nanoparticles) using nanowarming, reaching a rate of [~]88 {degrees}C/min with a newly developed 120 kW radiofrequency (RF) coil operating at 35kA/m and 360kHz. This work demonstrates that human organ scale vitrification and rewarming is physically achievable, thereby contributing to technology that enables human organ banking.

bioengineering↗

bioRxiv2024

PAF1C allosterically activates CDK12/13 kinase during RNAPII transcript elongation

The mechanisms ensuring temporally correct, site-specific phosphorylation of the RNA polymerase II C-terminal domain (CTD) by cyclin-dependent kinases (CDKs) during the transcription cycle remain poorly understood. Here, we present results from in vitro reconstitution of CTD phosphorylation combined with in vivo evidence to show that human CDK12 and CDK9 both co-phosphorylate CTD Serine 5 and Serine 2. However, only phosphorylation by CDK12 is stimulated by association with the elongation-specific factor PAF1C, in which the CDC73 subunit contains a short, conserved motif capable of association with and activation of CDK12/Cyclin K. This motif is necessary for cell proliferation and crucial for CTD phosphorylation and transcript elongation. Together, these data provide new insight into basic mechanisms ensuring CDK specificity in the RNAPII transcription cycle. One-Sentence SummaryPAF1C facilitates RNAPII phosphorylation in gene bodies through direct contacts with the active site of CDK12/13.

molecular biology↗

bioRxiv2024

Genomic and evolutionary evidence for drought adaptation of grass allopolyploid Brachypodium hybridum

Climate change increases the frequency and severity of drought worldwide, threatening the environmental resilience of cultivated grasses. However, the genetic diversity in many wild grasses could contribute to the development of climate-adapted varieties. Here, we elucidated the impact of polyploidy on drought response using allotetraploid Brachypodium hybridum (Bh) and its progenitor diploid species B. stacei (Bs). Our findings suggest that progenitor species genomic legacies resulting from hybridization and whole-genome duplications conferred greater ecological adaptive advantages to Bh over Bs. Genes related to stomatal regulation and immune response from S-subgenomes were under positive selection during speciation, underscoring their evolutionary importance in adapting to environmental stresses. Biased expression in polyploid subgenomes [B. stacei-type (Bhs) and B. distachyon-type (Bhd)] significantly influenced differential gene expression, with the dominant subgenome exhibiting more differential expression. B. hybridum adapted a drought escape strategy characterized by higher photosynthetic capacity and lower WUEi than Bs, driven by a highly correlated co-expression network involving genes in the circadian rhythm pathway. In summary, our study showed the influence of polyploidy on ecological and environmental adaptation and resilience in model Brachypodium grasses. These insights hold promise for informing the breeding of climate-resilient cereal crops and pasture grasses.

evolutionary biology↗

bioRxiv2024

Building a literature knowledge base towards transparent biomedical AI

As artificial intelligence (AI) continues to advance and scale up in biomedical research, concerns about AIs trustworthiness and transparency have grown. There is a critical need to systematically bring accurate and relevant biomedical knowledge into AI applications for transparency and provenance. Knowledge graphs have emerged as a powerful tool that integrates heterogeneous knowledge by explicitly describing biomedical knowledge as entities and relationships between entities. However, PubMed, the largest and most comprehensive repository of biomedical knowledge, exists primarily as unstructured text and is under utilized for advanced machine learning tasks. To address the challenge, we developed LiteralGraph, a computational framework to extract biomedical terms and relationships from PubMed literature into a unified knowledge graph. Using this framework, we established the Genomic Literature Knowledge Base (GLKB), which consolidates 14,634,427 biomedical relationships between 3,276,336 biomedical terms from over 33 million PubMed abstracts and nine well-established biomedical repositories. The database is coupled with RESTful APIs and a user-friendly web interface that makes it accessible to researchers for various usages. We demonstrated the broad utility of GLKB towards transparent AI in three distinct application scenarios. In the LLM grounding scenario, we developed a Retrieval Augmented Generation (RAG) agent to reduce LLM hallucination in biomedical question answering. In the hypothesis generation scenario, we elucidated the potential functions of RFX6 in type 2 diabetes (T2D) using the vast evidence from PubMed articles. In the machine learning scenario, we utilized GLKB to provide semantic knowledge in predictive tasks and scientific fact-checking.

bioinformatics↗

bioRxiv2024

Discovery of novel 1,4-dicarbonylthiosemicarbazides as DNA gyrase inhibitors for the treatment of MRSA infection

Antibiotic resistance has become a serious threat to public health, thus novel antibiotics are urgently needed to combat drug-resistant bacteria including MRSA (methicillin-resistant S. aureus). The 1,4-dicarbonylthiosemicarbazide is an interesting chemotype that could exhibit antibacterial activity. However, the currently available compounds are not as potent as clinical antibiotics. Herein, we adopted the computer-aided drug design strategy, substructure search, to retrieve antibacterial 1,4-dicarbonylthiosemicarbazide derivatives, and identified compound B5 (Specs ID: AG-690/15432331) from the Specs chemical library that exhibited moderate activity (minimum inhibitory concentration (MIC): 6.25 {micro}g/mL) against S. aureus (ATCC 29213). Based on that compound, we further designed and synthesized 45 derivatives, and evaluated their antibacterial activity. Eight derivatives were more potent than or equivalent to vancomycin (MIC: 1.56 {micro}g/mL). We compared the three most potent ones for their cytotoxicity to HepG2 and HUVEC cells and selected compound 1b as our lead compound for comprehensive biological evaluation. As a result, compound 1b exhibited a bacteriostatic mode, and was active against a panel of gram-positive bacteria strains, metabolically stable, and effective to protect the mice from MRSA infection. More importantly, we applied 2D similarity calculation and reverse docking to predict potential targets of compound 1b. Through experimental validation and molecular dynamics simulation, we were able to confirm that compound 1b inhibited S. aureus DNA gyrase (IC50: 1.81 {micro}M) and DNA supercoiling, potentially by binding to the ATPase domain, where ASP81, GLU58 and GLN91 formed key hydrogen bonds. Taken together, we have discovered a new class of DNA gyrase inhibitors represented by compound 1b for the treatment of MRSA infection, through the design, synthesis, and biological evaluation of novel 1,4-dicarbonylthiosemicarbazides. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/611349v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@549dadorg.highwire.dtl.DTLVardef@13bff64org.highwire.dtl.DTLVardef@1fc2c00org.highwire.dtl.DTLVardef@acee76_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIAn interesting 1,4-dicarbonylthiosemicarbazide derivative B5 with moderate antibacterial activity for S. aureus was discovered by substructure search. C_LIO_LIBased on B5, 45 new 1,4-dicarbonylthiosemicarbazides were designed, synthesized and biologically evaluated, which led to the discovery of a promising lead compound 1b. C_LIO_LICompound 1b exhibited good antibacterial activity for a panel of gram-positive bacteria strains, and was effective to protect mice from MRSA infection. C_LIO_LIThe 1,4-dicarbonylthiosemicarbazides represented by compound 1b were discovered as a new class of DNA gyrase inhibitors, by target prediction and experimental validation. C_LI

pharmacology and toxicology↗

bioRxiv2024

Deep Generative Optimization of mRNA Codon Sequences for Enhanced Protein Production and Therapeutic Efficacy

Messenger RNA (mRNA) therapeutics show immense promise, but their efficacy is limited by suboptimal protein expression. Here, we present RiboDecode, a deep learning framework that generates mRNA codon sequences for enhanced mRNA translation. RiboDecode introduces several advances, including direct learning from large-scale ribosome profiling data and generative exploration of a large sequence space. In silico analysis demonstrates RiboDecode s robust predictive accuracy for unseen genes and cellular environments. In vitro experiments showed substantial improvements in protein expression, significantly outperforming past methods. In addition, RiboDecode enables mRNA design with consideration of cellular context and demonstrates robust performance across different mRNA formats, including m1{Psi}-modified and circular mRNAs, an important feature for mRNA therapeutics. In vivo mouse studies showed that optimized influenza hemagglutinin mRNAs induce ten times stronger neutralizing antibody responses against influenza virus compared to the unoptimized sequence. In an optic nerve crush model, optimized nerve growth factor mRNAs achieve equivalent neuroprotection of retinal ganglion cells at one-fifth the dose of the unoptimized sequence. Collectively, RiboDecode represents a paradigm shift from rule-based to a data-driven, context-aware approach for mRNA therapeutic applications, enabling the development of more potent and dose-efficient treatments.

bioinformatics↗

bioRxiv2024

A first-in-kind MAPK13 inhibitor that can correct stem cell reprogramming and post-injury disease

The stress kinase MAPK13 (aka p38delta-MAPK) is an attractive entry point for therapeutic intervention because it regulates the structural remodeling that can develop after epithelial injury in the lung and likely other tissue sites. However, a selective, safe, and effective MAPK13 inhibitor is not yet available for experimental or clinical application. Here we identify a first-in-kind MAPK13 inhibitor using structure-based drug design combined with a screening funnel for cell safety and molecular specificity. In a mouse model of severe respiratory viral infection, treatment with this inhibitor (formulated as NuP-4A for intravenous use or Nu4-B for inhaled delivery) did not influence recovery from acute infectious illness, but still down-regulated basal-epithelial stem cell (basal-ESC) hyperplasia/metaplasia and in turn airway inflammation, mucus production, and pathophysiology biomarkers of chronic lung disease. Treatment prevented and reversed disease readouts equivalently to Mapk13 gene-knockout, and this benefit persisted after stopping treatment as a sign of disease modification. Further, NuP-4 treatment even at pM levels directly blocked basal-ESC reprogramming endpoints in organoid and cell-culture models derived from non-disease control and asthma subjects. The results thereby provide a new tool compound and drug candidate for basal-ESC reprogramming towards muco-obstructive lung diseases like asthma and any overlap with COPD and related diseases that depend on overactivity of MAPK13.

immunology↗