Biology subjects

Meng, S.

Publications and source records attributed to Meng, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Goal directed closed-loop training of network bursts in cortical cultures produces improved performance and error correction over days

Dissociated neural cultures are living systems with no evolutionary history in their current form, which makes them a testbed for asking what goals neural tissue can learn to pursue once it is removed from its evolved body. It remains unclear which features of network activity such a culture can be trained to control, and whether that training is retained from one day to the next. We built an open-source closed-loop platform, the Holistic Agential Learning platform (HAL), that detects a network burst on a high-density microelectrode array, estimates its spatial origin in real time, and applies a minimal reinforcement rule. Here, a burst that originates off the goal side triggers global random stimulation that persists until the next burst. Over days of training, rat cortical cultures (n=10) increased the fraction of bursts that initiated on the goal side. This gain accrued between sessions, with little change within a session, a consolidation-like pattern that we interpret as a statement about timescale while the mechanism remains untested. The burst origin moved toward the goal side, while the burst peak and the repertoire of propagation directions were preserved. Trained cultures also recovered from incorrect states more reliably over days, while the rate at which they entered those states was unchanged, and this recovery effect was the most robust difference from unstimulated controls (n=6). Cultures that began on either side of chance converged to a similar level of performance. Damaged cultures (n=6) with comparable burst statistics showed neither the across-day gain nor the consolidation-like pattern. Training reweighted the activity patterns each culture already had, and we saw no new ones, which we read as a simple form of niche construction in which the tissue keeps a trace of its history that biases what it does next. These results identify burst initiation and error recovery as trainable variables in a novel living system, and they support training the tissue rather than engineering the machine.

bioengineering↗

bioRxiv2026

The RNA-binding protein TRIM71 Promotes Supporting Cell Reprogramming and Hair Cell Regeneration by Activating Sall4

Hair cell (HC) loss in the auditory organ (cochlea) is irreversible and represents the leading cause of deafness in humans. The absence of HC regeneration is primarily due to the limited plasticity of cochlear supporting cells (SCs). Using a novel doxycycline-inducible TRIM71 transgenic mouse model, this study demonstrates that overexpression of the RNA-binding protein TRIM71 promotes spontaneous cochlear HC regeneration in neonatal mice. Experiments in cochlear organoids indicate that TRIM71 reprograms SCs into progenitor-like cells and that this reprogramming is further enhanced by coactivation of follistatin (FST). FST augments TRIM71-induced increases in chromatin accessibility at progenitor and HC-specific gene loci, facilitating their transcriptional activation in SCs. Notably, FST also enhances TRIM71-induced reactivation of Sall4, which, like Trim71, is highly expressed in early otic progenitors. Using cochlear organoids and explants, we show that the early otic transcription factor SALL4 is required for TRIM71-induced HC formation. By contrast, SALL4 overexpression inhibits HC formation by maintaining reprogrammed SCs in an undifferentiated, proliferative state. These findings establish TRIM71 as an activator of HC regeneration in vivo, provide mechanistic insights into TRIM71's role in SC reprogramming, and identify SALL4 as its essential effector.

cell biology↗

bioRxiv2026

Temporal stasis in three facets of biodiversity reveals mechanisms of community assembly across elevation gradients

Understanding spatial and temporal variation in community composition is central to protecting and monitoring biodiversity. Similarity in the composition of two communities decreases along spatial and temporal gradients, a relationship known as distance decay. Comparing distance-decay relationships across taxonomic, functional, and bioclimatic facets of diversity provides a means of interrogating niche-based versus neutral influences on community assembly. Furthermore, the context in which these facets yield overlapping or complementary information about global change impacts remains poorly understood. In this study, we examined spatiotemporal distance-decay relationships for taxonomic, functional, and bioclimatic facets of alpine plant diversity leveraging elevation gradients on five peaks in the White Mountains, California, USA, sampled at 3-4 time points between 2007 and 2024. Using multivariate Bayesian beta regression models, we estimated the slopes of elevation distance decay over multiple surveys and across taxonomic, functional and bioclimatic diversity to understand how spatial distance-decay relationships are changing through time and across different facets of diversity. We found strong spatial distance decay of taxonomic similarity across all peaks, with the highest elevation peak showing the strongest decay. Functional and bioclimatic similarities decayed more weakly than taxonomic similarity, suggesting environmental filtering shapes trait and niche distributions. Critically, spatial decay patterns showed no temporal signal across facets of diversity, indicating community stasis rather than biotic homogenization or differentiation. This study adds further evidence that xeric alpine plant communities are resisting climate change impacts through time.

ecology↗

bioRxiv2026

AI-Guided Multi-Objective Engineering of Glucoamylase Enables Acidification-Free Starch Saccharification

Glucoamylase is essential for industrial starch saccharification, but the limited thermostability and near-neutral pH tolerance of fungal glucoamylases necessitate cooling and acidification of liquefied starch. Here, we developed an artificial intelligence-guided strategy to simultaneously improve the thermostability, pH tolerance, and catalytic activity of glucoamylase from Penicillium oxalicum (PoGA). Two property-specific machine-learning models, CASPE-T and CASPE-A, identified substitutions associated with thermostability and pH tolerance, respectively. Experimental screening identified beneficial substitutions in 11 of 21 CASPE-T and 12 of 22 CASPE-A candidates. Folding-energy-guided recombination integrated the two traits while maintaining structural compatibility. The optimal variant, PoGA T513E/Q305N, exhibited 2.21-fold higher specific activity than the wild type, with half-life extended from 22.3 to 57.9 min at 60 degrees C and from 16.6 to 64.7 min at pH 8.0. Molecular dynamics simulations attributed these improvements to reinforcement of high-occupancy hydrogen-bonding networks, suppression of conformational fluctuations in the linker and carbohydrate-binding module, enhanced long-range dynamic coordination, and preservation of a compact catalytic architecture. At 60 degrees C and pH 6.5 without acidification, PoGA T513E/Q305N produced 219.9 g/L glucose and achieved 89.1% starch conversion, 31.4% higher than the wild type. This work provides an efficient framework for multi-objective enzyme engineering and sustainable starch biorefining.

synthetic biology↗

bioRxiv2026

Life without cytoplasm: sperm sustain protein production utilizing cytoplasmic droplets and mitochondria as translational apparatuses

Sperm present a unique paradox: heavily compacted chromatin silences transcription, and loss of cytoplasm during spermiation eliminates the conventional translational apparatus, yet sperm require [~]10 days of protein-demanding epididymal maturation to acquire motility and fertilization competence. How sperm produce the necessary proteins has remained enigmatic. Here, we show that mammalian sperm sustain protein synthesis through a biphasic translational program. In testicular sperm, a residual cytoplasmic droplet retains the full complement of translational machinery, including ribosomes and intact tRNAs, and supports nascent protein synthesis. As sperm enter the epididymis, this droplet is progressively fragmented, and protein synthesis shifts to the midpiece, where mitochondrial translation machinery becomes active. Proteomic and functional analyses indicate that both systems contribute to sperm maturation. Inhibiting cytoplasmic translation in testicular sperm or mitochondrial translation in epididymal sperm abolishes motility. These findings reveal how cytoplasm-free sperm overcome transcriptional silence to complete maturation and support male fertility. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/744062v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@e4285forg.highwire.dtl.DTLVardef@11685d7org.highwire.dtl.DTLVardef@1ad1913org.highwire.dtl.DTLVardef@1495d6a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2026

Holomycin from Yersinia ruckeri mediates fish infection at low temperature

Why microbes invest energy in producing structurally complex natural products at extremely low concentrations within hosts remains an important topic of interest in microbial ecology. This is because such compounds with potential "biomolecular activities" can reflect molecule-target interactions, thereby providing conceptual and mechanistic insights that inform the rational design of essential clinical agents. Here, we uncover the in situ ecological function of the dithiolopyrrolone antibiotic holomycin produced by the fish pathogen Yersinia ruckeri. We show that holomycins biosynthesis is strictly gated by low temperature and that trace amounts of holomycin accumulate in vivo during infection in rainbow trout. In addition, the holomycin-deficient mutant leads to markedly reduced virulence. Integrated multiomics, phenotypic analyses, and in vivo bioassay test reveal that holomycin is not a direct lethal factor but instead remodels host-associated microbiota and enhances Y. ruckeri biofilm formation. These coordinated effects promote pathogen colonization and infection progression. Our findings establish holomycin as a host-associated effector and illustrate how its existence and ecological function are mechanistically intertwined in the evolution of pathogenic bacterial chemical arsenals.

microbiology↗

bioRxiv2025

ZNF638 represses the transcription of HBV closed circular DNA involving HUSH complex-mediated histone modifications of epigenetic silencing

Hepatitis B virus (HBV) infection poses a critical threat to public health burden worldwide. As the major template of viral transcription, the covalently closed circular DNAs (cccDNAs) of HBV was known to form microchromosomes and interact with various host proteins. In the present study, ZNF638 was found to significantly reduce the transcription of HBV into pgRNAs, and subsequently reduce cccDNA formation and viral propagation. We discovered that ZNF638 was able to bind the preS and S gene regions of HBV, repressing the transcription of cccDNA upon increased modification of H3K9me3 mediated by SETDB1. This epigenetic silencing of cccDNA transcription was further demonstrated to involve the activity of HUSH, a multi-protein complex to mediate epigenetic modifications of histone into suppressed nucleosomes. In in vivo models, we evaluated the effects of ZNF638 deficiency on HBV-targeting siRNA therapy. A significant reduction of the efficacy was observed in animals with reduced ZNF638 expression. In summary, we report that ZNF638 is a potent host factor to repress the transcription of HBV DNAs and to attenuate HBV infection. The role of ZNF638 on HBV repression involves its binding to cccDNA at specific regions for recruiting HUSH complex to write H3K9me3 histone marks for epigenetic silencing. ZNF638 serves as a critical host factor to associate HBV infection and disease progression. Additionally, ZNF638 serves as a potential indicator to predict the outcome of HBV-targeting siRNA therapy.

biochemistry↗

bioRxiv2024

Graph Network-Based Analysis of Disease-Gene-Drug Associations: Zero-Shot Disease-Drug Prediction and Analysis Strategies

Existing drug repurposing methods have key limitations, primarily stemming from their reliance on known direct associations between diseases and drugs for supervised learning, as well as the need for large amounts of prior disease or drug information or feature data. In practice, many disease-drug connections remain unknown, and prior information is often complex and difficult to acquire and organize, limiting the applicability of these models. Furthermore, these models generally lack interpretability, making it difficult for experts to assess the reliability of predictions based solely on standard metrics, which raises doubts about the trustworthiness of their results. To address these challenges, we propose ZS-GNT, an innovative new workflow for zero-shot drug repurposing that leverages a novel and ingenious graph data meta-path linking scheme, which does not require any known disease-drug associations or their prior features. This approach is implemented using the Graph Neural Transformer (GNT) algorithm. The method infers disease-drug relationships indirectly through gene action, utilizing disease-gene associations and gene-drug interactions. It also generates a top drug-top gene linkage map, providing clinicians with a visual tool to assess the plausibility of suggested drugs before advancing to clinical trials. Experimental results show that, under the same linking scheme, the GNT algorithm achieved interaction link prediction accuracies of 95.86%, 99.28%, and 99.54% for three diseases, surpassing four other baseline methods. In a test involving a random selection of 100 diseases for drug discovery, among the top 5 recommended drugs from the candidates identified by ZS-GNT from a pool of 33,251 total drugs, the validation rate reached 47.05%, demonstrating the models effectiveness in drug discovery.

bioinformatics↗

bioRxiv2024

Deep Learning Unravels Potential Antibiotic-Resistance Drugs against Klebsiella Pneumoniae

BackgroundKlebsiella pneumoniae (KP) is a critical pathogen recognized by the World Health Organization due to its high mortality rates and resistance to antibiotics. Developing effective treatments for KP is essential to mitigate the growing threat of multidrug-resistant infections. This study leverages deep learning techniques to identify and validate potential drug candidates against KP, accelerating the drug discovery process and reducing associated risks. ResultsA comprehensive dataset was constructed, comprising 3,475 drugs selected from the DrugBank database, filtered for their potential efficacy and safety. Using convolutional neural networks (CNNs) for drug-drug interaction analysis, a prediction accuracy of 72% was achieved. Evolutionary Scale Modeling (ESM) was employed to calculate molecular similarities between drugs and KP strains, identifying five promising candidates with structural similarities exceeding 85% to known KP targets. A drug repurposing knowledge graph (DRKG) further validated these findings, with the PairRE model outperforming other approaches in ranking potential drug candidates. ConclusionsThis study presents a scalable and efficient framework for identifying and validating drug candidates to combat antibiotic-resistant KP. By integrating deep learning models, molecular similarity analysis, and knowledge graph techniques, this approach shortens the drug discovery timeline from years to months. The identified candidates hold significant promise for preclinical and clinical testing, offering a pathway to effective therapies against KP and other multidrug-resistant pathogens.

bioinformatics↗

bioRxiv2024

Deep Learning with Evolutionary Scale Modeling to discover Antibiotic-Resistance Drug against Klebsiella Pneumoniae

The development of effective antibiotics is crucial in combating antibiotic-resistant pathogens such as Klebsiella pneumoniae (KP). This study utilizes deep learning, specifically Evolutionary Scale Modeling (ESM), to identify potential drug candidates. By analyzing molecular similarities between known drugs and KP strains, we aim to accelerate the discovery of new treatments and reduce the risks associated with clinical trials. This approach may shed new lights in the field of drug repositioning.

bioinformatics↗

bioRxiv2024

Differentiation Protocol-Dependent Variability in hiPSC-Derived Endothelial Progenitor Functionality

PurposeWith multiple groups generating methods for differentiating induced pluripotent stem cells (hiPSCs) into endothelial cells/endothelial progenitors (ECs/EPs), there is a need to better understand the specific endothelial subtypes that different differentiation protocols produce. This is especially important for accurate tissue modeling as researchers continue to incorporate the endothelium into engineered tissues. MethodsWe illustrated the heterogeneity of cells produced from different differentiation protocols by focusing on two selected protocols, one driving differentiation exclusively using small molecules (SM Protocol) and one driving differentiation primarily using growth factors (GF Protocol). We characterized the cells through a combination of vasculogenic computational analysis following encapsulation in 3D hydrogels, RNA sequencing, and measurement of soluble factor release. ResultsVasculogenic computational analysis indicates that cells from the GF protocol formed more dense and interconnected vasculature compared to cells from the SM protocol. Likewise, RNA-seq analysis showed GF-derived cell enrichment in pathways involved in cell migration and angiogenesis. In addition, GF-derived cells favor differentiation to arterial endothelial cells as well as predisposition to undergoing a partial endothelial-to-mesenchymal transition, whereas SM-derived cells resemble immature progenitors based on higher proliferation rates as well as ECM remodeling. These trends also persisted following extended 3D culture. ConclusionsThe results demonstrate that despite using the same starting hiPSC population and isolating EPs using the same surface marker, the two differentiation protocols yield highly distinct cell populations. This work highlights the importance of understanding the specific endothelial subtypes produced by different differentiation protocols for the creation of more accurate tissue models. Lay SummaryAlthough multiple groups have created protocols for differentiating human induced pluripotent stem cells (hiPSCs) to endothelial progenitors (EPs), it is not clear if different differentiation protocols generate different endothelial subtypes, matching the variance seen in vivo To that end, we performed an in-depth characterization of two selected hiPSC-EP differentiation protocols, primarily focusing on cells cultured in 3D hydrogels, to better understand the specific endothelial subtypes produced. We found significant differences in both cell maturity and cell phenotype that persisted even after extended culture. Future WorkFuture work will involve extending the existing study to include additional hiPSC-EP differentiation protocols as well as conducting single-cell RNAseq to better understand the makeup of different cell populations both before and after isolating CD34+ cells. Because smooth muscle cells play an important role in vessel stabilization, we will also incorporate hiPSC-derived smooth muscle cells into the system.

bioengineering↗

bioRxiv2024

Dynamic Electrical Stimulation Promotes hiPSC-CM Differentiation and Functionality

Human induced pluripotent stem cell differentiated cardiomyocytes (hiPSC-CMs) hold great potential to resolve cardiovascular disease but are stymied by their functional immaturity. The complex electric potentials measured during cardiogenesis point to the potential of exogenous electrical stimulation in improving cardiac differentiation and functionality. Herein, we create, validate, and implement a low-cost electrical stimulation device to stimulate hiPSCs during cardiac differentiation. Notably, our open-source device enables the generation of complex electrical stimulation regimes that may vary in frequency and pulse duration over time. Our results demonstrate that dynamic stimulation during differentiation improves cardiac differentiation efficiency, calcium handling, and flow velocity, and promotes significant transcriptomic pathway enrichment compared to static stimulation or no stimulation controls. Moreover, dynamic stimulation enhances electrochemical coupling and promotes the expression of cardiogenic pathways, potentially via sarcomere development. We anticipate that more complex dynamic electrical stimulation regimens may be generated to further optimize hiPSC-CM functionality and maturity.

bioengineering↗

bioRxiv2024

Long-Term Monolayer Cultivation Captures Homeostatic and Regenerative Features of Human Colonic Epithelial Cells

Primary intestinal epithelial stem cell culture methods have significantly advanced understanding of mammalian intestinal development and disease. However, progress has been hampered by inconsistent methodological reporting and challenges comparing in vitro systems with in vivo observations. We previously established a unique method for long-term 2{-}dimensional (2D) cultivation of mouse lECs using an air-liquid interface (ALI) technique which appears to faithfully recapitulate homeostatic and regenerative features in vitro. Here, we further refined these methods and optimized protocols for long-term, self-organizing 2D cultivation of human lECs. During the culture, we observed that epithelial cells undergo a dynamic morphological transition from squamous to columnar shape. Using single cell transcriptomics, we identified both major lineages and minor populations, including enteroendocrine cells, tuft cells, and BEST4/CA7+ cells. Leveraging the power and scalability of a biomedical foundation model (BMFM) trained on single cell RNA sequencing data, we performed classification tasks to identify cell types across sample sources and to quantitatively benchmark our in vitro differentiated cells against cells collected from patient biopsies. We observed a striking degree of similarity between our in vitro differentiated cells and the corresponding cell types in vivo for multiple differentiated lineages. This novel approach using BMFM holds promise to expand our understanding of the regulatory mechanisms including gene-gene regulation underlying homeostasis and regeneration as well as the functions of rare and poorly understood lineages within the human intestinal epithelia. Moreover, these methods are generalizable to other organs and can be used to assess the correspondence of cells across experimental modalities. SignificanceThis manuscript addresses challenges in quantitative comparisons of cell types grown in vitro vs their in vivo counterparts. Here we use the intestinal epithelium as a model system to address this challenge. We devised an in vitro culture platform that supports multipotent intestinal epithelial stem cells and their numerous differentiated progeny. This system gives rise to all known rare and abundant lineages in correct proportions. Novel use of biomedical foundation models pre-trained on publicly available data and then fine-tuned to data from this platform enabled demonstration of high concordance of multiple in vitro differentiated lineages with the corresponding cells in vivo.

cell biology↗

bioRxiv2023

The Natural Products Discovery Center: Release of the First 8490 Sequenced Strains for Exploring Actinobacteria Biosynthetic Diversity

Actinobacteria, the bacterial phylum most renowned for natural product discovery, has been established as a valuable source for drug discovery and biotechnology but is underrepresented within accessible genome and strain collections. Herein, we introduce the Natural Products Discovery Center (NPDC), featuring 122,449 strains assembled over eight decades, the genomes of the first 8490 NPDC strains (7142 Actinobacteria), and the online NPDC Portal making both strains and genomes publicly available. A comparative survey of RefSeq and NPDC Actinobacteria highlights the taxonomic and biosynthetic diversity within the NPDC collection, including three new genera, hundreds of new species, and [~]7000 new gene cluster families. Selected examples demonstrate how the NPDC Portals strain metadata, genomes, and biosynthetic gene clusters can be leveraged using genome mining approaches. Our findings underscore the ongoing significance of Actinobacteria in natural product discovery, and the NPDC serves as an unparalleled resource for both Actinobacteria strains and genomes.

microbiology↗

bioRxiv2023

MCT4 and CD147 co-localize with MMP14 in invadopodia and autolysosomes and collectively stimulate breast cancer cell invasion by increasing extracellular matrix degradation

The lactate-proton cotransporter MCT4 and its chaperone CD147 are upregulated in breast cancers, correlating with decreased patient survival. Here, we test the hypothesis that MCT4 and CD147 favor breast cancer invasion through interdependent effects on extracellular matrix (ECM) degradation. MCT4 and CD147 expression and membrane localization were strongly reciprocally interdependent in MDA-MB-231 invasive breast cancer cells. Knockdown (KD) and overexpression (OE) of MCT4 and/or CD174 in- and decreased, respectively, migration, invasion, and fluorescent gelatin degradation. OE of both proteins increased gelatin degradation and appearance of the matrix metalloprotease (MMP)-generated collagen-I cleavage product reC1M more than each protein alone, suggesting a concerted role in ECM degradation. MCT4 and CD147 co-localized strongly with invadopodia markers at the plasma membrane and with MMP14, the lysosomal marker LAMP-1, and in some cases the autophagosome marker LC3, in F-actin-decorated, large intracellular vesicles. We conclude that MCT4 and CD147 reciprocally regulate each other and support migration and invasiveness of MDA-MB-231 breast cancer cells in an interdependent manner. Mechanistically, this involves the MCT4-CD147-dependent stimulation of ECM degradation and specifically of MMP-mediated collagen-I degradation. We suggest that the MCT4-CD147 complex is co-delivered to invadopodia with MMP14.

cancer biology↗

bioRxiv2023

miR-252 targeting temperature receptor CcTRPM to mediate the transition from summer-form to winter-form of Cacopsylla chinensis

Temperature determines the geographical distribution of organisms and affects the outbreak and damage of pests. Insects seasonal polyphenism is a successful strategy adopted by some species to adapt the changeable external environment. Cacopsylla chinensis (Yang & Li) showed two seasonal morphotypes, summer-form and winter-form, with significant differences in morphological characteristics. Low temperature is the key environmental factor to induce its transition from summer-form to winter-form. However, the detailed molecular mechanism remains unknown. Here, we firstly confirmed that low temperature of 10{degrees}C induced the transition from summer-form to winter-form by affecting the cuticle thickness and chitin content. Subsequently, we demonstrated that CcTRPM functions as a temperature receptor to regulate this transition. In addition, miR-252 was identified to mediate the expression of CcTRPM to involve in this morphological transition. Finally, we found CcTre1 and CcCHS1, two rate-limiting enzymes of insect chitin biosyntheis, act as the critical down-stream signal of CcTRPM in mediating this behavioral transition. Taken together, our results revealed that a signal transduction cascade mediates the seasonal polyphenism in C. chinensis. These findings not only lay a solid foundation for fully clarifying the ecological adaptation mechanism of C. chinensis outbreak, but also broaden our understanding about insect polymorphism.

evolutionary biology↗

bioRxiv2023

IL-15 enhances functional properties and responses of CD28-negative CD4+ cytotoxic T cells expanded in Systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disorder that results in an attack by bodys immune system of its own tissues, causing chronic inflammation and tissue damage. T cells play a key role in the pathogenesis of SLE, as they secrete pro-inflammatory cytokines as well as mediate direct effects on target tissues. Recently, CD4-positive T cells with cytotoxic potential were showed to be involved in autoimmune disease progression and tissue damage. However, whether this cell type expands and plays effector functions in SLE patients remain to be elucidated. Analyzing single-cell RNA sequencing (scRNA-Seq) data and flow cytometry data, we find that cytotoxic CD4+CD28- T cells are present in SLE patients. We also show that these cells expand most prominently in patients affected by lupus nephritis, and they exhibit cytotoxic activity against human renal glomerular endothelial cells in vitro. In addition, our study suggests that Interleukin-15 (IL-15) promotes the expansion, proliferation and cytotoxic function of CD4+CD28- T cells in SLE patients. Tofacitinib, a selective JAK3 inhibitor, inhibits the effect of IL-15 on CD4+CD28- T cells. Together, our study clearly demonstrated that CD4+ CD28- T cells characterized by proinflammatory properties and cytolytic function expand in SLE patients. The pathogenic potential of these CD4+ CD28- T cells is driven by IL-15/IL-15R/JAK3/STAT5 signaling pathway, which may open new avenues for therapeutic intervention to prevent progression of SLE patients.

immunology↗

bioRxiv2021

Influence of Strain Post-Processing on Brain Injury Prediction

Finite element head models are a tool to better understand brain injury mechanisms. Many of the models use strain as output but with different percentile values such as 100th, 95th, 90th, and 50th percentiles. Some use the element value, whereas other use the nodal average value for the element. Little is known how strain post-processing is affecting the injury predictions and evaluation of different prevention systems. The objective of this study was to evaluate the influence of strain output on injury prediction and ranking. Two models with different mesh densities were evaluated (KTH Royal Institute of Technology head model and the Total Human Models for Safety (THUMS)). Pulses from reconstructions of American football impacts with and without a diagnosis of mild traumatic brain injury were applied to the models. The value for 100th, 99th, 95th, 90th, and 50th percentile for element and nodal averaged element strain was evaluated based on peak values, injury risk functions, injury predictability, correlation in ranking, and linear correlation. The injury risk functions were affected by the post-processing of the strain, especially the 100th percentile element value stood out. Meanwhile, the area under the curve (AUC) value was less affected, as well as the correlation in ranking (Kendalls tau 0.71-1.00) and the linear correlation (Pearsons r2 0.72-1.00). With the results presented in this study, it is important to stress that the same post-processed strain should be used for injury predictions as the one used to develop the risk function.

bioengineering↗