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Sun, W.

Publications and source records attributed to Sun, W..

At least 163 records · Page 9Linked to original sources

Biomechanical stress analysis of Type-A aortic dissection at pre-dissection, post-dissection, and post-repair states

Acute type A aortic dissection remains a deadly and elusive condition, with risk factors such as hypertension, bicuspid aortic valves, and genetic predispositions. As existing guidelines for surgical intervention based solely on aneurysm diameter face scrutiny, there is a growing need to consider other predictors and parameters, including wall stress, in assessing dissection risk. Through our research, we aim to elucidate the biomechanical underpinnings of aortic dissection and provide valuable insights into its prediction and prevention. We applied finite element analysis (FEA) to assess stress distribution on a rare dataset comprising computed tomography (CT) images obtained from eight patients at three stages of aortic dissection: pre-dissection (preD), post-dissection (postD), and post-repair (postR). Our findings reveal significant increases in both mean and peak aortic wall stresses during the transition from the preD state to the postD state, reflecting the mechanical impact of dissection. Surgical repair effectively restores aortic wall diameter to pre-dissection levels, documenting its effectiveness in mitigating further complications. Furthermore, we identified stress concentration regions within the aortic wall that closely correlated with observed dissection borders, offering insights into high-risk areas. This study demonstrates the importance of considering biomechanical factors when assessing aortic dissection risk. Despite some limitations, such as uniform wall thickness assumptions and the absence of dynamic blood flow considerations, our patient-specific FEA approach provides valuable mechanistic insights into aortic dissection. These findings hold promise for improving predictive models and informing clinical decisions to enhance patient care.

bioengineering↗

Alternative Splicing of Latrophilin-3 Controls Synapse Formation

How synapses are assembled and specified in brain is incompletely understood. Latrophilin- 3, a postsynaptic adhesion-GPCR, mediates Schaffer-collateral synapse formation in the hippocampus but the mechanisms involved remained unclear. Here we show that Latrophilin-3 organizes synapses by a convergent dual-pathway mechanism by which Latrophilin-3 simultaneously activates GS/cAMP-signaling and recruits phase-separated postsynaptic protein scaffolds. We found that cell type-specific alternative splicing of Latrophilin-3 controls its G protein coupling mode, resulting in Latrophilin-3 variants that predominantly signal via Gs and cAMP or via G12/13. A CRISPR-mediated genetic switch of Latrophilin-3 alternative splicing from a GS- to a G12/13-coupled mode impaired synaptic connectivity similar to the overall deletion of Latrophilin-3, suggesting that GS/cAMP- signaling by Latrophilin-3 splice variants mediates synapse formation. Moreover, GS- but not G12/13-coupled splice variants of Latrophilin-3 recruit phase-transitioned postsynaptic protein scaffolds that are clustered by binding of presynaptic Latrophilin-3 ligands. Strikingly, neuronal activity promotes alternative splicing of the synaptogenic variant of Latrophilin-3, thereby enhancing synaptic connectivity. Together, these data suggest that activity- dependent alternative splicing of a key synaptic adhesion molecule controls synapse formation by parallel activation of two convergent pathways, GS/cAMP signaling and the phase separation of postsynaptic protein scaffolds.

neuroscience↗

Probiotic neoantigen delivery vectors for precision cancer immunotherapy

Microbial systems have been synthetically engineered to deploy therapeutic payloads in vivo1-4. With emerging evidence that bacteria naturally home to tumors5-7 and modulate anti-tumor immunity8,9, one promising application is the development of bacterial vectors as precision cancer vaccines10-12. In this study, we engineered probiotic E. coli Nissle 1917 (EcN) as an anti-tumor vaccination platform optimized for enhanced production and cytosolic delivery of neoepitope-containing peptide arrays, with increased susceptibility to blood clearance and phagocytosis. These features enhance both safety and immunogenicity, achieving a system which drives potent and specific T cell-mediated anti-cancer immunity that effectively controls or eliminates tumor growth and extends survival in advanced murine primary and metastatic solid tumors. We demonstrate that the elicited anti-tumor immune response involves extensive priming and activation of neoantigen-specific CD4+ and CD8+ T cells, broader activation of both T and NK cells, and a reduction of tumor-infiltrating immunosuppressive myeloid and regulatory T and B cell populations. Taken together, this work leverages the advantages of living medicines to deliver arrays of tumor-specific neoantigen-derived epitopes within the optimal context to induce specific, effective, and durable systemic anti-tumor immunity.

synthetic biology↗

Gut microbial genomes with paired isolates from China signify probiotic and cardiometabolic effects

The gut microbiome displays significant genetic differences between populations while systematic characterization of the genomic landscape of the gut microbiome in Asia populations remains limited. Here, we present the Chinese gut microbial reference (CGMR) set, comprising 101,060 high quality metagenomic assembled genomes (MAGs) of 3,707 non-redundant species paired with 1,376 live isolates from a national wide collection of 3,234 fecal samples across China. This improved reference set contains 987 novel species compared with existing resources worldwide. By associating MAGs with geographic and phenotypic characteristics, we observed regional-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. We further conducted mice experiments to confirm the probiotic effects of two Faecalibacterium intestinalis isolates in alleviating constipation, the cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and the functional potential of isolates from the two new species belonging to the genera Parabacteroides and Lactobacillus in host lipids metabolism. Our study not only expands the current microbial genomes with paired isolates but also demonstrates their probiotic and cardiometabolic effects on hosts, contributing to the mechanistic understanding of host-microbe interactions and the translation of microbiome-based personalized therapies.

microbiology↗

Pseudorabies virus causes splenic injury via inducing the oxidative stress and apoptpsos related factors in mice

Pseudorabies virus (PRV) is an immunosuppressive disease that causes significant damage to the pig industry. This study aimed to detect the effects of PRV on oxidative stress related factors and cell apoptosis in the spleen, providing a basis for the research on the pathogenesis of PRV in mice model. Pathological observation was performed by hematoxylin and eosin Y staining. Biochemical and Flow cytometry method were performed to determine the reactive oxygen species profile of the spleen post-infection and apoptosis detection. In addition, q-PCR and Western blot were adopted to measure the apoptotic conditions of the spleen infected with PRV. The results indicated that the ROS level in the PRV infection group was remarkedly increased (p<0 01) at a time-dependent pattern. Furthermore, the Malondialdehyde levels in the spleen of mice in the infection group increased significantly (p<0.01) in a time-dependent mode. However, the Catalase, Superoxide dismutase, and Glutathione activity and expression levels in the infection group were significantly decreased with the control group (p<0 01) in a time-dependent manner. Furthermore, the ratio of splenocyte apoptosis in the infection group significantly increased (p<0 05, p<0 01) in a time-dependent manner. In conclusion, PRV infection causes apoptosis of the spleen via oxidative stress in mice.

microbiology↗

The role of neutrophil typing in homeostatic resilience protective model of inflammatory preconditioning

Sepsis is a systemic inflammatory response syndrome (SIRS) characterized by a dysregulated host response to infection that results in organ dysfunction. The response of neutrophils to early inflammation is critical, interferon regulatory factors 4 (IRF4) and interferon regulatory factors 5 (IRF5) are expressed in most cell types of the immune system, but the relationship between the role of IRF4 and IRF5 in preconditioning-protected septic peritonitis mouse model and neutrophils response remains unknown. In this study, we used an E.coli-induced septic peritonitis mouse model and zebrafish model to explore the relationship between neutrophil inflammation and IRF subtype changes in the process of septic peritonitis. Mechanistically, we found that the protein complex formed by polymorphonuclear neutrophils (PMN) and IRF5/MyD88 can secrete pro-inflammatory factors and directly kill invading bacteria. Author SummaryNumerous animal and clinical sepsis studies have shown that markedly impaired recruitment of neutrophils to sites of infection and failure to clear bacteria contribute to excessive inflammation and increased mortality in sepsis. In our previous work, we established an Escherichia coli (E.coli) lethal septic peritonitis model and a preconditioning-protected septic peritonitis mouse model. In the early stage of septic peritonitis, a large number of PMN infiltrate the peritoneal cavity, which produces an inflammatory response to invasive bacteria. In this study, the switching process between pro-inflammatory and anti-inflammatory attracted our attention. Our research shows that IRF5-IRF4 regulatory axis leads to a PMN phenotype switch in sepsis and the expression of IRF5 and IRF4 was related to PMN pro-inflammatory (N1 type) and anti-inflammatory (N2 type) phenotypes, respectively.

immunology↗

Distinct Microstructural Heterogeneities Underpin Specific Micromechanical Properties in Human ACL Femoral and Tibial Entheses

The anterior cruciate ligament (ACL) is anchored to the femur and tibia by a specialized interface tissue called the enthesis, which transfers forces in multiple directions and magnitudes without accruing fatigue damage during loading cycles over a lifetime. However, the precise structural and mechanical characteristics of the ACL femoral enthesis (FE) and tibial enthesis (TE) and their intricate interplay are unknown. In this study, we identified two ultrathin-graded mineralization regions in the FE ([~]21 m) and TE ([~]14 m), both of which exhibited distinct biomolecular compositions and mineral assembly patterns. FE interface exhibited progressively maturing hydroxyapatites (HAps), whereas minerals at the TE interface region changed from an amorphous phase (ACP) to HAps with increasing crystallinity. The LC-MS/MS results revealed that MGP protein uniquely enriched at the TE interface may be favorable for stabilizing ACP, while CLEC11A enriched at the FE interface could facilitate osteogenesis of the interface. The finite element analysis results indicated that the FE model was more resistant to shearing, while the TE model facilitated tensile resistance. It suggested that the great discrepancy in biomolecular expression and the corresponding mineral assembling heterogeneities together contributed to the superior mechanical properties of both the FE and TE models. These findings provide new perspectives regarding the management of ACL injury and the development of high-performance interface materials.

bioengineering↗

Pneumonic plague protection induced by a monophosphoryl lipid A decorated Yersinia outer-membrane-vesicle vaccine

A newly constructed Yersinia pseudotuberculosis mutant (YptbS46) carrying the lpxE insertion and pmrF-J deletion exclusively synthesized an adjuvant form of lipid A, monophosphoryl lipid A (MPLA). Outer membrane vesicles (OMVs) isolated from YptbS46 harboring an lcrV expression plasmid, pSMV13, were designated OMV46-LcrV, which contained MPLA and high amounts of LcrV and displayed low activation of Toll-like receptor 4 (TLR4). Similar to the previous OMV44-LcrV, intramuscular prime-boost immunization with 30 {micro}g of OMV46-LcrV exhibited substantially reduced reactogenicity and conferred complete protection to mice against a high-dose of respiratory Y. pestis challenge. OMV46-LcrV immunization induced robust adaptive responses in both lung mucosal and systemic compartments and orchestrated innate immunity in the lung, which were correlated with rapid bacterial clearance and unremarkable lung damage during Y. pestis challenge. Additionally, OMV46-LcrV immunization conferred long-term protection. Moreover, immunization with reduced doses of OMV46-LcrV exhibited further lower reactogenicity and still provided great protection against pneumonic plague. Our studies strongly demonstrate the feasibility of OMV46-LcrV as a new type of plague vaccine candidate.

immunology↗

Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function

The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian sModel (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development.

neuroscience↗

Learning produces a hippocampal cognitive map in the form of an orthogonalized state machine

Cognitive maps confer animals with flexible intelligence by representing spatial, temporal, and abstract relationships that can be used to shape thought, planning, and behavior. Cognitive maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. Here, we employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different versions of linear tracks in virtual reality. The results provide a detailed view of the formation of a cognitive map in the hippocampus. Throughout learning, both the animal behavior and hippocampal neural activity progressed through multiple intermediate stages, gradually revealing improved task representation that mirrored improved behavioral efficiency. The learning process led to progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent structure of the task. We show that a Hidden Markov Model (HMM) and a biologically plausible recurrent neural network trained using Hebbian learning can both capture core aspects of the learning dynamics and the orthogonalized representational structure in neural activity. In contrast, we show that gradient-based learning of sequence models such as Long Short-Term Memory networks (LSTMs) and Transformers do not naturally produce such orthogonalized representations. We further demonstrate that mice exhibited adaptive behavior in novel task settings, with neural activity reflecting flexible deployment of the state machine. These findings shed light on the mathematical form of cognitive maps, the learning rules that sculpt them, and the algorithms that promote adaptive behavior in animals. The work thus charts a course toward a deeper understanding of biological intelligence and offers insights toward developing more robust learning algorithms in artificial intelligence.

neuroscience↗

Persistence of intact HIV-1 proviruses in the brain during suppressive antiretroviral therapy

HIV-1 reservoir cells that circulate in peripheral blood during suppressive antiretroviral therapy (ART) have been well characterized, but little is known about the dissemination of HIV-1-infected cells across multiple anatomical tissues, especially the central nervous system (CNS). Here, we performed single-genome, near full-length HIV-1 next-generation sequencing to evaluate the proviral landscape in distinct anatomical compartments, including multiple CNS tissues, from 3 ART-treated participants at autopsy. While lymph nodes and, to a lesser extent, gastrointestinal and genitourinary tissues represented tissue hotspots for the persistence of intact proviruses, we also observed intact proviruses in CNS tissue sections, particularly in the basal ganglia. Multi-compartment dissemination of clonal intact and defective proviral sequences occurred across multiple anatomical tissues, including the CNS, and evidence for the clonal proliferation of HIV-1-infected cells was found in the basal ganglia, in the frontal lobe, in the thalamus and in periventricular white matter. Deep analysis of HIV-1 reservoirs in distinct tissues will be informative for advancing HIV-1 cure strategies.

microbiology↗

Haplotype-phased genome revealed the butylphthalide biosynthesis and hybrid origin of Ligusticum chuanxiong

Butylphthalide, one type of phthalides, is one of the first-line drugs for ischemic stroke therapy, while no enzyme involved in its biosynthesis pathway has been reported. Here, we present the first haplotype-resolved genome of Ligusticum chuanxiong Hort., a long-cultivated and phthalide-rich medicinal plant in Apiaceae. Based on comprehensive candidate gene screening, four Fe (II)- and 2-oxoglutarate-dependent dioxygenases (2OGDs) and two CYPs were mined and further biochemically verified as phthalide C-4/C-5 desaturase (P4,5Ds) that converts senkyunolide A to l-n-butylphthalide (l-NBP) and ligustilide to butylidenephthalide. The substrate promiscuity and functional redundancy featured for P4,5Ds may contribute to the high phthalide diversity in L. chuanxiong. Notably, comparative genomic evidence supported L. chuanxiong as a diploid hybrid with L. sinense as a potential parent. The two haplotypes demonstrated exceptional structure variance and diverged around 3.42 million years ago (Ma). Our study is an icebreaker for the dissection of phthalide biosynthesis pathway and reveals the hybrid origin of L. chuanxiong. These findings will facilitate the future metabolic engineering for l-NBP production and breeding efforts for L. chuanxiong.

synthetic biology↗

Human subcutaneous adipose tissue variability is driven by VEGFA, ACTA2, adipocyte density, and ancestral history of the patient

Adipose tissue is a dynamic regulatory organ that has profound effects on the overall health of patients. Unfortunately, inconsistencies in human adipose tissues are extensive and multifactorial including large variability in cellular sizes, lipid content, inflammation, extracellular matrix components, mechanics, and cytokines secreted. Given the high human variability, and since much of what is known about adipose tissue is from animal models, we sought to establish correlations and patterns between biological, mechanical, and epidemiological properties of human adipose tissues. To do this, twenty-six independent variables were cataloged for twenty patients that included patient demographics and factors that drive health, obesity, and fibrosis. A factorial analysis for mixed data (FAMD) was used to analyze patterns in the dataset (with BMI > 25) and a correlation matrix was used to identify interactions between quantitative variables. Vascular endothelial growth factor A (VEGFA) and actin alpha 2, smooth muscle (ACTA2) gene expression were the highest loading in the first two dimensions of the FAMD. The number of adipocytes was also a key driver of patient-related differences, where a decrease in the density of adipocytes was associated with aging. Aging was also correlated with a decrease in overall lipid percentage of subcutaneous tissue (with lipid deposition being favored extracellularly), an increase in transforming growth factor-{beta}1 (TGF{beta}1), and an increase in M1 macrophage polarization. An important finding was that self-identified race contributed to variance between patients in this study, where Black patients had significantly lower gene expression levels of TGF{beta}1 and ACTA2. This finding supports the urgent need to account for patient ancestry in biomedical research to develop better therapeutic strategies for all patients. Another important finding was that TGF{beta} induced factor homeobox 1 (TGIF1), an understudied signaling molecule, is highly correlated with leptin signaling and was correlated with metabolic inflammation. Finally, this study revealed an interesting gene expression pattern where M1 and M2 macrophage markers were correlated with each other, and leptin, in patients with a BMI > 25. This finding supports growing evidence that macrophage polarization in obesity involves a complex, interconnecting network system rather than a full switch in activation patterns from M2 to M1 with increasing body mass. Overall, this study reinforces key findings in animal studies and identifies important areas for future research, where human and animal studies are divergent. Understanding key drivers of human patient variability is required to unravel the complex metabolic health of unique patients.

physiology↗

Neural Network Models for Sequence-Based TCR and HLA Association Prediction

T cells rely on their T cell receptors (TCRs) to recognize foreign antigens presented by human leukocyte antigen (HLA) proteins. TCRs contain a record of an individuals past immune activities, and some TCRs are observed only in individuals with certain HLA alleles. As a result, characterising TCRs requires a thorough understanding of TCR-HLA associations. To this end, we propose a neural network method named Deep learning Prediction of TCR-HLA association (DePTH) to predict TCR-HLA associations based on their amino acid sequences. We show that the DePTH can be used to quantify the functional similarities of HLA alleles, and that these HLA similarities are associated with the survival outcomes of cancer patients who received immune checkpoint blockade treatment.

genomics↗

Single-cell RNA-sequencing identifies a novel subset of CD9+ reparative macrophages modulated by CCN2 derived from Nlrx1 deficient cardiomyocytes in the infarcted heart

RationaleNlrx1, a pattern recognition receptor belonging to the NLR family, is highly expressed in the heart and is significantly increased after myocardial infarction in vivo, however, the role of Nlrx1 in post-infarction inflammation and healing is poorly understood. Although the effects of infiltrating macrophages on survival of cardiomyocytes and healing of injured hearts have been intensely studied, whether or not and how surviving cardiomyocytes might influence the phenotype and function of macrophages in the infarcted hearts was largely unexplored. ObjectiveTo investigate the role of Nlrx1 in post-infarction inflammation and healing and to dissect the underlying mechanism. Methods and resultsSingle cell RNA-sequencing of 23,805 cells isolated from infarcted hearts revealed 7 clusters of infarct macrophages including CCR2+, Isg+, Mki67+ proliferative, and LYVE1+ cardiac resident macrophages, and identified a novel subset of CD9+Il1rn+ macrophages, which were characterized by high expression of Cd9, Il1rn, Gpnmb and Spp1, and downregulation of proinflammatory cytokines and chemokines. CD9+Il1rn+ macrophages were largely found in infarcted hearts of Nlrx1KO mice, and were transcriptionally unique with reparative phenotype. Loss of Nlrx1 attenuated ventricular dysfunction and adverse remodeling, and decreased post-infarction mortality. Flow cytometry analysis showed markedly increased number of CD9+ macrophages and higher mean fluorescence intensity of CD9 in Nlrx1KO mice. RNA-seq analysis revealed that CD9+ macrophages of Nlrx1KO infarcted hearts exhibited a reparative and anti-inflammatory phenotype as featured by upregulation of wound healing-associated genes including CD9, Spp1 and Fn1, and downregulation of proinflammatory genes. Conditioned medium from Nlrx1 deficient cardiomyocytes upon hypoxia stimulation skewed macrophage polarization towards a reparative and inflammation-suppressed phenotype. Gain-and loss-of function of Nlrx1 combined with RNA-seq analysis identified CCN2, whose expression and secretion were significantly increased in Nlrx1 deficient cardiomyocytes upon hypoxia, as a cardiomyocytes-derived mediator responsible, at least partly, for reprograming macrophage towards a reparative phenotype. In vivo, CCN2 expression was markedly elevated in Nlrx1KO infarcted hearts. Moreover, exogenous CCN2 partially mediated macrophage transition towards a reparative phenotype. ConclusionsCD9+ IL1rn+ macrophages modulated by Nlrx1 deficient cardiomyocytes-derived CCN2, is a novel subset of reparative macrophages contributing to infarct healing. Inhibition of myocardial Nlrx1 and/or activation of CCN2 to boost CD9+ IL1rn+ reparative macrophages may represent new therapeutics for infarct healing following ischemic injury.

immunology↗

Synergistic Integration of Deep Neural Networks and Finite Element Method with Applications for Biomechanical Analysis of Human Aorta

Motivation: Patient-specific finite element analysis (FEA) has the potential to aid in the prognosis of cardiovascular diseases by providing accurate stress and deformation analysis in various scenarios. It is known that patient-specific FEA is time-consuming and unsuitable for time-sensitive clinical applications. To mitigate this challenge, machine learning (ML) techniques, including deep neural networks (DNNs), have been developed to construct fast FEA surrogates. However, due to the data-driven nature of these ML models, they may not generalize well on new data, leading to unacceptable errors. MethodsWe propose a synergistic integration of DNNs and finite element method (FEM) to overcome each others limitations. We demonstrated this novel integrative strategy in forward and inverse problems. For the forward problem, we developed DNNs using state-of-the-art architectures, and DNN outputs were then refined by FEM to ensure accuracy. For the inverse problem of heterogeneous material parameter identification, our method employs a DNN as regularization for the inverse analysis process to avoid erroneous material parameter distribution. ResultsWe tested our methods on biomechanical analysis of the human aorta. For the forward problem, the DNN-only models yielded acceptable stress errors in majority of test cases; yet, for some test cases that could be out of the training distribution (OOD), the peak stress errors were larger than 50%. The DNN-FEM integration eliminated the large errors for these OOD cases. Moreover, the DNN-FEM integration was magnitudes faster than the FEM-only approach. For the inverse problem, the FEM-only inverse method led to errors larger than 50%, and our DNN-FEM integration significantly improved performance on the inverse problem with errors less than 1%.

bioengineering↗

Temporal colonization of the gut microbiome in neonatal Bos taurus at single nucleotide resolution

BackgroundThe rumen of neonatal calves is underdeveloped and exhibits limited functionality during early life. Thus, the acquisition and colonization of microbes in the gut are key to establishing a healthy host-microbiome symbiosis for neonatal calves. Microbiome-linked health outcomes appear to be the consequences of individual strains of specific microbes. However, the temporal colonization of pioneering microbial strains and their linkages to the health and growth of neonatal calves are poorly understood. ResultsTo address this, we longitudinally profiled the gut microbiome of 36 neonatal calves from birth up to 2 months postpartum and carried out microbial transplantation (MT) to reshape their gut microbiome. Genomic reconstruction of deeply sequenced fecal samples resulted in a total of 3,931 metagenomic assembled genomes (MAGs), of which 397 were identified as new species when compared with existing databases of Bos taurus. Single nucleotide level metagenomic profiling shows a rapid influx of microbes after birth, followed by strong selection during the first few weeks of life. MT was found to reshape the genetic makeup of 33 MAGs (FDR<0.05), mainly from Prevotella and Bacteroides species. We further linked over 20 million microbial single nucleotide variations (SNVs) to 736 plasma metabolites, which enabled us to characterize 24 study-wide significant associations (P < 4.4x10-9) that identify the potential microbial genetic regulation of host immune and neuro-related metabolites, including glutathione and L-dopa. Our integration analyses further revealed that microbial genetic variations may influence the health status and growth performance of neonatal calves by modulating metabolites via structural regulation of their encoded proteins. For instance, we found that the albumin levels and total antioxidant capacity in neonatal calves were correlated with L-dopa, which was determined by SNVs via structural regulations of metabolic enzymes. ConclusionsThe current results indicate that the temporal colonization of microbial strains and MT-induced strain replacement are integral in the development of the gut microbiome of neonatal calves and may help to develop strategies that can improve the health status and growth performance of neonatal calves.

microbiology↗

PyTorch-FEA: Autograd-enabled Finite Element Analysis Methods with Applications for Biomechanical Analysis of Human Aorta

MotivationFinite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed. MethodsIn this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance. ResultsWe applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.

bioengineering↗