Zinc transporter 1 functions in copper uptake and cuproptosis.

Copper (Cu) is a co-factor for several essential metabolic enzymes. Disruption of Cu homeostasis results in genetic diseases such as Wilson's disease. Here, we show that the zinc transporter 1 (ZnT1), known to export zinc (Zn) out of the cell, also mediates Cu2+ entry into cells and is required for Cu2+-induced cell death, cuproptosis. Structural analysis and functional characterization indicate that Cu2+ and Zn2+ share the same primary binding site, allowing Zn2+ to compete for Cu2+ uptake. Among ZnT members, ZnT1 harbors a unique inter-subunit disulfide bond that stabilizes the outward-open conformations of both protomers to facilitate efficient Cu2+ transport. Specific knockout of the ZnT1 gene in the intestinal epithelium caused the loss of Lgr5+ stem cells due to Cu deficiency. ZnT1, therefore, functions as a dual Zn2+ and Cu2+ transporter and potentially serves as a target for using Zn2+ in the treatment of Wilson's disease caused by Cu overload.

Aerobic, resistance, or combined exercise training and cardiovascular risk profile in overweight or obese adults: the CardioRACE trial.

BACKGROUND AND AIMS: To determine the comparative efficacy of resistance, aerobic, and combined resistance plus aerobic exercise on cardiovascular disease (CVD) risk profile. METHODS: This randomized controlled trial enrolled 406 adults aged 35-70 years with overweight or obesity and elevated blood pressure. Participants were randomly assigned to resistance (n = 102), aerobic (n = 101), combined resistance plus aerobic exercise (n = 101), or no-exercise control (n = 102). All exercise participants were prescribed 1 h of time-matched supervised exercise (the combination group with 30 min of each resistance and aerobic exercise) three times per week for 1 year. The primary outcome was the change from baseline to 1 year in the standardized composite Z-score of four well-established CVD risk factors: systolic blood pressure, low-density lipoprotein (LDL) cholesterol, fasting glucose, and per cent body fat. RESULTS: Among 406 participants (53% women), 381 (94%) completed 1-year follow-up. Compared with the control group, the composite Z-score decreased at 1 year, which indicates improved CVD risk profile, in the aerobic {mean difference, -0.15 [95% confidence interval (CI): -0.27 to -0.04]; P = .01} and combination [mean difference, -0.16 (95% CI: -0.27 to -0.04); P = .009] groups, but not in the resistance [mean difference, -0.02 (95% CI: -0.14 to 0.09); P = .69] group. Both aerobic and combination groups had greater reductions in the composite Z-score compared with the resistance group (both P = .03), and there was no difference between the aerobic and combination groups (P = .96). Regarding the four individual CVD risk factors, only per cent body fat decreased in all three exercise groups at 1 year, but systolic blood pressure, LDL cholesterol, and fasting glucose did not decrease in any exercise groups, compared with the control group. CONCLUSIONS: In adults with overweight or obesity, aerobic exercise alone or combined resistance plus aerobic exercise, but not resistance exercise alone, improved composite CVD risk profile compared with the control.

Targeting GPR65 alleviates hepatic inflammation and fibrosis by suppressing the JNK and NF-κB pathways.

BACKGROUND: G-protein coupled receptors (GPCRs) are recognized as attractive targets for drug therapy. However, it remains poorly understood how GPCRs, except for a few chemokine receptors, regulate the progression of liver fibrosis. Here, we aimed to reveal the role of GPR65, a proton-sensing receptor, in liver fibrosis and to elucidate the underlying mechanism. METHODS: The expression level of GPR65 was evaluated in both human and mouse fibrotic livers. Furthermore, Gpr65-deficient mice were treated with either bile duct ligation (BDL) for 21 d or carbon tetrachloride (CCl4) for 8 weeks to investigate the role of GPR65 in liver fibrosis. A combination of experimental approaches, including Western blotting, quantitative real-time reverse transcription­polymerase chain reaction (qRT-PCR), and enzyme-linked immunosorbent assay (ELISA), confocal microscopy and rescue studies, were used to explore the underlying mechanisms of GPR65's action in liver fibrosis. Additionally, the therapeutic potential of GPR65 inhibitor in the development of liver fibrosis was investigated. RESULTS: We found that hepatic macrophages (HMs)-enriched GPR65 was upregulated in both human and mouse fibrotic livers. Moreover, knockout of Gpr65 significantly alleviated BDL- and CCl4-induced liver inflammation, injury and fibrosis in vivo, and mouse bone marrow transplantation (BMT) experiments further demonstrated that the protective effect of Gpr65 knockout is primarily mediated by bone marrow-derived macrophages (BMMs). Additionally, in vitro data demonstrated that Gpr65 silencing and GPR65 antagonist inhibited, while GPR65 overexpression and application of GPR65 endogenous and exogenous agonists enhanced the expression and release of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and transforming growth factor-ß (TGF-ß), all of which subsequently promoted the activation of hepatic stellate cells (HSCs) and the damage of hepatocytes (HCs). Mechanistically, GPR65 overexpression, the acidic pH and GPR65 exogenous agonist induced up-regulation of TNF-α and IL-6 via the Gαq-Ca2+-JNK/NF-κB pathways, while promoted the expression of TGF-ß through the Gαq-Ca2+-MLK3-MKK7-JNK pathway. Notably, pharmacological GPR65 inhibition retarded the development of inflammation, HCs injury and fibrosis in vivo. CONCLUSIONS: GPR65 is a major regulator that modulates the progression of liver fibrosis. Thus, targeting GPR65 could be an effective therapeutic strategy for the prevention of liver fibrosis.

lncRNA Helf promotes hepatic inflammation and fibrosis by interacting with PTBP1 to facilitate PIK3R5 mRNA stabilization.

BACKGROUND: Hepatic fibrosis is a common consequence of chronic liver diseases without approved antifibrotic therapies. Long noncoding RNAs (lncRNAs) play an important role in various pathophysiological processes. However, the functions of certain lncRNAs involved in mediating the antifibrotic role remain largely unclear. METHODS: The RNA level of lnc-High Expressed in Liver Fibrosis (Helf) was detected in both mouse and human fibrotic livers. Furthermore, lnc-Helf-silenced mice were treated with carbon tetrachloride (CCl4) or bile duct ligation (BDL) to investigate the function of lnc-Helf in liver fibrosis. RESULTS: We found that lnc-Helf has significantly higher expression in human and mouse fibrotic livers as well as M1 polarized hepatic macrophages (HMs) and activated hepatic stellate cells (HSCs). In vivo studies showed that silencing lnc-Helf by AAV8 vector alleviates CCl4- and BDL-induced hepatic inflammation and fibrosis. Furthermore, in vitro experiments revealed that lnc-Helf promotes HSCs activation and proliferation, as well as HMs M1 polarization and proliferation in the absence or presence of cytokine stimulation. Mechanistically, our data illustrated that lnc-Helf interacts with RNA binding protein PTBP1 to promote its interaction with PIK3R5 mRNA, resulting in increased stability and activating the AKT pathway, thus promoting HSCs and HMs activation and proliferation, which augments hepatic inflammation and fibrosis. CONCLUSION: Our results unveil a lnc-Helf/PTBP1/PIK3R5/AKT feedforward, amplifying signaling that exacerbates the process of hepatic inflammation and fibrosis, thus providing a possible therapeutic strategy for hepatic fibrosis.

Gut bacteria induce IgA expression in pituitary hormone-secreting cells during aging.

Pituitary hormone decline is a hallmark of aging. However, the precise gene regulation mechanism during pituitary aging is unclear. Here, we characterized the cell population alteration and global transcriptional change during pituitary aging through single-cell RNA sequencing (scRNA-seq). We found that mRNA-encoding components of protein translational machinery declined the most in the pituitary during aging. Remarkably, Immunoglobulin A (IgA) was found to be expressed in hormone-secreting cells, and the IgA expression level increased dramatically in aged pituitary. Moreover, the pituitary IgA expression was regulated by gut microbiota. The non-hematopoietic origin of the IgA+ cells in the pituitary was further confirmed through bone marrow transplantation. Somatotropes were identified as the most prominent IgA-producing cells through lineage tracing. Thus, pituitary hormone-secreting cells can generate IgA in an age-dependent manner, and such a process is influenced by gut bacteria.

Sufu limits sepsis-induced lung inflammation via regulating phase separation of TRAF6.

Rationale: Sepsis is a potentially life-threatening condition caused by the body's response to a severe infection. Although the identification of multiple pathways involved in inflammation, tissue damage and aberrant healing during sepsis, there remain unmet needs for the development of new therapeutic strategies essential to prevent the reoccurrence of infection and organ injuries. Methods: Expression of Suppressor of Fused (Sufu) was evaluated by qRT-PCR, western blotting, and immunofluorescence in murine lung and peritoneal macrophages. The significance of Sufu expression in prognosis was assessed by Kaplan-Meier survival analysis. The GFP-TRAF6-expressing stable cell line (GFP-TRAF6 Blue cells) were constructed to evaluate phase separation of TRAF6. Phase separation of TRAF6 and the roles of Sufu in repressing TRAF6 droplet aggregation were analyzed by co-immunoprecipitation, immunofluorescence, Native-PAGE, FRAP and in vitro assays using purified proteins. The effects of Sufu on sepsis-induced lung inflammation were evaluated by cell function assays, LPS-induced septic shock model and polymicrobial sepsis-CLP mice model. Results: We found that Sufu expression is reduced in early response to lipopolysaccharide (LPS)-induced acute inflammation in murine lung and peritoneal macrophages. Deletion of Sufu aggravated LPS-induced and CLP (cecal ligation puncture)-induced lung injury and lethality in mice, and augmented LPS-induced proinflammatory gene expression in cultured macrophages. In addition, we identified the role of Sufu as a negative regulator of the Toll-Like Receptor (TLR)-triggered inflammatory response. We further demonstrated that Sufu directly interacts with TRAF6, thereby preventing oligomerization and autoubiquitination of TRAF6. Importantly, TRAF6 underwent phase separation during LPS-induced inflammation, which is essential for subsequent ubiquitination activation and NF-κB activity. Sufu inhibits the phase-separated TRAF6 droplet formation, preventing NF-κB activation upon LPS stimulation. In a septic shock model, TRAF6 depletion rescued the augmented inflammatory phenotype in mice with myeloid cell-specific deletion of Sufu. Conclusions: These findings implicated Sufu as an important inhibitor of TRAF6 in sepsis and suggest that therapeutics targeting Sufu-TRAF6 may greatly benefit the treatment of sepsis.

Transforming Growth Factor Beta Promotes Inflammation and Tumorigenesis in Smad4-Deficient Intestinal Epithelium in a YAP-Dependent Manner.

Transforming growth factor beta (TGF-ß), a multifunctional cytokine, plays critical roles in immune responses. However, the precise role of TGF-ß in colitis and colitis-associated cancer remains poorly defined. Here, it is demonstrated that TGF-ß promotes the colonic inflammation and related tumorigenesis in the absence of Smad family member 4 (Smad4). Smad4 loss in intestinal epithelium aggravates colitis and colitis-associated neoplasia induced by dextran sulfate sodium (DSS) and azoxymethane/dextran sulfate sodium (AOM/DSS), leading to over-activated immune responses and increased TGF-ß1 levels. In Smad4-deficient organoids, TGF-ß1 stimulates spheroid formation and impairs intestinal stem cell proliferation and lineage specification. YAP, whose expression is directly upregulated by TGF-ß1 after Smad4 deletion, mediates the effect of TGF-ß1 by interacting with Smad2/3. Attenuation of YAP/TAZ prevents TGF-ß1-induced spheroid formation in Smad4-/- organoids and alleviates colitis and colitis-associated cancer in Smad4-deficient mice. Collectively, these results highlight an integral role of the TGF-ß/Smad4 axis in restraining intestinal inflammation and tumorigenesis and suggest TGF-ß or YAP signaling as therapeutic targets for these gastrointestinal diseases intervention.

Asynchronous and error-prone longitudinal data analysis via functional calibration.

In many longitudinal settings, time-varying covariates may not be measured at the same time as responses and are often prone to measurement error. Naive last-observation-carried-forward methods incur estimation biases, and existing kernel-based methods suffer from slow convergence rates and large variations. To address these challenges, we propose a new functional calibration approach to efficiently learn longitudinal covariate processes based on sparse functional data with measurement error. Our approach, stemming from functional principal component analysis, calibrates the unobserved synchronized covariate values from the observed asynchronous and error-prone covariate values, and is broadly applicable to asynchronous longitudinal regression with time-invariant or time-varying coefficients. For regression with time-invariant coefficients, our estimator is asymptotically unbiased, root-n consistent, and asymptotically normal; for time-varying coefficient models, our estimator has the optimal varying coefficient model convergence rate with inflated asymptotic variance from the calibration. In both cases, our estimators present asymptotic properties superior to the existing methods. The feasibility and usability of the proposed methods are verified by simulations and an application to the Study of Women's Health Across the Nation, a large-scale multisite longitudinal study on women's health during midlife.

Minimax Powerful Functional Analysis of Covariance Tests: with Application to Longitudinal Genome-Wide Association Studies.

We model the Alzheimer's Disease-related phenotype response variables observed on irregular time points in longitudinal Genome-Wide Association Studies as sparse functional data and propose nonparametric test procedures to detect functional genotype effects while controlling the confounding effects of environmental covariates. Our new functional analysis of covariance tests are based on a seemingly unrelated kernel smoother, which takes into account the within-subject temporal correlations, and thus enjoy improved power over existing functional tests. We show that the proposed test combined with a uniformly consistent nonparametric covariance function estimator enjoys the Wilks phenomenon and is minimax most powerful. Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, where an application of the proposed test lead to the discovery of new genes that may be related to Alzheimer's Disease.

Semiparametric function-on-function quantile regression model with dynamic single-index interactions.

In this paper we propose a new semiparametric function-on-function quantile regression model with time-dynamic single-index interactions. Our model is very flexible in taking into account of the nonlinear time-dynamic interaction effects of the multivariate longitudinal/functional covariates on the longitudinal response, that most existing quantile regression models for longitudinal data are special cases of our proposed model. We propose to approximate the bivariate nonparametric coefficient functions by tensor product B-splines, and employ a check loss minimization approach to estimate the bivariate coefficient functions and the index parameter vector. Under some mild conditions, we establish the asymptotic normality of the estimated single-index coefficients using projection orthogonalization technique, and obtain the convergence rates of the estimated bivariate coefficient functions. Furthermore, we propose a score test to examine whether there exist interaction effects between the covariates. The finite sample performance of the proposed method is illustrated by Monte Carlo simulations and an empirical data analysis.

Unified Principal Component Analysis for Sparse and Dense Functional Data under Spatial Dependency.

We consider spatially dependent functional data collected under a geostatistics setting, where locations are sampled from a spatial point process. The functional response is the sum of a spatially dependent functional effect and a spatially independent functional nugget effect. Observations on each function are made on discrete time points and contaminated with measurement errors. Under the assumption of spatial stationarity and isotropy, we propose a tensor product spline estimator for the spatio-temporal covariance function. When a coregionalization covariance structure is further assumed, we propose a new functional principal component analysis method that borrows information from neighboring functions. The proposed method also generates nonparametric estimators for the spatial covariance functions, which can be used for functional kriging. Under a unified framework for sparse and dense functional data, infill and increasing domain asymptotic paradigms, we develop the asymptotic convergence rates for the proposed estimators. Advantages of the proposed approach are demonstrated through simulation studies and two real data applications representing sparse and dense functional data, respectively.

Causal mediation analysis between resistance exercise and reduced risk of cardiovascular disease based on the Aerobics Center Longitudinal Study.

Health benefits of resistance exercise (RE), particularly in lowering cardiovascular disease (CVD) risks, are less understood in comparison to aerobic exercise (AE). Motivated by big data from the Aerobics Center Longitudinal Study (ACLS), we study the direct and indirect effects of RE on CVD risks. The primary outcome in our study, total CVD events (CVD morbidity and mortality combined), is modeled as a survival outcome. To investigate the pathway from RE to CVD outcome through potential mediators, we first conduct causal mediation analysis based on marginal structural models (MSMs). To fully account the information from repeated measurements of the mediators, we also adopt a joint model of the CVD survival outcome and multiple longitudinal trajectories of the mediators. Results show statistically significant direct effects of RE and AE on lowering the risk of total CVD events under each pathway. The causal effect of RE and AE on CVD risk is also studied across different age and gender groups. Furthermore, we produce a ranking for the relative importance of the potential risk factors for CVD, with total cholesterol ranking the highest.

Predictive Functional Linear Models with Diverging Number of Semiparametric Single-Index Interactions.

When predicting crop yield using both functional and multivariate predictors, the prediction performances benefit from the inclusion of the interactions between the two sets of predictors. We assume the interaction depends on a nonparametric, single-index structure of the multivariate predictor and reduce each functional predictor's dimension using functional principal component analysis (FPCA). Allowing the number of FPCA scores to diverge to infinity, we consider a sequence of semiparametric working models with a diverging number of predictors, which are FPCA scores with estimation errors. We show that the parametric component of the model is root-n consistent and asymptotically normal, the overall prediction error is dominated by the estimation of the nonparametric interaction function, and justify a CV-based procedure to select the tuning parameters.

Isorhamnetin Suppresses Human Gastric Cancer Cell Proliferation through Mitochondria-Dependent Apoptosis.

Derivates of natural products have been wildly utilized in the treatment of malignant tumors. Isorhamnetin (ISO), a most important active ingredient derived from flavonoids, shows great potential in tumor therapy. However, the therapeutic effects of ISO on gastric cancer (GC) remain unclear. Here, we demonstrate that ISO treatment dramatically inhibited the proliferation of two types of GC cells (AGS-1 and HGC-27) both in vitro and in vivo in time- and dose-dependent manners. These results are consistent with the transcriptomic analysis of ISO-treated GC cells, which yielded hundreds of differentially expressed genes that were enriched with cell growth and apoptosis. Mechanically, ISO treatment initiated the activation of caspase-3 cascade and elevated the expression of mitochondria-associated Bax/Bcl-2, cytosolic cytochrome c, followed by the activation of the cleavage of caspase-3 as well as poly ADP-ribose polymerase (PARP), resulting in the severe reduction of the mitochondrial potential and the accumulation of reactive oxygen species (ROS), while pre-treatment of the caspase-3 inhibitor could block the anti-tumor effect. Therefore, these results indicate that ISO treatment induces the apoptosis of GC cells through the mitochondria-dependent apoptotic pathway, providing a potential strategy for clinical GC therapy.

ESTIMATION FOR EXTREME CONDITIONAL QUANTILES OF FUNCTIONAL QUANTILE REGRESSION.

Quantile regression as an alternative to modeling the conditional mean function provides a comprehensive picture of the relationship between a response and covariates. It is particularly attractive in applications focused on the upper or lower conditional quantiles of the response. However, conventional quantile regression estimators are often unstable at the extreme tails, owing to data sparsity, especially for heavy-tailed distributions. Assuming that the functional predictor has a linear effect on the upper quantiles of the response, we develop a novel estimator for extreme conditional quantiles using a functional composite quantile regression based on a functional principal component analysis and an extrapolation technique from extreme value theory. We establish the asymptotic normality of the proposed estimator under some regularity conditions, and compare it with other estimation methods using Monte Carlo simulations. Finally, we demonstrate the proposed method by empirically analyzing two real data sets.

From multivariate to functional data analysis: fundamentals, recent developments, and emerging areas.

Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for Journal of Multivariate Analysis. We review some fundamental concepts of FDA, their origins and connections from multivariate analysis, and some of its recent developments, including multi-level functional data analysis, high-dimensional functional regression, and dependent functional data analysis. We also discuss the impact of these new methodology developments on genetics, plant science, wearable device data analysis, image data analysis, and business analytics. Two real data examples are provided to motivate our discussions.

Extreme quantile estimation for partial functional linear regression models with heavy-tailed distributions.

In this article, we propose a novel estimator of extreme conditional quantiles in partial functional linear regression models with heavy-tailed distributions. The conventional quantile regression estimators are often unstable at the extreme tails due to data sparsity, especially for heavy-tailed distributions. We first estimate the slope function and the partially linear coefficient using a functional quantile regression based on functional principal component analysis, which is a robust alternative to the ordinary least squares regression. The extreme conditional quantiles are then estimated by using a new extrapolation technique from extreme value theory. We establish the asymptotic normality of the proposed estimator and illustrate its finite sample performance by simulation studies and an empirical analysis of diffusion tensor imaging data from a cognitive disorder study.

Dans cet article, un nouvel estimateur de quantiles conditionnels extrêmes est élaboré dans le cadre de modèles de régression linéaire fonctionnelle partielle avec des distributions à queues lourdes. Il est bien connu que la rareté des observations dans les ailes extrêmes de distributions à queues lourdes rend souvent les estimateurs de régression quantile usuels instables. Pour parer à la non robustesse des moindres carrés classiques, les auteurs ont commencé par estimer la fonction de pente et le coefficient partiellement linéaire d'une régression quantile en ayant recours à une approche basée sur l'analyse en composantes principales fonctionnelles. Ensuite, ils ont estimé les quantiles conditionnels extrêmes à l'aide d'une nouvelle technique d'extrapolation issue de la théorie des valeurs extrêmes. En plus d'établir la normalité asymptotique de l'estimateur proposé, les auteurs illustrent ses bonnes performances à distance finie par le biais d'une étude de simulation et une mise en oeuvre pratique sur les données d'imagerie de diffusion par tenseurs provenant d'une étude portant sur des troubles cognitifs.

VLM catecholaminergic neurons control tumor growth by regulating CD8+ T cells.

It is known that tumor growth can be influenced by the nervous system. It is not known, however, if tumors communicate directly with the central nervous system (CNS) or if such interactions may impact tumor growth. Here, we report that ventrolateral medulla (VLM) catecholaminergic (CA) neurons in the mouse brain are activated in tumor-bearing mice and the activity of these neurons significantly alter tumor growth in multiple syngeneic and spontaneous mouse tumor models. Specific ablation of VLM CA neurons by a dopamine-ß-hydroxylase (DBH) promotor-activated apoptosis-promoting caspase-3 in Dbh-Cre mice as well as inhibition of these neurons by a chemogenetic method slowed tumor progression. Consistently, chemogenetic activation of VLM CA neurons promoted tumor growth. The tumor inhibition effect of VLM CA neuron ablation is mitigated in Dbh-Cre;Rag1-/- mice, indicating that this regulatory effect is mediated by the adaptive immune system. Specific depletion of CD8+ T cells using an anti-CD8+ antibody also mitigated the tumor suppression resulting from the VLM CA neuron ablation. Finally, we showed that the VLM CA neuronal ablation had an additive antitumor effect with paclitaxel treatment. Collectively, our study uncovered the role of VLM CA neurons in the mouse brain in controlling tumor growth in the mouse body.

Growth dynamics and heritability for plant high-throughput phenotyping studies using hierarchical functional data analysis.

In modern high-throughput plant phenotyping, images of plants of different genotypes are repeatedly taken throughout the growing season, and phenotypic traits of plants (e.g., plant height) are extracted through image processing. It is of interest to recover whole trait trajectories and their derivatives at both genotype and plant levels based on observations made at irregular discrete time points. We propose to model trait trajectories using hierarchical functional principal component analysis (HFPCA) and show that the problem of recovering derivatives of the trajectories is reduced to estimating derivatives of eigenfunctions, which is solved by differentiating eigenequations. Based on HFPCA, we also propose a new measure for the broad-sense heritability by allowing it to vary over time during plant growth. Simulation studies show that the proposed procedure performs better than its competitors in terms of recovering both trait trajectories and their derivatives. Interesting characteristics of plant growth and heritability dynamics are revealed in the application to a modern plant phenotyping study.

Non-muscle myosin heavy chain 9 maintains intestinal homeostasis by preventing epithelium necroptosis and colitis adenoma formation.

Non-muscle myosin IIA plays an important role in cell adhesion, cell migration, and tissue architecture. We previously showed that low activity of the heavy chain of non-muscle myosin II Myh9 is beneficial to LGR5+ intestinal stem cell maintenance. However, the function of Myh9 in adult mouse intestinal epithelium is largely unclear. In this study, we used the inducible Villin-creERT2 knockout approach to delete Myh9 in adult mouse intestinal epithelium and observed that homozygous deletion of Myh9 causes colitis-like morphologic changes in intestine, leads to a high sensitivity to dextran sulfate sodium and promotes colitis-related adenoma formation in the colon. Myh9 deletion disturbs cell junctions and impairs intestinal lumen barrier integrity, promoting the necroptosis of epithelial cells. Consistently, these changes can be partially rescued by Ripk3 knockout. Our results indicate that Myh9 is required for the maintenance of intestinal epithelium integrity and the prevention of cell necroptosis.