TRAF6 and TRAF2/3 Binding Motifs in CD40 Differentially Regulate B Cell Function in T-Dependent Antibody Responses and Dendritic Cell Function in Experimental Autoimmune Encephalomyelitis.

Expression of the costimulatory molecule CD40 on both B cells and dendritic cells (DCs) is required for induction of experimental autoimmune encephalomyelitis (EAE), and cell-autonomous CD40 expression on B cells is required for primary T-dependent (TD) Ab responses. We now ask whether the function of CD40 expressed by different cell types in these responses is mediated by the same or different cytoplasmic domains. CD40 has been reported to possess multiple cytoplasmic domains, including distinct TRAF6 and TRAF2/3 binding motifs. To elucidate the in vivo function of these motifs in B cells and DCs involved in EAE and TD germinal center responses, we have generated knock-in mice containing distinct CD40 cytoplasmic domain TRAF-binding site mutations and have used these animals, together with bone marrow chimeric mice, to assess the roles that these motifs play in CD40 function. We found that both TRAF2/3 and TRAF6 motifs of CD40 are critically involved in EAE induction and demonstrated that this is mediated by a role of both motifs for priming of pathogenic T cells by DCs. In contrast, the TRAF2/3 binding motif, but not the TRAF6 binding motif, is required for B cell CD40 function in TD high-affinity Ab responses. These data demonstrate that the requirements for expression of specific TRAF-binding CD40 motifs differ for B cells or DCs that function in specific immune responses and thus identify targets for intervention to modulate these responses.

Automating the Detection of IV Fluid Contamination Using Unsupervised Machine Learning.

BACKGROUND: Intravenous (IV) fluid contamination is a common cause of preanalytical error that can delay or misguide treatment decisions, leading to patient harm. Current approaches for detecting contamination rely on delta checks, which require a prior result, or manual technologist intervention, which is inefficient and vulnerable to human error. Supervised machine learning may provide a means to detect contamination, but its implementation is hindered by its reliance on expert-labeled training data. An automated approach that is accurate, reproducible, and practical is needed. METHODS: A total of 25 747 291 basic metabolic panel (BMP) results from 312 721 patients were obtained from the laboratory information system (LIS). A Uniform Manifold Approximation and Projection (UMAP) model was trained and tested using a combination of real patient data and simulated IV fluid contamination. To provide an objective metric for classification, an "enrichment score" was derived and its performance assessed. Our current workflow was compared to UMAP predictions using expert chart review. RESULTS: UMAP embeddings from real patient results demonstrated outliers suspicious for IV fluid contamination when compared with the simulated contamination's embeddings. At a flag rate of 3 per 1000 results, the positive predictive value (PPV) was adjudicated to be 0.78 from 100 consecutive positive predictions. Of these, 58 were previously undetected by our current clinical workflows, with 49 BMPs displaying a total of 56 critical results. CONCLUSIONS: Accurate and automatable detection of IV fluid contamination in BMP results is achievable without curating expertly labeled training data.

CD40 Drives Central Nervous System Autoimmune Disease by Inducing Complementary Effector Programs via B Cells and Dendritic Cells.

Costimulatory CD40 plays an essential role in autoimmune diseases, including experimental autoimmune encephalomyelitis (EAE), a murine model of human multiple sclerosis (MS). However, how CD40 drives autoimmune disease pathogenesis is not well defined. Here, we used a conditional knockout approach to determine how CD40 orchestrates a CNS autoimmune disease induced by recombinant human myelin oligodendrocyte glycoprotein (rhMOG). We found that deletion of CD40 in either dendritic cells (DCs) or B cells profoundly reduced EAE disease pathogenesis. Mechanistically, CD40 expression on DCs was required for priming pathogenic Th cells in peripheral draining lymph nodes and promoting their appearance in the CNS. By contrast, B cell CD40 was essential for class-switched MOG-specific Ab production, which played a crucial role in disease pathogenesis. In fact, passive transfer of MOG-immune serum or IgG into mice lacking CD40 on B cells but not DCs reconstituted autoimmune disease, which was associated with inundation of the spinal cord parenchyma by Ig and complement. These data demonstrate that CD40 supports distinct effector programs in B cells and DCs that converge to drive a CNS autoimmune disease and identify targets for intervention.

The effects of preconception and early gestation SARS-CoV-2 infection on pregnancy outcomes and placental pathology.

OBJECTIVE: To evaluate if peri-pregnancy timing of a PCR+ test for SARS-CoV-2 RNA affects pregnancy outcomes and placental pathology. METHODS: This is a retrospective cohort study conducted in a tertiary center. Pregnancy outcomes and placental pathology were compiled for women who tested positive for SARS-CoV-2 RNA from a nasopharyngeal swab assessed by RT-PCR. The population comprised four groups that were PCR+ preconception (T0) or in the 1st (T1), 2nd (T2), or 3rd (T3) trimester of pregnancy. A fifth, control group (TC) tested PCR- for SARS-CoV-2 before delivery. RESULTS: Seventy-one pregnancies were studied. The T0 group exhibited lower gestational ages at delivery, had infants with the lowest birth weights, the highest rate of pregnancy loss before 20 weeks. Features of maternal vascular malperfusion and accelerated villous maturation were prominent findings in the histopathology of placentas from women PCR+ for SARS-CoV-2 RNA, especially in the T0 and the T1 groups. CONCLUSION: Women at highest risk for pregnancy complications are those who test PCR+ for viral RNA preconception or during first trimester of pregnancy.

A multi-modal diagnostic model improves detection of cardiac amyloidosis among patients with diagnostic confirmation by cardiac biopsy.

BACKGROUND: Timely recognition of cardiac amyloidosis is clinically important, but the diagnosis is frequently delayed. OBJECTIVES: We sought to identify a multi-modality approach with the highest diagnostic accuracy in patients evaluated by cardiac biopsy, the diagnostic gold standard. METHODS: Consecutive patients (N = 242) who underwent cardiac biopsy for suspected amyloidosis within an 18-year period were retrospectively identified. Cardiac biomarker, ECG, and echocardiography results were examined for correlation with biopsy-proven disease. A prediction model for cardiac amyloidosis was derived using multivariable logistic regression. RESULTS: The overall cohort was characterized by elevated BNP (median 727 ng/mL), increased left ventricular wall thickness (IWT; median 1.7 cm), and reduced voltage-to-mass ratio (median 0.06 mm/[g/m2]). One hundred and thirteen patients (46%) had either light chain (n = 53) or transthyretin (n = 60) amyloidosis by cardiac biopsy. A prediction model including age, relative wall thickness, left atrial pressure by E/e', and low limb lead voltage (<0.5 mV) showed good discrimination for cardiac amyloidosis with an optimism-corrected c-index of 0.87 (95% CI 0.83-0.92). The diagnostic accuracy of this model (79% sensitivity, 84% specificity) surpassed that of traditional screening parameters, such as IWT in the absence of left ventricular hypertrophy on ECG (98% sensitivity, 20% specificity) and IWT with low limb lead voltage (49% sensitivity, 91% specificity). CONCLUSION: Among patients with an advanced infiltrative cardiomyopathy phenotype, traditional biomarker, ECG, and echocardiography-based screening tests have limited individual diagnostic utility for cardiac amyloidosis. A prediction algorithm including age, relative wall thickness, E/e', and low limb lead voltage improves the detection of cardiac biopsy-proven disease.

Optimizing management of replacement fluids for therapeutic plasma exchange: Use of an automated mathematical model to predict post-procedure fibrinogen and antithrombin levels in high-risk patients.

BACKGROUND: Therapeutic plasma exchange (TPE) utilizes an extracorporeal circuit to remove pathologic proteins causing serious illness. When processing a patient's entire blood volume through an extracorporeal circuit, proteins responsible for maintaining hemostatic system homeostasis can reach critically low levels if replacement fluid types and volumes are not carefully titrated, which may increase complications. METHODS: The charts from 27 patients undergoing 46 TPE procedures were reviewed to evaluate the accuracy of our predictive mathematical model, utilizing the following patient information: weight, hematocrit, pre- and post-TPE factor levels (fibrinogen, n = 46, and antithrombin, n = 23), process volume and volumes of fluids (eg, plasma, albumin, and normal saline) administered during TPE and adverse events during and after TPE. RESULTS: Altogether, 25% of patients experienced minor adverse events that resolved spontaneously or with management. There were no bleeding or thrombotic complications. The mean difference between predicted and measured post-TPE fibrinogen concentrations was -0.29 mg/dL (SD ±23.0, range -59 to 37), while percent difference between measured and predicted fibrinogen concentration was 0.94% (SD ±10.8, range of -22 to 19). The mean difference between predicted and measured post-TPE antithrombin concentrations were 0.89% activity (SD ±10.0, range -23 to 14), while mean percent difference between predicted and measured antithrombin concentrations was 3.87% (SD ±14.5, range -25 to 38). CONCLUSIONS: Our model reliably predicts post-TPE fibrinogen and antithrombin concentrations, and may help optimize patient management and attenuate complications.

Large-Scale Assessment of Scan-Time Variability and Multiple-Procedure Efficiency for Cross-Sectional Neuroradiological Exams in Clinical Practice.

Scheduling of CT and MR exams requires reasonable estimates for expected scan duration. However, scan-time variability and efficiency gains from combining multiple exams are not quantitatively well characterized. In this work, we developed an informatics approach to quantify typical duration, duration variability, and multiple-procedure efficiency on a large scale, and used the approach to analyze 48,766 CT- and MR-based neuroradiological exams performed over one year. We found MR exam durations demonstrated higher absolute variability, but lower relative variability and lower multiple-procedure efficiency, compared to CT exams (p < 0.001). Our approach enables quantification of real-world operational performance and variability to inform optimal patient scheduling, efficient resource utilization, and sustainable service planning.

In Silico Docking of Alkylphosphocholine Analogs to Human Serum Albumin Predicts Partitioning and Pharmacokinetics.

Alkylphosphocholine (APC) analogs are a novel class of broad-spectrum tumor-targeting agents that can be used for both diagnosis and treatment of cancer. The potential for clinical translation for APC analogs will strongly depend on their pharmacokinetic (PK) profiles. The aim of this work was to understand how the chemical structures of various APC analogs impact binding and PK. To achieve this aim, we performed in silico docking analysis, in vitro and in vivo partitioning experiments, and in vivo PK studies. Our results have identified 7 potential high-affinity binding sites of these compounds on human serum albumin (HSA) and suggest that the size of the functional group directly influences the albumin binding, partitioning, and PK. Namely, the bulkier the functional groups, the weaker the agent binds to albumin, the more the agent partitions onto lipoproteins, and the less time the agent spends in circulation. The results of these experiments provide novel molecular insights into the binding, partitioning, and PK of this class of compounds and similar molecules as well as suggest pharmacological strategies to alter their PK profiles. Importantly, our methodology may provide a way to design better drugs by better characterizing the PK profile for lead compound optimization.

Performance of a Modern Glucose Meter in ICU and General Hospital Inpatients: 3 Years of Real-World Paired Meter and Central Laboratory Results.

OBJECTIVE: Due to accuracy concerns, the Food and Drug Administration issued guidances to manufacturers that resulted in Center for Medicare and Medicaid Services stating that the use of meters in critically ill patients is "off-label" and constitutes "high complexity" testing. This is causing significant workflow problems in ICUs nationally. We wished to determine whether real-world accuracy of modern glucose meters is worse in ICU patients compared with non-ICU inpatients. DESIGN: We reviewed glucose results over the preceding 3 years, comparing results from paired glucose meter and central laboratory tests performed within 60 minutes of each other in ICU versus non-ICU settings. SETTING: Seven ICU and 30 non-ICU wards at a 1,300-bed academic hospital in the United States. SUBJECTS: A total of 14,763 general medicine/surgery inpatients and 20,970 ICU inpatients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Compared meter results with near simultaneously performed laboratory results from the same patient by applying the 2016 U.S. Food and Drug Administration accuracy criteria, determining mean absolute relative difference and examining where paired results fell within the Parkes consensus error grid zones. A higher percentage of glucose meter results from ICUs than from non-ICUs passed 2016 Food and Drug Administration accuracy criteria (p < 10) when comparing meter results with laboratory results. At 1 minute, no meter result from ICUs posed dangerous or significant risk by error grid analysis, whereas at 10 minutes, less than 0.1% of ICU meter results did, which was not statistically different from non-ICU results. CONCLUSIONS: Real-world accuracy of modern glucose meters is at least as accurate in the ICU setting as in the non-ICU setting at our institution.

Long-term effects of delayed-release dimethyl fumarate in multiple sclerosis: Interim analysis of ENDORSE, a randomized extension study.

BACKGROUND: Delayed-release dimethyl fumarate (DMF) demonstrated strong efficacy and a favorable benefit-risk profile for patients with relapsing-remitting multiple sclerosis (RRMS) in phase 3 DEFINE/CONFIRM studies. ENDORSE is an ongoing long-term extension of DEFINE/CONFIRM. OBJECTIVE: We report efficacy and safety results of a 5-year interim analysis of ENDORSE (2 years DEFINE/CONFIRM; minimum 3 years ENDORSE). METHODS: In ENDORSE, patients randomized to DMF 240 mg twice (BID) or thrice daily (TID) in DEFINE/CONFIRM continued this dosage, and those initially randomized to placebo (PBO) or glatiramer acetate (GA) were re-randomized to DMF 240 mg BID or TID. RESULTS: For patients continuing DMF BID (BID/BID), annualized relapse rates were 0.202, 0.163, 0.139, 0.143, and 0.138 (years 1-5, respectively) and 63%, 73%, and 88% were free of new or enlarging T2 hyperintense lesions, new T1 hypointense lesions, and gadolinium-enhanced lesions, respectively, at year 5. Adverse events (AEs; serious adverse events (SAEs)) were reported in 91% (22%; BID/BID), 95% (24%; PBO/BID), and 88% (16%; GA/BID) of the patients. One case of progressive multifocal leukoencephalopathy was reported in the setting of severe, prolonged lymphopenia. CONCLUSION: Treatment with DMF was associated with continuously low clinical and magnetic resonance imaging (MRI) disease activity in patients with RRMS. These interim data demonstrate a sustained treatment benefit and an acceptable safety profile with DMF.

A circadian gene expression atlas in mammals: implications for biology and medicine.

To characterize the role of the circadian clock in mouse physiology and behavior, we used RNA-seq and DNA arrays to quantify the transcriptomes of 12 mouse organs over time. We found 43% of all protein coding genes showed circadian rhythms in transcription somewhere in the body, largely in an organ-specific manner. In most organs, we noticed the expression of many oscillating genes peaked during transcriptional "rush hours" preceding dawn and dusk. Looking at the genomic landscape of rhythmic genes, we saw that they clustered together, were longer, and had more spliceforms than nonoscillating genes. Systems-level analysis revealed intricate rhythmic orchestration of gene pathways throughout the body. We also found oscillations in the expression of more than 1,000 known and novel noncoding RNAs (ncRNAs). Supporting their potential role in mediating clock function, ncRNAs conserved between mouse and human showed rhythmic expression in similar proportions as protein coding genes. Importantly, we also found that the majority of best-selling drugs and World Health Organization essential medicines directly target the products of rhythmic genes. Many of these drugs have short half-lives and may benefit from timed dosage. In sum, this study highlights critical, systemic, and surprising roles of the mammalian circadian clock and provides a blueprint for advancement in chronotherapy.

Clinicopathogenomic analysis of mismatch repair proficient colorectal adenocarcinoma uncovers novel prognostic subgroups with differing patterns of genetic evolution.

Cancer somatic genetic evolution is a direct contributor to heterogeneity at the clonal and molecular level in colorectal adenocarcinoma (COAD). We sought to determine the extent to which genetic evolution may be detected in COAD in routinely obtained single clinical specimens and establish clinical significance with regard to clinicopathologic and outcome data. One hundred and twenty three cases of routinely collected mismatch repair proficient COAD were sequenced on the Illumina Truseq Amplicon assay. Measures of intratumoral heterogeneity and the preferential timing of mutational events were assessed and compared to clinicopathologic data. Survival subanalysis was performed on 55 patients. Patient age (p = 0.013) and specimen percent tumor (p = 0.033) was associated with clonal diversity, and biopsy (p = 0.044) and metastasis (p = 0.044) returned fewer mutations per case. APC and TP53 mutations preferentially occurred early while alterations in FBXW7, FLT3, SMAD4, GNAS and PTEN preferentially occurred as late events. Temporal heterogeneity was evident in KRAS and PIK3CA mutations. Hierarchical clustering revealed a TP53 mutant subtype and a MAPK-PIK3CA subtype with differing patterns of late mutational events. Survival subanalysis showed a decreased median progression free survival for the MAPK-PIK3CA subtype (8 months vs. 13 months; univariate logrank p = 0.0380, cox model p= 0.018). Neoadjuvant therapy associated mutations were found for ERBB2 (p = 0.0481) and FBXW7 (p = 0.015). Our data indicate novel molecular subtypes of mismatch repair proficient COAD display differing patterns of genetic evolution which correlate with clinical outcomes. Furthermore, we report treatment acquired and/or selected mutations in ERBB2 and FBXW7.

Analysis of Cancer-Targeting Alkylphosphocholine Analogue Permeability Characteristics Using a Human Induced Pluripotent Stem Cell Blood-Brain Barrier Model.

Cancer-targeting alkylphosphocholine (APC) analogues are being clinically developed for diagnostic imaging, intraoperative visualization, and therapeutic applications. These APC analogues derived from chemically synthesized phospholipid ethers were identified and optimized for cancer-targeting specificity using extensive structure-activity studies. While they strongly label human brain cancers associated with disrupted blood-brain barriers (BBB), APC permeability across intact BBB remains unknown. Three of our APC analogues, CLR1404 (PET radiotracer), CLR1501 (green fluorescence), and CLR1502 (near-infrared fluorescence), were tested for permeability across a BBB model composed of human induced pluripotent stem cell-derived brain microvascular endothelial cells (iPSC-derived BMECs). This in vitro BBB system has reproducibly consistent high barrier integrity marked by high transendothelial electrical resistance (TEER > 1500 Ω-cm(2)) and functional expression of drug efflux transporters. The radioiodinated and fluorescent APC analogues demonstrated fairly low permeability across the iPSC-BMEC (35 ± 5.7 (CLR1404), 54 ± 3.2 (CLR1501), and 26 ± 4.9 (CLR1502) × 10(-5) cm/min) compared with BBB-impermeable sucrose (13 ± 2.5) and BBB-permeable diazepam (170 ± 29). Only the fluorescent APC analogues (CLR1501, CLR1502) underwent BCRP and MRP polarized drug efflux transport in the brain-to-blood direction of the BBB model, and this efflux can be specifically blocked with pharmacological inhibition. None of the tested APC analogues appeared to undergo substantial P-gp transport. Limited permeability of the APC analogues across an intact BBB into normal brain likely contributes to the high tumor to background ratios observed in initial human trials. Moreover, addition of fluorescent moieties to APCs resulted in greater BMEC efflux via MRP and BCRP, and may affect fluorescence-guided applications. Overall, the characterization of APC analogue permeability across human BBB is significant for advancing future brain tumor-targeted applications of these agents.

Detecting the H3F3A mutant allele found in high-grade pediatric glioma by real-time PCR.

Diffuse intrinsic pontine glioma (DIPG) is an aggressive pediatric brain tumor with a median survival of 1 year after diagnosis. It has been reported recently that about 80% of DIPG cases and 70% of midline glioblastomas contain a mutation at one allele of the H3F3A gene (encoding histone H3 variant H3.3), replacing the lysine 27 with methionine (K27M). In order to facilitate diagnosis of DIPG patients, a quick and reliable method to identify the H3F3A K27M mutation is needed. Here, we describe a real-time PCR-based procedure involving a mutant-specific primer, a blocker oligonucleotide, and a reverse primer that can differentiate samples with H3F3A K27M mutation from those that do not. We first tested four different mutant-specific primers for their ability to selectively amplify H3F3A K27M-mutant allele and found that one primer amplified the mutant allele more efficiently than the rest. We then determined the optimal concentration of blocker oligo that significantly improved amplification of the H3F3A K27M-mutant allele. Using this optimized real-time PCR assay, we analyzed eleven samples, two of which containing H3F3A K27M mutation, and found that these two samples were differentially amplified from the nine others. In addition, we were able to discern the H3F3A K27M mutation in a newly obtained pediatric brainstem glioblastoma sample whose H3.3 status was not known previously, and in three other DIPG samples as well as paraffin embedded samples. These results demonstrate that we have developed a new reliable procedure for detecting the H3F3A K27M mutation in pediatric glioblastoma patient samples.

BDIS-SLAM: a lightweight CPU-based dense stereo SLAM for surgery.

PURPOSE: Common dense stereo simultaneous localization and mapping (SLAM) approaches in minimally invasive surgery (MIS) require high-end parallel computational resources for real-time implementation. Yet, it is not always feasible since the computational resources should be allocated to other tasks like segmentation, detection, and tracking. To solve the problem of limited parallel computational power, this research aims at a lightweight dense stereo SLAM system that works on a single-core CPU and achieves real-time performance (more than 30 Hz in typical scenarios). METHODS: A new dense stereo mapping module is integrated with the ORB-SLAM2 system and named BDIS-SLAM. Our new dense stereo mapping module includes stereo matching and 3D dense depth mosaic methods. Stereo matching is achieved with the recently proposed CPU-level real-time matching algorithm Bayesian Dense Inverse Searching (BDIS). A BDIS-based shape recovery and a depth mosaic strategy are integrated as a new thread and coupled with the backbone ORB-SLAM2 system for real-time stereo shape recovery. RESULTS: Experiments on in vivo data sets show that BDIS-SLAM runs at over 30 Hz speed on modern single-core CPU in typical endoscopy/colonoscopy scenarios. BDIS-SLAM only consumes around an additional 12 % time compared with the backbone ORB-SLAM2. Although our lightweight BDIS-SLAM simplifies the process by ignoring deformation and fusion procedures, it can provide a usable dense mapping for modern MIS on computationally constrained devices. CONCLUSION: The proposed BDIS-SLAM is a lightweight stereo dense SLAM system for MIS. It achieves 30 Hz on a modern single-core CPU in typical endoscopy/colonoscopy scenarios (image size around 640 × 480 ). BDIS-SLAM provides a low-cost solution for dense mapping in MIS and has the potential to be applied in surgical robots and AR systems. Code is available at https://github.com/JingweiSong/BDIS-SLAM .

Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans.

Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for understanding tumor growth dynamics and designing personalized radiotherapy treatment plans.Mathematical models of GBM growth can complement the data in the prediction of spatial distributions of tumor cells. However, this requires estimating patient-specific parameters of the model from clinical data, which is a challenging inverse problem due to limited temporal data and the limited time between imaging and diagnosis. This work proposes a method that uses Physics-Informed Neural Networks (PINNs) to estimate patient-specific parameters of a reaction-diffusion PDE model of GBM growth from a single 3D structural MRI snapshot. PINNs embed both the data and the PDE into a loss function, thus integrating theory and data. Key innovations include the identification and estimation of characteristic non-dimensional parameters, a pre-training step that utilizes the non-dimensional parameters and a fine-tuning step to determine the patient specific parameters. Additionally, the diffuse domain method is employed to handle the complex brain geometry within the PINN framework. Our method is validated both on synthetic and patient datasets, and shows promise for real-time parametric inference in the clinical setting for personalized GBM treatment.

MicroRNA-217 promotes ethanol-induced fat accumulation in hepatocytes by down-regulating SIRT1.

Ethanol-mediated inhibition of hepatic sirtuin 1 (SIRT1) plays a crucial role in the pathogenesis of alcoholic fatty liver disease. Here, we investigated the underlying mechanisms of this inhibition by identifying a new hepatic target of ethanol action, microRNA-217 (miR-217). The role of miR-217 in the regulation of the effects of ethanol was investigated in cultured mouse AML-12 hepatocytes and in the livers of chronically ethanol-fed mice. In AML-12 hepatocytes and in mouse livers, chronic ethanol exposure drastically and specifically induced miR-217 levels and caused excess fat accumulation. Further studies revealed that overexpression of miR-217 in AML-12 cells promoted ethanol-mediated impairments of SIRT1 and SIRT1-regulated genes encoding lipogenic or fatty acid oxidation enzymes. More importantly, miR-217 impairs functions of lipin-1, a vital lipid regulator, in hepatocytes. Taken together, our novel findings suggest that miR-217 is a specific target of ethanol action in the liver and may present as a potential therapeutic target for treating human alcoholic fatty liver disease.

Ethanol administration exacerbates the abnormalities in hepatic lipid oxidation in genetically obese mice.

Alcohol consumption synergistically increases the risk and severity of liver damage in obese patients. To gain insight into cellular or molecular mechanisms underlying the development of fatty liver caused by ethanol-obesity synergism, we have carried out animal experiments that examine the effects of ethanol administration in genetically obese mice. Lean wild-type (WT) and obese (ob/ob) mice were subjected to ethanol feeding for 4 wk using a modified Lieber-DeCarli diet. After ethanol feeding, the ob/ob mice displayed much more pronounced changes in terms of liver steatosis and elevated plasma levels of alanine aminotransferase and aspartate aminotransferase, indicators of liver injury, compared with control mice. Mechanistic studies showed that ethanol feeding augmented the impairment of hepatic sirtuin 1 (SIRT1)-AMP-activated kinase (AMPK) signaling in the ob/ob mice. Moreover, the impairment of SIRT1-AMPK signaling was closely associated with altered hepatic functional activity of peroxisome proliferator-activated receptor γ coactivator-α and lipin-1, two vital downstream lipid regulators, which ultimately contributed to aggravated fatty liver observed in ethanol-fed ob/ob mice. Taken together, our novel findings suggest that ethanol administration to obese mice exacerbates fatty liver via impairment of the hepatic lipid metabolism pathways mediated largely by a central signaling system, the SIRT1-AMPK axis.