The Role of Interferon Regulatory Factors in Liver Diseases.

The interferon regulatory factors (IRFs) family comprises 11 members that are involved in various biological processes such as antiviral defense, cell proliferation regulation, differentiation, and apoptosis. Recent studies have highlighted the roles of IRF1-9 in a range of liver diseases, including hepatic ischemia-reperfusion injury (IRI), alcohol-induced liver injury, Con A-induced liver injury, nonalcoholic fatty liver disease (NAFLD), cirrhosis, and hepatocellular carcinoma (HCC). IRF1 is involved in the progression of hepatic IRI through signaling pathways such as PIAS1/NFATc1/HDAC1/IRF1/p38 MAPK and IRF1/JNK. The regulation of downstream IL-12, IL-15, p21, p38, HMGB1, JNK, Beclin1, ß-catenin, caspase 3, caspase 8, IFN-γ, IFN-ß and other genes are involved in the progression of hepatic IRI, and in the development of HCC through the regulation of PD-L1, IL-6, IL-8, CXCL1, CXCL10, and CXCR3. In addition, IRF3-PPP2R1B and IRF4-FSTL1-DIP2A/CD14 pathways are involved in the development of NAFLD. Other members of the IRF family also play moderately important functions in different liver diseases. Therefore, given the significance of IRFs in liver diseases and the lack of a comprehensive compilation of their molecular mechanisms in different liver diseases, this review is dedicated to exploring the molecular mechanisms of IRFs in various liver diseases.

Research progress of SIRTs activator resveratrol and its derivatives in autoimmune diseases.

Autoimmune diseases (AID) have emerged as prominent contributors to disability and mortality worldwide, characterized by intricate pathogenic mechanisms involving genetic, environmental, and autoimmune factors. In response to this challenge, a growing body of research in recent years has delved into genetic modifications, yielding valuable insights into AID prevention and treatment. Sirtuins (SIRTs) constitute a class of NAD-dependent histone deacetylases that orchestrate deacetylation processes, wielding significant regulatory influence over cellular metabolism, oxidative stress, immune response, apoptosis, and aging through epigenetic modifications. Resveratrol, the pioneering activator of the SIRTs family, and its derivatives have captured global scholarly interest. In the context of AID, these compounds hold promise for therapeutic intervention by modulating the SIRTs pathway, impacting immune cell functionality, suppressing the release of inflammatory mediators, and mitigating tissue damage. This review endeavors to explore the potential of resveratrol and its derivatives in AID treatment, elucidating their mechanisms of action and providing a comprehensive analysis of current research advancements and obstacles. Through a thorough examination of existing literature, our objective is to advocate for the utilization of resveratrol and its derivatives in AID treatment while offering crucial insights for the formulation of innovative therapeutic approaches.

The roles of nuclear orphan receptor NR2F6 in anti-viral innate immunity.

Proper transcription regulation by key transcription factors, such as IRF3, is critical for anti-viral defense. Dynamics of enhancer activity play important roles in many biological processes, and epigenomic analysis is used to determine the involved enhancers and transcription factors. To determine new transcription factors in anti-DNA-virus response, we have performed H3K27ac ChIP-Seq and identified three transcription factors, NR2F6, MEF2D and MAFF, in promoting HSV-1 replication. NR2F6 promotes HSV-1 replication and gene expression in vitro and in vivo, but not dependent on cGAS/STING pathway. NR2F6 binds to the promoter of MAP3K5 and activates AP-1/c-Jun pathway, which is critical for DNA virus replication. On the other hand, NR2F6 is transcriptionally repressed by c-Jun and forms a negative feedback loop. Meanwhile, cGAS/STING innate immunity signaling represses NR2F6 through STAT3. Taken together, we have identified new transcription factors and revealed the underlying mechanisms involved in the network between DNA viruses and host cells.

Cross-Modal Graph Semantic Communication Assisted by Generative AI in the Metaverse for 6G.

Recently, the development of the Metaverse has become a frontier spotlight, which is an important demonstration of the integration innovation of advanced technologies in the Internet. Moreover, artificial intelligence (AI) and 6G communications will be widely used in our daily lives. However, the effective interactions with the representations of multimodal data among users via 6G communications is the main challenge in the Metaverse. In this work, we introduce an intelligent cross-modal graph semantic communication approach based on generative AI and 3-dimensional (3D) point clouds to improve the diversity of multimodal representations in the Metaverse. Using a graph neural network, multimodal data can be recorded by key semantic features related to the real scenarios. Then, we compress the semantic features using a graph transformer encoder at the transmitter, which can extract the semantic representations through the cross-modal attention mechanisms. Next, we leverage a graph semantic validation mechanism to guarantee the exactness of the overall data at the receiver. Furthermore, we adopt generative AI to regenerate multimodal data in virtual scenarios. Simultaneously, a novel 3D generative reconstruction network is constructed from the 3D point clouds, which can transfer the data from images to 3D models, and we infer the multimodal data into the 3D models to increase realism in virtual scenarios. Finally, the experiment results demonstrate that cross-modal graph semantic communication, assisted by generative AI, has substantial potential for enhancing user interactions in the 6G communications and Metaverse.

Synaptic density patterns in early Alzheimer's disease assessed by independent component analysis.

Synaptic loss is a primary pathology in Alzheimer's disease and correlates best with cognitive impairment as found in post-mortem studies. Previously, we observed in vivo reductions of synaptic density with [11C]UCB-J PET (radiotracer for synaptic vesicle protein 2A) throughout the neocortex and medial temporal brain regions in early Alzheimer's disease. In this study, we applied independent component analysis to synaptic vesicle protein 2A-PET data to identify brain networks associated with cognitive deficits in Alzheimer's disease in a blinded data-driven manner. [11C]UCB-J binding to synaptic vesicle protein 2A was measured in 38 Alzheimer's disease (24 mild Alzheimer's disease dementia and 14 mild cognitive impairment) and 19 cognitively normal participants. [11C]UCB-J distribution volume ratio values were calculated with a whole cerebellum reference region. Principal components analysis was first used to extract 18 independent components to which independent component analysis was then applied. Subject loading weights per pattern were compared between groups using Kruskal-Wallis tests. Spearman's rank correlations were used to assess relationships between loading weights and measures of cognitive and functional performance: Logical Memory II, Rey Auditory Verbal Learning Test-long delay, Clinical Dementia Rating sum of boxes and Mini-Mental State Examination. We observed significant differences in loading weights among cognitively normal, mild cognitive impairment and mild Alzheimer's disease dementia groups in 5 of the 18 independent components, as determined by Kruskal-Wallis tests. Only Patterns 1 and 2 demonstrated significant differences in group loading weights after correction for multiple comparisons. Excluding the cognitively normal group, we observed significant correlations between the loading weights for Pattern 1 (left temporal cortex and the cingulate gyrus) and Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019), Mini-Mental State Examination (r = 0.48, P = 0.0055) and Logical Memory II score (r = 0.44, P = 0.013). For Pattern 2 (temporal cortices), significant associations were demonstrated between its loading weights and Logical Memory II score (r = 0.34, P = 0.0384). Following false discovery rate correction, only the relationship between the Pattern 1 loading weights with Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019) and Mini-Mental State Examination (r = 0.48, P = 0.0055) remained statistically significant. We demonstrated that independent component analysis could define coherent spatial patterns of synaptic density. Furthermore, commonly used measures of cognitive performance correlated significantly with loading weights for two patterns within only the mild cognitive impairment/mild Alzheimer's disease dementia group. This study leverages data-centric approaches to augment the conventional region-of-interest-based methods, revealing distinct patterns that differentiate between mild cognitive impairment and mild Alzheimer's disease dementia, marking a significant advancement in the field.

Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification.

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve the quality and quantitative accuracy of Ki images by utilizing deep learning techniques to reduce the noise in dynamic PET images. We propose a novel denoising technique, Population-based Deep Image Prior (PDIP), which integrates population-based prior information into the optimization process of Deep Image Prior (DIP). Specifically, the population-based prior image is generated from a supervised denoising model that is trained on a prompts-matched static PET dataset comprising 100 clinical studies. The 3D U-Net architecture is employed for both the supervised model and the following DIP optimization process. We evaluated the efficacy of PDIP for noise reduction in 25%-count and 100%-count dynamic PET images from 23 patients by comparing with two other baseline techniques: the Prompts-matched Supervised model (PS) and a conditional DIP (CDIP) model that employs the mean static PET image as the prior. Both the PS and CDIP models show effective noise reduction but result in smoothing and removal of small lesions. In addition, the utilization of a single static image as the prior in the CDIP model also introduces a similar tracer distribution to the denoised dynamic frames, leading to lower Ki in general as well as incorrect Ki in the descending aorta. By contrast, as the proposed PDIP model utilizes intrinsic image features from the dynamic dataset and a large clinical static dataset, it not only achieves comparable noise reduction as the supervised and CDIP models but also improves lesion Ki predictions.

Research progress on Sirtuins (SIRTs) family modulators.

Sirtuins (SIRTs) represent a class of nicotinamide adenine dinucleotide (NAD+)-dependent protein deacetylases that exert a crucial role in cellular signal transduction and various biological processes. The mammalian sirtuins family encompasses SIRT1 to SIRT7, exhibiting therapeutic potential in counteracting cellular aging, modulating metabolism, responding to oxidative stress, inhibiting tumors, and improving cellular microenvironment. These enzymes are intricately linked to the occurrence and treatment of diverse pathological conditions, including cancer, autoimmune diseases, and cardiovascular disorders. Given the significance of histone modification in gene expression and chromatin structure, maintaining the equilibrium of the sirtuins family is imperative for disease prevention and health restoration. Mounting evidence suggests that modulators of SIRTs play a crucial role in treating various diseases and maintaining physiological balance. This review delves into the molecular structure and regulatory functions of the sirtuins family, reviews the classification and historical evolution of SIRTs modulators, offers a systematic overview of existing SIRTs modulation strategies, and elucidates the regulatory mechanisms of SIRTs modulators (agonists and inhibitors) and their clinical applications. The article concludes by summarizing the challenges encountered in SIRTs modulator research and offering insights into future research directions.

Prevention of postoperative nausea and vomiting after orthognathic surgery: a scoping review.

INTRODUCTION: Postoperative nausea and vomiting (PONV) is one of the most common adverse events following orthognathic surgery. It's a distressing feeling for patients and continues to be the cause of postoperative complications such as bleeding, delayed healing, and wound infection. This scoping review aims to identify effective PONV prophylaxis strategies during orthognathic surgery that have emerged in the past 15 years. METHODS: We searched Pubmed, Cochrane Controlled Register of Trials, and Embase from 2008 to May 2023. Studies meeting the following criteria were eligible for inclusion: (1) recruited patients undergo any orthognathic surgery; (2) evaluated any pharmacologic or non-pharmacologic method to prevent PONV. Studies meeting the following criteria were excluded: (1) case series, review papers, or retrospective studies; (2) did not report our prespecified outcomes. RESULTS: Twenty-one studies were included in this review. Pharmacological methods for PONV prevention include ondansetron and dexamethasone (3 studies), peripheral nerve block technique (4 studies), dexmedetomidine (1 study), pregabalin (2 studies), nefopam (2 studies), remifentanil (1 study), propofol (2 studies), and penehyclidine (1 study). Non-pharmacologic methods include capsicum plaster (1 study), throat packs (2 studies) and gastric aspiration (2 studies). CONCLUSIONS: Based on current evidence, we conclude that prophylactic antiemetics like dexamethasone, ondansetron, and penehyclidine are the first defense against PONV. Multimodal analgesia with nerve block techniques and non-opioid analgesics should be considered due to their notable opioid-sparing and PONV preventive effect. For the non-pharmacological methods, throat packs are not recommended for routine use because of their poor effect and serious complications. More prospective RCTs are required to confirm whether gastric aspiration can prevent PONV effectively for patients undergoing orthognathic surgery.

Transcription Factor Pdr3p Promotes Carotenoid Biosynthesis by Activating GAL Promoters in Saccharomyces cerevisiae.

Pleiotropic drug resistance (PDR) family proteins have been extensively studied for their roles in transporting hydrophobic substances, including carotenoids. Overexpression of the PDR family regulator Pdr3p was recently found to boost the biosynthesis of carotenoids, which could not be explained by enhanced product secretion due to the meager extracellular proportions. To provide insights into the possible mechanism, comparative transcriptomics, reverse metabolic engineering, and electrophoretic mobility shift assay (EMSA) were conducted. Transcriptomic data suggested an unexpected correlation between Pdr3p overexpression and the transcriptional levels of GAL promoter-driven genes. This assumption was verified using mCherry and the lycopene synthetic pathway as the reporters. qRT-PCR and EMSA provided further evidence for the activation of GAL promoters by Pdr3p binding to their upstream activation sequences (UASs). This work gives insight into the mechanism of Pdr3p-promoted carotenoid production and highlights the complicated metabolic networking between transcriptional factors and promoters in yeast.

The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J.

PURPOSE: Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [11C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo. METHODS: We evaluated age-related changes in gray matter synaptic density, volume, and blood flow using [11C]UCB-J PET and magnetic resonance imaging (MRI) in a wide age range of 80 cognitive normal subjects (21-83 years old). Partial volume correction was applied to the PET data. RESULTS: Significant age-related decreases were found in 13, two, and nine brain regions for volume, synaptic density, and blood flow, respectively. The prefrontal cortex showed the largest volume decline (4.9% reduction per decade: RPD), while the synaptic density loss was largest in the caudate (3.6% RPD) and medial occipital cortex (3.4% RPD). The reductions in caudate are consistent with previous SV2A PET studies and likely reflect that caudate is the site of nerve terminals for multiple major tracts that undergo substantial age-related neurodegeneration. There was a non-significant negative relationship between volume and synaptic density reductions in 16 gray matter regions. CONCLUSION: MRI and [11]C-UCB-J PET showed age-related decreases of gray matter volume, synaptic density, and blood flow; however, the regional patterns of the reductions in volume and SV2A binding were different. Those patterns suggest that MR-based measures of GM volume may not be directly representative of synaptic density.

Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET.

OBJECTIVE: Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. METHODS: DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. RESULTS: Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r = -0.55, p <0.001, df = 31) but not CN (r = 0.13, p = 0.62, df = 15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. CONCLUSION: In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.

Dietary and lifestyle oxidative balance scores are independently and jointly associated with nonalcoholic fatty liver disease: a 20 years nationally representative cross-sectional study.

Background: Oxidative stress is an important contributor to the progression of nonalcoholic fatty liver disease (NAFLD), but whether dietary and lifestyle pro- and antioxidants may have combined or independent effects on NAFLD, and advanced liver fibrosis (AHF) remains unclear. We aimed to elucidate the relationship between a well-established oxidative balance score (OBS) and NAFLD/AHF. Methods: This was a cross-sectional study. We included adult participants with complete data from the National Health and Nutrition Examination Survey 1999-2018. Survey-weighted adjusted multivariate regression analyses were used to examine the association of all OBS with NAFLD/AHF. A combination of restricted cubic splines, mediation analysis, stratified analysis, and sensitivity analysis were used to further elucidate these associations. Results: We included 6,341 eligible adult participants with prevalence of NAFLD and AHF of 30.2 and 13.9%, respectively. In the fully adjusted model, the highest quartile of OBS, dietary OBS, and lifestyle OBS were associated with 65, 55, and 77% reduced risk of NAFLD, respectively, compared with the reference population, respectively. However, all OBS were not associated with the risk of AHF. All OBS were nonlinearly associated with risk of NAFLD and had a more pronounced reduced risk for OBS, dietary OBS, and lifestyle OBS after exceeding 26, 21, and 5 points, respectively. OBS may exert a protective effect indirectly through inflammation, oxidative stress, and glycolipid metabolism markers. Stratification and sensitivity analyses demonstrate the robustness of our findings. Conclusion: All OBS were nonlinearly and negatively associated with NAFLD risk. These effects may exert indirectly through inflammation, oxidative stress, and glycolipid metabolism markers.

Generation of Whole-Body FDG Parametric Ki Images from Static PET Images Using Deep Learning.

FDG parametric Ki images show great advantage over static SUV images, due to the higher contrast and better accuracy in tracer uptake rate estimation. In this study, we explored the feasibility of generating synthetic Ki images from static SUV ratio (SUVR) images using three configurations of U-Nets with different sets of input and output image patches, which were the U-Nets with single input and single output (SISO), multiple inputs and single output (MISO), and single input and multiple outputs (SIMO). SUVR images were generated by averaging three 5-min dynamic SUV frames starting at 60 minutes post-injection, and then normalized by the mean SUV values in the blood pool. The corresponding ground truth Ki images were derived using Patlak graphical analysis with input functions from measurement of arterial blood samples. Even though the synthetic Ki values were not quantitatively accurate compared with ground truth, the linear regression analysis of joint histograms in the voxels of body regions showed that the mean R2 values were higher between U-Net prediction and ground truth (0.596, 0.580, 0.576 in SISO, MISO and SIMO), than that between SUVR and ground truth Ki (0.571). In terms of similarity metrics, the synthetic Ki images were closer to the ground truth Ki images (mean SSIM = 0.729, 0.704, 0.704 in SISO, MISO and MISO) than the input SUVR images (mean SSIM = 0.691). Therefore, it is feasible to use deep learning networks to estimate surrogate map of parametric Ki images from static SUVR images.

Cooperation of MLL1 and Jun in controlling H3K4me3 on enhancers in colorectal cancer.

BACKGROUND: Enhancer dysregulation is one of the important features for cancer cells. Enhancers enriched with H3K4me3 have been implicated to play important roles in cancer. However, their detailed features and regulatory mechanisms have not been well characterized. RESULTS: Here, we profile the landscape of H3K4me3-enriched enhancers (m3Es) in 43 pairs of colorectal cancer (CRC) samples. M3Es are widely distributed in CRC and averagely possess around 10% of total active enhancers. We identify 1322 gain variant m3Es and 367 lost variant m3Es in CRC. The target genes of the gain m3Es are enriched in immune response pathways. We experimentally prove that repression of CBX8 and RPS6KA5 m3Es inhibits target gene expression in CRC. Furthermore, we find histone methyltransferase MLL1 is responsible for depositing H3K4me3 on the identified Vm3Es. We demonstrate that the transcription factor AP1/JUN interacts with MLL1 and regulates m3E activity. Application of a small chemical inhibitor for MLL1 activity, OICR-9429, represses target gene expression of the identified Vm3Es, enhances anti-tumor immunity and inhibits CRC growth in an animal model. CONCLUSIONS: Taken together, our study illustrates the genome-wide landscape and the regulatory mechanisms of m3Es in CRC, and reveals potential novel strategies for cancer treatment.

Inter-pass motion correction for whole-body dynamic PET and parametric imaging.

Whole-body dynamic FDG-PET imaging through continuous-bed-motion (CBM) mode multi-pass acquisition protocol is a promising metabolism measurement. However, inter-pass misalignment originating from body movement could degrade parametric quantification. We aim to apply a non-rigid registration method for inter-pass motion correction in whole-body dynamic PET. 27 subjects underwent a 90-min whole-body FDG CBM PET scan on a Biograph mCT (Siemens Healthineers), acquiring 9 over-the-heart single-bed passes and subsequently 19 CBM passes (frames). The inter-pass motion correction was executed using non-rigid image registration with multi-resolution, B-spline free-form deformations. The parametric images were then generated by Patlak analysis. The overlaid Patlak slope Ki and y-intercept Vb images were visualized to qualitatively evaluate motion impact and correction effect. The normalized weighted mean squared Patlak fitting errors (NFE) were compared in the whole body, head, and hypermetabolic regions of interest (ROI). In Ki images, ROI statistics were collected and malignancy discrimination capacity was estimated by the area under the receiver operating characteristic curve (AUC). After the inter-pass motion correction was applied, the spatial misalignment appearance between Ki and Vb images was successfully reduced. Voxel-wise normalized fitting error maps showed global error reduction after motion correction. The NFE in the whole body (p = 0.0013), head (p = 0.0021), and ROIs (p = 0.0377) significantly decreased. The visual performance of each hypermetabolic ROI in Ki images was enhanced, while 3.59% and 3.67% average absolute percentage changes were observed in mean and maximum Ki values, respectively, across all evaluated ROIs. The estimated mean Ki values had substantial changes with motion correction (p = 0.0021). The AUC of both mean Ki and maximum Ki after motion correction increased, possibly suggesting the potential of enhancing oncological discrimination capacity through inter-pass motion correction.

Emerging role of α-Klotho in energy metabolism and cardiometabolic diseases.

BACKGROUND AND AIM: Klotho was first identified as a gene associated with aging and longevity in 1997. α-Klotho is an anti-aging protein and its role in energy metabolism, various cardiovascular diseases (CVDs), and metabolic disorders is increasingly being recognized. In this review, we aimed to outline the potential protective role and therapeutic prospects of α-Klotho in energy metabolism and cardiometabolic diseases (CMDs). METHODS: We comprehensively reviewed the relevant literature in PubMed using the keywords 'Klotho', 'metabolism', 'cardiovascular', 'diabetes', 'obesity', 'metabolic syndrome', and 'nonalcoholic fatty liver disease'. RESULTS: α-Klotho can be divided into membrane-bound Klotho, secreted Klotho, and the most studied circulating soluble Klotho that can act as a hormone. Klotho gene polymorphisms have been implicated in energy metabolism and CMDs. α-Klotho can inhibit insulin/insulin growth factor-1 signaling and its overexpression can lead to a 'healthy insulin resistance' and may exert beneficial effects on the regulation of glycolipid metabolism and central energy homeostasis. α-Klotho, mainly serum Klotho, has been revealed to be protective against CVDs, diabetes and its complications, obesity, and nonalcoholic fatty liver disease. Human recombinant Klotho protein/Klotho gene delivery, multiple drugs, or natural products, and exercise can increase α-Klotho expression. CONCLUSION: Overall, α-Klotho has demonstrated its potential as a promising target for modulating energy metabolism and CMDs, and further research is needed to explore its utilization in clinical practice in the future.

Estrogen regulates duodenal glucose absorption by affecting estrogen receptor-α on glucose transporters.

The mechanisms of estrogen in glucose metabolism are well established; however, its role in glucose absorption remains unclear. In this study, we investigated the effects of estrogen on glucose absorption in humans, mice, and SCBN intestinal epithelial cells. We first observed a correlation between estrogen and blood glucose in young women and found that glucose tolerance was significantly less in the premenstrual phase than in the preovulatory phase. Similarly, with decreased serum estradiol levels in ovariectomized mice, estrogen receptors alpha (ERα) and beta (ERß) in the duodenum were reduced, and weight and abdominal fat increased significantly. The expression of sodium/glucose cotransporter 1 (SGLT1) and glucose transporter 2 (GLUT2) and glucose absorption in the duodenum decreased significantly. Estrogen significantly upregulated SGLT1 and GLUT2 expression in SCBN cells. Silencing of ERα, but not ERß, reversed this trend, suggesting that ERα may be key to estrogen-regulating glucose transporters. A mechanistic study revealed that downstream, estrogen regulates the protein kinase C (PKC) pathway. Overall, our findings indicate that estrogen promotes glucose absorption, and estrogen and ERα deficiency can inhibit SGLT1 and GLUT2 expression through the PKC signaling pathway, thereby reducing glucose absorption.

Principal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer's disease.

BACKGROUND: Synaptic loss is considered an early pathological event and major structural correlate of cognitive impairment in Alzheimer's disease (AD). We used principal component analysis (PCA) to identify regional patterns of covariance in synaptic density using [11C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance. METHODS: [11C]UCB-J binding was measured in 45 amyloid + participants with AD and 19 amyloid- cognitively normal participants aged 55-85. A validated neuropsychological battery assessed performance across five cognitive domains. PCA was applied to the pooled sample using distribution volume ratios (DVR) standardized (z-scored) by region from 42 bilateral regions of interest (ROI). RESULTS: Parallel analysis determined three significant PCs explaining 70.2% of the total variance. PC1 was characterized by positive loadings with similar contributions across the majority of ROIs. PC2 was characterized by positive and negative loadings with strongest contributions from subcortical and parietooccipital cortical regions, respectively, while PC3 was characterized by positive and negative loadings with strongest contributions from rostral and caudal cortical regions, respectively. Within the AD group, PC1 subject scores were positively correlated with performance across all cognitive domains (Pearson r = 0.24-0.40, P = 0.06-0.006), PC2 subject scores were inversely correlated with age (Pearson r = -0.45, P = 0.002) and PC3 subject scores were significantly correlated with CDR-sb (Pearson r = 0.46, P = 0.04). No significant correlations were observed between cognitive performance and PC subject scores in CN participants. CONCLUSIONS: This data-driven approach defined specific spatial patterns of synaptic density correlated with unique participant characteristics within the AD group. Our findings reinforce synaptic density as a robust biomarker of disease presence and severity in the early stages of AD.

Removal of epigenetic repressive mark on inflammatory genes in fat liver.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide. The detailed epigenomic changes during fat accumulation in liver are not clear yet. Here, we performed ChIP-Seq analysis in the liver tissues of high-fat diet and regular chow diet mice and investigated the dynamic landscapes of H3K27ac and H3K9me3 marks on chromatin. We find that the activated typical enhancers marked with H3K27ac are enriched on lipid metabolic pathways in fat liver; however, super enhancers do not change much. The regions covered with H3K9me3 repressive mark seem to undergo great changes, and its peak number and intensity both decrease in fat liver. The enhancers located in lost H3K9me3 regions are enriched in lipid metabolism and inflammatory pathways; and motif analysis shows that they are potential targets for transcription factors involved in metabolic and inflammatory processes. Our study has revealed that H3K9me3 may play an important role during the pathogenesis of NAFLD through regulating the accessibility of enhancers.