Ficolin 3 promotes ferroptosis in HCC by downregulating IR/SREBP axis-mediated MUFA synthesis.

BACKGROUND: Targeting ferroptosis has been identified as a promising approach for the development of cancer therapies. Monounsaturated fatty acid (MUFA) is a type of lipid that plays a crucial role in inhibiting ferroptosis. Ficolin 3 (FCN3) is a component of the complement system, serving as a recognition molecule against pathogens in the lectin pathway. Recent studies have reported that FCN3 demonstrates inhibitory effects on the progression of certain tumors. However, whether FCN3 can modulate lipid metabolism and ferroptosis remains largely unknown. METHODS: Cell viability, BODIPY-C11 staining, and MDA assay were carried out to detect ferroptosis. Primary hepatocellular carcinoma (HCC) and xenograft models were utilized to investigate the effect of FCN3 on the development of HCC in vivo. A metabonomic analysis was conducted to assess alterations in intracellular and HCC intrahepatic lipid levels. RESULTS: Our study elucidates a substantial decrease in the expression of FCN3, a component of the complement system, leads to MUFA accumulation in human HCC specimens and thereby significantly promotes ferroptosis resistance. Overexpression of FCN3 efficiently sensitizes HCC cells to ferroptosis, resulting in the inhibition of the oncogenesis and progression of both primary HCC and subcutaneous HCC xenograft. Mechanistically, FCN3 directly binds to the insulin receptor ß (IR-ß) and its pro-form (pro-IR), inhibiting pro-IR cleavage and IR-ß phosphorylation, ultimately resulting in IR-ß inactivation. This inactivation of IR-ß suppresses the expression of sterol regulatory element binding protein-1c (SREBP1c), which subsequently suppresses the transcription of genes related to de novo lipogenesis (DNL) and lipid desaturation, and consequently downregulates intracellular MUFA levels. CONCLUSIONS: These findings uncover a novel regulatory mechanism by which FCN3 enhances the sensitivity of HCC cells to ferroptosis, indicating that targeting FCN3-induced ferroptosis is a promising strategy for HCC treatment.

Distinguishing bipolar depression, bipolar mania, and major depressive disorder by gut microbial characteristics.

BACKGROUND: Gut microbial disturbance has been widely confirmed in mood disorders. However, little is known about whether gut microbial characteristics can distinguish major depressive disorder (MDD), bipolar depression (BP-D), and bipolar mania (BP-M). METHODS: This was a prospective case-control study. The composition of gut microbiota was profiled using 16S ribosomal RNA (rRNA) gene sequencing of fecal samples and compared between healthy controls (HC; n = 46), MDD (n = 51), BP-D (n = 44), and patients with BP-M (n = 45). RESULTS: Gut microbial compositions were remarkably changed in the patients with MDD, BP-D, and BP-M. Compared to HC, distinct gut microbiome signatures were found in MDD, BP-D, and BP-M, and some gut microbial changes were overlapping between the three mood disorders. Furthermore, we identified a signature of 7 operational taxonomic units (OUT; Prevotellaceae-related OUT22, Prevotellaceae-related OUT31, Prevotellaceae-related OTU770, Ruminococcaceae-related OUT70, Bacteroidaceae-related OTU1536, Propionibacteriaceae-related OTU97, Acidaminococcaceae-related OTU34) that can distinguish patients with MDD from those with BP-D, BP-M, or HC, with area under the curve (AUC) values ranging from 0.910 to 0.996. CONCLUSION: Our results provide the clinical rationale for the discriminative diagnosis of MDD, BP-D, and BP-M by characteristic gut microbial features.

Coagulation Factor VII Fine-tunes Hepatic Steatosis by Blocking AKT-CD36-Mediated Fatty Acid Uptake.

Nonalcoholic fatty liver disease (NAFLD) is considered a risk factor for cardiovascular and cerebrovascular disease owing to its close association with coagulant disturbances. However, the precise biological functions and mechanisms that connect coagulation factors to NAFLD pathology remain inadequately understood. Herein, with unbiased bioinformatics analyses followed by functional testing, we demonstrate that hepatic expression of coagulation factor VII (FVII) decreases in patients and mice with NAFLD/nonalcoholic steatohepatitis (NASH). By using adenovirus-mediated F7-knockdown and hepatocyte-specific F7-knockout mouse models, our mechanistic investigations unveil a noncoagulant function of hepatic FVII in mitigating lipid accumulation and lipotoxicity. This protective effect is achieved through the suppression of fatty acid uptake, orchestrated via the AKT-CD36 pathway. Interestingly, intracellular FVII directly interacts with AKT and PP2A, thereby promoting their association and triggering the dephosphorylation of AKT. Therapeutic intervention through adenovirus-mediated liver-specific overexpression of F7 results in noteworthy improvements in liver steatosis, inflammation, injury, and fibrosis in severely afflicted NAFLD mice. In conclusion, our findings highlight coagulation factor FVII as a critical regulator of hepatic steatosis and a potential target for the treatment of NAFLD and NASH.

Childhood abuse influences clinical features of major depressive disorder by modulating the functional network of the right amygdala subregions.

Childhood trauma and the amygdala play essential roles in major depressive disorder (MDD) mechanisms. However, the neurobiological mechanism among them remains unclear. Therefore, we explored the relationship among the amygdala subregion's abnormal functional connectivity (FC), clinical features, and childhood trauma in MDD. We obtained resting-state functional magnetic resonance imaging (fMRI) in 115 MDD patients and 91 well-matched healthy controls (HC). Amygdala subregions were defined according to the Human Brainnetome Atlas. The case vs. control difference in FCs was extracted. After controlling for age, sex, and education years, the mediations between the detected abnormal FCs and clinical features were analyzed, including the onset age of MDD and the Hamilton Depression Scale-24 (HAMD-24) reductive rate. Compared with HC subjects, we found, only the right amygdala subregions, namely the right medial amygdala (mAmyg.R) and the right lateral amygdala (lAmyg.R), showed a significant decrease in whole-brain FCs in MDD patients. Only childhood abuse experiences were significantly associated with amygdala subregion connectivity and clinical features in MDD patients. Additionally, The FCs between the mAmyg.R and extensive frontal, temporal, and subcortical regions mediated between the early life abuses and disease onset or treatment outcome. The findings indicate that the abnormal connectivity of the right amygdala subregions is involved in MDD's pathogenesis and clinical characteristics.

Targeting hepatic ceruloplasmin mitigates nonalcoholic steatohepatitis by modulating bile acid metabolism.

Nonalcoholic steatohepatitis (NASH) is a condition that progresses from nonalcoholic fatty liver disease (NAFLD) and is characterized by hepatic fat accumulation, inflammation, and fibrosis. It has the potential to develop into cirrhosis and liver cancer, and currently no effective pharmacological treatment is available. In this study, we investigate the therapeutic potential of targeting ceruloplasmin (Cp), a copper-containing protein predominantly secreted by hepatocytes, for treating NASH. Our result show that hepatic Cp is remarkedly upregulated in individuals with NASH and the mouse NASH model. Hepatocyte-specific Cp ablation effectively attenuates the onset of dietary-induced NASH by decreasing lipid accumulation, curbing inflammation, mitigating fibrosis, and ameliorating liver damage. By employing transcriptomics and metabolomics approaches, we have discovered that hepatic deletion of Cp brings about remarkable restoration of bile acid (BA) metabolism during NASH. Hepatic deletion of Cp effectively remodels BA metabolism by upregulating Cyp7a1 and Cyp8b1, which subsequently leads to enhanced BA synthesis and notable alterations in BA profiles. In conclusion, our studies elucidate the crucial involvement of Cp in NASH, highlighting its significance as a promising therapeutic target for the treatment of this disease.

Prediction of Early Antidepressant Efficacy in Patients with Major Depressive Disorder Based on Multidimensional Features of rs-fMRI and P11 Gene DNA Methylation: Prédiction de l'efficacité précoce d'un antidépresseur chez des patients souffrant du trouble dépressif majeur d'après les caractéristiques multidimensionnelles de la méthylation de l'ADN du gène P11 et de la IRMf-rs.

OBJECTIVE: This study established a machine learning model based on the multidimensional data of resting-state functional activity of the brain and P11 gene DNA methylation to predict the early efficacy of antidepressant treatment in patients with major depressive disorder (MDD). METHODS: A total of 98 Han Chinese MDD were analysed in this study. Patients were divided into 51 responders and 47 nonresponders according to whether the Hamilton Depression Rating Scale-17 items (HAMD-17) reduction rate was ≥50% after 2 weeks of antidepressant treatment. At baseline, the Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples. Resting-state functional magnetic resonance imaging (rs-fMRI) scan detected the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in 116 brain regions. The least absolute shrinkage and selection operator analysis method was used to perform feature reduction and feature selection. Four typical machine learning methods were used to establish support vector machine (SVM), random forest (RF), Naïve Bayes (NB), and logistic regression (LR) prediction models based on different combinations of functional activity of the brain, P11 gene DNA methylation and clinical/demographic features after screening. RESULTS: The SVM model based on ALFF, ReHo, FC, P11 methylation, and clinical/demographic features showed the best performance, with 95.92% predictive accuracy and 0.9967 area under the receiver operating characteristic curve, which was better than RF, NB, and LR models. CONCLUSION: The multidimensional data features combining rs-fMRI, DNA methylation, and clinical/demographic features can predict the early antidepressant efficacy in MDD.

Microstructural abnormalities of white matter in the cingulum bundle of adolescents with major depression and non-suicidal self-injury.

BACKGROUND: Non-suicidal self-injury (NSSI) is prevalent in major depressive disorder (MDD) during adolescence, but the underlying neural mechanisms are unclear. This study aimed to investigate microstructural abnormalities in the cingulum bundle associated with NSSI and its clinical characteristics. METHODS: 130 individuals completed the study, including 35 healthy controls, 47 MDD patients with NSSI, and 48 MDD patients without NSSI. We used tract-based spatial statistics (TBSS) with a region of interest (ROI) analysis to compare the fractional anisotropy (FA) of the cingulum bundle across the three groups. receiver-operating characteristics (ROC) analysis was employed to evaluate the ability of the difficulties with emotion regulation (DERS) score and mean FA of the cingulum to differentiate between the groups. RESULTS: MDD patients with NSSI showed reduced cingulum integrity in the left dorsal cingulum compared to MDD patients without NSSI and healthy controls. The severity of NSSI was negatively associated with cingulum integrity (r = -0.344, p = 0.005). Combining cingulum integrity and DERS scores allowed for successful differentiation between MDD patients with and without NSSI, achieving a sensitivity of 70% and specificity of 83%. CONCLUSIONS: Our study highlights the role of the cingulum bundle in the development of NSSI in adolescents with MDD. The findings support a frontolimbic theory of emotion regulation and suggest that cingulum integrity and DERS scores may serve as potential early diagnostic tools for identifying MDD patients with NSSI.

The Interaction of LAMA2 and Duration of Illness Affects the Thickness of the Right Transverse Temporal Gyrus in Major Depressive Disorder.

Background: Depression is a heritable brain disorder. Laminin genes were recently identified to affect the brain's overall thickness through neurogenesis, differentiation, and migration in depression. This study aims to explore the effects of the LAMA2's single nucleotide polymorphisms (SNP), a subunit gene of laminin, on the detected brain regions of patients with major depressive disorder (MDD). Methods: The study included 89 patients with MDD and 60 healthy controls with T1-weighted structural magnetic resonance imaging and blood samples for genotyping. The interactions between LAMA2 gene SNPs and diagnosis as well as duration of illness (DOI) were explored on brain measures controlled for age, gender, and site. Results: The right transverse temporal gyrus and right parahippocampal gyrus showed reduced thickness in MDD. Almost all seven LAMA2 SNPs showed significant interactions with diagnosis on both gyrus (corrected p < 0.05 or trending). In MDD, rs6569604, rs2229848, rs2229849, rs2229850, and rs2784895 interacted with DOI on the right transverse temporal gyrus (corrected p < 0.05), but not the right parahippocampal gyrus. Conclusion: The thickness of the right transverse temporal gyrus in patients with MDD may be affected by LAMA2 gene and DOI.

Abnormal spontaneous activity of regions related to mood regulation mediates the effect of childhood emotional neglect on major depressive disorder.

This study investigated the mediating factors between childhood emotional neglect (EN) and major depressive disorder (MDD) and whether combining multi-indicator could help diagnose MDD. Regional homogeneity (ReHo) and clinical features were compared between 33 MDD patients and 36 healthy controls (HC). Mediation analysis was employed to explore whether social support or ReHo mediates the association between EN and MDD. The linear discriminant analysis model was constructed with EN, social support, and ReHo, and applied to distinguish MDD from HC in both primary and replication cohorts. We found that MDD patients experienced severer EN and poorer social support, and exhibited lower ReHo in the left middle occipital gyrus and bilateral postcentral gyrus, and higher ReHo in the right cerebellum crus1. EN could affect MDD directly and indirectly through ReHo in these discrepant brain regions and social support. Combining ReHo values of these four distinct brain regions, EN, and objective support could classify MDD patients from HC, and the 10-fold cross-validation accuracy within-study replication and in the independent cohort was 83.78 % ± 1.49 % and 82.72 % ± 2.22 %, respectively. These findings suggested that childhood EN, social support, and emotional-related regions' ReHo were associated with risks of MDD, providing new insights into the pathological mechanisms underlying MDD.

Childhood trauma and social support affect symptom profiles through cortical thickness abnormalities in major depressive disorder: A structural equation modeling analysis.

BACKGROUND: Childhood trauma, low social support, and alexithymia are recognized as risk factors for major depressive disorder (MDD). However, the mechanisms of risk factors, symptoms, and corresponding structural brain abnormalities in MDD are not fully understood. Structural equation modeling (SEM) has advantages in studying multivariate interrelationships. We aim to illustrate their relationships using SEM. METHODS: 313 MDD patients (213 female; mean age 42.49 years) underwent magnetic resonance imaging and completed assessments. We integrated childhood trauma, alexithymia, social support, anhedonia, depression, anxiety, suicidal ideation and cortical thickness into a multivariate SEM. RESULTS: We first established the risk factors-clinical phenotype SEM with an adequate fit. Cortical thickness results show a negative correlation of childhood trauma with the left middle temporal gyrus (MTG) (p = 0.012), and social support was negatively correlated with the left posterior cingulate cortex (PCC) (p < 0.001). The final good fit SEM (χ2 = 32.92, df = 21, χ2/df = 1.57, CFI = 0.962, GFI = 0.978, RMSEA = 0.043) suggested two pathways, with left PCC thickness mediating the relationship between social support and suicidal ideation, and left MTG thickness mediating between childhood trauma and anhedonia/anxiety. CONCLUSION: Our findings provide evidence for the impact of risk factor variables on the brain structure and clinical phenotype of MDD patients. Insufficient social support and childhood trauma might lead to corresponding cortical abnormalities in PCC and MTG, affecting the patient's mood and suicidal ideation. Future interventions should aim at these nodes.

Pharmacotherapies of NAFLD: updated opportunities based on metabolic intervention.

Non-alcoholic fatty liver disease (NAFLD) is a chronic liver disease that is becoming increasingly prevalent, and it ranges from simple steatosis to cirrhosis. However, there is still a lack of pharmacotherapeutic strategies approved by the Food and Drug Administration, which results in a higher risk of death related to carcinoma and cardiovascular complications. Of note, it is well established that the pathogenesis of NAFLD is tightly associated with whole metabolic dysfunction. Thus, targeting interconnected metabolic conditions could present promising benefits to NAFLD, according to a number of clinical studies. Here, we summarize the metabolic characteristics of the development of NAFLD, including glucose metabolism, lipid metabolism and intestinal metabolism, and provide insight into pharmacological targets. In addition, we present updates on the progresses in the development of pharmacotherapeutic strategies based on metabolic intervention globally, which could lead to new opportunities for NAFLD drug development.

The trends of psychosomatic symptoms and perceived stress among healthcare workers during the COVID-19 pandemic in China: Four cross-sectional nationwide surveys, 2020-2023.

An unseen wave of vast infection was detected in China in December 2022, and healthcare workers faced inevitable challenges and heavy stress. We aimed to present a dynamic mental health map and, most importantly, provide a timely report of the current situation in healthcare workers. The current study conducted four national cross-sectional online surveys from February and March 2020, Apr 2022, and Jan 2023. The Psychosomatic Symptom Scale (PSSS) and Perceived Stress Scale-10 (PSS-10) were used to assess psychosomatic symptoms and perceived stress. Fourteen thousand nine hundred forty-five participants (8578 healthcare workers and 6367 others) participated in the surveys. The prevalence of psychosomatic syndrome, reflected by PSSS, was 19.3% (Wave1), 22.9% (Wave2), 36.4% (Wave3), and 60.7% (Wave4) among healthcare workers, compared to 24.0% (Wave1), 35.7% (Wave2), 34.2% (Wave3) and 50.5% (Wave4) among the others. In addition, healthcare workers exhibited lower PSSS total scores at the beginning but higher in later waves. Despite their infection status, they now suffer from more severe psychosomatic symptoms than the rest of society. Our findings suggest that healthcare workers in China have now experienced severe psychosomatic symptoms and tremendous stress. Therefore, there is an urgent need to utilize social support for them.

Betaine-homocysteine methyltransferase promotes adipocyte commitment and insulin resistance via p38 MAPK/Smad signaling.

OBJECTIVE: Betaine-homocysteine methyltransferase (Bhmt) belongs to the family of methyltransferases and is involved in the one-carbon metabolic cycle, which is associated with the risk of diabetes and adiposity. This study aimed to explore whether Bhmt participated in the development of obesity or its associated diabetes, as well as the mechanism involved. METHODS: The expression levels of Bhmt were examined in stromal vascular fraction cells and mature adipocytes in obesity and nonobesity. Knockdown and overexpression of Bhmt in C3H10T1/2 cells were used to investigate Bhmt's function in adipogenesis. Bhmt's role in vivo was analyzed using an adenovirus-expressing system and a high-fat diet-induced obesity mouse model. RESULTS: Bhmt was highly expressed in stromal vascular fraction cells rather than mature adipocytes of adipose tissue and was upregulated in adipose tissue in obesity and C3H10T1/2-commited preadipocytes. Overexpression of Bhmt promoted adipocyte commitment and differentiation in vitro and exacerbated adipose tissue expansion in vivo, with a concomitant increase in insulin resistance, whereas Bhmt silencing exhibited opposite effects. Mechanistically, Bhmt-induced adipose expansion was mediated by stimulating the p38 MAPK/Smad pathway. CONCLUSIONS: The findings of this study highlight the obesogenic and diabetogenic role of adipocytic Bhmt and propose Bhmt as a promising therapeutic target for obesity and obesity-related diabetes.

Integrating functional neuroimaging and serum proteins improves the diagnosis of major depressive disorder.

BACKGROUND: The lack of effective objective diagnostic biomarkers for major depressive disorder (MDD) leads to high misdiagnosis. Compared with healthy controls (HC), abnormal brain functions and protein levels are often observed in MDD. However, it is unclear whether combining these changed multidimensional indicators could help improve the diagnosis of MDD. METHODS: Sixty-three MDD and eighty-one HC subjects underwent resting-state fMRI scans, among whom 37 MDD and 45 HC provided blood samples. Amplitudes of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and serum levels of brain-derived neurotrophic factor (BDNF), cortisol, and multiple cytokines were measured and put into the linear discriminant analysis (LDA) to construct corresponding MDD diagnostic models. The area under the receiver operating characteristic curve (AUC) of 5-fold cross-validation was calculated to evaluate each model's performance. RESULTS: Compared with HC, MDD patients' spontaneous brain activity, serum BDNF, cortisol, interleukin (IL)-4, IL-6, and IL-10 levels changed significantly. The combinations of unidimensional multi-indicator had better diagnostic performance than a single one. The model consisted of multidimensional multi-indicator further exhibited conspicuously superior diagnostic efficiency than those constructed with unidimensional multi-indicator, and its AUC, sensitivity, specificity, and accuracy of 5-fold cross-validation were 0.99, 92.0 %, 100.0 %, and 96.3 %, respectively. LIMITATIONS: This cross-sectional study consists of relatively small samples and should be replicated in larger samples with follow-up data to optimize the diagnostic model. CONCLUSIONS: MDD patients' neuroimaging features and serum protein levels significantly changed. The model revealed by LDA could diagnose MDD with high accuracy, which may serve as an ideal diagnostic biomarker for MDD.

Predicting the diagnosis of various mental disorders in a mixed cohort using blood-based multi-protein model: a machine learning approach.

The lack of objective diagnostic methods for mental disorders challenges the reliability of diagnosis. The study aimed to develop an easily accessible and useable objective method for diagnosing major depressive disorder (MDD), schizophrenia (SZ), bipolar disorder (BPD), and panic disorder (PD) using serum multi-protein. Serum levels of brain-derived neurotrophic factor (BDNF), VGF (non-acronymic), bicaudal C homolog 1 (BICC1), C-reactive protein (CRP), and cortisol, which are generally recognized to be involved in different pathogenesis of various mental disorders, were measured in patients with MDD (n = 50), SZ (n = 50), BPD (n = 55), and PD along with 50 healthy controls (HC). Linear discriminant analysis (LDA) was employed to construct a multi-classification model to classify these mental disorders. Both leave-one-out cross-validation (LOOCV) and fivefold cross-validation were applied to validate the accuracy and stability of the LDA model. All five serum proteins were included in the LDA model, and it was found to display a high overall accuracy of 96.9% when classifying MDD, SZ, BPD, PD, and HC groups. Multi-classification accuracy of the LDA model for LOOCV and fivefold cross-validation (within-study replication) reached 96.9 and 96.5%, respectively, demonstrating the feasibility of the blood-based multi-protein LDA model for classifying common mental disorders in a mixed cohort. The results suggest that combining multiple proteins associated with different pathogeneses of mental disorders using LDA may be a novel and relatively objective method for classifying mental disorders. Clinicians should consider combining multiple serum proteins to diagnose mental disorders objectively.

Serum metabolomic profiling revealed potential diagnostic biomarkers in patients with panic disorder.

BACKGROUND: Currently, specific metabolites and diagnostic biomarkers of panic disorder (PD) patients have not been identified in clinical practice. The aim of this study was to explore metabolites and metabolic pathways in serum through a metabolomics method. METHODS: Fifty-five PD patients who completed 2 weeks of inpatient treatment and 55 healthy control subjects (HCs) matched for age, sex and BMI were recruited. Ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) was used to detect metabolites in serum. Multivariate Statistical Analysis was used to identify differential metabolites. The relevant biometabolic pathways were further identified by the online tool MetaboAnalyst 5.0. RESULTS: 43 different metabolites in PD patients compared to HCs (P < 0.05) were screened. Pathway analysis showed that these small molecules were mainly associated with amino acid metabolism. 14 metabolites were significantly changed after 2 weeks of drug treatment (P < 0.05), which were mainly associated with tryptophan metabolism. CONCLUSION: In conclusion, our analysis of metabolomics of PD patients at baseline and two weeks after treatment screened for differential metabolites that could be potential diagnostic biomarkers involved in PD pathogenesis and influence some biometabolic pathways such as phenylalanine metabolism and tryptophan metabolism. In the future, we can summarize and observe the dynamic changes of differential metabolites that appear more frequently in similar studies to further explore the underlying mechanisms of PD evolution.

A novel small compound TOIDC suppresses lipogenesis via SREBP1-dependent signaling to curb MAFLD.

BACKGROUND: Inhibition of hepatic lipogenesis is widely regarded as an effective treatment for metabolic-associated fatty liver disease (MAFLD), although numerous related drugs have failed to reach clinical application. The goal of this study is to identify a novel small compound that can effectively treat MAFLD. METHODS: Primary hepatocytes were first exposed to palmitic acid and oleic acid, then treated with compounds prior to high through screening for cellular lipid content. The efficacy of these compounds was measured by Nile Red staining and triglyceride analysis. The potential cellular toxicity caused by these compounds was evaluated by CCK8 assay. qPCR and Western blot were used to determine expression of RNAs and proteins, respectively. The compound was intraperitoneally injected into diet-induced obese (DIO) mice to examine its efficacy in vivo. RESULTS: We identified the dimethyl 1-methyl-2-thioxoindoline-3,3-dicarboxylate (TOIDC) as a powerful chemical to reduce cellular lipid with minimal cellular toxicity. When injected intraperitoneally, TOIDC effectively ameliorates MAFLD in DIO mice. Mechanically, TOIDC suppresses de novo lipogenesis through inhibiting sterol regulatory element-binding protein 1 (SREBP1). CONCLUSIONS: Our findings indicate that TOIDC could be a promising lead compound to develop new drugs to treat MAFLD.

Downregulation of hepatic ceruloplasmin ameliorates NAFLD via SCO1-AMPK-LKB1 complex.

Copper deficiency has emerged to be associated with various lipid metabolism diseases, including non-alcoholic fatty liver disease (NAFLD). However, the mechanisms that dictate the association between copper deficiency and metabolic diseases remain obscure. Here, we reveal that copper restoration caused by hepatic ceruloplasmin (Cp) ablation enhances lipid catabolism by promoting the assembly of copper-load SCO1-LKB1-AMPK complex. Overnutrition-mediated Cp elevation results in hepatic copper loss, whereas Cp ablation restores copper content to the normal level without eliciting detectable hepatotoxicity and ameliorates NAFLD in mice. Mechanistically, SCO1 constitutively interacts with LKB1 even in the absence of copper, and copper-loaded SCO1 directly tethers LKB1 to AMPK, thereby activating AMPK and consequently promoting mitochondrial biogenesis and fatty acid oxidation. Therefore, this study reveals a mechanism by which copper, as a signaling molecule, improves hepatic lipid catabolism, and it indicates that targeting copper-SCO1-AMPK signaling pathway ameliorates NAFLD development by modulating AMPK activity.

Combined serum IL-6, C-reactive protein, and cortisol may distinguish patients with anhedonia in major depressive disorder.

Neuroinflammation and anhedonia in major depressive disorder (MDD) are closely connected, though the exact mechanism is unclear. This study aimed to investigate the relationships between cytokines, C-reactive protein (CRP), cortisol, and anhedonia, revealing the potential predictive value in identifying anhedonic MDD. In total, 66 patients with MDD (29 with anhedonia and 37 without anhedonia) and 66 healthy controls (HCs) were included. The severity of depression and anhedonia was evaluated using the Hamilton Rating Scale for Depression-24 (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS), respectively. Serum cytokines were measured using flow cytofluorometric kits, while CRP and cortisol were measured using enzyme-linked immunosorbent assay kits. We found higher serum levels of interleukin-2 (IL-2), IL-6, and cortisol in MDD than in HC where anhedonic MDD was highest. CRP and IL-6 were positively associated with anhedonia, and cortisol levels were related to both anhedonia and depression. A combination of IL-6, CRP, and cortisol had optimal predictive value for distinguishing anhedonic MDD. Anhedonic MDD has unique neuroendocrine-immune characteristics compared with those without anhedonia. The combination of IL-6, CRP, and cortisol might be an early marker to distinguish anhedonic MDD.