14-3-3 proteins contribute to autophagy by modulating SINAT-mediated degradation of ATG13.

In multicellular eukaryotes, autophagy is a conserved process that delivers cellular components to the vacuole or lysosome for recycling during development and stress responses. Induction of autophagy activates AUTOPHAGY-RELATED PROTEIN 1 (ATG1) and ATG13 to form a protein kinase complex that initiates autophagosome formation. However, the detailed molecular mechanism underlying the regulation of this protein complex in plants remains unclear. Here, we determined that in Arabidopsis thaliana, the regulatory proteins 14-3-3λ and 14-3-3κ redundantly modulate autophagy dynamics by facilitating SEVEN IN ABSENTIA OF ARABIDOPSIS THALIANA (SINAT)-mediated proteolysis of ATG13a and ATG13b. 14-3-3λ and 14-3-3κ directly interacted with SINATs and ATG13a/b in vitro and in vivo. Compared to wild-type (WT), the 14-3-3λ 14-3-3κ double mutant showed increased tolerance to nutrient starvation, delayed leaf senescence, and enhanced starvation-induced autophagic vesicles. Moreover, 14-3-3s were required for SINAT1-mediated ubiquitination and degradation of ATG13a. Consistent with their roles in ATG degradation, the 14-3-3λ 14-3-3κ double mutant accumulated higher levels of ATG1a/b/c and ATG13a/b than the WT upon nutrient deprivation. Furthermore, the specific association of 14-3-3s with phosphorylated ATG13a was crucial for ATG13a stability and formation of the ATG1-ATG13 complex. Thus, our findings demonstrate that 14-3-3λ and 14-3-3κ function as molecular adaptors to regulate autophagy by modulating the homeostasis of phosphorylated ATG13.

Zinc finger BED-type containing 3 promotes hepatic steatosis by interacting with polypyrimidine tract-binding protein 1.

AIMS/HYPOTHESIS: The relationship between metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes mellitus, insulin resistance and the metabolic syndrome is well established. While zinc finger BED-type containing 3 (ZBED3) has been linked to type 2 diabetes mellitus and the metabolic syndrome, its role in MASLD remains unclear. In this study, we aimed to investigate the function of ZBED3 in the context of MASLD. METHODS: Expression levels of ZBED3 were assessed in individuals with MASLD, as well as in cellular and animal models of MASLD. In vitro and in vivo analyses were conducted using a cellular model of MASLD induced by NEFA and an animal model of MASLD induced by a high-fat diet (HFD), respectively, to investigate the role of ZBED3 in MASLD. ZBED3 expression was increased by lentiviral infection or tail-vein injection of adeno-associated virus. RNA-seq and bioinformatics analysis were employed to examine the pathways through which ZBED3 modulates lipid accumulation. Findings from these next-generation transcriptome sequencing studies indicated that ZBED3 controls SREBP1c (also known as SREBF1; a gene involved in fatty acid de novo synthesis); thus, co-immunoprecipitation and LC-MS/MS were utilised to investigate the molecular mechanisms by which ZBED3 regulates the sterol regulatory element binding protein 1c (SREBP1c). RESULTS: In this study, we found that ZBED3 was significantly upregulated in the liver of individuals with MASLD and in MASLD animal models. ZBED3 overexpression promoted NEFA-induced triglyceride accumulation in hepatocytes in vitro. Furthermore, the hepatocyte-specific overexpression of Zbed3 promoted hepatic steatosis. Conversely, the hepatocyte-specific knockout of Zbed3 resulted in resistance of HFD-induced hepatic steatosis. Mechanistically, ZBED3 interacts directly with polypyrimidine tract-binding protein 1 (PTBP1) and affects its binding to the SREBP1c mRNA precursor to regulate SREBP1c mRNA stability and alternative splicing. CONCLUSIONS/INTERPRETATION: This study indicates that ZBED3 promotes hepatic steatosis and serves as a critical regulator of the progression of MASLD. DATA AVAILABILITY: RNA-seq data have been deposited in the NCBI Gene Expression Omnibus ( www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE231875 ). MS proteomics data have been deposited to the ProteomeXchange Consortium via the iProX partner repository ( https://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD041743 ).

ITGB3-enriched extracellular vesicles mediate the formation of osteoclastic pre-metastatic niche to promote lung adenocarcinoma bone metastasis.

The regulatory mechanisms underlying bone metastasis in lung adenocarcinoma (LUAD) are not yet fully understood despite the frequent occurrence of bone involvement. This study aimed to examine the involvement and mechanism of integrin subunit beta 3 (ITGB3) in the process of LUAD bone metastasis. Our findings indicate that ITGB3 facilitates the migration and invasion of LUAD cells in vitro and metastasis to the bone in vivo. Furthermore, ITGB3 stimulates osteoclast production and activation, thereby expediting osteolytic lesion progression. Extracellular vesicles (EVs) isolated from the conditioned medium (CM) of LUAD cells overexpressing ITGB3 determined that ITGB3 facilitates osteoclastogenesis and enhances osteoclast activity by utilizing EVs-mediated transport to RAW264.7 cells. Our in vivo findings demonstrated that ITGB3-EVs augmented the population of osteoclasts, thereby establishing an osteoclastic pre-metastatic niche (PMN) conducive to the colonization and subsequent growth of LUAD cells in the bone. ITGB3 is enriched in serum EVs of patients diagnosed with LUAD bone metastasis, potentially facilitating osteoclast differentiation and activation in vitro. Our research illustrates that ITGB3-EVs derived from LUAD cells facilitate osteoclast differentiation and activation by modulating the phosphorylation level of p38 MAPK. This process ultimately leads to the generation of osteolytic PMN and accelerates the progression of bone metastasis.

Peripheral Inflammatory and Immune Landscape in Multiple System Atrophy: A Cross-Sectional Study.

BACKGROUND: Neuroinflammation might contribute to the pathogenesis of multiple systemic atrophy (MSA). However, specific alterations in the peripheral inflammatory and immune profiles of patients with MSA remain unclear. OBJECTIVES: To determine the peripheral inflammatory and immune profiles of patients with MSA and their potential value as biomarkers for facilitating clinical diagnosis and monitoring disease severity. METHODS: This cross-sectional study included 235, 240, and 235 patients with MSA, patients with Parkinson's disease (PD), and healthy controls (HCs), respectively. Inflammatory and immune parameters were measured in peripheral blood, differences between groups were assessed, and clusters were analyzed. Associations between the parameters and clinical characteristics of MSA were assessed using Spearman and partial correlation analyses. RESULTS: Significant differences were observed especially in monocytes, neutrophils-to-lymphocyte ratio (NLR) and neutrophils-to-lymphocyte ratio (MPV) between MSA patients and HCs (P < 0.01). Monocytes and uric acid (UA) levels were also significantly different between the MSA and PD patients (P < 0.05). The combination of NLR and MPV distinguished MSA-P patients from HCs (areas under the curve = 0.824). In addition, complement components C4 and C3 were significantly correlated with the Scale Outcomes in PD for Autonomic Symptoms and Wexner scale, whereas immunoglobulin G (IgG) was significantly correlated with scores of Unified Multiple System Atrophy Rating Scale (P < 0.05). CONCLUSIONS: In MSA patients, monocytes, NLR and MPV might serve as potential diagnostic biomarkers, whereas MLR, C3, C4, and IgG significantly correlate with disease severity. © 2023 International Parkinson and Movement Disorder Society.

Deep learning for malignancy risk estimation of incidental sub-centimeter pulmonary nodules on CT images.

OBJECTIVES: To establish deep learning models for malignancy risk estimation of sub-centimeter pulmonary nodules incidentally detected by chest CT and managed in clinical settings. MATERIALS AND METHODS: Four deep learning models were trained using CT images of sub-centimeter pulmonary nodules from West China Hospital, internally tested, and externally validated on three cohorts. The four models respectively learned 3D deep features from the baseline whole lung region, baseline image patch where the nodule located, baseline nodule box, and baseline plus follow-up nodule boxes. All regions of interest were automatically segmented except that the nodule boxes were additionally manually checked. The performance of models was compared with each other and that of three respiratory clinicians. RESULTS: There were 1822 nodules (981 malignant) in the training set, 806 (416 malignant) in the testing set, and 357 (253 malignant) totally in the external sets. The area under the curve (AUC) in the testing set was 0.754, 0.855, 0.928, and 0.942, respectively, for models derived from baseline whole lung, image patch, nodule box, and the baseline plus follow-up nodule boxes. When baseline models externally validated (follow-up images not available), the nodule-box model outperformed the other two with AUC being 0.808, 0.848, and 0.939 respectively in the three external datasets. The resident, junior, and senior clinicians achieved an accuracy of 67.0%, 82.5%, and 90.0%, respectively, in the testing set. The follow-up model performed comparably to the senior clinician. CONCLUSION: The deep learning algorithms solely mining nodule information can efficiently predict malignancy of incidental sub-centimeter pulmonary nodules. CLINICAL RELEVANCE STATEMENT: The established models may be valuable for supporting clinicians in routine clinical practice, potentially reducing the number of unnecessary examinations and also delays in diagnosis. KEY POINTS: • According to different regions of interest, four deep learning models were developed and compared to evaluate the malignancy of sub-centimeter pulmonary nodules by CT images. • The models derived from baseline nodule box or baseline plus follow-up nodule boxes demonstrated sufficient diagnostic accuracy (86.4% and 90.4% in the testing set), outperforming the respiratory resident (67.0%) and junior clinician (82.5%). • The proposed deep learning methods may aid clinicians in optimizing follow-up recommendations for sub-centimeter pulmonary nodules and may lead to fewer unnecessary diagnostic interventions.

Anemoside B4, a new pyruvate carboxylase inhibitor, alleviates colitis by reprogramming macrophage function.

OBJECTIVES: Colitis is a global disease usually accompanied by intestinal epithelial damage and intestinal inflammation, and an increasing number of studies have found natural products to be highly effective in treating colitis. Anemoside B4 (AB4), an abundant saponin isolated from Pulsatilla chinensis (Bunge), which was found to have strong anti-inflammatory activity. However, the exact molecular mechanisms and direct targets of AB4 in the treatment of colitis remain to be discovered. METHODS: The anti-inflammatory activities of AB4 were verified in LPS-induced cell models and 2, 4, 6-trinitrobenzene sulfonic (TNBS) or dextran sulfate sodium (DSS)-induced colitis mice and rat models. The molecular target of AB4 was identified by affinity chromatography analysis using chemical probes derived from AB4. Experiments including proteomics, molecular docking, biotin pull-down, surface plasmon resonance (SPR), and cellular thermal shift assay (CETSA) were used to confirm the binding of AB4 to its molecular target. Overexpression of pyruvate carboxylase (PC) and PC agonist were used to study the effects of PC on the anti-inflammatory and metabolic regulation of AB4 in vitro and in vivo. RESULTS: AB4 not only significantly inhibited LPS-induced NF-κB activation and increased ROS levels in THP-1 cells, but also suppressed TNBS/DSS-induced colonic inflammation in mice and rats. The molecular target of AB4 was identified as PC, a key enzyme related to fatty acid, amino acid and tricarboxylic acid (TCA) cycle. We next demonstrated that AB4 specifically bound to the His879 site of PC and altered the protein's spatial conformation, thereby affecting the enzymatic activity of PC. LPS activated NF-κB pathway and increased PC activity, which caused metabolic reprogramming, while AB4 reversed this phenomenon by inhibiting the PC activity. In vivo studies showed that diisopropylamine dichloroacetate (DADA), a PC agonist, eliminated the therapeutic effects of AB4 by changing the metabolic rearrangement of intestinal tissues in colitis mice. CONCLUSION: We identified PC as a direct cellular target of AB4 in the modulation of inflammation, especially colitis. Moreover, PC/pyruvate metabolism/NF-κB is crucial for LPS-driven inflammation and oxidative stress. These findings shed more light on the possibilities of PC as a potential new target for treating colitis.

Golgi protein ACBD3 downregulation sensitizes cells to ferroptosis.

Ferroptosis, a form of cell death driven by iron-dependent lipid peroxidation, is emerging as a promising target in cancer therapy. It is regulated by a network of molecules and pathways that modulate lipid metabolism, iron homeostasis and redox balance, and related processes. However, there are still numerous regulatory molecules intricately involved in ferroptosis that remain to be identified. Here, we indicated that suppression of Golgi protein acyl-coenzyme A binding domain A containing 3 (ACBD3) increased the sensitivity of Henrieta Lacks and PANC1 cells to ferroptosis. ACBD3 knockdown increases labile iron levels by promoting ferritinophagy. This increase in free iron, coupled with reduced levels of glutathione peroxidase 4 due to ACBD3 knockdown, leads to the accumulation of reactive oxygen species and lipid peroxides. Moreover, ACBD3 knockdown also results in elevated levels of polyunsaturated fatty acid-containing glycerophospholipids through mechanisms that remain to be elucidated. Furthermore, inhibition of ferrtinophagy in ACBD3 downregulated cells by knocking down the nuclear receptor co-activator 4 or Bafilomycin A1 treatment impeded ferroptosis. Collectively, our findings highlight the pivotal role of ACBD3 in governing cellular resistance to ferroptosis and suggest that pharmacological manipulation of ACBD3 levels is a promising strategy for cancer therapy.

Pulse pressure variation guided goal-direct fluid therapy decreases postoperative complications in elderly patients undergoing laparoscopic radical resection of colorectal cancer: a randomized controlled trial.

OBJECTIVE: The use of goal-directed fluid therapy (GDFT) has been shown to reduce complications and improve prognosis in high-risk abdominal surgery patients. However, the utilization of pulse pressure variation (PPV) guided GDFT in laparoscopic surgery remains a subject of debate. We hypothesized that utilizing PPV guidance for GDFT would optimize short-term prognosis in elderly patients undergoing laparoscopic radical resection for colorectal cancer compared to conventional fluid therapy. METHODS: Elderly patients undergoing laparoscopic radical resection of colorectal cancer were randomized to receive either PPV guided GDFT or conventional fluid therapy and explore whether PPV guided GDFT can optimize the short-term prognosis of elderly patients undergoing laparoscopic radical resection of colorectal cancer compared with conventional fluid therapy. RESULTS: The incidence of complications was significantly lower in the PPV group compared to the control group (32.8% vs. 57.1%, P = .009). Additionally, the PPV group had a lower occurrence of gastrointestinal dysfunction (19.0% vs. 39.3%, P = .017) and postoperative pneumonia (8.6% vs. 23.2%, P = .033) than the control group. CONCLUSION: Utilizing PPV as a monitoring index for GDFT can improve short-term prognosis in elderly patients undergoing laparoscopic radical resection of colorectal cancer. REGISTRATION NUMBER: ChiCTR2300067361; date of registration: January 5, 2023.

Attention-enhanced dilated convolution for Parkinson's disease detection using transcranial sonography.

BACKGROUND: Transcranial sonography (TCS) plays a crucial role in diagnosing Parkinson's disease. However, the intricate nature of TCS pathological features, the lack of consistent diagnostic criteria, and the dependence on physicians' expertise can hinder accurate diagnosis. Current TCS-based diagnostic methods, which rely on machine learning, often involve complex feature engineering and may struggle to capture deep image features. While deep learning offers advantages in image processing, it has not been tailored to address specific TCS and movement disorder considerations. Consequently, there is a scarcity of research on deep learning algorithms for TCS-based PD diagnosis. METHODS: This study introduces a deep learning residual network model, augmented with attention mechanisms and multi-scale feature extraction, termed AMSNet, to assist in accurate diagnosis. Initially, a multi-scale feature extraction module is implemented to robustly handle the irregular morphological features and significant area information present in TCS images. This module effectively mitigates the effects of artifacts and noise. When combined with a convolutional attention module, it enhances the model's ability to learn features of lesion areas. Subsequently, a residual network architecture, integrated with channel attention, is utilized to capture hierarchical and detailed textures within the images, further enhancing the model's feature representation capabilities. RESULTS: The study compiled TCS images and personal data from 1109 participants. Experiments conducted on this dataset demonstrated that AMSNet achieved remarkable classification accuracy (92.79%), precision (95.42%), and specificity (93.1%). It surpassed the performance of previously employed machine learning algorithms in this domain, as well as current general-purpose deep learning models. CONCLUSION: The AMSNet proposed in this study deviates from traditional machine learning approaches that necessitate intricate feature engineering. It is capable of automatically extracting and learning deep pathological features, and has the capacity to comprehend and articulate complex data. This underscores the substantial potential of deep learning methods in the application of TCS images for the diagnosis of movement disorders.

Structural and functional insights into the epigenetic regulator MRG15.

MORF4-related gene on chromosome 15 (MRG15), a chromatin remodeller, is evolutionally conserved and ubiquitously expressed in mammalian tissues and cells. MRG15 plays vital regulatory roles in DNA damage repair, cell proliferation and division, cellular senescence and apoptosis by regulating both gene activation and gene repression via associations with specific histone acetyltransferase and histone deacetylase complexes. Recently, MRG15 has also been shown to rhythmically regulate hepatic lipid metabolism and suppress carcinoma progression. The unique N-terminal chromodomain and C-terminal MRG domain in MRG15 synergistically regulate its interaction with different cofactors, affecting its functions in various cell types. Thus, how MRG15 elaborately regulates target gene expression and performs diverse functions in different cellular contexts is worth investigating. In this review, we provide an in-depth discussion of how MRG15 controls multiple physiological and pathological processes.