Prolonged ventricular repolarization associated with mild cognitive impairment and white matter hyperintensities: a cross-sectional study.

Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen's criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval.

EEF1B2 regulates bone marrow-derived mesenchymal stem cells bone-fat balance via Wnt/ß-catenin signaling.

The pathological advancement of osteoporosis is caused by the uneven development of bone marrow-derived mesenchymal stem cells (BMSCs) in terms of osteogenesis and adipogenesis. While the role of EEF1B2 in intellectual disability and tumorigenesis is well established, its function in the bone-fat switch of BMSCs is still largely unexplored. During the process of osteogenic differentiation, we observed an increase in the expression of EEF1B2, while a decrease in its expression was noted during adipogenesis. Suppression of EEF1B2 hindered the process of osteogenic differentiation and mineralization while promoting adipogenic differentiation. On the contrary, overexpression of EEF1B2 enhanced osteogenesis and strongly inhibited adipogenesis. Furthermore, the excessive expression of EEF1B2 in the tibias has the potential to mitigate bone loss and decrease marrow adiposity in mice with osteoporosis. In terms of mechanism, the suppression of ß-catenin activity occurred when EEF1B2 function was suppressed during osteogenesis. Our collective findings indicate that EEF1B2 functions as a regulator, influencing the differentiation of BMSCs and maintaining a balance between bone and fat. Our finding highlights its potential as a therapeutic target for diseases related to bone metabolism.

CRIP1 regulates osteogenic differentiation of bone marrow stromal cells and pre-osteoblasts via the Wnt signaling pathway.

With the aging of the global demographic, the prevention and treatment of osteoporosis are becoming crucial issues. The gradual loss of self-renewal and osteogenic differentiation capabilities in bone marrow stromal cells (BMSCs) is one of the key factors contributing to osteoporosis. To explore the regulatory mechanisms of BMSCs differentiation, we collected bone marrow cells of femoral heads from patients undergoing total hip arthroplasty for single-cell RNA sequencing analysis. Single-cell RNA sequencing revealed significantly reduced CRIP1 (Cysteine-Rich Intestinal Protein 1) expression and osteogenic capacity in the BMSCs of osteoporosis patients compared to non-osteoporosis group. CRIP1 is a gene that encodes a member of the LIM/double zinc finger protein family, which is involved in the regulation of various cellular processes including cell growth, development, and differentiation. CRIP1 knockdown resulted in decreased alkaline phosphatase activity, mineralization and expression of osteogenic markers, indicating impaired osteogenic differentiation. Conversely, CRIP1 overexpression, both in vitro and in vivo, enhanced osteogenic differentiation and rescued bone mass reduction in ovariectomy-induced osteoporosis mice model. The study further established CRIP1's modulation of osteogenesis through the Wnt signaling pathway, suggesting that targeting CRIP1 could offer a novel approach for osteoporosis treatment by promoting bone formation and preventing bone loss.

Optimising brain age estimation through transfer learning: A suite of pre-trained foundation models for improved performance and generalisability in a clinical setting.

Estimated age from brain MRI data has emerged as a promising biomarker of neurological health. However, the absence of large, diverse, and clinically representative training datasets, along with the complexity of managing heterogeneous MRI data, presents significant barriers to the development of accurate and generalisable models appropriate for clinical use. Here, we present a deep learning framework trained on routine clinical data (N up to 18,890, age range 18-96 years). We trained five separate models for accurate brain age prediction (all with mean absolute error ≤4.0 years, R2 ≥ .86) across five different MRI sequences (T2 -weighted, T2 -FLAIR, T1 -weighted, diffusion-weighted, and gradient-recalled echo T2 *-weighted). Our trained models offer dual functionality. First, they have the potential to be directly employed on clinical data. Second, they can be used as foundation models for further refinement to accommodate a range of other MRI sequences (and therefore a range of clinical scenarios which employ such sequences). This adaptation process, enabled by transfer learning, proved effective in our study across a range of MRI sequences and scan orientations, including those which differed considerably from the original training datasets. Crucially, our findings suggest that this approach remains viable even with limited data availability (as low as N = 25 for fine-tuning), thus broadening the application of brain age estimation to more diverse clinical contexts and patient populations. By making these models publicly available, we aim to provide the scientific community with a versatile toolkit, promoting further research in brain age prediction and related areas.

Decreased expression of GEM in osteoarthritis cartilage regulates chondrogenic differentiation via Wnt/ß-catenin signaling.

BACKGROUND: GEM (GTP-binding protein overexpressed in skeletal muscle) is one of the atypical small GTPase subfamily members recently identified as a regulator of cell differentiation. Abnormal chondrogenesis coupled with an imbalance in the turnover of cartilaginous matrix formation is highly relevant to the onset and progression of osteoarthritis (OA). However, how GEM regulates chondrogenic differentiation remains unexplored. METHODS: Cartilage tissues were obtained from OA patients and graded according to the ORASI and ICRS grading systems. The expression alteration of GEM was detected in the Grade 4 cartilage compared to Grade 0 and verified in OA mimic culture systems. Next, to investigate the specific function of GEM during these processes, we generated a Gem knockdown (Gem-Kd) system by transfecting siRNA targeting Gem into ATDC5 cells. Acan, Col2a1, Sox9, and Wnt target genes of Gem-Kd ATDC5 cells were detected during induction. The transcriptomic sequencing analysis was performed to investigate the mechanism of GEM regulation. Wnt signaling pathways were verified by real-time PCR and immunoblot analysis. Finally, a rescue model generated by treating Gem-KD ATDC5 cells with a Wnt signaling agonist was established to validate the mechanism identified by RNA sequencing analysis. RESULTS: A decreased expression of GEM in OA patients' cartilage tissues and OA mimic chondrocytes was observed. While during chondrogenesis differentiation and cartilage matrix formation, the expression of GEM was increased. Gem silencing suppressed chondrogenic differentiation and the expressions of Acan, Col2a1, and Sox9. RNA sequencing analysis revealed that Wnt signaling was downregulated in Gem-Kd cells. Decreased expression of Wnt signaling associated genes and the total ß-CATENIN in the nucleus and cytoplasm were observed. The exogenous Wnt activation exhibited reversed effect on Gem loss-of-function cells. CONCLUSION: These findings collectively validated that GEM functions as a novel regulator mediating chondrogenic differentiation and cartilage matrix formation through Wnt/ß-catenin signaling.

A+T rich interaction domain protein 3a (Arid3a) impairs Mertk-mediated efferocytosis in cholestasis.

BACKGROUND & AIMS: Macrophages are key elements in the pathogenesis of cholestatic liver diseases. Arid3a plays a prominent role in the biologic properties of hematopoietic stem cells, B lymphocytes and tumor cells, but its ability to modulate macrophage function during cholestasis remains unknown. METHODS: Gene and protein expression and cellular localization were assessed by q-PCR, immunohistochemistry, immunofluorescence staining and flow cytometry. We generated myeloid-specific Arid3a knockout mice and established three cholestatic murine models. The transcriptome was analyzed by RNA-seq. A specific inhibitor of the Mertk receptor was used in vitro and in vivo. Promoter activity was determined by chromatin immunoprecipitation-seq against Arid3a and a luciferase reporter assay. RESULTS: In cholestatic murine models, myeloid-specific deletion of Arid3a alleviated cholestatic liver injury (accompanied by decreased accumulation of macrophages). Arid3a-deficient macrophages manifested a more reparative phenotype, which was eliminated by in vitro treatment with UNC2025, a specific inhibitor of the efferocytosis receptor Mertk. Efferocytosis of apoptotic cholangiocytes was enhanced in Arid3a-deficient macrophages via upregulation of Mertk. Arid3a negatively regulated Mertk transcription by directly binding to its promoter. Targeting Mertk in vivo effectively reversed the protective phenotype of Arid3a deficiency in macrophages. Arid3a was upregulated in hepatic macrophages and circulating monocytes in primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC). Mertk was correspondingly upregulated and negatively correlated with Arid3a expression in PBC and PSC. Mertk+ cells were located in close proximity to cholangiocytes, while Arid3a+ cells were scattered among immune cells with greater spatial distances to hyperplastic cholangiocytes in PBC and PSC. CONCLUSIONS: Arid3a promotes cholestatic liver injury by impairing Mertk-mediated efferocytosis of apoptotic cholangiocytes by macrophages during cholestasis. The Arid3a-Mertk axis is a promising novel therapeutic target for cholestatic liver diseases. IMPACT AND IMPLICATIONS: Macrophages play an important role in the pathogenesis of cholestatic liver diseases. This study reveals that macrophages with Arid3a upregulation manifest a pro-inflammatory phenotype and promote cholestatic liver injury by impairing Mertk-mediated efferocytosis of apoptotic cholangiocytes during cholestasis. Although we now offer a new paradigm to explain how efferocytosis is regulated in a myeloid cell autonomous manner, the regulatory effects of Arid3a on chronic liver diseases remain to be further elucidated.

Temporal transcriptome features identify early skeletal commitment during human epiphysis development at single-cell resolution.

Human epiphyseal development has been mainly investigated through radiological and histological approaches, uncovering few details of cellular temporal genetic alternations. Using single-cell RNA sequencing, we investigated the dynamic transcriptome changes during post-conception weeks (PCWs) 15-25 of human distal femoral epiphysis cells. We find epiphyseal cells contain multiple subtypes distinguished by specific markers, gene signatures, Gene Ontology (GO) enrichment analysis, and gene set variation analysis (GSVA). We identify the populations committed to cartilage or ossification at this time, although the secondary ossification centers (SOCs) have not formed. We describe the temporal alternation in transcriptional expression utilizing trajectories, transcriptional regulatory networks, and intercellular communication analyses. Moreover, we find the emergence of the ossification-committed population is correlated with the COL2A1-(ITGA2/11+ITGB1) signaling. NOTCH signaling may contribute to the formation of cartilage canals and ossification via NOTCH signaling. Our findings will advance the understanding of single-cell genetic changes underlying fetal epiphysis development.

Multi-Modal Learning for Predicting the Genotype of Glioma.

The isocitrate dehydrogenase (IDH) gene mutation is an essential biomarker for the diagnosis and prognosis of glioma. It is promising to better predict glioma genotype by integrating focal tumor image and geometric features with brain network features derived from MRI. Convolutional neural networks show reasonable performance in predicting IDH mutation, which, however, cannot learn from non-Euclidean data, e.g., geometric and network data. In this study, we propose a multi-modal learning framework using three separate encoders to extract features of focal tumor image, tumor geometrics and global brain networks. To mitigate the limited availability of diffusion MRI, we develop a self-supervised approach to generate brain networks from anatomical multi-sequence MRI. Moreover, to extract tumor-related features from the brain network, we design a hierarchical attention module for the brain network encoder. Further, we design a bi-level multi-modal contrastive loss to align the multi-modal features and tackle the domain gap at the focal tumor and global brain. Finally, we propose a weighted population graph to integrate the multi-modal features for genotype prediction. Experimental results on the testing set show that the proposed model outperforms the baseline deep learning models. The ablation experiments validate the performance of different components of the framework. The visualized interpretation corresponds to clinical knowledge with further validation. In conclusion, the proposed learning framework provides a novel approach for predicting the genotype of glioma.

Nonalcoholic steatohepatitis critically rewires the ischemia/reperfusion-induced dysregulation of cardiolipins and sphingolipids in mice.

Background: Lipid dysregulation plays a fundamental role in nonalcoholic steatohepatitis (NASH), which is an emerging critical risk factor that aggravates hepatic ischemia/reperfusion (I/R) injury. However, the specific lipids that mediate the aggressive I/R injury in NASH livers have not yet been identified. Methods: The mouse model of hepatic I/R injury on NASH was established on C56B/6J mice by first feeding the mice with a Western-style diet to induce NASH, then the NASH mice were subjected to surgical procedures to induce hepatic I/R injury. Untargeted lipidomics were performed to determine hepatic lipids in NASH livers with I/R injury through ultra-high performance liquid chromatography coupled with mass spectrometry. The pathology associated with the dysregulated lipids was examined. Results: Lipidomics analyses identified cardiolipins (CL) and sphingolipids (SL), including ceramides (CER), glycosphingolipids, sphingosines, and sphingomyelins, as the most relevant lipid classes that characterized the lipid dysregulation in NASH livers with I/R injury. CER were increased in normal livers with I/R injury, and the I/R-induced increase of CER was further augmented in NASH livers. Metabolic pathway analysis revealed that the enzymes involved in the synthesis and degradation of CER were highly upregulated in NASH livers with I/R injury, including serine palmitoyltransferase 3 (Sptlc3), ceramide synthase 2 (Cers2), neutral sphingomyelinase 2 (Smpd3), and glucosylceramidase beta 2 (Gba2) that produced CER, and alkaline ceramidase 2 (Acer2), alkaline ceramidase 3 (Acer3), sphingosine kinase 1 (Sphk1), sphingosine-1-phosphate lyase (Sgpl1), and sphingosine-1-phosphate phosphatase 1 (Sgpp1) that catalyzed the degradation of CER. CL were not affected by I/R challenge in normal livers, but CL was dramatically reduced in NASH livers with I/R injury. Consistently, metabolic pathway analyses revealed that the enzymes catalyzing the generation of CL were downregulated in NASH-I/R injury, including cardiolipin synthase (Crls1) and tafazzin (Taz). Notably, the I/R-induced oxidative stress and cell death were found to be aggravated in NASH livers, which were possibly mediated by the reduction of CL and accumulation of CER. Conclusions: The I/R-induced dysregulation of CL and SL were critically rewired by NASH, which might potentially mediate the aggressive I/R injury in NASH livers.

Multi-UAV Path Planning in GPS and Communication Denial Environment.

This paper proposes a feature fusion algorithm for solving the path planning problem of multiple unmanned aerial vehicles (UAVs) using GPS and communication denial conditions. Due to the blockage of GPS and communication, UAVs cannot obtain the precise position of a target, which leads to the failure of path planning algorithms. This paper proposes a feature fusion proximal policy optimization (FF-PPO) algorithm based on deep reinforcement learning (DRL); the algorithm can fuse image recognition information with the original image, realizing the multi-UAV path planning algorithm without an accurate target location. In addition, the FF-PPO algorithm adopts an independent policy for multi-UAV communication denial environments, which enables the distributed control of UAVs such that multi-UAVs can realize the cooperative path planning task without communication. The success rate of our proposed algorithm can reach more than 90% in the multi-UAV cooperative path planning task. Finally, the feasibility of the algorithm is verified by simulations and hardware.

A regulatory variant at 19p13.3 is associated with primary biliary cholangitis risk and ARID3A expression.

Genome-wide association studies have identified 19p13.3 locus associated with primary biliary cholangitis (PBC). Here we aim to identify causative variant(s) and initiate efforts to define the mechanism by which the 19p13.3 locus variant(s) contributes to the pathogenesis of PBC. A genome-wide meta-analysis of 1931 PBC subjects and 7852 controls in two Han Chinese cohorts confirms the strong association between 19p13.3 locus and PBC. By integrating functional annotations, luciferase reporter assay and allele-specific chromatin immunoprecipitation, we prioritize rs2238574, an AT-Rich Interaction Domain 3A (ARID3A) intronic variant, as a potential causal variant at 19p13.3 locus. The risk allele of rs2238574 shows higher binding affinity of transcription factors, leading to an increased enhancer activity in myeloid cells. Genome-editing demonstrates the regulatory effect of rs2238574 on ARID3A expression through allele-specific enhancer activity. Furthermore, knock-down of ARID3A inhibits myeloid differentiation and activation pathway, and overexpression of the gene has the opposite effect. Finally, we find ARID3A expression and rs2238574 genotypes linked to disease severity in PBC. Our work provides several lines of evidence that a non-coding variant regulates ARID3A expression, presenting a mechanistic basis for association of 19p13.3 locus with the susceptibility to PBC.

Structural connectome quantifies tumour invasion and predicts survival in glioblastoma patients.

Glioblastoma is characterized by diffuse infiltration into the surrounding tissue along white matter tracts. Identifying the invisible tumour invasion beyond focal lesion promises more effective treatment, which remains a significant challenge. It is increasingly accepted that glioblastoma could widely affect brain structure and function, and further lead to reorganization of neural connectivity. Quantifying neural connectivity in glioblastoma may provide a valuable tool for identifying tumour invasion. Here we propose an approach to systematically identify tumour invasion by quantifying the structural connectome in glioblastoma patients. We first recruit two independent prospective glioblastoma cohorts: the discovery cohort with 117 patients and validation cohort with 42 patients. Next, we use diffusion MRI of healthy subjects to construct tractography templates indicating white matter connection pathways between brain regions. Next, we construct fractional anisotropy skeletons from diffusion MRI using an improved voxel projection approach based on the tract-based spatial statistics, where the strengths of white matter connection and brain regions are estimated. To quantify the disrupted connectome, we calculate the deviation of the connectome strengths of patients from that of the age-matched healthy controls. We then categorize the disruption into regional disruptions on the basis of the relative location of connectome to focal lesions. We also characterize the topological properties of the patient connectome based on the graph theory. Finally, we investigate the clinical, cognitive and prognostic significance of connectome metrics using Pearson correlation test, mediation test and survival models. Our results show that the connectome disruptions in glioblastoma patients are widespread in the normal-appearing brain beyond focal lesions, associated with lower preoperative performance (P < 0.001), impaired cognitive function (P < 0.001) and worse survival (overall survival: hazard ratio = 1.46, P = 0.049; progression-free survival: hazard ratio = 1.49, P = 0.019). Additionally, these distant disruptions mediate the effect on topological alterations of the connectome (mediation effect: clustering coefficient -0.017, P < 0.001, characteristic path length 0.17, P = 0.008). Further, the preserved connectome in the normal-appearing brain demonstrates evidence of connectivity reorganization, where the increased neural connectivity is associated with better overall survival (log-rank P = 0.005). In conclusion, our connectome approach could reveal and quantify the glioblastoma invasion distant from the focal lesion and invisible on the conventional MRI. The structural disruptions in the normal-appearing brain were associated with the topological alteration of the brain and could indicate treatment target. Our approach promises to aid more accurate patient stratification and more precise treatment planning.

Serum Biomarkers for Autoimmune Hepatitis Type 1: the Case for CD48 and a Review of the Literature.

In autoimmune hepatitis (AIH), the persisting inflammation contributes to fibrosis progression, for which conventional biochemical markers manifest relatively unsatisfactory prediction. Herein, we assessed the value of serum CD48 (sCD48) as an indicator for inflammation and fibrosis in AIH type 1. The levels of sCD48 were detected first in an exploratory cohort using ELISA. In this cohort, compared with healthy controls (4.90 ng/mL, P < 0.0001), primary biliary cholangitis (7.32 ng/mL, P < 0.0001), and non-alcoholic fatty liver disease (7.76 ng/mL, P < 0.0001), sCD48 levels were elevated in AIH (12.81 ng/mL) and correlated with histological inflammation and fibrosis. Further using multivariate logistic regression analysis, sCD48 was identified as an independent predictor for both significant inflammation (G3-4) and advanced fibrosis (S3-4). Two predictive scores, based on sCD48, were constructed for diagnosing significant inflammation and advanced fibrosis (sCD48-AIH-SI and sCD48-AIH-AF, respectively). Using these data as a premise, predictive abilities were subsequently evaluated and verified in a validation cohort. In the exploratory cohort, the area under the receiver operating characteristic curve of sCD48 and sCD48-AIH-SI, for significant inflammation, were 0.748 and 0.813, respectively. Besides, during treatment follow-up, sCD48 levels gradually decreased from immunosuppression initiation to re-evaluation biopsy, in parallel with aspartate transaminase, total sera IgG, and fibrosis-4 score. For AIH patients in a re-evaluation biopsy cohort, sCD48 could predict significant fibrosis (S2-4). Further using immunohistochemistry, hepatic CD48 expression was elevated in AIH patients and decreased after treatment. In conclusion, sCD48 and sCD48-based predictive scores predict histological inflammation and fibrosis in AIH-1. Detecting sCD48 might help in the clinical management of AIH.

Prognostic significance of MRI-based late-course tumor volume in locoregionally advanced nasopharyngeal carcinoma.

BACKGROUND: To validate tumor volume-based imaging markers for predicting local recurrence-free survival (LRFS) in locoregionally advanced nasopharyngeal carcinoma patients, who underwent induction chemotherapy followed by definitive intensity-modulated radiotherapy. METHODS: We enrolled 145 patients with stage III-IVA nasopharyngeal carcinoma in this retrospective study. Pre-treatment tumor volume (Vpre) and late-course volume (LCV) were measured based on the MRIs scanned before treatment and during the first 3 days in the sixth week of radiotherapy, respectively. The volume regression rate (VRR) was calculated according to Vpre and LCV. Receiver operating characteristic (ROC) curves were used to identify the cut-off best separating patient subgroups in assessing the prognostic value of Vpre, LCV and VRR. The Kaplan-Meier method was used for survival analysis. Prognostic analyses were performed using univariate and multivariate COX proportional hazard models. RESULTS: The LCV was 5.3 ± 0.5 (range 0-42.1) cm3; The VRR was 60.4 ± 2.2% (range 2.9-100.0). The median follow-up period was 36 months (range 6-98 months). The cut-off value of LCV determined by the ROC was 6.8 cm3 for LRFS prediction (sensitivity 68.8%; specificity 79.8%). The combination of LCV and VRR for LRFS prediction (AUC = 0.79, P < 0.001, 95% CI 0.67-0.90), LCV (AUC = 0.74, P = 0.002, 95% CI 0.60-0.88) and Vpre (AUC = 0.71, P = 0.007, 95% CI 0.56-0.85) are better than T category (AUC = 0.64, P = 0.062, 95% CI 0.50-0.79) alone. Patients with LCV ≤ 6.8 cm3 had significantly longer LRFS (P < 0.001), disease-free survival (DFS, P < 0.001) and overall survival (OS, P = 0.005) than those with LCV > 6.8 cm3. Multivariate Cox regression showed LCV was the only independent prognostic factor for local control (HR = 7.80, 95% CI 2.69-22.6, P < 0.001). CONCLUSIONS: LCV is a promising prognostic factor for local control and chemoradiosensitivity in patients with locoregionally advanced NPC. The LCV, and the combination of LCV with VRR are more robust predictors for patient survival than T category.

The burden associated with, and management of, difficult-to-treat depression in patients under specialist psychiatric care in the United Kingdom.

BACKGROUND: Major depressive disorder (MDD) is common and often has sub-optimal response to treatment. Difficult-to-treat depression (DTD) is a new concept that describes 'depression that continues to cause significant burden despite usual treatment efforts'. AIMS: To identify patients with likely DTD in UK secondary care and examine demographic, disease and treatment data as compared with 'non-DTD' MDD patients. METHODS: Anonymised electronic health records (EHRs) of five specialist mental health National Health Service (NHS) Trusts in the United Kingdom were analysed using a natural language processing model. Data on disease characteristics, comorbidities and treatment histories were extracted from structured fields and using natural language algorithms from unstructured fields. Patients with MDD aged ⩾18 years were included in the analysis; those with presumed DTD were identified on the basis of MDD history (duration and recurrence) and number of treatments prescribed. RESULTS: In a sample of 28,184 patients with MDD, 19% met criteria for DTD. Compared to the non-DTD group, patients with DTD were more likely to have severe depression, suicidal ideation, and comorbid psychiatric and/or physical illness, as well as higher rates of hospitalisation. They were also more likely to be in receipt of unemployment and sickness/disability benefits. More intensive treatment strategies were used in the DTD group, including higher rates of combination therapy, augmentation, psychotherapy and electroconvulsive therapy. CONCLUSION: This study demonstrates the feasibility of identifying patients with probable DTD from EHRs and highlights the increased burden associated with MDD in these patients.

Manifold Roles of Ceramide Metabolism in Non-Alcoholic Fatty Liver Disease and Liver Cancer.

Non-alcoholic fatty liver disease (NAFLD) is a metabolic disorder manifested in hepatic fat accumulation (hepatic steatosis) in the absence of heavy alcohol use. NAFLD consists of four major stages ranging from simple steatosis or non-alcoholic fatty liver (NAFL) to more advanced stages, non-alcoholic steatohepatitis (NASH), fibrosis, and cirrhosis. NFLAD may further advance to hepatocellular carcinoma (HCC). Primary causes of NAFLD are obesity and obesity-associated insulin resistance (IR). As a result of the obesity pandemic, NAFLD has become one of the most common liver disorders worldwide and both the incidence and mortality rate of HCC that develops from NAFLD are increasing steadily. As treatment options are not available for advanced NAFLD, a better understanding of the molecular mechanisms for NAFLD development and progression is urgently needed. Emerging evidence suggests that dysregulation of the metabolism of sphingolipids contributes to development and progression of NAFLD and NAFLD-associated HCC. The present chapter summarizes roles of bioactive sphingolipids, ceramides, sphingosine, and sphingosine-1-phosphate (S1P) and their metabolizing enzymes in NAFLD and HCC.

Utility of 2-Diphenylphosphoryloxy-1,3-Dienes in Multicomponent Hetero-Diels-Alder Reactions to Construct Functionalized Six-Membered Nitrogen Heterocycles.

The utility of 2-diphenylphosphoryloxy-1,3-dienes for the construction of substituted six-membered nitrogen heterocycles is presented. These dienes undergo boron trifluoride-promoted aza-Diels-Alder reactions when reacted with imines or related species formed in situ using aldehydes and amine derivatives. The stability of the dienes allows this three-component reaction to be carried out with no special precautions to eliminate water or air. Thirty-one examples of this process are presented. The usefulness of the enol phosphate functional group is highlighted in further reactions after the cycloaddition step to generate functionalized piperidenes or pyridines.

BOEC-Exo Addition Promotes In Vitro Maturation of Bovine Oocyte and Enhances the Developmental Competence of Early Embryos.

Exosomes are nano-sized vesicles with abundant nucleic acids, proteins, lipids, and other regulatory molecules. The aim of this study was to examine the effect of BOEC-Exo on bovine in vitro oocyte maturation and in vitro embryo development. We found that a 3% Exo supplementation to IVM media significantly enhanced the oocyte maturation and reduced the accumulation of ROS in MII-stage bovine oocytes. Oocyte maturation related genes (GDF9 and CPEB1) also confirmed that 3% Exo treatment to oocytes significantly (p < 0.05) enhanced the oocyte maturation. Next, we cultured bovine cumulus cells and assessed the effects of 3% Exo, which showed a reduced level of apoptotic proteins (caspase-3 and p-NF-κB protein expressions). Furthermore, we examined the gap junction (CX43 and CX37) and cumulus cells expansion related genes (HAS2, PTX3, and GREM1) in cumulus-oocyte complexes (COCs), and all those genes showed significantly (p < 0.05) higher expressions in 3% Exo-treated COCs as compared with the control group. Moreover, peroxisome proliferator-activated receptors (PPARs) and lipid metabolism-related genes (CPT1 and FABP3) were also analyzed in both the control and 3% Exo groups and the results showed significant (p < 0.05) enhancement in the lipid metabolism. Finally, the oocytes matured in the presence of 3% Exo showed a significantly higher rate of embryo development and better implantation potential. Finally, we concluded that Exo positively influenced bovine oocyte in vitro maturation and improved the early embryo's developmental competence.

Altered faecal microbiome and metabolome in IgG4-related sclerosing cholangitis and primary sclerosing cholangitis.

OBJECTIVE: Multiple clinical similarities exist between IgG4-related sclerosing cholangitis (IgG4-SC) and primary sclerosing cholangitis (PSC), and while gut dysbiosis has been extensively studied in PSC, the role of the gut microbiota in IgG4-SC remains unknown. Herein, we aimed to evaluate alterations of the gut microbiome and metabolome in IgG4-SC and PSC. DESIGN: We performed 16S rRNA gene amplicon sequencing of faecal samples from 135 subjects with IgG4-SC (n=34), PSC (n=37) and healthy controls (n=64). A subset of the samples (31 IgG4-SC, 37 PSC and 45 controls) also underwent untargeted metabolomic profiling. RESULTS: Compared with controls, reduced alpha-diversity and shifted microbial community were observed in IgG4-SC and PSC. These changes were accompanied by differences in stool metabolomes. Importantly, despite some common variations in the microbiota composition and metabolic activity, integrative analyses identified distinct host-microbe associations in IgG4-SC and PSC. The disease-associated genera and metabolites tended to associate with the transaminases in IgG4-SC. Notable depletion of Blautia and elevated succinic acid may underlie hepatic inflammation in IgG4-SC. In comparison, potential links between the microbial or metabolic signatures and cholestatic parameters were detected in PSC. Particularly, concordant decrease of Eubacterium and microbiota-derived metabolites, including secondary bile acids, implicated novel host-microbial metabolic pathways involving cholestasis of PSC. Interestingly, the predictive models based on metabolites were more effective in discriminating disease status than those based on microbes. CONCLUSIONS: Our data reveal that IgG4-SC and PSC possess divergent host-microbe interplays that may be involved in disease pathogenesis. These data emphasise the uniqueness of IgG4-SC.