Sorafenib inhibits ossification of the posterior longitudinal ligament by blocking LOXL2-mediated vascularization.

Ossification of the Posterior Longitudinal Ligament (OPLL) is a degenerative hyperostosis disease characterized by the transformation of the soft and elastic vertebral ligament into bone, resulting in limited spinal mobility and nerve compression. Employing both bulk and single-cell RNA sequencing, we elucidate the molecular characteristics, cellular components, and their evolution during the OPLL process at a single-cell resolution, and validate these findings in clinical samples. This study also uncovers the capability of ligament stem cells to exhibit endothelial cell-like phenotypes in vitro and in vivo. Notably, our study identifies LOXL2 as a key regulator in this process. Through gain-and loss-of-function studies, we elucidate the role of LOXL2 in the endothelial-like differentiation of ligament cells. It acts via the HIF1A pathway, promoting the secretion of downstream VEGFA and PDGF-BB. This function is not related to the enzymatic activity of LOXL2. Furthermore, we identify sorafenib, a broad-spectrum tyrosine kinase inhibitor, as an effective suppressor of LOXL2-mediated vascular morphogenesis. By disrupting the coupling between vascularization and osteogenesis, sorafenib demonstrates significant inhibition of OPLL progression in both BMP-induced and enpp1 deficiency-induced animal models while having no discernible effect on normal bone mass. These findings underscore the potential of sorafenib as a therapeutic intervention for OPLL.

Current State of Consultation-liaison Psychiatry in China and Future Directions.

This article provides an overview of the history and current status of Consultation-Liaison Psychiatry (CLP) in China and its development within the Chinese Society of Psychosomatic Medicine. Over the past decade, various CLP practice models have been developed to meet the diverse needs of different regions in China. Notably, the Chinese Multidisciplinary Integrated Centers of Psychosomatic Medicine have been established as regional hubs throughout the country. Additionally, this article delves into the role of Chinese traditional medicine in the practice of CLP in China. Finally, several projects involving CLP-based multidisciplinary collaboration are highlighted. We hope this article offers a bird's-eye view of CLP in China and opens a window for future collaboration with CLP initiatives in other countries.

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.

Synthesis and Evaluation of [18F]AlF-NOTA-c-DVAP: A Novel PET Probe for Imaging GRP78 in Cancer.

GRP78, a member of the HSP70 superfamily, is an endoplasmic reticulum chaperone protein overexpressed in various cancers, making it a promising target for cancer imaging and therapy. Positron emission tomography (PET) imaging offers unique advantages in real time, noninvasive tumor imaging, rendering it a suitable tool for targeting GRP78 in tumor imaging to guide targeted therapy. Several studies have reported successful tumor imaging using PET probes targeting GRP78. However, existing PET probes face challenges such as low tumor uptake, inadequate in vivo distribution, and high abdominal background signal. Therefore, this study introduces a novel peptide PET probe, [18F]AlF-NOTA-c-DVAP, for targeted tumor imaging of GRP78. [18F]AlF-NOTA-c-DVAP was radiolabeled with fluoride-18 using the aluminum-[18F]fluoride ([18F]AlF) method. The study assessed the partition coefficients, stability in vitro, and metabolic stability of [18F]AlF-NOTA-c-DVAP. Micro-PET imaging, pharmacokinetic analysis, and biodistribution studies were carried out in tumor-bearing mice to evaluate the probe's performance. Docking studies and pharmacokinetic analyses of [18F]AlF-NOTA-c-DVAP were also performed. Immunohistochemical and immunofluorescence analyses were conducted to confirm GRP78 expression in tumor tissues. The probe's binding affinity to GRP78 was analyzed by molecular docking simulation. [18F]AlF-NOTA-c-DVAP was radiolabeled in just 25 min with a high yield of 51 ± 16%, a radiochemical purity of 99%, and molar activity within the range of 20-50 GBq/µmol. [18F]AlF-NOTA-c-DVAP demonstrated high stability in vitro and in vivo, with a logD value of -3.41 ± 0.03. Dynamic PET imaging of [18F]AlF-NOTA-c-DVAP in tumors showed rapid uptake and sustained retention, with minimal background uptake. Biodistribution studies revealed rapid blood clearance and excretion through the kidneys following a single-compartment reversible metabolic model. In PET imaging, the T/M ratios for A549 tumors (high GRP78 expression), MDA-MB-231 tumors (medium expression), and HepG2 tumors (low expression) at 60 min postintravenous injection were 10.48 ± 1.39, 6.25 ± 0.47, and 3.15 ± 1.15% ID/g, respectively, indicating a positive correlation with GRP78 expression. This study demonstrates the feasibility of using [18F]AlF-NOTA-c-DVAP as a PET tracer for imaging GRP78 in tumors. The probe shows promising results in terms of stability, specificity, and tumor targeting. Further research may explore the clinical utility and potential therapeutic applications of this PET tracer for cancer diagnosis.

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.

Altered Static and Dynamic Brain Functional Topological Organization in Patients with Dysthyroid Optic Neuropathy.

CONTEXT: Dysthyroid optic neuropathy (DON) is a serious vision-threatening complication of thyroid-associated ophthalmopathy (TAO). Exploration of the underlying mechanisms of DON is critical for its timely clinical diagnosis. OBJECTIVE: We hypothesized that TAO patients with DON may have altered brain functional networks. We aimed to explore the alterations of static and dynamic functional connectomes in patients with and without DON using resting-state functional MRI with graph theory method. DESIGN: A cross-sectional study. SETTING: Grade A tertiary hospital. PARTICIPANTS: Sixty-six TAO patients (28 DON and 38 non-DON) and 30 healthy controls (HCs). MAIN OUTCOME MEASURES: Topological properties of functional networks. RESULTS: For static properties, DON patients exhibited lower global efficiency (Eg), local efficiency, normalized clustering coefficient, small-worldness (σ), and higher characteristic path length (Lp) than HCs. Both DON and non-DON patients exhibited varying degrees of abnormalities in nodal properties. Meanwhile, compared with non-DON, DON patients exhibited abnormalities in nodal properties in orbitofrontal cortex and visual network (VN). For dynamic properties, DON group exhibited higher variance in Eg and Lp than non-DON and HC groups. A strengthened subnetwork with VN as the core was identified in DON cohort. Significant correlations were found between network properties and clinical variables. For distinguishing DON, the combination of static and dynamic network properties exhibited optimal diagnostic performance. CONCLUSION: Functional network alterations were observed in both DON and non-DON patients, providing novel insights into the underlying neural mechanisms of disease. Functional network properties may be potential biomarkers for reflecting the progression of TAO from non-DON to DON.

Alzheimer's disease early diagnostic and staging biomarkers revealed by large-scale cerebrospinal fluid and serum proteomic profiling.

Amyloid-ß, tau pathology, and biomarkers of neurodegeneration make up the core diagnostic biomarkers of Alzheimer disease (AD). However, these proteins represent only a fraction of the complex biological processes underlying AD, and individuals with other brain diseases in which AD pathology is a comorbidity also test positive for these diagnostic biomarkers. More AD-specific early diagnostic and disease staging biomarkers are needed. In this study, we performed tandem mass tag proteomic analysis of paired cerebrospinal fluid (CSF) and serum samples in a discovery cohort comprising 98 participants. Candidate biomarkers were validated by parallel reaction monitoring-based targeted proteomic assays in an independent multicenter cohort comprising 288 participants. We quantified 3,238 CSF and 1,702 serum proteins in the discovery cohort, identifying 171 and 860 CSF proteins and 37 and 323 serum proteins as potential early diagnostic and staging biomarkers, respectively. In the validation cohort, 58 and 21 CSF proteins, as well as 12 and 18 serum proteins, were verified as early diagnostic and staging biomarkers, respectively. Separate 19-protein CSF and an 8-protein serum biomarker panels were built by machine learning to accurately classify mild cognitive impairment (MCI) due to AD from normal cognition with areas under the curve of 0.984 and 0.881, respectively. The 19-protein CSF biomarker panel also effectively discriminated patients with MCI due to AD from patients with other neurodegenerative diseases. Moreover, we identified 21 CSF and 18 serum stage-associated proteins reflecting AD stages. Our findings provide a foundation for developing blood-based tests for AD screening and staging in clinical practice.

Diagnosis of dysthyroid optic neuropathy: combined value of orbital MRI and intracranial visual pathway diffusion kurtosis imaging.

OBJECTIVES: To evaluate the combined performance of orbital MRI and intracranial visual pathway diffusion kurtosis imaging (DKI) in diagnosing dysthyroid optic neuropathy (DON). METHODS: We retrospectively enrolled 61 thyroid-associated ophthalmopathy (TAO) patients, including 25 with DON (40 eyes) and 36 without DON (72 eyes). Orbital MRI-based apical muscle index (MI), diameter index (DI) of the optic nerve (ON), area index (AI) of the ON, apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) of the ON, DKI-based kurtosis fractional anisotropy (KFA) and mean kurtosis (MK) of the optic tract (OT), optic radiation (OR), and Brodmann areas (BAs) 17, 18, and 19 were measured and compared between groups. The diagnostic performances of models were evaluated using receiver operating characteristic curve analyses and compared using the DeLong test. RESULTS: TAO patients with DON had significantly higher apical MI, apical AI, and SIR of the ON, but significantly lower ADC of the ON than those without DON (p < 0.05). Meanwhile, the DON group exhibited significantly lower KFA across the OT, OR, BA17, BA18, and BA19 and lower MK at the OT and OR than the non-DON group (p < 0.05). The model integrating orbital MRI and intracranial visual pathway DKI parameters performed the best in diagnosing DON (AUC = 0.926), with optimal diagnostic sensitivity (80%) and specificity (94.4%), followed by orbital MRI combination (AUC = 0.890), and then intracranial visual pathway DKI combination (AUC = 0.832). CONCLUSION: Orbital MRI and intracranial visual pathway DKI can both assist in diagnosing DON. Combining orbital and intracranial imaging parameters could further optimize diagnostic efficiency. CLINICAL RELEVANCE STATEMENT: The novel finding could bring novel insights into the precise diagnosis and treatment of dysthyroid optic neuropathy, accordingly, contributing to the improvement of the patients' prognosis and quality of life in the future. KEY POINTS: • Orbital MRI and intracranial visual pathway diffusion kurtosis imaging can both assist in diagnosing dysthyroid optic neuropathy. • Combining orbital MRI and intracranial visual pathway diffusion kurtosis imaging optimized the diagnostic efficiency of dysthyroid optic neuropathy.

Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy.

Clear cell ovarian carcinoma (CCOC) is a relatively rare subtype of ovarian cancer (OC) with high degree of resistance to standard chemotherapy. Little is known about the underlying molecular mechanisms, and it remains a challenge to predict its prognosis after chemotherapy. Here, we first analyzed the proteome of 35 formalin-fixed paraffin-embedded (FFPE) CCOC tissue specimens from a cohort of 32 patients with CCOC (H1 cohort) and characterized 8697 proteins using data-independent acquisition mass spectrometry (DIA-MS). We then performed proteomic analysis of 28 fresh frozen (FF) CCOC tissue specimens from an independent cohort of 24 patients with CCOC (H2 cohort), leading to the identification of 9409 proteins with DIA-MS. After bioinformatics analysis, we narrowed our focus to 15 proteins significantly correlated with the recurrence free survival (RFS) in both cohorts. These proteins are mainly involved in DNA damage response, extracellular matrix (ECM), and mitochondrial metabolism. Parallel reaction monitoring (PRM)-MS was adopted to validate the prognostic potential of the 15 proteins in the H1 cohort and an independent confirmation cohort (H3 cohort). Interferon-inducible transmembrane protein 1 (IFITM1) was observed as a robust prognostic marker for CCOC in both PRM data and immunohistochemistry (IHC) data. Taken together, this study presents a CCOC proteomic data resource and a single promising protein, IFITM1, which could potentially predict the recurrence and survival of CCOC.

Escitalopram-induced QTc prolongation and its relationship with KCNQ1, KCNE1, and KCNH2 gene polymorphisms.

BACKGROUND: Escitalopram can cause prolongation of the QT interval on the electrocardiogram (ECG). However, only some patients get pathological QTc prolongation in clinic. We investigated the influence of KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors on escitalopram-induced QTc prolongation. METHODS: A total of 713 patients prescribed escitalopram were identified and had at least one ECG recording in this retrospective study. 472 patients with two or more ECG data were divided into QTc prolongation (n = 119) and non-prolongation (n = 353) groups depending on the threshold change in QTc of 30 ms above baseline value (∆QTc ≥ 30 ms). 45 patients in the QTc prolongation group and 90 patients in the QTc non-prolongation group were genotyped for 43 single nucleotide polymorphisms (SNPs) of KCNQ1, KCNE1, and KCNH2 genes. RESULTS: Patients with QTc prolongation (∆QTc ≥ 30 ms) got higher escitalopram dose (10.3 mg) than patients without QTc prolongation (9.4 mg), although no significant relationship was found between QTc interval and escitalopram dose in the linear mixed model. Patients who were older/coronary disease/hypertension or carried with KCNE1 rs1805127 C allele, KCNE1 rs4817668 C allele, KCNH2 rs3807372 AG/GG genotype were significantly at risk for QTc prolongation (∆QTc ≥ 30 ms). Concomitant antipsychotic treatment was associated with a longer QTc interval. LIMITATIONS: A relatively small sample size and lack of the blood concentration of escitalopram restricted the accurate relationship between escitalopram dose and QTc interval. CONCLUSION: Our study revealed that KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors provide a complementary effect in escitalopram-induced QTc prolongation.

Structural and Functional Brain Changes After Glucocorticoid Therapy in Thyroid-Associated Ophthalmopathy.

OBJECTIVE: To investigate the brain structural and functional alterations in patients with thyroid-associated ophthalmopathy (TAO) before and after glucocorticoid therapy, using voxel-based morphometry (VBM) as well as resting-state functional magnetic resonance imaging (MRI) with amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo). METHODS: Between 2019 and 2022, 32 patients with TAO and 23 healthy controls underwent pre-therapy MRI in Nanjing, China. Intravenous glucocorticoid therapy was administered to all patients. At 3 months after end of therapy, 26 patients were available for rescanned MRI. VBM, ALFF, and ReHo were used to evaluate the brain structural and functional differences. RESULTS: Before therapy, TAO patients showed significantly decreased gray matter volume (GMV) in the left orbital part of superior frontal gyrus (ORBsup) and medial superior frontal gyrus (SFGmed) than healthy controls. Patients had higher ALFF values in bilateral gyrus rectus and olfactory cortex and lower values in bilateral cuneus. Patients also showed decreased ReHo values in bilateral lingual gyrus. After therapy, increased GMV in the left anterior cingulate gyrus and SFGmed, increased ALFF values in bilateral cuneus and superior occipital gyrus, and increased ReHo values in bilateral SFGmed were found in TAO patients compared to the pre-therapy cohort. Compared to controls, decreased GMV in left ORBsup was observed in post-therapy TAO patients. CONCLUSION: Our results indicated that TAO might cause functional and structural deficits in the visual and emotional regions of the brain, with recovery in the former and partial restoration in the latter after effective glucocorticoid therapy. These findings may lead to deeper understanding of the pathophysiological mechanism behind TAO.

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.

PKM2 is a potential prognostic biomarker and related to immune infiltration in lung cancer.

Pyruvate kinase M2 (PKM2), a subtype of pyruvate kinase, plays a crucial role as a key enzyme in the final step of glycolysis. It is involved in regulating the tumor microenvironment and accelerating tumor progression. However, the relationship between PKM2 expression and the prognosis and immune infiltration remains unclear in lung cancer. In this study, we analyzed PKM2 expression in pan-cancer, and investigated its association with prognosis and immune cell infiltration of lung cancer by using multiple online databases, including Gent2, Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), PrognoScan, Kaplan-Meier plotter, and The Human Protein Atlas (HPA). The results showed that PKM2 expression is elevated in tumor tissues compared with the adjacent normal tissues of most cancers, including lung cancer. Prognostic analysis indicated that high expression of PKM2 was associated with poorer prognosis in overall lung cancer patients, especially in lung adenocarcinoma (LUAD). Notably, PKM2 exhibited a strong correlation with B cells and CD4+ T cells in LUAD; and with B cells, CD8+ T cells, CD4+ cells, and macrophages in lung squamous cell carcinoma (LUSC). Furthermore, PKM2 expression displayed a significant negative correlation with the expression of immune cell markers in both LUAD and LUSC. These findings suggested that PKM2 could serve as a promising prognostic biomarker for lung cancer and provided insights into its essential role in modulating the immune cell infiltration.

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.

Increased brain iron in patients with thyroid-associated ophthalmopathy: a whole-brain analysis.

Background: To investigate the whole-brain iron deposition alternations in patients with thyroid-associated ophthalmopathy (TAO) using quantitative susceptibility mapping (QSM). Methods: Forty-eight patients with TAO and 33 healthy controls (HCs) were enrolled. All participants underwent brain magnetic resonance imaging scans and clinical scale assessments. QSM values were calculated and compared between TAO and HCs groups using a voxel-based analysis. A support vector machine (SVM) analysis was performed to evaluate the performance of QSM values in differentiating patients with TAO from HCs. Results: Compared with HCs, patients with TAO showed significantly increased QSM values in the bilateral caudate nucleus (CN), left thalamus (TH), left cuneus, left precuneus, right insula and right middle frontal gyrus. In TAO group, QSM values in left TH were positively correlated with Hamilton Depression Rating Scale (HDRS) scores (r = 0.414, p = 0.005). The QSM values in right CN were negatively correlated with Montreal Cognitive Assessment (MoCA) scores (r = -0.342, p = 0.021). Besides that, a nearly negative correlation was found between QSM values in left CN and MoCA scores (r = -0.286, p = 0.057). The SVM model showed a good performance in distinguishing patients with TAO from the HCs (area under the curve, 0.958; average accuracy, 90.1%). Conclusion: Patients with TAO had significantly increased iron deposition in brain regions corresponding to known visual, emotional and cognitive deficits. QSM values could serve as potential neuroimaging markers of TAO.

Network analysis of psychosomatic symptoms in pharmacists during the pandemic.

We explored the networks and discriminant abilities of the current Psychosomatic Symptoms Scale (PSSS) in pharmacists for future abbreviation. Ten thousand seven hundred twenty-one pharmacists participated in this study through an online investigation. We used network analysis to reveal the central and bridge symptoms between the subscales (psychological and somatic symptoms) of the PSSS. Then, we utilized item response theory (IRT) to identify discriminant abilities of the current 26-item of PSSS. Over twenty percent of the pharmacists were troubled with significant psychosomatic issues during the pandemic. Risk factors included age, lack of support, and impaired general health conditions. The network analysis revealed that "Irritability" was central to the psychological subscale and "Fatigue" was central to the somatic subscale. "Irritability-Fatigue," "Fatigue-Obsession," and "Self-injury idea-Perineum discomfort" was bridging between the somatic and psychological subscales. IRT found that "Anhedonia," "Depression," "Tightness," "Palpitations," and "Difficulty breathing" were highly discriminated. A future version of PSSS could be abbreviated according to the highlighted items, and they should also be emphasized in future psychosomatic research and targets for intervention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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.

A hybrid machine learning and regression method for cell type deconvolution of spatial barcoding-based transcriptomic data.

Spatial barcoding-based transcriptomic (ST) data require cell type deconvolution for cellular-level downstream analysis. Here we present SDePER, a hybrid machine learning and regression method, to deconvolve ST data using reference single-cell RNA sequencing (scRNA-seq) data. SDePER uses a machine learning approach to remove the systematic difference between ST and scRNA-seq data (platform effects) explicitly and efficiently to ensure the linear relationship between ST data and cell type-specific expression profile. It also considers sparsity of cell types per capture spot and across-spots spatial correlation in cell type compositions. Based on the estimated cell type proportions, SDePER imputes cell type compositions and gene expression at unmeasured locations in a tissue map with enhanced resolution. Applications to coarse-grained simulated data and four real datasets showed that SDePER achieved more accurate and robust results than existing methods, suggesting the importance of considering platform effects, sparsity and spatial correlation in cell type deconvolution.

Consecutive engineering of anodic graphene supported cobalt monoxide composite and cathodic nanosized lithium cobalt oxide materials with improved lithium-ion storage performances.

Downsizing the electrochemically active materials in both cathodic and anodic electrodes commonly brings about enhanced lithium-ion storage performances. It is particularly meaningful to explore simplified and effective strategies for exploiting nanosized electrode materials in the advanced lithium-ion batteries. In this work, the spontaneous reaction between few-layered graphene oxide (GO) and metallic cobalt (Co) foils in mild hydrothermal condition is for the first time employed to synthesize a reduced graphene oxide (RGO) supported nanosized cobalt monoxide (CoO) anode material (CoO@RGO). Furthermore, the CoO@RGO sample is converted to nanosized lithium cobalt oxide cathode material (LiCoO2, LCO) by taking the advantages of the self-templated effect. As a result, both the CoO@RGO anode and the LCO cathode exhibit inspiring lithium-ion storage properties. In half-cells, the CoO@RGO sample maintains a reversible capacity of 740.6 mAh·g-1 after 300 cycles at the current density of 1000 mA·g-1 while the LCO sample delivers a reversible capacity of 109.1 mAh·g-1 after 100 cycles at the current density of 100 mA·g-1. In the CoO@RGO//LCO full-cells, the CoO@RGO sample delivers a reversible capacity of 553.9 mAh·g-1 after 50 cycles at the current density of 200 mA·g-1. The reasons for superior electrochemical behaviors of the samples have been revealed, and the strategy in this work can be considered to be straightforward and effective for engineering both anode and cathode materials for lithium-ion batteries.