Blockade of Voltage-Gated K Channels in Rabbit Coronary Arterial Smooth Muscle Cells by the Antipsychotic Drug Zotepine.

Zotepine is a second-generation antipsychotic that demonstrates significant efficacy in antagonizing D and 5-HT receptors. Although clinical investigations have shown that administering zotepine is associated with an increased prevalence of hyperglycemia and a heightened risk of cardiovascular disease, the side effects of zotepine on voltage-gated K (Kv) channels have not been established. Zotepine suppressed the vascular Kv channels in rabbit coronary arterial smooth muscle cells in a concentration-dependent manner, with an IC of 5.

Shinjulactone A Blocks Vascular Inflammation and the Endothelial-Mesenchymal Transition.

Objective: The endothelial inflammatory response plays an important role in atherogenesis by inducing nuclear factor (NF)κB-dependent cell adhesion molecule expression and monocyte recruitment. Here, we screened for natural ligands and investigated the ability of shinjulactone A to inhibit interleukin-1β (IL-1β)-induced endothelial inflammatory signaling.

Methods: The natural compound library included 880 single compounds isolated from medicinal plants by the Korean Medicinal Material Bank.

A Longitudinal Study on Attenuated Structural Covariance in Patients With Somatic Symptom Disorder.

Objective: This study was performed to investigate altered regional gray matter volume (rGMV) and structural covariance related to somatic symptom disorder (SSD) and longitudinal changes after treatment. Additionally, this study examined the relationships of structural alteration with its phenotypic subtypes.

Methods: Forty-three unmedicated patients with SSD and thirty normal controls completed psychological questionnaires and neurocognitive tests, as well as brain magnetic resonance imaging.

Longitudinal qEEG changes correlate with clinical outcomes in patients with somatic symptom disorder.

Objective: The quantitative electroencephalography (qEEG) of patients with somatic symptom disorder (SSD) was not yet thoroughly studied. This study aimed to investigate qEEG of SSD patients compared with those of normal controls (NCs), and changes therein after treatment.

Methods: SSD patients currently without treatment and age- and sex-matched NCs were recruited.

The relationships between cognitive control and psychological symptoms in patients with somatic symptom disorder: a pilot longitudinal study.

Introduction: The present study explored how neurocognitive function correlated with the clinical symptoms of somatic symptom disorder (SSD) by evaluating changes in cognitive abilities according to differences in relevant factors.

Methods: A total of 44 patients with SSD and 30 healthy controls completed tests assessing various neurocognitive domains, including verbal memory, psychomotor speed, executive function, working memory, and sustained and divided attention. They also completed questionnaires for psychological assessment.

Psychological Characteristics in Patients with Chronic Complex Regional Pain Syndrome: Comparisons with Patients with Major Depressive Disorder and Other Types of Chronic Pain.

Objective: This study investigated psychological characteristics of patients with chronic complex regional pain syndrome (CRPS) and examined relationships between psychosocial factors and pain severity.

Methods: In total, 76 patients with CRPS, 95 patients with other types of chronic pain, 171 healthy controls, and 66 patients with major depressive disorder (MDD) were included. Minnesota Multiphasic Personality Inventory (MMPI-2) profiles and scores on the Beck Depression Inventory and State-Trait Anxiety Inventory were calculated.

ChimerDB 4.0: an updated and expanded database of fusion genes.

Fusion genes represent an important class of biomarkers and therapeutic targets in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data (ChimerSeq) and text mining of publications (ChimerPub) with extensive manual annotations (ChimerKB). In this update, we present all three modules substantially enhanced by incorporating the recent flood of deep sequencing data and related publications.

FusionScan: accurate prediction of fusion genes from RNA-Seq data.

Identification of fusion gene is of prominent importance in cancer research field because of their potential as carcinogenic drivers. RNA sequencing (RNA-Seq) data have been the most useful source for identification of fusion transcripts. Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible.

Diagnostic Neuroimaging in Headache Patients: A Systematic Review and Meta-Analysis.

Objective: Neuroimaging in headache patients identifies clinically significant neurological abnormalities and plays an important role in excluding secondary headache diagnoses. We performed a systematic review and meta-analysis of the existing guidelines and studies surrounding neuroimaging in headache patients.

Methods: The research question involved determining the prevalence of detecting clinically significant neurological abnormalities using neuroimaging in patients suspected of primary headache.

Proteogenomic Characterization of Human Early-Onset Gastric Cancer.

We report proteogenomic analysis of diffuse gastric cancers (GCs) in young populations. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival.

ChimerDB 3.0: an enhanced database for fusion genes from cancer transcriptome and literature data mining.

Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining.