Dexmedetomidine alleviates H2O2-induced oxidative stress and cell necroptosis through activating of α2-adrenoceptor in H9C2 cells

Molecular Biology Reports - Oxidative stress induced necroptosis is important in myocardial ischemia/reperfusion injury. Dexmedetomidine (Dex), an α2-adrenoceptor (α2-AR) agonist, has...     

Identification of NCAPH as a biomarker for prognosis of breast cancer

Molecular Biology Reports - Non-SMC condensin I complex subunit H (NCAPH) is a structural component of chromosomes during mitosis, which up-regulates in various cancers. However, the role of NCAPH...     

Identification of a transforming growth factor-β type I receptor transcript in Eriocheir sinensis and its molting-related expression in muscle tissues

The transforming growth factor-β (TGF-β) signaling pathway is conserved across animals, and knowledge of its roles during the molt cycle in crustaceans is presently very limited. This study investigates the roles of the TGF-β receptor in molting-related muscle growth in Eriocheir sinensis. Using the RT-PCR and RACE techniques, we obtained a 1722 bp cDNA sequence encoding a transforming growth factor-β type I receptor in Eriocheir sinensis, designated EsTGFBRI, which contains a 124 bp 5′-untranslated region, a 20 bp partial 3′-untranslated region and a 1578 bp open reading frame encoding 525 amino acids. The deduced EsTGFBRI contains an N-terminal 24 amino acid signal peptide, an activin type I and II receptor domain, a transmembrane helix region, a glycine-serine-rich motif, and a conserved serine/threonine kinase catalytic domain including an activation loop. The qRT-PCR results showed that EsTGFBRI gene was highly expressed in the intermolt testis and ovary in mature crabs. In juvenile crabs, the mRNA levels of EsTGFBRI in claw and abdominal muscles in the later premolt D_3–4 stage were significantly higher than those in the intermolt C and postmolt A–B stages. There was no significant change in EsTGFBRI mRNA levels in walking leg muscles during the molt cycle. The results suggest that EsTGFBRI is probably play roles in molting-related muscle growth in E. sinensis. This study provides a necessary basis for elucidating the functions of TGF-β-like signaling mediated by TGFBRI in molting-related muscle growth in crustaceans.

     

Parthenolide ameliorates tweak-induced podocytes injury

Molecular Biology Reports - Parthenolide (PTL) is a natural product from the shoots of Tanacetum parthenium, which has immunomodulatory effects in multiply type of diseases. This study aimed to...     

HAP1 Modulates Epileptic Seizures by Regulating GABAAR Function in Patients with Temporal Lobe Epilepsy and in the PTZ-Induced Epileptic Model

Neurochemical Research - The number of γ-aminobutyric acid type A receptors (GABAARs) expressed on the surface membrane and at synaptic sites is implicated in the enhanced excitation of...     

The Downregulation of Truncated TrkB Receptors Modulated by MicroRNA-185 Activates Full-Length TrkB Signaling and Suppresses the Epileptiform Discharges in Cultured Hippocampal Neurons

Neurochemical Research - Epilepsy is a common neurological disorder characterised by occurrence of spontaneous recurrent epileptiform discharges (SREDs) in neurons. The cellular mechanisms that...     

Long noncoding RNA LINC01234 promoted cell proliferation and invasion via miR-1284/TRAF6 axis in colorectal cancer

Colorectal cancer is one of the most common and leading malignancies globally. Long noncoding RNAs (lncRNAs) function as potentially critical regulator in colorectal cancer. LINC01234, a novel lncRNA in tumor biology, regulates the progression of various tumors. However, the tumorigenic mechanism of LINC01234 in colorectal cancer is still unclear. This study was performed with the aim to prospectively investigate clinical significance, effect, and mechanism of lncRNA LINC01234 in colorectal cancer. First, we found that LINC01234, localized in the cytoplasm, was increased in both colorectal cancer cell lines and tissues. Subsequent functional assays suggested LINC01234 knockdown suppressed cell proliferation, migration, and invasion of colorectal cancer cells, while blocked cell cycle and induced cell apoptosis. Moreover, we identified that miR-1284 was target of LINC01234, we further demonstrated a negative correlation with LINC01234 in colorectal cancer tissues and cells. Furthermore, miR-1284 targeted and suppressed tumor necrosis factor receptor–associated factor 6 (TRAF6). Loss-of-function assay revealed that LINC01234 silencing suppressed colorectal cancer progression through inhibition of miR-1284. In vivo subcutaneous xenotransplanted tumor model indicated LINC01234 knockdown inhibited in vivo tumorigenic ability of colorectal cancer via downregulation of TRAF6. Collectively, this study clarified the biological significance of LINC01234/miR-1284/TRAF6 axis in colorectal cancer progression, providing insights into LINC01234 as novel potential therapeutic target for colorectal cancer therapeutic from bench to clinic.     

Genome-Wide Analysis of the Apple (Malus domestica) Cysteine-Rich Receptor-Like Kinase (CRK) Family: Annotation,Genomic Organization,and Expression Profiles in Response to Fungal Infection

Plant Molecular Biology Reporter - Cysteine-rich receptor-like kinases (CRKs) took crucial roles in plant cell growth and development, as well as environmental adaption. Apple (Malus domestica) had...     

ProDCoNN: Protein design using a convolutional neural network

Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this problem as predicting the residue type given the 3D structural environment around the C _α atom of a residue, which is repeated for each residue of a protein. We designed a nine-layer 3D deep convolutional neural network (CNN) that takes as input a gridded box with the atomic coordinates and types around a residue. Several CNN layers were designed to capture structure information at different scales, such as bond lengths, bond angles, torsion angles, and secondary structures. Trained on a very large number of protein structures, the method, called ProDCoNN (protein design with CNN), achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets.