Calcium- and sodium-activated potassium channels (KCa, KNa) in GtoPdb v.2021.3

Calcium- and sodium- activated potassium channels are members of the 6TM family of K channels which comprises the voltage-gated KV subfamilies, including the KCNQ subfamily, the EAG subfamily (which includes hERG channels), the Ca2+-activated Slo subfamily (actually with 6 or 7TM) and the Ca2+- and Na+-activated SK subfamily (nomenclature as agreed by the NC-IUPHAR Subcommittee on Calcium- and sodium-activated potassium channels [125]). As for the 2TM family, the pore-forming a subunits form tetramers and heteromeric channels may be formed within subfamilies (e.g. KV1.1 with KV1.2; KCNQ2 with KCNQ3)

Calcium- and sodium-activated potassium channels (KCa, KNa) in GtoPdb v.2023.1

Calcium- and sodium- activated potassium channels are members of the 6TM family of K channels which comprises the voltage-gated KV subfamilies, including the KCNQ subfamily, the EAG subfamily (which includes hERG channels), the Ca2+-activated Slo subfamily (actually with 6 or 7TM) and the Ca2+- and Na+-activated SK subfamily (nomenclature as agreed by the NC-IUPHAR Subcommittee on Calcium- and sodium-activated potassium channels [126]). As for the 2TM family, the pore-forming a subunits form tetramers and heteromeric channels may be formed within subfamilies (e.g. KV1.1 with KV1.2; KCNQ2 with KCNQ3)

Calcium- and sodium-activated potassium channels (version 2019.4) in the IUPHAR/BPS Guide to Pharmacology Database

Calcium- and sodium- activated potassium channels are members of the 6TM family of K channels which comprises the voltage-gated KV subfamilies, including the KCNQ subfamily, the EAG subfamily (which includes herg channels), the Ca2+-activated Slo subfamily (actually with 6 or 7TM) and the Ca2+- and Na+-activated SK subfamily (nomenclature as agreed by the NC-IUPHAR Subcommittee on Calcium- and sodium-activated potassium channels [124]). As for the 2TM family, the pore-forming a subunits form tetramers and heteromeric channels may be formed within subfamilies (e.g. KV1.1 with KV1.2; KCNQ2 with KCNQ3)

Deregulation of Sucrose-Controlled Translation of a bZIP-Type Transcription Factor Results in Sucrose Accumulation in Leaves

Sucrose is known to repress the translation of Arabidopsis thaliana AtbZIP11 transcript which encodes a protein belonging to the group of S (S - stands for small) basic region-leucine zipper (bZIP)-type transcription factor. This repression is called sucrose-induced repression of translation (SIRT). It is mediated through the sucrose-controlled upstream open reading frame (SC-uORF) found in the AtbZIP11 transcript. The SIRT is reported for 4 other genes belonging to the group of S bZIP in Arabidopsis. Tobacco tbz17 is phylogenetically closely related to AtbZIP11 and carries a putative SC-uORF in its 5′-leader region. Here we demonstrate that tbz17 exhibits SIRT mediated by its SC-uORF in a manner similar to genes belonging to the S bZIP group of the Arabidopsis genus. Furthermore, constitutive transgenic expression of tbz17 lacking its 5′-leader region containing the SC-uORF leads to production of tobacco plants with thicker leaves composed of enlarged cells with 3–4 times higher sucrose content compared to wild type plants. Our finding provides a novel strategy to generate plants with high sucrose content

Early pregnancy peripheral blood gene expression and risk of preterm delivery: a nested case control study

<p>Abstract</p> <p>Background</p> <p>Preterm delivery (PTD) is a significant public health problem associated with greater risk of mortality and morbidity in infants and mothers. Pathophysiologic processes that may lead to PTD start early in pregnancy. We investigated early pregnancy peripheral blood global gene expression and PTD risk.</p> <p>Methods</p> <p>As part of a prospective study, ribonucleic acid was extracted from blood samples (collected at 16 weeks gestational age) from 14 women who had PTD (cases) and 16 women who delivered at term (controls). Gene expressions were measured using the GeneChip^®Human Genome U133 Plus 2.0 Array. Student's T-test and fold change analysis were used to identify differentially expressed genes. We used hierarchical clustering and principle components analysis to characterize signature gene expression patterns among cases and controls. Pathway and promoter sequence analyses were used to investigate functions and functional relationships as well as regulatory regions of differentially expressed genes.</p> <p>Results</p> <p>A total of 209 genes, including potential candidate genes (e.g. PTGDS, prostaglandin D2 synthase 21 kDa), were differentially expressed. A set of these genes achieved accurate pre-diagnostic separation of cases and controls. These genes participate in functions related to immune system and inflammation, organ development, metabolism (lipid, carbohydrate and amino acid) and cell signaling. Binding sites of putative transcription factors such as EGR1 (early growth response 1), TFAP2A (transcription factor AP2A), Sp1 (specificity protein 1) and Sp3 (specificity protein 3) were over represented in promoter regions of differentially expressed genes. Real-time PCR confirmed microarray expression measurements of selected genes.</p> <p>Conclusions</p> <p>PTD is associated with maternal early pregnancy peripheral blood gene expression changes. Maternal early pregnancy peripheral blood gene expression patterns may be useful for better understanding of PTD pathophysiology and PTD risk prediction.</p

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases

Global report on preterm birth and stillbirth (2 of 7): discovery science

<p>Abstract</p> <p>Background</p> <p>Normal and abnormal processes of pregnancy and childbirth are poorly understood. This second article in a global report explains what is known about the etiologies of preterm births and stillbirths and identifies critical gaps in knowledge. Two important concepts emerge: the continuum of pregnancy, beginning at implantation and ending with uterine involution following birth; and the multifactorial etiologies of preterm birth and stillbirth. Improved tools and data will enable discovery scientists to identify causal pathways and cost-effective interventions.</p> <p>Pregnancy and parturition continuum</p> <p>The biological process of pregnancy and childbirth begins with implantation and, after birth, ends with the return of the uterus to its previous state. The majority of pregnancy is characterized by rapid uterine and fetal growth without contractions. Yet most research has addressed only uterine stimulation (labor) that accounts for <0.5% of pregnancy.</p> <p>Etiologies</p> <p>The etiologies of preterm birth and stillbirth differ by gestational age, genetics, and environmental factors. Approximately 30% of all preterm births are indicated for either maternal or fetal complications, such as maternal illness or fetal growth restriction. Commonly recognized pathways leading to preterm birth occur most often during the gestational ages indicated: (1) inflammation caused by infection (22-32 weeks); (2) decidual hemorrhage caused by uteroplacental thrombosis (early or late preterm birth); (3) stress (32-36 weeks); and (4) uterine overdistention, often caused by multiple fetuses (32-36 weeks). Other contributors include cervical insufficiency, smoking, and systemic infections. Many stillbirths have similar causes and mechanisms. About two-thirds of late fetal deaths occur during the antepartum period; the other third occur during childbirth. Intrapartum asphyxia is a leading cause of stillbirths in low- and middle-income countries.</p> <p>Recommendations</p> <p>Utilizing new systems biology tools, opportunities now exist for researchers to investigate various pathways important to normal and abnormal pregnancies. Improved access to quality data and biological specimens are critical to advancing discovery science. Phenotypes, standardized definitions, and uniform criteria for assessing preterm birth and stillbirth outcomes are other immediate research needs.</p> <p>Conclusion</p> <p>Preterm birth and stillbirth have multifactorial etiologies. More resources must be directed toward accelerating our understanding of these complex processes, and identifying upstream and cost-effective solutions that will improve these pregnancy outcomes.</p

Transcription analysis of the myometrium of labouring and non-labouring women

An incomplete understanding of the molecular mechanisms that initiate normal human labour at term seriously hampers the development of effective ways to predict, prevent and treat disorders such as preterm labour. Appropriate analysis of large microarray experiments that compare gene expression in non-labouring and labouring gestational tissues is necessary to help bridge these gaps in our knowledge. In this work, gene expression in 48 (22 labouring, 26 non-labouring) lower-segment myometrial samples collected at Caesarean section were analysed using Illumina HT-12 v4.0 BeadChips. Normalised data were compared between labouring and non-labouring groups using traditional statistical methods and a novel network graph approach. We sought technical validation with quantitative real-time PCR, and biological replication through inverse variance-weighted meta-analysis with published microarray data. We have extended the list of genes suggested to be associated with labour: Compared to non-labouring samples, labouring samples showed apparent higher expression at 960 probes (949 genes) and apparent lower expression at 801 probes (789 genes) (absolute fold change ≥1.2, rank product percentage of false positive value (RP-PFP) <0.05). Although half of the women in the labouring group had received pharmaceutical treatment to induce or augment labour, sensitivity analysis suggested that this did not confound our results. In agreement with previous studies, functional analysis suggested that labour was characterised by an increase in the expression of inflammatory genes and network analysis suggested a strong neutrophil signature. Our analysis also suggested that labour is characterised by a decrease in the expression of muscle-specific processes, which has not been explicitly discussed previously. We validated these findings through the first formal meta-analysis of raw data from previous experiments and we hypothesise that this represents a change in the composition of myometrial tissue at labour. Further work will be necessary to reveal whether these results are solely due to leukocyte infiltration into the myometrium as a mechanism initiating labour, or in addition whether they also represent gene changes in the myocytes themselves. We have made all our data available at www.ebi.ac.uk/arrayexpress/ (accession number E-MTAB-3136) to facilitate progression of this work

The Concise guide to pharmacology 2019/20: Ion channels

The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide represents approximately 400 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.14749. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2019, and supersedes data presented in the 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate

THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Ion channels

The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15539. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate