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)

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)

Voltage-gated potassium channels (version 2019.4) in the IUPHAR/BPS Guide to Pharmacology Database

The 6TM family of K channels comprises the voltage-gated KV subfamilies, the EAG subfamily (which includes hERG channels), the Ca2+-activated Slo subfamily (actually with 7TM, termed BK) and the Ca2+-activated SK subfamily. These channels possess a pore-forming α subunit that comprise tetramers of identical subunits (homomeric) or of different subunits (heteromeric). Heteromeric channels can only be formed within subfamilies (e.g. Kv1.1 with Kv1.2; Kv7.2 with Kv7.3). The pharmacology largely reflects the subunit composition of the functional channel

Voltage-gated potassium channels (Kv) in GtoPdb v.2021.3

The 6TM family of K channels comprises the voltage-gated KV subfamilies, the EAG subfamily (which includes hERG channels), the Ca2+-activated Slo subfamily (actually with 7TM, termed BK) and the Ca2+-activated SK subfamily. These channels possess a pore-forming α subunit that comprise tetramers of identical subunits (homomeric) or of different subunits (heteromeric). Heteromeric channels can only be formed within subfamilies (e.g. Kv1.1 with Kv1.2; Kv7.2 with Kv7.3). The pharmacology largely reflects the subunit composition of the functional channel

allogeneic hematopoietic cell transplantation hct in the eighth decade of life how much does age matter

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Functional Consequences of the Human Leptin Receptor ( LEPR ) Q223R Transversion

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93715/1/oby.2008.489.pd

Digitise This! A Quick and Easy Remote Sensing Method to Monitor the Daily Extent of Dredge Plumes

Technological advancements in remote sensing and GIS have improved natural resource managers’ abilities to monitor large-scale disturbances. In a time where many processes are heading towards automation, this study has regressed to simple techniques to bridge a gap found in the advancement of technology. The near-daily monitoring of dredge plume extent is common practice using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and associated algorithms to predict the total suspended solids (TSS) concentration in the surface waters originating from floods and dredge plumes. Unfortunately, these methods cannot determine the difference between dredge plume and benthic features in shallow, clear water. This case study at Barrow Island, Western Australia, uses hand digitising to demonstrate the ability of human interpretation to determine this difference with a level of confidence and compares the method to contemporary TSS methods. Hand digitising was quick, cheap and required very little training of staff to complete. Results of ANOSIM R statistics show remote sensing derived TSS provided similar spatial results if they were thresholded to at least 3 mg L-1. However, remote sensing derived TSS consistently provided false-positive readings of shallow benthic features as Plume with a threshold up to TSS of 6 mg L-1, and began providing false-negatives (excluding actual plume) at a threshold as low as 4 mg L-1. Semi-automated processes that estimate plume concentration and distinguish between plumes and shallow benthic features without the arbitrary nature of human interpretation would be preferred as a plume monitoring method. However, at this stage, the hand digitising method is very useful and is more accurate at determining plume boundaries over shallow benthic features and is accessible to all levels of management with basic training

Fetal growth and birth weight are independently reduced by malaria infection and curable sexually transmitted and reproductive tract infections in Kenya, Tanzania, and Malawi: A pregnancy cohort study

Objective Malaria and sexually transmitted and reproductive tract infections (STIs/RTIs) are highly prevalent in sub-Saharan Africa and associated with poor pregnancy outcomes. We investigated the individual and combined effects of malaria and curable STIs/RTIs on fetal growth in Kenya, Tanzania, and Malawi. Methods This study was nested within a randomized trial comparing monthly intermittent preventive treatment for malaria in pregnancy with sulfadoxine-pyrimethamine versus dihydroartemisinin-piperaquine, alone or combined with azithromycin. Fetal weight gain was assessed by serial prenatal ultrasound. Malaria was assessed monthly, and Treponema pallidum, Neisseria gonorrhoeae, Trichomonas vaginalis, Chlamydia trachomatis and bacterial vaginosis at enrolment and in the third trimester. The effect of malaria and STIs/RTIs on fetal weight/birthweight Z-scores was evaluated using mixed-effects linear regression. Results 1,435 pregnant women had fetal/birth weight assessed 3,950 times. Compared to women without malaria or STIs/RTIs (n=399), malaria-only (n=267), STIs/RTIs-only (n=410) or both (n=353) were associated with reduced fetal growth (adjusted mean difference in fetal/birth weight Z-score [95% CI]: malaria=-0.18 [-0.31,-0.04], p=0.01]; STIs/RTIs=-0.14 [-0.26,-0.03], p=0.01]; both=-0.20 [-0.33,-0.07], p=0.003). Paucigravidae experienced the greatest impact. Conclusion Malaria and STIs/RTIs are associated with poor fetal growth especially among paucigravidae women with dual infections. Integrated antenatal interventions are needed to reduce the burden of both malaria and STIs/RTIs

The choice of reference chart affects the strength of the association between malaria in pregnancy and small for gestational age: an individual participant data meta-analysis comparing the Intergrowth-21 with a Tanzanian birthweight chart

Background: The prevalence of small for gestational age (SGA) may vary depending on the chosen weight-for-gestational-age reference chart. An individual participant data meta-analysis was conducted to assess the implications of using a local reference (STOPPAM) instead of a universal reference (Intergrowth-21) on the association between malaria in pregnancy and SGA. Methods: Individual participant data of 6,236 newborns were pooled from seven conveniently identified studies conducted in Tanzania and Malawi from 2003–2018 with data on malaria in pregnancy, birthweight, and ultrasound estimated gestational age. Mixed-effects regression models were used to compare the association between malaria in pregnancy and SGA when using the STOPPAM and the Intergrowth-21 references, respectively. Results: The 10th percentile for birthweights-for-gestational age was lower for STOPPAM than for Intergrowth-21, leading to a prevalence of SGASTOPPAM of 14.2% and SGAIG21 of 18.0%, p < 0.001. The association between malaria in pregnancy and SGA was stronger for STOPPAM (adjusted odds ratio (aOR) 1.30 [1.09–1.56], p < 0.01) than for Intergrowth-21 (aOR 1.19 [1.00–1.40], p = 0.04), particularly among paucigravidae (SGASTOPPAM aOR 1.36 [1.09–1.71], p < 0.01 vs SGAIG21 aOR 1.21 [0.97–1.50], p = 0.08). Conclusions: The prevalence of SGA may be overestimated and the impact of malaria in pregnancy underestimated when using Intergrowth-21. Comparing local reference charts to global references when assessing and interpreting the impact of malaria in pregnancy may be appropriate