Modulation de l’adressage membranaire et de la fonction du canal CaV2.3 par les résidus leucine du domaine guanylate kinase impliqués dans la liaison à forte affinité de CaVβ

Les canaux Ca2+ activés par le voltage (CaV) sont des protéines membranaires qui génèrent des courants Ca2+ dans les cellules excitables suite à une dépolarisation membranaire. Ces complexes oligomériques sont classifiés selon les propriétés structurelles de la sous-unité principale qui forme le pore du canal, soit la sous-unité CaVα1. La sous-unité auxiliaire CaVβ module l’expression membranaire et la dépendance au voltage du « gating » de la sous-unité CaVα1 des canaux HVA (« high-voltage-activated ») CaV1 et CaV2. La sous-unité CaVβ est formée par un domaine SH3 (« Src homology-3 ») connecté à un domaine GK (« guanylate kinase-like ») par le biais d’un domaine variable HOOK. Dans le but d’identifier les résidus dans la CaVβ3 qui sont responsables de la densité membranaire du CaV2.3, nous avons produit des mutants de la sous-unité auxiliaire le long de ses domaines fonctionnels. Cela dit, la délétion complète du domaine SH3 ainsi que la délétion du domaine HOOK n’ont pas modifié la densité membranaire de CaV2.3 ni ses propriétés d’activation. Cependant, la délétion de cinq résidus dans le domaine GK interrompt l’expression membranaire et l’expression fonctionnelle de CaV2.3. La mutation de résidus identifiés précédemment comme soutenant une affinité de liaison de l’ordre du nanomolaire dans le domaine GK de CaVβ n’a pas modifié de manière significative l’adressage membranaire de CaV2.3. Toutefois, les mutations de quatre résidus leucine dans les régions α3, α6, β10 et α9 du domaine GK ont grandement réduit l’adressage membranaire du canal CaV2.3. Nos résultats confirment que le domaine GK contient les déterminants moléculaires responsables de la fonction chaperone de CaVβ. Cela dit, l’adressage membranaire induit par CaVβ semble être déterminé par des éléments structuraux qui ne sont pas strictement dépendants d’une liaison à haute affinité de CaVβ sur CaVα1.Voltage-activated Ca2+ channels (CaV) are membrane proteins that play a key role in promoting Ca2+ influx in response to membrane depolarization in excitable cells. They form oligomeric complexes that are classified according to the structural properties of the pore-forming CaVα1 subunit. Auxiliary CaVβ subunits modulate cell-surface expression and voltage-dependent gating of high-voltage-activated (HVA) CaV1 and CaV2 α1 subunits. CaVβ subunits are formed by a Src homology-3 (SH3) domain and a guanylate kinase-like (GK) domain connected through a variable HOOK-domain. In order to identify the residues responsible for the CaVβ3-induced membrane density of CaV2.3, we produced mutants along CaVβ3’s fonctionnal domains. Complete deletion of the SH3 domain as well as deletion of the HOOK domain did not alter plasma membrane targeting of CaV2.3 nor its typical activation gating. In contrast, 5-residue deletions in the GK domain disrupted cell surface trafficking and functional expression of CaV2.3. Mutations of residues known to carry nanomolar affinity binding in the GK domain of CaVβ did not significantly alter cell surface density. Mutations of a quartet of leucine residues in the α3, α6, β10, and α9 regions of the GK domain, each expected to curtail protein-protein interaction, were found to significantly impair cell surface targeting of CaV2.3 channels. Altogether, our results confirm that the GK domain includes the molecular determinants carrying the chaperone function of CaVβ. However, CaVβ-induced cell surface targeting appears to be determined by structural elements that are not strictly dominated by high-affinity binding of CaVβ onto CaVα1

Functional characterization of CaVα2δ mutations associated with sudden cardiac death

L-type Ca(2+) channels play a critical role in cardiac rhythmicity. These ion channels are oligomeric complexes formed by the pore-forming CaVα1 with the auxiliary CaVβ and CaVα2δ subunits. CaVα2δ increases the peak current density and improves the voltage-dependent activation gating of CaV1.2 channels without increasing the surface expression of the CaVα1 subunit. The functional impact of genetic variants of CACNA2D1 (the gene encoding for CaVα2δ), associated with shorter repolarization QT intervals (the time interval between the Q and the T waves on the cardiac electrocardiogram), was investigated after recombinant expression of the full complement of L-type CaV1.2 subunits in human embryonic kidney 293 cells. By performing side-by-side high resolution flow cytometry assays and whole-cell patch clamp recordings, we revealed that the surface density of the CaVα2δ wild-type protein correlates with the peak current density. Furthermore, the cell surface density of CaVα2δ mutants S755T, Q917H, and S956T was not significantly different from the cell surface density of the CaVα2δ wild-type protein expressed under the same conditions. In contrast, the cell surface expression of CaVα2δ D550Y, CaVα2δ S709N, and the double mutant D550Y/Q917H was reduced, respectively, by ≈30-33% for the single mutants and by 60% for the latter. The cell surface density of D550Y/Q917H was more significantly impaired than protein stability, suggesting that surface trafficking of CaVα2δ was disrupted by the double mutation. Co-expression with D550Y/Q917H significantly decreased CaV1.2 currents as compared with results obtained with CaVα2δ wild type. It is concluded that D550Y/Q917H reduced inward Ca(2+) currents through a defect in the cell surface trafficking of CaVα2δ. Altogether, our results provide novel insight in the molecular mechanism underlying the modulation of CaV1.2 currents by CaVα2δ

Internal Communications, Engagement and Trust in a Mission-Based Organization: Examining how the strength of the mission of an organization plays a role in engagement, trust in leadership and communication

This paper describes a SDN-based solution that, by leveraging and coordinating many functionalities that reside at both WDM and Ethernet layers, orchestrates network resources with the aim to maximize host-to-host data transfer rate

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Future of the Renal Biopsy: Time to Change the Conventional Modality Using Nanotechnology

At the present time, imaging guided renal biopsy is used to provide diagnoses in most types of primary and secondary renal diseases. It has been claimed that renal biopsy can provide a link between diagnosis of renal disease and its pathological conditions. However, sometimes there is a considerable mismatch between patient renal outcome and pathological findings in renal biopsy. This is the time to address some new diagnostic methods to resolve the insufficiency of conventional percutaneous guided renal biopsy. Nanotechnology is still in its infancy in renal imaging; however, it seems that it is the next step in renal biopsy, providing solutions to the limitations of conventional modalities

A WDM Network Controller with Real-time Updates of the Physical Layer Abstraction

This paper describes the implementation of a wavelength division multiplexing (WDM) network controller that accounts for the varying conditions of the network physical layer in real-time. A newly added software module is used to estimate the physical layer quality of transmission (QoT-E) in the form of a single transmission figure of merit for every line span in the network, i.e., the optical signal-to-noise ratio (OSNR) degradation. The estimated OSNR degradation is used to verify lightpath feasibility in the network, and produce optimal routing and wavelength assignment solutions in real-time, without the need for a separate network planning tool. The OSNR degradation is estimated without requiring detailed knowledge of the optical components deployed in the network, and consequently the approach is vendor-agnostic. The accuracy of the estimated OSNR degradation is assessed experimentally, and its impact on two network-wide performance indicators is studied through simulation