Enhancement of Cell Membrane Invaginations, Vesiculation and Uptake of Macromolecules by Protonation of the Cell Surface

The different pathways of endocytosis share an initial step involving local inward curvature of the cell’s lipid bilayer. It has been shown that to generate membrane curvature, proteins or lipids enforce transversal asymmetry of the plasma membrane. Thus it emerges as a general phenomenon that transversal membrane asymmetry is the common required element for the formation of membrane curvature. The present study demonstrates that elevating proton concentration at the cell surface stimulates the formation of membrane invaginations and vesiculation accompanied by efficient uptake of macromolecules (Dextran-FITC, 70 kD), relative to the constitutive one. The insensitivity of proton induced uptake to inhibiting treatments and agents of the known endocytic pathways suggests the entry of macromolecules to proceeds via a yet undefined route. This is in line with the fact that neither ATP depletion, nor the lowering of temperature, abolishes the uptake process. In addition, fusion mechanism such as associated with low pH uptake of toxins and viral proteins can be disregarded by employing the polysaccharide dextran as the uptake molecule. The proton induced uptake increases linearly in the extracellular pH range of 6.5 to 4.5, and possesses a steep increase at the range of 4> pH>3, reaching a plateau at pH≤3. The kinetics of the uptake implies that the induced vesicles release their content to the cytosol and undergo rapid recycling to the plasma membrane. We suggest that protonation of the cell’s surface induces local charge asymmetries across the cell membrane bilayer, inducing inward curvature of the cell membrane and consequent vesiculation and uptake

Variation in the COVID-19 infection-fatality ratio by age, time, and geography during the pre-vaccine era: a systematic analysis

Background The infection-fatality ratio (IFR) is a metric that quantifies the likelihood of an individual dying once infected with a pathogen. Understanding the determinants of IFR variation for COVID-19, the disease caused by the SARS-CoV-2 virus, has direct implications for mitigation efforts with respect to clinical practice, non-pharmaceutical interventions, and the prioritisation of risk groups for targeted vaccine delivery. The IFR is also a crucial parameter in COVID-19 dynamic transmission models, providing a way to convert a population's mortality rate into an estimate of infections.Methods We estimated age-specific and all-age IFR by matching seroprevalence surveys to total COVID-19 mortality rates in a population. The term total COVID-19 mortality refers to an estimate of the total number of deaths directly attributable to COVID-19. After applying exclusion criteria to 5131 seroprevalence surveys, the IFR analyses were informed by 2073 all-age surveys and 718 age-specific surveys (3012 age-specific observations). When seroprevalence was reported by age group, we split total COVID-19 mortality into corresponding age groups using a Bayesian hierarchical model to characterise the non-linear age pattern of reported deaths for a given location. To remove the impact of vaccines on the estimated IFR age pattern, we excluded age-specific observations of seroprevalence and deaths that occurred after vaccines were introduced in a location. We estimated age-specific IFR with a non-linear meta-regression and used the resulting age pattern to standardise all-age IFR observations to the global age distribution. All IFR observations were adjusted for baseline and waning antibody-test sensitivity. We then modelled age-standardised IFR as a function of time, geography, and an ensemble of 100 of the top-performing covariate sets. The covariates included seven clinical predictors (eg, age-standardised obesity prevalence) and two measures of health system performance. Final estimates for 190 countries and territories, as well as subnational locations in 11 countries and territories, were obtained by predicting age-standardised IFR conditional on covariates and reversing the age standardisation.Findings We report IFR estimates for April 15, 2020, to January 1, 2021, the period before the introduction of vaccines and widespread evolution of variants. We found substantial heterogeneity in the IFR by age, location, and time. Age-specific IFR estimates form a J shape, with the lowest IFR occurring at age 7 years (0-0023%, 95% uncertainty interval [UI] 0-0015-0-0039) and increasing exponentially through ages 30 years (0-0573%, 0-0418-0-0870), 60 years (1-0035%, 0-7002-1-5727), and 90 years (20-3292%, 14-6888-28-9754). The countries with the highest IFR on July 15, 2020, were Portugal (2-085%, 0-946-4-395), Monaco (1-778%, 1-265-2-915), Japan (1-750%, 1-302-2-690), Spain (1-710%, 0-991-2-718), and Greece (1-637%, 1-155-2-678). All-age IFR varied by a factor of more than 30 among 190 countries and territories.After age standardisation, the countries with the highest IFR on July 15, 2020, were Peru (0-911%, 0-636-1-538), Portugal (0-850%, 0-386-1-793), Oman (0-762%, 0-381-1-399), Spain (0-751%, 0-435-1-193), and Mexico (0-717%, 0-426-1-404). Subnational locations with high IFRs also included hotspots in the UK and southern and eastern states of the USA. Sub-Saharan African countries and Asian countries generally had the lowest all-age and age-standardised IFRs. Population age structure accounted for 74% of logit-scale variation in IFRs estimated for 39 in-sample countries on July 15, 2020. A post-hoc analysis showed that high rates of transmission in the care home population might account for higher IFRs in some locations. Among all countries and territories, we found that the median IFR decreased from 0-466% (interquartile range 0-223-0-840) to 0-314% (0-143-0-551) between April 15, 2020, and Jan 1, 2021.Interpretation Estimating the IFR for global populations helps to identify relative vulnerabilities to COVID-19. Information about how IFR varies by age, time, and location informs clinical practice and non-pharmaceutical interventions like physical distancing measures, and underpins vaccine risk stratification. IFR and mortality risk form a J shape with respect to age, which previous research, such as that by Glynn and Moss in 2020, has identified to be a common pattern among infectious diseases. Understanding the experience of a population with COVID-19 mortality requires consideration for local factors; IFRs varied by a factor of more than 30 among 190 countries and territories in this analysis. In particular, the presence of elevated age-standardised IFRs in countries with well resourced health-care systems indicates that factors beyond health-care capacity are important. Potential extenuating circumstances include outbreaks among care home residents, variable burdens of severe cases, and the population prevalence of comorbid conditions that increase the severity of COVID-19 disease. During the pre-vaccine period, the estimated 33% decrease in median IFR over 8 months suggests that treatment for COVID-19 has improved over time. Estimating IFR for the pre-vaccine era provides an important baseline for describing the progression of COVID-19 mortality patterns.Funding Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license

Exploring the interpersonal-, organization-, and system-level factors that influence the implementation and use of an innovation-synoptic reporting-in cancer care

<p>Abstract</p> <p>Background</p> <p>The dominant method of reporting findings from diagnostic and surgical procedures is the narrative report. In cancer care, this report inconsistently provides the information required to understand the cancer and make informed patient care decisions. Another method of reporting, the synoptic report, captures specific data items in a structured manner and contains only items critical for patient care. Research demonstrates that synoptic reports vastly improve the quality of reporting. However, synoptic reporting represents a complex innovation in cancer care, with implementation and use requiring fundamental shifts in physician behaviour and practice, and support from the organization and larger system. The objective of this study is to examine the key interpersonal, organizational, and system-level factors that influence the implementation and use of synoptic reporting in cancer care.</p> <p>Methods</p> <p>This study involves three initiatives in Nova Scotia, Canada, that have implemented synoptic reporting within their departments/programs. Case study methodology will be used to study these initiatives (the cases) in-depth, explore which factors were barriers or facilitators of implementation and use, examine relationships amongst factors, and uncover which factors appear to be similar and distinct across cases. The cases were selected as they converge and differ with respect to factors that are likely to influence the implementation and use of an innovation in practice. Data will be collected through in-depth interviews, document analysis, observation of training sessions, and examination/use of the synoptic reporting tools. An audit will be performed to determine/quantify use. Analysis will involve production of a case record/history for each case, in-depth analysis of each case, and cross-case analysis, where findings will be compared and contrasted across cases to develop theoretically informed, generalisable knowledge that can be applied to other settings/contexts. Ethical approval was granted for this study.</p> <p>Discussion</p> <p>This study will contribute to our knowledge base on the multi-level factors, and the relationships amongst factors in specific contexts, that influence implementation and use of innovations such as synoptic reporting in healthcare. Such knowledge is critical to improving our understanding of implementation processes in clinical settings, and to helping researchers, clinicians, and managers/administrators develop and implement ways to more effectively integrate innovations into routine clinical care.</p

Cardioembolic Stroke in Atrial Fibrillation-Rationale for Preventive Closure of the Left Atrial Appendage

Atrial fibrillation is the most common cardiac arrhythmias, and a major cause of morbidity and mortality due to cardioembolic stroke. The left atrial appendage is the major site of thrombus formation in non-valvular atrial fibrillation. Loss of atrial systole in atrial fibrillation and increased relative risk of associated stroke point strongly toward a role for stasis of blood in left atrial thrombosis, although thrombus formation is multifactorial, and much more than blood flow irregularities are implicated. Oral anticoagulation with vitamin-K-antagonists is currently the most effective prophylaxis for stroke in atrial fibrillation. Unfortunately, this treatment is often contraindicated, particularly in the elderly, in whom risk of stroke is high. Moreover, given the risk of major bleeding, there is reason to be skeptical of the net benefit when warfarin is used in those patients. This work reviews the pathophysiology of cardioembolic stroke and critically spotlights the current status of preventive anticoagulation therapy. Various techniques to exclude the left atrial appendage from circulation were discussed as a considerable alternative for stroke prophylaxis

Importance of Non-Selective Cation Channel TRPV4 Interaction with Cytoskeleton and Their Reciprocal Regulations in Cultured Cells

BACKGROUND: TRPV4 and the cellular cytoskeleton have each been reported to influence cellular mechanosensitive processes as well as the development of mechanical hyperalgesia. If and how TRPV4 interacts with the microtubule and actin cytoskeleton at a molecular and functional level is not known. METHODOLOGY AND PRINCIPAL FINDINGS: We investigated the interaction of TRPV4 with cytoskeletal components biochemically, cell biologically by observing morphological changes of DRG-neurons and DRG-neuron-derived F-11 cells, as well as functionally with calcium imaging. We find that TRPV4 physically interacts with tubulin, actin and neurofilament proteins as well as the nociceptive molecules PKCepsilon and CamKII. The C-terminus of TRPV4 is sufficient for the direct interaction with tubulin and actin, both with their soluble and their polymeric forms. Actin and tubulin compete for binding. The interaction with TRPV4 stabilizes microtubules even under depolymerizing conditions in vitro. Accordingly, in cellular systems TRPV4 colocalizes with actin and microtubules enriched structures at submembranous regions. Both expression and activation of TRPV4 induces striking morphological changes affecting lamellipodial, filopodial, growth cone, and neurite structures in non-neuronal cells, in DRG-neuron derived F11 cells, and also in IB4-positive DRG neurons. The functional interaction of TRPV4 and the cytoskeleton is mutual as Taxol, a microtubule stabilizer, reduces the Ca2+-influx via TRPV4. CONCLUSIONS AND SIGNIFICANCE: TRPV4 acts as a regulator for both, the microtubule and the actin. In turn, we describe that microtubule dynamics are an important regulator of TRPV4 activity. TRPV4 forms a supra-molecular complex containing cytoskeletal proteins and regulatory kinases. Thereby it can integrate signaling of various intracellular second messengers and signaling cascades, as well as cytoskeletal dynamics. This study points out the existence of cross-talks between non-selective cation channels and cytoskeleton at multiple levels. These cross talks may help us to understand the molecular basis of the Taxol-induced neuropathic pain development commonly observed in cancer patients

Search for neutral MSSM Higgs bosons decaying to a pair of tau leptons in pp collisions

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Measurement of top quark–antiquark pair production in association with a W or Z boson in pp collisions at √s=8 TeV

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Searches for electroweak production of charginos, neutralinos, and sleptons decaying to leptons and W, Z, and Higgs bosons in pp collisions at 8 TeV

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Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

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