Signal Transmission in the Auditory System

Contains table of contents for Section 3, an introduction, and reports on seven research projects.National Institutes of Health Grant 5 R01 DC00194National Institutes of Health Grant P01 DC00119National Institutes of Health Grant F32 DC00073National Institutes of Health Grant 5 R01 DC00473National Institutes of Health Grant 2 R01 DC00238National Institutes of Health Grant 2 R01 DC00235National Institutes of Health Grant 5 P01 DC00361National Institutes of Health Grant T32 DC00006Whitaker Health Sciences Fun

Signal Transmission in the Auditory System

Contains table of contents for Section 3 and reports on nine research projects.National Institutes of Health (Grant 5 P01 NS13126)National Institutes of Health (Grant 5 P01 NS23734)National Institutes of Health (Grant 5 R01 NS18682)National Institutes of Health (Grant 5 RO1 NS25995)National Institutes of Health (Grant 5 R01 NS20269)National Institutes of Health (Grant 5 R01 NS20322)National Institutes of Health (Grant 5 T32 NS07047)Johnson and Johnson Foundatio

Signal Transmission in the Auditory System

Contains table of contents for Section 3, an introduction and reports on six research projects.Health Sciences FundNational Institutes of Health Grant 5 R01 DC00194National Institutes of Health Grant 8 P01 DC00119National Institutes of Health Grant 5 R01 DC00473National Institutes of Health Grant 5 R01 DC00238National Institutes of Health Grant 5 T32 DC00006National Institutes of Health Grant 5 P01 DC00361National Institutes of Health Grant 5 R01 DC00235Peoples Republic of China FellowshipUnisys Corporation Doctoral FellowshipWhitaker Health Sciences Fellowshi

Signal Transmission in the Auditory System

Contains table of contents for Section 3, an introduction and reports on nine research projects.National Institutes of Health Grant 5 T32 NS07047National Institutes of Health Grant 5 P01 NS13126National Institutes of Health Grant 8 R01 DC00194National Institutes of Health Grant 5 R01 NS25995National Institutes of Health Grant 8 R01 DC00238National Institutes of Health Grant 5 R01 NS20322National Institutes of Health Grant 5 R01 DC00235National Institutes of Health Grant 5 R01 NS20269National Institutes of Health Grant 1 P01 NS23734Johnson and Johnson FoundationUnisys Corporation Doctoral Fellowshi

Evolutionary Descent of Prion Genes from the ZIP Family of Metal Ion Transporters

In the more than twenty years since its discovery, both the phylogenetic origin and cellular function of the prion protein (PrP) have remained enigmatic. Insights into a possible function of PrP may be obtained through the characterization of its molecular neighborhood in cells. Quantitative interactome data demonstrated the spatial proximity of two metal ion transporters of the ZIP family, ZIP6 and ZIP10, to mammalian prion proteins in vivo. A subsequent bioinformatic analysis revealed the unexpected presence of a PrP-like amino acid sequence within the N-terminal, extracellular domain of a distinct sub-branch of the ZIP protein family that includes ZIP5, ZIP6 and ZIP10. Additional structural threading and orthologous sequence alignment analyses argued that the prion gene family is phylogenetically derived from a ZIP-like ancestral molecule. The level of sequence homology and the presence of prion protein genes in most chordate species place the split from the ZIP-like ancestor gene at the base of the chordate lineage. This relationship explains structural and functional features found within mammalian prion proteins as elements of an ancient involvement in the transmembrane transport of divalent cations. The phylogenetic and spatial connection to ZIP proteins is expected to open new avenues of research to elucidate the biology of the prion protein in health and disease

Interactome Analyses Identify Ties of PrPC and Its Mammalian Paralogs to Oligomannosidic N-Glycans and Endoplasmic Reticulum-Derived Chaperones

The physiological environment which hosts the conformational conversion of the cellular prion protein (PrPC) to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrPC interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd) and Shadoo (Sprn), two mammalian PrPC paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrPC and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI) were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrPC with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrPSc. A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrPC organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins

Left ventricular speckle tracking-derived cardiac strain and cardiac twist mechanics in athletes: a systematic review and meta-analysis of controlled studies

Background: The athlete’s heart is associated with physiological remodeling as a consequence of repetitive cardiac loading. The effect of exercise training on left ventricular (LV) cardiac strain and twist mechanics are equivocal, and no meta-analysis has been conducted to date. Objective: The objective of this systematic review and meta-analysis was to review the literature pertaining to the effect of different forms of athletic training on cardiac strain and twist mechanics and determine the influence of traditional and contemporary sporting classifications on cardiac strain and twist mechanics. Methods: We searched PubMed/MEDLINE, Web of Science, and ScienceDirect for controlled studies of aged-matched male participants aged 18–45 years that used two-dimensional (2D) speckle tracking with a defined athlete sporting discipline and a control group not engaged in training programs. Data were extracted independently by two reviewers. Random-effects meta-analyses, subgroup analyses, and meta-regressions were conducted. Results: Our review included 13 studies with 945 participants (controls n = 355; athletes n = 590). Meta-analyses showed no athlete–control differences in LV strain or twist mechanics. However, moderator analyses showed greater LV twist in high-static low-dynamic athletes (d = –0.76, 95% confidence interval [CI] –1.32 to –0.20; p < 0.01) than in controls. Peak untwisting velocity (PUV) was greater in high-static low-dynamic athletes (d = –0.43, 95% CI –0.84 to –0.03; p < 0.05) but less than controls in high-static high-dynamic athletes (d = 0.79, 95% CI 0.002–1.58; p = 0.05). Elite endurance athletes had significantly less twist and apical rotation than controls (d = 0.68, 95% CI 0.19–1.16, p < 0.01; d = 0.64, 95% CI 0.27–1.00, p = 0.001, respectively) but no differences in basal rotation. Meta-regressions showed LV mass index was positively associated with global longitudinal (b = 0.01, 95% CI 0.002–0.02; p < 0.05), whereas systolic blood pressure was negatively associated with PUV (b = –0.06, 95% CI –0.13 to –0.001; p = 0.05). Conclusion: Echocardiographic 2D speckle tracking can identify subtle physiological differences in adaptations to cardiac strain and twist mechanics between athletes and healthy controls. Differences in speckle tracking echocardiography-derived parameters can be identified using suitable sporting categorizations

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe