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Approaches to manage nonalcoholic fatty liver disease (NAFLD) are limited by an incomplete understanding of disease pathogenesis. The aim of this study was to identify hepatic gene-expression patterns associated with different patterns of liver injury in a high-risk cohort of adults with obesity. Using the NanoString Technologies (Seattle, WA) nCounter assay, we quantified expression of 795 genes, hypothesized to be involved in hepatic fibrosis, inflammation, and steatosis, in liver tissue from 318 adults with obesity. Liver specimens were categorized into four distinct NAFLD phenotypes: normal liver histology (NLH), steatosis only (steatosis), nonalcoholic steatohepatitis without fibrosis (NASH F0), and NASH with fibrosis stage 1-4 (NASH F1-F4). One hundred twenty-five genes were significantly increasing or decreasing as NAFLD pathology progressed. Compared with NLH, NASH F0 was characterized by increased inflammatory gene expression, such as gamma-interferon-inducible lysosomal thiol reductase (IFI30) and chemokine (C-X-C motif) ligand 9 (CXCL9), while complement and coagulation related genes, such as C9 and complement component 4 binding protein beta (C4BPB), were reduced. In the presence of NASH F1-F4, extracellular matrix degrading proteinases and profibrotic/scar deposition genes, such as collagens and transforming growth factor beta 1 (TGFB1), were simultaneously increased, suggesting a dynamic state of tissue remodeling. Conclusion: In adults with obesity, distinct states of NAFLD are associated with intrahepatic perturbations in genes related to inflammation, complement and coagulation pathways, and tissue remodeling. These data provide insights into the dynamic pathogenesis of NAFLD in high-risk individuals.

A hot isostatic pressing rejuvenation heat treatment is applied to a CMSX-4 type SX superalloy after it has been subjected to a low-cycle fatigue test to rupture. The evolution of microstructural defects, such as pores and cracks which are present after fatigue, has been tracked in 3D by X-ray tomography before and after rejuvenation. From the rejuvenated specimen, series of metallographic cross sections were prepared and investigated by scanning electron microscopy for getting complementary 2D information at high resolution. The micrographs were stitched to a panorama which was then matched into the 3D representation of the specimen volume. By combining 3D and 2D data, statistical volume-related quantities were achieved, while detailed characteristics have been assigned to individual defects present in the 2D panorama micrograph. This technique is in general appropriate for length-scale bridging microstructural investigations. Results of the performed investigations concerning the rejuvenation effect on the microstructure are presented and discussed.

T cell exhaustion is associated with failure to clear chronic infections and malignant cells. Defining the molecular mechanisms of T cell exhaustion and reinvigoration is essential to improving immunotherapeutic modalities. Here we confirmed pervasive phenotypic, functional and transcriptional differences between memory and exhausted antigen-specific CD8+ T cells in human hepatitis C virus (HCV) infection before and after treatment. After viral cure, phenotypic changes in clonally stable exhausted T cell populations suggested differentiation toward a memory-like profile. However, functionally, the cells showed little improvement, and critical transcriptional regulators remained in the exhaustion state. Notably, T cells from chronic HCV infection that were exposed to antigen for less time because of viral escape mutations were functionally and transcriptionally more similar to memory T cells from spontaneously resolved HCV infection. Thus, the duration of T cell stimulation impacts exhaustion recovery, with antigen removal after long-term exhaustion being insufficient for the development of functional T cell memory. Lauer and colleagues examine CD8+ T cells following cure of human hepatitis C virus (HCV) infection. CD8+ T cells exposed to chronic HCV-specific activation show durable functional, phenotypic and transcriptional exhaustion that is maintained even after antigen stimulus is removed.

Introduction Understanding the costs to increase vaccination demand among under-vaccinated populations, as well as costs incurred by beneficiaries and caregivers for reaching vaccination sites, is essential to improving vaccination coverage. However, there have not been systematic analyses documenting such costs for beneficiaries and caregivers seeking vaccination. Methods We searched PubMed, Scopus, and the Immunization Delivery Cost Catalogue (IDCC) in 2019 for the costs for beneficiaries and caregivers to 1) seek and know how to access vaccination (i.e., costs to immunization programs for social mobilization and interventions to increase vaccination demand), 2) take time off from work, chores, or school for vaccination (i.e., productivity costs), and 3) travel to vaccination sites. We assessed if these costs were specific to populations that faced other non-cost barriers, based on a framework for defining hard-to-reach and hard-to-vaccinate populations for vaccination. Results We found 57 studies describing information, education, and communication (IEC) costs, social mobilization costs, and the costs of interventions to increase vaccination demand, with mean costs per dose at $0.41 (standard deviation (SD) $0.83), $18.86 (SD $50.65) and $28.23 (SD $76.09) in low-, middle-, and high-income countries, respectively. Five studies described productivity losses incurred by beneficiaries and caregivers seeking vaccination ($38.33 per person; SD $14.72; n = 3). We identified six studies on travel costs incurred by beneficiaries and caregivers attending vaccination sites ($11.25 per person; SD $9.54; n = 4). Two studies reported social mobilization costs per dose specific to hard-to-reach populations, which were 2–3.5 times higher than costs for the general population. Eight studies described barriers to vaccination among hard-to-reach populations. Conclusion Social mobilization/IEC costs are well-characterized, but evidence is limited on costs incurred by beneficiaries and caregivers getting to vaccination sites. Understanding the potential incremental costs for populations facing barriers to reach vaccination sites is essential to improving vaccine program financing and planning.

Introduction Economic evidence on how much it may cost for vaccinators to reach populations is important to plan vaccination programs. Moreover, knowing the incremental costs to reach populations that have traditionally been undervaccinated, especially those hard-to-reach who are facing supply-side barriers to vaccination, is essential to expanding immunization coverage to these populations. Methods We conducted a systematic review to identify estimates of costs associated with getting vaccinators to all vaccination sites. We searched PubMed and the Immunization Delivery Cost Catalogue (IDCC) in 2019 for the following costs to vaccinators: (1) training costs; (2) labor costs, per diems, and incentives; (3) identification of vaccine beneficiary location; and (4) travel costs. We assessed if any of these costs were specific to populations that are hard-to-reach for vaccination, based on a framework for examining supply-side barriers to vaccination. Results We found 19 studies describing average vaccinator training costs at $0.67/person vaccinated or targeted (SD $0.94) and $0.10/dose delivered (SD $0.07). The average cost for vaccinator labor and incentive costs across 29 studies was $2.15/dose (SD $2.08). We identified 13 studies describing intervention costs for a vaccinator to know the location of a beneficiary, with an average cost of $19.69/person (SD $26.65), and six studies describing vaccinator travel costs, with an average cost of $0.07/dose (SD $0.03). Only eight of these studies described hard-to-reach populations for vaccination; two studies examined incremental costs per dose to reach hard-to-reach populations, which were 1.3–2 times higher than the regular costs. The incremental cost to train vaccinators was $0.02/dose, and incremental labor costs for targeting hard-to-reach populations were $0.16–$1.17/dose. Conclusion Additional comparative costing studies are needed to understand the potential differential costs for vaccinators reaching the vaccination sites that serve hard-to-reach populations. This will help immunization program planners and decision-makers better allocate resources to extend vaccination programs.

Individuals can use information stored in episodic long-term memory (LTM) to optimize performance in a working memory (WM) task, and the WM system negotiates the exchange of information between WM and LTM depending on the current memory load. In this study, we assessed the ability of different accounts of interactions between LTM and WM to explain these findings, by investigating whether the position of pre-learnt information within a memory list encoded into WM affects the benefit it provides to immediate memory. In two experiments we varied the input position of previously learned word-word pairs within a set of four to-be-remembered pairs. We replicated previous findings of superior performance when these LTM pairs were included in the WM task and show that the position in the list in which these LTM pairs were included not seem to matter. These results are most consistent with the idea that having access to information in LTM reduces or removes the need to rely on WM for its storage, implying that people “offload” information in conditions containing LTM pairs.

Introduction During a pandemic, there are many situations in which the first available vaccines may not have as high effectiveness as vaccines that are still under development or vaccines that are not yet ready for distribution, raising the question of whether it is better to go with what is available now or wait. Methods In 2020, the team developed a computational model that represents the U.S. population, COVID-19 coronavirus spread, and vaccines with different possible efficacies (to prevent infection or to reduce severe disease) and vaccination timings to estimate the clinical and economic value of vaccination. Results Except for a limited number of situations, mainly early on in a pandemic and for a vaccine that prevents infection, when an initial vaccine is available, waiting for a vaccine with a higher efficacy results in additional hospitalizations and costs over the course of the pandemic. For example, if a vaccine with a 50% efficacy in preventing infection becomes available when 10% of the population has already been infected, waiting until 40% of the population are infected for a vaccine with 80% efficacy in preventing infection results in 15.6 million additional cases and 1.5 million additional hospitalizations, costing $20.6 billion more in direct medical costs and $12.4 billion more in productivity losses. Conclusions This study shows that there are relatively few situations in which it is worth foregoing the first COVID-19 vaccine available in favor of a vaccine that becomes available later on in the pandemic even if the latter vaccine has a substantially higher efficacy.

Pain disability is a primary target of treatment for chronic pain. Self-compassion shows promise as an intervention to reduce pain disability, but mechanisms linking self-compassion with less pain disability remain to be identified. This study examined two potential mechanisms, health self-efficacy and future self-identification (FSI), as parallel mediators of the relation between self-compassion and pain disability. Adults ( N = 188; Mage = 40.34, SD = 11.53; 70.9% female) screened for chronic pain were recruited through online convenience sampling. Participants completed self-report measures of demographics, health status, and primary study variables. Self-compassion was positively associated with FSI and self-efficacy, but only self-efficacy was found to mediate the negative relation between self-compassion and pain disability, such that self-compassion was associated with higher self-efficacy, which was associated with less pain disability. Future experimental and longitudinal studies can establish whether the negative relation between self-compassion and pain disability is causal and mediated via health self-efficacy.

BACKGROUND Teaching caregivers to respond to normal infant night awakenings in ways other than feeding is a common obesity prevention effort. Models can simulate caregiver feeding behavior while controlling for variables that are difficult to manipulate or measure in real life. METHODS We developed a virtual infant model representing an infant with an embedded metabolism and his/her daily sleep, awakenings, and feeds from their caregiver each day as the infant aged from 6 to 12 months (recommended age to introduce solids). We then simulated different night feeding interventions and their impact on infant body mass index (BMI). RESULTS Reducing the likelihood of feeding during normal night wakings from 79% to 50% to 10% lowered infant BMI from the 84th to the 75th to the 62nd percentile by 12 months, respectively, among caregivers who did not adaptively feed (e.g., adjust portion sizes of solid foods with infant growth). Among caregivers who adaptively feed, all scenarios resulted in relatively stable BMI percentiles, and progressively reducing feeding probability by 10% each month showed the least fluctuations. CONCLUSIONS Reducing night feeding has the potential to impact infant BMI, (e.g., 10% lower probability can reduce BMI by 20 percentile points) especially among caregivers who do not adaptively feed. IMPACT Teaching caregivers to respond to infant night waking with other soothing behaviors besides feeding has the potential to reduce infant BMI. When reducing the likelihood of feeding during night wakings from 79% to 50% to 10%, infants dropped from the 84th BMI percentile to the 75th to the 62nd by 12 months, respectively, among caregivers who do not adaptively feed. Night-feeding interventions have a greater impact when caregivers do not adaptively feed their infant based on their growth compared to caregivers who do adaptively feed. Night-feeding interventions should be one of the several tools in a multi-component intervention for childhood obesity prevention.

Introduction: With norovirus vaccine candidates currently under development, now is the time to identify the vaccine characteristics and implementation thresholds at which vaccination becomes cost effective and cost saving in a community setting. Methods: In 2020, a norovirus transmission, clinical, and economics computational simulation model representing different U.S. population segments was developed to simulate the spread of norovirus and the potential impact of vaccinating children aged

Background: Opsonization, is the molecular mechanism by which target molecules promote interactions with phagocyte cell surface receptors to remove unwanted cells by induced phagocytosis. We designed an in vitro system to demonstrate that this procedure could be driven to eliminate adipocytes, using peptides mimicking regions of the complement protein C3b to promote opsonization and enhance phagocytosis. Two cell lines were used: (1) THP-1 monocytes differentiated to macrophages, expressing the C3b opsonin receptor CR1 in charge of the removal of unwanted coated complexes; (2) 3T3-L1 fibroblasts differentiated to adipocytes, expressing AQP7, to evaluate the potential of peptides to stimulate opsonization. (3) A co-culture of the two cell lines to demonstrate that phagocytosis could be driven to cell withdrawal with high efficiency and specificity. Results: An array of peptides were designed and chemically synthesized p3691 and p3931 joined bound to the CR1 receptor activating phagocytosis (p

With the coronavirus disease 2019 (COVID-19) pandemic, one of the major concerns is the direct medical cost and resource use burden imposed on the US health care system. We developed a Monte Carlo simulation model that represented the US population and what could happen to each person who got infected. We estimated resource use and direct medical costs per symptomatic infection and at the national level, with various "attack rates" (infection rates), to understand the potential economic benefits of reducing the burden of the disease. A single symptomatic COVID-19 case could incur a median direct medical cost of $3,045 during the course of the infection alone. If 80 percent of the US population were to get infected, the result could be a median of 44.6 million hospitalizations, 10.7 million intensive care unit (ICU) admissions, 6.5 million patients requiring a ventilator, 249.5 million hospital bed days, and $654.0 billion in direct medical costs over the course of the pandemic. If 20 percent of the US population were to get infected, there could be a median of 11.2 million hospitalizations, 2.7 million ICU admissions, 1.6 million patients requiring a ventilator, 62.3 million hospital bed days, and $163.4 billion in direct medical costs over the course of the pandemic.

BACKGROUND: Currently, there are no solutions to prevent congenital transmission of Chagas disease during pregnancy, which affects 1–40% of pregnant women in Latin America and is associated with a 5% transmission risk. With therapeutic vaccines under development, now is the right time to determine the economic value of such a vaccine to prevent congenital transmission. METHODS: We developed a computational decision model that represented the clinical outcomes and diagnostic testing strategies for an infant born to a Chagas-positive woman in Mexico and evaluated the impact of vaccination. RESULTS: Compared to no vaccination, a 25% efficacious vaccine averted 125 [95% uncertainty interval (UI): 122–128] congenital cases, 1.9 (95% UI: 1.6–2.2) infant deaths, and 78 (95% UI: 66–91) DALYs per 10,000 infected pregnant women; a 50% efficacious vaccine averted 251 (95% UI: 248–254) cases, 3.8 (95% UI: 3.6–4.2) deaths, and 160 (95% UI: 148–171) DALYs; and a 75% efficacious vaccine averted 376 (95% UI: 374–378) cases, 5.8 (95% UI: 5.5–6.1) deaths, and 238 (95% UI: 227–249) DALYs. A 25% efficacious vaccine was cost-effective (incremental cost-effectiveness ratio

Introduction With Zika vaccine candidates under development and women of childbearing age being the primary target population, now is the time to map the vaccine (e.g., efficacy and duration of protection) and vaccination (e.g., cost) characteristic thresholds at which vaccination becomes cost effective, highly cost effective, and cost saving. Methods A Markov model was developed (to represent 2019 circumstances, US$ and INT$, Region of the Americas) to simulate a woman of childbearing age and the potential risk and clinical course of a Zika infection. Results Compared with no vaccination, vaccination was cost effective (incremental cost–effectiveness ratio: US$1,254–$82,900/disability-adjusted life years averted) when the risk of infection was ≥0.05%–0.08% (varying with country income), vaccine efficacy was ≥25%, and vaccination cost was US$1–$7,500 (INT$5–$10,000 depending on country income level). Vaccination was dominant (i.e., saved costs and provided beneficial health effects) when the infection risk was ≥0.1% for a vaccine efficacy ≥75% and when the infection risk was ≥0.5% for a vaccine efficacy ≥25%, for scenarios where vaccination conferred a 1-year duration of protection and cost ≤$200. In some cases, the vaccine was cost effective when the risk was as low as 0.015%, the cost was as high as $7,500 (INT$10,000), the efficacy was as low as 25%, and the duration of protection was 1 year. Conclusions The thresholds at which vaccination becomes cost effective and cost saving can provide targets for Zika vaccine development and implementation.

Background When trying to control regional spread of antibiotic-resistant pathogens such as carbapenem-resistant Enterobacteriaceae (CRE), decision makers must choose the highest-yield facilities to target for interventions. The question is, with limited resources, how best to choose these facilities. Methods Using our Regional Healthcare Ecosystem Analyst–generated agent-based model of all Chicago metropolitan area inpatient facilities, we simulated the spread of CRE and different ways of choosing facilities to apply a prevention bundle (screening, chlorhexidine gluconate bathing, hand hygiene, geographic separation, and patient registry) to a resource-limited 1686 inpatient beds. Results Randomly selecting facilities did not impact prevalence, but averted 620 new carriers and 175 infections, saving $6.3 million in total costs compared to no intervention. Selecting facilities by type (eg, long-term acute care hospitals) yielded a 16.1% relative prevalence decrease, preventing 1960 cases and 558 infections, saving $62.4 million more than random selection. Choosing the largest facilities was better than random selection, but not better than by type. Selecting by considering connections to other facilities (ie, highest volume of discharge patients) yielded a 9.5% relative prevalence decrease, preventing 1580 cases and 470 infections, and saving $51.6 million more than random selection. Selecting facilities using a combination of these metrics yielded the greatest reduction (19.0% relative prevalence decrease, preventing 1840 cases and 554 infections, saving $59.6 million compared with random selection). Conclusions While choosing target facilities based on single metrics (eg, most inpatient beds, most connections to other facilities) achieved better control than randomly choosing facilities, more effective targeting occurred when considering how these and other factors (eg, patient length of stay, care for higher-risk patients) interacted as a system.

Face mask wearing has been an important part of the response to the COVID-19 pandemic. As vaccination coverage progresses in countries, relaxation of such practices is increasing. Subsequent COVID-19 surges have raised the questions of whether face masks should be encouraged or required and for how long. Here, we aim to assess the value of maintaining face masks use indoors according to different COVID-19 vaccination coverage levels in the USA.In this computational simulation-model study, we developed and used a Monte Carlo simulation model representing the US population and SARS-CoV-2 spread. Simulation experiments compared what would happen if face masks were used versus not used until given final vaccination coverages were achieved. Different scenarios varied the target vaccination coverage (70-90%), the date these coverages were achieved (Jan 1, 2022, to July 1, 2022), and the date the population discontinued wearing face masks.Simulation experiments revealed that maintaining face mask use (at the coverage seen in the USA from March, 2020, to July, 2020) until target vaccination coverages were achieved was cost-effective and in many cases cost saving from both the societal and third-party payer perspectives across nearly all scenarios explored. Face mask use was estimated to be cost-effective and usually cost saving when the cost of face masks per person per day was ≤US$1·25. In all scenarios, it was estimated to be cost-effective to maintain face mask use for about 2-10 weeks beyond the date that target vaccination coverage (70-90%) was achieved, with this added duration being longer when the target coverage was achieved during winter versus summer. Factors that might increase the transmissibility of the virus (eg, emergence of the delta [B.1.617.2] and omicron [B.1.1.529] variants), or decrease vaccine effectiveness (eg, waning immunity or escape variants), or increase social interactions among certain segments of the population, only increased the cost savings or cost-effectiveness provided by maintaining face mask use.Our study provides strong support for maintaining face mask use until and a short time after achieving various final vaccination coverage levels, given that maintaining face mask use can be not just cost-effective, but even cost saving. The emergence of the omicron variant and the prospect of future variants that might be more transmissible and reduce vaccine effectiveness only increases the value of face masks.The Agency for Healthcare Research and Quality, the National Institute of General Medical Sciences, the National Science Foundation, the National Center for Advancing Translational Sciences, and the City University of New York.

The GH and IGF-1 axis is a candidate disease-modifying target in nonalcoholic fatty liver disease (NAFLD) given its lipolytic, anti-inflammatory and anti-fibrotic properties. IGF-1 receptor (IGF-1R) and GH receptor (GHR) expression in adult, human hepatic tissue is not well understood across the spectrum of NAFLD severity. Therefore, we sought to investigate hepatic IGF-1R and GHR expression in subjects with NAFLD utilizing gene expression analysis (GEA) and immunohistochemistry (IHC).GEA (n = 318) and IHC (n = 30) cohorts were identified from the Massachusetts General Hospital NAFLD Tissue Repository. GEA subjects were categorized based on histopathology as normal liver histology (NLH), steatosis only (Steatosis), nonalcoholic steatohepatitis (NASH) without fibrosis (NASH F0), and NASH with fibrosis (NASH F1-4) with GEA by the Nanostring nCounter assay. IHC subjects were matched for age, body mass index (BMI), sex, and diabetic status across three groups (n = 10 each): NLH, Steatosis, and NASH with fibrosis (NASH F1-3). IHC for IGF-1R, IGF-1 and GHR was performed on formalin-fixed, paraffin-embedded hepatic tissue samples.IGF-1R gene expression did not differ across NAFLD severity while IGF-1 gene expression decreased with increasing NAFLD severity, including when controlled for BMI and age. GHR expression did not differ by severity of NAFLD based on GEA or IHC.IGF-1R and GHR expression levels were not significantly different across NAFLD disease severity. However, expression of IGF-1 was lower with increasing severity of NAFLD. Additional research is needed regarding the contribution of the GH/IGF-1 axis to the pathophysiology of NAFLD and NASH.

Background & Aims: With or without antiviral treatment, few individuals achieve sustained functional cure of chronic hepatitis B virus (HBV) infection. A better definition of what mediates functional cure is essential for improving immunotherapeutic strategies. We aimed to compare HBV-specific T cell responses in patients with different degrees of viral control. Methods: We obtained blood from 124 HBV-infected individuals, including those with acute self-limiting HBV infection, chronic infection, and chronic infection with functional cure. We screened for HBV-specific T cell specificities by ELISpot, assessed the function of HBV-specific T cells using intracellular cytokine staining, and characterized HBV-specific CD4 T cells using human leukocyte antigen (HLA) class II tetramer staining, all directly ex vivo. Results: ELISpot screening readily identified HBV-specific CD4 and CD8 T cell responses in acute resolving infection compared with more limited reactivity in chronic infection. Applying more sensitive assays revealed higher frequencies of functional HBV-specific CD4 T cells, but not CD8 T cells, in functional cure compared to chronic infection. Function independent analysis using HLA multimers also identified more HBV-specific CD4 T cell responses in functional cure compared to chronic infection, with the emergence of CD4 T cell memory both after acute and chronic infection. Conclusions: Functional cure is associated with higher frequencies of functional HBV-specific CD4 memory T cell responses. Thus, immunotherapeutic approaches designed to induce HBV functional cure should also aim to improve CD4 T cell responses. Lay summary: Immunotherapy is a form of treatment that relies on harnessing the power of an individual's immune system to target a specific disease or pathogen. Such approaches are being developed for patients with chronic HBV infection, in an attempt to mimic the immune response in patients who control HBV infection spontaneously, achieving a so-called functional cure. However, what exactly defines protective immune responses remains unclear. Herein, we show that functional cure is associated with robust responses by HBV-specific CD4 T cells (a type of immune cell).

Inositol poly- and pyrophosphates (InsPs and PP-InsPs) are a group of central eukaryotic metabolites and signaling molecules. Due to the diverse cellular functions and widespread diseases InsPs and PP-InsPs are associated with, pharmacological targeting of the kinases involved in their biosynthesis has become a significant research interest in the last decade. In particular, the development of inhibitors for inositol hexakisphosphate kinases (IP6Ks) has leaped forward, while other inositol phosphate kinases have received scant attention. This review summarizes the efforts undertaken so far for discovering potent and selective inhibitors for this diverse group of small molecule kinases. The benefits of pharmacological inhibition are highlighted, given the multiple kinase-independent functions of inositol phosphate kinases. The distinct structural families of InsP and PP-InsP kinases are presented, and we discuss how compound availability for different inositol phosphate kinase families varies drastically. Lead compound discovery and optimization for the inositol kinases would benefit from detailed structural information on the ATP-binding sites of these kinases, as well as reliable biochemical and cellular read-outs to monitor inositol phosphate kinase activity in complex settings. Efforts to further tune well-established inhibitors, while simultaneously reviving tool compound development for the more neglected kinases from this family are indisputably worthwhile, considering the large potential therapeutic benefits.

Jet engines of airplanes are designed such that in some components damage occurs and accumulates in service without being critical up to a certain level of damage. Since maintenance, repair, and component exchange are very cost-intensive, it is necessary to predict efficiently the component lifetime with high accuracy. A former developed lifetime model, based on interpolated results of aerodynamic and structural mechanics simulations, uses material parameters estimated from literature values of standard creep experiments. For improved accuracy, an experimental procedure is developed for the characterization of the short-time creep behavior, which is relevant for the operation of turbine blades of jet engines. To consider microstructural influences resulting from the manufacturing of thin-walled single crystal turbine blades, small-scale specimens from used turbine blades are extracted and tested in short- and medium-time creep experiments. Based on experimental results and literature values, a creep model, which describes the fracture behavior for a wide range of creep loads, is calibrated and is now used for the lifetime prediction of turbine blades under real loading conditions. Flugzeugtriebwerke sind so ausgelegt, dass in einigen Komponenten während des Betriebs Schädigungen auftreten und akkumulieren können, ohne dass diese kritisch werden. Wegen der hohen Kosten von Wartung, Reparatur und Austausch ist es notwendig, die Lebensdauer der Komponenten möglichst effizient und genau vorherzusagen. Ein vorab entwickeltes Lebensdauermodell, welches auf interpolierten Ergebnissen von aerodynamischen und strukturmechanischen Simulationen basiert, nutzt in der Literatur verfügbare Daten aus Standard-Kriechversuchen. Um die Genauigkeit der Lebensdauervorhersage zu verbessern, wird eine Versuchstechnik zur experimentellen Charakterisierung des betriebsrelevanten Kurzzeit-Kriechverhaltens entwickelt. Mikrostrukturelle Einflüsse aus der Herstellung der dünnwandigen einkristallinen Turbinenschaufeln werden berücksichtigt, indem die Proben für die Kriechversuche aus gebrauchten Turbinenschaufeln extrahiert werden. Mit den Daten von Kriechversuchen mit kurzen bzw. mittleren Standzeiten wird nun das Lebensdauermodell kalibriert, so dass für einen weiten Bereich von Kriechlasten das Bruchverhalten von Turbinenschaufeln unter Betriebsbedingungen erfasst wird.

With the rise of digital technologies, electronic learning and communication tools are becoming a firm part of academia to promote knowledge of health sciences. This study sought to analyse the attitude of students regarding social media and digital learning for study purposes in sport and exercise science. A survey was carried out with a questionnaire (20 main items) in six sport science faculties, equally spread across Germany (G), Italy (I) and the United Kingdom (UK) between February and October 2017. The focus areas were students’ usage of social media (Facebook, Google+, Instagram, LinkedIn, Skype, Twitter, WhatsApp, YouTube) for academic purposes and their use of e-learning. Data were analysed by quantitative and qualitative methods. 229 students participated in the study (G: 68, I: 121, UK: 40). While YouTube was mostly used for receiving knowledge, WhatsApp and Facebook showed additional preferences for peer contacts for learning purposes and knowledge discussions. Preferred online data sources were PubMed (77%), free access journals (67%), YouTube (66%) and Wikipedia (63%). Often used digital learning materials were own universities’ PowerPoints (77%), scripts (59%) and scientific articles (53%). However, some preferences showed national differences. The evaluated participants showed an overall high use of social media and e-learning tools for their studies. Students would like more digital learning sources made available to them by their institutions. However, some differences in preferences of digital learning or communication tools may exist and this should be considered for international approaches to promote health knowledge among students.

BACKGROUND: Since special efforts are necessary to vaccinate people living far from fixed vaccination posts, decision makers are interested in knowing the economic value of such efforts. METHODS: Using our immunization geospatial information system platform and a measles compartment model, we quantified the health and economic value of a 2-dose measles immunization outreach strategy for children

Background Understanding the economics of vaccination is essential to developing immunization strategies that can be employed successfully with limited resources, especially when vaccinating populations that are hard-to-reach. Methods Based on the input from interviews with 24 global experts on immunization economics, we developed a systems map of the mechanisms (i.e., necessary steps or components) involved in vaccination, and associated costs and benefits, focused at the service delivery level. We used this to identify the mechanisms that may be different for hard-to-reach populations. Results The systems map shows different mechanisms that determine whether a person may or may not get vaccinated and the potential health and economic impacts of doing so. The map is divided into two parts: 1) the costs of vaccination, representing each of the mechanisms involved in getting vaccinated (n = 23 vaccination mechanisms), their associated direct vaccination costs (n = 18 vaccination costs), and opportunity costs (n = 5 opportunity costs), 2) the impact of vaccination, representing mechanisms after vaccine delivery (n = 13 impact mechanisms), their associated health effects (n = 10 health effects for beneficiary and others), and economic benefits (n = 13 immediate and secondary economic benefits and costs). Mechanisms that, when interrupted or delayed, can result in populations becoming hard-to-reach include getting vaccines and key stakeholders (e.g., beneficiaries/caregivers, vaccinators) to a vaccination site, as well as vaccine administration at the site. Conclusion Decision-makers can use this systems map to understand where steps in the vaccination process may be interrupted or weak and identify where gaps exist in the understanding of the economics of vaccination. With improved understanding of system-wide effects, this map can help decision-makers inform targeted interventions and policies to increase vaccination coverage in hard-to-reach populations.

Background With multiple coronavirus disease 2019 (COVID-19) vaccines available, understanding the epidemiologic, clinical, and economic value of increasing coverage levels and expediting vaccination is important. Methods We developed a computational model (transmission and age-stratified clinical and economics outcome model) representing the United States population, COVID-19 coronavirus spread (February 2020–December 2022), and vaccination to determine the impact of increasing coverage and expediting time to achieve coverage. Results When achieving a given vaccination coverage in 270 days (70% vaccine efficacy), every 1% increase in coverage can avert an average of 876 800 (217 000–2 398 000) cases, varying with the number of people already vaccinated. For example, each 1% increase between 40% and 50% coverage can prevent 1.5 million cases, 56 240 hospitalizations, and 6660 deaths; gain 77 590 quality-adjusted life-years (QALYs); and save $602.8 million in direct medical costs and $1.3 billion in productivity losses. Expediting to 180 days could save an additional 5.8 million cases, 215 790 hospitalizations, 26 370 deaths, 206 520 QALYs, $3.5 billion in direct medical costs, and $4.3 billion in productivity losses. Conclusions Our study quantifies the potential value of decreasing vaccine hesitancy and increasing vaccination coverage and how this value may decrease with the time it takes to achieve coverage, emphasizing the need to reach high coverage levels as soon as possible, especially before the fall/winter.

Finding medications or vaccines that may decrease the infectious period of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could potentially reduce transmission in the broader population. We developed a computational model of the U.S. simulating the spread of SARS-CoV-2 and the potential clinical and economic impact of reducing the infectious period duration. Simulation experiments found that reducing the average infectious period duration could avert a median of 442,852 [treating 25% of symptomatic cases, reducing by 0.5 days, reproductive number (R0) 3.5, and starting treatment when 15% of the population has been exposed] to 44.4 million SARS-CoV-2 cases (treating 75% of all infected cases, reducing by 3.5 days, R0 2.0). With R0 2.5, reducing the average infectious period duration by 0.5 days for 25% of symptomatic cases averted 1.4 million cases and 99,398 hospitalizations; increasing to 75% of symptomatic cases averted 2.8 million cases. At $500/person, treating 25% of symptomatic cases saved $209.5 billion (societal perspective). Further reducing the average infectious period duration by 3.5 days averted 7.4 million cases (treating 25% of symptomatic cases). Expanding treatment to 75% of all infected cases, including asymptomatic infections (R0 2.5), averted 35.9 million cases and 4 million hospitalizations, saving $48.8 billion (societal perspective and starting treatment after 5% of the population has been exposed). Our study quantifies the potential effects of reducing the SARS-CoV-2 infectious period duration., Author summary Finding medications or vaccines that may decrease the infectious period of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could potentially reduce transmission in the broader population. We developed a computational model of the U.S. simulating the spread of SARS-CoV-2 and the potential clinical and economic impact of reducing the infectious period duration. Our simulation experiments found that reducing the average infectious period duration could avert a median of 442,852 to 44.4 million SARS-CoV-2 cases, varying the proportion of cases treated, average duration of the infectious period, and the reproductive rate. At $500/person, treating 25% of symptomatic cases saved $209.5 billion (societal perspective, R0 2.5). Further reducing the average infectious period duration by 3.5 days averted 7.4 million cases (treating 25% of symptomatic cases). Expanding treatment to 75% of all infected cases, including asymptomatic infections (R0 2.5), averted 35.9 million cases and 4 million hospitalizations, saving $48.8 billion (societal perspective and starting treatment after 5% of the population has been exposed). Our study suggests that finding ways to reduce the infectious period of SARS-CoV-2 could help decrease its spread and impact.

Typically, long-term acute care hospitals (LTACHs) have less experience in and incentives to implementing aggressive infection control for drug-resistant organisms such as carbapenem-resistant Enterobacteriaceae (CRE) than acute care hospitals. Decision makers need to understand how implementing control measures in LTACHs can impact CRE spread regionwide. Using our Chicago metropolitan region agent-based model to simulate CRE spread and control, we estimated that a prevention bundle in only LTACHs decreased prevalence by a relative 4.6%–17.1%, averted 1,090–2,795 new carriers, 273–722 infections and 37–87 deaths over 3 years and saved $30.5–$69.1 million, compared with no CRE control measures. When LTACHs and intensive care units intervened, prevalence decreased by a relative 21.2%. Adding LTACHs averted an additional 1,995 carriers, 513 infections, and 62 deaths, and saved $47.6 million beyond implementation in intensive care units alone. Thus, LTACHs may be more important than other acute care settings for controlling CRE, and regional efforts to control drug-resistant organisms should start with LTACHs as a centerpiece.

T cells play an important role to build up an effective immune response and are essential in the eradication of pathogens. To establish a long-lasting protection even after a re-challenge with the same pathogen, some T cells differentiate into memory T cells. Recently, a certain subpopulation of memory T cells at different tissue-sites of infection was detected—tissue-resident memory T cells (TRM cells). These cells can patrol in the tissue in order to encounter their cognate antigen to establish an effective protection against secondary infection. The liver as an immunogenic organ is exposed to a variety of pathogens entering the liver through the systemic blood circulation or via the portal vein from the gut. It could be shown that intrahepatic TRM cells can reside within the liver tissue for several years. Interestingly, hepatic TRM cell differentiation requires a distinct cytokine milieu. In addition, TRM cells express specific surface markers and transcription factors, which allow their identification delimited from their circulating counterparts. It could be demonstrated that liver TRM cells play a particular role in many liver diseases such as hepatitis B and C infection, non-alcoholic fatty liver disease and even play a role in the development of hepatocellular carcinoma and in building long-lasting immune responses after vaccination. A better understanding of intrahepatic TRM cells is critical to understand the pathophysiology of many liver diseases and to identify new potential drug targets for the development of novel treatment strategies.

Both acute and chronic hepatic inflammation likely result from an imbalance in the TH1/TH2 cell response and can lead to liver fibrosis and end-stage liver disease. More recently, a novel CD4+ T helper cell subset was described, characterized by the production of IL-17 and IL-22. These TH17 cells 50were predominantly implicated in host defense against infections and in autoimmune diseases. Interestingly, studies over the last 10 years revealed that the development of TH17 cells favors pro-inflammatory responses in almost all tissues and there is a reciprocal relationship between TH17 and TReg cells. The balance between TH17and TReg cells is critical for immune reactions, especially in injured liver tissue and the return to immune homeostasis. The pathogenic contribution of TH17 and TReg cells in autoimmunity, acute infection, and chronic liver injury is diverse and varies among disease etiologies. Understanding the mechanisms underlying TH17 cell development, recruitment, and maintenance, along with the suppression of TReg cells, will inform the development of new therapeutic strategies in liver diseases. Active manipulation of the balance between pathogenic and regulatory processes in the liver may assist in the restoration of homeostasis, especially in hepatic inflammation.

Both acute and chronic hepatic inflammation likely result from an imbalance in the TH1/TH2 cell response and can lead to liver fibrosis and end-stage liver disease. More recently, a novel CD4+ T helper cell subset was described, characterized by the production of IL-17 and IL-22. These TH17 cells 50were predominantly implicated in host defense against infections and in autoimmune diseases. Interestingly, studies over the last 10 years revealed that the development of TH17 cells favors pro-inflammatory responses in almost all tissues and there is a reciprocal relationship between TH17 and TReg cells. The balance between TH17and TReg cells is critical for immune reactions, especially in injured liver tissue and the return to immune homeostasis. The pathogenic contribution of TH17 and TReg cells in autoimmunity, acute infection, and chronic liver injury is diverse and varies among disease etiologies. Understanding the mechanisms underlying TH17 cell development, recruitment, and maintenance, along with the suppression of TReg cells, will inform the development of new therapeutic strategies in liver diseases. Active manipulation of the balance between pathogenic and regulatory processes in the liver may assist in the restoration of homeostasis, especially in hepatic inflammation.

In fabricating electronic components or devices via Aerosol Jet Printing (AJP) there are numerous options for commercially available Metal NanoParticle (MNP) inks. Regardless of the MNP ink selected, the electrical properties of the final product are not commensurate to those of the bulk metal due to the inherent porosity and impurity-infused composition that is characteristic of these heterogeneous feedstock. Hence, choosing the best MNP ink for a particular application can be difficult, even among those based on the same metal, as each ink formulation can yield different performance metrics depending on the specific formulation and the conditions under which it is processed. In this article, the DC conductivity of AJP pads and the Radio Frequency (RF) transmission loss of AJP Coplanar Waveguides (CPWs) are presented for three different, commercially available silver MNP inks; Advanced Nano Products (ANP) Silverjet DGP 40LT-15C, Clariant Prelect TPS 50 G2, and UT Dots UTDAg40X. We determined conductivity values by measuring the printed pad thicknesses using stylus profilometry and measuring sheet resistances using a co-linear 4-point probe. Additionally, we collected RF spectra using a performance network analyzer over the 10 MHz – 40 GHz range. A complete description of the preparation, AJP procedure, and sintering is provided. Conductivity and RF data are presented for several scenarios including sintering temperatures, sintering atmospheres, and un-sintered storage conditions. We anticipate this dataset will serve as a useful reference for benchmarking electrical performance and troubleshooting pre- and post-processing steps for Ag nanoparticle based AJP inks.

Background Although norovirus outbreaks periodically make headlines, it is unclear how much attention norovirus may receive otherwise. A better understanding of the burden could help determine how to prioritize norovirus prevention and control. Methods We developed a computational simulation model to quantify the clinical and economic burden of norovirus in the United States. Results A symptomatic case generated $48 in direct medical costs, $416 in productivity losses ($464 total). The median yearly cost of outbreaks was $7.6 million (range across years, $7.5–$8.2 million) in direct medical costs, and $165.3 million ($161.1–$176.4 million) in productivity losses ($173.5 million total). Sporadic illnesses in the community (incidence, 10–150/1000 population) resulted in 14 118–211 705 hospitalizations, 8.2–122.9 million missed school/work days, $0.2–$2.3 billion in direct medical costs, and $1.4–$20.7 billion in productivity losses ($1.5–$23.1 billion total). The total cost was $10.6 billion based on the current incidence estimate (68.9/1000). Conclusion Our study quantified norovirus’ burden. Of the total burden, sporadic cases constituted >90% (thus, annual burden may vary depending on incidence) and productivity losses represented 89%. More than half the economic burden is in adults ≥45, more than half occurs in winter months, and >90% of outbreak costs are due to person-to-person transmission, offering insights into where and when prevention/control efforts may yield returns.

BackgroundGiven the continuing coronavirus disease 2019 (COVID-19) pandemic and much of the U.S. implementing social distancing due to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing.MethodsIn 2020, we developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination.ResultsSimulation experiments revealed that when vaccine efficacy exceeded 70%, coverage exceeded 60%, and vaccination occurred on day 1, the attack rate dropped to 22% with daily cases not exceeding 3.2 million (reproductive rate, R0, 2.5). When R0 was 3.5, the attack rate dropped to 41% with daily cases not exceeding 14.4 million. Increasing coverage to 75% when vaccination occurred by day 90 resulted in 5% attack rate and daily cases not exceeding 258,029when R0 was 2.5 and a 26% attack rate and maximum daily cases of 22.6 million when R0 was 3.5. When vaccination did not occur until day 180, coverage (i.e., those vaccinated plus those otherwise immune) had to reach 100%. A vaccine with an efficacy between 40% and 70% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages.ConclusionOur study found that to either prevent or largely extinguish an epidemic without any other measures (e.g., social distancing), the vaccine has to have an efficacy of at least 70%.

Introduction Given the continuing COVID-19 pandemic and much of the U.S. implementing social distancing owing to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing. Methods In 2020, the team developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination. Results Simulation experiments revealed that to prevent an epidemic (reduce the peak by >99%), the vaccine efficacy has to be at least 60% when vaccination coverage is 100% (reproduction number=2.5–3.5). This vaccine efficacy threshold rises to 70% when coverage drops to 75% and up to 80% when coverage drops to 60% when reproduction number is 2.5, rising to 80% when coverage drops to 75% when the reproduction number is 3.5. To extinguish an ongoing epidemic, the vaccine efficacy has to be at least 60% when coverage is 100% and at least 80% when coverage drops to 75% to reduce the peak by 85%–86%, 61%–62%, and 32% when vaccination occurs after 5%, 15%, and 30% of the population, respectively, have already been exposed to COVID-19 coronavirus. A vaccine with an efficacy between 60% and 80% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages. Conclusions This study found that the vaccine has to have an efficacy of at least 70% to prevent an epidemic and of at least 80% to largely extinguish an epidemic without any other measures (e.g., social distancing).

T cell exhaustion is associated with failure to clear chronic infections and malignant cells. Defining the molecular mechanisms of T cell exhaustion and reinvigoration is essential to improving immunotherapeutic modalities. Here we confirmed pervasive phenotypic, functional, and transcriptional differences between memory and exhausted antigen-specific CD8+ T cells in human hepatitis C virus (HCV) infection before and after treatment. After viral cure, phenotypic changes in clonally stable exhausted T cell populations suggested differentiation towards a memory-like profile. However, functionally, the cells showed little improvement and critical transcriptional regulators remained in the exhaustion state. Notably, T cells from chronic HCV infection that were exposed to antigen for less time because of viral escape mutations were functionally and transcriptionally more similar to memory T cells from spontaneously resolved HCV infection. Thus, T cell stimulation duration impacts exhaustion recovery, with antigen removal after long-term exhaustion being insufficient for development of functional T cell memory.

Background The protection that an influenza vaccine offers can vary significantly from person to person due to differences in immune systems, body types, and other factors. The question, then, is what is the value of efforts to reduce this variability such as making vaccines more personalized and tailored to individuals. Methods We developed a compartment model of the United States to simulate different influenza seasons and the impact of reducing the variability in responses to the influenza vaccine across the population. Results Going from a vaccine that varied in efficacy (0–30%) to one that had a uniform 30% efficacy for everyone averted 16.0–31.2 million cases, $1.9–$3.6 billion in direct medical costs, and $16.1–$42.7 billion in productivity losses. Going from 0–50% in efficacy to just 50% for everyone averted 27.7–38.6 million cases, $3.3–$4.6 billion in direct medical costs, and $28.8–$57.4 billion in productivity losses. Going from 0–70% to 70% averted 33.6–54.1 million cases, $4.0–$6.5 billion in direct medical costs, and $44.8–$64.7 billion in productivity losses. Conclusions This study quantifies for policy makers, funders, and vaccine developers and manufacturers the potential impact of efforts to reduce variability in the protection that influenza vaccines offer (eg, developing vaccines that are more personalized to different individual factors).

With the coronavirus disease 2019 (COVID-19) pandemic, one of the major concerns is the direct medical cost and resource use burden imposed on the US health care system. We developed a Monte Carlo simulation model that represented the US population and what could happen to each person who got infected. We estimated resource use and direct medical costs per symptomatic infection and at the national level, with various "attack rates" (infection rates), to understand the potential economic benefits of reducing the burden of the disease. A single symptomatic COVID-19 case could incur a median direct medical cost of $3,045 during the course of the infection alone. If 80 percent of the US population were to get infected, the result could be a median of 44.6 million hospitalizations, 10.7 million intensive care unit (ICU) admissions, 6.5 million patients requiring a ventilator, 249.5 million hospital bed days, and $654.0 billion in direct medical costs over the course of the pandemic. If 20 percent of the US population were to get infected, there could be a median of 11.2 million hospitalizations, 2.7 million ICU admissions, 1.6 million patients requiring a ventilator, 62.3 million hospital bed days, and $163.4 billion in direct medical costs over the course of the pandemic.