Uptake Data Research Articles

A novel urokinase plasminogen activator receptor-targeted peptide-based probe for in-vivo molecular imaging of glioblastoma.

The urokinase plasminogen activator receptor (uPAR) is a promising biomarker for cancer diagnosis and therapy. We herein fabricated a new type of uPAR-targeted imaging probe Al18F-NOTA-VC and preliminarily evaluated its potential application in PET imaging of the glioma model in vivo. Peptide VC was synthesized and identified by MALDI-TOF-MS. The IC50 between VC/precursor NOTA-VC and uPAR was then determined before the synthesis and purification of Al18F-NOTA-VC, followed by further studies of in-vitro properties of Al18F-NOTA-VC. Meanwhile, the AE105-based probe followed a similar procedure in-vitro test. Finally, the PET imaging properties, including uPAR-targeting ability and the metabolism of Al18F-NOTA-VC, were investigated. The VC and NOTA-VC were obtained successfully and demonstrated a good affinity with uPAR. Followed by Al18F labeling successfully, excellent properties, including the serum stability, water solubility, and specificity of Al18F-NOTA-VC, were obtained in-vitro test compared with AE105 based probe. An excellent tumor uptake and renal excretion data of Al18F-NOTA-VC were acquired from in-vivo U87MG tumor model PET imaging, consistent with the subsequent biodistribution study. In addition to the excellent specificity and high tumor/normal tissue contrast for uPAR-targeted PET imaging of U87MG tumor, Al18F-NOTA-VC possessed promising clearance ability by renal system route. These excellent properties facilitated Al18F-NOTA-VC to be a promising imaging agent for uPAR high-expressing tumors and, thus, provided a paradigm for developing peptide-based probes for uPAR-associated disease diagnosis.

Impacts of Surface Adsorption on Water Uptake within a Metal Organic Nanotube Material.

The confinement-dependent properties of solvents, particularly water, within nanoporous spaces impart unique physical and chemical behavior compared to those of the bulk. This has previously been demonstrated for a U(VI)-based metal organic nanotube that displays ice-like arrays of water molecules within the 1-D pore space and complete selectivity to H2O over all other solvents and isotopologues. Based upon our previous work on D2O and HTO adsorption processes, we suggested that the water uptake was controlled by a two-step process: (1) surface adsorption via hydrogen bonding to hydrophilic amine and carboxylic groups and (2) diffusion of the water into the hydrophobic 1-D nanochannels. The current study seeks to evaluate this hypothesis and expand our existing kinetic model for the water diffusion step to account for the initial surface adsorption process. Vapor sorption experiments, paired with thermogravimetric and Fourier-transform infrared analyses, yielded uptake data that were fit using a Langmuir model for the surface-adsorption step of the mechanism. The water adsorption curve was designated a type IV Brunauer-Emmett-Teller isotherm, which indicated that our original hypothesis was correct. Additional work with binary solvent systems enabled us to evaluate the uptake in a range of conditions and determine that the uptake is not controlled by the vapor pressure but is instead completely dependent on the relative humidity of the system.

Model-Based Analysis of a Highly Efficient CO2 Separation Process Using Flexible Metal–Organic Frameworks with Isotherm Hysteresis

To realize large-scale CO2 separation to prevent global warming, energy and space saving separation technologies are required. Flexible metal–organic frameworks (flexible MOFs) with gate-opening properties have been found to be promising adsorbents, but the unconventional sigmoidal shapes and hysteresis of the isotherms have hindered quantitative evaluation of their applications in separation processes. This paper is the first to evaluate ELM-11, a flexible MOF that exhibits sigmoidal isotherms with hysteresis, in a process model and quantify its advantages over a conventional adsorbent. Based on the experimental uptake data, isotherm models for adsorption and desorption were developed, and their parameters were estimated. The resulting isotherm models are incorporated into a rigorous dynamic model of partial differential algebraic equations (PDAEs) to simulate a vacuum pressure swing adsorption (VPSA) process to evaluate the process performance. Numerical challenges to solve the PDAEs, including sigmoidal and hysteresis isotherm models, were resolved with the proposed numerical approaches. Sensitivity analysis for feed pressure and temperature was performed to identify the optimal operating strategy. A comparison with a conventional adsorbent, zeolite 13X, showed that high selectivity and sigmoidal isotherms of ELM-11 give higher productivity and CO2 product purity exceeding 99% without rinse and purge operations as well as lower power consumption for the compressor and vacuum pump.

Mapping glycine uptake and its metabolic conversion to glutathione in mouse mammary tumors using functional mass spectrometry imaging.

Although glutathione plays a key role in cancer cell viability and therapy response there is no clear trend in relating the level of this antioxidant to clinical stage, histological grade, or therapy response in patient tumors. The likely reason is that static levels of glutathione are not a good indicator of how a tissue deals with oxidative stress. A better indicator is the functional capacity of the tissue to maintain glutathione levels in response to this stress. However, there are few methods to assess glutathione metabolic function in tissue. We have developed a novel functional mass spectrometry imaging (fMSI) method that can map the variations in the conversion of glycine to glutathione metabolic activity across tumor tissue sections by tracking the fate of three glycine isotopologues administered in a timed sequence to tumor-bearing anesthetized mice. This fMSI method generates multiple time point kinetic data for substrate uptake and glutathione production from each spatial location in the tissue. As expected, the fMSI data shows glutathione metabolic activity varies across the murine 4T1 mammary tumor. Although glutathione levels are highest at the tumor periphery there are regions of high content but low metabolic activity. The timed infusion method also detects variations in delivery of the glycine isotopologues thereby providing a measure of tissue perfusion, including evidence of intermittent perfusion, that contributes to the observed differences in metabolic activity. We believe this new approach will be an asset to linking molecular content to tissue function.

Application of Metals Modified Carbon Based Material for Hydrogen Storage

The dependence on fossil fuel caused negative impact on the environment. It was predicted that the fossil fuel will be depleted in the near future. Various studies have been conducted to search for alternative clean energy supply.Hydrogen arises as a potential candidate due to its high energy storage and clean combustion of water vapor. However, the wide application of hydrogen energy met challenges.The hydrogen was often need to be stored in compressed tank and under specific pressures. It will require fossil fuel to provide the energy for the storage process. In order to solve that issue, different materials have been researched to store hydrogen at atmosphere pressure and room temperature.Nanomaterials materials have been used in many applications [1-30]. Carbon based materials are very attractive in many applications ranging from water purifications, catalysts support, gases purification and storage.In this study, we utilize cobalt, and nickel to improve the hydrogen storage ability of activated carbon. The activated carbon used in this study, derived from sustainable coconut shells.The structure and chemical composition of the composites was confirmed by using Powder X-Ray Diffraction (P-XRD), Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and Fourier Transform Infrared (FTIR). The BET surface area as well as the hydrogen uptake of all materials were measured using Micromeritics ASAP 2020.In conclusion, the hydrogen uptake data show that carbon-based material synthesized in this study significantly enhanced the hydrogen storage capacity. For example, the percentage of hydrogen uptake for nickel modified activated carbon was 5%.

(Invited) A Formalism Relating the Relative Humidity to the Proton Conductivity Mechanism of Membranes

The relationship between relative humidity of gas phase and proton conductivity in proton exchange membranes has been subject of extensive investigations [1],[2]. Herein, a theoretical framework is presented which describes proton transport in relation to stepwise equilibria that reflect the water uptake. In the proposed model, at first, the hydration process is treated as a stepwise equilibrium process, in agreement with experimental observations. Several hierarchical levels of structure evolve with increasing hydration. These levels are easily confirmed by the analysis of the electric response of perfluorinated based membranes by complex dielectric and conductivity spectra. Thus, a wide range of literature data on hydration of Nafion as a function of activity and temperature has been analyzed by means of the proposed model to extract chemical parameters diagnostic of the type of interactions characterizing the hydrophilic domains of membranes.These parameters, which are crucial in order to modulate the ion transport phenomena in ionomers, are then introduced into the model to describe the functional dependence of conductivity on water activity in gas phase. The treatment of proton conductivity is built on the approaches commonly adopted to describe transport in solids [3]. Key proton migration phenomena appropriate to the levels of the structural hierarchy are considered. The conductivity model is used to describe a set of conductivity vs. water uptake data as a function of temperature, with data taken to exceptionally low water contents. The formalism is then used to analyze a set of data for a perfluorosulfonic acid (PFSA) membrane as a function of hydration, temperature and polymer equivalent weight. The main advantage of the proposed framework is the possibility of a straightforward application to multiple membrane types based on the energetics of water uptake. Actually, the focus on chemical interactions allows to better correlate the effects of the morphology and relaxation events of the matrix to the proton migration phenomena of the membrane. Acknowledgements This work has received funding from: (a) the European Union’s Horizon 2020 research and innovation program under grant agreement 881603; (b) the project ‘Advanced Low-Platinum hierarchical Electrocatalysts for low-T fuel cells’ funded by EIT Raw Materials.

Routine Maternal Vaccine Uptake during the COVID-19 Pandemic.

This study examines the impact of the coronavirus disease 2019 (COVID-19) pandemic on influenza and tetanus toxoid, reduced diphtheria toxoid and acellular pertussis (Tdap) vaccine uptake in a pregnant, low-income population. This retrospective cohort study included women initiating prenatal care before (May-November 2019) or during the COVID-19 pandemic (May-November 2020) at two large Medicaid clinics. All patients entered prenatal care before 20 weeks and delivered full-term. Medical records were reviewed for vaccine uptake and demographic data. Multivariate logistic regression analysis was used to compare vaccination rates prior to and during the COVID-19 pandemic. Additional analysis was performed to identify association of demographic factors with vaccine uptake. IRB approval was obtained for this study. A total of 939 patients met inclusion criteria, with 462 initiating care prior to and 477 initiating care during the COVID-19 pandemic. Influenza vaccination uptake was 78% (362/462) in the prepandemic group, significantly decreasing to 61% (291/477) in the pandemic group (p <0.01, odds ratio [OR] = 0.38, confidence interval [CI]: 0.26-0.53). Tdap vaccination uptake was 85% (392/462) in the prepandemic group, significantly decreasing to 76% (361/477) in the pandemic group (p <0.01, OR = 0.56, CI: 0.40-0.79). The decrease in influenza vaccine uptake was most significant in non-Hispanic Black patients, decreasing from 64% (73/114) in the prepandemic group to 35% (35/101) in the pandemic group (p <0.01, OR = 0.30, CI: 0.17-0.52), while there was no significant difference in age or parity in relation to vaccination status. Routine vaccination uptake significantly decreased during the COVID-19 pandemic in a low-income population of pregnant women, with decrease more pronounced on influenza vaccine than on Tdap vaccine uptake, especially in non-Hispanic Black patients. · Influenza and Tdap vaccination uptake during pregnancy has decreased during the COVID-19 pandemic.. · Influenza vaccine uptake decreased more than Tdap in pregnancy during the COVID-19 pandemic.. · The greatest decrease was seen in influenza vaccine uptake in non-Hispanic Black patients..

Adoption of renewable home heating systems: An agent-based model of heat pumps in Ireland

Consumer adoption of renewable energy technologies such as heat pumps for home heating is crucial in reducing greenhouse gas emissions and reliance on imported fossil fuels. In recognition of their potential, policymakers in several countries have introduced various financial incentives to encourage the uptake of renewable energy technologies. However, consumers' purchasing decisions and choice of a particular technology is a complex process that goes beyond financial aspects. In this paper, we examine the adoption decisions and diffusion of heat pumps for residential home heating using an agent-based modeling and simulation approach. In particular, we model the influence of three factors: economic, psychological, and social networks, on the future uptake of heat pumps. We utilize recent nationally representative Irish household survey data and historical heat pump uptake data to derive model parameters for decision rules based on empirical data and simulate the adoption of heat pumps in existing Irish homes until 2030. We further analyze the implications of those future uptakes on electricity demand, bill savings, and reduction in CO2 emissions. The findings of this research based on the case study of Ireland should be useful to policymakers and companies in devising monetary and non-monetary interventions aimed at increasing future actual uptake of heat pumps and other renewable energy technologies.

Using a digital personal recovery resource in routine mental health practice: feasibility, acceptability and outcomes

Background Digital technologies enable the dissemination of multimedia resources to support adults with serious mental illness in their self-management and personal recovery. However, delivery needs to accommodate engagement and accessibility challenges. Aims We examined how a digital resource, designed for mental health workers and consumers to use together in session, would be used in routine practice. Methods Thirty consumers and their workers participated. The web-based resource, Self-Management And Recovery Technology (SMART), was available to use within and between sessions, for a 6-month period. Workers initiated in-session use where relevant. Feasibility was explored via uptake and usage data; and acceptability and impact via questionnaires. A pre-post design assessed recovery outcomes for consumers and relationship outcomes for consumers and workers. Results In participating mental health practitioner-consumer dyads, consumers gave strong acceptability ratings, and reported improved working relationships. However, the resource was typically used in one-third or fewer appointments, with consumers expressing a desire for greater in-session use. Improvements in self-rated personal recovery were not observed, possibly contributed to by low usage. Conclusions In-session use was found helpful by consumers but may be constrained by other demands in mental health care delivery: collaborative use may require dedicated staff time or more formal implementation.

Feasibility and outcomes of narrative enhancement and cognitive therapy (NECT) for reducing self-stigma among people with severe mental illness in the Netherlands: A pilot study.

The narrative enhancement and cognitive therapy (NECT) intervention aims to reduce self-stigma among people with severe mental illness. Based on previous studies that showed the intervention's beneficial outcomes, we conducted an uncontrolled pilot study of NECT in the Netherlands to assess both feasibility in delivering NECT and outcomes of the intervention for self-stigma, hope, recovery, and self-concept clarity. Feasibility was assessed through uptake and implementation data that included an assessment of enhancing and impeding factors according to surveys with NECT facilitators, and interviews with participants. Outcomes of NECT were studied through scales that assess self-stigma, self-concept clarity, hope, personal recovery, and quality of life. Forty-one participants from five treatment sites participated in the pilot study, among whom 78% were considered "exposed" (i.e., attended at least six sessions). The analysis of enhancing and impeding factors indicated that support from the organization, sense of ownership, expectations of outcomes, and content of the intervention were reported as important in the implementation process. Participants reported decreases in self-stigma and increases in hope during the intervention. Assessments of feasibility provided valuable insights regarding ways to improve implementation of the intervention (such as increasing facilitators' sense of ownership of the intervention). Outcomes of NECT showed a decrease in self-stigma and improvement of hope among participants in this pilot study, supporting the previously found positive effects of the intervention. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Evaluation of uptake values of FDG: Body surface area Vs. body weight correction

The uptake of Fluorine-18 fluoro-deoxy-glucose (18F-FDG) in tumors is assessed using the Standardized Uptake Values (SUVs). These values are usually normalized for the body weight of the patients (SUVbw). However, reported literature revealed an overestimation of uptake in obese patients who suffer from higher body fat content with low uptake of the 18F-FDG. Normalization of 18F-FDG uptake using body surface area (SUVbsa) may present a solution to overestimating uptake. The current study aims to evaluate uptake values of FDG in the tumor versus liver using two standardizing parameters: weight and area. Data for liver and tumor uptake were collected from 40 patients who underwent FDG-PET scans. Regarding uptake for the liver, the standardization using body weight, SUVbw, was calculated as tissue concentration over activity injected per body weight. Using surface area, SUVbsa used activity injected per surface area rather than weigh in the denominator. The correlation was performed to determine the association between the factors of age, body mass index (BMI), and liver SUVmax. The SUVbsa ranged between 0.79 and 5.8, and SUVbw ranged between 3.11 and 28.36. The range, as well as the standard deviation, were by far more in SUVbw than SUVbsa and the independence of the values on the size of patients proves that the latter is a preferable standardization method.

The associations between COVID-19 vaccination and psychological disorders among healthcare workers in China

IntroductionCOVID-19 has caused an unprecedented psychological affection that might impact the nationwide vaccination program in China. This study was to explore the association between COVID-19 vaccination and psychological disorders among healthcare workers. MethodsThe study included 1571 healthcare workers from an anonymous online survey. Participants' sociodemographic characteristics, uptake data for the COVID-19 vaccine, and scores of the Depression, Anxiety, and Stress Scale (DASS-21) were collected. Nonparametric tests were conducted to compare the mean scores of DASS-21 between different subgroups. The potential factors related to psychological disorders of healthcare workers were analyzed using logistic regression. ResultsThe vaccination rate was 69.6 %, the incidence of vaccine-related adverse events was 35.13 %, and the prevalence of depression, anxiety, and stress were 24.8 %, 32 %, and 33.4 % in this study, respectively. Compared to vaccinated participants (single-dose and double-dose vaccines), unvaccinated participants got significantly higher mean scores of DASS-21 (p < 0.05 for all). Vaccinated participants who suffered no adverse events scored significantly lower than those who suffered 1–2 or ≥3 adverse events (p < 0.05 for all). Vaccination was negatively associated with higher depression, anxiety, and stress, however, the number of vaccine-related adverse events was positively associated with them. LimitationsAs this is a cross-sectional study, we could only speculate on the causality. ConclusionsAn obvious impact of the psychological disorders on the COVID-19 vaccine coverage and related adverse events was detected in this study. Public health agencies should attach great importance to the psychological states of our citizens before getting vaccinated.

Synthesis of Cocos nucifera derived surfactant and its application in growth kinetics of methane gas hydrates for energy storage and transportation

The impact of surfactants on the formation kinetics and storage of gaseous fuels such as methane, propane, and hydrogen in the form of gas hydrates is well known. However, the excess generation of stable, hard, and toxic foam is one of the significant operational challenges (for the scale-up of gas hydrate processes) associated with conventional surfactants. This study is an attempt to fulfill the quest for mild, inexpensive, biocompatible, and efficient hydrate former required to develop a sustainable gas hydrate process. The present investigation reports the synthesis and application of Cocosnucifera-derived surfactant (CDS). The synthesized surfactant CDS may help in filling the gap by opening new opportunities in the storage and transport of natural gas in the form of gas hydrates. Here, the synthesis of CDS was followed by its characterization by H1 NMR, C13 NMR, FTIR (ATR), µ-DSC/TGA, and XRD, in addition to property evaluation such as foam stability, wettability, recovery, and recyclability. The comparative methane gas hydrate investigations on sodium dodecyl sulfate (SDS), sodium dodecyl benzene sulfonate (SDBS), and CDS were launched to determine their gas uptake behavior and water conversion efficiencies. Moreover, the morphology study was conducted to determine the real-time gas hydrate growth patterns and behavior to predict its correlation with the gas uptake data and mass transfer limitations. Overall, CDS surfactant showed competitive growth of the methane gas hydrates and proved a promising substitute for kinetic promotion. Additionally, the gas storage and transportation studies were conducted using laboratory-developed pellets under controlled conditions, and a process flow diagram based on the gas hydrate technology was demonstrated.

Selecting ideal drugs for encapsulation in thermosensitive liposomes and other triggered nanoparticles

Objective Thermosensitive liposomes (TSL) and other triggered drug delivery systems (DDS) are promising therapeutic strategies for targeted drug delivery. However, successful designs with candidate drugs depend on many variables, including nanoparticle formulation, drug properties, and cancer cell properties. We developed a computational model based on experimental data to predict the potential efficacies of drugs when used with triggered DDS, such as TSL. Methods A computer model based on the Krogh cylinder was developed to predict uptake and cell survival with four anthracyclines when delivered by intravascular triggered DDS (e.g., TSL): doxorubicin (DOX), idarubicin (IDA), pirarubicin (PIR), and aclarubicin (ACLA). We simulated three tumor types derived from SVR angiosarcoma, LLC lung cancer, or SCC-1 oral carcinoma cells. In vitro cellular drug uptake and cytotoxicity data were obtained experimentally and incorporated into the model. Results For all three cell lines, ACLA and IDA had the fastest cell uptake, with slower uptake for DOX and PIR. Cytotoxicity was highest for IDA and lowest for ACLA. The computer model predicted the highest tumor drug uptake for ACLA and IDA, resulting from their rapid cell uptake. Overall, IDA was most effective and produced the lowest tumor survival fraction, with DOX being the second best. Perivascular drug penetration was reduced for drugs with rapid cell uptake, potentially limiting delivery to cancer cells distant from the vasculature. Conclusion Combining simple in vitro experiments with a computer model could provide a powerful screening tool to evaluate the potential efficacy of candidate investigative drugs preceding TSL encapsulation and in vivo studies.

Web-Based Psychological Interventions for People Living With and Beyond Cancer: Meta-Review of What Works and What Does Not for Maximizing Recruitment, Engagement, and Efficacy.

BackgroundDespite high levels of psychological distress experienced by many patients with cancer, previous research has identified several barriers to accessing traditional face-to-face psychological support. Web-based psychosocial interventions have emerged as a promising alternative.ObjectiveThis meta-review aimed to synthesize evidence on recruitment challenges and enablers, factors that promote engagement and adherence to web-based intervention content, and factors that promote the efficacy of web-based psychosocial interventions for patients with cancer and cancer survivors.MethodsWe conducted a systematic search of previous reviews that investigated the recruitment, engagement, and efficacy of web-based and app-based psychosocial interventions in adult patients with cancer and cancer survivors. We searched PubMed, CINAHL, PsycINFO, and the Cochrane Library database for relevant literature. The search terms focused on a combination of topics pertaining to neoplasms and telemedicine. Two independent authors conducted abstract screening, full text screening, and data extraction for each identified article.ResultsA total of 20 articles met eligibility criteria. There was inconsistency in the reporting of uptake and engagement data; however, anxiety about technology and perceived time burden were identified as 2 key barriers. Web-based psychosocial oncology interventions demonstrated efficacy in reducing depression and stress but reported weak to mixed findings for distress, anxiety, quality of life, and well-being. Although no factors consistently moderated intervention efficacy, preliminary evidence indicated that multicomponent interventions and greater communication with a health care professional were preferred by participants and were associated with superior effects.ConclusionsSeveral consistently cited barriers to intervention uptake and recruitment have emerged, which we recommend future intervention studies address. Preliminary evidence also supports the superior efficacy of multicomponent interventions and interventions that facilitate communication with a health care professional. However, a greater number of appropriately powered clinical trials, including randomized trials with head-to-head comparisons, are needed to enable more confident conclusions regarding which web-based psychosocial oncology interventions work best and for whom.Trial RegistrationPROSPERO CRD42020202633; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=202633

(Invited, Digital Presentation) Detailed Chemical Modeling of Solid Electrolyte Interphase Growth and Evolution

The solid electrolyte interphase (SEI) is a layer that forms at the anode-electrolyte interphase in lithium ion batteries. The layer forms due to voltage instability of the electrolyte at low anode potentials, but serves to passivate the electrolyte to protect against further uncontrolled decomposition. In theory, the SEI is self-limiting, but in reality, continued growth over the battery’s lifetime leads to capacity fade, poor rate capability, and eventually cell death. Though significant progress in recent years has improved the SEI’s function and stability, poor understanding of its most basic chemistry impedes “rational design” of SEI layers for advanced battery applications. Understanding and quantifying the elementary chemistry of the SEI is made challenging by the layer’s thickness (10s to ~100 nm), chemical sensitivity, mechanical fragility, and complex chemistry (upwards of 100 reactions have been proposed). For these reasons, These factors combine to make studying the fundamental chemistry of SEI growth and evolution a significant challenge. Both the computational tools to model the SEI’s complex chemistry and the experimental data required to validate such models are all too rare.This talk will provide an overview of recent efforts to model the fundamental electrochemistry of SEI growth and evolution. The simulations are based on a continuum-scale, finite-volume framework, and leverage the open-source software package Cantera to enable efficient simulation of arbitrarily complex electrochemical mechanisms. Simulation results, as in Figure 1, are validated against two operando measurements of the SEI grown on a non-intercalating tungsten anode: depth profiling via neutron reflectometry (NR), and SEI mass uptake data via quartz crystal microbalance with dissipation (QCM-D) taken during cyclic voltammetry cycling. Interrogation of the detailed model results provide insights into the complex phenomena controlling initial SEI growth, and validation against NR and QCM-D data identify prominent reaction pathways and key chemical species present in the SEI. Finally, we will conclude by discussing future steps, includuing transferring mechanistic insights to new scales, geometries, and chemistries, and coupling models with inputs from atomistic simulations. Figure 1

Prominent Fatigue but No Motor Fatigability in Non-Hospitalized Patients With Post-COVID-Syndrome.

ObjectivesFatigue is a frequent and often disabling symptom in patients with post-COVID syndrome. To better understand and evaluate the symptom of motor fatigue in the context of the post-COVID syndrome, we conducted treadmill walking tests to detect the phenomenon of motor fatigability or to evaluate whether evidence of organic lesions of the motor system could be found, similar to patients with multiple sclerosis.MethodTwenty-nine non-hospitalized patients with post-COVID syndrome completed the Fatigue Scale for Motor and Cognitive Function (FSMC) questionnaire to determine the trait component of subjective fatigue before they were tested on a treadmill walking at a moderate speed for up to 60 min or until exhaustion. During the walking test oxygen uptake, ventilation and acceleration data of both feet were collected. To determine motor performance fatigability, the Fatigue Index Kliniken Schmieder (FKS) was calculated using the attractor method.ResultsThe average walking duration was 42.7 ± 18.6 min with 15 subjects stopping the walking test prematurely. The FSMC score revealed a severe cognitive (37.6 ± 8.2) and motor (37.1 ± 7.8) fatigue averaged over all subjects but only two subjects showed an FKS above the normal range (>4), representing performance fatigability. There was no significant correlation between subjective fatigue (FSMC) and FKS as well as walking time. Absolute values of oxygen uptake and ventilation were in the normal range reported in literature (r = 0.9, p < 0.05), although eight subjects did not produce a steady-state behavior.ConclusionAlmost all patients with post-COVID syndrome and subjectively severe motor fatigue, did not show motor fatigability nor severe metabolic anomalies. This is argued against organic, permanent damage to the motor system, as is often seen in MS. Many of the patients were - to our and their own surprise - motorically more exertable than expected.

When do persuasive messages on vaccine safety steer COVID-19 vaccine acceptance and recommendations? Behavioural insights from a randomised controlled experiment in Malaysia

IntroductionVaccine safety is a primary concern among vaccine-hesitant individuals. We examined how seven persuasive messages with different frames, all focusing on vaccine safety, influenced Malaysians to accept the COVID-19 vaccine,...

Data-Driven Real-Time Strategic Placement of Mobile Vaccine Distribution Sites

The deployment of vaccines across the US provides significant defense against serious illness and death from COVID-19. Over 70% of vaccine-eligible Americans are at least partially vaccinated, but there are pockets of the population that are under-vaccinated, such as in rural areas and some demographic groups (e.g. age, race, ethnicity). These pockets are extremely susceptible to the Delta variant, exacerbating the healthcare crisis and increasing the risk of new variants. In this paper, we describe a data-driven model that provides real-time support to Virginia public health officials by recommending mobile vaccination site placement in order to target under-vaccinated populations. Our strategy uses fine-grained mobility data, along with US Census and vaccination uptake data, to identify locations that are most likely to be visited by unvaccinated individuals. We further extend our model to choose locations that maximize vaccine uptake among hesitant groups. We show that the top recommended sites vary substantially across some demographics, demonstrating the value of developing customized recommendation models that integrate fine-grained, heterogeneous data sources. We also validate our recommendations by analyzing the success rates of deployed vaccine sites, and show that sites placed closer to our recommended areas administered higher numbers of doses. Our model is the first of its kind to consider evolving mobility patterns in real-time for suggesting placement strategies customized for different targeted demographic groups.

COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups.

This cross-sectional ecological study examined the relationship between neighborhood-level standard occupational groups in the USA and COVID-19 vaccine uptake using 774 census tract data, each consisting of approximately 1600 housing units. The neighborhood-level COVID-19 vaccination uptake data were retrieved from Harris County Public Health, Harris County, Texas. The standard occupational group data were from the US Census Bureau. We calculated the incidence rate ratios (IRRs) for vaccine uptake using bivariate and multivariable Poisson regression models. In the adjusted models, we found that the healthcare practitioner/technician (IRR: 1.008; 95% CI: 1.003–1.014; p = 0.001), business/management/legal (IRR: 1.011; 95% CI: 1.008–1.013; p < 0.001), computer/engineering/life/physical/social science (IRR: 1.018; 95% CI: 1.013–1.023; p < 0.001), and arts/design/entertainment/sports/media (IRR: 1.031; 95% CI: 1.018–1.044; p < 0.001) occupational groups were more likely to have received the full regimen of a COVID-19 vaccine. On the contrary, the building/installation/maintenance/repair (IRR: 0.991; 95% CI: 0.987–0.995; p < 0.001), construction/extraction/production (IRR: 0.991; 95% CI: 0.988–0.995; p < 0.001), transportation/material moving (IRR: 0.992; 95% CI: 0.987–0.997; p = 0.002), food preparation/serving related (IRR: 0.995; 95% CI: 0.990–0.999; p = 0.023), and personal care/services (IRR: 0.991; 95% CI: 0.985–0.998; p = 0.017) groups were less likely to have received the complete dose of a COVID-19 vaccine. White-collar workers were more likely to be vaccinated than blue-collar workers. We adjusted for age, sex, and race/ethnicity in the multivariable analysis. The low vaccine uptake among certain occupational groups remains a barrier to pandemic control. Engaging labor-centered stakeholders in the development of vaccination interventions may increase uptake.