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Face masks are an important tool for preventing the spread of COVID-19. However, it is unclear how different types of masks affect speech recognition in different levels of background noise. To address this, we investigated the effects of four masks (a surgical mask, N95 respirator, and two cloth masks) on recognition of spoken sentences in multi-talker babble. In low levels of background noise, masks had little to no effect, with no more than a 5.5% decrease in mean accuracy compared to a no-mask condition. In high levels of noise, mean accuracy was 2.8-18.2% lower than the no-mask condition, but the surgical mask continued to show no significant difference. The results demonstrate that different types of masks generally yield similar accuracy in low levels of background noise, but differences between masks become more apparent in high levels of noise.

In the past decade, advances in genome sequencing have allowed researchers to uncover the history of hybridization in diverse groups of species, including our own. Although the field has made impressive progress in documenting the extent of natural hybridization, both historical and recent, there are still many unanswered questions about its genetic and evolutionary consequences. Recent work has suggested that the outcomes of hybridization in the genome may be in part predictable, but many open questions about the nature of selection on hybrids and the biological variables that shape such selection have hampered progress in this area. We synthesize what is known about the mechanisms that drive changes in ancestry in the genome after hybridization, highlight major unresolved questions, and discuss their implications for the predictability of genome evolution after hybridization.

With COVID-19 vaccine roll-out ongoing in many countries globally, monitoring of breakthrough infections is of great importance. Antibodies persist in the blood after a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Since COVID-19 vaccines induce immune response to the Spike protein of the virus, which is the main serosurveillance target to date, alternative targets should be explored to distinguish infection from vaccination. Multiplex immunoassay data from 1,513 SARS-CoV-2 RT-qPCR-tested individuals (352 positive and 1,161 negative) without COVID-19 vaccination history were used to determine the accuracy of Nucleoprotein-specific immunoglobulin G (IgG) in detecting past SARS-CoV-2 infection. We also described Spike S1 and Nucleoprotein-specific IgG responses in 230 COVID-19 vaccinated individuals (Pfizer/BioNTech). The sensitivity of Nucleoprotein seropositivity was 85% (95% confidence interval: 80–90%) for mild COVID-19 in the first two months following symptom onset. Sensitivity was lower in asymptomatic individuals (67%, 50–81%). Participants who had experienced a SARS-CoV-2 infection up to 11 months preceding vaccination, as assessed by Spike S1 seropositivity or RT-qPCR, produced 2.7-fold higher median levels of IgG to Spike S1 ≥ 14 days after the first dose as compared to those unexposed to SARS-CoV-2 at ≥ 7 days after the second dose (p = 0.011). Nucleoprotein-specific IgG concentrations were not affected by vaccination in infection-naïve participants. Serological responses to Nucleoprotein may prove helpful in identifying SARS-CoV-2 infections after vaccination. Furthermore, it can help interpret IgG to Spike S1 after COVID-19 vaccination as particularly high responses shortly after vaccination could be explained by prior exposure history.

The COVID-19 pandemic was in 2020 and 2021 for a large part mitigated by reducing contacts in the general population. To monitor how these contacts changed over the course of the pandemic in the Netherlands, a longitudinal survey was conducted where participants reported on their at-risk contacts every two weeks, as part of the European CoMix survey. The survey included 1659 participants from April to August 2020 and 2514 participants from December 2020 to September 2021. We categorized the number of unique contacted persons excluding household members, reported per participant per day into six activity levels, defined as 0, 1, 2, 3–4, 5–9 and 10 or more reported contacts. After correcting for age, vaccination status, risk status for severe outcome of infection, and frequency of participation, activity levels increased over time, coinciding with relaxation of COVID-19 control measures.

The dynamic reorganization of some cellular biopolymers in response to signals has inspired efforts to create artificial materials with similar properties. Freeman et al. created hydrogels based on peptide amphiphiles that can bear DNA strands that assemble into superstructures and that disassemble in response to chemical triggers. The addition of DNA conjugates induced transitions from micelles to fibers and bundles of fibers. The resulting hydrogels were used as an extracellular matrix mimic for cultured cells. Switching the hydrogel between states also switched astrocytes between their reactive and naïve phenotypes. Science , this issue p. 808 Large-scale redistribution of molecules in a supramolecular material generates chemically reversible superstructures. Soft structures in nature, such as protein assemblies, can organize reversibly into functional and often hierarchical architectures through noncovalent interactions. Molecularly encoding this dynamic capability in synthetic materials has remained an elusive goal. We report on hydrogels of peptide-DNA conjugates and peptides that organize into superstructures of intertwined filaments that disassemble upon the addition of molecules or changes in charge density. Experiments and simulations demonstrate that this response requires large-scale spatial redistribution of molecules directed by strong noncovalent interactions among them. Simulations also suggest that the chemically reversible structures can only occur within a limited range of supramolecular cohesive energies. Storage moduli of the hydrogels change reversibly as superstructures form and disappear, as does the phenotype of neural cells in contact with these materials.

Background To inform future response planning we aimed to assess SARS‐CoV‐2 trends in infection‐ and/or vaccine‐induced immunity, including breakthrough infections, among (sub)groups, professions and regions in the Dutch population during the Variant of Concern (VOC)‐era. Methods In this prospective population‐based cohort, randomly selected participants (n = 9985) aged 1–92 years (recruited early‐2020) donated home‐collected fingerstick‐blood samples at six timepoints in 2021/2022, covering waves dominated by Alpha, Delta, and multiple Omicron (sub‐)variants. IgG antibody assessment against Spike‐S1 and Nucleoprotein was combined with vaccination‐ and testing data to estimate infection‐induced (inf) and total (infection‐ and vaccination‐induced) seroprevalence. Results Nationwide inf‐seroprevalence rose modestly from 12% (95% CI 11–13) since Alpha to 26% (95% CI 24–28) amidst Delta, while total seroprevalence increased rapidly to 87% (95% CI 85–88), particularly in elderly and those with comorbidities (i.e., vulnerable groups). Interestingly, highest infection rates were noticeable among low/middle educated elderly, non‐Western, those in contact professions, adolescents and young adults, and in low‐vaccination coverage regions. Following Omicron emergence, inf‐seroprevalence elevated sharply to 62% (95% CI 59–65) and further to 86% (95% CI 83–90) in late‐2022, with frequent breakthrough infections and decreasing seroprevalence dissimilarities between most groups. Whereas > 90% of < 60‐year‐olds had been infected at least once, 30% of vaccinated vulnerable individuals had still not acquired hybrid immunity. Conclusions Groups identified to have been infected disproportionally during the acute phase of the pandemic require specific attention in evaluation of control measures and future response planning worldwide. Furthermore, ongoing tailored vaccination efforts and (sero‐)monitoring of vulnerable groups may remain important.

The stress response allows the body to overcome obstacles and prepare for threats, but sustained levels of stress can damage one’s health. Stress has long been measured through physical tests and questionnaires that rely primarily on user-inputted data, which can be subjective and inaccurate. To quantify the amount of stress that the body is experiencing biologically, analytical detection of biomarkers associated with the stress response recently have been developed. Novel stress sensing devices focus on cortisol sweat sensing as a part of wearable, flexible devices. These devices promise a real-time, continuous collection of stress data that can be used in clinical diagnoses or for personal stress monitoring and mediation.

Clinical decision support systems (CDSSs) are computerized tools that support clinical decision-making processes. Primary care decision-making is complex and has the potential to influence quality of care provided and patient outcomes. CDSS not only assist providers with clinical decision-making to ensure quality standards are met, reflect evidence-informed practice, and reduce variation in care, but also help patients navigate and receive an appropriate care pathway amidst numerous, often complex, options. Therefore, this scoping review will aim to identify existing CDSSs for supporting primary point-of-care providers, directing patients to appropriate management pathways, and supporting the clinical examination (i.e., medical history-taking and physical examination) process for patients with shoulder disorders. At the primary point-of-care system level, a CDSS for shoulder disorders will improve clinical efficiency and support decision-making. Scoping review methodology and reporting will be conducted according to Arksey and O'Malley's 6-step framework, the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P), and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) extension for Scoping Reviews (PRISMA-ScR) reporting guide. A robust search strategy will be applied across four databases: MEDLINE (Ovid), EMBASE (Ovid), CINAHL (Ebsco), and Scopus (Elsevier). Two blinded reviewers will independently evaluate all titles and corresponding abstracts based on pre-specified inclusion and exclusion criteria. Inter-rater reliability (IRR) agreement will be established during an initial pilot-screening phase against a random selection of 20 records (minimum) until reaching Cohen's Kappa ≥ 0.81. Data extraction will be completed by one reviewer and validated by a second. An effective and high-quality CDSS that is affordable, easy to use, easily accessible, compatible with existing clinical processes, and generalizable across diverse settings will help to support primary point-of-care providers in diagnosing and managing patients presenting with shoulder disorders, thus improving quality of care for patients.

We describe health-related quality of life during the COVID-19 pandemic in the general Dutch population and correlations with restrictive measures. Data were obtained from 18-85 year-old participants of two population-based cohort studies (February 2021-July 2022): PIENTER Corona (n = 8,019) and VASCO (n = 45,413). Per cohort, mean scores of mental and physical health and health utility from the SF-12 were calculated by age group, sex and presence of a medical risk condition. Spearman correlations with stringency of measures were calculated. Both cohorts showed comparable results. Participants <30 years had lowest health utility and mental health score, and highest physical health score. Health utility and mental health score increased with age (up to 79 years), while physical health score decreased with age. Women and participants with a medical risk condition scored lower than their counterparts. Fluctuations were small over time but most pronounced among participants <60 years, and correlated weakly, but mostly positively with measure stringency. During the Dutch COVID-19 epidemic, health utility and mental health scores were lower and fluctuated strongest among young adults compared to older adults. In our study population, age, sex and presence of a medical risk condition seemed to have more impact on health scores than stringency of COVID-19 non-pharmaceutical interventions.

On a single night in 2023, more than 653,000 people experienced homelessness in the United States. In this overview, we highlight structural and individual risk factors that can lead to homelessness, explore evidence on the relationship between homelessness and health, discuss programmatic and policy innovations, and provide policy recommendations. Health system efforts to address homelessness and improve the health of homeless populations have included interventions such as screening for social needs and medical respite programs. Initiatives using the Housing First approach to permanent supportive housing have a strong track record of success. Health care financing innovations using Medicaid Section 1115 waivers offer promising new approaches to improving health and housing for people experiencing homelessness. To substantially reduce homelessness and its many adverse health impacts, changes are needed to increase the supply of affordable housing for households with very low incomes. Health care providers and systems should leverage their political power to advocate for policies that scale durable, evidence-based solutions to reduce homelessness, including increased funding to expand housing choice vouchers and greater investment in the creation and preservation of affordable housing.