Stochastic Electrochemical Measurement of a Biofouling Layer on Gold.

Adsorption of a biofouling layer on the surface of biosensors decreases the electrochemical activity and hence shortens the service life of biosensors, particularly implantable and wearable biosensors. Real-time quantification of the loss of activity is important for in situ assessment of performance while presenting an opportunity to compensate for the loss of activity and recalibrate the sensor to extend the service life. Here, we introduce an electrochemical noise measurement technique as a tool for the quantification of the formation of a biofouling layer on the surface of gold. The technique uniquely affords thermodynamic and kinetic information without applying an external bias (potential and/or current), hence allowing the system to be appraised in its innate state. The technique relies on the analysis of non-faradaic current and potential fluctuations that are intrinsically generated by the interaction of charged species at the electrode surface, i.e., gold. An analytical model is extended to explain the significance of parameters drawn from statistical analysis of the noise signal. This concept is then examined in buffered media in the presence of albumin, a common protein in the blood and a known source of a fouling layer in biological systems. Results indicate that the statistical analysis of the noise signal can quantify the loss of electrochemical activity, which is also corroborated by impedance spectroscopy as a complementary technique.

NLC-Based Sunscreen Formulations with Optimized Proportion of Encapsulated and Free Filters Exhibit Enhanced UVA and UVB Photoprotection.

The topical use of sunscreens is recommended for avoiding the damaging effects of UV radiation. However, improvements are still needed in the existing products to enhance their photoprotection effectiveness and safety. This involves minimizing the use of chemical UV filters while providing enhanced and prolonged photoprotection. This work investigated novel sunscreen formulations and their UV protection effects by encapsulating Uvinul® A, Tinosorb® S, and Uvinul® T150 into nanostructured lipid carriers (NLCs) based on bacuri butter and raspberry seed oil. First, the impact of critical formulation and process parameters on NLCs' particle size was evaluated using a 22 Face Centered Central Composite Design. Then, formulations were evaluated in terms of critical quality factors, in vitro skin permeation, and in vitro and in vivo photoprotection activities. The developed NLCs-containing formulations exhibited appropriate size (122-135 nm), PdI (<0.3), encapsulation efficiency (>90%), and drug content (>80%), which were preserved for at least 90 days under different stability conditions. Moreover, these NLCs-based formulations had equivalent skin permeation to emulsion-based controls, and the addition of NLCs into sunscreen cream bases in the optimum proportion of 20% (w/w) resulted in enhanced UVA and UVB photoprotection levels, despite a 10% reduction in the total filters content. Altogether, these results describe the application of nanoencapsulated organic UV filters in innovative sunscreen formulations to achieve superior photoprotection and cosmeceutical properties.

Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic.

The COVID-19 pandemic offers an unprecedented natural experiment providing insights into the emergence of collective behavioral changes of both exogenous (government mandated) and endogenous (spontaneous reaction to infection risks) origin. Here, we characterize collective physical distancing-mobility reductions, minimization of contacts, shortening of contact duration-in response to the COVID-19 pandemic in the pre-vaccine era by analyzing de-identified, privacy-preserving location data for a panel of over 5.5 million anonymized, opted-in U.S. devices. We define five indicators of users' mobility and proximity to investigate how the emerging collective behavior deviates from typical pre-pandemic patterns during the first nine months of the COVID-19 pandemic. We analyze both the dramatic changes due to the government mandated mitigation policies and the more spontaneous societal adaptation into a new (physically distanced) normal in the fall 2020. Using the indicators here defined we show that: a) during the COVID-19 pandemic, collective physical distancing displayed different phases and was heterogeneous across geographies, b) metropolitan areas displayed stronger reductions in mobility and contacts than rural areas; c) stronger reductions in commuting patterns are observed in geographical areas with a higher share of teleworkable jobs; d) commuting volumes during and after the lockdown period negatively correlate with unemployment rates; and e) increases in contact indicators correlate with future values of new deaths at a lag consistent with epidemiological parameters and surveillance reporting delays. In conclusion, this study demonstrates that the framework and indicators here presented can be used to analyze large-scale social distancing phenomena, paving the way for their use in future pandemics to analyze and monitor the effects of pandemic mitigation plans at the national and international levels.

Approaches to Improving the Selectivity of Nanozymes.

Nanozymes mimic enzymes and that includes their selectivity. To achieve selectivity, significant inspiration for nanoparticle design can come from the geometric and molecular features that make enzymes selective catalysts. The two central features enzymes use are control over the arrangement of atoms in the active site and the placing of the active site down a nanoconfined substrate channel. The implementation of enzyme-inspired features has already been shown to both improve activity and selectivity of nanoparticles for a variety of catalytic and sensing applications. The tuning and control of active sites on metal nanoparticle surfaces ranges from simply changing the composition of the surface metal to sophisticated approaches such as the immobilization of single atoms on a metal substrate. Molecular frameworks provide a powerful platform for the implementation of isolated and discrete active sites while unique diffusional environments further improve selectivity. The implementation of nanoconfined substrate channels around these highly controlled active sites offers further ability to control selectivity through altering the solution environment and transport of reactants and products. Implementing these strategies together offers a unique opportunity to improve nanozyme selectivity in both sensing and catalysis.

Association of serum testosterone with chronic obstructive pulmonary disease (COPD) in a nationally representative sample of White, Black, and Hispanic men.

BACKGROUND: The association between total testosterone (T) and chronic obstructive pulmonary disease (COPD), remains poorly understood. We aim to investigate this association and how it varies by smoking status, body fatness, and race/ethnicity in a nationally representative sample of American men. METHODS: Data included a full sample (NHANES 1988-1991, 1999-2004, 2011-2012) and subset sample (excluding 2011-2012, no estradiol and SHBG levels available) of 2748 and 906 men (≥20 years), respectively. COPD was measured by self-report or spirometry test. Total T (ng/mL) was measured among men who participated in a morning examination session. Weighted multivariable-adjusted logistic regression models were conducted. RESULTS: Low T was positively associated with self-reported COPD in the full sample (OR = 2.10, 95% CI = 1.18-3.74, Ptrend = 0.010), and when stratified by current smokers and body fatness. When examined across race and ethnicity strata, this association persisted among White men (OR = 2.50, 95% CI = 1.30-4.79, Ptrend = 0.002) but not among Hispanic or Black men. In the subset sample, low T was positively associated with self-reported COPD (OR = 1.42, 95% CI, 0.57,3.55, Ptrend = 0.04), including among smokers and White men, but not body fatness. No significant associations were observed with COPD defined with spirometry plus self-report. CONCLUSION: Low levels of T were associated with an increased prevalence of self-reported COPD in the full and subset samples. Similar associations were observed after stratifying by smoking status, body fatness, and race/ethnicity in the full sample and subset sample. Prospective studies are warranted to confirm these significant associations among understudied and underserved populations.

Microplastics in oral healthcare products (OHPs) and their environmental health risks and mitigation measures.

The environmental input of microplastics from personal care products has received significant attention; however, less focus has been paid to oral healthcare products. The present study assessed the occurrence of microplastics in commercially available oral healthcare products such as toothbrushes, toothpastes, toothpowder, mouthwash, dental floss, and mouth freshener spray that have a pan-India distribution. The extracted microplastics were quantified and characterised using a microscope and ATR-FTIR. All products showed microplastic contamination, where toothbrushes showed the maximum particles (30-120 particles/brush) and mouth freshener sprays (0.2-3.5 particles/ml) had the least abundance. Fragments, fibres, beads, and films were the various shapes of microplastics observed, where fragments (60%) were dominant. Various colours such as pink, green, blue, yellow, black, and colourless were observed, where colourless (40%) particles were dominant. Microplastics were categorized into three sizes: <0.1 mm (63%), 0.1-0.3 mm (35%), and >0.3 mm (2%). Four major types of polymers, such as polyethylene (52%), polyamide (30%), polyethylene terephthalate (15%), and polybutylene terephthalate (3%), were identified. Risk assessment studies such as Daily Microplastics Emission (DME), Annual Microplastics Exposure (AME), and Polymer Hazard Index (PHI) were carried out. The DME projection for India was the highest for mouthwash (74 billion particles/day) and the least for mouth freshener sprays (0.36 billion particles/day). The AME projection for an individual was the highest in toothbrushes (48,910 particles ind.-1 yr.-1) and the least in mouth freshener sprays (111 particles ind.-1 yr.-1). PHI shows that the identified polymers fall under the low-to high-risk categories. This study forecasts the community health risks linked to microplastics in oral healthcare products and suggests mitigation strategies. It has the potential to shape environmental policy development in response.

Pd nanoparticles embedded in nanolignin (Pd@LNP) as a water dispersible catalytic nanoreactor for Cr(VI), 4-nitrophenol reduction and CC coupling reactions.

The use of water-dispersible and sustainable Pd nanocatalysts to reduce toxic heavy metal ions and catalyze important organic reactions has profound significance for the environmental remediation and the catalytic industry. In this work, a novel water-dispersible and recyclable Pd@LNPs nanoreactor composed of Pd nanoparticle cluster core and LNPs shell was developed in microwave reactor in aqueous solution. It turned out that Pd nanoparticles grew uniformly and stably inside LNPs nanosphere due to the coordinated binding and interaction between Pd and the functional groups in LNPs, which was significantly different from surface loading. The green and biodegradable LNPs nanospheres are not only used as reducing agents for Pd (II) and nanocarriers, but also act as individual nanocontainers to provide favorable sites for reactions and effectively control the entry and release of reactants and products. Furthermore, the excellent and efficient catalytic properties of Pd@LNPs were exhibited by CC coupling reactions and the reduction of Cr(VI) and 4-nitrophenol. The Pd@LNPs prepared in this study have the advantages of excellent dispersion, great recyclability, high turnover frequency and better green sustainability metrics. It will have a great significance for the development of the potential high-value of lignin and the progress in the field of bio-nanocatalysts.

Immediate smoking cessation support during lung cancer screening: long-term outcomes from two randomised controlled trials.

BACKGROUND: Immediate smoking cessation interventions delivered alongside targeted lung health checks (TLHCs) to screen for lung cancer increase self-reported abstinence at 3 months. The impact on longer term, objectively confirmed quit rates remains to be established. METHODS: We followed up participants from two clinical trials in people aged 55-75 years who smoked and took part in a TLHC. These randomised participants in the TLHC by day of attendance to either usual care (UC) (signposting to smoking cessation services) or an offer of immediate smoking cessation support including pharmacotherapy. In the QuLIT1 trial, this was delivered face to face and in QuLIT2, it was delivered remotely. Follow-up was conducted 12 months after the TLHC by telephone interview with subsequent biochemical verification of smoking cessation using exhaled CO. RESULTS: 430 people were enrolled initially (115 in QuLIT1 and 315 in QuLIT2), with 4 deaths before 12 months leaving 426 (62.1±5.27 years old and 48% women) participants for analysis. At 12 months, those randomised to attend on smoking cessation support intervention days had higher quit rates compared with UC adjusted for age, gender, deprivation, and which trial they had been in; self-reported 7-day point prevalence (20.0% vs 12.8%; adjusted OR (AOR)=1.78; 95% CI 1.04 to 2.89) and CO-verified quits (12.1% vs 4.7%; AOR=2.97; 95% CI 1.38 to 6.90). Those in the intervention arm were also more likely to report having made a quit attempt (30.2% vs UC 18.5%; AOR 1.90; 95% CI 1.15 to 3.15). CONCLUSION: Providing immediate smoking cessation support alongside TLHC increases long term, biochemically confirmed smoking abstinence. TRIAL REGISTRATION NUMBER: ISRCTN12455871.

Quantitative subcellular reconstruction reveals a lipid mediated inter-organelle biogenesis network.

The structures and functions of organelles in cells depend on each other but have not been systematically explored. We established stable knockout cell lines of peroxisomal, Golgi and endoplasmic reticulum genes identified in a whole-genome CRISPR knockout screen for inducers of mitochondrial biogenesis stress, showing that defects in peroxisome, Golgi and endoplasmic reticulum metabolism disrupt mitochondrial structure and function. Our quantitative total-organelle profiling approach for focussed ion beam scanning electron microscopy revealed in unprecedented detail that specific organelle dysfunctions precipitate multi-organelle biogenesis defects, impair mitochondrial morphology and reduce respiration. Multi-omics profiling showed a unified proteome response and global shifts in lipid and glycoprotein homeostasis that are elicited when organelle biogenesis is compromised, and that the resulting mitochondrial dysfunction can be rescued with precursors for ether-glycerophospholipid metabolic pathways. This work defines metabolic and morphological interactions between organelles and how their perturbation can cause disease.

Host-pathogen coevolution promotes the evolution of general, broad-spectrum resistance and reduces foreign pathogen spillover risk.

Genetic variation for disease resistance within host populations can strongly impact the spread of endemic pathogens. In plants, recent work has shown that within-population variation in resistance can also affect the transmission of foreign spillover pathogens if that resistance is general. However, most hosts also possess specific resistance mechanisms that provide strong defenses against coevolved endemic pathogens. Here we use a modeling approach to ask how antagonistic coevolution between hosts and their endemic pathogen at the specific resistance locus can affect the frequency of general resistance, and therefore a host's vulnerability to foreign pathogens. We develop a two-locus model with variable recombination that incorporates both general resistance (effective against all pathogens) and specific resistance (effective against endemic pathogens only). With coevolution, when pathogens can evolve to evade specific resistance, we find that the regions where general resistance can evolve are greatly expanded, decreasing the risk of foreign pathogen invasion. Furthermore, coevolution greatly expands the conditions that maintain polymorphisms at both resistance loci, thereby driving greater genetic diversity within host populations. This genetic diversity often leads to positive correlations between host resistance to foreign and endemic pathogens, similar to those observed in natural populations. However, if resistance loci become linked, the resistance correlations can shift to negative. If we include a third linkage-modifying locus in our model, we find that selection often favors complete linkage. Our model demonstrates how coevolutionary dynamics with an endemic pathogen can mold the resistance structure of host populations in ways that affect its susceptibility to foreign pathogen spillovers, and that the nature of these outcomes depends on resistance costs, as well as the degree of linkage between resistance genes.

Financial Performance is Associated With PPE Shortages in Chain-Affiliated Nursing Homes During the COVID-19 Pandemic: A Longitudinal Study.

Many nursing homes operated at thin profit margins prior to the COVID-19 pandemic. This study examines the role of nursing homes' financial performance and chain affiliation in shortages of personal protection equipment (PPE) during the first year of the COVID-19 pandemic. We constructed a longitudinal file of 79 868 nursing home-week observations from 10 872 unique facilities. We found that a positive profit margin was associated with a 21.0% lower probability of reporting PPE shortages in chain-affiliated nursing homes, but not in non-chain nursing homes. Having adequate financial resources may help nursing homes address future emergencies, especially those affiliated with a multi-facility chain.

Radiomics-based decision support tool assists radiologists in small lung nodule classification and improves lung cancer early diagnosis.

BACKGROUND: Methods to improve stratification of small (≤15 mm) lung nodules are needed. We aimed to develop a radiomics model to assist lung cancer diagnosis. METHODS: Patients were retrospectively identified using health records from January 2007 to December 2018. The external test set was obtained from the national LIBRA study and a prospective Lung Cancer Screening programme. Radiomics features were extracted from multi-region CT segmentations using TexLab2.0. LASSO regression generated the 5-feature small nodule radiomics-predictive-vector (SN-RPV). K-means clustering was used to split patients into risk groups according to SN-RPV. Model performance was compared to 6 thoracic radiologists. SN-RPV and radiologist risk groups were combined to generate "Safety-Net" and "Early Diagnosis" decision-support tools. RESULTS: In total, 810 patients with 990 nodules were included. The AUC for malignancy prediction was 0.85 (95% CI: 0.82-0.87), 0.78 (95% CI: 0.70-0.85) and 0.78 (95% CI: 0.59-0.92) for the training, test and external test datasets, respectively. The test set accuracy was 73% (95% CI: 65-81%) and resulted in 66.67% improvements in potentially missed [8/12] or delayed [6/9] cancers, compared to the radiologist with performance closest to the mean of six readers. CONCLUSIONS: SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.

Wastewater surveillance facilitates climate change-resilient pathogen monitoring.

Traditional disease surveillance systems are ill-equipped to handle climate change-driven shifts in pathogen dynamics. If paired with wastewater surveillance, a cost-effective and scalable approach for generating high-resolution health data, such next-generation systems can enable effective resource allocation and delivery of targeted interventions.

Sing to me, baby: Infants show neural tracking and rhythmic movements to live and dynamic maternal singing.

Infant-directed singing has unique acoustic characteristics that may allow even very young infants to respond to the rhythms carried through the caregiver's voice. The goal of this study was to examine neural and movement responses to live and dynamic maternal singing in 7-month-old infants and their relation to linguistic development. In total, 60 mother-infant dyads were observed during two singing conditions (playsong and lullaby). In Study 1 (n = 30), we measured infant EEG and used an encoding approach utilizing ridge regressions to measure neural tracking. In Study 2 (n =40), we coded infant rhythmic movements. In both studies, we assessed children's vocabulary when they were 20 months old. In Study 1, we found above-threshold neural tracking of maternal singing, with superior tracking of lullabies than playsongs. We also found that the acoustic features of infant-directed singing modulated tracking. In Study 2, infants showed more rhythmic movement to playsongs than lullabies. Importantly, neural coordination (Study 1) and rhythmic movement (Study 2) to playsongs were positively related to infants' expressive vocabulary at 20 months. These results highlight the importance of infants' brain and movement coordination to their caregiver's musical presentations, potentially as a function of musical variability.

Lung extracellular matrix modulates KRT5+ basal cell activity in pulmonary fibrosis.

Aberrant expansion of KRT5+ basal cells in the distal lung accompanies progressive alveolar epithelial cell loss and tissue remodelling during fibrogenesis in idiopathic pulmonary fibrosis (IPF). The mechanisms determining activity of KRT5+ cells in IPF have not been delineated. Here, we reveal a potential mechanism by which KRT5+ cells migrate within the fibrotic lung, navigating regional differences in collagen topography. In vitro, KRT5+ cell migratory characteristics and expression of remodelling genes are modulated by extracellular matrix (ECM) composition and organisation. Mass spectrometry- based proteomics revealed compositional differences in ECM components secreted by primary human lung fibroblasts (HLF) from IPF patients compared to controls. Over-expression of ECM glycoprotein, Secreted Protein Acidic and Cysteine Rich (SPARC) in the IPF HLF matrix restricts KRT5+ cell migration in vitro. Together, our findings demonstrate how changes to the ECM in IPF directly influence KRT5+ cell behaviour and function contributing to remodelling events in the fibrotic niche.

Host-pathogen coevolution promotes the evolution of general, broad-spectrum resistance and reduces foreign pathogen spillover risk.

Genetic variation for disease resistance within host populations can strongly impact the spread of endemic pathogens. In plants, recent work has shown that within-population variation in resistance can also affect the transmission of foreign spillover pathogens if that resistance is general. However, most hosts also possess specific resistance mechanisms that provide strong defenses against coevolved endemic pathogens. Here we use a modeling approach to ask how antagonistic coevolution between hosts and their endemic pathogen at the specific resistance locus can affect the frequency of general resistance, and therefore a host's vulnerability to foreign pathogens. We develop a two-locus model with variable recombination that incorporates both general (resistance to all pathogens) and specific (resistance to endemic pathogens only). We find that introducing coevolution into our model greatly expands the regions where general resistance can evolve, decreasing the risk of foreign pathogen invasion. Furthermore, coevolution greatly expands which conditions maintain polymorphisms at both resistance loci, thereby driving greater genetic diversity within host populations. This genetic diversity often leads to positive correlations between host resistance to foreign and endemic pathogens, similar to those observed in natural populations. However, if resistance loci become linked, the resistance correlations can shift to negative. If we include a third, linkage modifying locus into our model, we find that selection often favors complete linkage. Our model demonstrates how coevolutionary dynamics with an endemic pathogen can mold the resistance structure of host populations in ways that affect its susceptibility to foreign pathogen spillovers, and that the nature of these outcomes depends on resistance costs, as well as the degree of linkage between resistance genes.

Multiple Instance Learning Improves Ames Mutagenicity Prediction for Problematic Molecular Species.

The prediction of Ames mutagenicity continues to be a concern in both regulatory and pharmacological toxicology. Traditional quantitative structure-activity relationship (QSAR) models of mutagenicity make predictions based on molecular descriptors calculated on a chemical data set used in their training. However, it is known that molecules such as aromatic amines can be non-mutagenic themselves but metabolically activated by S9 rodent liver enzyme in Ames tests forming molecules such as iminoquinones or amine substituents that better stabilize mutagenic nitrenium ions in known pathways of mutagenicity. Modern in silico modeling methods can implicitly model these metabolites through consideration of the structural elements relevant to their formation but do not include explicit modeling of these metabolites' potential activity. These metabolites do not have a known individual mutagenicity label and, in their current state, cannot be fitted into a traditional QSAR model. Multiple instance learning (MIL) however can be applied to a group of metabolites and their parent under a single mutagenicity label. Here we trained MIL models on Ames data, first with an aromatic amines data set (n = 457), a class known to require metabolic activation, and subsequently on a larger data set (n = 6505) incorporating multiple molecular species. MIL was shown to be able to predict Ames mutagenicity with performance in line with previously established models (balanced accuracy = 0.778), suggesting its potential utility in Ames prediction applications. Furthermore, the MIL model predicted well on identified hard-to-predict molecule groups relative to the models in which these molecule groups were identified. These results are presumably due to the increased consideration of the metabolic contribution to the mutagenic outcome. Further exploration of MIL as a supplement to existing models could aid in the prediction of chemicals where implicit modeling of metabolites cannot fully grasp their characteristics. This paper demonstrates the potential of an MIL approach to modeling Ames tests with S9 and is particularly relevant to metabolically activated xenobiotic mutagens.

Anthocyanins and reactive oxygen species: a team of rivals regulating plant development?

Anthocyanins are a family of water-soluble vacuolar pigments present in almost all flowering plants. The chemistry, biosynthesis and functions of these flavonoids have been intensively studied, in part due to their benefit for human health. Given that they are efficient antioxidants, intense research has been devoted to studying their possible roles against damage caused by reactive oxygen species (ROS). However, the redox homeostasis established between antioxidants and ROS is important for plant growth and development. On the one hand, high levels of ROS can damage DNA, proteins, and lipids, on the other, they are also required for cell signaling, plant development and stress responses. Thus, a balance is needed in which antioxidants can remove excessive ROS, while not precluding ROS from triggering important cellular signaling cascades. In this article, we discuss how anthocyanins and ROS interact and how a deeper understanding of the balance between them could help improve plant productivity, nutritional value, and resistance to stress, while simultaneously maintaining proper cellular function and plant growth.

Nanoconfinement Allows a Less Active Cascade Catalyst to Produce More C2+ Products in Electrochemical CO2 Reduction.

Enzymes with multiple distinct active sites linked by substrate channels combined with control over the solution environment near the active sites enable the formation of complex products from simple reactants via the confinement of intermediates. We mimic this concept to facilitate the electrochemical carbon dioxide reduction reaction using nanoparticles with a core that produces intermediate CO at different rates and a porous copper shell. CO2 reacts at the core to produce CO which then diffuses through the Cu to give higher order hydrocarbon molecules. By altering the rate of CO2 delivery, the activity of the CO producing site, and the applied potential, we show that the nanoparticle with lower activity for CO formation produces greater amounts of hydrocarbon products. This is attributed to a combination of higher local pH and the lower amount of CO, resulting in more stable nanoparticles. However, when lower amounts of CO2 were delivered to the core, the particles that are more active for CO formation produce more C3 products. The importance of these results is twofold. They show that in cascade reactions, more active intermediate producing catalysts do not necessarily give greater amounts of high-value products. The effect an intermediate producing active site has on the local solution environment around the secondary active site plays an important role. As the less active catalyst for producing CO also possesses greater stability, we show that nanoconfinement can be used to get the best of both worlds with regard to having a stable catalyst with high activity.

Introduction: Healthcare Practitioners' Emotions and the Politics of Well-Being in Twentieth Century Anglo-America.

From the stress of burnout to the gratification of camaraderie, medicine is suffused with emotions that educators, administrators, and reformers have sought to shape. Yet historians of medicine have only begun to analyze how emotions have structured health care work. This introductory essay frames a special issue on health care practitioners' emotions in the twentieth-century United Kingdom and United States. We argue that the massive bureaucratic and scientific changes in medicine after the Second World War helped to reshape affective aspects of care. The articles in this issue emphasize the intersubjectivity of feelings in healthcare settings and the mutually constitutive relationship between patients' and providers' emotions. Bridging the history of medicine with the history of emotion demonstrates how emotions are instilled rather than innate, social as well as personal, and, above all else, change over time. The articles reckon with the power dynamics of healthcare. They address the policies and practices that institutions, organizations, and governments have implemented to shape, govern, or manage the affective experiences and well-being of healthcare workers. And they point to important new directions in the history of medicine.