Mechanical compression regulates tumor spheroid invasion into a 3D collagen matrix.

Uncontrolled growth of tumor cells in confined spaces leads to the accumulation of compressive stress within the tumor. Although the effects of tension within 3D extracellular matrices (ECMs) on tumor growth and invasion are well established, the role of compression in tumor mechanics and invasion is largely unexplored. In this study, we modified a Transwell assay such that it provides constant compressive loads to spheroids embedded within a collagen matrix. We used microscopic imaging to follow the single cell dynamics of the cells within the spheroids, as well as invasion into the 3D ECMs. Our experimental results showed that malignant breast tumor (MDA-MB-231) and non-tumorigenic epithelial (MCF10A) spheroids responded differently to a constant compression. Cells within the malignant spheroids became more motile within the spheroids and invaded more into the ECM under compression; whereas cells within non-tumorigenic MCF10A spheroids became less motile within the spheroids and did not display apparent detachment from the spheroids under compression. These findings suggest that compression may play differential roles in healthy and pathogenic epithelial tissues and highlight the importance of tumor mechanics and invasion.

Spatial Mapping of Hematopoietic Clones in Human Bone Marrow.

Clonal hematopoiesis (CH) is the expansion of somatically mutated cells in the hematopoietic compartment of individuals without hematopoietic dysfunction. Large CH clones (i.e., >2% variant allele fraction) predispose to hematologic malignancy, but CH is detected at lower levels in nearly all middle-aged individuals. Prior work has extensively characterized CH in peripheral blood, but the spatial distribution of hematopoietic clones in human bone marrow is largely undescribed. To understand CH at this level, we developed a method for spatially aware somatic mutation profiling and characterized the bone marrow of a patient with polycythemia vera. We identified the complex clonal distribution of somatic mutations in the hematopoietic compartment, the restriction of somatic mutations to specific subpopulations of hematopoietic cells, and spatial constraints of these clones in the bone marrow. This proof of principle paves the way to answering fundamental questions regarding CH spatial organization and factors driving CH expansion and malignant transformation in the bone marrow. SIGNIFICANCE: CH occurs commonly in humans and can predispose to hematologic malignancy. Although well characterized in blood, it is poorly understood how clones are spatially distributed in the bone marrow. To answer this, we developed methods for spatially aware somatic mutation profiling to describe clonal heterogeneity in human bone marrow. See related commentary by Austin and Aifantis, p. 139.

Impact of COVID-19 vaccination on symptoms and immune phenotypes in vaccine-naïve individuals with Long COVID.

Background: Long COVID contributes to the global burden of disease. Proposed root cause hypotheses include the persistence of SARS-CoV-2 viral reservoir, autoimmunity, and reactivation of latent herpesviruses. Patients have reported various changes in Long COVID symptoms after COVID-19 vaccinations, leaving uncertainty about whether vaccine-induced immune responses may alleviate or worsen disease pathology. Methods: In this prospective study, we evaluated changes in symptoms and immune responses after COVID-19 vaccination in 16 vaccine-naïve individuals with Long COVID. Surveys were administered before vaccination and then at 2, 6, and 12 weeks after receiving the first vaccine dose of the primary series. Simultaneously, SARS-CoV-2-reactive TCR enrichment, SARS-CoV-2-specific antibody responses, antibody responses to other viral and self-antigens, and circulating cytokines were quantified before vaccination and at 6 and 12 weeks after vaccination. Results: Self-report at 12 weeks post-vaccination indicated 10 out of 16 participants had improved health, 3 had no change, 1 had worse health, and 2 reported marginal changes. Significant elevation in SARS-CoV-2-specific TCRs and Spike protein-specific IgG were observed 6 and 12 weeks after vaccination. No changes in reactivities were observed against herpes viruses and self-antigens. Within this dataset, higher baseline sIL-6R was associated with symptom improvement, and the two top features associated with non-improvement were high IFN-ß and CNTF, among soluble analytes. Conclusions: Our study showed that in this small sample, vaccination improved the health or resulted in no change to the health of most participants, though few experienced worsening. Vaccination was associated with increased SARS-CoV-2 Spike protein-specific IgG and T cell expansion in most individuals with Long COVID. Symptom improvement was observed in those with baseline elevated sIL-6R, while elevated interferon and neuropeptide levels were associated with a lack of improvement.

CD44 and ß1-integrin are both engaged in cell traction force generation in hyaluronic acid-rich extracellular matrices.

Mechanical properties of the extracellular matrices (ECMs) critically regulate a number of important cell function including growth, differentiation and migration. Type I collagen and glycosaminoglycans (GAGs) are two primary components of ECMs that contribute to tissue mechanics with the collagen fiber network sustaining tension and GAGs withstanding compression. Collagen stiffness as well as its architecture are known to be important role players in cell-ECM mechanical interactions, however, much less is known about how GAGs within ECMs regulate cell force generation and invasion. Inspired by a recent theoretical work from the Shenoy lab that GAGs play important roles in cell - ECM interactions, we hereby present experimental studies on the role of hyaluronic acid (HA, an unsulfated GAG) in single tumor cell traction force generation within HA collagen cogels using a recently developed 3D cell traction force microscopy. Our work revealed that CD44, a cell surface adhesion receptor to HA, was engaged in cell traction force generation in conjunction with ß1-integrin. Furthermore, we found that HA significantly modified the architecture and mechanics of the collagen fiber network, decreased tumor cells' propensity to remodel the collagen network, decreased traction force generation and transmission distance, and attenuated tumor invasion in agreement with theoretical predictions. Our findings highlighted the significance of CD44 and HA engagement in cell-ECM mechanical interactions, providing new insights on the mechanical model of cellular force transmission.

Droplet Digital PCR for Oncogenic KMT2A Fusion Detection.

Acute myeloid leukemia (AML) is an aggressive blood cancer diagnosed in approximately 120,000 individuals worldwide each year. During treatment for AML, detecting residual disease is essential for prognostication and treatment decision-making. Currently, methods for detecting residual AML are limited to identifying approximately 1:100 to 1:1000 leukemic cells (morphology and DNA sequencing) or are difficult to implement (flow cytometry). AML arising after chemotherapy or radiation exposure is termed therapy-related AML (t-AML) and is exceptionally aggressive and treatment resistant. t-AML is often driven by oncogenic fusions that result from prior treatments that introduce double-strand DNA breaks. The most common t-AML-associated translocations affect KMT2A. There are at least 80 known KMT2A fusion partners, but approximately 80% of fusions involve only five partners-AF9, AF6, AF4, ELL, and ENL. We present a novel droplet digital PCR assay targeting the most common KMT2A-rearrangements to enable detection of rare AML cells harboring these fusions. This assay was benchmarked in cell lines and patient samples harboring oncogenic KMT2A fusions and demonstrated a limit of detection of approximately 1:1,000,000 cells. Future application of this assay could improve disease detection and treatment decision-making for patients with t-AML with KMT2A fusions and premalignant oncogenic fusion detection in at-risk individuals after chemotherapy exposure.

Mechanical compression regulates tumor spheroid invasion into a 3D collagen matrix.

Uncontrolled growth of tumor cells in confined spaces leads to the accumulation of compressive stress within the tumor. Although the effects of tension within 3D extracellular matrices on tumor growth and invasion are well established, the role of compression in tumor mechanics and invasion is largely unexplored. In this study, we modified a Transwell assay such that it provides constant compressive loads to spheroids embedded within a collagen matrix. We used microscopic imaging to follow the single cell dynamics of the cells within the spheroids, as well as invasion into the 3D extracellular matrices (EMCs). Our experimental results showed that malignant breast tumor (MDA-MB-231) and non-tumorigenic epithelial (MCF10A) spheroids responded differently to a constant compression. Cells within the malignant spheroids became more motile within the spheroids and invaded more into the ECM under compression; whereas cells within non-tumorigenic MCF10A spheroids became less motile within the spheroids and did not display apparent detachment from the spheroids under compression. These findings suggest that compression may play differential roles in healthy and pathogenic epithelial tissues and highlights the importance of tumor mechanics and invasion.

Coding long COVID: characterizing a new disease through an ICD-10 lens.

BACKGROUND: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of long COVID are still in flux, and the deployment of an ICD-10-CM code for long COVID in the USA took nearly 2 years after patients had begun to describe their condition. Here, we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for "Post COVID-19 condition, unspecified." METHODS: We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code (n = 33,782), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan. RESULTS: We established the diagnoses most commonly co-occurring with U09.9 and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty and low unemployment. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients. CONCLUSIONS: This work offers insight into potential subtypes and current practice patterns around long COVID and speaks to the existence of disparities in the diagnosis of patients with long COVID. This latter finding in particular requires further research and urgent remediation.

Long COVID: major findings, mechanisms and recommendations.

Long COVID is an often debilitating illness that occurs in at least 10% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. More than 200 symptoms have been identified with impacts on multiple organ systems. At least 65 million individuals worldwide are estimated to have long COVID, with cases increasing daily. Biomedical research has made substantial progress in identifying various pathophysiological changes and risk factors and in characterizing the illness; further, similarities with other viral-onset illnesses such as myalgic encephalomyelitis/chronic fatigue syndrome and postural orthostatic tachycardia syndrome have laid the groundwork for research in the field. In this Review, we explore the current literature and highlight key findings, the overlap with other conditions, the variable onset of symptoms, long COVID in children and the impact of vaccinations. Although these key findings are critical to understanding long COVID, current diagnostic and treatment options are insufficient, and clinical trials must be prioritized that address leading hypotheses. Additionally, to strengthen long COVID research, future studies must account for biases and SARS-CoV-2 testing issues, build on viral-onset research, be inclusive of marginalized populations and meaningfully engage patients throughout the research process.

SARS-CoV-2 Reinfection is Preceded by Unique Biomarkers and Related to Initial Infection Timing and Severity: an N3C RECOVER EHR-Based Cohort Study.

Although the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection incidence (5.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present novel findings that Long COVID diagnoses occur closer to the index date for infection or reinfection in the Omicron BA epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between first infection and reinfection (chi-squared value: 9446.2, p-value: 0) with a medium effect size (Cramer's V: 0.18, DoF = 4).

Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes.

BACKGROUND: Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. METHODS: We present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning. FINDINGS: We found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems. INTERPRETATION: Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC. FUNDING: NIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

miR21 deletion in osteocytes has direct and indirect effects on skeletal muscle in a sex-dimorphic manner in mice.

BACKGROUND: Osteocytic microRNA21 (miR21) removal alters cytokine production and bone mass by modulating osteoclast and osteoblast differentiation and activity. Removing osteocytic miR21 increases osteoclast/osteoblast numbers and bone mass in male mice, whereas it decreases osteoclasts/osteoblasts without affecting bone mass in female mice. On the other hand, it leads to sex-independent increases in bone mechanical properties. Because changes in bone remodeling and strength affect skeletal muscle through bone-muscle crosstalk, we investigated whether osteocytic miR21 deletion influences skeletal muscle. METHODS: miR21fl/fl mice and 8kbDMP1-Cre mice were mated to obtain miR21-deficient mice primarily in the osteocyte (OtmiR21Δ) and littermate controls (miR21fl/fl). Four-month-old male and female mice were analyzed. Body composition was examined by DXA/Piximus and gene expression was assessed by qPCR. Ex vivo cultures of long bones devoid of bone-marrow cells from male and female 4-month-old were maintained for 48 h. Conditioned media were collected and used for the C2C12 assays. Two-way ANOVA analyses were performed to determine the contributions of genotype and sex and their interaction to the effects of miR21 deficiency. RESULTS: Lean body mass was increased only in female OtmiR21Δ mice, although miR21 levels in soleus muscle were similar in miR21fl/fl (0.05 ± 0.02) and OtmiR21Δ (0.09 ± 0.04) mice. Female, but not male, OtmiR21Δ mice exhibited increased soleus (42%) and gastrocnemius (21%) muscle weight compared to miR21fl/fl littermates. However, muscle strength and gastrocnemius muscle fiber cross-sectional area were unaltered for either sex. Kinase phosphorylation (phospho/total protein ratio) in soleus muscle, measured as a surrogate for kinase activity by means of multiplex analysis, was also selectively changed depending on the mouse sex. Thus, female OtmiR21Δ mice had higher T185/Y187-ERK1/2 but lower S473-Akt phosphorylation than miR21fl/fl controls, while male OtmiR21Δ mice had higher S473-Akt phosphorylation, suggesting sex-dimorphic shifts in anabolic vs. catabolic signaling. Consistently, levels of FOXO3 and MuRF-1, known to be regulated by Akt, were only increased in male OtmiR21Δ mice. Atrogin-1 mRNA levels were upregulated in female OtmiR21Δ mice, suggesting a potential shift in protein regulation. Sex-specific effects were also found by exposing myotube cultures to conditioned media from 48-h-cultured marrow-flushed bones. Thus 5-day differentiated C2C12 myotubes treated with conditioned media of female OtmiR21Δ mice exhibit 12% higher average diameter compared to cells exposed to miR21fl/fl bone conditioned media. Yet, conditioned media from male bones had no effect on myotube size. CONCLUSIONS: We present a novel aspect of bone-muscle crosstalk in which osteocyte-derived miR21 influences skeletal muscle size, but not strength, in female but not male mice; whereas, intracellular signaling alterations resulting from loss of miR21 seem to alter protein dynamics in a sex-dimorphic fashion.

Coding Long COVID: Characterizing a new disease through an ICD-10 lens.

Background: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes Long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of Long COVID are still in flux, and the deployment of an ICD-10-CM code for Long COVID in the US took nearly two years after patients had begun to describe their condition. Here we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for "Post COVID-19 condition, unspecified." Methods: We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code ( n = 21,072), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan. Results: We established the diagnoses most commonly co-occurring with U09.9, and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty, high education, and high access to medical care. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients. Conclusions: This work offers insight into potential subtypes and current practice patterns around Long COVID, and speaks to the existence of disparities in the diagnosis of patients with Long COVID. This latter finding in particular requires further research and urgent remediation.

Diet, but not food type, significantly affects micronutrient and toxic metal profiles in urine and/or plasma; a randomized, controlled intervention trial.

BACKGROUND: Observational studies have linked Mediterranean Diets (MedDiets) and organic food consumption with positive health outcomes, which may be explained by higher mineral micronutrient and phenolic intake and lower dietary exposure to toxic compounds. OBJECTIVES: We aimed to determine the effects of diet and food type (organic compared with conventional) on urinary excretion (UE) and/or plasma concentrations of mineral micronutrients, phenolics, and toxic metals. METHODS: Healthy adult participants were randomly allocated to a conventional (n = 14) or an intervention (n = 13) group. During a 2-wk period, the intervention group consumed a MedDiet made entirely from organic foods, whereas the conventional group consumed a MedDiet made from conventional foods. Before and after the intervention period, both groups consumed their habitual Western diets made from conventional foods. The primary outcome was UE and/or plasma concentrations of selected mineral micronutrients, toxic metals, and phenolic markers. In addition, we monitored diets using food diaries. The participants were aware of study group assignment, but the study assessors were not. RESULTS: Changing from a Western Diet to a MedDiet for 2 wk resulted in significant increases in UE of total phenolics and salicylic acid (by 46% and 45%, respectively), the mineral micronutrients Co, I, and Mn (by 211%, 70%, and 102%, respectively), and the toxic metal Ni (by 42%), and plasma Se concentrations (by 14%). However, no significant effects of food type (organic compared with conventional) were detected. Redundancy analysis identified vegetables, coffee, wine, and fruit as positive drivers for UE of phenolic markers and mineral micronutrients, and fish consumption as a positive driver for UE of Cd and Pb. CONCLUSIONS: Although small effects of food type cannot be ruled out, our study suggests that only changing to a MedDiet with higher fruit and vegetable, and lower meat, consumption results in a large increase in phenolic and mineral micronutrient intakes. This trial was registered at clinicaltrials.gov as NCT03254537.

Generalizable Long COVID Subtypes: Findings from the NIH N3C and RECOVER Programs.

Accurate stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, the natural history of long COVID is incompletely understood and characterized by an extremely wide range of manifestations that are difficult to analyze computationally. In addition, the generalizability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. We present a method for computationally modeling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning procedures. Using k-means clustering of this similarity matrix, we found six distinct clusters of PASC patients, each with distinct profiles of phenotypic abnormalities. There was a significant association of cluster membership with a range of pre-existing conditions and with measures of severity during acute COVID-19. Two of the clusters were associated with severe manifestations and displayed increased mortality. We assigned new patients from other healthcare centers to one of the six clusters on the basis of maximum semantic similarity to the original patients. We show that the identified clusters were generalizable across different hospital systems and that the increased mortality rate was consistently observed in two of the clusters. Semantic phenotypic clustering can provide a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.

Development of a Campus-Wide Community Service Initiative during a Pandemic.

Community service serves as a major aspect of pharmacy education; however, coronavirus disease 2019 (COVID-19) represented a significant disruption to student involvement. The College of Pharmacy student council, which serves as the local student government organization for the University of Florida College of Pharmacy, Jacksonville campus, developed a community service initiative to offer more consistent opportunities for students to participate in community service events, while adapting to COVID-19 restrictions. A retrospective, qualitative review of this initiative demonstrates the potential value of this model. Prior to this initiative, students relied on individual student organizations to provide service opportunities to their members. This excluded portions of the student body and led to sparse and inconsistent events, with limited variation in the types of service events available. Furthermore, de-centralized planning of service opportunities increased the difficulty of ensuring that COVID-19 safety restrictions were followed appropriately. This initiative resulted in 39 students logging over 200 service hours through nine events in the first seven months after its development. Despite the challenges presented by the COVID-19 pandemic, our centralized initiative serves as a model for improving community service involvement.

Performance and milk quality parameters of Jersey crossbreds in low-input dairy systems.

Previous work has demonstrated some benefit from alternative breeds in low-input dairying, although there has been no systematic analysis of the simultaneous effect of Jersey crossbreeding on productivity, health, fertility parameters or milk nutritional quality. This work aimed to understand the effects of, and interactions/interrelations between, dairy cow genotypes (Holstein-Friesian (HF), Holstein-Friesian × Jersey crossbreds (HF × J)) and season (spring, summer, autumn) on milk yield; basic composition; feed efficiency, health, and fertility parameters; and milk fatty acid (FA) profiles. Milk samples (n = 219) and breed/diet data were collected from 74 cows in four UK low-input dairy farms between March and October 2012. HF × J cows produced milk with more fat (+ 3.2 g/kg milk), protein (+ 2.9 g/kg milk) and casein (+ 2.7 g/kg milk); and showed higher feed, fat, and protein efficiency (expressed as milk, fat and protein outputs per kg DMI) than HF cows. Milk from HF × J cows contained more C4:0 (+ 2.6 g/kg FA), C6:0 (+ 1.9 g/kg FA), C8:0 (+ 1.3 g/kg FA), C10:0 (+ 3.0 g/kg FA), C12:0 (+ 3.7 g/kg FA), C14:0 (+ 4.6 g/kg FA) and saturated FA (SFA; + 27.3 g/kg milk) and less monounsaturated FA (MUFA; -23.7 g/kg milk) and polyunsaturated FA (- 22.3 g/kg milk). There was no significant difference for most health and fertility parameters, but HF × J cows had shorter calving interval (by 39 days). The superior feed, fat and protein efficiency of HF × J cows, as well as shorter calving interval can be considered beneficial for the financial sustainability of low-input dairy farms; and using such alternative breeds in crossbreeding schemes may be recommended. Although statistically significant, it is difficult to determine if differences observed between HF and HF × J cows in fat composition are likely to impact human health, considering average population dairy fat intakes and the relatively small difference. Thus, the HF × J cow could be used in low-input dairying to improve efficiency and productivity without impacting milk nutritional properties.

Your ID, please? The effect of facemasks and makeup on perceptions of age of young adult female faces.

During the COVID-19 pandemic, wearing facemasks was mandatory in the United Kingdom except for individuals with medical exemptions. Facemasks cover the full lower half of the face; however, the effect of facemasks on age perception is not yet known. The present study examined whether age estimation accuracy of unfamiliar young adult women is impaired when the target is wearing a facemask. This study also examined whether makeup, which has previously been shown to increase error bias, further impairs age estimation accuracy when paired with a facemask. The findings indicate that both facemasks and makeup tend to result in overestimation of the young women's age compared to neutral faces, but the combination of both is not additive. Individual level analysis also revealed large individual differences in age estimation accuracy ranging from estimates within 1 year of the target's actual age, and age estimates which deviated by up to 20 years.