Deep mutational scanning identifies SARS-CoV-2 Nucleocapsid escape mutations of currently available rapid antigen tests.

The effects of mutations in continuously emerging variants of SARS-CoV-2 are a major concern for the performance of rapid antigen tests. To evaluate the impact of mutations on 17 antibodies used in 11 commercially available antigen tests with emergency use authorization, we measured antibody binding for all possible Nucleocapsid point mutations using a mammalian surface-display platform and deep mutational scanning. The results provide a complete map of the antibodies' epitopes and their susceptibility to mutational escape. Our data predict no vulnerabilities for detection of mutations found in variants of concern. We confirm this using the commercial tests and sequence-confirmed COVID-19 patient samples. The antibody escape mutational profiles generated here serve as a valuable resource for predicting the performance of rapid antigen tests against past, current, as well as any possible future variants of SARS-CoV-2, establishing the direct clinical and public health utility of our system.

Multisite Mpox Infection and Viral Dynamics Among Persons With HIV in Metro Atlanta.

The 2022 mpox outbreak primarily involved sexual transmission among men who have sex with men and disproportionately affected persons with human immunodeficiency virus (HIV). We examined viral dynamics and clinical features in a cohort evaluated for mpox infection at a comprehensive HIV clinic in Atlanta, Georgia. Viral DNA was found in 8 oropharyngeal and 5 anorectal specimens among 10 mpox cases confirmed by lesion swab polymerase chain reaction. Within-participant anatomic site of lowest cycle threshold (Ct) value varied, and lower Ct values were found in oropharyngeal and anorectal swabs when corresponding symptoms were present. This provides insight into mpox infection across multiple anatomic sites among people with HIV.

The New Normal: Delayed Peak SARS-CoV-2 Viral Loads Relative to Symptom Onset and Implications for COVID-19 Testing Programs.

BACKGROUND: Early in the coronavirus disease 2019 (COVID-19) pandemic, peak viral loads coincided with symptom onset. We hypothesized that in a highly immune population, symptom onset might occur earlier in infection, coinciding with lower viral loads. METHODS: We assessed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A viral loads relative to symptom duration in symptomatic adults (≥16 years) presenting for testing in Georgia (4/2022-4/2023; Omicron variant predominant). Participants provided symptom duration and recent testing history. Nasal swabs were tested by Xpert Xpress SARS-CoV-2/Flu/RSV assay and cycle threshold (Ct) values recorded. Nucleoprotein concentrations in SARS-CoV-2 polymerase chain reaction (PCR)-positive samples were measured by single molecule array. To estimate hypothetical antigen rapid diagnostic test (Ag RDT) sensitivity on each day after symptom onset, percentages of individuals with Ct value ≤30 or ≤25 were calculated. RESULTS: Of 348 newly-diagnosed SARS-CoV-2 PCR-positive individuals (65.5% women, median 39.2 years), 317/348 (91.1%) had a history of vaccination, natural infection, or both. By both Ct value and antigen concentration measurements, median viral loads rose from the day of symptom onset and peaked on the fourth/fifth day. Ag RDT sensitivity estimates were 30.0%-60.0% on the first day, 59.2%-74.8% on the third day, and 80.0%-93.3% on the fourth day of symptoms.In 74 influenza A PCR-positive individuals (55.4% women; median 35.0 years), median influenza viral loads peaked on the second day of symptoms. CONCLUSIONS: In a highly immune adult population, median SARS-CoV-2 viral loads peaked around the fourth day of symptoms. Influenza A viral loads peaked soon after symptom onset. These findings have implications for ongoing use of Ag RDTs for COVID-19 and influenza.

Total Synthesis of a PSGL-1 Glycopeptide Analogue for Targeted Inhibition of P-Selectin.

The high affinity interaction between P-selectin glycoprotein ligand-1 (PSGL-1) and P-selectin is mediated by a multimotif glycosulfopeptide (GSP) recognition domain consisting of clustered tyrosine sulfates and a Core 2 O-glycan terminated with sialyl LewisX (C2-O-sLeX). These distinct GSP motifs are much more common than previously appreciated within a wide variety of functionally important domains involved in protein-protein interactions. However, despite the potential of GSPs to serve as tools for fundamental studies and prospects for drug discovery, their utility has been limited by the absence of chemical schemes for synthesis on scale. Herein, we report the total synthesis of GSnP-6, an analogue of the N-terminal domain of PSGL-1, and potent inhibitor of P-selectin. An efficient, scalable, hydrogenolysis-free synthesis of C2-O-sLeX-Thr-COOH was identified by both convergent and orthogonal one-pot assembly, which afforded this crucial building block, ready for direct use in solid phase peptide synthesis (SPPS). C2-O-sLeX-Thr-COOH was synthesized in 10 steps with an overall yield of 23% from the 4-O,5-N oxazolidinone thiosialoside donor. This synthesis represents an 80-fold improvement in reaction yield as compared to prior reports, achieving the first gram scale synthesis of SPPS ready C2-O-sLeX-Thr-COOH and enabling the scalable synthesis of GSnP-6 for preclinical evaluation. Significantly, we established that GSnP-6 displays dose-dependent inhibition of venous thrombosis in vivo and inhibits vaso-occlusive events in a human sickle cell disease equivalent microvasculature-on-a-chip system. The insights gained in formulating this design strategy can be broadly applied to the synthesis of a wide variety of biologically important oligosaccharides and O-glycan bearing glycopeptides.

BiliQML: a supervised machine-learning model to quantify biliary forms from digitized whole slide liver histopathological images.

The progress of research focused on cholangiocytes and the biliary tree during development and following injury is hindered by limited available quantitative methodologies. Current techniques include two-dimensional standard histological cell-counting approaches, which are rapidly performed, error prone, and lack architectural context or three-dimensional analysis of the biliary tree in opacified livers, which introduce technical issues along with minimal quantitation. The present study aims to fill these quantitative gaps with a supervised machine-learning model (BiliQML) able to quantify biliary forms in the liver of anti-keratin 19 antibody-stained whole slide images. Training utilized 5,019 researcher-labeled biliary forms, which following feature selection, and algorithm optimization, generated an F score of 0.87. Application of BiliQML on seven separate cholangiopathy models [genetic (Afp-CRE;Pkd1l1null/Fl, Alb-CRE;Rbp-jkfl/fl, and Albumin-CRE;ROSANICD), surgical (bile duct ligation), toxicological (3,5-diethoxycarbonyl-1,4-dihydrocollidine), and therapeutic (Cyp2c70-/- with ileal bile acid transporter inhibition)] allowed for a means to validate the capabilities and utility of this platform. The results from BiliQML quantification revealed biological and pathological differences across these seven diverse models, indicating a highly sensitive, robust, and scalable methodology for the quantification of distinct biliary forms. BiliQML is the first comprehensive machine-learning platform for biliary form analysis, adding much-needed morphologic context to standard immunofluorescence-based histology, and provides clinical and basic science researchers with a novel tool for the characterization of cholangiopathies.NEW & NOTEWORTHY BiliQML is the first comprehensive machine-learning platform for biliary form analysis in whole slide histopathological images. This platform provides clinical and basic science researchers with a novel tool for the improved quantification and characterization of biliary tract disorders.

Redefining hyperviscosity in acute leukemia: Potential implications for red cell transfusions in the microvasculature.

Hyperleukocytosis is an emergency of acute leukemia leading to blood hyperviscosity, potentially resulting in life-threatening microvascular obstruction, or leukostasis. Due to the high number of red cells in the circulation, hematocrit/hemoglobin levels (Hct/Hgb) are major drivers of blood viscosity, but how Hct/Hgb mediates hyperviscosity in acute leukemia remains unknown. In vivo hemorheological studies are difficult to conduct and interpret due to issues related to visualizing and manipulating the microvasculature. To that end, a multi-vessel microfluidic device recapitulating the size-scale and geometry of the microvasculature was designed to investigate how Hct/Hgb interacts with acute leukemia to induce "in vitro" leukostasis. Using patient samples and cell lines, the degree of leukostasis was different among leukemia immunophenotypes with respect to white blood cell (WBC) count and Hct/Hgb. Among lymphoid immunophenotypes, severe anemia is protective against in vitro leukostasis and Hct/Hgb thresholds became apparent above which in vitro leukostasis significantly increased, to a greater extent with B-cell acute lymphoblastic leukemia (ALL) versus T-cell ALL. In vitro leukostasis in acute myeloid leukemia was primarily driven by WBC with little interaction with Hct/Hgb. This sets the stage for prospective clinical studies assessing how red cell transfusion may affect leukostasis risk in immunophenotypically different acute leukemia patients.

What's in a Name? Experimental Evidence of Gender Bias in Recommendation Letters Generated by ChatGPT.

BACKGROUND: Artificial intelligence chatbots such as ChatGPT (OpenAI) have garnered excitement about their potential for delegating writing tasks ordinarily performed by humans. Many of these tasks (eg, writing recommendation letters) have social and professional ramifications, making the potential social biases in ChatGPT's underlying language model a serious concern. OBJECTIVE: Three preregistered studies used the text analysis program Linguistic Inquiry and Word Count to investigate gender bias in recommendation letters written by ChatGPT in human-use sessions (N=1400 total letters). METHODS: We conducted analyses using 22 existing Linguistic Inquiry and Word Count dictionaries, as well as 6 newly created dictionaries based on systematic reviews of gender bias in recommendation letters, to compare recommendation letters generated for the 200 most historically popular "male" and "female" names in the United States. Study 1 used 3 different letter-writing prompts intended to accentuate professional accomplishments associated with male stereotypes, female stereotypes, or neither. Study 2 examined whether lengthening each of the 3 prompts while holding the between-prompt word count constant modified the extent of bias. Study 3 examined the variability within letters generated for the same name and prompts. We hypothesized that when prompted with gender-stereotyped professional accomplishments, ChatGPT would evidence gender-based language differences replicating those found in systematic reviews of human-written recommendation letters (eg, more affiliative, social, and communal language for female names; more agentic and skill-based language for male names). RESULTS: Significant differences in language between letters generated for female versus male names were observed across all prompts, including the prompt hypothesized to be neutral, and across nearly all language categories tested. Historically female names received significantly more social referents (5/6, 83% of prompts), communal or doubt-raising language (4/6, 67% of prompts), personal pronouns (4/6, 67% of prompts), and clout language (5/6, 83% of prompts). Contradicting the study hypotheses, some gender differences (eg, achievement language and agentic language) were significant in both the hypothesized and nonhypothesized directions, depending on the prompt. Heteroscedasticity between male and female names was observed in multiple linguistic categories, with greater variance for historically female names than for historically male names. CONCLUSIONS: ChatGPT reproduces many gender-based language biases that have been reliably identified in investigations of human-written reference letters, although these differences vary across prompts and language categories. Caution should be taken when using ChatGPT for tasks that have social consequences, such as reference letter writing. The methods developed in this study may be useful for ongoing bias testing among progressive generations of chatbots across a range of real-world scenarios. TRIAL REGISTRATION: OSF Registries osf.io/ztv96; https://osf.io/ztv96.

Hidden behind thromboinflammation: revealing the roles of von Willebrand factor in sickle cell disease pathophysiology.

PURPOSE OF REVIEW: This review provides an update on the pathophysiology of sickle cell disease (SCD) with a particular focus on the dysregulation of the von Willebrand factor (VWF) - ADAMTS13 axis that contributes to its pathogenesis. In discussing recent developments, we hope to encourage new and ongoing discussions surrounding therapeutic targets for SCD. RECENT FINDINGS: Within the last 5 years, the role of VWF in the pathophysiology of SCD has been further elucidated and is now a target of study in ongoing clinical trials. SUMMARY: The pathophysiology of SCD is multifaceted, as it involves systemwide vascular activation, altered blood rheology, and the activation of immune responses and coagulative pathways. The presence of VWF in excess in SCD, particularly in its largest multimeric form, greatly contributes to its pathogenesis. Understanding the molecular mechanisms that underly the presence of large VWF multimers in SCD will provide further insight into the pathogenesis of SCD and provide specific targets for therapy.

Probing interactions of red blood cells and contracting fibrin platelet clots.

Contraction of blood clots plays an important role in blood clotting, a natural process that restores hemostasis and regulates thrombosis in the body. Upon injury, a chain of events culminate in the formation of a soft plug of cells and fibrin fibers attaching to wound edges. Platelets become activated and apply contractile forces to shrink the overall clot size, modify clot structure, and mechanically stabilize the clot. Impaired blood clot contraction results in unhealthy volumetric, mechanical, and structural properties of blood clots associated with a range of severe medical conditions for patients with bleeding and thrombotic disorders. Due to the inherent mechanical complexity of blood clots and a confluence of multiple interdependent factors governing clot contraction, the mechanics and dynamics of clot contraction and the interactions with red blood cells (RBCs) remain elusive. Using an experimentally informed, physics-based mesoscale computational model, we probe the dynamic interactions among platelets, fibrin polymers, and RBCs, and examine the properties of contracted blood clots. Our simulations confirm that RBCs strongly affect clot contraction. We find that RBC retention and compaction in thrombi can be solely a result of mechanistic contraction of fibrin mesh due to platelet activity. Retention of RBCs hinders clot contraction and reduces clot contractility. Expulsion of RBCs located closer to clot outer surface results in the development of a dense fibrin shell in thrombus clots commonly observed in experiments. Our simulations identify the essential parameters and interactions that control blood clot contraction process, highlighting its dependence on platelet concentration and the initial clot size. Furthermore, our computational model can serve as a useful tool in clinically relevant studies of hemostasis and thrombosis disorders, and post thrombotic clot lysis, deformation, and breaking.

Navigating the complexities of mobile medical app development from idea to launch, a guide for clinicians and biomedical researchers.

With today's pace of rapid technological advancement, many patient issues in modern medicine are increasingly solvable by mobile app solutions, which also have the potential to transform how clinical research is conducted. However, many critical challenges in the app development process impede bringing these translational technologies to patients, caused in large part by the lack of knowledge among clinicians and biomedical researchers of "what it takes" to design, develop, and maintain a successful medical app. Indeed, problems requiring mobile app solutions are often nuanced, requiring more than just clinical expertise, and issues such as the cost and effort required to develop and maintain a well-designed, sustainable, and scalable mobile app are frequently underestimated. To bridge this skill set gap, we established an academic unit of designers, software engineers, and scientists that leverage human-centered design methodologies and multi-disciplinary collaboration to develop clinically viable smartphone apps. In this report, we discuss major misconceptions clinicians and biomedical researchers often hold regarding medical app development, the steps we took to establish this unit to address these issues and the best practices and lessons learned from successfully ideating, developing, and launching medical apps. Overall, this report will serve as a blueprint for clinicians and biomedical researchers looking to better benefit their patients or colleagues via medical mobile apps.

Sensitivity of rapid antigen tests against SARS-CoV-2 Omicron and Delta variants.

Rapid antigen tests (RATs) have become an invaluable tool for combating the COVID-19 pandemic. However, concerns have been raised regarding the ability of existing RATs to effectively detect emerging SARS-CoV-2 variants. We compared the performance of 10 commercially available, emergency use authorized RATs against the Delta and Omicron SARS-CoV-2 variants using both individual patient and serially diluted pooled clinical samples. The RATs exhibited lower sensitivity for Omicron samples when using PCR cycle threshold (CT) value (a rough proxy for RNA concentration) as the comparator. Interestingly, however, they exhibited similar sensitivity for Omicron and Delta samples when using quantitative antigen concentration as the comparator. We further found that the Omicron samples had lower ratios of antigen to RNA, which offers a potential explanation for the apparent lower sensitivity of RATs for that variant when using C T value as a reference. Our findings underscore the complexity in assessing RAT performance against emerging variants and highlight the need for ongoing evaluation in the face of changing population immunity and virus evolution.

Prevalence of SARS-CoV-2 in hemoglobinopathies is modified by age and race.

Prior literature has established a positive association between sickle cell disease and risk of contracting SARS-CoV-2. Data from a cross-sectional study evaluating COVID-19 testing devices (n = 10,567) was used to examine the association between underlying health conditions and SARS-CoV-2 infection in an urban metropolis in the southern United States. Firth's logistic regression was used to fit the model predicting SARS-CoV-2 positivity using vaccine status and different medical conditions commonly associated with COVID-19. Another model using the same method was built using SARS-CoV-2 positivity as the outcome and hemoglobinopathy presence, age (<16 Years vs. ≥16 Years), race/ethnicity and comorbidities, including hemoglobinopathy, as the factors. Our first model showed a significant association between hemoglobinopathy and SARS-CoV-2 infection (OR: 2.28, 95 % CI: (1.17,4.35), P = 0.016). However, in the second model, this association was not maintained (OR: 1.35, 95 % CI: (0.72,2.50), P = 0.344). We conclude that the association between SARS-CoV-2 positivity and presence of hemoglobinopathies like sickle cell disease is confounded by race, age, and comorbidity status. Our results illuminate previous findings by identifying underlying clinical/demographic factors that confound the reported association between hemoglobinopathies and SARS-CoV-2. These findings demonstrate how social determinants of health may influence disease manifestations more than genetics alone.

Bridging the Divide: Unintended Consequences of the Shift to Home-Based Telemedicine.

OBJECTIVE: To evaluate the impact on health care access of the change in telemedicine delivery from a clinic-based model, in which patients connect with their healthcare provider from local telemedicine clinics, to a home-based model, in which patients independently connect from their homes. STUDY DESIGN: In this retrospective analysis, we compared relative uptake in telemedicine services in Period 1 (01/01/2019 to 03/15/2020, prepandemic, clinic-based model) vs Period 2 (03/16/2020 to 06/30/2022, home-based model) within a tertiary pediatric hospital system. Using multivariable logistic regression, we investigated the influence of telemedicine delivery model on patient sociodemographic characteristics of completed telemedicine visits. RESULTS: We analyzed 400 539 patients with 1 406 961 completed outpatient encounters (52% White, 35% Black), of which 62 920 (4.5%) were telemedicine. In the clinic-based model (Period 1), underserved populations had greater likelihoods of accessing telemedicine: Hispanic ethnicity (OR = 1.41, P = .028) vs reference group non-Hispanic, Medicaid (OR = 2.62, P < .001) vs private insurance, and low-income neighborhood (OR = 3.40, P < .001) vs medium-income. In aggregate, telemedicine utilization rapidly increased from Period 1 (1.5 encounters/day) to Period 2 (107.9 encounters/day). However, underserved populations saw less relative increase (Medicaid [OR = 0.28, P < .001], Hispanic [OR = 0.53, P < .001], low-income [OR = 0.23, P < .001]). CONCLUSIONS: We observe that the clinic-based model offers more equitable access, while the home-based model offers more absolute access, suggesting that a hybrid model that offers both home-based and clinic-based services may result in more absolute and equitable access to telemedicine.

Are children with sickle cell disease at particular risk from the harmful effects of air pollution? Evidence from a large, urban/peri-urban cohort.

INTRODUCTION: Pathophysiologic pathways of sickle cell disease (SCD) and air pollution involve inflammation, oxidative stress, and endothelial damage. It is therefore plausible that children with SCD are especially prone to air pollution's harmful effects. METHODS: Patient data were collected from a single-center, urban/peri-urban cohort of children with confirmed SCD. Daily ambient concentrations of particulate matter (PM2.5 ) were collected via satellite-derived remote-sensing technology, and carbon monoxide (CO), nitrogen dioxide (NO2 ), and ozone from local monitoring stations. We used multivariable regression to quantify associations of pollutant levels and daily counts of emergency department (ED) visits, accounting for weather and time trends. For comparison, we quantified the associations of pollutant levels with daily all-patient (non-SCD) ED visits to our center. RESULTS: From 2010 to 2018, there were 17,731 ED visits by 1740 children with SCD (64.8% HbSS/HbSß0 ). Vaso-occlusive events (57.8%), respiratory illness (17.1%), and fever (16.1%) were the most common visit diagnoses. Higher 3-day (lags 0-2) rolling mean PM2.5 and CO levels were associated with daily ED visits among those with SCD (PM2.5 incident rate ratio [IRR] 1.051 [95% confidence interval: 1.010-1.094] per 9.4 µg/m3 increase; CO 1.088 [1.045-1.132] per 0.5 ppm). NO2 showed positive associations in secondary analyses; ozone levels were not associated with ED visits. The comparison, all-patient ED visit analyses showed lower IRR for all pollutants. CONCLUSIONS: Our results suggest short-term air pollution levels as triggers for SCD events and that children with SCD may be more vulnerable to air pollution than those without SCD. Targeted pollution-avoidance strategies could have significant clinical benefits in this population.

A novel mobile health application to support cancer surveillance needs of patients and families with cancer predisposition syndromes.

BACKGROUND: At least 5%-10% of malignancies occur secondary to an underlying cancer predisposition syndrome (CPS). For these families, cancer surveillance is recommended with the goal of identifying malignancy earlier, in a presumably more curable form. Surveillance protocols, including imaging studies, bloodwork, and procedures, can be complex and differ based on age, gender, and syndrome, which adversely affect adherence. Mobile health (mHealth) applications (apps) have been utilized in oncology and could help to facilitate adherence to cancer surveillance protocols. METHODS: Applying a user-centered mobile app design approach, patients with a CPS and/or primary caregivers were interviewed to identify current methods for care management and barriers to compliance with recommended surveillance protocols. Broad themes from these interviews informed the design of the mobile app, HomeTown, which was subsequently evaluated by usability experts. The design was then converted into software code in phases, evaluated by patients and caregivers in an iterative fashion. User population growth and app usage data were assessed. RESULTS: Common themes identified included general distress surrounding surveillance protocol scheduling and results, difficulty remembering medical history, assembling a care team, and seeking resources for self-education. These themes were translated into specific functional app features, including push reminders, syndrome-specific surveillance recommendations, ability to annotate visits and results, storage of medical histories, and links to reliable educational resources. CONCLUSIONS: Families with CPS demonstrate a desire for mHealth tools to facilitate adherence to cancer surveillance protocols, reduce related distress, relay medical information, and provide educational resources. HomeTown may be a useful tool for engaging this patient population.

Hemostasis-on-a-chip / incorporating the endothelium in microfluidic models of bleeding.

Currently, point-of-care assays for human platelet function and coagulation are used to assess bleeding risks and drug testing, but they lack intact endothelium, a critical component of the human vascular system. Within these assays, the assessment of bleeding risk is typically indicated by the lack of or reduced platelet function and coagulation without true evaluation of hemostasis. Hemostasis is defined as the cessation of bleeding. Additionally, animal models of hemostasis also, by definition, lack human endothelium, which may limit their clinical relevance. This review discusses the current state-of-the-art of hemostasis-on-a-chip, specifically, human cell-based microfluidic models that incorporate endothelial cells, which function as physiologically relevant in vitro models of bleeding. These assays recapitulate the entire process of vascular injury, bleeding, and hemostasis, and provide real-time, direct observation, thereby serving as research-enabling tools that enhance our understanding of hemostasis and also as novel drug discovery platforms.

The human body's response to stop bleeding after a vascular injury involves a complex but finely tuned cascade of interactions between the blood, the blood vessel wall, and the physical flow of the blood. Accordingly, in vitro models that incorporate those aspects that occur in vivo are highly needed for research and clinical purposes. Here, we review the state of the art of these technologies, hemostasis-on-a-chip devices that aim to achieve those goals. These physiologically relevant "microchips" mimic the bleeding process as well as the cessation thereof, and can be leveraged as research-enabling tools, platforms for drug discovery, and clinical testing.

Label-free hematology analysis using deep-ultraviolet microscopy.

Hematological analysis, via a complete blood count (CBC) and microscopy, is critical for screening, diagnosing, and monitoring blood conditions and diseases but requires complex equipment, multiple chemical reagents, laborious system calibration and procedures, and highly trained personnel for operation. Here we introduce a hematological assay based on label-free molecular imaging with deep-ultraviolet microscopy that can provide fast quantitative information of key hematological parameters to facilitate and improve hematological analysis. We demonstrate that this label-free approach yields 1) a quantitative five-part white blood cell differential, 2) quantitative red blood cell and hemoglobin characterization, 3) clear identification of platelets, and 4) detailed subcellular morphology. Analysis of tens of thousands of live cells is achieved in minutes without any sample preparation. Finally, we introduce a pseudocolorization scheme that accurately recapitulates the appearance of cells under conventional staining protocols for microscopic analysis of blood smears and bone marrow aspirates. Diagnostic efficacy is evaluated by a panel of hematologists performing a blind analysis of blood smears from healthy donors and thrombocytopenic and sickle cell disease patients. This work has significant implications toward simplifying and improving CBC and blood smear analysis, which is currently performed manually via bright-field microscopy, and toward the development of a low-cost, easy-to-use, and fast hematological analyzer as a point-of-care device and for low-resource settings.

Nucleocapsid Antigenemia Is a Marker of Acute SARS-CoV-2 Infection.

Detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is essential for diagnosis, treatment, and infection control. Polymerase chain reaction (PCR) fails to distinguish acute from resolved infections, as RNA is frequently detected after infectiousness. We hypothesized that nucleocapsid in blood marks acute infection with the potential to enhance isolation and treatment strategies. In a retrospective serosurvey of inpatient and outpatient encounters, we categorized samples along an infection timeline using timing of SARS-CoV-2 testing and symptomatology. Among 1860 specimens from 1607 patients, the highest levels and frequency of antigenemia were observed in samples from acute SARS-CoV-2 infection. Antigenemia was higher in seronegative individuals and in those with severe disease. In our analysis, antigenemia exhibited 85.8% sensitivity and 98.6% specificity as a biomarker for acute coronavirus disease 2019 (COVID-19). Thus, antigenemia sensitively and specifically marks acute SARS-CoV-2 infection. Further study is warranted to determine whether antigenemia may aid individualized assessment of active COVID-19.

Hyperviscosity syndromes; hemorheology for physicians and the use of microfluidic devices.

PURPOSE OF REVIEW: Hyperviscosity syndromes can lead to significant morbidity and mortality. Existing methods to measure microcirculatory rheology are not readily available and limited in relevance and accuracy at this level. In this review, we review selected hyperviscosity syndromes and the advancement of their knowledge using microfluidic platforms. RECENT FINDINGS: Viscosity changes drastically at the microvascular level as the physical properties of the cells themselves become the major determinants of resistance to blood flow. Current, outdated viscosity measurements only quantify whole blood or serum. Changes in blood composition, cell number, or the physical properties themselves lead to increased blood viscosity. Given the significant morbidity and mortality from hyperviscosity syndromes, new biophysical tools are needed and being developed to study microvascular biophysical and hemodynamic conditions at this microvascular level to help predict those at risk and guide therapeutic treatment. SUMMARY: The use of 'lab-on-a-chip' technology continues to rise to relevance with point of care, personalized testing and medicine as customizable microfluidic platforms enable independent control of many in vivo factors and are a powerful tool to study microcirculatory hemorheology.

Predictive Value of Isolated Symptoms for Diagnosis of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children Tested During Peak Circulation of the Delta Variant.

BACKGROUND: Coronavirus disease 2019 (COVID-19) testing policies for symptomatic children attending US schools or daycare vary, and whether isolated symptoms should prompt testing is unclear. We evaluated children presenting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing to determine if the likelihood of having a positive SARS-CoV-2 test differed between participants with 1 symptom vs ≥2 symptoms, and to examine the predictive capability of isolated symptoms. METHODS: Participants aged <18 years presenting for clinical SARS-CoV-2 molecular testing in 6 sites in urban/suburban/rural Georgia (July-October, 2021; Delta variant predominant) were queried about individual symptoms. Participants were classified into 3 groups: asymptomatic, 1 symptom only, or ≥2 symptoms. SARS-CoV-2 test results and clinical characteristics of the 3 groups were compared. Sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs) for isolated symptoms were calculated by fitting a saturated Poisson model. RESULTS: Of 602 participants, 21.8% tested positive and 48.7% had a known or suspected close contact. Children reporting 1 symptom (n = 82; odds ratio [OR], 6.00 [95% confidence interval {CI}, 2.70-13.33]) and children reporting ≥2 symptoms (n = 365; OR, 5.25 [95% CI, 2.66-10.38]) were significantly more likely to have a positive COVID-19 test than asymptomatic children (n = 155), but they were not significantly different from each other (OR, 0.88 [95% CI, .52-1.49]). Sensitivity and PPV were highest for isolated fever (33% and 57%, respectively), cough (25% and 32%), and sore throat (21% and 45%); headache had low sensitivity (8%) but higher PPV (33%). Sensitivity and PPV of isolated congestion/rhinorrhea were 8% and 9%, respectively. CONCLUSIONS: With high Delta variant prevalence, children with isolated symptoms were as likely as those with multiple symptoms to test positive for COVID-19. Isolated fever, cough, sore throat, or headache, but not congestion/rhinorrhea, offered the highest predictive value.