A deep learning framework for predicting the neutralizing activity of COVID-19 therapeutics and vaccines against evolving SARS-CoV-2 variants (preprint)

Understanding how viral variants evade neutralization is crucial for improving antibody-based treatments, especially with rapidly evolving viruses like SARS-CoV-2. Yet, conventional assays are limited in the face of rapid viral evolution, relying on a narrow set of viral isolates, and falling short in capturing the full spectrum of variants. To address this, we have developed a deep learning approach to predict changes in neutralizing antibody activity of COVID-19 therapeutics and vaccines against emerging viral variants. First, we trained a variational autoencoder (VAE) using all 67,885 unique SARS-CoV-2 spike protein sequences from the NCBI virus (up to October 31, 2022) database to encode spike protein variants into a latent space. Using this VAE and a curated dataset of 7,069 in vitro assay data points from the NCATS OpenData Portal, we trained a neural network regression model to predict fold changes in neutralizing activity of 40 COVID-19 therapeutics and vaccines against spike protein sequence variants, relative to their neutralizing activity against the ancestral strain (Wuhan-Hu-1). Our model also employs Bayesian inference to quantify prediction uncertainty, providing more nuanced and informative estimates. To validate the model\'s predictive capacity, we assessed its performance on a test set of in vitro assay data collected up to eight months after the data included in the model training (N = 980). The model accurately predicted fold changes in neutralizing activity for this prospective dataset, with an R2 of 0.77. Expanding our methodology to include all available data from NCBI virus and NCATS OpenData Portal up to date, we assessed predicted changes in activity for current COVID-19 monoclonal antibodies and vaccines against newly identified SARS-CoV-2 lineages. Our predictions suggest that current therapeutic and vaccine-induced antibodies will have significantly reduced activity against newer XBB descendants, notably EG.5, FL.1.5.1, and XBB.1.16. Using the model, we were able to primarily attribute the observed predicted loss in activity to the F456L spike mutation found in EG.5 and FL.1.5.1 sequences. Conversely, mRNA-bivalent vaccines are predicted to be less susceptible to the recent BA.2.86 variant compared to new XBB descendants. These findings align closely with recent research, underscoring the potential of deep learning in shaping therapeutic and vaccine strategies for emerging viral variants.

Dynamics of SARS-CoV-2 Seroprevalence in a Large US population Over a Period of 12 Months (preprint)

Due to a combination of asymptomatic or undiagnosed infections, the proportion of the United States population infected with SARS-CoV-2 was unclear from the beginning of the pandemic. We previously established a platform to screen for SARS-CoV-2 positivity across a representative proportion of the US population, from which we reported that almost 17 million Americans were estimated to have had undocumented infections in the Spring of 2020. Since then, vaccine rollout and prevalence of different SARS-CoV-2 variants have further altered seropositivity trends within the United States population. To explore the longitudinal impacts of the pandemic and vaccine responses on seropositivity, we re-enrolled participants from our baseline study in a 6- and 12- month follow-up study to develop a longitudinal antibody profile capable of representing seropositivity within the United States during a critical period just prior to and during the initiation of vaccine rollout. Initial measurements showed that, since July 2020, seropositivity elevated within this population from 4.8% at baseline to 36.2% and 89.3% at 6 and 12 months, respectively. We also evaluated nucleocapsid seropositivity and compared to spike seropositivity to identify trends in infection versus vaccination relative to baseline. These data serve as a window into a critical timeframe within the COVID-19 pandemic response and serve as a resource that could be used in subsequent respiratory illness outbreaks.

Evaluation of a remote monitoring app in head and neck cancer follow-up care.

BACKGROUND: A remote monitoring app was developed for head and neck cancer (HNC) follow-up during the SARS-CoV-2 pandemic. This mixed-methods study provides insight in the usability and patients' experiences with the app to develop recommendations for future use. METHODS: Patients were invited to participate if they were treated for HNC, used the app at least once and were in clinical follow-up. A subset was selected for semi-structured interviews through purposive sampling considering gender and age. This study was conducted between September 2021-May 2022 at a Dutch university medical center. RESULTS: 135 of the 216 invited patients completed the questionnaire, resulting in a total mHealth usability score of 4.72 (± 1.13) out of 7. Thirteen semi-structured interviews revealed 12 barriers and 11 facilitators. Most of them occurred at the level of the app itself. For example, patients received no feedback when all their answers were normal. The app made patients feel more responsible over their follow-up, but could not fulfill the need for personal contact with the attending physician. Patients felt that the app could replace some of the outpatient follow-up visits. CONCLUSIONS: Our app is user-friendly, makes patients feel more in control and remote monitoring can reduce the frequency of outpatient follow-up visits. The barriers that emerged must be resolved before the app can be used in regular HNC follow-up. Future studies should investigate the appropriate ratio of remote monitoring to outpatient follow-up visits and the cost-effectiveness of remote monitoring in oncology care on a larger scale.

Preferred Information Source Correlates to COVID-19 Risk Misperception.

Inaccurate perceptions of COVID-19 (coronavirus disease 2019) risk may decrease compliance with public health mitigation practices, in turn increasing disease burden. The extent to which public perceptions of COVID-19 risk are inaccurate is not well studied. This study investigates the relationship between preferred information sources and inaccurate COVID-19 risk perception. A cross-sectional online survey of adults in the United States using online snowball techniques was administered between April 9, 2020 and July 12, 2020. Raking techniques were used to generate a representative U.S. sample from 10,650 respondents. Respondents who did not provide an answer to key questions were excluded. The remaining sample included 1,785 health care workers (HCW) and 4,843 non-HCW. Subjective risk was measured as the product of perceived likelihood of COVID-19 infection and perceived harm from infection. Objective risk was measured as a function of the presence of known COVID-19 risk factors. Discrepancies between subjective and objective risk were compared between respondents with different preferred information sources. Chi Square contingency tables and pair-wise correlation were used to evaluate differences to 95% confidence. For HCW and non-HCW, the greatest overestimation of personal COVID-19 risk assessment (p < .05 for all differences) were found in those whose preferred source of information was social media (HCW: 62.1%; non-HCW: 64.5%), followed by internet news sources (HCW: 59.6%, non-HCW%: 59.1%), government websites (HCW: 54%, non-HCW = 51.8%), other sources (HCW: 50.7%, non-HCW = 51.4%), and television news (HCW: 46.1%, non-HCW: 47.6%). Preferred information sources correlate with inaccuracies in personal COVID-19 risk assessment. Public health information campaigns should consider targeting groups whose preferred information sources correlate to higher inaccuracies in COVID-19 risk perceptions. [HLRP: Health Literacy Research and Practice. 2023;7(2):e105-e110.].

Protective immunity induced by an inhaled SARS-CoV-2 subunit vaccine.

Targeting the site of infection is a promising strategy for improving vaccine effectivity. To date, licensed COVID-19 vaccines have been administered intramuscularly despite the fact that SARS-CoV-2 is a respiratory virus. Here, we aim to induce local protective mucosal immune responses with an inhaled subunit vaccine candidate, ISR52, based on the SARS-CoV-2 Spike S1 protein. When tested in a lethal challenge hACE2 transgenic SARS-CoV-2 mouse model, intranasal and intratracheal administration of ISR52 provided superior protection against severe infection, compared to the subcutaneous injection of the vaccine. Interestingly for a protein-based vaccine, inhaled ISR52 elicited both CD4 and CD8 T-cell Spike-specific responses that were maintained for at least 6 months in wild-type mice. Induced IgG and IgA responses cross-reacting with several SARS- CoV-2 variants of concern were detected in the lung and in serum and protected animals displayed neutralizing antibodies. Based on our results, we are developing ISR52 as a dry powder formulation for inhalation, that does not require cold-chain distribution or the use of needle administration, for evaluation in a Phase I/II clinical trial.

Latent class analysis of health, social, and behavioral profiles associated with psychological distress among pregnant and postpartum women during the COVID-19 pandemic in the United States.

BACKGROUND: There is a growing body of literature documenting negative mental health impacts from the COVID-19 pandemic. The purpose of this study was to identify risk and protective factors associated with mental health and well-being among pregnant and postpartum women during the pandemic. METHODS: This was a cross-sectional, anonymous online survey study distributed to pregnant and postpartum (within 6 months) women identified through electronic health records from two large healthcare systems in the Northeastern and Midwestern United States. Survey questions explored perinatal and postpartum experiences related to the pandemic, including social support, coping, and health care needs and access. Latent class analysis was performed to identify classes among 13 distinct health, social, and behavioral variables. Outcomes of depression, anxiety, and stress were examined using propensity-weighted regression modeling. RESULTS: Fit indices demonstrated a three-class solution as the best fitting model. Respondents (N = 616) from both regions comprised three classes, which significantly differed on sleep- and exercise-related health, social behaviors, and mental health: Higher Psychological Distress (31.8%), Moderate Psychological Distress (49.8%), and Lower Psychological Distress (18.4%). The largest discriminatory issue was support from one's social network. Significant differences in depression, anxiety, and stress severity scores were observed across these three classes. Reported need for mental health services was greater than reported access. CONCLUSIONS: Mental health outcomes were largely predicted by the lack or presence of social support, which can inform public health decisions and measures to buffer the psychological impact of ongoing waves of the COVID-19 pandemic on pregnant and postpartum women. Targeted early intervention among those in higher distress categories may help improve maternal and child health.

Results From a Phase 4, Multicenter, Randomized, Double-Blind, Placebo-Controlled Study of Repository Corticotropin Injection for the Treatment of Pulmonary Sarcoidosis.

INTRODUCTION: Long-term treatment of pulmonary sarcoidosis with glucocorticoids has been associated with toxicity and other adverse events, highlighting the need for alternative therapies. The goal of this study was to evaluate the efficacy and safety of repository corticotropin injection (RCI, Acthar® Gel) in patients with pulmonary sarcoidosis and to validate endpoints for use in future clinical trials. METHODS: In this multicenter, randomized, placebo-controlled trial, subjects received subcutaneous RCI (80 U) twice weekly or matching placebo through 24 weeks in a double-blind treatment phase, followed by an optional 24-week open-label extension. Efficacy was measured by glucocorticoid tapering, pulmonary function tests, chest imaging, patient-reported outcomes, and a novel sarcoidosis treatment score (STS). Safety was assessed by adverse events, physical examinations, vital signs, clinical laboratory abnormalities, and imaging. The study was terminated early due to low enrollment caused by the COVID-19 pandemic, thereby precluding statistical analysis. RESULTS: Fifty-five subjects were randomized to receive either RCI (n = 27) or placebo (n = 28). Mean STS at week 24 showed greater improvement with RCI (1.4) compared with placebo (0.7). At week 48, those who remained on RCI had an STS of 1.8 compared with 0.9 in those who switched from placebo to RCI. More subjects in the RCI group discontinued glucocorticoids at week 24 compared to the placebo group. Glucocorticoid discontinuation was comparable at week 48 for those who switched from placebo to RCI and those who continued RCI. Similar trends in favor of RCI over placebo were observed with the other efficacy endpoints. No new or unexpected safety signals were identified. CONCLUSIONS: RCI was safe and well tolerated, with trends in efficacy data suggesting greater improvement with RCI compared to placebo in patients receiving standard-of-care therapy for pulmonary sarcoidosis. The study also provided validation of efficacy endpoints that may be used in larger trials for pulmonary sarcoidosis. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03320070.

Pulmonary sarcoidosis is a disease characterized by inflammation of the lungs. Standard treatments include glucocorticoids, which may have harmful side effects. This clinical trial investigated whether repository corticotropin injection (RCI, Acthar^® Gel) was safe and effective in patients who were already taking glucocorticoids to treat pulmonary sarcoidosis. Patients were randomly assigned to be in one of two treatment groups: RCI or placebo. In the first 24 weeks of the study, 27 patients were injected with RCI twice weekly, while 28 patients were injected with an inactive substance (placebo). Forty-seven patients continued into an optional phase of the study for an additional 24 weeks in which all patients received RCI twice weekly. A sarcoidosis treatment score and assessments of lung health, general health, and fatigue were used to determine whether RCI was effective. These assessments showed greater improvements with RCI compared to placebo. Patients who switched from placebo to RCI showed similar improvements to those who remained on RCI throughout the entire study. Patients receiving RCI were able to discontinue their use of glucocorticoids more quickly than those taking placebo, thus helping them to avoid the harmful side effects of the glucocorticoids. Side effects for RCI were mostly mild or moderate, and no new or unexpected safety concerns for RCI were seen throughout the study.

SARS-CoV-2 Spike N-Terminal Domain Engages 9-O-Acetylated α2-8-Linked Sialic Acids.

SARS-CoV-2 viruses engage ACE2 as a functional receptor with their spike protein. The S1 domain of the spike protein contains a C-terminal receptor binding domain (RBD) and an N-terminal domain (NTD). The NTD of other coronaviruses includes a glycan binding cleft. However, for the SARS-CoV-2 NTD, protein-glycan binding was only observed weakly for sialic acids with highly sensitive methods. Amino acid changes in the NTD of variants of concern (VoC) show antigenic pressure, which can be an indication of NTD-mediated receptor binding. Trimeric NTD proteins of SARS-CoV-2, alpha, beta, delta, and omicron did not reveal a receptor binding capability. Unexpectedly, the SARS-CoV-2 beta subvariant strain (501Y.V2-1) NTD binding to Vero E6 cells was sensitive to sialidase pretreatment. Glycan microarray analyses identified a putative 9-O-acetylated sialic acid as a ligand, which was confirmed by catch-and-release ESI-MS, STD-NMR analyses, and a graphene-based electrochemical sensor. The beta (501Y.V2-1) variant attained an enhanced glycan binding modality in the NTD with specificity toward 9-O-acetylated structures, suggesting a dual-receptor functionality of the SARS-CoV-2 S1 domain, which was quickly selected against. These results indicate that SARS-CoV-2 can probe additional evolutionary space, allowing binding to glycan receptors on the surface of target cells.

Well-Defined Heparin Mimetics Can Inhibit Binding of the Trimeric Spike of SARS-CoV-2 in a Length-Dependent Manner.

The emergence of new SARS-CoV-2 variants and the dangers of long-covid necessitate the development of broad-acting therapeutics that can reduce viral burden. SARS-CoV-2 employs heparan sulfate (HS) as an initial cellular attachment factor, and therefore, there is interest in developing heparin as a therapeutic for SARS-CoV-2. Its use is, however, complicated by structural heterogeneity and the risk of causing bleeding and thrombocytopenia. Here, we describe the preparation of well-defined heparin mimetics by a controlled head-to-tail assembly of HS oligosaccharides having an alkyne or azide moiety by copper-catalyzed azide-alkyne cycloaddition (CuAAC). Alkyne- and azide-containing sulfated oligosaccharides were prepared from a common precursor by modifying an anomeric linker with 4-pentynoic acid and by enzymatic extension with an N-acetyl-glucosamine having an azide moiety at C-6 (GlcNAc6N3), respectively, followed by CuAAC. The process of enzymatic extension with GlcNAc6N3 followed by CuAAC with the desired alkyne-containing oligosaccharides could be repeated to give compounds composed of 20 and 27 monosaccharides, respectively. The heparin mimetics could inhibit the binding of the SARS-CoV-2 spike or RBD to immobilized heparin or to Vero E6 cells. The inhibitory potency increased with increasing chain length, and a compound composed of four sulfated hexasaccharides linked by triazoles had a similar potency as unfractionated heparin. Sequence analysis and HS microarray binding studies with a wide range of RBDs of variants of concern indicate that they have maintained HS-binding capabilities and selectivities. The heparin mimetics exhibit no or reduced binding to antithrombin-III and platelet factor 4, respectively, which are associated with side effects.

Nirmatrelvir-ritonivir, COVID-19, and possible adverse cutaneous reactions.

Nirmatrelvir-ritonivir (Paxlovid) recently received emergency use authorization for the treatment of coronavirus disease 2019 (COVID-19). Literature has linked numerous cutaneous adverse effects to nirmatrelvir and ritonavir, the copackaged tablets within Paxlovid. A review and comparison of these adverse effects to the common cutaneous manifestations of COVID-19 is provided. Numerous drug-to-drug interactions exist between nirmatrelvir-ritonivir and commonly-used medications within dermatology.

Virtual Recruitment Effects on Matched Residents in Family Medicine: Experiences From Central Pennsylvania.

Background and Objectives: As a result of the COVID-19 pandemic, interviews during the 2021 US residency match were conducted virtually, a practice again recommended and repeated by many programs in 2022. The impact of virtual interviews on recruitment and match outcomes has recently been of interest, with results showing the virtual format to be mostly well received by applicants due to cost, travel, and scheduling benefits. Few studies have looked at pre/posttransition comparisons of applicant geographic and demographic data. We compared objective match outcomes between in-person and virtual interviews across three residency programs. Methods: We conducted a retrospective cross-sectional analysis of National Residency Matching Program data between 2015-2022 across three family medicine residency programs. Primary outcomes were fill rate, average rank position, distance from program, and percentage of underrepresented in medicine demographic status for matched applicants. We compared aggregate in-person data (2015-2019) to aggregate virtual data (2020-2022) for each program using χ2, Fisher Exact test, or 2-tailed t tests to 95% confidence. Results: Saint Joseph Hospital in Reading, Pennsylvania, a 3-year community-based university affiliated program, had significantly more unfilled positions during virtual recruitment (P=.0058). Mount Nittany Medical Center in State College, Pennsylvania, a 3-year community based university-affiliated program, had a significant difference in distance of matched residents' current address (P=.048). Virtual interviews were not associated with significant differences in average position on rank list, average distance from permanent address zip code, or percentage of underrepresented in medicine (URiM) demographic status for matched applicants. Conclusions: The impact of virtual interviewing on unfilled positions and geographic data is likely site specific and generally small, as some programs had significant structural changes. Further research is needed to confirm the generalizability of these results and explore future comparisons of demographic and geographic characteristics of matched applicants pre/posttransition to the virtual format.

Chest Compressions and Defibrillation as Aerosolgenerating Procedures

SARS-CoV-2 is a highly contagious respiratory pathogen associated with significant mortality in certain patient populations. Patients may be asymptomatic, which causes problems regarding infection control and prevention. Health professionals are required to adhere to strict protocols regarding infection control and personal protective equipment (PPE), particularly when engaging in resuscitation activities thought to be aerosol-generating procedures (AGPs). While adherence to enhanced PPE protocols can delay life-saving interventions, non-adherence may put responders at risk. The aim of this scoping literature review was to establish if chest compressions and defibrillation should be classified as AGPs. Following application of systematic literature search criteria, a limited selection of studies was identified in relation to chest compressions and defibrillation as AGPs. An assumption that endotracheal intubation posed a high risk of nosocomial transmission was noted. Emerging evidence suggests that endotracheal intubation produces fewer aerosol particles than coughing so could be classed as a low-risk-procedure. Because of the lack of adequate prospective studies investigating chest compressions and defibrillation as AGPs, there is a clear need to perform further, well-controlled studies to better understand the aerosol-generating potential of chest compressions and defibrillation.

Predicting students' intention to continue online learning post-COVID-19 pandemic: extension of the unified theory of acceptance and usage technology

PurposeThe purpose of this study is to predict the intention to continue online learning post the coronavirus disease 2019 (COVID-19) pandemic among students in the two largest universities of higher learning in Botswana. Furthermore, the purposes of this study are to elucidate the nexus between performance expectancy and continuance intention to establish the effects of efforts expectancy on continuance intention to investigate the relationship between social influence and continuance intention to determine the relationship between facilitating conditions and continuance intention and to examine the relationship between satisfaction and continuance intention using the extended unified theory of acceptance and usage technology (UTAUT) model postulated by Venkatesh et al. (2003).Design/methodology/approachThe study is based on the descriptive research design, using a structured questionnaire to collect quantitative data from 509 undergraduate and postgraduate students at Botswana's two major Universities using convenience sampling strategy. An online survey was used to gather primary data due to the COVID-19 pandemic. The study employed correlation and regression analysis in testing the five hypothesized relationships.FindingsUsing the extended theory of UTAUT as a theoretical lens, the study found that: performance expectancy, social influence and satisfaction predict continuance intention of online learning services. These factors have shown to be good predictors of intention in previous research. Expectancy effort had no influence on intention.Research limitations/implicationsThe current study covered on only university students from two tertiary institutions;therefore, results cannot safely be generalized to the student population in the country. Therefore, future research should consider enlisting more universities to be more representative, focusing on lecturers, which is an important group in fostering online teaching that could have a spill-over effect on the students' continued online learning.Practical implicationsImplications for online technology selection: These findings suggest that although most universities temporarily adopted online teaching as an emergency solution, students appear to have felt that the outcomes delivered by the system improved their performance. This implies that academic institutions need to consider adjusting the curriculum to promote online learning in the future, whether there is pandemic or no pandemic. Implications for teaching and learning: First, the concept of social influence suggests that lecturers can make use of online chat discussion boards and rooms to foster student collaboration and a sense of community. Second, and finally online service providers should foster a close relationship with students to understand their expectations and extend the performance of their applications to satisfy their users.Originality/valueThis study contributes to literature on online learning during the COVID-19 pandemic period by including satisfaction and continuance intention to the original UTAUT model thus extending the practical value of the model. This study extends knowledge on the factors that determine continuance intention by incorporating satisfaction in addition to the four factors of the traditional UTAUT. The study provides evidence for the predominance of satisfaction over the four traditional factors in predicting intention to continue online learning among students.

Pathology Education Powered by Virtual and Digital Transformation: Now and the Future

[...]standing on the crest of yet another wave of change, driven by artificial intelligence (AI) and machine learning,2 pathology educators may soon be challenged to convey the best ways to apply these tools to the problems of diagnostic pathology for the coming generation of learners and the present corps of practitioners.3 Hence, this collaborative effort aims to describe the genetic code governing the transmission of pathology knowledge to subsequent generations of medical professionals.4 We aim to expose not just the code but also the supporting array of catalysts, enhancers, and other cofactors now in place to ensure we have a robust and potent supply of pathologists. APPLYING DP IN UNDERGRADUATE MEDICAL, DENTAL, VETERINARY, AND ALLIED HEALTH EDUCATION Beginning in 1985, this technology has been progressively more widely implemented in undergraduate medical, dental, veterinary, and allied health (nursing, pharmacy, medical technology, etc) education platforms in the United States and internationally.5,11-26 As noted above, virtual microscopy laboratories, available on personal devices or in school-based computer labs, have replaced fixed laboratories housing gross specimens, boxes of glass slides, and student microscopes. WSI with links to supplementary resources, such as gross and radiologic images and additional study material, provide enrichment for the teaching and learning experience in the new virtual environment. [...]significant exposure to microanatomy and the laboratory methods of pathology underpinning so much of diagnosis, therapy, and management is foundational.

Longitudinal study of an emerging COVID-19 stigma: Media exposure, danger appraisal, and stress

Media coverage of coronavirus disease (COVID-19) has played a critical role throughout the pandemic: sharing news about the novel virus, policies and practices to mitigate it, and the race to create and distribute vaccines. The media coverage, however, has been critiqued as stigmatizing. Although this critique is not new, there is limited understanding of how and why new stigmas emerge from exposure to media coverage. Drawing upon the model of stigma communication (Smith et al., 2019) and the attribution model of stigma (Corrigan et al., 2003), we investigated a novel model of stigma emergence that delineates two kinds of longitudinal processes: (a) a message-effects process, in which exposure to mediated messages about COVID-19 leads to public stigma through danger appraisal and (b) a coping process in which stress and rumination shape later perceptions of public stigma. To test the model, we tracked an emerging COVID-19 stigma with a two-wave survey of a prospective, longitudinal cohort living in one county in a mid-Atlantic state (N = 883). The results supported this model. The longitudinal processes of stigma emergence and implications for COVID-19 stigma are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Rapid Real-time Squiggle Classification for Read until using RawMap

ReadUntil enables Oxford Nanopore Technology's (ONT) sequencers to selectively sequence reads of target species in real-time. This enables efficient microbial enrichment for applications such as microbial abundance estimation and is particularly beneficial for metagenomic samples with a very high fraction of non-target reads (> 99% can be human reads). However, read-until requires a fast and accurate software filter that analyzes a short prefix of a read and determines if it belongs to a microbe of interest (target) or not. The baseline Read Until pipeline uses a deep neural network-based basecaller called Guppy and is slow and inaccurate for this task (~60% of bases sequenced are unclassified). We present RawMap, an efficient CPU-only microbial species-agnostic Read Until classifier for filtering non-target human reads in the squiggle space. RawMap uses a Support Vector Machine (SVM), which is trained to distinguish human from microbe using non-linear and non-stationary characteristics of ONT's squiggle output (continuous electrical signals). Compared to the baseline Read Until pipeline, RawMap is a 1327X faster classifier and significantly improves the sequencing time and cost, and compute time savings. We show that RawMap augmented pipelines reduce sequencing time and cost by ~24% and computing cost by 22%. Additionally, since RawMap is agnostic to microbial species, it can also classify microbial species it is not trained on. We also discuss how RawMap may be used as an alternative to the RT-PCR test for viral load quantification of SARS-CoV-2.

Facile electrochemical affinity measurements of small and large molecules.

A novel miniaturized sensor for electrochemical detection that contains graphene- and gold nanoparticles was functionalized with proteins. Using cyclic voltammetry (CV) and differential pulse voltammetry (DPV) it was possible to observe and quantify interactions of molecules with these proteins. The protein binders included carbohydrate ligands as small as carbohydrates up to COVID-19 spike protein variants engaged in protein-protein interactions. The system uses off-the-shelf sensors combined with an affordable potentiostat and yet is sensitive enough for small ligand binding.

Covid-19 vaccine acceptance among individuals incarcerated in Connecticut state jails.

BACKGROUND: Vaccine hesitancy is common among incarcerated populations and, despite vaccination programs, vaccine acceptance within residents remains low, especially within jails. With the goal of assessing the Connecticut DOC's COVID-19 vaccine program within jails we examined if residents of DOC operated jails were more likely to become vaccinated following incarceration than in the community. Specifically, we conducted a retrospective cohort analysis among people who spent at least one night in a DOC-operated jail between February 2 and November 8, 2021, and were eligible for vaccination at the time of incarceration (intake). We compared the vaccination rates before and after incarceration using an age-adjusted survival analysis with a time-varying exposure of incarceration and an outcome of vaccination. RESULTS: During the study period, 3,716 people spent at least one night in jail and were eligible for vaccination at intake. Of these residents, 136 were vaccinated prior to incarceration, 2,265 had a recorded vaccine offer, and 479 were vaccinated while incarcerated. The age-adjusted hazard of vaccination following incarceration was significantly higher than prior to incarceration (12.5; 95% Confidence Intervals: 10.2-15.3). CONCLUSIONS: We found that residents were more likely to become vaccinated in jail than in the community. Though these findings highlight the utility of vaccination programs within jails, the low level of vaccination in this population speaks to the need for additional program development within jails and the community.