Presymptomatic Individuals Research Articles

Prediction of viral symptoms using wearable technology and artificial intelligence: A pilot study in healthcare workers.

Conventional testing and diagnostic methods for infections like SARS-CoV-2 have limitations for population health management and public policy. We hypothesize that daily changes in autonomic activity, measured through off-the-shelf technologies together with app-based cognitive assessments, may be used to forecast the onset of symptoms consistent with a viral illness. We describe our strategy using an AI model that can predict, with 82% accuracy (negative predictive value 97%, specificity 83%, sensitivity 79%, precision 34%), the likelihood of developing symptoms consistent with a viral infection three days before symptom onset. The model correctly predicts, almost all of the time (97%), individuals who will not develop viral-like illness symptoms in the next three days. Conversely, the model correctly predicts as positive 34% of the time, individuals who will develop viral-like illness symptoms in the next three days. This model uses a conservative framework, warning potentially pre-symptomatic individuals to socially isolate while minimizing warnings to individuals with a low likelihood of developing viral-like symptoms in the next three days. To our knowledge, this is the first study using wearables and apps with machine learning to predict the occurrence of viral illness-like symptoms. The demonstrated approach to forecasting the onset of viral illness-like symptoms offers a novel, digital decision-making tool for public health safety by potentially limiting viral transmission.

A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the Remote Early Detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial

A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the Remote Early Detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial

Asymptomatic individuals can increase the final epidemic size under adaptive human behavior

Infections produced by non-symptomatic (pre-symptomatic and asymptomatic) individuals have been identified as major drivers of COVID-19 transmission. Non-symptomatic individuals, unaware of the infection risk they pose to others, may perceive themselves—and be perceived by others—as not presenting a risk of infection. Yet, many epidemiological models currently in use do not include a behavioral component, and do not address the potential consequences of risk misperception. To study the impact of behavioral adaptations to the perceived infection risk, we use a mathematical model that incorporates the behavioral decisions of individuals, based on a projection of the system’s future state over a finite planning horizon. We found that individuals’ risk misperception in the presence of non-symptomatic individuals may increase or reduce the final epidemic size. Moreover, under behavioral response the impact of non-symptomatic infections is modulated by symptomatic individuals’ behavior. Finally, we found that there is an optimal planning horizon that minimizes the final epidemic size.

A SARS-CoV-2 nucleocapsid ELISA represents a low-cost alternative to lateral flow testing for community screening in LMI countries

Background Controlling the spread of SARS-CoV-2 is problematic because of transmission driven by asymptomatic and pre-symptomatic individuals. Community screening can help identify these individuals but is often too expensive for countries with limited health care resources. Low-cost ELISA assays may address this problem, but their use has not yet been widely reported.Methods We developed a SARS-CoV-2 nucleocapsid ELISA and assessed its diagnostic performance on nose and throat swab samples from UK hospitalised patients and sputum samples from patients in Ghana.Results The ELISA had a limit of detection of 8.4 pg/ml antigen and 16 pfu/ml virus. When tested on UK samples (128 positive and 10 negative patients), sensitivity was 58.6% (49.6–67.2) rising to 78.3% (66.7–87.3) if real-time PCR Ct values > 30 were excluded, while specificity was 100% (69.2–100). In a second trial using the Ghanaian samples (121 positive, 96 negative), sensitivity was 52% (42.8–61.2) rising to 72.6% (61.8–81.2) when a > 30 Ct cut-off was applied, while specificity was 100% (96.2–100).Conclusions: Our data show that nucleocapsid ELISAs can test a variety of patient sample types while achieving levels of sensitivity and specificity required for effective community screening. Further investigations into the opportunities that this provides are warranted.

Apolipoprotein B is a novel marker for early tau pathology in Alzheimer's disease.

IntroductionWe examine the role of brain apolipoprotein B (apoB) as a putative marker of early tau pathology and cognitive decline.MethodsCerebrospinal fluid (CSF) samples from cognitively normal and Alzheimer's disease (AD) participants were collected to measure protein levels of apoB and AD biomarkers amyloid beta (Aβ), t‐tau and p‐tau, as well as synaptic markers GAP43, SYNAPTOTAGMIN‐1, synaptosome associated protein 25 (SNAP‐25), and NEUROGRANIN. CSF apoB levels were contrasted with positron emission tomography (PET) scan measures of Aβ (18F‐NAV4694) and Tau (flortaucipir) along with cognitive assessment alterations over 6 to 8 years.ResultsCSF apoB levels were elevated in AD participants and correlated with t‐tau, p‐tau, and the four synaptic markers in pre‐symptomatic individuals. In the latter, CSF apoB levels correlated with PET flortaucipir‐binding in entorhinal, parahippocampal, and fusiform regions. Baseline CSF apoB levels were associated with longitudinal visuospatial cognitive decline.DiscussionCSF apoB markedly associates with early tau dysregulation in asymptomatic subjects and identifies at‐risk individuals predisposed to develop visuospatial cognitive decline over time.

Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing

The rapid identification and isolation of infected individuals remains a key strategy for controlling the spread of SARS-CoV-2. Frequent testing of populations to detect infection early in asymptomatic or presymptomatic individuals can be a powerful tool for intercepting transmission, especially when the viral prevalence is low. However, RT-PCR testing—the gold standard of SARS-CoV-2 diagnosis—is expensive, making regular testing of every individual unfeasible. Sample pooling is one approach to lowering costs. By combining samples and testing them in groups the number of tests required is reduced, substantially lowering costs. Here we report on the implementation of pooling strategies using 3-d and 4-d hypercubes to test a professional sports team in South Africa. We have shown that infected samples can be reliably detected in groups of 27 and 81, with minimal loss of assay sensitivity for samples with individual Ct values of up to 32. We report on the automation of sample pooling, using a liquid-handling robot and an automated web interface to identify positive samples. We conclude that hypercube pooling allows for the reliable RT-PCR detection of SARS-CoV-2 infection, at significantly lower costs than lateral flow antigen (LFA) tests.

Transmission of SARS-CoV-2 associated with aircraft travel: a systematic review.

Rationale for the reviewAir travel may be associated with viruses spread via infected passengers and potentially through in-flight transmission. Given the novelty of the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, transmission associated with air travel is based on transmission dynamics of other respiratory viruses. Our objective was to provide a rapid summary and evaluation of relevant data on SARS-CoV-2 transmission aboard aircraft, report policy implications and to highlight research gaps requiring urgent attention.MethodsWe searched four electronic databases (1 February 2020–27 January 2021) and included studies on SARS-CoV-2 transmission aboard aircraft. We assessed study quality based on five criteria and reported important findings.Key findingsWe included 18 studies on in-flight SARS-CoV-2 transmission (130 unique flights) and 2 studies on wastewater from aircraft. The quality of evidence from most published studies was low. Two wastewater studies reported PCR-positive samples with high cycle threshold values (33–39). Index case definition was heterogeneous across studies. The proportion of contacts traced ranged from 0.68 to 100%. Authors traced 2800/19 729 passengers, 140/180 crew members and 8/8 medical staff. Altogether, 273 index cases were reported, with 64 secondary cases. Three studies, each investigating one flight, reported no secondary cases. Secondary attack rate among studies following up >80% of passengers and crew (including data on 10 flights) varied between 0 and 8.2%. The studies reported on the possibility of SARS-CoV-2 transmission from asymptomatic, pre-symptomatic and symptomatic individuals. Two studies performed viral cultures with 10 positive results. Genomic sequencing and phylogenetic analysis were performed in individuals from four flights.ConclusionCurrent evidence suggests SARS-CoV-2 can be transmitted during aircraft travel, but published data do not permit any conclusive assessment of likelihood and extent. The variation in design and methodology restricts the comparison of findings across studies. Standardized guidelines for conducting and reporting future studies of transmission on aircraft should be developed.

Health care practitioners' experience-based opinions on providing care after a positive newborn screen for Pompe disease

The addition of Pompe disease (PD) and other conditions with later-onset forms to newborn screening (NBS) in the United States (US) has been controversial. NBS technology cannot discern infantile-onset PD (IOPD) from later-onset PD (LOPD) without clinical follow-up. This study explores genetic health care practitioners’ (HCPs) experiences and challenges providing NBS patient care throughout the US and their resultant opinions on NBS for PD. An online survey was distributed to genetic counselors, geneticists, NBS follow-up care coordinators, and nurse practitioners caring for patients with positive NBS results for PD. Analysis of 78 surveys revealed the majority of participating HCPs support inclusion of PD on NBS. Almost all HCPs (93.3%) feel their state has sufficient resources to provide follow-up medical care for IOPD; however, only three-fourths (74.6%) believed this for LOPD. Common barriers included time lag between NBS and confirmatory results, insurance difficulties for laboratory testing, and family difficulties in seeking medical care. HCPs more frequently encountered barriers providing care for LOPD than IOPD (53.9% LOPD identified ≥3 barriers, 31.1% IOPD). HCPs also believe creation of a population of presymptomatic individuals with LOPD creates a psychological burden on the family (87.3% agree/strongly agree), unnecessary medicalization of the child (63.5% agree/strongly agree), and parental hypervigilance (68.3% agree/strongly agree). Opinions were markedly divided on the use of reproductive benefit as a justification for NBS. Participants believe additional education for pediatricians and other specialists would be beneficial in providing care for patients with both IOPD and LOPD, in addition to the creation of evidence-based official guidelines for care and supportive resources for families with LOPD.

Group Testing for SARS-CoV-2 Allows for Up to 10-Fold Efficiency Increase Across Realistic Scenarios and Testing Strategies.

Background: Due to the ongoing COVID-19 pandemic, demand for diagnostic testing has increased drastically, resulting in shortages of necessary materials to conduct the tests and overwhelming the capacity of testing laboratories. The supply scarcity and capacity limits affect test administration: priority must be given to hospitalized patients and symptomatic individuals, which can prevent the identification of asymptomatic and presymptomatic individuals and hence effective tracking and tracing policies. We describe optimized group testing strategies applicable to SARS-CoV-2 tests in scenarios tailored to the current COVID-19 pandemic and assess significant gains compared to individual testing.Methods: We account for biochemically realistic scenarios in the context of dilution effects on SARS-CoV-2 samples and consider evidence on specificity and sensitivity of PCR-based tests for the novel coronavirus. Because of the current uncertainty and the temporal and spatial changes in the prevalence regime, we provide analysis for several realistic scenarios and propose fast and reliable strategies for massive testing procedures.Key Findings: We find significant efficiency gaps between different group testing strategies in realistic scenarios for SARS-CoV-2 testing, highlighting the need for an informed decision of the pooling protocol depending on estimated prevalence, target specificity, and high- vs. low-risk population. For example, using one of the presented methods, all 1.47 million inhabitants of Munich, Germany, could be tested using only around 141 thousand tests if the infection rate is below 0.4% is assumed. Using 1 million tests, the 6.69 million inhabitants from the city of Rio de Janeiro, Brazil, could be tested as long as the infection rate does not exceed 1%. Moreover, we provide an interactive web application, available at www.group-testing.com, for visualizing the different strategies and designing pooling schemes according to specific prevalence scenarios and test configurations.Interpretation: Altogether, this work may help provide a basis for an efficient upscaling of current testing procedures, which takes the population heterogeneity into account and is fine-grained towards the desired study populations, e.g., mild/asymptomatic individuals vs. symptomatic ones but also mixtures thereof.Funding: German Science Foundation (DFG), German Federal Ministry of Education and Research (BMBF), Chan Zuckerberg Initiative DAF, and Austrian Science Fund (FWF).

On the effectiveness of tracking and testing in SEIR models for improving health vs. economy trade-offs

We study the effectiveness of tracking and testing policies for suppressing epidemic outbreaks. We evaluate the performance of tracking-based intervention methods on a network SEIR model, which we augment with an additional parameter to model pre-symptomatic and asymptomatic individuals, and study the effectiveness of these methods in combination with or as an alternative to quarantine and global lockdown policies. Our focus is on the basic trade-off between human-lives lost and economic costs, and on how this trade-off changes under different quarantine, lockdown, tracking, and testing policies. Our main findings are as follows: (1) Tests combined with patient quarantines reduce both economic costs and mortality, however, an extensive-scale testing capacity is required to achieve a significant improvement. (2) Tracking significantly reduces both economic costs and mortality. (3) Tracking combined with a moderate testing capacity can achieve containment without lockdowns. (4) In the presence of a flow of new incoming infections, dynamic “On–Off” lockdowns are more efficient than fixed lockdowns. In this setting as well, tracking strictly improves efficiency. The results show the extreme usefulness of policies that combine tracking and testing for reducing mortality and economic costs, and their potential to contain outbreaks without imposing any social distancing restrictions. This highlights the difficult social question of trading-off these gains against patient privacy, which is inevitably infringed by tracking.

Defining the optimal dose and therapeutic window in SMA with respiratory distress type I model mice, FVB/NJ-Ighmpb2nmd-2J

Spinal muscular atrophy with respiratory distress type 1 (SMARD1) is an autosomal recessive disorder that develops in infancy and arises from mutation of the immunoglobulin helicase μ-binding protein 2 (IGHMBP2) gene. Whereas IGHMBP2 is ubiquitously expressed, loss or reduction of function leads to alpha motor neuron loss and skeletal muscle atrophy. We previously developed a gene therapy strategy for SMARD1 using a single-stranded AAV9-IGHMBP2 vector and compared two different delivery methods in a validated SMARD1 mouse model. An important question in the field relates to the temporal requirements for this or any potential treatment. To examine the therapeutic window, we utilized our recently developed SMARD1 model, FVB/NJ-Ighmpb2nmd-2J, to deliver AAV9-IGHMBP2 at four different time points starting at post-natal day 2 (P2) through P8. At each time point, significant improvements were observed in survival, weight gain, and motor function. Similarly, treatment improved important hallmarks of disease, including motor unit pathology. Whereas improvements were more pronounced in the early-treatment groups, even the later-treatment groups displayed significant phenotypic improvements. This work suggests that an effective gene therapy strategy could provide benefits to pre-symptomatic and early-symptomatic individuals, thereby expanding the potential therapeutic window for SMARD1.

Modeling Epidemic Spread among a Commuting Population Using Transport Schemes

Understanding the dynamics of the spread of COVID-19 between connected communities is fundamental in planning appropriate mitigation measures. To that end, we propose and analyze a novel metapopulation network model, particularly suitable for modeling commuter traffic patterns, that takes into account the connectivity between a heterogeneous set of communities, each with its own infection dynamics. In the novel metapopulation model that we propose here, transport schemes developed in optimal transport theory provide an efficient and easily implementable way of describing the temporary population redistribution due to traffic, such as the daily commuter traffic between work and residence. Locally, infection dynamics in individual communities are described in terms of a susceptible-exposed-infected-recovered (SEIR) compartment model, modified to account for the specific features of COVID-19, most notably its spread by asymptomatic and presymptomatic infected individuals. The mathematical foundation of our metapopulation network model is akin to a transport scheme between two population distributions, namely the residential distribution and the workplace distribution, whose interface can be inferred from commuter mobility data made available by the US Census Bureau. We use the proposed metapopulation model to test the dynamics of the spread of COVID-19 on two networks, a smaller one comprising 7 counties in the Greater Cleveland area in Ohio, and a larger one consisting of 74 counties in the Pittsburgh–Cleveland–Detroit corridor following the Lake Erie’s American coastline. The model simulations indicate that densely populated regions effectively act as amplifiers of the infection for the surrounding, less densely populated areas, in agreement with the pattern of infections observed in the course of the COVID-19 pandemic. Computed examples show that the model can be used also to test different mitigation strategies, including one based on state-level travel restrictions, another on county level triggered social distancing, as well as a combination of the two.

Rapid antigen detection alone may not be sufficient for early diagnosis and/or mass screening of COVID‐19

Currently, COVID-19 pandemic is still severe, and the major challenge in the fight against this pandemic is how to early find pre-symptomatic and asymptomatic individuals and to eliminate silent transmission. Rapid antigen detection alone may not be sufficient for early diagnosis and/or mass screening of COVID-19, and direct probe-based RT-LAMP assay or other nucleic acid amplification (NAA)-based POCT strategies should be recommended to use alone or together with rapid antigen test in mass screening or community-based testing of SARS-CoV-2 This article is protected by copyright. All rights reserved.

Qualitative analysis of a mathematical model with presymptomatic individuals and two SARS-CoV-2 variants

The SARS-CoV-2 continues to spread across the world. During this COVID-19 pandemic, several variants of the SARS-CoV-2 have been found. Some of these new variants like the VOC-202012/01 of lineage B.1.1.7 or the most recently B.1.617 emerging in India have a higher infectiousness than those previously prevalent. We propose a mathematical model based on ordinary differential equations to investigate potential consequences of the appearance of a new more transmissible SARS-CoV-2 strain in a given region. The proposed mathematical model incorporates the presymptomatic and asymptomatic subpopulations in addition to the more usual susceptible, exposed, infected, and recovered subpopulations. This is important from a realistic point of view since it has been found recently that presymptomatic and asymptomatic individuals are relevant spreaders of the SARS-CoV-2. Using the next-generation matrix method, we find the basic reproduction number, {mathcal {R}}_{0}, an important threshold parameter that provides insight regarding the evolution and outcome of a certain instance of the COVID-19 pandemic. The local and global stability of system equilibria are also presented. In particular, for the global stability we construct a Lyapunov functional and use the LaSalle invariant principle to prove that if the basic reproduction ratio is less than unity, the infection-free equilibrium is globally asymptotically stable. On the other hand, if {mathcal {R}}_{0}>1 the endemic equilibrium is globally asymptotically stable. Finally, we present numerical simulations to numerically support the analytic results and to show the impact of the introduction of a new more contagious SARS-CoV-2 variant in a population.

Comparative diagnosis interest of NfL and pNfH in CSF and plasma in a context of FTD-ALS spectrum.

The 'Frontotemporal dementia-Amyotrophic lateral sclerosis Spectrum' (FAS) encompasses different phenotypes, including cognitive disorders (frontotemporal dementia, FTD) and/or motor impairments (amyotrophic lateral sclerosis, ALS). The aim of this study was to apprehend the specific uses of neurofilaments light chain (NfL) and phosphorylated neurofilaments heavy chain (pNfH) in a context of FAS. First, NfL and pNfH were measured in 39 paired cerebrospinal fluid (CSF) and plasma samples of FAS and primary psychiatric disorders (PPD) patients, considered as controls. Secondly, additional plasma samples were included to examine a larger cohort of 81 samples composed of symptomatic FAS and PPD patients, presymptomatic and non-carrier relatives individuals. The measures were performed using Simoa technology. There was a positive correlation between CSF and plasma values for NfL (p < 0.0001) and for pNfH (p = 0.0036). NfL values were higher for all phenotypes of symptomatic FAS patients compared to PPD patients (p = 0.0016 in CSF; p = 0.0003 in plasma). On the contrary, pNfH values were solely increased in FAS patients exhibiting motor impairment. Unlike symptomatic FAS patients, presymptomatic cases had comparable concentrations with non-carrier individuals. NfL, but not pNfH, appeared to be useful in a context of differential diagnosis between FTD and psychiatric patients. Nevertheless, pNfH seem more specific for the diagnosis and follow-up of motor impairments. In each specific indication, measures in CSF and plasma will provide identical interpretations.

COVID-19 Outbreak in a Hemodialysis Center Using Universal Masking and Eye Protection

Background: Up to half of all new SARS-CoV-2 infections are acquired from presymptomatic or asymptomatic individuals. Hemodialysis patients and healthcare providers (HCPs) may be at increased risk for COVID-19 due to the need for extended close contact. Universal masking and eye protection are strategies used to reduce SARS-CoV-2 exposure, particularly from presymptomatic or asymptomatic individuals. We describe an outbreak of COVID-19 in an outpatient hemodialysis center despite universal masking and universal HCP eye protection. Methods: An COVID-19 outbreak investigation was performed in a hemodialysis center where universal masking was in use by all HCPs and patients and universal eye protection (goggles, safety glasses) was in use by all HCPs when directly encountering patients. After a cluster of cases was identified in early November 2020, all patients and HCPs were tested for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (RT-PCR) when symptomatic and weekly until the conclusion of the outbreak. Results: From November 12, 2020, through December 7, 2020, 14 (23.3%) of 60 patients and 9 (28.1%) of 32 HCPs tested positive for SARS-CoV-2 by RT-PCR (Figure 1). The median ages of the patients and HCPs were 64 years (range, 42–87) and 42 years (range, 29–68), respectively. Also, 5 (5.4%) individuals (3 patients and 2 HCPs) were asymptomatic at the time of testing. Furthermore, 7 (7.6%) individuals (5 patients and 2 HPCs) were hospitalized; 2 patients and no HCPs died. No lapses in universal masking or, for HCPs, eye protection prior to or during the outbreak were identified during the investigation. All HCPs and patients wore medical-grade face masks that were discarded at the end of the day; HCPs wore safety glasses or goggles during patient interactions. Although audits of face mask and eye protection compliance were not performed, independent interviews supported high HCP and patient adherence prior to the outbreak. Neither the staff nor patients shared meals at or outside the hemodialysis center. Most patients and HCPs shared the same hemodialysis shift, suggesting the presence of an index case; however, a source case could not be identified despite an extensive investigation. Conclusions: Universal masking and eye protection have been shown to reduce transmission of SARS-CoV-2 from presymptomatic or asymptomatic individuals in the healthcare setting. This report suggests that such measures cannot prevent all outbreaks. We speculate that certain factors associated with hemodialysis care, such as prolonged close patient–HCP contact, may have facilitated this outbreak. Whether nonadherence to universal masking and eye protection or failure of empiric droplet precautions contributed to this outbreak remains unknown.Funding: NoDisclosures: None

Evaluating the Relationship between Cycle Threshold Values and Reported COVID-19 Symptoms among Healthcare Workers

Background: SARS-CoV-2 detected by reverse transcription polymerase chain reaction (RT-PCR) can persist for weeks to months in some individuals. Cycle threshold (Ct) values represent the number of cycles needed to amplify viral ribonucleic acid (RNA) to reach a detectable level. As such, Ct values are inversely related to the amount of virus in a sample. As knowledge of SARS-CoV-2 viral dynamics continues to evolve, understanding the relationship between Ct values, type of symptoms, and timing of symptom onset can help determine when infected individuals are most likely to be infectious. Methods: We conducted a retrospective cohort study of 1,027 healthcare workers (HCWs) who tested positive for SARS-CoV-2 by RT-PCR from nasopharyngeal specimens between June 27, 2020, and September 21, 2020. All HCWs were interviewed within 72 hours of their diagnosis for symptom history. Due to multiple PCR platforms being in use in our facility, only 360 HCWs (35%) had Ct values available for analysis. Multivariate linear regression models examined the effect of COVID-19–related symptoms and timing of symptom onset to test on Ct values. Results: The most frequently reported symptoms were congestion (55.6%), cough (50.3%), and headache (46.7%). Other symptoms less commonly reported were fatigue (36.7%), loss of taste or smell (36.4%), fever (35.4%), muscle aches (33.3%), sore throat (27.4%), and diarrhea (26.7%). Symptomatic HCWs (88.3% of sample) had lower Ct values (ORF-1 M = 22.66, SD = 5.17; E-Gene M = 24.34, SD = 6.60) than asymptomatic individuals (ORF-1 M = 25.46, SD = 6.06; E-Gene M = 29.34, SD = 7.96). Of all symptoms measured, only presence of fever, congestion, and muscle aches predicted significantly lower Ct values. Mean Ct values decreased 2 days prior to symptom onset, were lowest the day of symptom onset, then increased in a curvilinear fashion. There were no significant 2-way interactions between symptoms and time of symptom onset to testing. Conclusions: The curvilinear pattern of Ct values over time from symptom onset are consistent with disease progression patterns and support current understanding of infectivity being highest 2 days prior to symptom onset through day 8. Presence of fever, congestion, and muscle aches are significantly correlated with lower Ct values, suggesting that these symptoms are associated with higher viral load. Although Ct values are not without limitations, our findings support the current understanding that presymptomatic and symptomatic individuals, particularly those with fever, congestion, and muscle aches, may pose higher risk of transmission to others.Funding: NoDisclosures: None

Neurofilament Light Chain as Biomarker for Amyotrophic Lateral Sclerosis and Frontotemporal Dementia.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two related currently incurable neurodegenerative diseases. ALS is characterized by degeneration of upper and lower motor neurons causing relentless paralysis of voluntary muscles, whereas in FTD, progressive atrophy of the frontal and temporal lobes of the brain results in deterioration of cognitive functions, language, personality, and behavior. In contrast to Alzheimer’s disease (AD), ALS and FTD still lack a specific neurochemical biomarker reflecting neuropathology ex vivo. However, in the past 10 years, considerable progress has been made in the characterization of neurofilament light chain (NFL) as cerebrospinal fluid (CSF) and blood biomarker for both diseases. NFL is a structural component of the axonal cytoskeleton and is released into the CSF as a consequence of axonal damage or degeneration, thus behaving in general as a relatively non-specific marker of neuroaxonal pathology. However, in ALS, the elevation of its CSF levels exceeds that observed in most other neurological diseases, making it useful for the discrimination from mimic conditions and potentially worthy of consideration for introduction into diagnostic criteria. Moreover, NFL correlates with disease progression rate and is negatively associated with survival, thus providing prognostic information. In FTD patients, CSF NFL is elevated compared with healthy individuals and, to a lesser extent, patients with other forms of dementia, but the latter difference is not sufficient to enable a satisfying diagnostic performance at individual patient level. However, also in FTD, CSF NFL correlates with several measures of disease severity. Due to technological progress, NFL can now be quantified also in peripheral blood, where it is present at much lower concentrations compared with CSF, thus allowing less invasive sampling, scalability, and longitudinal measurements. The latter has promoted innovative studies demonstrating longitudinal kinetics of NFL in presymptomatic individuals harboring gene mutations causing ALS and FTD. Especially in ALS, NFL levels are generally stable over time, which, together with their correlation with progression rate, makes NFL an ideal pharmacodynamic biomarker for therapeutic trials. In this review, we illustrate the significance of NFL as biomarker for ALS and FTD and discuss unsolved issues and potential for future developments.

(Invited) Sars-Cov-2 Rapidplex: A Graphene-Based Multiplexed Telemedicine Platform for Rapid COVID-19 Diagnosis

The COVID-19 pandemic is an ongoing global challenge for public health systems. Rapid and early identification of infection is critical in preventing widespread COVID-19 infection by presymptomatic and asymptomatic individuals, especially in the community and in-home settings. I will introduce an ultrasensitive and low-cost telemedicine platform, the SARS-CoV-2 RapidPlex, based on target-specific immunoassays built off laser-engraved graphene for rapid and remote assessment of COVID-19 biomarkers (i.e., nucleocapsid protein, anti-spike protein IgG and IgM, and C-reactive protein). Multiplex sensing of these targets provides information on three key aspects of COVID-19 disease: viral infection, immune response, and disease severity. We successfully evaluated the applicability of our SARS-CoV-2 RapidPlex platform with COVID-19-positive and COVID-19-negative blood and saliva samples. Based on this pilot study, our multiplexed immunosensor platform may allow for high-frequency at-home testing for COVID-19 telemedicine diagnosis and monitoring. Figure 1

More than the Eye Can See: Shedding New Light on SARS-CoV-2 Lateral Flow Device-Based Immunoassays.

Containing the global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been an unprecedented challenge due to high horizontal transmissivity and asymptomatic carriage rates. Lateral flow device (LFD) immunoassays were introduced in late 2020 to detect SARS-CoV-2 infection in asymptomatic or presymptomatic individuals rapidly. While LFD technologies have been used for over 60 years, their widespread use as a public health tool during a pandemic is unprecedented. By the end of 2020, data from studies into the efficacy of the LFDs emerged and showed these point-of-care devices to have very high specificity (ability to identify true negatives) but inadequate sensitivity with high false-negative rates. The low sensitivity (<50%) shown in several studies is a critical public health concern, as asymptomatic or presymptomatic carriers may wrongly be assumed to be noninfectious, posing a significant risk of further spread in the community. Here, we show that the direct visual readout of SARS-CoV-2 LFDs is an inadequate approach to discriminate a potentially infective viral concentration in a biosample. We quantified significant immobilized antigen–antibody-labeled conjugate complexes within the LFDs visually scored as negative using high-sensitivity synchrotron X-ray fluorescence imaging. Correlating quantitative X-ray fluorescence measurements and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) determined numbers of viral copies, we identified that negatively scored samples could contain up to 100 PFU (equivalent here to ∼10 000 RNA copies/test). The study demonstrates where the shortcomings arise in many of the current direct-readout SARS-CoV-2 LFDs, namely, being a deficiency in the readout as opposed to the potential level of detection of the test, which is orders of magnitude higher. The present findings are of importance both to public health monitoring during the Coronavirus Disease 2019 (COVID-19) pandemic and to the rapid refinement of these tools for immediate and future applications.