Cross-platform comparison of highly-sensitive immunoassays for inflammatory markers in a COVID-19 cohort (preprint)

A variety of commercial platforms are available for the simultaneous detection of multiple cytokines and associated proteins, often employing antibody pairs to capture and detect target proteins. In this study, we comprehensively evaluated the performance of three distinct platforms: the fluorescent bead-based Luminex assay, the proximity extension-based Olink assay, and a novel proximity ligation assay platform known as Alamar NULISAseq. These assessments were conducted on serum samples from the NIH IMPACC study, with a focus on three essential performance metrics: detectability, correlation, and differential expression. Our results reveal several key findings. Firstly, the Alamar platform demonstrated the highest overall detectability, followed by Olink and then Luminex. Secondly, the correlation of protein measurements between the Alamar and Olink platforms tended to be stronger than the correlation of either of these platforms with Luminex. Thirdly, we observed that detectability differences across the platforms often translated to differences in differential expression findings, although high detectability did not guarantee the ability to identify meaningful biological differences. Our study provides valuable insights into the comparative performance of these assays, enhancing our understanding of their strengths and limitations when assessing complex biological samples, as exemplified by the sera from this COVID-19 cohort.

NULISA: a novel proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing (preprint)

The blood proteome holds great promise for precision medicine but poses daunting challenges due to the low abundance of the majority of plasma proteins and the vast dynamic range across the proteome. We report the development and validation of a novel proteomic analysis technology - NUcleic acid Linked Immuno-Sandwich Assay (NULISA) - that incorporates a dual capture and release mechanism to suppress the assay background to the minimum, thus drastically improving the signal-to-noise ratio. NULISA improves the sensitivity of the proximity ligation assay by over 10,000-fold to the attomolar level, which is enabled by antibody-conjugated DNA sequences that mediate the purification of immunocomplexes and contain target- and sample-specific barcodes for next-generation sequencing-based, highly multiplexed analysis. To demonstrate its performance and utility, we developed a 200-plex NULISA targeting 124 cytokines and chemokines and 80 other immune response-related proteins that demonstrated superior sensitivity for detecting low-abundance proteins and high concordance with other immunoassays. The ultra-high sensitivity enabled the detection of previously difficult-to-detect but biologically important, low-abundance biomarkers in patients with autoimmune diseases and COVID-19. Fully automated NULISA uniquely addresses longstanding challenges in the proteomic analysis of liquid biopsy samples and makes broad and in-depth proteomic analysis accessible to the general research community and future diagnostic applications.

Development of a ferritin-based nanoparticle vaccine against the SARS-CoV-2 Omicron variant (preprint)

A new SARS-CoV-2 variant named Omicron (B.1.1.529) discovered initially in South Africa has recently been proposed as a variant of concern (VOC) by the World Health Organization, because of its high transmissibility and resistance to current vaccines and therapeutic antibodies. Therefore, rapid development of vaccines against prevalent variants including Omicron is urgently needed for COVID-19 prevention. Here, we designed a self-assembling ferritin-based nanoparticle (FNP) vaccine against the SARS-CoV-2 Omicron variant. The purified Fc-RBD Omicron automatically formed a dimer depending on the nature of the Fc tag, thus assembling onto the nanoparticles by the Fc-protein A tag interaction (FNP-Fc-RBD Omicron ). The results of hACE2-transgenic mice immunization showed that SARS-CoV-2 Omicron RBD-specific IgG titer induced by FNP-Fc-RBDOmicron was much higher than that by Fc-RBD Omicron . Consistently, the sera showed a higher neutralizing activity against SARS-CoV-2 Omicron BA.1 and BA.2 in the FNP-Fc-RBD Omicron immunized mice, indicating that immunization of a self-assembling ferritin-based nanoparticle vaccine offers a robust humoral immune response against Omicron variants. This study offers a great potential for the quick response of the emerging SARS-CoV-2 variants and affords versatility to develop universal vaccines against other emerging and reemerging coronaviruses in the future.

Evaluation on potential detriments from lockdown-related isolation to mental health among school-aged youth in central China (preprint)

Background: Home isolation is a generally effective strategy for coronavirus disease control during lockdown periods. This study is to determine the potential adverse consequences of home isolation to mental health among school-aged youth after lifting of major lockdown measures in central China. Methods: This cohort study assessed the mental health of school-aged children and adolescents enrolled in Wuhan city and nearby areas in Hubei province, China, from July 1 to August 31, 2020. Post-lockdown responses to anxiety, depression, sleep disturbances and post-traumatic stress symptoms were assessed in online questionnaire-based surveys. Participants’ scores for the Zung self-rated anxiety scale, the Patient Health Questionnaire-9, the self-rating scale of sleep and the post-traumatic stress disorder self-rating scale (PTSS) were analyzed. Results: Questionnaire responses of 730 school children were collected. Among the participants, 6.25% of them had scores above thresholds for PTSS, 5.81% had anxiety, and 48.84% had depression. All subjects reported that they experienced sleep disturbances. Subjects who had anxiety might have a high risk for developing depression [OR: 16.07, p =0.008, 95%CI (2.08-123.94)] and PTSS [OR: 12.97, p <0.001, 95%CI (5.41-31.11)]. Both depression [OR: 17.35, p =0.006, 95%CI (2.28-131.87)] and PTSS [OR: 14.18, p <0.001, 95%CI (6.00-33.47)] were risk factors for developing anxiety among participants. Interestingly, higher educational levels of primary caregivers were a risk factor for developing depression [OR: 1.62, p =0.005, 95%CI (1.16-2.28)] in the participants, but a protective factor against PTSS [OR: 0.47, p =0.048, 95%CI (0.23-0.99)].Conclusions: The local youth had less than expected degree of increases in their self-reported PTSS and anxiety, after exiting lockdown-related isolation. As a result of a combination of compensatory mechanisms including internet-based home-schooling and increased intra-familial interactions, home isolation did not affect the mental health of local school-aged youth to an extent as great as expected.Trial registration: The Registration number of this trial is ChiCTR2000033054.

Index and First-Generation Cases in a COVID-19 Outbreak — Jilin Province, China, 2021

What is already known on this topic? Contact tracing and testing with isolated medical care of identified cases is a key strategy for interrupting chains of transmission of COVID-19 and reducing mortality associated with COVID-19. At the early phases of the COVID-19 pandemic, due to test capacity limitations, case finding often started from suspected cases. What is added by this report? The index patient infected 74 individuals who were close contacts that were identified through contact tracing, and exposed individuals were monitored in quarantine with daily polymerase chain reaction (PCR) testing. All individuals were asymptomatic initially, but all PCR-positive individuals eventually developed symptoms. Infectivity was documented up to 8 days before being confirmed as a symptomatic case, approximately 4 days before turning PCR positive. What are the implications for public health practice? During an outbreak, we suggest tracing close contacts from both PCR-positive individuals and suspected cases, rather than from suspected cases alone. Due to the long period of infectivity before turning PCR positive or developing symptoms, close contacts that had contact with a newly PCR positive case within 4 days should be judged as at risk of being infected;close contacts that had contact within 8 days of a newly symptomatic case should be judged as at risk being infected.

OmicPioneer-sc: an integrated, interactive visualization environment for single-cell sequencing data (preprint)

OmicPioneer-sc is an open-source data visualization/analysis package that integrates dimensionality-reduction plots (DRPs) such as t-SNE and UMAP with Next-Generation Clustered Heat Maps (NGCHMs) and Pathway Visualization Modules (PVMs) in a seamless, highly interactive exploratory environment. It includes fluent zooming and navigation, a statistical toolkit, dozens of link-outs to external public bioinformatic resources, high-resolution graphics that meet the requirements of all major journals, and the ability to store all metadata needed to reproduce the visualizations at a later time. A user-friendly, multi-panel graphical interface enables non-informaticians to interact with the system without programming, asking and answering questions that require navigation among the three types of modules or extension from them to the Gene Ontology or information on therapies. The visual integration can be useful for detective work to identify and annotate cell-types for color-coding of the DRPs, and multiple NGCHMs can be layered on top of each other (with toggling among them) as an aid to multi-omic analysis. The tools are available in containerized form with APIs to facilitate incorporation as a plug-in to other bioinformatic environments. The capabilities of OmicPioneer-sc are illustrated here through application to a single-cell RNA-seq airway dataset pertinent to the biology of both cancer and COVID-19. [Supplemental material is available for this article.]

Impact of stopping therapy during the SARS-CoV-2 pandemic in persons with lymphoma (preprint)

IntroductionThe severe acute respiratory syndrome-2 (SARS-CoV-2) pandemic disrupted medical care for persons with cancer including those with lymphoma. Many professional societies recommend postponing, decreasing or stopping anti-cancer therapy in selected persons during the pandemic. However, although seemingly sensible these recommendations are not evidence-based and their impact on anxiety and health-related quality-of-life (HRQoL) is unknown. MethodsSurveyed 2532 subjects including 1060 persons with lymphoma, 948 caregivers and 524 normal, uninvolved persons using a purposed-designed questionnaire on a patient organization website. Respondents also completed the Zung Self-Rating Anxiety and patient respondents, the EORTC QLQ-C30 instruments to quantify anxiety and HRQoL. We also evaluated caregiver support and an online education programme of the Chinese Society of Clinical Oncology (CSCO). Data of HRQoL from a 2019 pre-pandemic online survey of 1106 persons with lymphoma was a control. Results33% (95% Confidence Interval [CI] 30, 36%) of lymphoma patients and 31% (28, 34%) of caregivers but only 21% (17, 24%) of normal individuals had any level of anxiety (both pair-wise P < 0.001). Amongst lymphoma respondents physical exercise and better caregiver support were associated with less anxiety whereas female sex, receiving therapy and reduced therapy intensity were associated with more anxiety. Paradoxically, lymphoma respondents during the pandemic had better HRQoL than pre-pandemic controls. Reduced therapy intensity was associated with worse HRQoL whereas respondents who scored caregiver support and the online patient education programme high had better HRQoL. ConclusionsDuring the SARS-CoV-2 pandemic lymphoma patients and their caregivers had significantly higher incidence of anxiety compared with normals. Lymphoma respondents reported better HRQoL compared with pre-pandemic controls. Reduced therapy-intensity in patients with cancer may have unanticipated adverse effects on anxiety and HRQoL. Regular and intense support by caregivers and online education programmes alleviate anxiety and improve HRQoL.

Towards Data-Efficient Learning: A Benchmark for COVID-19 CT Lung and Infection Segmentation (preprint)

Purpose: Accurate segmentation of lung and infection in COVID-19 CT scans plays an important role in the quantitative management of patients. Most of the existing studies are based on large and private annotated datasets that are impractical to obtain from a single institution, especially when radiologists are busy fighting the coronavirus disease. Furthermore, it is hard to compare current COVID-19 CT segmentation methods as they are developed on different datasets, trained in different settings, and evaluated with different metrics. Methods: To promote the development of data-efficient deep learning methods, in this paper, we built three benchmarks for lung and infection segmentation based on 70 annotated COVID-19 cases, which contain current active research areas, e.g., few-shot learning, domain generalization, and knowledge transfer. For a fair comparison among different segmentation methods, we also provide standard training, validation and testing splits, evaluation metrics and, the corresponding code. Results: Based on the state-of-the-art network, we provide more than 40 pre-trained baseline models, which not only serve as out-of-the-box segmentation tools but also save computational time for researchers who are interested in COVID-19 lung and infection segmentation. We achieve average Dice Similarity Coefficient (DSC) scores of 97.3\%, 97.7\%, and 67.3\% and average Normalized Surface Dice (NSD) scores of 90.6\%, 91.4\%, and 70.0\% for left lung, right lung, and infection, respectively. Conclusions: To the best of our knowledge, this work presents the first data-efficient learning benchmark for medical image segmentation and the largest number of pre-trained models up to now. All these resources are publicly available, and our work lays the foundation for promoting the development of deep learning methods for efficient COVID-19 CT segmentation with limited data.

Electrophysiology in the time of coronavirus: coping with the great wave. (preprint)

Aims: To chart the effect of the COVID-19 pandemic on the activity of interventional electrophysiology services in affected regions. Methods: We reviewed the electrophysiology laboratory records in 3 affected cities: Wenzhou in China, Milan in Italy and London, United Kingdom. We interviewed electrophysiologists in each centre to gather information on the impact of the pandemic on working patterns and on the health of staff members. Results: There was a striking decline in interventional electrophysiology activity in each of the centres. The decline occurred within a week of the recognition of widespread community transmission of the virus in each region and shows a striking correlation with the national figures for new diagnoses of COVID-19 in each case. During the period of restriction, work-flow dropped to <5% of normal, consisting of emergency cases only. In 2 of 3 centres, electrophysiologists were redeployed to perform emergency work outside electrophysiology. Among the centres studied, only Wenzhou has seen a recovery from the restrictions in activity. Following an intense nationwide program of public health interventions, local transmission of COVID-19 ceased to be detectable after February 18th allowing the electrophysiology service to resume with a strict testing regime for all patients. Conclusion: Interventional electrophysiology is vulnerable to closure in times of great social difficulty including the COVID-19 pandemic. Intense public health intervention can permit suppression of local disease transmission allowing resumption of some normal activity.

Design and preliminary application of regional control and prevention auxiliary information system under the attack of COVID-19 infectious disease / 中华医学科研管理杂志

Objective@#To propose the concept of a novel regional control and prevention (RCP) system for the outbreak of COVID-19 infectious disease, design an emergency epidemic prevention information system based on the existing network architecture and information system in the region, and a remote intelligent medical consultation and remote office platform, research and develop the technology of risk assessment and early warning for people in the region, and improve the regions’prevention and control ability facing emergency of major infectious diseases.@*Methods@#Taking colleges, affiliated (teaching) hospitals, and cloud applications as typical RCP regional units, the existing local area network interaction methods between the cloud and universities and affiliated (teaching) hospitals are established to realize remote work in the network environment, remote medical imaging, psychological and ethical consultation and interaction; applying multi-agent propagation model based on complex network, combining Global Positioning System (GPS), Radio Frequency Identification (RFID), and electronic fence technology, to realize the risk classification and early warning of units and personnel in the area.@*Results@#In the RCP, a system architecture combining campus network, affiliated (teaching) hospital intranet, and the Internet is used. Dynamic connection is made using distributed technology and cloud storage. The data buffer mechanism of the intermediary database in the network realized telemedicine consultation and telecommuting. Relying on the platform, multi-agent propagation model based on complex network and cellular automaton model are used to realize the score and early warning of population exposure risk in the region by using GPS, RFID and electronic fence technology.@*Conclusions@#In the epidemic phase of major infectious diseases, the construction of RCP can improve the response speed of wartime epidemic prevention, provide reasonable data-based warnings and risk ratings, and reduce the exposure risk of susceptible people. The design and development of RCP is a systematic project that needs to combine regional structural and functional characteristics, and the foundation of the early informatization work in the region and the level of the emergency development team determine the development progress, maintenance, and actual application effects. It is recommended to establish a peacetime and wartime combined RCP mode and incorporate it into the government's disease control system to improve the national and regional level of prevention and control of major infectious diseases.