Physically Meaningful Surrogate Data for COPD.

The rapidly increasing prevalence of debilitating breathing disorders, such as chronic obstructive pulmonary disease (COPD), calls for a meaningful integration of artificial intelligence (AI) into respiratory healthcare. Deep learning techniques are "data hungry" whilst patient-based data is invariably expensive and time consuming to record. To this end, we introduce a novel COPD-simulator, a physical apparatus with an easy to replicate design which enables rapid and effective generation of a wide range of COPD-like data from healthy subjects, for enhanced training of deep learning frameworks. To ensure the faithfulness of our domain-aware COPD surrogates, the generated waveforms are examined through both flow waveforms and photoplethysmography (PPG) waveforms (as a proxy for intrathoracic pressure) in terms of duty cycle, sample entropy, FEV1/FVC ratios and flow-volume loops. The proposed simulator operates on healthy subjects and is able to generate FEV1/FVC obstruction ratios ranging from greater than 0.8 to less than 0.2, mirroring values that can observed in the full spectrum of real-world COPD. As a final stage of verification, a simple convolutional neural network is trained on surrogate data alone, and is used to accurately detect COPD in real-world patients. When training solely on surrogate data, and testing on real-world data, a comparison of true positive rate against false positive rate yields an area under the curve of 0.75, compared with 0.63 when training solely on real-world data.

Multivariate Multiscale Cosine Similarity Entropy and Its Application to Examine Circularity Properties in Division Algebras.

The extension of sample entropy methodologies to multivariate signals has received considerable attention, with traditional univariate entropy methods, such as sample entropy (SampEn) and fuzzy entropy (FuzzyEn), introduced to measure the complexity of chaotic systems in terms of irregularity and randomness. The corresponding multivariate methods, multivariate multiscale sample entropy (MMSE) and multivariate multiscale fuzzy entropy (MMFE), were developed to explore the structural richness within signals at high scales. However, the requirement of high scale limits the selection of embedding dimension and thus, the performance is unavoidably restricted by the trade-off between the data size and the required high scale. More importantly, the scale of interest in different situations is varying, yet little is known about the optimal setting of the scale range in MMSE and MMFE. To this end, we extend the univariate cosine similarity entropy (CSE) method to the multivariate case, and show that the resulting multivariate multiscale cosine similarity entropy (MMCSE) is capable of quantifying structural complexity through the degree of self-correlation within signals. The proposed approach relaxes the prohibitive constraints between the embedding dimension and data length, and aims to quantify the structural complexity based on the degree of self-correlation at low scales. The proposed MMCSE is applied to the examination of the complex and quaternion circularity properties of signals with varying correlation behaviors, and simulations show the MMCSE outperforming the standard methods, MMSE and MMFE.

Identification of T Cell Epitopes in the Spike Glycoprotein of Severe Acute Respiratory Syndrome Coronavirus 2 in Rhesus Macaques.

The T cell response is an important detection index in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine development. The present study was undertaken to determine the T cell epitopes in the spike (S) protein of SARS-CoV-2 that dominate the T cell responses in SARS-CoV-2-infected patients. PBMCs from rhesus macaques vaccinated with a DNA vaccine encoding the full-length S protein were isolated, and an ELISPOT assay was used to identify the recognized T cell epitopes among a total of 158 18-mer and 10-aa-overlapping peptides spanning the full-length S protein. Six multipeptide-based epitopes located in the S1 region, with four of the six located in the receptor-binding domain, were defined as the most frequently recognized epitopes in macaques. The conservation of the epitopes across species was also verified, and peptide mixtures for T cell response detection were established. Six newly defined T cell epitopes were found in the current study, which may provide a novel potential target for T cell response detection and the diagnosis and vaccine design of SARS-CoV-2 based on multipeptide subunit-based epitopes.

A novel DNA and protein combination COVID-19 vaccine formulation provides full protection against SARS-CoV-2 in rhesus macaques.

The current study aims to develop a safe and highly immunogenic COVID-19 vaccine. The novel combination of a DNA vaccine encoding the full-length Spike (S) protein of SARS-CoV-2 and a recombinant S1 protein vaccine induced high level neutralizing antibody and T cell immune responses in both small and large animal models. More significantly, the co-delivery of DNA and protein components at the same time elicited full protection against intratracheal challenge of SARS-CoV-2 viruses in immunized rhesus macaques. As both DNA and protein vaccines have been proven safe in previous human studies, and DNA vaccines are capable of eliciting germinal center B cell development, which is critical for high-affinity memory B cell responses, the DNA and protein co-delivery vaccine approach has great potential to serve as a safe and effective approach to develop COVID-19 vaccines that provide long-term protection.

Variational Embedding Multiscale Sample Entropy: A Tool for Complexity Analysis of Multichannel Systems.

Entropy-based methods have received considerable attention in the quantification of structural complexity of real-world systems. Among numerous empirical entropy algorithms, conditional entropy-based methods such as sample entropy, which are associated with amplitude distance calculation, are quite intuitive to interpret but require excessive data lengths for meaningful evaluation at large scales. To address this issue, we propose the variational embedding multiscale sample entropy (veMSE) method and conclusively demonstrate its ability to operate robustly, even with several times shorter data than the existing conditional entropy-based methods. The analysis reveals that veMSE also exhibits other desirable properties, such as the robustness to the variation in embedding dimension and noise resilience. For rigor, unlike the existing multivariate methods, the proposed veMSE assigns a different embedding dimension to every data channel, which makes its operation independent of channel permutation. The veMSE is tested on both stimulated and real world signals, and its performance is evaluated against the existing multivariate multiscale sample entropy methods. The proposed veMSE is also shown to exhibit computational advantages over the existing amplitude distance-based entropy methods.

Characteristics of the tree shrew humoral immune system.

Preclinical studies require an immune response similar to that of humans in a small animal model that is convenient to operate. Based on genome alignment, tree shrews are small animals considered to be more similar to primates than are rodents, and many human disease models have been established with tree shrews. However, the characteristics of the humoral immune response of tree shrews remain to be elucidated. In this study, the genetic sequence of the heavy chain constant region of tree shrew immunoglobulin (Ig) was complemented, and the results of immunoglobulin domain homology and transcriptome analysis showed that the tree shrew genome encodes only four classes of antibodies and does not encode IgD. The oldest IgM antibody has the highest homology with primates. After the complete sequence of each type of antibody was obtained, the tree shrew antibody protein was further expressed and purified by in vitro recombination, and an IgG quantitative evaluation system was established. The highly effective immuno protective effect induced by HSV-1 infection and the significant bactericidal effect induced by Neisseria meningitidis group C polysaccharide immunization showed that tree shrews exhibited immune responses more similar to humans than to mice. This may provide better predictive value for vaccine preclinical research.

CRISPR-Cas9 system-driven site-specific selection pressure on Herpes simplex virus genomes.

The CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9) system has been widely used for viral genome editing, transcription regulation and chromosomal localization in eukaryotic cells. In this study, a guide RNA (gRNA) that specifically recognizes HSV-1 viral genomes was used in the CRISPR-Cas9 system to inhibit viral replication. This inhibition could be achieved with both wild type Cas9 protein and Cas9 nickase (D10A). By targeting viral genomes containing sequences recognized by the gRNA, the CRISPR-Cas9 system distinguished between different viral genome sequences and provided single nucleotide-specific selection pressure to significantly change the proportions of viruses in a mixed viral pool. This finding indicates the utility of this tool for virus selection without the need for antibiotics or reporter genes, which could potentially save time compared to other methods used for screening and purifying mutant viruses.