SARS-CoV-2 is the underlying cause for the COVID-19 pandemic. Like most enveloped RNA viruses, SARS-CoV-2 uses a homotrimeric surface antigen to gain entry into host cells. Here we describe S-Trimer, ...a native-like trimeric subunit vaccine candidate for COVID-19 based on Trimer-Tag technology. Immunization of S-Trimer with either AS03 (oil-in-water emulsion) or CpG 1018 (TLR9 agonist) plus alum adjuvants induced high-level of neutralizing antibodies and Th1-biased cellular immune responses in animal models. Moreover, rhesus macaques immunized with adjuvanted S-Trimer were protected from SARS-CoV-2 challenge compared to vehicle controls, based on clinical observations and reduction of viral loads in lungs. Trimer-Tag may be an important platform technology for scalable production and rapid development of safe and effective subunit vaccines against current and future emerging RNA viruses.
Abstract
Motivation
Immune cells are important components of the immune system and are crucial for disease initiation, progression, prognosis and survival. Although several computational methods have ...been designed for predicting the abundance of immune cells, very few tools are applicable to mouse. Given that, mouse is the most widely used animal model in biomedical research, there is an urgent need to develop a precise algorithm for predicting mouse immune cells.
Results
We developed a tool named Immune Cell Abundance Identifier for mouse (ImmuCellAI-mouse), for estimating the abundance of 36 immune cell (sub)types from gene expression data in a hierarchical strategy of three layers. Reference expression profiles and robust marker gene sets of immune cell types were curated. The abundance of cells in three layers was predicted separately by calculating the ssGSEA enrichment score of the expression deviation profile per cell type. Benchmark results showed high accuracy of ImmuCellAI-mouse in predicting most immune cell types, with correlation coefficients between predicted value and real cell proportion of most cell types being larger than 0.8. We applied ImmuCellAI-mouse to a mouse breast tumor dataset and revealed the dynamic change of immune cell infiltration during treatment, which is consistent with the findings of the original study but with more details. We also constructed an online server for ImmuCellAI-mouse, on which users can upload expression matrices for analysis. ImmuCellAI-mouse will be a useful tool for studying the immune microenvironment, cancer immunology and immunotherapy in mouse models, providing an indispensable supplement for human disease studies.
Availability and implementation
Software is available at http://bioinfo.life.hust.edu.cn/ImmuCellAI-mouse/.
Supplementary information
Supplementary data are available at Bioinformatics online.
Energy loss within organic solar cells (OSCs) is undesirable as it reduces cell efficiency1–4. In particular, non-radiative recombination loss3 and energetic disorder5, which are closely related to ...the tail states below the band edge and the overall photon energy loss, need to be minimized to improve cell performance. Here, we report how the use of a small-molecule acceptor with torsion-free molecular conformation can achieve a very low degree of energetic disorder and mitigate energy loss in OSCs. The resulting single-junction OSC has an energy loss due to non-radiative recombination of just 0.17 eV and a high power conversion efficiency of up to 16.54% (certified as 15.89% by the National Renewable Energy Laboratory). The findings take studies of organic photovoltaics deeper into a new regime, beyond the limits of energetic disorder and large energy offset for charge generation.An organic solar cell designed with minimal energetic disorder exhibits very low energy loss due to non-radiative recombination and highly efficient operation.
An efficient multiwavelet-based time-varying modeling scheme is proposed for time–frequency analysis (TFA) of electroencephalogram (EEG) data. In the new multiwavelet-based parametric modeling ...framework, the time-dependent parameters in the time-varying model are locally represented using a novel multiwavelet decomposition scheme. An effective orthogonal least squares (OLS) algorithm aided by mutual information criterion is then applied for sparse model selection and parameter estimation. The resultant estimation of time-dependent spectral density in the signal can simultaneously achieve a high resolution in both time and frequency, which is a powerful TFA technique for nonstationary biomedical signals including EEG. Two examples, one for an artificial EEG signal and another for a real EEG signal are included to show the effectiveness and applicability of the new proposed approach. Simulation studies and applications to real EEG data elucidate that the proposed wavelet approach is capable of achieving a high time–frequency representation for nonstationary processes.
Irritable bowel syndrome (IBS) is the most common functional bowel disorder worldwide and is associated with visceral hypersensitivity, gut motility, immunomodulation, gut microbiota alterations, and ...dysfunction of the brain-gut axis; however, its pathophysiology remains poorly understood. Gut microbiota and its metabolites are proposed as possible etiological factors of IBS. The aim of our study was to investigate specific types of microbiota-derived metabolites, especially bile acids, short-chain fatty acids, vitamins, amino acids, serotonin and hypoxanthine, which are all implicated in the pathogenesis of IBS. Metabolites-focused research has identified multiple microbial targets relevant to IBS patients, important roles of microbiota-derived metabolites in the development of IBS symptoms have been established. Thus, we provide an overview of gut microbiota and their metabolites on the different subtypes of IBS (constipation-predominant IBS-C, diarrhea-predominant IBS-D) and present controversial views regarding the role of microbiota in IBS.
Abstract
Simulation of the stretch blow molding (SBM) process necessitates to develop a model able to reproduce the material behavior at high strain rate, large deformation with temperature gradient. ...On the other hand, both the need to understand polyethylene terephthalate (PET) material characteristics and the final bottle performance requirements continue to get higher. That necessitates a regular update of the identification of the model. Bottle producers are interested by managing this identification without a specific complex apparatus not available in an industrial context. The work presented here describes an in‐situ adjustment process for upgrading all parameters of a visco‐hyperelastic (VHE) model from a small number of blowing tests that do not necessitate complex equipment. The accuracy of the adjustment process is validated through the ability of the updated VHE model to reproduce the final shape, the pressure evolution and the tension of the rod during an industrial blowing of PET bottles.
Objectives
To investigate the potential of dual-energy computed tomography (DECT) parameters in identifying metastatic cervical lymph nodes in oral squamous cell carcinoma (OSCC) patients and to ...explore the relationships between DECT and pathological features.
Methods
Clinical and DECT data were collected from patients who underwent radical resection of OSCC and cervical lymph node dissection between November 2019 and June 2021. Microvascular density was assessed using the Weidner counting method. The electron density (ED) and effective atomic number (
Z
eff
) in non - contrast phase and iodine concentration (IC), normalized IC, slope of the energy spectrum curve (
λ
HU
), and dual-energy index (DEI) in parenchymal phase were compared between metastatic and non - metastatic lymph nodes. Student’s
t
-test, Pearson’s rank correlation, and receiver operating characteristic curves were performed.
Results
The inclusion criteria were met in 399 lymph nodes from 103 patients. Metastatic nodes (
n
= 158) displayed significantly decreased ED, IC, normalized IC,
λ
HU
, and DEI values compared with non-metastatic nodes (
n
= 241) (all
p
< 0.01). Strong correlations were found between IC (
r
= 0.776), normalized IC (
r
= 0.779),
λ
HU
(
r
= 0.738), DEI (
r
= 0.734), and microvascular density. Area under the curve (AUC) for normalized IC performed the highest (0.875) in diagnosing metastatic nodes. When combined with the width of nodes, AUC increased to 0.918.
Conclusion
DECT parameters IC, normalized IC,
λ
HU
, and DEI reflect pathologic changes in lymph nodes to a certain extent, and aid for detection of metastatic cervical lymph nodes from OSCC.
Key Points
• Electron density, iodine concentration, normalized iodine concentration, λ
HU
, and dual-energy index values showed significant differences between metastatic and non-metastatic nodes.
• Strong correlations were found between iodine concentration, normalized iodine concentration, slope of the spectral Hounsfield unit curve, dual-energy index, and microvascular density.
• DECT qualitative parameters reflect the pathologic changes in lymph nodes to a certain extent, and aid for the detection of metastatic cervical lymph nodes from oral squamous cell carcinoma.
The automatic detection of epileptic seizures from electroencephalography (EEG) signals is crucial for the localization and classification of epileptic seizure activity. However, seizure processes ...are typically dynamic and nonstationary, and thus, distinguishing rhythmic discharges from nonstationary processes is one of the challenging problems. In this paper, an adaptive and localized time-frequency representation in EEG signals is proposed by means of multiscale radial basis functions (MRBF) and a modified particle swarm optimization (MPSO) to improve both time and frequency resolution simultaneously, which is a novel MRBF-MPSO framework of the time-frequency feature extraction for epileptic EEG signals. The dimensionality of extracted features can be greatly reduced by the principle component analysis algorithm before the most discriminative features selected are fed into a support vector machine (SVM) classifier with the radial basis function (RBF) in order to separate epileptic seizure from seizure-free EEG signals. The classification performance of the proposed method has been evaluated by using several state-of-art feature extraction algorithms and other five different classifiers like linear discriminant analysis, and logistic regression. The experimental results indicate that the proposed MRBF-MPSO-SVM classification method outperforms competing techniques in terms of classification accuracy, and shows the effectiveness of the proposed method for classification of seizure epochs and seizure-free epochs.
An anisotropic visco-hyperelastic (VHE) model for polyethylene terephthalate (PET) is used to simulate the stretch blow molding process. The biaxiality needs to be taken into account for an accurate ...identification of the model parameters related to the induced anisotropy. Thanks to the use of a biaxial elongation apparatus developed at MSME, nonequibiaxial tension tests on PET have been managed on optimized specimen in order to provide data complementary to the equibiaxial (EB) tension test. This last enables the correct identification of the temperature and strain rate influence, because both viscous and elastic parts of the model need to test the material in nonequibiaxial (NEB) conditions. The procedure already used for EB tension test is extended to constant width and an intermediate case, NEB cases. The VHE model developed to simulate the PET behavior in the stretch blow molding conditions is identified from these three different biaxial tests: differences and dispersions are discussed. The origin of this dispersion is found out and solved by a modification of the model. This leads to a reduction of the number of parameters in the proposed VHE model.
Luteolin is a flavonoid in a variety of fruits, vegetables, and herbs, which has shown anti-inflammatory, antioxidant, and anti-cancer neuroprotective activities. In this study, we investigated the ...potential beneficial effects of luteolin on memory deficits and neuroinflammation in a triple-transgenic mouse model of Alzheimer's disease (AD) (3 × Tg-AD). The mice were treated with luteolin (20, 40 mg · kg
· d
, ip) for 3 weeks. We showed that luteolin treatment dose-dependently improved spatial learning, ameliorated memory deficits in 3 × Tg-AD mice, accompanied by inhibiting astrocyte overactivation (GFAP) and neuroinflammation (TNF-α, IL-1β, IL-6, NO, COX-2, and iNOS protein), and decreasing the expression of endoplasmic reticulum (ER) stress markers GRP78 and IRE1α in brain tissues. In rat C6 glioma cells, treatment with luteolin (1, 10 µM) dose-dependently inhibited LPS-induced cell proliferation, excessive release of inflammatory cytokines, and increase of ER stress marker GRP78. In conclusion, luteolin is an effective agent in the treatment of learning and memory deficits in 3 × Tg-AD mice, which may be attributable to the inhibition of ER stress in astrocytes and subsequent neuroinflammation. These results provide the experimental basis for further research and development of luteolin as a therapeutic agent for AD.
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