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PubMed2026

A Multiepitope Intranasal Adenoviral Vaccine Induces Robust Mucosal Immunity and Protection against SARS‑CoV‑2.

BACKGROUND: Vaccination has been central to mitigating the COVID-19 pandemic; however, the continual emergence of SARS-CoV-2 variants of concern (VOCs) has reduced the effectiveness of current intramuscular vaccines that primarily target the Spike (S) protein. Although updated formulations are periodically introduced, there remains a critical need for next-generation vaccine platforms capable of inducing broad, variant-independent protection. Here we evaluate a heterologous intranasal (i.n.) prime-boost vaccination strategy using bovine adenoviral (BAd) and chimpanzee adenoviral (ChAd) vectors expressing the S1 subunit in combination with either full-length membrane (M) and nucleocapsid (N) proteins (Ad-S1 + N + M) or multiepitope constructs derived from M and N (Ad-S1 + Epi/N + Epi/M). The constructs were incorporated with the autophagy-inducing peptide C5 (AIP-C5) to enhance antigen-specific T-cell responses. RESULTS: In BALB/c mice, Ad-S1 + Epi/N + Epi/M vaccination induced robust S1-specific immunity while simultaneously inducing strong N- and M-specific humoral and cellular responses that were comparable to or greater than those induced by Ad-S1 + N + M. All S1-containing formulations generated high neutralizing antibody titers (~ 3.8 log₁₀) against Omicron B.1.1.529 and BA.2.86 variants, although titers against the ancestral Wuhan strain were approximately one log₁₀ lower. In K18-hACE2 mice, i.n. immunization with S1-expressing vectors provided near-complete protection against BA.2.86 challenge, with undetectable lung viral titers and viral genome copies. CONCLUSION: An i.n. multiepitope adenoviral vaccine incorporating conserved SARS-CoV-2 antigens induces robust mucosal, humoral, and cellular immune responses and confers significant protection following SARS-CoV-2 challenge.

Animals↗
PubMed2006

Human rhinovirus induces robust IP-10 release by monocytic cells, which is independent of viral replication but linked to type I interferon receptor ligation and STAT1 activation.

Human rhinovirus (HRV)-induced respiratory infections are associated with elevated levels of IFN-gamma-inducible protein 10 (IP-10), which is an enhancer of T lymphocyte chemotaxis and correlates with symptom severity and T lymphocyte number. Increased IP-10 expression is exhibited by airway epithelial cells following ex vivo HRV challenge and requires intracellular viral replication; however, there are conflicting reports regarding the necessity of type I IFN receptor ligation for IP-10 expression. Furthermore, the involvement of resident airway immune cells, predominantly bronchoalveolar macrophages, in contributing to HRV-stimulated IP-10 elaboration remains unclear. In this regard, our findings demonstrate that ex vivo exposure of human peripheral blood monocytes and bronchoalveolar macrophages (monocytic cells) to native or replication-defective HRV serotype 16 (HRV16) resulted in similarly robust levels of IP-10 release, which occurred in a time- and dose-dependent manner. Furthermore, HRV16 induced a significant increase in type I IFN (IFN-alpha) release and STAT1 phosphorylation in monocytes. Neutralization of the type I IFN receptor and inhibition of JAK or p38 kinase activity strongly attenuated HRV16-stimulated STAT1 phosphorylation and IP-10 release. Thus, this work supports a model, wherein HRV16-induced IP-10 release by monocytic cells is modulated via autocrine/paracrine action of type I IFNs and subsequent JAK/STAT pathway activity. Our findings demonstrating robust activation of monocytic cells in response to native and/or replication-defective HRV16 challenge represent the first evidence indicating a mechanistic disparity in the activation of macrophages when compared with epithelial cells and suggest that macrophages likely contribute to cytokine elaboration following HRV challenge in vivo.

Cell Communication↗
PubMed2000

Pramlintide injection drug product robustness studies.

The article examines the effects of temperature excursions and actual dose withdrawal on the quality of pramlintide injection, a multidose liquid parenteral formulation. Studies were designed to demonstrate product robustness under conditions that may occur during patient use. Pramlintide %Purity was determined by two high-performance liquid chromatography (HPLC) methods, a reversed-phase (RP-HPLC) and a strong-cation exchange (SCX-HPLC) method. A second RP-HPLC method was used to determine pramlintide potency and the concentration of the m-cresol preservative. Antimicrobial preservative effectiveness testing was per USP and European Pharmacopeia (Ph. Eur.). Short-term stability studies were undertaken to probe the effects of the following conditions: 5 degrees C to 40 degrees C and 5 degrees C to -20 degrees C temperature cycling over 10 days; once daily or four-times daily dose withdrawal over 12 or 42 days; and combined 30 degrees C storage and four-times daily dose withdrawal over 42 days. In all cases, pramlintide %Purity and potency values remained essentially unchanged or unchanged relative to controls. Similarly, product appearance, and m-cresol concentration and preservative effectiveness were not significantly affected by the stress conditions used in the 5 studies. Pramlintide injection drug product is extremely robust to challenging stress conditions that may occur during patient use of this multidose product for chronic administration.

Amyloid↗
PubMed1997

Measuring the angle of attack of beating insect wings: robust three-dimensional reconstruction from two-dimensional images

A robust technique for determining the angle of attack of insect wings from film of free flight has to date proved elusive. This report describes the development of two new methods ­ the Strips and Planes techniques ­ which were designed to overcome some of the limitations experienced in previous studies. The accuracy and robustness of these novel methods were tested extensively using simulated hawkmoth wing outlines generated for a realistic range of wing positions and torsion. The results were compared with those from two existing methods ­ the Symmetry and Landmarks procedures. The performance of the latter technique will be strongly species-dependent; it could not be successfully applied to hawkmoth flight because of practical difficulties in obtaining suitable landmarks. The Planes method was the least successful of the remaining techniques, especially during those phases of the wingbeat when the orientations of the two wings relative to the camera viewpoint were similar. The Symmetry and Strips methods were tested further to investigate the effects on their performance of introducing additional camber or wing motion asymmetry. The results showed clearly that the Strips method should be the technique of choice wherever the axis of wing torsion is close to the longitudinal axis of the wing. The procedure involves the experimenter matching a model wing divided into chordwise strips to the true wing outline digitized from high-speed film. The use of strips rather than the points digitized in previous studies meant that the analysis required only one wing outline to be digitized. Symmetry of motion between the left and right wings is not assumed. The implications of requiring human input to the Strips method, as opposed to the strictly numerical algorithms of the alternative techniques, are discussed. It is argued that the added flexibility that this provides in dealing with images which have typically been recorded in suboptimal conditions outweighs the introduction of an element of subjectivity. Additional observations arising from the use of the Strips analysis with high-speed video sequences of hawkmoth flight are given.

Journal Article↗
PubMed2006

Robustness of cascade pH and dissolved oxygen control in symbiotic nisin production process system of Lactococcus lactis and Kluyveromyces marxianus.

In symbiotic processes, different organisms coexist stably and interact by sharing the same metabolites and environmental conditions. The robustness of a symbiotic nisin production process system composed of the lactic acid bacterium Lactococcus lactis subsp. lactis (ATCC11454) and dairy yeast Kluyveromyces marxianus (MS1) was studied. It was found that this symbiotic process system was robust to the initial disturbance in the inoculum sizes of both microorganisms and pH.

Biotechnology↗
PubMed2000

An examination of the robustness of the empirical Bayes and other approaches for testing main and interaction effects in repeated measures designs.

In a previous paper, Boik presented an empirical Bayes (EB) approach to the analysis of repeated measurements. The EB approach is a blend of the conventional univariate and multivariate approaches. Specifically, in the EB approach, the underlying covariance matrix is estimated by a weighted sum of the univariate and multivariate estimators. In addition to demonstrating that his approach controls test size and frequently is more powerful than either the epsilon-adjusted univariate or multivariate approaches, Boik showed how conventional multivariate software can be used to conduct EB analyses. Our investigation examined the Type I error properties of the EB approach when its derivational assumptions were not satisfied as well as when other factors known to affect the conventional tests of significance were varied. For comparative purposes we also investigated procedures presented by Huynh and by Keselman, Carriere, and Lix, procedures designed for non-spherical data and covariance heterogeneity, as well as an adjusted univariate and multivariate test statistic. Our results indicate that when the response variable is normally distributed and group sizes are equal, the EB approach was robust to violations of its derivational assumptions and therefore is recommended due to the power findings reported by Boik. However, we also found that both the EB approach and the adjusted univariate and multivariate procedures were prone to depressed or elevated rates of Type I error when data were non-normally distributed and covariance matrices and group sizes were either positively or negatively paired with one another. On the other hand, the Huynh and Keselman et al. procedures were generally robust to these same pairings of covariance matrices and group sizes.

Bayes Theorem↗
PubMed2000

Dogs as catalysts for social interactions: robustness of the effect.

It is known that pet dogs can act as catalysts for human social interactions, and it has been suggested that this may enhance feelings of well-being. Two studies were carried out to establish the robustness of this effect. In Study 1, a highly trained dog was used to ensure that the dog itself did not solicit attention from passers-by, and data were collected across a range of normal daily activities in which a dog could be included, not confined to conventional dog walking areas as in previous studies. Being accompanied by a dog increased the frequency of social interactions, especially interactions with strangers. In Study 2, also using a trained dog, a different (male) participant observer was dressed either smartly or scruffily. Although there were significantly more interactions when he was smartly dressed, the greatest effect was between the Dog present and No Dog conditions irrespective of the handler's dress. It is concluded that the social catalysis effect is very robust, which opens the way for investigating possible consequences of the effect for well-being and health.

Adult↗
PubMed2005

Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.

Robustness of the recently proposed "pseudo open-loop control" algorithm against various system errors has been investigated for the representative example of the Gemini-South 8-m telescope multiconjugate adaptive-optics system. The existing model to represent the adaptive-optics system with pseudo open-loop control has been modified to account for misalignments, noise and calibration errors in deformable mirrors, and wave-front sensors. Comparison with the conventional least-squares control model has been done. We show with the aid of both transfer-function pole-placement analysis and Monte Carlo simulations that POLC remains remarkably stable and robust against very large levels of system errors and outperforms in this respect least-squares control. Approximate stability margins as well as performance metrics such as Strehl ratios and rms wave-front residuals averaged over a 1-arc min field of view have been computed for different types and levels of system errors to quantify the expected performance degradation.

Journal Article↗
PubMed2006

Second-order robust regularization cost function for detecting and reconstructing phase discontinuities.

We propose a robust method for computing discontinuous phase maps from a fringe pattern with carrier frequency. Our algorithm is based on the minimization of an edge-preserving regularized cost function, specifically, on a robust regularized potential that uses a paradigm called the plate with adaptive rest condition, i.e., a second-order edge-preserving potential. Given that the proposed cost function is not convex, our method uses as its initial point an overly smoothed phase computed with a standard fringe analysis method and then reconstructs the phase discontinuities. Although the method is general purpose, it is introduced in the context of interferometric gauge-block calibration. The performance of the algorithm is demonstrated by numerical experiments with both synthetic and real data.

Journal Article↗
PubMed1994

Robust physics-based analysis of thermal and visual imagery.

Extensions to an existing physics-based approach for intersensory perception in which thermal and visual imagery of outdoor scenes is analyzed simultaneously for object recognition are discussed. The existing approach uses a model that is based on the principle of the conservation of energy at the surface of the imaged object. The model permits the computation of physically meaningful features that may be used for object classification. Two significant extensions are discussed. First, the model is used to analyze a temporal sequence of spatially registered thermal and visual imagery. Second, the energy-exchange model is used to formulate a linear-regression task in which the physical properties of the imaged object are the unknown parameters that are estimated. A statistically robust scheme is presented for this task. The robust technique minimizes sensitivity to outliers caused by segmentation errors and misregistration, which are endemic to multisensor fusion. Thus reliable physics-based features are made available by this approach.

Hot Temperature↗
PubMed2001

Robust fringe density and direction estimation in noisy phase maps.

A method for automated fringe analysis is presented. It robustly estimates local fringe density and direction in noisy wrapped phase maps. Such information can be used to improve the performance of two-dimensional phase unwrapping methods, to construct phase-jump-preserving filtering strategies, and also to perform robust segmentation of phase data. The method, which is highly insensitive to noise, is model based and performs the estimation in the Fourier domain.

Journal Article↗
PubMed2001

Robust structure from motion estimation using inertial data.

The utility of using inertial data for the structure-from-motion (SfM) problem is addressed. We show how inertial data can be used for improved noise resistance, reduction of inherent ambiguities, and handling of mixed-domain sequences. We also show that the number of feature points needed for accurate and robust SfM estimation can be significantly reduced when inertial data are employed. Cramér-Rao lower bounds are computed to quantify the improvements in estimating motion parameters. A robust extended-Kalman-filter-based SfM algorithm using inertial data is then developed to fully exploit the inertial information. This algorithm has been tested by using synthetic and real image sequences, and the results show the efficacy of using inertial data for the SfM problem.

Journal Article↗
PubMed2005

Robust phase demodulation of interferograms with open or closed fringes.

We present two robust algorithms for fringe pattern analysis with partial-field and closed fringes. The algorithm for partial-field fringe patterns is presented as a refinement method for precomputed coarse phases. Such an algorithm consists of the minimization of a regularized cost function that incorporates an outlier rejection strategy, which causes the algorithm to become robust. On the basis of the phase refinement method, we propose a propagative scheme for phase retrieval from closed-fringe interferograms. The algorithm performance is demonstrated by demodulating closed-fringe interferograms with complex spatial distribution of stationary points and gradients in the illumination components.

Journal Article↗
PubMed2025

A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data.

Transfer learning aims to integrate useful information from multi-source datasets to improve the learning performance of target data. This can be effectively applied in genomics when we learn the gene associations in a target tissue, and data from other tissues can be integrated. However, heavy-tail distribution and outliers are common in genomics data, which poses challenges to the effectiveness of current transfer learning approaches. In this paper, we study the transfer learning problem under high-dimensional linear models with t-distributed error (Trans-PtLR), which aims to improve the estimation and prediction of target data by borrowing information from useful source data and offering robustness to accommodate complex data with heavy tails and outliers. In the oracle case with known transferable source datasets, a transfer learning algorithm based on penalized maximum likelihood and expectation-maximization algorithm is established. To avoid including non-informative sources, we propose to select the transferable sources based on cross-validation. Extensive simulation experiments as well as an application demonstrate that Trans-PtLR demonstrates robustness and better performance of estimation and prediction when heavy-tail and outliers exist compared to transfer learning for linear regression model with normal error distribution. Data integration, Variable selection, T distribution, Expectation maximization algorithm, Genotype-Tissue Expression, Cross validation.

Linear Models↗
PubMed2006

In vivo robustness analysis of cell division cycle genes in Saccharomyces cerevisiae.

Intracellular biochemical parameters, such as the expression level of gene products, are considered to be optimized so that a biological system, including the parameters, works effectively. Those parameters should have some permissible range so that the systems have robustness against perturbations, such as noise in gene expression. However, little is known about the permissible range in real cells because there has been no experimental technique to test it. In this study, we developed a genetic screening method, named "genetic tug-of-war" (gTOW) that evaluates upper limit copy numbers of genes in a model eukaryote Saccharomyces cerevisiae, and we applied it for 30 cell-cycle related genes (CDC genes). The experiment provided unique quantitative data that could be used to argue the system-level properties of the cell cycle such as robustness and fragility. The data were used to evaluate the current computational model, and refinements to the model were suggested.

Cell Cycle↗
PubMed2004

Comparing folding codes in simple heteropolymer models of protein evolutionary landscape: robustness of the superfunnel paradigm.

Understanding the evolution of biopolymers is a key element in rationalizing their structures and functions. Simple exact models (SEMs) are well-positioned to address general principles of evolution as they permit the exhaustive enumeration of both sequence and structure (conformational) spaces. The physics-based models of the complete mapping between genotypes and phenotypes afforded by SEMs have proven valuable for gaining insight into how adaptation and selection operate among large collections of sequences and structures. This study compares the properties of evolutionary landscapes of a variety of SEMs to delineate robust predictions and possible model-specific artifacts. Among the models studied, the ruggedness of evolutionary landscape is significantly model-dependent; those derived from more protein-like models appear to be smoother. We found that a common practice of restricting protein structure space to maximally compact lattice conformations results in (i.e., "designs in") many encodable (designable) structures that are not otherwise encodable in the corresponding unrestrained structure space. This discrepancy is especially severe for model potentials that seek to mimic the major role of hydrophobic interactions in protein folding. In general, restricting conformations to be maximally compact leads to larger changes in the model genotype-phenotype mapping than a moderate shifting of reference state energy of the model potential function to allow for more specific encoding via the "designing out" effects of repulsive interactions. Despite these variations, the superfunnel paradigm applies to all SEMs we have tested: For a majority of neutral nets across different models, there exists a funnel-like organization of native stabilities for the sequences in a neutral net encoding for the same structure, and the thermodynamically most stable sequence is also the most robust against mutation.

Biophysics↗
PubMed2004

The population genetic theory of hidden variation and genetic robustness.

One of the most solid generalizations of transmission genetics is that the phenotypic variance of populations carrying a major mutation is increased relative to the wild type. At least some part of this higher variance is genetic and due to release of previously hidden variation. Similarly, stressful environments also lead to the expression of hidden variation. These two observations have been considered as evidence that the wild type has evolved robustness against genetic variation, i.e., genetic canalization. In this article we present a general model for the interaction of a major mutation or a novel environment with the additive genetic basis of a quantitative character under stabilizing selection. We introduce an approximation to the genetic variance in mutation-selection-drift balance that includes the previously used stochastic Gaussian and house-of-cards approximations as limiting cases. We then show that the release of hidden genetic variation is a generic property of models with epistasis or genotype-environment interaction, regardless of whether the wild-type genotype is canalized or not. As a consequence, the additive genetic variance increases upon a change in the environment or the genetic background even if the mutant character state is as robust as the wild-type character. Estimates show that this predicted increase can be considerable, in particular in large populations and if there are conditionally neutral alleles at the loci underlying the trait. A brief review of the relevant literature suggests that the assumptions of this model are likely to be generic for polygenic traits. We conclude that the release of hidden genetic variance due to a major mutation or environmental stress does not demonstrate canalization of the wild-type genotype.

Data Interpretation, Statistical↗
PubMed2005

A comparison of three estimators of the population-scaled recombination rate: accuracy and robustness.

We have performed simulations to assess the performance of three population genetics approximate-likelihood methods in estimating the population-scaled recombination rate from sequence data. We measured performance in two ways: accuracy when the sequence data were simulated according to the (simplistic) standard model underlying the methods and robustness to violations of many different aspects of the standard model. Although we found some differences between the methods, performance tended to be similar for all three methods. Despite the fact that the methods are not robust to violations of the underlying model, our simulations indicate that patterns of relative recombination rates should be inferred reasonably well even if the standard model does not hold. In addition, we assess various techniques for improving the performance of approximate-likelihood methods. In particular we find that the composite-likelihood method of Hudson (2001) can be improved by including log-likelihood contributions only for pairs of sites that are separated by some prespecified distance.

Computer Simulation↗