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PubMed1993

A recombinant immunotoxin containing a disulfide-stabilized Fv fragment.

B3(dsFv)-PE38KDEL is a recombinant immunotoxin composed of the Fv region of monoclonal antibody B3 connected to a truncated form of Pseudomonas exotoxin (PE38KDEL), in which the unstable Fv heterodimer (composed of heavy- and light-chain variable regions) is held together and stabilized by a disulfide bond [termed disulfide-stabilized Fv (dsFV)]. A computer modeled structure of the B3(Fv), made by mutating and energy minimizing the amino acid sequence and structure of McPC603, enabled us to identify positions in conserved framework regions that "hypothetically" could be used for disulfide stabilization without changing the structure or affecting antigen binding. This prediction was evaluated experimentally by constructing a disulfide-linked two-chain dsFv-immunotoxin that was produced in Escherichia coli. The activity and specificity of this immunotoxin was indistinguishable from its single-chain Fv (scFv) counterpart, indicating that, as in B3(scFv), the structure of the binding region is retained in B3(dsFv). Because we introduced the stabilizing disulfide bond in between two framework residues in a position that is conserved in most Fv molecules, this method of linkage between the heavy- and light-chain variable regions should be generally applicable to construct immunotoxins and dsFv molecules using other antibodies. Furthermore, the finding that B3(dsFv) was much more stable at 37 degrees C in human plasma than B3(scFv) indicates that dsFvs are possibly more versatile for therapeutic application than scFvs.

ADP Ribose Transferases↗
PubMed1992

Numerical comparisons of two formulations of the logistic regressive models with the mixed model in segregation analysis of discrete traits.

Segregation analysis of discrete traits can be conducted by the classical mixed model and the recently introduced regressive models. The mixed model assumes an underlying liability to the disease, to which a major gene, a multifactorial component, and random environment contribute independently. Affected persons have a liability exceeding a threshold. The regressive logistic models assume that the logarithm of the odds of being affected is a linear function of major genotype effects, the phenotypes of older relatives, and other covariates. A formulation of the regressive models, based on an underlying liability model, has been recently proposed. The regression coefficients on antecedents are expressed in terms of the relevant familial correlations and a one-to-one correspondence with the parameters of the mixed model can thus be established. Computer simulations are conducted to evaluate the fit of the two formulations of the regressive models to the mixed model on nuclear families. The two forms of the class D regressive model provide a good fit to a generated mixed model, in terms of both hypothesis testing and parameter estimation. The simpler class A regressive model, which assumes that the outcomes of children depend solely on the outcomes of parents, is not robust against a sib-sib correlation exceeding that specified by the model, emphasizing testing class A against class D. The studies reported here show that if the true state of nature is that described by the mixed model, then a regressive model will do just as well. Moreover, the regressive models, allowing for more patterns of family dependence, provide a flexible framework to understand gene-environment interactions in complex diseases.

Computer Simulation↗
PubMed2000

Type II pneumocytes are preferentially located along thick elastic fibers forming the framework of human alveoli.

Type II pneumocytes were found to be preferentially located on thick elastic fibers which formed the main structural framework of the alveoli in humans. Eight lobes resected from eight patients with adenocarcinoma or atypical adenomatous hyperplasia and two lobes from two necropsies were examined. Four small specimens of normal lung tissue were obtained from each lobe fixed in a buffered formalin. Thick sections (200-300 microm) were stained with hematoxylin to contrast nuclei or with elastica staining to demonstrate elastic fibers and immunostained with an antibody against Thomsen-Friedenreich antigen after pretreatment with sialidase to visualize type II pneumocytes. Alveolar structure and the distribution of type II pneumocytes were examined in 3D reconstructions generated using a standard microscope, a personal computer and NIH-Image software. Nuclei including those of type I and type II pneumocytes and endothelial cells were distributed diffusely throughout the alveolar wall. Thick elastic fibers constructed the main structural framework of the alveoli and formed the sides of the polygonal alveoli. Type II pneumocytes were found to be linearly located along these thick elastic fibers. This previously undisclosed distribution of type II pneumocytes may be concerned with alveolar rapid movement.

Adult↗
PubMed2006

Testing the potential for computational chemistry to quantify biophysical properties of the non-proteinaceous amino acids.

Although most proteins of most living organisms are constructed from the same set of 20 amino acids, all indications are that this standard alphabet represents a mere subset of what was available to life during early evolution. However, we currently lack an appropriate quantitative framework with which to test the qualitative hypotheses that have been offered to date as explanations for nature's "choices." Specifically, although many indices have been developed to describe the 20 standard amino acids, few or no comparable data extend to prebiotically plausible alternatives because of the costly and time-consuming bench experiments that would be required. Computational chemistry (specifically quantitative structure property relationship methods) offers a potentially fast, cost-effective remedy for this knowledge gap by predicting such molecular properties in silico. Thus, we investigated the use of various freely accessible programs to predict three key amino acid properties (hydrophobicity, charge, and size). We assessed the accuracy of these predictions by comparisons with experimentally determined counterparts for appropriate test data sets. In light of these results, and factors of software accessibility and transparency, we suggest a method for further computational assessments of prebiotically plausible amino acids. The results serve as a starting point for future quantitative analysis of amino acid alphabet evolution.

Amino Acids↗
PubMed2003

Inference and computation with population codes.

In the vertebrate nervous system, sensory stimuli are typically encoded through the concerted activity of large populations of neurons. Classically, these patterns of activity have been treated as encoding the value of the stimulus (e.g., the orientation of a contour), and computation has been formalized in terms of function approximation. More recently, there have been several suggestions that neural computation is akin to a Bayesian inference process, with population activity patterns representing uncertainty about stimuli in the form of probability distributions (e.g., the probability density function over the orientation of a contour). This paper reviews both approaches, with a particular emphasis on the latter, which we see as a very promising framework for future modeling and experimental work.

Animals↗
PubMed2002

Technique analysis in sports: a critical review.

This paper critically reviews technique analysis as an analytical method used within sports biomechanics as a part of performance analysis. The concept of technique as 'a specific sequence of movements' appears to be well established in the literature, but the concept of technique analysis is less well developed. Although several descriptive and analytical goals for technique analysis can be identified, the main justification given for its use is to aid in the improvement of performance. However, the conceptual framework underpinning this process is poorly developed with a lack of distinction between technique and performance. The methods of technique analysis have been divided into qualitative, quantitative and predictive components. Qualitative technique analysis is characterized by observation and subjective judgement. Several aids to observation are identified, including phase analysis, temporal analysis and critical feature analysis. Although biomechanical principles of movement can be used to form judgements about technique, little agreement exists about the number and categories of these principles. A 'deterministic' model can be used to identify factors that affect performance but, in doing so, technique variables are frequently overlooked. Quantitative technique analysis relies on biomechanical data collection methods. The identification of key technique variables that affect performance is a major issue, but these are poorly distinguished from other variables that affect performance. Quantitative analysis is not suitable for establishing the characteristics of the whole skill, but new methods, such as the use of artificial neural networks, are described that may be able to overcome this limitation. Other methods based on modelling and computer simulation also have potential for focusing on the whole skill. Predictive technique analysis encompasses these developments and offers an attractive interface between the scientist and coach through visual animation methods. I conclude that biomechanists need to clarify the underpinning rationale, framework and scope for the various approaches to technique analysis.

Biomechanical Phenomena↗
PubMed2003

A thermodynamic framework for the magnesium-dependent folding of RNA.

The goal of this review is to present a unified picture of the relationship between ion binding and RNA folding based on recent theoretical and computational advances. In particular, we present a model describing how the association of magnesium ions is coupled to the tertiary structure folding of several well-characterized RNA molecules. This model is developed in terms of the nonlinear Poisson-Boltzmann (NLPB) equation, which provides a rigorous electrostatic description of the interaction between Mg(2+) and specific RNA structures. In our description, most of the ions surrounding an RNA behave as a thermally fluctuating ensemble distributed according to a Boltzmann weighted average of the mean electrostatic potential around the RNA. In some cases, however, individual ions near the RNA may shed some of their surrounding waters to optimize their Coulombic interactions with the negatively charged ligands on the RNA. These chelated ions are energetically distinct from the surrounding ensemble and must be treated explicitly. This model is used to explore several different RNA systems that interact differently with Mg(2+). In each case, the NLPB equation accurately describes the stoichiometric and energetic linkage between Mg(2+) binding and RNA folding without requiring any fitted parameters in the calculation. Based on this model, we present a physical description of how Mg(2+) binds and stabilizes specific RNA structures to promote the folding reaction.

Binding Sites↗
PubMedDate not supplied

[Quantitative changes in the ultrastructural elements of presynapses exposed to low-intensity laser radiation within the framework of a factorial model].

The ultrastructure elements of presynaptic terminals (PT) in a dorsal horn of cat spinal cord were studied morphometrically in norm and after helium-neon laser irradiation. The disperse computer analysis showed changes in a median terminal radius, the number and localization of synaptic vesicles, and no changes in the shape and length of the plasmalemma profile of the irradiated PT.

Animals↗
PubMed2026

Comparative Genomics-Guided Epitope Prioritization and in Silico Design of a Multi-Epitope DNA Vaccine Candidate Against Megalocytivirus pagrus 1.

Megalocytivirus pagrus 1 infection is a World Organisation for Animal Health-listed aquatic animal disease caused by a virus species comprising the RSIV, ISKNV, and TRBIV genogroups. Here, we integrated comparative genomics and immunoinformatics to prioritize a multi-epitope protein construct, pMEV, and to design a DNA vaccine candidate encoding it, with emphasis on RSIV-type infection relevant to rock bream aquaculture. Analysis of 61 complete genomes identified 28 core gene clusters, from which myristoylated membrane protein (MMP) and major capsid protein (MCP) were prioritized as source antigens for epitope screening. Four cytotoxic T-cell, five helper T-cell, and five linear B-cell epitope candidates were selected based on sequence-based screening and exploratory peptide-MHC docking. The selected epitopes were assembled with rock bream beta-defensin-3, PADRE, and peptide linkers to generate the 283-aa pMEV construct. Sequence-based physicochemical analyses indicated properties relevant to subsequent structural and expression-based evaluation, while computationally refined structural modeling identified nine putative conformational B-cell epitope regions. TLR3 docking, normal mode analysis, and a 200-ns molecular dynamics simulation characterized the structural behavior of the selected computational complex without inferring receptor activation. C-ImmSim further generated model-dependent generic humoral and helper T-cell-associated response patterns within a mammalian-based simulation framework. Finally, the pMEV coding sequence was codon-optimized and incorporated into an in silico pcDNA3.1(+)-based DNA vaccine design. Collectively, this study provides a comparative genomics-guided framework for prioritizing an experimentally testable multi-epitope DNA vaccine candidate against M. pagrus 1, while construct expression, immunogenicity, and protective efficacy remain to be evaluated experimentally.

Animals↗
PubMed2002

Empirical evaluation of a dynamic experiment design method for prediction of MHC class I-binding peptides.

The ability to predict MHC-binding peptides remains limited despite ever expanding demands for specific immunotherapy against cancers, infectious diseases, and autoimmune disorders. Previous analyses revealed position-specific preference of amino acids but failed to detect sequence patterns. Efforts to use computational analysis to identify sequence patterns have been hampered by the insufficiency of the number/quality of the peptide binding data. We propose here a dynamic experiment design to search for sequence patterns that are common to the MHC class I-binding peptides. The method is based on a committee-based framework of query learning using hidden Markov models as its component algorithm. It enables a comprehensive search of a large variety (20(9)) of peptides with a small number of experiments. The learning was conducted in seven rounds of feedback loops, in which our computational method was used to determine the next set of peptides to be analyzed based on the results of the earlier iterations. After these training cycles, the algorithm enabled a real number prediction of MHC binding peptides with an accuracy surpassing that of the hitherto best performing positional scanning method.

Algorithms↗
PubMed2002

Mechanisms underlying tissue selectivity of anandamide and other vanilloid receptor agonists.

Anandamide acts as a full vanilloid receptor agonist in many bioassay systems, but it is a weak activator of primary afferents in the airways. To address this discrepancy, we compared the effect of different vanilloid receptor agonists in isolated airways and mesenteric arteries of guinea pig using preparations containing different phenotypes of the capsaicin-sensitive sensory nerve. We found that anandamide is a powerful vasodilator of mesenteric arteries but a weak constrictor of main bronchi. These effects of anandamide are mediated by vanilloid receptors on primary afferents and do not involve cannabinoid receptors. Anandamide also contracts isolated lung strips, an effect caused by the hydrolysis of anandamide and subsequent formation of cyclooxygenase products. Although capsaicin is equally potent in bronchi and mesenteric arteries, anandamide, resiniferatoxin, and particularly olvanil are significantly less potent in bronchi. Competition experiments with the vanilloid receptor antagonist capsazepine did not provide evidence of vanilloid receptor heterogeneity. Arachidonoyl-5-methoxytryptamine (VDM13), an inhibitor of the anandamide membrane transporter, attenuates responses to olvanil and anandamide, but not capsaicin and resiniferatoxin, in mesenteric arteries. VDM13 did not affect responses to these agonists in bronchi, suggesting that the anandamide membrane transporter is absent in this phenotype of the sensory nerve. Computer simulations using an operational model of agonism were consistent, with differences in intrinsic efficacy and receptor content being responsible for the remaining differences in agonist potency between the tissues. This study describes differences between vanilloid receptor agonists regarding tissue selectivity and provides a conceptual framework for developing tissue-selective vanilloid receptor agonists devoid of bronchoconstrictor activity.

Animals↗
PubMed2003

Identification of metaphors for virtual environment training systems.

The objective of this effort was to develop potential metaphors for assisting wayfinding and navigation in current virtual environment (VE) training systems. Although VE purports a number of advantages over traditional, full-scale simulator training devices (deployability, footprint, cost, maintainability, scalability, networking), little design guidance exists beyond individual instantiations with specific platforms. A review of metaphors commonly incorporated into human-computer interactive systems indicated that existing metaphors have largely been used as orientation aids, mainly in the form of guided navigational assistance, with some position guidance. Advanced metaphor design concepts were identified that would not only provide trainees with a useful orienting framework but also enhance visual access and help differentiate an environment. The effectiveness of these concepts to aid navigation and wayfinding in VEs must be empirically validated.

Computer Simulation↗
PubMed2000

The human adult skeletal muscle transcriptional profile reconstructed by a novel computational approach.

By applying a novel software tool, information on 4080 UniGene clusters was retrieved from three adult human skeletal muscle cDNA libraries, which were selected for being neither normalized nor subtracted. Reconstruction of a transcriptional profile of the corresponding tissue was attempted by a computational approach, classifying each transcript according to its level of expression. About 25% of the transcripts accounted for about 80% of the detected transcriptional activity, whereas most genes showed a low level of expression. This in silico transcriptional profile was then compared with data obtained by a SAGE study. A fairly good agreement between the two methods was observed. About 400 genes, highly expressed in skeletal muscle or putatively skeletal muscle-specific, may represent the minimal set of genes needed to determine the tissue specificity. These genes could be used as a convenient reference to monitor major changes in the transcriptional profile of adult human skeletal muscle in response to different physiological or pathological conditions, thus providing a framework for designing DNA microarrays and initiating biological studies.

Adult↗
PubMed1991

Antibodies in passive immunization studies: characteristics and consequences.

Antibodies to neuropeptides or hormones are frequently used in passive immunization studies to unravel their physiological role in signal transfer. In such in vivo experiments antibodies are considered to bind and thereby to biologically inactivate the endogenous substance during its journey from its site of secretion to its site of action (signalling time). However, little is known about the mechanism of action and characteristics of antibodies that determine such biological activity. Since the signalling time in neuronal and hormonal communication is short, the kinetics of antibody binding is an important feature. Here, we present a theoretical framework to describe antibody binding kinetics which can contribute to the design of passive immunization protocols. The specific effects of variation in antibody concentration, dissociation constant, and on-rate constant on these binding kinetics are demonstrated. Simple methods are described to determine these parameters, which may guide the selection of antibodies for passive immunization studies. When time is limited, the on-rate constant and the local antibody concentration are the most important determinants. Several points are illustrated for CRF signal transfer in the rat. CRF signalling time in the hypothalamo-pituitary complex, as established from dye transport experiments, was 3-7 sec. Based on parameters measured for a rat monoclonal antibody to CRF (PFU 83), we computed that half-maximal and full blockades of ether-induced ACTH secretion were associated with approximately 85% and more than 99% binding of CRF, respectively. From the theoretical framework presented in this study we conclude that, in general, the kinetics of antigen binding are sufficiently fast for antibodies to interfere with hormonal and probably nonsynaptic neuronal signal transfer. However, interference with fast signalling processes (less than 10 msec), which may occur in the brain, is unlikely.

Animals↗
PubMed2026

REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.

SUMMARY: We introduce REACTOR, a computational tool designed to detect differential activity of transcriptional regulators and their target genes (regulons) in single-cell RNA-sequencing data. It expands the currently available framework for regulon analysis by introducing a robust statistical test to detect differential regulon activity between conditions, such as disease versus control, with multiple replicates. By contrasting different conditions, REACTOR enables identification of key condition- and cell type-specific regulons. To demonstrate the use of REACTOR, we illustrate its performance in a publicly available COVID-19 dataset. AVAILABILITY: REACTOR R-package together with an implementation vignette are available at https://www.github.com/elolab/REACTOR.

Regulon↗
PubMed2003

Physician leadership: influence on practice-based learning and improvement.

In response to the technology and information explosion, practice-based learning and improvement is emerging within the medical field to deliver systematic practice-linked improvements. However, its emergence has been inhibited by the slow acceptance of evidence-based medicine among physicians, who are reluctant to embrace proven high-performance leadership principles long established in other high-risk fields. This reluctance may be attributable to traditional medical training, which encourages controlling leadership styles that magnify the resistance common to all change efforts. To overcome this resistance, physicians must develop the same leadership skills that have proven to be critical to success in other service and high-performance industries. Skills such as self-awareness, shared authority, conflict resolution, and nonpunitive critique can emerge in practice only if they are taught. A dramatic shift away from control and blame has become a requirement for achieving success in other industries based on complex group process. This approach is so mainstream that the burden of proof that cooperative leadership is not a requirement for medical improvement falls to those institutions perpetuating the outmoded paradigm of the past. Cooperative leadership skills that have proven central to implementing change in the information era are suggested as a core cultural support for practice-based learning and improvement. Complex adaptive systems theory, long used as a way to understand evolutionary biology, and more recently computer science and economics, predicts that behavior emerging among some groups of providers will be selected for duplication by the competitive environment. A curriculum framework needed to teach leadership skills to expand the influence of practice-based learning and improvement is offered as a guide to accelerate change.

Delivery of Health Care↗
PubMed1990

Fatty acids on the A/Japan/305/57 influenza virus hemagglutinin have a role in membrane fusion.

The covalent attachment of fatty acid moieties to proteins is a widespread post-translational modification of viral and cell proteins yet the functional consequences of acylation are not well understood. We have determined that the A/Japan/305/57 influenza virus hemagglutinin (HA) contains three potential acylation sites at cysteine residues 211, 218 and 221 in the cytoplasmic domain of the molecule. Site-directed mutagenesis of one or more of these sites has no effect on biosynthesis, transport or receptor binding activity of the molecule; however, modification of any single site is sufficient to abolish completely or inhibit severely membrane fusion activity, a function essential for virus infectivity. We present a molecular model of the transmembrane and cytoplasmic domains of the HA to illustrate the potential orientation of these fatty acids and to provide a conceptual framework for further experimentation.

Acylation↗
PubMedDate not supplied

Statistical description of microcirculatory flow as measured with an MR method.

Quantification of microcirculatory flow is important for the functional assessment of biologic systems. The authors describe a method of analyzing the dependence of the magnetic resonance (MR) signal intensity on microcirculatory flow. A gel bead phantom was used to simulate the randomly oriented flow capillaries, and the MR signal intensity of the phantom was studied at different flow velocities by using velocity-sensitized and -compensated spin-echo pulse sequences. A theoretical model based on the spin-phase phenomenon is proposed to elucidate the effect of flow on signal intensity. The velocity phase of a spin depends on its path and the corresponding velocity-encoding gradients. A Monte Carlo simulation was used to generate the path of a spin on the basis of a statistical model for flow through a random capillary network. From the velocity-phase distribution of a group of spins within a voxel, the signal attenuation due to flow can be calculated. The results of the statistical model and experimental measurements agreed well. Also, T1 and T2 effects in MR flow measurements were investigated. The current study provides a theoretical framework for understanding MR measurements of microcirculatory flow.

Blood Flow Velocity↗