Linking hyperelastic theoretical models and experimental data of vaginal tissue through histological data

Mechanical characterization of living tissues and computer-based simulations related to medical issues, has become increasingly important to improve diagnostic processes and treatments evaluation. This work proposes a link between the mechanical testing and the material model predictions through histological data of vaginal tissue. Histological data was used to link tensile testing experiments with material-dependent parameters; the approach was adequate to capture the nonlinear response of ovine vaginal tissue over a large strain range.The experimental data obtained on a previous study, has two main components: tensile testing and histological analysis of the ovine vaginal tissue. Uniaxial tensile test data and histological data were collected from three sheep groups: virgins, pregnant and parous. The distal part of vaginal wall was selected since it is prone to tears induced by vaginal delivery.The HGO (Holzapfel-Gasser-Ogden) model parameters were fitted using a stochastic approach, namely the Simple Genetic Algorithm (SGA). The SGA was able to fit the experimental data successfully (R² > 0.986). The dimensionless coefficient ξ, was highly correlated with histological data. The ratio was seen to increase linearly with increasing collagen content.Coefficient ξ brings a new way of interpreting and understanding experimental data; it connects the nonlinear mechanical behaviour (tensile test) with tissue’s morphology (histology). It can be used as an ‘inverse’ (approximate) method to estimate the mechanical properties without direct experimental measurements, through basic histology.In this context, the proposed methodology appears very promising in estimating the response of the tissue via histological information.     

Qualification of long-stored samples of serum banks for seroepidemiological studies.

Serum samples were tested for antibodies against polio virus and measles virus from two serum banks after having been stored under different conditions for several years. The results are compared with those ones obtained immediately after sampling. Despite of small increases of antibody-negative samples and of small decreases of the titres the suitability of the samples stored could be shown. Special attention should be given to the establishment, e.g. in the framework of Expanded Programme on Immunization of the World Health Organization and in order to study new pathogens unknown to date, and the technical preconditions for that should be planed.     

Ice-cap. A high-throughput method for capturing plant tissue samples for genotype analysis

High-throughput genotype screening is rapidly becoming a standard research tool in the post-genomic era. A major bottleneck currently exists, however, that limits the utility of this approach in the plant sciences. The rate-limiting step in current high-throughput pipelines is that tissue samples from living plants must be collected manually, one plant at a time. In this article I describe a novel method for harvesting tissue samples from living seedlings that eliminates this bottleneck. The method has been named Ice-Cap to reflect the fact that ice is used to capture the tissue samples. The planting of seeds, growth of seedlings, and harvesting of tissue are all performed in a 96-well format. I demonstrate the utility of this system by using tissue harvested by Ice-Cap to genotype a population of Arabidopsis seedlings that is segregating a previously characterized mutation. Because the harvesting of tissue is performed in a nondestructive manner, plants with the desired genotype can be transferred to soil and grown to maturity. I also show that Ice-Cap can be used to analyze genomic DNA from rice (Oryza sativa) seedlings. It is expected that this method will be applicable to high-throughput screening with many different plant species, making it a useful technology for performing marker assisted selection.     

A model of a code of ethics for tissue banks operating in developing countries

Ethical practice in the field of tissue banking requires the setting of principles, the identification of possible deviations and the establishment of mechanisms that will detect and hinder abuses that may occur during the procurement, processing and distribution of tissues for transplantation. This model of a Code of Ethics has been prepared with the purpose of being used for the elaboration of a Code of Ethics for tissue banks operating in the Latin American and the Caribbean, Asia and the Pacific and the African regions in order to guide the day-to-day operation of these banks. The purpose of this model of Code of Ethics is to assist interested tissue banks in the preparation of their own Code of Ethics towards ensuring that the tissue bank staff support with their actions the mission and values associated with tissue banking.     

A new device for the freeze-clamping of tissue samples

Measurement of metabolite concentrations in tissue samples involves the following procedures: Removal of the sample from the animal, temporary arrest of metabolism, extraction (including weighing, homogenization, final fixation, and neutralization) and assay. Rapid temporary fixation following the sampling of tissue is essential to prevent autolytic changes in metabolite concentrations (1,2). The freeze-clamping technique described by Wollenberger et al. (3) meets this requirement as long as the final thickness of the freeze-clamped sample is sufficiently small. For brain tissue the limit seems to be about 2 mm (4).In our laboratory we have made extensive use of the freeze-clamping tongs of Wollenberger et al., especially for small tissue samples freeze-clamped in situ. However, when in situ clamping can not be used when more than 2–3 g of tissue must be sampled, the freeze-clamping press described below has proven very useful.     

A device for high-throughput monitoring of degradation in soft tissue samples

This work describes the design and validation of a novel device, the High-Throughput Degradation Monitoring Device (HDD), for monitoring the degradation of 24 soft tissue samples over incubation periods of several days inside a cell culture incubator. The device quantifies sample degradation by monitoring its deformation induced by a static gravity load. Initial instrument design and experimental protocol development focused on quantifying cartilage degeneration. Characterization of measurement errors, caused mainly by thermal transients and by translating the instrument sensor, demonstrated that HDD can quantify sample degradation with <6 μm precision and <10 μm temperature-induced errors. HDD capabilities were evaluated in a pilot study that monitored the degradation of fresh ex vivo human cartilage samples by collagenase solutions over three days. HDD could robustly resolve the effects of collagenase concentration as small as 0.5 mg/ml. Careful sample preparation resulted in measurements that did not suffer from donor-to-donor variation (coefficient of variance <70%). Due to its unique combination of sample throughput, measurement precision, temporal sampling and experimental versality, HDD provides a novel biomechanics-based experimental platform for quantifying the effects of proteins (cytokines, growth factors, enzymes, antibodies) or small molecules on the degradation of soft tissues or tissue engineering constructs. Thereby, HDD can complement established tools and in vitro models in important applications including drug screening and biomaterial development.     

A novel, inexpensive, and sensitive method for analysis of tyrosine hydroxylase activity in tissue samples.

Tyrosine hydroxylase activity in whole mouse brains was measured $\text{in v}\text{vitro}$. The L-dihydroxyphenylaline (L-DOPA) formed by the enzyme was quantitated by liquid chromatography with electrochemical detection (LCEC). An investigation of the incubation factors (added Fe⁺², DOPA decarboxylase inhibitor concentration, substrate concentration, amount of tissue, time of incubation) is reported. Under optimal conditions the activity was found to be 15.1 ± 0.6 (S.E.M.) nmol DOPA formed/hr./g. tissue.     

Supply and use of human tissue for research purposes: survey of BATB affiliated tissue banks

This paper describes a survey undertaken to identify the extent of supply and use of human tissue in research by BATB affiliated tissue banks. Approximately one third of tissue banks registered with the BATB are currently supplying samples that are found to be unsuitable for clinical use, for research. These banks all obtain consent for research and all supply tissue for in-house research. Some tissue is transferred to other public and commercial institutions. A harmonised network approach is proposed as the way forward to meet the increasing demand for human tissue in research.     

Resources for image-based high-throughput phenotyping in crops and data sharing challenges

High-throughput phenotyping (HTP) platforms are capable of monitoring the phenotypic variation of plants through multiple types of sensors, such as red green and blue (RGB) cameras, hyperspectral sensors, and computed tomography, which can be associated with environmental and genotypic data. Because of the wide range of information provided, HTP datasets represent a valuable asset to characterize crop phenotypes. As HTP becomes widely employed with more tools and data being released, it is important that researchers are aware of these resources and how they can be applied to accelerate crop improvement. Researchers may exploit these datasets either for phenotype comparison or employ them as a benchmark to assess tool performance and to support the development of tools that are better at generalizing between different crops and environments. In this review, we describe the use of image-based HTP for yield prediction, root phenotyping, development of climate-resilient crops, detecting pathogen and pest infestation, and quantitative trait measurement. We emphasize the need for researchers to share phenotypic data, and offer a comprehensive list of available datasets to assist crop breeders and tool developers to leverage these resources in order to accelerate crop breeding.

Various approaches are used to analyze high-throughput phenotyping data and tools can be developed and assessed using available image-based datasets.     

A simple procedure for simulating samples of tissue using Voronoi diagrams

OBJECTIVE: To describe a simple and quick procedure for modeling samples of tissue with Voronoi diagrams. STUDY DESIGN: Instead of calculating the centers of the so-called Dirichlet domains (i.e., the polygonal areas occupied by individual cells), the centroid of such areas is used to generate Voronoi diagrams. The coordinates of the centroids are calculated by simply averaging the coordinates of the points of the cell contours; that is much simpler and faster than any geometric procedure for locating the Dirichlet centers. Using the centroids as centers, circles are allowed to grow until no space on the surface is available. With this procedure it is easy to control the rate of growth of individual cells or groups of cells according to any rule or rules. It is also possible to simulate the effects of removing > or = 1 cells from the sample. CONCLUSION: The procedure was successfully applied to modeling some of the changes that can occur in a real sample of human corneal endothelium. The procedure is simple, completely automated, efficient and flexible and can be easily implemented on a personal computer. It can be used to test growth or communication strategies among cells.     

Consent and confidentiality in the light of recent demands for data sharing

Many attempts have been made to formalize ethical requirements for research. Among the most prominent mechanisms are informed consent requirements and data protection regimes. These mechanisms, however, sometimes appear as obstacles to research. In this opinion paper, we critically discuss conventional approaches to research ethics that emphasize consent and data protection. Several recent debates have highlighted other important ethical issues and underlined the need for greater openness in order to uphold the integrity of health‐related research. Some of these measures, such as the sharing of individual‐level data, pose problems for standard understandings of consent and privacy. Here, we argue that these interpretations tend to be overdemanding: They do not really protect research subjects and they hinder the research process. Accordingly, we suggest another way of framing these requirements. Individual consent must be situated alongside the wider distribution of knowledge created when the actions, commitments, and procedures of researchers and their institutions are opened to scrutiny. And instead of simply emphasizing privacy or data protection, we should understand confidentiality as a principle that facilitates the sharing of information while upholding important safeguards. Consent and confidentiality belong to a broader set of safeguards and procedures to uphold the integrity of the research process.     

Support vector machine classification and validation of cancer tissue samples using microarray expression data

MOTIVATION: DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results. RESULTS: We demonstrate the method in detail on samples consisting of ovarian cancer tissues, normal ovarian tissues, and other normal tissues. The dataset consists of expression experiment results for 97,802 cDNAs for each tissue. As a result of computational analysis, a tissue sample is discovered and confirmed to be wrongly labeled. Upon correction of this mistake and the removal of an outlier, perfect classification of tissues is achieved, but not with high confidence. We identify and analyse a subset of genes from the ovarian dataset whose expression is highly differentiated between the types of tissues. To show robustness of the SVM method, two previously published datasets from other types of tissues or cells are analysed. The results are comparable to those previously obtained. We show that other machine learning methods also perform comparably to the SVM on many of those datasets. AVAILABILITY: The SVM software is available at http://www.cs. columbia.edu/ approximately bgrundy/svm.