Vision-based force measurement using neural networks for biological cell microinjection

This paper presents a vision-based force measurement method using an artificial neural network model. The proposed model is used for measuring the applied load to a spherical biological cell during micromanipulation process. The devised vision-based method is most useful when force measurement capability is required, but it is very challenging or even infeasible to use a force sensor. Artificial neural networks in conjunction with image processing techniques have been used to estimate the applied load to a cell. A bio-micromanipulation system capable of force measurement has also been established in order to collect the training data required for the proposed neural network model. The geometric characterization of zebrafish embryos membranes has been performed during the penetration of the micropipette prior to piercing. The geometric features are extracted from images using image processing techniques. These features have been used to describe the shape and quantify the deformation of the cell at different indentation depths. The neural network is trained by taking the visual data as the input and the measured corresponding force as the output. Once the neural network is trained with sufficient number of data, it can be used as a precise sensor in bio-micromanipulation setups. However, the proposed neural network model is applicable for indentation of any other spherical elastic object. The results demonstrate the capability of the proposed method. The outcomes of this study could be useful for measuring force in biological cell micromanipulation processes such as injection of the mouse oocyte/embryo.     

Measuring size distribution in highly heterogeneous systems with fluorescence correlation spectroscopy

Fluorescence correlation spectroscopy (FCS) is a sensitive and widely used technique for measuring diffusion. FCS data are conventionally modeled with a finite number of diffusing components and fit with a least-square fitting algorithm. This approach is inadequate for analyzing data obtained from highly heterogeneous systems. We introduce a Maximum Entropy Method based fitting routine (MEMFCS) that analyzes FCS data in terms of a quasicontinuous distribution of diffusing components, and also guarantees a maximally wide distribution that is consistent with the data. We verify that for a homogeneous specimen (green fluorescent protein in dilute aqueous solution), both MEMFCS and conventional fitting yield similar results. Further, we incorporate an appropriate goodness of fit criterion in MEMFCS. We show that for errors estimated from a large number of repeated measurements, the reduced chi(2) value in MEMFCS analysis does approach unity. We find that the theoretical prediction for errors in FCS experiments overestimates the actual error, but can be empirically modified to serve as a guide for estimating the goodness of the fit where reliable error estimates are unavailable. Finally, we compare the performance of MEMFCS with that of a conventional fitting routine for analyzing simulated data describing a highly heterogeneous distribution containing 41 diffusing species. Both methods fit the data well. However, the conventional fit fails to reproduce the essential features of the input distribution, whereas MEMFCS yields a distribution close to the actual input.     

绿脓杆菌抗毒素精制方法与效价测定方法的研究

本文采用胃酶消化──硫酸铵盐析法对绿脓杆菌外毒素Ａ（ＰＥＡ）免疫马血浆进行了试制提纯,对该法酶处理及热变性中影响精制效果的几个主要因素进行了比较试验,同时对文中采用的４种效价测定方法进行了筛选。结果表明,胃酶消化法可用于ＰＥＡ免疫马血浆的精制;效价测定以生物学方法（细胞毒性中和试验、小鼠致死毒性中和试验）为佳。综合比较试验的结果,本文拟订了ＰＥＡ免疫马血浆精制的“修订法”并与“常规法”进行了精制比较。初步结果表明,修订法的精制效果优于常规法。     

Unsupervised fuzzy clustering using Weighted Incremental Neural Networks

A new more efficient variant of a recently developed algorithm for unsupervised fuzzy clustering is introduced. A Weighted Incremental Neural Network (WINN) is introduced and used for this purpose. The new approach is called FC-WINN (Fuzzy Clustering using WINN). The WINN algorithm produces a net of nodes connected by edges, which reflects and preserves the topology of the input data set. Additional weights, which are proportional to the local densities in input space, are associated with the resulting nodes and edges to store useful information about the topological relations in the given input data set. A fuzziness factor, proportional to the connectedness of the net, is introduced in the system. A watershed-like procedure is used to cluster the resulting net. The number of the resulting clusters is determined by this procedure. Only two parameters must be chosen by the user for the FC-WINN algorithm to determine the resolution and the connectedness of the net. Other parameters that must be specified are those which are necessary for the used incremental neural network, which is a modified version of the Growing Neural Gas algorithm (GNG). The FC-WINN algorithm is computationally efficient when compared to other approaches for clustering large high-dimensional data sets.     

An analysis of muscular load and performance in using a pen-tablet system

The present paper aims to investigate two characteristics; task performance and muscular load during skill process for the pen-tablet input system with the mouse input system on the PC in order to determine the comprehensive usability for the pen-tablet system. Two computer tasks were designed for the study: task SL and task PT. Task SL was a repetitive computer-drawing including typical mouse motions such as clicking and drag-dropping. Task PT was a polygon tracing task requiring fine-controlled movements with the input device. Surface electromyography (EMG) and performance data were measured during the task. When the pen-tablet was being used, low amplitudes of EMGs for the biceps brachii, the flexor digitorum superficialis, and the extensor digitorum were found, whereas no EMG difference for the trapezius was found for both tasks. On the first day, the performance with the mouse was much higher than the performance with the pen-tablet in terms of error rates and the number of completed trials. However, the performance with the pen-tablet exceeded the performance with the mouse from the second day on, and the subjects performed better with the pen-tablet than with the mouse. Current results imply that the skill process for the pen-tablet system was very short and the subjects felt comfortable to use the new system from the beginning.     

Modified Box-Cox transform for modulating the dynamic range of flow cytometry data

We describe an algorithm, Vout = Integer ([2(12)-1/2(12 lambda)-1] V lambda in-1) + 1; lambda greater than 0 based upon Box-Cox transformations as an alternative to nonlinear electronic amplifiers to expand or compress high- or low-amplitude flow cytometer-derived signals. If the indexing parameter lambda less than 1, input channels in the high-amplitude input range are compressed in the output range as occurs when an electronic logarithmic amplifier is used. However, if lambda greater than 1, input channels in the low-amplitude input range are compressed in the output range as occurs when an electronic power amplifier is used. Our modified Box-Cox transform can be implemented either during data collection or off-line for the transformation of previously collected raw data. The transform is the equivalent of an infinite class of nonlinear amplifiers. As the transform is implemented in software, it does not suffer from many of the disadvantages of nonlinear electronic amplifiers.     

A modified distance variable for the Hill formalism for kinetic models of muscle contraction

The distance variable of the Hill formalism for kinetic models of muscle contraction is compared to a modified distance variable. Instead of measuring the distance from a fixed point on the myosin filament to a neighboring actin, the modified variable measures the deviation of the myosin cross-bridge from its equilibrium position. Although for attached cross-bridges the two definitions are equivalent, the new variable is an index of cross-bridge conformation for cross-bridges of all states. The modified variable may be used to complement the use of the Hill variable, or to replace it. The utility of the modified variable is illustrated by an example which matches cross-bridge structures to biochemical kinetic data and to the free energy functions necessary for the design of a kinetic model.     

Mouse strain specific gene expression differences for illumina microarray expression profiling in embryos

ABSTRACT: BACKGROUND: In the field of mouse genetics the advent of technologies like microarray based expression profiling dramatically increased data availability and sensitivity, yet these advanced methods are often vulnerable to the unavoidable heterogeneity of in vivo material and might therefore reflect differentially expressed genes between mouse strains of no relevance to a targeted experiment. The aim of this study was not to elaborate on the usefulness of microarray analysis in general, but to expand our knowledge regarding this potential "background noise" for the widely used Illumina microarray platform surpassing existing data which focused primarily on the adult sensory and nervous system, by analyzing patterns of gene expression at different embryonic stages using wild type strains and modern transgenic models of often non-isogenic backgrounds. RESULTS: Wild type embryos of 11 mouse strains commonly used in transgenic and molecular genetic studies at three developmental time points were subjected to Illumina microarray expression profiling in a strain-by-strain comparison. Our data robustly reflects known gene expression patterns during mid-gestation development. Decreasing diversity of the input tissue and/or increasing strain diversity raised the sensitivity of the array towards the genetic background. Consistent strain sensitivity of some probes was attributed to genetic polymorphisms or probe design related artifacts. CONCLUSION: Our study provides an extensive reference list of gene expression profiling background noise of value to anyone in the field of developmental biology and transgenic research performing microarray expression profiling with the widely used Illumina microarray platform. Probes identified as strain specific background noise further allow for microarray expression profiling on its own to be a valuable tool for establishing genealogies of mouse inbred strains.     

Monte Carlo Vadose Zone Model for Soil Remedial Criteria

Many vadose zone models are available for environmental remediation, but few offer the procedures for verifying model predictions with field data and for dealing with uncertainties associated with model input parameters. This article presents a modified model combining a one-dimensional vadose-zone transport model and a simple groundwater mixing model with a function of Monte Carlo simulation (MCS). The modified model is applied to determine soil remedial concentrations for methyl tertiary butyl ether (MTBE). The modified model generates a distribution of MTBE ground-water concentrations at the point of compliance. This distribution can be used to estimate the risk of exceeding groundwater quality standard given soil remedial concentrations. In a case study, soil remedial concentration for MTBE is established to be 5?µg/kg, with a 95% and 10?µg/kg with a 50% probability that groundwater concentration will not exceed the water quality objective of 13?µg/L. Furthermore, this study uses MCS to investigate uncertainties of model input parameter hydraulic conductivity (K). One set of data (K1) is based on the results of hydraulic conductivity laboratory tests, and the other (K2) is based on the results of slug tests conducted in the field. As expected, the laboratory data show smaller K values than the field data. The comparison of the MCS results obtained from the two sets of K data indicates that the MTBE groundwater concentrations calculated based on K1 are generally 160 to 625% greater than those calculated based on K2 at the same percentiles of the MCS distribution. A higher soil remedial concentration of9jig/kg is then calculated based on the MCS results from K2 at 95%ile and 19?µg/kg at 50%ile.     

Assessment of DNA damage at the dimer level: measurement of the formamide lesion

UVC-radiation-induced DNA damage was measured in mouse fibroblast cells using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in conjunction with isotopically labeled internal standards. The thymine glycol and formamide lesions were assayed in the form of modified dinucleoside monophosphates. The 8-oxo-7,8-dihydroguanine lesion was measured as the modified nucleoside. DNA damage in cells treated with tirapazamine was also measured. Tirapazamine is a chemotherapeutic agent that acts via a free radical mechanism. The two agents, UVC radiation and tirapazamine, produce markedly different profiles of DNA damage, reflecting their respective mechanisms of action. Both agents produce significant amounts of thymine glycol and formamide damage, but only the former produced a measurable amount of the 8-oxo-7,8-dihydroguanine lesion. The merits of measuring DNA damage at the dimer level are discussed.     

Physio-climatic classification of South Africa's woodland biome

In an effort to develop more holistic ecosystem approaches to resource assessment and management, landscapes need to be stratified into homogeneous geographic regions. These regions can then be used in a monitoring framework to develop reliable estimates of ecosystem productivity. A regional characterization of the woodland biome has been developed for South Africa, delineated by satellite imagery and using environmental data and a rigorous statistical methodology. Distribution maps of key environmental variables are analyzed by factor analysis, an iterative clustering technique and maximum likelihood classification to quantify and identify homogeneous physio-climatic units.A spatial clustering technique was used to identify regions, which are statistically different with regard to five physiographic, climatic and edaphic variables deemed important within southern African savanna woodlands. The woodland biome of South Africa at 1km resolution was successively divided. Thirty year mean monthly temperature, total plant-available water balance of soil, elevation, landscape topographic position, and landscape soil fertility were used as input classification variables.The map data were submitted to a factor analysis and varimax axis rotation. The factor analysis removes correlations from the input variables, reduces the dimensionality, and normalizes the axis measurements. A cluster analysis was performed on the three principal factor scores using a modified iterative optimization clustering procedure to determine the finest level of classes statistically permitable. Twenty-seven identified unimodal cluster signatures were then submitted to a maximum likelihood classification where the statistical probability of the GIS cell assignment is carried out to determine class membership. The final map of custom physio-climatic regions is described, and these custom regions are compared with a vegetation potential map of the woodland types identified in the South African summer rainfall zone.     

Colour As a Signal for Entraining the Mammalian Circadian Clock

Twilight is characterised by changes in both quantity (“irradiance”) and quality (“colour”) of light. Animals use the variation in irradiance to adjust their internal circadian clocks, aligning their behaviour and physiology with the solar cycle. However, it is currently unknown whether changes in colour also contribute to this entrainment process. Using environmental measurements, we show here that mammalian blue–yellow colour discrimination provides a more reliable method of tracking twilight progression than simply measuring irradiance. We next use electrophysiological recordings to demonstrate that neurons in the mouse suprachiasmatic circadian clock display the cone-dependent spectral opponency required to make use of this information. Thus, our data show that some clock neurons are highly sensitive to changes in spectral composition occurring over twilight and that this input dictates their response to changes in irradiance. Finally, using mice housed under photoperiods with simulated dawn/dusk transitions, we confirm that spectral changes occurring during twilight are required for appropriate circadian alignment under natural conditions. Together, these data reveal a new sensory mechanism for telling time of day that would be available to any mammalian species capable of chromatic vision.     

Quantitative succinate-dehydrogenase histochemistry. I. A Methodological study on mammalian and fish muscle.

In enzyme histochemistry formazan production can be used as a measure for oxidative enzyme activity. The formazan deposits can be measured quantitatively per cell with a scanning and integrating microspectrophotometer. Optimal conditions are described for the estimation of histochemical succinate dehydrogenase activity in sections of fish bodymusculature and mouse soleus and plantaris muscle. It is shown that when proper measuring conditions are chosen a ditetrazolium salt (TNBT) can be used in quantitative enzyme histochemistry and that the optimal conditions for the histochemical succinate dehydrogenase reaction in muscle fibres of fish and mouse muscle are somewhat different for these two species. The differences in pH, temperature and succinate sensitivity are the most prominent.     

Bioavailability of Soil-Borne Chemicals: Method Development and Validation

Chemicals present in contaminated soils generally exhibit altered bioavailability compared to other vehicles used in studies of chemical toxicity. Methods used to assess the bioavailability of soil-borne chemicals have generally been modified versions of methods that are widely used in biomedical research. Oral and dermal bioavailability of semivolatile organic chemicals and metals in soil has been assessed by a variety of in vivo and in vitro methods. Due to variations in metabolism and excretion of different chemicals, approaches to measuring bioavailability must be selected with an understanding of disposition of the chemical being studied. Standard methods need to be modified due to constraints associated with doses relevant to environmental concentrations, the need to reflect weathering behavior in soils over time, and the need to generate data applicable to human health risk assessments. Estimates of relative bioavailability for chemicals in soil can be used directly to modify exposure estimates. Application of bioavailability data in a site-specific risk assessment requires regulatory acceptance of the data. Acceptance of the data will generally be dependent on either the use of a validated test method or a careful scientific review of the test method employed. A process for validating newly developed alternative toxicity methods for routine use developed by the Interagency Coordinating Committee on the Validation of Alternative Methods provides relevant guidance for assessing in vitro methods, but method validation should not be the only litmus test for inclusion of bioavailability data in risk assessments.     

Quantitative succinate-dehydrogenase histochemistry

Summary In enzyme histochemistry formazan production can be used as a measure for oxidative enzyme activity. The formazan deposits can be measured quantitatively per cell with a scanning and integrating microspectrophotometer. Optimal conditions are described for the estimation of histochemical succinate dehydrogenase activity in sections of fish bodymusculature and mouse soleus and plantaris muscle. It is shown that when proper measuring conditions are choosen a ditetrazolium salt (TNBT) can be used in quantitative enzyme histochemistry and that the optimal conditions for the histochemical succinate dehydrogenase reaction in muscle fibres of fish and mouse muscle are somewhat different for these two species. The differences in pH, temperature and succinate sensitivity are the most prominent.     

Receptive Field Vectors of Genetically-Identified Retinal Ganglion Cells Reveal Cell-Type-Dependent Visual Functions

Sensory stimuli are encoded by diverse kinds of neurons but the identities of the recorded neurons that are studied are often unknown. We explored in detail the firing patterns of eight previously defined genetically-identified retinal ganglion cell (RGC) types from a single transgenic mouse line. We first introduce a new technique of deriving receptive field vectors (RFVs) which utilises a modified form of mutual information (“Quadratic Mutual Information”). We analysed the firing patterns of RGCs during presentation of short duration (~10 second) complex visual scenes (natural movies). We probed the high dimensional space formed by the visual input for a much smaller dimensional subspace of RFVs that give the most information about the response of each cell. The new technique is very efficient and fast and the derivation of novel types of RFVs formed by the natural scene visual input was possible even with limited numbers of spikes per cell. This approach enabled us to estimate the ''visual memory'' of each cell type and the corresponding receptive field area by calculating Mutual Information as a function of the number of frames and radius. Finally, we made predictions of biologically relevant functions based on the RFVs of each cell type. RGC class analysis was complemented with results for the cells’ response to simple visual input in the form of black and white spot stimulation, and their classification on several key physiological metrics. Thus RFVs lead to predictions of biological roles based on limited data and facilitate analysis of sensory-evoked spiking data from defined cell types.     

显微注射法制备遗传工程小鼠模型的研究

遗传工程小鼠模型是基因功能、人类疾病发病机制及新药研究开发的最重要的模式生物之一。在建立遗传工程小鼠模型的众多方法中,显微注射法是目前国际上公认的制备转基因及基因剔除动物模型的首选。在进行了大量显微注射工作后,简要介绍建立遗传工程小鼠模型的基本技术与方法,并对在显微操作过程中较为关键的因素进行一些分析和讨论。     

Comparison of Radioimmuno and Carbon Nanotube Field-Effect Transistor Assays for Measuring Insulin-Like Growth Factor-1 in a Preclinical Model of Human Breast Cancer

Background

To realize the promise of personalized medicine, diagnostic instruments used for detecting and measuring biomarkers must become smaller, faster and less expensive. Although most techniques used currently to detect biomarkers are sensitive and specific, many suffer from several disadvantages including their complexity, high cost and long turnaround time. One strategy to overcome these problems is to exploit carbon nanotube (CNT) based biosensors, which are sensitive, use inexpensive disposable components and can be easily adapted to current assay protocols. In this study we investigated the applicability of using a CNT field-effect transistor (CNT-FET) as a diagnostic instrument for measuring cancer biomarkers in serum using a mouse model of Breast Cancer Susceptibility 1-related breast cancer. Insulin like growth factor-1 (IGF-1) was chosen because it is highly relevant in breast cancer and because measuring serum IGF-1 levels by conventional methods is complicated due to specific IGF-1 serum binding proteins.

Findings

Our results show that there is good correlation between the two platforms with respect to detecting serum IGF-1. In fact, the CNT-FETs required only one antibody, gave real-time results and required approximately 100-fold less mouse serum than the radioimmunoassay.

Conclusions

Both IGF-1 radioimmuno and CNT-FET assays gave comparable results. Indeed, the CNT-FET assay was simpler and faster than the radioimmunoassay. Additionally, the low serum sample required by CNT-FETs can be especially advantageous for studies constricted by limited amount of human clinical samples and for mouse studies, since animals often need to be sacrificed to obtain enough serum for biomarker evaluation.