Method for measuring a comprehensive energy budget in a proliferating cell system over multiple cell cycles

Isolated cell systems are now being used very effectively to study a range of important biochemical questions, but their energy metabolism has never been comprehensively investigated. We have developed a system, using J2E cells, which enables us to measure total ATP turnover and the contribution of various fuels and pathways to this total in a dynamic, proliferating preparation. Cells are cultured in 500 ml airtight glass containers which enables (1) the measurement of oxygen consumption, (2) the collection and measurement of ¹⁴CO₂ production from labelled fuels, and (3) the measurement of metabolite utilization and production. Data on cell numbers are then used to produce a curve of cell number vs. time, the area under which (cell numbers · hour) is used as a base by which all measurements and experiments are compared. To our knowledge this is the first time a comprehensive energy budget has been measured in a proliferating cell system over a period that covers multiple cell cycles. J Cell Physiol 170:1–7, 1997 © 1997 Wiley-Liss, Inc.     

Evidence for an intercellular covalent reaction essential in antigen-specific T cell activation

The inductive interaction between class II+ APC and Th cell was investigated in a human system at the chemical level. The study set out to test the predictions of a model of Ag presentation in which epsilon-amino groups and carbonyl groups at the surface of APC and T cell react covalently to form reversible intercellular Schiff bases. In the experimental system of oxidative mitogenesis this process results in T cell activation. If oxidative mitogenesis is an experimental amplification of a physiologic process, and intercellular Schiff base formation is essential in Ag presentation, then it should be possible to inhibit Ag presentation by prior formation of Schiff bases on the surface of participating cells. In this situation Ag-induced T cell activation and T cell activation induced by periodate oxidation should invariably behave in the same way. It should also be possible to demonstrate Schiff base formation occurring between accessory cells and lymphocytes directly and definitively by means of specific reduction with sodium cyanoborohydride. Aldehyde treatment of accessory cells should prevent this intercellular Schiff base formation. In this study the following observations were made. 1) Both Ag-specific and periodate-induced T cell activation were inhibited by aldehyde treatment of class II+ accessory cells. 2) Noncross-linking donors of carbonyl groups other than aldehydes inhibited Ag-specific T cell activation. 3) Brief, low-dose treatment of T cells with aldehydes inhibited Ag-dependent T-cell activation. 4) Exogenous amino groups in the form of lysine and other amino acids inhibited both Ag-specific and periodate-induced T-cell activation. 5) The weak reducing agent sodium cyanoborohydride which is specific for Schiff bases at neutral pH inhibited both Ag-induced and periodate-induced T cell activation. Responses to PHA were markedly prolonged by this reagent. 6) Schiff base formation occurring between accessory cells and lymphocytes was detected directly and definitively by means of radiolabeling with NaCNB(3H)3 at neutral pH. These data are consistent with the view that the formation of reversible covalent Schiff bases between ligands on APC and T cell is an essential process in Ag-induced T cell activation.     

Real-time fuzzy-knowledge-based control of Baker's yeast production

A real-time fuzzy-knowledge-based system for fault diagnosis and control of bioprocesses was constructed using the object-oriented programming environment Small-talk/V Mac. The basic system was implemented in a Macintosh Quadra 900 computer and built to function connected on line to the process computer. Fuzzy logic was employed in handling uncertainties both in the knowledge and in measurements. The fuzzy sets defined for the process variables could be changed on-line according to process dynamics. Process knowledge was implemented in a graphical two-level hierachical knowledge base. In on-line process control the system first recognizes the current process phase on the basis of top-level rules in the knowledge-base. Then, according to the results of process diagnosis based on measurement data, the appropriate control strategy is subsequently inferred making use of the lower level rules describing the process during the phase in question. (c) 1995 John Wiley & Sons, Inc.     

An intelligent control method based on fuzzy logic for a robotic testing system for the human spine

In previous biomechanical studies of the human spine, we implemented a hybrid controller to investigate load-displacement characteristics. We found that measurement errors in both position and force caused the controller to be less accurate than predicted. As an alternative to hybrid control, a fuzzy logic controller (FLC) has been developed and implemented in a robotic testing system for the human spine. An FLC is a real-time expert system that can emulate part of a human operator's knowledge by using a set of action rules. The FLC provides simple but robust solutions that cover a wide range of system parameters and can cope with significant disturbances. It can be viewed as a heuristic and modular way of defining a nonlinear, table-based control system. In this study, an FLC is developed which uses the force difference and the change in force difference as the input parameters, and the displacement as the output parameter. A rule-table based on these parameters is designed for the controller Experiments on a physical model composed of springs demonstrate the improved performance of the proposed method.     

ISYMOD: a knowledge warehouse for the identification, assembly and analysis of bacterial integrated systems

MOTIVATION: Complex biological functions emerge from interactions between proteins in stable supra-molecular assemblies and/or through transitory contacts. Most of the time protein partners of the assemblies are composed of one or several domains which exhibit different biochemical functions. Thus the study of cellular process requires the identification of different functional units and their integration in an interaction network; such complexes are referred to as integrated systems. In order to exploit with optimum efficiency the increased release of data, automated bioinformatics strategies are needed to identify, reconstruct and model such systems. For that purpose, we have developed a knowledge warehouse dedicated to the representation and acquisition of bacterial integrated systems involved in the exchange of the bacterial cell with its environment. RESULTS: ISYMOD is a knowledge warehouse that consistently integrates in the same environment the data and the methods used for their acquisition. This is achieved through the construction of (1) a domain knowledge base (DKB) devoted to the storage of the knowledge about the systems, their functional specificities, their partners and how they are related and (2) a methodological knowledge base (MKB) which depicts the task layout used to identify and reconstruct functional integrated systems. Instantiation of the DKB is obtained by solving the tasks of the MKB, whereas some tasks need instances of the DKB to be solved. AROM, an object-based knowledge representation system, has been used to design the DKB, and its task manager, AROMTasks, for developing the MKB. In this study two integrated systems, ABC transporters and two component systems, both involved in adaptation processes of a bacterial cell to its biotope, have been used to evaluate the feasibility of the approach.     

3D虚拟复原精度的差异对头骨测量数值的影响——以Mimics软牛为例

近年来,根据三维软件虚拟复原的头骨来获取测量数据的方法被越来越多地应用在古生物,特别是古人类学的研究中,然而对于三维软件不同精度虚拟复原的头骨,其测量数值是否有差异,研究者并不是很清楚。本文以Mimics软件为例,根据其复原模型简化规则,选择未精简的最佳精度模型作为标准进行配对t检验或非参数检验,通过对43例云南人头骨的顶骨矢状弦长、颅周长、头盖部面积、乳突小房表面积、颅容量、乳突小房体积等六个测量项目的对比和分析,对Mimics软件低、中、高、最佳四种精度3D虚拟复原头骨间的测量差异进行了研究。结果显示：颅周长、头盖部面积、颅容量、乳突小房体积四项的所有简化精度模型的测量数据均与最佳精度模型测量数据的差异具有显著性;而除高精度组外,顶骨矢状弦长及乳突小房表面积的其余精度组测量数据均与最佳精度组差异具有显著性;此外,顶骨矢状弦长、颅周长、头盖部面积、颅容量的简化精度与最佳精度的测量差异占比均小于3%.而乳突小房表面积的低精度与最佳精度测量差异占比可超过50%,乳突小房体积的低精度与最佳精度测量差异占比可超过120%。这一结果提示我们,在测量Mimics复原的三维模型时,体量大差异小的测量项可以在较低精度的复原模型上进行测量;而对头骨内部腔窦这样体量小表面粗糙的结构,复原模型的精度选择及测量数据比较需要格外谨慎。     

草地有害啮齿动物监测专家系统设计介绍

主要介绍了青藏高原草地有害啮齿动物监测专家系统的建造原理和方法。该系统由综合数据库、知识库、推理机、知识编辑语言及系统建造支持环境等部分组成,文中详细说明各部分的主要功能以及与其他部分的相互关系。该系统可对青藏高原有害动物种群动态进行长期监测,快速准确地预测预报草地植被受害状况,并根据生态环境特点,对有害啮齿动物综合治理进行规划,为用户提供长期治理的技术和多种可供选择的可行性方案。     

Preliminary research on body composition measurement using X-ray phase contrast imaging

Body composition measurement is of cardinal significance for medical and clinical applications. Currently, the dual-energy X-ray absorptiometry (DEXA) technique is widely applied for this measurement. In this study, we present a novel measurement method using the absorption and phase information obtained simultaneously from the X-ray grating-based interferometer (XGI). Rather than requiring two projection data sets with different X-ray energy spectra, with the proposed method, both the areal densities of the bone and the surrounding soft tissue can be acquired utilizing one projection data set. By using a human body phantom constructed to validate the proposed method, experimental results have shown that the compositions can be calculated with an improved accuracy comparing to the dual energy method, especially for the soft tissue measurement. Since the proposed method can be easily implemented on current XGI setup, it will greatly extend the applications of the XGI, and meanwhile has the potential to be an alternative to DEXA for human body composition measurement.     

Land management: data availability and process understanding for global change studies

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human‐induced changes in terrestrial ecosystems that do not result in land‐cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one‐tenth of the ice‐free land surface is under intense human management, half under medium and one‐fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.     

Cytomics, the human cytome project and systems biology: top-down resolution of the molecular biocomplexity of organisms by single cell analysis

A large amount of structural and functional information is obtained by molecular cell phenotype analysis of tissues, organs and organisms at the single cell level by image or flow cytometry in combination with bioinformatic knowledge extraction (cytomics) concerning nuclei acids, proteins and metabolites (cellular genomics, proteomics and metabolomics) as well as cell function parameters like intracellular pH, transmembrane potentials or ion gradients. In addition, differential molecular cell phenotypes between diseased and healthy cells provide molecular data patterns for (i) predictive medicine by cytomics or for (ii) drug discovery purposes using reverse engineering of the data patterns by biomedical cell systems biology. Molecular pathways can be explored in this way including the detection of suitable target molecules, without detailed a priori knowledge of specific disease mechanisms. This is useful during the analysis of complex diseases such as infections, allergies, rheumatoid diseases, diabetes or malignancies. The top-down approach reaching from single cell heterogeneity in cell systems and tissues down to the molecular level seems suitable for a human cytome project to systematically explore the molecular biocomplexity of human organisms. The analysis of already existing data from scientific studies or routine diagnostic procedures will be of immediate value in clinical medicine, for example as personalized therapy by cytomics.     

Optimization of the human adenosine A2a receptor yields in Saccharomyces cerevisiae

G-protein coupled receptors (GPCRs) have been implicated in many human diseases and have emerged as important drug targets. Despite their medical relevance, knowledge about GPCR structure is limited, mainly due to difficulties associated with producing large amounts of functional protein and isolating this protein in functional form. However, our previous results indicate that when the human adenosine A(2)a receptor (A(2)aR) is expressed in Saccharomyces cerevisiae, high yields can be achieved. In light of these initial results and in anticipation of future purification efforts, experiments were conducted to optimize the system for maximum total protein yield. Emphasis was placed on not only producing large quantities of A(2)aR in each cell but also achieving high cell density in batch culture. Therefore, temperature, media pH, inducer concentration in the media, and induction cell density were tested for their effects on both cell growth (as measured by optical density, OD(600)) and per cell A(2)aR expression levels. For these studies, the A(2)aR expression levels were determined using a previously described A(2)aR-green fluorescent protein (GFP) fusion, so that expression could be monitored by fluorescence. Overall the data indicate that at late times ( approximately 60 h of expression) approximately 75% higher total batch protein yields can be achieved using lower expression temperatures or 60% higher using elevated induction cell density. The highest yields correspond to approximately 28 mg per liter of culture of total A(2)aR. Amounts of functional receptor were shown to increase on a per cell basis by decreasing expression temperature up to 25 h of expression, but at late time points ( approximately 60 h) functional yields did not appreciably improve. When compared to other reports of GPCR expression in yeast it is clear that this system is among those producing the highest GPCR protein yields per culture both before and after optimization.     

Medical data base system with an ability of automated diagnosis.

We carried out an experiment on a medical information system in which a clinical data base is combined organically with computer programs for automated diagnosis. In this system, the parameters for automated diagnosis are devised to be renewed as the contents of the data base (patient's information) increase. This system can be regarded as a data base possessing a kind of diagnosing ability which grows up with time. We have named this system "Intelligent Data Base". The algorithm for computer diagnosis used in this study is based on maximum likelihood method, and each likelihood is weighted with a prior probability of each disease. The discrimination efficiency of this method is logically equal to that of the Bayes rule. First 27 cases were learnt by the system and correct diagnosis was obtained in 78% of the cases. When cases for learning increased to 82, the percentage of correct diagnosis was improved to 95%.     

Human DEAD-box ATPase DDX3 shows a relaxed nucleoside substrate specificity

Human DDX3 (hDDX3) is a DEAD-box protein shown to possess RNA-unwinding and adenosine triphosphatase (ATPase) activities. The hDDX3 protein has been implicated in nuclear mRNA export, cell growth control, and cancer progression. In addition, a role of this protein in the replication of human immunodeficiency virus Type 1 and in the pathogenesis of hepatitis C virus has been recently proposed. Its enzymological properties, however, are largely unknown. In this work, we characterized its ATPase activity. We show that hDDX3 ATPase activity is stimulated by various ribo- and deoxynucleic acids. Comparative analysis with different nucleoside triphosphate analogs showed that the hDDX3 ATPase couples high catalytic efficiency to a rather relaxed substrate specificity, both in terms of base selection and sugar selection. In addition, its ability to recognize the L-stereoisomers of both 3' deoxy- and 2',3' dideoxy-ribose, points to a relaxed stereoselectivity. On the basis of these results, we hypothesize the presence of structural determinants on both the base and the sugar moieties, critical for nucleoside binding to the enzyme. Our results expand the knowledge about the DEAD-box RNA helicases in general and can be used for rational design of selective inhibitors of hDDX3, to be tested as potential antitumor and antiviral agents.     

The impact of new technologies on human population studies

Human population studies involve clinical or epidemiological observations that associate environmental exposures with health endpoints and disease. Clearly, these are the most sought after data to support assessments of human health risk from environmental exposures. However, the foundations of many health risk assessments rest on experimental studies in rodents performed at high doses that elicit adverse outcomes, such as organ toxicity or tumors. Using the results of human studies and animal data, risk assessors define the levels of environmental exposures that may lead to disease in a portion of the population. These decisions on potential health risks are frequently based on the use of default assumptions that reflect limitations in our scientific knowledge. An important immediate goal of toxicogenomics, including proteomics and metabonomics, is to offer the possibility of making decisions affecting public health and public based on detailed toxicity, mechanistic, and exposure data in which many of the uncertainties have been eliminated. Ultimately, these global technologies will dramatically impact the practice of public health and risk assessment as applied to environmental health protection. The impact is already being felt in the practice of toxicology where animal experimentation using highly controlled dose-time parameters is possible. It is also being seen in human population studies where understanding human genetic variation and genomic reactions to specific environmental exposures is enhancing our ability to uncover the causes of variations in human response to environmental exposures. These new disciplines hold the promise of reducing the costs and time lines associated with animal and human studies designed to assess both the toxicity of environmental pollutants and efficacy of therapeutic drugs. However, as with any new science, experience must be gained before the promise can be fulfilled. Given the numbers and diversity of drugs, chemicals and environmental agents; the various species in which they are studied and the time and dose factors that are critical to the induction of beneficial and adverse effects, it is only through the development of a profound knowledge base that toxicology and environmental health can rapidly advance. The National Institute of Environmental Health Sciences (NIEHS), National Center for Toxicogenomics and its university-based Toxicogenomics Research Consortium (TRC), and resource contracts, are engaged in the development, application and standardization of the science upon which to the build such a knowledge base on Chemical Effects in Biological Systems (CEBS). In addition, the NIEHS Environmental Genome Project (EGP) is working to systematically identify and characterize common sequence polymorphisms in many genes with suspected roles in determining chemical sensitivity. The rationale of the EGP is that certain genes have a greater than average influence over human susceptibility to environmental agents. If we identify and characterize the polymorphism in those genes, we will increase our understanding of human disease susceptibility. This knowledge can be used to protect susceptible individuals from disease and to reduce adverse exposure and environmentally induced disease.     

Hormones in the nucleus. Immunologically demonstrable biogenic amines (serotonin, histamine) in the nucleus of rat peritoneal mast cells

Using 1-ethyl-3(3-dimethyl-aminopropyl)-carbodiimide (EDAC) fixation and immunocytochemical confocal microscopic study, bright serotonin and histamine fluorescence appeared in the nucleus of rat peritoneal mast cells. In case of paraformaldehyde fixation, this was not observed. The phenomenon can be explained by the cross-linking effect of EDAC, which did not allow the efflux of biogenic amines from the nucleus. This means that biogenic amines are present in the nucleus of mast cells, and this is supported by the flow cytometric measurement data of the whole cell. Other hormones studied (triiodothyronine, insulin, and endorphin) were not present in the nucleus. Four pharmaca with biogenic amine-influencing character in the central nervous system were used for studying the relation between the external (surrounding and cytoplasmic) and nuclear biogenic amine content of mast cells. Fluoxetine, a serotonin reuptake inhibitor depleted nuclear as well as cytoplasmic serotonin content. Clorgyline, a MAO-A inhibitor, decreased cytoplasmic serotonin content and weakened nuclear serotonin fluorescence. The tryptophan hydroxylase inhibitor, para-chlorophenylalanine (PCPA), and the mast cell degranulator, Compound 48/80, reduced cytoplasmic serotonin content without influencing nuclear content. Histamine fluorescence was influenced solely by fluoxetine. The results show that nuclear 5-HT content is dependent firstly of serotonin uptake and reuptake. To our knowledge, this is the first exact report on the presence of non-steroid-type-receptor-transported hormones inside the nucleus of a cell.     

A knowledge base for predicting protein localization sites in eukaryotic cells

To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing a knowledge base by organizing various experimental and computational observations as a collection of if-then rules. Here we report an expert system, which utilizes this knowledge base, for predicting localization sites of proteins only from the information on the amino acid sequence and the source origin. We collected data for 401 eukaryotic proteins with known localization sites (subcellular and extracellular) and divided them into training data and testing data. Fourteen localization sites were distinguished for animal cells and 17 for plant cells. When sorting signals were not well characterized experimentally, various sequence features were computationally derived from the training data. It was found that 66% of the training data and 59% of the testing data were correctly predicted by our expert system. This artificial intelligence approach is powerful and flexible enough to be used in genome analyses.     

Two-photon fluorescence cross-correlation spectroscopy as a potential tool for high-throughput screening of DNA repair activity

Several lines of evidence indicate that differences in DNA repair capacity are an important source of variability in cancer risk. However, traditional assays for measurement of DNA repair activity in human samples are laborious and time-consuming. DNA glycosylases are the first step in base excision repair of a variety of modified DNA bases. Here, we describe the development of a new sensitive DNA glycosylase assay based on fluorescence cross-correlation spectroscopy (FCCS) with two-photon excitation. FCCS was applied to the measurement of uracil DNA glycosylase activity of human cell extracts and validated by comparison with standard gel electrophoresis assay. Our results indicate that FCCS can be adapted to efficient assays for DNA glycosylase activity in protein extracts from human cells. This method has a potential for the development of automated screening of large number of samples.     

Comparison of in vitro models for the prediction of compound absorption across the human intestinal mucosa

Several in vitro assays have been developed to evaluate the gastrointestinal absorption of compounds. Our aim was to compare 3 of these methods: 1) the bio-mimetic artificial membrane permeability assay (BAMPA) method, which offers a high-throughput, noncellular approach to the measurement of passive transport; 2) the traditional Caco-2 cell assay, the use of which as a high-throughput tool is limited by the long cell differentiation time (21 days); and 3) The BioCoat high-throughput screening Caco-2 Assay System, which reduces Caco-2 cell differentiation to 3 days. The transport of known compounds (such as cephalexin, propranolol, or chlorothiazide) was studied at pH 7.4 and 6.5 in BAMPA and both Caco-2 cell models. Permeability data obtained was correlated to known values of human absorption. Best correlations (r = 0.9) were obtained at pH 6.5 for BAMPA and at pH 7.4 for the Caco-2 cells grown for 21 days. The Caco-2 BioCoat HTS Caco-2 Assay System does not seem to be adequate for the prediction of absorption. The overall results indicate that BAMPA and the 21-day Caco-2 system can be complementary for an accurate prediction of human intestinal absorption.     

Estimation of unmeasured ground reaction force data based on the oscillatory characteristics of the center of mass during human walking

To enhance the wearability of portable motion-monitoring devices, the size and number of sensors are minimized, but at the expense of quality and quantity of data collected. For example, owing to the size and weight of low-frequency force transducers, most currently available wearable gait measurement systems provide only limited, if any, elements of ground reaction force (GRF) data. To obtain the most GRF information possible with a minimal use of sensors, we propose a GRF estimation method based on biomechanical knowledge of human walking. This includes the dynamics of the center of mass (CoM) during steady human gait resembling the oscillatory behaviors of a mass-spring system. Available measurement data were incorporated into a spring-loaded inverted pendulum with translating pivot. The spring stiffness and simulation parameters were tuned to match, as accurately as possible, the available data and oscillatory characteristics of walking. Our results showed that the model simulation estimated reasonably well the unmeasured GRF. Using the vertical GRF and CoP profile for gait speeds ranging from 0.93 to 1.89 m/s, the anterior-posterior (A-P) GRF was estimated and resulted in an average correlation coefficient of R = 0.982 ± 0.009. Even when the ground contact timing and gait speed information were alone available, our method estimated GRFs resulting in R = 0.969 ± 0.022 for the A-P and R = 0.891 ± 0.101 for the vertical GRFs. This research demonstrates that the biomechanical knowledge of human walking, such as inherited oscillatory characteristics of the CoM, can be used to gain unmeasured information regarding human gait dynamics.     

Uncovering signal transduction networks from high-throughput data by integer linear programming

Signal transduction is an important process that transmits signals from the outside of a cell to the inside to mediate sophisticated biological responses. Effective computational models to unravel such a process by taking advantage of high-throughput genomic and proteomic data are needed to understand the essential mechanisms underlying the signaling pathways. In this article, we propose a novel method for uncovering signal transduction networks (STNs) by integrating protein interaction with gene expression data. Specifically, we formulate STN identification problem as an integer linear programming (ILP) model, which can be actually solved by a relaxed linear programming algorithm and is flexible for handling various prior information without any restriction on the network structures. The numerical results on yeast MAPK signaling pathways demonstrate that the proposed ILP model is able to uncover STNs or pathways in an efficient and accurate manner. In particular, the prediction results are found to be in high agreement with current biological knowledge and available information in literature. In addition, the proposed model is simple to be interpreted and easy to be implemented even for a large-scale system.