Biophysical Reviews and Letters

This review compares the functional characteristics of liver mitochondria isolated from (i) the hibernating animals and (ii) of mitochondria studied in situ in motile Tetrahymena pyriformis during stationary growth phase, washed with a substrate-free medium. To explain the considered data, a hypothesis is proposed that the prerequisite for surviving under metabolic depression is a rearrangement of mitochondrial morphology to a condensed state. Such remodeling is induced either (1) by low mitochondrial electrical potential difference across the inner mitochondrial membrane for Tetrahymena, or (2) by low temperature for liver mitochondria. A special methodical part is focused on sources of errors and selection of suitable methods during metabolic depression investigation.

Collective cell migration is a key element in morphogenesis, cancer formation and wound healing. The multicellular dynamics of epithelial cell layers were studied in experiment and theory over the last years. Yet little is known about cell patches of finite size that should lead over from single cell behavior to collective motion. Here we study the migration and proliferation of small assemblies of epithelial cells (5-23 cells initially). Cells are released at defined time using removable poly(ethylene glycol)-dimethlacrylate (PEG-DMA) stencils with circular apertures, wherein cells were seeded. Using time-lapse microscopy we determine cell number, cell patch area and shape of multiple patches in parallel. We confirm exponential growth in cell number but find the area of the patches expanding faster than exponential in the early phase. The area is, however, well-described if cell proliferation is superimposed by elastic area dilation assuming that the cell groups were initially compressed. The elastic relaxation time is of the same order as the measured doubling time. Furthermore, analysis of the center-of-mass movement of the patches reveals bursts of directed motion, which coincide with asymmetric cell growth. In these cases the contours of the patches seem to result from a tug-of-war like scenario of opposing leader cells.

This work aimed to study the photo disruptive effect of a Q-switched Nd:YAG laser with two different energy protocols on the rheological properties of the vitreous humor after treatment of posterior vitreous detachment (PVD). Twenty-one New Zealand albino rabbits were used in this study and divided into three groups. One group was used as control (n = 6 eyes), the second group (n = 18) was treated with Q-switched Nd:YAG laser energy of 5 mJ × 100 pulse (× means times) delivered to the anterior, middle and posterior vitreous respectively (n = 6 eyes for each). The third group (n = 18 eyes) was treated with 10 mJ × 50 pulse delivered to the anterior, middle and posterior vitreous respectively (n = 6 eyes for each). After two weeks, the protein content, refractive index (RI) and the rheological properties of vitreous humor were determined. The protein content, refractive index, consistency, shear stress and viscosity were increased especially for irradiation of the mid-vitreous, and posterior vitreous. The flow index remained below unity indicating the non-Newtonian behavior of the vitreous humor. Application of Q-switched Nd:YAG laser on mid-vitreous and posterior vitreous induce deleterious effect on the gel state of the vitreous humor.

Networks are used to abstract large, highly-coupled sets of objects. Their analyses have included network classification into a few broad classes and selection of small substructures that perform simple yet common tasks. One issue that has received little attention is how the state of a network can be moved according to a pre-specified set of guidelines. In this paper, we address this question in the context of gene networks. In general, neither the full membership of the gene network associated with a biological process nor the precise form of interactions between nodes is known. What is available, through microarrays or sequencing, are gene expression profiles of an organism or its viable mutants. Our approach relies only on these expression profiles, and not on the availability of an accurate model for the network. The first step is to select a small set of core- or master- nodes, such as transcription factors or microRNAs, that can be used to alter the levels of many of the remaining genes in the network. We ask how the state — or solution — of the gene network changes as the levels of these master nodes are altered externally. The object of our study is, not the network, but the surface of these solutions. We argue that it can be approximated using gene expression profiles of the organism and single manipulation of master node activity. This is done through an "effective model." The effective model as well as error estimates for its predictions can be derived from experimental data. The method is validated using synthetic gene networks that have stationary solutions and those that are periodically driven, e.g., circadian networks. An effective model for the oxygen-deprivation network of E.coli is constructed using previously published gene expression profiles, and used to predict the expression levels in a double knockout mutant. Less that 30% of the predictions lie outside the 5% confidence level. We propose the use of the effective model methodology to compute how Drosophila melanogaster in the normal state can be genetically altered into a pre-defined sleep deprived-like state.

We present significantly advanced studies of the previously introduced physical growth mechanism and unite it with biochemical growth factors. Obtained results allowed formulation of the general growth law which governs growth and evolutional development of all living organisms, their organs and systems. It was discovered that the growth cycle is predefined by the distribution of nutritional resources between maintenance needs and biomass production. This distribution is quantitatively defined by the growth ratio parameter, which depends on the geometry of an organism, phase of growth and, indirectly, the organism's biochemical machinery. The amount of produced biomass, in turn, defines the composition of biochemical reactions. Changing amount of nutrients diverted to biomass production is what forces organisms to proceed through the whole growth and replication cycle. The growth law can be formulated as follows: the rate of growth is proportional to influx of nutrients and growth ratio. Considering specific biochemical components of different organisms, we find influxes of required nutrients and substitute them into the growth equation; then, we compute growth curves for amoeba, wild type fission yeast, and fission yeast's mutant. In all cases, predicted growth curves correspond very well to experimental data. Obtained results prove validity and fundamental scientific value of the discovery.