Biological staining: mechanisms and theory

New staining techniques continue to be introduced, and older ones continue to be used and improved. Several factors control specificity, selectivity and visibility of the end product in any procedure using dyes, fluorochromes, inorganic reagents or histochemical reactions applied to sections or similar preparations. Local concentration of the tissue target often determines the intensity of the observed color, as does the fine structure within the object being stained, which may facilitate or impede diffusion of dyes and other reagents. Several contributions to affinity control the specificity of staining. These include electrical forces, which result in accumulation of dye ions in regions of oppositely charged tissue polyions. Weaker short-range attractions (hydrogen bonding, van der Waals forces or hydrophobic bonding, depending on the solvent) hold dyes ions and histochemical end products in contact with their macromolecular substrates. Nonionic forces can also increase visibility of stained sites by causing aggregation of dye molecules. Covalent bonds between dye and tissue result in the strongest binding, such as in methods using Schiff's reagent and possibly also some mordant dyes. The rate at which a reagent gains access to or is removed from targets in a section or other specimen affect what is stained, especially when more then one dye is used, together or sequentially. Rate-controlled staining is greatly influenced by the presence and type of embedding medium, such as a resin, that infiltrates the tissue. The rates of chemical reactions are major determinants of outcome in many histochemical techniques. Selective staining of different organelles within living cells is accomplished mainly with fluorochromes and is controlled by mechanisms different from those that apply to fixed tissues. Quantitative structure-activity relations (QSAR) of such reagents can be derived from such molecular properties as hydrophilic-hydrophobic balance, extent of conjugated bond systems, acid-base properties and ionic charge. The QSAR correlates with staining of endoplasmic reticulum, lysosomes, mitochondria, DNA, or the plasma membranes of living cells.     

Biological computation: hearts and flytraps

The original computers were people using algorithms to get mathematical results such as rocket trajectories. After the invention of the digital computer, brains have been widely understood through analogies with computers and now artificial neural networks, which have strengths and drawbacks. We define and examine a new kind of computation better adapted to biological systems, called biological computation, a natural adaptation of mechanistic physical computation. Nervous systems are of course biological computers, and we focus on some edge cases of biological computing, hearts and flytraps. The heart has about the computing power of a slug, and much of its computing happens outside of its forty thousand neurons. The flytrap has about the computing power of a lobster ganglion. This account advances fundamental debates in neuroscience by illustrating ways that classical computability theory can miss complexities of biology. By this reframing of computation, we make way for resolving the disconnect between human and machine learning.

     

Biological optics: circularly polarised crustaceans

A novel visual capability, the detection of circularly polarised light, has been demonstrated in a mantis shrimp, a colourful crustacean from tropical reefs.     

Biological invasions: Lessons for ecology

Anthropogenic introduction of species is homogenizing the earth's biota. Consequences of introductions are sometimes great, and are directly related to global climate change, biodiversity AND release of genetically engineered organisms. Progress in invasion studies hinges on the following research trends: realization that species' ranges are naturally dynamic; recognition that colonist species and target communities cannot be studied independently, but that species-community interactions determine invasion success; increasingly quantitative tests of how species and habitat characteristics relate to invasibility and impact; recognition from paleobiological, experimental and modeling studies that history, chance and determinism together shape community invasibility.     

Biological Boundaries and Biological Age

The chronologic age classically used in demography is often unable to give useful information about which exact stage in development or aging processes has reached an organism. Hence, we propose here to explain in some applications for what reason the chronologic age fails in explaining totally the observed state of an organism, which leads to propose a new notion, the biological age. This biological age is essentially determined by the number of divisions before the Hayflick’s limit the tissue or mitochondrion in a critical organ (in the sense where its loss causes the death of the whole organism) has already used for its development and adult phases. We give a precise definition of the biological age of an organ based on the Hayflick’s limit of its cells and we introduce a desynchronization index (the cell entropy) for some critical tissues or membranes, which are mainly skin, intestinal endothelium, alveoli epithelium and mitochondrial inner membrane. In these actively metabolising interface tissues or membranes, there is a rapid turnover of cells, of their cytoplasmic constituents such as proteins, and of membrane lipids. The boundaries corresponding to these tissues, cells or membranes have vital functions of interface with the environment (protection, homeothermy, nutrition and respiration) and have a rapid turnover (the total cell renewal time is in mice equal to 3 weeks for the skin, 1.5 day for the intestine, 4 months for the alveolae and 11 days for mitochondrial inner membrane) conditioning their biological age. The biological age of a tissue is made of two major components: (1) first, its embryonic age based on the distance (in number of divisions) between the birth date of its first differentiated cell and the time until it reaches its final boundary at the end of its development and (2) second, its adult age whose complement until its death is just the lapse of time made of the sum of remaining cell cycle durations authorized by its Hayflick’s limit. From this definition, we calculate the global biological lifespan of an organism and revisit notions like demographic survival curves, duration and synchrony of cell cycles, living boundaries from proto-cells to organs, and embryonic and adult phases duration.