Igors Kuzmins

Cybernetics is a wide-ranging field concerned with regulatory and purposive systems. The core concept of cybernetics is circular causality or feedback—where the observed outcomes of actions are taken as inputs for further action in ways that support the pursuit and maintenance of particular conditions, or their disruption. Cybernetics is named after an example of circular causality, that of steering a ship,[a] where the helmsperson maintains a steady course in a changing environment by adjusting their steering in continual response to the effect it is observed as having.[1] Other examples of circular causal feedback include: technological devices such as thermostats (where the action of a heater responds to measured changes in temperature, regulating the temperature of the room within a set range); biological examples such as the coordination of volitional movement through the nervous system; and processes of social interaction such as conversation.[2] Cybernetics is concerned with feedback processes such as steering however they are embodied,[3] including in ecological, technological, biological, cognitive, and social systems, and in the context of practical activities such as designing, learning, managing, conversation, and the practice of cybernetics itself. Cybernetics' transdisciplinary[4] and "antidisciplinary"[5] character has meant that it intersects with a number of other fields, leading to it having both wide influence and diverse interpretations.

Cybernetics has its origins in exchanges between numerous fields during the 1940s, including anthropology, mathematics, neuroscience, psychology, and engineering. Initial developments were consolidated through meetings such as the Macy Conferences and the Ratio Club. At its most prominent during the 1950s and 1960s, cybernetics is a precursor to fields such as computing, artificial intelligence, cognitive science, complexity science, and robotics amongst others. It is closely related to systems science, which was developed in parallel. Early focuses included purposeful behaviour,[6] neural networks, heterarchy,[7] information theory, and self-organising systems. As cybernetics developed, it became broader in scope to include work in domains such as design,[8] family therapy, management and organisation, pedagogy, sociology, and the creative arts.[9] At the same time, questions arising from circular causality have been explored in relation to the philosophy of science, ethics, and constructivist approaches, while cybernetics has also been associated with counter-cultural movements.[10] Contemporary cybernetics thus varies widely in scope and focus, with cyberneticians variously adopting and combining technical, scientific, philosophical, creative, and critical approaches.

The term cybernetics comes from the ancient Greek word kybernetikos (“good at steering”), referring to the art of the helmsman. In the first half of the 19th century, the French physicist André-Marie Ampère, in his classification of the sciences, suggested that the still nonexistent science of the control of governments be called cybernetics. The term was soon forgotten, however, and it was not used again until the American mathematician Norbert Wiener published his book Cybernetics in 1948. In that book Wiener made reference to an 1868 article by the British physicist James Clerk Maxwell on governors and pointed out that the term governor is derived, via Latin, from the same Greek word that gives rise to cybernetics. The date of Wiener’s publication is generally accepted as marking the birth of cybernetics as an independent science.

Wiener defined cybernetics as “the science of control and communications in the animal and machine.” This definition relates cybernetics closely with the theory of automatic control and also with physiology, particularly the physiology of the nervous system. For instance, a “controller” might be the human brain, which might receive signals from a “monitor” (the eyes) regarding the distance between a reaching hand and an object to be picked up. The information sent by the monitor to the controller is called feedback, and on the basis of this feedback the controller might issue instructions to bring the observed behaviour (the reach of the hand) closer to the desired behaviour (the picking up of the object). Indeed, some of the earliest work done in cybernetics was the study of control rules by which human action takes place, with the goal of constructing artificial limbs that could be tied in with the brain.

In subsequent years the computer and the areas of mathematics related to it (e.g., mathematical logic) had a great influence on the development of cybernetics—for the simple reason that computers can be used not only for automatic calculation but also for all conversions of information, including the various types of information processing used in control systems. This enhanced ability of computers has made possible two different views of cybernetics. The narrower view, common in Western countries, defines cybernetics as the science of the control of complex systems of various types—technical, biological, or social. In many Western countries particular emphasis is given to aspects of cybernetics used in the generation of control systems in technology and in living organisms. A broader view of cybernetics arose in Russia and the other Soviet republics and prevailed there for many years. In this broader definition, cybernetics includes not only the science of control but all forms of information processing as well. In this way computer science, considered a separate discipline in the West, is included as one of the component parts of cybernetics.

In translation, messenger RNA (mRNA) is decoded in a ribosome, outside the nucleus, to produce a specific amino acid chain, or polypeptide. The polypeptide later folds into an active protein and performs its functions in the cell. The ribosome facilitates decoding by inducing the binding of complementary tRNA anticodon sequences to mRNA codons. The tRNAs carry specific amino acids that are chained together into a polypeptide as the mRNA passes through and is "read" by the ribosome.

Translation proceeds in three phases:

1. Initiation: The ribosome assembles around the target mRNA. The first tRNA is attached at the start codon.
2. Elongation: The last tRNA validated by the small ribosomal subunit (accommodation) transfers the amino acid it carries to the large ribosomal subunit which binds it to the one of the precedingly admitted tRNA (transpeptidation). The ribosome then moves to the next mRNA codon to continue the process (translocation), creating an amino acid chain.
3. Termination: When a stop codon is reached, the ribosome releases the polypeptide. The ribosomal complex remains intact and moves on to the next mRNA to be translated.

In prokaryotes (bacteria and archaea), translation occurs in the cytosol, where the large and small subunits of the ribosome bind to the mRNA. In eukaryotes, translation occurs in the cytoplasm or across the membrane of the endoplasmic reticulum in a process called co-translational translocation. In co-translational translocation, the entire ribosome/mRNA complex binds to the outer membrane of the rough endoplasmic reticulum (ER) and the new protein is synthesized and released into the ER; the newly created polypeptide can be stored inside the ER for future vesicle transport and secretion outside the cell, or immediately secreted.

Many types of transcribed RNA, such as transfer RNA, ribosomal RNA, and small nuclear RNA, do not undergo translation into proteins.

A number of antibiotics act by inhibiting translation. These include anisomycin, cycloheximide, chloramphenicol, tetracycline, streptomycin, erythromycin, and puromycin. Prokaryotic ribosomes have a different structure from that of eukaryotic ribosomes, and thus antibiotics can specifically target bacterial infections without any harm to a eukaryotic host's cells.

• Ribosomes bind to mRNA in the cytoplasm and move along the molecule in a 5’ – 3’ direction until it reaches a start codon (AUG)
• Anticodons on tRNA molecules align opposite appropriate codons according to complementary base pairing (e.g. AUG = UAC)
• Each tRNA molecule carries a specific amino acid (according to the genetic code)
• Ribosomes catalyse the formation of peptide bonds between adjacent amino acids (via condensation reactions)
• The ribosome moves along the mRNA molecule synthesising a polypeptide chain until it reaches a stop codon
• At this point translation ceases and the polypeptide chain is released

The key components of translation are:

• Messenger RNA (goes to…)
• Ribosome (reads sequence in …)
• Codons (recognised by …)
• Anticodons (found on …)
• Transfer RNA (which carries …)
• Amino acids (which join via …)
• Peptide bonds (to form …)
• Polypeptides

Abstract

Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for transcriptome-wide analysis of differential gene expression and differential splicing of mRNAs. However, as next-generation sequencing technologies have developed, so too has RNA-seq. Now, RNA-seq methods are available for studying many different aspects of RNA biology, including single-cell gene expression, translation (the translatome) and RNA structure (the structurome). Exciting new applications are being explored, such as spatial transcriptomics (spatialomics). Together with new long-read and direct RNA-seq technologies and better computational tools for data analysis, innovations in RNA-seq are contributing to a fuller understanding of RNA biology, from questions such as when and where transcription occurs to the folding and intermolecular interactions that govern RNA function.

he goal of synthetic biology is to generate an array of tunable and characterized parts, or modules, with which any desirable synthetic biological circuit can be easily designed and implemented.[2] These circuits can serve as a method to modify cellular functions, create cellular responses to environmental conditions, or influence cellular development. By implementing rational, controllable logic elements in cellular systems, researchers can use living systems as engineered "biological machines" to perform a vast range of useful functions.

he goal of synthetic biology is to generate an array of tunable and characterized parts, or modules, with which any desirable synthetic biological circuit can be easily designed and implemented.[2] These circuits can serve as a method to modify cellular functions, create cellular responses to environmental conditions, or influence cellular development. By implementing rational, controllable logic elements in cellular systems, researchers can use living systems as engineered "biological machines" to perform a vast range of useful functions.

In vitro diagnosticsIn vitro diagnostics (IVDs) are tests that can detect disease, conditions and infections. In vitro simply means ‘in glass’, meaning these tests are typically conducted in test tubes and similar equipment, as opposed to in vivo tests, which are conducted in the body itself. In vitro tests may be done in laboratories, health care facilities or even in the home. The tests themselves can be performed on a variety of instruments ranging from small, handheld tests to complex laboratory instruments. They allow doctors to diagnose patients effectively and work to provide appropriate treatments. Diagnosis is a driver of patient, financial and health systems impact, and a critical enabler of universal health coverage, but it is also the weakest link in the care cascade. This is especially true in primary healthcare settings in low- and middle-income countries. These countries often lack an integrated network of laboratories used for such diagnosis; however, broad set of IVDs is available for testing patients in the primary care setting where laboratories are not available.