Knowledge management

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Knowledge_management 

Knowledge management (KM) is the collection of methods relating to creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organisational objectives by making the best use of knowledge.

An established discipline since 1991, KM includes courses taught in the fields of business administration, information systems, management, library, and information science. Other fields may contribute to KM research, including information and media, computer science, public health and public policy. Several universities offer dedicated master's degrees in knowledge management.

Many large companies, public institutions, and non-profit organisations have resources dedicated to internal KM efforts, often as a part of their business strategy, IT, or human resource management departments. Several consulting companies provide advice regarding KM to these organizations.

Knowledge management efforts typically focus on organisational objectives such as improved performance, competitive advantage, innovation, the sharing of lessons learned, integration, and continuous improvement of the organisation. These efforts overlap with organisational learning and may be distinguished from that by a greater focus on the management of knowledge as a strategic asset and on encouraging the sharing of knowledge. KM is an enabler of organizational learning.

The most complex scenario for knowledge management may be found in the context of supply chain as it involves multiple companies without an ownership relationship or hierarchy between them, being called by some authors as transorganizational or interorganizational knowledge. That complexity is additionally increased by industry 4.0 (or 4th industrial revolution) and digital transformation, as new challenges emerge from both the volume and speed of information flows and knowledge generation.

History

Knowledge management efforts have a long history, including on-the-job discussions, formal apprenticeship, discussion forums, corporate libraries, professional training, and mentoring programs. With increased use of computers in the second half of the 20th century, specific adaptations of technologies such as knowledge bases, expert systems, information repositories, group decision support systems, intranets, and computer-supported cooperative work have been introduced to further enhance such efforts.

In 1999, the term personal knowledge management was introduced; it refers to the management of knowledge at the individual level.

In the enterprise, early collections of case studies recognised the importance of knowledge management dimensions of strategy, process and measurement. Key lessons learned include people and the cultural norms which influence their behaviors are the most critical resources for successful knowledge creation, dissemination and application; cognitive, social and organisational learning processes are essential to the success of a knowledge management strategy; and measurement, benchmarking and incentives are essential to accelerate the learning process and to drive cultural change. In short, knowledge management programs can yield impressive benefits to individuals and organisations if they are purposeful, concrete and action-orientated.

Research

KM emerged as a scientific discipline in the early 1990s. It was initially supported by individual practitioners, when Skandia hired Leif Edvinsson of Sweden as the world's first Chief Knowledge Officer (CKO). Hubert Saint-Onge (formerly of CIBC, Canada), started investigating KM long before that. The objective of CKOs is to manage and maximise the intangible assets of their organizations. Gradually, CKOs became interested in practical and theoretical aspects of KM, and the new research field was formed. The KM idea has been taken up by academics, such as Ikujiro Nonaka (Hitotsubashi University), Hirotaka Takeuchi (Hitotsubashi University), Thomas H. Davenport (Babson College) and Baruch Lev (New York University).

In 2001, Thomas A. Stewart, former editor at Fortune magazine and subsequently the editor of Harvard Business Review, published a cover story highlighting the importance of intellectual capital in organizations. The KM discipline has been gradually moving towards academic maturity. First, is a trend toward higher cooperation among academics; single-author publications are less common. Second, the role of practitioners has changed. Their contribution to academic research declined from 30% of overall contributions up to 2002, to only 10% by 2009. Third, the number of academic knowledge management journals has been steadily growing, currently reaching 27 outlets.

Multiple KM disciplines exist; approaches vary by author and school. As the discipline matured, academic debates increased regarding theory and practice, including:

• Techno-centric with a focus on technology, ideally those that enhance knowledge sharing and creation.
• Organisational with a focus on how an organisation can be designed to facilitate knowledge processes best.
• Ecological with a focus on the interaction of people, identity, knowledge, and environmental factors as a complex adaptive system akin to a natural ecosystem.

Regardless of the school of thought, core components of KM roughly include people/culture, processes/structure and technology. The details depend on the perspective. KM perspectives include:

• community of practice
• social network analysis
• intellectual capital
• information theory
• complexity science
• constructivism

The practical relevance of academic research in KM has been questioned with action research suggested as having more relevance and the need to translate the findings presented in academic journals to a practice.

Dimensions

Different frameworks for distinguishing between different 'types of' knowledge exist. One proposed framework for categorising the dimensions of knowledge distinguishes tacit knowledge and explicit knowledge. Tacit knowledge represents internalised knowledge that an individual may not be consciously aware of, such as to accomplish particular tasks. At the opposite end of the spectrum, explicit knowledge represents knowledge that the individual holds consciously in mental focus, in a form that can easily be communicated to others.

The Knowledge Spiral as described by Nonaka & Takeuchi.

Ikujiro Nonaka proposed a model (SECI, for Socialisation, Externalisation, Combination, Internalisation) which considers a spiraling interaction between explicit knowledge and tacit knowledge. In this model, knowledge follows a cycle in which implicit knowledge is 'extracted' to become explicit knowledge, and explicit knowledge is 're-internalised' into implicit knowledge.

Hayes and Walsham (2003) describe knowledge and knowledge management as two different perspectives. The content perspective suggests that knowledge is easily stored; because it may be codified, while the relational perspective recognises the contextual and relational aspects of knowledge which can make knowledge difficult to share outside the specific context in which it is developed.

Early research suggested that KM needs to convert internalised tacit knowledge into explicit knowledge to share it, and the same effort must permit individuals to internalise and make personally meaningful any codified knowledge retrieved from the KM effort.

Subsequent research suggested that a distinction between tacit knowledge and explicit knowledge represented an oversimplification and that the notion of explicit knowledge is self-contradictory. Specifically, for knowledge to be made explicit, it must be translated into information (i.e., symbols outside our heads). More recently, together with Georg von Krogh and Sven Voelpel, Nonaka returned to his earlier work in an attempt to move the debate about knowledge conversion forward.

A second proposed framework for categorising knowledge dimensions distinguishes embedded knowledge of a system outside a human individual (e.g., an information system may have knowledge embedded into its design) from embodied knowledge representing a learned capability of a human body's nervous and endocrine systems.

A third proposed framework distinguishes between the exploratory creation of "new knowledge" (i.e., innovation) vs. the transfer or exploitation of "established knowledge" within a group, organisation, or community. Collaborative environments such as communities of practice or the use of social computing tools can be used for both knowledge creation and transfer.

Strategies

Knowledge may be accessed at three stages: before, during, or after KM-related activities. Organisations have tried knowledge capture incentives, including making content submission mandatory and incorporating rewards into performance measurement plans. Considerable controversy exists over whether such incentives work and no consensus has emerged.

One strategy to KM involves actively managing knowledge (push strategy). In such an instance, individuals strive to explicitly encode their knowledge into a shared knowledge repository, such as a database, as well as retrieving knowledge they need that other individuals have provided (codification). Another strategy involves individuals making knowledge requests of experts associated with a particular subject on an ad hoc basis (pull strategy). In such an instance, expert individual(s) provide insights to requestor (personalisation). When talking about strategic knowledge management, the form of the knowledge and activities to share it defines the concept between codification and personalization. The form of the knowledge means that it’s either tacit or explicit. Data and information can be considered as explicit and know-how can be considered as tacit. 

Hansen et al. defined the two strategies (codification and personalisation). Codification means a system-oriented method in KM strategy for managing explicit knowledge with organizational objectives. Codification strategy is document-centered strategy, where knowledge is mainly codified as “people-to-document” method. Codification relies on information infrastructure, where explicit knowledge is carefully codified and stored. Codification focuses on collecting and storing codified knowledge in electronic databases to make it accessible. Codification can therefore refer to both tacit and explicit knowledge. In contrast, personalisation encourages individuals to share their knowledge directly. Personification means human-oriented KM strategy where the target is to improve knowledge flows through networking and integrations related to tacit knowledge with knowledge sharing and creation. Information technology plays a less important role, as it only facilitates communication and knowledge sharing.

Other knowledge management strategies and instruments for companies include:

• Knowledge sharing (fostering a culture that encourages the sharing of information, based on the concept that knowledge is not irrevocable and should be shared and updated to remain relevant)
  • Make knowledge-sharing a key role in employees' job description
  • Inter-project knowledge transfer
  • Intra-organisational knowledge sharing
  • Inter-organisational knowledge sharing
  • Knowledge retention also known as Knowledge Continuation: activities addressing the challenge of knowledge loss as a result of people leaving
  • Mapping knowledge competencies, roles and identifying current or future predicted gaps.
  • Defining for each chosen role the main knowledge that should be retained, and building rituals in which the knowledge is documented or transferred on, from the day they start their job.
  • Transfer of knowledge and information prior to employee departure by means of sharing documents, shadowing, mentoring, and more,
• Proximity & architecture (the physical situation of employees can be either conducive or obstructive to knowledge sharing)
• Storytelling (as a means of transferring tacit knowledge)
• Cross-project learning
• After-action reviews
• Knowledge mapping requires the organization to know what kind of knowledge organization has and how is it distributed throughout the company, and how to efficiently use and re-use that knowledge. (a map of knowledge repositories within a company accessible by all)
• Communities of practice
• Expert directories (to enable knowledge seeker to reach to the experts)
• Expert systems (knowledge seeker responds to one or more specific questions to reach knowledge in a repository)
• Best practice transfer
• Knowledge fairs
• Competency-based management (systematic evaluation and planning of knowledge related competences of individual organisation members)
• Master–apprentice relationship, Mentor-mentee relationship, job shadowing
• Collaborative software technologies (wikis, shared bookmarking, blogs, social software, etc.)
• Knowledge repositories (databases, bookmarking engines, etc.)
• Measuring and reporting intellectual capital (a way of making explicit knowledge for companies)
• Knowledge brokers (some organisational members take on responsibility for a specific "field" and act as first reference on a specific subject)
• Knowledge farming (using note-taking software to cultivate a knowledge graph, part of knowledge agriculture)
• Knowledge capturing (refers to a process where trained people extract valuable or else desired knowledge from experts and embed it in databases)

Motivations

Multiple motivations lead organisations to undertake KM. Typical considerations include:

• Making available increased knowledge content in the development and provision of products and services
• Achieving shorter development cycles
• Improving consistency of knowledge and standardized expert skills among staff
• Facilitating and managing innovation and organisational learning
• Leveraging expertises across the organisation
• Increasing network connectivity between internal and external individuals
• Managing business environments and allowing employees to obtain relevant insights and ideas appropriate to their work
• Solving intractable or wicked problems
• Managing intellectual capital and assets in the workforce (such as the expertise and know-how possessed by key individuals or stored in repositories)

KM technologies

Knowledge management (KM) technology can be categorised:

• Groupware—Software that facilitates collaboration and sharing of organisational information. Such applications provide tools for threaded discussions, document sharing, organisation-wide uniform email, and other collaboration-related features.
• Workflow systems—Systems that allow the representation of processes associated with the creation, use and maintenance of organisational knowledge, such as the process to create and utilise forms and documents.
• Content management and document management systems—Software systems that automate the process of creating web content and/or documents. Roles such as editors, graphic designers, writers and producers can be explicitly modeled along with the tasks in the process and validation criteria. Commercial vendors started either to support documents or to support web content but as the Internet grew these functions merged and vendors now perform both functions.
• Enterprise portals—Software that aggregates information across the entire organisation or for groups such as project teams.
• eLearning—Software that enables organisations to create customised training and education. This can include lesson plans, monitoring progress and online classes.
• Planning and scheduling software—Software that automates schedule creation and maintenance. The planning aspect can integrate with project management software.
• Telepresence—Software that enables individuals to have virtual "face-to-face" meetings without assembling at one location. Videoconferencing is the most obvious example.
• Semantic technology such as ontologies—Systems that encode meaning alongside data to give machines the ability to extract and infer information.

These categories overlap. Workflow, for example, is a significant aspect of a content or document management systems, most of which have tools for developing enterprise portals.

Proprietary KM technology products such as Lotus Notes defined proprietary formats for email, documents, forms, etc. The Internet drove most vendors to adopt Internet formats. Open-source and freeware tools for the creation of blogs and wikis now enable capabilities that used to require expensive commercial tools.

KM is driving the adoption of tools that enable organisations to work at the semantic level, as part of the Semantic Web. Some commentators have argued that after many years the Semantic Web has failed to see widespread adoption, while other commentators have argued that it has been a success.

Knowledge barriers

Just like knowledge transfer and knowledge sharing, the term "knowledge barriers" is not a uniformly defined term and differs in its meaning depending on the author. Knowledge barriers can be associated with high costs for both companies and individuals.

Knowledge retention

Knowledge retention is part of knowledge management. It helps convert tacit form of knowledge into an explicit form. It is a complex process which aims to reduce the knowledge loss in the organization.  Knowledge retention is needed when expert knowledge workers leave the organization after a long career. Retaining knowledge prevents losing intellectual capital. 

According to DeLong(2004) knowledge retention strategies are divided into four main categories:

• Human resources, processes and practices
• Knowledge transfer practices
• Knowledge recovery practices
• Information technologies used to capture, store and share knowledge.

Knowledge retention projects are usually introduced in three stages: decision making, planning and implementation. There are differences among researchers on the terms of the stages. For example, Dalkir talks about knowledge capture, sharing and acquisition and Doan et al. introduces initiation, implementation and evaluation. Furthermore, Levy introduces three steps (scope, transfer, integration) but also recognizes a “zero stage” for initiation of the project.

Neurogenesis

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Neurogenesis 

 

Neurogenesis
A neurosphere of neural stem cells in rat embryo spreads out into a single layer of cells. A) Neurosphere of subventricular zone cells after two days in culture. B) Shows the neurosphere at four days in culture and cells migrating away. C) Cells at the periphery of the neurosphere mostly having extending processes.
Identifiers
MeSH	D055495

Neurogenesis is the process by which nervous system cells, the neurons, are produced by neural stem cells (NSCs). It occurs in all species of animals except the porifera (sponges) and placozoans. Types of NSCs include neuroepithelial cells (NECs), radial glial cells (RGCs), basal progenitors (BPs), intermediate neuronal precursors (INPs), subventricular zone astrocytes, and subgranular zone radial astrocytes, among others.

Neurogenesis is most active during embryonic development and is responsible for producing all the various types of neurons of the organism, but it continues throughout adult life in a variety of organisms. Once born, neurons do not divide (see mitosis), and many will live the lifespan of the animal.

Neurogenesis in mammals

Developmental neurogenesis

Model of mammalian neurogenesis 

During embryonic development, the mammalian central nervous system (CNS; brain and spinal cord) is derived from the neural tube, which contains NSCs that will later generate neurons. However, neurogenesis doesn't begin until a sufficient population of NSCs has been achieved. These early stem cells are called neuroepithelial cells (NEC)s, but soon take on a highly elongated radial morphology and are then known as radial glial cells (RGC)s. RGCs are the primary stem cells of the mammalian CNS, and reside in the embryonic ventricular zone, which lies adjacent to the central fluid-filled cavity (ventricular system) of the neural tube. Following RGC proliferation, neurogenesis involves a final cell division of the parent RGC, which produces one of two possible outcomes. First, this may generate a subclass of neuronal progenitors called intermediate neuronal precursors (INP)s, which will divide one or more times to produce neurons. Alternatively, daughter neurons may be produced directly. Neurons do not immediately form neural circuits through the growth of axons and dendrites. Instead, newborn neurons must first migrate long distances to their final destinations, maturing and finally generating neural circuitry. For example, neurons born in the ventricular zone migrate radially to the cortical plate, which is where neurons accumulate to form the cerebral cortex. Thus, the generation of neurons occurs in a specific tissue compartment or 'neurogenic niche' occupied by their parent stem cells.

The rate of neurogenesis and the type of neuron generated (broadly, excitatory or inhibitory) are principally determined by molecular and genetic factors. These factors notably include the Notch signaling pathway, and many genes have been linked to Notch pathway regulation. The genes and mechanisms involved in regulating neurogenesis are the subject of intensive research in academic, pharmaceutical, and government settings worldwide.

The amount of time required to generate all the neurons of the CNS varies widely across mammals, and brain neurogenesis is not always complete by the time of birth. For example, mice undergo cortical neurogenesis from about embryonic day (post-conceptional day) (E)11 to E17, and are born at about E19.5. Ferrets are born at E42, although their period of cortical neurogenesis does not end until a few days after birth. In contrast, neurogenesis in humans generally begins around gestational week (GW) 10 and ends around GW 25 with birth about GW 38–40.

Epigenetic modification

As embryonic development of the mammalian brain unfolds, neural progenitor and stem cells switch from proliferative divisions to differentiative divisions. This progression leads to the generation of neurons and glia that populate cortical layers. Epigenetic modifications play a key role in regulating gene expression in the cellular differentiation of neural stem cells. Epigenetic modifications include DNA cytosine methylation to form 5-methylcytosine and 5-methylcytosine demethylation. These modifications are critical for cell fate determination in the developing and adult mammalian brain.

DNA cytosine methylation is catalyzed by DNA methyltransferases (DNMTs). Methylcytosine demethylation is catalyzed in several stages by TET enzymes that carry out oxidative reactions (e.g. 5-methylcytosine to 5-hydroxymethylcytosine) and enzymes of the DNA base excision repair (BER) pathway.

Adult neurogenesis

Main article: Adult neurogenesis

Neurogenesis can be a complex process in some mammals. In rodents for example, neurons in the central nervous system arise from three types of neural stem and progenitor cells: neuroepithelial cells, radial glial cells and basal progenitors, which go through three main divisions: symmetric proliferative division; asymmetric neurogenic division; and symmetric neurogenic division. Out of all the three cell types, neuroepithelial cells that pass through neurogenic divisions have a much more extended cell cycle than those that go through proliferative divisions, such as the radial glial cells and basal progenitors. In the human, adult neurogenesis has been shown to occur at low levels compared with development, and in only three regions of the brain: the adult subventricular zone (SVZ) of the lateral ventricles, the amygdala and the dentate gyrus of the hippocampus; although more recent (2020) research confirms adult neurogenesis throughout the brain.

Subventricular zone

In many mammals, including rodents, the olfactory bulb is a brain region containing cells that detect smell, featuring integration of adult-born neurons, which migrate from the SVZ of the striatum to the olfactory bulb through the rostral migratory stream (RMS). The migrating neuroblasts in the olfactory bulb become interneurons that help the brain communicate with these sensory cells. The majority of those interneurons are inhibitory granule cells, but a small number are periglomerular cells. In the adult SVZ, the primary neural stem cells are SVZ astrocytes rather than RGCs. Most of these adult neural stem cells lie dormant in the adult, but in response to certain signals, these dormant cells, or B cells, go through a series of stages, first producing proliferating cells, or C cells. The C cells then produce neuroblasts, or A cells, that will become neurons.

Hippocampus

Significant neurogenesis also occurs during adulthood in the hippocampus of many mammals, from rodents to some primates, although its existence in adult humans is debated. The hippocampus plays a crucial role in the formation of new declarative memories, and it has been theorized that the reason human infants cannot form declarative memories is because they are still undergoing extensive neurogenesis in the hippocampus and their memory-generating circuits are immature. Many environmental factors, such as exercise, stress, and antidepressants have been reported to change the rate of neurogenesis within the hippocampus of rodents. Some evidence indicates postnatal neurogenesis in the human hippocampus decreases sharply in newborns for the first year or two after birth, dropping to "undetectable levels in adults."

Neurogenesis in other organisms

Neurogenesis has been best characterized in model organisms such as the fruit fly Drosophila melanogaster. Neurogenesis in these organisms occur in the medulla cortex region of their optic lobes. These organisms can represent a model for the genetic analysis of adult neurogenesis and brain regeneration. There has been research that discuss how the study of “damage-responsive progenitor cells” in Drosophila can help to identify regenerative neurogenesis and how to find new ways to increase brain rebuilding. Recently, a study was made to show how “low-level adult neurogenesis” has been identified in Drosophila, specifically in the medulla cortex region, in which neural precursors could increase the production of new neurons, making neurogenesis occur. In Drosophila, Notch signaling was first described, controlling a cell-to-cell signaling process called lateral inhibition, in which neurons are selectively generated from epithelial cells. In some vertebrates, regenerative neurogenesis has also been shown to occur.

Substance-induced neurogenesis

• DMT: In September 2020, an in vitro and in vivo study showed that DMT present in the ayahuasca infusion promotes neurogenesis. A study showed that a low dose (0.1 mg/kg) of psilocybin given to mouse increased neurogenesis in the hippocampus 2 weeks after administration, while a high dose (1 mg/kg) significantly decreased neurogenesis.

Other findings

There is evidence that new neurons are produced in the dentate gyrus of the adult mammalian hippocampus, the brain region important for learning, motivation, memory, and emotion. A study reported that newly made cells in the adult mouse hippocampus can display passive membrane properties, action potentials and synaptic inputs similar to the ones found in mature dentate granule cells. These findings suggested that these newly made cells can mature into more practical and useful neurons in the adult mammalian brain. Recent studies confirm that microglia, the resident immune cell of the brain, establish direct contacts with the cell bodies of developing neurons, and through these connections, regulate neurogenesis, migration, integration and the formation of neuronal networks.

Neuropeptide

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Neuropeptide

 

Neuropeptide Y

Neuropeptides are chemical messengers made up of small chains of amino acids that are synthesized and released by neurons. Neuropeptides typically bind to G protein-coupled receptors (GPCRs) to modulate neural activity and other tissues like the gut, muscles, and heart.

There are over 100 known neuropeptides, representing the largest and most diverse class of signaling molecules in the nervous system. Neuropeptides are synthesized from large precursor proteins which are cleaved and post-translationally processed then packaged into dense core vesicles. Neuropeptides are often co-released with other neuropeptides and neurotransmitters in a single neuron, yielding a multitude of effects. Once released, neuropeptides can diffuse widely to affect a broad range of targets.

Synthesis

Neuropeptides are synthesized from large, inactive precursor proteins called prepropeptides. Prepropeptides contain sequences for a family of distinct peptides and often contain repeated copies of the same peptides, depending on the organism. In addition to the precursor peptide sequences, prepropeptides also contain a signal peptide, spacer peptides, and cleavage sites. The signal peptide sequence guides the protein to the secretory pathway, starting at the endoplasmic reticulum. The signal peptide sequence is removed in the endoplasmic reticulum, yielding a propeptide. The propeptide travels to the Golgi apparatus where it is proteolytically cleaved and processed into multiple peptides. Peptides are packaged into dense core vesicles, where further cleaving and processing, such as C-terminal amidation, can occur. Dense core vesicles are transported throughout the neuron and can release peptides at the synaptic cleft, cell body, and along the axon.

Mechanism

Neuropeptides are released by dense core vesicles after depolarization of the cell. Compared to classical neurotransmitter signaling, neuropeptide signaling is more sensitive. Neuropeptide receptor affinity is in the nanomolar to micromolar range while neurotransmitter affinity is in the micromolar to millimolar range. Additionally, dense core vesicles contain a small amount of neuropeptide (3 - 10mM) compared to synaptic vesicles containing neurotransmitters (e.g. 100mM for acetylcholine). Evidence shows that neuropeptides are released after high-frequency firing or bursts, distinguishing dense core vesicle from synaptic vesicle release. Neuropeptides utilize volume transmission and are not reuptaken quickly, allowing diffusion across broad areas (nm to mm) to reach targets. Almost all neuropeptides bind to GPCRs, inducing second messenger cascades to modulate neural activity on long time-scales.

Expression of neuropeptides in the nervous system is diverse. Neuropeptides are often co-released with other neuropeptides and neurotransmitters, yielding a diversity of effects depending on the combination of release. For example, vasoactive intestinal peptide is typically co-released with acetylcholine. Neuropeptide release can also be specific. In Drosophila larvae, for example, eclosion hormone is expressed in just two neurons.

Discovery

The first neuropeptide, Substance P, was discovered by Ulf von Euler and John Gaddum in 1931. In the early 1900s, chemical messengers were crudely extracted from whole animal brains and tissues and studied for their physiological effects. In an effort to isolate and study acetylcholine, von Euler and Gaddum made a crude powder extract from whole equine brain and intestine and found that it induced muscle contractions and depressed blood pressure. The effects were not abolished by atropine and thus could not solely be attributed to acetylcholine. Substance P was first purified and sequenced in 1971 by Michael Chang and Susan Leeman, revealing its 11 amino-acid peptide chain. Similar methods were used to identify other neuropeptides in the early 1950s, such as vasopressin and oxytocin.

In insects, proctolin was the first neuropeptide to be isolated and sequenced. In 1975, Alvin Starratt and Brian Brown extracted the pentapeptide from hindgut muscles of the cockroach and found that its application enhanced muscle contractions. While Starratt and Brown initially thought of proctolin as an excitatory neurotransmitter, proctolin was later confirmed as a neuromodulatory peptide.

The term “neuropeptide” was first used in the 1970s by David de Wied, who studied the effects of the peptide hormones ACTH, MSH, and vasopressin on learning and memory.

Receptor targets

Most neuropeptides act on G-protein coupled receptors (GPCRs). Neuropeptide-GPCRs fall into two families: rhodopsin-like and the secretin class.  Most peptides activate a single GPCR, while some activate multiple GPCRs (e.g. AstA, AstC, DTK). Peptide-GPCR binding relationships are highly conserved across animals. Aside from conserved structural relationships, some peptide-GPCR functions are also conserved across the animal kingdom. For example, neuropeptide F/neuropeptide Y signaling is structurally and functionally conserved between insects and mammals.

Although peptides mostly target metabotropic receptors, there is some evidence that neuropeptides bind to other receptor targets. Peptide-gated ion channels (FMRFamide-gated sodium channels) have been found in snails and Hydra. Other examples of non-GPCR targets include: insulin-like peptides and tyrosine-kinase receptors in Drosophila and atrial natriuretic peptide and eclosion hormone with membrane-bound guanylyl cyclase receptors in mammals and insects.

Actions

Neuropeptides are extremely ancient and highly diverse chemical messengers. Indeed, placozoans such as Trichoplax, extremely basal animals which do not yet possess neurones, use peptides for cell-to-cell communication in a way similar to the neuropeptides of higher animals.

Due to their modulatory and diffusive nature, neuropeptides can act on multiple time and spatial scales. Below are some examples of neuropeptide actions:

Corelease

Neuropeptides are often co-released with other neurotransmitters and neuropeptides to modulate synaptic activity. Synaptic vesicles and dense core vesicles can have differential activation properties for release, resulting in context-dependent corelease combinations. For example, insect motor neurons are glutamatergic and some contain dense core vesicles with proctolin. At low frequency activation, only glutamate is released, yielding fast and rapid excitation of the muscle. At high frequency activation however, dense core vesicles release proctolin, inducing prolonged contractions. Thus, neuropeptide release can be fine-tuned to modulate synaptic activity in certain contexts.

Some regions of the nervous system are specialized to release distinctive sets of peptides. For example, the hypothalamus and the pituitary gland release peptides (e.g. TRH, GnRH, CRH, SST) that act as hormones In one subpoplation of the arcuate nucleus of the hypothalamus, three anorectic peptides are co-expressed: α-melanocyte-stimulating hormone (α-MSH), galanin-like peptide, and cocaine-and-amphetamine-regulated transcript (CART), and in another subpopulation two orexigenic peptides are co-expressed, neuropeptide Y and agouti-related peptide (AGRP). These peptides are all released in different combinations to signal hunger and satiation cues.

The following is a list of neuroactive peptides coreleased with other neurotransmitters. Transmitter names are shown in bold.

Norepinephrine (noradrenaline). In neurons of the A2 cell group in the nucleus of the solitary tract), norepinephrine co-exists with:

• Galanin
• Enkephalin
• Neuropeptide Y

GABA

• Somatostatin (in the hippocampus)
• Cholecystokinin
• Neuropeptide Y (in the arcuate nucleus)

Acetylcholine

• VIP
• Substance P

Dopamine

• Cholecystokinin
• Neurotensin
• Glucagon-like peptide-1 (in the nucleus accumbens)

Epinephrine (adrenaline)

• Neuropeptide Y
• Neurotensin

Serotonin (5-HT)

• Substance P
• TRH
• Enkephalin

Some neurons make several different peptides. For instance, Vasopressin co-exists with dynorphin and galanin in magnocellular neurons of the supraoptic nucleus and paraventricular nucleus, and with CRF (in parvocellular neurons of the paraventricular nucleus)

Oxytocin in the supraoptic nucleus co-exists with enkephalin, dynorphin, cocaine-and amphetamine regulated transcript (CART) and cholecystokinin.

Evolution of Neuropeptide Signaling

Peptides are ancient signaling systems that are found in almost all animals on Earth (sponges are the exception). Genome sequencing reveals evidence of neuropeptide genes in Cnidaria, Ctenophora, and Placozoa, some of oldest living animals with nervous systems or neural-like tissues. Recent studies also show genomic evidence of neuropeptide processing machinery in metazoans and choanoflagellates, suggesting that neuropeptide signaling may predate the development of nervous tissues. Additionally, Ctenophore and Placozoa neural signaling is entirely peptidergic and lacks the major amine neurotransmitters such as acetylcholine, dopamine, and serotonin. This also suggests that neuropeptide signaling developed before amine neurotransmitters.

Examples

Peptide signals play a role in information processing that is different from that of conventional neurotransmitters, and many appear to be particularly associated with specific behaviours. For example, oxytocin and vasopressin have striking and specific effects on social behaviours, including maternal behaviour and pair bonding. CCAP has several functions including regulating heart rate, allatostatin and proctolin regulate food intake and growth, bursicon controls tanning of the cuticle and corazonin has a role in cuticle pigmentation and moulting.

Neuroendocrinology

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Neuroendocrinology

Neuroendocrinology is the branch of biology (specifically of physiology) which studies the interaction between the nervous system and the endocrine system; i.e. how the brain regulates the hormonal activity in the body. The nervous and endocrine systems often act together in a process called neuroendocrine integration, to regulate the physiological processes of the human body. Neuroendocrinology arose from the recognition that the brain, especially the hypothalamus, controls secretion of pituitary gland hormones, and has subsequently expanded to investigate numerous interconnections of the endocrine and nervous systems.

The endocrine system consists of numerous glands throughout the body that produce and secrete hormones of diverse chemical structure, including peptides, steroids, and neuroamines. Collectively, hormones regulate many physiological processes. The neuroendocrine system is the mechanism by which the hypothalamus maintains homeostasis, regulating reproduction, metabolism, eating and drinking behaviour, energy utilization, osmolarity and blood pressure.

Neuroendocrine system

Hypothalamus

Hypothalamic interaction with the posterior and anterior pituitary glands. The hypothalamus produces the hormones oxytocin and vasopressin in its endocrine cells (left). These are released at nerve endings in the posterior pituitary gland and then secreted into the systemic circulation. The hypothalamus releases tropic hormones into the hypophyseal portal system to the anterior pituitary (right). The anterior pituitary then secretes trophic hormones into the circulation which elicit different responses from various target tissues. These responses then signal back to the hypothalamus and anterior pituitary to either stop producing or continue to produce their precursor signals.

 

Main article: Hypothalamus

The hypothalamus is commonly known as the relay center of the brain because of its role in integrating inputs from all areas of the brain and producing a specific response. In the neuroendocrine system, the hypothalamus receives electrical signals from different parts of the brain and translates those electrical signals into chemical signals in the form of hormones or releasing factors. These chemicals are then transported to the pituitary gland and from there to the systemic circulation.

Pituitary gland

Main article: Pituitary gland

The pituitary gland is divided into three lobes: the anterior pituitary, the intermediate pituitary lobe, and the posterior pituitary. The hypothalamus controls the anterior pituitary's hormone secretion by sending releasing factors, called tropic hormones, down the hypothalamo-hypophysial portal system. For example, thyrotropin-releasing hormone released by the hypothalamus in to the portal system stimulates the secretion of thyroid-stimulating hormone by the anterior pituitary.

The posterior pituitary is directly innervated by the hypothalamus; the hormones oxytocin and vasopressin are synthesized by neuroendocrine cells in the hypothalamus and stored at the nerve endings in the posterior pituitary. They are secreted directly into systemic circulation by the hypothalamic neurons.

Major neuroendocrine axes

Oxytocin and vasopressin (also called anti-diuretic hormone), the two neurohypophysial hormones of the posterior pituitary gland (the neurohypophysis), are secreted from the nerve endings of magnocellular neurosecretory cells into the systemic circulation. The cell bodies of the oxytocin and vasopressin neurons are in the paraventricular nucleus and supraoptic nucleus of the hypothalamus, respectively, and the electrical activity of these neurons is regulated by afferent synaptic inputs from other brain regions.

By contrast, the hormones of the anterior pituitary gland (the adenohypophysis) are secreted from endocrine cells that, in mammals, are not directly innervated, yet the secretion of these hormones (adrenocorticotrophic hormone, luteinizing hormone, follicle-stimulating hormone, thyroid-stimulating hormone, prolactin, and growth hormone) remains under the control of the hypothalamus. The hypothalamus controls the anterior pituitary gland via releasing factors and release-inhibiting factors; these are substances released by hypothalamic neurons into blood vessels at the base of the brain, at the median eminence. These vessels, the hypothalamo-hypophysial portal vessels, carry the hypothalamic factors to the anterior pituitary, where they bind to specific receptors on the surface of the hormone-producing cells.

For example, the secretion of growth hormone is controlled by two neuroendocrine systems: the growth hormone-releasing hormone (GHRH) neurons and the somatostatin neurons, which stimulate and inhibit GH secretion, respectively. The GHRH neurons are located in the arcuate nucleus of the hypothalamus, whereas the somatostatin cells involved in growth hormone regulation are in the periventricular nucleus. These two neuronal systems project axons to the median eminence, where they release their peptides into portal blood vessels for transport to the anterior pituitary. Growth hormone is secreted in pulses, which arise from alternating episodes of GHRH release and somatostatin release, which may reflect neuronal interactions between the GHRH and somatostatin cells, and negative feedback from growth hormone.

Functions

The neuroendocrine systems control reproduction in all its aspects, from bonding to sexual behaviour. They control spermatogenesis and the ovarian cycle, parturition, lactation, and maternal behaviour. They control the body's response to stress and infection. They regulate the body's metabolism, influencing eating and drinking behaviour, and influence how energy intake is utilised, that is, how fat is metabolised. They influence and regulate mood, body fluid and electrolyte homeostasis, and blood pressure.

The neurons of the neuroendocrine system are large; they are mini factories for producing secretory products; their nerve terminals are large and organised in coherent terminal fields; their output can often be measured easily in the blood; and what these neurons do and what stimuli they respond to are readily open to hypothesis and experiment. Hence, neuroendocrine neurons are good "model systems" for studying general questions, like "how does a neuron regulate the synthesis, packaging, and secretion of its product?" and "how is information encoded in electrical activity?"

History

Pioneers

Ernst and Berta Scharrer, of the University of Munich the Albert Einstein College of Medicine are credited as co-founders the field of neuroendocrinology with their initial observations and proposals in 1945 concerning neuropeptides.

Geoffrey Harris is considered by many to be the "father" of neuroendocrinology. Harris, the Dr. Lee's Professor of Anatomy at Oxford University, is credited with showing that the anterior pituitary gland of mammals is regulated by hormones secreted by hypothalamic neurons into the hypothalamohypophysial portal circulation. By contrast, the hormones of the posterior pituitary gland are secreted into the systemic circulation directly from the nerve endings of hypothalamic neurons. This seminal work was done in collaboration with Dora Jacobsohn of Lund University.

The first of these factors to be identified are thyrotropin-releasing hormone (TRH) and gonadotropin-releasing hormone (GnRH). TRH is a small peptide that stimulates the secretion of thyroid-stimulating hormone; GnRH (also called luteinizing hormone-releasing hormone) stimulates the secretion of luteinizing hormone and follicle-stimulating hormone.

Roger Guillemin, a medical student of Faculté de Médecine of Lyon, and Andrew W. Schally of Tulane University isolated these factors from the hypothalamus of sheep and pigs, and then identified their structures. Guillemin and Schally were awarded the Nobel Prize in Physiology and Medicine in 1977 for their contributions to understanding "the peptide hormone production of the brain".

In 1952, Andor Szentivanyi, of the University of South Florida, and Geza Filipp wrote the world's first research paper showing how neural control of immunity takes place through the hypothalamus.

Modern scope

Today, neuroendocrinology embraces a wide range of topics that arose directly or indirectly from the core concept of neuroendocrine neurons. Neuroendocrine neurons control the gonads, whose steroids, in turn, influence the brain, as do corticosteroids secreted from the adrenal gland under the influence of adrenocorticotrophic hormone. The study of these feedbacks became the province of neuroendocrinologists. The peptides secreted by hypothalamic neuroendocrine neurons into the blood proved to be released also into the brain, and the central actions often appeared to complement the peripheral actions. So understanding these central actions also became the province of neuroendocrinologists, sometimes even when these peptides cropped up in quite different parts of the brain that appeared to serve functions unrelated to endocrine regulation. Neuroendocrine neurons were discovered in the peripheral nervous system, regulating, for instance, digestion. The cells in the adrenal medulla that release adrenaline and noradrenaline proved to have properties between endocrine cells and neurons, and proved to be outstanding model systems for instance for the study of the molecular mechanisms of exocytosis. And these, too, have become, by extension, neuroendocrine systems.

Neuroendocrine systems have been important to our understanding of many basic principles in neuroscience and physiology, for instance, our understanding of stimulus-secretion coupling. The origins and significance of patterning in neuroendocrine secretion are still dominant themes in neuroendocrinology today.

Neuroendocrinology is also used as an integral part of understanding and treating neurobiological brain disorders. One example is the augmentation of the treatment of mood symptoms with thyroid hormone. Another is the finding of a transthyretin (thyroxine transport) problem in the cerebrospinal fluid of some patients diagnosed with schizophrenia.

Experimental techniques

Since the original experiments by Geoffrey Harris investigating the communication of the hypothalamus with the pituitary gland, much has been learned about the mechanistic details of this interaction. Various experimental techniques have been employed. Early experiments relied heavily on the electrophysiology techniques used by Hodgkin and Huxley. Recent approaches have incorporated various mathematical models to understand previously identified mechanisms and predict systemic response and adaptation under various circumstances.

Electrophysiology

Electrophysiology experiments were used in the early days of neuroendocrinology to identify the physiological happenings in the hypothalamus and the posterior pituitary especially. In 1950, Geoffrey Harris and Barry Cross outlined the oxytocin pathway by studying oxytocin release in response to electrical stimulation. In 1974, Walters and Hatton investigated the effect of water dehydration by electrically stimulating the supraoptic nucleus—the hypothalamic center responsible for the release of vasopressin. Glenn Hatton dedicated his career to studying the physiology of the Neurohypophyseal system, which involved studying the electrical properties of hypothalamic neurons. Doing so enabled investigation into the behavior of these neurons and the resulting physiological effects. Studying the electrical activity of neuroendocrine cells enabled the eventual distinction between central nervous neurons, neuroendocrine neurons, and endocrine cells.

Mathematical Models

Hodgkin-Huxley Model

The Hodgkin-Huxley model translates data about the current of a system at a specific voltage into time-dependent data describing the membrane potential. Experiments using this model typically rely on the same format and assumptions, but vary the differential equations to answer their particular questions. Much has been learned about vasopressin, GnRH, somatotrophs, corticotrophs, and lactotrophic hormones by employing this method.

Integrate-and-Fire Model

The integrate-and-fire model aims for mathematic simplicity in describing biological systems by focusing on, and only on the threshold activity of a neuron. By doing so, the model successfully reduces the complexity of a complicated system; however it ignores the actual mechanisms of action and replaces them with functions that define how the output of a system depends on its input. This model has been used to describe the release of hormones to the posterior pituitary gland, specifically oxytocin and vasopressin.

Functional or Mean Fields Model

The functional or mean fields model relies on the premise "simpler is better". It strives to reduce the complexity of modelling multi-faceted systems by using a single variable to describe an entire population of cells. The alternative would be to use a different set of variables for each population. When attempting to model a system where multiple populations of cells interact, using several sets quickly becomes overcomplicated. This model has been used to describe several systems, especially involving the reproductive cycle (menstrual cycles, luteinizing hormone, prolactin surges). Functional models also exist to represent cortisol secretion, and growth hormone secretion.

Unconditional love

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Unconditional_love

 

Parental love is said to be the best example of unconditional love.

Unconditional love is known as affection without any limitations, or love without conditions. This term is sometimes associated with other terms such as true altruism or complete love. Each area of expertise has a certain way of describing unconditional love, but most will agree that it is that type of love which has no bounds and is unchanging.

In Christianity, unconditional love is thought to be part of the Four Loves; affection, friendship, eros, and charity. In ethology, or the study of animal behavior, unconditional love would refer to altruism, which in turn refers to the behavior by individuals that increases the fitness of another while decreasing the fitness of the individual committing the act. In psychology, unconditional love refers to a state of mind in which one has the goal of increasing the welfare of another, despite the lack of any evidence of benefit for oneself.

Conditional love

Some authors make a distinction between unconditional love and conditional love. In conditional love, love is "earned" on the basis of conscious or unconscious conditions being met by the lover, whereas in unconditional love, love is "given freely" to the loved one "no matter what". Loving is primary. Conditional love requires some kind of finite exchange, whereas unconditional love is seen as infinite and measureless.

Unconditional love should not be confused with unconditional dedication: unconditional dedication or "duty" refers to an act of the will irrespective of feelings (e.g. a person may consider that they have a duty to stay with someone); unconditional love is an act of the feelings irrespective of will.

Unconditional love separates the individual from their behavior. However, the individual may exhibit behaviors that are unacceptable in a particular situation.

Humanistic psychology

Humanistic psychologist Carl Rogers spoke of an unconditional positive regard and dedication towards one single support. Rogers stated that the individual needed an environment that provided them with genuineness, authenticity, openness, self-disclosure, acceptance, empathy, and approval. Rogers proposed this idea of Unconditional Positive Regard not only in social and familial situations, but also encouraged getting the healthy loving environment in therapy situations as well. It is important that in face-to-face therapy settings this environment is fostered along with empathy and understanding for the individual. It is through unconditional positive regard that change happens because the individual can feel that openness, love, and ability to be themselves again which fosters a true desire to change for the right reasons. 

Also, Abraham Maslow supported the unconditional love perspective by saying that in order to grow, an individual had to have a positive perspective of themselves. In Man's Search For Meaning, logotherapist and Holocaust survivor Viktor Frankl draws parallels between the human capacity to love unconditionally and living a meaningful life. Frankl writes: "Love is the only way to grasp another human being in the innermost core of his personality. No one can become fully aware of the essence of another human being unless he loves him. ... Furthermore, by his love, the loving person enables the beloved person to actualize ... potentialities." For Frankl, unconditional love is a means by which we enable and reach human potential.

Neurological basis

There has been some evidence to support a neural basis for unconditional love, showing that it stands apart from other types of love.

In a study conducted by Mario Beauregard and his colleagues, using an fMRI procedure, they studied the brain imaging of participants who were shown different sets of images either referring to "maternal love" (unconditional love) or "romantic love". Seven areas of the brain became active when these participants called to mind feelings of unconditional love. Three of these were similar to areas that became active when it came to romantic love. The other four active parts activated during the unconditional love portions of the experiment were different, showing certain brain regions associated with rewarding aspects, pleasurable (non-sexual) feelings, and human maternal behaviors. Through the associations made between the different regions, results show that the feeling of love for someone without the need of being rewarded is different from the feeling of romantic love.

Along with the idea of "mother love", which is commonly associated with unconditional love, a study found patterns in the neuroendocrine system and motivation-affective neural system. Using the fMRI procedure, mothers watched a video of themselves playing with their children in a familiar environment, like home. The procedure found part of the amygdala and nucleus accumbens were responsive on levels of emotion and empathy. Emotion and empathy (compassion) are descriptives of love, therefore it supports the idea that the neural occurrences are evidence of unconditional love.

Religious perspective

Christianity

In Christianity, the term "unconditional love" can be used to indicate God's love for a person irrespective of that person's love for God. This comes from the concept of God sending His only Son, Jesus Christ down from heaven to earth to die on a cross in order to take the punishment for all of humanity's sins. If someone chooses to believe in this, commonly called "The Gospel", then Jesus' price on the cross pays for their sins so they can freely enter into heaven, and not hell. The term is not explicitly used in the Bible, and advocates for God's conditional or unconditional love, using different passages or interpretations to support their point of view, are both encountered due to the different facets of God's nature. The cross is a clear indicator of God's unconditional love in that there is no way to earn one's way to heaven, one must simply believe. In all other religions cited below, there is a conditional striving to achieve a sense of unconditional love, based on one's own efforts and understanding. In Christianity, it all depends on Jesus, not the person's effort nor understanding. A passage in scriptures cites this "For it is by grace you have been saved, through faith—and this is not from yourselves, it is the gift of God—" Ephesians 2:8,9, NIV. God's discipline can be viewed as conditional based on people's choices, but His actual love through Jesus is unconditional, and this is where some may become confused. His salvation is a free gift, but His discipline, which is shaping of good character, can look more conditional. Ultimately, knowing God and free passage to heaven have already been supplied by a God of unconditional love, one can simply choose to believe in order to receive such love. The civil rights leader and Pastor, Dr. Martin Luther King Jr. was quoted as saying "I believe that unarmed truth and unconditional love will have the final word in reality".

Buddhism

In Buddhism one of the most important concepts is called "bodhicitta". There are two kinds of Bodhicitta. They are relative and absolute bodhicitta.

In relative bodhicitta, one learns about the desire to gain the understanding of unconditional love, which in Buddhism is expressed as loving-kindness and compassion. The point is to develop bodhicitta for all living (sentient) beings.

Absolute bodhicitta is a more esoteric tantric teaching. Understanding the principle of loving-kindness and compassion is expressed when one treats all living beings as if one was or had been (in former lives) their own mother. One's mother will do anything for the benefit of her child. The most loving of all relationships may be that between a mother and her child. Of course, if all beings treated all other living beings as they would their own child, then there would be much less enmity in this world.

The importance of this cannot be overstated. At every moment one has the opportunity to make a choice how to act, and to be completely mindful of one's actions means that in every interaction with another being one will consciously act with loving-kindness and compassion toward every other being, no matter what the nature of that interaction.

Hinduism

Hinduism and Buddhism, the Sanskrit word "bhakti" is apparently used by some to refer to unconditional love, even though its root meaning seems to be "participate". Bhakti or bhakthi is unconditional religious devotion of a devotee in worship of a divine.

Islam

In Islamic belief, unconditional love can only be directed to Allah. The highest spiritual attainment in Islam is related to the love of God. "Yet there are men who take (for worship) others besides God, as equal (with God): They love them as they should love God. But those of Faith are overflowing in their love for God."

O lovers! The religion of the love of God is not found in Islam alone.

In the realm of love, there is neither belief, nor unbelief.

In Islamic Sufism, unconditional love is the basis for the divine love Ishq-e-Haqeeqi, elaborated by many great Muslim saints to date. Prominent mystics explain the concept in its entirety and describe its hardcore reality.

Rabia of Basra was the one who first set forth the doctrine of divine love known as ishq-e-haqeeqi and is widely considered to be the most important of the early renunciants, one mode of piety that would eventually become labeled as Sufism.

She prayed:

O Lord, if I worship You because of Fear of Hell,
then burn me in Hell;

If I worship You because I desire Paradise,
then exclude me from Paradise;

But if I worship You for Yourself alone,
then deny me not your Eternal Beauty.

Ishq itself means to love God selflessly and unconditionally. For Rumi, "Sufism" itself is Ishq and not the path of asceticism (zuhd). According to Sultan Bahoo, Ishq means to serve God unconditionally by devoting one's entire life to Him and asking no reward in return.

Other religions

Neopaganism in general, and Wicca in particular, commonly use a traditional inspirational text Charge of the Goddess, which affirms that the Goddess's "law is love unto all beings".

Mohism, China around 500 BCE, bases its entire premise on the supremacy of such an element, comparing one's duty to the indiscriminate generosity of "The Sky", or "Heaven", in contrast to Confucianism, which based its model of society on family love and duty. Later schools engaged in much debate on exactly how unconditional one could be in actual society (cf. "...who is my neighbour?" in "The Good Samaritan" story of Jesus of Nazareth).

Unitarian Universalism, though not having a set religious creed or doctrine, generally accepts the belief that all human begins are worthy and in need of unconditional love though charity in the community and spiritual understanding. The Unitarian Universalist Association explicitly argues this in the Seven Principles, where the "inherent worth and dignity" of all humans is a regularly cited source arguing for unconditional love.