47 research outputs found

    Expression of Nestin by Neural Cells in the Adult Rat and Human Brain

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    Neurons and glial cells in the developing brain arise from neural progenitor cells (NPCs). Nestin, an intermediate filament protein, is thought to be expressed exclusively by NPCs in the normal brain, and is replaced by the expression of proteins specific for neurons or glia in differentiated cells. Nestin expressing NPCs are found in the adult brain in the subventricular zone (SVZ) of the lateral ventricle and the subgranular zone (SGZ) of the dentate gyrus. While significant attention has been paid to studying NPCs in the SVZ and SGZ in the adult brain, relatively little attention has been paid to determining whether nestin-expressing neural cells (NECs) exist outside of the SVZ and SGZ. We therefore stained sections immunocytochemically from the adult rat and human brain for NECs, observed four distinct classes of these cells, and present here the first comprehensive report on these cells. Class I cells are among the smallest neural cells in the brain and are widely distributed. Class II cells are located in the walls of the aqueduct and third ventricle. Class IV cells are found throughout the forebrain and typically reside immediately adjacent to a neuron. Class III cells are observed only in the basal forebrain and closely related areas such as the hippocampus and corpus striatum. Class III cells resemble neurons structurally and co-express markers associated exclusively with neurons. Cell proliferation experiments demonstrate that Class III cells are not recently born. Instead, these cells appear to be mature neurons in the adult brain that express nestin. Neurons that express nestin are not supposed to exist in the brain at any stage of development. That these unique neurons are found only in brain regions involved in higher order cognitive function suggests that they may be remodeling their cytoskeleton in supporting the neural plasticity required for these functions

    Circum-Mediterranean cultural heritage and medicial plant uses in traditional animal healthcare: a field survey in eight selected areas within the RUBIA project

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    During the years 2003Âż2005, a comparative ethnobotanical field survey was conducted on remedies used in traditional animal healthcare in eight Mediterranean areas. The study sites were selected within the EU-funded RUBIA project, and were as follows: the upper Kelmend Province of Albania; the Capannori area in Eastern Tuscany and the Bagnocavallo area of Romagna, Italy; Cercle de Ouezanne, Morocco; Sierra de Aracena y Picos de Aroche Natural Park in the province of Huelva, Spain; the St. Catherine area of the Sinai Peninsula, Egypt; Eastern and Western Crete, Greece; the Paphos and Larnaca areas of Cyprus; and the Mitidja area of Algeria. One hundred and thirty-six veterinary preparations and 110 plant taxa were recorded in the survey, with Asteraceae and Lamiaceae being the most quoted botanical families. For certain plant species the survey uncovered veterinary phytotherapeutical indications that were very uncommon, and to our knowledge never recorded before. These include Anabasis articulata (Chenopodiaceae), Cardopatium corymbosum (Asteraceae), Lilium martagon (Liliaceae), Dorycnium rectum (Fabaceae), Oenanthe pimpinelloides (Apiaceae), Origanum floribundum (Lamiaceae), Tuberaria lignosa (Cistaceae), and Dittrichia graveolens (Asteraceae). These phytotherapeutical indications are briefly discussed in this report, taking into account modern phytopharmacology and phytochemistry. The percentage of overall botanical veterinary taxa recorded in all the study areas was extremely low (8%), however when all taxa belonging to the same botanical genus are considered, this portion increases to 17%. Nevertheless, very few plant uses were found to be part of a presumed "Mediterranean" cultural heritage in veterinary practices, which raises critical questions about the concept of Mediterraneanism in ethnobotany and suggests that further discussion is required. Nearly the half of the recorded veterinary plant uses for mammals uncovered in this survey have also been recorded in the same areas in human folk medicine, suggesting a strong link between human and veterinary medical practices, and perhaps also suggesting the adaptive origins of a few medical practices. Since most of the recorded data concern remedies for treating cattle, sheep, goats, and camels, it would be interesting to test a few of the recorded phytotherapeuticals in the future, to see if they are indeed able to improve animal healthcare in breeding environments, or to raise the quality of dairy and meat products in the absence of classical, industrial, veterinary pharmaceuticals

    Community-Wide Assessment of Protein-Interface Modeling Suggests Improvements to Design Methodology

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    The CAPRI and CASP prediction experiments have demonstrated the power of community wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting there may be important physical chemistry missing in the energy calculations. 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the non-polar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were on average structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a non-binder

    Structure-Based Predictive Models for Allosteric Hot Spots

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    In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

    The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

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    Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events

    World Congress Integrative Medicine & Health 2017: Part one

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    Advanced models for water simulations

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