Knowledge of Brazilian dentists and students in treating dentine hypersensitivity

Objective: To evaluate knowledge of undergraduates and qualified dentists from a Brazilian Dental School in treating Dentine Hypersensitivity (DH). Methodology: Data obtained from a 22-item questionnaire were analysed and arranged in distribution figures. Results: Of 100 respondents, 66.3% indicated that up to 25% of their patients had DH; 41.7%, that the duration of discomfort was up to eight weeks; 78.4%, that they examined a patient with DH within the last two-four weeks; and 70.4%, that this was done after the patient initiated the conversation on DH. Most of participants responded DH affects patients’ quality of life, and its aetiology was attrition, exposed dentine, occlusal interference, gingival recession or abrasion. The most common ways to diagnose DH were sensitivity history analysis, clinical examination, clinical testing and probing; and conflicting conditions were fractured restoration, bleaching sensitivity, marginal leakage, chipped tooth and periodontal disease. Furthermore, 82.5% and 78.7% of respondents indicated they were confident in diagnosing DH and providing advice to patients, but only 38.8% identified hydrodynamic theory as its underlying mechanism. To evaluate pain from DH they considered self-assessment, dental examination, dietary analysis and thermal assessment; and as recommendations, the use of desensitizing dentifrices, education on toothbrushing, in-office application of desensitizing products, and restorations. Conclusion: There is still confusion concerning the aetiology, the diagnosis and the subsequent management of DH, and both students and qualified dentists need better education

Selective laser melting–enabled electrospinning: Introducing complexity within electrospun membranes

Additive manufacturing technologies enable the creation of very precise and well-defined structures that can mimic hierarchical features of natural tissues. In this article, we describe the development of a manufacturing technology platform to produce innovative biodegradable membranes that are enhanced with controlled microenvironments produced via a combination of selective laser melting techniques and conventional electrospinning. This work underpins the manufacture of a new generation of biomaterial devices that have significant potential for use as both basic research tools and components of therapeutic implants. The membranes were successfully manufactured and a total of three microenvironment designs (niches) were chosen for thorough characterisation. Scanning electron microscopy analysis demonstrated differences in fibre diameters within different areas of the niche structures as well as differences in fibre density. We also showed the potential of using the microfabricated membranes for supporting mesenchymal stromal cell culture and proliferation. We demonstrated that mesenchymal stromal cells grow and populate the membranes penetrating within the niche-like structures. These findings demonstrate the creation of a very versatile tool that can be used in a variety of tissue regeneration applications including bone healing

Economic-demographic interactions in long-run growth

Cliometrics confirms that Malthus’ model of the pre-industrial economy, in which increases in productivity raise population but higher population drives down wages, is a good description for much of demographic/economic history. A contributor to the Malthusian equilibrium was the Western European Marriage Pattern, the late age of female first marriage, which promised to retard the fall of living standards by restricting fertility. The demographic transition and the transition from Malthusian economies to modern economic growth attracted many Cliometric models surveyed here. A popular model component is that lower levels of mortality over many centuries increased the returns to, or preference for, human capital investment so that technical progress eventually accelerated. This initially boosted birth rates and population growth accelerated. Fertility decline was earliest and most striking in late eighteenth century France. By the 1830s the fall in French marital fertility is consistent with a response to the rising opportunity cost of children. The rest of Europe did not begin to follow until end of the nineteenth century. Interactions between the economy and migration have been modelled with Cliometric structures closely related to those of natural increase and the economy. Wages were driven up by emigration from Europe and reduced in the economies receiving immigrants

Too close for comfort: spatial patterns in acorn barnacle populations

Spatial patterns in aggregations form as a result of the interplay between costs and benefits experienced by individuals. Such self-organisation of aggregations can be explained using a zonal model in which a short-range zone of repulsion and longer-range zone of attraction surrounding individuals leads to emergent pattern properties. The signal of these processes can be detected using spatial pattern analyses. Furthermore, in sessile organisms, post-settlement mortality reveals the relative costs and benefits of positions within the aggregation. Acorn barnacles are known to require contact with conspecifics for reproduction and are therefore believed to aggregate for this purpose; isolated individuals may also be more susceptible to abiotic stress and predation. At short distances, however, competition for space and resources is likely to occur. In this study spatial patterns of barnacles (Semibalanus balanoides L.) were analysed using pair-correlation functions. Individuals were dispersed at distances below 0.30 cm, but peak relative density occurred at a distance of 0.36 cm from conspecifics. This is much closer than required for reproductive access, implying a strong aggregative drive, up to the point of physical contact with neighbours. Nevertheless, analysis of dead barnacles illustrated that such proximity carries a cost as barnacles with many neighbours were more likely to have died. The inferences obtained from these patterns are that barnacles aggregate as closely as they can, and that local neighbourhood competition is a powerful determinant of mortality. These processes give rise to the observed pattern properties

Effects of Simulated Microgravity on Embryonic Stem Cells

There have been many studies on the biological effects of simulated microgravity (SMG) on differentiated cells or adult stem cells. However, there has been no systematic study on the effects of SMG on embryonic stem (ES) cells. In this study, we investigated various effects (including cell proliferation, cell cycle distribution, cell differentiation, cell adhesion, apoptosis, genomic integrity and DNA damage repair) of SMG on mouse embryonic stem (mES) cells. Mouse ES cells cultured under SMG condition had a significantly reduced total cell number compared with cells cultured under 1 g gravity (1G) condition. However, there was no significant difference in cell cycle distribution between SMG and 1G culture conditions, indicating that cell proliferation was not impaired significantly by SMG and was not a major factor contributing to the total cell number reduction. In contrast, a lower adhesion rate cultured under SMG condition contributed to the lower cell number in SMG. Our results also revealed that SMG alone could not induce DNA damage in mES cells while it could affect the repair of radiation-induced DNA lesions of mES cells. Taken together, mES cells were sensitive to SMG and the major alterations in cellular events were cell number expansion, adhesion rate decrease, increased apoptosis and delayed DNA repair progression, which are distinct from the responses of other types of cells to SMG

Protein structure and evolution: are they constrained globally by a principle derived from information theory?

That the physicochemical properties of amino acids constrain the structure, function and evolution of proteins is not in doubt. However, principles derived from information theory may also set bounds on the structure (and thus also the evolution) of proteins. Here we analyze the global properties of the full set of proteins in release 13-11 of the SwissProt database, showing by experimental test of predictions from information theory that their collective structure exhibits properties that are consistent with their being guided by a conservation principle. This principle (Conservation of Information) defines the global properties of systems composed of discrete components each of which is in turn assembled from discrete smaller pieces. In the system of proteins, each protein is a component, and each protein is assembled from amino acids. Central to this principle is the inter-relationship of the unique amino acid count and total length of a protein and its implications for both average protein length and occurrence of proteins with specific unique amino acid counts. The unique amino acid count is simply the number of distinct amino acids (including those that are post-translationally modified) that occur in a protein, and is independent of the number of times that the particular amino acid occurs in the sequence. Conservation of Information does not operate at the local level (it is independent of the physicochemical properties of the amino acids) where the influences of natural selection are manifest in the variety of protein structure and function that is well understood. Rather, this analysis implies that Conservation of Information would define the global bounds within which the whole system of proteins is constrained; thus it appears to be acting to constrain evolution at a level different from natural selection, a conclusion that appears counter-intuitive but is supported by the studies described herein

Inhibition of nuclear factor kappa-B signaling reduces growth in medulloblastoma in vivo

Abstract Background Medulloblastoma is a highly malignant pediatric brain tumor that requires surgery, whole brain and spine irradiation, and intense chemotherapy for treatment. A more sophisticated understanding of the pathophysiology of medulloblastoma is needed to successfully reduce the intensity of treatment and improve outcomes. Nuclear factor kappa-B (NFκB) is a signaling pathway that controls transcriptional activation of genes important for tight regulation of many cellular processes and is aberrantly expressed in many types of cancer. Methods To test the importance of NFκB to medulloblastoma cell growth, the effects of multiple drugs that inhibit NFκB, pyrrolidine dithiocarbamate, diethyldithiocarbamate, sulfasalazine, curcumin and bortezomib, were studied in medulloblastoma cell lines compared to a malignant glioma cell line and normal neurons. Expression of endogenous NFκB was investigated in cultured cells, xenograft flank tumors, and primary human tumor samples. A dominant negative construct for the endogenous inhibitor of NFκB, IκB, was prepared from medulloblastoma cell lines and flank tumors were established to allow specific pathway inhibition. Results We report high constitutive activity of the canonical NFκB pathway, as seen by Western analysis of the NFκB subunit p65, in medulloblastoma tumors compared to normal brain. The p65 subunit of NFκB is extremely highly expressed in xenograft tumors from human medulloblastoma cell lines; though, conversely, the same cells in culture have minimal expression without specific stimulation. We demonstrate that pharmacological inhibition of NFκB in cell lines halts proliferation and leads to apoptosis. We show by immunohistochemical stain that phosphorylated p65 is found in the majority of primary tumor cells examined. Finally, expression of a dominant negative form of the endogenous inhibitor of NFκB, dnIκB, resulted in poor xenograft tumor growth, with average tumor volumes 40% smaller than controls. Conclusions These data collectively demonstrate that NFκB signaling is important for medulloblastoma tumor growth, and that inhibition can reduce tumor size and viability in vivo. We discuss the implications of NFκB signaling on the approach to managing patients with medulloblastoma in order to improve clinical outcomes.</p

Stereological Analysis of Neuron, Glial and Endothelial Cell Numbers in the Human Amygdaloid Complex

Cell number alterations in the amygdaloid complex (AC) might coincide with neurological and psychiatric pathologies with anxiety imbalances as well as with changes in brain functionality during aging. This stereological study focused on estimating, in samples from 7 control individuals aged 20 to 75 years old, the number and density of neurons, glia and endothelial cells in the entire AC and in its 5 nuclear groups (including the basolateral (BL), corticomedial and central groups), 5 nuclei and 13 nuclear subdivisions. The volume and total cell number in these territories were determined on Nissl-stained sections with the Cavalieri principle and the optical fractionator. The AC mean volume was 956 mm3 and mean cell numbers (x106) were: 15.3 neurons, 60 glial cells and 16.8 endothelial cells. The numbers of endothelial cells and neurons were similar in each AC region and were one fourth the number of glial cells. Analysis of the influence of the individuals’ age at death on volume, cell number and density in each of these 24 AC regions suggested that aging does not affect regional size or the amount of glial cells, but that neuron and endothelial cell numbers respectively tended to decrease and increase in territories such as AC or BL. These accurate stereological measures of volume and total cell numbers and densities in the AC of control individuals could serve as appropriate reference values to evaluate subtle alterations in this structure in pathological conditions

Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with (“lesional”) and without (“non-lesional”) radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68–75%) compared to models to lateralize the side of TLE (56–73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67–75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68–76%) than models that stratified non-lesional patients (53–62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care