Role of Fibroblast Populations in Periodontal Wound Healing and Tissue Remodeling

After injury to periodontal tissues, a sequentially phased healing response is initiated that enables wound closure and partial restoration of tissue structure and function. Wound closure in periodontal tissues involves the tightly regulated coordination of resident cells in epithelial and connective tissue compartments. Multiple cell populations in these compartments synergize their metabolic activities to reestablish a mucosal seal that involves the underlying periodontal connective tissues and the attachment of these tissues to the tooth surface. The formation of an impermeable seal around the circumference of the tooth is of particular significance in oral health since colonization of tooth surfaces by pathogenic biofilms promotes inflammation, which can contribute to periodontal tissue degradation and tooth loss. The reformation of periodontal tissue structures in the healing response centrally involves fibroblasts, which synthesize and organize the collagen fibers that link alveolar bone and gingiva to the cementum covering the tooth root. The synthesis and remodeling of nascent collagen matrices are of fundamental importance for the reestablishment of a functional periodontium and are mediated by diverse, multi-functional fibroblast populations that reside within the connective tissues of gingiva and periodontal ligament. Notably, after gingival wounding, a fibroblast sub-type (myofibroblast) arises, which is centrally involved in collagen synthesis and fibrillar remodeling. While myofibroblasts are not usually seen in healthy, mature connective tissues, their formation is enhanced by wound-healing cytokines. The formation of myofibroblasts is also modulated by the stiffness of the extracellular matrix, which is mechanosensed by resident precursor cells in the gingival connective tissue microenvironment. Here, we consider the cellular origins and the factors that control the differentiation and matrix remodeling functions of periodontal fibroblasts. An improved understanding of the regulation and function of periodontal fibroblasts will be critical for the development of new therapies to optimize the restoration of periodontal structure and function after wounding

Social Experiments in the Mesoscale: Humans Playing a Spatial Prisoner's Dilemma

Background: The evolutionary origin of cooperation among unrelated individuals remains a key unsolved issue across several disciplines. Prominent among the several mechanisms proposed to explain how cooperation can emerge is the existence of a population structure that determines the interactions among individuals. Many models have explored analytically and by simulation the effects of such a structure, particularly in the framework of the Prisoner’s Dilemma, but the results of these models largely depend on details such as the type of spatial structure or the evolutionary dynamics. Therefore, experimental work suitably designed to address this question is needed to probe these issues. Methods and Findings: We have designed an experiment to test the emergence of cooperation when humans play Prisoner’s Dilemma on a network whose size is comparable to that of simulations. We find that the cooperation level declines to an asymptotic state with low but nonzero cooperation. Regarding players ’ behavior, we observe that the population is heterogeneous, consisting of a high percentage of defectors, a smaller one of cooperators, and a large group that shares features of the conditional cooperators of public goods games. We propose an agent-based model based on the coexistence of these different strategies that is in good agreement with all the experimental observations. Conclusions: In our large experimental setup, cooperation was not promoted by the existence of a lattice beyond a residual level (around 20%) typical of public goods experiments. Our findings also indicate that both heterogeneity and a ‘‘moody’

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

How do nutrient conditions and species identity influence the impact of mesograzers in eelgrass-epiphyte systems?

Coastal eutrophication is thought to cause excessive growth of epiphytes in eelgrass beds, threatening the health and survival of these ecologically and economically valuable ecosystems worldwide. Mesograzers, small crustacean and gastropod grazers, have the potential to prevent seagrass loss by grazing preferentially and efficiently on epiphytes. We tested the impact of three mesograzers on epiphyte biomass and eelgrass productivity under threefold enriched nutrient concentrations in experimental indoor mesocosm systems under summer conditions. We compared the results with earlier identical experiments that were performed under ambient nutrient supply. The isopod Idotea baltica, the periwinkle Littorina littorea, and the small gastropod Rissoa membranacea significantly reduced epiphyte load under high nutrient supply with Rissoa being the most efficient grazer, but only high densities of Littorina and Rissoa had a significant positive effect on eelgrass productivity. Although all mesograzers increased epiphyte ingestion with higher nutrient load, most likely as a functional response to the quantitatively and qualitatively better food supply, the promotion of eelgrass growth by Idotea and Rissoa was diminished compared to the study performed under ambient nutrient supply. Littorina maintained the level of its positive impact on eelgrass productivity regardless of nutrient concentrations

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.publishedVersio

Effects of ranolazine on astrocytes and neurons in primary culture

Ranolazine (Rn) is an antianginal agent used for the treatment of chronic angina pectoris when angina is not adequately controlled by other drugs. Rn also acts in the central nervous system and it has been proposed for the treatment of pain and epileptic disorders. Under the hypothesis that ranolazine could act as a neuroprotective drug, we studied its effects on astrocytes and neurons in primary culture. We incubated rat astrocytes and neurons in primary cultures for 24 hours with Rn (10−7, 10−6 and 10−5 M). Cell viability and proliferation were measured using trypan blue exclusion assay, MTT conversion assay and LDH release assay. Apoptosis was determined by Caspase 3 activity assay. The effects of Rn on proinflammatory mediators IL-β and TNF-α was determined by ELISA technique, and protein expression levels of Smac/Diablo, PPAR-γ, Mn-SOD and Cu/Zn-SOD by western blot technique. In cultured astrocytes, Rn significantly increased cell viability and proliferation at any concentration tested, and decreased LDH leakage, Smac/Diablo expression and Caspase 3 activity indicating less cell death. Rn also increased anti-inflammatory PPAR-γ protein expression and reduced pro-inflammatory proteins IL-1 β and TNFα levels. Furthermore, antioxidant proteins Cu/Zn-SOD and Mn-SOD significantly increased after Rn addition in cultured astrocytes. Conversely, Rn did not exert any effect on cultured neurons. In conclusion, Rn could act as a neuroprotective drug in the central nervous system by promoting astrocyte viability, preventing necrosis and apoptosis, inhibiting inflammatory phenomena and inducing anti-inflammatory and antioxidant agents

Ancient mitochondrial DNA provides high-resolution time scale of the peopling of the Americas

The exact timing, route, and process of the initial peopling of the Americas remains uncertain despite much research. Archaeological evidence indicates the presence of humans as far as southern Chile by 14.6 thousand years ago (ka), shortly after the Pleistocene ice sheets blocking access from eastern Beringia began to retreat. Genetic estimates of the timing and route of entry have been constrained by the lack of suitable calibration points and low genetic diversity of Native Americans. We sequenced 92 whole mitochondrial genomes from pre-Columbian South American skeletons dating from 8.6 to 0.5 ka, allowing a detailed, temporally calibrated reconstruction of the peopling of the Americas in a Bayesian coalescent analysis. The data suggest that a small population entered the Americas via a coastal route around 16.0 ka, following previous isolation in eastern Beringia for ~2.4 to 9 thousand years after separation from eastern Siberian populations. Following a rapid movement throughout the Americas, limited gene flow in South America resulted in a marked phylogeographic structure of populations, which persisted through time. All of the ancient mitochondrial lineages detected in this study were absent from modern data sets, suggesting a high extinction rate. To investigate this further, we applied a novel principal components multiple logistic regression test to Bayesian serial coalescent simulations. The analysis supported a scenario in which European colonization caused a substantial loss of pre-Columbian lineages