Oral Condition and Incident Coronary Heart Disease: A Clustering Analysis

Poor oral health has been linked to coronary heart disease (CHD). Clustering clinical oral conditions routinely recorded in adults may identify their CHD risk profile. Participants from the Paris Prospective Study 3 received, between 2008 and 2012, a baseline routine full-mouth clinical examination and an extensive physical examination and were thereafter followed up every 2 y until September 2020. Three axes defined oral health conditions: 1) healthy, missing, filled, and decayed teeth; 2) masticatory capacity denoted by functional masticatory units; and 3) gingival inflammation and dental plaque. Hierarchical cluster analysis was performed with multivariate Cox proportional hazards regression models and adjusted for age, sex, smoking, body mass index, education, deprivation (EPICES score; Evaluation of Deprivation and Inequalities in Health Examination Centres), hypertension, type 2 diabetes, LDL and HDL serum cholesterol (low- and high-density lipoprotein), triglycerides, lipid-lowering medications, NT-proBNP and IL-6 serum level. A sample of 5,294 participants (age, 50 to 75 y; 37.10% women) were included in the study. Cluster analysis identified 3,688 (69.66%) participants with optimal oral health and preserved masticatory capacity (cluster 1), 1,356 (25.61%) with moderate oral health and moderately impaired masticatory capacity (cluster 2), and 250 (4.72%) with poor oral health and severely impaired masticatory capacity (cluster 3). After a median follow-up of 8.32 y (interquartile range, 8.00 to 10.05), 128 nonfatal incident CHD events occurred. As compared with cluster 1, the risk of CHD progressively increased from cluster 2 (hazard ratio, 1.45; 95% CI, 0.98 to 2.15) to cluster 3 (hazard ratio, 2.47; 95% CI, 1.34 to 4.57; P < 0.05 for trend). To conclude, middle-aged individuals with poor oral health and severely impaired masticatory capacity have more than twice the risk of incident CHD than those with optimal oral health and preserved masticatory capacity (ClinicalTrials.gov NCT00741728)

Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo

Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype

Edge-centric queries stream management based on an ensemble model

The Internet of things (IoT) involves numerous devices that can interact with each other or with their environment to collect and process data. The collected data streams are guided to the cloud for further processing and the production of analytics. However, any processing in the cloud, even if it is supported by improved computational resources, suffers from an increased latency. The data should travel to the cloud infrastructure as well as the provided analytics back to end users or devices. For minimizing the latency, we can perform data processing at the edge of the network, i.e., at the edge nodes. The aim is to deliver analytics and build knowledge close to end users and devices minimizing the required time for realizing responses. Edge nodes are transformed into distributed processing points where analytics queries can be served. In this paper, we deal with the problem of allocating queries, defined for producing knowledge, to a number of edge nodes. The aim is to further reduce the latency by allocating queries to nodes that exhibit low load (the current and the estimated); thus, they can provide the final response in the minimum time. However, before the allocation, we should decide the computational burden that a query will cause. The allocation is concluded by the assistance of an ensemble similarity scheme responsible to deliver the complexity class for each query. The complexity class, thus, can be matched against the current load of every edge node. We discuss our scheme, and through a large set of simulations and the adoption of benchmarking queries, we reveal the potentials of the proposed model supported by numerical results

Metabolite profiling and antioxidative activity of Sage (Salvia fruticosa Mill.) under the influence of genotype and harvesting period

Two cultivated accessions of Salvia fruticosa Mill. were investigated and evaluated for their essential oil, phenolic composition and antioxidant activity, during different harvesting time. The essential oil and its major compound 1.8 cineole, presented their higher yields during the early summer harvesting. The advanced analytical LC–MS/MS method applied in this work led to the identification of thirty five compounds with rosmarinic acid, the diterpene artefact carnosol and several flavones and flavonols as the main phenolic constituents, the concentration of which varied largely from spring to autumn. The antioxidant activity of respective methanolic extracts was determined using the Ferric Reducing Ability of Plasma (FRAP), 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) assays, as a quality control tool. High positive correlations were observed between FRAP and ABTS antioxidant activities and total phenolic/flavonoid content, and particular phenolic constituent

Optimisation of off-design internal combustion-organic Rankine engine combined cycles

Organic Rankine cycle (ORC) engines are an efficient means of converting low - to - medium renewable or waste heat to useful power . In practical applications, ORC systems experience varying thermal input profile , due to the dynamic nature of real heat source s . M aximis ing the uptake of this technology requires optim ised ORC design s and sizing to maintain high efficiency and power output, not only at full - load operation, but also under off - design conditions. Key for maintaining the efficient operation of the sys tem is the maximisation of heat extraction from the heat source, in the ORC evaporator. In this paper, the off - design operation of an ICE - ORC combined heat and power (CHP) system is investigated, to optimise the ORC performance under varying ICE load condi tions. First, the ORC engine thermodynamic design is optimised for the 100% load operation of the ICE. Alternative working fluids are inv estigated, including low ODP/ GWP refrigerants and hydrocarbons. The ORC system is then sized using two different heat e xchanger (HEX) architectures; tube - in - tube (DPHEX) and plate (PHEX) design s , at design conditions. The sizing results reveal that the PHEX area requirements are almost 50% lower than the respective ones for DPHEX, while recovering equivalent quantities of heat. Next, the ORC engine operation is optimised at part - load ICE condition s , and the HEX heat transfer coefficients (HTCs) are predicted. R esults indicate that : i) PHEX HTCs are up to 50% higher than DPHEX equivalents ; ii) HTCs decrease at part load f or both HEXs, but because the average temperature difference increases, the overall HEX effectiveness improves; and iii) the ORC system with a PHEX evaporator has slightly higher power output tha n the DPHEX equivalent at off - design operation. Overall, t he modelling tool developed here can predict ORC performance over an operating envelope and allows the selecti on of optimal design s and size s of ORC HEXs

Off-design optimisation of organic Rankine cycle (ORC) engines with piston expanders for medium-scale combined heat and power applications

Organic Rankine cycle (ORC) engines often operate under variable heat-source conditions, so maximising performance at both nominal and off-design operation is crucial for the wider adoption of this technology. In this work, an off-design optimisation tool is developed and used to predict the impact of varying heat-source conditions on ORC operation. Unlike previous efforts where the performance of ORC engine components is assumed fixed, here we consider explicitly the time-varying operational characteristics of these components. A bottoming ORC system is first optimised for maximum power output when recovering heat from the exhaust gases of an internal-combustion engine (ICE) running at full load. A double-pipe heat exchanger (HEX) model is used for sizing the ORC evaporator and condenser, and a piston-expander model for sizing the expander. The ICE is then run at part-load, thus varying the temperature and mass flow rate of the exhaust gases. The tool predicts the new off-design heat transfer coefficients in the heat exchangers, and the new optimum expander operating points. Results reveal that the ORC engine power output is underestimated by up to 17% when the off-design operational characteristics of these components are not considered. In particular, the piston-expander isentropic efficiency increases at off-design operation by 10–16%, due to the reduced pressure ratio and flow rate in the system, while the evaporator effectiveness improves by up to 15%, due to the higher temperature difference across the HEX and a higher proportion of heat transfer taking place in the two-phase evaporating zone. As the ICE operates further away from its nominal point, the off-design ORC engine power output reduces by a lesser extent than that of the ICE. At an ICE part-load operation of 60% (by electrical power), the optimised ORC engine with fluids such as R1233zd operates at 77% of its nominal capacity. ORC off-design performance maps are generated, for characterising and predicting system performance, which can be used, along with the optimisation tool, by ORC system designers, manufacturers and plant operators to identify optimum performance under real operating conditions

The antimicrobial effect of oregano essential oil, nisin and their combination against Salmonella Enteritidis in minced sheep meat during refrigerated storage

The antimicrobial effect of oregano essential oil (EO) at 0.6 or 0.9%, nisin at 500 or 1000 IU/g, and their combination against Salmonella Enteritidis was studied in minced sheep meat during storage at 4 degrees or 10 degrees C for 12 days. Sensory evaluation showed that the addition of oregano EO at 0.6 or 0.9% in minced sheep meat was organoleptically acceptable, and attribute scores were higher for the EO at 0.6 than 0.9%. According to compositional analysis of the oregano EO, the phenols carvacrol (80.15%) and thymol (4.82%) were the predominant components. Treatment of minced sheep meat with nisin at 500 or 1000 IU/g, proved insufficient to act against S. Enteritidis. The combination of the oregano EO at 0.6% with nisin at 500 IU/g showed stronger antimicrobial activity against S. Enteritidis than the oregano EO at 0.6% but lower than the combination with nisin at 1000 IU/g, which in turn was lower than that of the oregano EO at 0.9%. In its turn, oregano EO at 0.9% showed lower antimicrobial activity than its combinations with nisin at 500 or 1000 IU/g, which showed a bactericidal effect against the pathogen. The inhibition percentages of all treatments against S. Enteritidis at 10 degrees C were higher than those at 4 degrees C. (C) 2009 Elsevier B.V. All rights reserved

Antibacterial activity of oregano and thyme essential oils against Listeria monocytogenes and Escherichia coli O157:H7 in feta cheese packaged under modified atmosphere

The antibacterial activity of the essential oils (EO) of oregano and thyme added at doses of 0.1 or 0.2 and 0.1 ml/100 g, respectively, to feta cheese inoculated with Escherichia coli O157:H7 or Listeria monocytogenes was investigated during cheese storage under modified atmosphere packaging (MAP) of 50% CO(2) and 50% N(2) at 4 degrees C. Compositional analysis showed that the predominant phenols were carvacrol and thymol for both EO. In control feta inoculated with the pathogens and stored under MAP, results showed that E. coli O157:H7 and L monocytogenes strains survived up to 32 and 28 days of storage. However, in feta cheese treated with oregano EO at the dose of 0.1 ml/100 g, E. coli O157:H7 or L monocytogenes survived up to 22 and 18 days, respectively, whereas at the dose of 0.2 ml/100 g up to 16 or 14 days, respectively. Feta cheese treated with thyme EO at 0.1 ml/100 g showed populations of E. coli O157:H7 or L monocytogenes not significantly different (P>0.05) than those of feta cheese treated with oregano at 0.1 ml/100 g. Although both essential oils exhibited equal antibacterial activity against both pathogens, the populations of L. monocytogenes decreased faster (P<0.05) than those of E. coli O157:H7 during the refrigerated storage, indicating a stronger antibacterial activity of both essential oils against the former pathogen. (C) 2010 Elsevier Ltd. All rights reserved