A case-control study of airways obstruction among construction workers.

BACKGROUND: While smoking is the major cause of chronic obstructive pulmonary disease (COPD), occupational exposures to vapors, gases, dusts, and fumes (VGDF) increase COPD risk. This case-control study estimated the risk of COPD attributable to occupational exposures among construction workers. METHODS: The study population included 834 cases and 1243 controls participating in a national medical screening program for older construction workers between 1997 and 2013. Qualitative exposure indices were developed based on lifetime work and exposure histories. RESULTS: Approximately 18% (95% CI = 2-24%) of COPD risk can be attributed to construction-related exposures, which are additive to the risk contributed by smoking. A measure of all VGDF exposures combined was a strong predictor of COPD risk. CONCLUSIONS: Construction workers are at increased risk of COPD as a result of broad and complex effects of many exposures acting independently or interactively. Control methods should be implemented to prevent worker exposures, and smoking cessation should be promoted.

Menthol attenuates respiratory irritation and elevates blood cotinine in cigarette smoke exposed mice.

Addition of menthol to cigarettes may be associated with increased initiation of smoking. The potential mechanisms underlying this association are not known. Menthol, likely due to its effects on cold-sensing peripheral sensory neurons, is known to inhibit the sensation of irritation elicited by respiratory irritants. However, it remains unclear whether menthol modulates cigarette smoke irritancy and nicotine absorption during initial exposures to cigarettes, thereby facilitating smoking initiation. Using plethysmography in a C57Bl/6J mouse model, we examined the effects of L-menthol, the menthol isomer added to cigarettes, on the respiratory sensory irritation response to primary smoke irritants (acrolein and cyclohexanone) and smoke of Kentucky reference 2R4 cigarettes. We also studied L-menthol's effect on blood levels of the nicotine metabolite, cotinine, immediately after exposure to cigarette smoke. L-menthol suppressed the irritation response to acrolein with an apparent IC₅₀ of 4 ppm. Suppression was observed even at acrolein levels well above those necessary to produce a maximal response. Cigarette smoke, at exposure levels of 10 mg/m³ or higher, caused an immediate and marked sensory irritation response in mice. This response was significantly suppressed by L-menthol even at smoke concentrations as high as 300 mg/m³. Counterirritation by L-menthol was abolished by treatment with a selective inhibitor of Transient Receptor Potential Melastatin 8 (TRPM8), the neuronal cold/menthol receptor. Inclusion of menthol in the cigarette smoke resulted in roughly a 1.5-fold increase in plasma cotinine levels over those observed in mice exposed to smoke without added menthol. These findings document that, L-menthol, through TRPM8, is a strong suppressor of respiratory irritation responses, even during highly noxious exposures to cigarette smoke or smoke irritants, and increases blood cotinine. Therefore, L-menthol, as a cigarette additive, may promote smoking initiation and nicotine addiction.

Docetaxel Resistance in Prostate Cancer: Taking It Up a Notch.

Notch signaling is implicated in prostate cancer progression and docetaxel resistance. Cui and colleagues describe the additive efficacy and mechanisms of a γ-secretase inhibitor, PF-03084014, and docetaxel in preclinical models of prostate cancer, suggesting the need for further clinical development of Notch pathway modulators in men with metastatic prostate cancer.

Serum cholesterol levels within the high normal range are associated with better cognitive performance among Chinese elderly

© 2016, Serdi and Springer-Verlag France.Objectives: The association between cognitive function and cholesterol levels is poorly understood and inconsistent results exist among the elderly. The purpose of this study is to investigate the association of cholesterol level with cognitive performance among Chinese elderly. Design: A cross-sectional study was implemented in 2012 and data were analyzed using generalized additive models, linear regression models and logistic regression models. Setting: Community-based setting in eight longevity areas in China. Subjects: A total of 2000 elderly aged 65 years and over (mean 85.8±12.0 years) participated in this study. Measurements: Total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C) concentration were determined and cognitive impairment was defined as Mini-Mental State Examination (MMSE) score≤23. Results: There was a significant positive linear association between TC, TG, LDL-C, HDL-C and MMSE score in linear regression models. Each 1 mmol/L increase in TC, TG, LDL-C and HDL-C corresponded to a decreased risk of cognitive impairment in logistic regression models. Compared with the lowest tertile, the highest tertile of TC, LDL-C and HDL-C had a lower risk of cognitive impairment. The adjusted odds ratios and 95% CI were 0.73(0.62–0.84) for TC, 0.81(0.70–0.94) for LDL-C and 0.81(0.70–0.94) for HDL-C. There was no gender difference in the protective effects of high TC and LDL-C levels on cognitive impairment. However, for high HDL-C levels the effect was only observed in women. High TC, LDL-C and HDL-C levels were associated with lower risk of cognitive impairment in the oldest old (aged 80 and older), but not in the younger elderly (aged 65 to 79 years). Conclusions: These findings suggest that cholesterol levels within the high normal range are associated with better cognitive performance in Chinese elderly, specifically in the oldest old. With further validation, low cholesterol may serve a clinical indicator of risk for cognitive impairment in the elderly.

Androgens and breast cancer

We have recently demonstrated that physiological levels of androgens exert direct and potent inhibitory effects on the growth of human breast cancer ZR-75-1 cells in vivo in nude mice as well as in vitro under both basal and estrogen-stimulated conditions. The inhibitory effect of androgens has also been confirmed on the growth of dimethylbenz(a)anthracene (DMBA)-induced mammary carcinoma in the rat. Such observations are in close agreement with the clinical data showing that androgens and the androgenic compound medroxyprogesterone acetate (MPA) have beneficial effects in breast cancer in women comparable to other endocrine therapies, including tamoxifen. Although the inhibitory action of androgens on cell proliferation in estrogen-induced ZR-75-1 cells results, in part, from their suppressive effect on expression of the estrogen receptor, the androgens also exert a direct inhibitory effect independent of estrogens. Androgens cause a global slowing effect on the duration of the cell cycle. These observations support clinical data showing that androgenic compounds induce an objective remission after failure of antiestrogen therapy as well as those indicating that the antiproliferative action of androgens is additive to that of antiestrogens. We have also recently demonstrated in ZR-75-1 human breast cancer cells the antagonism between androgens and estrogens on the expression of GCDFP-15 and GCDFP-24 which are two major proteins secreted in human gross cystic disease fluid. The effects of androgens and estrogens as well as those of progestins and glucocorticoids on GCDFP-15 and GCDFP-24 mRNA levels and secretion are opposite to those induced by the same steroids on cell growth in ZR-75-1 cells.

Efecto de la varianza genética aditiva generacional sobre las componentes de la respuesta a la selección en una población con generaciones superpuestas

p.221-230

A reified temporal logic

This paper presents a reified temporal logic for representing and reasoning about temporal and non-temporal relationships between non-temporal assertions. A clear syntax and semantics for the logic is formally provided. Three types of predicates, temporal predicates, non-temporal predicates and meta-predicates, are introduced. Terms of the proposed language are partitioned into three types, temporal terms, non-temporal terms and propositional terms. Reified propositions consist of formulae with each predicate being either a temporal predicate or a meta-predicate. Meta-predicates may take both temporal terms and propositional terms together as arguments or take propositional terms alone. A standard formula of the classical first-order language with each predicate being a non-temporal predicate taking only non-temporal terms as arguments is reified as just a propositional term. A general time ontology has been provided which can be specialized to a variety of existing temporal systems. The new logic allows one to predicate and quantify over propositional terms while according a special status of time; for example, assertions such as ‘effects cannot precede their causes’ is ensured in the logic, and some problematic temporal aspects including the delay time between events and their effects can be conveniently expressed. Applications of the logic are presented including the characterization of the negation of properties and their contextual sentences, and the expression of temporal relations between actions and effects.

Maximum-likelihood estimator for coarse carrier frequency offset estimation in OFDM systems

Orthogonal frequency division multiplexing (OFDM) systems are more sensitive to carrier frequency offset (CFO) compared to the conventional single carrier systems. CFO destroys the orthogonality among subcarriers, resulting in inter-carrier interference (ICI) and degrading system performance. To mitigate the effect of the CFO, it has to be estimated and compensated before the demodulation. The CFO can be divided into an integer part and a fractional part. In this paper, we investigate a maximum-likelihood estimator (MLE) for estimating the integer part of the CFO in OFDM systems, which requires only one OFDM block as the pilot symbols. To reduce the computational complexity of the MLE and improve the bandwidth efficiency, a suboptimum estimator (Sub MLE) is studied. Based on the hypothesis testing method, a threshold Sub MLE (T-Sub MLE) is proposed to further reduce the computational complexity. The performance analysis of the proposed T-Sub MLE is obtained and the analytical results match the simulation results well. Numerical results show that the proposed estimators are effective and reliable in both additive white Gaussian noise (AWGN) and frequency-selective fading channels in OFDM systems.

Zinc polycarboxylate dental cement for the controlled release of an active organic substance: proof of concept

The potential of employing zinc polycarboxylate dental cement as a controlled release material has been studied. Benzalkonium chloride was used as the active ingredient, and incorporated at concentrations of 1, 2 and 3% by mass within the cement. At these levels, there was no observable effect on the speed of setting. Release was followed using an ion-selective electrode to determine changes in chloride ion concentration with time. This technique showed that the additive was released when the cured cement was placed in water, with release occurring by a diffusion mechanism for the first 3 h, but continuing beyond that for up to 1 week. Diffusion coefficients were in the range 5.62 × 10(−6) cm(2) s(−1) (for 1% concentration) to 10.90 × 10(−6) cm(2) s(−1) (for 3% concentration). Up to 3% of the total loading of benzalkonium chloride was released from the zinc polycarboxylate after a week, which is similar to that found in previous studies with glass-ionomer cement. It is concluded that zinc polycarboxylate cement is capable of acting as a useful material for the controlled release of active organic compounds.

The influence of alkali metal chlorides on the loss of water from glass-ionomer dental cements

The water loss behaviour of a clinical glass-ionomer dental cement has been studied with and without the addition of alkali metal chlorides. Dehydrating conditions were provided by placing specimens in a desiccator over concentrated sulphuric acid. Cements were prepared using either pure water or an aqueous solution of metal chloride (LiCl, NaCl, KCl) at 1.0 mol/dm(3). In addition, NaCl at 0.5 mol/dm(3) was also used to fabricate cements. Disc-shaped specimens of size 6 mm diameter x 2 mm thickness were made, six performulation, and cured at 37 degrees C for 1 hour They were then exposed to desiccating conditions, and the mass measured at regular intervals. All formulations were found to lose water in a diffusion process that equilibrated after approximately 3 weeks. Diffusion coefficients ranged from 2.27 (0.13) x 10(9) with no additive to 1.85 (0.07) x 10(9) m(2)/s with 1.0 mol/dm(3) KCl. For the salts, diffusion coefficients decreased in the order LiCl > NaCl > KCl. There was no statistically significant difference between the diffusion coefficients for 1.0 and 0.5 mol/dm(3) NaCl. For all salts at 1.0 mol/dm(3) and also additive-free cements, equilibrium losses were, with statistical limits, the same, ranging from 6.23 to 6.34%. On the other hand, 0.5 mol/dm(3) NaCl lost significantly more water 7.05%.

Can effective teaching and learning strategies help student nurses to retain drug calculation skills?

Student nurses need to develop and retain drug calculation skills in order accurately to calculate drug dosages in clinical practice. If student nurses are to qualify and be fit to practise accurate drug calculation skills, then educational strategies need to not only show that the skills of student nurses have improved but that these skills have been retained over a period of time. A quasi-experimental approach was used to test the effectiveness of a range of strategies in improving retention of drug calculation skills. The results from an IV additive drug calculation test were used to compare the drug calculation skills of student nurses between two groups of students who had received different approaches to teaching drug calculation skills. The sample group received specific teaching and learning strategies in relation to drug calculation skills and the second group received only lectures on drug calculation skills. All test results for students were anonymous. The results from the test for both groups were statistically analysed using the Mann Whitney test to ascertain whether the range of strategies improved the results for the IV additive test. The results were further analysed and compared to ascertain the types and numbers of errors made in each of the sample groups. The results showed that there is a highly significant difference between the two samples using a two-tailed test (U=39.5, p<0.001). The strategies implemented therefore did make a difference to the retention of drug calculation skills in the students in the intervention group. Further research is required into the retention of drug calculation skills by students and nurses, but there does appears to be evidence to suggest that sound teaching and learning strategies do result in better retention of drug calculation skills.

Analysis of classification accuracy for pre-filtered multichannel remote sensing data

Noise is one of the main factors degrading the quality of original multichannel remote sensing data and its presence influences classification efficiency, object detection, etc. Thus, pre-filtering is often used to remove noise and improve the solving of final tasks of multichannel remote sensing. Recent studies indicate that a classical model of additive noise is not adequate enough for images formed by modern multichannel sensors operating in visible and infrared bands. However, this fact is often ignored by researchers designing noise removal methods and algorithms. Because of this, we focus on the classification of multichannel remote sensing images in the case of signal-dependent noise present in component images. Three approaches to filtering of multichannel images for the considered noise model are analysed, all based on discrete cosine transform in blocks. The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix). The proposed classification system combines the pre-processing stage where a DCT-based filter processes the blocks of the multichannel remote sensing image and the classification stage. Two modern classifiers are employed, radial basis function neural network and support vector machines. Simulations are carried out for three-channel image of Landsat TM sensor. Different cases of learning are considered: using noise-free samples of the test multichannel image, the noisy multichannel image and the pre-filtered one. It is shown that the use of the pre-filtered image for training produces better classification in comparison to the case of learning for the noisy image. It is demonstrated that the best results for both groups of quantitative criteria are provided if a proposed 3D discrete cosine transform filter equipped by variance stabilizing transform is applied. The classification results obtained for data pre-filtered in different ways are in agreement for both considered classifiers. Comparison of classifier performance is carried out as well. The radial basis neural network classifier is less sensitive to noise in original images, but after pre-filtering the performance of both classifiers is approximately the same.

Drivers of euphausiid species abundance and numerical abundance in the Atlantic Ocean

Mid-ocean ridges are common features of the world’s oceans but there is a lack of understanding as to how their presence affects overlying pelagic biota. The Mid-Atlantic Ridge (MAR) is a dominant feature of the Atlantic Ocean. Here, we examined data on euphausiid distribution and abundance arising from several international research programmes and from the continuous plankton recorder. We used a generalized additive model (GAM) framework to explore spatial patterns of variability in euphausiid distribution on, and at either side of, the MAR from 60°N to 55°S in conjunction with variability in a suite of biological, physical and environmental parameters. Euphausiid species abundance peaked in mid-latitudes and was significantly higher on the ridge than in adjacent waters, but the ridge did not influence numerical abundance significantly. Sea surface temperature (SST) was the most important single factor influencing both euphausiid numerical abundance and species abundance. Increases in sea surface height variance, a proxy for mixing, increased the numerical abundance of euphausiids. GAM predictions of variability in species abundance as a function of SST and depth of the mixed layer were consistent with present theories, which suggest that pelagic niche availability is related to the thermal structure of the near surface water: more deeply-mixed water contained higher euphausiid biodiversity. In addition to exposing present distributional patterns, the GAM framework enables responses to potential future and past environmental variability including temperature change to be explored.

Effects of environmental conditions on the seasonal distribution of phytoplankton biomass in the North Sea

We study the spatial and seasonal variability of phytoplankton biomass (as phytoplankton color) in relation to the environmental conditions in the North Sea using data from the Continuous Plankton Recorder survey. By using only environmental fields and location as predictor variables we developed a nonparametric model (generalized additive model) to empirically explore how key environmental factors modulate the spatio-temporal patterns of the seasonal cycle of algal biomass as well as how these relate to the ,1988 North Sea regime shift. Solar radiation, as manifest through changes of sea surface temperature (SST), was a key factor not only in the seasonal cycle but also as a driver of the shift. The pronounced increase in SST and in wind speed after the 1980s resulted in an extension of the season favorable for phytoplankton growth. Nutrients appeared to be unimportant as explanatory variables for the observed spatio-temporal pattern, implying that they were not generally limiting factors. Under the new climatic regime the carrying capacity of the whole system has been increased and the southern North Sea, where the environmental changes have been more pronounced, reached a new maximum.

Seasonal plankton dynamics along a cross-shelf gradient off northern Spain

The development of population models able to reproduce the dynamics of zooplankton is a central issue when trying to understand how a changing environment would affect zooplankton in the future. Using 10 years of monthly data on phytoplankton and zooplankton abundance in the Bay of Biscay from the IEO's RADIALES time-series programme, we built non-parametric Generalized Additive Models (GAMs) able to reproduce the dynamics of plankton on the basis of environmental factors (nutrients, temperature, upwelling and photoperiod). We found that the interaction between these two plankton components is approximately linear, whereas the effects of environmental factors are non-linear. With the inclusion of the environmental variability, the main seasonal and inter-annual dynamic patterns observed within the studied plankton assemblage indicate the prevalence of bottom-up regulatory control. The statistically deduced models were used to simulate the dynamics of the phytoplankton and zooplankton. A good agreement between observations and simulations was obtained, especially for zooplankton. We are presently developing spatio-temporal GAM models for the North Sea based on the Continuous Plankton Recorder database.