Subchondral bone proteomics in osteoarthritis: Current status and perspectives

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Is green space in the living environment associated with people's feelings of social safety?

Abstract. The authors investigate whether the percentage of green space in people's living environ- ment affects their feelings of social safety positively or negatively. More specifically they investigate the extent to which this relationship varies between urban and rural areas, between groups in the community that can be identified as more or less vulnerable, and the extent to which different types of green space exert different influences. The study includes 83736 Dutch citizens who were interviewed about their feelings of social safety. The percentage of green space in the living environment of each respondent was calculated, and data analysed by use of a three-level latent variable model, controlled for individual and environmental background characteristics. The analyses suggest that more green space in people's living environment is associated with enhanced feelings of social safetyöexcept in very strongly urban areas, where enclosed green spaces are associated with reduced feelings of social safety. Contrary to the common image of green space as a dangerous hiding place for criminal activity which causes feelings of insecurity, the results suggest that green space generally enhances feelings of social safety. The results also suggest, however, that green space in the most urban areas is a matter of concern with respect to social safety.

Algorithmic statistics: forty years later

Algorithmic statistics has two different (and almost orthogonal) motivations. From the philosophical point of view, it tries to formalize how the statistics works and why some statistical models are better than others. After this notion of a "good model" is introduced, a natural question arises: it is possible that for some piece of data there is no good model? If yes, how often these bad ("non-stochastic") data appear "in real life"? Another, more technical motivation comes from algorithmic information theory. In this theory a notion of complexity of a finite object (=amount of information in this object) is introduced; it assigns to every object some number, called its algorithmic complexity (or Kolmogorov complexity). Algorithmic statistic provides a more fine-grained classification: for each finite object some curve is defined that characterizes its behavior. It turns out that several different definitions give (approximately) the same curve. In this survey we try to provide an exposition of the main results in the field (including full proofs for the most important ones), as well as some historical comments. We assume that the reader is familiar with the main notions of algorithmic information (Kolmogorov complexity) theory.Comment: Missing proofs adde

Is subchondral cyst an indicator for osteoblast dysfunction in knee osteoarthritis?

Free Paper Presentation Session 6 – Adult Joint Reconstruction: no. 6.5INTRODUCTION: Subchondral bone cyst (SBC) is a key radiological feature in advanced OA. The presence of SBC was reported in a relation to the risk of cartilage loss and total knee arthroplasty (TKA). Whilst the link between SBCs and bone dysmetabolism in hip OA was studied, their links in knee OA remain unknown. Therefore we try to elucidate the relationship between SBC and subchondral bone disturbance from tissue and cellular levels in ...postprin

Multiscale Analysis of Biological Data by Scale-Dependent Lyapunov Exponent

Physiological signals often are highly non-stationary (i.e., mean and variance change with time) and multiscaled (i.e., dependent on the spatial or temporal interval lengths). They may exhibit different behaviors, such as non-linearity, sensitive dependence on small disturbances, long memory, and extreme variations. Such data have been accumulating in all areas of health sciences and rapid analysis can serve quality testing, physician assessment, and patient diagnosis. To support patient care, it is very desirable to characterize the different signal behaviors on a wide range of scales simultaneously. The Scale-Dependent Lyapunov Exponent (SDLE) is capable of such a fundamental task. In particular, SDLE can readily characterize all known types of signal data, including deterministic chaos, noisy chaos, random 1/fα processes, stochastic limit cycles, among others. SDLE also has some unique capabilities that are not shared by other methods, such as detecting fractal structures from non-stationary data and detecting intermittent chaos. In this article, we describe SDLE in such a way that it can be readily understood and implemented by non-mathematically oriented researchers, develop a SDLE-based consistent, unifying theory for the multiscale analysis, and demonstrate the power of SDLE on analysis of heart-rate variability (HRV) data to detect congestive heart failure and analysis of electroencephalography (EEG) data to detect seizures

Precision measurement of the B0s-B¯0s oscillation frequency with the decay B0s → D−sπ+

A key ingredient to searches for physics beyond the Standard Model in B0s mixing phenomena is the measurement of the B0s– ${{\overline{ {\mathrm {B}}}{}}^0_{\mathrm { s}}}$ oscillation frequency, which is equivalent to the mass difference Δms of the B0s mass eigenstates. Using the world's largest B0s meson sample accumulated in a dataset, corresponding to an integrated luminosity of 1.0 fb−1, collected by the LHCb experiment at the CERN LHC in 2011, a measurement of Δms is presented. A total of about 34 000 B0s → D−sπ+ signal decays are reconstructed, with an average decay time resolution of 44 fs. The oscillation frequency is measured to be Δms = 17.768 ± 0.023 (stat) ± 0.006 (syst) ps−1, which is the most precise measurement to date

Proximal femoral resection arthroplasty for patients with cerebral palsy and dislocated hips: 20 patients followed for 1–6 years

Background and purpose Chronic hip dislocation in non-ambulatory individuals with cerebral palsy (CP) can lead to severe problems, of which pain is often the most severe. We studied the outcome of proximal femoral resection, especially regarding pain, sitting balance, perineal care, and patient satisfaction

Incidencia, prevalencia y factores de riesgo relacionados con los síntomas de ansiedad durante el embarazo

Symptoms of anxiety are one of the most prevalent emotional responses in women during their reproductive phase and especially during pregnancy. Objective: Estimate the incidence and prevalence of anxiety throughout the three trimesters of pregnancy in addition to studying the possible risk factors associated with anxiety symptoms. Method: A sample of 385 pregnant women participated in a longitudinal study in which the GAD-7 questionnaire was used. Results: Anxiety prevalence was 19.5% in the first trimester. In the second trimester, it was 16.8%, with an incidence of 0.048%. In the third trimester, it was 17.2%, with an incidence of 0.068%. The following predictive factors of anxiety symptoms were identified: being a smoker, presence of previous illness and changes in social relationships. Conclusions: High incidence and prevalence of anxiety symptoms occur during pregnancy; consequently, applicable preventive policies should be developed.Los síntomas de ansiedad son una de las respuestas emocionales más prevalentes en las mujeres durante su fase reproductiva y especialmente en el embarazo. Objetivo: estimar la incidencia y prevalencia de la ansiedad a lo largo de los tres trimestres del embarazo además de estudiar los posibles factores de riesgo asociados a los síntomas de ansiedad. Método: una muestra de 385 gestantes participaron en un estudio longitudinal en el que se utilizó el cuestionario GAD-7. Resultados: la prevalencia fue de 19,5% en el primer trimestre. En el segundo trimestre fue de 16,8%, y una incidencia de 0.048%. En el tercer trimestre fue de 17,2%, y la incidencia de 0.068%. Como factores predictores de los síntomas de ansiedad se han encontrado: ser fumadora, la presencia de enfermedades previas y cambios en las relaciones sociales. Conclusiones: durante el embarazo aparecen unas altas tasas de incidencia y prevalencia en los síntomas de ansiedad, por lo que se deberían desarrollar políticas preventivas al respecto

Antifungal activity of aqueous and corn steep liquor extract of Ficus exasperata, Anonna muricata and Azadiractha indica

This study investigated the activity of aqueous and corn steep liquor (CSL) extracts of Ficus exaperasta, Azadirachta indica and Annona muricata against Candida spp isolated from high vagina swab samples. Phytochemical screening of the plants was done using standard methods, the antifungal activity of the plant’s extracts and standard drugs were tested against isolates of Candida spp using the agar well diffusion method; the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) were also determined using microdilution standardized techniques. Phytochemical screening of the aqueous and CSL extracts of the plants revealed the presence of tannin, saponin, phenols and flavonoids. Among the five Candida strains, the zone of inhibition (ZI) produced by the plant extracts against C. kefyra shows a range of 6-28 mm; C. kruseia: 5-25 mm; C. albican: 0-18 mm; C. kefyrb: 0-27 mm; while, C. kruseib ZI: 0-18 mm. CSL extract had higher inhibitory action compared with aqueous extract while F. exasperata and A. muricata gave better antifungal activity against the tested Candida strains. The MIC of the aqueous and CSL extracts of the F. exasperata ranged between 6.25-12.5 mg/ml; A. muricata: 3.125-12.5mg/ml, while the aqueous and CSL extracts of A. indica was found to have no activity at all the tested concentrations against C. albican, C. kruseiaand C. kruseib, similar observation for the MFC. This study proved the antifungal efficacy of aqueous and CSL extracts of F. exasperata, A. muricata, and A. indica against isolates of Candida species which are usually implicated in candidiasis