Restless legs syndrome/Willis–Ekbom disease prevalence in beta thalassemia patients

Purpose Both beta thalassemia and restless legs syndrome (RLS) patients share some common pathophysiological characteristics related to iron handling. In the present study, the aim was to explore the prevalence of RLS as well as to explore potential association between the syndrome and various quality of life-related parameters in a sample of beta thalassemia patients. Methods One hundred fourteen (age 40 ± 11 yr, 59 M/55F) beta thalassemia patients participated in this cross-sectional descriptive study. Patients were screened for RLS based on the international RLS study group diagnostic criteria as well as a battery of validated questionnaires. Results The prevalence of RLS in this sample of beta thalassemia patients was zero. The quality of life score was low (78 ± 18). Iron levels were within normal range (191 ± 66 mcg/dL) while ferritin levels were high as expected (1836 ± 225 ng/dL). Conclusions Our sample of patients comes from central Greece where the prevalence of RLS in the general population is 4% while in renal failure patients is 27%. To our surprise, there was no presence of RLS among this sample of beta thalassemia patients. The adequate levels of iron and ferritin often seen in these patients could be the reason of the absence of RLS symptoms

Supervised Human-Guided Data Exploration

Peer reviewe

Observation of Blue Corona Discharges and Cloud Microphysics in the Top of Thunderstorm Cells in Cyclone Fani

Blue corona discharges are often observed at the top of thunderclouds. They are bursts of streamers, but the cloud conditions that enable them are not well known. Here we present observations by the Atmosphere-Space Interactions Monitor (ASIM) of 92 discharges during its ∼1 min pass over tropical cyclone Fani in the Bay of Bengal from 20:10:55 to 20:12:05 UTC on 30 April 2019. The discharges were observed in convective cells forming in the rainbands of the cyclone where Convective Available Potential Energy reached ∼6,000 J kg. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite passed over one of the cells ∼12 min after ASIM from 20:23:58 to 20:24:14 UTC. It measured the cloud microphysics related to the discharges and indicated they occurred in a convection region with the cloud top overshooting for over 20 min. The updraft lifted ice particles to lower stratospheric altitudes and formed the gullwing-shaped cirrus. The discharges are found at an average altitude of ∼16 km where the cloud environment contained ∼2 × 10 m ice particles with ∼50 µm radius, resulting in a photon mean free path of ∼3 m. Around 20% of the blue corona discharges coincide with Narrow Bipolar Events indentified from the Earth Networks Total Lightning Network. Our observations suggest that the overshooting cloud top formed by deep convection and a surge in lightning activity facilitated conditions for the blue corona discharges. This work provides the first-ever estimate of important microphysical parameters related to blue corona discharges based on data measurements, establishing a reference for future empirical and theoretical studies. © 2023. The Authors.This work was supported by Independent Research Fund Denmark (Danmarks Frie Forskningsfond) under Grant agreement 1026-00420B. The project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant agreement SAINT 722337. ASIM is a mission of the European Space Agency (ESA) and is funded by ESA and by national grants of Denmark, Norway and Spain. The ASIM Science Data Center is supported by ESA PRODEX contracts C 4000115884 (DTU) and 4000123438 (Bergen). With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S)

Towards elucidating carnosic acid biosynthesis in Lamiaceae: Functional characterization of the three first steps of the pathway in Salvia fruticosa and Rosmarinus officinalis

Carnosic acid (CA) is a phenolic diterpene with anti-tumour, anti-diabetic, antibacterial and neuroprotective properties that is produced by a number of species from several genera of the Lamiaceae family, including Salvia fruticosa (Cretan sage) and Rosmarinus officinalis (Rosemary). To elucidate CA biosynthesis, glandular trichome transcriptome data of S. fruticosa were mined for terpene synthase genes. Two putative diterpene synthase genes, namely SfCPSand SfKSL, showing similarities to copalyl diphosphate synthase and kaurene synthase-like genes, respectively, were isolated and functionally characterized. Recombinant expression in Escherichia coli followed by in vitro enzyme activity assays confirmed that SfCPS is a copalyl diphosphate synthase. Coupling of SfCPS with SfKSL, both in vitro and in yeast, resulted in the synthesis miltiradiene, as confirmed by 1D and 2D NMR analyses (1H, 13C, DEPT, COSY H-H, HMQC and HMBC). Coupled transient in vivo assays of SfCPS and SfKSL in Nicotiana benthamiana further confirmed production of miltiradiene in planta. To elucidate the subsequent biosynthetic step, RNA-Seq data of S. fruticosa and R. officinalis were searched for cytochrome P450 (CYP) encoding genes potentially involved in the synthesis of the first phenolic compound in the CA pathway, ferruginol. Three candidate genes were selected, SfFS, RoFS1 and RoFS2. Using yeast and N. benthamiana expression systems, all three where confirmed to be coding for ferruginol synthases, thus revealing the enzymatic activities responsible for the first three steps leading to CA in two Lamiaceae genera

Assessment of the general public's knowledge about rheumatic diseases: evidence from a Portuguese population-based survey

Background. To identify incorrect beliefs and common knowledge about rheumatic diseases in the general population. Methods. Participants were selected during the follow-up of a representative cohort of adult population of Porto, Portugal; 1626 participants completed a questionnaire that included general knowledge items about rheumatic diseases. Discrete and continuous latent variable models were used to identify knowledge flaws and the target groups. Odds ratios (OR) estimated by multinomial logistic regression, and 95% confidence intervals (95%CI) were computed to evaluate magnitude of associations. Results. A continuous latent variable model identified two dimensions: one related to general beliefs (latent 1) and another concerning characteristics, treatment and impact of rheumatic diseases (latent 2). A 3-class latent variable model refined these results: the first class presented the lowest probabilities of correct answer for items associated with the first latent (mean of 39%), and the second class presented the lowest probabilities of correct answer for items with the second latent (mean of 62%). The third class showed the highest probability of a correct answer for almost all the items (mean of 79%). The age and sex standardized prevalence of the classes was 25.7%, 30.8% and 43.5%. Taking class 2 as reference, class 1 was positively associated with the presence of rheumatic diseases (OR = 2.79; CI95% = (2.10-3.70)), with females (OR = 1.28 CI95% = (0.99-1.67)) and older individuals (OR = 1.04; CI95% = (1.03-1.05)), and was negatively associated with education (OR = 0.84; CI95% = (0.81-0.86)); class 3 was positively associated with education (OR = 1.03; CI95% = (1.00-1.05)) and the presence of rheumatic diseases (OR = 1.29; CI95% = (0.97-1.70)). Conclusions. There are several knowledge flaws about rheumatic diseases in the general public. One out of four participants considered false general beliefs as true and approximately 30% did not have detailed knowledge on rheumatic disease. Higher education and the presence of disease contributed positively to the overall knowledge. These results suggest some degree of effectiveness of patient education, either conducted by health professionals or self-driven. © 2010 Severo et al; licensee BioMed Central Ltd

Development and Validation of a New Method to Measure Walking Speed in Free-Living Environments Using the Actibelt® Platform

Walking speed is a fundamental indicator for human well-being. In a clinical setting, walking speed is typically measured by means of walking tests using different protocols. However, walking speed obtained in this way is unlikely to be representative of the conditions in a free-living environment. Recently, mobile accelerometry has opened up the possibility to extract walking speed from long-time observations in free-living individuals, but the validity of these measurements needs to be determined. In this investigation, we have developed algorithms for walking speed prediction based on 3D accelerometry data (actibelt®) and created a framework using a standardized data set with gold standard annotations to facilitate the validation and comparison of these algorithms. For this purpose 17 healthy subjects operated a newly developed mobile gold standard while walking/running on an indoor track. Subsequently, the validity of 12 candidate algorithms for walking speed prediction ranging from well-known simple approaches like combining step length with frequency to more sophisticated algorithms such as linear and non-linear models was assessed using statistical measures. As a result, a novel algorithm employing support vector regression was found to perform best with a concordance correlation coefficient of 0.93 (95%CI 0.92–0.94) and a coverage probability CP1 of 0.46 (95%CI 0.12–0.70) for a deviation of 0.1 m/s (CP2 0.78, CP3 0.94) when compared to the mobile gold standard while walking indoors. A smaller outdoor experiment confirmed those results with even better coverage probability. We conclude that walking speed thus obtained has the potential to help establish walking speed in free-living environments as a patient-oriented outcome measure