ABSTRACT
We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilize the 2-min cadence TESS data for a sample of 117 stars ...to classify their behaviour regarding variability and place them in the Hertzsprung–Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74 per cent for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system. Furthermore, our sample contains many high-frequency pulsators, allowing us to probe the frequency variability of hot young δ Scuti stars, which were lacking in the Kepler mission data set, and identify promising targets for future asteroseismic modelling. The TESS data also allow us to refine the stellar parameters of SX Phoenicis, which is believed to be a blue straggler.
Tuning is an essential requirement for the search of dark matter axions employing haloscopes since its mass is not known yet to the scientific community. At the present day, most haloscope tuning ...systems are based on mechanical devices which can lead to failures due to the complexity of the environment in which they are used. However, the electronic tuning making use of ferroelectric materials can provide a path that is less vulnerable to mechanical failures and thus complements and expands current tuning systems. In this work, we present and design a novel technique for using the ferroelectric Potassium Tantalate (KTaO3 or KTO) material as a tuning element in haloscopes based on coupled microwave cavities. In this line, the structures used in the Relic Axion Detector Exploratory Setup (RADES) group are based on several cavities that are connected by metallic irises, which act as interresonator coupling elements. In this article, we also show how to use these KTaO3 films as interresonator couplings between cavities, instead of inductive or capacitive metallic windows used in the past. These two techniques represent a crucial upgrade over the current systems employed in the dark matter axions community, achieving a tuning range of 2.23% which represents a major improvement as compared to previous works (< 0.1%) for the same class of tuning systems. The theoretical and simulated results shown in this work demonstrate the interest of the novel techniques proposed for the incorporation of this kind of ferroelectric media in multicavity resonant haloscopes in the search for dark matter axions.
Levels of cocaine and other psychoactive substances in atmospheric particulate matter (PM) were determined in urban environments representing distinct social behaviours with regard to drug abuse: ...night-life, university and residential areas. Three cities (with population >1 million and <0.3 million inhabitants) were selected. Mean daily levels of drugs in PM were 11–336 pg/m
3 for cocaine, 23–34 pg/m
3 for cannabinoids, and 5–90 pg/m
3 for heroin. The highest levels were recorded on weekends, with factors with respect to weekdays of 1–3 for cocaine, 1–2 for cannabinoids and 1.1–1.7 for heroin. Higher levels were detected in the night-life areas, pointing towards consumption and trafficking as major emission sources, and possibly ruling out drug manufacture. The similarities in temporal trends at all sites suggested a city-scale transport of psychoactive substances. Correlations were detected between cocaine and amphetamine consumption (
r
2 = 0.98), and between heroin and cannabinoids (
r
2>0.82).
► Cocaine, heroin, cannabis and related illicit drugs are found in detectable amounts in urban air. ► Illicit drug consumption and small-scale trafficking are the major emission sources. ► Illicit drugs remain in atmospheric particles and are transported across cities during at least 5 days. ► Levels of illicit drugs increase from residential to night-life areas, and maximise on weekends. ► Correlations between illicit drugs were detected, suggesting differences in consumer groups.
The presence of illicit drugs in atmospheric particles can be used to track illicit drug abuse.
BackgroundPatients with Systemic lupus erythematosus (SLE) have a well-known increased risk of major comorbidities, but they are also very heterogeneous in term of prevalence of comorbid conditions. ...The relationship of the comorbidities with the outcomes and the severity of index disease is less known.ObjectivesEvaluate the interactions between comorbid conditions, on a large multicenter SLE cohort from RELESSER register, and its impact in severity and outcomes.MethodsData about 14 cumulative comorbidities, as previously defined 1, where derived from patients with SLE (ACR-97 criteria) included in the retrospective phase of RELESSER. Severity Katz Index (SKI) and SLICC/ACR Damage Index (SDI) were calculated.An unsupervised cluster analysis using K-means method was implemented to define clusters. ANOVA and Tukey tests were used to compare continuous numerical variables; Kruskal-Wallis test to discrete variables and the Chi-square test (or Fisher’s exact test) to categorical ones.ResultsA total of 3658 SLE patients (ACR-97 criteria) were included. Median SKI: 2 (interquartile range (IQR):1-3); median SDI:1(IQR:0-2). Demographic data are shown in Table 1.The comorbidities considered and their prevalence were: Thyroiditis (8.3%), peptic ulcer (3.8%), severe hepatopathy (1.0%), obstructive pulmonary disease (2.7%), Diabetes (5.0%), cardiovascular event (CVE) (11.0%), cardiac arrhythmia (4.2%), pulmonary embolism (3.4%), dementia (0.7%), malignancy (5.9%); serious infection (19.3%), end stage renal disease (2.8%), osteoporosis (7.3%) and depression (17.1%).Four cluster, with markedly different comorbidity profiles and outcomes were identified (table 3): one subgroup was clustered around depression (100% of the cases) (cluster 2), another cluster (cluster 3) with > 1 serious infection (100%) and cluster 4, with 100% of CVE. In cluster 1, no patient had any of the 3 defining comorbidities in the rest of the clusters. There were no statistically significant differences between clusters in death by SLE. The clusters are characterized in more detail in table 1, where a just summary of the main comorbidities included in the analysis is displayed.ConclusionCluster analysis identifies well-differentiated subgroups of SLE patients as regard comorbidities and associated mortality and severity of the disease.Reference1Rúa-Figueroa I et al. National registry of patients with systemic lupus erythematosus of the Spanish Society of Rheumatology: objectives and methodology. Reumatol Clin 2014;10(1):17-24.Table 1.Cluster of comorbidities and outcomes, N (%) unless specifiedCluster 1 dCluster 2 aCluster 3 bCluster 4 cp-valueAge, mean (SD)44.8 (14.1)49.8 (14.1)46.7 (14.3)46.7 (14.3)<0.001Male sex214 (9.2) a,c25 (4.8)51 (12.2) a63 (16.3) a,d<0.001Time with SLE (years), mean (SD)129.2 (95.9)159.3 (101.4) d170.3 (100.3) d169 (113) d<0.001Cardiovascular event0 (0) c0 (0) c0 (0) c388 (100)<0.001Cardiac arrhythmia53 (2.3) b,c17 (3.3) c19 (4.5) c,d61 (15.7)<0.001Malignancy110 (4.7) a,c46 (8.9) d25 (6.0)31 (8.0) d0.001Serious infection0 (0)122 (23.6)418 (100)165 (42.5)<0.001End stage renal disease27 (1.2) b,c11 (2.1) b,c26 (6.2) a,d34 (8.8) a,d<0.001Osteoporosis79 (3.4)71 (13.8) d41 (9.8) c,d69 (17.8) b,d<0.001Depression0 (0) a,c516 (100)0 (0) a,c94 (24.4)<0.001Glucocorticoids1890 (86)451 (91.3) b,d400 (98)354 (93.2) b,d<0.001Cyclophosphamide or mycophenolate501 (23.5)145 (29.7)216 (54.3)139 (37.4)<0.001Antimalarials1869 (85.4) b,c433 (86.9) b,c317 (78.3)263 (71.1)<0.001SKI*, mean (SD)2.3 (1.4)2.8 (1.8)3.5 (1.8) a,d3.5 (2) a,d<0.001SDI**, mean (SD)0.7 (1)1.3 (1.8)1.6 (1.8)3.3 (2.5)<0.001Death46 (2.2)27 (5.6)45 (11.6)90 (25.2)<0.001Death by lupus14 (36.8) #8 (40) #8 (19.5) #24 (30.4) #0.27*Severity Katz Index; ** SLICC/ACR Damage Index. Regarding age, the p-value for the comparation between group 1 and 3 is 0.0498. #: no significant. a,b,c or d means the only significant comparison.AcknowledgementsResearch Unit of the Spanish Society of Rheumatology. Spanish Foundation of.Rheumatology financial supporting, through the research intensification grants program. GSK financial.supporting,Disclosure of InterestsNone Declared.
Inflammation is known to be related to the leading causes of death including cardiovascular disease, several types of cancer, obesity, type 2 diabetes, depression-suicide and other chronic diseases. ...In the context of whole dietary patterns, the Dietary Inflammatory Index (DII®) was developed to appraise the inflammatory potential of the diet.
We prospectively assessed the association between DII scores and all-cause mortality in two large Spanish cohorts and valuated the consistency of findings across these two cohorts and results published based on other cohorts.
We assessed 18,566 participants in the “Seguimiento Universidad de Navarra” (SUN) cohort followed-up during 188,891 person-years and 6790 participants in the “PREvencion con DIeta MEDiterránea” (PREDIMED) randomized trial representing 30,233 person-years of follow-up. DII scores were calculated in both cohorts from validated FFQs. Higher DII scores corresponded to more proinflammatory diets. A total of 230 and 302 deaths occurred in SUN and PREDIMED, respectively. In a random-effect meta-analysis we included 12 prospective studies (SUN, PREDIMED and 10 additional studies) that assessed the association between DII scores and all-cause mortality.
After adjusting for a wide array of potential confounders, the comparison between extreme quartiles of the DII showed a positive and significant association with all-cause mortality in both the SUN (hazard ratio HR = 1.85; 95% CI: 1.15, 2.98; P-trend = 0.004) and the PREDIMED cohort (HR = 1.42; 95% CI: 1.00, 2.02; P-trend = 0.009). In the meta-analysis of 12 cohorts, the DII was significantly associated with an increase of 23% in all-cause mortality (95% CI: 16%–32%, for the highest vs lowest category of DII).
Our results provide strong and consistent support for the hypothesis that a pro-inflammatory diet is associated with increased all-cause mortality.
The SUN cohort and PREDIMED trial were registered at clinicaltrials.gov as NCT02669602 and at isrctn.com as ISRCTN35739639, respectively.
Background:Improving quality of life (QoL) is one of the key targets when treating systemic lupus erythematosus (SLE) patients. The Lupus impact Tracker (LIT) is a 10-item questionnaire that has ...demonstrated being a reliable and valid tool to assess the impact 1 of the disease in SLE patients. LIT may range between 0 (no impact on QoL) and 100 (maximum impact on QoL).Objectives:To analyze the variables potentially associated with a greater influence on QoL (higher LIT score) in SLE patientsMethods:The study population corresponds to RELESSER-PROS prospective cohort with data from patients at their first annual visit (V1). The LIT score was divided into 4 groups based on the quartile distribution, and the distribution of variables in each of the 4 groups was analysed. The Chi-square or Fisher test was used for categorical variables, while ANOVA or Kruskal-Wallis tests were employed for continuous variables. Subsequently, a logistic regression model was fitted to analyse the variables influencing the presence of LIT scores greater than 50 points. A significance level of 5% was used for the entire analysis, and the R software was employed.Results:A total of 1417 SLE patients were prospectively included in the study: 1275 (90%) female/142 (10%) male; 1299 (94.2%) Caucasian. The mean (±SD) age at SLE diagnosis and at study entry (V1) were 34.7 (±13.9) and 56.0 (±1.0) years, respectively.The median (Q1-Q3) value of LIT at V1 was 25 (10-47.5). The domains of LIT who scored the most for the final value were “pain/fatigue” with a mean (±SD) score per question: 1.52 (±1.07) and “emotional health” with 1.29 (±1.18). On the other hand, the domains of LIT that scored the least were “body image dissatisfaction” and “lupus medication adverse effects” with 0.87 (±1.20) and 0.69 (±1.09) per question, respectively.At V1, the mean (±SD) clinical (without serology) SLEDAI score was 1.92 (±3.26) and the mean (±SD) SLE Damage Index (SDI) score was 1.42 (±1.77). We observed significantly higher cSLEDAI and SDI scores in the subgroup of patients with higher (50,100) LIT values (Table 1). When we performed a bivariant correlation analysis between LIT score and both cSLEDAI and SDI we observed that correlation was low: Spearman’s Correlation Coefficient 0.093 and 0.17, respectively. We observed that patients with higher LIT values were less likely in LLDAS and in 2021 DORIS remission (p=0.04 for remission).We also analyse the influence of some variables other than activity and damage on QoL of SLE patients such as educational and laboral status, comorbidities (chronic obstructive, pulmonary disease, dyslipemia, fibromyalgia, depression, thyroid disease, cardiovascular comorbidity and gastroduodenal ulcer) and therapies (glucocorticoid treatment and doses, immunosuppressive therapy, antimalarial treatment and biologic therapy). We carried out a multivariant analysis with the previously mentioned variables, defining “LIT score > 50” as the dependent variable. Table 2 shows the variables with significant independent association with a higher impact of SLE on QoL in the multivariate analysis.Conclusion:SLE has a significant impact on QoL of the patients, “pain/fatigue” and “emotional health” being the domains of QoL affected the most. Beyond activity and damage, comorbidities such as fibromyalgia, depression and thyroid disease as well as being on higher daily dose of prednisone are significantly associated with higher impact on QoL of SLE patients. On the other hand, some socioeconomic variables and being on hydroxychloroquine are significantly associated with better QoL. These results highlight the relevance of considering these factors when making clinical decisions, with the purpose of optimizing medical care of SLE patients.REFERENCES:1 Jolly M, Garris CP, Mikolaitis RA, et al. Development and validation of the Lupus Impact Tracker: a patient-completed tool for clinical practice to assess and monitor the impact of systemic lupus erythematosus. Arthritis Care Res (Hoboken). 2014;66(10):1542-1550. doi:10.1002/acr.22349Acknowledgements:The RELESSER Registry was supported by the Spanish Society of Rheumatology. This work was supported by the grant Fondo de Investigaciones sanitarias/Instituto de Salud Carlos III (FIS/ISCIII)-Fondo Europeo de Desarrollo regional (FEDER) (Grant number PI11/02857). RELESSER PROS is funded by GSK.Disclosure of Interests:None declared.
BackgroundImprovement on health-related quality of life (HRQoL) in patients with Systemic Lupus Erythematosus (SLE) remains a challenge. There is limited data on the level of agreement on remission ...according to physician and patient and remission impact on HRQoL and long-term outcomes.ObjectivesTo investigate the prevalence and level of agreement between remission according to physician and patient criteria and to evaluate the impact of remission on HRQoL in patients with SLE.MethodsProspective study of patients included in RELESSER-PROS, a multicenter register of SLE patients. Protocol of the register has been previously described 1. Remission according to physician was defined in agreement with DORIS 2021 criteria: clinical SLEDAI 0, physician global assessment ≤2 on a 0-10 Likert scale (equivalent to ≤0.5 on a 0-3 scale), stable low-dose prednisone (≤5mg) and stable immunosuppressive/ biologic agents if remission on therapy. Remission according to patient was defined as SLAQ (Systemic Lupus Activity Questionnaire) question 1 with no flare in the last 3 months (score 0).Patients were classified in three groups according to remission status by DORIS, SLAQ or both. Level of agreement was assessed using kappa statistics. Acceptable level of agreement was considered if kappa >0.60.Results1102 patients, with a follow-up of at least 2 years (data from 3 visits available) were included in this analysis. Patient characteristics according remission status at baseline are presented in the Table 1. At baseline, remission by DORIS was present in 16.1%, by SLAQ 16.7% and 2.45% by both. Remission by DORIS was more frequent among patients with higher education, on immunosuppressant and biological therapy and patients with history of hospitalization; remission by SLAQ was more frequent among women, obese patients, and those on antimalarials (p<0.05). Symptoms reported in patients who considered themselves in remission were mainly cutaneous and articular (53.3%). Mean SLEDAI in patients on remission by SLAQ was 3.28 (3.78). Patients in remission by DORIS had significantly better results in patient reported outcomes (PRO) measured by EQ-5D and LIT (p<0.05). Level of agreement in remission according to physician and patient was 78.04% (k=0.061) at baseline, 63.39% (k=0.039), and 62.73% (k=0.099) in year 2 and 5 respectively. Kappa level of agreement was low.ConclusionOur results reflect low level of agreement between physician and patients in terms of remission status with increasing disagreement in the follow-up. Patients in remission by DORIS shows better results in EQ-5D and LIT.Reference1 Rúa-Figueroa I, et al. Reumatol Clin. 2014;10(1):17-24.Table 1.Patient characteristics according remission status at baselineRemission by DORIS (n=177)Remission by SLAQ (n=184)Remission by both criteria (n=27)p-valueAge at diagnosis (years), mean (SD)34.6 (14.87)36.64 (13.74)33.77 (13.12)0.181Female sex, n (%)160/176 (90.9%)166/182 (91.2%)27/27 (100%)0.004Disease duration (yrs), mean (SD)15.26 (8.18)13.71 (7.7)19.8 (7.66)0.069Highest education57/172 (33.1%)40/180 (22.2%)13/26 (50%)<0.001Medication, n (%) Off-therapy Antimalarials Immunosuppressants (AZA, MTX, MMF) Biological therapy (rituximab, belimumab)0/177 (0%) 79/176 (44.9%) 63/175 (36%) 14/176 (8%)36/182 (19.8%) 100/182 (54.9%) 36/180 (20%) 8/178 (4.5%)0/27 (0%) 14/27 (51.9%) 12/27 (44.4%) 4/27 (14.8%)1 <0.001 <0.001 <0.001Obesity (BMI>30), n (%)18/162 (11.1%)44/176 (25%)3/24 (12.5%)0.003Hospital admission, n (%)57/176 (32.4%)40/182 (22%)7/26 (26.9%)<0.001SLEDAI, mean (SD)1.66 (1.66)3.28 (3.78)1.78 (1.5)<0.001SLAQ, mean (SD)26.15 (2.55)27.98 (1.81)27.63 (1.96)<0.001EQ-5D67.53 (19.31)63.22 (20.12)64.54 (17.7)0.041LIT26.68 (21.76)34.37 (20.34)31.3 (18.34)0.0007SLICC/ACR Damage Index1.57 (1.74)1.42 (1.84)1.37 (1.9)0.437Mortality0/177 (0%)0/184 (0%)0/27 (0%)1AZA azathioprine, MTX methotrexate, MMF mycophenolate, BMI body mass index, EQ-5D EuroQol-5D, LIT lupus impact trackerAcknowledgements:NIL.Disclosure of InterestsNone Declared.
Spinal muscular atrophy (SMA) is an autosomal recessive disorder that affects motor neurons. It is caused by mutations in the survival motor neuron gene 1 (SMN1). The SMN2 gene, which is the highly ...homologous SMN1 copy that is present in all the patients, is unable to prevent the disease. An SMN2 dosage method was applied to 45 patients with the three SMA types (I-III) and to four pairs of siblings with chronic SMA (II-III) and different phenotypes. Our results confirm that the SMN2 copy number plays a key role in predicting acute or chronic SMA. However, siblings with different SMA phenotypes show an identical SMN2 copy number and identical markers, indicating that the genetic background around the SMA locus is insufficient to account for the intrafamilial variability. In our results, age of onset appears to be the most important predictor of disease severity in affected members of the same family. Given that SMN2 is regarded as a target for potential pharmacological therapies in SMA, the identification of genetic factors other than the SMN genes is necessary to better understand the pathogenesis of the disease in order to implement additional therapeutic approaches.
Hirschsprung's disease (HSCR) is a congenital disorder characterised by the absence of ganglia along variable lengths of the intestine. The RET gene is the major HSCR gene. Reduced penetrance of RET ...mutations and phenotypic variability suggest the involvement of additional modifying genes in the disease. A RET-dependent modifier locus was mapped to 9q31 in families bearing no coding sequence (CDS) RET mutations. Yet, the 9q31 causative locus is to be identified. To fine-map the 9q31 region, we genotyped 301 tag-SNPs spanning 7 Mb on 137 HSCR Dutch trios. This revealed two HSCR-associated regions that were further investigated in 173 Chinese HSCR patients and 436 controls using the genotype data obtained from a genome-wide association study recently conducted. Within one of the two identified regions SVEP1 SNPs were found associated with Dutch HSCR patients in the absence of RET mutations. This ratifies the reported linkage to the 9q31 region in HSCR families with no RET CDS mutations. However, this finding could not be replicated. In Chinese, HSCR was found associated with IKBKAP. In contrast, this association was stronger in patients carrying RET CDS mutations with p = 5.10 × 10⁻⁶ OR = 3.32 (1.99, 5.59) after replication. The HSCR-association found for IKBKAP in Chinese suggests population specificity and implies that RET mutation carriers may have an additional risk. Our finding is supported by the role of IKBKAP in the development of the nervous system.
Purpose
Snoring and obstructive sleep apnea syndrome (OSA) are frequent conditions in pediatrics. Glycated hemoglobin (Hb
A1C
) is a useful homeostatic biomarker of glycemia and may reflect ...alterations deriving from sleep breathing disorders. The aim of this study was to relate the severity of OSA with blood Hb
A1C
levels in children.
Methods
A descriptive observational study in snoring patients was performed. All patients underwent a sleep study and classified either as simple snorers (apnea–hypopnea index; AHI ≤ 1 episodies/h) or as OSA patients (AHI > 1 episodes/h). In the following morning, a blood glycemic profile (fasting glucose, insulin, Hb
A1C
, and the HOMA index) was performed to every individual.
Results
A total of 48 patients were included. Hb
A1C
levels were shown to be increased in the moderate OSA (AHI > 5 episodes/h) group (5.05 ± 0.25 vs. 5.24 ± 0.29%;
p
= 0.019). Significant correlations were found between Hb
A1C
values and AHI (
r
= 0.345;
p
= 0.016) and also with oxygen desaturation index (
r
= 0.40;
p
= 0.005). Correlations remained significant after adjusting by age and body mass index. The AHI-associated change in Hb
A1C
was 13.4% (
p
= 0.011).
Conclusions
In the pediatric population, Hb
A1C
is a biomarker associated with OSA severity, and this relationship is age- and obesity-independent. The fact that this association was observed in snoring patients could help the physician in the distinction between those patients affected with OSA and those with simple snoring. Therefore, Hb
A1C
measurement could play a major role in the diagnosis and the management of the syndrome.
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