Trends in type 2 diabetes detection among adults in the USA, 1999-2014

Objective To examine recent trends in type 2 diabetes detection among adults in the USA. Research design and methods We used data from the 1999–2014 National Health and Nutrition Examination Surveys on non-pregnant adults (aged ≥18 years) not reporting a diagnosis of diabetes (n=16 644 participants, averaging about 2000 for each 2-year cycle). We defined undiagnosed diabetes as a fasting plasma glucose ≥126 mg/dL or a hemoglobin A1c ≥6.5% (48 mmol/mol). We measured case detection as the probability of finding undiagnosed type 2 diabetes among the population without diagnosed diabetes. Linear regression models were used to examine trends overall and by sociodemographic characteristics (ie, age, gender, race/ethnicity, education, poverty-income ratio (PIR)). Results Age-standardized probability of finding undiagnosed type 2 diabetes was 3.0% (95% CI 2.1% to 4.2%) during 1999–2000 and 2.8% (2.2%–3.6%) during 2013–2014 (P for trend=0.52). Probability increased among Mexican-Americans (P for trend=0.01) but decreased among adults aged 65 years or older (P for trend=0.04), non-Hispanic (NH) white (P for trend=0.02), and adults in the highest PIR tertile (P for trend=0.047). For all other sociodemographic groups, no significant trends were detected. Conclusions We found little evidence of increased detection of undiagnosed type 2 diabetes among adults in the USA during the past 15 years. Although improvements were seen among NH white, older, and wealthy adults, these improvements were not large. As the scope of primary prevention efforts increases, case detection may improve

PHANGS-JWST First Results: A Combined HST and JWST Analysis of the Nuclear Star Cluster in NGC 628

We combine archival Hubble Space Telescope and new James Webb Space Telescope imaging data covering the ultraviolet to mid-infrared regime to morphologically analyze the nuclear star cluster (NSC) of NGC 628, a grand-design spiral galaxy. The cluster is located in a 200 pc × 400 pc cavity lacking both dust and gas. We find roughly constant values for the effective radius (r eff ∼ 5 pc) and ellipticity (ε ∼ 0.05), while the Sérsic index (n) and position angle (PA) drop from n ∼ 3 to ∼2 and PA ∼ 130° to 90°, respectively. In the mid-infrared, r eff ∼ 12 pc, ε ∼ 0.4, and n ∼ 1-1.5, with the same PA ∼ 90°. The NSC has a stellar mass of log 10 ( M ⋆ nsc / M ⊙ ) = 7.06 ± 0.31 , as derived through B − V, confirmed when using multiwavelength data, and in agreement with the literature value. Fitting the spectral energy distribution (SED), excluding the mid-infrared data, yields a main stellar population age of (8 ± 3) Gyr with a metallicity of Z = 0.012 ± 0.006. There is no indication of any significant star formation over the last few gigayears. Whether gas and dust were dynamically kept out or evacuated from the central cavity remains unclear. The best fit suggests an excess of flux in the mid-infrared bands, with further indications that the center of the mid-infrared structure is displaced with respect to the optical center of the NSC. We discuss five potential scenarios, none of them fully explaining both the observed photometry and structure

Anxiety disorders in headache patients in a specialised clinic: prevalence and symptoms in comparison to patients in a general neurological clinic

Data from several studies indicate an association of headache with anxiety disorders. In this study, we assessed and differentiated anxiety disorders in 100 headache patients by using the PSWQ (Penn State Worry Questionnaire) screening tool for generalised anxiety disorder (GAD) and the ACQ (Agoraphobic Cognitions Questionnaire) and BSQ (Body Sensation Questionnaire) for panic disorder (PD). Control groups were constructed: (1) on the basis of epidemiological studies on PD and GAD in the general population and (2) by including neurological patients. 37.0% of headache patients had a GAD. 27% of headache patients met the score for PD in the BSQ, 4.0% in the ACQ. Significant results were obtained in comparison to the general population (p < 0.001) and with regard to GAD in comparison with a sample of neurological patients (p < 0.005). The BSQ significantly correlated with the number of medication days (p < 0.005). The results confirm the increased prevalence of GAD in headache patients. PD seems to increase the risk of medication overuse

Telomerase activity, apoptosis and cell cycle progression in ataxia telangiectasia lymphocytes expressing TCL1

Individuals affected by ataxia telangiectasia (AT) have a marked susceptibility to cancer. Ataxia telangiectasia cells, in addition to defects in cell cycle checkpoints, show dysfunction of apoptosis and of telomeres, which are both thought to have a role in the progression of malignancy. In 1-5% of patients with AT, clonal expansion of T lymphocytes carrying t(14;14) chromosomal translocation, deregulating TCL1 gene(s), has been described. While it is known that these cells can progress with time to a frank leukaemia, the molecular pathway leading to tumorigenesis has not yet been fully investigated. In this study, we compared AT clonal cells, representing 88% of the entire T lymphocytes (AT94-1) and expressing TCL1 oncogene (ATM- TCL1 +), cell cycle progression to T lymphocytes of AT patients without TCL1 expression (ATM- TCL1-) by analysing their spontaneous apoptosis rate, spontaneous telomerase activity and telomere instability. We show that in ATM- TCL1+ lymphocytes, apoptosis rate and cell cycle progression are restored back to a rate comparable with that observed in normal lymphocytes while telomere dysfunction is maintained. © 2003 Cancer Research UK

EGFR Tyrosine Kinase Inhibitors Activate Autophagy as a Cytoprotective Response in Human Lung Cancer Cells

Epidermal growth factor receptor tyrosine kinase inhibitors gefitinib and erlotinib have been widely used in patients with non-small-cell lung cancer. Unfortunately, the efficacy of EGFR-TKIs is limited because of natural and acquired resistance. As a novel cytoprotective mechanism for tumor cell to survive under unfavorable conditions, autophagy has been proposed to play a role in drug resistance of tumor cells. Whether autophagy can be activated by gefitinib or erlotinib and thereby impair the sensitivity of targeted therapy to lung cancer cells remains unknown. Here, we first report that gefitinib or erlotinib can induce a high level of autophagy, which was accompanied by the inhibition of the PI3K/Akt/mTOR signaling pathway. Moreover, cytotoxicity induced by gefitinib or erlotinib was greatly enhanced after autophagy inhibition by the pharmacological inhibitor chloroquine (CQ) and siRNAs targeting ATG5 and ATG7, the most important components for the formation of autophagosome. Interestingly, EGFR-TKIs can still induce cell autophagy even after EGFR expression was reduced by EGFR specific siRNAs. In conclusion, we found that autophagy can be activated by EGFR-TKIs in lung cancer cells and inhibition of autophagy augmented the growth inhibitory effect of EGFR-TKIs. Autophagy inhibition thus represents a promising approach to improve the efficacy of EGFR-TKIs in the treatment of patients with advanced non-small-cell lung cancer

Mental disorders as risk factors: assessing the evidence for the Global Burden of Disease Study

Background: Mental disorders are associated with a considerable burden of disease as well as being risk factors for other health outcomes. The new Global Burden of Disease (GBD) Study will make estimates for both the disability and mortality directly associated with mental disorders, as well as the burden attributable to other health outcomes. Herein we discuss the process by which health outcomes in which mental disorders are risk factors are selected for inclusion in the GBD Study. We make suggestions for future research to strengthen the body of evidence for mental disorders as risk factors

Nonlinear analysis of EEG signals at different mental states

BACKGROUND: The EEG (Electroencephalogram) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. This work discusses the effect on the EEG signal due to music and reflexological stimulation. METHODS: In this work, nonlinear parameters like Correlation Dimension (CD), Largest Lyapunov Exponent (LLE), Hurst Exponent (H) and Approximate Entropy (ApEn) are evaluated from the EEG signals under different mental states. RESULTS: The results obtained show that EEG to become less complex relative to the normal state with a confidence level of more than 85% due to stimulation. CONCLUSIONS: It is found that the measures are significantly lower when the subjects are under sound or reflexologic stimulation as compared to the normal state. The dimension increases with the degree of the cognitive activity. This suggests that when the subjects are under sound or reflexologic stimuli, the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed stat

Outcomes of COVID-19 in patients with primary systemic vasculitis or polymyalgia rheumatica from the COVID-19 Global Rheumatology Alliance physician registry: a retrospective cohort study

BACKGROUND: Patients with primary systemic vasculitis or polymyalgia rheumatica might be at a high risk for poor COVID-19 outcomes due to the treatments used, the potential organ damage cause by primary systemic vasculitis, and the demographic factors associated with these conditions. We therefore aimed to investigate factors associated with COVID-19 outcomes in patients with primary systemic vasculitis or polymyalgia rheumatica. METHODS: In this retrospective cohort study, adult patients (aged ≥18 years) diagnosed with COVID-19 between March 12, 2020, and April 12, 2021, who had a history of primary systemic vasculitis (antineutrophil cytoplasmic antibody [ANCA]-associated vasculitis, giant cell arteritis, Behçet's syndrome, or other vasculitis) or polymyalgia rheumatica, and were reported to the COVID-19 Global Rheumatology Alliance registry were included. To assess COVID-19 outcomes in patients, we used an ordinal COVID-19 severity scale, defined as: (1) no hospitalisation; (2) hospitalisation without supplemental oxygen; (3) hospitalisation with any supplemental oxygen or ventilation; or (4) death. Multivariable ordinal logistic regression analyses were used to estimate odds ratios (ORs), adjusting for age, sex, time period, number of comorbidities, smoking status, obesity, glucocorticoid use, disease activity, region, and medication category. Analyses were also stratified by type of rheumatic disease. FINDINGS: Of 1202 eligible patients identified in the registry, 733 (61·0%) were women and 469 (39·0%) were men, and their mean age was 63·8 years (SD 17·1). A total of 374 (31·1%) patients had polymyalgia rheumatica, 353 (29·4%) had ANCA-associated vasculitis, 183 (15·2%) had giant cell arteritis, 112 (9·3%) had Behçet's syndrome, and 180 (15·0%) had other vasculitis. Of 1020 (84·9%) patients with outcome data, 512 (50·2%) were not hospitalised, 114 (11·2%) were hospitalised and did not receive supplemental oxygen, 239 (23·4%) were hospitalised and received ventilation or supplemental oxygen, and 155 (15·2%) died. A higher odds of poor COVID-19 outcomes were observed in patients who were older (per each additional decade of life OR 1·44 [95% CI 1·31–1·57]), were male compared with female (1·38 [1·05–1·80]), had more comorbidities (per each additional comorbidity 1·39 [1·23–1·58]), were taking 10 mg/day or more of prednisolone compared with none (2·14 [1·50–3·04]), or had moderate, or high or severe disease activity compared with those who had disease remission or low disease activity (2·12 [1·49–3·02]). Risk factors varied among different disease subtypes. INTERPRETATION: Among patients with primary systemic vasculitis and polymyalgia rheumatica, severe COVID-19 outcomes were associated with variable and largely unmodifiable risk factors, such as age, sex, and number of comorbidities, as well as treatments, including high-dose glucocorticoids. Our results could be used to inform mitigation strategies for patients with these diseases. FUNDING: American College of Rheumatology and the European Alliance of Associations for Rheumatology

Aging Affects the Mental Rotation of Left and Right Hands

BACKGROUND:Normal aging significantly influences motor and cognitive performance. Little is known about age-related changes in action simulation. Here, we investigated the influence of aging on implicit motor imagery. METHODOLOGY/PRINCIPAL FINDINGS:Twenty young (mean age: 23.9+/-2.8 years) and nineteen elderly (mean age: 78.3+/-4.5 years) subjects, all right-handed, were required to determine the laterality of hands presented in various positions. To do so, they mentally rotated their hands to match them with the hand-stimuli. We showed that: (1) elderly subjects were affected in their ability to implicitly simulate movements of the upper limbs, especially those requiring the largest amplitude of displacement and/or with strong biomechanical constraints; (2) this decline was greater for movements of the non-dominant arm than of the dominant arm. CONCLUSIONS/SIGNIFICANCE:These results extend recent findings showing age-related alterations of the explicit side of motor imagery. They suggest that a general decline in action simulation occurs with normal aging, in particular for the non-dominant side of the body

Unlocking the power of big data in new product development

This study explores how big data can be used to enable customers to express unrecognised needs. By acquiring this information, managers can gain opportunities to develop customer-centred products. Big data can be defined as multimedia-rich and interactive low-cost information resulting from mass communication. It offers customers a better understanding of new products and provides new, simplified modes of large-scale interaction between customers and firms. Although previous studies have pointed out that firms can better understand customers’ preferences and needs by leveraging different types of available data, the situation is evolving, with increasing application of big data analytics for product development, operations and supply chain management. In order to utilise the customer information available from big data to a larger extent, managers need to identify how to establish a customer-involving environment that encourages customers to share their ideas with managers, contribute their know-how, fiddle around with new products, and express their actual preferences. We investigate a new product development project at an electronics company, STE, and describe how big data is used to connect to, interact with and involve customers in new product development in practice. Our findings reveal that big data can offer customer involvement so as to provide valuable input for developing new products. In this paper, we introduce a customer involvement approach as a new means of coming up with customer-centred new product development