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Background: The risk for major depression and obesity is increased in adolescents and adults with attention-deficit / hyperactivity disorder (ADHD) and adolescent ADHD predicts adult depression and obesity. Non-pharmacological interventions to treat and prevent these co-morbidities are urgently needed. Bright light therapy (BLT) improves day–night rhythm and is an emerging therapy for major depression. Exercise intervention (EI) reduces obesity and improves depressive symptoms. To date, no randomized controlled trial (RCT) has been performed to establish feasibility and efficacy of these interventions targeting the prevention of co-morbid depression and obesity in ADHD. We hypothesize that the two manualized interventions in combination with mobile health-based monitoring and reinforcement will result in less depressive symptoms and obesity compared to treatment as usual in adolescents and young adults with ADHD.
Methods: This trial is a prospective, pilot phase-IIa, parallel-group RCT with three arms (two add-on treatment groups [BLT, EI] and one treatment as usual [TAU] control group). The primary outcome variable is change in the Inventory of Depressive Symptomatology total score (observer-blinded assessment) between baseline and ten weeks of intervention. This variable is analyzed with a mixed model for repeated measures approach investigating the treatment effect with respect to all three groups. A total of 330 participants with ADHD, aged 14 – < 30 years, will be screened at the four study centers. To establish effect sizes, the sample size was planned at the liberal significance level of α = 0.10 (two-sided) and the power of 1-β = 80% in order to find medium effects. Secondary outcomes measures including change in obesity, ADHD symptoms, general psychopathology, health-related quality of life, neurocognitive function, chronotype, and physical fitness are explored after the end of the intervention and at the 12-week follow-up.
Discussion: This is the first pilot RCT on the use of BLT and EI in combination with mobile health-based monitoring and reinforcement targeting the prevention of co-morbid depression and obesity in adolescents and young adults with ADHD. If at least medium effects can be established with regard to the prevention of depressive symptoms and obesity, a larger scale confirmatory phase-III trial may be warranted.
Trial registration: German Clinical Trials Register, DRKS00011666. Registered on 9 February 2017. ClinicalTrials.gov, NCT03371810. Registered on 13 December 2017.
Plants, fungi and algae are important components of global biodiversity and are fundamental to all ecosystems. They are the basis for human well-being, providing food, materials and medicines. Specimens of all three groups of organisms are accommodated in herbaria, where they are commonly referred to as botanical specimens.The large number of specimens in herbaria provides an ample, permanent and continuously improving knowledge base on these organisms and an indispensable source for the analysis of the distribution of species in space and time critical for current and future research relating to global biodiversity. In order to make full use of this resource, a research infrastructure has to be built that grants comprehensive and free access to the information in herbaria and botanical collections in general. This can be achieved through digitization of the botanical objects and associated data.The botanical research community can count on a long-standing tradition of collaboration among institutions and individuals. It agreed on data standards and standard services even before the advent of computerization and information networking, an example being the Index Herbariorum as a global registry of herbaria helping towards the unique identification of specimens cited in the literature.In the spirit of this collaborative history, 51 representatives from 30 institutions advocate to start the digitization of botanical collections with the overall wall-to-wall digitization of the flat objects stored in German herbaria. Germany has 70 herbaria holding almost 23 million specimens according to a national survey carried out in 2019. 87% of these specimens are not yet digitized. Experiences from other countries like France, the Netherlands, Finland, the US and Australia show that herbaria can be comprehensively and cost-efficiently digitized in a relatively short time due to established workflows and protocols for the high-throughput digitization of flat objects.Most of the herbaria are part of a university (34), fewer belong to municipal museums (10) or state museums (8), six herbaria belong to institutions also supported by federal funds such as Leibniz institutes, and four belong to non-governmental organizations. A common data infrastructure must therefore integrate different kinds of institutions.Making full use of the data gained by digitization requires the set-up of a digital infrastructure for storage, archiving, content indexing and networking as well as standardized access for the scientific use of digital objects. A standards-based portfolio of technical components has already been developed and successfully tested by the Biodiversity Informatics Community over the last two decades, comprising among others access protocols, collection databases, portals, tools for semantic enrichment and annotation, international networking, storage and archiving in accordance with international standards. This was achieved through the funding by national and international programs and initiatives, which also paved the road for the German contribution to the Global Biodiversity Information Facility (GBIF).Herbaria constitute a large part of the German botanical collections that also comprise living collections in botanical gardens and seed banks, DNA- and tissue samples, specimens preserved in fluids or on microscope slides and more. Once the herbaria are digitized, these resources can be integrated, adding to the value of the overall research infrastructure. The community has agreed on tasks that are shared between the herbaria, as the German GBIF model already successfully demonstrates.We have compiled nine scientific use cases of immediate societal relevance for an integrated infrastructure of botanical collections. They address accelerated biodiversity discovery and research, biomonitoring and conservation planning, biodiversity modelling, the generation of trait information, automated image recognition by artificial intelligence, automated pathogen detection, contextualization by interlinking objects, enabling provenance research, as well as education, outreach and citizen science.We propose to start this initiative now in order to valorize German botanical collections as a vital part of a worldwide biodiversity data pool.
Objectives: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance.
Low platelet count predicts reduced survival in potentially resectable hepatocellular carcinoma
(2022)
The prognostic role of platelet count in hepatocellular carcinoma (HCC) remains unclear, and in fact both thrombocytopenia and thrombocytosis are reported as predictors of unfavourable outcomes. This study aimed to clarify the prognostic value of preoperative platelet count in potentially resectable HCC. We retrospectively reviewed 128 patients who underwent hepatic resection for HCC at a tertiary academic centre (2007–2019). Patient data were modelled by regression analysis, and platelet count was treated as a continuous variable. 89 patients had BCLC 0/A tumours and 39 had BCLC B tumours. Platelet count was higher in patients with larger tumours and lower in patients with higher MELD scores, advanced fibrosis, and portal hypertension (p < 0.001 for all listed variables). After adjusting for BCLC stage and tumour diameter, low platelet count associated with reduced overall survival (hazard ratio 1.25 per 50/nL decrease in platelet count, 95% confidence interval (CI) 1.02–1.53, p = 0.034) and increased perioperative mortality (odds ratio 1.96 per 50/nL decrease in platelet count, 95% CI 1.19–3.53, p = 0.014). Overall, low platelet count correlates with increased liver disease severity, inferior survival, and excess perioperative mortality in resectable HCC. These insights might be applied in clinical practice to better select patients for resection.
the benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor’s data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI95%) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83–87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI95%: − 6, 7) to 8 (CI95%: 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems.
Exercise interventions in mental disorders have evidenced a mood-enhancing effect. However, the association between physical activity and affect in everyday life has not been investigated in adult individuals with ADHD, despite being important features of this disorder. As physical activity and affect are dynamic processes in nature, assessing those in everyday life with e-diaries and wearables, has become the gold standard. Thus, we used an mHealth approach to prospectively assess physical activity and affect processes in individuals with ADHD and controls aged 14–45 years. Participants wore accelerometers across a four-day period and reported their affect via e-diaries twelve times daily. We used multilevel models to identify the within-subject effects of physical activity on positive and negative affect. We split our sample into three groups: 1. individuals with ADHD who were predominantly inattentive (n = 48), 2. individuals with ADHD having a combined presentation (i.e., being inattentive and hyperactive; n = 95), and 3. controls (n = 42). Our analyses revealed a significant cross-level interaction (F(2, 135.072)=5.733, p = 0.004) of physical activity and group on positive affect. In details, all groups showed a positive association between physical activity and positive affect. Individuals with a combined presentation significantly showed the steepest slope of physical activity on positive affect (slope_inattentive=0.005, p<0.001; slope_combined=0.009, p<0.001; slope_controls=0.004, p = 0.008). Our analyses on negative affect revealed a negative association only in the individuals with a combined presentation (slope=-0.003; p = 0.001). Whether this specifically pronounced association in individuals being more hyperactive might be a mechanism reinforcing hyperactivity needs to be empirically clarified in future studies.
The ALICE experiment has measured low-mass dimuon production in pp collisions at √s=7 TeV in the dimuon rapidity region 2.5<y<4. The observed dimuon mass spectrum is described as a superposition of resonance decays (η,ρ,ω,η′,ϕ) into muons and semi-leptonic decays of charmed mesons. The measured production cross sections for ω and ϕ are σω(1<pt<5 GeV/c,2.5<y<4)=5.28±0.54(stat)±0.49(syst) mb and σϕ(1<pt<5 GeV/c,2.5<y<4)=0.940±0.084(stat)±0.076(syst) mb. The differential cross sections d2σ/dydpt are extracted as a function of pt for ω and ϕ. The ratio between the ρ and ω cross section is obtained. Results for the ϕ are compared with other measurements at the same energy and with predictions by models.
The ALICE Collaboration reports the measurement of the relative J/ψ yield as a function of charged particle pseudorapidity density dNch/dη in pp collisions at √s=7 TeV at the LHC. J/ψ particles are detected for pt>0, in the rapidity interval |y|<0.9 via decay into e+e−, and in the interval 2.5<y<4.0 via decay into μ+μ− pairs. An approximately linear increase of the J/ψ yields normalized to their event average (dNJ/ψ/dy)/〈dNJ/ψ/dy〉 with (dNch/dη)/〈dNch/dη〉 is observed in both rapidity ranges, where dNch/dη is measured within |η|<1 and pt>0. In the highest multiplicity interval with 〈dNch/dη(bin)〉=24.1, corresponding to four times the minimum bias multiplicity density, an enhancement relative to the minimum bias J/ψ yield by a factor of about 5 at 2.5<y<4 (8 at |y|<0.9) is observed.
he first measurements of the invariant differential cross sections of inclusive π0 and η meson production at mid-rapidity in proton–proton collisions at s=0.9 TeV and s=7 TeV are reported. The π0 measurement covers the ranges 0.4<pT<7 GeV/c and 0.3<pT<25 GeV/c for these two energies, respectively. The production of η mesons was measured at s=√7 TeV in the range 0.4<pT<15 GeV/c. Next-to-Leading Order perturbative QCD calculations, which are consistent with the π0 spectrum at s=0.9 TeV, overestimate those of π0 and η mesons at s=√7 TeV, but agree with the measured η/π0 ratio at s=√7 TeV.