Benthic algal vegetation in Isfjorden, Svalbard

Benthic algal vegetation was investigated at 10 sites in Isfjorden, Svalbard. Five sites were visited during summer 2010 and five during summer 2012. Both the littoral and sublittoral vegetation were sampled, the littoral by hand-picking and use of a throwable rake and the sublittoral using a triangular dredge. A total of 88 different taxa were registered, comprising 17 Chlorophyta, 40 Ochrophyta, 30 Rhodophyta and the Xantophyceae Vaucheria sp. The green algae Ulvaria splendens (Ruprecht) Vinogradova was recorded in Svalbard for the first time. Most of the sites consisted of hard bottom substrate, but one site, Kapp Wijk, consisted of loose-lying calcareous red algae (rhodoliths) and had species not recorded elsewhere. The sublittoral at the other sites was dominated by kelp. Molecular analysis confirmed the presence of the red alga Ceramium virgatum and a dwarf form of the brown alga Fucus vesiculosus. This study provides a baseline for future studies investigating changes in the vegetation due to environmental changes

Genomic epidemiology of Streptococcus dysgalactiae subsp. equisimilis strains causing invasive disease in Norway during 2018

Background: Streptococcus dysgalactiae subspecies equisimilis (SDSE) is an emerging global pathogen, yet the epidemiology and population genetics of SDSE species have not been extensively characterized. Methods: We carried out whole genome sequencing to characterize 274 SDSE isolates causing bloodstream infections obtained through national surveillance program in 2018. We conducted multilocus sequence typing (MLST), emm-typing, core genome phylogeny, as well as investigated key features associated with virulence. Moreover, comparison to SDSE from other geographic regions were performed in order to gain more insight in the evolutionary dynamics in SDSE. Results: The phylogenetic analysis indicated a substantial diversity of emm-types and sequence types (STs). Briefly, 17 emm-types and 58 STs were identified that formed 10 clonal complexes (CCs). The predominant ST-types were ST20 (20%), ST17 (17%), and ST29 (11%). While CC17 and CC29 clades showed a substantial heterogeneity with well-separated emm-associated subclades, the CC20 clade harboring the stG62647 emm-type was more homogenous and the most prevalent in the present study. Moreover, we observed notable differences in the distribution of clades within Norway, as well as several disseminated CCs and also distinct geographic variations when compared to data from other countries. We also revealed extensive intra-species recombination events involving surface exposed virulence factors, including the emm gene important for phylogenetic profiling. Conclusion: Recombination events involving the emm as well as other virulence genes in SDSE, are important mechanisms in shaping the genetic variability in the SDSE population, potentially offering selective advantages to certain lineages. The enhanced phylogenetic resolution offered by whole genome sequencing is necessary to identify and delimitate outbreaks, monitor and properly characterize emerging strains, as well as elucidate bacterial population dynamics.publishedVersio

Hepatic and renal concentrations of copper and other trace elements in hippopotami (Hippopotamus amphibius L.) living in and adjacent to the Kafue and Luangwa Rivers in Zambia

Hepatic and renal concentrations of the elements arsenic, cadmium, cobalt, copper, lead, manganese, mercury, molybdenum, selenium and zinc were studied in samples collected from hippopotami from the Kafue River in the Kafue National Park and the Luangwa River in the Southern Luangwa National Park in Zambia. There were no significant differences between trace element concentrations in the tissues of the hippopotami taken in the Kafue River and the Luangwa River. The concentrations of copper and other essential elements were similar to those reported in normal domestic and wild ruminants. Judging by the results obtained in this study, pollution from the mining activity around the Kafue River drainage area in the Copperbelt region has not led to any accumulation of elements in tissues of the hippopotami in the Kafue National Park. The trace element concentrations observed may serve as reference for similar future studies on hippopotami.The articles have been scanned in colour with a HP Scanjet 5590; 600dpi. Adobe Acrobat v.9 was used to OCR the text and also for the merging and conversion to the final presentation PDF-format.NUFU (Norwegian Council for Higher Education's program for development research and education).mn201

A linear model of gravity wave drag for hydrostatic sheared flow over elliptical mountains

An analytical model of orographic gravity wave drag due to sheared flow past elliptical mountains is developed. The model extends the domain of applicability of the well-known Phillips model to wind profiles that vary relatively slowly in the vertical, so that they may be treated using a WKB approximation. The model illustrates how linear processes associated with wind profile shear and curvature affect the drag force exerted by the airflow on mountains, and how it is crucial to extend the WKB approximation to second order in the small perturbation parameter for these effects to be taken into account. For the simplest wind profiles, the normalized drag depends only on the Richardson number, Ri, of the flow at the surface and on the aspect ratio, γ, of the mountain. For a linear wind profile, the drag decreases as Ri decreases, and this variation is faster when the wind is across the mountain than when it is along the mountain. For a wind that rotates with height maintaining its magnitude, the drag generally increases as Ri decreases, by an amount depending on γ and on the incidence angle. The results from WKB theory are compared with exact linear results and also with results from a non-hydrostatic nonlinear numerical model, showing in general encouraging agreement, down to values of Ri of order one

Content Validity of the Geriatric Depression Scale in Inpatient Health Care Settings

The content validity of the Geriatric Depression Scale (GDS) for use in inpatient health care settings was evaluated. Clinical experience has shown that one or more questions may not be appropriate in such settings. These questions ask about behaviors or feelings with which the examinee may not be able to identify with because they have been in an inpatient setting during the past week. Twenty-five Subject Matter Experts (SMEs) evaluated the GDS-30 as to whether each item appropriately assesses the construct of depression for inpatients in a medical care setting. SMEs were identified by an online search of the Florida Division of Medical Quality Assurance database; inclusion criteria are presented. Nineteen SMEs held a Ph.D. and six held a Psy.D. Years of post-licensure practice experience ranged from 10 to 48 years with a mean of 23.12 years (SD = 10.07). Using the Content Validity Ratio, four questions emerged as inappropriate (statistically significant at, or below, an alpha level of .025). The lack of content validity of these questions necessitates their omission when psychometrically assessing depression in elderly inpatients. Recommended revised cutoff values are presented. Utilizing the recommended modification to the GDS presented here should reduce false positives when psychometrically assessing depression in elderly inpatients

Predicting persistent depressive symptoms in older adults : a machine learning approach to personalised mental healthcare

Background Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and such approaches offer powerful predictive abilities. We investigated the utility of a machine learning approach to predict the persistence of depressive symptoms in older adults. Method Baseline demographic and psychometric data from 284 patients were used to predict the likelihood of older adults having persistent depressive symptoms after 12 months, using a machine learning approach (‘extreme gradient boosting’). Predictive performance was compared to a conventional statistical approach (logistic regression). Data were drawn from the ‘treatment-as-usual’ arm of the CASPER (CollAborative care and active surveillance for Screen-Positive EldeRs with subthreshold depression) trial. Results Predictive performance was superior using machine learning compared to logistic regression (mean AUC 0.72 vs. 0.67, p < 0.0001). Using machine learning, an average of 89% of those predicted to have PHQ-9 scores above threshold at 12 months, actually did, compared to 78% using logistic regression. However, mean negative predictive values were somewhat lower for the machine learning approach (45% vs. 35%). Limitations A relatively small sample size potentially limited the predictive power of the algorithm. In addition, PHQ-9 scores were used as an indicator of persistent depressive symptoms, and whilst well validated, a clinical interview would have been preferable. Conclusions : Overall, our findings support the potential application of machine learning in personalised mental healthcare. Keywords DepressionMachine learningOld age psychiatr

Dysfunctional beliefs and attitudes about sleep (DBAS) mediate outcomes in dCBT-I on psychological distress, fatigue, and insomnia severity

Objective/background Digital cognitive behavioral therapy for insomnia (dCBT-I) improves several sleep and health outcomes in individuals with insomnia. This study investigates whether changes in Dysfunctional Beliefs and Attitudes about Sleep (DBAS) during dCBT-I mediate changes in psychological distress, fatigue, and insomnia severity. Patients/methods The study presents a secondary planned analysis of data from 1073 participants in a randomized control trial (Total sample = 1721) of dCBT-I compared with patient education (PE). Self-ratings with the Dysfunctional Beliefs and Attitudes about Sleep (DBAS), the Hospital Anxiety Depression Scale (HADS), the Chalder Fatigue Scale (CFQ), and the Insomnia Severity Index (ISI) were obtained at baseline and 9-week follow-up. Hayes PROCESS mediation analyses were conducted to test for mediation. Results and conclusion sDBAS scores were significantly reduced at 9-week follow-up for those randomized to dCBT-I (n = 566) compared with PE (n = 507). The estimated mean difference was −1.49 (95% CI -1.66 to −1.31, p < .001, Cohen's d. = 0.93). DBAS mediated all the effect of dCBT-I on the HADS and the CFQ, and 64% of the change on the ISI (Estimated indirect effect −3.14, 95% CI -3.60 to −2.68) at 9-week follow-up compared with PE. Changes in the DBAS fully mediated the effects of dCBT-I on psychological distress and fatigue, and the DBAS partially mediated the effects on insomnia severity. These findings may have implications for understanding how dCBT-I works and highlights the role of changing cognitions in dCBT-I.publishedVersio

Digital cognitive behaviour therapy for insomnia in individuals with self-reported insomnia and chronic fatigue: A secondary analysis of a large scale randomized controlled trial

Insomnia is associated with fatigue, but it is unclear whether response to cognitive behaviour therapy for insomnia is altered in individuals with co-occurring symptoms of insomnia and chronic fatigue. This is a secondary analysis using data from 1717 participants with self-reported insomnia in a community-based randomized controlled trial of digital cognitive behaviour therapy for insomnia compared with patient education. We employed baseline ratings of the Chalder Fatigue Questionnaire to identify participants with more or fewer symptoms of self-reported chronic fatigue (chronic fatigue, n = 592; no chronic fatigue, n = 1125). We used linear mixed models with Insomnia Severity Index, Short Form-12 mental health, Short Form-12 physical health, and the Hospital Anxiety and Depression Scale separately as outcome variables. The main covariates were main effects and interactions for time (baseline versus 9-week follow-up), intervention, and chronic fatigue. Participants with chronic fatigue reported significantly greater improvements following digital cognitive behaviour therapy for insomnia compared with patient education on the Insomnia Severity Index (Cohen's d = 1.36, p < 0.001), Short Form-12 mental health (Cohen's d = 0.19, p = 0.029), and Hospital Anxiety and Depression Scale (Cohen's d = 0.18, p = 0.010). There were no significant differences in the effectiveness of digital cognitive behaviour therapy for insomnia between chronic fatigue and no chronic fatigue participants on any outcome. We conclude that in a large community-based sample of adults with insomnia, co-occurring chronic fatigue did not moderate the effectiveness of digital cognitive behaviour therapy for insomnia on any of the tested outcomes. This may further establish digital cognitive behaviour therapy for insomnia as an adjunctive intervention in individuals with physical and mental disorders.publishedVersio

Functional divergence in the role of N-linked glycosylation in smoothened signaling

The G protein-coupled receptor (GPCR) Smoothened (Smo) is the requisite signal transducer of the evolutionarily conserved Hedgehog (Hh) pathway. Although aspects of Smo signaling are conserved from Drosophila to vertebrates, significant differences have evolved. These include changes in its active sub-cellular localization, and the ability of vertebrate Smo to induce distinct G protein-dependent and independent signals in response to ligand. Whereas the canonical Smo signal to Gli transcriptional effectors occurs in a G protein-independent manner, its non-canonical signal employs Gαi. Whether vertebrate Smo can selectively bias its signal between these routes is not yet known. N-linked glycosylation is a post-translational modification that can influence GPCR trafficking, ligand responsiveness and signal output. Smo proteins in Drosophila and vertebrate systems harbor N-linked glycans, but their role in Smo signaling has not been established. Herein, we present a comprehensive analysis of Drosophila and murine Smo glycosylation that supports a functional divergence in the contribution of N-linked glycans to signaling. Of the seven predicted glycan acceptor sites in Drosophila Smo, one is essential. Loss of N-glycosylation at this site disrupted Smo trafficking and attenuated its signaling capability. In stark contrast, we found that all four predicted N-glycosylation sites on murine Smo were dispensable for proper trafficking, agonist binding and canonical signal induction. However, the under-glycosylated protein was compromised in its ability to induce a non-canonical signal through Gαi, providing for the first time evidence that Smo can bias its signal and that a post-translational modification can impact this process. As such, we postulate a profound shift in N-glycan function from affecting Smo ER exit in flies to influencing its signal output in mice