Duration of untreated psychosis: Impact of the definition of treatment onset on its predictive value over three years of treatment.

While reduction of DUP (Duration of Untreated Psychosis) is a key goal in early intervention strategies, the predictive value of DUP on outcome has been questioned. We planned this study in order to explore the impact of three different definition of "treatment initiation" on the predictive value of DUP on outcome in an early psychosis sample. 221 early psychosis patients aged 18-35 were followed-up prospectively over 36 months. DUP was measured using three definitions for treatment onset: Initiation of antipsychotic medication (DUP1); engagement in a specialized programme (DUP2) and combination of engagement in a specialized programme and adherence to medication (DUP3). 10% of patients never reached criteria for DUP3 and therefore were never adequately treated over the 36-month period of care. While DUP1 and DUP2 had a limited predictive value on outcome, DUP3, based on a more restrictive definition for treatment onset, was a better predictor of positive and negative symptoms, as well as functional outcome at 12, 24 and 36 months. Globally, DUP3 explained 2 to 5 times more of the variance than DUP1 and DUP2, with effect sizes falling in the medium range according to Cohen. The limited predictive value of DUP on outcome in previous studies may be linked to problems of definitions that do not take adherence to treatment into account. While they need replication, our results suggest effort to reduce DUP should continue and aim both at early detection and development of engagement strategies

Fisheye Photogrammetry to Survey Narrow Spaces in Architecture and a Hypogea Environment

Nowadays, the increasing computation power of commercial grade processors has actively led to a vast spreading of image-based reconstruction software as well as its application in different disciplines. As a result, new frontiers regarding the use of photogrammetry in a vast range of investigation activities are being explored. This paper investigates the implementation of fisheye lenses in non-classical survey activities along with the related problematics. Fisheye lenses are outstanding because of their large field of view. This characteristic alone can be a game changer in reducing the amount of data required, thus speeding up the photogrammetric process when needed. Although they come at a cost, field of view (FOV), speed and manoeuvrability are key to the success of those optics as shown by two of the presented case studies: the survey of a very narrow spiral staircase located in the Duomo di Milano and the survey of a very narrow hypogea structure in Rome. A third case study, which deals with low-cost sensors, shows the metric evaluation of a commercial spherical camera equipped with fisheye lenses

Novel Selective Estrogen Receptor Modulator Ameliorates Murine Colitis

Estrogen-receptor-mediated signaling has been suggested to decrease the inflammatory response in monocyte macrophages. Previously, we showed that a novel selective estrogen receptor modulator (SERM2) promotes anti-inflammatory phenotype of monocytes in vitro. In this study, we demonstrate the potential of SERM2 in amelioration of colitis. We utilized a dextran sodium sulfate (DSS)-induced colitis model in FVB/n mice to demonstrate the effects of orally administered SERM2 on the clinical status of the mice and the histopathological changes in the colon, as well as proportion of Mrc-1 positive macrophages. SERM2 nuclear receptor affinities were measured by radioligand binding assays. Orally administered, this compound significantly alleviated DSS-induced colitis in male mice and induced local estrogen receptor activation in the inflamed colon, as well as promoting anti-inflammatory cytokine expression and infiltration of anti-inflammatory monocytes. We show that this novel drug candidate has an affinity to estrogen receptors alpha and beta and progesterone receptors, but not to glucocorticoid receptor, thus expressing unique binding properties compared to other sex steroid receptor ligands. These results indicate that novel drug candidates to alleviate inflammatory conditions of the colon could be found among sex steroid receptor activating compounds

Leishmania braziliensis Infection Enhances Toll-Like Receptors 2 and 4 Expression and Triggers TNF-α and IL-10 Production in Human Cutaneous Leishmaniasis

Cutaneous leishmaniasis (CL) caused by infection with Leishmania braziliensis is characterized by an exaggerated inflammatory response that controls the parasite burden, but also contributes to pathology. While myeloid cells are required to eliminate the parasite, recent studies indicate that they may also participate in the inflammatory response driving disease progression. The innate immune response to leishmania is driven in part by the Toll-like receptors (TLRs) TLR2, TLR4, and TLR9. In this study, we used flow cytometric analysis to compare TLR2 and TLR4 expression in monocyte subsets (classical, intermediate, and non-classical) from CL patients and healthy subjects (HS). We also determined if there was an association of either the pro-inflammatory cytokine TNF or the anti-inflammatory cytokine IL-10 with TLR2 or TLR4 expression levels after L. braziliensis infection. In vitro infection with L. braziliensis caused CL monocytes to up-regulate TLR2 and TLR4 expression. We also found that intermediate monocytes expressed the highest levels of TLR2 and TLR4 and that infected monocytes produced more TNF and IL-10 than uninfected monocytes. Finally, while classical and intermediate monocytes were mainly responsible for TNF production, classical monocytes were the main source of IL-10. Collectively, our studies revealed that up-regulated TLR2/4 expression and TNF production by intermediate/inflammatory subsets of monocytes from patients correlates with detrimental outcome of cutaneous leishmaniasis

Healing in the Sámi North

There is a special emphasis today on integrating traditional healing within health services. However, most areas in which there is a system of traditional healing have undergone colonization and a number of pressures suppressing tradition for hundreds of years. The question arises as to how one can understand today’s tradition in light of earlier traditions. This article is based on material collected in Sámi areas of Finnmark and Nord-Troms Norway; it compares local healing traditions with what is known of earlier shamanic traditions in the area. The study is based on 27 interviews among healers and their patients. The findings suggest that although local healing traditions among the Sámi in northern Norway have undergone major transformations during the last several hundred years, they may be considered an extension of a long-standing tradition with deep roots in the region. Of special interest are also the new forms tradition may take in today’s changing global society

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Fisheye multi-camera system calibration for surveying narrow and complex architectures

Narrow spaces and passages are not a rare encounter in cultural heritage, the shape and extension of those areas place a serious challenge on any techniques one may choose to survey their 3D geometry. Especially on techniques that make use of stationary instrumentation like terrestrial laser scanning. The ratio between space extension and cross section width of many corridors and staircases can easily lead to distortions/drift of the 3D reconstruction because of the problem of propagation of uncertainty. This paper investigates the use of fisheye photogrammetry to produce the 3D reconstruction of such spaces and presents some tests to contain the degree of freedom of the photogrammetric network, thereby containing the drift of long data set as well. The idea is that of employing a multi-camera system composed of several fisheye cameras and to implement distances and relative orientation constraints, as well as the pre-calibration of the internal parameters for each camera, within the bundle adjustment. For the beginning of this investigation, we used the NCTech iSTAR panoramic camera as a rigid multi-camera system. The case study of the Amedeo Spire of the Milan Cathedral, that encloses a spiral staircase, is the stage for all the tests. Comparisons have been made between the results obtained with the multicamera configuration, the auto-stitched equirectangular images and a data set obtained with a monocular fisheye configuration using a full frame DSLR. Results show improved accuracy, down to millimetres, using a rigidly constrained multi-camera