Early Detection and Treatment of Psychosis: The Bern Child and Adolescent Psychiatric Perspective

Commonly conceptualized as neurodevelopmental disorders of yet poorly understood aetiology, schizophrenia and other nonorganic psychoses remain one of the most debilitating illnesses with often poor outcome despite all progress in treatment of the manifest disorder. Drawing on the frequent poor outcome of psychosis and its association with the frequently extended periods of untreated first-episode psychosis (FEP) including its prodrome, an early detection and treatment of both the FEP and the preceding at-risk mental state (ARMS) have been increasingly studied. Thereby both approaches are confronted with different problems, for example, treatment engagement in FEP and predictive accuracy in ARMS. They share, however, the problems related to the lack of understanding of developmental, that is, age-related, peculiarities and of the presentation and natural course of their cardinal symptoms in the community. Most research on early detection and intervention in FEP and ARMS is still related to clinical psychiatric samples, and little is known about symptom presentation and burden and help-seeking in the general population related to these experiences. Furthermore, in particular in the early detection of an ARMS, studies often address adolescents and young adults alike without consideration of developmental characteristics, thereby applying risk criteria that have been developed predominately in adults. Combining our earlier experiences described in this paper in child and adolescent, and general psychiatry as well as in both lines of research, that is, on early psychosis and its treatment and on the early detection of psychosis, in particular in its very early states by subjective disturbances in terms of basic symptoms, age-related developmental and epidemiological aspects have therefore been made the focus of our current studies in Bern, thus making our line of research unique

Detection and quantification of leptospires in urine of dogs: a maintenance host for the zoonotic disease leptospirosis.

Leptospirosis is a global zoonotic disease. Pathogenic Leptospira species, the causative agent of leptospirosis, colonize the renal tubules of chronically infected maintenance hosts such as dogs, rats and cattle. Maintenance hosts typically remain clinically asymptomatic and shed leptospires into the environment via urine. In contrast, accidental hosts such as humans can suffer severe acute forms of the disease. Infection results from direct contact with infected urine or indirectly, through contaminated water sources. In this study, a quantitative real-time PCR specific for lipL32 was designed to detect the urinary shedding of leptospires from dogs. The sensitivity and specificity of the assay was evaluated using both a panel of pathogenic Leptospira species and clinical microbial isolates, and samples of urine collected from experimentally infected rats and non-infected controls. The lower limit of detection was approximately 3 genome equivalents per reaction. The assay was applied to canine urine samples collected from local dog sanctuaries and the University Veterinary Hospital (UVH) at University College Dublin. Of 525 canine urine samples assayed, 37 were positive, indicating a prevalence of urinary shedding of leptospires of 7.05%. These results highlight the need to provide effective canine vaccination strategies and raise public health awareness.

Detection and management of drug-resistant tuberculosis in HIV-infected patients in lower-income countries.

SETTING Drug resistance threatens tuberculosis (TB) control, particularly among human immunodeficiency virus (HIV) infected persons. OBJECTIVE To describe practices in the prevention and management of drug-resistant TB under antiretroviral therapy (ART) programs in lower-income countries. DESIGN We used online questionnaires to collect program-level data on 47 ART programs in Southern Africa (n = 14), East Africa (n = 8), West Africa (n = 7), Central Africa (n = 5), Latin America (n = 7) and the Asia-Pacific (n = 6 programs) in 2012. Patient-level data were collected on 1002 adult TB patients seen at 40 of the participating ART programs. RESULTS Phenotypic drug susceptibility testing (DST) was available in 36 (77%) ART programs, but was only used for 22% of all TB patients. Molecular DST was available in 33 (70%) programs and was used in 23% of all TB patients. Twenty ART programs (43%) provided directly observed therapy (DOT) during the entire course of treatment, 16 (34%) during the intensive phase only, and 11 (23%) did not follow DOT. Fourteen (30%) ART programs reported no access to second-line anti-tuberculosis regimens; 18 (38%) reported TB drug shortages. CONCLUSIONS Capacity to diagnose and treat drug-resistant TB was limited across ART programs in lower-income countries. DOT was not always implemented and drug supplies were regularly interrupted, which may contribute to the global emergence of drug resistance.

Simultaneous detection and discrimination of virulent and benign Dichelobacter nodosus in sheep of flocks affected by foot rot and in clinically healthy flocks by competitive real-time PCR.

Ovine foot rot caused by Dichelobacter nodosus is affecting sheep worldwide. The current diagnostic methods are difficult and cumbersome. Here, we present a competitive real-time PCR based on allelic discrimination of the protease genes aprV2 and aprB2. This method allows direct detection and differentiation of virulent and benign D. nodosus from interdigital skin swabs in a single test. Clinically affected sheep harbored high loads of only virulent strains, whereas healthy sheep had lower loads of predominantly benign strains.

Dispersive approach to hadronic light-by-light scattering and the muon ɡ − 2

The largest uncertainties in the Standard Model calculation of the anomalous magnetic moment of the muon (ɡ − 2)μ come from hadronic contributions. In particular, it can be expected that in a few years the subleading hadronic light-by-light (HLbL) contribution will dominate the theory uncertainty. We present a dispersive description of the HLbL tensor. This new, model-independent approach opens up an avenue towards a data-driven determination of the HLbL contribution to the (ɡ − 2)μ.

Detection and quantification of Flavobacterium psychrophilum in water and fish tissue samples by quantitative real time PCR.

BACKGROUND Flavobacterium psychrophilum is the agent of Bacterial Cold Water Disease and Rainbow Trout Fry Syndrome, two diseases leading to high mortality. Pathogen detection is mainly carried out using cultures and more rapid and sensitive methods are needed. RESULTS We describe a qPCR technique based on the single copy gene β' DNA-dependent RNA polymerase (rpoC). Its detection limit was 20 gene copies and the quantification limit 103 gene copies per reaction. Tests on spiked spleens with known concentrations of F. psychrophilum (106 to 101 cells per reaction) showed no cross-reactions between the spleen tissue and the primers and probe. Screening of water samples and spleens from symptomless and infected fishes indicated that the pathogen was already present before the outbreaks, but F. psychrophilum was only quantifiable in spleens from diseased fishes. CONCLUSIONS This qPCR can be used as a highly sensitive and specific method to detect F. psychrophilum in different sample types without the need for culturing. qPCR allows a reliable detection and quantification of F. psychrophilum in samples with low pathogen densities. Quantitative data on F. psychrophilum abundance could be useful to investigate risk factors linked to infections and also as early warning system prior to potential devastating outbreak.

Spatial-temporal clustering of companion animal enteric syndrome: detection and investigation through the use of electronic medical records from participating private practices

SUMMARY There is interest in the potential of companion animal surveillance to provide data to improve pet health and to provide early warning of environmental hazards to people. We implemented a companion animal surveillance system in Calgary, Alberta and the surrounding communities. Informatics technologies automatically extracted electronic medical records from participating veterinary practices and identified cases of enteric syndrome in the warehoused records. The data were analysed using time-series analyses and a retrospective space-time permutation scan statistic. We identified a seasonal pattern of reports of occurrences of enteric syndromes in companion animals and four statistically significant clusters of enteric syndrome cases. The cases within each cluster were examined and information about the animals involved (species, age, sex), their vaccination history, possible exposure or risk behaviour history, information about disease severity, and the aetiological diagnosis was collected. We then assessed whether the cases within the cluster were unusual and if they represented an animal or public health threat. There was often insufficient information recorded in the medical record to characterize the clusters by aetiology or exposures. Space-time analysis of companion animal enteric syndrome cases found evidence of clustering. Collection of more epidemiologically relevant data would enhance the utility of practice-based companion animal surveillance.

Detection and functional portrayal of a novel class of dihydrotestosterone derived selective progesterone receptor modulators (SPRM).

In early pregnancy, abortion can be induced by blocking the actions of progesterone receptors (PR). However, the PR antagonist, mifepristone (RU38486), is rather unselective in clinical use because it also cross-reacts with other nuclear receptors. Since the ligand-binding domain of human progesterone receptor (hPR) and androgen receptor (hAR) share 54% identity, we hypothesized that derivatives of dihydrotestosterone (DHT), the cognate ligand for hAR, might also regulate the hPR. Compounds designed and synthesized in our laboratory were investigated for their affinities for hPRB, hAR, glucocorticoid receptor (hGRα) and mineralocorticoid receptor (hMR), using whole cell receptor competitive binding assays. Agonistic and antagonistic activities were characterized by reporter assays. Nuclear translocation was monitored using cherry-hPRB and GFP-hAR chimeric receptors. Cytostatic properties and apoptosis were tested on breast cancer cells (MCF7, T-47D). One compound presented a favorable profile with an apparent neutral hPRB antagonistic function, a selective cherry-hPRB nuclear translocation and a cytostatic effect. 3D models of human PR and AR with this ligand were constructed to investigate the molecular basis of selectivity. Our data suggest that these novel DHT-derivatives provide suitable templates for the development of new selective steroidal hPR antagonists.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

Light-quark and gluon jet discrimination in pp collisions at √s=7 TeV with the ATLAS detector

A likelihood-based discriminant for the identification of quark- and gluon-initiated jets is built and validated using 4.7 fb−1 √ of proton–proton collision data at √s = 7 TeV collected with the ATLAS detector at the LHC. Data sampleswith enriched quark or gluon content are used in the construction and validation of templates of jet properties that are the input to the likelihood-based discriminant. The discriminating power of the jet tagger is established in both data and Monte Carlo samples within a systematic uncertainty of ≈ 10–20 %. In data, light-quark jets can be tagged with an efficiency of ≈ 50% while achieving a gluon-jet mis-tag rate of ≈ 25% in a pT range between 40 GeV and 360 GeV for jets in the acceptance of the tracker. The rejection of gluon-jets found in the data is significantly below what is attainable using a Pythia 6Monte Carlo simulation, where gluon-jet mis-tag rates of 10% can be reached for a 50% selection efficiency of light-quark jets using the same jet properties.

Unified detection and tracking of instruments during retinal microsurgery

Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not naturally take advantage of target motion continuity during detection. The advantage of local optimization is efficiency and accuracy, but it requires additional algorithms to initialize tracking when the target is lost. To bridge these two approaches, we propose a framework for unified detection and tracking as a time-series Bayesian estimation problem. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a target in each frame. To do this we integrate the Active Testing (AT) paradigm with Bayesian filtering, and this results in a framework capable of both detecting and tracking robustly in situations where the target object enters and leaves the field of view regularly. We demonstrate our approach on a retinal tool tracking problem and show through extensive experiments that our method provides an efficient and robust tracking solution.

Detection and quantification of 56 new psychoactive substances in whole blood and urine by LC-MS/MS

BACKGROUND New psychoactive substances (NPS) have become increasingly prevalent and are sold in internet shops as 'bath salts' or 'research chemicals' and comprehensive bioanalytical methods are needed for their detection. METHODOLOGY We developed and validated a method using LC and MS/MS to quantify 56 NPS in blood and urine, including amphetamine derivatives, 2C compounds, aminoindanes, cathinones, piperazines, tryptamines, dissociatives and others. Instrumentation included a Synergi Polar-RP column (Phenomenex) and a 3200 QTrap mass spectrometer (AB Sciex). Run time was 20 min. CONCLUSION A novel method is presented for the unambiguous identification and quantification of 56 NPS in blood and urine samples in clinical and forensic cases, e.g., intoxications or driving under the influence of drugs.

Cold Microwave-Enabled Protein Detection and Quantification.

Protein screening/detection is an essential tool in many laboratories. Owing to the relatively large time investments that are required by standard protocols, the development of methods with higher throughput while maintaining an at least comparable signal-to-noise ratio is highly beneficial in many research areas. This chapter describes how cold microwave technology can be used to enhance the rate of molecular interactions and provides protocols for dot blots, Western blots, and ELISA procedures permitting a completion of all incubation steps (blocking and antibody steps) within 24-45 min.

Dish Detection and Segmentation for Dietary Assessment on Smartphones

Diet-related chronic diseases severely affect personal and global health. However, managing or treating these diseases currently requires long training and high personal involvement to succeed. Computer vision systems could assist with the assessment of diet by detecting and recognizing different foods and their portions in images. We propose novel methods for detecting a dish in an image and segmenting its contents with and without user interaction. All methods were evaluated on a database of over 1600 manually annotated images. The dish detection scored an average of 99% accuracy with a .2s/image run time, while the automatic and semi-automatic dish segmentation methods reached average accuracies of 88% and 91% respectively, with an average run time of .5s/image, outperforming competing solutions.