The Hamburg-Model of Integrated Care for Patients with Psychosis: Part 1

Objective: The "Hamburg model" designates an integrated care model for severely ill patients with psychotic disorders financed by the health insurance system in accordance with § 140 SGB V.Methods: It comprises comprehensive and long-term treatment within a regional network of the psychosis center of the University Medical Center Hamburg-Eppendorf (UKE) and private psychiatrists. The treatment model consists of therapeutic assertive community treatment (ACT) provided by a highly specialized treatment team and need-adapted in- and outpatient care.Results and conclusions: The present article summarizes the disease- and treatment-specific rationales for the model development as well as the model structure and treatment contents. The article further summarizes the effectiveness and efficiency results of a study comparing the Hamburg model and treatment as usual (without ACT) within a 12-month follow-up study (ACCESS trial).

Biodiversity effects on nitrate concentrations in soil solution: a Bayesian model

Ecosystems are faced with high rates of species loss which has consequences for their functions and services. To assess the effects of plant species diversity on the nitrogen (N) cycle, we developed a model for monthly mean nitrate (NO3-N) concentrations in soil solution in 0-30 cm mineral soil depth using plant species and functional group richness and functional composition as drivers and assessing the effects of conversion of arable land to grassland, spatially heterogeneous soil properties, and climate. We used monthly mean NO3-N concentrations from 62 plots of a grassland plant diversity experiment from 2003 to 2006. Plant species richness (1-60) and functional group composition (1-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Plant community composition, time since conversion from arable land to grassland, soil texture, and climate data (precipitation, soil moisture, air and soil temperature) were used to develop one general Bayesian multiple regression model for the 62 plots to allow an in-depth evaluation using the experimental design. The model simulated NO3-N concentrations with an overall Bayesian coefficient of determination of 0.48. The temporal course of NO3-N concentrations was simulated differently well for the individual plots with a maximum plot-specific Nash-Sutcliffe Efficiency of 0.57. The model shows that NO3-N concentrations decrease with species richness, but this relation reverses if more than approx. 25 % of legume species are included in the mixture. Presence of legumes increases and presence of grasses decreases NO3-N concentrations compared to mixtures containing only small and tall herbs. Altogether, our model shows that there is a strong influence of plant community composition on NO3-N concentrations.

The effects of endothelin-1 on coronary perfusion pressure during cardiopulmonary resuscitation in a canine model

OBJECTIVE To study the hemodynamic effects of exogenously administered endothelin-1 (ET-1), a peptide produced by endothelial cells with potent non-adrenergically mediated vasoconstrictor properties. METHODS A prospective drug intervention study was carried out in a resuscitation research laboratory. Fifteen mixed-breed dogs were anesthetized and instrumented for hemodynamic monitoring. Asphyxia arrest was produced by clamping the endotracheal tube. Hemodynamic data were collected continuously. Following loss of aortic fluctuations monitored by thoracic aortic catheter, the animals remained in pulseless electrical activity (PEA) for 10 minutes. After 10 minutes of no-flow PEA, closed-chest CPR was begun and the animals were randomized to one of three treatment groups (EPI, 0.02 mg/kg epinephrine IV every 3 minutes; ENDO, 100 micrograms ET-1 IV at 0 minutes; and EPI/ENDO, a combination of the EPI and ENDO treatments). RESULTS ENDO and EPI alone produced similar coronary perfusion pressures (CPPs). The EPI/ENDO combination produced significantly improved CPP compared with that of either EPI or ENDO alone. In the EPI group, the best mean CPP was 16 +/- 14 mm Hg and occurred 7 minutes after drug administration. In the ENDO group, the best mean CPP was 28 +/- 7 mm Hg and occurred 13 minutes after drug administration. In the EPI/ENDO combination group, the best mean CPP was 61 +/- 37 mm Hg and occurred 7 minutes after drug administration (p < 0.05 compared with the EPI and ENDO groups alone). CONCLUSION ET-1 is a potent vasoconstrictor. The combination of EPI and ENDO significantly improved CPP compared with that for either agent alone. ET-1 should be investigated further as a vasoconstrictor in cardiac arrest.

Spontaneous supersymmetry breaking in the 2D N=1 Wess-Zumino Model

We study the phase diagram of the two-dimensional N=1 Wess-Zumino model on the lattice using Wilson fermions and the fermion loop formulation. We give a complete nonperturbative determination of the ground state structure in the continuum and infinite volume limit. We also present a determination of the particle spectrum in the supersymmetric phase, in the supersymmetry broken phase and across the supersymmetry breaking phase transition. In the supersymmetry broken phase, we observe the emergence of the Goldstino particle.

A new model construction by making a detour via intuitionistic theories I: Operational set theory without choice is Π1-equivalent to KP

We introduce a version of operational set theory, OST−, without a choice operation, which has a machinery for Δ0Δ0 separation based on truth functions and the separation operator, and a new kind of applicative set theory, so-called weak explicit set theory WEST, based on Gödel operations. We show that both the theories and Kripke–Platek set theory KPKP with infinity are pairwise Π1Π1 equivalent. We also show analogous assertions for subtheories with ∈-induction restricted in various ways and for supertheories extended by powerset, beta, limit and Mahlo operations. Whereas the upper bound is given by a refinement of inductive definition in KPKP, the lower bound is by a combination, in a specific way, of realisability, (intuitionistic) forcing and negative interpretations. Thus, despite interpretability between classical theories, we make “a detour via intuitionistic theories”. The combined interpretation, seen as a model construction in the sense of Visser's miniature model theory, is a new way of construction for classical theories and could be said the third kind of model construction ever used which is non-trivial on the logical connective level, after generic extension à la Cohen and Krivine's classical realisability model.

Use of activity monitors for assessment of pruritus in an acute model of canine atopic dermatitis

BACKGROUND: We developed a canine model of acute atopic dermatitis to evaluate the potential of compounds to treat pruritus and skin lesions induced in Dermatophagoides farinae (Df)-sensitized dogs. HYPOTHESIS/OBJECTIVES: The aim was to investigate the effectiveness of long-term recording activity monitors to assess pruritus induced by allergen challenges. ANIMALS: Thirty-two Df-sensitized laboratory dogs. METHODS: In two blinded crossover studies, 28 Df-sensitized dogs were challenged on 3 days with a Df slurry applied to clipped abdominal skin. Dogs were treated with a positive control (prednisolone 1 mg/kg once daily for 5 days, starting 1 day before challenge) or left untreated; all were fitted with activity monitors. To confirm pruritus, a parallel study with four dogs was conducted, filming the dogs before and during challenge and assessing the film for pruritic behaviour. RESULTS: The activity of dogs treated with prednisolone was significantly lower between 00.00 and 03.00 h and between 03.00 and 06.00 h compared with untreated dogs (repeated-measures ANCOVA; P < 0.0001). To determine whether the recorded night-time activity corresponded to pruritic manifestations, we compared activity monitor and video recordings of four dogs for two periods (16.30-20.30 and 24.00-03.00 h) before and during a Df challenge. The correlation between night-time activity monitor activity and observed pruritic behaviour was highly significant (test of correlation coefficient versus zero: r = 0.57, P < 0.0001). CONCLUSIONS AND CLINICAL IMPORTANCE: Determination of night-time activity with activity monitors after allergen challenge appears to be an objective and practical way to assess pruritus in this experimental model of canine atopic dermatitis.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A novel Statistical Shape Model for treatment planning of Retinoblastoma

Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes. Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

The Silencing of N-myc Downstream-Regulated Gene-1 in an Orthotopic Pancreatic Cancer Model Leads to More Aggressive Tumor Growth and Metastases

BACKGROUND: The understanding of molecular mechanisms leading to poor prognosis in pancreatic cancer may help develop treatment options. N-myc downstream-regulated gene-1 (NDRG1) has been correlated to better prognosis in pancreatic cancer. Therefore, we thought to analyze how the loss of NDRG1 affects progression in an orthotopic xenograft animal model of recurrence. METHODS: Capan-1 cells were silenced for NDRG1 (C(sil)) or transfected with scrambled shRNA (C(scr)) and compared for anchorage-dependent and anchorage-independent growth, invasion and tube formation in vitro. In an orthotopic xenograft model of recurrence tumors were grown in the pancreatic tail. The effect of NDRG1 silencing was evaluated on tumor size and metastasis. RESULTS: The silencing of NDRG1 in Capan-1 cells leads to more aggressive tumor growth and metastasis. We found faster cell growth, double count of invaded cells and 1.8-fold increase in tube formation in vitro. In vivo local tumors were 5.9-fold larger (p = 0.006) and the number of metastases was higher in animals with tumors silenced for NDRG1 primarily (3 vs. 1.1; p = 0.005) and at recurrence (3.3 vs. 0.9; p = 0.015). CONCLUSION: NDRG1 may be an interesting therapeutic target as its silencing in human pancreatic cancer cells leads to a phenotype with more aggressive tumor growth and metastasis.

Effect of surface restoring on subsurface variability in a climate model during 1949–2005

Initializing the ocean for decadal predictability studies is a challenge, as it requires reconstructing the little observed subsurface trajectory of ocean variability. In this study we explore to what extent surface nudging using well-observed sea surface temperature (SST) can reconstruct the deeper ocean variations for the 1949–2005 period. An ensemble made with a nudged version of the IPSLCM5A model and compared to ocean reanalyses and reconstructed datasets. The SST is restored to observations using a physically-based relaxation coefficient, in contrast to earlier studies, which use a much larger value. The assessment is restricted to the regions where the ocean reanalyses agree, i.e. in the upper 500 m of the ocean, although this can be latitude and basin dependent. Significant reconstruction of the subsurface is achieved in specific regions, namely region of subduction in the subtropical Atlantic, below the thermocline in the equatorial Pacific and, in some cases, in the North Atlantic deep convection regions. Beyond the mean correlations, ocean integrals are used to explore the time evolution of the correlation over 20-year windows. Classical fixed depth heat content diagnostics do not exhibit any significant reconstruction between the different existing bservation-based references and can therefore not be used to assess global average time-varying correlations in the nudged simulations. Using the physically based average temperature above an isotherm (14°C) alleviates this issue in the tropics and subtropics and shows significant reconstruction of these quantities in the nudged simulations for several decades. This skill is attributed to the wind stress reconstruction in the tropics, as already demonstrated in a perfect model study using the same model. Thus, we also show here the robustness of this result in an historical and observational context.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

Clinical Validation of a Peritoneal Dialysis Prescription Model in the PatientOnLine Software

Peritoneal transport characteristics and residual renal function require regular control and subsequent adjustment of the peritoneal dialysis (PD) prescription. Prescription models shall facilitate the prediction of the outcome of such adaptations for a given patient. In the present study, the prescription model implemented in the PatientOnLine software was validated in patients requiring a prescription change. This multicenter, international prospective cohort study with the aim to validate a PD prescription model included patients treated with continuous ambulatory peritoneal dialysis. Patients were examined with the peritoneal function test (PFT) to determine the outcome of their current prescription and the necessity for a prescription change. For these patients, a new prescription was modeled using the PatientOnLine software (Fresenius Medical Care, Bad Homburg, Germany). Two to four weeks after implementation of the new PD regimen, a second PFT was performed. The validation of the prescription model included 54 patients. Predicted and measured peritoneal Kt/V were 1.52 ± 0.31 and 1.66 ± 0.35, and total (peritoneal + renal) Kt/V values were 1.96 ± 0.48 and 2.06 ± 0.44, respectively. Predicted and measured peritoneal creatinine clearances were 42.9 ± 8.6 and 43.0 ± 8.8 L/1.73 m2/week and total creatinine clearances were 65.3 ± 26.0 and 63.3 ± 21.8 L/1.73 m2/week, respectively. The analysis revealed a Pearson's correlation coefficient for peritoneal Kt/V of 0.911 and Lin's concordance coefficient of 0.829. The value of both coefficients was 0.853 for peritoneal creatinine clearance. Predicted and measured daily net ultrafiltration was 0.77 ± 0.49 and 1.16 ± 0.63 L/24 h, respectively. Pearson's correlation and Lin's concordance coefficient were 0.518 and 0.402, respectively. Predicted and measured peritoneal glucose absorption was 125.8 ± 38.8 and 79.9 ± 30.7 g/24 h, respectively, and Pearson's correlation and Lin's concordance coefficient were 0.914 and 0.477, respectively. With good predictability of peritoneal Kt/V and creatinine clearance, the present model provides support for individual dialysis prescription in clinical practice. Peritoneal glucose absorption and ultrafiltration are less predictable and are likely to be influenced by additional clinical factors to be taken into consideration.

Nonperturbative estimate of the heavy quark momentum diffusion coefficient

We estimate the momentum diffusion coefficient of a heavy quark within a pure SU(3) plasma at a temperature of about 1.5Tc. Large-scale Monte Carlo simulations on a series of lattices extending up to 1923×48 permit us to carry out a continuum extrapolation of the so-called color-electric imaginary-time correlator. The extrapolated correlator is analyzed with the help of theoretically motivated models for the corresponding spectral function. Evidence for a nonzero transport coefficient is found and, incorporating systematic uncertainties reflecting model assumptions, we obtain κ=(1.8–3.4)T3. This implies that the “drag coefficient,” characterizing the time scale at which heavy quarks adjust to hydrodynamic flow, is η−1D=(1.8–3.4)(Tc/T)2(M/1.5  GeV)  fm/c, where M is the heavy quark kinetic mass. The results apply to bottom and, with somewhat larger systematic uncertainties, to charm quarks.

Biochemical MRI predicts hip osteoarthritis in an experimental ovine femoroacetabular impingement model

BACKGROUND Cam-type femoroacetabular impingement (FAI) resulting from an abnormal nonspherical femoral head shape leads to chondrolabral damage and is considered a cause of early osteoarthritis. A previously developed experimental ovine FAI model induces a cam-type impingement that results in localized chondrolabral damage, replicating the patterns found in the human hip. Biochemical MRI modalities such as T2 and T2* may allow for evaluation of the cartilage biochemistry long before cartilage loss occurs and, for that reason, may be a worthwhile avenue of inquiry. QUESTIONS/PURPOSES We asked: (1) Does the histological grading of degenerated cartilage correlate with T2 or T2* values in this ovine FAI model? (2) How accurately can zones of degenerated cartilage be predicted with T2 or T2* MRI in this model? METHODS A cam-type FAI was induced in eight Swiss alpine sheep by performing a closing wedge intertrochanteric varus osteotomy. After ambulation of 10 to 14 weeks, the sheep were euthanized and a 3-T MRI of the hip was performed. T2 and T2* values were measured at six locations on the acetabulum and compared with the histological damage pattern using the Mankin score. This is an established histological scoring system to quantify cartilage degeneration. Both T2 and T2* values are determined by cartilage water content and its collagen fiber network. Of those, the T2* mapping is a more modern sequence with technical advantages (eg, shorter acquisition time). Correlation of the Mankin score and the T2 and T2* values, respectively, was evaluated using the Spearman's rank correlation coefficient. We used a hierarchical cluster analysis to calculate the positive and negative predictive values of T2 and T2* to predict advanced cartilage degeneration (Mankin ≥ 3). RESULTS We found a negative correlation between the Mankin score and both the T2 (p < 0.001, r = -0.79) and T2* values (p < 0.001, r = -0.90). For the T2 MRI technique, we found a positive predictive value of 100% (95% confidence interval [CI], 79%-100%) and a negative predictive value of 84% (95% CI, 67%-95%). For the T2* technique, we found a positive predictive value of 100% (95% CI, 79%-100%) and a negative predictive value of 94% (95% CI, 79%-99%). CONCLUSIONS T2 and T2* MRI modalities can reliably detect early cartilage degeneration in the experimental ovine FAI model. CLINICAL RELEVANCE T2 and T2* MRI modalities have the potential to allow for monitoring the natural course of osteoarthrosis noninvasively and to evaluate the results of surgical treatments targeted to joint preservation.

External validation of the Hospital-patient One-year Mortality Risk (HOMR) model for predicting death within 1 year after hospital admission

BACKGROUND Predicting long-term survival after admission to hospital is helpful for clinical, administrative and research purposes. The Hospital-patient One-year Mortality Risk (HOMR) model was derived and internally validated to predict the risk of death within 1 year after admission. We conducted an external validation of the model in a large multicentre study. METHODS We used administrative data for all nonpsychiatric admissions of adult patients to hospitals in the provinces of Ontario (2003-2010) and Alberta (2011-2012), and to the Brigham and Women's Hospital in Boston (2010-2012) to calculate each patient's HOMR score at admission. The HOMR score is based on a set of parameters that captures patient demographics, health burden and severity of acute illness. We determined patient status (alive or dead) 1 year after admission using population-based registries. RESULTS The 3 validation cohorts (n = 2,862,996 in Ontario, 210 595 in Alberta and 66,683 in Boston) were distinct from each other and from the derivation cohort. The overall risk of death within 1 year after admission was 8.7% (95% confidence interval [CI] 8.7% to 8.8%). The HOMR score was strongly and significantly associated with risk of death in all populations and was highly discriminative, with a C statistic ranging from 0.89 (95% CI 0.87 to 0.91) to 0.92 (95% CI 0.91 to 0.92). Observed and expected outcome risks were similar (median absolute difference in percent dying in 1 yr 0.3%, interquartile range 0.05%-2.5%). INTERPRETATION The HOMR score, calculated using routinely collected administrative data, accurately predicted the risk of death among adult patients within 1 year after admission to hospital for nonpsychiatric indications. Similar performance was seen when the score was used in geographically and temporally diverse populations. The HOMR model can be used for risk adjustment in analyses of health administrative data to predict long-term survival among hospital patients.

MASP-1 Induced Clotting--The First Model of Prothrombin Activation by MASP-1.

Mannan-binding lectin-associated serine protease-1 (MASP-1), a protein of the complement lectin pathway, resembles thrombin in terms of structural features and substrate specificity. Due to its interplay with several coagulation factors, it has the ability to induce fibrin clot formation independent of the usual coagulation activation pathways. We have recently shown that MASP-1 activates prothrombin and identified arginine (R) 155, R271, and R393 as potential cleavage sites. FXa cleaves R320 instead of R393, and thrombin cleaves R155 and R284 in prothrombin. Here we have used three arginine-to-glutamine mutants of prothrombin, R271Q, R320Q, R393Q and the serine-to-alanine active site mutant S525A to investigate in detail the mechanism of MASP-1 mediated prothrombin activation. Prothrombin wildtype and mutants were digested with MASP-1 and the cleavage products were analysed by SDS-PAGE and N-terminal sequencing. A functional clotting assay was performed by thrombelastography. We have found that MASP-1 activates prothrombin via two simultaneous pathways, either cleaving at R271 or R393 first. Both pathways result in the formation of several active alternative thrombin species. Functional studies confirmed that both R393 and R320 are required for prothrombin activation by MASP-1, whereas R155 is not considered to be an important cleavage site in this process. In conclusion, we have described for the first time a detailed model of prothrombin activation by MASP-1.