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Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
Objectives: Current treatments for chronic depression have focused on reducing interpersonal problems and negative affect, but paid little attention to promoting prosocial motivation and positive affect. Following this treatment focus, the objective of the present study was to examine whether the combination of metta (Loving Kindness) group meditation and subsequent tailored individual therapy focusing on kindness towards oneself and others (metta-based therapy, MBT) shows greater improvements in depressive symptoms than a wait list control group in patients with chronic depression. Methods: Forty-eight patients with DSM-5 persistent depressive disorder were randomly assigned to MBT or a wait list control condition. Outcome was assessed after group meditation, after subsequent individual therapy, and at 6-month follow-up. The primary outcome measure was an independent blind rating of depressive symptoms at post-test. Secondary outcome included changes in self-reported depression, behavioral activation, rumination, social functioning, mindfulness, compassion, and clinician-rated emotion regulation. Results: Mixed-design analyses showed significant differences between MBT and WLC in changes from pre- to post-test in clinician-rated and self-rated depression, behavioral activation, rumination, social functioning, mindfulness, and emotion regulation. Most of the changes occurred during group meditation and were associated with large effect sizes. Improvements were maintained at 6-month follow-up. Conclusions: The results provide preliminary support for the effectiveness of MBT in treating chronic depression. Trial Registration: ISRCTN, ISRCTN97264476.
Einleitung: Am 16.12.06 wurde im Eurotransplant-Gebiet der MELD-Score (MELD) als Allokationsbasis zur Lebertransplantation (OLT) eingeführt. Ziel ist eine Reduktion der Sterblichkeit auf der Warteliste. Material und Methoden: 100 Patienten wurden in die prospektive Analyse der MELD-Allokation vom 16.12.06 bis 15.09.07 einbezogen. Ergebnisse: Aktuell warten 68 Pat., 28 Pat. wurden transplantiert, 4 Pat. sind auf der Warteliste (WL) verstorben (4%). Der mittlere MELD auf der WL beträgt 17,2 +/- 5,2 (7-28). Bei 12 Pat. liegt eine Standard-exception (SE) (n=10 HCC, n=2 metabolische Erkrankung) mit einem Match-MELD von 25,6 +/-2,06 vor (24-28). Die Todesursachen der vier auf der WL verstorbenen Pat. waren eine akute Varizenblutung (MELD 9), zwei kardiale Versagen (MELD 13, 18) und eine MRSA-Sepsis (MELD 29, NT-Status). Die 28 transplantierten Pat. hatte zum Zeitpunkt der Transplantation einen mittleren MELD von 27,66 +/- 5,1 Punkten (21 bis 40). 20 Pat. wurden aufgrund des Labor-MELD (28,4 +/- 5,3, 24-40) transplantiert, wobei 7 Pat. einen MELD über 30 aufwiesen. Die Wartezeit lag bei 11,55 +/- 5,3 Tagen. 8 Pat. erhielten bei SE bei HCC (MELD 24 +/- 0, 24) ein Organ nach einer Wartezeit von 320 +/- 9,7 Tagen. Aktuell leben 23 der 28 transplantierten Pat. Bei zwei verstorbenen Pat. war die Todesursache ein kardiales Versagen, bei zwei Patienten eine primäre Non-Funktion sowie ein septisches Multiorganversagen. Schlussfolgerung: Während der ersten Monate der MELD Allokation lag die Letalität auf der WL in unserem Zentrum bei 4%. Patienten mit einem mittleren MELD über 27 erhielten Organangebote und konnten nach kurzer Wartezeit transplantiert werden.
Conventional treatments for mood disorders primarily focus on reducing negative affect, but little on enhancing positive affect. Loving-kindness meditation (LKM) is a traditional meditation practice directly oriented toward enhancing unconditional and positive emotional states of kindness towards oneself and others. We report here two independent and uncontrolled studies carried out at different centers, one in Boston, USA (n = 10), and one in Frankfurt, Germany (n = 8), to examine the potential therapeutic utility of a brief LKM group intervention for symptoms of dysthymia and depression. Results at both centers suggest that LKM was associated with large-sized effects on self-reported symptoms of depression (d = 3.33 and 1.90), negative affect (d = 1.98 and 0.92), and positive affect (d = 1.63 and 0.94). Large effects were also found for clinician-reported changes in depression, rumination and specific positive emotions, and moderate effects for changes in adaptive emotion regulation strategies. The qualitative data analyses provide additional support for the potential clinical utility of the intervention. This proof-of-concept evaluation of LKM as a clinical strategy warrants further investigation.
Noneequilibrium models (three-fluid hydrodynamics and UrQMD) use to discuss the uniqueness of often proposed experimental signatures for quark matter formation in relativistic heavy ion collisions. It is demonstrated that these two models - although they do treat the most interesting early phase of the collisions quite differently(thermalizing QGP vs. coherent color fields with virtual particles) - both yields a reasonable agreement with a large variety of the available heavy ion data.
Fragment mass distributions for fission after full momentum transfer were measured in the reactions of 30Si,34,36 S,31P,40Ar + 238U at bombarding energies around the Coulomb barrier. Mass distributions change significantly as a function of incident beam energy. The asymmetric fission probability increases at sub-barrier energy. The phenomenon is interpreted as an enhanced quasifission probability owing to orientation effects on fusion and/or quasifission. The evaporation residue (ER) cross sections were measured in the reactions of 30Si + 238U and 34S + 238U to obtain information on fusion. In the latter reaction, significant suppression of fusion was implied. This suggests that fission events different from compound nucleus are included in the masssymmetric fragments. The results are supported by a model calculation based on a dynamical calculation using Langevin equation, in which the mass distribution for fusion-fission and quasifission fragments are separately determined.
Fission fragment mass distributions were measured in heavy-ion induced fissions using 238U target nucleus. The measured mass distributions changed drastically with incident energy. The results are explained by a change of the ratio between fusion and qasifission with nuclear orientation. A calculation based on a fluctuation dissipation model reproduced the mass distributions and their incident energy dependence. Fusion probability was determined in the analysis, and the values were consistent with those determined from the evaporation residue cross sections.
Recent calculations applying statistical mechanics indicate that in a setting with compactified large extra dimensions a black hole might evolve into a (quasi-)stable state with mass close to the new fundamental scale M f. Black holes and therefore their relics might be produced at the LHC in the case of extra-dimensional topologies. In this energy regime, Hawking's evaporation scenario is modified due to energy conservation and quantum effects. We reanalyse the evaporation of small black holes including the quantisation of the emitted radiation due to the finite surface of the black hole. It is found that observable stable black hole relics with masses sim 1-3 M f would form which could be identified by a delayed single jet with a corresponding hard momentum kick to the relic and by ionisation, e.g. in a TPC.
Since the domestication of the urus, 10.000 years ago, mankind utilizes bovine milk for different purposes. Besides usage as a nutrient also the external application of milk on skin has a long tradition going back to at least the ancient Aegypt with Cleopatra VII as a great exponent. In order to test whether milk has impact on skin physiology, cultures of human skin fibroblasts were exposed to commercial bovine milk. Our data show significant induction of proliferation by milk (max. 2,3-fold, EC50: 2,5% milk) without toxic effects. Surprisingly, bovine milk was identified as strong inducer of collagen 1A1 synthesis at both, the protein (4-fold, EC50: 0,09% milk) and promoter level. Regarding the underlying molecular pathways, we show functional activation of STAT6 in a p44/42 and p38-dependent manner. More upstream, we identified IGF-1 and insulin as key factors responsible for milk-induced collagen synthesis. These findings show that bovine milk contains bioactive molecules that act on human skin cells. Therefore, it is tempting to test the herein introduced concept in treatment of atrophic skin conditions induced e.g. by UV light or corticosteroids.