Bone tissue is a highly vascularized and dynamic system with a complex construction. In order to develop a construct for implant purposes in bone tissue engineering, a proper understanding of the complex dependencies between different cells and cell types would provide further insight into the highly regulated processes during bone repair, namely, angiogenesis and osteogenesis, and might result in sufficiently equipped constructs to be beneficial to patients and thereby accomplish their task. This study is based on anin vitrococulture model consisting of outgrowth endothelial cells and primary osteoblasts and is currently being used in different studies of bone repair processes with special regard to angiogenesis and osteogenesis. Coculture systems of OECs and pOBs positively influence the angiogenic potential of endothelial cells by inducing the formation of angiogenic structures in long-term cultures. Although many studies have focused on cell communication, there are still numerous aspects which remain poorly understood. Therefore, the aim of this study is to investigate certain growth factors and cell communication molecules that are important during bone repair processes. Selected growth factors like VEGF, angiopoietins, BMPs, and IGFs were investigated during angiogenesis and osteogenesis and their expression in the cultures was observed and compared after one and four weeks of cultivation. In addition, to gain a better understanding on the origin of different growth factors, both direct and indirect coculture strategies were employed. Another important focus of this study was to investigate the role of “gap junctions,” small protein pores which connect adjacent cells. With these bridges cells are able to exchange signal molecules, growth factors, and other important mediators. It could be shown that connexins, the gap junction proteins, were located around cell nuclei, where they await their transport to the cell membrane. In addition, areas in which two cells formed gap junctions were found.

Gender differences play a pivotal role in the pathophysiology and treatment of major depressive disorder. This is strongly supported by a mean 2:1 female-male ratio of depression consistently observed throughout studies in developed nations. Considering the urgent need to tailor individualized treatment strategies to fight depression more efficiently, a more precise understanding of gender-specific aspects in the pathophysiology and treatment of depressive disorders is fundamental. However, current treatment guidelines almost entirely neglect gender as a potentially relevant factor. Similarly, the vast majority of animal experiments analysing antidepressant treatment in rodent models exclusively uses male animals and does not consider gender-specific effects. Based on the growing interest in innovative and rapid-acting treatment approaches in depression, such as the administration of ketamine, its metabolites or electroconvulsive therapy, this review article summarizes the evidence supporting the importance of gender in modulating response to rapid acting antidepressant treatment. We provide an overview on the current state of knowledge and propose a framework for rodent experiments to ultimately decode gender-dependent differences in molecular and behavioural mechanisms involved in shaping treatment response.

There is evidence that symptomatology in patients with major depressive disorder (MDD) changes with age. However, studies comparing depressive symptomatology between different age groups during antidepressant therapy are rare. We compared demographic and clinical characteristics in depressed patients of different age groups at baseline and during treatment. 889 MDD inpatients were divided into four age groups (18-29, 30-39, 40-49, 50-65 yrs.). Demographic and clinical characteristics including depressive symptomatology (assessed by the Inventory of Depressive Symptoms) were assessed at baseline and weekly during treatment. At baseline, young patients (18-29 years) significantly more often reported cognitive symptoms like irritability, suicidality, negative self-concept and interpersonal sensitivity and more often suffered from drug abuse and comorbid personality disorders. Late middle aged patients (50-65 years) significantly more often suffered from neuro-vegetative symptoms such as reduced general interest, sexual interest and sleep disturbances and more often showed a recurrent MDD and comorbid physical disorders. During therapy, symptoms such as interpersonal sensitivity in young patients and low interest in sex in late middle aged patients persisted until the end of treatment while all other symptoms declined until day 56. The herein presented age differences in depressive symptomatology only hold true for the study medication and are not generalizable to other antidepressants agents. There are substantial differences in the clinical presentation of depression between age groups. Whereas many of these differences disappear during treatment, some differences persisted until the end of treatment. These findings my help to more specifically tailor the treatment of depressed patients.

Response to antidepressant treatment in major depressive disorder (MDD) cannot be predicted currently, leading to uncertainty in medication selection, increasing costs, and prolonged suffering for many patients. Despite tremendous efforts in identifying response-associated genes in large genome-wide association studies, the results have been fairly modest, underlining the need to establish conceptually novel strategies. For the identification of transcriptome signatures that can distinguish between treatment responders and nonresponders, we herein submit a novel animal experimental approach focusing on extreme phenotypes. We utilized the large variance in response to antidepressant treatment occurring in DBA/2J mice, enabling sample stratification into subpopulations of good and poor treatment responders to delineate response-associated signature transcript profiles in peripheral blood samples. As a proof of concept, we translated our murine data to the transcriptome data of a clinically relevant human cohort. A cluster of 259 differentially regulated genes was identified when peripheral transcriptome profiles of good and poor treatment responders were compared in the murine model. Differences in expression profiles from baseline to week 12 of the human orthologues selected on the basis of the murine transcript signature allowed prediction of response status with an accuracy of 76% in the patient population. Finally, we show that glucocorticoid receptor (GR)-regulated genes are significantly enriched in this cluster of antidepressant-response genes. Our findings point to the involvement of GR sensitivity as a potential key mechanism shaping response to antidepressant treatment and support the hypothesis that antidepressants could stimulate resilience-promoting molecular mechanisms. Our data highlight the suitability of an appropriate animal experimental approach for the discovery of treatment response-associated pathways across species. Major depression is the second leading cause of disability worldwide. However, only one-third of patients with depression benefit from the first antidepressant compound they are prescribed. It is a fundamental problem that the outcomes of individual antidepressant treatments are still highly unpredictable. In clinical studies, discovery of biomarkers for antidepressant response is hampered by confounding factors such as the heterogeneity of the disease phenotype and additional environmental factors, e.g., previous life events and different schedules of psychopharmacological treatment, which reduce the power to detect true response biomarkers. To overcome some of these limitations, we have established a conceptually novel approach that allows the selection of extreme phenotypes in an antidepressant-responsive mouse strain. In the first step, we identify signatures in the transcriptome of peripheral blood associated with responses following stratification into good and poor treatment responders. As proof of concept, we translate the murine data to a population of depressed patients. We show that differences in expression profiles from baseline to week 12 of the human orthologues predict response status in patients. We finally provide evidence that sensitivity of the glucocorticoid receptor could be a potential key mechanism shaping response to antidepressant treatment.