The paradox of the 'wounded healer'

This doctoral portfolio consists of three different pieces of work related to the paradox of the ‘wounded healer’. It aims to reflect my journey as a practitioner-researcher. The different pieces show different aspects of this journey. The portfolio contains an original piece of research, an advanced client study and process report and thirdly a journal article. Jung (1951) introduced the archetype of the wounded healer to promote using personal experiences of healing to enhance empathy in the healing relationship. For therapists, this paradox describes the discrepancy of an acknowledgement of woundedness, while containing the client’s hopes and expectations of being healed, by projecting a sense of wholeness (Gerson, 1996; Groesbeck, 1975; Miller & Baldwin, 2013). Street (2005) refers to this when he describes the therapists’ life as the journey of a white knight, using his super powers on his way to the Holy Grail. Some suggest that the therapist’s wounds are a source of creativity (Adler, 1985) or sense of humanity (Martin, 2011), while others note the potential of pathology (e.g. Barnett, 2007) or power abuse (Guggenbuhl-Craig, 1971). Whichever way, the therapeutic work is always influenced by the therapists’ wounds and life changes (Gerson, 1996) and adds to the therapists’ personal ‘mythology’ (Guggenbuhl- Craig, 1995, p. 75)

Expression of muscle anabolic and metabolic factors in mechanically loaded MLO-Y4 osteocytes

Lack of physical activity results in muscle atrophy and bone loss, which can be counteracted by mechanical loading. Similar molecular signaling pathways are involved in the adaptation of muscle and bone mass to mechanical loading. Whether anabolic and metabolic factors regulating muscle mass, i.e., insulin-like growth factor-I isoforms (IGF-I Ea), mechano growth factor (MGF), myostatin, vascular endothelial growth factor (VEGF), or hepatocyte growth factor (HGF), are also produced by osteocytes in bone in response to mechanical loading is largely unknown. Therefore, we investigated whether mechanical loading by pulsating fluid flow (PFF) modulates the mRNA and/or protein levels of muscle anabolic and metabolic factors in MLO-Y4 osteocytes. Unloaded MLO-Y4 osteocytes expressed mRNA of VEGF, HGF, IGF-I Ea, and MGF, but not myostatin. PFF increased mRNA levels of IGF-I Ea (2.1-fold) and MGF (2.0-fold) at a peak shear stress rate of 44Pa/s, but not at 22Pa/s. PFF at 22 Pa/s increased VEGF mRNA levels (1.8- to 2.5-fold) and VEGF protein release (2.0- to 2.9-fold). Inhibition of nitric oxide production decreased (2.0-fold) PFF-induced VEGF protein release. PFF at 22 Pa/s decreased HGF mRNA levels (1.5-fold) but increased HGF protein release (2.3-fold). PFF-induced HGF protein release was nitric oxide dependent. Our data show that mechanically loaded MLO-Y4 osteocytes differentially express anabolic and metabolic factors involved in the adaptive response of muscle to mechanical loading (i.e., IGF-I Ea, MGF, VEGF, and HGF). Similarly to muscle fibers, mechanical loading enhanced expression levels of these growth factors in MLO-Y4 osteocytes. Although in MLO-Y4 osteocytes expression levels of IGF-I Ea and MGF of myostatin were very low or absent, it is known that the activity of osteoblasts and osteoclasts is strongly affected by them. The abundant expression levels of these factors in muscle cells, in combination with low expression in MLO-Y4 osteocytes, provide a possibility that growth factors expressed in muscle could affect signaling in bone cells

Assessing Site Productivity in Tropical Moist Forests: A Review

Reliable estimates of site productivity are essential for improved predictions of timber yields and for meaningful simulation studies. Few suitable techniques exist for tropical moist forests. Conventional indices such as site index cannot be estimated reliably for stands with many species or indeterminate ages. Emerging techniques require two steps: calibration and validation with permanent sample plots, and correlation with easily measured stand parameters. One promising index for the tropical moist forest is based on the expected diameter increment of individual trees adjusted for tree size and competition. Measures of stand height such as maximum stand height, canopy height and the height-diameter relationship may also prove useful. Proposed measures should satisfy four criteria: they should be reproducible and consistent over long periods of time; indicative of the site, and not unduly influenced by stand condition or management history; correlated with the site's productive potential; and at least as good as any other productivity measures available

Models predicting the growth response to growth hormone treatment in short children independent of GH status, birth size and gestational age

<p>Abstract</p> <p>Background</p> <p>Mathematical models can be used to predict individual growth responses to growth hormone (GH) therapy. The aim of this study was to construct and validate high-precision models to predict the growth response to GH treatment of short children, independent of their GH status, birth size and gestational age. As the GH doses are included, these models can be used to individualize treatment.</p> <p>Methods</p> <p>Growth data from 415 short prepubertal children were used to construct models for predicting the growth response during the first years of GH therapy. The performance of the models was validated with data from a separate cohort of 112 children using the same inclusion criteria.</p> <p>Results</p> <p>Using only auxological data, the model had a standard error of the residuals (SD_res), of 0.23 SDS. The model was improved when endocrine data (GH_maxprofile, IGF-I and leptin) collected before starting GH treatment were included. Inclusion of these data resulted in a decrease of the SD_resto 0.15 SDS (corresponding to 1.1 cm in a 3-year-old child and 1.6 cm in a 7-year old). Validation of these models with a separate cohort, showed similar SD_resfor both types of models. Preterm children were not included in the Model group, but predictions for this group were within the expected range.</p> <p>Conclusion</p> <p>These prediction models can with high accuracy be used to identify short children who will benefit from GH treatment. They are clinically useful as they are constructed using data from short children with a broad range of GH secretory status, birth size and gestational age.</p

Effects of biogas production on inter- and in-farm competition

Biogas production is one of the influential innovations of recent decades in German agriculture. Due to high guaranteed energy prices biogas production led to distortions in agricultural and land markets. This paper provides insights in effects of biogas production on farms, farm structures and rural areas for the region Altmark, Germany, for the period 2012-2026 by using the agent-based simulation model AgriPoliS. AgriPoliS enables to simulate agricultural structural change and impacts of policies based on a linear programming approach. To maximize the household-income, farm agents can invest, produce and compete against each other on the land rental market. To analyse effects of biogas production, biogas plants, possible substrate mixtures and feed-in remunerations are introduced in the model. In our analyses, we focus on 1) the choice of production of farms, 2) the competition between farms, and 3) impacts on rural areas including environmental issues and labour market. Our simulation results show that biogas production provides especially for farmers with high management capabilities and large farms a profitable income opportunity. On average, biogas farms cannot increase their profitability. As result of an increased value added through biogas production and high competition among farms, rental prices increase and thus a high share of the value added is transferred to the land owners. Biogas production leads to an intensification of land use, especially to increases in cultivation of grass and maize silage instead of meadows and other crops, and in livestock production. This may cause negative environmental effects. On the other hand both, the intensification and the biogas production have positive effects on the labour market as biogas farms have an additional workforce demand