Therapeutic collaboration and resistance: describing the nature and quality of the therapeutic relationship within ambivalence events using the therapeutic collaboration coding system

We understand ambivalence as a cyclical movement between two opposing parts of the self. The emergence of a novel part produces an innovative moment, challenging the current maladaptive self-narrative. However, the novel part is subsequently attenuated by a return to the maladaptive self-narrative. This study focused on the analysis of the therapeutic collaboration in episodes in which a relatively poor-outcome client in narrative therapy expressed ambivalence. Method: For our analysis we used the Therapeutic Collaboration Coding System, developed to assess whether and how the therapeutic dyad is working within the therapeutic zone of proximal development (TZPD). Results: Results showed that when the therapist challenged the client after the emergence of ambivalence, the client tended to invalidate (reject or ignore) the therapist’s intervention. Conclusions: This suggests that in such ambivalence episodes the therapist did not match the client’s developmental level, and by working outside the TZPD unintentionally contributed to the maintaining the client’s ambivalence

Hydrolysis of α-lactalbumin by cardosin A immobilized on highly activated supports

In the present research effort, production of derivatives of cardosin A (a plant protease) encompassing full stabilization of its dimeric structure has been achieved, via covalent, multi-subunit immobilization onto highly activated agarose-glutaraldehyde supports. Boiling such enzyme derivatives in the presence of sodium dodecyl sulfate and β-mercaptoethanol did not lead to leaching of enzyme, thus providing evidence for the effectiveness of the attachment procedure. Furthermore, the cardosin A derivatives prepared under optimal conditions presented ca. half the specific activity of the enzyme in soluble form, and were successfully employed at laboratory-scale trials to perform (selective) hydrolysis of α-lactalbumin (α-La), one of the major proteins in bovine whey. Hydrolysates of α-La were assayed for by the OPA method, as well as by FPLC, SDS–PAGE and HPLC. Thermal inactivation of the immobilized cardosin A was also assessed at 40, 50 and 55 °C; at these temperatures, no thermal denaturation took place during incubation for 48 h. The highest degree of hydrolysis was attained by 5 h reaction, at 55 °C and pH 5.2. SDS–PAGE of α-La hydrolysates displayed bands corresponding to low molecular weight peptides. Our results suggest that cardosin A in immobilized form is a good candidate to bring about proteolysis in the dairy industry, namely in whey processing

Glutaminolysis and Fumarate Accumulation Integrate Immunometabolic and Epigenetic Programs in Trained Immunity

Induction of trained immunity (innate immune memory) is mediated by activation of immune and metabolic pathways that result in epigenetic rewiring of cellular functional programs. Through network-level integration of transcriptomics and metabolomics data, we identify glycolysis, glutaminolysis, and the cholesterol synthesis pathway as indispensable for the induction of trained immunity by β-glucan in monocytes. Accumulation of fumarate, due to glutamine replenishment of the TCA cycle, integrates immune and metabolic circuits to induce monocyte epigenetic reprogramming by inhibiting KDM5 histone demethylases. Furthermore, fumarate itself induced an epigenetic program similar to β-glucan-induced trained immunity. In line with this, inhibition of glutaminolysis and cholesterol synthesis in mice reduced the induction of trained immunity by β-glucan. Identification of the metabolic pathways leading to induction of trained immunity contributes to our understanding of innate immune memory and opens new therapeutic avenues

A comprehensive assessment of the transcriptome of cork oak (Quercus suber) through EST sequencing

Background: Cork oak (Quercus suber) is one of the rare trees with the ability to produce cork, a material widely used to make wine bottle stoppers, flooring and insulation materials, among many other uses. The molecular mechanisms of cork formation are still poorly understood, in great part due to the difficulty in studying a species with a long life-cycle and for which there is scarce molecular/genomic information. Cork oak forests are of great ecological importance and represent a major economic and social resource in Southern Europe and Northern Africa. However, global warming is threatening the cork oak forests by imposing thermal, hydric and many types of novel biotic stresses. Despite the economic and social value of the Q. suber species, few genomic resources have been developed, useful for biotechnological applications and improved forest management. Results: We generated in excess of 7 million sequence reads, by pyrosequencing 21 normalized cDNA libraries derived from multiple Q. suber tissues and organs, developmental stages and physiological conditions. We deployed a stringent sequence processing and assembly pipeline that resulted in the identification of ~159,000 unigenes. These were annotated according to their similarity to known plant genes, to known Interpro domains, GO classes and E.C. numbers. The phylogenetic extent of this ESTs set was investigated, and we found that cork oak revealed a significant new gene space that is not covered by other model species or EST sequencing projects. The raw data, as well as the full annotated assembly, are now available to the community in a dedicated web portal at http://www.corkoakdb.org. Conclusions: This genomic resource represents the first trancriptome study in a cork producing species. It can be explored to develop new tools and approaches to understand stress responses and developmental processes in forest trees, as well as the molecular cascades underlying cork differentiation and disease response.Peer Reviewe

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio