Chapter 1 The multifaceted picture of transdisciplinarity in marine research

Chapter 1 = The Swiss psychologist Jean Piaget is considered responsible for coining the term transdisciplinarity’ in the 1970s, defining it as a higher stage after the interdisciplinary relations. To date, transdisciplinarity research is a growing field in academia, but still there is no uniform definition. In this book chapter, we explore how the term ‘transdisciplinarity’ is used in marine research including different fields like quantitative ecology and modeling, marine social science or marine conservation. We used a quantitative full-text analysis of peer-reviewed journal publications from 1992 to 2021, ensuring to include most recent contributions to the analysis. A total of over 6000 publications could be identified, about 500 of these focusing on marine realm. We applied an agglomerative hierarchical cluster analysis (program R) to consider relative frequencies of significant conceptual words within the transdisciplinary landscape. Multiple research clusters have been identified and further divided regarding the study background (e.g., meta-analysis, case study, theory)

Chapter 1 The multifaceted picture of transdisciplinarity in marine research

Chapter 1 = The Swiss psychologist Jean Piaget is considered responsible for coining the term transdisciplinarity’ in the 1970s, defining it as a higher stage after the interdisciplinary relations. To date, transdisciplinarity research is a growing field in academia, but still there is no uniform definition. In this book chapter, we explore how the term ‘transdisciplinarity’ is used in marine research including different fields like quantitative ecology and modeling, marine social science or marine conservation. We used a quantitative full-text analysis of peer-reviewed journal publications from 1992 to 2021, ensuring to include most recent contributions to the analysis. A total of over 6000 publications could be identified, about 500 of these focusing on marine realm. We applied an agglomerative hierarchical cluster analysis (program R) to consider relative frequencies of significant conceptual words within the transdisciplinary landscape. Multiple research clusters have been identified and further divided regarding the study background (e.g., meta-analysis, case study, theory)

A meta-analysis of the stony coral tissue loss disease microbiome finds key bacteria in unaffected and lesion tissue in diseased colonies

Stony coral tissue loss disease (SCTLD) has been causing significant whole colony mortality on reefs in Florida and the Caribbean. The cause of SCTLD remains unknown, with the limited concurrence of SCTLD-associated bacteria among studies. We conducted a meta-analysis of 16S ribosomal RNA gene datasets generated by 16 field and laboratory SCTLD studies to find consistent bacteria associated with SCTLD across disease zones (vulnerable, endemic, and epidemic), coral species, coral compartments (mucus, tissue, and skeleton), and colony health states (apparently healthy colony tissue (AH), and unaffected (DU) and lesion (DL) tissue from diseased colonies). We also evaluated bacteria in seawater and sediment, which may be sources of SCTLD transmission. Although AH colonies in endemic and epidemic zones harbor bacteria associated with SCTLD lesions, and aquaria and field samples had distinct microbial compositions, there were still clear differences in the microbial composition among AH, DU, and DL in the combined dataset. Alpha-diversity between AH and DL was not different; however, DU showed increased alpha-diversity compared to AH, indicating that, prior to lesion formation, corals may undergo a disturbance to the microbiome. This disturbance may be driven by Flavobacteriales, which were especially enriched in DU. In DL, Rhodobacterales and Peptostreptococcales–Tissierellales were prominent in structuring microbial interactions. We also predict an enrichment of an alpha-toxin in DL samples which is typically found in Clostridia. We provide a consensus of SCTLD-associated bacteria prior to and during lesion formation and identify how these taxa vary across studies, coral species, coral compartments, seawater, and sediment

Functional neuroanatomy underlying the clinical subcategorization of minimally conscious state patients

peer reviewedPatients in a minimally conscious state (MCS) show restricted signs of awareness but are unable to communicate. We assessed cerebral glucose metabolism in MCS patients and tested the hypothesis that this entity can be subcategorized into MCS- (i.e., patients only showing nonreflex behavior such as visual pursuit, localization of noxious stimulation and/or contingent behavior) and MCS+ (i.e., patients showing command following).Patterns of cerebral glucose metabolism were studied using [(18)F]-fluorodeoxyglucose-PET in 39 healthy volunteers (aged 46 +/- 18 years) and 27 MCS patients of whom 13 were MCS- (aged 49 +/- 19 years; 4 traumatic; 21 +/- 23 months post injury) and 14 MCS+ (aged 43 +/- 19 years; 5 traumatic; 19 +/- 26 months post injury). Results were thresholded for significance at false discovery rate corrected p < 0.05.We observed a metabolic impairment in a bilateral subcortical (thalamus and caudate) and cortical (fronto-temporo-parietal) network in nontraumatic and traumatic MCS patients. Compared to MCS-, patients in MCS+ showed higher cerebral metabolism in left-sided cortical areas encompassing the language network, premotor, presupplementary motor, and sensorimotor cortices. A functional connectivity study showed that Broca's region was disconnected from the rest of the language network, mesiofrontal and cerebellar areas in MCS- as compared to MCS+ patients.The proposed subcategorization of MCS based on the presence or absence of command following showed a different functional neuroanatomy. MCS- is characterized by preserved right hemispheric cortical metabolism interpreted as evidence of residual sensory consciousness. MCS+ patients showed preserved metabolism and functional connectivity in language networks arguably reflecting some additional higher order or extended consciousness albeit devoid of clinical verbal or nonverbal expression

Is there anybody in there? Detecting awareness in disorders of consciousness.

The bedside detection of awareness in disorders of consciousness (DOC) caused by acquired brain injury is not an easy task. For this reason, differential diagnosis using neuroimaging and electrophysiological tools in search for objective markers of consciousness is being employed. However, such tools cannot be considered as diagnostic per se, but as assistants to the clinical evaluation, which, at present, remains the gold standard. Regarding therapeutic management in DOC, no evidence-based recommendations can be made in favor of a specific treatment. The present review summarizes clinical and paraclinical studies that have been conducted with neuroimaging and electrophysiological techniques in search of residual awareness in DOC. We discuss the medical, scientific and ethical implications that derive from these studies and we argue that, in the future, the role of neuroimaging and electrophysiology will be important not only for the diagnosis and prognosis of DOC but also in establishing communication with these challenging patients