In 2015, the UN adopted the Sustainable Development Goals (SDGs), addressing social, environmental, and economic targets. Global partnerships, transnational, and interdisciplinary research are ...essential for achieving progress towards the SDGs. This study analyzes 4593 research articles at the meta-level, explicitly referring to the SDGs. This a comparably small amount of research items directly addressing the goals. However, comparisons with existing approaches using different queries are possible. Research that links to the SDGs through its title, keywords, or abstract facilitates knowledge sharing on the goals as it is easier to identify relevant work. Using scientometric means, we assessed the corresponding sources, research areas, affiliated countries, thematic foci, and the availability of funding acknowledgments. The results are useful for identifying research gaps and potential collaboration possibilities. The outcomes suggest that most research referring to the SDGs comes from the research areas Life Sciences & Biomedicine and Social Sciences. The most predominant SDG among the analyzed research articles is SDG 3 (“good health and well-being”). A relatively high share of open access articles contributes to the idea of knowledge sharing for the SDGs. Nearly 37% of all articles count as international publications, i.e., as being co-authored by authors from affiliations of multiple countries.
Background
Radiation-associated angiosarcoma (RAAS) of the breast is an aggressive malignancy affecting 1 in 1000 breast cancer patients. This study aimed to determine differences in treatments and ...outcomes for RAAS initially managed through a sarcoma multi-disciplinary team (SMDT) compared with an outside center (OC) and to describe outcomes after recurrence.
Methods
Patients with a diagnosis of breast RAAS between 2004 and 2019 were identified from our sarcoma database. Clinicopathologic characteristics, recurrence patterns, and factors predictive of survival were assessed. Differences in local recurrence-free survival (LRFS) and disease-specific survival (DSS) were estimated using Kaplan-Meier and compared using the log-rank test.
Results
Surgery was performed for 49 women with RAAS, who had a median age of 74 years (range 41–89 years). Primary management was performed by SMDT for 26 patients and by OC for 23 patients. Radical mastectomy and reconstruction were performed for 96% of the SMDT group versus 17% of the OC group (
p
= 0.00001). The proportion patients who received chemotherapy, radiation, or both was 42.3% in the SMDT group and 0% in the OC group. During a median follow-up period of 26 months, recurrence was experienced by 38% (10/26) of the SMDT cohort and 83% (19/23) of the OC cohort (
p
= 0.002). The 3-year LRFS was better in the SMDT cohort (59.3% vs 31.8%;
p
= 0.019). Of the 29 recurrences 16 received chemotherapy and 6 received radiation, surgery, or both. At the last follow-up visit, 20 patients were in first remission, 1 patient was in second remission, 8 patients were alive with disease, and 20 patients had died of disease.
Conclusion
Initial treatment by SMDT was associated with more extensive surgery, multimodal treatments, and a better 3-year LRFS. Patients with breast RAAS likely benefit from early referral and treatment by an SMDT.
Large uncertainties still dominate the hypothesis of an abrupt large-scale shift of the Amazon forest caused by climate change Amazonian forest dieback (AFD) even though observational evidence shows ...the forest and regional climate changing. Here, we assess whether mitigation or adaptation action should be taken now, later, or not at all in light of such uncertainties. No action/later action would result in major social impacts that may influence migration to large Amazonian cities through a causal chain of climate change and forest degradation leading to lower river-water levels that affect transportation, food security, and health. Net-present value socioeconomic damage over a 30-year period after AFD is estimated between US dollar (USD) $957 billion (×10⁹) and $3,589 billion (compared with Gross Brazilian Amazon Product of USD $150 billion per year), arising primarily from changes in the provision of ecosystem services. Costs of acting now would be one to two orders of magnitude lower than economic damages. However, while AFD mitigation alternatives—e.g., curbing deforestation—are attainable (USD $64 billion), their efficacy in achieving a forest resilience that prevents AFD is uncertain. Concurrently, a proposed set of 20 adaptation measures is also attainable (USD $122 billion) and could bring benefits even if AFD never occurs. An interdisciplinary research agenda to fill lingering knowledge gaps and constrain the risk of AFD should focus on developing sound experimental and modeling evidence regarding its likelihood, integrated with socioeconomic assessments to anticipate its impacts and evaluate the feasibility and efficacy of mitigation/adaptation options.
Among the diverse methodological approaches that are currently represented in the postmodern studies, the one, which dominates nowadays, is the statement that there cannot be any methodology in ...postmodernism per se otherwise it would be a “relapse” into constructing one more “universalizing method”. Evidently, this assertion is stipulated by the highly pluralized context of the postmodern “normalization of change”, the transformations of the socio- cultural order in accordance with the postparadigmatic shift of the theory. Postmodern researchers both implicitly and explicitly state that the only way to “manage” the increasing pluralism and diversity is unmasking prior modernist ideas and ideals in the individual and general meanings of the human experience. On the other hand, the postmodern methodological “openness” encourages academic ambivalence, which results in the denial of the universal notions and absolute moral values. With the apparent postmodernist accent on the interdisciplinary approaches, the “scientific conditions” have become even more complicated: nowadays philosophy, history, theology, gender studies, arts are being connected with biology, genetics, cybernetics, economics, etc. As one of the main components of the postmodern intertextual analysis the historical method is vividly represented both in the western feminist theory and in the eastern post-colonial criticism, poetics of fiction and cultural studies. All mentioned above, appearing in the pluralized modes, occasion the turn into considering interdisciplinary techniques more scrupulously. The objective of this research is to reconstruct conceptually the comparative-historical methodology in the theoretical field of the postmodern humanities with the focus on the specific character of the interpretation of history in the cultural texts. The main thesis of the research reflects the reconstruction of the historical methods as an important systematic and meaning-conscious component in postmodern theoretical studies. The research proves that nowadays historical approaches are significant and valid because they locate certain techniques into the contemporary scholarly work in order to properly utilize the sources and pieces of evidence in writing “history”. The value of the comparative-historical method is also based on the fact that it proposes some models and patterns in dealing with the analysis of the particular theory in interdisciplinary studies. The historical narrative with its objective to tell the “truth” cannot be reflected according to some simple schemes, without taking into account the “hardcore” role of the context in the hermeneutic reading of history. Though there is a view that historiography is located “between” modernity and postmodernity, the articulated point of view is that postmodernism, being a theoretical cluster of historical disruption and “brokenness”, in fact, cannot reject the tradition of historicism in the humanitarian studies.
The peer merit review of research proposals has been the major mechanism to decide grant awards. However, research proposals have become increasingly interdisciplinary. It has been a longstanding ...challenge to assign interdisciplinary proposals to appropriate reviewers so proposals are fairly evaluated. One of the critical steps in reviewer assignment is to generate accurate interdisciplinary topic labels for proposal-reviewer matching. Existing systems mainly collect topic labels manually generated by principle investigators. However, such human-reported labels can be non-accurate, incomplete, labor intensive, and time costly. What role can AI play in developing a fair and precise proposal reviewer assignment system? In this study, we collaborate with the National Science Foundation of China to address the task of automated interdisciplinary topic path detection. For this purpose, we develop a deep Hierarchical Interdisciplinary Research Proposal Classification Network (HIRPCN). Specifically, we first propose a hierarchical transformer to extract the textual semantic information of proposals. We then design an interdisciplinary graph and leverage GNNs to learn representations of each discipline in order to extract interdisciplinary knowledge. After extracting the semantic and interdisciplinary knowledge, we design a level-wise prediction component to fuse the two types of knowledge representations and detect interdisciplinary topic paths for each proposal. We conduct extensive experiments and expert evaluations on three real-world datasets to demonstrate the effectiveness of our proposed model.
The use of black box machine learning models whose decisions cannot be understood limits the acceptance of predictions in interdisciplinary research and camouflages artificial learning ...characteristics leading to predictions for other than anticipated reasons. Consequently, there is increasing interest in explainable artificial intelligence to rationalize predictions and uncover potential pitfalls. Among others, relevant approaches include feature attribution methods to identify molecular structures determining predictions and counterfactuals (CFs) or contrastive explanations. CFs are defined as variants of test instances with minimal modifications leading to opposing predictions. In medicinal chemistry, CFs have thus far only been little investigated although they are particularly intuitive from a chemical perspective. We introduce a new methodology for the systematic generation of CFs that is centered on well‐defined structural analogues of test compounds. The approach is transparent, computationally straightforward, and shown to provide a wealth of CFs for test sets. The method is made freely available.
A new computational methodology is introduced for the generation of counterfactuals to explain machine learning predictions in medicinal chemistry.
This study explores the characteristics of scientific activity patterns through co-author affiliations to obtain new insights into interdisciplinary research. To classify the interdisciplinarity in ...research, we explored and compared two different approaches: the diversity of disciplines reflected in the listed affiliations of the authors and the diversity of the subject categories reflected in the reference list. To assess the diversity in departmental affiliations, we developed an explorative methodology that retrieves feature words from a combination of manual work and the thesaurus function in the Thomson Data Analyzer text mining tool. To assess the diversity in references, we followed the conventional approach applied in previous work. With both approaches, we relied on diversity as the measure for assessing interdisciplinarity of 157,710 articles published in
PloS One
(2007–2016). Based on a comparison between the results of both approaches, our study confirms that different methodologies and indicators can produce seriously inconsistent, and even contradictory results. In addition, different indicators may capture different understandings of such a multi-faceted concept as interdisciplinarity. Our results are summarized in a schematic representation of this twofold perspective as a method of indexing the different types of interdisciplinarity commonly found in research studies.
Junior faculty face challenges in establishing independent research careers. Declining funding combined with a shift to multidisciplinary, collaborative science necessitates new mentorship models and ...enhanced institutional support.
Two multidisciplinary mentorship programs to promote grant success for junior faculty were established at the Duke University School of Medicine beginning in 2011. These four-month programs-the Path to Independence Program (PtIP) for National Institutes of Health (NIH) R applicants and the K Club for NIH K applicants-use multiple senior faculty mentors and professional grant-writing staff to provide a 20-hour joint curriculum comprising a series of lectures, hands-on workshops, career development counseling, peer groups, and an internal study section. In March 2016, the authors analyzed the success rate for all NIH grants submitted by participants since program enrollment. In a 2015 postprogram survey, participants rated their feelings of support and competency across six skill factors.
From October 2011 to March 2016, the programs engaged 265 senior faculty mentors, 145 PtIP participants, and 138 K Club participants. Success rates for NIH grant applications were 28% (61 awards/220 decisions) for PtIP participants-an increase over the 2010 Duke University junior faculty baseline of 11%-and 64% (38/59) for K Club participants. Respondents reported significantly increased feelings of support and self-ratings for each competency post program.
The authors plan to expand the breadth of both the mentorship pool and faculty served. Broad implementation of similar programs elsewhere could bolster success, satisfaction, and retention of junior faculty investigators.
Despite specialists' efforts to find the best solutions for cancer diagnosis and therapy, this pathology remains the biggest health threat in the world. Global statistics concerning deaths associated ...with cancer are alarming; therefore, it is necessary to intensify interdisciplinary research in order to identify efficient strategies for cancer diagnosis and therapy, by using new molecules with optimal therapeutic potential and minimal adverse effects. This review focuses on studies of porphyrin macrocycles with regard to their structural and spectral profiles relevant to their applicability in efficient cancer diagnosis and therapy. Furthermore, we present a critical overview of the main commercial formulations, followed by short descriptions of some strategies approached in the development of third-generation photosensitizers.
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