FAIR degree assessment in agriculture datasets using the F-UJI tool

For the agricultural scientific community, data sharing is crucial both for the advancement of the discipline and ability to meet global challenges, such as the target no. 2, i.e., “Zero Hunger,” of the Sustainable Development Goals (SDG 2030). In this context, FAIR (Findable, Accessible, Interoperable and Reusable) principles play an important role, as they guarantee the findability, accessibility, interoperability, and reusability of shared data. To improve the practice of data sharing, institutions, funders, and publishers are increasingly demanding data be shared as well as be of an acceptable level of quality, including compliance with FAIR principles. Therefore, the objective of this work is twofold: first, this research aims to determine the degree of compliance with the FAIR principles exhibited by a number of datasets; and second, it aims to explore useful and valid methodologies and procedures that can be used to perform this evaluation quickly, automatically, and effectively. For this purpose, the Data Citation Index (DCI) was used to obtain many datasets in the field of agriculture, which were further grouped by repositories and evaluated using the automated assessment tool F-UJI provided by the FAIRsFAIR project. The results indicated that the principle that exhibited the highest scores was “Findable”, while “Reusable” received the lowest scores, as none of the analysed repositories achieved a 50% compliance score in this respect. The datasets published in the Zenodo and Dryad repositories exhibited better overall results in terms of the FAIR principles, and the AG Commons repository was the third best rated repository, representing only one of the first three repositories belonging to the agricultural sector. Regarding the use of F-UJI as an automated assessment tool and DCI as a source for obtaining datasets, we conclude that this methodology is useful, and that although it can be improved, it is easy to use and implement by other scientific groups and agents of interest.     

Ten simple rules for making a vocabulary FAIR

We present ten simple rules that support converting a legacy vocabulary—a list of terms available in a print-based glossary or in a table not accessible using web standards—into a FAIR vocabulary. Various pathways may be followed to publish the FAIR vocabulary, but we emphasise particularly the goal of providing a globally unique resolvable identifier for each term or concept. A standard representation of the concept should be returned when the individual web identifier is resolved, using SKOS or OWL serialised in an RDF-based representation for machine-interchange and in a web-page for human consumption. Guidelines for vocabulary and term metadata are provided, as well as development and maintenance considerations. The rules are arranged as a stepwise recipe for creating a FAIR vocabulary based on the legacy vocabulary. By following these rules you can achieve the outcome of converting a legacy vocabulary into a standalone FAIR vocabulary, which can be used for unambiguous data annotation. In turn, this increases data interoperability and enables data integration.     

Is DIA proteomics data FAIR? Current data sharing practices,available bioinformatics infrastructure and recommendations for the future

Data independent acquisition (DIA) proteomics techniques have matured enormously in recent years, thanks to multiple technical developments in, for example, instrumentation and data analysis approaches. However, there are many improvements that are still possible for DIA data in the area of the FAIR (Findability, Accessibility, Interoperability and Reusability) data principles. These include more tailored data sharing practices and open data standards since public databases and data standards for proteomics were mostly designed with DDA data in mind. Here we first describe the current state of the art in the context of FAIR data for proteomics in general, and for DIA approaches in particular. For improving the current situation for DIA data, we make the following recommendations for the future: (i) development of an open data standard for spectral libraries; (ii) make mandatory the availability of the spectral libraries used in DIA experiments in ProteomeXchange resources; (iii) improve the support for DIA data in the data standards developed by the Proteomics Standards Initiative; and (iv) improve the support for DIA datasets in ProteomeXchange resources, including more tailored metadata requirements.     

How FAIR are plant sciences in the twenty-first century? The pressing need for reproducibility in plant ecology and evolution

The need for open, reproducible science is of growing concern in the twenty-first century, with multiple initiatives like the widely supported FAIR principles advocating for data to be Findable, Accessible, Interoperable and Reusable. Plant ecological and evolutionary studies are not exempt from the need to ensure that the data upon which their findings are based are accessible and allow for replication in accordance with the FAIR principles. However, it is common that the collection and curation of herbarium specimens, a foundational aspect of studies involving plants, is neglected by authors. Without publicly available specimens, huge numbers of studies that rely on the field identification of plants are fundamentally not reproducible. We argue that the collection and public availability of herbarium specimens is not only good botanical practice but is also fundamental in ensuring that plant ecological and evolutionary studies are replicable, and thus scientifically sound. Data repositories that adhere to the FAIR principles must make sure that the original data are traceable to and re-examinable at their empirical source. In order to secure replicability, and adherence to the FAIR principles, substantial changes need to be brought about to restore the practice of collecting and curating specimens, to educate students of their importance, and to properly fund the herbaria which house them.     

Highlights from this issue

Autophagy or Type II Programmed Cell Death (PCD) is a major intracellular pathway for the degradation and recycling of proteins, ribosomes and entire organelles. The role of this pathway in the anti-tumor effect of radiotherapy and in radiation toxicity is obscure. A complicated machinery of genes and proteins is involved in the regulation of autophagy as a response to a variety of stress factors including hypoxia, nutrient deprivation, cytotoxic agents and radiotherapy. Continuously accumulating data suggest that autophagic response of cancer cells to radiotherapy is a major pathway which, in contrast to apoptosis that leads to death, may lead to either death or cellular survival. A variety of agents have been recognized that induce or block autophagy, directly interfering with the cytotoxic effect of radiotherapy. Simultaneous targeting of autophagy and apoptosis during radiotherapy seems to further augment the anti-tumor effect. Radiobiology research should focus on the differential effect of fractionation on the induction of autophagy in different tumors and on the manipulation of this with autophagy triggering agents. Whether manipulation of this pathway in normal tissues may be used to confer cytoportection deserves also thorough investigation. Moreover, the role of pretreatment autophagic indices in tumor cells in predicting radiotherapy and chemotherapy outcome should be examined in translational studies.     

Prostate cancer radiation therapy: A physician’s perspective

Prostate cancer is the second most common cancer in men and a major cause of cancer deaths worldwide. Ionizing radiation has played a substantial role in the curative treatment of this disease. The historical evolution of radiotherapy techniques through 3D-conformal radiotherapy (3D-CRT), intensity-modulated radiotherapy (IMRT), and image-guided radiotherapy (IGRT) has allowed more accurate and precise treatments toward significant improvements in the therapeutic ratio. The addition of androgen deprivation therapy has significantly improved overall survival becoming the standard therapy for intermediate- and high-risk disease. Many randomized controlled trials have shown improved local control with dose escalation, and hypofractionated RT has been consolidated with proven efficacy and safe clinical results. However, several questions remain open in the radiotherapeutic management of prostate cancer patients and hopefully ongoing studies will shed light on these uncertainties. More individualized approaches are essential through better prognostic and novel predictive biomarkers of prostate radiotherapy response. Clinicians should critically interpret the evolving technologies in prostate cancer radiotherapy with important optimism but balancing the costs and the actual magnitude of clinical benefit. This article provides an overview of the basic aspects of radiotherapy treatment in localized prostate cancer from a physician’s perspective.     

Technical note: GAMMORA,a free,open-source,and validated GATE-based model for Monte-Carlo simulations of the Varian TrueBeam

PurposeMonte Carlo (MC) is the reference computation method for medical physics. In radiotherapy, MC computations are necessary for some issues (such as assessing figures of merit, double checks, and dose conversions). A tool based on GATE is proposed to easily create full MC simulations of the Varian TrueBeam STx.MethodsGAMMORA is a package that contains photon phase spaces as a pre-trained generative adversarial network (GAN) and the TrueBeam’s full geometry. It allows users to easily create MC simulations for simple or complex radiotherapy plans such as VMAT. To validate the model, the characteristics of generated photons are first compared to those provided by Varian (IAEA format). Simulated data are also compared to measurements in water and heterogeneous media. Simulations of 8 SBRT plans are compared to measurements (in a phantom). Two examples of applications (a second check and interplay effect assessment) are presented.ResultsThe simulated photons generated by the GAN have the same characteristics (energy, position, and direction) as the IAEA data. Computed dose distributions of simple cases (in water) and complex plans delivered in a phantom are compared to measurements, and the Gamma index (3%/3mm) was always superior to 98%. The feasibility of both clinical applications is shown.ConclusionsThis model is now shared as a free and open-source tool that generates radiotherapy MC simulations. It has been validated and used for five years. Several applications can be envisaged for research and clinical purposes.     

AutoFAIR-A portal for automating FAIR assessments for bioinformatics resources

BackgroundResearch in Bioinformatics generates tools and datasets in Bioinformatics at a very fast rate. Meanwhile, a lot of effort is going into making these resources findable and reusable to improve resource discovery by researchers in the course of their work.PurposeThis paper proposes a semi-automated tool to assess a resource according to the Findability, Accessibility, Interoperability and Reusability (FAIR) criteria. The aim is to create a portal that presents the assessment score together with a report that researchers can use to gauge a resource.MethodOur system uses internet searches to automate the process of generating FAIR scores. The process is semi-automated in that if a particular property of the FAIR scores has not been captured by AutoFAIR, a user is able to amend and supply the information to complete the assessment.ResultsWe compare our results against FAIRshake that was used as the benchmark tool for comparing the assessments. The results show that AutoFAIR was able to match the FAIR criteria in FAIRshake with minimal intervention from the user.ConclusionsWe show that AutoFAIR can be a good repository for storing metadata about tools and datasets, together with comprehensive reports detailing the assessments of the resources. Moreover, AutoFAIR is also able to score workflows, giving an overall indication of the FAIRness of the resources used in a scientific study.     

Measuring output factors and beam profiles formed by multileaf collimators using Fricke gel dosimeter

The accuracy and precision are necessary factors in radiotherapy, especially for measurements involving output factors and beam profiles; in this case multileaf collimators (MLCs) and dosimeter systems are not employed to obtain an adequate absorbed dose. In this work, output factors and beam profiles using multileaf collimators were obtained through the Fricke Xylenol Gel (FXG) dosimeter irradiated with 6 MV photon beams. From the results, FXG dosimetry demonstrated to be an adequate dosimetric tool for radiotherapy applications using MLC.     

The future of Radiation Oncology: Considerations of Young Medical Doctor

Radiation therapy plays an increasingly important role in the management of cancer. Currently, more than 50% of all cancer patients can expect to receive radiotherapy during the course of their disease, either in a primary management (radical or adjuvant radiotherapy) or for symptom control (palliative radiotherapy).Radiation oncology is a very unique branch of medicine connected with clinical knowledge and also with medical physics. In recent years, this approach has become increasingly absorbed with technological advances. This increasing emphasis on technology, together with other important changes in the health-care economic environment, now place the specialty of radiation oncology in a precarious position. New treatment technologies are evolving at a rate unprecedented in radiation therapy, paralleled by improvements in computer hardware and software. These techniques allow assessment of changes in the tumour volume and its location during the course of therapy (interfraction motion) so that re-planning can adjust for such changes in an adaptive radiotherapy process.If radiation oncologists become simply the guardians of a single therapeutic modality they may find that time marches by and, while the techniques will live on, the specialty may not. This article discusses these threats to the field and examines strategies by which we may evolve, diversify, and thrive.     

Medical physics in radiotherapy: The importance of preserving clinical responsibilities and expanding the profession's role in research,education, and quality control

Medical physicists have long had an integral role in radiotherapy. In recent decades, medical physicists have slowly but surely stepped back from direct clinical responsibilities in planning radiotherapy treatments while medical dosimetrists have assumed more responsibility. In this article, I argue against this gradual withdrawal from routine therapy planning. It is essential that physicists be involved, at least to some extent, in treatment planning and clinical dosimetry for each and every patient; otherwise, physicists can no longer be considered clinical specialists. More importantly, this withdrawal could negatively impact treatment quality and patient safety. Medical physicists must have a sound understanding of human anatomy and physiology in order to be competent partners to radiation oncologists. In addition, they must possess a thorough knowledge of the physics of radiation as it interacts with body tissues, and also understand the limitations of the algorithms used in radiotherapy. Medical physicists should also take the lead in evaluating emerging challenges in quality and safety of radiotherapy. In this sense, the input of physicists in clinical audits and risk assessment is crucial. The way forward is to proactively take the necessary steps to maintain and advance our important role in clinical medicine.     

Integration of evidence across human and model organism studies: A meeting report

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration—particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.     

Tissue TGF-β expression following conventional radiotherapy and pulsed low-dose-rate radiation

The release of inflammatory cytokines has been implicated in the toxicity of conventional radiotherapy (CRT). Transforming growth factor β (TGF-β) has been suggested to be a risk marker for pulmonary toxicity following radiotherapy. Pulsed low-dose rate radiotherapy (PLDR) is a technique that involves spreading out a conventional radiotherapy dose into short pulses of dose with breaks in between to reduce toxicities. We hypothesized that the more tolerable toxicity profile of PLDR compared with CRT may be related to differential expression of inflammatory cytokines such as TGF-β in normal tissues. To address this, we analyzed tissues from mice that had been subjected to lethal doses of CRT and PLDR by histology and immunohistochemistry (IHC). Equivalent physical doses of CRT triggered more cellular atrophy in the bone marrow, intestine, and pancreas when compared with PLDR as indicated by hematoxylin and eosin staining. IHC data indicates that TGF-β expression is increased in the bone marrow, intestine, and lungs of mice subjected to CRT as compared with tissues from mice subjected to PLDR. Our in vivo data suggest that differential expression of inflammatory cytokines such as TGF-β may play a role in the more favorable normal tissue late response following treatment with PLDR.     

Open data and algorithms for open science in AI-driven molecular informatics

Recent years have seen a sharp increase in the development of deep learning and artificial intelligence-based molecular informatics. There has been a growing interest in applying deep learning to several subfields, including the digital transformation of synthetic chemistry, extraction of chemical information from the scientific literature, and AI in natural product-based drug discovery. The application of AI to molecular informatics is still constrained by the fact that most of the data used for training and testing deep learning models are not available as FAIR and open data. As open science practices continue to grow in popularity, initiatives which support FAIR and open data as well as open-source software have emerged. It is becoming increasingly important for researchers in the field of molecular informatics to embrace open science and to submit data and software in open repositories. With the advent of open-source deep learning frameworks and cloud computing platforms, academic researchers are now able to deploy and test their own deep learning models with ease. With the development of new and faster hardware for deep learning and the increasing number of initiatives towards digital research data management infrastructures, as well as a culture promoting open data, open source, and open science, AI-driven molecular informatics will continue to grow. This review examines the current state of open data and open algorithms in molecular informatics, as well as ways in which they could be improved in future.     

Role of the autotaxin–lysophosphatidate axis in the development of resistance to cancer therapy

Autotaxin (ATX) is a secreted enzyme that hydrolyzes lysophosphatidylcholine to produce lysophosphatidate (LPA), which signals through six G-protein coupled receptors (GPCRs). Signaling through LPA is terminated by its degradation by a family of three lipid phosphate phosphatases (LPPs). LPP1 also attenuates signaling downstream of the activation of LPA receptors and some other GPCRs. The ATX-LPA axis mediates a plethora of activities such as cell proliferation, survival, migration, angiogenesis and inflammation, which perform an important role in facilitating wound healing. This wound healing response is hijacked by cancers where there is decreased expression of LPP1 and LPP3 and increased expression of ATX. This maladaptive regulation of LPA signaling also causes chronic inflammation, which has been recognized as one of the hallmarks in cancer. The increased LPA signaling promotes cell survival and migration and attenuates apoptosis, which stimulates tumor growth and metastasis. The wound healing functions of increased LPA signaling also protect cancer cells from effects of chemotherapy and radiotherapy. In this review, we will summarize knowledge of the ATX-LPA axis and its role in the development of resistance to chemotherapy and radiotherapy. We will also offer insights for developing strategies of targeting ATX-LPA axis as a novel part of cancer treatment. This article is part of a Special Issue entitled Lysophospholipids and their receptors: New data and new insights into their function edited by Susan Smyth, Viswanathan Natarajan and Colleen McMullen.     

Towards a unified data infrastructure to support European and global microbiome research: a call to action

High-quality microbiome research relies on the integrity, management and quality of supporting data. Currently biobanks and culture collections have different formats and approaches to data management. This necessitates a standard data format to underpin research, particularly in line with the FAIR data standards of findability, accessibility, interoperability and reusability. We address the importance of a unified, coordinated approach that ensures compatibility of data between that needed by biobanks and culture collections, but also to ensure linkage between bioinformatic databases and the wider research community.     

SBRT and extreme hypofractionation: A new era in prostate cancer treatments?

AimRadiation therapy (RT) is a standard therapeutic option for prostate cancer (PC). In the last decades, several innovative technology applications have been introduced. 3-Dimensional conformal RT, volumetric/rotational intensity modulated RT associated or not with image-guided RT, are becoming largely diffused in the treatment of PC.BackgroundConsidering that PC could have a low α/β ratio, similar to late-reacting normal tissues, it could also be highly responsive to fraction size. Thus, the reduction of the number of fractions and the increase of the dose/fraction seem to be reasonable choices in the treatment of this cancer. This review reported the technology evolution, the radiobiological and the clinical data about the role of extreme hypofractionated RT in the treatment approach of PC patients.Materials and methodsMedline search and analysis of published studies containing key words: prostate cancer, radiotherapy, stereotactic radiotherapy.ResultsRecent technological developments, combined with an improved knowledge of the radiobiological models in favor of a high sensitivity of PC to larger fraction sizes are opening a new scenario in its treatment, reporting favorable efficacy and acceptable toxicity, despite short follow-up.ConclusionThus, thanks to technological improvement and the recent radiobiological data, “extreme hypofractionated RT” has been strongly introduced in the last years as a potential solid treatment option for PC.     

Clinical applications of alanine/electron spin resonance dosimetry

This paper discusses the clinical applications of electron spin resonance (ESR) dosimetry focusing on the ESR/alanine system. A review of few past studies in this area is presented offering a critical overview of the challenges and opportunities for extending this system into clinical applications. Alanine/ESR dosimetry fulfills many of the required properties for several clinical applications such as water-equivalent composition, independence of the sensitivity for the energy range used in therapy and high precision. Improvements in sensitivity and the development of minidosimeters coupled with the use of a spectrometer of higher microwave frequency expanded the possibilities for clinical applications to the new modalities of radiotherapy (intensity-modulated radiation therapy and radiosurgery) and to the detection of low doses such as those present in some radiological image procedures.