Scientific Questions Research Articles

Implementing a Biomedical Data Warehouse From Blueprint to Bedside in a Regional French University Hospital Setting: Unveiling Processes, Overcoming Challenges, and Extracting Clinical Insight.

Biomedical data warehouses (BDWs) have become an essential tool to facilitate the reuse of health data for both research and decisional applications. Beyond technical issues, the implementation of BDWs requires strong institutional data governance and operational knowledge of the European and national legal framework for the management of research data access and use. In this paper, we describe the compound process of implementation and the contents of a regional university hospital BDW. We present the actions and challenges regarding organizational changes, technical architecture, and shared governance that took place to develop the Nantes BDW. We describe the process to access clinical contents, give details about patient data protection, and use examples to illustrate merging clinical insights. More than 68 million textual documents and 543 million pieces of coded information concerning approximately 1.5 million patients admitted to CHUN between 2002 and 2022 can be queried and transformed to be made available to investigators. Since its creation in 2018, 269 projects have benefited from the Nantes BDW. Access to data is organized according to data use and regulatory requirements. Data use is entirely determined by the scientific question posed. It is the vector of legitimacy of data access for secondary use. Enabling access to a BDW is a game changer for research and all operational situations in need of data. Finally, data governance must prevail over technical issues in institution data strategy vis-à-vis care professionals and patients alike.

Seeking sand origins on Mars: Towards testing the volcaniclastic hypothesis globally

Aeolian processes are a dominant cause of Martian surface modification today. Sand is pervasive, even while the contemporary transport of sand at high-threshold wind speeds implies sand breakdown. Thus, detecting the origin(s) of sand on Mars is an important open question in Mars science. One long-standing hypothesis for an origin of Martian sand is as volcaniclastic sediments, either epiclastic (from the breakdown of effusive volcanic rock) or pyroclastic (from explosive sedimentation). Recent analyses identified the most likely pyroclastic unit on Mars, the Medusae Fossae Formation (MFF) – mapped as the Hesperian and Amazonian-Hesperian transitional units (Tanaka et al., 2014) – as an origin of Martian sand, a genesis consistent with inferences from other work. On these bases, we continued in this work to test for a volcaniclastic origin of Martian sand elsewhere on Mars. We inspected the seven units from the global geologic map of Mars interpreted as possibly/partially volcaniclastic and six geographic terrains ascribed as likely volcanogenic in a more recent analysis. Of these units and geographic terrains, potential sand sources (PSSs) were detected only within two locales: 1) the remaining (central and eastern) extent of the MFF, and 2) Arabia Terra. Arabia Terra shows more numerous PSS, commonly characterized as having proximal dune fields. The explosive volcanic history of the region points towards a pyroclastic origin, though the geologic complexity of the region suggests complexity in the provenance of Arabia Terra PSSs. In contrast to PSS identifications in the western MFF, PSSs in the central and eastern MFF were clustered along the contact of the MFF with lava plains, indicating a potential epiclastic sand origin. Thus, these results indicate both pyroclastic and potentially epiclastic origins for sand on Mars. However, these sand origins as detected by this work are confined to limited locales and (for the MFF) in the amount of sand generated. To further evaluate the amount of sand production in these two study regions from volcanogenic processes, spectroscopic analysis of PSSs in comparison with sand deposits would be a means to test first whether the PSSs were indeed generating sand and secondly if that sand were of volcanic origin. Potential sand flux modeling would be a means to establish the source location(s) of the sand. The origin(s) of the pervasive sand on Mars remain(s) to be better understood, for which the work presented here provides a foundation.

Understanding how cells and organisms keep time during development

A classical question in biology is how different processes are controlled in space and time, with research pointing to different mechanisms as timers. In this collection of Voices, we asked researchers to define their scientific questions related to time-keeping and the approaches they use to answer them.

Asking a question.

While scientific research should be carried out objectively, the choices of questions asked and approaches taken are deeply personal and subjective. I urge individuals to pursue questions they love and to periodically scrutinize the reasons (the philosophies) that drive that love. As a case study, I scrutinize the "whys" behind some of the scientific questions I pursued during my career.

The primacy of experience in language processing: Semantic priming is driven primarily by experiential similarity

The organization of semantic memory, including memory for word meanings, has long been a central question in cognitive science. Although there is general agreement that word meaning representations must make contact with sensory-motor and affective experiences in a non-arbitrary fashion, the nature of this relationship remains controversial. One prominent view proposes that word meanings are represented directly in terms of their experiential content (i.e., sensory-motor and affective representations). Opponents of this view argue that the representation of word meanings reflects primarily taxonomic structure, that is, their relationships to natural categories. In addition, the recent success of language models based on word co-occurrence (i.e., distributional) information in emulating human linguistic behavior has led to proposals that this kind of information may play an important role in the representation of lexical concepts. We used a semantic priming paradigm designed for representational similarity analysis (RSA) to quantitatively assess how well each of these theories explains the representational similarity pattern for a large set of words. Crucially, we used partial correlation RSA to account for intercorrelations between model predictions, which allowed us to assess, for the first time, the unique effect of each model. Semantic priming was driven primarily by experiential similarity between prime and target, with no evidence of an independent effect of distributional or taxonomic similarity. Furthermore, only the experiential models accounted for unique variance in priming after partialling out explicit similarity ratings. These results support experiential accounts of semantic representation and indicate that, despite their good performance at some linguistic tasks, the distributional models evaluated here do not encode the same kind of information used by the human semantic system.

Disagreement and Progress in Philosophy and in Empirical Sciences

ABSTRACT The fact that philosophy has not made much progress in finding answers to its big questions is often demonstrated with a comparison to natural sciences. Some have recently argued that the state of progress in philosophy is not so different than the sciences: there are many unresolved big questions in the sciences too, and philosophy has made progress on its smaller questions just like the sciences. I argue that this comparison is misleading: the situation in the two fields looks similar only if we focus on unresolved scientific questions that have philosophical import. The sciences have made progress on many questions that are significant but that are not ‘big’ in a philosophical sense, while philosophy has made less progress on its own significant questions. Moreover, ‘smaller’ questions in the sciences are significant in themselves, while smaller questions in philosophy do not have much significance beyond their contribution to the bigger debates. I conclude with brief remarks about what underlies the disparity between the two fields: to understand the slow pace of progress in philosophy we should pay attention to factors that are at the intersection of the nature of philosophical questions, current philosophical methodology and the sociology of academic philosophy.

Salinity affects microbial function genes related to nutrient cycling in arid regions.

Salinization damages soil system health and influences microbial communities structure and function. The response of microbial functions involved in the nutrient cycle to soil salinization is a valuable scientific question. However, our knowledge of the microbial metabolism functions in salinized soil and their response to salinity in arid desert environments is inadequate. Here, we applied metagenomics technology to investigate the response of microbial carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) cycling and the key genes to salinity, and discuss the effects of edaphic variables on microbial functions. We found that carbon fixation dominated the carbon cycle. Nitrogen fixation, denitrification, assimilatory nitrate reduction (ANRA), and nitrogen degradation were commonly identified as the most abundant processes in the nitrogen cycle. Organic phosphorus dissolution and phosphorus absorption/transport were the most enriched P metabolic functions, while sulfur metabolism was dominated by assimilatory sulfate reduction (ASR), organic sulfur transformation, and linkages between inorganic and organic sulfur transformation. Increasing salinity inhibited carbon degradation, nitrogen fixation, nitrogen degradation, anammox, ANRA, phosphorus absorption and transport, and the majority of processes in sulfur metabolism. However, some of the metabolic pathway and key genes showed a positive response to salinization, such as carbon fixation (facA, pccA, korAB), denitrification (narG, nirK, norBC, nosZ), ANRA (nasA, nirA), and organic phosphorus dissolution processes (pstABCS, phnCD, ugpAB). High salinity reduced the network complexity in the soil communities. Even so, the saline microbial community presented highly cooperative interactions. The soil water content had significantly correlations with C metabolic genes. The SOC, N, and P contents were significantly correlated with C, N, P, and S network complexity and functional genes. AP, NH4+, and NO3- directly promote carbon fixation, denitrification, nitrogen degradation, organic P solubilization and mineralization, P uptake and transport, ASR, and organic sulfur transformation processes. Soil salinity in arid region inhibited multiple metabolic functions, but prompted the function of carbon fixation, denitrification, ANRA, and organic phosphorus dissolution. Soil salinity was the most important factor driving microbial functions, and nutrient availability also played important roles in regulating nutrient cycling.

Population differences in dental cementum growth rates: Implications for using cementum thickness as a method for age estimation.

Age at death estimation is a key element to many research questions in biological anthropology, archeology, and forensic science. Dental cementum is a tissue of choice for the estimation of age at death in adult individuals as it continues deposition for the entirety of an individual's life. Previous works have devised regression formulas correlating cementum thickness to age at death. However, interpopulation variances are unknown, and it is therefore not clear whether regressions based on a single population are applicable to individuals with different ancestries. Here, we use a sample (n = 52) of teeth from individuals with known age at tooth extraction/death of European, African, and East Asian ancestry to assess whether there are interpopulations differences in cementum growth rate. We measured growth rate in four different areas (2nd and 5th decile of both the lingual and buccal aspect of the root) of each tooth and used nonparametric tests to evaluate population differences in growth rate between homologous regions of the teeth. The results of the analyses show that, even after controlling for tooth size, individuals of European ancestry have significantly lower growth rates than those of both African and East Asian ancestry across all four tooth areas. These results call into question the applicability of the regression formulas derived from European ancestry individuals to individuals of other ancestries.

Transformer enables ion transport behavior evolution and conductivity regulation for solid electrolyte

Ab initio molecular dynamics (AIMD) is an important technique for studying ion transport within solid electrolyte and interface effects between electrode and electrolyte, which is particularly critical for the rational design of new energy materials. However, AIMD is limited by the high-cost density functional theory (DFT) solution process and is unable to reach the time scale of the entire dynamic simulation, resulting in time-consuming AIMD calculations and a considerable scarcity of AIMD-based conductor data. Here, we propose a sequence relational large model based on transformer (T-AIMD) to infer ion diffusion from mean square displacement sequence data and hybrid multi-source material descriptor. T-AIMD successfully learns the whole long-range atomic diffusion to predict the ionic conductivity (σ) of any ion in any crystal structure to find fast-ion conductors, thus reducing the cost of AIMD simulation by a factor of 100. Using T-AIMD, we built the largest database of mixed ion conductors, and the σ of representative solid electrolytes has been successfully validated in previous battery experiments. Further, the manufactured solid-state battery with the predicted promising electrolyte exhibits almost no obvious capacity decay after 50 cycles with a high initial specific capacity of 1270 mAh g−1, which is promising to help devices work in extreme environments while guaranteeing battery life. By speeding up the prediction time of AIMD, the proposed T-AIMD opens the door for scientists to explore the atomic and molecular behaviors of other molecules/materials on long time scales, and will ultimately benefit the exploration of other key scientific questions in the energy field.

Docimological Quality Analysis of LLM-Generated Multiple Choice Questions in Computer Science and Medicine

Assessment is an essential part of education, both for teachers who assess their students as well as learners who may evaluate themselves. Multiple-choice questions (MCQ) are one of the most popular types of knowledge assessment, e.g., in medical education, as they can be automatically graded and can cover a wide range of learning items. However, the creation of high-quality MCQ items is a time-consuming task. The recent advent of Large Language Models (LLM), such as Generative Pre-trained Transformer (GPT), caused a new momentum for automatic question generation solutions. Still, evaluating generated questions according to the best practices for MCQ item writing is needed to ensure docimological quality. In this article, we propose an analysis of the quality of LLM-generated MCQs. We employ zero-shot approaches in two domains, namely computer science and medicine. In the former, we make use of 3 GPT-based services to generate MCQs. In the latter, we developed a plugin for the Moodle learning management system that generates MCQs based on learning material. We compare the generated MCQs against common multiple-choice item writing guidelines. Among the major challenges, we determined that while LLMs are certainly useful in generating MCQs more efficiently, they sometimes create broad items with ambiguous keys or implausible distractors. Human oversight is also necessary to ensure instructional alignment between generated items and course contents. Finally, we propose solutions for AQG developers.

Assessing the impact of climate change on landslides near Vejle, Denmark, using public data

Abstract. The possibility of increased landslide activity as a result of climate change has often been suggested, but few studies quantify this connection. Here, we present and utilize a workflow for the first time solely using publicly available data to assess the impact of future changes in landslide dynamic conditioning factors on landslide movement. In our case we apply the workflow to three slow-moving coastal landslides near Vejle, presenting the first study of its kind on Danish landslides. We examine modelled water table depth (WTD) as a dynamic conditioning factor using the DK-HIP model (Danish Hydrological Information and Prognosis system) that simulates historic and future WTD. The data show a clear correlation with landslide movement as recorded by the interferometric synthetic aperture radar (InSAR) time series for the period from 2015 to 2019. Movement of up to 84 mm yr−1 occurs during wet winter months when normalized WTD exceeds +0.5 m. During dry winters, no, or very little, seasonal landslide movement is observed. The DK-HIP model predicts an increase of up to 0.7 m in WTD at the study area by 2100 CE under the RCP8.5 (Representative Concentration Pathway) scenario (95 % confidence), which exceeds the levels this area has experienced in recent decades (mean increase of 0.2 m with a standard deviation of 0.25 m). This is likely to result in increased landslide activity and acceleration of movement. In a previous episode of increased landslide activity linked to extreme precipitation in the early 1980s, one of the examined landslides accelerated, causing damage to infrastructure and buildings. Our study clearly shows that these landslides are sensitive to climate change and highlights the potential of utilizing high-quality, publicly available data to address these complex scientific questions. The quality and quantity of such data are ever increasing, and so is the potential of this kind of approach.

Parent attitudes towards data sharing in developmental science.

Data sharing in developmental science is increasingly encouraged, supported by funder and publisher mandates for open data access. Data sharing can accelerate discovery, link researchers with high quality analytic expertise to researchers with large datasets and democratise the research landscape to enable researchers with limited funding to access large sample sizes. However, there are also significant privacy and security concerns, in addition to conceptual and ethical considerations. These are particularly acute for developmental science, where child participants cannot consent themselves. As we move forward into a new era of data openness, it is essential that we adequately represent the views of stakeholder communities in designing data sharing efforts. We conducted a comprehensive survey of the opinions of 195 parents on data sharing in developmental science. Survey themes included how widely parents are willing to share their child's data, which type of organisations they would share the data with and the type of consent they would be comfortable providing. Results showed that parents were generally supportive of curated, but not open, data sharing. In addition to individual privacy and security concerns, more altruistic considerations around the purpose of research were important. Parents overwhelmingly supported nuanced consenting models in which preferences for particular types of data sharing could be changed over time. This model is different to that implemented in the vast majority of developmental science research and is contrary to many funder or publisher mandates. The field should look to create shared repositories that implement features such as dynamic consent and mechanisms for curated sharing that allow consideration of the scientific questions addressed. Better communication and outreach are required to build trust in data sharing, and advanced analytic methods will be required to understand the impact of selective sharing on reproducibility and representativeness of research datasets.

پرسە نێودەوڵەتییەکان لە ڕوانگەی تیۆری ڕیاڵیزمەوە: پرسی ژینگە وەک نموونە

Different directions of realism theory, as the most prominent theory for studying issues and international relations, are close in several hypotheses and general lines, but when coming to details, they are different. This study examines international questions and environmental issues in particular in terms of these theoretical directions. In general, realistic theories agree on the hypothesis that international issues can be classified into high politics and low politics. But because in today’s world, the dangers and consequences of environmental pollution on international and world security have considerably increased, for this study, main question is that is environment in the perspectives of different directions of realism theory still a minor issue or has its role and position to become a key issue risen, or is it possible to rise? By relying on reliable sources and using each of deductive method, qualitative method and case studies, efforts have been made to investigate and address this scientific question. In order to achieve the goals and giving attention to the cause and the major problem, the study is divided into two main sections, each section includes accurate enquiries. Finally, the study positively proves its hypothesis, which in the perspective of realism theories, issues related to national interest and security are placed at the top of high issues pyramid, while environmental issues are given less importance by the state and international actors. However, at the same time, some differences in the understanding of realism theories are noticed, particularly in defensive realism, which claims that environment should be dealt with as an important subject in some places and stages of time, yet the offensive realism is the most pessimistic one in this aspect.

Model Diagnostic Analysis in a Cold Basin Influenced by Frozen Soils With the Aid of Stable Isotope

AbstractUnderstanding the hydrological processes on the Tibetan Plateau (TP) under climate change is an important scientific question. The frequent multiphase transfer exacerbates the complexity of hydrological processes on the TP, which brings equifinality problem to hydrological models and causes large uncertainties in quantifying the contributions of runoff components. Tracer‐aided hydrological models are helpful for improving model performances and have been adopted in cryospheric regions, but the influence of frozen soil has yet to be considered. This study adopted the Tracer‐aided Tsinghua Representative Elementary Watershed model (THREW‐T) in a typical cold basin with widespread frozen soil on the TP. The model structure was diagnosed with isotope by identifying the influences of frozen soil. A simplified catchment‐scale frozen soil module was incorporated into the model. Results showed that: (a) The THREW‐T model cannot simultaneously simulate baseflow and stream water isotope well. The imbalance of simulations on two objectives could be attributed to the influence of frozen soil, resulting in seasonal variation of soil‐related parameters, which was not considered in the model. (b) Incorporating the frozen soil module significantly improved the balance of baseflow and isotope simulation, simultaneously producing low baseflow and high contribution of subsurface runoff during wet seasons. (c) The frozen soil had little influence on the annual streamflow, but changed the runoff seasonality by reducing baseflow during dry seasons and increasing subsurface runoff during wet seasons. The frozen soil module was still simplified, and further work is needed to improve the physical representation of soil freeze‐thaw process. This study highlights the value of tracer‐aided hydrological modeling method on diagnosing model structure by identifying the influence of specific processes such as frozen soil.

Learning by Talking: Using Multimedia to Enhance Science Explanation Development of Neurodivergent Students

Becoming proficient in scientific discourse such as argumentation or developing explanations can be challenging for students, including neurodivergent students (e.g., autistic students, students with learning disabilities, students with ADHD). Students need to practice developing arguments and explanations as well as sharing their conclusions with others; however, these opportunities do not regularly occur. The use of multimedia technology shows promise in being an engaging and effective way to support student learning and discussion of science topics and phenomena. This study investigated the use of a multimedia presentation called Dialogic Instruction for Argumentative Learning in Science (DIALS) in supporting upper-elementary neurodivergent students to provide complete responses to science questions. DIALS provides a structured inquiry investigation to the student in which they learn about a phenomenon through completing scaffolded animated experiments, explicitly learning how to develop an argument and respond to others conclusions, and learning relevant content information to support their argument and explanation development. An adapted alternating treatments design approach was used in this study. The phenomena explored were counterbalanced between three options: DIALS, PowerPoint comparison lessons, or control probe slides. Results from this study show promise in the use of DIALS in enhancing student complete responding to questions and providing quality claims for why they think phenomena occur. Implications for the findings are discussed.

The high power laser facility at beamline ID24-ED at the ESRF

ABSTRACT This paper describes technical details and new scientific opportunities offered by the new High Power Laser Facility at the ESRF, opened to users since 2022. This facility enables laser-induced dynamic compression experiments probed by ultra-fast X-ray Absorption Spectroscopy at beamline ID24-ED. This capability allows to reach and probe more extreme pressure and temperature states and higher strain rates with respect to static compression, addressing open questions in fundamental, planetary and material science.

Estimating statistical power for structural equation models in developmental cognitive science: A tutorial in R

Determining the compositional structure and dimensionality of psychological constructs lies at the heart of many research questions in developmental science. Structural equation modeling (SEM) provides a versatile framework for formalizing and estimating the relationships among multiple latent constructs. While the flexibility of SEM can accommodate many complex assumptions on the underlying structure of psychological constructs, it makes a priori estimation of statistical power and required sample size challenging. This difficulty is magnified when comparing non-nested SEMs, which prevents the use of traditional likelihood-ratio tests. Sample size estimates for SEM model fit comparisons typically rely on generic rules of thumb. Such heuristics can be misleading because statistical power in SEM depends on a variety of model properties. Here, we demonstrate a Monte Carlo simulation approach for estimating a priori statistical power for model selection when comparing non-nested models in an SEM framework. We provide a step-by-step guide to this approach based on an example from our memory development research in children.

Fécondation in vitro : quel impact sur la santé à moyen et long terme des enfants conçus

Among the medical, scientific and ethical questions raised by in vitro fertilization (IVF), those concerning the medium and long-term health of children and young adults thus conceived are essential. Forty-five years after the birth of the first child and while more than 8 million people in the world have been conceived by IVF, the National Academy of Medicine has devoted a report to this theme, mainly analysing the results of numerous international studies. The published results are rather reassuring but they are not always consistent and many uncertainties remain. The Academy of Medicine calls for further epidemiological and clinical studies in better characterized populations and at later ages of life. The Academy also recommends developing basic research to better explain the potential effects of IVF.

Biochar Addition Increased Soil Carbon Storage but Did Not Exacerbate Soil Carbon Emission in Young Subtropical Plantation Forest

Forests play a crucial role in mitigating global warming, contributing approximately 46% of the global terrestrial carbon sink. However, it remains uncertain whether the addition of biochar to forests enhances the ecosystem’s carbon sink capacity. This study aims to address this scientific question by investigating whether biochar application increases carbon storage, potentially leading to an overall rise in carbon emissions by influencing soil respiration and identifying the underlying mechanisms. A controlled experiment was conducted in a young plantation forest that had grown for three years, where soil CO2 efflux rate and physicochemical properties, photosynthesis, and plant growth traits were measured across varying biochar addition rates (0, 5, and 10 t/ha) over five seasons. Then, statistical methods including one-way ANOVA, regression analysis, and structural equation modeling (SEM) were employed to assess differences in biological and abiotic factors among biochar addition gradients and understand the influencing mechanisms of soil CO2 efflux change. The findings revealed that biochar addition significantly increased the contents of soil organic carbon (SOC) and microbial biomass carbon (MBC), consequently promoting photosynthesis and plant growth (p < 0.05). Biochar addition accounted for 73.8% of the variation in soil CO2 efflux by affecting soil physicochemical properties, photosynthesis, and plant basal diameter growth. However, the net effect of biochar addition on soil CO2 efflux was found to be low. The positive effects of biochar addition on soil CO2 efflux via factors such as soil bulk density, total nitrogen (TN), MBC, and photosynthesis were counteracted by its negative impact through soil total phosphorus (TP), water content, pH, SOC, and plant basal diameter growth. Overall, our findings indicate that there was no significant increase in soil CO2 efflux in the short term (totaling 16 months) over the biochar addition gradient. However, we observed a substantial increase in soil carbon storage and an enhancement in the soil’s capacity to act as a carbon sink. Therefore, adding biochar to forests may be a feasible strategy to increase carbon sinks and mitigate global climate change.

Mechanisms of neuromodulatory volume transmission.

A wealth of neuromodulatory transmitters regulate synaptic circuits in the brain. Their mode of signaling, often called volume transmission, differs from classical synaptic transmission in important ways. In synaptic transmission, vesicles rapidly fuse in response to action potentials and release their transmitter content. The transmitters are then sensed by nearby receptors on select target cells with minimal delay. Signal transmission is restricted to synaptic contacts and typically occurs within ~1 ms. Volume transmission doesn't rely on synaptic contact sites and is the main mode of monoamines and neuropeptides, important neuromodulators in the brain. It is less precise than synaptic transmission, and the underlying molecular mechanisms and spatiotemporal scales are often not well understood. Here, we review literature on mechanisms of volume transmission and raise scientific questions that should be addressed in the years ahead. We define five domains by which volume transmission systems can differ from synaptic transmission and from one another. These domains are (1) innervation patterns and firing properties, (2) transmitter synthesis and loading into different types of vesicles, (3) architecture and distribution of release sites, (4) transmitter diffusion, degradation, and reuptake, and (5) receptor types and their positioning on target cells. We discuss these five domains for dopamine, a well-studied monoamine, and then compare the literature on dopamine with that on norepinephrine and serotonin. We include assessments of neuropeptide signaling and of central acetylcholine transmission. Through this review, we provide a molecular and cellular framework for volume transmission. This mechanistic knowledge is essential to define how neuromodulatory systems control behavior in health and disease and to understand how they are modulated by medical treatments and by drugs of abuse.