Miracle-dz/UniFAR-FTUs huggingface dataset:
Oxidation-reduction imaging of myoglobin unveils two-phase oxidation in the reperfused myocardium

Myocardial infarction (MI) is a serious cardiovascular problem that causes myocardial injury due to blood flow obstruction to a specific myocardial area. Under ischemic-reperfusion settings, a burst of reactive oxygen species is generated, leading to redox imbalance that could be attributed to several molecules, including myoglobin. Myoglobin is dynamic and exhibits various oxidation-reduction states that have been a subject of attention in the food industry, specifically for meat consumers. However, rarely if ever, have the myoglobin optical properties been used to understand the pathology of MI. In the current study, we develop a novel imaging pipeline that integrates tissue clearing, confocal and light sheet fluorescence microscopy, combined with imaging analysis, and processing tools to investigate and characterize the oxidation-reduction states of myoglobin in the ischemic area of the myocardium post-MI. Using spectral imaging, we have characterized the endogenous fluorescence of the myocardium and demonstrated that it aligns with the spectral profile of myoglobin. Under ischemia-reperfusion experimental settings, we report that the infarcted myocardium spectral signature is similar to that of oxidized myoglobin signal that peaks 3 hours post-reperfusion and decreases with cardioprotection. These results were correlated with MI measurements by Late Gadolinium Enhancement MRI. In conclusion, this seminal work suggests that the redox state of myoglobin can be used as a promising imaging biomarker for characterizing and estimating the size of the MI during early phases of reperfusion.
Non-LTE line formation for Ni/ii: Abundances and stellar parameters - Model atom and first results on BA-type stars

A comprehensive model atom for non-LTE line formation calculations for neutral and singly-ionized nitrogen is presented. Highly accurate radiative and collisional atomic data are incorporated, recently determined for astrophysical and fusion research using the R-matrix method in the close-coupling approximation. As a test and rst application of the model, nitrogen abundances are determined on the basis of line-blanketed LTE model atmospheres for ve stars, the main sequence object Vega (A0 V) and the supergiants Leo (A0 Ib), HD 111613 (A2 Iabe), HD 92207 (A0 Iae) and Ori (B8 Iae), using high S=N and high-resolution spectra at visual and near-IR wavelengths. The computed non-LTE line proles t the observations excellently for a given nitrogen abundance in each object. Moreover, the ionization equilibrium of N i/ii proves to be a sensitive temperature indicator for late B-type and early A-type supergiants { even at low metallicities { due to the apparent nitrogen overabundance in these objects. All supergiants within our sample show an enrichment of nitrogen on the order of0.3{0.6 dex, indicating the mixing of CN-cycled material into atmospheric layers, with the sum of the CNO abundances staying close to solar. This nding is in accordance with recent stellar evolution models accounting for mass-loss and rotation. For Vega, an underabundance of nitrogen by 0.25 dex is found, in good agreement with the similar underabundance of other light elements. The dependence of the non-LTE eects on the atmospheric parameters is discussed with special emphasis on the supergiants where a strong radiation eld at low particle densities favours deviations from LTE. Non-LTE eects systematically strengthen the N i/ii lines. For some N i lines in supergiants non-LTE abundance corrections in excess of 1 dex are found and they react sensitively to modications of the collisional excitation data. The influence of microturbulence on the statistical-equilibrium calculations is also investigated: the line-strengths of the strong N i features show some sensitivity due to modications of the line-formation depths and the departure coecients, while the { in this parameter range { weak N ii lines remain unaected.
Experimental Study on Wet Oxidation Process of VCSEL

The wet oxidation process is studied with experiments in vertical-cavity surface-emitting lasers (VCSEL) in order to accurately control the oxidation aperture and improve the performance of photo-electricity.Wet oxidation experiments are carried out upon the simulative wafers of VCSELs with the same structure at different temperature.Oxidation products are examined at different oxidation depths of oxidation layer by X-ray micro-analyses.The oxidation course is analyzed and discussed by changing of oxygen element content,and the law of oxidation rate vs time at constant temperature is obtained.The oxidation process stability and precision can be improved by lowering the oxidation temperature and prolonging the oxidation time.
A Comparative Cognitive-Semantic Analysis of Spatial Postpositions in Korean and Japanese

Korean and Japanese present remarkable similarities in the way spatial postpositions are associated with various spatial relations from ablative to locative to allative. This paper aims to explore whether the similarity in the semantic distribution of spatial postpositions in the two languages suggests their compatibility in the conceptual distribution of space. To answer this question, we investigate the extent of semantic overlaps in the distribution of spatial postpositions in the two languages. Based on the data from native speakers' judgment tests, we compare the semantic boundaries between two neighboring postpositions, and determine what semantic factors contribute to the differences. Findings from this study indicate that various semantic factors, such as verb types, the size of the location NP, and the direction of movement, influence the choice of spatial postpositions to differing degrees. It is also suggested that Korean is more semantically sensitive than Japanese, showing less overlap between the two particles. The complex interactions between spatial postpositions reflect the flexibility and elasticity of human categorization.
Neuroimaging Signatures of Metacognitive Improvement in Sensorimotor Timing

Error monitoring is an essential human ability underlying learning and metacognition. In the time domain, humans possess a remarkable ability to learn and adapt to temporal intervals, yet the neural mechanisms underlying this are not well understood. Recently, we demonstrated that humans exhibit improvements in sensorimotor time estimates when given the chance to incorporate feedback from a previous trial (Bader and Wiener 2021), suggesting that humans are metacognitively aware of their own timing errors. To test the neural basis of this metacognitive ability, human participants of both sexes underwent fMRI while they performed a visual temporal reproduction task with randomized suprasecond intervals (1-6s). Crucially, each trial was repeated following feedback, allowing a “re-do” to learn from the successes or errors in the initial trial. Behaviorally, we replicated our previous finding that subjects improve their performance on re-do trials despite the feedback being temporally uninformative (i.e. early or late). For neuroimaging, we observed a dissociation between estimating and reproducing time intervals, with the former more likely to engage regions associated with the default mode network (DMN), including the superior frontal gyri, precuneus, and posterior cingulate, whereas the latter activated regions associated traditionally with the “Timing Network” (TN), including the supplementary motor area (SMA), precentral gyrus, and right supramarginal gyrus. Notably, greater DMN involvement was observed in Re-do trials. Further, the extent of the DMN was greater on re-do trials, whereas for the TN it was more constrained. Finally, Task-based connectivity between these networks demonstrated higher inter-network correlation on initial trials, but primarily when estimating trials, whereas on re-do trials communication was higher during reproduction. Overall, these results suggest the DMN and TN work in concert to mediate subjective awareness of one’s sense of time for the purpose of improving timing performance. Significance Statement A finely tuned sense of time perception is imperative for everyday motor actions (e.g., hitting a baseball). Timing self-regulation requires correct assessment and updating duration estimates if necessary. Using a modified version of a classical task of time measurement, we explored the neural regions involved in error detection, time awareness, and learning to time. Reinforcing the role of the SMA in measuring temporal information and providing evidence of co-activation with the DMN, this study demonstrates that the brain overlays sensorimotor timing with a metacognitive awareness of its passage.
Genome-wide identification of nitrate-responsive microRNAs by small RNA sequencing in the rice restorer cultivar Nanhui 511

Rice productivity relies heavily on nitrogen fertilization, and improving nitrogen use efficiency (NUE) is important for hybrid rice breeding. Reducing nitrogen inputs is the key to achieving sustainable rice production and reducing environmental problems. Here, we analyzed the genome-wide transcriptomic changes in microRNAs (miRNAs) in the indica rice restorer cultivar Nanhui 511 (NH511) under high (HN) and low nitrogen (LN) conditions. The results showed that NH511 is sensitive to nitrogen supplies and HN conditions promoted the growth its lateral roots at the seedling stage. Furthermore, we identified 483 known miRNAs and 128 novel miRNAs by small RNA sequencing in response to nitrogen in NH511. We also detected 100 differentially expressed genes (DEGs), including 75 upregulated and 25 downregulated DEGs, under HN conditions. Among these DEGs, 43 miRNAs that exhibited a 2-fold change in their expression were identified in response to HN conditions, including 28 upregulated and 15 downregulated genes. Additionally, some differentially expressed miRNAs were further validated by qPCR analysis, which showed that miR443, miR1861b, and miR166k-3p were upregulated, whereas miR395v and miR444b.1 were downregulated under HN conditions. Moreover, the degradomes of possible target genes for miR166k-3p and miR444b.1 and expression variations were analyzed by qPCR at different time points under HN conditions. Our findings revealed comprehensive expression profiles of miRNAs responsive to HN treatments in an indica rice restorer cultivar, which advances our understanding of the regulation of nitrogen signaling mediated by miRNAs and provides novel data for high-NUE hybrid rice cultivation.
Spatial Double Generalized Beta Regression Models

In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models’ setting. Finally, we motivate the need for the innovative use of the generalized beta spatial regression model to the study of the performance of school children in Mathematics and Language, as well as in the analysis of illiteracy data, and present its results in the context of evaluating the quality of education in Colombia.
Identification of novel candidate targets for suppressing ovarian cancer progression through IL-33/ST2 axis components using the system biology approach

Background: Cancer-associated fibroblasts (CAFs) of ovarian cancer (OvC) are the most prevalent element of the tumor microenvironment (TM). By promoting angiogenesis, immunological suppression, and invasion, CAFs speed up the growth of tumors by changing the extracellular matrix’s structure and composition and/or initiating the epithelial cells (EPT). IL-33/ST2 signaling has drawn a lot of attention since it acts as a pro-tumor alarmin and encourages spread by altering TM. Methods: Differentially expressed genes (DEGs) of the OvC tumor microenvironment were found in the GEO database, qRT-PCR, western blotting, and immunohistochemistry, and their presence and changes in healthy and tumor tissue content were examined. Primary cultures of healthy fibroblasts and CAFs obtained from healthy and tumor tissues retrieved from OvC samples were used for in vitro and in vivo investigations. Cultured primary human CAFs were utilized to investigate the regulation and the IL-33/ST2 axis role in the inflammation reactions. Results: Although ST2 and IL-33 expression was detected in both epithelial (EPT) and fibroblast cells of ovarian cancer, they are more abundant in CAFs. Lipopolysaccharides, serum amyloid A1, and IL-1β, the inflammatory mediators, could all induce IL-33 expression through NF-κB activation in human CAFs. In turn, via the ST2 receptor, IL-33 affected the production of IL-6, IL-1β, and PTGS2 in human CAFs via the MAPKs-NF-κB pathway. Conclusion: Our findings suggest that IL-33/ST2 is affected by the interaction of CAFs and epithelial cells inside the tumor microenvironment. Activation of this axis leads to increased expression of inflammatory factors in tumor CAFs and EPT cells. Therefore, targeting the IL-33/ST2 axis could have potential value in the prevention of OvC progression.
Exploitation of alternative skin models from academia to industry: proposed functional categories to answer needs and regulation demands

The utilization of alternative skin models (ASM) for testing has sparked significant attention in both academic and industrial environments. This aligns with the 3R principle, which stands for replacement, reduction, and refinement for ethical animal experimentation (Niehues et al., 2018; Sonawane et al., 2022). In the field of dermatology, the development of ASM has become crucial (Mathes et al., 2014; Yun et al., 2018). Skin is a complex organ, and studying its biology and pathology often requires the use of animal models, which can be costly, time-consuming, react differently from human skin, and raise ethical concerns. ASM, based on human cells, reconstructed skin, ex vivo skin, organ-on-a-chip, and computational in silico models, have emerged as a promising solution, as they are more cost-effective and sustainable, present fewer ethical considerations, and, in certain cases, show advantages compared to the corresponding animal models (Danilenko et al., 2016). The transformation of ASM from research to industry has been slow but steady, as summarized in Table 1 (Casas et al., 2013; Araújo et al., 2014; Mathes et al., 2014; Abaci et al., 2015; Hayden et al., 2015; Lukács et al., 2019; Wang et al., 2021; Mehling et al., 2022; Silva and Tamburic, 2022). The use of various complementary models can contribute to the industry by providing data for safety, claim substantiation, and initial proof of concept, diminishing technology readiness level (TRL) gaps and shortening the time to market. Furthermore, ASM will enable the study of underrepresented populations from diverse ethnicities and genetic backgrounds. Despite their importance and benefits, challenges and gaps still need to be addressed to facilitate the translation of ASM into industrial applications. One of the main needs is their standardization to ensure that results are consistent and comparable across different laboratories and models. Currently, the validation process for these models can be complex and expensive (Worth and Balls, 2001), which has been a barrier to their adoption. More research is needed to streamline the validation process and to ensure that ASM can replace traditional animal testing methods (Bas et al., 2021). Additionally, the lack of complexity of some models (e.g., cut off from blood vessels and immune cell migration) can limit their usefulness in certain applications. Finally, regulatory challenges also need to be addressed to ensure the safety and efficacy of ASM for use in different industrial sectors such as pharmaceuticals, devices, cosmetics, chemicals, and health-tech. OPEN ACCESS
Tomato brown rugose fruit virus in aqueous environments – survival and significance of water-mediated transmission

Tomato brown rugose fruit virus (ToBRFV) has recently emerged as a major disease of tomatoes and peppers. ToBRFV is a seed- and contact-transmitted virus. In Slovenia, ToBRFV RNA was detected in samples of wastewater, river, and water used to irrigate plants. Even though the source of detected RNA could not be clearly established, this raised the question of the significance of the detection of ToBRFV in water samples and experimental studies were performed to address this question. The data presented here confirm that the release of virus particles from the roots of infected plants is a source of infectious ToBRFV particles in water and that the virus can remain infective up to four weeks in water stored at room temperature, while its RNA can be detected for much longer. These data also indicate that irrigation with ToBRFV-contaminated water can lead to plant infection. In addition, it has been shown that ToBRFV circulated in drain water in commercial tomato greenhouses from other European countries and that an outbreak of ToBRFV can be detected by regular monitoring of drain water. A simple method for concentrating ToBRFV from water samples and a comparison of the sensitivity of different methods, including the determination of the highest ToBRFV dilution still capable of infecting test plants, were also investigated. The results of our studies fill the knowledge gaps in the epidemiology and diagnosis of ToBRFV, by studying the role of water-mediated transmission, and provide a reliable risk assessment to identify critical points for monitoring and control.
Addressing marine restoration success: evidence of species and functional diversity recovery in a ten-year restored macroalgal forest

Active restoration actions are becoming increasingly common for the recovery of degraded ecosystems. However, establishing when an ecosystem is fully restored is rarely achieved, since the recovery of entire communities needs long-term trajectories. The lack of evidence of success is even more severe in marine ecosystems, especially in the context of macroalgal forests, where beyond the vegetation structure and species diversity there is no approximation determining the recovery of the overall functionality. Trait-based ecology facilitates the link between species composition and ecosystem functions and processes. In this study, we used a trait-based approach to assess functional recovery ten years after the start of a restoration action in a marine macroalgal forest. Species and functional diversity were compared among the restored locality, a nearby locality where the expansion of the restoration is naturally occurring, a neighbouring non-restored locality (at a distance of a few meters), and the only two remaining localities dominated by the same structural macroalga that were used as reference (non-perturbed). Species diversity and composition of the restored locality were similar to those found in reference macroalgal forests, while the non-restored and expansion locality showed different species composition and lower species diversity. Functional richness was 4-fold higher in the restored locality than in the non-restored one, even surpassing one reference macroalgal locality. The restored locality showed a greater number of trait categories, especially traits related to higher structural complexity and longer life spans, indicating changes in ecosystem functions and processes. The restoration of a canopy-forming macroalga is the first step to achieving the recovery of an entire macroalgal forest (i.e., associated species and functional diversity). The application of traditional taxonomical indices plus functional parameters provides useful insights into the assessment of the success of restoration actions at the community level, emerging as a promising approach to be replicated and contrasted in other marine and terrestrial ecosystems.
Shedding light on the composition of extreme microbial dark matter: alternative approaches for culturing extremophiles

More than 20,000 species of prokaryotes (less than 1% of the estimated number of Earth’s microbial species) have been described thus far. However, the vast majority of microbes that inhabit extreme environments remain uncultured and this group is termed “microbial dark matter. ” Little is known regarding the ecological functions and biotechnological potential of these underexplored extremophiles, thus representing a vast untapped and uncharacterized biological resource. Advances in microbial cultivation approaches are key for a detailed and comprehensive characterization of the roles of these microbes in shaping the environment and, ultimately, for their biotechnological exploitation, such as for extremophile-derived bioproducts (extremozymes, secondary metabolites, CRISPR Cas systems, and pigments, among others), astrobiology, and space exploration. Additional efforts to enhance culturable diversity are required due to the challenges imposed by extreme culturing and plating conditions. In this review, we summarize methods and technologies used to recover the microbial diversity of extreme environments, while discussing the advantages and disadvantages associated with each of these approaches. Additionally, this review describes alternative culturing strategies to retrieve novel taxa with their unknown genes, metabolisms, and ecological roles, with the ultimate goal of increasing the yields of more efficient bio-based products. This review thus summarizes the strategies used to unveil the hidden diversity of the microbiome of extreme environments and discusses the directions for future studies of microbial dark matter and its potential applications in biotechnology and astrobiology.
Human-centered design and evaluation of AI-empowered clinical decision support systems: a systematic review

Introduction Artificial intelligence (AI) technologies are increasingly applied to empower clinical decision support systems (CDSS), providing patient-specific recommendations to improve clinical work. Equally important to technical advancement is human, social, and contextual factors that impact the successful implementation and user adoption of AI-empowered CDSS (AI-CDSS). With the growing interest in human-centered design and evaluation of such tools, it is critical to synthesize the knowledge and experiences reported in prior work and shed light on future work. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic review to gain an in-depth understanding of how AI-empowered CDSS was used, designed, and evaluated, and how clinician users perceived such systems. We performed literature search in five databases for articles published between the years 2011 and 2022. A total of 19874 articles were retrieved and screened, with 20 articles included for in-depth analysis. Results The reviewed studies assessed different aspects of AI-CDSS, including effectiveness (e.g., improved patient evaluation and work efficiency), user needs (e.g., informational and technological needs), user experience (e.g., satisfaction, trust, usability, workload, and understandability), and other dimensions (e.g., the impact of AI-CDSS on workflow and patient-provider relationship). Despite the promising nature of AI-CDSS, our findings highlighted six major challenges of implementing such systems, including technical limitation, workflow misalignment, attitudinal barriers, informational barriers, usability issues, and environmental barriers. These sociotechnical challenges prevent the effective use of AI-based CDSS interventions in clinical settings. Discussion Our study highlights the paucity of studies examining the user needs, perceptions, and experiences of AI-CDSS. Based on the findings, we discuss design implications and future research directions.