Inflammation in Development and Aging: Insights from the Zebrafish Model.

Zebrafish are an emergent animal model to study human diseases due to their significant genetic similarity to humans, swift development, and genetic manipulability. Their utility extends to the exploration of the involvement of inflammation in host defense, immune responses, and tissue regeneration. Additionally, the zebrafish model system facilitates prompt screening of chemical compounds that affect inflammation. This study explored the diverse roles of inflammatory pathways in zebrafish development and aging. Serving as a crucial model, zebrafish provides insights into the intricate interplay of inflammation in both developmental and aging contexts. The evidence presented suggests that the same inflammatory signaling pathways often play instructive or beneficial roles during embryogenesis and are associated with malignancies in adults.

Study on Miscibility, Thermomechanical Behavior, and Thermoregulation Performance of Paraffin Wax/Bituminous Blends for Solar Thermal Energy Storage Applications.

The goal of this work was to study the miscibility, thermal stability, thermomechanical properties, and temperature regulation performance of paraffin wax/bitumen blends for their potential use in solar thermal energy storage applications. Results indicated that these blends present a suitable thermal stability, and their thermomechanical properties are strongly dependent on composition, developed microstructure, and temperature. Among all paraffin wax concentrations studied, the blend containing 40 wt % paraffin wax displays enhanced binder elastic properties together with lower thermal susceptibility compared to base bitumen. In addition, this binder also presents improved thermal properties (thermal conductivity and specific heat capacity) and still maintains a high crystallinity, thereby retaining a large enough latent heat to be used for thermal energy storage. Thus, results from the temperature regulation test, which was conducted by subjecting the sample to simulated solar irradiation at a constant radiant flux density, provide a higher latent heat thermoregulation index value than other microencapsulated phase change materials systems. Therefore, it can be stated that paraffin wax/bitumen blends are promising base materials to formulate form-stable products for thermal energy storage applications for thermoregulation purposes.

Altered CELF4 splicing factor enhances pancreatic neuroendocrine tumors aggressiveness influencing mTOR and everolimus response.

Pancreatic neuroendocrine tumors (PanNETs) comprise a heterogeneous group of tumors with growing incidence. Recent molecular analyses provided a precise picture of their genomic and epigenomic landscape. Splicing dysregulation is increasingly regarded as a novel cancer hallmark influencing key tumor features. We have previously demonstrated that splicing machinery is markedly dysregulated in PanNETs. Here, we aimed to elucidate the molecular and functional implications of CUGBP ELAV-like family member 4 (CELF4), one of the most altered splicing factors in PanNETs. CELF4 expression was determined in 20 PanNETs, comparing tumor and non-tumoral adjacent tissue. An RNA sequencing (RNA-seq) dataset was analyzed to explore CELF4-linked interrelations among clinical features, gene expression, and splicing events. Two PanNET cell lines were employed to assess CELF4 function in vitro and in vivo. PanNETs display markedly upregulated CELF4 expression, which is closely associated with malignancy features, altered expression of key tumor players, and distinct splicing event profiles. Modulation of CELF4 influenced proliferation in vitro and reduced in vivo xenograft tumor growth. Interestingly, functional assays and RNA-seq analysis revealed that CELF4 silencing altered mTOR signaling pathway, enhancing the effect of everolimus. We demonstrate that CELF4 is dysregulated in PanNETs, where it influences tumor development and aggressiveness, likely by modulating the mTOR pathway, suggesting its potential as therapeutic target.

Pedological formations on old mountain geomorphological surfaces of central Spain.

The chemo-morphological properties of soils on ancient landforms (quarzitic pliocene alluvial fans, pleistocene terraces), namely "rañizos", on middle-high mountains (Eastern-Central System, Iberian Peninsula, Rio Negro, Cogolludo) were investigated. Several properties were analyzed by standard procedures. A detailed soil diagnostics and classification on "rañizos" were done, unlike those widely studied on "rañas" (similar landform), by identifying parallel pedogenetic processes in both formations. The genetic and geographic features of Alfisols, Ultisols and Inceptisols are closely related to the nature of their parent materials, based on quartzite and quartz conglomerates, sometimes with an arkosic matrix, red shale, polygenic gravels and pebbles. Soil features were determined by genuine soil-forming inherent lithological rock properties. Other driving factors were flat topography and enough soil formation time to allow intense pedogenesis. The main soil-forming processes were intense weathering, clay enrichment horizons with illuviation, red color caused by iron oxide dehydration and signs of pseudogleyzation processes. Such pedological formations can be considered endemisms; that is, "rare" soils and, up to a point, "relict". The soil reaction is acid/slightly acid with low base saturation. Despite lying on mountains, soils are characterized by moderate-low organic matter content. Soil conditions and climate provide good vine production requirements despite acidity levels. A common feature of all Rio Negro soils is the presence of gravel (size up to 3-5 cm), which is evenly distributed on arable layers. The results can be used to assess vineyard soil use in a potential Pago (Protected Denomination of Origin) and to extend the database of vineyard soils from poorly studied Mediterranean continental mountain regions.

The association of the RSC remodeler complex with chromatin is influenced by the prefoldin-like Bud27 and determines nucleosome positioning and polyadenylation sites usage in Saccharomyces cerevisiae.

The tripartite interaction between the chromatin remodeler complex RSC, RNA polymerase subunit Rpb5 and prefoldin-like Bud27 is necessary for proper RNA pol II elongation. Indeed lack of Bud27 alters this association and affects transcription elongation. This work investigates the consequences of lack of Bud27 on the chromatin association of RSC and RNA pol II, and on nucleosome positioning. Our results demonstrate that RSC binds chromatin in gene bodies and lack of Bud27 alters this association, mainly around polyA sites. This alteration impacts chromatin organization and leads to the accumulation of RNA pol II molecules around polyA sites, likely due to pausing or arrest. Our data suggest that RSC is necessary to maintain chromatin organization around those sites, and any alteration of this organization results in the widespread use of alternative polyA sites. Finally, we also find a similar molecular phenotype that occurs upon TOR inhibition with rapamycin, which suggests that alternative polyadenylation observed upon TOR inhibition is likely Bud27-dependent.

Southward migration of the zero-degree isotherm latitude over the Southern Ocean and the Antarctic Peninsula: Cryospheric, biotic and societal implications.

The seasonal movement of the zero-degree isotherm across the Southern Ocean and Antarctic Peninsula drives major changes in the physical and biological processes around maritime Antarctica. These include spatial and temporal shifts in precipitation phase, snow accumulation and melt, thawing and freezing of the active layer of the permafrost, glacier mass balance variations, sea ice mass balance and changes in physiological processes of biodiversity. Here, we characterize the historical seasonal southward movement of the monthly near-surface zero-degree isotherm latitude (ZIL), and quantify the velocity of migration in the context of climate change using climate reanalyses and projections. From 1957 to 2020, the ZIL exhibited a significant southward shift of 16.8 km decade-1 around Antarctica and of 23.8 km decade-1 in the Antarctic Peninsula, substantially faster than the global mean velocity of temperature change of 4.2 km decade-1, with only a small fraction being attributed to the Southern Annular Mode (SAM). CMIP6 models reproduce the trends observed from 1957 to 2014 and predict a further southward migration around Antarctica of 24 ± 12 km decade-1 and 50 ± 19 km decade-1 under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The southward migration of the ZIL is expected to have major impacts on the cryosphere, especially on the precipitation phase, snow accumulation and in peripheral glaciers of the Antarctic Peninsula, with more uncertain changes on permafrost, ice sheets and shelves, and sea ice. Longer periods of temperatures above 0 °C threshold will extend active biological periods in terrestrial ecosystems and will reduce the extent of oceanic ice cover, changing phenologies as well as areas of productivity in marine ecosystems, especially those located on the sea ice edge.

Artificial intelligence extracts key insights from legal documents to predict intimate partner femicide.

Legal documents serve as valuable repositories of information pertaining to crimes, encompassing not only legal aspects but also relevant details about criminal behaviors. To date and the best of our knowledge, no studies in the field examine legal documents for crime understanding using an Artificial Intelligence (AI) approach. The present study aims to fill this research gap by identifying relevant information available in legal documents for crime prediction using Artificial Intelligence (AI). This innovative approach will be applied to the specific crime of Intimate Partner Femicide (IPF). A total of 491 legal documents related to lethal and non-lethal violence by male-to-female intimate partners were extracted from the Vlex legal database. The information included in these documents was analyzed using AI algorithms belonging to Bayesian, functions-based, instance-based, tree-based, and rule-based classifiers. The findings demonstrate that specific information from legal documents, such as past criminal behaviors, imposed sanctions, characteristics of violence severity and frequency, as well as the environment and situation in which this crime occurs, enable the correct detection of more than three-quarters of both lethal and non-lethal violence within male-to-female intimate partner relationships. The obtained knowledge is crucial for professionals who have access to legal documents, as it can help identify high-risk IPF cases and shape strategies for preventing crime. While this study focuses on IPF, this innovative approach has the potential to be extended to other types of crimes, making it applicable and beneficial in a broader context.

Quantification of High-dimensional Non-Gaussianities and Its Implication to Fisher Analysis in Cosmology.

It is well known that the power spectrum is not able to fully characterize the statistical properties of non-Gaussian density fields. Recently, many different statistics have been proposed to extract information from non-Gaussian cosmological fields that perform better than the power spectrum. The Fisher matrix formalism is commonly used to quantify the accuracy with which a given statistic can constrain the value of the cosmological parameters. However, these calculations typically rely on the assumption that the sampling distribution of the considered statistic follows a multivariate Gaussian distribution. In this work, we follow Sellentin & Heavens and use two different statistical tests to identify non-Gaussianities in different statistics such as the power spectrum, bispectrum, marked power spectrum, and wavelet scattering transform (WST). We remove the non-Gaussian components of the different statistics and perform Fisher matrix calculations with the Gaussianized statistics using Quijote simulations. We show that constraints on the parameters can change by a factor of ∼2 in some cases. We show with simple examples how statistics that do not follow a multivariate Gaussian distribution can achieve artificially tight bounds on the cosmological parameters when using the Fisher matrix formalism. We think that the non-Gaussian tests used in this work represent a powerful tool to quantify the robustness of Fisher matrix calculations and their underlying assumptions. We release the code used to compute the power spectra, bispectra, and WST that can be run on both CPUs and GPUs.

Ultrasound-Based Recovery of Anti-Inflammatory and Antimicrobial Extracts of the Acidophilic Microalga Coccomyxa onubensis.

In the present study, the recovery of valuable molecules of proven anti-inflammatory and antimicrobial activity of the acidophilic microalga Coccomyxa onubensis (C. onubensis) were evaluated using green technologies based on ultrasound-assisted extraction (UAE). Using a factorial design (3 × 2) based on response surface methodology and Pareto charts, two types of ultrasonic equipment (bath and probe) were evaluated to recover valuable compounds, including the major terpenoid of C. onubensis, lutein, and the antimicrobial activity of the microalgal extracts obtained under optimal ultrasound conditions (desirability function) was evaluated versus conventional extraction. Significant differences in lutein recovery were observed between ultrasonic bath and ultrasonic probe and conventional extraction. Furthermore, the antimicrobial activity displayed by C. onubensis UAE-based extracts was greater than that obtained in solvent-based extracts, highlighting the effects of the extracts against pathogens such as Enterococcus hirae and Bacillus subtilis, followed by Staphylococcus aureus and Escherichia coli. In addition, gas chromatography-mass spectrometry was performed to detect valuable anti-inflammatory and antimicrobial biomolecules present in the optimal C. onubensis extracts, which revealed that phytol, sterol-like, terpenoid, and even fatty acid structures could also be responsible for the antibacterial activities of the extracts. Moreover, UAE displayed a positive effect on the recovery of valuable molecules, improving biocidal effects. Our study results facilitate the use of green technology as a good tool in algal bioprocess engineering, improving energy consumption and minimizing environmental impacts and process costs, as well as provide a valuable product for applications in the field of biotechnology.

P2X7 Receptor Regulates Collagen Expression in Human Intestinal Fibroblasts: Relevance in Intestinal Fibrosis.

Intestinal fibrosis is a common complication that affects more than 50% of Crohn´s Disease (CD) patients. There is no pharmacological treatment against this complication, with surgery being the only option. Due to the unknown role of P2X7 in intestinal fibrosis, we aim to analyze the relevance of this receptor in CD complications. Surgical resections from CD and non-Inflammatory Bowel Disease (IBD) patients were obtained. Intestinal fibrosis was induced with two different murine models: heterotopic transplant model and chronic-DSS colitis in wild-type and P2X7-/- mice. Human small intestine fibroblasts (HSIFs) were transfected with an siRNA against P2X7 and treated with TGF-ß. A gene and protein expression of P2X7 receptor was significantly increased in CD compared to non-IBD patients. The lack of P2X7 in mice provoked an enhanced collagen deposition and increased expression of several profibrotic markers in both murine models of intestinal fibrosis. Furthermore, P2X7-/- mice exhibited a higher expression of proinflammatory cytokines and a lower expression of M2 macrophage markers. Moreover, the transient silencing of the P2X7 receptor in HSIFs significantly induced the expression of Col1a1 and potentiated the expression of Col4 and Col5a1 after TGF-ß treatment. P2X7 regulates collagen expression in human intestinal fibroblasts, while the lack of this receptor aggravates intestinal fibrosis.

Transcription by the Three RNA Polymerases under the Control of the TOR Signaling Pathway in Saccharomyces cerevisiae.

Ribosomes are the basis for protein production, whose biogenesis is essential for cells to drive growth and proliferation. Ribosome biogenesis is highly regulated in accordance with cellular energy status and stress signals. In eukaryotic cells, response to stress signals and the production of newly-synthesized ribosomes require elements to be transcribed by the three RNA polymerases (RNA pols). Thus, cells need the tight coordination of RNA pols to adjust adequate components production for ribosome biogenesis which depends on environmental cues. This complex coordination probably occurs through a signaling pathway that links nutrient availability with transcription. Several pieces of evidence strongly support that the Target of Rapamycin (TOR) pathway, conserved among eukaryotes, influences the transcription of RNA pols through different mechanisms to ensure proper ribosome components production. This review summarizes the connection between TOR and regulatory elements for the transcription of each RNA pol in the budding yeast Saccharomyces cerevisiae. It also focuses on how TOR regulates transcription depending on external cues. Finally, it discusses the simultaneous coordination of the three RNA pols through common factors regulated by TOR and summarizes the most important similarities and differences between S. cerevisiae and mammals.

Simple lessons from complex learning: what a neural network model learns about cosmic structure formation.

We train a neural network model to predict the full phase space evolution of cosmological N-body simulations. Its success implies that the neural network model is accurately approximating the Green's function expansion that relates the initial conditions of the simulations to its outcome at later times in the deeply nonlinear regime. We test the accuracy of this approximation by assessing its performance on well-understood simple cases that have either known exact solutions or well-understood expansions. These scenarios include spherical configurations, isolated plane waves, and two interacting plane waves: initial conditions that are very different from the Gaussian random fields used for training. We find our model generalizes well to these well-understood scenarios, demonstrating that the networks have inferred general physical principles and learned the nonlinear mode couplings from the complex, random Gaussian training data. These tests also provide a useful diagnostic for finding the model's strengths and weaknesses, and identifying strategies for model improvement. We also test the model on initial conditions that contain only transverse modes, a family of modes that differ not only in their phases but also in their evolution from the longitudinal growing modes used in the training set. When the network encounters these initial conditions that are orthogonal to the training set, the model fails completely. In addition to these simple configurations, we evaluate the model's predictions for the density, displacement, and momentum power spectra with standard initial conditions for N-body simulations. We compare these summary statistics against N-body results and an approximate, fast simulation method called COLA (COmoving Lagrangian Acceleration). Our model achieves percent level accuracy at nonlinear scales of k ∼ 1 Mpc - 1 h , representing a significant improvement over COLA.

Augmenting astrophysical scaling relations with machine learning: Application to reducing the Sunyaev-Zeldovich flux-mass scatter.

Complex astrophysical systems often exhibit low-scatter relations between observable properties (e.g., luminosity, velocity dispersion, oscillation period). These scaling relations illuminate the underlying physics, and can provide observational tools for estimating masses and distances. Machine learning can provide a fast and systematic way to search for new scaling relations (or for simple extensions to existing relations) in abstract high-dimensional parameter spaces. We use a machine learning tool called symbolic regression (SR), which models patterns in a dataset in the form of analytic equations. We focus on the Sunyaev-Zeldovich flux-cluster mass relation (YSZ - M), the scatter in which affects inference of cosmological parameters from cluster abundance data. Using SR on the data from the IllustrisTNG hydrodynamical simulation, we find a new proxy for cluster mass which combines YSZ and concentration of ionized gas (cgas): M ∝ Yconc3/5 ≡ YSZ3/5(1 - A cgas). Yconc reduces the scatter in the predicted M by ∼20 - 30% for large clusters (M ≳ 1014 h-1 M⊙), as compared to using just YSZ. We show that the dependence on cgas is linked to cores of clusters exhibiting larger scatter than their outskirts. Finally, we test Yconc on clusters from CAMELS simulations and show that Yconc is robust against variations in cosmology, subgrid physics, and cosmic variance. Our results and methodology can be useful for accurate multiwavelength cluster mass estimation from upcoming CMB and X-ray surveys like ACT, SO, eROSITA and CMB-S4.

Fe (III)-Mediated Antioxidant Response of the Acidotolerant Microalga Coccomyxa onubensis.

Coccomyxa onubensis (C. onubensis) is an acidotolerant microalga isolated from Tinto River (Huelva), which contains high levels of metal cations in solution, mainly Fe (II) and (III), and Cu (II). Fe is more bioavailable at low pH, mainly because Fe (II) and Fe (III) are far more soluble, especially Fe (III). For this reason, this study aims to evaluate both physiological and biochemical responses of C. onubensis when subjected to Fe (III)-induced stress. Changes in growth, photosynthetic viability and antioxidant responses to the induced oxidative stress were determined. The results obtained suggest that the addition of moderate Fe (III) levels to C. onubensis cultures results in improved growth and photosynthetic viability. Increases in the intracellular levels of the enzyme superoxide dismutase (SOD) and flavonoids, used as antioxidant response biomarkers, a point at Fe (III)-mediated oxidative stress induction. The apparent decrease in the content of other phenolic molecules and polyunsaturated fatty acids might be understood as a sign of antioxidant molecules' involvement in reactive oxygen species (ROS) scavenging. In conclusion, a noticeable antioxidant capacity displayed by C. onubensis allows the use of moderate Fe (III) levels to trigger the accumulation of valuable antioxidant molecules, allowing the production of cell extracts with potential anti-inflammatory activity.

Evolution of snow algae, from cosmopolitans to endemics, revealed by DNA analysis of ancient ice.

Recent studies of microbial biogeography have revealed the global distribution of cosmopolitans and dispersal of regional endemics, but little is known about how these processes are affected by microbial evolution. Here, we compared DNA sequences from snow/glacier algae found in an 8000-year-old ice from a glacier in central Asia with those from modern snow samples collected at 34 snow samples from globally distributed sites at the poles and mid-latitudes, to determine the evolutionary relationship between cosmopolitan and endemic phylotypes of snow algae. We further applied a coalescent theory-based demographic model to the DNA sequences. We found that the genus Raphidonema (Trebouxiophyceae) was distributed over both poles and mid-latitude regions and was detected in different ice core layers, corresponding to distinct time periods. Our results indicate that the modern cosmopolitan phylotypes belonging to Raphidonema were persistently present long before the last glacial period. Furthermore, endemic phylotypes originated from ancestral cosmopolitan phylotypes, suggesting that modern regional diversity of snow algae in the cryosphere is a product of microevolution. These findings suggest that the cosmopolitans dispersed across the world and then derived new localized endemics, which thus improves our understanding of microbial community formation by microevolution in natural environments.

An approach for evaluating the bioavailability and risk assessment of potentially toxic elements using edible and inedible plants-the Remance (Panama) mining area as a model.

Mining affects the environment, particularly through the persistence of accumulation of tailings materials; this is aggravated under tropical climatic conditions, which favours the release of potentially toxic elements (PTEs) bioavailable to the local flora and fauna and supposing a risk to human health. The Remance gold mine (Panamá), exploited intermittently for more than 100 years, and has remained derelict for over 20 years. Within the area live farmers who carry out subsistence agriculture and livestock activities. The objective of this study has been to study the transference of PTEs in the local agricultural soil-plants system, with the goal of identifying their bioavailability to perform a human risk assessment. The results obtained of the Bioaccumulation coefficient in local plants show very weak to strong absorption of As (< 0.001-1.50), Hg (< 0.001-2.38), Sb (0.01-7.83), Cu (0.02-2.89), and Zn (0.06-5.32). In the case of Cu in grass (18.3 mg kg-1) and plants (16.9 mg kg-1) the concentrations exceed the maximum authorised value in animal nutrition for ruminants (10 mg kg-1). The risk to human health for edible plants exceeds the non-carcinogenic risk for rice, corn, cassava, and tea leaves for Sb (HQ 19.450, 18.304, 6.075, 1.830, respectively), the carcinogenic risk for Cu (CR = 2.3 × 10-3, 7.7 × 10 -4, 1.1 × 10-3, 1.0 × 10-3, respectively), and the carcinogenic risk for As in rice, corn and tea leaves (CR = 8 × 10-5, 3 × 10-5, 3 × 10-5, respectively). Urgent measures are needed to alleviate these effects.

The uprise of RNA biology in neuroendocrine neoplasms: altered splicing and RNA species unveil translational opportunities.

Neuroendocrine neoplasms (NENs) comprise a highly heterogeneous group of tumors arising from the diffuse neuroendocrine system. NENs mainly originate in gastrointestinal, pancreatic, and pulmonary tissues, and despite being rare, show rising incidence. The molecular mechanisms underlying NEN development are still poorly understood, although recent studies are unveiling their genomic, epigenomic and transcriptomic landscapes. RNA was originally considered as an intermediary between DNA and protein. Today, compelling evidence underscores the regulatory relevance of RNA processing, while new RNA molecules emerge with key functional roles in core cell processes. Indeed, correct functioning of the interrelated complementary processes comprising RNA biology, its processing, transport, and surveillance, is essential to ensure adequate cell homeostasis, and its misfunction is related to cancer at multiple levels. This review is focused on the dysregulation of RNA biology in NENs. In particular, we survey alterations in the splicing process and available information implicating the main RNA species and processes in NENs pathology, including their role as biomarkers, and their functionality and targetability. Understanding how NENs precisely (mis)behave requires a profound knowledge at every layer of their heterogeneity, to help improve NEN management. RNA biology provides a wide spectrum of previously unexplored processes and molecules that open new avenues for NEN detection, classification and treatment. The current molecular biology era is rapidly evolving to facilitate a detailed comprehension of cancer biology and is enabling the arrival of personalized, predictive and precision medicine to rare tumors like NENs.

RNA Pol II Assembly Affects ncRNA Expression.

RNA pol II assembly occurs in the cytoplasm before translocation of the enzyme to the nucleus. Affecting this assembly influences mRNA transcription in the nucleus and mRNA decay in the cytoplasm. However, very little is known about the consequences on ncRNA synthesis. In this work, we show that impairment of RNA pol II assembly leads to a decrease in cryptic non-coding RNAs (preferentially CUTs and SUTs). This alteration is partially restored upon overcoming the assembly defect. Notably, this drop in ncRNAs is only partially dependent on the nuclear exosome, which suggests a major specific effect of enzyme assembly. Our data also point out a defect in transcription termination, which leads us to propose that CTD phosphatase Rtr1 could be involved in this process.

Tailored Intraoperative MRI Strategies in High-Grade Glioma Surgery: A Machine Learning-Based Radiomics Model Highlights Selective Benefits.

BACKGROUND AND OBJECTIVES: In high-grade glioma (HGG) surgery, intraoperative MRI (iMRI) has traditionally been the gold standard for maximizing tumor resection and improving patient outcomes. However, recent Level 1 evidence juxtaposes the efficacy of iMRI and 5-aminolevulinic acid (5-ALA), questioning the continued justification of iMRI because of its associated costs and extended surgical duration. Nonetheless, drawing from our clinical observations, we postulated that a subset of intricate HGGs may continue to benefit from the adjunctive application of iMRI. METHODS: In a prospective study of 73 patients with HGG, 5-ALA was the primary technique for tumor delineation, complemented by iMRI to detect residual contrast-enhanced regions. Suboptimal 5-ALA efficacy was defined when (1) iMRI detected contrast-enhanced remnants despite 5-ALA's indication of a gross total resection or (2) surgeons observed residual fluorescence, contrary to iMRI findings. Radiomic features from preoperative MRIs were extracted using a U2-Net deep learning algorithm. Binary logistic regression was then used to predict compromised 5-ALA performance. RESULTS: Resections guided solely by 5-ALA achieved an average removal of 93.14% of contrast-enhancing tumors. This efficacy increased to 97% with iMRI integration, albeit not statistically significant. Notably, for tumors with suboptimal 5-ALA performance, iMRI's inclusion significantly improved resection outcomes (P-value: .00013). The developed deep learning-based model accurately pinpointed these scenarios, and when enriched with radiomic parameters, showcased high predictive accuracy, as indicated by a Nagelkerke R2 of 0.565 and a receiver operating characteristic of 0.901. CONCLUSION: Our machine learning-driven radiomics approach predicts scenarios where 5-ALA alone may be suboptimal in HGG surgery compared with its combined use with iMRI. Although 5-ALA typically yields favorable results, our analyses reveal that HGGs characterized by significant volume, complex morphology, and left-sided location compromise the effectiveness of resections relying exclusively on 5-ALA. For these intricate cases, we advocate for the continued relevance of iMRI.

RNA Polymerases IV and V Are Involved in Olive Fruit Development.

Transcription is carried out in most eukaryotes by three multimeric complexes (RNA polymerases I, II and III). However, plants contain two additional RNA polymerases (IV and V), which have evolved from RNA polymerase II. RNA polymerases II, IV and V contain both common and specific subunits that may specialise some of their functions. In this study, we conducted a search for the genes that putatively code for the specific subunits of RNA polymerases IV and V, as well as those corresponding to RNA polymerase II in olive trees. Based on the homology with the genes of Arabidopsis thaliana, we identified 13 genes that putatively code for the specific subunits of polymerases IV and V, and 16 genes that code for the corresponding specific subunits of polymerase II in olives. The transcriptomic analysis by RNA-Seq revealed that the expression of the RNA polymerases IV and V genes was induced during the initial stages of fruit development. Given that RNA polymerases IV and V are involved in the transcription of long non-coding RNAs, we investigated their expression and observed relevant changes in the expression of this type of RNAs. Particularly, the expression of the intergenic and intronic long non-coding RNAs tended to increase in the early steps of fruit development, suggesting their potential role in this process. The positive correlation between the expression of RNA polymerases IV and V subunits and the expression of non-coding RNAs supports the hypothesis that RNA polymerases IV and V may play a role in fruit development through the synthesis of this type of RNAs.