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Fuzzy dark matter (FDM), consisting of ultralight bosons, is an intriguing alternative to cold dark matter. Numerical simulations solving the Schrödinger–Poisson (SP) equation, which governs FDM dynamics, show that FDM halos consist of a central solitonic core (representing the ground state of the SP equation), surrounded by a large envelope of excited states. Wave interference gives rise to density fluctuations of order unity throughout the envelope and causes the soliton to undergo density oscillations and execute a confined random walk in the central region of the halo. The resulting gravitational potential perturbations are an efficient source of dynamical heating. Using high-resolution numerical simulations of a 6.6 × 109 M ⊙ FDM halo with boson mass m b = 8 × 10−23 eV, we investigate the impact of this dynamical heating on the structure and kinematics of spheroidal dwarf galaxies of a fixed mass but different initial sizes and ellipticities. The galaxies are set up in equilibrium in the time-and-azimuthally averaged halo potential and evolved for 10 Gyr in the live FDM halo. We find that they continuously increase their sizes and central velocity dispersions. In addition, their kinematic structures become strongly radially anisotropic, especially in the outskirts. Dynamical heating also causes initially ellipsoidal galaxies to become more spherical over time from the inside out and gives rise to distorted, nonconcentric isodensity contours. These telltale characteristics of dynamical heating of dwarf galaxies in FDM halos can potentially be used to constrain the boson mass.

Accurate recognition and linking of oncologic entities in clinical notes is essential for extracting insights across cancer research, patient care, clinical decision-making, and treatment optimization. We present the Neuro-Symbolic System for Cancer (NSSC), a hybrid AI framework that integrates neurosymbolic methods with named entity recognition (NER) and entity linking (EL) to transform unstructured clinical notes into structured terms using medical vocabularies, with the Unified Medical Language System (UMLS) as a case study. NSSC was evaluated on a dataset of clinical notes from breast cancer patients, demonstrating significant improvements in the accuracy of both entity recognition and linking compared to state-of-the-art models. Specifically, NSSC achieved a 33% improvement over BioFalcon and a 58% improvement over scispaCy. By combining large language models (LLMs) with symbolic reasoning, NSSC improves the recognition and interoperability of oncologic entities, enabling seamless integration with existing biomedical knowledge. This approach marks a significant advancement in extracting meaningful information from clinical narratives, offering promising applications in cancer research and personalized patient care. Graphical abstract

Microalgae cultures were used for a WW treatment to remediate nutrients while producing biomass and recycling water. In these trials, raceway ponds (RWPs; 1 and 0.5 ha) were located next to a municipal (WW) treatment plant in Mérida, Spain. The ponds were used for continuous, all-year-round microalgae production using WW as a source of nutrients. Neither CO2 nor air was supplied to cultures. The objective was to validate photosynthesis monitoring techniques in large-scale bioreactors. Various in-situ/ex-situ methods based on chlorophyll fluorescence and oxygen evolution measurements were used to follow culture performance. Photosynthesis variables gathered with these techniques were compared to the physiological behavior and growth of cultures. Good photosynthetic activity was indicated by the build-up of dissolved oxygen concentration up to 380% saturation, high photochemical yield (Fv/Fm = 0.62–0.71), and relative electron transport rate rETR between 200 and 450 μmol e− m−2 s−1 at midday, which resulted in biomass productivity of about 15–25 g DW m−2 day−1. The variables represent reliable markers reflecting the physiological status of microalgae cultures. Using waste nutrients, the biomass production cost can be significantly decreased for abundant biomass production in large-scale bioreactors, which can be exploited for agricultural purposes.

Anthropogenic impacts on water resources, especially by ​​nutrient discharge, is a worldwide problem in marine coastal areas. In this context, seaweed cultivation in aquaculture wastewater can be considered as an alternative for effluent mitigation, where the biomass becomes a source of valuable compounds. The current study examined the potential use of the seaweeds Ulva pseudorotundata and Ulva rigida to remove nutrients to treat effluents from the culture of Chelon labrosus . Two experiments were conducted under pilot-scale conditions to evaluate the nutrient uptake, photosynthetic activity, and biomass production of the seaweed species cultivated under 50 and 100% effluent concentrations. Photosynthetic parameters were determined by in vivo chlorophyll a fluorescence associated to photosystem II 3 times a day to estimate photosynthetic performance and seaweed physiology throughout the experiment: optimal quantum yield ( F v /F m ), in situ and ex situ electron transport rate (ETR), photosynthetic efficiency (α ETR ), saturation irradiance ( E k ), and the maximum non-photochemical quenching (NPQ max ). To evaluate seaweed metabolism and biomass compounds, elemental and biochemical composition were analyzed in the beginning and end of each experiment. Results regarding the nutrient source showed that both species removed more than 65% of ammonium after 3 hours of experimentation. At the end of the experiments, up to 94.8% of the initial ammonium was sequestered from the effluent. Additionally, after 5 days of cultivation under 50% fish effluent both Ulva species were able to remove more than 85% of the nitrate. Although a decrease in uptake efficiency was observed in cultures with 100% fish effluent, at the end of the experiment more than 440 µmol L -1 of nitrate was removed, considering all treatment conditions. The biomass values showed that growth rates of seaweed cultivated in 100% effluent were higher than those obtained in 50% effluent. Moreover, when cultivated in the 100% effluent concentration, a significant increment in protein content was detected in both Ulva species. Our results contribute to the understanding of biofiltration and photosynthetic performance of two different Ulva species in order to improve growth optimization, enhancement of biofiltration capacity and also to boost management practices of seaweed cultivation in aquaculture effluent treatment systems.

The microalga Scenedesmus sp. (Chlorophyceae) was cultured in a raceway pond (RWP) placed in a greenhouse. The objective of this case study was to monitor the photosynthesis performance and selected physicochemical variables (irradiance, temperature, dissolved oxygen concentration) of microalgae cultures in situ at various depths of RWP. The data of actual photochemical yield Y(II), the electron transport rate monitored by in vivo chlorophyll fluorescence and photosynthetic oxygen production both in situ and ex situ revealed that (i) even in diluted cultures (0.6 g DW L−1), the active photic layer in the culture was only about 1 cm, indicating that most of the culture was “photosynthetically” inactive; (ii) the mechanism of non-photochemical quenching may not be fast enough to respond once the cells move from the surface to the deeper layers; and (iii) even when cells were exposed to a high dissolved oxygen concentration of about 200% sat and higher, the cultures retained a relatively high Y(II) > 0.35 when monitored in situ. The presented work can be used as exemplary data to optimize the growth regime of microalgae cultures in large-scale RWPs by understanding the interplay between photosynthetic activity, culture depth and cell concentration.

Research in seaweed cultivation technologies aims to increase production and reduce costs, leading to more efficient and sustainable processes. In this study, we analyzed the outdoor production of Ulva compressa cultured in summertime at different stocking densities of 0.6, 0.8 and 1.0 kg Fresh weight (FW) m−2 in a raceway photobioreactor with 30 m2 surface (3000 L), and its relation to photosynthetic activity. Under the experimental conditions of high temperature (>28–30 °C) and pH > 9 in culture water, higher seaweed density resulted in lower specific growth rate. The biomass production has been related to photosynthetic activity by using in vivo chlorophyll a fluorescence. Dynamic photoinhibition was observed at noon, which was less severe in cultures with higher algal densities. However, photosynthesis recovered in the afternoon. Seaweeds that were acclimatized for a week to the conditions of 1.0 kg FW m−2 stocking density showed an increase in biomass growth and absence of photoinhibition compared to non-acclimatized thalli. In conclusion, the cultivation of U. compressa in a mid-scale raceway photobiorreactor under conditions of high irradiance and temperature and low nutrient input, exhibited the best photosynthetic performance and hence the highest growth rates for the highest culture density assayed (1.0 kg FW m−2).

We report the crystal structures at 2.05 and 2.45 Å resolution of two antibodies, 13G10 and 14H7, directed against an iron(III)-αααβ-carboxyphenylporphyrin, which display some peroxidase activity. Although these two antibodies differ by only one amino acid in their variable λ-light chain and display 86% sequence identity in their variable heavy chain, their complementary determining regions (CDR) CDRH1 and CDRH3 adopt very different conformations. The presence of Met or Leu residues at positions preceding residue H101 in CDRH3 in 13G10 and 14H7, respectively, yields to shallow combining sites pockets with different shapes that are mainly hydrophobic. The hapten and other carboxyphenyl-derivatized iron(III)-porphyrins have been modeled in the active sites of both antibodies using protein ligand docking with the program GOLD. The hapten is maintained in the antibody pockets of 13G10 and 14H7 by a strong network of hydrogen bonds with two or three carboxylates of the carboxyphenyl substituents of the porphyrin, respectively, as well as numerous stacking and van der Waals interactions with the very hydrophobic CDRH3. However, no amino acid residue was found to chelate the iron. Modeling also allows us to rationalize the recognition of alternative porphyrinic cofactors by the 13G10 and 14H7 antibodies and the effect of imidazole binding on the peroxidase activity of the 13G10/porphyrin complexes.

We present an adaptation of model-based clustering for partially labeled data, that is capable of finding hidden cluster labels. All the originally known and discoverable clusters are represented using localized feature subset selections (subspaces), obtaining clusters unable to be discovered by global feature subset selection. The semi-supervised projected model-based clustering algorithm (SeSProC) also includes a novel model selection approach, using a greedy forward search to estimate the final number of clusters. The quality of SeSProC is assessed using synthetic data, demonstrating its effectiveness, under different data conditions, not only at classifying instances with known labels, but also at discovering completely hidden clusters in different subspaces. Besides, SeSProC also outperforms three related baseline algorithms in most scenarios using synthetic and real data sets.

The antifungal effect of ethanolic extract fractions of Annona cherimola leaves against the mycelial growth of Fusarium oxysporum was studied. The ethanolic crude extract was solvent partitioned and the ethyl acetate phase was fractionated by column or preparative thin-layer chromatography. All fractions were developed on TLC and analyzed for acetogenins (ACG) with Kedde reagent. The antifungal effect assays were carried out in vitro by the diffusion method on PDA plates. The ethanolic extract of A. cherimola leaves was highly active against F. oxysporum growth; subfractions obtained from the antifungal screening had a significant effect (p < 0.05) on the F. oxysporum growth parameters. The screening showed that as the purification steps progressed, the inhibition of mycelial growth increased. Six bioactive ACG (Annomolon-B, 34-epi annomolon B, almunequin, cherimoline 1, cherimoline 2, and isocherimoline 1) were identified by LC–QTOF-MS/MS. These findings suggested that bioactive ACG from A. cherimola leaves could be an alternative resource of a promising botanical fungicide to control plant diseases caused by F. oxysporum.

En el presente artículo, el autor analiza la relación entre el uso de plataformas digitales educativas y la motivación en el proceso de enseñanza-aprendizaje del inglés como lengua extranjera en el nivel medio superior. En un contexto de creciente digitalización, dichas plataformas se consolidan como recursos clave para apoyar la práctica docente y atender los intereses de los estudiantes. Se examina cómo su incorporación influye en la motivación, al promover la interacción, el aprendizaje autónomo y el compromiso académico. Estos planteamientos teóricos fundamentan un protocolo de tesis centrado en las tecnologías del aprendizaje y del conocimiento y su impacto en la motivación académica de estudiantes de educación media superior en el aprendizaje del inglés como lengua extranjera contemporánea actual vigente.