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Abstract Piangua, Anadara tuberculosa, is an economically important mollusk for the human population living on the Colombian Pacific Coast. In the last years, the demand and exploitation of this mollusk have increased, putting it at risk to the point of being endangered. This research aimed to identify the genetic diversity and population structure of piangua in two localities on the Pacific Coast of Colombia. We assembled a chromosome-level genome using PacBio-Hifi and Arima sequencing. We obtained 274 scaffolds with an N50 of 45.42 Mbp, a total size of 953 Mbp, and a completeness of 91% based on BUSCO scores. The transposable elements accounted for 30.29% of the genome, and 24,317 genes were annotated. Genome-guided variant calling for 89 samples using DArT sequencing data delivered 4,825 bi-allelic SNPs, which supported genetic diversity and population structure analyses. Data showed that the piangua populations in the two localities were under expansion events more than 100k years ago. However, results also showed a reduction in genetic diversity, as evidenced by the loss of heterozygosity, which may be caused by high levels of inbreeding, probably due to a recent overexploitation. Furthermore, although we evidenced gene flow between the two localities, there is also a subtle geographical population structure between the two localities and among mangroves in one of the localities. This is the first study in Colombia that provides relevant genetic information on piangua to lay the foundations for conservation strategies.

Abstract Light-emitting diodes (LEDs) have revolutionized artificial lighting, but also exposed the detrimental health effects that stem from insufficient exposure to natural light. Human-centric artificial lighting requires both visual quality and circadian lighting performance that mimics daylight’s evolving spectral power distribution (SPD). Here, we present a color-tunable LED-based light source that achieves SPDs similar to various conditions of daylight and incandescent lighting over the range of visible wavelengths. This light source is comprised of a linear combination of light converter channels containing dyes exhibiting thermally activated delayed fluorescence (TADF) fabricated through additive manufacturing, photoexcited by violet-emitting LEDs (VLED). This hybrid light source establishes a new benchmark for state-of-the-art artificial lighting at approximating daylight, with Illuminating Engineering Society (IES) color gamut index R g values within 3%, IES color fidelity index R f values within 7% through CCT values ranging from 4277 K to 22,333 K. We propose efficiency metrics to accurately quantify similarity between light sources and the respective reference daylight spectrum encompassing visual and circadian effects, facilitating WLED benchmarking. The efficiency metrics pertaining to circadian lighting performance remain within 10% over the same CCT range. These results advance lighting science to address simultaneously the grand challenges of health and sustainability.

Abstract In citrus, the synthetic auxin 3,5,6-trichloro-2-pyridyloxyacetic acid (3,5,6-TPA), applied as a foliar spray at a concentration of 15 mg l− 1 during physiological fruitlet abscission, caused additional fruitlet drop and reduced the number of fruits reaching maturity. The effect was much more pronounced at full physiological abscission than after. In this study, this thinning effect was successfully exploited for the first time in sour orange trees grown in an urban environment, reducing harvesting costs by up to almost 40%. This effect is mediated by the leaves, which alter their photosynthetic activity. Our results show a reduction of carbon fixation and sucrose synthesis in the leaf, by 3,5,6-TPA repression of the RbcS, SUS1 and SUSA genes, its transport to the fruit, as shown by the reduced expression of the sucrose transporter genes SUT3 and SUT4, and its hydrolysis in the fruit, mainly by repression of the SUS1 gene expression. Genes involved in auxin homeostasis in the fruit, TRN2 and PIN1, were also repressed. The coordinated repression of all these genes is consistent with the decrease in the fruit cell division rate, as shown by the repression of CYCA1-1 gene, leading to the production of ethylene, which ultimately induces fruitlet abscission.

Abstract Seasonal rhythms are gaining attention given their impact on metabolic disorders development such as obesity gut microbiota is emerging as a key factor in mediating this link. However, the underlying mechanisms are still poorly understood. In this regard, corticosterone may play a role as it has been shown to be affected by gut bacteria and seasonal rhythms, and has been linked to obesity. Thus, this study aimed to investigate if seasonal rhythms effects on corticosterone are influenced by gut microbiota in obese rats and whether this may be related to seasonal and clock genes expression in the pituitary gland and colon. Fischer 344 male rats fed with cafeteria diet (CAF) were housed under different photoperiods for 9 weeks and treated with an antibiotic cocktail (ABX) in drinking water during the last 4 weeks. Rats fed with standard chow and CAF-fed rats without ABX were included as controls. ABX altered gut microbiota, corticosterone levels and seasonal clock expression in the pituitary depending on photoperiod conditions. These results suggest a link between gut bacteria, seasonal rhythms and corticosterone and a novel nutrigenomic target for obesity.

Abstract Image segmentation of the liver is an important step in treatment planning for liver cancer. However, manual segmentation at a large scale is not practical, leading to increasing reliance on deep learning models to automatically segment the liver. This manuscript develops a generalizable deep learning model to segment the liver on T1-weighted MR images. In particular, three distinct deep learning architectures (nnUNet, PocketNet, Swin UNETR) were considered using data gathered from six geographically different institutions. A total of 819 T1-weighted MR images were gathered from both public and internal sources. Our experiments compared each architecture’s testing performance when trained both intra-institutionally and inter-institutionally. Models trained using nnUNet and its PocketNet variant achieved mean Dice-Sorensen similarity coefficients>0.9 on both intra- and inter-institutional test set data. The performance of these models suggests that nnUNet and PocketNet liver segmentation models trained on a large and diverse collection of T1-weighted MR images would on average achieve good intra-institutional segmentation performance.

Abstract The addition of ground heat exchangers (GHEs) to a pit lake’s basin has the potential for abundant, clean and renewable geothermal energy extraction using shallow geothermal systems. Basin-embedded GHEs avoid direct interaction with mine water, which has been shown to impact efficiency and longevity in mine open-loop geothermal systems negatively. The now accelerated closure of open-pit coal mines presents itself as an opportunity to use this technology. However, no guidelines currently exist for designing or operating GHEs embedded in the sediment of water bodies. Furthermore, the two-way coupling between the complex annual thermal fluid dynamics that lakes are naturally subjected to and heat fluxes on the sediments and the GHE system has not been explored. In this study, we develop and validate finite element models to assess the relevance of lake thermal stratification in the performance of a geothermal system embedded in water bodies basins, e.g., on open-pit mine closures, under temperate residential thermal loads. The results show that the pit lake’s role as a thermal sink improves significantly when the lake’s thermal dynamics are accounted for, with an increase of up to 292% in the lake’s available energy budget. A minor variation in energy budget (~8%) was found whether the lake is modelled explicitly or simplified as a transient Dirichlet temperature boundary condition. This small difference vanishes if horizontal circulation along the lake is considered, highlighting the lake’s thermal energy potential. Finally, the impact on the GHE Coefficient of Performance (COP) is evaluated, with a maximum of ~15% difference among all cases.

Abstract Plant diseases pose significant threats to agriculture, impacting both food safety and public health. Traditional plant disease detection systems are typically limited to recognizing disease categories included in the training dataset, rendering them ineffective against new disease types. Although out-of-distribution (OOD) detection methods have been proposed to address this issue, the impact of fine-tuning paradigms on these methods has been overlooked. This paper focuses on studying the impact of fine-tuning paradigms on the performance of detecting unknown plant diseases. Currently, fine-tuning on visual tasks is mainly divided into visual-based models and visual-language-based models. We first discuss the limitations of large-scale visual language models in this task: textual prompts are difficult to design. To avoid the side effects of textual prompts, we futher explore the effectiveness of purely visual pre-trained models for OOD detection in plant disease tasks. Specifically, we employed five publicly accessible datasets to establish benchmarks for open-set recognition, OOD detection, and few-shot learning in plant disease recognition. Additionally, we comprehensively compared various OOD detection methods, fine-tuning paradigms, and factors affecting OOD detection performance, such as sample quantity. The results show that visual prompt tuning outperforms fully fine-tuning and linear probe tuning in out-of-distribution detection performance, especially in the few-shot scenarios. Notably, the max-logit-based on visual prompt tuning achieves an AUROC score of 94.8 $$\%$$ % in the 8-shot setting, which is nearly comparable to the method of fully fine-tuning on the full dataset (95.2 $$\%$$ % ), which implies that an appropriate fine-tuning paradigm can directly improve OOD detection performance. Finally, we visualized the prediction distributions of different OOD detection methods and discussed the selection of thresholds. Overall, this work lays the foundation for unknown plant disease recognition, providing strong support for the security and reliability of plant disease recognition systems. We will release our code at https://github.com/JiuqingDong/PDOOD to further advance this field.

Abstract Monometallic and bimetallic Cu:Ni catalysts with different Cu:Ni molar ratios (3:1, 2:1, 1:1, 1:2, 1:3) were synthesized by wetness impregnation on activated carbon and characterized by TPR (temperature programmed reduction), XRD (X-ray diffraction) and XPS (X-ray photoelectron spectroscopy). The synthesized catalysts were evaluated in the gas phase production of diethyl carbonate from ethanol and carbon dioxide. The largest catalytic activity was obtained over the bimetallic catalyst with a Cu:Ni molar ratio of 3:1. Its improved activity was attributed to the formation of a Cu–Ni alloy on the surface of the catalyst, evidenced by XPS and in agreement with a previous assignment based on Vegard law and TPR analysis. During the reaction rate experiments, it observed the presence of a maximum of the reaction rate as a function of temperature, a tendency also reported for other carbon dioxide–alcohol reactions. It showed that the reaction rate-temperature data can be adjusted with a reversible rate equation. The initial rate as a function of reactant partial pressure data was satisfactorily adjusted using the forward power law rate equation and it was found that the reaction rate is first order in CO2 and second order in ethanol.

Abstract Freshwater fishes are among the most threatened taxa worldwide owing to changes in land use, species introductions, and climate change. Although more than half of the freshwater fishes in the Chilean Mediterranean ecoregion are considered vulnerable or endangered, still little is known about their biogeography. Fishes of the family Perciliidae are endemic of this region and ideal cases to study potential implications of global warming given their endangered conservation status, small size, restricted range, and limited dispersal capacity in fragmented habitats. Here, we model the spatial distribution of habitats for Percilia irwini and P. gillissi under current (1970–2000) and future (2050–2080) climatic scenarios (SSP245, SSP585). We implement maximum entropy (MaxEnt) models adapted for stream networks using high-resolution datasets of selected geophysical and climatic variables. At present, both species inhabit relatively low-quality habitats. In the future (SSP585), suitable habitats for P. irwini are predicted to be reduced drastically (99%) with potential local extirpations in its northern range. Similarly, up to 62% of suitable habitats for P. gillissi would also be reduced in the future. Our study provides insights about assessing future threats and vulnerability of endemic, endangered, range-restricted, and small-bodied freshwater species in this region and elsewhere.

Abstract Pitseed goosefoot (Chenopodium berlandieri) is a free-living North American member of an allotetraploid complex that includes the Andean pseudocereal quinoa (C. quinoa). Like quinoa, pitseed goosefoot was domesticated, possibly independently, in eastern North America (subsp. jonesianum) and Mesoamerica (subsp. nuttaliae). To test the utility of C. berlandieri as a resource for quinoa breeding, we produced the whole-genome DNA sequence of PI 433,231, a huauzontle from Puebla, México. The 1.295 Gb genome was assembled into 18 pseudomolecules and annotated using RNAseq data from multiple tissues. Alignment with the v.2.0 genome of Chilean-origin C. quinoa cv. ‘QQ74’ revealed several inversions and a 4A-6B reciprocal translocation. Despite these rearrangements, some quinoa x pitseed goosefoot crosses produce highly fertile hybrids with faithful recombination, as evidenced by a high-density SNP linkage map constructed from a Bolivian quinoa ‘Real-1’ × BYU 937 (Texas coastal pitseed goosefoot) F2 population. Recombination in that cross was comparable to a ‘Real-1’ × BYU 1101 (Argentine C. hircinum) F2 population. Furthermore, SNP-based phylogenetic and population structure analyses of 90 accessions supported the hypothesis of multiple independent domestications and descent from a common 4 × ancestor, with a likely North American Center of Origin.

Abstract Migration of nib Cd to the testa during fermentation can be achieved with high temperatures (> 45 °C) and low nib pH values ( nib Cd) from the fourth day. Cd migration could increase by extensive fermentation until the sixth day in high temperatures and probably by the adsorbent capacity of the testa. Genotype-by-treatment interactions were present for the nib Cd reduction, and a universal percentage of decrease of Cd for each genotype with fermentation cannot be expected. Selecting genotypes with highly adsorbent testa combined with controlled temperatures would help reduce the Cd concentration in the cacao raw material, improving its safety and quality.

Abstract Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of tumors that exhibit an unpredictable and broad spectrum of clinical presentations and biological aggressiveness. Surgical resection is still the only curative therapeutic option for localized PanNET, but the majority of patients are diagnosed at an advanced and metastatic stage with limited therapeutic options. Key factors limiting the development of new therapeutics are the extensive heterogeneity of PanNETs and the lack of appropriate clinically relevant models. In that context, genomic sequencing of human PanNETs revealed recurrent mutations and structural alterations in several tumor suppressors. Here, we demonstrated that combined loss of MEN1, ATRX, and PTEN, tumor suppressors commonly mutated in human PanNETs, triggers the development of high-grade pancreatic neuroendocrine tumors in mice. Histopathological evaluation and gene expression analyses of the developed tumors confirm the presence of PanNET hallmarks and significant overlap in gene expression patterns found in human disease. Thus, we postulate that the presented novel genetically defined mouse model is the first clinically relevant immunocompetent high-grade PanNET mouse model.

Abstract As the human–primate interface expands, many nonhuman primate (NHP) populations exploit anthropogenic foods to survive, while some populations opportunistically target them. Though anthropogenic food consumption is sometimes associated with greater reproductive output and survival in these populations, there is a dearth of research on possible health effects. We explore how differential exposure to anthropogenic foods is linked to variation in isotopic compositions (δ13C and δ15N) and body weights in Barbary macaques (Macaca sylvanus) in the Upper Rock Nature Reserve, Gibraltar. We placed monkeys into three categories based on anthropogenic food exposure. We then analyzed individuals for isotopic signatures (N = 147) and body weight measurements (N = 80). Using the lowest exposure category as the comparison, we found body weights and δ15N values, but not δ13C values, significantly differed across key categories. Within categories, we found no significant associations between sex and δ13C or δ15N values, suggesting that individuals within categories consumed similar foods regardless of sex. We found a significant interaction effect between category and sex for predicting body weights. These results suggest that sex plays a role in how anthropogenic foods are accessed and consumed regardless of exposure, which may result in differential health profiles for female and male macaques.

Abstract Chagas disease is a leading cause of non-ischemic cardiomyopathy in endemic regions of Central and South America. In Belize, Triatoma dimidiata sensu lato has been identified as the predominate taxon but vectorial transmission of Chagas disease is considered to be rare in the country. We recently identified an acute case of vector-borne Chagas disease in the northern region of Belize. Here we present a subsequent investigation of triatomines collected around the case-patient’s home. We identified yet undescribed species, closely related to Triatoma huehuetenanguensis vector by molecular systematics methods occurring in the peridomestic environment. The identification of a T. cruzi-positive, novel species of Triatoma in Belize indicates an increased risk of transmission to humans in the region and warrants expanded surveillance and further investigation.

Abstract Species’ ecological niches are frequently analysed to gain insights into how anthropogenic changes affect biodiversity. Coping with these changes often involves shifts in niche expression, which can disrupt local biotic interactions. Secondary contact zones, where competition and ecological segregation commonly occur, are ideal for studying the ecological factors influencing species’ niches. In this study, we investigated the effect of climate and landscape factors on the ecological niches of two viper species, Vipera aspis and Vipera latastei, across three contact zones in northern Iberia, characterized by varying levels of landscape alteration. Using niche overlap tests, ecological niche models and spatial analyses we observed local variation in the expression of the species’ niches across the three contact zones, resulting from the different abiotic and biotic conditions of each area. Rather than spatial niche segregation, we observed high niche overlap, suggesting niche convergence. A pattern of asymmetrical niche variation was identified in all contact zones, driven by species' climatic tolerances and the environmental conditions of each area. V. aspis generally exhibited a wider niche, except in the southernmost zone where the pure Mediterranean climate favored V. latastei. Human-induced landscape changes intensified niche asymmetry, by favoring the most generalist V. aspis over the specialist V. latastei, increasing habitat overlap, and likely competition. This study presents a comprehensive analysis of niche expression at range margins, anticipating a heightened impact of landscape changes in V. latastei. The methodological framework implemented here, and our findings, hold significant relevance for biodiversity management and conservation in human-impacted areas.

Abstract A key parameter of interest recovered from hyperpolarized (HP) MRI measurements is the apparent pyruvate-to-lactate exchange rate, $$k_{{\textrm PL}}$$ k P L , for measuring tumor metabolism. This manuscript presents an information-theory-based optimal experimental design approach that minimizes the uncertainty in the rate parameter, $$k_{{\textrm PL}}$$ k P L , recovered from HP-MRI measurements. Mutual information is employed to measure the information content of the HP measurements with respect to the first-order exchange kinetics of the pyruvate conversion to lactate. Flip angles of the pulse sequence acquisition are optimized with respect to the mutual information. A time-varying flip angle scheme leads to a higher parameter optimization that can further improve the quantitative value of mutual information over a constant flip angle scheme. However, the constant flip angle scheme, 35 and 28 degrees for pyruvate and lactate measurements, leads to an accuracy and precision comparable to the variable flip angle schemes obtained from our method. Combining the comparable performance and practical implementation, optimized pyruvate and lactate flip angles of 35 and 28 degrees, respectively, are recommended.

Abstract The creation of artistic images through the use of Artificial Intelligence is an area that has been gaining interest in recent years. In particular, the ability of Neural Networks to separate and subsequently recombine the style of different images, generating a new artistic image with the desired style, has been a source of study and attraction for the academic and industrial community. This work addresses the challenge of generating artistic images that are framed in the style of pictorial Impressionism and, specifically, that imitate the style of one of its greatest exponents, the painter Claude Monet. After having analysed several theoretical approaches, the Cycle Generative Adversarial Networks are chosen as base model. From this point, a new training methodology which has not been applied to cyclical systems so far, the top-k approach, is implemented. The proposed system is characterised by using in each iteration of the training those k images that, in the previous iteration, have been able to better imitate the artist’s style. To evaluate the performance of the proposed methods, the results obtained with both methodologies, basic and top-k, have been analysed from both a quantitative and qualitative perspective. Both evaluation methods demonstrate that the proposed top-k approach recreates the author’s style in a more successful manner and, at the same time, also demonstrate the ability of Artificial Intelligence to generate something as creative as impressionist paintings.

Abstract There is a consensus about the strong correlation between the elasticity of cells and tissue and their normal, dysplastic, and cancerous states. However, developments in cell mechanics have not seen significant progress in clinical applications. In this work, we explore the possibility of using phonon acoustics for this purpose. We used phonon microscopy to obtain a measure of the elastic properties between cancerous and normal breast cells. Utilising the raw time-resolved phonon-derived data (300 k individual inputs), we employed a deep learning technique to differentiate between MDA-MB-231 and MCF10a cell lines. We achieved a 93% accuracy using a single phonon measurement in a volume of approximately 2.5 μm3. We also investigated means for classification based on a physical model that suggest the presence of unidentified mechanical markers. We have successfully created a compact sensor design as a proof of principle, demonstrating its compatibility for use with needles and endoscopes, opening up exciting possibilities for future applications.

Abstract Nitroso-compounds are potentially mutagenic and carcinogenic compounds due to their ability to alkylate DNA bases. One of the most common sources of human exposure to nitroso-compounds is their formation in the acidic environment of the stomach by the reaction between electron-rich molecules present in the lumen and sodium nitrite ingested in the diet. To date, the formation of nitroso-compounds by the reaction of nitrite with food components has been investigated in depth, but little attention has been paid to substances secreted in the stomach, such as dopamine or serotonin, whose reaction products with nitrite have proven mutagenic properties. In this article, we present a kinetic study with UV–visible spectroscopy of the nitrosation reactions of both molecules, as well as of L-tyrosine, the amino-acid precursor of dopamine. We determined the kinetic parameters and reaction mechanisms for the reactions, studying the influence of the reactants concentration, pH, temperature, and ionic strength on the reaction rate. In all cases, the favoured reaction product was a stable nitroso-compound. Serotonin, the molecule whose product was the most mutagenic, underwent two consecutive nitrosation reactions. These findings suggest that additional biological research is needed to understand how this reaction alters the function of these neurotransmitters as well as the potentially toxic effects they may have once nitrosated.

Abstract Atmospheric longwave downward radiation (L d) is one of the significant components of net radiation (Rn), and it drives several essential ecosystem processes. L d can be estimated with simple empirical methods using atmospheric emissivity (εa) submodels. In this study, eight global models for εa were evaluated, and the best-performing model was calibrated on a global scale using a parametric instability analysis approach. The climatic data were obtained from a dynamically consistent scale resolution of basic atmospheric quantities and computed parameters known as NCEP/NCAR reanalysis (NNR) data. The performance model was evaluated with monthly average values from the NNR data. The Brutsaert equation demonstrated the best performance, and then it was calibrated. The seasonal global trend of the Brutsaert equation calibrated coefficient ranged between 1.2 and 1.4, and the K-means analysis identified five homogeneous zones (clusters) with similar behavior. Finally, the calibrated Brutsaert equation improved the Rn estimation, with an error reduction, at the worldwide scale, of 64%. Meanwhile, the error reduction for each cluster ranged from 18 to 77%. Hence, Brutsaert’s equation coefficient should not be considered a constant value for use in εa estimation, nor in time or location.

Abstract The electronic prescription refill rate (EPRR) of 183 consecutive patients was determined over a 19-month retrospective study period, divided into 7 months PRE (Sep-19 to Mar-20) and 12 months POST pandemic (Apr-20 to Mar-21), in order to compare adherence to inhaled corticosteroids (ICS) in patients with asthma prior to and during the COVID-19 pandemic. Before the pandemic (PRE), an average of 0.58 inhalers/month were refill from the pharmacy; [SD 0.33], very similar to the 0.59 inhalers/month; [SD 0.34] retrieved during the 12 subsequent months since the pandemic (POST) (p = 0.768). EPRR showed no differences (p = 0.784). When EPRR was dichotomous or ordinal categorised no differences were found either (p = 0.851 and 0.928), even when McNemar's test was used (p = 0.949), with prevalences of nonadherence (EPRR

Abstract Animal venoms are rich sources of neuroactive compounds, including anti-inflammatory, antiepileptic, and antinociceptive molecules. Our study identified a protonectin peptide from the wasp Parachartergus fraternus' venom using mass spectrometry and cDNA library construction. Using this peptide as a template, we designed a new peptide, protonectin-F, which exhibited higher antinociceptive activity and less motor impairment compared to protonectin. In drug interaction experiments with naloxone and AM251, Protonectin-F's activity was decreased by opioid and cannabinoid antagonism, two critical antinociception pathways. Further experiments revealed that this effect is most likely not induced by direct action on receptors but by activation of the descending pain control pathway. We noted that protonectin-F induced less tolerance in mice after repeated administration than morphine. Protonectin-F was also able to decrease TNF-α production in vitro and modulate the inflammatory response, which can further contribute to its antinociceptive activity. These findings suggest that protonectin-F may be a potential molecule for developing drugs to treat pain disorders with fewer adverse effects. Our results reinforce the biotechnological importance of animal venom for developing new molecules of clinical interest.