The Interactive Effects of the Anti-Sea Lice Pesticide Azamethiphos and Temperature on Oxidative Damage and Antioxidant Responses in the Oyster Ostrea chilensis.

Azamethiphos is used in the salmon industry to treat sea lice and is subsequently discharged into the sea, which may affect non-target species (NTS). A rise in seawater temperature could enhance the sensitivity of NTS. Thus, in the present investigation, the combined effects of azamethiphos (0 µg L-1, 15 µg L-1 and 100 µg L-1) and temperature (12 °C and 15 °C) was assessed over time (7 days) in the gonads and gills of the oyster Ostrea chilensis, assessing its oxidative damage (lipid peroxidation and protein carbonyls) and total antioxidant capacity. Our results indicated that in gonads and gills, lipid peroxidation levels increased over time during exposure to both pesticide concentrations. Protein carbonyl levels in gills increased significantly in all experimental treatments; however, in gonads, only pesticide concentration and exposure time effected a significant increase in protein damage. In both, gill and gonad temperature did not influence oxidative damage levels. Total antioxidant capacity in gonads was influenced only by temperature treatment, whereas in the gills, neither temperature nor azamethiphos concentration influenced defensive responses. In conclusion, our results indicated the time of pesticide exposure (both concentrations) had a greater influence than temperature on the cellular damage in this oyster.

Design and Biocompatibility of Biodegradable Poly(octamethylene suberate) Nanoparticles to Treat Skin Diseases.

Biodegradable aliphatic polyester formulations as carriers for topical drug delivery show the potential to encapsulate structurally different therapeutic compounds. Poly(octamethylene suberate) (POS) nanoparticles (POS-NPs) were used as a matrix to encapsulate four therapeutic molecules used to treat skin disorders: caffeine (CF), quercetin (QR), hydrocortisone (HC), and adapalene (AD). Hydrophobicity and chemical structure of bioactive compounds (BCs) influenced the physicochemical stability of drug-loaded nanoparticles. The particle size of drug-loaded nanoparticles was between 254.9 nm for the CF-POS-NP and 1291.3 for QR-POS-NP. Particles had a negative charge from -27.6 mV (QR) to -49.2 mV (HC). Drug loading content for all BC-POS-NPs varies between 36.11 ± 1.48% (CF-POS-NP) and 66.66 ± 4.87% (AD-POS-NP), and their entrapment efficiency is relatively high (28.30 ± 1.81% and 99.95 ± 0.04%, respectively). Calorimetric analysis showed the appearance of polymorphism for AD- and HC-loaded systems and the drug's complete solubilisation into all nanoparticle formulations. FTIR and NMR spectra showed apparent drug incorporation into the polymer matrix of NPs. The encapsulation of BCs enhanced the antioxidative effect. The prepared POS nanoparticles' cytotoxicity was studied using two dermal cell lines, keratinocyte (HaCaT) cells and fibroblasts (HDFn). The nanoparticle cytotoxic effect was more substantial on HaCaT cell lines. A reconstructed human epidermis (RHE) was successfully used to investigate the penetration of polymeric NPs. Based on permeation and histology studies, HC-POS-NPs and CF-POS-NPs were shown not to be suitable for dermal applications with the explored drug concentrations. AD presents a high permeation rate and no toxic impact on RHE.

Photoacoustic processing of decellularized extracellular matrix for biofabricating living constructs.

The diverse biomolecular landscape of tissue-specific decellularized extracellular matrix (dECM) biomaterials provides a multiplicity of bioinstructive cues to target cells, rendering them highly valuable for various biomedical applications. However, the isolation of dECM biomaterials entails cumbersome xenogeneic enzymatic digestions and also additional inactivation procedures. Such, increases processing time, increments costs and introduces residues of non-naturally present proteins in dECM formulations that remain present even after inactivation. To overcome these limitations, herein we report an innovative conjugation of light and ultrasound-mediated dECM biomaterial processing for fabricating dECM biomaterials. Such approach gathers on ultrasound waves to facilitate dECM-in-liquid processing and visible light photocrosslinking of tyrosine residues naturally present in dECM biomaterials. This dual step methodology unlocked the in-air production of cell laden dECM hydrogels or programmable dECM hydrogel spherical-like beads by using superhydrophobic surfaces. These in-air produced units do not require any additional solvents and successfully supported both fibroblasts and breast cancer cells viability upon encapsulation or surface seeding. In addition, the optimized photoacoustic methodology also enabled a rapid formulation of dECM biomaterial inks with suitable features for biofabricating volumetrically defined living constructs through embedded 3D bioprinting. The biofabricated dECM hydrogel constructs supported cell adhesion, spreading and viability for 7 days. Overall, the implemented photoacoustic processing methodology of dECM biomaterials offers a rapid and universal strategy for upgrading their processing from virtually any tissue. STATEMENT OF SIGNIFICANCE: Leveraging decellularized extracellular matrix (dECM) as cell instructive biomaterials has potential to open new avenues for tissue engineering and in vitro disease modelling. The processing of dECM remains however, lengthy, costly and introduces non-naturally present proteins in the final biomaterials formulations. In this regard, here we report an innovative light and ultrasound two-step methodology that enables rapid dECM-in-liquid processing and downstream photocrosslinking of dECM hydrogel beads and 3D bioprinted constructs. Such photoacoustic based processing constitutes a universally applicable method for processing any type of tissue-derived dECM biomaterials.

A Scoping Review to Contribute to Knowledge About Culturally Adapting Interventions for Latino Family Caregivers of Persons Living With Dementia.

INTRODUCTION: Few interventions have focused on Latino family caregivers to persons with dementia, addressing their unique needs. This review aimed to identify best practices in cultural adaptation to make recommendations for adapting interventions for Latino family caregivers of persons living with dementia. METHOD: This scoping review was conducted following the Joanna Briggs Institute Scoping Review guidelines, with findings extracted and summarized from 17 studies addressing cultural adaptation. RESULTS: Frameworks guiding the adaptations were comprehensive, addressing cultural values and traditions and the social context faced by Latino family caregivers. Features of the adaptations included diverse teams of researchers and community members, including Latino family caregivers, to inform the integration of cultural values into the content, mode, and place of intervention delivery. DISCUSSION: Culturally adapting evidence-based interventions will increase the number of available interventions for Latino family caregivers to persons living with dementia, thus reducing inequities in caregiver support.

Rapid DNA methylation-based classification of pediatric brain tumors from ultrasonic aspirate specimens.

BACKGROUND: Although cavitating ultrasonic aspirators are commonly used in neurosurgical procedures, the suitability of ultrasonic aspirator-derived tumor material for diagnostic procedures is still controversial. Here, we explore the feasibility of using ultrasonic aspirator-resected tumor tissue to classify otherwise discarded sample material by fast DNA methylation-based analysis using low pass nanopore whole genome sequencing. METHODS: Ultrasonic aspirator-derived specimens from pediatric patients undergoing brain tumor resection were subjected to low-pass nanopore whole genome sequencing. DNA methylation-based classification using a neural network classifier and copy number variation analysis were performed. Tumor purity was estimated from copy number profiles. Results were compared to microarray (EPIC)-based routine neuropathological histomorphological and molecular evaluation. RESULTS: 19 samples with confirmed neuropathological diagnosis were evaluated. All samples were successfully sequenced and passed quality control for further analysis. DNA and sequencing characteristics from ultrasonic aspirator-derived specimens were comparable to routinely processed tumor tissue. Classification of both methods was concordant regarding methylation class in 17/19 (89%) cases. Application of a platform-specific threshold for nanopore-based classification ensured a specificity of 100%, whereas sensitivity was 79%. Copy number variation profiles were generated for all cases and matched EPIC results in 18/19 (95%) samples, even allowing the identification of diagnostically or therapeutically relevant genomic alterations. CONCLUSION: Methylation-based classification of pediatric CNS tumors based on ultrasonic aspirator-reduced and otherwise discarded tissue is feasible using time- and cost-efficient nanopore sequencing.

Development of a Novel HS-GC/MS Method Using the Total Ion Spectra Combined with Machine Learning for the Intelligent and Automatic Evaluation of Food-Grade Paraffin Wax Odor Level.

The intensity of the odor in food-grade paraffin waxes is a pivotal quality characteristic, with odor panel ratings currently serving as the primary criterion for its assessment. This study presents an innovative method for assessing odor intensity in food-grade paraffin waxes, employing headspace gas chromatography with mass spectrometry (HS/GC-MS) and integrating total ion spectra with advanced machine learning (ML) algorithms for enhanced detection and quantification. Optimization was conducted using Box-Behnken design and response surface methodology, ensuring precision with coefficients of variance below 9%. Analytical techniques, including hierarchical cluster analysis (HCA) and principal component analysis (PCA), efficiently categorized samples by odor intensity. The Gaussian support vector machine (SVM), random forest, partial least squares regression, and support vector regression (SVR) algorithms were evaluated for their efficacy in odor grade classification and quantification. Gaussian SVM emerged as superior in classification tasks, achieving 100% accuracy, while Gaussian SVR excelled in quantifying odor levels, with a coefficient of determination (R2) of 0.9667 and a root mean square error (RMSE) of 6.789. This approach offers a fast, reliable, robust, objective, and reproducible alternative to the current ASTM sensory panel assessments, leveraging the analytical capabilities of HS-GC/MS and the predictive power of ML for quality control in the petrochemical sector's food-grade paraffin waxes.

Evolution of tissue-specific expression of ancestral genes across vertebrates and insects.

Regulation of gene expression is arguably the main mechanism underlying the phenotypic diversity of tissues within and between species. Here we assembled an extensive transcriptomic dataset covering 8 tissues across 20 bilaterian species and performed analyses using a symmetric phylogeny that allowed the combined and parallel investigation of gene expression evolution between vertebrates and insects. We specifically focused on widely conserved ancestral genes, identifying strong cores of pan-bilaterian tissue-specific genes and even larger groups that diverged to define vertebrate and insect tissues. Systematic inferences of tissue-specificity gains and losses show that nearly half of all ancestral genes have been recruited into tissue-specific transcriptomes. This occurred during both ancient and, especially, recent bilaterian evolution, with several gains being associated with the emergence of unique phenotypes (for example, novel cell types). Such pervasive evolution of tissue specificity was linked to gene duplication coupled with expression specialization of one of the copies, revealing an unappreciated prolonged effect of whole-genome duplications on recent vertebrate evolution.

In-Bath 3D Printing of Anisotropic Shape-Memory Cryogels Functionalized with Bone-Bioactive Nanoparticles.

Cryogels exhibit unique shape memory with full recovery and structural stability features after multiple injections. These constructs also possess enhanced cell permeability and nutrient diffusion when compared to typical bulk hydrogels. Volumetric processing of cryogels functionalized with nanosized units has potential to widen their biomedical applications, however this has remained challenging and relatively underexplored. In this study, we report a novel methodology that combines suspension 3D printing with directional freezing for the fabrication of nanocomposite cryogels with configurable anisotropy. When compared to conventional bulk or freeze-dried hydrogels, nanocomposite cryogel formulations exhibit excellent shape recovery (>95%) and higher pore connectivity. Suspension printing, assisted with a prechilled metal grid, was optimized to induce anisotropy. The addition of calcium- and phosphate-doped mesoporous silica nanoparticles into the cryogel matrix enhanced bioactivity toward orthopedic applications without hindering the printing process. Notably, the nanocomposite 3D printed cryogels exhibit injectable shape memory while also featuring a lamellar topography. The fabrication of these constructs was highly reproducible and exhibited potential for a cell-delivery injectable cryogel with no cytotoxicity to human-derived adipose stem cells. Hence, in this work, it was possible to combine a gravity defying 3D printed methodology with injectable and controlled anisotropic macroporous structures containing bioactive nanoparticles. This methodology ameliorates highly tunable injectable 3D printed anisotropic nanocomposite cryogels with a user-programmable degree of structural complexity.

Dietary metabarcoding reveals the simplification of bird-pest interaction networks across a gradient of agricultural cover.

Agriculture is vital for supporting human populations, but its intensification often leads to landscape homogenization and a decline in non-provisioning ecosystem services. Ecological intensification and multifunctional landscapes are suggested as nature-based alternatives to intensive agriculture, using ecological processes like natural pest regulation to maximize food production. Birds are recognized for their role in increasing crop yields by consuming invertebrate pests in several agroecosystems. However, the understanding of how bird species, their traits and agricultural land cover influence the structure of bird-pest interactions remains limited. We sampled bird-pest interactions monthly for 1 year, at four sites within a multifunctional landscape, following a gradient of increasing agricultural land cover. We analysed 2583 droppings of 55 bird species with DNA metabarcoding and detected 225 pest species in 1139 samples of 42 bird species. As expected, bird-pest interactions were highly variable across bird species. Dietary pest richness was lower in the fully agricultural site, while predation frequency remained consistent across the agricultural land cover gradient. Network analysis revealed a reduction in the complexity of bird-pest interactions as agricultural coverage increased. Bird species abundance affected the bird's contribution to the network structure more than any of the bird traits analysed (weight, phenology, invertebrate frequency in diet and foraging strata), with more common birds being more important to network structure. Overall, our results show that increasing agricultural land cover increases the homogenization of bird-pest interactions. This shows the importance of maintaining natural patches within agricultural landscapes for biodiversity conservation and enhanced biocontrol.

A agricultura é essencial para suportar a população humana, mas a sua intensificação geralmente leva à homogeneização da paisagem e à redução dos serviços do ecossistema que não sejam de provisão. A intensificação ecológica e paisagens multifuncionais são sugeridas como alternativas naturais à agricultura intensiva, utilizando processos ecológicos como a regulação natural de pragas para maximizar a produção de alimentos. As aves são conhecidas pelo seu papel no aumento da produtividade das culturas por consumirem pragas em diversos agroecossistemas. Contudo, o conhecimento de como as espécies de aves, as suas características e a cobertura agrícola influenciam as interações entre aves e pragas são limitados. Nós amostrámos estas interações mensalmente durante um ano, em quatro locais, numa paisagem multifuncional, ao longo um gradiente de aumento da cobertura agrícola. Analisamos 2583 dejetos de 55 espécies de aves com DNA metabarcoding e detetamos 225 espécies praga em 1139 amostras de 42 espécies de aves. Como esperado, as interações entre aves e pragas foram muito distintas entre as várias espécies de aves. A riqueza de pragas na dieta foi menor no local completamente dominado por área agrícola, enquanto a frequência de predação de pragas foi constante ao longo do gradiente de cobertura agrícola. A análise de redes demonstrou uma redução na complexidade das interações entre aves e pragas à medida que a cobertura agrícola aumenta. A abundância das espécies de aves influenciou mais a contribuição das aves para a estrutura da rede do que qualquer uma das características analisadas (peso, fenologia, frequência de invertebrados na dieta e estrato de alimentação), sendo as aves mais comuns as mais importantes na estrutura da rede. De forma geral, os nossos resultados indicam que o aumento da cobertura agrícola aumenta a homogeneização das interações entre aves e pragas. Isto demonstra a importância de preservar áreas naturais em paisagem agrícolas para a conservação de biodiversidade e melhor controlo biológico.

FTIR Spectroscopy and Blood-Derived Extracellular Vesicles Duo in Alzheimer's Disease.

Background: Alzheimer's disease (AD) diagnosis is difficult, and new accurate tools based on peripheral biofluids are urgently needed. Extracellular vesicles (EVs) emerged as a valuable source of biomarker profiles for AD, since their cargo is disease-specific and these can be easily isolated from easily accessible biofluids, as blood. Fourier Transform Infrared (FTIR) spectroscopy can be employed to analyze EVs and obtain the spectroscopic profiles from different regions of the spectra, simultaneously characterizing carbohydrates, nucleic acids, proteins, and lipids. Objective: The aim of this study was to identify blood-derived EVs (bdEVs) spectroscopic signatures with AD discriminatory potential. Methods: Herein, FTIR spectra of bdEVs from two biofluids (serum and plasma) and distinct sets of Controls and AD cases were acquired, and EVs' spectra analyzed. Results: Analysis of bdEVs second derivative peaks area revealed differences between Controls and AD cases in distinct spectra regions, assigned to carbohydrates and nucleic acids, amides, and lipids. Conclusions: EVs' spectroscopic profiles presented AD discriminatory value, supporting the use of bdEVs combined with FTIR as a screening or complementary tool for AD diagnosis.

A school-based physical activity intervention in primary school: effects on physical activity, sleep, aerobic fitness, and motor competence.

Objective: The "Super Quinas" project evaluated the effectiveness of an intervention program to improve physical activity, aerobic fitness, sleep, and motor competence on children in primary school. Methods: The experimental group (n = 19) enrolled in a 12-week intervention program (one more extra-curricular activity class of 60 min per week) compared to the CG (n = 19), all aged 9-10 years. Physical activity (PA) and sleep were measured by accelerometry, and aerobic fitness was measured by Children's Yo-Yo test (YYIR1C) during the 1st week (PRE), the 6th week (DUR), and the 12th week (POST) of the intervention program. Motor Competence in PRE and POST intervention was also assessed by the Motor Competence Assessment (MCA) instrument. Heart rate (HR, assessed using HR monitors), and enjoyment level were recorded during all intervention program classes. A linear mixed model analysis (i.e., within-subject analyses) was performed. Results: Comparing the EG and CG in DUR and POST, the EG spent ~18 min and ~ 34 min more time in moderate to vigorous physical activity (MVPA) per day (p < 0.001); had ~44 min and ~ 203 min less sedentary time per day (p < 0.001); performed more 44 and 128 m in the Children's Yo-Yo test compared to CG (p < 0.001) and slept more 17 and 114 min per night (p < 0.001). In POST motor competence was significantly better (27%) in the EG compared to CG (p < 0.001). The %HRmax during the extra-curricular classes ranged between 65 and 81% (i.e., light to moderate intensities), and the enjoyment between fun and great fun. Conclusion: Our findings suggest that adding one more extra-curricular activity class of 60 min per week for 12 weeks effectively increased the levels of physical activity, aerobic fitness, sleep duration, and motor competence in children aged 9-10 years.

Transient species driving ecosystem multifunctionality: Insights from competitive interactions between rocky intertidal mussels.

Anthropogenic biodiversity loss poses a significant threat to ecosystem functioning worldwide. Numerically dominant and locally rare (i.e., transient) species are key components of biodiversity, but their contribution to multiple ecosystem functions (i.e., multifunctionality) has been seldomly assessed in marine ecosystems. To fill this gap, here we analyze the effects of a dominant and a transient species on ecosystem multifunctionality. In an observational study conducted along ca. 200 km of the southeastern Pacific coast, the purple mussel Perumytilus purpuratus numerically dominated the mid-intertidal and the dwarf mussel Semimytilus patagonicus exhibited low abundances but higher recruitment rates. In laboratory experiments, the relative abundances of both species were manipulated to simulate the replacement of P. purpuratus by S. patagonicus and five proxies for ecosystem functions-rates of clearance, oxygen consumption, total biodeposit, organic biodeposit, and excretion-were analyzed. This replacement had a positive, linear, and significant effect on the combined ecosystem functions, particularly oxygen consumption and excretion rates. Accordingly, S. patagonicus could well drive ecosystem functioning given favorable environmental conditions for its recovery from rarity. Our study highlights therefore the key role of transient species for ecosystem performance. Improving our understanding of these dynamics is crucial for effective ecosystem conservation, especially in the current scenario of biological extinctions and invasions.

Ionome mapping and amino acid metabolome profiling of Phaseolus vulgaris L. seeds imbibed with computationally informed phytoengineered copper sulphide nanoparticles.

This study reports the effects of a computationally informed and avocado-seed mediated Phyto engineered CuS nanoparticles as fertilizing agent on the ionome and amino acid metabolome of Pinto bean seeds using both bench top and ion beam analytical techniques. Physico-chemical analysis of the Phyto engineered nanoparticles with scanning-electron microscopy, transmission electron microscopy, X-ray diffraction, and Fourier Transform Infrared Spectroscopy confirmed the presence of CuS nanoparticles. Molecular dynamics simulations to investigate the interaction of some active phytocompounds in avocado seeds that act as reducing agents with the nano-digenite further showed that 4-hydroxybenzoic acid had a higher affinity for interacting with the nanoparticle's surface than other active compounds. Seeds treated with the digenite nanoparticles exhibited a unique ionome distribution pattern as determined with external beam proton-induced X-ray emission, with hotspots of Cu and S appearing in the hilum and micropyle area that indicated a possible uptake mechanism via the seed coat. The nano-digenite also triggered a plant stress response by slightly altering seed amino acid metabolism. Ultimately, the nano-digenite may have important implications as a seed protective or nutritive agent as advised by its unique distribution pattern and effect on amino acid metabolism.

Machine learning-based approaches to Vis-NIR data for the automated characterization of petroleum wax blends.

Petroleum waxes are products derived from lubricating oils with a wide spectrum of industrial and consumer applications that depend on their composition. In addition, the intended applications of this product are also subject to the practice of blending petroleum waxes with different chemical characteristics (e.g., paraffin waxes and microwaxes) to achieve the appropriate physicochemical properties. This study introduces a novel method based on visible and near-infrared spectroscopy (Vis-NIR) combined with machine learning (ML) for the characterization of blends of the two types of commonly marketed petroleum waxes (paraffin waxes and microwaxes). With spectroscopic data, Partial Least Squared Regression (PLSR), Support Vector Regression (SVR), and Random Forest (RF) Regression-based regression ML models have been developed, obtaining satisfactory results for the characterization of the percentage of blending in petroleum waxes. Moreover, strategies using wrapper variable selection methods like the Boruta algorithm and Genetic Algorithm (GA) have been implemented to assess if fewer predictors enhance model performance. Particularly, the application of wrapper variable selection methods, specifically the Boruta algorithm, has led to an improvement in the performance of the models obtained. Results obtained by the Boruta-PLS model showed the best performance with an RMSE of 2.972 and an R2 of 0.9925 for the test set and an RMSE of 1.814 and an R2 of 0.9977 for the external validation set. Additionally, this model allowed for establishing the relative importance of the variables in the characterization of the waxes mixture, pointing out that the hydrocarbon content ratio is critical in the determination of this value. An interactive web application was developed using the best model developed for easy processing of the data by the users.

One-Step Purification of Recombinant Cutinase from an E. coli Extract Using a Stabilizing Triazine-Scaffolded Synthetic Affinity Ligand.

Cutinase from Fusarium solani pisi is an enzyme that bridges functional properties between lipases and esterases, with applications in detergents, food processing, and the synthesis of fine chemicals. The purification procedure of recombinant cutinase from E. coil extracts is a well-established but time-consuming process, which involves a sequence of two anionic exchange chromatography steps followed by dialysis. Affinity chromatography is the most efficient method for protein purification, the major limitation of its use being often the availability of a ligand selective for a given target protein. Synthetic affinity ligands that specifically recognize certain sites on the surface of proteins are highly desirable for affinity processes due to their cost-effectiveness, durability, and reusability across multiple cycles. Additionally, these ligands establish moderate affinity interactions with the target protein, making it possible to purify proteins under gentle conditions while maintaining high levels of activity recovery. This study aimed to develop a new method for purifying cutinase, utilizing triazine-scaffolded biomimetic affinity ligands. These ligands were previously screened from a biased-combinatorial library to ensure their binding ability to cutinase without compromising its biological function. A lead ligand, designated as 11/3', [4-({4-chloro-6-[(2-methylbutyl)amino]-1,3,5-triazin-2-yl}amino)benzoic acid], was chosen and directly synthesized onto agarose. Experiments conducted at different scales demonstrated that this ligand (with an affinity constant Ka ≈ 104 M-1) exhibited selectivity towards cutinase, enabling the purification of the enzyme from an E. coli crude production medium in a single step. Under optimized conditions, the protein and activity yields reached 25% and 90%, respectively, with a resulting cutinase purity of 85%.

Partnership in Cancer Research (PCAR) Program Increases Medical Student Knowledge and Confidence to Perform Cancer Research.

Arkansas has a high cancer burden, and a pressing need exists for more medical students to pursue oncology as a career. The Partnership in Cancer Research (PCAR) program provides a summer research experience at the University of Arkansas for Medical Sciences for 12 medical students who have completed their first year of medical training. A majority of participants spend time pursuing cancer research in basic science, clinical, or community-based research. Students report on their research progress in an interactive "Live from the Lab!" series and assemble a final poster presentation describing their findings. Other activities include participation in a moderated, cancer-patient support group online, lecture series on cancer topics, medical simulations, palliative care clinic visit, "Death Over Dinner" event, and an entrepreneurship competition. Students completed surveys over PCAR's first 2 years in operation to evaluate all aspects of the program. Surveys reveal that students enthusiastically embraced the program in its entirety. This was especially true of the medical simulations which received the highest evaluations. Most significantly, surveys revealed that the program increased cancer knowledge and participant confidence to perform cancer research.

GproteinDb in 2024: new G protein-GPCR couplings, AlphaFold2-multimer models and interface interactions.

G proteins are the major signal proteins of ∼800 receptors for medicines, hormones, neurotransmitters, tastants and odorants. GproteinDb offers integrated genomic, structural, and pharmacological data and tools for analysis, visualization and experiment design. Here, we present the first major update of GproteinDb greatly expanding its coupling data and structural templates, adding AlphaFold2 structure models of GPCR-G protein complexes and advancing the interactive analysis tools for their interfaces underlying coupling selectivity. We present insights on coupling agreement across datasets and parameters, including constitutive activity, agonist-induced activity and kinetics. GproteinDb is accessible at https://gproteindb.org.

DNA metabarcoding, diversity partitioning and null models reveal mechanisms of seasonal trophic specialization in a Mediterranean warbler.

Optimal Foraging Theory (OFT) predicts that a population's trophic niche expansion should occur in periods of food scarcity as individuals begin to opportunistically exploit sub-optimal food items. However, the Niche Variation Hypothesis (NVH) posits that niche widening may result from increased among-individual differentiation due to food partitioning to avoid competition. We tested these hypotheses through a DNA metabarcoding study of the Sardinian Warbler (Curruca melanocephala) diet over a year. We used null models and the decomposition of beta diversity on among-individual dietary differentiation to infer the mechanisms driving the population's niche variation. Warblers fed frequently on berries, with a peak in late summer and, to a lesser extent, in autumn. Their diet also included a wide range of arthropods, with their prevalence varying among seasons. Consistent with OFT, the population's niche width was narrower in spring/summer when the population was strongly specialized in berries. In winter, the population's niche expanded, possibly reflecting seasonal declines in food abundance. As predicted by NVH, among-individual differentiation tended to be higher in winter, but this was mainly due to increased differences in dietary richness rather than to the partitioning of resources. Overall, our results suggest that within-individual niche does not increase in lean periods, and instead, individuals adopt either a more opportunistic or more specialized foraging strategy. Increased competition in periods of scarcity may help explain such patterns, but instead of showing increased food partitioning as expected from NVH, it may reflect OFT mechanisms on individuals with differential competitive ability to access better food resources.

Driver mutations in GNAQ and GNA11 genes as potential targets for precision immunotherapy in uveal melanoma patients.

Uveal melanoma (UM) is the most common ocular malignancy in adults. Nearly 95% of UM patients carry the mutually exclusive mutations in the homologous genes GNAQ (amino acid change Q209L/Q209P) and GNA11 (aminoacid change Q209L). UM is located in an immunosuppressed organ and does not suffer immunoediting. Therefore, we hypothesize that driver mutations in GNAQ/11 genes could be recognized by the immune system. Genomic and transcriptomic data from primary uveal tumors were collected from the TCGA-UM dataset (n = 80) and used to assess the immunogenic potential for GNAQ/GNA11 Q209L/Q209P mutations using a variety of tools and HLA type information. All prediction tools showed stronger GNAQ/11 Q209L binding to HLA than GNAQ/11 Q209P. The immunogenicity analysis revealed that Q209L is likely to be presented by more than 73% of individuals in 1000 G databases whereas Q209P is only predicted to be presented in 24% of individuals. GNAQ/11 Q209L showed a higher likelihood to be presented by HLA-I molecules than almost all driver mutations analyzed. Finally, samples carrying Q209L had a higher immune-reactive phenotype. Regarding cancer risk, seven HLA genotypes with low Q209L affinity show higher frequency in uveal melanoma patients than in the general population. However, no clear association was found between any HLA genotype and survival. Results suggest a high potential immunogenicity of the GNAQ/11 Q209L variant that could allow the generation of novel therapeutic tools to treat UM like neoantigen vaccinations.