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Antiphospholipid syndrome (APS) is known as a rare etiology of embolic ischemic stroke. In individuals below 50 years, up to 20% of strokes are associated with APS, whereas in patients >50 years, it is considered a very seldom cause of stroke. We describe the course of a 66-year-old white woman, who experienced four embolic strokes with large vessel occlusion over a period of 2 years, which were repeatedly and successfully treated by mechanical thrombectomy. Initially attributed to atrial fibrillation and treated with direct oral anticoagulants, the patient was finally diagnosed with primary APS due to isolated anti-beta 2-glycoprotein antibodies and successfully treated after several stroke recurrences. After initiation of Vitamin K antagonist therapy, no further strokes occurred. For recurrent embolic stroke despite oral anticoagulation, late-onset APS might be considered a rare etiology also in the elderly.

This paper studies the complexity of classical modal logics and of their extension with fixed-point operators, using translations to transfer results across logics. In particular, we show several complexity results for multi-agent logics via translations to and from the $\mu$-calculus and modal logic, which allow us to transfer known upper and lower bounds. We also use these translations to introduce terminating and non-terminating tableau systems for the logics we study, based on Kozen's tableau for the $\mu$-calculus and the one of Fitting and Massacci for modal logic. Finally, we describe these tableaux with $\mu$-calculus formulas, thus reducing the satisfiability of each of these logics to the satisfiability of the $\mu$-calculus, resulting in a general 2EXP upper bound for satisfiability testing.

Blood cells play a fundamental role in maintaining systemic homeostasis, by responding dynamically to various physiological and environmental stimuli [...]

Abstract Polysaccharide coating is a biodegradable alternative to conventional packings used for delaying senescence in vegetables. This work investigated the properties of cassava and chitosan biopolymeric film and its use as edible coatings to preserve the shelf-life (7 °C and 70% relative humidity (RH)) of green asparagus, with previous cold storage (1 °C and 90% RH) for 7 days. Based on a previous assessment of the films obtained from a) cassava (2.5%), b) chitosan (0.5%), and c) a blend of cassava-chitosan (Cassava+) (2.5 + 0.5%), it could be verified that cassava-chitosan blend films showed improved barrier property (water vapor transmission rate (WVTR) of 38.06 g/(m2.h)) and mechanical properties, with tensile strength of 0.021 MPa, elongation at break of 1.93% and Young’s module of 0.011 MPa. Cassava+ based coating resulted in a lower weight loss and colour L* parameter and minimized textural changes in basal-section of commercial green asparagus spears during a shelf-life of seven days (7 °C and 70% RH), with previous cold storage. All coated spears maintained overall higher carbohydrate levels than the control, except to sucrose which gradually decreased in basal sections and increased in the apical sections of asparagus spears, irrespective of treatment. Edible coating did not affect asparagine concentrations which steadily increased throughout the shelf-life of the spears. The blend (Cassava+) kept for a longer the green asparagus quality. However, spears under a shelf-life of seven days (7 °C and 70% RH), with previous cold storage under 1 °C and 90% RH conditions, developed tip-rot physiological disorder.

Honey authentication is a complex process which traditionally requires costly and time-consuming analytical techniques not readily available to the producers. This study aimed to develop non-invasive sensor methods coupled with a multivariate data analysis to detect the type and percentage of exogenous sugar adulteration in UK honeys. Through-container spatial offset Raman spectroscopy (SORS) was employed on 17 different types of natural honeys produced in the UK over a season. These samples were then spiked with rice and sugar beet syrups at the levels of 10%, 20%, 30%, and 50% w/w. The data acquired were used to construct prediction models for 14 types of honey with similar Raman fingerprints using different algorithms, namely PLS-DA, XGBoost, and Random Forest, with the aim to detect the level of adulteration per type of sugar syrup. The best-performing algorithm for classification was Random Forest, with only 1% of the pure honeys misclassified as adulterated and Calluna vulgaris and 3 Erica cinerea) produced in the UK and corresponding subsamples spiked with high fructose sugar cane syrup, and an exploratory data analysis with PCA and a classification with Random Forest were performed, both showing clear separation between the pure and adulterated samples at medium (40%) and high (60%) adulteration levels and a 90% success at low adulteration levels (20%). The results of this study demonstrate the potential of SORS in combination with machine learning to be applied for the authentication of honey samples and the detection of exogenous sugars in the form of sugar syrups. A major advantage of the SORS technique is that it is a rapid, non-invasive method deployable in the field with potential application at all stages of the supply chain.

Milk is a biological fluid with a dynamic composition of micronutrients and bioactive molecules that serves as a vital nutrient source for infants. Milk composition is affected by multiple factors, including genetics, geographical location, environmental conditions, lactation phase, and maternal nutrition, and plays a key role in dictating its microbiome. This study addresses a less-explored aspect, comparing the microbial communities in human breast milk with those in mature milk from species that are used for milk consumption. Since mature animal milk is used as a supplement for both the infant (formula) and the child/adolescent, our main aim was to identify shared microbial communities in colostrum and mature human milk. Using 16S rRNA metagenomic sequencing, we focused on characterizing the milk microbiota in the Northern Greek population by identifying shared microbial communities across samples and comparing the relative abundance of prevalent genera. We analyzed ten human milk samples (from five mothers), with five collected three days postpartum (colostrum) and five collected thirty to forty days postpartum (mature milk) from corresponding mothers. To perform an interspecies comparison of human milk microbiota, we analyzed five goat and five bovine milk samples from a local dairy industry, collected fifty to seventy days after birth. Alpha diversity analysis indicated moderate diversity and stability in bovine milk, high richness in goat milk, and constrained diversity in breast milk. Beta diversity analysis revealed significant distinctions among mammalian species, emphasizing both presence/absence and abundance-based clustering. Despite noticeable differences, shared microbial components underscore fundamental aspects across all mammalian species, highlighting the presence of a core microbiota predominantly comprising the Proteobacteria, Firmicutes, and Actinobacteriota phyla. At the genus level, Acinetobacter, Gemella, and Sphingobium exhibit significant higher abundance in human milk compared to bovine and goat milk, while Pseudomonas and Atopostipes are more prevalent in animal milk. Our comparative analysis revealed differences and commonalities in the microbial communities of various mammalian milks and unraveled the existence of a common fundamental milk core microbiome. We thus revealed both species-specific and conserved microbial communities in human, bovine, and goat milk. The existence of a common core microbiome with conserved differences between colostrum and mature human milk underscores fundamental similarities in the microbiota of milk across mammalian species, which could offer valuable implications for optimizing the nutritional quality and safety of dairy products as well as supplements for infant health.

The bioaccessibility of bioactive compounds plays a major role in the nutritional value of foods, but there is a lack of systematic studies assessing the effect of the food matrix on bioaccessibility. Curcuminoids are phytochemicals extracted from Curcuma longa that have captured public attention due to claimed health benefits. The aim of this study is to develop a mathematical model to predict curcuminoid’s bioaccessibility in biscuits and custard based on different fibre type formulations. Bioaccessibilities for curcumin-enriched custards and biscuits were obtained through in vitro digestion, and physicochemical food properties were characterised. A strong correlation between macronutrient concentration and bioaccessibility was observed (p = 0.89) and chosen as a main explanatory variable in a Bayesian hierarchical linear regression model. Additionally, the patterns of food matrix effects on bioaccessibility were not the same in custards as in biscuits; for example, the hemicellulose content had a moderately strong positive correlation to bioaccessibility in biscuits (p = 0.66) which was non-significant in custards (p = 0.12). Using a Bayesian hierarchical approach to model these interactions resulted in an optimisation performance of r2 = 0.97 and a leave-one-out cross-validation score (LOOCV) of r2 = 0.93. This decision-support system could assist the food industry in optimising the formulation of novel food products and enable consumers to make more informed choices.

Partial information decompositions (PIDs) aim to categorize how a set of source variables provides information about a target variable redundantly, uniquely, or synergetically. The original proposal for such an analysis used a lattice-based approach and gained significant attention. However, finding a suitable underlying decomposition measure is still an open research question at an arbitrary number of discrete random variables. This work proposes a solution with a non-negative PID that satisfies an inclusion–exclusion relation for any f-information measure. The decomposition is constructed from a pointwise perspective of the target variable to take advantage of the equivalence between the Blackwell and zonogon order in this setting. Zonogons are the Neyman–Pearson region for an indicator variable of each target state, and f-information is the expected value of quantifying its boundary. We prove that the proposed decomposition satisfies the desired axioms and guarantees non-negative partial information results. Moreover, we demonstrate how the obtained decomposition can be transformed between different decomposition lattices and that it directly provides a non-negative decomposition of Rényi-information at a transformed inclusion–exclusion relation. Finally, we highlight that the decomposition behaves differently depending on the information measure used and how it can be used for tracing partial information flows through Markov chains.

Gardenia jasminoides Ellis is an evergreen shrub with white fragrant flowers, and it is cultivated for its ornamental, aromatic and medicinal value. The present study aimed to select desirable genotypes for potential commercial exploitation as pot plants or use in perfumery. Thus, 32 genotypes of G. jasminoides plants derived from seedlings, whose seeds were obtained from Australia and the USA, were evaluated for their genetic diversity in relation to four commercial cultivars (‘Pelion’, ‘Joy’, ‘Grandiflora’ and ‘Kimberly’, used as reference cultivars) using ISSR and SCoT markers. A cluster analysis separated the gardenia genotypes into the following three clusters: one cluster comprised the 16 genotypes originating from Australia, one included the 16 genotypes originating from the USA, and the third cluster contained the four reference cultivars. In other words, there was a clear demarcation of the genotypes investigated according to their geographical origin. In addition, the gardenia genotypes were evaluated for their morphological and chemical characteristics. Thus, flower- and leaf-related traits with ornamental value were measured, while the volatile compounds of flower extracts were identified with GC-MS analysis. Genotype 29-5 was selected for its acceptable morphological traits and genotype 51-8 for its rich volatile compounds. The major volatile compounds responsible for the floral aroma of the various gardenia genotypes examined were α-farnesene, benzyl tiglate, cis-3-hexenyltiglate, jasminelactone and linalool.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies worldwide, while it persists as the fourth most prevalent cause of cancer-related death in the United States of America. Although there are several novel therapeutic strategies for the approach of this intensely aggressive tumor, it remains a clinical challenge, as it is hard to identify in early stages, due to its asymptomatic course. A diagnosis is usually established when the disease is already in its late stages, while its chemoresistance constitutes an obstacle to the optimal management of this malignancy. The discovery of novel diagnostic and therapeutic tools is considered a necessity for this tumor, due to its low survival rates and treatment failures. One of the most extensively investigated potential diagnostic and therapeutic modalities is extracellular vesicles (EVs). These vesicles constitute nanosized double-lipid membraned particles that are characterized by a high heterogeneity that emerges from their distinct biogenesis route, their multi-variable sizes, and the particular cargoes that are embedded into these particles. Their pivotal role in cell-to-cell communication via their cargo and their implication in the pathophysiology of several diseases, including pancreatic cancer, opens new horizons in the management of this malignancy. Meanwhile, the interplay between pancreatic carcinogenesis and short non-coding RNA molecules (micro-RNAs or miRs) is in the spotlight of current studies, as they can have either a role as tumor suppressors or promoters. The deregulation of both of the aforementioned molecules leads to several aberrations in the function of pancreatic cells, leading to carcinogenesis. In this review, we will explore the role of extracellular vesicles and miRNAs in pancreatic cancer, as well as their potent utilization as diagnostic and therapeutic tools.

Sickle cell disease (SCD) is heterogeneous in terms of manifestation severity, even more so when in compound heterozygosity with beta-thalassemia. The aim of the present study was to stratify βSβ+ patient blood samples in a severity-dependent manner. Blood from thirty-two patients with HbS/β-thalassemia compound heterozygosity was examined for several parameters (e.g., hemostasis, inflammation, redox equilibrium) against healthy controls. Additionally, SCD patients were a posteriori (a) categorized based on the L-glutamine dose and (b) clustered into high-/low-RDW subgroups. The patient cohort was characterized by anemia, inflammation, and elevated coagulation. Higher-dose administration of L-glutamine was associated with decreased markers of inflammation and oxidation (e.g., intracellular reactive oxygen species) and an altered coagulation profile. The higher-RDW group was characterized by increased hemolysis, elevated markers of inflammation and stress erythropoiesis, and oxidative phenomena (e.g., membrane-bound hemoglobin). Moreover, the levels of hemostasis parameters (e.g., D-Dimers) were greater compared to the lower-RDW subgroup. The administration of higher doses of L-glutamine along with hydroxyurea seems to attenuate several features in SCD patients, probably by enhancing antioxidant power. Moreover, anisocytosis may alter erythrocytes’ coagulation processes and hemolytic propensity. This results in the disruption of the redox and pro-/anti-inflammatory equilibria, creating a positive feedback loop by inducing stress erythropoiesis and, thus, the occurrence of a mixed erythrocyte population.

Oxidative phenomena are considered to lie at the root of the accelerated senescence observed in red blood cells (RBCs) stored under standard blood bank conditions. It was recently shown that the addition of uric (UA) and/or ascorbic acid (AA) to the preservative medium beneficially impacts the storability features of RBCs related to the handling of pro-oxidant triggers. This study constitutes the next step, aiming to examine the links between hemolysis, redox, and metabolic parameters in control and supplemented RBC units of different storage times. For this purpose, a paired correlation analysis of physiological and metabolism parameters was performed between early, middle, and late storage in each subgroup. Strong and repeated correlations were observed throughout storage in most hemolysis parameters, as well as in reactive oxygen species (ROS) and lipid peroxidation, suggesting that these features constitute donor-signatures, unaffected by the diverse storage solutions. Moreover, during storage, a general “dialogue” was observed between parameters of the same category (e.g., cell fragilities and hemolysis or lipid peroxidation and ROS), highlighting their interdependence. In all groups, extracellular antioxidant capacity, proteasomal activity, and glutathione precursors of preceding time points anticorrelated with oxidative stress lesions of upcoming ones. In the case of supplemented units, factors responsible for glutathione synthesis varied proportionally to the levels of glutathione itself. The current findings support that UA and AA addition reroutes the metabolism to induce glutathione production, and additionally provide mechanistic insight and footing to examine novel storage optimization strategies.

Epigenetic clocks are accurate tools for age prediction and are of great interest for fisheries management and conservation biology. Here, we review the necessary computational steps and tools in order to build an epigenetic clock in any species focusing on fish. Currently, a bisulfite conversion method which allows the distinction of methylated and unmethylated cytosines is the recommended method to be performed at single nucleotide resolution. Typically, reduced representation bisulfite sequencing methods provide enough coverage of CpGs to select from for age prediction while the exact implemented method depends on the specific objectives and cost of the study. Sequenced reads are controlled for their quality, aligned to either a reference or a deduced genome and methylation levels of CpGs are extracted. Methylation values are obtained in biological samples of fish that cover the widest age range possible. Using these datasets, machine learning statistical procedures and, in particular, penalized regressions, are applied in order to identify a set of CpGs the methylation of which in combination is enough to accurately predict age. Training and test datasets are used to build the optimal model or “epigenetic clock”, which can then be used to predict age in independent samples. Once a set of CpGs is robustly identified to predict age in a given species, DNA methylation in only a small number of CpGs is necessary, thus, sequencing efforts including data and money resources can be adjusted to interrogate a small number of CpGs in a high number of samples. Implementation of this molecular resource in routine evaluations of fish population structure is expected to increase in the years to come due to high accuracy, robustness and decreasing costs of sequencing. In the context of overexploited fish stocks, as well as endangered fish species, accurate age prediction with easy-to-use tools is much needed for improved fish populations management and conservation.

Honey authentication is a complex process which traditionally requires costly and time-consuming analytical techniques not readily available to the producers. This study aimed to develop non-invasive sensor methods coupled with a multivariate data analysis to detect the type and percentage of exogenous sugar adulteration in UK honeys. Through-container spatial offset Raman spectroscopy (SORS) was employed on 17 different types of natural honeys produced in the UK over a season. These samples were then spiked with rice and sugar beet syrups at the levels of 10%, 20%, 30%, and 50% w/w. The data acquired were used to construct prediction models for 14 types of honey with similar Raman fingerprints using different algorithms, namely PLS-DA, XGBoost, and Random Forest, with the aim to detect the level of adulteration per type of sugar syrup. The best-performing algorithm for classification was Random Forest, with only 1% of the pure honeys misclassified as adulterated and <3.5% of adulterated honey samples misclassified as pure. Random Forest was further employed to create a classification model which successfully classified samples according to the type of adulterant (rice or sugar beet) and the adulteration level. In addition, SORS spectra were collected from 27 samples of heather honey (24 Calluna vulgaris and 3 Erica cinerea) produced in the UK and corresponding subsamples spiked with high fructose sugar cane syrup, and an exploratory data analysis with PCA and a classification with Random Forest were performed, both showing clear separation between the pure and adulterated samples at medium (40%) and high (60%) adulteration levels and a 90% success at low adulteration levels (20%). The results of this study demonstrate the potential of SORS in combination with machine learning to be applied for the authentication of honey samples and the detection of exogenous sugars in the form of sugar syrups. A major advantage of the SORS technique is that it is a rapid, non-invasive method deployable in the field with potential application at all stages of the supply chain. [ABSTRACT FROM AUTHOR]

Cholangiocarcinomas (CCAs) constitute a heterogeneous group of highly malignant epithelial tumors arising from the biliary tree. This cluster of malignant tumors includes three distinct entities, the intrahepatic, perihilar, and distal CCAs, which are characterized by different epidemiological and molecular backgrounds, as well as prognosis and therapeutic approaches. The higher incidence of CCA over the last decades, the late diagnostic time that contributes to a high mortality and poor prognosis, as well as its chemoresistance, intensified the efforts of the scientific community for the development of novel diagnostic tools and therapeutic approaches. Extracellular vesicles (EVs) comprise highly heterogenic, multi-sized, membrane-enclosed nanostructures that are secreted by a large variety of cells via different routes of biogenesis. Their role in intercellular communication via their cargo that potentially contributes to disease development and progression, as well as their prospect as diagnostic biomarkers and therapeutic tools, has become the focus of interest of several current studies for several diseases, including CCA. The aim of this review is to give a rundown of the current knowledge regarding the emerging role of EVs in cholangiocarcinogenesis and their future perspectives as diagnostic and therapeutic tools.

The distribution of age classes is a key demographic parameter of populations and thus proper age estimation is crucial for fisheries management and for conservation biology. Age estimation in fishes has traditionally relied on the analysis of growth marks in hard structures such as otoliths. However, besides being lethal this method is time-consuming, can have low accuracy in some species and cannot be applied in others. Thus, there is a need for the development of new methods. DNA methylation is an epigenetic modification consisting in the addition of a methyl group in cytosine-guanine loci. Aging is associated with changes in DNA methylation. Among a background of global and weak genome hypomethylation, there are some loci in which age-associated DNA methylation changes are of a “clock-like” nature and thus predictable. Chronological age estimators built from DNA methylation are termed ‘epigenetic clocks’. Epigenetic clocks have been developed in the last ten years for many species, notably vertebrates, including already several fish species. Here, we review the piscine epigenetic clocks built so far and outline the major considerations to be taken into account for the development of new epigenetic clocks for additional species, which include the number of samples to be collected and tissues to be targeted. The steps on how to develop such a clock and the techniques available to do so are also discussed. Next, we focus on the features of epigenetic clocks as measuring devices, considering aspects such as accuracy, precision and reproducibility. Finally, we discuss the possibility of developing a multi-species piscine epigenetic clock and how processing automation can greatly reduce the cost per sample. One important knowledge gap is to determine how environmental changes, especially temperature and food availability, may affect the tick rate of piscine epigenetic clocks. Improved age prediction through the use of piscine epigenetic clocks can contribute to better fisheries management practices in a context of overexploited fish stocks worldwide, and in the estimation of age classes in endangered species.

Redox imbalance and oxidative stress have emerged as generative causes of the structural and functional degradation of red blood cells (RBC) that happens during their hypothermic storage at blood banks. The aim of the present study was to examine whether the antioxidant enhancement of stored RBC units following uric (UA) and/or ascorbic acid (AA) supplementation can improve their storability as well as post-transfusion phenotypes and recovery by using in vitro and animal models, respectively. For this purpose, 34 leukoreduced CPD/SAGM RBC units were aseptically split in 4 satellite units each. UA, AA or their mixture were added in the three of them, while the fourth was used as control. Hemolysis as well as redox and metabolic parameters were studied in RBC units throughout storage. The addition of antioxidants maintained the quality parameters of stored RBCs, (e.g., hemolysis, calcium homeostasis) and furthermore, shielded them against oxidative defects by boosting extracellular and intracellular (e.g., reduced glutathione; GSH) antioxidant powers. Higher levels of GSH seemed to be obtained through distinct metabolic rewiring in the modified units: methionine-cysteine metabolism in UA samples and glutamine production in the other two groups. Oxidatively-induced hemolysis, reactive oxygen species accumulation and membrane lipid peroxidation were lower in all modifications compared to controls. Moreover, denatured/oxidized Hb binding to the membrane was minor, especially in the AA and mix treatments during middle storage. The treated RBC were able to cope against pro-oxidant triggers when found in a recipient mimicking environment in vitro, and retain control levels of 24h recovery in mice circulation. The currently presented study provides (a) a detailed picture of the effect of UA/AA administration upon stored RBCs and (b) insight into the differential metabolic rewiring when distinct antioxidant “enhancers” are used.