Type I collagen, prevalent in the extracellular matrix, is biocompatible and crucial for tissue engineering and wound healing, including angiogenesis and vascular maturation/stabilization as required processes of newly formed tissue constructs or regeneration. Sometimes, improper vascularization causes unexpected outcomes. Vascularization failure may be caused by extracellular matrix collagen and non-collagen components heterogeneously. This study compares the angiogenic potential of collagen type I-based scaffolds and collagen type I/glycosaminoglycans scaffolds by using the chick embryo chorioallantoic membrane (CAM) model and IKOSA digital image analysis. Two clinically used biomaterials, Xenoderm (containing type I collagen derived from decellularized porcine extracellular matrix) and a dual-layer collagen sponge (DLC, with a biphasic composition of type I collagen combined with glycosaminoglycans) were tested for their ability to induce new vascular network formation. The AI-based IKOSA app enhanced the research by calculating from stereomicroscopic images angiogenic parameters such as total vascular area, branching sites, vessel length, and vascular thickness. The study confirmed that Xenoderm caused a fast angiogenic response and substantial vascular growth, but was unable to mature the vascular network. DLC scaffold, in turn, produced a slower angiogenic response, but a more steady and organic vascular maturation and stabilization. This research can improve collagen-based knowledge by better assessing angiogenesis processes. DLC may be preferable to Xenoderm or other materials for functional neovascularization, according to the findings. Full article

Sesame seeds are important resources for relieving oxidation stress-related diseases. Although a significant variation in seeds’ antioxidant capability is observed, the underlying biochemical and molecular basis remains elusive. Thus, this study aimed to reveal major seed components and key molecular mechanisms that drive the variability of seeds’ antioxidant activity (AOA) using a panel of 400 sesame accessions. The seeds’ AOA, total flavonoid, and phenolic contents varied from 2.03 to 78.5%, 0.072 to 3.104 mg CAE/g, and 2.717 to 21.98 mg GAE/g, respectively. Analyses revealed that flavonoids and phenolic acids are the main contributors to seeds’ AOA variation, irrespective of seed coat color. LC-MS-based polyphenol profiling of high (HA) and low (LA) antioxidant seeds uncovered 320 differentially accumulated phenolic compounds (DAPs), including 311 up-regulated in HA seeds. Tricin, persicoside, 5,7,4′,5′-tetrahydro-3′,6-dimethoxyflavone, 8-methoxyapigenin, and 6,7,8-tetrahydroxy-5-methoxyflavone were the top five up-regulated in HA. Comparative transcriptome analysis at three seed developmental stages identified 627~2357 DEGs and unveiled that differential regulation of flavonoid biosynthesis, phenylpropanoid biosynthesis, and stilbene biosynthesis were the key underlying mechanisms of seed antioxidant capacity variation. Major differentially regulated phenylpropanoid structural genes and transcription factors were identified. SINPZ0000571 (MYB), SINPZ0401118 (NAC), and SINPZ0500871 (C3H) were the most highly induced TFs in HA. Our findings may enhance quality breeding. Full article

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km² (23.47%), with cropland, forest land, and water areas reduced by 570.77 km² (4.38%), 526.05 km² (1.76%), and 429.89 km² (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA. Full article

Ember accumulation on and around homes can lead to spot fires and home ignition. Post wildland fire assessments suggest that this mechanism is one of the leading causes of home destruction in wildland urban interface (WUI) fires. However, the process of ember deposition and accumulation on and around houses remains poorly understood. Herein, we develop a deep learning (DL) model to analyze data from a series of ember-related wind tunnel experiments for a range of wind conditions and roof slopes. The developed model is designed to identify building roof regions where embers will remain in contact with the rooftop. Our results show that the DL model is capable of accurately predicting the position and fraction of the roof on which embers remain in place as a function of the wind speed, wind direction, roof slope, and location on the windward and leeward faces of the rooftop. The DL model was augmented with explainable AI (XAI) measures to examine the extent of the influence of these parameters on the rooftop ember coverage and potential ignition. Full article

Group B Streptococcus (GBS) is a major cause of contagious bovine mastitis (CBM) in Brazil. The GBS population is composed of host-generalist and host-specialist lineages, which may differ in antimicrobial resistance (AMR) and zoonotic potential, and the surveillance of bovine GBS is crucial to developing effective CBM control and prevention measures. Here, we investigated bovine GBS isolates (n = 156) collected in Brazil between 1987 and 2021 using phenotypic testing and whole-genome sequencing to uncover the molecular epidemiology of bovine GBS. Clonal complex (CC) 61/67 was the predominant clade in the 20th century; however, it was replaced by CC91, with which it shares a most common recent ancestor, in the 21st century, despite the higher prevalence of AMR in CC61/67 than in CC91, and high selection pressure for AMR from indiscriminate antimicrobial use in the Brazilian dairy industry. CC103 also emerged as a dominant CC in the 21st century, and a considerable proportion of herds had two or more GBS strains, suggesting poor biosecurity and within-herd evolution due to the chronic nature of CBM problems. The majority of bovine GBS belonged to serotype Ia or III, which was strongly correlated with CCs. Ninety-three isolates were resistant to tetracycline (≥8 μg/mL; tetO = 57, tetM = 34 or both = 2) and forty-four were resistant to erythromycin (2.0 to >4 μg/mL; ermA = 1, ermB = 38, mechanism unidentified n = 5). Only three isolates were non-susceptible to penicillin (≥8.0 μg/mL), providing opportunities for improved antimicrobial stewardship through the use of narrow-spectrum antimicrobials for the treatment of dairy cattle. The common bovine GBS clades detected in this study have rarely been reported in humans, suggesting limited risk of interspecies transmission of GBS in Brazil. This study provides new data to support improvements to CBM and AMR control, bovine GBS vaccine design, and the management of public health risks posed by bovine GBS in Brazil. Full article

The proper coordination of directional overcurrent relays (DOCRs) is crucial in electrical power systems. The coordination of DOCRs in a multi-loop power system is expressed as an optimization problem. The aim of this study focuses on improving the protection system’s performance by minimizing the total operating time of DOCRs via effective coordination with main and backup DOCRs while keeping the coordination constraints within allowable limits. The coordination problem of DOCRs is solved by developing a new application strategy called Fractional Order Derivative Moth Flame Optimizer (FODMFO). This approach involves incorporating the ideas of fractional calculus (FC) into the mathematical model of the conventional moth flame algorithm to improve the characteristics of the optimizer. The FODMFO approach is then tested on the coordination problem of DOCRs in standard power systems, specifically the IEEE 3, 8, and 15 bus systems as well as in 11 benchmark functions including uni- and multimodal functions. The results obtained from the proposed method, as well as its comparison with other recently developed algorithms, demonstrate that the combination of FOD and MFO improves the overall efficiency of the optimizer by utilizing the individual strengths of these tools and identifying the globally optimal solution and minimize the total operating time of DOCRs up to an optimal value. The reliability, strength, and dependability of FODMFO are supported by a thorough statistics study using the box-plot, histograms, empirical cumulative distribution function demonstrations, and the minimal fitness evolution seen in each distinct simulation. Based on these data, it is evident that FODMFO outperforms other modern nature-inspired and conventional algorithms. Full article

Artificial intelligence, particularly machine learning, has gained prominence in medical research due to its potential to develop non-invasive diagnostics. Pulmonary hypertension presents a diagnostic challenge due to its heterogeneous nature and similarity in symptoms to other cardiovascular conditions. Here, we describe the development of a supervised machine learning model using non-invasive signals (orthogonal voltage gradient and photoplethysmographic) and a hand-crafted library of 3298 features. The developed model achieved a sensitivity of 87% and a specificity of 83%, with an overall Area Under the Receiver Operator Characteristic Curve (AUC-ROC) of 0.93. Subgroup analysis showed consistent performance across genders, age groups and classes of PH. Feature importance analysis revealed changes in metrics that measure conduction, repolarization and respiration as significant contributors to the model. The model demonstrates promising performance in identifying pulmonary hypertension, offering potential for early detection and intervention when embedded in a point-of-care diagnostic system. Full article

Pickup vehicle scheduling in steel logistics parks is an important problem for determining the outbound efficiency of steel products. In a steel logistics park, each yard contains different types of steel products, which provides flexible yard selection for each pickup operation. In this case, the yard allocation and the loading sequence for each vehicle must be considered simultaneously in pickup vehicle scheduling, which greatly increases the scheduling complexity. To overcome this challenge, in this paper, we propose a pickup vehicle scheduling problem with mixed steel storage (PVSP-MSS) to optimize the makespan of pickup vehicles and the makespan of steel logistics parks simultaneously. The optimization problem is formulated as a multi-objective mixed-integer linear programming model, and an enhanced algorithm based on SPEA2 (ESPEA) is proposed to solve the problem with a high efficiency. In the ESPEA, a cooperative initialization strategy is firstly proposed to initialize the vehicle pickup sequence for each yard. Then, an insertion decoding method is designed to improve the scheduling efficiency, utilizing the idle time of a yard. Furthermore, local search technology based on critical paths is proposed for the ESPEA to improve the solution quality. Experiments are executed based on data collected from a real steel logistics park. The results confirm that the ESPEA can significantly reduce both the makespan of each pickup vehicle and the makespan of the steel logistics park. Full article

Background: The prevalence of obesity has increased in patients with type 1 diabetes (T1D) and latent autoimmune diabetes of the adult (LADA), limiting the use of clinical features such as the body mass index for its differentiation with type 2 diabetes (T2D). Additionally, some patients with maturity-onset diabetes of the young (MODY) or LADA are misdiagnosed as having T2D. The evaluation of autoantibodies and genetic testing are not fully available. We aimed to evaluate the utility of a widely available and less expensive diagnostic tool such as C-peptide to differentiate between T1D, T2D, MODY, and LADA. Methods: Our study included 38 patients with T1D, 49 with T2D, 13 with MODY, and 61 with LADA. We recorded anthropometric measurements, biochemical profiles, and antidiabetic treatment and determined C-peptide, anti-GAD65, and anti-IA2 antibodies. Results: C-peptide concentration differed significantly among populations (T1D: 0.2 ng/mL; T2D: 2.4 ng/mL; MODY: 1.14 ng/mL; LADA: 1.87 ng/mL). Through a ROC curve, we observed that the C-peptide cut-off point of 0.95 ng/mL allows differentiation between T1D and T2D (sensitivity 82%, specificity 77%); 0.82 ng/mL between T1D and LADA (sensitivity 82%, specificity 77%); and 1.65 ng/mL between T2D and MODY (sensitivity 72%, specificity 72%). Conclusions: C-peptide is useful for the diagnostic differentiation of patients with type 1, type 2 diabetes, MODY, and LADA. Full article

The aim of the present study was to evaluate depressive-like, anxiety-like, and perseverative-like behaviors in a binge eating model. Juvenile Wistar rats, using the binge eating model, were compared to caloric restriction, induced stress, and control groups. Rats of the induced stress group presented binge-like behaviors in standard food intake in the second cycle of the experiment when compared to the caloric restriction group and the binge eating model group. Depressive-like behavior was observed in the binge eating model group with longer immobility time (p < 0.001) and less swim time (p < 0.001) in comparison to the control group. Anxiety-like behavior was observed by shorter duration of burying latency in the binge eating model group when compared to the induced stress group (p = 0.04) and a longer duration of burying time when compared to the control group (p = 0.02). We observed perseverative-like behavior by the binge model group, who made more entries to the new arm (p = 0.0004) and spent a longer time in the new arm when compared to the control group (p = 0.0001). Our results show differences in behaviors between the groups of rats studied. These results suggest that calorie restriction–refeeding, along with stress, may lead to depressive-like, anxiety-like, and perseverative-like behavioral changes in male Wistar rats. Full article

Aging and age-related diseases are associated with a decline in the capacity of protein turnover. Intrinsically disordered proteins, as well as proteins misfolded and oxidatively damaged, prone to aggregation, are preferentially digested by the ubiquitin-independent proteasome system (UIPS), a major component of which is the 20S proteasome. Therefore, boosting 20S activity constitutes a promising strategy to counteract a decrease in total proteasome activity during aging. One way to enhance the proteolytic removal of unwanted proteins appears to be the use of peptide-based activators of the 20S. In this study, we synthesized a series of peptides and peptidomimetics based on the C-terminus of the Rpt5 subunit of the 19S regulatory particle. Some of them efficiently stimulated human 20S proteasome activity. The attachment of the cell-penetrating peptide TAT allowed them to penetrate the cell membrane and stimulate proteasome activity in HEK293T cells, which was demonstrated using a cell-permeable substrate of the proteasome, TAS3. Furthermore, the best activator enhanced the degradation of aggregation-prone α-synuclein and Tau-441. The obtained compounds may therefore have the potential to compensate for the unbalanced proteostasis found in aging and age-related diseases. Full article

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease widespread in Europe and Asia. HFRS is caused by negative-sensed single-stranded RNA orthohantaviruses transmitted to humans through inhaling aerosolized excreta of infected rodents. Symptoms of HFRS include acute kidney injury, thrombocytopenia, hemorrhages, and hypotension. The immune response raised against viral antigens plays an important role in the pathogenesis of HFRS. Inhibitory co-receptors are essential in regulating immune responses, mitigating immunopathogenesis, and reducing tissue damage. Our research showed an increased soluble form of inhibitory co-receptors TIM-3, LAG-3, and PD-1 in HFRS patients associated with disease severity. Our study aimed to investigate the impact of HFRS on the concentrations of soluble forms of inhibitory receptors TIM-3, LAG-3, and PD-1 in the patient’s serum and the potential correlation with key clinical parameters. Our study aimed to investigate the impact of HFRS on the concentrations of soluble forms of inhibitory receptors TIM-3, LAG-3, and PD-1 in the patient’s serum and their possible association with relevant clinical parameters. Using multiplex immunoassay, we found elevated levels of TIM-3, LAG-3, and PD-1 proteins in the serum of HFRS patients. Furthermore, increased levels were associated with creatinine, urea, lactate dehydrogenase concentrations, and platelet count. These findings suggest that these proteins play a role in regulating the immune response and disease progression. Full article

Several attempts have been made to evaluate the abundance and distribution of the bacterial community in the rhizosphere of medicinal plants. Many describe information based on an estimation of the community structure and the effects of plant cover in determining microbial community composition. The ability of plants to specifically shape their microbial community in general and medicinal plants in particular is largely unknown. With the arrival of molecular biology, understanding the microbial community’s composition, diversity, and function became possible. We hypothesized that microbial communities associated with medicinal shrubs would differ from each other. To test this hypothesis, we characterized the soil microbial composition under each of five Mediterranean medicinal plants, differentiated by their medicinal use and ecophysiological adaptation, namely, Salvia fruticosa, Pistacia lentiscus, Myrtus communis, Origanum syriacum, and Teucrium capitatum, and an open-space bare soil between the plants, inhabiting natural ecosystems characterized by similar climatic conditions typical of a Mediterranean environment. The results demonstrated the importance of plant ecophysiological adaptations, which play an important role in determining microbial community composition and functional diversity. The intensity of a plant’s response to its surroundings can have either positive or negative effects that will determine the microbial community composition and interactions among the belowground parts. A total of 11 phyla, 21 orders, and 409 genera were found in the soil rhizosphere in the vicinity of the four plants and open space samples. The distinguishing attributes of each shrub trigger and stimulate the microbial community’s rhizosphere. This results in distinct patterns of bacterial diversity and functionality between the different shrubs and the control. The rhizosphere bacterial community composition differed between the plants in a PERMANOVA test, but there was little difference in terms of phyla and order relative abundances. This study shows how five medicinal plants, coexisting in a common habitat, impact the bacterial community. The noticeable shift in bacterial composition further supports our discovery that root exudates effectively govern the makeup of soil bacterial communities. Full article

The abundance of fruit waste from the food industry and wineries, particularly peels, seeds, and other fruit pomace throughout the year, could lead to health and environmental hazards if not channelled into productive areas. Improving or transforming these waste products for better use in other vital sectors could be achieved via solid-state fermentation (SSF) since most waste products are solid. One such productive and important area is the feeding of livestock, which will guarantee millennium food security goals for many nations of the world. The nutritional and antioxidant composition of abundantly available fruit pomace and agro-industrial byproducts could be improved via solid-state fermentation for overall livestock productivity. They contain substantial dietary fibre, protein, and phenolic compounds; hence, improving them via fermentation could serve the livestock industry in dual capacities, including nutraceutical and conventional feedstuff. This review seeks to provide reinforcing evidence on the applicability and impact of fruit pomaces on livestock nutrition. The significant nutrient improvements, beneficial outcomes in feeding trials, and inconsistencies or areas of research gap were also explored. Full article

Recording large amounts of users’ sessions performed through 3D applications may provide crucial insights into interaction patterns. Such data can be captured from interactive experiences in public exhibits, remote motion tracking equipment, immersive XR devices, lab installations or online web applications. Immersive analytics (IA) deals with the benefits and challenges of using immersive environments for data analysis and related design solutions to improve the quality and efficiency of the analysis process. Today, web technologies allow us to craft complex applications accessible through common browsers, and APIs like WebXR allow us to interact with and explore virtual 3D environments using immersive devices. These technologies can be used to access rich, immersive spaces but present new challenges related to performance, network bottlenecks and interface design. WebXR IA tools are still quite new in the literature: they present several challenges and leave quite unexplored the possibility of synchronous collaborative inspection. The opportunity to share the virtual space with remote analysts in fact improves sense-making tasks and offers new ways to discuss interaction patterns together, while inspecting captured records or data aggregates. Furthermore, with proper collaborative approaches, analysts are able to share machine learning (ML) pipelines and constructively discuss the outcomes and insights through tailored data visualization, directly inside immersive 3D spaces, using a web browser. Under the H2IOSC project, we present the first results of an open-source pipeline involving tools and services aimed at capturing, processing and inspecting interactive sessions collaboratively in WebXR with other analysts. The modular pipeline can be easily deployed in research infrastructures (RIs), remote dedicated hubs or local scenarios. The developed WebXR immersive analytics tool specifically offers advanced features for volumetric data inspection, query, annotation and discovery, alongside spatial interfaces. We assess the pipeline through users’ sessions captured during two remote public exhibits, by a WebXR application presenting generative AI content to visitors. We deployed the pipeline to assess the different services and to better understand how people interact with generative AI environments. The obtained results can be easily adopted for a multitude of case studies, interactive applications, remote equipment or online applications, to support or accelerate the detection of interaction patterns among remote analysts collaborating in the same 3D space. Full article

The emergence of electric vehicles has brought new issues such as the problem of rolling element bearings (REBs) operating at high speeds. Losses due to these components in mechanical transmissions are a key issue and must therefore be taken into account right from the design stage of these systems. Among these losses, the one induced by the motion of rolling elements, known as drag loss, becomes predominant in high-speed REBs. Although an experimental approach is still possible, it is difficult to isolate this loss in order to study it properly. A numerical approach based on CFD is therefore a possible way forward, even if other issues arise. The aim of this article is to study the ability of such an approach to correctly estimate the drag coefficient associated with the motion of rolling elements. The influence of the numerical domain extension, the mesh refinement, the simplification of the ring shape, and the presence of the cage on the values of the drag coefficient is presented. While it seems possible to compromise on the calculation domain and mesh size, it appears that the other parameters must be taken into account as much as possible to obtain realistic results. Full article

With the continuous expansion of the transport network, the safe operation of high-speed railway rails has become a crucial issue. Defect detection on the surface of rails is a key part of ensuring the safe operation of trains. Despite the progress of deep learning techniques in defect detection on the rails’ surface, there are still challenges related to various problems, such as small datasets and the varying scales of defects. Based on this, this paper proposes an improved encoder–decoder architecture based on Swin Transformer network, named Rail-STrans, which is specifically designed for intelligent segmentation of high-speed rail surface defects. The problem of a small and black-and-white rail dataset is solved using self-made large and multiple rail surface defect datasets through field shooting, data labelling, and data expansion. In this paper, two Local Perception Modules (LPMs) are added to the encoding network, which helps to obtain local context information and improve the accuracy of detection. Then, the Multiscale Feature Fusion Module (MFFM) is added to the decoding network, which helps to effectively fuse the feature information of defects at different scales in the decoding process and improves the accuracy of defect detection at multiple scales. Meanwhile, the Spatial Detail Extraction Module (SDEM) is added to the decoding network, which helps to retain the spatial detail information in the decoding process and further improves the detection accuracy of small-scale defects. The experimental results show that the mean accuracy of the semantic segmentation of the method proposed in this paper can reach 90.1%, the mean dice coefficient can reach 89.5%, and the segmentation speed can reach 37.83 FPS, which is higher than other networks’ segmentation accuracy. And, at the same time, it can achieve higher efficiency. Full article

Adipose tissue is a multifunctional organ that regulates many physiological processes such as energy homeostasis, nutrition, the regulation of insulin sensitivity, body temperature, and immune response. In this review, we highlight the relevance of the different mediators that control adipose tissue activity through a systematic review of the main players present in white and brown adipose tissues. Among them, inflammatory mediators secreted by the adipose tissue, such as classical adipokines and more recent ones, elements of the immune system infiltrated into the adipose tissue (certain cell types and interleukins), as well as the role of intestinal microbiota and derived metabolites, have been reviewed. Furthermore, anti-obesity mediators that promote the activation of beige adipose tissue, e.g., myokines, thyroid hormones, amino acids, and both long and micro RNAs, are exhaustively examined. Finally, we also analyze therapeutic strategies based on those mediators that have been described to date. In conclusion, novel regulators of obesity, such as microRNAs or microbiota, are being characterized and are promising tools to treat obesity in the future. Full article

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike protein and the membrane (M) protein, which may imply an enhanced ability to evade immune responses. In this study, an examination of co-mutations within the spike RBD and their potential correlation with mutations in the M protein was conducted. The EVmutation method was utilized to analyze the distribution of the mutations to elucidate the relationship between the mutations in the spike RBD and the alterations in the M protein. Additionally, the Sequence-to-Sequence Transformer Model (S2STM) was employed to establish mapping between the amino acid sequences of the spike RBD and M proteins, offering a novel and efficient approach for streamlined sequence analysis and the exploration of their interrelationship. Certain mutations in the spike RBD, G339D-S373P-S375F and Q493R-Q498R-Y505, are associated with a heightened propensity for inducing mutations at specific sites within the M protein, especially sites 3 and 19/63. These results shed light on the concept of mutational synergy between the spike RBD and M proteins, illuminating a potential mechanism that could be driving the evolution of SARS-CoV-2. Full article

The aim of this study was to determine the peroxide values, acid numbers, oxidative stability (Rancimat method), antioxidant activity (DPPH method), antimicrobial activity (disc diffusion method), sensory properties (9-point hedonic scale), and fatty acid profiles (FAME) of five edible oils purchased from local Slovakian producers—grape seed oil, flax seed oil, walnut oil, poppy seed oil, and milk thistle seed oil. The peroxide value ranged from 2.27 (milk thistle oil) to 8.51 (flax seed oil) mmol O₂/kg. All these values were in accordance with regulations (upper limit of 20 mmol O₂/kg). The values of the acid number ranged from 0.11 (walnut oil) to 2.49 (milk thistle oil) mg KOH/g, and were in accordance with regulations as they did not exceed the value of 4 mg KOH/g. The oxidation stability was the lowest in flax seed oil (0.18 h) and the highest in grape seed oil (2.05 h). In milk thistle oil, the highest amounts of oleic and behenic acids, in flax seed oil, the highest amount of α-linolenic acid, and in grape seed oil, the highest amount of linolic acid were determined. Antioxidant activity was the strongest in the sample of grape seed oil—65.53 mg TEAC/L (Trolox equivalent antioxidant capacity). Samples of flax seed oil showed the strongest inhibition of Candida albicans CCM 8186 (4.58 mm) and Bacillus subtilis CCM 2010 (0.31 mm). Poppy seed oil was determined to be the most inhibiting towards Klebsiella pneumoniae CCM 2318 (3.68 mm). Milk thistle oil showed the strongest inhibition of Clostridium perfringens CCM 4435 (6.31 mm). Grape seed oil was the most inhibitory towards Staphylococcus aureus subs. aureus CCM 2461 (5.32 mm). Walnut oil showed the strongest activity towards Yersinia enterocolitica CCM 5671 (6.33 mm). The sensory analysis resulted in the samples of walnut and grape seed oil being awarded the highest scores for smell, taste, and overall acceptability. The tested edible oils are rich in biologically active compounds with antioxidant and antimicrobial activities. Their consumption can have a positive effect on the functioning of the human body and its health. Proper storage conditions are, however, necessary because of the susceptibility of these oils to oxidation. Full article

Objectives: This study aimed to identify predictors of remission or low disease activity (LDA) in patients with rheumatoid arthritis (RA) and low-ultrasound inflammation. Methods: A total of 80 patients with RA who fulfilled the 1987 ACR criteria for RA with a disease activity score of 28 joints (DAS28) > 3.2 were recruited. Over 1 year of therapy, we conducted blood tests every 6 months to examine erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), monocyte chemotactic protein-1 (MCP-1), neuraminidase 3 (Neu3), and α-2,3-sialyltrasnferse I (ST3Gal-1) levels in B cells and monocytes. Additionally, we evaluated physical function by using the Health Assessment Questionnaire–Disability Index (HAQ-DI). Data on demographic and clinical parameters were collected, and musculoskeletal ultrasonography was performed twice a year on 12 specific joints to assess synovial changes. One year later, we compared all collected data and laboratory or ultrasound results between patients achieving remission or LDA and those who did not in order to determine the predictors. Results: Age, the presence or absence of rheumatoid factor, and the number of conventional disease-modifying anti-rheumatic drugs used were not correlated with remission or LDA for DAS28 or Simplified Disease Activity Index formulas. However, male sex, low CRP levels, low ESR levels, and low HAQ-DI scores were associated with a higher likelihood of achieving remission or LDA for DAS28-ESR. Negative anticyclic citrullinated peptide (CCP) and low HAQ-DI scores were predictors of remission or LDA for DAS28-MCP-1. Interestingly, having less than two comorbidities is a good predictor of a combined remission/low disease activity state for SDAI and DAS28-MCP-1. Furthermore, Neu3 and ST3Gal-1 levels and ST3Gal-1/Neu3 ratios in B cells and monocytes had no significant correlation with total ultrasound scores. Nevertheless, monocyte ST3Gal-1 and Neu3 correlated significantly with DAS28-ESR >5.1 and DAS-MCP-1 >4.8 (both categories belong to high disease activity), respectively (rho = 0.609 with p = 0.012, and rho = 0.727 with p = 0.011, respectively). Monocyte ST3Gal-1/Neu3 ratios connected with DAS28-ESR >5.1 and 3.3 < SDAI ≦ 11 (low disease activity), respectively (rho = 0.662 with p = 0.005, and rho = 0.342 with p = 0.048, respectively). Conclusions: In patients with RA in Taiwan, male sex, low CRP levels, low ESR levels, and low HAQ-DI scores are predictors of remission or LDA for DAS28-ESR, which differ from the predictors for DAS28-MCP-1. Moreover, monocyte ST3Gal-1, Neu3, and their ratios correlated with different disease activity categories of DAS28-ESR, DAS28-MCP-1, and SDAI scores. Full article