Search Results (326,686)

Hazelnut is an important crop worldwide, and the characteristics of the fruits are quite variable according to a number of factors, including variety and cultivation conditions, which in turn can vary according to harvest year. This study aimed to investigate some physical and chemical characteristics of three hazelnut varieties grown in Portugal (Grada de Viseu, Tonda di Giffoni and Butler) along two different harvesting years (2021 and 2022). Also, the microbial quality was investigated for its relevance to the conservation of the fruits. The physical properties evaluated were biometric characteristics and colour, the chemical components analysed were moisture, lipids, protein, ash and fibre, and the microbial properties investigated were the microorganisms, moulds and yeasts. The results showed that, generically, statistically significant differences were found between the three varieties under study on several properties investigated. The kernel was confirmed as the lighter part of all hazelnuts, and when comparing between varieties, Tonda di Giffoni presented the lighter fruits in both harvesting years. With respect to weight, the Tonda di Giffoni variety was the lightest in both harvest years. Moisture content was observed to be higher than the recommended limits for two of the samples (Grada de Viseu in 2021: 6.01 ± 0.26 g/100 g and Butler in 2022: 6.02 ± 0.37 g/100 g), although the difference was marginal given that the recommended limit is 6%. Not surprisingly, lipids were the major chemical component, ranging from 66.46 ± 1.67 to 70.14 ± 1.75 g/100 g in 2021 and from 64.38 ± 1.67 to 77.77 g/100 g in 2022. It was further observed that the three varieties presented a satisfactory microbiological quality. Finally, applying factor analysis with principal components and Varimax rotation, a solution that explains 92.8% of the variance was obtained. This study provided information that is relevant for the characterisation and evaluation of variability according to the year of hazelnuts of three varieties cultivated in Portugal. Full article

As a semi-pelagic fish with commercial value, Mediterranean horse mackerel, Trachurus mediterraneus (Steindachner, 1868), is highly important both for the ecosystem, as a link between trophic levels, and for fisheries and local livelihoods. This study investigates the T. mediterraneus stock along the Romanian coast for more than 10 years (2014–2024), reporting the following data on its bio-ecological characteristics and stock status: size, age, sex ratio, and estimated biomass. Horse mackerel at the Romanian coast revealed an initially slower growth rate followed by acceleration in later years, which may reflect local ecological influences such as resource availability, environmental conditions, or selective pressure. The spatial distribution of the species along the Romanian shelf indicates a clear pattern of coastal aggregation, highlighting the need for targeted and precautionary fisheries management measures, aiming to ensure a sustainable stock. Full article

Background: Understanding the mechanisms underlying dental pain caused by pulpitis in humans has led to the development of animal models, such as the rat, which enable the study of the mechanisms underlying inflammation; the use of these models is considered ethically justified when the anticipated scientific benefits outweigh the potential impacts on animals in the harm/benefit balance. Objective: To develop a rat model of mechanically induced pulpitis and to evaluate the potential impact on animal well-being. Methods: Pulpitis was mechanically induced in male Lewis rats (13–16 weeks, 350–400 g) which were anesthetized and endotracheally intubated. Following pulp exposure, the cavity was sealed with either amalgam (n = 10) or zinc phosphate cement (n = 10). Following recovery and return to their housing, behavioral assessments and histological evaluations using Hematoxylin and Eosin (H&E) staining were conducted in separate cohorts at two time points: 3 h and 5 days following the procedure. Results: A standardized model of mechanically induced pulpitis was established and verified clinically and by histopathological analysis, which showed evidence of the inflammatory process and revealed no statistically significant differences in the scoring of pain, discomfort, or distress, nor in the measurements of food and water consumption or body weight. Conclusions: The behavioral assessments conducted in this study supported the implementation of a safe and easily reproducible model for future research aimed at elucidating the mechanisms underlying pulp inflammation. Full article

Treatment of locally advanced rectal cancer (LARC), clinical stages II–III, typically involves multimodal treatment options. Over the past decade, the role of radiation therapy as a neoadjuvant treatment for LARC has evolved and is currently a part of total neoadjuvant therapy (TNT). Some recently published studies advocate for the omission of radiation therapy entirely, while others report on a non-operative approach that emphasizes the use of higher radiation therapy doses. This review aims to evaluate the latest literature on the current role of radiation therapy in the management of LARC, with a discussion of how to best select the most appropriate treatment protocol based on individual patient and tumor characteristics, comorbidities, and personal needs and preferences. Full article

Background/Objectives: Glycogen storage disease type II, also known as Pompe disease (PD), is a rare autosomal recessive genetic disorder triggered by a deficiency in lysosomal acid α-glucosidase (GAA). Recently, we discovered two deleterious missense variants of the GAA gene, c.1799G>A (p.Arg600His) (a pathogenic mutation) and c.55G>A (p.Val19Met), in a domestic short-haired cat with PD. This study aimed to design genotyping assays for these two variants and ascertain their allele frequencies in Japanese cat populations. Methods: We developed fluorescent probe-based real-time polymerase chain reaction assays to genotype the c.1799G>A and c.55G>A variants. A total of 738 cats, comprising 99 purebred cats from 20 breeds and 540 mixed-breed cats, were screened using these assays. Results: Genotyping assays clearly differentiated all known genotypes of the two variants. None of the 738 cats tested carried the c.1799G>A variant. However, we identified cats with c.55G/A and c.55A/A genotypes in the purebred (A allele frequency: 0.081) and mixed-breed cats (0.473). A significant difference (p < 0.001) was observed in the A allele frequency between the two groups. Conclusions: The c.1799G>A mutation appears rare in cat populations, suggesting it may be confined to specific pedigree Japanese mixed-breed cats. The c.55G>A variant was detected in purebred and mixed-breed cats, suggesting that it may not be directly linked to feline PD. However, additional studies are required to elucidate the precise relationship between this variant and cardiac function. Genotyping assays will serve as valuable tools for diagnosing and genotyping feline PD. Full article

In recent years, researchers have become increasingly interested in identifying traits of cognitive impairment using audio from neuropsychological tests. Unfortunately, there is no universally accepted terminology system that can be used to describe language impairment, and considerable variability exists between clinicians, making detection particularly challenging. Furthermore, databases commonly used by the scientific community present sparse or unbalanced data, which hinders the optimal performance of machine learning models. Therefore, this study aims to test a new methodology for augmenting text data from neuropsychological tests in the Pitt Corpus database to increase classification and interpretability results. The proposed method involves augmenting text data with symptoms commonly present in subjects with cognitive impairment. This innovative approach has enabled us to differentiate between two groups in the database better than widely used text augmentation techniques. The proposed method yielded an increase in the metrics, achieving 0.8742 accuracy, 0.8744 F1-score, 0.8736 precision, and 0.8781 recall. It is shown that implementing large language models with commonly observed symptoms in the language of patients with cognitive impairment in text augmentation can improve the results in low-resource scenarios. Full article

Calcific aortic stenosis (CAS) is a newly emerging pandemic in elderly individuals due to the aging of the population in the world. Surgical Aortic Valve Replacement (SAVR) and Transcatheter Aortic Valve Replacement (TAVR) are the cornerstone of the management of severe aortic stenosis accompanied by one or more symptoms. Moreover, an appropriate interventional treatment of CAS, in elderly patients, is a very complex decision for heart teams, to avoid bad outcomes such as operative mortality, cardiovascular and all-cause death, hospitalization for heart failure, worsening of quality of life. In fact, CAS in the elderly is not only a focal valve disease, but a very complex clinical picture with different risk factors and etiologies, differing underlying pathophysiology, large phenotypic heterogeneity in a context of subjective biological, phenotypic and functional aging until frailty and disability. In this review, we analyzed separately and in a more integrated manner, the natural and prognostic histories of the progression of aortic stenosis, the phenotypes of myocardial damage and heart failure, within the metrics and aging trajectory. The aim is to suggest, during the clinical timing of valve disease, the best interval time for an appropriate and effective interventional treatment in each older patient, beyond subjective symptoms by integration of clinical, geriatric, chemical, and advanced imaging biomarkers. Full article

With countries around the world required to change their energy systems to mitigate climate change, offshore wind power has become one of the most important renewable energy sources. This study aims to analyze the potential for offshore wind power generation based on the water depth and annual average wind speed in the Akita region, Japan. A geographical information system was used not only for a conventional square mesh but also for a rectangular mesh when there is a prevailing wind, and a greater water depth was also considered. The results obtained indicate that the use of a rectangular mesh reduces the potential for implantable offshore wind turbines compared to a square mesh. It was also found that the potential for offshore wind power generation is significant up to a water depth of 500 m. Full article

Total knee replacement (TKR) is a common procedure for pain relief and restoration of the mobility of the knee joint in patients with severe knee joint problems. Despite this, some patients still suffer from stiffness, instability, or pain caused by soft tissue imbalance, malalignment, or implant-related issues. Previously, surgeons have had to use their experience and visual judgment to balance the knee, which has resulted in variability of outcomes. Smart knee implants are addressing these issues by using sensor technology to provide real-time feedback on joint motion, pressure distribution, and loading forces. This enables more accurate intra-operative adjustment, enhancing implant positioning and soft tissue balance and eliminating post-operative adjustment. These implants also enable post-operative monitoring, simplifying the ability to have more effective individualized rehabilitation programs directed at optimizing patient mobility and minimizing complications. While the patient pool for smart knee implantation remains not commonly documented, it was found in a study that 83.6% of the patients would opt to have the monitoring device implemented, and nearly 90% find reassurance in monitoring their healing indicators. As the number of knee replacements is likely to rise due to aging populations and the rising prevalence of joint disease, smart implants are a welcome development in orthopedics, optimizing long-term success and patient satisfaction. Smart knee implants are built with embedded sensors such as force, motion, temperature, and pressure detectors placed within the implant structure. These sensors provide real-time data during surgery and recovery, allowing earlier detection of complications and supporting tailored rehabilitation. The design aims to improve outcomes through better monitoring and personalized care. Full article

Background/Objectives: Patients with breast cancer who do not achieve a complete response to neoadjuvant chemotherapy (NAC) may benefit from intensified adjuvant systemic therapy. However, such treatment escalation is typically delayed until after tumour resection, which occurs several months into the treatment course. Quantitative ultrasound (QUS) can detect early microstructural changes in tumours and may enable timely identification of non-responders during NAC, allowing for earlier treatment intensification. In our previous prospective observational study, 100 breast cancer patients underwent QUS imaging before and four times during NAC. Machine learning algorithms based on QUS texture features acquired in the first week of treatment were developed and achieved 78% accuracy in predicting treatment response. In the current study, we aimed to validate these algorithms in an independent prospective cohort to assess reproducibility and confirm their clinical utility. Methods: We included breast cancer patients eligible for NAC per standard of care, with tumours larger than 1.5 cm. QUS imaging was acquired at baseline and during the first week of treatment. Tumour response was defined as a ≥30% reduction in target lesion size on the resection specimen compared to baseline imaging. Results: A total of 51 patients treated between 2018 and 2021 were included (median age 49 years; median tumour size 3.6 cm). Most were estrogen receptor–positive (65%) or HER2-positive (33%), and the majority received dose-dense AC-T (n = 34, 67%) or FEC-D (n = 15, 29%) chemotherapy, with or without trastuzumab. The support vector machine algorithm achieved an area under the curve of 0.71, with 86% accuracy, 91% specificity, 50% sensitivity, 93% negative predictive value, and 43% positive predictive value for predicting treatment response. Misclassifications were primarily associated with poorly defined tumours and difficulties in accurately identifying the region of interest. Conclusions: Our findings validate QUS-based machine learning models for early prediction of chemotherapy response and support their potential as non-invasive tools for treatment personalization and clinical trial development focused on early treatment intensification. Full article

Rheumatoid arthritis (RA) is a chronic inflammatory disease frequently associated with alterations in body composition, including reduced lean mass and increased fat mass. These alterations are thought to be driven by persistent systemic inflammation, which may be influenced by inflammatory activity and by therapeutic interventions. Objectives: This pilot study aimed to provide preliminary data on changes in body composition and inflammatory activity in biologic-naive patients with active RA during the initial 6 months of TNF inhibitor treatment, and to compare baseline body composition with healthy controls. We conducted a single-center, observational, 24-week pilot study of 70 biologic-naive RA patients with moderate-to-severe disease activity and 70 matched healthy controls. Lean mass, fat mass, and lean mass index (LMI) were measured using dual-energy X-ray absorptiometry at baseline for both groups, and after 6 months only in the RA group. Clinical, laboratory, adipokines, and cytokine parameters were also recorded. At baseline, RA patients had lower lean mass and LMI than controls. Over 6 months, RA patients showed significant clinical and laboratory improvement, with a corresponding increase in lean mass and LMI. No statistically significant change was observed in fat mass. The increase in lean mass was paralleled by a reduction in inflammatory markers. The LMI was inversely associated with female sex (β = −0.562) and C-reactive protein (β = −0.432) and directly associated with body mass index (β = 0.570). Similar associations were observed for total lean mass and change in lean mass, as well as for DAS28 (β = −0.333). This pilot study provides preliminary evidence that TNF inhibitor therapy may be associated with increased lean mass and decreased inflammation in RA patients. Owing to the absence of a comparator RA group not receiving TNF inhibitors, these findings should be interpreted as hypothesis-generating. Full article

Background: Clinical assessment of balance and postural disorders is usually carried out through several common practices including tests such as the Subjective Visual Vertical (SVV) and Limit of Stability (LOS). Nowadays, several cutting-edge technologies have been proposed as supporting tools for stability evaluation. Extended Reality (XR) emerges as a powerful instrument. This proof-of-concept study aims to assess the feasibility and potential clinical utility of a novel MR-based framework integrating HoloLens 2, Wii Balance Board, and Azure Kinect for multimodal balance assessment. An innovative test is also introduced, the Innovative Dynamic Balance Assessment (IDBA), alongside an MR version of the SVV test and the evaluation of their performance in a cohort of healthy individuals. Results: All participants reported SVV deviations within the clinically accepted ±2° range. The IDBA results revealed consistent sway and angular profiles across participants, with statistically significant differences in posture control between opposing target directions. System outputs were consistent, with integrated parameters offering a comprehensive representation of postural strategies. Conclusions: The MR-based framework successfully delivers integrated, multimodal measurements of postural control in healthy individuals. These findings support its potential use in future clinical applications for balance disorder assessment and personalized rehabilitation. Full article

Under the growing demand for processing multimodal and cross-lingual information, traditional retrieval systems have encountered substantial limitations when handling heterogeneous inputs such as images, textual layouts, and multilingual language expressions. To address these challenges, a unified retrieval framework has been proposed, which integrates visual features from images, layout-aware optical character recognition (OCR) text, and bilingual semantic representations in Chinese and English. This framework aims to construct a shared semantic embedding space that mitigates semantic discrepancies across modalities and resolves inconsistencies in cross-lingual mappings. The architecture incorporates three main components: a visual encoder, a structure-aware OCR module, and a multilingual Transformer. Furthermore, a joint contrastive learning loss has been introduced to enhance alignment across both modalities and languages. The proposed method has been evaluated on three core tasks: a single-modality retrieval task from image → OCR, a cross-lingual retrieval task between Chinese and English, and a joint multimodal retrieval task involving image, OCR, and language inputs. Experimental results demonstrate that, in the joint multimodal setting, the proposed model achieved a Precision@10 of 0.693, Recall@10 of 0.684, nDCG@10 of 0.672, and F1@10 of 0.685, substantially outperforming established baselines such as CLIP, LayoutLMv3, and UNITER. Ablation studies revealed that removing either the structure-aware OCR module or the cross-lingual alignment mechanism resulted in a decrease in mean reciprocal rank (MRR) to 0.561, thereby confirming the critical role of these components in reinforcing semantic consistency across modalities. This study highlights the powerful potential of large language models in multimodal semantic fusion and retrieval tasks, providing robust solutions for large-scale semantic understanding and application scenarios in multilingual and multimodal contexts. Full article

Cardiovascular–Kidney–Metabolic (CKM) syndrome symbolizes a single pathophysiologic entity including obesity, type 2 diabetes, chronic kidney disease, and cardiovascular disease. These conditions altogether accelerate adverse outcomes when they coexist. Recent evidence has shown that the function of glucagon-like peptide-1 receptor agonists (GLP-1RA) and sodium–glucose cotransporter-2 inhibitors (SGLT2i) alleviate stress on multiple organs. SGLT2i has been demonstrated to benefit heart failure, hemodynamic regulation, and renal protection while GLP-1RA on the other hand has been shown to demonstrate a strong impact on glycemic management, weight loss, and atherosclerotic cardiovascular disease. This review will aim to understand and evaluate the mechanistic rationalization, clinical evidence, and the potential therapeutic treatment of SGLT2 inhibitors and GLP-1 receptor agonists to treat individuals who have CKM syndrome. This analysis also assesses whether combination therapy can be a synergistic approach that may benefit patients but is still underutilized because of the lack of clear guidelines, the associated costs, and disparities in accessibility. Therefore, in this review, we will be discussing the combination therapy’s additive and synergistic effects, current recommendations and clinical evidence, and mechanistic insights of these GLT2 inhibitors and GLP-1 receptor agonists in CKM syndrome patients. Overall, early and combination usage of GLP-1RA and SGLT2i may be essential to demonstrating a significant shift in modern cardiometabolic therapy toward patient-centered care. Full article

With the growth of the plant-based food sector, increasing amounts of by-products are generated. Sea buckthorn pomace (SBP), a by-product of juice and other manufacturing products, is rich in bioactive compounds such as phenolics, oligosaccharides, proteins, and dietary fiber. The aim of the study was to evaluate the impact of modification methods, such as enzymatic hydrolysis and supercritical carbon dioxide extraction (SFE-CO₂), on the chemical composition and technological properties of SBP. SBP and SBP obtained after SFE-CO₂ (SBP-CO₂) were enzymatically modified using Pectinex^® Ultra Tropical, Viscozyme^® L, and Celluclast^® 1.5 L (Novozyme A/S, Bagsværd, Denmark). The SBP’s main constituent was insoluble dietary fiber (IDF), followed by crude proteins and lipids (respectively, 58.7, 21.1 and 12.6 g/100 in d.m.). SFE-CO₂ reduced the lipid content (by 85.7%) in the pomace while increasing protein and TDF content. Enzymatic hydrolysis decreased the content of both soluble dietary fiber (SDF) and IDF, and increased the content of mono- and oligosaccharides as well as free phenolics, depending on the commercial enzyme preparation used in SBP and SBP-CO₂ samples. Celluclast^® 1.5 L was the most effective in hydrolyzing IDF, while Viscozyme^® L and Pectinex^® Ultra Tropical were the most effective in degrading SDF. Enzymatic treatment improved water swelling capacity, water retention capacity, water solubility index, oil retention capacity of SBP and SBP-CO₂; however, it did not have a significant effect on the stability of the emulsions. Modification of SBP by SFE-CO₂ effectively increased WSC and WSI, however it reduced WRC. These findings highlight the potential of targeted modifications to enhance the nutritional and technological properties of SBP for functional food applications. Full article