Search Results (6,155)

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

Skin disorders are common and often chronic conditions with significant therapeutic challenges. Limitations of conventional treatments, such as adverse effects and antimicrobial resistance, have increased interest in plant-based alternatives. This article presents the phytochemical composition and pharmacological potential of several medicinal plants traditionally used in the treatment of skin diseases, including Rubus vulgaris, Plantago major, Artemisia terrae-albae, and Eryngium planum. Based on an analysis of scientific literature, the presence of bioactive compounds—including flavonoids, anthocyanins, phenolic acids, tannins, and sesquiterpenes—is summarized, along with their antioxidant, anti-inflammatory, and antimicrobial effects. Emphasis is placed on the correlation between traditional ethnomedicinal applications and pharmacological mechanisms. The findings support the potential of these species as sources for dermatological phytotherapeutics. Further research is needed to standardize active constituents, assess safety, and conduct clinical validation. Full article

Cancer and infectious diseases are major causes of global morbidity and mortality stressing the need to find novel drugs with promising dual anticancer and antimicrobial efficacy. Gold complexes have been studied for the past years due to their anticancer properties, with a few of them displaying antimicrobial properties, which support their pharmacological interest. Within this scope, we investigated six gold bisdithiolate complexes [Au (bdt)₂]⁻ (1), [Au (dcbdt)₂]⁻ (2), [Au (3-cbdt)₂]⁻ (3), [Au (4-cbdt)₂]⁻ (4), [Au (pdt)₂]⁻ (5) and [Au (dcdmp)₂]⁻ (6), and) against the ovarian cancer cell lines A2780 and A2780cisR, the Gram-positive bacteria Staphylococcus aureus Newman, the Gram-negative bacteria Escherichia coli ATCC25922 and Burkholderia contaminans IST408, and the pathogenic yeasts Candida glabrata CBS138 and Candida albicans SC5134. Complexes 2 and 6, with ligands containing aromatic pyrazine or phenyl rings, substituted with two cyanonitrile groups, showed after 24 h of incubation high anticancer activities against A2780 ovarian cancer cells (IC₅₀~5 µM), being also able to overcome cisplatin resistance in A2780cisR cells. Both complexes induced the formation of ROS, activated caspase-3/7, and induced necrosis (LDH release) in a dose-dependent way, in a greater extent in the case of 6. Among the bacterial and fungal strains tested, only complex 6 presented antimicrobial activity against S. aureus Newman, indicating that this complex is a potential novel anticancer and antibacterial agent. These results delve into the structure-activity relationship of the complexes, considering molecular alterations such as replacing a phenyl group for a pyrazine group, and the inclusion of one or two cyanonitrile appendage groups, and their effects on biological activity. Overall, both complexes were found to be promising leads for the development of future anticancer drugs against low sensitive or cisplatin resistant tumors. Full article

The increasing demand for food to meet the needs of the planet’s growing population requires, among other factors, greater and improved meat production. Meat quality is determined by key consumer-preferred traits, particularly tenderness, juiciness, and flavor. Recently, interest has grown in analyzing the genes associated with these phenotypic characteristics. Single-nucleotide polymorphisms (SNPs) are common genomic variations in cattle and represent the most widely used molecular markers. Research on SNP variation is now a major focus of genomic studies aimed at improving meat quality. Leptin levels reflect the amount of adipose tissue in meat, also known as marbling. Several SNPs in the leptin gene and its receptor have been linked to this meat quality trait. Similarly, SNPs in the calpain/calpastatin system play a significant role in postmortem muscle proteolysis and pork tenderness. This review examines these genetic variants as markers involved in the expression of phenotypic traits in meat products and explores their mechanisms of action. Additionally, it provides insights into the genetic variants associated with production-related characteristics. Full article

Growing interest in the future applications of nanotechnology in medicine has led to groundbreaking developments in nanosensors. Nanosensors are excellent platforms that provide reliable solutions for continuous monitoring and real-time detection of clinical targets. Nanosensors have attracted great attention due to their remarkable sensitivity, portability, selectivity, and automated data acquisition. The exceptional nanoscale properties of nanomaterials used in the nanosensors boost their sensing potential even at minimal concentrations of analytes present in a clinical sample. Along with applications in diverse sectors, the beneficial aspects of nanosensors have been exploited in healthcare systems to utilize their applications in diagnosing, treating, and preventing diseases. Hence, in this review, we have presented an overview of the disease-prognostic applications of nanosensors in chronic diseases through a detailed literature analysis. We focused on the advances in various nanosensors in the field of major diseases such as cancer, cardiovascular diseases, diabetes mellitus, and neurodegenerative diseases along with other prevalent diseases. This review demonstrates various categories of nanosensors with different nanoparticle compositions and detection methods suitable for specific diagnostic applications in clinical settings. The chemical properties of different nanoparticles provide unique characteristics to each nanosensors for their specific applications. This will aid the detection of potential biomarkers or pathological conditions that correlate with the early detection of various diseases. The potential challenges and possible recommendations of the applications of nanosensors for disease diagnosis are also discussed. The consolidated information present in the review will help to better understand the disease-prognostic potentials of nanosensors, which can be utilized to explore new avenues in improved therapeutic interventions and treatment modalities. Full article

Background/Objectives: Intramuscular immunization elicits systemic IgG and is the primary route of vaccine administration in humans. However, there is growing interest in utilizing other routes of administration to tailor antibody profiles, increase immunity at primary sites of infection, simplify administration, and eliminate needle waste. Here, we investigated the antibody profiles elicited by immunization with bacteriophage virus-like particle vaccine platforms at various routes of administration. Methods: We chose two model bacteriophage vaccines for investigation: bacteriophage MS2 virus-like particles (VLPs) recombinantly displaying a short, conserved peptide from Chlamydia trachomatis major outer membrane protein (MS2) and bacteriophage Qβ VLPs displaying oxycodone through chemical conjugation (Qβ). We comprehensively characterized the antibodies elicited systemically and at various mucosal sites when the vaccines were administered intramuscularly, intranasally or periocularly with or without an intramuscular prime using various prime/boost schemes. Results: Intranasal and periocular immunization elicited robust mucosal and systemic IgA responses for both MS2 and Qβ. The intramuscular prime followed by intranasal or periocular boosts elicited broad antibody responses, and increased antibodies titers at certain anatomical sites. Conclusions: These findings demonstrate the tractability of bacteriophage VLP-based vaccines in generating specific antibody profiles based on the prime–boost regimen and route of administration. Full article

Computational Thinking (CT) has been an important concept for the computer science education community in the last 20 years. In this work we performed a systematic review of the literature regarding the computational thinking of children from kindergarten to primary school. We compiled a large dataset of one hundred and twenty (120) studies from the literature. Through analysis of these studies, we tried to reveal important insights and draw interesting and valid conclusions. We analyzed various qualitative and quantitative aspects of the studies, including the sample size, the year of publication, the country of origin, the studies’ design and duration, the computational tools used, and so on. An important aspect of the work is to highlight differences between different study designs. We identified a total of 120 studies, with more than half of them (>50%) originating from Asian countries. Most studies (82.5%) conducted some form of intervention, aiming to improve their computational thinking in students. A smaller proportion (17.5%) were assessment studies in which the authors conducted assessments regarding the children’s computational thinking. On average, intervention studies had a smaller number of participants, but differences in duration could not be identified. There was also a lack of large-scale longitudinal studies. Block-based coding (i.e., Scratch) and Plugged and Unplugged activities were observed in high numbers in both categories of studies. CT assessment tools showed great variability. Efforts for standardization and reaching a consensus are needed in this regard. Finally, robotic systems have been found to play a major role in interventions over the last years. Full article

Smart cities are technologically advanced urban environments where interconnected systems and data-driven technologies enhance public service delivery and quality of life. These cities rely on information and communication technologies, the Internet of Things, big data, cloud computing, and other Industry 4.0 tools to support efficient city management and foster citizen engagement. Often referred to as digital cities, they integrate intelligent infrastructures and real-time data analytics to improve mobility, security, and sustainability. Ubiquitous sensors, paired with Artificial Intelligence, enable cities to monitor infrastructure, respond to residents’ needs, and optimize urban conditions dynamically. Given the increasing significance of Industry 4.0 in urban development, this study adopts a bibliometric approach to systematically review the application of these technologies within smart cities. Utilizing major academic databases such as Scopus and Web of Science the research aims to identify the primary Industry 4.0 technologies implemented in smart cities, assess their impact on infrastructure, economic systems, and urban communities, and explore the challenges and benefits associated with their integration. The bibliometric analysis included publications from 2016 to 2023, since the emergence of urban researchers’ interest in the technologies of the new industrial revolution. The task is to contribute to a deeper understanding of how smart cities evolve through the adoption of advanced technological frameworks. Research indicates that IoT and AI are the most commonly used tools in urban spaces, particularly in smart mobility and smart environments. Full article

Climate change negatively affects agriculture, causing desertification, salinisation, and drought. The biochar hydroinfiltrator (ES Patent No.: ES2793448 B2) is a device that increases the capture of rainwater or irrigation water for crops by increasing infiltration rates. Biochar, produced via biomass pyrolysis, has emerged as a promising agricultural amendment, as it helps to optimise moisture retention and improve soil structure, key aspects for boosting crop yields. There is growing interest in microorganisms’ plant-growth-promoting activity (PGP) by carrying out different activities considered growth promoters. The aim of the present study is to evaluate the use of a biochar hydroinfiltrator as a promoter of microbial activity when it is used in soil. Metagenomic analysis of soils with and without the device reveals that genera Bacillus and Sphingomonas became particularly enriched in soils with hydroinfiltrators. Also, in order to understand the interaction between the uses of biochar together with bacteria PGP, an in vitro test was carried out. Two microorganisms, previously selected for their characteristics as plant growth promoters, were inoculated in soils with and without biochar and they grew better after 15 to 30 days of inoculation, showing major CFU counts. This combined strategy—biochar hydroinfiltrator and PGP bacteria—offers an innovative, eco-friendly approach to sustainable agriculture, particularly under drought stress. Full article

The olive oil industry, a key component of Southern Europe’s agricultural sector, generates large amounts of by-products during processing, including olive leaves, branches, stones, and seeds. In the context of growing environmental concerns and limited natural resources—particularly in the Mediterranean regions—there is increasing interest in circular economy approaches that promote the valorization of agricultural residues. These by-products are rich in bioactive compounds, particularly phenolics such as oleuropein and hydroxytyrosol, which are well known for their antioxidant and anti-inflammatory activities. This study aimed to evaluate the phenolic content and antioxidant capacity of by-products from three olive cultivars using high-performance liquid chromatography with photodiode array detection (HPLC–PDA) and mass spectrometry (MS). The leaves and seeds, particularly from the “Cobrança” and a non-identified variety, presented the highest antioxidant activity, as well as the highest concentration of phenolic compounds, demonstrating once again the direct relationship between these two parameters. The identification of the compounds present demonstrated that the leaves and branches have a high diversity of phenolic compounds, particularly secoiridoids, flavonoids, phenylpropanoids, phenylethanoids, and lignans. An inverse relationship was observed between the chlorophyll and carotenoid content and the antioxidant activity, suggesting that phenolic compounds, rather than pigments, are the major contributors to antioxidant properties. Therefore, the by-products of the olive oil industry are a valuable source of sustainable bioactive compounds for distinct industrial sectors, such as the food, nutraceutical, and pharmaceutical industries, aligning with the European strategies for resource efficiency and waste reduction in the agri-food industries. Full article

Background: Preimplantation genetic testing for polygenic diseases (PGT-P) is a reproductive technology that has made it possible to assign risk scores to embryos for various complex polygenic conditions such as diabetes, hypertension, breast cancer, and schizophrenia. Whether there is public interest in utilizing PGT-P and what public opinions are regarding this technology is unknown. Therefore, the objective of our study was to evaluate the opinion of the general United States (US) public regarding PGT-P. Methods: A web-based questionnaire consisting of 25 questions was administered to a nationally representative sample of adult US residents according to age and sex. The survey contained a description of PGT-P, followed by questions with Likert-scale responses ranging from strongly agree to strongly disagree. Results: Of the 715 respondents recruited, 673 (94%) completed the survey. Most respondents agreed that use of PGT-P is ethical (54%), and another 37% were neutral; however, approximately 9% of respondents disagreed and were opposed to the use of PGT-P. Those that opposed PGT-P cited that it was “unethical” (46%) or “not natural” (39%), believed children could be negatively affected (31%), or stated that it went against their religion (15%). The majority of respondents did not know whether PGT-P was safe for embryos (68%) or children (67%) and felt that anyone should be able to utilize it (53%). Conclusions: Participants who were younger, were Atheist, or were Democrats were more likely to agree that “PGT-P is ethical”. This study identified that more than half of respondents supported the use of PGT-P. However, concerns regarding its safety and ethical implications persist. Full article

According to the World Health Organization, musculoskeletal injuries affect more than 1.71 billion people around the world. These injuries are a major public health issue and the leading cause of disability. There has been a recent interest in hydrogels as a potential biomaterial for musculoskeletal tissue regeneration. This is due to their high water content (70–99%), ECM-like structure, injectability, and controllable degradation rates. Recent preclinical studies indicate that they can enhance regeneration by modulating the release of bioactive compounds, growth factors, and stem cells. Composite hydrogels that combine natural and synthetic polymers, like chitosan and collagen, have compressive moduli that are advantageous for tendon–bone healing. Some of these hydrogels can even hold up to 0.8 MPa of tensile strength. In osteoarthritis models, functionalized systems such as microspheres responsive to matrix metalloproteinase-13 have demonstrated disease modulation and targeted drug delivery, while intelligent in situ hydrogels have exhibited a 43% increase in neovascularization and a 50% enhancement in myotube production. Hydrogel-based therapies have been shown to restore contractile force by as much as 80%, increase myofiber density by 65%, and boost ALP activity in bone defects by 2.1 times in volumetric muscle loss (VML) models. Adding TGF-β3 or MSCs to hydrogel systems improved GAG content by about 60%, collagen II expression by 35–50%, and O’Driscoll scores by 35–50% in cartilage regeneration. Full article

This research examines the shifting geography of small firm innovation in the U.S. by tracking the location of small business innovation research (SBIR) and small business technology transfer (STTR) awardees between 2010 and 2024. The SBIR and STTR are “seed fund” awards coordinated by the Small Business Administration (SBA) and funded through 11 U.S. federal agencies. Of particular interest is whether the number of individual SBA awards, awarded firms, and/or funding amounts are (1) becoming increasingly concentrated within regional innovation hubs and (2) exhibiting a shift toward or away from urban centers and other walkable, transit-accessible urban neighborhoods, particularly since 2020 and the COVID-19 pandemic. While the rise of remote work and pandemic-related fears may have reduced the desirability of urban spaces for both living and working, there remain significant benefits to spatial agglomeration that may be especially crucial for startups and other small firms in the knowledge- or information-intensive industries. The results suggest that innovative activity of smaller firms has indeed trended toward more centralized, denser, and walkable urban areas in recent years while also remaining fairly concentrated within major metropolitan innovation hubs. The pandemic appears to have resulted in a measurable, though potentially short-lived, cessation of these trends. Full article

Background: Despite growing interest in the literature on Parkinson’s disease (PD) on cognitive functioning, financial incompetence—a crucial aspect of daily living—and its modulation susceptibility by PD treatment regimens remains relatively understudied. Objective: This systematic review and meta-analysis aimed to synthesize existing evidence on how PD treatments affect financial capacity, assessing both direct financial competence and cognitive or behavioral proxies of financial decision-making. Methods: A comprehensive literature search according to PRISMA protocol was conducted across major biomedical databases, supplemented by gray literature and manual reference list checks. Eligible studies assessed financial capacity directly or indirectly through cognitive proxies (e.g., executive function, decision-making) or financial risk behaviors (e.g., impulse control disorders). Two separate meta-analyses were performed. Heterogeneity (I²), publication bias (Egger’s test), and sensitivity analyses were conducted to assess robustness. Results: Twenty-three studies met inclusion criteria. One study directly measured financial capacity and was analyzed narratively, reporting diminished competence in patients on levodopa therapy. A meta-analysis of cognitive proxies (10 studies) showed a moderate effect size (Hedges’ g = 0.70, 95% CI [0.45, 0.92], p < 0.001), indicating that PD treatments negatively affect executive function and financial decision-making. A second meta-analysis of impulse control and financial risk behaviors (12 studies) revealed a larger effect size (Hedges’ g = 0.98, 95% CI [0.75, 1.22], p < 0.001), strongly linking dopamine agonists to increased financial risk-taking. Moderate heterogeneity (I² = 45.8–60.5%) and potential publication bias (Egger’s test p = 0.027) were noted. Conclusions: These findings suggest that PD treatments negatively impact financial decision-making both directly and indirectly through cognitive and behavioral pathways. Integrating financial decision-making assessments into PD care, particularly for patients on dopamine agonists, is recommended. Future research should prioritize longitudinal studies and standardized neuropsychological measures to guide clinical practice and optimize patient outcomes. Full article

Stevia rebaudiana Bertoni, a semi-perennial herb from the Asteraceae family, is native to the Paraguay–Brazil border region. The growing industrial interest in this species is due to its natural sweetening properties, such as steviol and its derivatives, which offer sweetness without adding calories. Morphological traits are crucial for assessing genetic variability and ensuring distinctness, homogeneity, and stability (DHS) for cultivar protection. This study characterized 19 elite Stevia genotypes from Embrapa Cerrados’ Active Germplasm Bank (BAG) using 21 morphological descriptors from Brazil’s Ministry of Agriculture, Livestock, and Supply (MAPA). Genetic distances were calculated using the simple coincidence index complement method, and clustering was performed via the Unweighted Pair-Group Method with Arithmetic Mean (UPGMA). The results showed that 17 of the 21 descriptors (>80%) effectively differentiated the genotypes, revealing significant genetic variability. Dendrogram analysis identified at least four major similarity groups, highlighting the potential of these genotypes for Stevia breeding programs. These findings underscore the suitability of these elite genotypes for developing superior varieties adapted to Cerrado conditions, supporting future cultivation and genetic improvement efforts. Full article