Search Results (7,480)

Diabetic foot ulcers (DFUs), which affect approximately 15% of individuals with diabetes mellitus (DM), result from complex molecular disturbances involving chronic hyperglycemia, immune dysfunction, and infection. At the molecular level, chronic hyperglycemia promotes the formation of advanced glycation end products (AGEs), activates the AGE-RAGE-NF-κB axis, increases oxidative stress, and impairs macrophage polarization from the pro-inflammatory M1 to the reparative M2 phenotype, collectively disrupting normal wound healing processes. The local wound environment is further worsened by antibiotic-resistant polymicrobial infections, which sustain inflammatory signaling and promote extracellular matrix degradation. The rising threat of antimicrobial resistance complicates infection management even further. Recent studies emphasize that optimal glycemic control using antihyperglycemic agents such as metformin, Glucagon-like Peptide 1 receptor agonists (GLP-1 receptor agonists), and Dipeptidyl Peptidase 4 enzyme inhibitors (DPP-4 inhibitors) improves overall metabolic balance. These agents also influence angiogenesis, inflammation, and tissue regeneration through pathways including AMP-activated protein kinase (AMPK), mechanistic target of rapamycin (mTOR), and vascular endothelial growth factor (VEGF) signaling. Evidence indicates that maintaining glycemic stability through continuous glucose monitoring (CGM) and adherence to antihyperglycemic treatment enhances antibiotic effectiveness by improving immune cell function and reducing bacterial virulence. This review consolidates current molecular evidence on the combined effects of glycemic and antibiotic therapies in DFUs. It advocates for an integrated approach that addresses both metabolic and microbial factors to restore wound homeostasis and minimize the risk of severe outcomes such as amputation. Full article

Phewa Lake, Nepal’s second-largest natural lake, is under increasing ecological stress due to sedimentation, shoreline encroachment, and water quality decline driven by rapid urban growth, fragile mountainous catchments, and changing climate patterns. This study employs an integrated approach combining sediment yield estimation from its catchment using RUSLE, shoreline encroachment analysis via satellite imagery and historical records, and identification of pollution sources and socio-economic factors through field surveys and community consultations. The results show that steep, sparsely vegetated slopes are the primary sediment sources, with Harpan Khola (a tributary of Phewa Lake) contributing over 80% of the estimated 339,118 tons of annual sediment inflow. From 1962 to 2024, the lake has lost approximately 5.62 sq. km of surface area, primarily due to a combination of sediment deposition and human encroachment. Pollution from untreated sewage, urban runoff, and invasive aquatic weeds further degrades water quality and threatens biodiversity. Based on the findings, this study proposes a way forward to mitigate sedimentation, encroachment, and pollution, along with a sustainable revitalization plan. The approach of this study, along with the proposed sustainability measures, can be replicated in other lake systems within Nepal and in similar watersheds elsewhere. Full article

Expansive clays damage the foundations, slabs, and utilities of low- and mid-rise buildings, threatening daily operations and incurring billions of dollars in costs globally. This study pioneers a domain-informed machine learning framework, coupled with a collinearity-aware feature selection strategy, to predict soil swell potential solely from routine index properties. Following hard-limit filtering and Unified Soil Classification System (USCS) screening, 291 valid samples were extracted from a public dataset of 395 cases. A random forest benchmark model was developed using five correlated features, and a multicollinearity analysis, as indicated by the variance inflation factor, revealed exact linear dependence among the Atterberg limits. A parsimonious two-variable model, based solely on plasticity index (PI) and clay fraction (C), was retained. On an 80:20 stratified hold-out set, this simplified model reduced root mean square error (RMSE) from 9.0% to 6.8% and maximum residuals from 42% to 16%. Bootstrap analysis confirmed a median RMSE of 7.5% with stable 95% prediction intervals. Shapley Additive Explanations (SHAP) analysis revealed that PI accounted for approximately 75% of the model’s influence, highlighting the critical swell surge beyond PI ≈ 55%. This work introduces a rule-based cleaning pipeline and collinearity-aware feature selection to derive a robust, two-variable model balancing accuracy and interpretability, a lightweight, interpretable tool for foundation design, GIS zoning, and BIM workflows. Full article

Approximately 20% of emissions from air travel are attributed to the auxiliary power units (APUs) carried in commercial aircraft. This paper proposes to reduce greenhouse gas emissions in international air transport by adopting proton-exchange membrane (PEM) fuel cells to replace APUs in commercial aircraft: we consider the design of three compressed hydrogen storage vessels made of 304 stainless steel, 6061-T6 aluminium, and Grade 5 (Ti-6Al-4V) titanium and capable of delivering 440 kW—enough for a PEM fuel cell for a Boeing 777. Complete structural analyses for pressures from 35 MPa to 70 MPa and wall thicknesses of 25, 50, 100, and 150 mm are used to determine the optimal material for aviation applications. Key factors such as deformation, safety factors, and Von Mises equivalent stress are evaluated to ensure structural integrity under a range of operating conditions. In addition, CO₂ emissions from a conventional 440 kW gas turbine APU and an equivalent PEM fuel cell are compared. This study provides insights into optimal material selection for compressed hydrogen storage vessels, emphasising safety, reliability, cost, and weight reduction. Ultimately, this research aims to facilitate the adoption of fuel cell technology in aviation, contributing to greenhouse emissions reduction and hence sustainable air transport. Full article

Tissue hypoxia is commonly observed in head cancers and contributes to both molecular and functional changes in tumour cells. It is known to stimulate erythropoiesis, angiogenesis, and metabolic alterations within tumour cells. Glioblastoma, a type of brain tumour, is characterized by rapid proliferation and aggressive growth. Recent studies have indicated that natural products may hold potential as components of cancer therapy. Among these, Polish propolis and its active compound, quercetin, have demonstrated promising anti-cancer properties. The aim of this study was to evaluate the concentrations of selected cytokines—specifically IL-6, IL-9, vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF-BB), interferon gamma-induced protein 10 (IP-10), and monocyte chemoattractant protein-1 (MCP-1)—produced by astrocytes of the CCF-STTG1 cell line. The cytotoxic effects of ethanolic extract of propolis (EEP) and quercetin were assessed using the MTT assay. Astrocytes were stimulated with lipopolysaccharide (LPS, 200 ng/mL) and/or IFN-α (100 U/mL), followed by treatment with EEP or quercetin (25–50 µg/mL) under hypoxic conditions for two hours. Cytokine concentrations were measured using the xMAP Luminex Multiplex Immunoassay and the Multiplex Bead-Based Cytokine Kit. Our study demonstrated that Polish propolis and its component quercetin modulate the tumour microenvironment in vitro, primarily by altering the levels of specific cytokines. The HCA analysis revealed that IL-6 and MCP-1 formed a distinct cluster at the highest linkage distance (approximately 100% of Dmax), suggesting that their expression patterns are significantly different from those of the other cytokines and that they are more similar to each other than to the rest. PCA analysis showed that EEP-PL (50 μg/mL) with IFN-α and EEP-PL (50 μg/mL) with LPS exert similar activities on cytokine secretion by astrocytes. Similar effects were demonstrated for EEP-PL 50 μg/mL + LPS + IFN-α, EEP-PL 25 μg/mL + IFN-α and EEP-PL 25 μg/mL + LPS + IFN-α. Our findings suggest that Polish propolis and quercetin may serve as promising natural agents to support the treatment of stage IV malignant astrocytoma. Nonetheless, further research is needed to confirm these results. Full article

Ambient PM concentrations are influenced by various emission sources and weather conditions such as temperature, wind speed, and direction. Measurements using optical sensors cannot directly link pollution levels to specific sources. Data from roadside monitoring often show that a significant portion of PM originates from non-traffic sources. Therefore, vehicle-related PM emissions are typically estimated using simulation models based on average emission factors. This study uses the COPERT (Computer Programme to Calculate Emissions from Road Transport) model to estimate emissions from road vehicles under current conditions and future scenarios. These include the introduction of Euro 7 standards and a shift from internal combustion engine (ICE) vehicles to battery electric vehicles (BEVs). The analysis considers exhaust and non-exhaust emissions, as well as indirect emissions from electricity generation for BEV charging. The conducted study showed, among other findings, that replacing internal combustion engine vehicles with electric ones could reduce PM2.5 emissions by approximately 6% (2% when including indirect emissions from electricity generation) and PM10 emissions by about 10% (5% with indirect emissions), compared to the Euro 7 scenario. Full article

Immunological factors have gained growing recognition as key contributors to recurrent pregnancy loss (RPL) after in vitro fertilization (IVF), representing a major challenge in reproductive medicine. RPL affects approximately 1–2% of women trying to conceive naturally and up to 10–15% of those undergoing IVF, where overall success rates remain around 30–40% per cycle. An imbalance in maternal immunological tolerance toward the semi-allogeneic fetus during pregnancy may lead to miscarriage and implantation failure. IVF-related ovarian stimulation and embryo modification offer additional immunological complications that can exacerbate existing immune dysregulation. Recent advances in reproductive immunology have significantly deepened our understanding of the immune mechanisms underlying RPL following IVF, particularly highlighting the roles of regulatory T cells (T regs), natural killer cells, cytokine dysregulation, and disruptions in maternal–fetal immune tolerance. In order to better customize therapies, this evaluation incorporates recently discovered immunological biomarkers and groups patients according to unique immune profiles. Beyond conventional treatments like intralipid therapy and intravenous immunoglobulin, it also examines new immunomodulatory medications that target certain immune pathways, such as precision immunotherapies and novel cytokine modulators. We also discuss the debates over immunological diagnostics and therapies, such as intralipid therapy, intravenous immunoglobulin, corticosteroids, and anticoagulants. The heterogeneity of patient immune profiles combined with a lack of strong evidence highlights the imperative for precision medicine to improve therapeutic consistency. Novel indicators for tailored immunotherapy and emerging treatments that target particular immune pathways have encouraging opportunities to increase pregnancy success rates. Improving management approaches requires that future research prioritize large-scale clinical trials and the development of standardized immunological assessments. This review addresses the immunological factors in RPL during IVF, emphasizing underlying mechanisms, ongoing controversies, and novel therapeutic approaches to inform researchers and clinicians. Full article

Food-borne zoonoses, particularly anisakiosis caused by Anisakis spp., are an increasing public health concern due to the rising consumption of raw fish. Anisakiosis results from the ingestion of third-stage larvae of Anisakidae nematodes, with the genus Anisakis re-sponsible for approximately 97% of human cases. While regulatory protocols exist to minimize infection risk in commercial settings, domestic food preparation often lacks such safeguards, creating a gap in public health protection. In the Canary Islands, a major Spanish aquaculture region, farmed fish exhibit a low Anisakis prevalence, suggesting minimal risk from aquaculture products. In contrast, wild-caught fish demonstrate varia-ble parasitism, with recent studies reporting a 25% prevalence among commercial species. Methods: This study assessed Anisakis exposure in the Canary Islands by measuring specific IgG and IgE antibodies in 1043 serum samples collected from all seven islands between March 2014 and October 2015. ELISA assays detected anti-Anisakis antibodies, and the results were analyzed by age, sex, island, and isoclimatic zone. Results: Overall, 16.9% of samples were IgG-positive and 6.8% were IgE-positive. Seroprevalence was significantly higher in indi-viduals aged 60 years and above. Geographic heterogeneity was notable: La Palma had the highest IgG seroprevalence (35.3%), while El Hierro showed the highest IgE prevalence (16.3%). Temperate isoclimatic zones exhibited higher antibody prevalence than dry zones. These findings indicate variable Anisakis exposure across the Canary Islands, likely influenced by environmental and behavioral factors. Conclusions: The results highlight the need for targeted public health interventions to reduce the anisakiosis risk, particularly in regions and populations with elevated exposure. Full article

Developing a new drug costs approximately one to three billion dollars and takes around ten years; however, this process has only a ten percent success rate. To address this issue, new technologies that combine artificial intelligence (AI) and quantum computing can be leveraged in the pharmaceutical industry. The RSA cryptographic algorithm, developed by Rivest, Shamir, and Adleman in 1977, is one of the most widely used public-key encryption schemes in modern digital security. Its security foundation lies in the computational difficulty of factoring the product of two large prime numbers, a problem considered intractable for classical computers when the key size is sufficiently large (e.g., 2048 bits or more). A future application of using a detailed structural model of a protein is that digital drug design can be used to predict potential drug candidates, thereby reducing or eliminating the need for time-consuming laboratory and animal testing. Knowing the molecular structure of a possible candidate drug can provide insights into how drugs interact with targets at an atomic level, at significantly lower expenditures, and with maximum effectiveness. AI and quantum computers can rapidly screen out potential new drug candidates, determine the toxicity level of a known drug, and eliminate drugs with high toxicity at the beginning of the drug development phase, thereby avoiding expensive laboratory and animal testing. The Food and Drug Administration (FDA) and other regulatory bodies are increasingly supporting the use of in silico to in vitro/in vivo validation methods and assessments of drug safety and efficacy. Full article

In this paper, we provide a novel extended mixed differential model that is appealing to users because of its numerous free parameters. The motivation of this research arises from the opportunity for a general investigation of some outstanding classical and novel dynamical models. The higher energy levels known in the literature can be governed by appropriately added correction factors. Furthermore, the different applications of the considered model can be achieved only after a proper parameter calibration. All these necessitate the use of diverse optimization and approximation techniques. The proposed extended model is especially useful in the important field of decision making, namely the antenna array theory. This is due to the possibility of generating high-order Melnikov polynomials. The work is a natural continuation of the authors’ previous research on the topic of chaos generation via the term ${x\left|x\right|}^{a-1}$. Some specialized modules for investigating the dynamics of the proposed oscillators are provided. Last but not least, the so-defined dynamical model can be of interest for scientists and practitioners in the area of antenna array theory, which is an important part of the decision-making field. The stochastic control of oscillations is also the subject of our consideration. The underlying distributions we use may be symmetric, asymmetric or strongly asymmetric. The same is true for the mass in the tails, too. As a result, the stochastic control of the oscillations we purpose may exhibit a variety of possible behaviors. In the final section, we raise some important issues related to the methodology of teaching Master’s and PhD students. Full article

Background: Transcription factor pancreatic and duodenal homeobox 1 (PDX1) plays a central role in pancreatic development and insulin regulation. However, its role in breast cancer remains largely unexplored. Objective: This study investigated the effects of PDX1 knockdown and overexpression on MCF7 breast cancer cell proliferation and responsiveness to paclitaxel and doxorubicin. Methods: PDX1 knockdown and overexpression models were established in MCF7 cells. Cell viability was assessed using the XTT assay following exposure to paclitaxel (5–100 nM) or doxorubicin (125–10 µM). Gene and protein expression levels were analyzed by qRT-PCR and western blotting. Results: PDX1 knockdown in MCF7 cells led to a significant increase in proliferation compared to the scrambled control, with approximately 3.22-fold at 72 h, whereas PDX1 overexpression markedly reduced proliferation by about 2.4-fold at 72 h when compared with the control. Upon treatment with paclitaxel or doxorubicin, knockdown cells showed higher viability, indicating reduced drug sensitivity. In contrast, PDX1-overexpressing cells exhibited a significant decrease in viability after treatment with both drugs, demonstrating enhanced sensitivity. Conclusions: PDX1 exhibits tumor-suppressive properties in MCF7 cells and modulates drug response, suggesting that it may serve as a biomarker or therapeutic target in hormone receptor-positive breast cancer. Full article

Cities are the growth engines responsible for shaping the global economy, major contributors to climate change, and are significantly affected by it. However, the United Nations adopted the Sustainable Development Goals (SDGs) to make these cities and human settlements inclusive, safe, resilient, and sustainable. Yet, the rapid and unplanned urban expansion exacerbates various environmental challenges and reduces green cover in urban areas. To address these issues and meet the SDGs, stakeholders need to emphasise and optimise urban spaces. This study investigates the borough-level analysis of green spaces and human exposure to green spaces across London using satellite-derived datasets on vegetation and socio-economic factors to examine the variations in urban vegetation cover and urban population exposure to vegetation cover between 2017 and 2024. This study highlights the spatial disparity in green space coverage and exposure to green space between the inner and outer boroughs of London. The methodology used here suggests an average loss of approximately 11 and 9 percent in green space coverage and green space exposure to population, respectively, between 2017 and 2024 across London boroughs. Full article

To elucidate the key material parameters governing the tribological performance of ceramic composites under dry sliding against steel, this study presents a comprehensive comparative assessment of the microstructural characteristics, mechanical performance, and tribological behavior of two alumina–zirconia (Al₂O₃–ZrO₂) ceramic composites, each reinforced with a 42 vol.% carbide phase: zirconium carbide (ZrC) and tungsten carbide (WC). Specifically, tungsten carbide (WC) was selected for its exceptional bulk mechanical properties, while zirconium carbide (ZrC) was chosen to contrast its potentially different interfacial reactivity against a steel counterface. ZrC and WC were selected as reinforcing phases due to their high hardness and distinct chemical and interfacial properties, which were expected to critically affect the wear and friction behavior of the composites under demanding conditions. Specimens were consolidated via spark plasma sintering (SPS). The investigation encompassed macro- and nanoscale hardness measurements (Vickers hardness HV₁, HV₁₀; nanoindentation hardness H), elastic modulus (E), fracture toughness (K_IC), coefficient of friction (COF), and specific wear rate (W_s) under unlubricated reciprocating sliding against 100Cr6 steel at normal loads of 10 N and 25 N. The Al₂O₃–ZrO₂–WC composite exhibited an ultrafine-grained microstructure and markedly enhanced mechanical properties (HV₁₀ ≈ 20.9 GPa; H ≈ 33.6 GPa; K_IC ≈ 4.7 MPa·m^½) relative to the coarse-grained Al₂O₃–ZrO₂–ZrC counterpart (HV₁₀ ≈ 16.6 GPa; H ≈ 27.0 GPa; K_IC ≈ 3.2 MPa·m^½). Paradoxically, the ZrC-reinforced composite demonstrated superior tribological performance, with a low and load-independent specific wear rate (W_s ≈ 1.2 × 10⁻⁹ mm³/Nm) and a stable steady-state COF of approximately 0.46. Conversely, the WC-reinforced system exhibited significantly elevated wear volumes—particularly under the 25 N regime—and a higher, more fluctuating COF. Scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDX) of the wear tracks revealed the formation of a continuous, iron-enriched tribofilm on the ZrC composite, derived from counterface material transfer, whereas the WC composite surface displayed only sparse tribofilm development. These findings underscore that, in steel-paired tribological applications of Al₂O₃–ZrO₂–based composites, the efficacy of interfacial tribolayer generation can supersede intrinsic bulk mechanical attributes as the dominant factor governing wear resistance. Full article

Lung cancer is one of the most common and deadly forms of cancer worldwide, despite sustained efforts to encourage smoking cessation and raise awareness of the risk factors. In Romania, lung cancer is a significant health challenge, being the leading cause of death caused by cancer, especially amongst men. The incidence of lung cancer in connective tissue disease (CTD) varies in different studies from 4.5% in rheumatoid arthritis (RA), to 4.4% in polymyositis or dermatomyositis, and up to 11.1% in systemic sclerosis. However, older studies have shown an increased risk of cancer in patients with rheumatoid arthritis (RA), ranging from 10% to 30% compared to the general population, particularly in those undergoing methotrexate therapy. Rheumatoid arthritis affects approximately 40 per 100,000 people annually worldwide, with a three- to four-fold higher incidence in women. Non-small cell lung cancer (NSCLC), the most common lung cancer subtype, has been linked to RA, yet the association remains poorly defined, with limited insight into the underlying molecular mechanisms. We present the case of a 61-year-old male with a 49-pack-year smoking history and a known diagnosis of rheumatoid arthritis, currently managed with methotrexate therapy. He was admitted for evaluation due to a progressive decline in general condition, characterized by worsening dyspnea and chest pain, symptoms that had been longstanding but had markedly exacerbated over the past two weeks. Based on a chest CT performed prior to the patient’s admission to our clinic, subsequent diagnostic investigations established the diagnosis of pulmonary adenocarcinoma. The diagnostic process proved to be particularly challenging due to the presence of multiple comorbidities, which significantly impacted both the diagnostic approach and the overall clinical trajectory. Full article

As power grids continue to expand in scale, the occurrence of cascading failures within them can lead to significant economic losses. Therefore, assessing the criticality of grid nodes is crucial for ensuring the secure and stable operation of power systems and for mitigating losses when cascading failures occur. The classical Local Link Similarity (LLS) algorithm in complex networks evaluates the importance of network nodes from a neighborhood topology perspective, but it suffers from issues such as the excessive weighting of node degrees and the neglect of electrical parameters. Based on the classical algorithm, this paper first develops the Improved Local Link Similarity (ILLS) algorithm by substituting alternative similarity metrics and comparatively evaluating their performance. Building upon the ILLS, we then propose the Electrical LLS (ELLS) algorithm by integrating node power flow and electrical coupling connectivity as multiplicative factors, with optimal combinations determined via simulation experiments. Compared to classical approaches, ELLS demonstrates superior adaptability to power grid contexts and delivers enhanced accuracy in power system node importance assessments. These algorithms are applied to rank the node importance in the IEEE 300-bus system. Their performance is evaluated using the loss-of-load-size metric, comparing ELLS, ILLS, and the classical algorithm. The results demonstrate that under the loss-of-load-size metric, the ELLS algorithm achieves approximately 25% higher accuracy compared to both the ILLS and the classical algorithm, validating its effectiveness. Full article