Search Results (413)

Introduction: Tuberculosis [TB] and diabetes mellitus (DM) remain major public health concerns worldwide. TB negatively affects an individual’s glucose tolerance, increasing the risk of developing DM. Similarly, DM reduces the host’s ability to fight TB infection and increases the likelihood of developing TB and poor response to TB medication. This study analysed stigma and health-seeking behaviour in a sub-district of Accra Metropolis. Methods: We used a mixed-methods research approach involving a cross-sectional survey and in-depth interviews to explore community knowledge, stigma, and health-seeking behaviour related to TB and DM. A total of 437 individuals were selected for a survey using a simple random sampling technique, while 22 participants, including three TB patients, four nurses, one medical doctor, four students from a nursing and midwifery school, five students from a school of hygiene, and five community members, were involved in the study. Healthcare providers and patients were purposively selected, while students and community members were recruited through convenience sampling. Descriptive and logistic regression analyses were performed on the quantitative data using STATA, while the qualitative data were thematically analysed using the MAXQDA software. Results: Participants’ age, sex, and educational levels were significantly associated with their knowledge of TB and DM. Males were 0.600 times as likely as females to be knowledgeable about DM (95% CI: 0.386–0.934, p = 0.024). Social determinants of health, such as poverty, local beliefs, stigma, and negative attitudes from healthcare workers, may influence TB patients’ preference for traditional remedies over biomedical treatment. Conclusion: Therefore, we observed that addressing cultural barriers, stigma, and financial costs related to TB and diabetes care will help increase patients’ willingness for biomedical treatment. Full article

Long-term outcomes after hepatectomy for alveolar echinococcosis (AE) in immunosuppressed patients remain poorly investigated. This study evaluated recurrence rates and recurrence-free/overall survivals (RFS/OS) after AE resection in immunocompromised and immunocompetent patients. Consecutive patients operated for liver AE in two university hospitals were retrospectively collected (2000–2021). Immunosuppressed patients were defined as patients who had a reduced ability to fight infection due to certain diseases or treatments. 195 patients had hepatectomy for liver AE. Preoperative albendazole was given in 111 cases (57%). Fifty-two patients (27%) were considered immunosuppressed. Patients in the immunosuppressed and immunocompetent cohorts had similar preoperative characteristics. Recurrences occurred in 10 patients (immunosuppressed group: 4, non-immunosuppressed group: 6) within a median follow-up of 58 months (95%CI 48–68). No significant differences in RFS and OS were found between the immunosuppressed and immunocompetent groups (212 vs. 206 months, p = 0.625 and 236 vs. 210 months, p = 0.282). Two-year recurrence rates were 0% in the immunosuppressed cohort and 1% (1/142) in the immunocompetent patients (p = 0.466). Absence of preoperative albendazole and lesion size were predictive of recurrence after hepatectomy. Immunosuppression was not found to be a risk factor for recurrence (HR 1.4, p = 0.626). In this bicentric study, immunocompromised patients did not have significantly different recurrence rates, RFS, and OS than immunocompetent patients. Full article

Overcoming the climate crisis and growing environmental pollution is a fundamental problem facing society in the 21st century. These problems have both health and economic implications. Developing an effective system for managing pollutants and greenhouse gases seems crucial. The use of nanomaterial-based technologies may be the answer. The dynamic development of nanoscience has led to the discovery of unique properties of nanomaterials, resulting primarily from quantum constraints, while the development of techniques for obtaining nanostructures has increased their availability. The ability to be used in filtration processes, as well as for adsorption, photocatalysis, and disinfection, predisposes nanomaterials to applications in environmental bioremediation and wastewater treatment. This article provides an overview of technologies currently in use or that may play a significant role in the fight for a healthier environment in the near future. The results of using nanomaterial-based technologies in air and water purification processes to date have been positive, promising further development of effective green technologies. Full article

Background: ESKAPE constitutes a group of six nosocomial bacteria that can evade available antimicrobials due to their great potential to develop multi-drug resistance and biofilm-forming abilities. These pathogens often cause hospital-acquired infections and pose a serious threat to public health. The search for efficient innovative therapeutic strategies to fight ESKAPE bacteria have been intensively investigated topics. One promising approach to fight resistant pathogens and their biofilms is combination therapy, which allows the effectiveness against microorganisms to be increased while reducing the applied concentrations and risks of potential unwanted side effects. Objectives: The object of the study was to determine if there is an interaction of short lipopeptides ((C₁₀)₂-KKKK-NH₂, C₁₆-KK-NH₂) together with erythromycin and tetracycline against pathogens of the ESKAPE group (Acinetobacter baumannii, Enterobacter aerogenes, Enterococcus faecium Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus). Methods: The checkerboard assay was used to examine the activity of compounds applied in combinations against ESKAPE strains in planktonic cells and toward biofilms formed by Staphylococcus aures and Pseudomonas aeruginosa. Results: The lipopeptides demonstrated a great potential of their application as additives to conventional antimicrobials against Gram-negative bacteria, including microorganisms within biofilms. Full article

Malware remains a major threat to computer systems, posing serious risks to security and privacy by stealing sensitive data, disrupting services, and compromising system integrity. Traditional detection methods are often ineffective against rapidly evolving malware. In response, data-driven deep learning has emerged as a powerful alternative. Recent models have demonstrated promising performance in detecting malicious behavior by learning from these behavioral traces. Behavior-based detection represents a significant advancement in the fight against malware. This paper introduces a deep stacked Graph Convolutional Network (GCN) for effective malware behavioral analysis. The aggregation of multiple GCN layers and blocks results in dynamically performed Jumping Knowledge (JK) method, especially Long Short-Term Memory (LSTM). LSTM-based JK dynamically selects and weights the most informative GCN layers for each node to improve the model’s ability. Experimental results demonstrate the superior performance of our deep stacked Graph Convolutional Network with Dynamic Aggregation (DSGCN-DA) model, achieving an accuracy of 98.93% on the API-Call-Sequences dataset, outperforming the state-of-the-art approaches. Full article

The rapid spread of misinformation on social media has emerged as a major societal issue. Over 40% of British social media news-sharers admitted they had shared inaccurate or fake news. The extensive distribution of false information causes public trust deterioration while modifying public opinions and potentially destabilizing social and political systems. There are profound challenges due to this hard-to-detect, hard-to-stop reality and the financials and societal implications are remarkable. As an attempt to limit the challenges created from misinformation this paper introduces some preliminary work on detection of fake news and verification of their reliability based on online content. Large language models (LLMs) are being used along with natural language processing (NLP) techniques to evaluate news articles through their linguistic and contextual characteristics. Several models are compared on how they can typically identify typical indicators of misinformation through the analysis of extensive verified datasets to develop an ability to classify content as authentic or fabricated. This work has been through thorough testing to determine its operational effectiveness and dependability after completion. We present a relatively easy-to-use tool which enables a wide range of people also for those without a background in computer science to easily verify news accuracy before sharing or trusting it. This work could help to stop false information from spreading while promoting fact-based discussions and improving digital literacy skills. The research demonstrates how technology fights the fake news crisis to create an informed digital environment which supports public conversation protection and information integrity in the modern digital age. Full article

Algal carotenoids play a promising role in handling chronic diseases due to their diverse bioactive properties, including anti-inflammatory, antioxidant, and anticancer effects. This study assesses the activity of the antioxidant xanthophyll diatoxanthin (Dt), derived from marine diatoms, against triple-negative breast cancer (TNBC) cells using in vitro models, gene expression evaluation, and explores its role in potentiating the cytotoxic effect of chemotherapy. Dt exhibited selective activity against MDA-MB-231 and BT-549 TNBC cells at concentrations ≥12.5 ng/mL, with maximal effects observed at 25 ng/mL while sparing human umbilical vein endothelial cells (HUVECs) at these doses. When combined with doxorubicin (0.1–0.5 μM), Dt enhanced the anti-tumor efficacy in both TNBC cell lines, further reducing cell viability compared with doxorubicin alone (p < 0.05–0.001). Dt also exerted its activity in inhibiting migration and chemotaxis by approximately 30–50% compared with the controls (p < 0.01) and suppressing 3D-tumor spheroid growth at day 12 (up to >50% reduction, p < 0.001). Notably, secretome analysis revealed Dt-induced changes in inflammatory, oxidative and angiogenic mediators, highlighting its ability to modulate the TNBC microenvironment. Dt also downregulated key pro-survival, pro-angiogenic and pro-tumorigenic genes in both TNBC cell lines, supporting its role in disrupting oncogenic pathways. Angiogenesis-related genes were significantly reduced. Dt also decreased the expression of angiogenic mediators in HUVECs, supporting Dt’s role in inhibiting tumor vascularization. Results on gene expression regulation were also confirmed by RNA-Seq analysis. These findings pose Dt as a promising chemopreventing candidate in the challenging fight against TNBC, a well-known type of cancer that is aggressive and resistant to conventional therapies, targeting critical pathways for tumor survival, such as inflammation, angiogenesis, tumor cell growth, and cell migration. Given its selective activity against TNBC cells, ability to enhance chemotherapy efficacy, and modulation of the tumor microenvironment, Dt holds promise as a complementary drug for cancer prevention and interception. Future studies should focus on validating these effects in vivo and exploring Dt’s potential in combinatorial treatment strategies for cancer. Full article

Illegal dumping poses serious risks to ecosystems and human health, requiring effective and timely monitoring strategies. Advances in uncrewed aerial vehicles (UAVs), photogrammetry, and deep learning (DL) have created new opportunities for detecting and characterizing waste objects over large areas. Within the framework of the EMERITUS Project, an EU Horizon Europe initiative supporting the fight against environmental crimes, this study evaluates the performance of pre-trained prompt-based multimodal (PBM) DL models integrated into ArcGIS Pro for object detection and segmentation. To test such models, UAV surveys were specially conducted at a semi-controlled test site in northern Italy, producing very high-resolution orthoimages and video frames populated with simulated waste objects such as tyres, barrels, and sand piles. Three PBM models (CLIPSeg, GroundingDINO, and TextSAM) were tested under varying hyperparameters and input conditions, including orthophotos at multiple resolutions and frames extracted from UAV-acquired videos. Results show that model performance is highly dependent on object type and imagery resolution. In contrast, within the limited ranges tested, hyperparameter tuning rarely produced significant improvements. The evaluation of the models was performed using low IoU to generalize across different types of detection models and to focus on the ability of detecting object. When evaluating the models with orthoimagery, CLIPSeg achieved the highest accuracy with F1 scores up to 0.88 for tyres, whereas barrels and ambiguous classes consistently underperformed. Video-derived (oblique) frames generally outperformed orthophotos, reflecting a closer match to model training perspectives. Despite the current limitations in performances highlighted by the tests, PBM models demonstrate strong potential for democratizing GeoAI (Geospatial Artificial Intelligence). These tools effectively enable non-expert users to employ zero-shot classification in UAV-based monitoring workflows targeting environmental crime. Full article

The combination of antimicrobial agents with different mechanisms of action is an important step in the fight against drug-resistant microorganisms. In this study, the interaction of the lysozyme enzyme with ampicillin and colistin was investigated. These antibiotics are highly effective against Gram-positive (ampicillin) and Gram-negative (colistin) pathogenic microorganisms. Spectroscopic and kinetic methods and molecular docking were used in the research. The results of the spectroscopic analysis confirmed the intermolecular interaction of lysozyme with ampicillin or colistin. The formation of the lysozyme complex with ampicillin was accompanied by mixed quenching of the enzyme fluorescence and changes in its secondary structure (a slight decrease in the content of α-helices). The interaction of lysozyme with colistin was complemented by dynamic quenching of the enzyme fluorescence. The method of molecular docking established that the interactions of lysozyme with colistin were predominantly van der Waals, while hydrogen bonds predominated in the lysozyme complex with ampicillin. Despite the presence of interactions of ampicillin and colistin with amino acid residues from the active site of lysozyme, this did not affect its ability to cause destruction of bacterial cell walls. The results obtained can be used in the development of antibacterial drugs. Full article

This paper constructs a numerical simulation model for the fire and fire-fighting system of an all-electric vehicle ro-ro passenger ship to study the influence of fire characteristics and fire-fighting system layout parameters on the fire-extinguishing system. The simulation results show that the fire can spread to the upper deck within 52 s, and the smoke will fill the main deck within 57 s. The study found that the battery capacity has a super-linear relationship with the fire hazard, and the fire thermal spread radius of a 240 Ah battery can reach 3.5 m. The high-expansion foam system has a low applicability in quickly suppressing battery fires due to its response delay and limited cooling capacity for deep-seated fires; the fire-extinguishing efficiency of fine water mist has spatial dependence: 800 µm droplets achieve effective cooling in the core area of the fire source with stronger penetrating power, while 200 µm droplets show better environmental cooling ability in the surrounding area; at the same time, the large-angle nozzles with an angle of 80–120° have a wider coverage range and perform better in overall temperature control and smoke containment than small-angle nozzles. The study also verified the effectiveness of fire curtains in forming fire compartments through physical isolation, which can reduce the heat radiation range by approximately 3 m. This research provides an innovative solution for improving the fire safety level of transporting all-electric vehicles on ro-ro passenger ships. Full article

Cardiovascular morbidity and mortality rise precipitously during the 6th–9th decades of life, identifying aging as a critical risk factor. Simultaneously, older individuals are susceptible to severe viral infection, raising the question whether shared mechanisms exist that predispose to both cardiovascular disease (CVD) and failing anti-viral immunity. The aging process causes steady decline in immune fitness (immune aging), which undermines the ability to generate protective anti-viral immune responses. Paradoxically, the aging immune system supports unopposed inflammatory pathways (inflammaging), which exacerbates tissue inflammation in CVD, specifically atherosclerosis. Here, we review the current evidence of how innate and adaptive immune aging promotes tissue-destructive inflammation in atherosclerosis while failing to fight viral infections. Further, we consider how these two disease processes mutually influence each other. We propose that mounting an effective anti-viral response induces off-target bystander activation and exhausts immune cells, ultimately exacerbating CVD. Additionally, we explore how atherosclerotic CVD impacts innate immunity through epigenetic modification of hematopoietic precursors and metabolically conditioning immune cells, leading to a dysfunctional immune system that accelerates plaque inflammation while simultaneously impairing host defense. Full article

Background/Objectives: Due to the rising problem of antimicrobial resistance, there is increasing attention in the scientific community towards alternative approaches to combat Antimicrobial-Resistant (AMR) pathogens that do not involve the use of antibiotics. In this regard, the European Medicines Agency (EMA) and the European Food Safety Authority (EFSA) have promoted experimentation with predatory bacteria to fight antibiotic resistance. With the aim of identifying predatory bacteria suitable for the control of antibiotic-resistant bacteria, in this work we isolated a strain of Halobacteriovorax from an estuarine aquatic environment using a CTX-M-producing E. coli strain as prey and characterized it with respect to optimal physico-chemical parameters for growth and predation. Furthermore, we studied its predatory capacity against other E. coli strains and Multi-Drug-Resistant (MDR) Salmonella. Finally, we conducted challenge experiments to evaluate the growth of predator and prey over time. Methods: The Halobacteriovorax strain, designated HE7, was identified by 16S rRNA analysis. To isolate Halobacteriovorax and to evaluate its predatory ability towards different preys, the double-layer agar plating technique was applied. Results: HE7 showed in vitro predatory activity against all MDR strains of E. coli and Salmonella tested. In the 10⁷ predator/10³ prey and 10⁷ predator/10⁷ prey challenges, HE7 after 6 h achieved the total killing and a reduction of about 6 logs in the prey, respectively, maintaining this effect for up to 24 h. Conclusions: The results of this study highlight that HE7, but more generally Halobacteriovorax, could find application both alone and in an integrated context of antimicrobial strategies as an alternative to antibiotics. Full article

Background/Objectives: Extracellular vesicles (EVs) have become key facilitators of communication between cells, significantly influencing various physiological functions. Although EVs originating from mammalian cells have been heavily researched for their therapeutic applications, there is a growing interest in extracellular vesicles derived from edible plants (PDEVs) because of their unique bioactive characteristics. These nanovesicles (NVs) exhibit remarkable biocompatibility, low immunogenicity, and the ability to overcome biological barriers, making them promising candidates for biomedical applications. This study aimed to evaluate the antioxidant and anti-inflammatory properties of NVs isolated from Rosa canina berries. Methods: Antioxidant activity was assessed through in vitro assays, confirming their ability to fight oxidative stress. Additionally, enzymatic inhibition tests were conducted to explore their potential role in regulating key metabolic pathways associated with inflammation and oxidative damage. The antioxidant and anti-inflammatory activity of Rosa canina NVs was further tested on a THP-1 cell-based inflammation model, demonstrating their ability to modulate the inflammatory response at the cellular level. Moreover, the impact of these NVs on gut microbiota was investigated to assess their protective effects on antibiotic-induced dysbiosis. Results: The results demonstrated their ability to modulate oxidative stress, regulate enzymatic pathways, reduce inflammation in THP-1 cells, and influence gut microbiota in a positive manner. Full article

Active compounds used in agriculture are mainly in the form of acids. This applies primarily to substances that are inducers of systemic acquired resistance, which is one of the most promising methods of supporting plants in the fight against pathogens. The physicochemical properties and biological activity of such substances can be improved by derivatizing them to salt forms. We used the concept of ionic liquids to obtain novel compounds in the form of chlormequat ionic liquids. In this study we present synthesis and characterization of a series of novel ionic liquids composed of the chlormequat cation paired with plant resistance-inducing anions, including salicylic acid and its chlorinated derivatives, nicotinic acid and isonicotinic acid. The results indicate that the new compounds in the form of salts are characterized by better biological activity related to SAR induction and lower phytotoxicity compared to the parent compounds as their equivalents in acid forms. The obtained compounds demonstrated the ability to activate defense responses in tobacco and to reduce susceptibility to viral infection, highlighting their potential for further application in crop protection. Full article

The proliferation of counterfeit products poses a substantial threat to numerous industries. Blockchain technology (BCT) offers an effective solution for product traceability, providing a means to combat counterfeiting. However, BCT can verify the authenticity of the information but cannot confirm the veracity of the product itself, a problem known as counterfeiting at the source. To our knowledge, this issue has yet to be studied. The security level of BCT traceability is used to indicate its ability to combat counterfeiting. We establish game-theoretical models to investigate BCT adoption strategies for a typically authentic firm and a premium firm to fight counterfeiting in a vertically differentiated competition. This study demonstrates that BCT reduces deceptive counterfeiters’ incentive to pool with the branded firm and mitigates the negative impact of asymmetric information on the prices, market share, and profits of authentic products in a monopoly. In instances where the proportion of counterfeits is substantial, premium products will lose market share, a phenomenon often referred to as “bad money driving out good money.” In a vertically differentiated competition, if the quality of the premium product is below a certain threshold, it is recommended that the premium firm be the first to adopt BCT, while the typically authentic firm should not follow (Scenario NB). That is, Scenario NB is a win-win situation for both firms in the competition. The premium firm that has adopted BCT can offer a “free ride” to the typically authentic firm. Full article