Search Results (745)

Photodynamic therapy (PDT) has emerged as a promising therapeutic approach owing to its non-invasive nature and minimal toxicity. PDT involves the administration of a photosensitizing agent (PS), which, upon light activation, induces a photodynamic reaction (PDR), leading to targeted cell destruction. However, developing resistance to PDT poses a significant challenge to its effectiveness. Various factors, including properties and administration of PSs, mediate this resistance. Despite the widespread use of substances like 5-aminolevulinic acid (5-ALA) and protoporphyrin, their efficacy is limited due to restricted tumor penetration and a lack of tumor targeting. To address these limitations, nano-delivery techniques and newer PSs like Aza-BODIPY and its derivatives, which offer enhanced tissue penetration, are being explored. In this paper, we provide an overview of resistance mechanisms in PDT and discuss novel methods, substances, and technologies to overcome resistance to improve clinical outcomes in tumor treatment. Full article

Paddy fields are essential for food security and sustaining global dietary needs, yet urban expansion often encroaches on agricultural lands. Analyzing paddy fields and land use/land cover changes over time using satellite images provides critical insights for sustainable food production and balanced urban growth. However, mapping the paddy fields in tropical monsoon areas presents challenges due to persistent weather interference, monsoon-submerged fields, and a lack of training data. To address these challenges, this study proposed a flooding-assisted maximum likelihood classification (F-MLC) method. This approach utilizes accurate training datasets from intersecting flooded paddy field maps from the rainy and dry seasons, combined with the Automated Water Extraction Index (AWEI) to distinguish natural water bodies. The F-MLC method offers a robust solution for accurately mapping paddy fields and land use changes in challenging tropical monsoon climates. The classified images for 1989, 2000, 2013, and 2021 were produced and categorized into the following five major classes: urban areas, vegetation, paddy fields, water bodies, and other lands. The paddy field class derived for each year was validated using samples from various sources, contributing to the overall accuracies ranging from 83.6% to 90.4%, with a Kappa coefficient of between 0.80 and 0.88. The study highlights a significant decrease in paddy fields, while urban areas rapidly increased, replacing 23% of paddy fields between 1989 and 2021 in the watershed. This study demonstrates the potential of the F-MLC method for analyzing paddy fields and other land use changes over time in the tropical watershed. These findings underscore the urgent need for robust policy measures to protect paddy fields by clearly defining urban expansion boundaries, prioritizing paddy field preservation, and integrating these green spaces into urban development plans. Such measures are vital for ensuring a sustainable local food supply, promoting balanced urban growth, and maintaining ecological balance within the watershed. Full article

Deploying and effectively utilizing wireless sensor networks (WSNs) in underwater habitats remains a challenging task. In underwater wireless sensors networks (UWSNs), the availability of a continuous energy source for communicating with nodes is either very costly or is prohibited due to the marine life law enforcement agencies. So, in order to address this issue, we present a Q-learning-based approach to designing an energy-efficient medium access control (MAC) protocol for UWSNs through collision avoidance. The main goal is to prolong the network’s lifespan by optimizing the communication methods, specifically focusing on improving the energy efficiency of the MAC protocols. Factors affecting the energy consumption in communication are adjustments to the interference ranges, i.e., changing frequencies repeatedly to obtain optimal communication; data packet retransmissions in case of a false acknowledgment; and data packet collision occurrences in the channel. Our chosen protocol stands out by enabling sensor (Rx) nodes to avoid collisions without needing extra communication or prior interference knowledge. According to the results obtained through simulations, our protocol may increase the network’s performance in terms of network throughput by up to 23% when compared to benchmark protocols depending on the typical traffic load. It simultaneously decreases end-to-end latency, increases the packet delivery ratio (PDR), boosts channel usage, and lessens packet collisions by over 38%. All these gains result in minimizing the network’s energy consumption, with a proportional gain. Full article

Numerous Candida species are responsible for fungal infections; however, Candida albicans stands out among the others. Treatment with fluconazole is often ineffective due to the resistance phenotype mediated by transmembrane transporters and/or biofilm formation, mechanisms of resistance commonly found in C. albicans strains. A previous study by our group demonstrated that batzelladine D can inhibit the Pdr5p transporter in Saccharomyces cerevisiae. In the present study, our aim was to investigate the efficacy of batzelladine D in inhibiting the main efflux pumps of Candida albicans, CaCdr1p and CaCdr2p, as well as to evaluate the effect of the compound on C. albicans biofilm. Assays were conducted using a clinical isolate of Candida albicans expressing both transporters. Additionally, to allow the study of each transporter, S. cerevisiae mutant strains overexpressing CaCdr1p or CaCdr2p were used. Batzelladine D was able to reverse the fluconazole resistance phenotype by acting on both transporters. The compound synergistically improved the effect of fluconazole against the clinical isolate when tested in the Caenorhabditis elegans animal model. Moreover, the compound disrupted the preformed biofilm. Based on the obtained data, the continuation of batzelladine D studies as a potential new antifungal agent and/or chemosensitizer in Candida albicans infections can be suggested. Full article

Post-disaster reconstruction (PDR) is a complex and unpredictable process, especially concerning the construction sector, where understanding associated risks is increasingly vital. This study investigates and evaluates the present condition of post-disaster reconstruction risk (RoPDR) and discerns research trends and deficiencies in the domain via a systematic literature review (SLR) and bibliometric analysis. The Web of Science (WoS) was preferred for its extensive repository of pivotal research publications and its integrated analytical capabilities for producing representative data. This study performed a comprehensive bibliometric analysis of 204 peer-reviewed journal articles regarding the risks associated with post-disaster reconstruction from 1993 to 2024, utilizing the R statistical programming package RStudio Bibliometrix R version 4.3.1 to map the research landscape, identify literature gaps, and analyze rising trends. As a result of the analyses, the risks of post-disaster reconstruction were classified into four main clusters. Despite numerous studies exploring post-disaster reconstruction through diverse perspectives and methodologies, the associated risks of these projects remain inadequately analyzed. This inaugural bibliometric study in the realm of RoPDR utilizes novel techniques, such as the h-index, thematic mapping, and trend topic analysis, to attain a comprehensive understanding. Hence, the outcome of this study will aid scholars and practitioners in thoroughly comprehending the present condition and identifying prospective research directions. Full article

In recent times, interest in the chemistry of conjugated nitrodienes is still significantly increasing. In particular, the application of these compounds as building blocks to obtain heterocycles is a popular object of research. Therefore, in continuation of our research devoted to the topic of conjugated nitrodienes, experimental and quantum-chemical studies of a cycloaddition reaction between (1E,3E)-1,4-dinitro-1,3-butadiene and N-methyl azomethine ylide have been investigated. The computational results present that the tested reaction is realized through a pdr-type polar mechanism. In turn, the experimental study shows that in a course of this cycloaddition, only one reaction product in the form of 1-methyl-3-(trans-2-nitrovinyl)-Δ³-pyrroline is created. The constitution of this compound has been confirmed via spectroscopic methods. Finally, ADME analysis indicated that the synthesized Δ³-pyrroline exhibits biological potential, and it is a good drug candidate according to Lipinski, Veber and Egan rules. Nevertheless, PASS simulation showed that the compound exhibits weak antimicrobial, inhibitory and antagonist properties. Preliminary in silico research shows that although the obtained Δ³-pyrroline is not a good candidate for a drug, the presence of a nitrovinyl moiety in its structure indicates that the compound is an initial basis for further modifications. Full article

Due to the physical characteristics of acoustic channels, the performance of underwater acoustic communication networks (UACNs) is more susceptible to the impacts of multipath and Doppler effects. Channel quality can serve as a measure of the reliability of underwater communication links. A cross-layer routing protocol based on channel quality (CLCQ) is proposed to improve the overall network performance and resource utilization. First, the BELLHOP ray model is used to calculate the channel impulse response combined with the winter sound speed profile data of a specific sea area. Then, the channel impulse response is integrated into the communication system to evaluate the channel quality between nodes based on the bit error rate (BER). Finally, during the selection of the next hop node, a reinforcement learning algorithm is employed to facilitate cross-layer interaction within the protocol stack. The optimal relay node is determined by the channel quality index (BER) from the physical layer, the buffer state from the data link layer, and the node residual energy. To enhance the algorithm’s convergence speed, a forwarding candidate set selection method is proposed which takes into account node depth, residual energy, and buffer state. Simulation results show that the packet delivery rate (PDR) of the CLCQ is significantly higher than that of Q-Learning-Based Energy-Efficient and Lifetime-Extended Adaptive Routing (QELAR) and Geographic and Opportunistic Routing (GEDAR). Full article

Post-disaster reconstruction of the built environment represents a key global challenge that looks set to remain for the foreseeable future, but it also offers significant implications for the future sustainability and resilience of the built environment. The purpose of this research is to explore the current applications of advanced digital/Industry 4.0 technologies in the post-disaster reconstruction (PDR) process with a view to improving its effectiveness and efficiency and the sustainability and resilience of the built environment. The extant research literature from the Scopus database on built environment reconstruction is identified and described. In a novel literature review approach, small language models are used for the classification and filtering of technology-related articles. A qualitative content analysis is then carried out to understand the extent to which Industry 4.0 technologies are applied in current reconstruction practice, mapping their applications to specific phases of the PDR process and identifying dominant technologies and key trends in technology deployment. The study reveals a rapidly evolving landscape of technological innovation with transformative potential in enhancing the efficiency, effectiveness, and sustainability of rebuilding efforts, with dominant technologies including GIS, remote sensing, AI, and BIM. Key trends include increasing automation and data-driven decision-making, integration of multiple Industry 4.0/digital technologies, and a growing emphasis on incorporating community needs and local knowledge into reconstruction plans. The study highlights the need for future research to address key challenges, such as developing interoperable platforms, addressing the ethical implications of using AI and big data, and exploring the contribution of Industry 4.0/digital technologies to sustainable reconstruction practices. Full article

Background: Diabetic retinopathy (DR) is a leading cause of visual impairment globally among working-aged individuals. This study aims to update data on DR prevalence in Bulgaria. Methods: The present cross-sectional study was conducted between 1 January 2022 and 1 January 2023, using a local diabetes registry from the city of Varna as a sampling framework. In total, 587 diabetic patients underwent DR examination. Data included demographics, diabetes type/duration, treatment, and ophthalmic history. DR status was assessed using indirect slit-lamp biomicroscopy or digital fundus photography, graded by the International Clinical Diabetic Retinopathy Scale. Results: Of 587 participants, 13 were excluded due to cataract-related ungradable images. The median age was 65 years (IQR 56–73), with a slight female predominance (54%). The overall prevalence of any DR was 39.9% (95% CI 35.9–44.0), with non-proliferative DR (NPDR) at 27.5%, proliferative DR (PDR) at 7.3%, and macular edema (DME) at 5%. Type 1 diabetes patients had significantly higher DR prevalence (68.8%) than type 2 (34.1%, p < 0.001). Men exhibited higher DR prevalence. Age and diabetes duration correlated positively with DR prevalence. Insulin treatment was associated with higher DR prevalence (55.6%) than oral antidiabetic treatment (22.5%, p < 0.001) for type 2 diabetes patients. Among those diagnosed with DR, 70.9% received treatment, mainly laser therapy. Conclusions: These findings provide epidemiological insights for future research and emphasize the need for a comprehensive national DR screening program in Bulgaria. Technological advancements enable proactive measures to mitigate DR-related visual impairment and blindness, including widespread screening, even in rural areas. Full article

Diabetic retinopathy (DR) is the leading cause of visual impairment, particularly in the proliferative form (proliferative DR [PDR]). The impact of the PDR microenvironment on microglia, which are the resident immune cells in the central nervous system, and the specific pathological changes it may induce remain unclear. This study aimed to investigate the role of microglia in the progression of PDR under hypoxic and inflammatory conditions. We performed a comprehensive gene expression analysis using human-induced pluripotent stem cell-derived microglia under different stimuli (dimethyloxalylglycine (DMOG), lipopolysaccharide (LPS), and DMOG + LPS) to mimic the hypoxic inflammatory environment characteristic of PDR. Principal component analysis revealed distinct gene expression profiles, with 76 genes synergistically upregulated under combined stimulation. Notably, prostaglandin-endoperoxide synthase 2 (encoding cyclooxygenase (COX)-2) exhibited the most pronounced increase, leading to elevated prostaglandin E2 (PGE2) levels and driving pathological angiogenesis and inflammation via the COX-2/PGE2/PGE receptor 2 signaling axis. Additionally, the upregulation of the fibrogenic genes snail family transcriptional repressor 1 and collagen type I alpha 1 chain suggested a role for microglia in fibrosis. These findings underscore the critical involvement of microglia in PDR and suggest that targeting both the angiogenic and fibrotic pathways may present new therapeutic strategies for managing this condition. Full article

(1) Background: There is a need to scale and transform health professional education (HPE) globally to not only improve the quantity but also the quality of health workers. This paper describes the approach undertaken by a Health University in Lao PDR. (2) Approach: The HPE curriculum was designed in an iterative process with key stakeholders from both the institution and government, with external expert advice. (3) Outcomes: The curriculum was successfully developed consisting of nine core modules and one elective module, reflecting both elements seen globally in HPE curricula as well as reflecting local needs. The content and teaching methods were validated and reviewed through piloting with local education leaders. (4) Conclusions: Despite the need to scale HPE globally, there are few examples of how this can be achieved in countries in which large gaps exist in HPE capacity. This paper provides one such example, through recognizing that sustained external partnerships will still be needed for successful future implementation. Full article

Micropiles were first used to repair the damaged structures of “Scuola Angiulli” in Naples after World War II. They are known as small versions of regular piles, with a diameter of less than 30 cm, and are made of high-strength, steel casing and/or threaded bars, produce minimal noise and vibration during installation, and use lightweight machinery. They are capable to withstand axial loads and moderate lateral loads. They are used for underpinning existing foundations and to restore historical buildings and to support moderate structures. In the literature, several reports can be found dealing with micropiles, yet little has been reported on Micropiled-Raft Foundations (MPR). This technology did not receive the recognition it deserved until the 1970s when its technical and economic benefits were noted. A series of laboratory tests and numerical modeling were developed to examine the parameters governing the performance of MPR, including the relative density of the sand, the micropile spacing, and the rigidity of the raft. The numerical model, after being validated with the present experimental results, was used to generate data for a wide range of governing parameters. The theory developed by Poulos (2001) (PDR) to predict the capacity of pile-raft foundations was adopted for the design of MPR. The PDR method is widely used by geotechnical engineers because of its simplicity. Full article

Nowadays, Wireless Mesh Networks (WMNs) are widely deployed in communication areas due to their ease of implementation, dynamic self-organization, and cost-effectiveness. The design of routing protocols is critical for ensuring the performance and reliability of WMNs. Although there have been numerous experimental works on WMNs in the past decade, only a few of them have been tested in real-world scenarios. This article presents a comparative analysis of three proactive routing protocols, OLSR, BATMAN, and Babel, using Raspberry Pi 4 devices. The evaluation, conducted at Al-Farabi Kazakh National University, covers both indoor and outdoor scenarios, focusing on key metrics such as bandwidth, Packet Delivery Ratio (PDR), and jitter. In outdoor scenarios, OLSR achieved the highest bandwidth at 2.9 Mbps, while BATMAN and Babel lagged. Indoor tests revealed that Babel initially outperformed with the highest bandwidth of 57.19 Mb/s but suffered from scalability issues, while BATMAN and OLSR exhibited significant declines in performance as network size increased. For PDR, BATMAN performed best with a decline from 100% to 42.8%, followed by OLSR with a moderate drop, and Babel with the greatest decrease. For jitter, OLSR showed the most stable performance, increasing from 0.281 ms to 2.58 ms at eleven nodes, BATMAN exhibited moderate increases, and Babel experienced the highest rise. Full article

Background: Diabetic retinopathy (DR) is a leading cause of blindness in patients with type 2 diabetes mellitus (T2DM). Cardiovascular risk factors, such as hypertension, obesity, and dyslipidemia, may play a crucial role in the development and progression of DR, though the evidence remains mixed. This study aimed to assess cardiovascular risk factors as independent predictors of DR and to develop a predictive model for DR progression in T2DM patients. Methods: A retrospective cross-sectional study was conducted on 377 patients with T2DM who underwent a comprehensive eye exam. Clinical data, including blood pressure, lipid profile, BMI, and smoking status, were collected. DR staging was determined through fundus photography and classified as No DR, Non-Proliferative DR (NPDR), and Mild, Moderate, Severe, or Proliferative DR (PDR). A Multivariate Logistic Regression was used to evaluate the association between cardiovascular risk factors and DR presence. Several machine learning models, including Random Forest, XGBoost, and Support Vector Machines, were applied to assess the predictive value of cardiovascular risk factors and identify key predictors. Model performance was evaluated using accuracy, precision, recall, and ROC-AUC. Results: The prevalence of DR in the cohort was 41.6%, with 34.5% having NPDR and 7.1% having PDR. A multivariate analysis identified systolic blood pressure (SBP), LDL cholesterol, and body mass index (BMI) as independent predictors of DR progression (p < 0.05). The Random Forest model showed a moderate predictive ability, with an AUC of 0.62 for distinguishing between the presence and absence of DR XGBoost showing a better performance, featuring a ROC-AUC of 0.68, while SBP, HDL cholesterol, and BMI were consistently identified as the most important predictors across models. After tuning, the XGBoost model showed a notable improvement, with an ROC-AUC of 0.72. Conclusions: Cardiovascular risk factors, particularly BP and BMI, play a significant role in the progression of DR in patients with T2DM. The predictive models, especially XGBoost, showed moderate accuracy in identifying DR stages, suggesting that integrating these risk factors into clinical practice may improve early detection and intervention strategies for DR. Full article

Objectives: The aim of this study was to prepare monoclonal antibodies (mAbs) that broadly target Acinetobacter baumannii and protect against infection by multi-drug-resistant (MDR) A. baumannii from different sources. Methods: mAb 8E6 and mAb 1B5 were prepared by sequentially immunizing mice with a sublethal inoculation of three heterogeneous serotypes of pan-drug-resistant (PDR) A. baumannii, ST-208, ST-195, and ST-229. Results: The cross-recognition of heterogeneous bacteria (n = 13) by two mAbs and potential targets was verified, and the in vitro antibacterial efficacy of mAbs was assessed. The median killing rate of mAb 8E6 against A. baumannii in the presence of complement and dHL-60 cells was found to be 61.51%, while that of mAb 1B5 was 41.96%. When only dHL-60 cells were present, the killing rate of mAb 8E6 was 65.73%, while that of mAb 1B5 was 69.93%. We found that mAb 8E6 and mAb 1B5 broadly targeted MDR A. baumannii on the ATP synthase complex and were equipped with an antibacterial killing ability by enhancing the innate immune bacteriolytic effect of ST-208 and ST-195 strains. Both monoclonal antibodies were validated to protect against respiratory infection at 4 and 24 h via enhancing the release of innate immune substances and inflammatory cytokines, effectively shortening the disease period in mice. Conclusions: mAb 8E6 and mAb 1B5 significantly enhanced the opsonization process of phagocytosis against A. baumannii strains prevalent in southern China by targeting ATP synthase antigens thereof, resulting in protective effects in mice. Full article