Search Results (61,611)

The biological compatibility of endodontic sealers is a key determinant of periapical tissue healing. This in vitro study investigated the cytotoxic, pro-inflammatory, and redox-related effects of eight endodontic sealers on human periodontal ligament fibroblasts (HPdLFs): Biopulp (Chema-Elektromet), AH Plus (Dentsply Sirona), MTA Fillapex (Angelus), EndoSeal MTA (Maruchi), GuttaFlow (Coltène), AH Plus Bioceramic (Dentsply Sirona), TotalFill BC (FKG Dentaire SA), and BioRoot TM (Septodont). Cells were exposed for 24 h to 10-fold-diluted sealer extracts prepared in accordance with the manufacturers’ instructions, while control samples underwent identical procedures without sealer contact. Oxidative stress biomarkers, antioxidant defense parameters, protein oxidation indices, apoptotic activity (caspase-3), pro-inflammatory cytokines (IL-1, IL-6), and cell viability (MTT assay) were assessed. Under the applied conditions, all materials induced only limited global oxidative stress, with most alterations reflecting selective protein and glycoxidative modifications. Nevertheless, AH Plus, MTA Fillapex, and the calcium hydroxide-based Biopulp exhibited a less favorable redox profile and greater protein oxidation compared with calcium silicate-based sealers. AH Plus and EndoSeal MTA were associated with increased IL-6 release, whereas EndoSeal MTA moderately elevated IL-1 levels. BioRoot TM demonstrated the lowest cytokine expression, and TotalFill BC preserved high cell viability. Caspase-3 activity remained comparable across all experimental groups, indicating minimal induction of apoptosis. Full article

Plastic waste poses a major environmental issue because it persists in nature for long durations and recycling facilities are not readily available. The conversion of waste materials into hydrogen creates two beneficial effects that help decrease pollution levels and establish hydrogen as a clean energy source for sustainable low-carbon systems. In this study, an integrated process for plastic-to-hydrogen conversion was developed using Aspen HYSYS v14. The system uses pyrolysis, steam reforming, and the water–gas shift (WGS) reaction, through pseudo-components of polyethylene, polypropylene and polystyrene to model decomposition processes. Following optimization, the hydrogen fraction in the syngas rose from 0.664 to 0.733. At this stage, the process produced roughly 651 kg of hydrogen per hour in steady operation. In addition, char and pyrolysis oil were produced as co-products that can be valorized in circular economy applications The implementation of heat integration achieved an 8% reduction in utility demand that proves that internal energy recovery stands as a vital element for sustainable design. The techno-economic analysis showed that the project would achieve a 39% internal rate of return and payback period of 5.95 years, thus proving its financial stability. The research demonstrates how modern process modeling techniques enable the creation of clean technology systems that address plastic pollution problems while producing low-carbon hydrogen. Full article

Small communities in the Kingdom of Saudi Arabia (KSA) without a sewerage system commonly rely on septic tanks and long-distance transport of wastewater to the nearest centralized treatment facilities, resulting in high operational costs, social nuisance, and limited opportunities for treated effluent reuse. For a small community of 1300 persons in Al Qaraa (Qassim, KSA), this study performs life cycle analysis (LCA) to evaluate the environmental sustainability of a low-cost membrane bioreactor (LC-MBR)-type for decentralized on-site treatment as an alternative to wastewater transportation to a conventional extended aeration activated sludge process (EA-ASP)-type centralized system operating in the nearest larger city of Al-Bukayriyah. SimaPro^® 8.3.0.0 with the ecoinvent 3.0 database and ReCiPe 16 midpoint methodology shows that the decentralized LC-MBR scenario outperformed the centralized option with a 49 km-long wastewater transportation route in 13 out of 15 selected midpoint categories when considering relative and normalized impacts. In the EA-ASP, primary treatment dominated environmental impacts across most categories, driven by high energy demand for wastewater pumping, whereas freshwater and marine eutrophication were primarily influenced by treatment efficiency. With smaller normalized values, secondary treatment had a greater relative impact on urban and agricultural land occupation categories, attributed to the use of clay and rice bran in low-cost membrane fabrication in an LC-MBR. Tertiary treatment in the LC-MBR scenario, incorporating coagulation and granular activated carbon, significantly reduced freshwater eutrophication. Although normalized endpoint impacts indicated comparable ecosystem impacts for both systems, the LC-MBR resulted in 8% lower impacts on human health and 60% lower on resource depletion. Overall, the findings support decentralized wastewater treatment as a sustainable solution for small communities in arid regions and provide valuable insights for policy and decision-making. Full article

Background: Although blinded independent central review (BICR) can reduce assessment variability, it introduces additional financial and logistical burdens to trial operations. This study analyzed the discrepancy indexes (DIs) to evaluate differences between progression-free survival (PFS) assessments by local investigators (LIs) and BICR in randomized clinical trials (RCTs) of patients with metastatic melanoma. Methods: A comprehensive literature search was conducted on PubMed, Embase, and Cochrane databases up to 30 June 2024. The primary outcome was the DI, which was calculated for each trial as a ratio of the hazard ratios (HR)_BICR by HR_LI. The agreement between PFS HRs was also evaluated using the intraclass correlation coefficient (ICC) and Pearson’s correlation coefficient (r). Results: Twelve studies comprising 4915 patients were included in this study. Of these, 10 (83%) were Phase III, 11 (92%) were cutaneous melanoma, one was uveal, and all identified PFS as the primary endpoint. Most (86%) of the PFS comparisons yielded the same statistical inference by both BICR and LIs. The overall combined DI was calculated at 1.08 (95% CI: 1.01–1.15), indicating a statistically significant, numerically small difference in PFS evaluations driven primarily by the uveal Phase III double-blinded study, while there was a strong overall correlation [(ICC: 0.87, p < 0.001); (r = 0.89, 95% CI 0.67–0.96, p < 0.0001)]. Cutaneous melanoma trials demonstrated strong agreement between BICR and local investigator assessments. Conclusions: In randomized trials of metastatic cutaneous melanoma, LI-assessed PFS closely aligns with BICR and provides equivalent trial-level conclusions in most cases. These findings support the use of LI-assessed PFS as a valid and practical primary endpoint, without routine requirement for BICR. Central review should be reserved for selected scenarios. Full article

Urban air quality assessment is central to environmental sustainability and public health management. This study presents a structured comparative evaluation of Random Forest (RF), Support Vector Machine (SVM), LSTM, and Bi-LSTM models for pollutant-driven air quality classification under the Indian National Air Quality Index (NAQI) framework defined by CPCB guidelines. To provide a fair comparison, multi-pollutant data of Indian urban monitoring stations were preprocessed, and the class-balancing protocol and validation protocol were combined. RF had highest total accuracy (0.9971) in the held-out set, with Bi-LSTM (0.9615), LSTM (0.9495), and SVM (0.9442) coming next. Although ensemble methods proved to be very separable in line with the threshold-based NAQI structure, Bi-LSTM was more stable when it came to boundary-sensitive switches among the adjacent severity classes. Calibration analysis (multiclass Brier score: 0.08) showed consistent probabilistic behavior and interpretation, and using SHAP showed physically significant pollutant driving factors. The results explain the appropriateness of comparative models in organized AQI classification and present a reproducible assessment framework for the NAQI framework. Full article

Opioid-related iatrogenic harms, including opioid use disorder, overdose, and opioid-induced respiratory depression, constitute a major patient safety challenge. Although clinicians document key safety signals in unstructured clinical narratives, many of these indicators are not readily captured by conventional surveillance approaches that rely on structured administrative data. This clinically focused narrative review synthesizes 47 empirical studies published between 2009 and 2025 that applied artificial intelligence (AI) methods to identify opioid-related harms from clinical text and to address the resulting ascertainment gap. Across studies, administrative coding systems, including ICD-10, often under-ascertain opioid-related events, whereas text-based AI can identify additional cases and contextual details often documented primarily in narrative records, such as fluctuating mental status, suspected drug causality, and responses to naloxone. Methodologically, the literature has progressed from interpretable rule-based lexicons to machine learning and deep learning models and, more recently, to transformer-based approaches, including large language models (LLMs) for classification and schema-driven extraction. Rule-based systems established the feasibility of transparent surveillance and frequently recovered clinically documented cases missed by billing codes. Subsequent supervised and deep learning approaches expanded scalability and, in a smaller subset of studies, were integrated into electronic health record workflows with operational metrics reported. More recent transformer- and LLM-based studies emphasize richer extraction schemas and benchmark development, including characterization of overdose context and intentionality and identification of potential prodromal neurocognitive signals, although external validation, calibration, and prospective outcome evaluation remain inconsistently reported. Given that the evidence base is predominantly retrospective and that clinical workflow studies remain comparatively few, a pragmatic near-term clinical role is to provide detection-to-triage decision support rather than autonomous diagnosis, in which systems surface candidate cases with reviewable evidence for clinician adjudication. Future progress will require greater standardization of phenotype definitions, routine equity auditing and subgroup reporting, stronger external validation and calibration at operational thresholds, and a shift from retrospective discrimination metrics toward prospective assessments of the clinical workflow impact, clinical utility, and patient-centered outcomes. Full article

Buildings account for nearly 40% of global energy use and 36% of CO₂ emissions, positioning Net-Zero Energy Buildings (NZEBs) as vital for climate mitigation. However, large-scale adoption remains limited by technical, economic, and policy barriers. This study systematically reviews 1285 peer-reviewed articles (2015–2025) from Scopus and Web of Science, following PRISMA guidelines and thematic analysis to assess renewable energy integration and efficiency strategies. Results indicate that 70% of studies highlight emissions reduction and cost savings as key NZEB benefits, while 60% cite high storage costs and 45% report grid integration challenges. Only 30% of studies address policy dependency, revealing a research gap. Effective measures include passive solar design (up to 25% heating load reduction), high-performance envelopes (15–40% energy savings), and smart energy management (10–20% efficiency gains). Persistent obstacles involve high upfront costs, renewable variability, and rapid technological obsolescence. Achieving NZEB viability requires integrating energy-efficient design, affordable renewables, advanced storage, and coherent policy frameworks to accelerate the transition toward a sustainable, NZEB-built environment. Full article

Beamforming plays a central role in enhancing the performance of communication systems; however, suppressing sidelobes in planar antenna arrays (PAAs) while maintaining a compact aperture remains a challenging nonlinear optimization problem. This article presents a two-dimensional (2D) beamforming synthesis framework for PAAs based on the Fractional-Order African Vulture Optimization Algorithm (FO-AVOA), with the objective of minimizing the peak sidelobe level (PSLL) through the joint optimization of amplitude excitations and element placements. The proposed method is benchmarked against established metaheuristic optimizers, including Particle Swarm Optimization (PSO), the Gravitational Search Algorithm (GSA), hybrid PSO–GSA (PSOGSA), the Runge–Kutta Optimizer (RUN), the Slime Mould Algorithm (SMA), Harris Hawks Optimization (HHO), and the baseline African Vulture Optimization Algorithm (AVOA). Simulation results demonstrate that the FO-AVOA, coupled with the proposed 2D formulation, yields superior sidelobe suppression relative to the competing approaches, achieving a lower PSLL with fewer radiating elements, thereby reducing array complexity and overall implementation cost. The obtained results validate the suitability of the FO-AVOA for solving PAA in the context of BFA beamforming and suggest the potential utility of the FO-AVOA for pattern synthesis for other array shapes in various communication systems. Full article

Let p be a prime with $p\notin \{2,5\}$ and let $q=p^m$. This paper studies cyclic and self-orthogonal linear codes of length n over the finite local non-Frobenius ring $R_{p,u,v}={\mathbb{F}}_q+u{\mathbb{F}}_q+v{\mathbb{F}}_q,u^2=v^2=uv=vu=0.$ We define an ${\mathbb{F}}_q$-linear Gray map ${\pi }_n:R_{p,u,v}^n\to {\mathbb{F}}_q^{6n}$ and investigate the structural properties of Gray images of cyclic codes under this map. It is shown that ${\pi }_n$ preserves self-orthogonality and, when $gcd(n,p)=1$, transforms any cyclic code over $R_{p,u,v}$ into a quasi-cyclic code over ${\mathbb{F}}_q$ of length $6n$ with index dividing 6. Moreover, we completely characterize the possible quasi-cyclic indices of the Gray images, proving that only the values $l\in \{1,3,6\}$ can occur, and we establish necessary and sufficient conditions for each case in terms of the generators of the associated cyclic code. Several explicit examples are provided to illustrate the theoretical results and the resulting quasi-cyclic structures. Full article

Giardiasis, caused by Giardia duodenalis, is a common gastrointestinal infection. This study aimed to evaluate the effects of Hedera helix leaf extract (HLE) and HLE-loaded chitosan nanoparticles (HLE-CsNPs) against Giardia duodenalis isolates from individuals with gastrointestinal issues, using an experimental rat model. Stool samples from 147 participants were analyzed for Giardia duodenalis, with positive samples further characterized by nested PCR-RFLP, revealing a 4.8% prevalence, all belonging to assemblage B. Ten groups of male albino rats were used to evaluate the antigiardial activity of various treatments. This included five non-infected groups [one untreated and four treated with HLE, HLE-CsNPs, CsNPs, and metronidazole (MTZ)] and five infected groups [one untreated and four similarly treated]. Treatment efficacy was assessed using parasite counts, intestinal histopathology, CD117 immunohistochemistry, and markers of liver and kidney function. HLE-CsNPs markedly reduced Giardia cysts by 88.8%, approaching the 99.2% reduction achieved by MTZ, while also improving intestinal architecture and reducing inflammation. Importantly, HLE and HLE-CsNPs provided superior protection for the liver and kidneys compared to MTZ. In conclusion, HLE-CsNPs exhibited significant antigiardial activity and organ protection in rats, suggesting a potential alternative treatment for Giardia duodenalis isolated from individuals with gastrointestinal issues. Full article

The (3+1)-dimensional B-type Kadomtsev–Petviashvili (BKP) problem was examined in this paper using the developed Exp-function method (DEFM) and Lie symmetry analysis. The objective of this research is studying the BKP equation to get novel exact solutions. Symmetry analysis has been used to determine similarity variables and vector fields. The governing equation was reduced to five variant ordinary differential equations (ODEs). The DEFM was employed for four of them to obtain several novel exact solutions that contain arbitrary constants. The most appropriate choice of values for these optional constants contributed to the emergence of solutions, such as double waves, multisolitons, kink waves, anti-kink waves, and solitary waves. The obtained exact solutions are presented in a 3D graph. The behavior of the solutions can be utilized to explore the application of the governing equation in fluid dynamics, plasma physics, nonlinear optics, and ocean physics. Full article

Confocal laser endomicroscopy (CLE) is an innovative diagnostic modality that facilitates real-time in vivo optical biopsies of various tissues within luminal and ductal structures. Since its introduction in 2004, the application of this tool has broadened from diagnostic purposes to encompass management and prognostic evaluation in fields such as gastroenterology, neurosurgery, urology, and dermatology. This comprehensive review examines the current applications of endomicroscopy in Barrett’s esophagus (BE), inflammatory bowel disease (IBD), and colorectal lesions. Evidence from the literature suggests that CLE offers a potential solution to the diagnostic limitations associated with white-light endoscopy and histology. With a diagnostic accuracy nearly equivalent to that of histology, CLE is emerging as a promising tool to mitigate the delays related to awaiting histology results for clinical and therapeutic decision-making. However, its use is mainly as a complementary diagnostic method rather than an alternative to histopathology or other ancillary studies. Nevertheless, its widespread adoption remains limited, and further research is necessary to ascertain its overall benefits and cost implications of integrating it into patient care. Full article

Accurate apple detection and precise three-dimensional (3D) localisation are essential for autonomous robotic harvesting in orchard environments, where occlusion, illumination variation, depth noise, and the similar colour appearance of fruits and surrounding leaves present significant challenges. This paper proposes a dual-detector vision framework combined with depth-aware back-projection to achieve robust apple detection and metric 3D localisation in real time. The method integrates the complementary strengths of YOLOv8 and Mask R-CNN through confidence-weighted fusion of bounding boxes and pixel-wise union of segmentation masks, producing stabilised two-dimensional (2D) apple representations under visually ambiguous conditions. The fusion results are converted into dense 3D representations through depth-guided projection within the camera coordinate system representing the visible fruit surface. A depth-consistency weighting strategy assigns higher influence to depth-reliable pixels during centroid computation, thereby suppressing noisy or occluded depth measurements and improving the stability of 3D fruit centre estimation, while local intensity normalisation standardises neighbourhood-level pixel intensities to reduce the impact of shadows, highlights, and uneven lighting, enabling more consistent segmentation and detection across varying illumination conditions. Experimental results demonstrate an accuracy of 98.9%, an mAP of 94.2%, an F1-score of 93.3%, and a recall of 92.8%, while achieving real-time performance at 86.42 FPS, confirming the suitability of the proposed method for robotic harvesting in challenging orchard environments. Full article

Sharm El-Luli, located along the southern Red Sea coast of Egypt, is a semi-enclosed, shallow, mangrove-fringed lagoon characterized by limited hydrodynamic exchange, high salinity, and low terrigenous input. This study investigates the influence of sediment properties, hydrodynamic gradients, and mangrove-associated microhabitats on the spatial distribution of benthic ostracod assemblages within this lagoonal system. Eighteen surface sediment samples (W1–W18) were collected along an onshore–offshore gradient and analyzed for ostracod composition, sediment texture, carbonate and organic matter content, and water parameters including temperature, salinity, dissolved oxygen, pH, redox potential, and total dissolved solids. Thirty-four ostracod taxa were identified, revealing a pronounced inner–outer ecological partitioning across the lagoon. Redundancy analysis (RDA) demonstrates that ostracod distribution is primarily controlled by substrate heterogeneity, organic enrichment, salinity, and conductivity-related variables. The inner, low-energy mangrove margin is dominated by Aglaiocypris triebeli, Paranesidea fracticorallicola, and Hiltermannicythere rubrimaris, reflecting stressed, low-diversity conditions associated with organic-rich sediments and restricted circulation. In contrast, mid- and outer-lagoon stations host more diverse assemblages dominated by Xestoleberis spp., Neonesidea schulzi, Loxocorniculum ghardaquensis, and Jugosocythereis borchersi, indicative of better-flushed environments with higher carbonate content and stable marine salinity. These results demonstrate that benthic ostracods respond sensitively to fine-scale environmental gradients in mangrove-fringed lagoons, underscoring their value for assessing ecological health and sedimentary dynamics in semi-enclosed Red Sea coastal systems. Full article

Background/Objectives: Candidozyma auris is the most frequent multidrug-resistant fungal infection in the Arabian Peninsula, with high mortality rates; therefore, new medications are in high demand. Microbes in marine habitats have genetically evolved to survive under a variety of adverse conditions, including severe temperatures, salinity, pH, and other stress factors, by generating various bioactive metabolites. These bioactive secondary metabolites have strong potential for use as antifungal agents. Due to the shortage of antifungal medications and the emergence of treatment resistance in C. auris, identifying new therapeutics from synthetic bacterial components or natural materials has become a necessity. Natural molecules have numerous advantages over synthetic substances, including structural variation and low toxicity. Few next-generation sequence-based investigations have been carried out on anti-Candidozyma auris bacterial species to identify potential therapeutic candidates. Therefore, the aim of this study is to identify biosynthetic gene clusters from marine bacteria using next-generation sequencing to discover novel drug compounds against multidrug-resistant C. auris. Methods: More than 68 isolates were collected from various marine environments using standard techniques. All isolates were tested against the multidrug-resistant C. auris. Scanning electron microscopy was utilized to investigate the cell membrane rupture caused by defused metabolites of the IRMCESH58L bacterium in C. auris. The Vibrio sp. IRMCESH58L genome was sequenced using long-read nanopore sequencing technology. Results: The bacterial strain IRMCESH58L, isolated from a fish liver sample, showed the highest and most constant activity against C. auris. An in vitro toxicity test found that IRMCESH58L had no cell cytotoxicity against HFF-1 cells. The assembled plasmid-free genome is 6,556,025 bp (48.93% G+C), with an N50 of 909243. Comparative analysis confirmed its relation to Vibrio alginolyticus. Conclusions: Whole-genome analysis of the native bacterial strain IRMCESH58L revealed various biosynthetic gene clusters, including those involved in surfactin’s biosynthesis of putative natural anti-C. auris chemicals, but no pathogenic protein-coding genes, emphasizing the importance of marine bacteria in the fight against C. auris. Following this in vivo study, therapeutic targets will later be selected for further pre-clinical studies. Full article