Search Results (342)

Background: Patterns of failure (POFs) after first-line immune checkpoint inhibitor (ICI)-based therapy in patients with synchronous metastatic non-small cell lung cancer (NSCLC) without oncogenic driver alterations may guide the selection of candidates for local consolidative therapy (LCT). Methods: We retrospectively evaluated patients diagnosed with synchronous metastatic NSCLC between January 2017 and December 2023. Patients with oncogenic driver alterations, those who did not receive ICIs as first-line therapy, or those who lacked follow-up imaging were excluded. Patients were stratified into four groups according to the number of metastatic lesions: 1, 2, 3–5, and >5 lesions. POFs were classified as original site recurrence (OSR) or new site recurrence with or without OSR (NSR). Competing risk analyses were performed. Results: A total of 221 patients were analyzed, with a median follow-up of 28.1 months. Initial failure patterns did not differ significantly across lesion-number groups (p = 0.417). The 2-year cumulative incidence of OSR was not significantly different between the groups (p = 0.828). A trend toward a lower NSR was observed in patients with a single metastatic lesion (p = 0.063). Analysis of subsequent failures revealed a higher rate of NSR in the 1-lesion group than in the other groups (p = 0.043). No independent predictors of OSR were identified in multivariate analysis. Conclusions: In synchronous metastatic driver-negative NSCLC treated with first-line ICI-based therapy, both OSR and NSR were common and not clearly associated with metastatic burden, suggesting that lesion number alone may be insufficient for selecting candidates for LCT. Full article

Palm oil waste (POW) is generated during the production of palm oil, and a large quantity of this waste often travels to landfills for disposal. This review aims to provide a comprehensive understanding of the circular economy approach to sustainable engineering and environmental applications of POW, including its generation, disposal concerns, challenges, and prospects. This review provides an overview of the features, composition, and prospective applications of several POWs, including palm oil clinkers (POCs), palm oil fuel ashes (POFAs), palm oil kernel shells (POKSs), and palm oil fibres (POFs). Furthermore, this overview describes the different applications that POW has found, such as sustainable construction materials, renewable energy production, and environmental remediation. Moreover, this review discusses the leaching and risk assessment of POW. The overview also discusses the circular economy implications of using POW. The results showed that while some wastes are reused and recycled, a good quantity are still discarded in environmentally harmful ways. With this overview of a wide circular economy approach to the sustainable use of POW, there will be a rallying call to experts and researchers to identify research gaps that could contribute to the sustainable use of POW. The results of this overview of the sustainable engineering and environmental applications of POW with a circular economy approach indicate that cleaner production technologies and better environmental sustainability of the palm oil industry are feasible through proper waste management, renewable energy generation, resulting in minimal environmental impacts. Furthermore, this analysis will be very useful in providing tools to engineers, environmentalists, and other relevant stakeholders to enable the efficient and sustainable use of POW in the global circular economy. Full article

This study compared the wound-healing response and osteogenic gene expression profile of osteoblasts exposed to pediatric-equivalent concentrations of dexmedetomidine (DXMT) and propofol (POF). Human osteoblast-like SAOS-2 cells were assigned to control, low- and high-dose DXMT and POF groups based on pharmacokinetically derived free-drug levels. Scratch-wound closure was quantified over 24 h, and expression of osteogenesis- and cytoskeleton-related genes (RANKL, RUNX2, SP7, BMP2, VIM, VCL, OCN, ALP) was measured by SYBR Green quantitative Polymerase Chain Reaction (qPCR). Normality was assessed using the Shapiro–Wilk test, and group differences were analyzed with two-way ANOVA followed by Tukey’s multiple comparisons test (p < 0.05). All groups demonstrated complete scratch closure by 24 h, with no differences at 6 h. At 18 h, POF did not differ from the control, whereas DXMT significantly accelerated closure at both doses in a dose-dependent fashion. High-dose DXMT significantly increased VIM (3.95 ± 3.12, p = 0.0144) and BMP2 (2.28 ± 0.70, p = 0.0002) expression, while RUNX2, SP7, and RANKL remained comparable to controls. ALP (1.68 ± 0.40, p = 0.0005) and OCN (3.31 ± 0.35, p = 0.0108) were significantly elevated only in the high-dose DXMT group, whereas POF showed no significant effects. At clinically relevant concentrations, DXMT was associated with enhanced scratch closure and increased expression of selected osteogenesis- and cytoskeleton-related genes in SAOS-2 cells, whereas POF showed limited effects under the tested conditions. These findings suggest that DXMT may influence early in vitro cellular responses relevant to bone healing and should be further validated in functional differentiation models and in vivo studies. Full article

Wearable data gloves often suffer from electromagnetic interference, insufficient substrate stability, and limited capability for multi-degree-of-freedom motion measurement. To address these limitations, a flexible glove incorporating a hybrid POF-FBG sensing scheme was designed and fabricated. Plastic optical fibers (POFs) were side-polished and patterned with long-period gratings to improve sensitivity to wrist flexion-extension and abduction-adduction. Then fiber Bragg gratings (FBGs) were embedded in a polydimethylsiloxane substrate and encapsulated using thermoplastic polyurethane fixtures to reduce the influence of skin stretching and improve measurement accuracy of finger-joint angle. Moreover, a thermoplastic polyurethane skeleton with an adaptive sliding-rail structure was 3D printed to maintain the stability of the sensor placement at the joints. Experimental results demonstrated the mean absolute errors of 4.06°, 1.38° and 1.70° for wrist flexion-extension, abduction-adduction and finger-joint bending, respectively, along with excellent gesture classification using a support vector machine algorithm, which indicates great potential in virtual reality interaction and hand rehabilitation applications. Full article

Optical-fibre daylighting systems (OFDS) harvest solar energy as a renewable lighting resource by delivering sunlight deep into green buildings. This emerging technology for sustainable infrastructure reduces electric-lighting demand; however, reported performance is difficult to compare across heterogeneous designs, metrics, and validation practices. Therefore, a PRISMA 2020–reported systematic literature review (SLR) of OFDS studies from three databases (Google Scholar, Scopus, and Web of Science; 2000–2025) was conducted, synthesising primary research that quantifies system- or component-level performance, with a focus on (i) plastic optical fibre (POF) transmission characteristics; and (ii) POF-based illuminance model validation. After de-duplication and screening, 106 primary studies were included, and two meta-analyses were performed where data were harmonised from 29 studies in total. Across reported POF configurations, attenuation ranged from 150 to 800 dB/km with a pooled mean of 332.8 dB/km, corresponding to a mean 1 m transmission of 92.7% and median design length scales of ∼3.7 m for 80% transmission and ∼11.6 m to half-power. Across illuminance validation datasets, models showed high linear agreement with experimental measurements (coefficient of determination ($R^2$) = 0.99; slope = 0.99) but typically underpredicted illuminance (geometric mean ratio = 1.16; mean absolute error (MAE) = 27.3 lux; mean absolute percentage error (MAPE) = 17.6%). These findings underscore the need for a standardised evaluation framework, including consistent metric definitions, robust uncertainty reporting, and reusable validation datasets to enable variance-weighted synthesis, while also identifying short-run POF routing as a key lever for improving system efficiency. In addition to providing the OFDS research agenda, this study serves as a roadmap for the industrial development of daylighting systems for green buildings based on harvesting solar energy, with its novelty lying in the PRISMA-guided evidence synthesis and quantitative meta-analytic consolidation of POF transmission and illuminance-validation performance. Full article

Brain stroke (BS) and heart disease (HD) are leading causes of global mortality and long-term disability, underscoring the critical need for early and accurate diagnostic tools. This research addresses the dual challenge of developing high-performance predictive models while ensuring the privacy of sensitive patient data. We propose a framework that integrates ensemble machine learning (ML) models with a formal differential privacy (DP) mechanism. Using a dataset of 5110 samples with clinical features, we evaluate Extreme Gradient Boosting (XGB), Random Forest (RF), Light Gradient Boosting Machine (LGBM), and Categorical Boosting (CAT) for BS and HD prediction. To protect individual privacy, we apply the Gaussian mechanism of DP with two probabilities of failure (POF) parameters (10–5 and 10–6) and a privacy budget ranging from 0.5 to 5.0. A key novelty of this work is the application of Pareto frontier multi-objective optimization (PFMOO) to systematically identify the optimal trade-off between model accuracy and privacy constraints. Our approach successfully identifies optimal, privacy-preserving models: XGB achieves top performance for BS prediction (92.3% accuracy, 92.29% F1 score), with a POF of 10–6, while RF excels for HD detection (95.61% accuracy, 97.8% precision), with a POF of 10–5. Furthermore, we employ explainable AI (XAI) techniques, SHAP and LIME, to provide interpretability of the model decisions, enhancing clinical trust. This research delivers a robust, interpretable, and privacy-conscious framework for early disease detection, offering a significant advancement over existing methods by holistically balancing accuracy, data security, and transparency. Full article

Reliability assessment of semiconductor devices increasingly requires the consideration of multiple degradation mechanisms acting simultaneously over long stress durations. Conventional lifetime qualification and prediction approaches rely on simplified assumptions that can obscure the interpretation of measured degradation data and lead to large uncertainty when extrapolated over many orders of magnitude in time. A consistent analytical framework is therefore required to relate measured degradation behavior to meaningful reliability metrics. This work presents a general framework for semiconductor device reliability that is consistent with established reliability theory and explicitly accommodates multiple competing degradation mechanisms, consistent with modern JEDEC reliability standards. The framework presented here separates physical degradation processes from analytical representations used to interpret experimental data, allowing the effect of independent mechanisms to be combined without imposing an implied physical model. Degradation behaviors exhibiting sublinear time dependence, which are commonly observed across device technologies, are discussed within this context. We show that common data interpretation practices can introduce systematic errors when ssublinearkinetics are present, particularly regarding lifetime extrapolation. A reformulated analytical representation is introduced that improves clarity and robustness in lifetime extraction while remaining fully compatible with standard reliability theory. This framework supports more consistent reliability assessment and more credible lifetime prediction across materials, devices, and operating conditions. Full article

The ovaries are crucial reproductive organs that regulate the menstrual cycle and support pregnancy through the production of steroid hormones. They are highly susceptible to various environmental pollutants, which can lead to ovarian disorders. Luteal phase defect (LPD) and premature ovarian failure (POF) are common ovarian disorders in women. In this study, we integrate network toxicology with molecular docking and molecular dynamics simulations to elucidate the toxicological mechanisms of Benzo(a)pyrene (BaP), a widespread endocrine disruptor, in LPD and POF. Through systematic data mining of the GeneCards and OMIM databases, we identified 1336 targets associated with LPD and 2066 targets related to POF, as well as 220 BaP targets. Venn diagram analysis revealed 36 potential targets for BaP-induced LPD and 43 for BaP-induced POF. GO and KEGG enrichment analyses suggest that BaP-induced LPD and POF may share toxicological mechanisms. PPI network visualization indicated that EGFR, ESR1, and STAT3 are critical common targets for BaP-induced LPD and POF. Molecular docking and molecular dynamics simulations revealed that BaP exhibits strong binding affinity with all three core genes. In KGN cells modeling LPD and POF phenotypes, cellular experiments confirmed that BaP downregulated EGFR and ESR1 expression while upregulating STAT3 expression, thereby supporting the reliability of these targets in BaP-induced ovarian dysfunction. These findings provide insights into BaP-induced reproductive toxicity and offer a foundation for targeted clinical interventions to mitigate the effects of environmental pollutants on women’s reproductive health. Full article

Assessing genetic diversity in various native poultry breeds, including bantam/dwarf ones, is instrumental for their conservation as genetic resources, identifying their specific genetic features, and exploring the history of their genetic divergence. Rare chicken breeds are usually carriers of peculiar phenotypic traits, including adaptations to local conditions, disease resistance, and unique performance features. Here, we report for the first time SNP-based genetic characterization of the Russian Korolyok, translated as “kinglet,” relative to five other dwarf/small breeds: Cochin Bantam, Hamburg Bantam Silver Spangled, Polish White-crested Black, Red White-tailed Dwarf and Silkie White. We estimated phenotypes, heterozygosity, inbreeding, effective population size, and runs of homozygosity (ROHs). Some breeds had higher genetic diversity and others showed elevated inbreeding rates in their genomes. With lower effective population sizes (both presently and in the past), rare breeds came from a limited number of ancestors or were under strong selection pressure over many generations. Within 22 ROHs, we identified 26 prioritized candidate genes (GRB10, RPRD1A, APOOL, EAF2, SEMA5, HACD2, GALANT1, DACH2, CHM, POF1B, HDX, SLC15A2, PDIA5, SEC22, NR2F2, ARRDC4, IGF1R, SYNM, TMEM263, etc.). Our data offer whole-genome insights into genetic variability, history, phylogeny, selective sweeps, and candidate genes of a distinct indigenous Russian chicken breed and other bantam/dwarf breeds. Full article

Mass M (kg) and peak intrusion L (mm) are jointly minimized for a CFRP-enabled battery pack enclosure under the GB 38031-2025 −40° side-pole extrusion condition. A 50-run explicit FE design of experiments is conducted and deterministically partitioned into 37/5/5/3 for initial training, two sequential enrichment batches, and an independent hold-out test. Bayesian additive regression trees are trained as the primary surrogates for M, L, and Stress, and stress acceptability is enforced through a probability-of-feasibility (PoF) gate anchored to a baseline-scaled cap, σ_lim = 1.2 σ_base = 410.4 MPa. NSGA-II performed on the feasible surrogate landscape yields a bimodal feasible non-dominated set. The two branches correspond to two discrete levels of a key thickness variable x₄: a low-mass regime (n = 106) with M = 100.61–104.81 kg and L = 5.430–5.516 mm at x₄ ≈ 5.60 mm, and a stiffer regime (n = 94) with M = 110.69–115.08 kg and L = 5.362–5.430 mm at x₄ ≈ 8.00 mm. PoF screening eliminates part of the intermediate region where feasibility confidence is insufficient. Independent FE reruns further indicate that the PoF gate reduces deterministic misclassification near the stress boundary (e.g., one near-threshold candidate exceeds σ_lim, whereas others satisfy the cap with margin). Overall, the proposed workflow offers a traceable lightweighting route under extreme-cold uncertainty within a constrained FE budget. Full article

The rapid and accurate detection of SARS-CoV-2 biomarkers remains a critical requirement for effective outbreak control and decentralized diagnostics. Although RT-PCR is the current gold standard, its reliance on centralized laboratories and long processing times limits its applicability in point-of-care settings. In this context, optical biosensing platforms based on surface plasmon resonance (SPR) offer attractive features, including label-free, real-time, and quantitative detection. This study explores the use of synthetic receptors for the highly sensitive detection of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Specifically, soft molecularly imprinted polymer nanoparticles (nanoMIPs) were employed as synthetic receptors and integrated into a high-sensitivity, portable plasmonic platform based on a D-shaped plastic optical fiber (POF) SPR sensor. The nanoMIPs were selectively imprinted against the RBD, characterized by Dynamic Light Scattering (DLS), Isothermal Titration Calorimetry (ITC), and Scanning Electron Microscopy (SEM) to confirm nanoMIPs size, binding properties, and surface morphology. Next, the nanoMIPs were immobilized onto a gold-coated sensing surface, enabling enhanced specificity, affinity, and signal amplification compared to conventional biological recognition elements. The resulting RBD-SPR-nanoMIPs sensor demonstrated promising analytical performance, exhibiting high selectivity against potentially interfering proteins and an anticipated sensitivity suitable for RBD detection at femtomolar concentrations. The inherent stability of nanoMIPs suggests the potential for reusable SPR sensing platforms, paving the way for next-generation synthetic receptor-based plasmonic biosensors. Full article

Bio-epoxy composites were fabricated by casting a resin–hardener–filler mixture into 3D-printed molds, using different sea-originated secondary raw materials: mussel shell powder (MSP) (63–83 μm) and Posidonia oceanica short fibers (POF) (1–2 mm). Monofiller composites were prepared with 5 or 10 wt.% MSP, or 5 or 10 wt.% POF. Hybrid formulations were also produced, containing both MSP and POF in two combinations, where the total amount of filler again summed up at 10 wt.%. A subset of the samples was conditioned by immersion in a 35 ‰ NaCl solution reproducing seawater composition until saturation was reached. Characterization was carried out on unconditioned and conditioned samples by Shore D hardness and Charpy impact tests while performing three-point flexural loading only on unconditioned ones. Fracture morphology was also investigated. Adding MSP slightly enhanced resin hardness, whereas impact absorption exhibited, to a variable extent, a two-phase behavior, reproducing crack initiation and propagation. The MSP6-POF4 hybrid configuration provided the greatest improvement in absorbed energy (25–30% higher), which was retained after conditioning. The introduction of fillers, first separately, then in combination, resulted in a reduction in flexural strength to a similar extent for all unconditioned configurations. Finally, composite panels containing 10 wt.% MSP, 10 wt.% POF, and a 6MSP–4POF hybrid formulation, intended for prospective boat deck applications, were fabricated and compared with neat bio-epoxy, showing satisfactory consolidation. Density and post-molding dimensional shrinkage were measured on the panels. Full article

To enable mains-free wireless access in confined environments such as tunnels and mines, this paper proposes and experimentally demonstrates a converged power-over-fiber (PoF) and analog radio-over-fiber (A-RoF) system over a single standard single-mode fiber (SMF). Using wavelength-division multiplexing (WDM), the system employs 1310 nm/1330 nm channels for bidirectional RF transmission and a 1550 nm channel for optical power delivery, respectively, while an ultra-simplified remote unit (RU) with a steady-state power consumption of 0.37 W is designed to match the PoF power-delivery capability. Experimental results show that for back-to-back, 1 km and 2 km links, the A-RoF performance remains essentially unaffected, with error vector magnitude (EVM) remaining stable, as the delivered PoF optical power varies from 0 to 3 W. For the 2 km transmission case, an incident PoF optical power of 2 W at the photovoltaic power converter (PPC) is sufficient to sustain stable system operation for over 10 hours. Under these conditions, using an IEEE 802.11ax MCS-7 (64QAM ) waveform, the optimum operating point yields an EVM of approximately 0.7%, satisfying the MCS-7 modulation-quality requirement. Full article

Background: Ovarian granulosa cells (GCs) play a pivotal role in folliculogenesis, and their dysfunction is central to disorders such as polycystic ovary syndrome (PCOS) and premature ovarian failure (POF). MicroRNAs (miRNAs) have emerged as crucial post-transcriptional regulators of GC homeostasis. Method: This review synthesizes current evidence by systematically analyzing relevant studies, integrating data from in vitro GC models, animal experiments, human cell lines, and clinical samples to elucidate the specific mechanisms by which miRNAs regulate GCs. Results: miRNAs precisely modulate GC proliferation, apoptosis, steroidogenesis, and oxidative stress responses by targeting key signaling pathways (e.g., PI3K/AKT/mTOR, TGF-β/SMAD) and functional genes (e.g., TP53, CYP19A1). Exosomal miRNAs serve as vital mediators of communication within the follicular microenvironment. To date, nearly 200 miRNAs have been associated with PCOS. Conclusions: miRNAs constitute a decisive regulatory network governing GC fate, offering promising therapeutic targets for PCOS and POF. However, significant challenges remain, primarily miRNA pleiotropy and the lack of follicle-specific delivery systems. Future clinical translation requires rigorous validation in human-relevant models. Full article

Electrolyte degradation and trace water contamination critically affect the lifetime and safety of lithium-ion batteries. In organic-based electrolytes such as acetonitrile (MeCN), even small amounts of water can trigger ${\mathrm{PF}}_6^{-}$ hydrolysis, producing HF, POF₃, and related species that contribute to electrolyte ageing and alter interfacial reactions. This study explores the electrochemical signatures of ageing and moisture contamination in Bu₄NPF₆- and LiPF₆-based MeCN electrolytes through a systematic cyclic voltammetry protocol. Platinum electrodes with different surface morphologies—flat, Nafion-coated, and nanostructured—were compared to assess their sensitivity to water-induced degradation. Cathodic Faradaic currents appearing around −0.7 to −1.0 V vs. Ag/AgCl were attributed to the protonic species generated by ${\mathrm{PF}}_6^{-}$-induced hydrolysis. The presence of LiPF₆, commonly used in battery electrolytes, further increases the concentration of anions responsible for the protonic species, therefore contributing to the acceleration of the electrolyte degradation. Experiments using a Nafion proton-conductive membrane assess the protonic origin of these peaks. Meanwhile, nanostructured platinum exhibits approximately four times higher current responses and enhanced sensitivity to water additions, reflecting the influence of surface roughness and active area. Overall, the findings indicate that electrode morphology significantly influences the detectability of ageing- and water-driven reactions, supporting the potential of nanostructured Pt as a diagnostic material for in situ monitoring. Full article