Search Results (6,909)

Research on biomarkers reflecting tumor biology and systemic metabolism is crucial for improving the accuracy and personalization of breast cancer (BC) prognosis. We investigated circulating dodecanoic acid in 229 patients undergoing radiotherapy (RT) and assessed its association with progression-free survival and overall survival over six years. Patients were classified into two phenotypes based on post-RT changes in dodecanoic acid: The Increase Phenotype (IP) had lower baseline concentrations and showed a post-RT rise, whereas the Decrease Phenotype (DP) had higher pre-RT levels and declined after treatment. Dodecanoic acid levels were lower in tumors than in peritumoral samples, and their association with phenotypes varied by sampling region, suggesting that systemic changes reflect broader metabolic adaptations rather than local tissue concentrations. Post-RT increases in dodecanoic acid were associated with higher paraoxonase-1 activity, suggesting a link with antioxidant status. Patients in the IP group had a significantly lower risk of progression than those in the DP group, whereas no significant differences in overall survival were observed. These findings highlight the potential utility of dodecanoic acid measurement as a prognostic biomarker and suggest that modulating fatty acid metabolism could be explored as a therapeutic strategy. Full article

Land-use change strongly affects soil microbiota, yet the role of agroecological systems in shaping soil fungal communities remains poorly understood in tropical soils. We evaluated the diversity, trophic modes, community composition, and co-occurrence networks of culturable soil fungal taxa across a land-use gradient in the Colombian Andes–Amazon transition zone. Agroecological systems—including improved pasture (IP), cacao and copoazu agroforestry systems (CaAS and CoAS), secondary forest with agroforestry enrichment (SFAE), and a moriche palm swamp ecosystem (MPSE)—were compared with dominant land-uses (degraded pasture, DP and old-growth forest, OF). Fungi were isolated using the soil dilution plate method and identified based on morphological and molecular characteristics, and soil physicochemical properties were measured to evaluate their relationships with fungal community patterns. A total of 420 isolates were assigned to 93 fungal species. Alpha-diversity metrics revealed significantly higher fungal richness in OF and MPSE, and higher Shannon diversity in agroforestry and forest-based systems, whereas DP exhibited the lowest values. Ordination analyses showed clear differences in fungal community composition, with CoAS displaying the most distinct assemblage. Agroecological and forest-based systems favored saprotrophic and symbiotrophic modes. Co-occurrence network analyses indicated that MPSE, OF, and IP supported more complex and modular fungal networks. Soil pH and total phosphorus (TP) were key drivers of fungal community composition, whereas exchangeable calcium, TP, soil organic carbon, and base saturation were associated with network attributes. Overall, our findings highlight the importance of agroecological management for soil fungal diversity and network organization in Amazonian transition landscapes. Full article

Background/Objectives: Ciltacabtagene autoleucel (cilta-cel) for relapsed/refractory multiple myeloma is typically administered inpatient (IP) to monitor for cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Because cilta-cel toxicities are typically delayed, outpatient (OP) administration (infusion and early monitoring) is being explored. We synthesized available evidence on OP and IP administration. Methods: MEDLINE, Embase, and Cochrane Library were searched from inception to August 5, 2025, supplemented by conference and gray literature searches. Eligible studies of adults with multiple myeloma receiving cilta-cel reported efficacy, safety, resource use, costs, and/or quality-of-life outcomes; findings were synthesized descriptively due to heterogeneity. Results: Seventy-four records (56 studies) were included; 90 patients received OP cilta-cel. OP clinical evidence (primarily three real-world studies) showed high response rates (ORR: 95%; median follow-up 4.6 months) and reported 1-year PFS and OS of 86% and 96%. In IP studies, median ORR was 91%, with median 1-year PFS 76% and median 1-year OS 85%. Any-grade CRS and ICANS occurred in 79–84% and 17–22% of OP patients (largely low grade); IP cohorts reported a median ICANS incidence of 17% (range 5–23%). Most OP patients were later hospitalized (86–93%), but stays were shorter (median 4–6.5 days) than in an IP cohort (median 19 days). Comparisons were unadjusted and may reflect selection differences. One modeling-based economic analysis estimated savings of ~$19,000 per OP-treated patient. Conclusions: OP cilta-cel appears feasible for selected patients and may reduce costs without compromising outcomes. Findings are descriptive and hypothesis-generating and prospective multicenter studies are needed to define long-term safety, durability, quality of life, and cost-effectiveness. Full article

Internet-wide scanning is indispensable for security research and network measurement, yet its efficacy remains limited by significant visibility heterogeneity across global networks. Traditional centralized scanners suffer from single-point failures and offer a constrained perspective, while naive distributed approaches fail to intelligently leverage visibility variations, leading to redundant effort and incomplete coverage. This paper presents VistaScan, a novel distributed scanning system based on node visibility awareness, demonstrating that the visibility pattern among IP addresses is highly consistent within CIDR blocks, enabling a lightweight method for efficient and scalable quantification of per-node visibility. It first constructs a Visibility Matrix through efficient anchor probing, then employs a load-aware task allocation mechanism that assigns each block to the most capable node while filtering out entirely invisible blocks. Evaluation across global, regional, and challenging Special-Block tasks demonstrates that VistaScan consistently outperforms five baseline methods. It achieves near-optimal coverage (97.95%, 99.05%, and 97.58%, respectively), reduces probe volume by 64–93%, and shortens completion time by 13–19× compared to conventional centralized and distributed scanners. Furthermore, the visibility matrix derived from one port (TCP/80) effectively generalizes to other TCP ports (TCP/22, TCP/53), achieving coverages of 91.09% and 87.95%—preliminarily validating the practical generalizability of our approach. VistaScan provides both a highly efficient solution for Internet-scale distributed measurement and a new theoretical foundation based on visibility consistency, advancing the field from brute-force probing toward intelligent, low-overhead, and sustainable scanning practices. Full article

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent systemic inflammation, which contributes to progressive multi-organ dysfunction, particularly in metabolically active tissues such as the liver and kidneys. Bee bread (Perga), a fermented bee pollen product rich in bioactive compounds, has been reported to exert anti-inflammatory and organ-protective effects; however, its tissue-specific influence on inflammatory responses under diabetic conditions remains incompletely defined. Thirty-two male Wistar Albino rats were randomly assigned to four groups: Control, DM, DM + Perga, and Perga. Diabetes was induced by streptozotocin (STZ; 55 mg/kg, i.p.). Perga was administered orally at a dose of 0.5 g/kg/day for 28 days. Pro-inflammatory cytokine levels (CRP, TNF-α, IL-1β, and IL-6) were quantified in liver and kidney tissues using ELISA. Histopathological alterations were evaluated by hematoxylin and eosin staining. DM significantly increased the IL-1β, IL-6, and CRP levels in hepatic tissue and elevated TNF-α, IL-1β, IL-6, and CRP levels in renal tissue. Perga administration attenuated these inflammatory responses, particularly reducing IL-1β and IL-6 levels in the liver and all measured cytokines in the kidney. Histopathological analyses revealed hepatocyte degeneration and necrosis, sinusoidal dilatation, tubular epithelial degeneration, and glomerular damage in diabetic rats, whereas Perga treatment partially improved hepatic alterations and improved renal structural integrity. These findings indicate that Perga exerts tissue-specific anti-inflammatory and protective effects in experimental diabetes, with a more pronounced impact on renal inflammation than on hepatic responses. Although its effects on hepatic TNF-α and CRP levels were limited, Perga may act as a natural modulator of cytokine-mediated inflammatory processes. Further studies are warranted to elucidate the underlying molecular mechanisms. Full article

Outbreaks of Ips hauseri, a major bark beetle pest in Central Asian Picea schrenkiana forests, have intensified under climate warming and prolonged droughts. However, the reproductive behavior and gallery construction strategies of this species remain poorly understood, limiting our ability to predict its population dynamics. Here, we dissected 219 galleries from infested spruce trees in Hami, Xinjiang, during an outbreak period (2024–2025). We identified 11 distinct gallery morphologies, with harem size (number of females per male) ranging from one to seven. Gallery length was positively correlated with egg production. Reproductive output peaked at a harem size of five, beyond which both gallery dimensions and fecundity declined. Host tree diameter at breast height (DBH) significantly influenced gallery complexity, with larger trees supporting more maternal galleries. Upward-oriented galleries were longer and contained more eggs than downward ones. Intraspecific competition, mediated by gallery adjacency and spatial orientation, strongly affected offspring development. Our results demonstrate that I. hauseri exhibits flexible gallery architecture and reproductive adjustments in response to resource availability and competition—a behavioral plasticity that likely contributes to its outbreak potential. Monitoring gallery morphology and harem size could enhance early detection and population forecasting for this increasingly damaging forest pest. Full article

Timely and accurate identification of agricultural pests is imperative for precision crop protection. However, real-world pest recognition faces two critical challenges: the interference of complex field backgrounds, which introduces significant noise, and the severe large intra-class variance caused by pest metamorphosis, which confuses standard classifiers. To address these issues, this paper proposes a coarse-to-fine cascade framework that integrates object localization with fine-grained multi-modal classification. First, we deploy a YOLOv8-based detector to precisely localize and crop pest regions from cluttered environments, effectively eliminating background redundancy. Second, for the cropped targets, we design a fine-grained classification network based on ResNeXt50 integrated with the Convolutional Block Attention Module (CBAM) to extract discriminative features. Crucially, to tackle the challenge of multi-state pest morphologies, we propose a novel Adaptive Multi-Center Classification Head (AMC-Head). Unlike traditional methods that enforce a single feature center for each class, our approach dynamically allocates multiple latent sub-centers for each category, allowing the model to automatically disentangle and cluster distinct morphological representations within a single label. Extensive experiments on the large-scale benchmark dataset IP102 demonstrate that our method achieves an end-to-end accuracy of 91.4%, significantly outperforming single-stage baselines. The proposed framework effectively mitigates the impact of complex backgrounds and metamorphic variation, providing a robust solution for automated pest monitoring. Full article

Intellectual property (IP) is a cornerstone of sustainable industrial growth, yet unpredictable fluctuations in patent application filings pose a challenge to the administrative efficiency and sustainable governance of patent offices. This study aims to enhance strategic R&D governance by analyzing the seasonality of patent application filings using monthly data from the Republic of Korea (January 2001 to July 2024) and proposing a time series forecasting model that reflects this seasonality. To verify seasonal patterns, visual analyses (graphs, time series decomposition, and autocorrelation function plots) and the Kruskal–Wallis test were conducted. The results confirmed a clear 12-month seasonal pattern, characterized by a distinct “December Rush” at the end of each year. Based on these findings, we compared the autoregressive integrated moving average (ARIMA) and seasonal ARIMA (SARIMA) models, demonstrating that the SARIMA model offers superior predictive performance by effectively capturing these cyclical fluctuations. Furthermore, by segmenting data into private and public R&D sectors, we observed that private R&D exhibits more pronounced seasonal volatility, necessitating differentiated management strategies. This study highlights the critical role of seasonality in forecasting patent volumes and provides a data-driven framework for sustainable governance, offering actionable insights for optimizing resource allocation and policy support in the innovation ecosystem. Full article

Optical networks constitute the backbone of contemporary communication infrastructures, supporting massive bandwidth, low-latency services, and high levels of scalability across core, metro, and access domains. As these systems evolve toward elastic, software-defined, and multi-domain architectures, their exposure to sophisticated security threats increases significantly. This paper provides a comprehensive survey of vulnerabilities and countermeasures in modern optical networks, spanning the physical, control, and cross-layer dimensions. We analyze major architectures—including WDM, TDM, PON, EON, and IP-over-WDM—and examine how their structural properties shape their security posture. A threat taxonomy is presented covering physical-layer attacks such as fiber tapping, optical jamming, crosstalk exploitation, and signal injection; control-plane risks including spoofing, malicious signaling, and SDN manipulation; and broader cross-layer attack vectors. We review state-of-the-art defense mechanisms, including physical-layer security (PLS), spectrum randomization, chaotic optical coding, device-level authentication, survivability techniques, intelligent monitoring, and quantum-secure solutions such as QKD. By integrating insights from recent experimental and operational studies, the survey highlights emerging challenges and identifies open problems related to secure orchestration, multi-tenant environments, and quantum-era resilience. The objective is to guide researchers, engineers, and network operators toward robust and future-proof security strategies for next-generation optical infrastructures. Full article

Integrated Electrical Resistivity Imaging (ERI) and Induced Polarization (IP) studies were performed to identify potential tin (Sn) mineralization prospects in the Eastern Tin Belt of Peninsular Malaysia. A total of 23 profiles were obtained utilizing a Schlumberger configuration, generating resistivity and chargeability sections employed to delineate weathering structures, lithological connections, and structurally regulated anomalies. ERI models consistently delineate a three-tier subsurface structure consisting of conductive soil/alluvial deposits (5–300 Ωm), weathered bedrock (300–1500 Ωm), and resistive fresh bedrock (>1500 Ωm), featuring undulating basement relief beneath floodplain layers. IP data indicate localized, often pronounced chargeability anomalies (~5–40 ms; locally reaching ~50 ms), interpreted as corridors influenced by fractures and veins, especially when they align with significant resistivity contrasts at metamorphic–granitic boundaries and intrusive contacts. The integration of fence diagrams in the alluvial-over-granite zone reveals laterally consistent chargeability peaks at the alluvial–bedrock interface, suggesting enduring subsurface conduits. XRF examination of quartz-vein samples verifies Sn enrichment (599–717 ppm), corroborating a granite-related vein/alteration hypothesis and indicating possible isolated greisenized zones within the weathered granite. The integrated ERI–IP analysis identifies priority targets for subsequent trenching and borehole drilling to verify an anomaly’s origins and evaluate Sn grade and continuity. Full article

Network fault diagnosis has evolved in response to the needs of modern networks, transitioning from traditional methods, such as passive and active monitoring, to advanced learning techniques. While conventional methods often introduce invasive traffic and control overhead, newer approaches face challenges such as increased internal processes and the need for extensive knowledge of network behavior. Learning-based methods offer an advantage by not requiring a complete network model, allowing the use of statistical and Machine Learning techniques to process historical data. However, existing learning methods face limitations, such as the need for extensive data samples and extended retraining periods, which can leave systems vulnerable to failures, particularly in dynamic environments. This work addresses these issues by proposing an incremental learning approach for continuous fault diagnosis in IP-based networks. The approach utilizes online learning to process symptoms in real-time, adapting to network changes while managing data imbalance through drift detection and rebalancing strategies, such as ADWIN and SMOTE. We evaluated the performance of this method using 25 incremental algorithms on the SOFI dataset. The results, assessed using metrics such as recall, G-mean, kappa, and MCC, demonstrated high performance over time, indicating the potential for resilient, adaptive fault detection processes in dynamic network environments. Additionally, a non-invasive process can be ensured through peripheral observation of failure symptoms, provided that data collection does not increase network traffic, overhead control, or internal network processes. Full article

Rice blast, caused by Magnaporthe oryzae, severely threatens global rice production. Although the receptor-like cytoplasmic kinase OsRLCK118 positively regulates rice immunity, its downstream signaling mechanism remains unknown. To systematically identify OsRLCK118-interacting proteins, we performed immunoprecipitation–mass spectrometry (IP-MS) and a yeast library screen, yielding 781 and 287 candidates, respectively, with 35 overlapping hits. Among these, OsSAMS1, a known positive regulator of blast resistance, was selected for validation. Membrane yeast two-hybrid, split-luciferase complementation, and co-immunoprecipitation assays confirmed the physical interaction between OsRLCK118 and OsSAMS1. Furthermore, in vitro kinase assays showed that OsRLCK118 specifically phosphorylates OsSAMS1. These results uncover a novel signaling axis connecting pathogen recognition to ethylene biosynthesis via OsRLCK118-dependent phosphorylation of OsSAMS1, providing both mechanistic insight into rice immunity and potential genetic targets for resistance breeding. Full article

Background: Arterial hypertension (AH) and insulin-dependent diabetes mellitus (DM) are major comorbid risk factors for accelerated myocardial damage, yet the behavior of key stress-adaptive heat shock proteins HSP70 and HSP90 under combined stress remains unclear. This study aimed to characterize the expression profiles of HSP70 and HSP90 in left ventricular cardiomyocytes during isolated and comorbid AH and DM, and to evaluate their association with structural remodeling and expansion of interstitial elements. Methods: The study was conducted in accordance with the European Convention for the Protection of Vertebrate Animals (ethical approval No. 26, RUDN Institute of Medicine, 18 February 2021) on 25 male rats divided into five groups (n = 5 each): control—38-week-old Wistar–Kyoto (WKY) rats; AH—38-week-old spontaneously hypertensive rats (SHR); long-term AH—57-week-old SHR; DM—38-week-old WKY rats with streptozotocin-induced insulin-dependent DM (65 mg/kg, i.p.); AH+DM—38-week-old SHR with STZ-induced DM. After 30 days of DM, left ventricular (LV) tissue was analyzed by immunohistochemistry (IHC) for HSP70/HSP90 protein expression and by RT-qPCR for mRNA levels. Increased stromal elements in myocardium were quantified morphometrically as interstitial stromal volume fraction (%) on hematoxylin and eosin-stained sections. Results: HSP90 was significantly upregulated in all pathological groups. The most pronounced increase occurred in isolated DM, with a 4.0-fold rise in HSP90-positive area (21.80% vs. 5.45% in control) and a 1.82-fold increase in mRNA. In the AH+DM group, HSP90 mRNA expression was extremely elevated (25.93-fold), accompanied by a 3.7-fold increase in protein. In contrast, HSP70 protein was elevated only in the 38-week AH group (27.68% vs. 19.70% control, p ≤ 0.05), remained unchanged in isolated DM (19.50%), and was significantly reduced in AH+DM (14.71%, p ≤ 0.05), despite a modest 1.64-fold mRNA upregulation in DM. Morphometric analysis revealed progressive expansion of interstitial elements, most severe in AH+DM (9.43% stromal volume vs. 4.81% in control, p ≤ 0.05). Conclusions: Comorbid AH and DM provoke synergistic HSP90 upregulation, while HSP70 expression is markedly suppressed, indicating a shift from an adaptive to a maladaptive cellular-stress response. The imbalance between HSP90 and HSP70 may represent a key molecular mechanism underlying accelerated structural and functional deterioration of the myocardium in cardiometabolic comorbidity. Full article

Quercus gilva is a dominant species in the subtropical evergreen broad-leaved forests of East Asia with substantial economic and ecological value. However, efficient clonal propagation methods for this species remain limited. This study aimed to establish a micropropagation protocol for Q. gilva using nodal stem segments from two-year-old seedlings as explants, focusing on culture establishment, shoot induction, shoot proliferation, and ex vitro rooting. Aseptic culture was effectively established by rinsing explants under running water for 15 min, followed by immersion in 0.1% HgCl₂ for 8 min, which balanced contamination control and explant viability. Explant browning was reduced by pre-soaking in 1.0 g·L⁻¹ ascorbic acid (VC) and by supplementing the Murashige and Skoog (MS) medium with 3.0 g·L⁻¹ activated charcoal. The highest shoot induction percentage (80.0%) was obtained on MS medium containing 1.0 mg·L⁻¹ 2,4-D and 0.5 mg·L⁻¹ TDZ. Shoot proliferation was achieved by subculturing induced shoots on MS medium supplemented with 1.0 mg·L⁻¹ NAA and 1.0 mg·L⁻¹ 2iP. For ex vitro rooting, regenerated shoots were dipped in a solution containing 600.0 mg·L⁻¹ IBA plus 700.0 mg·L⁻¹ NAA and then transplanted into a substrate of peat and perlite (1:1, v/v), resulting in a rooting percentage of 70.0% and well-developed root systems. This study establishes a preliminary in vitro propagation framework for Q. gilva, providing a methodological reference for future studies aimed at improving clonal propagation efficiency. Full article

In this work, the authors introduce an entirely solar-powered LoRa-based WSN consisting of several nodes, two stoplights, and four cameras. The system has been used to monitor the semi-rural area of Panni (FG), Puglia, Italy. The WSN has a totally custom implementation in both the node-gateway side and the gateway-user interface side. In particular, the communication framework is entirely IoT-based, featuring both the MQTT protocol, for the direct control of apparatuses from the system user interface, and the more traditional TCP/IP protocol, implemented on NB-IoT. The proposed system is entirely solar-powered and features a 34.68 mWh/day consumption. Around a single communication session, the average power consumption inside the single node amounts to 1.4 mW. This paper gives an overview of the proposed system, with detailed explanations of each part, and measurements retrieved over a wide period to assess the functionality of the system. Full article