Search Results (67)

Background: Although the BRAF gene mutation in colorectal cancer has a prognostic value and a therapeutic interest, very few studies address the prevalence of this mutation in the Middle East, and hardly any among the Lebanese population. Moreover, we studied the correlation between this mutation and other clinical and pathological variables. Methods: In this descriptive, retrospective, single-center study, BRAF mutational status was reviewed in colorectal tumor samples collected from 2015 to 2021 of Lebanese patients with confirmed metastatic colorectal cancer. The genetic analysis was done in two different molecular laboratories. Clinical characteristics were selected from the computerized medical records of included patients. Statistical calculations were performed with SPSS (version 21.0) statistical software. Results: The study included 190 patients. BRAF mutation was detected in 10 patients (5.3%). A positive correlation was observed between the presence of a BRAF mutation and the right-sidedness of the tumor (p = 0.001) as well as with the presence of microsatellite instability (p = 0.004). However, we could not establish a relationship between BRAF mutation and other characteristics such as age (p = 0.682), gender (p = 0.392), the degree of histologic differentiation (p = 0.594), and the presence of peritoneal metastases (p = 0.707). Conclusions: The BRAF mutation was found in 5.3% of colorectal cancers in Lebanon. A positive correlation was suggested with the colon sidedness and the microsatellite instability. However, it was still insufficient to establish statistically significant associations between other variables and the BRAF mutation. Full article

This paper presents a comprehensive technology-oriented review of aerospace development in Peru, integrating historical scientific infrastructure, suborbital experimentation, orbital satellite missions, and a systematic literature review of contemporary engineering research. Beyond a descriptive historical account, the study evaluates national aerospace capabilities from a system-engineering perspective, emphasizing technology readiness levels (TRL), subsystem integration, and validation environments. A regional comparison based on UNOOSA, CelesTrak, and nanosatellite databases contextualizes Peru’s orbital activity within South America. Furthermore, a systematic literature review using the PRISMA 2020 methodology was performed covering the period 2000–2025. The systematic literature review identifies nine major aerospace research lines, quantifies institutional participation through bibliometric analysis, and assigns TRLs using consistent criteria derived from reported experimental and operational evidence. The results reveal a fragmented yet progressively maturing ecosystem, characterized by strong analytical and laboratory-level capabilities (TRL 2–5) but limited system-level integration and flight-qualified developments (TRLs $N\ge 6$). These findings highlight structural gaps in program continuity, test infrastructure, and transition mechanisms from academic prototyping to operational aerospace systems. Overall, this work establishes a technology assessment baseline for an emerging space nation, providing evidence-based insights relevant to aerospace engineering, technology management, and capacity-building strategies in developing space ecosystems. Full article

Background: Low-cost particulate matter sensors have enabled new opportunities for exposure monitoring but require evaluation before application in epidemiological studies. This study assessed the performance of the SPS30 sensor integrated into the ARMIE portable monitoring sensor-node under controlled laboratory conditions. Methods: Sensors were co-located with two comparison instruments—the optical DustTrak photometer and the combined Scanning Mobility Particle Sizer (SMPS) and Aerodynamic Particle Sizer (APS)—across multiple aerosol sources, including candle burning, cooking, cigarette smoke, and clean air, under both regular and high-humidity conditions. Calibration performance was evaluated using leave-one-sensor-out and leave-one-source-out approaches. Results: The ARMIE node demonstrated strong agreement with the DustTrak (r = 0.93–0.98) and maintained linear response characteristics across emission types. Calibration reduced mean errors and narrowed the limits of agreement. Agreement with the SMPS + APS was moderate (r = 0.74–0.94) and characterized by systematic underestimation at higher concentrations. Conclusions: Overall, the ARMIE node achieved high correlation with the DustTrak, demonstrating that low-cost optical sensors can reliably capture temporal variability in particle concentrations relative to mid-cost photometers. Full article

The Space–Air–Ground Integrated Network (SAGIN), a core architecture for 6G, faces formidable routing challenges stemming from its high-dynamic topological evolution and strong heterogeneous resource characteristics. Traditional protocols like OSPF suffer from excessive convergence latency due to frequent topology updates, while existing intelligent methods such as DQN remain confined to a passive reactive decision-making paradigm, failing to leverage spatiotemporal predictability of network dynamics. To address these gaps, this study proposes an adaptive routing algorithm (GCN-T-PPO) integrating a GCN-Transformer hybrid encoder, Particle Swarm Optimization (PSO), and Proximal Policy Optimization (PPO) with spatiotemporal attention. Specifically, the GCN-Transformer encoder captures spatial topological dependencies and long-term temporal traffic evolution, with PSO optimizing hyperparameters to enhance prediction accuracy. The PPO agent makes proactive routing decisions based on predicted network states (next K time steps) to adapt to both topological and traffic dynamics. Extensive simulations on real dataset-parameterized environments (CelesTrak TLE data, CAIDA 100G traffic statistics, CRAWDAD UAV mobility models) demonstrate that under 80% high load and bursty Pareto traffic, GCN-T-PPO reduces end-to-end latency by 42.4% and packet loss rate by 75.6%, while improving QoS satisfaction rate by 36.9% compared to DQN. It also outperforms SOTA baselines including OSPF, DDPG, D2-RMRL, and Graph-Mamba. Ablation studies validate the statistical significance (p < 0.05) of key components, confirming the synergistic gains from spatiotemporal joint modeling and proactive decision-making. This work advances SAGIN routing from passive response to active prediction, significantly enhancing network stability, resource utilization efficiency, and QoS guarantees, providing an innovative solution for 6G global seamless coverage and intelligent connectivity. Full article

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, characterized primarily by motor impairments due to the loss of dopaminergic neurons. Despite extensive research, the precise causes of PD remain unknown, and reliable non-invasive biomarkers are still lacking. This study aimed to explore gene expression profiles in peripheral blood to identify potential biomarkers for PD using machine learning approaches. We analyzed microarray-based gene expression data from 105 individuals (50 PD patients, 33 with other neurodegenerative diseases, and 22 healthy controls) obtained from the GEO database (GSE6613). Preprocessing was performed using the “affy” package in R with Expresso normalization. Feature selection and classification were conducted using a decision tree approach (C4.5/J48 algorithm in WEKA), and model performance was evaluated with 10-fold cross-validation. Additional classifiers such as Support Vector Machine (SVM), the Naive Bayes classifier and Multilayer Perceptron Neural Network (MLP) were used for comparison. ROC curve analysis and Gene Ontology (GO) enrichment analysis were applied to the selected genes. A nine-gene decision tree model (TMEM104, TRIM33, GJB3, SPON2, SNAP25, TRAK2, SHPK, PIEZO1, RPL37) achieved 86.71% accuracy, 88% sensitivity, and 87% specificity. The model significantly outperformed other classifiers (SVM, Naive Bayes, MLP) in terms of overall predictive accuracy. ROC analysis showed moderate discrimination for some genes (e.g., TRAK2, TRIM33, PIEZO1), and GO enrichment revealed associations with synaptic processes, inflammation, mitochondrial transport, and stress response pathways. Our decision tree model based on blood gene expression profiles effectively discriminates between PD, other neurodegenerative conditions, and healthy controls, offering a non-invasive method for potential early diagnosis. Notably, TMEM104, TRIM33, and SNAP25 emerged as promising candidate biomarkers, warranting further investigation in larger and synthetic datasets to validate their clinical relevance. Full article

Mitochondrial dynamics are important for cellular health and include morphology, fusion, fission, vesicle formation, transport and contact formation with other organelles. Myosin XIX (Myo19) is an actin-based motor, which competes with TRAK1/2 adaptors of microtubule-based motors for binding to the outer mitochondrial membrane receptors Mitochondrial Rho GTPases 1/2 (Miro). Currently, it is poorly understood how Myo19 contributes to mitochondrial dynamics. Here, we report on a Myo19-deficient mouse model and the ultrastructure of the mitochondria from cells of Myo19-deficient mice and HEK cells, Miro-deficient HEK cells and TRAK1-deficient HAP1 cells. Myo19-deficient mitochondria in MEFs and HEK cells have morphological alterations in the inner mitochondrial membrane with reduced numbers of malformed cristae. In addition, mitochondria in Myo19-deficient cells showed fewer ER–mitochondria contact sites (ERMCSs). In accordance with the ultrastructural observations, Myo19-deficient MEFs had lower oxygen consumption rates and a reduced abundance of OXPHOS supercomplexes. The simultaneous loss of Miro1 and Miro 2 led to a comparable mitochondria phenotype and reduced ERMCSs as observed upon the loss of Myo19. However, the loss of TRAK1 caused only a reduction in the number of cristae, but not ERMCSs. These results demonstrate that both actin- and microtubule-based motors regulate cristae formation, but only Myo19 and its membrane receptor Miro regulate ERMCSs. Full article

Particulate matter (PM2.5) is a critical indicator of air quality and has significant health implications. This study presents the development and evaluation of a custom-built PM2.5 device, named the P-Tracker, designed to offer an accessible alternative to commercially available air quality monitors. This paper presents the design framework used to address the requirements of a low-cost, accessible device which meets the performance of existing commercial systems. Step-by step build instructions are provided for hardware and software development and connection to the P-tracker open access website which displays the data and interactive map. To demonstrate the performance, the P-Tracker was compared against leading consumer devices, including the AtmoTube Pro by AtmoTech Inc., Flow by Plume Labs, View Plus by Airthings, and the Smart Citizen Kit 2.1 by Fab Lab Barcelona, across four controlled tests. The tests included: (1) a controlled paper combustion test in which all devices were exposed to combustion aerosols in a sealed environment alongside the DustTrak 8530 (TSI Incorporated, Shoreview, MN, USA), used as the gold standard reference, where the P-Tracker achieved a Pearson correlation of 0.99 with DustTrak over the final measurement period; (2) an outdoor test comparing readings with a stationary reference sensor, Osiris (Turnkey Instruments Ltd., Rudheath, UK), where the P-Tracker recorded a mean PM2.5 concentration of 3.08 µg/m³, closely aligning with the Osiris measurement of 3.53 µg/m³ and achieving a Pearson correlation of 0.77; (3) a controlled indoor air quality assessment, where the P-Tracker displayed stable readings with a standard deviation of 0.11 µg/m³, comparable to the AtmoTube Pro; and (4) a real-world kitchen environment test, where the P-Tracker effectively captured fluctuations in PM2.5 levels due to cooking activities, maintaining a consistent response with the DustTrak reference. The results indicate varied degrees of agreement across devices in different conditions, with the P-Tracker demonstrating strong correlation and low error margins in high-pollution and controlled scenarios. This research underscores the potential of open-source, low-cost, custom-built air quality sensors which may be developed and deployed by communities to provide hyperlocal measurements of air pollution. Full article

Background: Understanding the genetic mechanisms and identifying potential therapeutic targets are essential for clarifying Autism Spectrum Disorder (ASD) etiology and improving treatments. This study aims to bridge the gap between basic transcriptomic discoveries and clinical applications in ASD research. Methods: Differentially expressed genes (DEGs) of GSE18123 datase were identified. A protein–protein interaction (PPI) network was constructed. Functional enrichment analysis was performed to link genetic loci to relevant biological pathways. Connectivity Map (CMap) analysis was used to predict potential drugs. Furthermore, immune infiltration correlation analysis explored associations between key genes and immune cell subpopulations. Diagnostic performance of top genes was evaluated by receiver operating characteristic (ROC) analysis. Results: The functional enrichment analysis successfully revealed relevant biological processes associated with ASD, while the CMap analysis predicted potential drugs that were consistent with some clinical trial results. Random forest analysis selected ten key feature genes (SHANK3, NLRP3, SERAC1, TUBB2A, MGAT4C, TFAP2A, EVC, GABRE, TRAK1, and GPR161) with the highest importance scores for autism prediction. Immune infiltration analysis showed significant correlations in genes and multiple immune cell types, demonstrating complex pleiotropic associations within the immune microenvironment. ROC curve analysis indicated that most top genes had strong discriminatory power in differentiating ASD from controls, particularly MGAT4C (AUC = 0.730), highlighting its potential as a robust biomarker. Conclusions: This study effectively bridges the basic transcriptomic discoveries and clinical applications in ASD research. The findings contribute to a better understanding of the etiology of ASD and provide potential therapeutic leads. Future research could focus on validating these potential drugs in clinical studies, as well as further exploring the biological functions of the identified genes to develop more targeted and effective treatments for ASD. Full article

With the rapid growth in satellite types and numbers in space information networks, accurate and fast inter-satellite link prediction has become a core requirement for topology modeling and capability evaluation. However, the current space information networks are characterized by large scales and the coexistence of multi-orbit satellites, posing dual challenges to inter-satellite link prediction. Link state prediction demands higher accuracy with limited computing power, while diverse satellite communication antenna loads require stronger generalization to adapt to different scenarios. To address these issues, this paper proposes a fully connected neural network model based on Bayesian optimization. By introducing a weighted loss function, the model effectively handles data imbalance in the link states. Combined with Bayesian optimization, the neural network hyperparameters and weighted loss function coefficients are fine-tuned, significantly improving the prediction accuracy and scene adaptability. Experimental results show that the BO-FCNN model exhibited an excellent performance on the test dataset, with an F1 score of 0.91 and an average accuracy of 93%. In addition, validation with actual satellite data from CelesTrak confirms the model’s real-world performance and its potential as a reliable solution for inter-satellite link prediction. Full article

Hay quality is a key factor in equine respiratory health, with microbiological contaminants in inhaled organic dust posing significant risks. Sensory assessment has been used to evaluate hay hygiene, but its value to identify deficiencies remains unclear. This study aimed to explore the potential of sensory assessment to predict both particulate matter (PM) dust concentrations and microbiological contamination. Fifty hay samples were collected from horse owners and evaluated using a structured sensory examination, microbiological analyses, and dust concentration measurements obtained with the Hay-Shaker device and a DustTrak DRX 8534. Sensory examination rated only 28% of samples as adequate, with 52% showing minor and 20% major deficiencies. Microbiological analysis found that 46% of samples met acceptable standards. Regression analysis showed that abnormal musty odor was the strongest predictor of increased dust concentrations, including the respirable fraction (PM4, <4 µm), while visible impurities were associated with microbial contamination. These findings suggest that sensory attributes such as odor and impurity are valuable indicators of hay hygiene. Structured protocols for sensory examination may offer a simple and cost-effective tool for assessing hay quality in equine environments. Full article

In addition to the use of reference instruments, low-cost sensors (LCSs) are becoming increasingly popular for air quality monitoring both indoors and outdoors. These sensors provide real-time measurements of pollutants and facilitate better spatial and temporal coverage. However, these simpler devices are typically characterised by lower accuracy and precision and can be more sensitive to the environmental conditions than the reference instruments. It is therefore crucial to characterise the applicability and limitations of these instruments, for which a possible solution is their comparison with reference measurements in real-world conditions. To this end, a measurement campaign has been carried out to evaluate the PM_2.5 readings of several low- and medium-cost air quality instruments of different types and categories (IQAir AirVisual Pro, TSI DustTrak™ II Aerosol Monitor 8532, Xiaomi Mijia Air Detector, and Xiaomi Smartmi PM_2.5 Air Detector). A GRIMM EDM180 instrument was used as the reference. This campaign took place in Budapest, Hungary, from 12 November to 15 December 2020, during typically humid and foggy weather conditions, when the air pollution level was high due to the increased anthropogenic emissions, including wood burning for heating purposes. The results indicate that the individual sensors tracked the dynamics of PM_2.5 concentration changes well (in a linear fashion), but the readings deviated from the reference measurements to varying degrees. Even though the AirVisual sensors performed generally well (0.85 < R² < 0.93), the accuracy of the units showed inconsistency (13–93%) with typical overestimation, and their readings were significantly affected by elevated relative humidity levels and by temperature. Despite the overall overestimation of PM_2.5 by the Xiaomi sensors, they also exhibited strong correlation coefficients with the reference, with R² values of 0.88 and 0.94. TSI sensors exhibited slight underestimations with high explained variance (R² = 0.93–0.94) and good accuracy. The results indicated that despite the inherent bias, the low-cost sensors are capable of capturing the temporal variability of PM_2.5, thus providing relevant information. After simple and multiple linear regression-based correction, the low-cost sensors provided acceptable results. The results indicate that sensor data correction is a necessary prerequisite for the usability of the instruments. The ensemble method is a reasonable alternative for more accurate estimations of PM_2.5. Full article

Background: High-grade serous ovarian cancer (HGSOC) is a highly aggressive malignancy with poor prognosis due to late-stage diagnosis and limited treatments. Identifying differentially expressed genes (DEGs), and immune cell infiltration patterns may improve prognostic assessment and therapeutic strategies. Methods: We conducted a meta-analysis of gene expression data from the GEO (Gene Expression Omnibus, NCBI). DEGs were identified, functionally enriched, and analyzed for protein-protein interactions. Overlaps with oncogenes and tumor suppressor genes were examined. Cox survival analysis and a gene expression-based risk stratification model were developed. Immune infiltration differences were assessed using deconvolution methods. Results: A total of 11 studies (291 HGSOC, 96 controls) identified 892 DEGs, mainly involved in mitochondrial function, vesicle trafficking, and immune regulation. Key oncogenes (EZH2, PDK1, ERBB2) and tumor suppressor genes (BRCA1, DUSP22) were identified. Survival analysis associated the expression of SEC24B, TGOLN2, TRAK1, and CAST with poor prognosis. Low-risk patients had higher activated dendritic cells and CD4+ memory T cells while high-risk patients were enriched in common lymphoid progenitors and megakaryocyte-erythroid progenitors. Conclusions: This study identifies key DEGs in HGSOC progression and presents a risk stratification model predicting patient outcomes. Full article

Particulate matter (PM) originating from road dust is an increasing concern in urban air quality, particularly as non-exhaust emissions from tire–pavement interactions gain prominence. Existing models often focus on meteorological and traffic-related variables while oversimplifying pavement surface characteristics, limiting their applicability across diverse spatial and traffic conditions. This study investigates the influence of concrete pavement macrotexture—specifically the Mean Texture Depth (MTD) and surface wavelength—on PM₁₀ resuspension. Field data were collected using a vehicle-mounted DustTrak 8530 sensor following the TRAKER protocol, enabling real-time monitoring near the tire–pavement interface. A multivariable linear regression model was used to evaluate the effects of MTD, wavelength, and the interaction between silt loading (sL) and PM₁₀ content, achieving a high adjusted R² of 0.765. The surface wavelength and sL–PM₁₀ interaction were statistically significant (p < 0.01). The PM₁₀ concentrations increased with the MTD up to a threshold of approximately 1.4 mm, after which the trend plateaued. A short wavelength (<4 mm) resulted in 30–50% higher PM₁₀ emissions compared to a longer wavelength (>30 mm), likely due to enhanced air-pumping effects caused by more frequent aggregate contact. Among pavement types, Transverse Tining (T.Tining) exhibited the highest emissions due to its high MTD and short wavelength, whereas Exposed Aggregate Concrete Pavement (EACP) and the Next-Generation Concrete Surface (NGCS) showed lower emissions with a moderate MTD (1.0–1.4 mm) and longer wavelength. Mechanistically, a low MTD means there is a lack of sufficient voids for dust retention but generates less turbulence, producing moderate emissions. In contrast, a high MTD combined with a very short wavelength intensifies tire contact and localized air pumping, increasing emissions. Therefore, an intermediate MTD and moderate wavelength configuration appears optimal, balancing dust retention with minimized turbulence. These findings offer a texture-informed framework for integrating pavement surface characteristics into PM emission models, supporting sustainable and emission-conscious pavement design. Full article

Autism spectrum disorder (ASD) is a neurodevelopmental impairment that occurs due to mutations related to the formation of the nervous system, combined with the impact of various epigenetic and environmental factors. This necessitates the identification of the genetic variations involved in ASD pathogenesis. We performed whole exome sequencing (WES) in a cohort of 22 Bulgarian male and female individuals showing ASD features alongside segregation analyses of their families. A targeted panel of genes was chosen and analyzed for each case, based on a detailed examination of clinical data. Gene analyses revealed that specific variants concern key neurobiological processes involving neuronal architecture, development, and function. These variants occur in a number of genes, including SHANK3, DLG3, NALCN, and PACS2 which are critical for synaptic signaling imbalance, CEP120 and BBS5 for ciliopathies, SPTAN1 for spectrins structure, SPATA5, TRAK1, and VPS13B for neuronal organelles trafficking and integrity, TAF6, SMARCB1, DDX3X, MECP2, and SETD1A for gene expression, CDK13 for cell cycle control, ALDH5A1, DPYD, FH, and PDHX for mitochondrial function, and PQBP1, HUWE1, and WDR45 for neuron homeostasis. Novel single nucleotide variants in the SPATA5, CEP120, BBS5, SETD1A, TRAK1, VPS13B, and DDX3X genes have been identified and proposed for use in ASD diagnostics. Our data contribute to a better understanding of the complex neurobiological features of autism and are applicable in the diagnosis and development of personalized therapeutic approaches. Full article

The final stage of green waste treatment typically occurs in composting plants, where waste is biologically stabilised through the activity of microorganisms. The composting process is accompanied by the emission of volatile organic compounds responsible for odour perception. Such nuisance odours are commonly regarded as atmospheric air pollutants and are subject to monitoring and legal regulation. Olfactometry remains the standard method for quantifying odours. Unfortunately, due to its dependence on human evaluators, it is often regarded as both labour-intensive and costly. Electronic noses are an emerging measurement method that could be used for such applications. This manuscript reports experimental measurements that were carried out at a composting facility specialising in the processing of biodegradable materials. VOC concentration was measured by the TSI OmniTrak™ Solution. The efficiency of the deodourisation process was evaluated by means of field olfactometry. A gas sensor array of a PEN3 electronic nose was used for the on-site measurements of emitted gas characteristics. A strong correlation between measurements by the three distinct techniques was confirmed. Three different phases of the composting process could be distinguished in the collected results. Full article