Search Results (35,646)

Background: To investigate the effect of angiotensin-(1-7) [Ang-(1-7)] on serum metabolomics in obese type 2 diabetic (T2DM) mice. Methods: Four-week-old male C57BL/6 mice were fed a high-fat diet and intraperitoneally injected with streptozotocin (35 mg/kg) to establish an obese T2DM model. Mice were randomized into control, T2DM and T2DM+Ang-(1-7) groups (n = 6). Body weight and blood glucose were recorded weekly. At 10 weeks, blood glucose, serum inflammatory factors, lipid profiles, and pancreatic β-cell insulin secretion were detected; serum metabolite alterations were analyzed via untargeted metabolomics. Results: 1. Ang-(1-7) intervention decreased blood glucose (p < 0.05) and CRP levels (p < 0.01), and alleviated dyslipidemia (p < 0.05 or p < 0.01), as well as β-cell morphology and insulin expression in obese T2DM mice. 2. Non-targeted metabolomics analysis suggested that Ang-(1-7) may alleviate abnormal amino acid metabolic pathways by regulating levels of metabolites such as L-valine, L-proline, L-histidine, and glutamic acid. This intervention also tended to reduce multiple lipid metabolites, including Omega-3 Arachidonic Acid Ethyl Ester, phosphatidylcholine, and glycerophosphocholine, thereby participating in the modulation of lipid metabolism balance. KEGG enrichment analysis further indicated that Ang-(1-7) was involved in the regulation of protein digestion and the absorption pathway, as well as the HIF-1 signaling pathway related to oxidative stress, bile acid metabolism pathway, and other signaling pathways, and improving the insulin secretion pathway, pyrimidine metabolism, and TCA cycle energy metabolism pathway. Conclusions: Ang-(1-7) may partially improve metabolic disturbances in obese T2DM mice, which is potentially associated with the modulation of multiple metabolic processes, including amino acid metabolism, lipid metabolism, insulin secretion, and TCA cycle energy metabolism. Full article

Contactless vital signs monitoring is becoming increasingly relevant in scenarios where conventional sensors are impractical or not recommended. In this manuscript, a radar-based contactless system for the joint reconstruction of phonocardiogram (PCG) waveforms and cardiac state segmentation is illustrated. The proposed method exploits a self-attention one-dimensional (1D) U-Net fed by a pre-processed radar-derived input to estimate a PCG-like waveform, its envelope, and the four main cardiac phases: S1, systole, S2, and diastole. The accuracy of our method has been assessed on a public synchronized radar–PCG dataset acquired by means of a 24 GHz Doppler radar and a digital stethoscope. On the test subset, the proposed model achieved a 13.4885 dB reduction in log-spectral distance relative to the radar input signal, indicating a marked improvement in waveform fidelity. Segmentation performance also improved, with Micro-${\mathrm{F}}_1$ increasing from 74.41% to 84.17% and Macro-${\mathrm{F}}_1$ from 68.40% to 80.43% on average. Experimental results demonstrated the viability of real-time low-power embedded hardware deployment for contactless auscultation and continuous cardiac monitoring applications. The findings confirm that respiratory interference and low-amplitude signals complicate S2 detection, especially when exacerbated by subject motion. Full article

Ascosphaera apis, an obligate lethal fungal pathogen that infects bee larvae, and causes chalkbrood disease, poses a significant threat to the global beekeeping industry. Long non-coding RNAs (lncRNAs) are employed by pathogens to enhance infectivity and evade host immunity. Here, lncRNAs in A. apis spores (AaCK group) and the guts of 4-, 5-, and 6-day-old Apis cerana cerana worker larvae inoculated with A. apis spores (AaT1, AaT2, and AaT3 groups) were identified, characterized, and validated. Additionally, the expression pattern of fungal lncRNAs during infection was analyzed, followed by an investigation of the regulatory manners and roles of differentially expressed lncRNAs (DElncRNAs). A total of 1379 lncRNAs were identified in AaCK, AaT1, AaT2, and AaT3 groups using bioinformatics, involving various types such as sense lncRNAs, antisense lncRNAs, bidirectional lncRNAs, intergenic lncRNAs, and intronic lncRNAs. Additionally, 4, 9, and 75 up-regulated lncRNAs as well as 2, 1, and 15 down-regulated ones were identified in the 4-, 5-, and 6-day-old larval guts following A. apis inoculation. Fifteen DElncRNAs as potential antisense lncRNAs may interact with 15 sense-strand mRNAs in the AaCK vs. AaT3 comparison group. Cis-acting analysis identified 10, 16, and 136 upstream and downstream genes of DElncRNAs in the aforementioned comparison groups, involving a series of GO terms and KEGG pathways like metabolic process and biosynthesis of secondary metabolites. Following the trans-acting investigation, 752, 821, and 1327 co-transcribed genes with DElncRNAs were discovered, spanning an array of functional terms and pathways such as biological processes and glycerophospholipid metabolism. Analysis of a competing endogenous RNA (ceRNA) network indicated that 1 and 5 DElncRNAs in the AaCK vs. AaT1 and AaCK vs. AaT3 comparison groups potentially targeted 1 and 2 miRNAs, further targeting 208 and 286 mRNAs, respectively. Further analysis identified one ceRNA axis relevant to the MAPK signaling pathway and several ceRNA networks associated with the biosynthesis of secondary metabolites. Finally, RT-qPCR results confirmed that the expression trends of six randomly selected DElncRNAs were consistent with those in the transcriptome data. These findings not only offer a foundation for elucidating the mechanisms underlying DElncRNA-mediated A. apis infection but also enrich our understanding of honeybee host–fungal pathogen interactions. Full article

Osteoporosis in women is strongly influenced by menopause, a major physiological transition that reshapes bone metabolism. Although low bone mineral density (BMD) in premenopausal women and osteoporosis in postmenopausal women share the clinical outcome of skeletal fragility, it remains unclear whether they reflect a shared molecular program or distinct regulatory mechanisms. Here, we compared genetic signals associated with premenopausal and postmenopausal low BMD in Korean women using two independent genotyping platforms with distinct variant coverage. After allele harmonization and heterogeneity testing, variants were classified as reversal signals, showing directionally discordant effects across menopausal status, or stable signals, showing concordant effects. Gene-level association analysis was performed using Multi-marker Analysis of GenoMic Annotation (MAGMA), followed by functional enrichment and network-based analyses. Reversal and stable signals showed distinct biological patterns. Reversal signals consistently converged on cyclic nucleotide-related pathways, including cyclic adenosine monophosphate/cyclic guanosine monophosphate (cAMP/cGMP) signaling and nitric oxide-mediated processes, whereas stable signals were more broadly distributed across pathways related to ion homeostasis, cell–substrate adhesion, and structural maintenance. These pathway-level patterns were reproducible across platforms despite limited SNP-level overlap. These findings suggest that low BMD across the menopausal transition is better resolved at the gene and pathway levels than at the level of individual SNPs. Full article

Series arc faults on the DC side of photovoltaic (PV) systems are a critical hazard that can trigger system fires. Conventional contact-based detection methods suffer from cumbersome installation and high retrofit cost, whereas existing non-contact approaches mostly rely on megahertz-level high-frequency sampling and therefore require expensive radio-frequency instrumentation or high-performance computing platforms. As a result, it remains difficult to simultaneously achieve strong interference immunity and real-time performance on low-cost embedded devices with limited resources. To address this engineering paradox between high-frequency sampling and constrained computational capability, this paper proposes a fully embedded, non-contact arc fault detection system based on a 12–80 kHz low-frequency sub-band selection strategy. By exploiting the physical characteristic of broadband energy elevation induced by arc faults, the proposed strategy avoids dependence on high-bandwidth hardware. Guided by this strategy, a Moebius-topology coaxial shielded loop antenna is employed as the near-field sensor, while an ultra-simplified passive analog front end is constructed directly by using the on-chip programmable gain amplifier and analog-to-digital converter of the microcontroller unit, enabling efficient signal acquisition and fast Fourier transform processing within the target sub-band. To cope with complex background noise in the low-frequency range, an environment-adaptive baseline mechanism based on exponential moving average and exponential absolute deviation is developed for dynamic decoupling. In addition, a lightweight INT8-quantized multilayer perceptron is introduced as a nonlinear auxiliary module, thereby forming a robust hybrid decision architecture with complementary rule-based and artificial intelligence components. Experimental results show that, under the tested household, laboratory, and PV-site conditions, the proposed system achieved an overall detection rate of 97%, while the remaining 3% mainly corresponded to failed ignition or non-sustained arc attempts rather than persistent false triggering during normal monitoring. Full article

Alzheimer’s disease (AD) is a serious neurodegenerative disorder that can severely affect behavior and thinking patterns, and is accompanied by frequent memory loss. The early diagnosis of AD is essential, as this can benefit the patient, but detecting AD is a complex process due to the nature of its associated clinical data. Electroencephalography (EEG) serves as a promising and cost-effective technique for analyzing AD-related brain activity patterns. In this work, a consolidated framework for detecting AD using EEG signals and hybrid models is proposed that uses a dataset that is available online. For the feature extraction module, five efficient techniques—Principal Component Analysis (PCA), Kernel Partial Least Squares (KPLS), Kriging Model, Isomap, and K-means clustering—are used. For feature selection, with the help of biomimetics-based concepts, three efficient algorithms are used: hybrid Cuckoo Search Optimization–Rat Swarm Optimization (CSO-RSO), Zebra Optimization (ZOA), and hybrid Gravitational Search Algorithm–Particle Swarm Optimization (GSA-PSO). Four interesting hybrid classifiers are utilized here to detect AD using EEG signals—hybrid Extreme Learning Machine–Adaboost (ELM–Adaboost), hybrid Classification and Regression Trees–Adaboost (CART–Adaboost), and hybrid weighted broad learning system-based Adaboost (HWBLSA), followed by a hybrid machine learning classification model with a soft voting technique—and, finally, these are compared with other standard machine learning classifiers. The highest classification accuracy of 98.71% is found when the Kriging Model feature extraction concept is combined with the hybrid GSA-PSO feature selection method and classified with the ELM–Adaboost classifier. Full article

Lunar optical and synthetic aperture radar (SAR) imagery provide complementary information for characterizing the lunar surface. However, their joint use remains challenging because of substantial cross-modality differences and severe illumination constraints, particularly in polar regions. To address this challenge, we propose LS2ODiff (Lunar SAR-to-Optical Diffusion), a diffusion-based framework designed for SAR-to-optical image translation in lunar environments. LS2ODiff uses SAR observations as conditional guidance in the diffusion process and incorporates a partial-convolution strategy into the U-Net backbone to handle irregular invalid regions. In addition, self-attention modules are incorporated into the downsampling stages of the U-Net to model long-range spatial dependencies and enhance global structural consistency in complex lunar terrain. We further construct a dedicated paired dataset of the lunar south polar region by registering Chandrayaan-II DFSAR data with Lunar Reconnaissance Orbiter (LRO) Narrow-Angle Camera (NAC) imagery. Comparative experiments against Pix2Pix, CycleGAN, SynDiff, and ConDiff demonstrate that LS2ODiff achieves better visual fidelity and quantitative performance in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), Fréchet inception distance (FID), and learned perceptual image patch similarity (LPIPS). These results demonstrate the potential of diffusion models for high-fidelity lunar image translation, offering new opportunities for polar terrain interpretation and future exploration missions. Full article

Background: Atherosclerosis preferentially develops at arterial regions exposed to low shear stress (LSS), highlighting the critical role of local hemodynamic forces in disease initiation and progression. Emerging evidence indicates that endothelial lipid metabolism is a key determinant of vascular homeostasis; however, whether LSS directly regulates endothelial lipid droplets’ (LDs) dynamics remains unclear. In particular, the mechano-transduction pathways linking shear stress to lysosome-mediated lipid processing within the endothelium have yet to be defined. Methods: Complementary in vitro flow systems and in vivo atheroprone models were employed to examine the effects of LSS on endothelial lipid metabolism. Endothelial LDs accumulation, lysosome-dependent lipophagy, and atherosclerotic lesion development were systematically assessed under LSS conditions. Mechanistically, molecular profiling and rapamycin-mediated functional rescue were conducted to delineate the role of the KLF4/TFEB/ATP1A1 signaling axis in LSS-induced impairment of lysosome-dependent lipophagy. Results: We found that LSS induced pathological accumulation of LDs in vascular endothelial cells, accompanied by a marked suppression of lysosome-dependent lipophagy. Elucidation of the mechanism showed that LSS downregulated the shear-responsive transcription factor KLF4, resulting in aberrant phosphorylation of transcription factor EB (TFEB) and impaired TFEB nuclear translocation. Consequently, the TFEB transcriptional program governing lysosomal function was disrupted, including reduced expression of the TFEB target ATP1A1, leading to defective lysosomal acidification and blockade of lipid autophagic flux. Restoration of the KLF4/TFEB/ATP1A1 axis reactivated lipophagy, alleviated endothelial lipid burden, and significantly attenuated atherosclerotic lesion development. Conclusions: Our findings demonstrate that disruption of the KLF4/TFEB/ATP1A1 signaling pathway mediates LSS-induced impairment of endothelial lipophagy, thereby driving pathological LDs accumulation. This highlights the potential of restoring this axis as a therapeutic strategy to attenuate atherosclerotic progression. Full article

The persistence of an immunosuppressive microenvironment remains a formidable challenge for cancer immunotherapy, particularly in tumors with immune-excluded or immune-desert phenotypes. Increasing evidence indicates that chronic inflammation and tumor progression are intrinsically linked through shared signaling hubs, including NF-κB and PI3K/Akt. Osthole, a natural coumarin compound, has been reported to exhibit both potent anti-inflammatory and antitumor activities; however, whether these effects reflect a coordinated regulation of the inflammation–cancer axis remains unclear. In this study, we deployed an integrative framework founded on network pharmacology, molecular docking, and rigorous molecular dynamics simulations, complemented by literature-based evidence synthesis, to computationally explore the potential mechanisms underlying Osthole’s dual activities. Our analysis revealed that Osthole’s predicted targets are significantly enriched in signaling pathways bridging inflammatory and oncogenic processes, most notably the PI3K/Akt, NF-κB, and TGF-β/Smad pathways. Crucially, MD simulations provided supportive computational evidence, suggesting that Osthole forms stable, energetically favorable complexes with core protein hubs (AKT1, RELA, and TGFB1) under the simulated conditions. Evidence from representative inflammatory and tumor models supports the biological plausibility of these predictions, including suppression of pro-inflammatory signaling, mitigation of maladaptive tissue remodeling, and induction of apoptosis. Furthermore, in hepatocellular carcinoma models, Osthole-mediated apoptosis appeared linked to HMGB1-related inflammatory signaling, highlighting its potential to modulate the local immune niche. Collectively, this convergence of systems-level predictions and dynamic structural evidence identifies Osthole as a promising multi-target candidate for the coordinated regulation of inflammation-associated tumor progression, providing a robust rationale for further experimental validation. Full article

Objective: In this study, Dehydroepiandrosterone (DHEA-induced Polycystic Ovary Syndrome (PCOS) mice were used as models to evaluate the improvement effect of Vitexin (Vit) on ovarian fibrosis and explore the mechanism of action of the NR4A1/NLRP3 signaling pathway. Method: Sixty 4-week-old female ICR mice of the same batch number were selected and their systems were divided into 6 groups (n = 10): normal (Control, Ctrl) group, model (Polycystic Ovary Syndrome, PCOS) group, treatment (Vitexin, The Vit group, normal NR4A1 gene silencing group (Ctrl NR4A1^-/-), NR4A1 gene silencing model group (PCOS NR4A1^-/-), and NR4A1 gene silencing treatment group (Vit NR4A1^-/-). Silencing gene modeling was performed by tail vein injection of adeno-associated virus (serotype AAV-8), and the mouse genotypes were detected by qRT-PCR technology 14 days after injection. After the genotype was determined, the PCOS group and the PCOS NR4A1^-/- group were administered dehydroepandrosterone (6 mg/100 g/d) by gavage for 28 consecutive days for modeling, while the Vit group and the Vit NR4A1^-/- group were treated with dehydroepandrosterone + vitexin (10 mg/kg/d) by gavage for 28 consecutive days. All mice were raised with pure water and regular maintenance food. After 4 weeks of drug intervention, the mice were euthanized and samples were collected. The pathological changes in ovarian tissue were observed by H&E staining, and the degree of ovarian tissue fibrosis was observed by Masson staining. The levels of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px), malondialdehyde (MDA), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in mouse serum were detected by biochemical kits. The levels of inflammatory factors (IL-1β, IL-6, IL-18, TNF-α) in mouse serum were determined by enzyme-linked immunosorbent assay. Real-time fluorescence quantitative PCR (qRT-PCR) was used to detect oxidative kinase (Gsta4, Prdx3, Mgst1, Gpx3, Gsr), inflammatory factors (Nlrp3, Caspase-1, Asc, Il-1β, Il-18, Tnf-α) and fibrotic pathway-related genes (Tgf-β1, Smad3, Collagen1, CTGF, α-SMA, Mmp-13, and β-catenin) in ovarian tissues. The levels of inflammatory factors (NLRP3, Caspase-1, ASC, IL-1β, IL-18, TNF-α, IκBα) and fibrosis in mice were determined by Western blot method, and statistical description and analysis were performed using SPSS software. Result: In the wild-type genotype group, compared with the PCOS group, Vit treatment could effectively regulate the metabolic abnormalities of PCOS mice, including inhibiting excessive weight gain, restoring normal glucose tolerance, and reducing body fat content. After Vit treatment, the levels of MDA, TC, TG, LDL, IL-1β, IL-6, IL-18 and TNF-α in the serum of PCOS mice were significantly reduced, while the levels of SOD and HDL in the serum of PCOS mice were increased. The staining results indicated that Vit treatment could significantly inhibit the process of ovarian fibrosis in PCOS mice. The results of WB and PCR demonstrated that after Vit gavage treatment in mice, inflammatory and fibrotic factors such as Nlrp3, Caspase-1, Asc, Il-1β, Il-18, Tgf-β1, Smad3, Collagen1, CTGF, and α-SMA in ovarian tissues could be significantly down-regulated, and the fibrotic level of ovarian tissues could be reduced. Among the same measurement indicators, the silenced NR4A1 group showed a certain degree of increase compared with the wild genotype group, but there was no significant difference. Conclusions: Vit intervention can restore the sex hormone levels and follicular development in ovarian tissues of PCOS mice, regulate reproductive endocrine disorders and abnormal lipid metabolism levels, and regulate the expression of Collagen I, a-SMA and CTGF in the ovaries by inhibiting the NR4A1/NLRP3 signaling pathway, thereby improving the ovarian fibrosis level of PCOS mice. It is suggested that it may play a key role in the treatment of PCOS and the prevention and delay of its long-term complications. Full article

Goose blood has anticancer properties and was recorded in ancient China, but the specific molecular mechanisms underlying this effect still require further exploration. In this study, SW1990 cells were treated with goose serum or plasma, and transcriptome analysis was performed to explore the function of goose blood on cancer cells. Metabolomic profiling was also performed on goose serum, goose plasma, chicken serum, and chicken plasma to identify the bioactive substances responsible for the anticancer effect. The study examined the effects of goose plasma and serum on SW1990 cells and compared the metabolites between goose and chicken blood. Wound scratch, CCK-8, and Annexin V-PI assays showed that goose plasma and serum inhibited SW1990 cell proliferation at 24 and 48 h. Both treatments reduced cell viability, with serum inducing early and late apoptosis and plasma inducing late apoptosis. RNA sequencing (RNA-seq) identified 2259 (1418 upregulated, 841 downregulated) and 2731 (1844 upregulated, 887 downregulated) differentially expressed genes (DEGs) in the plasma and serum groups versus the negative control (NC), respectively, and 689 DEGs between the plasma and serum groups. Gene Ontology (GO) and KEGG pathway analyses revealed that the DEGs were enriched in processes such as lipid metabolism, JAK-STAT, and IL-17 pathways. Untargeted liquid chromatography–tandem mass spectrometry (LC-MS/MS) analysis identified distinct metabolites in goose and chicken blood, with unique metabolites and differential ones between groups. In SW1990 cells, four metabolite subclusters matched the plasma and serum effects. In summary, goose blood can suppress cancer cells by regulating gene expression to affect the key signaling pathways involved in cancer cell apoptosis and autophagy. Certain metabolites present at high concentrations in goose blood, such as cucurbitacin D and Oleoyl-L-carnitine, may also contribute to the inhibition of cancer cell proliferation and migration. These findings suggest that goose blood holds broad application prospects as a future auxiliary drug for cancer treatment, and this study provides a theoretical basis for the further application of goose products. Full article

Ultrafast physical random bit generators (PRBGs) are essential components for modern applications in secure communication, quantum cryptography, encrypted optical fiber sensing and artificial intelligence. While optical chaos-based PRBGs offer high-speed capabilities, conventional systems often rely on discrete components that suffer from system complexity and environmental instability. This paper proposes and experimentally demonstrates a robust, integrated solution using a two-section mutual injection DFB laser. The device was fabricated using the reconstruction equivalent chirp (REC) technique, which provides precise control over grating phase variation while utilizing low-cost, high-volume fabrication methods. The laser sections, each measuring 450 μm in length, were designed with a free-running wavelength difference of 0.3 nm to ensure a flat optical spectrum and enhanced chaotic dynamics. By optimizing the bias currents, we achieved a chaos RF bandwidth of 20.1 GHz. Notably, the resulting chaotic signal lacks time-delayed signatures, which simplifies the randomness extraction process. To generate random bits, the chaotic waveform was sampled by an 8-bit analog-to-digital converter at 100 GSa/s. Following post-processing through delay-subtracting and the extraction of the four least significant bits (4-LSBs), we realized a total physical random bit rate of 400 Gb/s. The randomness of the generated sequence was successfully verified using the NIST SP 800-22 statistical test suite. This approach offers a compact, energy-efficient, and high-performance integrated chaotic source suitable for secure communication and high-performance computation. Full article

NanoArduSiPM represents a paradigm shift in the ArduSiPM (Architected Detection Unit for Silicon Photomultipliers) roadmap, evolving from a standalone instrument into a high-density modular building block (36 mm × 42 mm × 3 mm, 7 g). This revision does not merely pursue miniaturization; it re-engineers the signal-processing chain to maintain high performance within a scaled-down footprint, enabling the transition from single-unit detection to scalable, distributed multi-detector systems. NanoArduSiPM is based on a three-layer architecture comprising an external scintillator and Silicon Photomultiplier (SiPM) detection module, a dedicated high-speed discrete analog front-end, and a System-on-Chip (SoC) for embedded acquisition and processing. The physical implementation adopts high-integrity PCB routing and rigorous isolation techniques designed to suppress digital–analog coupling, a critical requirement in such a compact form factor. This deterministic layout strategy provides the architectural foundation for time-tagging capabilities, currently under quantitative characterization, by addressing the fundamental sources of signal interference at the hardware level. Beyond hardware integration, NanoArduSiPM introduces the capability for extended firmware functionality, including event tagging via external inputs and the implementation of coincidence and veto logic. This framework supports the acquisition of multiple correlated histograms and allows multiple units to be interconnected on a shared SPI bus. By shifting from standalone operation to a coordinated, hierarchical architecture, NanoArduSiPM enables distributed detection schemes where event selection and correlation are handled natively within the system, reducing the dependency on external data acquisition electronics. The compact modular architecture, together with the high-performance discrete analog front-end and embedded data handling, makes NanoArduSiPM suitable for applications where low mass and low power consumption are critical, targeting applications such as space-based payloads, laboratory instrumentation, remote sensing, and large-scale distributed multi-channel detection systems. While no radiation-tolerance qualification of the complete system has been performed in this work, the microcontroller family used in the design is also available in radiation-tolerant variants, which may support future implementations targeting more demanding radiation environments. Full article

Low-cost IoT-based air quality sensors enable dense monitoring networks but suffer from significant measurement noise and instability particularly in dynamic environments. Conventional fixed-window smoothing reduces noise but introduces a trade-off between signal stability and temporal responsiveness, often attenuating short-term pollution events. This paper proposes an adaptive filtering algorithm that dynamically adjusts the averaging window size based on short-term signal variability. The method relies on real-time variance estimation to balance noise suppression and sensitivity to rapid changes without increasing computational complexity. The approach is implemented within an IoT-based monitoring framework and evaluated using parallel measurements with a certified reference device. Comparative analysis against a certified reference device demonstrates strong agreement, with Pearson correlation coefficients reaching r = 0.88 for PM_2.5 and r = 0.86 for PM₁₀, and low error levels (RMSE ≈ 2.1–2.2 µg/m³). The proposed adaptive filtering approach preserves temporal dynamics while improving signal stability and robustness compared to raw and fixed-window filtering. In addition, this method improves event detection stability, achieving low false alarm rates and near real-time response (latency < 1 sampling interval), supporting RPA-based workflow triggering. The results show that the proposed adaptive filtering provides an efficient and lightweight solution for real-time signal processing on resource-constrained devices, making it suitable for large-scale deployment in environmental monitoring systems. Full article

Prenatal exposure to ionizing radiation is a known risk factor for neurodevelopmental deficits; however, the molecular mechanisms linking chronic embryonic insult to abnormal brain development remain poorly understood. This study investigated the long-term consequences of chronic prenatal gamma irradiation throughout gestation in C57BL/6 mice. Behavioural analysis of adult offspring revealed a specific increase in depression-like behaviours, with no significant alterations in anxiety or general exploratory activity. Immunohistochemical assessment demonstrated a significant reduction in adult hippocampal neurogenesis, marked by decreased doublecortin (DCX)-positive newborn neurons in the subgranular zone and fewer NeuN-positive mature neurons in the dentate gyrus hilus. Integrated RNA-seq, qPCR, and Western blot analyses implicated the upregulation of the Mef2c/Egr1 signalling pathway in this neurogenic deficit. Furthermore, miRNA sequencing identified a pronounced decrease in miR-1843a-3p, which was subsequently validated to directly target Mef2c. Collectively, these findings suggest that prenatal gamma irradiation disrupts neurogenic processes and adult brain function, leading to specific behavioral abnormalities. This long-term impairment is associated with, and may be at least partially mediated by, dysregulation of the miR-1843a-3p/Mef2c/Egr1 pathway. Full article