Search Results (1,796)

Moisture significantly reduces the load-carrying capacity of lubricating oil films, accelerates oxidative degradation, and induces equipment corrosion, making it a critical hazard factor affecting lubrication reliability. To overcome the limitations of existing methods for determining water content—such as complex operation, poor real-time performance, and high cost—this paper proposes a radio frequency identification (RFID)-based method for lubricating oil water content detection via the orthogonal fusion of phase and received signal strength indicator (RSSI) as an off-line analytical tool. The method exploits the signal variation characteristics when RF signals penetrate media with different dielectric properties; by analyzing the phase and RSSI of backscattered RFID signals, non-contact moisture sensing is achieved. First, a theoretical model integrating phase and RSSI for water content detection is established to reveal the differential response mechanisms of the two parameters to water content. Second, a detection method based on phase-RSSI orthogonal fusion is proposed, and performance evaluation metrics are constructed. Finally, comparative experiments with different detection approaches are conducted. It is found that as water content increases, the mean phase continuously rises with significantly increased fluctuation, while RSSI exhibits a linear decreasing trend, demonstrating clear complementary response characteristics. Compared with single-phase or single-RSSI methods, the proposed fusion method achieves a coefficient of determination (R²) of 0.95 over the 0–2.0% water content range, with reliable detection verified at concentrations as low as 0.1%, and exhibits superior detection sensitivity in the low-water-content range. Furthermore, it possesses a type-discrimination capability absent in single-parameter methods—that is, it can effectively distinguish whether response variations originate from moisture contamination or non-moisture interference. The method offers stable response and high detection efficiency, providing a new approach for accurate determination of water content in lubricating oil. Full article

Food spoilage along the supply chain represents a major global challenge, contributing to economic losses, environmental impacts, and food safety concerns. Graphene-based materials have emerged as promising platforms for real-time food freshness monitoring owing to their high surface area, electrical conductivity, chemical sensitivity, and compatibility with flexible sensing architectures. This review critically examines graphene-based sensing strategies for food freshness and spoilage monitoring, including chemiresistive, dielectric, field-effect, optical/fluorescence, photoelectrochemical, mass-sensitive, and colorimetric approaches. Representative sensing platforms are compared in terms of analytical performance, including detection range, limit of detection, selectivity, response and recovery times, calibration, reproducibility, and stability. Particular attention is given to machine-learning-assisted sensing, multifunctional platforms for temperature, humidity, and gas monitoring, and the challenges associated with real-world implementation, including environmental interference, sensor fouling, signal drift, long-term stability, and cross-matrix validation. Finally, commercialization readiness, integration into intelligent packaging, and safety and regulatory considerations related to graphene-based food-contact applications are discussed. Overall, the review identifies the main technological gaps and future research priorities toward robust, scalable, and practical graphene-based systems for real-time food freshness monitoring. Full article

Dengue is a mosquito-transmitted viral disease caused by the positive-sense RNA dengue virus (DENV), which comprises four antigenically distinct serotypes (1–4). Although DENV circulates predominantly in tropical and subtropical regions, its global incidence continues to increase. As most patients present viremia at the onset of clinical manifestations, real-time RT-PCR has become a widely adopted method for early dengue detection. The AP Biotech Discovery^® Dengue Virus RT-PCR Detection Kit enables qualitative detection of DENV RNA (serotypes 1–4) by real-time RT-PCR in serum or plasma samples. The assay was recently cleared by ANMAT (National Administration of Drugs, Food and Medical Technology) as an in vitro diagnostic (IVD) assay. The Limit of Detection (LoD) was calculated for all 4 serotypes. Clinical validation was conducted among 296 serum and 221 plasma samples previously characterized as DENV-positive and -negative specimens. Among the positive samples, 56 had serotype characterization, including 25 DENV-1 and 31 DENV-2 samples. The resulting clinical sensitivity and specificity were 97.8%, 100.0% and 100.0%, 99.1% respectively. Additional validation studies demonstrated high reproducibility across three independent laboratories, absence of cross-reactivity with other febrile pathogens, and no interference from endogenous and exogenous substances at clinical levels. Collectively, these findings support the AP Biotech Discovery^® Dengue Virus RT-PCR Detection Kit (AP Biotech, Lomas de Zamora, Argentina) as a sensitive, specific, and highly reproducible device for early dengue diagnosis and surveillance. Full article

Small objects in unmanned aerial vehicle (UAV) imagery often occupy only a few pixels, making their responses vulnerable to downsampling, cluttered backgrounds, and cross-scale feature misalignment. Most detector improvements handle backbone representation, encoder context modeling, and neck fusion as separate design choices, so the frequency structure of tiny targets and the geometric consistency of multi-scale features remain underused. FSA-DETR addresses this gap with a frequency-aware and structure-aligned design built on Real-Time Detection Transformer (RT-DETR). Its central idea is to treat UAV small-object detection as a frequency–structure representation problem: high-frequency target cues are enhanced in the backbone and encoder, while local structural orientation is aligned during cross-scale fusion. The design combines a Cross-stage Spectral-Aware Multi-scale Block, a Wavelet-enhanced Intra-scale Transformer Encoder, and a Spectral Orientation-Aligned Fusion module. On VisDrone2019, FSA-DETR achieves 21.5% AP and 37.5% AP50, improving the RT-DETR baseline by 1.6% and 2.4%, respectively, while reducing the computational cost to 48.8 GFLOPs and the parameter count to 15.04 M. The small-object metric APs increases by 1.3%, and the broader size-stratified gains indicate improved sensitivity to aerial targets across multiple scales. On AI-TOD, FSA-DETR obtains 22.5% AP and 51.9% AP50, suggesting that the same frequency–structure design transfers to extremely tiny objects. Under the reported benchmark protocol, explicitly coupling frequency-sensitive perception with structure-aligned fusion improves UAV small-object detection while keeping the complete model smaller than the RT-DETR baseline used in this study; this suggests that separating spectral discrimination from geometric alignment is a useful design pattern for UAV detectors. Full article

Xishuangbanna (XIS) cucumber (Cucumis sativus) originated from low-altitude southwest China and shows extreme cold sensitivity. Nano-hydroxyapatite (nHAP), known for its high bioavailability and surface reactivity relative to bulk HAP, was applied to enhance the cold tolerance of XIS seedlings. We optimized fertilization timing and fertilizer concentration. By determining physiological parameters alongside gene expression profiling and transcriptomic analysis, we preliminarily dissected the physiological and molecular mechanisms underlying nHAP-enhanced chilling tolerance. nHAP application preserved free and bound water even at 24 h into the cold-stress treatment, as detected by nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI). Exposure to cold stress caused a chilling injury index (CII) of 73.33%, while foliar spraying of nHAP at gradient concentration reduced CII values by 9.09–54.55%. At the same time, electrolyte leakage and malondialdehyde content were decreased by 6.68–61.41% and 12.92–67.16% respectively; chlorophyll content increased by 0.01–73.42%; SOD, POD, and soluble protein content increased by 10.54–161.53%, 16.50–154.33%, and 2.03–63.26%, respectively. Soil application of nHAP showed a similar but weaker effect than foliar spraying on alleviating chilling injury, and the optimal concentration was 1000 mg/L. Quantitative Real-Time PCR (qRT-PCR) revealed that foliar spraying of nHAP upregulated the gene expression of Superoxide dismutase genes (CsCu/ZnSOD and CsMnSOD) and major facility superfamily genes (CsSPX-MFS1 and CsSPX-MFS2) in the cold treatment. We then profiled the transcriptome changes in seedling leaves during the cold treatment after foliar spraying of nHAP. Without nHAP application, cold stress resulted in a total of 6795 differentially expressed genes (DEGs), which were functionally enriched in plant–pathogen interaction and plant hormone signal transduction pathways. Under nHAP application, cold stress only caused 776 DEGs, which were functionally enriched in plant hormone signal transduction and galactose metabolism. These findings suggest that nHAP could improve the cold tolerance of cucumber seedlings through boosting antioxidant activity and plant hormone signaling pathways. Full article

Lumpy skin disease (LSD) is a transboundary viral disease of cattle, including Asian water buffalo and yaks, and certain wild ruminants (e.g., African buffalo, giraffe, wildebeest, eland, and Arabian oryx). It is caused by lumpy skin disease virus (LSDV), a member of the genus Capripoxvirus (family Poxviridae) together with goatpox virus (GTPV) and sheeppox virus (SPPV). High nucleotide identity and serological cross-reactivity among these viruses hinder differential diagnosis. The aim of this study was to develop a Duplex TaqMan-MGB qPCR Assay for Differential Detection of Chinese Epidemic Lumpy Skin Disease Virus Strains and Goatpox Virus. We developed a duplex TaqMan-MGB real-time PCR (qPCR) assay targeting the LSDV GPCR and GTPV RPO30 loci. Virus-specific primers and MGB probes were designed, and the reaction was optimized for single-tube, two-target detection. The assay showed no cross-amplification, limits of detection of 1 × 10¹ copies/μL (LSDV) and 1 × 10¹ copies/μL (GTPV), and coefficients of variation < 1%. The assay was applied to 175 yak-derived field specimens from Qinghai–Tibet Plateau, of which 16 and 36 were positive for LSDV and GTPV, respectively. LSDV- and GTPV-positive samples showed specific amplification in the FAM and VIC channels, respectively. The duplex format enables concurrent detection and unambiguous differentiation of LSDV and GTPV and is compatible with high-throughput screening. This sensitive, specific, and reproducible assay supports surveillance and control of LSD in endemic and at-risk regions. Full article

Smart chemical sensors have emerged as promising tools for real-time monitoring of food spoilage in both fermented and non-fermented products. By detecting key spoilage indicators—including biogenic amines, ammonia, hydrogen sulfide, methane, pH variations, and microbial volatile organic compounds (MVOCs)—these systems enable rapid, on-site assessment of food quality, offering a viable alternative to conventional, time-consuming laboratory analyses. Recent advances encompass diverse sensing mechanisms, including chemiresistive platforms based on conducting polymers and MEMS (Microelectromechanical Systems); optical/colorimetric systems using dyes, metal–organic frameworks, and porphyrins; and electrochemical and biosensing approaches employing enzymes, antibodies, aptamers, and whole-cell recognition elements. These sensors demonstrate high sensitivity (ppb–ppm range), enabling early detection of spoilage before sensory perception or microbiological threshold exceedance. Their applicability has been validated across a wide range of food matrices, including meat, fish, dairy products, vegetables, beverages, and fermented foods. Despite significant progress, key challenges persist, including signal drift, limited specificity, susceptibility to environmental factors such as humidity and temperature, and interference from complex food matrices. Furthermore, integration into intelligent packaging requires the development of flexible, food-safe, and regulatory-compliant materials. Emerging approaches that combine sensor arrays with machine learning and MVOC pattern recognition are enhancing predictive accuracy and enabling food classification across commodity types. Overall, smart chemical sensing technologies are rapidly transitioning from laboratory prototypes to practical applications in intelligent packaging and wireless monitoring systems, with ongoing research focused on improving robustness, standardization, and scalability for commercial deployment. This article provides an overview of the topic, drawing on the available bibliography from the last five years and the most-cited scientific databases. Full article

Listeria monocytogenes (LM), one of the most virulent foodborne pathogens, poses a serious threat to public health due to its strong environmental adaptability and high pathogenicity. Rapid, sensitive, and real-time detection of LM is of great importance. Chemiresistive gas sensors have attracted enormous attention in LM detection owing to their advantages of low cost, simple structure, fast response, and easy miniaturization, which can achieve indirect detection of LM by recognizing its specific metabolic volatile organic compounds. This review summarizes the recent progress in chemiresistive gas sensors for the detection of LM metabolites. First, the metabolic characteristics of LM and the typical volatile organic compound (3-hydroxy-2-butanone) as its characteristic biomarker are introduced. Then, the performance and sensing mechanisms of different types of chemiresistive gas sensors for LM metabolite detection are summarized and elaborated systematically. The application of chemiresistive gas sensors for the detection of actual samples and the progress in the design of related detection devices are introduced. Finally, the current challenges faced by chemiresistive gas sensors in LM metabolite detection and their future development prospects are discussed. This review provides a comprehensive reference for the research and practical application of chemiresistive gas sensors in Listeria monocytogenes detection. Full article

Micro-sprinkler irrigation is commonly used to optimize plant growing environments and prevent growth inhibition and yield losses caused by high air temperatures (T_a) in greenhouses. Nevertheless, instantaneous photosynthetic rate measurements suffer from time lag, and the temporally dynamic microclimate alterations induced by micro-sprinkling make it difficult to reproduce the real ambient conditions for crop growth. Therefore, two treatments, namely micro-sprinkling combined with drip irrigation (MSDI) and conventional drip irrigation control (DI), were established in a Venlo-type greenhouse. Continuous chlorophyll fluorescence (ChlF) monitoring combined with rapid light curves under fixed photosynthetically active radiation was adopted to investigate the diurnal alleviation effects of micro-sprinkling on tomatoes under high-temperature stress. This study found that Φ_PSII was more sensitive than Fv/Fm in detecting changes in PSII photochemical performance under high-temperature stress. Micro-sprinkling showed greater mitigation effects under moderate heat stress, with the highest enhancement in Φ_PSII (approximately 0.12) observed when leaf temperature (T_l) was around 34.5 °C. However, the improvement effect decreased under extreme heat conditions, and Φ_PSII increased by only 0.017 when T_a exceeded 38 °C. The slope of the fitted line between Φ_PSII and PAR on sunny days increased with increasing heat stress, indicating the enhanced sensitivity of PSII photochemical regulation to thermal stress. Compared with DI, MSDI increased tomato yield by 31.2% and 47.6% in 2021 and 2022, respectively, while improving fruit quality by increasing single fruit weight, fruit shape index, and soluble sugar content. In addition, MSDI increased SPAD, Fv/Fm, Φ_PSII, and ETR by 9.6–15.6%, 8.8–14.8%, 10.3–13.3%, and 10.3–19.6%, respectively, indicating improved PSII photochemical performance under high-temperature conditions. In conclusion, micro-sprinkling mitigated part of the negative effects of high-temperature stress and significantly improved tomato yields and fruit quality, which could be used in agricultural production. Full article

Background/Objectives: Human papillomavirus (HPV) testing is widely used in cervical cancer screening because of its high sensitivity, although its limited specificity requires effective triage strategies. This study aimed to evaluate the association between relative viral load (RVL) and cervical lesion severity, focusing on HPV-positive women with non-high-grade cytology. Methods: The study included 997 women with histological outcomes from a cohort of 2765 HPV-positive individuals identified among 37,030 women screened in the Bari metropolitan area (Italy) using a real-time HPV-DNA test. Associations between RVL, estimated using the ΔCt method, and lesion severity were assessed using histological and cytological classifications. Logistic regression models evaluated the independent effect of RVL, adjusting for age and HPV detection channel. Results: Lower ΔCt values (indicating higher RVL) were significantly associated with high-grade lesions (CIN2+) (OR = 0.91, 95% CI: 0.89–0.94, p < 0.001). The association was observed for HPV16 and the pooled 12-high-risk HPV detection channel, while no significant association was observed for HPV18. A similar association was observed when cytological classification was used as the outcome. Age showed a modest effect, with reduced odds of high-grade lesions observed in women aged ≥50 years. Among women with non-high-grade cytology who subsequently underwent histological assessment, 17.6% had underlying CIN2+, and RVL remained significantly associated with lesion severity in this subgroup. However, ΔCt showed only modest discrimination for high-grade lesions [AUC = 0.643 (95% CI: 0.605–0.681)]. Conclusions: Higher HPV RVL is associated with increased lesion severity, particularly for HPV16 and the pooled 12-high-risk detection channel, but not for HPV18. Given its modest standalone discriminatory performance and the selected nature of the histologically verified cohort, ΔCt should be considered an exploratory marker rather than a validated triage tool. Prospective validation is required to determine whether it provides incremental clinical value. Full article

Background/Objectives: To evaluate the diagnostic accuracy of a standalone artificial intelligence fracture detection software on foot and ankle radiographs, compared with board-certified musculoskeletal radiologists, with emphasis on midfoot injuries. Materials and Methods: This retrospective single-center diagnostic accuracy study included adult patients presenting to the emergency department with acute foot or ankle trauma. Radiographs were interpreted in real time, analyzed retrospectively by musculoskeletal (MSK) radiologists during the routine workflow and subsequently analyzed independently by an artificial intelligence system. The reference standard was structured clinical follow-up, complemented by cross-sectional imaging when the radiograph was equivocal. Diagnostic performance metrics and inter-reader agreement were calculated. Results: A total of 701 examinations (mean age, 42 ± 17 years; 376 men) were included; 319 fractures were identified, including 29 Chopart and 26 Lisfranc injuries. Overall sensitivity, specificity, and accuracy were 74.3%, 83.0%, and 79.0% for artificial intelligence, 84.0%, 95.5%, and 90.3% for radiologists, respectively (p < 0.0001; κ = 0.65). For Chopart and Lisfranc fractures, radiologists demonstrated higher sensitivity, while specificity remained excellent for both approaches, but the paired comparisons did not reach significance. Conclusions: Standalone artificial intelligence achieved high diagnostic performance for foot and ankle fracture detection on radiographs but was less sensitive than MSK radiologists for complex midfoot injuries. Full article

Both Chicken anemia virus (CAV) and Gyrovirus galga 1 (GyVg1) belong to the family Anelloviridae and genus Gyrovirus. They are non-enveloped, single-stranded circular DNA viruses that can infect chicken populations, leading to similar clinical symptoms such as growth retardation and immunosuppression, making clinical differentiation challenging. This study established a duplex TaqMan real-time PCR assay to simultaneously detect CAV and GyVg1. Specific primers and probes were developed to target the VP3 gene of CAV (labeled with VIC) and the VP1 gene of GyVg1 (labeled with FAM). The optimization process involved fine-tuning reaction conditions, such as primer/probe concentrations and annealing temperature, through a systematic matrix approach. The assay demonstrated remarkable linearity under optimized conditions (0.4 μmol/L primers, 0.2 μmol/L probes, and an annealing temperature of 52 °C), yielding high R² values of 0.9973 for CAV and 0.9981 for GyVg1. The method exhibited high specificity, showing no cross-reactivity with other common avian pathogens. The limits of detection were 1.0 × 10⁰ copies/μL for CAV and 1.0 × 10¹ copies/μL for GyVg1, making it 10-fold more sensitive than conventional PCR. Intra-assay and inter-assay coefficients of variation were below 1.5% and 2.5%, respectively, indicating excellent reproducibility. When tested on 411 clinical samples from Shandong Province, CAV showed a positivity rate of 48.66% (200/411), GyVg1 18.73% (77/411), and a co-detection rate of 17.52% (72/411). Moreover, 25 complete genome sequences of GyVg1 (2376 bp each) were acquired from positive samples. These sequences exhibited a nucleotide identity ranging from 93.6% to 99.3% among the isolates and 92.2% to 99.6% with reference strains. The phylogenetic analysis, which was based on whole-genome sequences, categorized the Shandong isolates into four clusters (I–IV). Notably, the strains were dispersed across these clusters and were intertwined with references from various regions and hosts. This observation suggests the absence of distinct geographic clustering and implies frequent cross-regional and cross-species transmission. In summary, this duplex real-time PCR assay offers a sensitive, specific, and dependable method for concurrently detecting and distinguishing CAV and GyVg1. The study’s findings reveal a significant co-infection rate and genetic variation in GyVg1, underscoring the importance of increased surveillance and deeper exploration of its pathogenicity and transmission patterns. Full article

The development of sustainable, smart food packaging materials that simultaneously provide antimicrobial protection and real-time monitoring of food quality is a critical frontier in food safety. This study reports the fabrication of a multifunctional amphiphilic emulgel designed for the detection of pathogen-induced metabolic pH changes in food systems. The system utilizes Pomegranate-derived nitrogen-doped quasi-spherical carbon dots (QS-CDs) as fluorescent nanoprobes and Rosemary Essential Oil (REO) as a natural antimicrobial agent, both encapsulated within a polyelectrolyte complex of chitosan and sugarcane bagasse-derived carboxymethyl cellulose (CMC). A low degree of substitution (DS = 0.4) was specifically engineered for the CMC to ensure an amphiphilic character, enabling nanocomposite complex stabilization of the REO droplets without synthetic surfactants. Structural characterization via Transmission Electron Microscopy (TEM) revealed well-dispersed QS-CDs (4.71–6.62 nm) and stable oil droplets (~605.49 nm) anchored within a zipped polymer network. Thermal analysis (TGA/DSC) using the Coats–Redfern model revealed a significant synergistic effect: the smart-emulgel exhibits a distinct two-stage degradation profile, with the high-temperature stage requiring an activation energy (E_a) of 95.19 kJ/mol, a substantial increase over the corresponding stage in the CD-emulgel baseline (18.69 kJ/mol). This enhanced stability is complemented by a slight increase in crystallinity (X_c from 0.11 to 0.14). While the smart-emulgel remains predominantly amorphous, this shift suggests that the integration of REO and QS-CDs into the polymer network promotes the formation of localized, more ordered domains, contributing to a more robust and structurally integrated matrix. The emulgel demonstrated a dual-mode optical response (colorimetric and fluorometric) sensitive to the metabolic byproducts (e.g., organic acids, amines, other alkaline compounds) produced by Escherichia coli and Staphylococcus aureus. These findings were corroborated by Density Functional Theory (DFT) calculations, which confirmed the thermodynamic stability and optimized electronic energy gaps for pH-responsive sensing. This research provides a green, high-performance platform for the real-time monitoring of food freshness and the prevention of foodborne illnesses. Full article

This study investigates the electrochemical properties of polymer-based microelectrode arrays (pMEAs) and their performance in measuring oxygen (O₂) and hydrogen peroxide (H₂O₂). Morphological characterization by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) revealed a uniform, fine-grained platinum surface with nanoscale roughness, consistent with the Ti/Pt/Au/Pt multilayer stack architecture. The electrochemical behavior of the pMEAs was assessed using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), which demonstrated favorable responses for both O₂ reduction and H₂O₂ oxidation, together with low impedance (41.1 kΩ at 1 kHz). For O₂ detection, amperometric measurements at −0.6 V vs. Ag/AgCl indicated a sensitivity of −0.25 ± 0.04 nA μM⁻¹ and a detection limit of 5.4 ± 1.4 nM. For H₂O₂ detection, application of +0.7 V vs. Ag/AgCl resulted in a sensitivity of 88.13 ± 7.61 nA mM⁻¹ and a detection limit of 41.9 ± 5.6 nM. Selectivity evaluation showed effective interferent exclusion following m-phenylenediamine electrodeposition, without compromising analytical performance. Overall, these findings indicate the suitability of pMEAs for real-time, in vivo monitoring of O₂ and H₂O₂ in brain tissue with high spatial and temporal resolution, supporting applications in oxidative stress research and neurometabolic sensing. Full article

Biogenic amines (BAs) are nitrogenous compounds formed by microbial decarboxylation of amino acids in protein-rich foods. Their accumulation indicates spoilage and poses health risks. Traditional methods like high-performance liquid chromatography (HPLC) and gas chromatography (GC) are sensitive but time-consuming, limiting on-site use. Rapid technologies based on specific recognition molecules offer feasible alternatives for real-time monitoring. This review summarizes five categories of recognition elements: antibodies, aptamers, molecularly imprinted polymers (MIPs), enzymes, and peptides for BA detection in foods. These elements convert BA concentrations into optical, electrical, or colorimetric signals, establishing a complete biosensing chain. Integration with portable platforms (lateral flow assays (LFAs), microfluidic chips, smart labels, and smartphone devices) is also discussed. Recognition-element-based sensing enables high-selectivity and rapid monitoring of BAs in foods. Antibody/aptamer systems excel in specific histamine detection, enzyme platforms in rapid total amine assessment, and MIPs in chemical stability and matrix tolerance. Yet practical application is limited by poor selectivity for similar amines, matrix interference, insufficient real-food validation, and device standardization. Our future focus will be on AI-assisted design, multi-target arrays, smartphone quantification, and IoT-enabled freshness monitoring. Full article