Search Results (1,645)

Accurate and stable mapping of crop types is fundamental to agricultural monitoring and food security. However, inter-annual phenological shifts driven by variations in air temperature, precipitation, and sowing dates introduce systematic changes in the spectral distributions associated with the same day of year (DOY). As a result, the “date–spectrum–class” mapping learned during training can become misaligned when applied to a new year, leading to increased misclassification and unstable performance. To tackle this problem, we develop TABS-Net (Temporal–Spectral Attentive Block with Space–Time Fusion Network). The core contributions of this study are summarized as follows: (1) we propose an end-to-end 3D CNN framework to jointly model spatial, temporal, and spectral information; (2) we design and embed CBAM3D modules into the backbone to emphasize informative bands and key time windows; and (3) we introduce DOY positional encoding and temporal jitter during training to explicitly align seasonal timing and simulate phenological shifts, thereby enhancing cross-year robustness. We conduct a comprehensive evaluation on a Cropland Data Layer (CDL) subset. Within a single year, TABS-Net delivers higher and more balanced overall accuracy, Macro-F1, and mIoU than strong baselines, including 2D stacking, 1D temporal convolution/LSTM, and transformer models. In cross-year experiments, we quantify temporal stability using inter-annual robustness (IAR); with both DOY encoding and temporal jitter enabled, the model attains IAR values close to one for major crop classes, effectively compensating for phenological misalignment and inter-annual variability. Ablation studies show that DOY encoding and temporal jitter are the primary contributors to improved inter-annual consistency, while CBAM3D reduces crop–crop and crop–background confusion by focusing on discriminative spectral regions such as the red-edge and near-infrared bands and on key growth stages. Overall, TABS-Net combines higher accuracy with stronger robustness across multiple years, offering a scalable and transferable solution for large-area, multi-year remote sensing crop mapping. Full article

Pigs are a major source of animal protein for humans and serve as valuable biomedical models. Compared to Western commercial pig breeds, Jinhua pigs are characterized by superior meat quality due to dynamic muscle development and fat deposition. However, studies investigating dynamic transcriptional regulation of swine meat quality traits across developmental stages remain limited. In this work, we collected longissimus dorsi muscle tissue from three Jinhua and three Landrace × Yorkshire pigs at 1, 90, and 180 days of age, respectively. We have uncovered differentially expressed genes and transcripts, alternative splicing events, and gene fusion events across development stages utilizing RNA sequencing data. CKM exhibited consistent breed-specific alternative splicing and gene fusion events across all three stages, representing a stable regulator of muscle development in Jinhua pigs. On the other hand, our findings highlight day 90 as a critical “window phase” for muscle development and meat quality differences between Jinhua and Landrace × Yorkshire pigs at this stage, exhibiting the greatest number of inter-breed differences in transcriptomic genetic regulation. Additionally, time series analysis revealed that genes with peak expression at day 90 were significantly enriched in pathways associated with muscle development and function. Finally, we identified PFKM, PRKAG3, and CKM as candidate genes with age-specific expression and post-transcriptional regulation that likely influence muscle development. This study advances understanding of transcriptional regulation in pig muscle with implications for meat quality improvement. Full article

The Tibetan chicken (TC) is a small indigenous breed native to the Qinghai–Tibet Plateau in China, exhibiting remarkable adaptation to the plateau’s extreme high-altitude environment. Its strong hypoxia tolerance is reflected in the ability to maintain normal embryonic cardiac structure and function during hypoxic incubation or high-altitude incubation. This study performed transcriptome sequencing of embryonic heart tissues from TC and White Leghorn (WL) incubated for 9, 11, and 16 days in Lhasa (altitude of 3650 m). A total of 1788 differentially expressed genes (DEGs) were identified through inter-breed comparison. Some DEGs were enriched in signaling pathways related to angiogenesis, apelin signaling, and myocardial contraction. Through integrating temporal expression analysis and weighted gene co-expression network analysis (WGCNA), we identified six key candidate DEGs (CREB3L2, MYH7B, CREB1, LOXL2, MICAL2, and AKAP13) that are involved in hypoxic response, myocardial structural remodeling, and regulation of signaling pathways. These genes likely represent core components of the molecular network underlying hypoxic adaptation in TC embryos. Overall, our findings provide a molecular basis for understanding the genetic mechanisms of hypoxic adaptation during embryonic cardiac development in chickens. Full article

Background/Objectives: Inter-individual variability in injury severity represents a major barrier to reproducibility in neonatal hypoxia–ischemia (HI) models. Objective early postoperative stratification of animals is therefore essential for standardized group allocation and reliable assessment of experimental outcomes. This study aimed to evaluate whether laser speckle contrast imaging (LSCI) can be used as a rapid, noninvasive tool for early post hoc stratification of ischemic brain damage severity in neonatal mice following HI. Methods: Neonatal CD-1 mice (postnatal day 9; n = 60) underwent hypoxia–ischemia using a modified Rice–Vannucci protocol. Cerebral perfusion was assessed by laser speckle contrast imaging at baseline, 3 h, and 7 days after HI. The difference in mean perfusion between ipsilateral and contralateral hemispheres at 3 h (Δ perfusion) was used to stratify animals into severity groups. Brain injury was quantified by 2,3,5-triphenyltetrazolium chloride (TTC) staining at 24 h and 7 days. Survival was monitored for 7 days and analyzed using Kaplan–Meier curves and the log-rank (Mantel–Cox) test. Results: LSCI-derived Δ perfusion at 3 h enabled the formation of distinct injury-severity groups (no visible damage, mild, moderate, and severe) with significant between-group differences (p < 0.0001). TTC-based lesion area increased stepwise across severity groups, and Δ perfusion correlated with lesion size when all animals were analyzed together (r = 0.688, p = 0.0011). No significant correlations were observed within individual severity groups, indicating that the overall association was driven primarily by between-group differences. Survival analysis revealed 75% mortality in the severe injury group (p < 0.0001). Conclusions: LSCI represents a robust and practical approach for early, objective, group-level stratification of neonatal mice by HI injury severity, thereby improving reproducibility and statistical validity in preclinical studies. However, its ability to predict outcomes within individual severity categories is limited, and repeated long-term measurements may pose technical challenges. Full article

Background: Advanced glycation end products (AGEs) play a pivotal role in various human pathologies, including aging and metabolic diseases, and their formation may have significant physiological consequences for human health. Fructoselysine (FL) is an intermediate in the formation of AGEs, and its accumulation has been associated with detrimental health effects. Although several chromatographic methods have been developed for AGEs detection and quantification, no mass spectrometry-based approach has previously been established to quantify FL in different human biological matrices. Methods: In this study, we present a novel UHPLC-HRMS/MS method for the identification and quantification of this compound in various biological matrices, including plasma, feces, and urine. Results: The method demonstrates excellent linearity, accuracy, and precision, with limit of detection (LOD) of 0.02 µM and limit of quantification (LOQ) of 0.06 µM. Recovery rates ranged from 95% to 109% and intra- and inter-day relative standard deviations (RSDs) were below 10%, indicating robust analytical performance. The validated method was successfully applied to quantify FL in plasma, feces, and urine samples from healthy individuals. Additionally, given the known association between AGEs and diabetes, we analyzed a small cohort of prediabetic patients and observed elevated circulating levels of FL compared to healthy controls. Conclusions: This study introduces a sensitive and reliable method for the specific detection and quantification of FL in biological samples and provides new insights into early molecular changes associated with prediabetic condition to improve early diagnosis in aging related diseases. Full article

Background and Objectives: Endothelial dysfunction is an early indicator of cardiovascular disease and is commonly assessed using flow-mediated dilation (FMD). Although handheld ultrasound (HHUS) devices improve measurement accessibility, image analysis for conventional flow-mediated dilation (FMD) assessment remains time-consuming and highly operator-dependent. This study aimed to evaluate the between-day test–retest reliability of an AI-assisted brachial artery image analysis workflow integrating HHUS imaging with a YOLO_v12 deep learning model in postmenopausal women. Materials and Methods: Seventeen postmenopausal women aged 55–70 years completed two flow-mediated dilation assessments conducted seven days apart. Brachial artery images were acquired using a standardized FMD protocol with a handheld ultrasound system. An AI-assisted image analysis workflow based on a YOLO_v12 deep learning model was used to automatically measure baseline diameter (D_base), peak diameter (D_peak), absolute FMD (FMD_abs), and relative FMD (FMD%). Between-day reliability was evaluated using intraclass correlation coefficients (ICCs), coefficients of variation (CVs), and Bland–Altman analysis. Results: Good between-day repeatability was observed for baseline and peak diameters, with ICCs of 0.81 and 0.76 and low CVs (3.26% and 3.22%), respectively. Functional vascular outcomes also demonstrated good reliability, with ICCs of 0.81 for FMD_abs and 0.87 for FMD%. However, higher CVs were observed for FMD_abs (17.15%) and FMD% (19.09%), indicating substantial inter-individual variability. Bland–Altman analysis showed a small mean difference for FMD% (0.34%), with no evidence of systematic bias. Conclusions: An AI-assisted HHUS image analysis workflow integrating a YOLO_v12 deep learning model demonstrates acceptable between-day reliability for diameter-based and dilation-based measures of flow-mediated dilation in postmenopausal women. While variability in functional responses exists, the proposed system is feasible for research-oriented vascular assessment, providing a methodological foundation for future validation and clinical translation studies. Full article

Vulnerability to heat and cold is influenced by many characteristics. This study analyzed determinants of vulnerability at the district level in the whole of Austria. Daily deaths (1970–2020) and daily temperatures per district were entered into time series models using negative binomial General Additive Models controlling for long-term and seasonal trends and for the day of the week. District-wise effect estimates of 111 districts in total were entered into linear meta-regression models seeking determinants of inter-district variation in heat and cold vulnerability. Generally, temperature effects on the daily number of deaths were highly significant in all districts, with higher death rates occurring when the same-day temperature exceeded a clear threshold and higher death rates with declining temperature averaged over the previous 14 days, in that case not showing any clear threshold effect. A higher heat vulnerability was observed for more densely populated areas, especially for the city of Vienna, for districts with a higher percentage of singles, of homeless people, of unemployed, and of migrants. Surprisingly, a higher percentage of outdoor workers seemed to be protective. Higher cold vulnerability was found for an increasingly autochthonous population, for districts with a higher employment rate, with more commuters, more agricultural workers, and more green spaces. Full article

This study provides a comprehensive, long-term evaluation of inter-sensor radiometric calibration biases for the NOAA OMPS Nadir and CrIS instruments using four complementary validation methodologies implemented within the Inter-Sensor Radiometric Bias Assessment (iSensor-RCBA) portal, a component of the STAR Integrated Calibration/Validation System. Overall, SDR data quality from the three OMPS Nadir instruments and three CrIS instruments aboard SNPP, NOAA-20, and NOAA-21 remains stable. The iSensor-RCBA portal has also proven to be a powerful diagnostic resource, enabling the detection of both new and previously unrecognized calibration issues and anomalies. Using the 32-day averaged difference method, we were the first to discover and identify the root cause of an inconsistency near 280 nm in inter-sensor radiometric biases between the SNPP and NOAA-20 OMPS NP instruments. The same method also revealed an unusual radiometric feature in NOAA-21 CrIS SDRs over the southern high latitudes during spring and summer. In addition, we derived decade-long degradation rates at 11 Metop-B GOME-2 wavelengths using an independent dataset—Simultaneous Nadir Overpass observations between SNPP OMPS and Metop-B GOME-2. Furthermore, iSensor-RCBA monitoring confirmed two geolocation anomalies in SNPP CrIS through a new approach involving SNO-based inter-sensor biases between GOES-16 ABI and SNPP CrIS. These cases demonstrate that iSensor-RCBA is not only a monitoring visualization tool but also a diagnostic tool that delivers unique, complementary insight into instrument performance, enabling early identification of radiometric and geolocation issues across JPSS and other satellite missions. Importantly, the analysis methods used in this study are broadly applicable to current and future missions, including JPSS-03, JPSS-04, and non-NOAA satellite systems. Full article

To promote the sustainable utilization of agricultural solid waste, this study proposes a novel approach for reinforcing soft clay using a peanut ash (PA)–cement composite stabilizer. The unconfined compressive strength (UCS) of pure cement and PA–cement composite systems was tested at curing ages of 3, 7, and 28 days, while the durability of the stabilized clay was evaluated through dry–wet cycling. Given that PA is rich in pozzolanic components, its addition may influence the hydration process of cement. Therefore, hydration heat analysis was conducted to examine the early hydration behavior, and XRD and TG analyses were employed to identify the composition and quantity of hydration products. SEM observations were further used to characterize the microstructural evolution of the stabilized matrix. By integrating mechanical and microstructural analyses, the solidification mechanism of the PA–cement stabilizer was elucidated. Mechanical test results indicate that the reinforcing effect increases with the stabilizer dosage. Pure cement exhibited superior strength at 3 days; however, after 7 days, specimens incorporating 5% PA showed higher strength than those stabilized solely with cement. At 28 days, the UCS of the 15% cement + 5% PA specimen reached 3.12 MPa, 11.03% higher than that of the 20% cement specimen and comparable to the 25% cement specimen (3.15 MPa). After five dry–wet cycles, the strength reduction of the 15% cement + 5% PA specimen was 22.76%, compared to 31.31% for the 20% cement specimen, indicating improved durability. Microscopic analyses reveal that PA reduces hydration heat and does not participate in early hydration, leading to lower early strength. However, its pozzolanic reactivity contributes to secondary hydration at later stages, promoting the formation of additional C-S-H gel and ettringite. These hydration products fill the inter-lamellar pores of the clay and increase matrix density. Conversely, excessive PA content (≥10%) exerts a dilution effect, reducing the amount of hydration products and weakening the mechanical performance. Overall, the use of an appropriate PA dosage in combination with cement enhances both strength and durability while reducing cement consumption, providing an effective pathway for the high-value utilization of agricultural solid waste resources. Full article

Objectives: This study aimed to define the learning curve required for cardiac surgery residents to acquire basic technical and interpretive skills in transit-time flow measurement (TTFM) and high-resolution epicardial ultrasonography (HRUS) during coronary artery bypass grafting (CABG). Methods: Prospective, observational, single-center study evaluating performance using a novel scoring system combining functional (TTFM) and anatomical (HRUS) assessment criteria. This study was registered on ClinicalTrials.gov (Identifier: NCT06589323). Nine cardiac surgery residents without prior hands-on experience in TTFM or HRUS were enrolled. Twenty-seven elective CABG patients (67 grafts) were analyzed. Each measurement was compared with those obtained by an expert benchmark surgeon (N.T.) under standardized hemodynamic conditions. Results: Residents achieved the predefined primary endpoint (combined TTFM + HRUS score/number of grafts ≥ 11) after a median of 3 cases (IQR 2–4) and 7 anastomoses (IQR 7–10). Kaplan–Meier analysis showed a progressive increase in the probability of success, with a sharp rise after the seventh anastomosis. A shorter interval between attempts (<30 days) was significantly associated with earlier achievement of the endpoint (p < 0.05). Median acquisition time for TTFM was 25 s, with <10% inter-observer variability across all flow parameters. HRUS images of adequate quality were obtained within 60 s in >90% of cases, though slightly lower success rates were observed for lateral and inferior wall targets. No resident- or procedure-related variable was independently associated with performance improvement. Conclusions: Mastery of basic TTFM and HRUS skills requires only a few cases and anastomoses, demonstrating a short and attainable learning curve. These findings challenge the perception of a steep learning process and support the routine use of intraoperative graft verification techniques in all CABG procedures. Full article

Background/Objectives: This study evaluated the validity of DEXA-derived muscle quantification by assessing its agreement with AI-assisted CT measurements of muscle volume and intramuscular adipose tissue. It also examined whether inter-limb asymmetry improves DEXA–CT agreement beyond absolute DEXA values. The influence of lower-limb rotation on DEXA measurements was assessed, and the study aimed to clarify how DEXA should be obtained and interpreted to more accurately reflect true muscle status. Methods: Fifty-two patients who completed CT and DEXA within 14 days were included. CT was used to obtain pure muscle volume and intramuscular adipose tissue (IMAT) using a standardized AI segmentation protocol, and corresponding DEXA thigh segmentation provided lean mass and fat percentage. Position-specific correlation analysis, regression, and Bland–Altman agreement testing were performed for 104 limbs. The same analyses were applied to inter-limb differences to isolate within-person asymmetry and reduce between-person variance. Results: DEXA lean mass correlated with CT pure muscle volume (r = 0.776, p < 0.001), and inter-limb asymmetry further improved alignment with CT (r = 0.857, p < 0.001). However, DEXA fat mass asymmetry demonstrated no association with CT IMAT asymmetry (r = −0.004, p = 0.979). When results were stratified by the recorded rotational groups, the highest correlation was observed in the neutral position (r = 0.900, p < 0.001). Bland–Altman analyses showed wide limits of agreement for all absolute measurements, whereas inter-limb asymmetry demonstrated markedly narrower limits of agreement, indicating superior numerical consistency. Conclusions: Absolute DEXA estimates showed limited agreement with CT and varied with limb position. Inter-limb asymmetry improved lean mass assessment, whereas fat mass and percentage did not correspond to CT-based IMAT. DEXA may therefore be used as a complementary tool for evaluating regional muscle quantity, but not for assessing muscle quality. Full article

Background/Objectives: Advanced 3D cell culture techniques enhance the physiological relevance of in vitro models, while supporting the 3Rs principles (Reduction, Refinement, and Replacement) of animal experimentation. In this context, 3D collagen-based systems mimic key extracellular matrix properties, enabling more accurate cellular organization and phenotype. However, changes in culture dimensionality can affect RT-qPCR reference gene stability, underscoring the need for careful validation when combining 2D and 3D systems. Methods: AML12 cells were cultured for 7 days under different 2D and collagen-based 3D conditions. The expression stability of nine candidate housekeeping genes was systematically evaluated using established algorithms (BestKeeper, NormFinder, geNorm, RefFinder, and ΔCt method), followed by inter-group statistical and correlation analyses of raw Ct values. Albumin gene expression was used as a target gene. Results: Although all candidate genes initially met acceptable variability thresholds, a stepwise, exclusion-based analysis revealed distinct performance differences. Hprt, Ppia, and Actb emerged as the most stable, showing no intra-group variability or interaction with Albumin expression. Nevertheless, Ywhaz and Rplp0, despite their high stability, were compromised by significant correlation with Albumin. Furthermore, Ywhaz showed significant downregulation under 3D culture conditions. B2M, Gapdh, 18S, and Hmbs exhibited increased variability, likely reflecting metabolic and microenvironmental heterogeneity associated with prolonged 2D cultivation of AML12 cells. Conclusions: Overall, this study highlights the importance of context-dependent, exclusion-based reference gene validation when comparing 2D and 3D models, and demonstrates a new approach for reliable gene expression normalization in complex in vitro culture systems. Full article

Background/Objectives: Therapeutic drug monitoring (TDM) of β-lactams (BL), BL/β-lactamase inhibitor (BLI) combinations (BL/BLIc), and of fosfomycin may play a key role in optimizing antimicrobial therapy and in preventing resistance development, especially when used by continuous infusion in critically ill or immunocompromised patients. Unfortunately, analytical methods for simultaneously quantifying multiple BL/BLIc in plasma are still lacking. Methods: The aim of this study was to develop and validate two rapid, sensitive, and accurate UPLC–qTOF–MS/MS methods for the simultaneous quantification of five novel β-lactam or β-lactam/β-lactamase inhibitor combinations (ceftolozane/tazobactam, ceftazidime/avibactam, meropenem/vaborbactam, cefiderocol, and ceftobiprole) along with fosfomycin. Methods: Human plasma samples were prepared by protein precipitation using methanol containing isotopically labeled internal standards. Chromatographic separation was achieved within 10–12 min using two Agilent Poroshell columns (EC-C18 and PFP) under positive and negative electrospray ionization modes. The method was validated according to the EMA guidelines by assessing selectivity, linearity, precision, accuracy, matrix effects, extraction recovery, and stability. Results: The methods exhibited excellent linearity (R² ≥ 0.998) across the calibration ranges for all of the analytes (1.56–500 µg/mL), with limits of quantification ranging from 1.56 to 15.62 µg/mL. Intra- and inter-day precision and accuracy were always within ±15%. Extraction recovery always exceeded 92%, and the matrix effects were effectively corrected through isotopic internal standards. No carry-over or isobaric interferences were observed. All the analytes were stable for up to five days at 4 °C, but the BL and BL/BLIc stability was affected by multiple freeze–thaw cycles. Conclusions: These UPLC-qTOF-MS/MS multi-analyte methods enabled a simultaneous, reliable quantification in plasma of five novel beta-lactams and of fosfomycin. Robustness, high throughput, and sensitivity make these multi-methods feasible for real-time TDM, supporting personalized antimicrobial dosing and improved therapeutic outcomes in patients with severe or multidrug-resistant infections. Full article

Accurate multivariate traffic flow forecasting is critical for intelligent transportation systems yet remains challenging due to the complex interplay of temporal dynamics and spatial interactions. While Transformer-based models have shown promise in capturing long-range temporal dependencies, most existing approaches compress multidimensional observations into flattened sequences—thereby neglecting explicit modeling of cross-dimensional (i.e., spatial or inter-variable) relationships, which are essential for capturing traffic propagation, network-wide congestion, and node-specific behaviors. To address this limitation, we propose TSAformer, a novel Transformer architecture that explicitly preserves and jointly models time and dimension as dual structural axes. TSAformer begins with a multimodal input embedding layer that encodes raw traffic values alongside temporal context (time-of-day and day-of-week) and node-specific positional features, ensuring rich semantic representation. The core of TSAformer is the Two-Stage Attention (TSA) module, which first models intra-dimensional temporal evolution via time-axis self-attention then captures inter-dimensional spatial interactions through a lightweight routing mechanism—avoiding quadratic complexity while enabling all-to-all cross-node communication. Built upon TSA, a hierarchical encoder–decoder (HED) structure further enhances forecasting by modeling traffic patterns across multiple temporal scales, from fine-grained fluctuations to macroscopic trends, and fusing predictions via cross-scale attention. Extensive experiments on three real-world traffic datasets—including urban road networks and highway systems—demonstrate that TSAformer consistently outperforms state-of-the-art baselines across short-term and long-term forecasting horizons. Notably, it achieves top-ranked performance in 36 out of 58 critical evaluation scenarios, including peak-hour and event-driven congestion prediction. By explicitly modeling both temporal and dimensional dependencies without structural compromise, TSAformer provides a scalable, interpretable, and high-performance solution for spatiotemporal traffic forecasting. Full article

Background: Ischemia–reperfusion injury is a major contributor to early graft dysfunction after kidney transplantation and is associated with endothelial damage, reflected by circulating soluble thrombomodulin (sTM). This exploratory study aimed to assess very early graft-level changes in renal vein sTM during reperfusion using a paired-kidney design, in which kidneys from the same donor were preserved using different strategies: static cold storage (SCS) and hypothermic machine perfusion (HMP). Methods: Renal vein blood samples were collected intraoperatively at 1 and 30 min after reperfusion. Plasma sTM concentrations were determined using ELISA. Early graft function was monitored during the first 7 days post-transplantation. Results: Cold ischemia time was longer in the HMP group than in the SCS group (20 ± 8 h vs. 13 ± 6 h, p < 0.05). At 1 min post-reperfusion, sTM levels were comparable between groups. In the HMP group, sTM decreased significantly between 1 and 30 min after reperfusion, whereas no change was observed in the SCS group. Between-group differences at either time point did not reach statistical significance. Early renal function parameters improved in both groups, with no significant inter-group differences. No cases of delayed graft function or graft thrombosis occurred. Conclusions: Kidney preservation strategy may modulate very early graft-level endothelial responses during reperfusion, reflected by renal vein sTM dynamics. Although a limited sample size may have reduced the ability to detect between-group differences, very early renal vein sTM measurements may provide insight into ischemia–reperfusion injury. Clinical relevance requires validation in larger studies. Full article