Search Results (9,489)

Gut microbiota regulate the intestinal expression of drug-metabolizing enzymes, transporters, and barrier properties that determine oral drug absorption and disposition. This study compares germ-free Swiss Webster mice to mice colonized with fecal microbiota from a single human donor, evaluating microbiota-driven differences in colonic gene expression and P-gp protein expression, as well as small intestinal mucosal permeability. Transcriptomic analysis of colonic tissue revealed microbiota-induced upregulation of genes encoding P-gp and other drug transporters, including MCT1 and OCTN2. Immunofluorescence also indicated greater P-gp expression and apical localization in colonized mice. Gene expression of drug-metabolizing enzymes was also higher in colonized mice, including phase I enzymes (carboxylesterase 2 paralogs), phase II enzymes (UDP-glucuronosyltransferases and glutathione S-transferases), and enzymes responsible for synthesizing their co-substrates, UDP-glucuronic acid and glutathione. Small intestinal mucosal explants demonstrated lower permeability to ¹⁴C-labeled polyethylene glycol 4000 in colonized mice compared to germ-free mice. In the colon, transcriptomic analysis identified microbiota-dependent changes in genes regulating paracellular tight junctions and actomyosin contractility. These results show that human-derived gut microbiota alter gene expression in the mouse colon, identifying candidate microbiota-responsive genes relevant to oral drug absorption and disposition. Full article

UAVs increasingly rely on accurate SLAM for aerial mapping and inspection in GPS-denied environments. 3D Gaussian Splatting (3DGS) has opened a new direction for UAV mapping by allowing SLAM systems to build dense, photorealistic, and renderable maps. Yet in 3DGS SLAM the map is optimized from the pose graph, so a false loop closure can deform both the UAV trajectory and the Gaussian map consumed by downstream UAV autonomy. Reliable loop admission is therefore relevant to safe GPS-denied operation because it protects the state and map estimates on which autonomous functions depend. The present work evaluated this upstream estimation-integrity problem; it did not measure closed-loop guidance, control, or navigation-safety outcomes. We address the loop-admission problem that arises after a place-recognition (PR) module proposes a candidate loop and relative-pose seed. GSSeq is a rendered-reference sequential verifier that uses the current Gaussian map as active evidence before inserting a loop factor. It renders RGB-D references with the PR seed, checks LiDAR/rendered-depth consistency and image/rendered-reference consistency over active support, and propagates the seed through a short query trajectory window. A loop is admitted only when this evidence remains geometrically supported and photometrically stable. On fixed LiDAR-PR candidate sets spanning MARS-LVIG, MUN-FRL, and independent NTU-VIRAL aerial sequences together with ground-mobility benchmarks, GSSeq provides a competitive precision-oriented operating point while suppressing false loop admissions. Thresholds calibrated only on NTU-VIRAL spms_01 combine rendered RGB agreement with LiDAR-submap geometry and are then frozen for spms_02. On this held-out sequence, GSSeq rejects all seven false-positive BTC factors while retaining one of three true-positive factors. The trajectory-to-map experiment reduced ATE RMSE from $2.609\mathrm{m}$ to $1.417\mathrm{m}$ and improved selected-view PSNR from $13.80\mathrm{dB}$ to $16.46\mathrm{dB}$. These results show that rendered verification can preserve an aligned, renderable UAV trajectory-map pair before unsupported loop factors reshape the SLAM map. Full article

This study presents a sensor-fused field investigation and simulation-based analysis of four horizontal and vertical traffic-calming devices—two raised speed tables, a speed hump, and a raised crosswalk—installed along a 5250-ft two-lane residential collector in Nashville, TN, USA. A dual-sensor architecture combining a Miovision Scout video-based vehicle counter and WAAS/EGNOS-augmented GPS probe-vehicle logging (5 m 3-D RMS horizontal accuracy, 1 Hz sampling) was used to reconstruct 30 quality-controlled free-flow vehicle trajectories and 12-h per-lane volume counts. A spatial kinematic transform (a = v·dv/dx) was applied to extract device-specific approach-deceleration and post-device recovery-acceleration rates, and a three-parameter log-logistic cumulative-distribution function was fitted to the field-observed desired-speed percentiles (root-mean-square error below 0.043 for both speed-table devices). The camera- and GPS-derived observations were used to calibrate and statistically validate a PTV VISSIM microsimulation replica of the corridor, achieving a mean-speed calibration error of 0.71% or better at every device, a GEH statistic below 1.5 at all four analysis turning movements, and independent travel-time validation errors of 5.7–12.1%, within the accepted 15% threshold. The validated model was then used to reconstruct device- and spacing-specific May–Keller macroscopic speed–density–flow relationships, calibrated against simulated capacities of 650–775 vehicles per hour per lane at 350-, 700-, and 1050-ft device spacing. Results show capacity reductions of 20–33% relative to free-flow conditions and yield kinematically derived maximum recommended spacings of 265–630 ft to maintain crossing speeds at or below 15 mph, depending on device geometry. The findings demonstrate a reproducible, low-cost sensor-fusion workflow for quantifying the safety–capacity trade-off of traffic-calming corridors and for informing the design of sensor-in-the-loop adaptive-calming infrastructure. Full article

With the increasing penetration of wind and photovoltaic generation, microgrids are playing an increasingly important role in promoting renewable energy accommodation, enhancing operational flexibility, and enabling low-carbon energy management. However, the strong uncertainty of renewable generation and load demand, together with the coupling effects of electricity, hydrogen, and carbon markets, poses significant challenges to the optimal planning and operation of microgrid energy storage systems. To address these issues, this paper proposes a bi-level optimal sizing framework for an electric–hydrogen hybrid energy storage system (EHH-ESS) in a microgrid under multi-market coupling. First, typical wind–solar–load scenarios are generated using a Wasserstein generative adversarial network with gradient penalty (WGAN-GP), so as to capture the stochastic characteristics and temporal correlations of renewable generation and load demand. Then, a multi-market coupling index (MCI), integrating electricity price, hydrogen price, and carbon price signals, is constructed to characterize time-varying economic and low-carbon operating incentives and to guide coordinated dispatch decisions. On this basis, a bi-level multi-objective optimization model is established. The upper level determines the optimal capacities of battery storage, electrolyzers, fuel cells, and hydrogen tanks, while the lower level performs hourly coordinated operation of the microgrid under multi-market conditions. The model considers annual equivalent total cost, renewable energy curtailment rate, and carbon emissions as objective functions, and is solved using the NSGA-III algorithm. Compared with the no-storage benchmark, the proposed scheme improves the annual operating economics and renewable-energy accommodation under the studied market conditions. The proposed method significantly reduces annual operating cost and improves renewable energy accommodation. However, under the current carbon price and grid emission factor settings, the optimal economic solution increases carbon emissions relative to the baseline, indicating a trade-off between economic arbitrage and low-carbon operation. Full article

Smartphone GNSS metadata remains an underexplored source for evaluating navigation-signal integrity in real-world conditions. We investigated GPS behavior recorded by a Samsung Galaxy A72 smartphone across two European flights (EXP03: Rome–Bucharest, n = 377; EXP10: Bucharest–Lisbon, n = 78) and 275 terrestrial reference photographs (Cabo da Roca, Portugal). A total of 730 photographs were analyzed using a seven-indicator taxonomy, conceptually inspired by Receiver Autonomous Integrity Monitoring (RAIM) principles, covering anti-spoofing, anti-sniffing, and anti-tampering checks. GPS capture rates reached 100% (Timestamp Camera) and 83.3% (native camera) up to 11,439 m WGS84, among the highest EXIF altitude profiles reported to date. Velocity spikes (1560–1875 km/h), one at cruise altitude and one during landing, were indistinguishable from GPS spoofing at the EXIF level, and their physical origin is undetermined. Phantom geolocation was absent in flight (0/442) versus 37.3% on the ground, consistent with GPS constellation visibility as the primary factor. In total, 88% (n = 920) of JPEG files lacked the standard EOI marker, generating false positives in integrity validators. Findings are device-specific, derived from non-independent observations, and require replication before generalizing to other GNSS receivers or latitudes. The framework offers a methodological basis for EXIF integrity analysis relevant to EU AI Act Article 10(3) data quality and UAV precision-agriculture georeferencing. Full article

Regular exercise mediates inter-tissue communication between skeletal muscle and the immune system through skeletal muscle-derived secretory factors, providing an important molecular basis for the beneficial effects of exercise on chronic inflammation, metabolic dysregulation, and impaired tissue repair. As key effector cells of the innate immune system, macrophages do not simply conform to a dichotomous classification of classically activated M1 macrophages and alternatively activated M2 macrophages; rather, their functional states constitute a dynamic spectrum shaped by exercise load, recovery time window, tissue microenvironment, and disease context. This review focuses on recent advances in exercise-induced skeletal muscle secretory factors involved in macrophage functional remodeling. Representative signals, including interleukin-6 (IL-6), irisin, meteorin-like protein (METRNL), fibroblast growth factor 21 (FGF21), oncostatin M (OSM), decorin, myostatin, chemokines, and extracellular vesicles, are systematically summarized in terms of their exercise responsiveness, evidence for skeletal muscle origin, and evidence supporting macrophage regulation. Based on these dimensions, an evidence-strength grading framework is further proposed. Moreover, this review integrates key signaling axes, including glycoprotein 130 (gp130)/Janus kinase (JAK)/signal transducer and activator of transcription (STAT), signal transducer and activator of transcription 6 (STAT6)/peroxisome proliferator-activated receptor gamma (PPARγ), AMP-activated protein kinase (AMPK)/nuclear factor erythroid 2-related factor 2 (Nrf2)/nuclear factor kappa B (NF-κB), transforming growth factor beta (TGF-β)/Smad, and chemokine receptor pathways, to explain how exercise-induced secretory networks participate in the dynamic regulation of the macrophage functional spectrum through immune cell recruitment, inflammatory clearance, immunometabolic reprogramming, matrix remodeling, and repair-niche formation. Current evidence indicates the translational potential of exercise-induced skeletal muscle secretory factors in skeletal muscle repair, metabolic inflammation, aging-related functional decline, and cancer rehabilitation. However, this field still faces several major challenges, including insufficient tracing of skeletal muscle-derived signals, limited direct causal validation, a lack of human tissue-level evidence, and unclear exercise dose–response relationships. Future studies should combine tissue-specific genetic interventions, receptor blockade, single-cell and spatial omics, metabolic flux analysis, and standardized human exercise interventions to further clarify the mechanistic basis and application boundaries of exercise-induced skeletal muscle–macrophage communication, thereby providing a theoretical foundation for precision exercise prescription and chronic inflammation intervention. Full article

Immune stress under intensive high density production conditions impairs broiler health and performance, highlighting the need for effective nutritional strategies. This study established an immune stress model by intraperitoneal lipopolysaccharide (LPS) injection to investigate the mechanism by which Glycyrrhiza polysaccharides (GPs) alleviate LPS-induced immune stress. A total of 240 AA broilers were randomly assigned to four groups: control (CON), GP, LPS, and GP + LPS, with six replicates per group and ten birds per replicate. During the stress phase (28 d), LPS challenge increased serum ACTH and CORT concentrations and altered several immune-related parameters; whereas, GP supplementation improved ileal morphology and reduced serum IL-1β, NF-κB, and TNF-α concentrations. Significant GP × LPS interactions were observed for IL-4, IgA, IgG, and iNOS. During the recovery phase (35 d), GP supplementation increased serum IgA and decreased iNOS, while significant GP × LPS interactions were detected for IL-1β, NF-κB, and sCD4. Notably, GP attenuated the LPS-associated increase in NF-κB. Integrated multi-omics analysis indicated coordinated regulation at transcriptional and proteomic levels. GP upregulated FOS, JUN, and CATH3 and enriched NF-κB and Wnt signaling at the transcript level, while increasing IRF1 and CATH3 and decreasing CTNNBIP1 at the protein level, primarily involving Wnt and MAPK pathways. Joint analysis identified CATH3 as a central regulatory target. Collectively, GP alleviates immune stress by restraining excessive inflammation and modulating Wnt/MAPK signaling, thereby promoting intestinal structural recovery. Full article

Background: The number of vaccines recommended for adults and older people has increased in recent years, and same-visit coadministration represents a potential strategy to improve vaccination coverage and timeliness. However, its implementation in primary care may depend on general practitioners’ (GPs) attitudes, vaccination experience, and organisational factors. This study investigated knowledge, attitudes, and practices (KAP) regarding vaccine coadministration among GPs in Apulia, Southern Italy. Methods: We conducted an anonymous cross-sectional online survey between January and June 2026 among practicing GPs and general practice trainees working in outpatient primary care settings in Apulia. The questionnaire assessed vaccination activity, intended coadministration practices, perceived effects on vaccine effectiveness and coverage, safety in very old adults or patients with multimorbidity, and perceived barriers to vaccination. Descriptive and bivariate analyses were performed, followed by multivariable logistic regression to identify factors independently associated with a positive perception of coadministration safety in very old or multimorbid patients. An additional sensitivity analysis excluded respondents reporting insufficient information to assess safety. Results: A total of 256 physicians completed the survey; 71.1% were aged ≥50 years. Most respondents had administered adult vaccines during the previous year, and 68.0% were classified as high vaccinators, having administered three or more different vaccine types. Although 68.0% believed that coadministration could increase vaccination coverage, only 13.3% reported willingness to administer three or more vaccines during a single visit. Overall, 50.0% considered coadministration very or fairly safe in very old or multimorbid patients, 24.2% considered it slightly or not at all safe, and 25.8% reported insufficient information to assess its safety. In the fully adjusted model, high vaccination activity was associated with higher odds of a positive safety perception (adjusted odds ratio [aOR] 1.93, 95% confidence interval [CI] 1.01–3.70), whereas difficulties using vaccination IT platforms were associated with lower odds (aOR 0.48, 95% CI 0.26–0.86). Age ≥ 50 years was not independently associated with the outcome after adjustment (aOR 0.66, 95% CI 0.35–1.26). Conclusions: GPs in Apulia showed generally favorable attitudes toward vaccine coadministration, although substantial uncertainty remained regarding its use in very old and multimorbid patients. Confidence in coadministration was primarily associated with greater vaccination activity and fewer difficulties with vaccination IT platforms, whereas age-related differences observed in bivariate analyses were attenuated after multivariable adjustment. Educational, organisational, and digital-support interventions may facilitate broader implementation of same-visit adult vaccination in primary care. Full article

High-precision long-baseline coordinate transfer is essential for maintaining spatial reference frames, and the modernized multi-frequency signals of BDS-3 provide new opportunities for this task. However, existing long-baseline network solutions still rely mainly on legacy frequency combinations, and quantitative evidence for pure new-frequency BDS-3 combinations in large-scale coordinate transfer remains limited. This study evaluates the applicability of BDS-3 high- and low-frequency signal combinations for long-baseline position datum transfer and investigates frequency-combination selection. Seven continuous stations were used to form 21 long baselines. Five dual-frequency schemes were tested, including four BDS-3 combinations, namely B1I/B3I, B1I/B2a, B1C/B2a, and B1C/B3I, and one GPS reference combination, L1/L5. Double-differenced ionosphere-free baseline processing and three-dimensional constrained network adjustment were applied. Performance was assessed using carrier-phase precision, normalized root mean square (NRMS), baseline vector quality, and point-transfer differences. The results show that the BDS-3 B1C/B2a new-frequency combination achieved the best overall consistency among the BDS-3 schemes, with an average high-frequency carrier-phase precision of 6.3 mm, a mean NRMS of 0.23, millimeter-level baseline vector formal-error RMS, and a 19.7 mm point difference at the unknown station DCMS. Given that the evaluation is based on seven consecutive days of observations, the long-term applicability of the proposed strategy requires further validation. Full article

Atmospheric water vapor is a major driver of Earth’s climate, yet despite its vital role in driving extreme weather and informing Numerical Weather Prediction (NWP) models, precise quantification of Precipitable Water Vapor (PWV) remains a challenge due to its high spatial and temporal variability. To provide an upgraded evaluation reflecting the most recent data and next-generation instrumentation, this study evaluates the accuracy, relative to radiosonde measurements, in calculating PWV values across six different instruments: Microwave Radiometer (MWR), NOAA-21, TROPOMI, Pandora spectrometer, AERONET sun-photometer, and GNSS/GPS against the bias-corrected Vaisala RS-92 and RS-41 radiosondes over Beltsville, Maryland, utilizing an updated 2024–2025 database. As a certified GRUAN site, HUBC adheres to strict international observation standards designed specifically to provide reference-quality data and comprehensive corrections for systematic errors. This rigorous framework justifies their application as the definitive ‘referent truth’ benchmark for remote sensing validation. RMSE and bias were the primary metrics used to assess relative accuracy. GPS measurements provided the highest level of relative accuracy, yielding the lowest RMSE (1.50 mm) and a near-unity linear fit (y = 0.98x). NOAA-21 and TROPOMI exhibit higher random noise when compared to ground-based instrumentation, yet both obtain high relative accuracy retrievals with negligible biases. AERONET and Pandora also showed strong performance with low RMSEs and R² values of 0.986 and 0.988, respectively, while slightly underestimating PWV. In contrast, the Radiometer performed with the lowest relative accuracy, characterized by the highest RMSE (6.19 mm) and a significant negative bias (−5.55 mm). Although all instruments maintained high correlation coefficients (R² ≥ 0.904), these results indicate that satellite and ground-based remote sensing provide reliable PWV retrievals, while GPS presents the most robust benchmark for high-accuracy PWV retrievals relative to radiosonde measurements. The findings also underscore the need for instrument-specific calibration constants to better align remote sensing retrievals with in situ observations. Full article

Global Positioning System (GPS) positioning accuracy is strongly affected by inaccurate noise modeling and non-Gaussian pseudorange measurement errors, including heavy-tailed disturbances and abnormal outliers caused by multipath propagation and signal degradation. Conventional extended Kalman filters (EKFs) generally assume Gaussian measurement noise with fixed covariance matrices, which limits their robustness under degraded measurement conditions. This study proposes a Student-t robust quantum-behaved particle swarm optimization-based extended Kalman filter (ST-QPSO-EKF) for adaptive GPS state estimation. The proposed framework combines quantum-behaved particle swarm optimization (QPSO) with a Student-t-based robust measurement update, where the process-noise scaling factor, measurement-noise scaling factor, and Student-t degrees-of-freedom parameter are jointly optimized. The optimized parameters are obtained through an offline calibration stage and subsequently applied in the recursive GPS filtering process. A nonlinear GPS navigation simulation was conducted using Gaussian, Student-t heavy-tailed, and outlier-contaminated pseudorange measurement scenarios. The proposed method was compared with conventional EKF, QPSO-EKF, and Student-t EKF using 20 independent Monte Carlo realizations. The results demonstrate that QPSO-EKF provides improved accuracy under nominal Gaussian conditions, whereas ST-QPSO-EKF achieves superior performance under non-Gaussian measurement environments. Under Student-t heavy-tailed noise, ST-QPSO-EKF reduced the position RMSE to 3.814 m, while under outlier-contaminated noise it achieved a position RMSE of 3.952 m, outperforming the other compared methods. In addition, the proposed method maintained comparable online computational cost because the QPSO optimization was performed offline. The results indicate that jointly optimizing covariance parameters and Student-t robustness provides an effective strategy for improving GPS positioning reliability under complex pseudorange measurement conditions. Full article

Background: The sensitivity of ultrasound plus alpha-fetoprotein (AFP) for early-stage hepatocellular carcinoma (HCC) detection remains suboptimal, prompting interest in blood-based biomarkers as an alternative strategy. The ASAP [age, sex, AFP, PIVKA-II] score has promising performance, although validation in contemporary Western populations is needed. Methods: We conducted a case–control study in which the cases were patients with HCC and the controls had cirrhosis without HCC. AFP, PIVKA-II, LG2m, and GP73 were measured using the Abbott Alinity platform, and ASAP scores were calculated. Sensitivity and specificity for early-stage HCC (BCLC stage 0/A) were compared between ASAP and ultrasound plus AFP using McNemar’s chi-square test. Results: Among 294 patients (median age of 61 years, 67.7% men), 50.7% had HCC (69.1% BCLC 0/A), and 49.3% had cirrhosis. The performance of individual biomarkers for early-stage HCC was moderate to poor (AUROC: AFP 0.71, PIVKA-II 0.73, LG2m 0.51, and GP73 0.53). ASAP, at a cutoff of ≥0.526, demonstrated a sensitivity of 88.3% for early-stage HCC, with specificity of 54.5%. Sensitivity was higher in men and viremic HCV, whereas specificity was higher in younger individuals, women, and Child–Pugh A cirrhosis. In subgroup analysis (n = 178), ASAP had comparable sensitivity to ultrasound plus AFP (85.5% vs. 90.3%; p = 0.51) but lower specificity (53.4% vs. 93.1%; p < 0.001). Using the Youden-optimized cutoff (≥0.804) improved specificity to 83.4% while maintaining a sensitivity of 68.0% for early-stage HCC. Conclusions: ASAP demonstrated high sensitivity for early-stage HCC detection but low specificity. These findings suggest a need for optimized cutoffs prior to implementation in clinical practice. Full article

Rising recognition of attention deficit hyperactivity disorder (ADHD) in adults and children is reshaping how Australian health systems organise diagnosis, prescribing and long-term management. This has coincided with sharp increases in ADHD medicine dispensing, high private assessment costs and prolonged waiting times for psychiatrists and paediatricians. Australian states and territories have commenced reforms that expand the role of general practitioners (GPs) in ADHD diagnosis, prescribing and long-term management. This commentary assesses whether these reforms can expand timely and equitable access while maintaining diagnostic accuracy, medication safety and specialist referral. It uses the New South Wales (NSW) model as a detailed exemplar because it has developed a staged pathway: trained continuation prescribers support previously diagnosed patients who are stable on psychostimulant treatment, while endorsed prescribers receive further accredited training or recognition of prior learning to assess, diagnose, initiate and adjust psychostimulant treatment. The commentary distinguishes professional specialty status from ADHD-specific competency: specialist registration in general practice establishes the professional status of qualified Australian GPs, whereas safe extension of ADHD diagnosis and psychostimulant prescribing requires condition-specific education, competency assessment, prescribing authority, monitoring and defined referral pathways. It reviews Australian reforms, explains the NSW training and governance pathway, compares overseas approaches, and identifies safeguards needed to avoid diagnostic compression, overdiagnosis, stimulant diversion and widening inequity. The central argument is that GP involvement should be framed as trained, governed primary-care capacity. If adequately funded, audited and linked to specialist escalation pathways, the model may reduce access barriers while preserving diagnostic rigour. Full article

Background/Objectives: Actinic keratosis (AK) is the key precursor of invasive cutaneous squamous cell carcinoma (cSCC). Rising incidence, ageing populations, and limited dermatologists’ availability, particularly in rural and underserved regions, underscore the need for more inclusive care pathways. As in other common diseases such as diabetes or hypertension, general practitioners (GPs) could play a pivotal role in improving access, early recognition, and management of AK, provided that systemic barriers are addressed. Methods: This article synthesises current evidence and expert insights from a European multi-country advisory process, focusing on Italy, France, Germany, Spain, Portugal, the Netherlands, and Greece. The advisory board comprised dermatologists selected based on their clinical expertise and national representativeness, and consensus was reached through structured discussion and iterative review of background materials. Results/Conclusions: The study outlines unmet needs, barriers, and enablers for GPs’ involvement and proposes a structured strategy supported by consensus recommendations. It offers a pragmatic model for improving AK care through stronger collaboration between primary care and dermatology. Greater GPs’ involvement may support earlier recognition, better triage, improved access to care, and more efficient use of specialist services, while ensuring that complex or high-risk lesions remain under dermatologists’ oversight. This may help optimise AK care pathways across Europe. Full article

Dementia is a leading cause of disability and death worldwide, yet diagnosis in primary care remains substantially lower than expected, delaying access to treatment, support and future care planning. The Facing Dementia Together Practice Change Program was developed as a co-designed, multicomponent intervention to improve dementia diagnosis in Australian general practice. A mixed-methods process evaluation used the RE-AIM framework with the addition of Appropriateness. The intervention included Primary Health Network (PHN) engagement, GP education, clinical resources, audit and benchmarking reports, specialist support, and a dementia risk-alert tool. Data were collected through surveys, stakeholder interviews, website analytics and program documentation. Clinicians who participated reported increased confidence and changes in dementia-related clinical behaviours, while education, resources and benchmarking were perceived as valuable. However, overall reach was limited by competing clinical priorities, workforce pressures, lack of financial incentives, and PHN implementation challenges. The dementia risk-alert tool was feasible but achieved limited uptake because of software compatibility, usability concerns and incomplete electronic medical record data. Although the program was acceptable to participating clinicians, limited reach constrained its potential impact. These findings highlight organizational, workforce, digital infrastructure and policy factors that influenced implementation of multicomponent interventions in routine primary care. Full article