Sci Rep. 2026 Jun 2;16(1):16980. doi: 10.1038/s41598-026-56238-6.
NO ABSTRACT
PMID:42230952 | DOI:10.1038/s41598-026-56238-6
Sci Rep. 2026 Jun 2. doi: 10.1038/s41598-026-55998-5. Online ahead of print.
ABSTRACT
This study aimed to assess diagnostic values of kinetic parameters in ultrafast dynamic contrast magnetic resonance imaging. The diagnostic performance of ultrafast kinetic parameters (time to enhancement [TTE], maximum slope [MS], time to peak, peak enhancement [PE], and wash-in slope [WIS]), and their correlations with the immunohistopathological findings of breast cancer were evaluated for 101 histologically proven breast lesions. We found that the areas under the curves of five ultrafast kinetic parameters in masses (0.69-0.81) and for MS, PE, and WIS in non-mass enhancement (NME) (0.91-0.94) were comparable to those of Breast Imaging Reporting and Data System (BI-RADS) categorizations (mass: 0.85, NME: 0.83) without statistically significant differences. Values of ultrafast kinetic parameters differed significantly according to invasiveness (invasive vs. non-invasive: TTE, p = 0.029; MS, p = 0.040; PE, p = 0.032; and WIS, p = 0.009), immunohistopathological findings (high vs. low Ki-67: TTE, p = 0.020; MS, p = 0.004; PE, p = 0.003; and WIS, p < 0.001), hormone receptor (negative vs. positive: MS, p = 0.033; and WIS, p = 0.042), and triple-negative status (triple-negative vs. non-triple-negative: MS, p = 0.028; and WIS, p = 0.011) in breast cancer. In conclusion, ultrafast kinetic parameters demonstrate diagnostic performance comparable to that of BI-RADS categories for both mass and NME and may be associated with the immunohistopathological findings of breast cancer.
PMID:42230942 | DOI:10.1038/s41598-026-55998-5
Sci Rep. 2026 Jun 2. doi: 10.1038/s41598-026-55651-1. Online ahead of print.
ABSTRACT
Financial fraud detection requires screening massive transaction networks where evolving topologies, extreme label sparsity, and asymmetric misclassification costs make traditional classification paradigms ineffective. We propose ST-CGNN, a spatio-temporal contrastive graph neural network that frames operational screening as a multi-task learning problem in which a shared encoder is supervised by a contrastive regularizer and an evidential triage head. Concretely, ST-CGNN combines a continuous-time heterogeneous encoder with a hard-negative contrastive regularizer and an evidential output head, so that structural representations and uncertainty-aware prioritization are trained from a common backbone with summed losses rather than as a sequential, modular pipeline. Evaluated under strict chronological constraints on large-scale public and controlled benchmarks, ST-CGNN consistently outperforms state-of-the-art GNNs and post-hoc calibration methods. Specifically, on the DGraph-Fin benchmark, the proposed evidential triage score improves Precision@100 to 0.884 and achieves a calibrated ECE of 0.034. On Elliptic, the difference between ST-CGNN and the best competitor (MTP-GAT) lies within seed variance and is not statistically distinguishable; gains concentrate on benchmarks where heterogeneity and bursty timing dominate. Paired bootstrap tests and selective-prediction analysis confirm that this shared-encoder design significantly enhances the reliability of fixed-budget analyst reviews, providing a robust foundation for high-stakes risk management in dynamic transaction environments.
PMID:42230938 | DOI:10.1038/s41598-026-55651-1
Sci Rep. 2026 Jun 2. doi: 10.1038/s41598-026-55468-y. Online ahead of print.
ABSTRACT
During the last decades, the production of bioplastics has emerged as a promising alternative to mitigate the environmental impact generated by the accumulation of unmanaged plastic waste on natural ecosystems. Biodegradable bioplastics are expected to be less persistent than conventional oil-based polymers; however, the conditions under which biodegradation tests are conducted may lead to discrepancies between laboratory results and the real environmental conditions. For freshwater ecosystems, previous studies have highlighted important gaps, such as the variability caused by the inoculum. To assess if the use of commercial lyophilized bacteria as inoculum reduces the test variability, the biodegradation of three microplastics (MPs) with distinct polymer origins, poly-3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV), polylactic acid (PLA), and polypropylene (PP), was studied in closed respirometers. Subsequently, following the reduction of the variability, the impact of the incubation temperature was evaluated at 10, 20 and 30 °C. Finally, the potential differences in the biodegradation process caused using different inocula were assessed with three different inoculum sources: the commercial freeze-dried bacteria, an activated sludge and digestate from biowaste. The results showed that freeze-dried bacteria could be used as an alternative inoculum to reduce inter-laboratory differences in the standardized test. Although no statistical differences were observed for PHB under identical incubation conditions with the freeze-dried inoculum, the results showed that the biodegradation of PHBV is highly influenced by temperature with higher values obtained at 35 °C than at 20 °C and 10 °C. Finally, the diversity and relative abundance of the inocula may significantly influence biodegradation outcomes, highlighting the inoculum source as a critical factor contributing to variability in this type of assay.
PMID:42230919 | DOI:10.1038/s41598-026-55468-y
Sci Rep. 2026 Jun 2. doi: 10.1038/s41598-026-54091-1. Online ahead of print.
ABSTRACT
This study compared the effectiveness of Automated Fiber Quantification (AFQ) and Tract-Based Spatial Statistics (TBSS) in detecting white matter (WM) changes in patients with moderate-to-severe obstructive sleep apnea (OSA), aiming to identify the more suitable method for investigating WM alterations of OSA patients. It also explored the potential neuropathological links between WM changes and anxiety/depression in OSA. Thirty-three untreated patients with moderate-severe OSA and 28 good sleepers without sleep disorders underwent 3.0T MRI scans. TBSS was used to construct WM skeletons and compare diffusion tensor imaging (DTI) metrics between groups. AFQ was then applied to extract 20 major fiber tracts from each subject, with each tract divided into 100 nodes to precisely localize affected areas. TBSS revealed no significant group differences after correction. In contrast, AFQ identified significant changes: decreased fractional anisotropy at nodes 77-78 of the forceps major (positively correlated with anxiety scores); increased mean diffusivity at nodes 23-24 of the right thalamic radiation; and increased axial diffusivity at nodes 54-57 of the right inferior fronto-occipital fasciculus (negatively correlated with anxiety and depression scores), and nodes 66-68 of the right superior longitudinal fasciculus. AFQ is more sensitive than TBSS in detecting focal WM changes in OSA, allowing precise localization of affected fiber nodes. These WM alterations, particularly in the corpus callosum and right inferior fronto-occipital fasciculus, are linked to anxiety and depression, offering insights into the neuropathological mechanisms of anxiety and depression in OSA.
PMID:42230913 | DOI:10.1038/s41598-026-54091-1
Sci Rep. 2026 Jun 1. doi: 10.1038/s41598-026-55442-8. Online ahead of print.
ABSTRACT
In this paper, a distributed event-based control architecture is proposed to improve the security and environmental performance of cyber-physical smart grids. The strategy concurrently responds to coordinated cyberattacks, such as false data injection (FDI) and denial-of-service (DoS), and incorporates carbon emission trading (CET) into the optimization of the energy dispatch. It constructs a novel event-based resilient consensus algorithm (ERCA), which incorporates attack detection and recovery schemes into a distributed decision-making framework. The algorithm employs a trust-node-based correction strategy and reliable acknowledgment signaling to maintain reliable state estimation and coordination under communication interruptions and data falsification. By incorporating carbon-pricing directly into the local cost functions, the framework enables generation units and responsive loads to achieve economically efficient and low-carbon operation without centralized supervision. Convergence of the proposed method is rigorously established under simultaneous FDI and DoS attacks. Simulation studies on an IEEE 41-bus system confirm that the framework maintains power balance, stabilizes electricity prices, ensures consistency in reported emissions, and reduces overall carbon output, even in the presence of stealthy and disruptive cyber intrusions.
PMID:42230878 | DOI:10.1038/s41598-026-55442-8
Sci Rep. 2026 Jun 2. doi: 10.1038/s41598-026-54798-1. Online ahead of print.
ABSTRACT
To date, little is known regarding the treatment effects of different timed-dosing antihypertensive medications among hypertensive patients with albuminuria. We aimed to investigate whether morning or evening dosing of antihypertensive medication differentially affects early changes in albuminuria.We conducted an open-label, single-center, assessor-masked, parallel-group, pilot randomized controlled trial among adult hypertensive patients with albuminuria (urinary albumin‒creatinine ratio [UACR] ≥ 30 mg/g) receiving at least one antihypertensive medication. The participants were assigned (1:1) to receive antihypertensive medications either in the morning (6:00-10:00 AM) or in the evening (6:00-10:00 PM), with a treatment follow-up at 3 months. The primary outcome was the change in the log UACR. The secondary outcomes were changes in blood pressure and kidney function. Post hoc outcomes included clinically meaningful control of outcomes.Among the 60 participants enrolled (mean age, 65.6 years; proportion of females, 51.7%; median UACR, 116.1 mg/g), 58 patients completed the trial. The absolute changes in log UACR over 3 months were – 0.21 (95% CI, -0.40 to -0.03; n = 31) for morning-dosing and – 0.22 (95% CI, -0.46 to 0.01; n = 27) for evening-dosing, with an adjusted difference of -0.01 (95% CI, -0.32 to 0.30; P = 0.955) between the groups. No statistically significant difference was observed for secondary and post hoc outcomes. No safety profile concerns were identified. Among hypertensive patients with albuminuria, chronotherapy, whether administered in the morning or evening, did not affect early treatment outcomes in terms of the UACR, blood pressure, or kidney function. Trial registration: Thai Clinical Trials Registry (TCTR); TCTR20240930002; Registration date: 30/09/2024; retrospectively registered.
PMID:42230872 | DOI:10.1038/s41598-026-54798-1
Sci Rep. 2026 Jun 2;16(1):16986. doi: 10.1038/s41598-026-54633-7.
ABSTRACT
Wound healing is a complicated process, so it’s critical to identify efficient ways to hasten recovery. Platelet-rich plasma (PRP) and zinc oxide nanoparticles (ZnO NPs) have demonstrated potential in improving cutaneous wound healing in a variety of species. But little is known about their combined effects, especially in dogs. Therefore, this study determined how topical infiltration of PRP and ZnO NPs ointment, both separately and in combination, affect the healing of dogs’ cutaneous wounds. Thirty-six full skin wounds were induced in the chest of six adult mongrel dogs. These wounds were randomly divided into six equal groups (6 wounds each) according to treatment protocol: group 1 served as a control and the wounds were dressed daily with normal saline only, group 2: the wounds were dressed daily with lanolin only, group 3: the wounds were infiltrated once with PRP, group 4: the wounds were treated with PRP single infiltration combined with lanolin ointment daily dressing, group 5: the wounds were dressed daily with ZnO NPs ointment, and group 6: the wounds were infiltrated once with PRP and daily dressed with ZnO NPs ointment. Wound healing progress was monitored; epithelialization, wound contraction, and overall healing were assessed. Total antioxidant capacity (TAC), malondialdehyde (MDA) and the concentration of platelets derived growth factor beta (PDGFβ) were measured on wound fluid. Gene expression of matrix extracellular phosphoglycoprotien (MEPE), transforming growth factor beta (TGF-β) and tumor necrosis factor alpha (TNF-α) were also evaluated on skin biopsies at day 0, 5, 10 and 20. Histopathology, immunohistochemistry and staining of collagen bundles were performed on skin biopsies at 5, 10 and 20 days of wound induction. All data were statistically analyzed. There was a significant interaction between the group and time across all parameters (P < 0.001). The PRP-ZnO NPs group consistently has a great effect on wound size reduction, contraction, healing, epithelialization, and antioxidant activity, along with higher MEPE and PDGFβ expression and arranged parallel collagen bundles, indicating enhanced regeneration. While PRP alone showed the strongest TGF-β increase and anti-inflammatory effect (lowest TNF-α). PRP-ZnO NPs provided the best overall balance between regeneration and inflammation control. All treatments surpassed the control and lanolin groups, which showed minimal improvement. PRP-Lanolin and ZnO NPs offered moderate benefits but were less effective than PRP-ZnO NPs or PRP. ZnO NPs and PRP work together to improve skin wound healing in dogs; PRP promotes regenerative signaling, while ZnO NPs reduce oxidative stress and microbial load.
PMID:42230869 | DOI:10.1038/s41598-026-54633-7
Sci Rep. 2026 Jun 2. doi: 10.1038/s41598-026-53540-1. Online ahead of print.
ABSTRACT
While full ledger access is theoretically possible on public blockchains, in reality it is often not possible. Things that can be seen are limited by storage limitations, client design, indexing services, and off-chain execution pathways. This means that entire ledger objects are rarely used for empirical blockchain analysis; instead, observable projections are typically used. In this research, the observability of blockchain is recast as an inferential problem with incomplete observation. Studying identifiability, information loss, and irreducible uncertainty under coarsened access, the framework defines a full ledger, an observable ledger, and an observability mechanism. Three distinct visibility regimes, independent Bernoulli, clustered, and activity-dependent, are assessed in the simulation study. Reduced visibility raises uncertainty inflation, root mean squared error, variance, and mean squared error across all three regimes. The most severe deterioration happens when the condition of the underlying ledger determines visibility. This empirical study employs Google BigQuery’s publicly indexed Ethereum block data spanning blocks 18,000,000 to 18,001,000. Over the chosen Ethereum period, descriptive summaries reveal a large amount of fluctuation in gas utilised, transaction count, and basic charge per gas at the block level. Experiments with controlled missingness on the observed slice reveal that RMSE and trend estimate bias grow with increasing missingness, and that the degree of distortion is significantly affected by whether the incompleteness is MCAR-like, MAR-like, or MNAR-like. This research proves that partial observability isn’t just a secondary data issue; it can significantly affect inference on Ethereum block-level summaries.
PMID:42230851 | DOI:10.1038/s41598-026-53540-1
Sci Rep. 2026 Jun 3. doi: 10.1038/s41598-026-50941-0. Online ahead of print.
ABSTRACT
Real-world evidence on 12-month outcomes of guselkumab (GUS) in psoriatic arthritis (PsA) remains limited. This multicenter observational study aimed to identify predictors of 12-month DAPSA remission (DAPSA < 4) in patients with PsA treated with GUS. Secondary objectives were to assess remission rates and changes in disease activity at 6 and 12 months. We screened all patients with PsA initiating GUS across 26 Italian rheumatology centers. Data collected included demographics, disease activity measured by DAPSA, and psoriasis (PsO) extent classified as 0%, < 10%, 10-20%, or > 20% body surface area. A multivariable logistic regression model restricted to patients with an evaluable 6-month assessment was used to identify predictors of 12-month DAPSA remission. Covariates included age, sex, smoking status, body mass index, disease duration, number of prior advanced therapies, axial involvement, and 6-month articular and/or cutaneous response. Articular response was defined as DAPSA remission (DAPSA < 4), and cutaneous response as improvement by at least one PsO body surface area severity category. A two-sided p value < 0.05 was considered statistically significant. Of 278 initiators, 199 were evaluable at 6 months. At month 6, 18 patients had a combined articular and cutaneous response, 9 had an articular-only response, 74 had a cutaneous-only response, and 98 had no response. In intention-to-treat analyses, DAPSA remission was achieved by 12% at 6 months and 20% at 12 months; corresponding per-protocol rates were 16% and 30%. Median DAPSA decreased from 27.0 at baseline to 11.9 at 6 months and 8.6 at 12 months. In multivariable analysis, combined response (OR 64.6, 95% CI 5.7-731.2), joint-only response (OR 16.9, 95% CI 4.4-65.2), and skin-only response (OR 2.5, 95% CI 1.04-6.2) were associated with 12-month DAPSA remission. In routine practice, 6-month response status stratified the probability of 12-month DAPSA remission. Early articular remission and combined articular-cutaneous response showed the strongest associations, whereas skin-only improvement was a modest but statistically significant predictor and should not be interpreted as a strong determinant of later articular remission.
PMID:42230809 | DOI:10.1038/s41598-026-50941-0