Search Results (20,383)

Background/Objectives: Imidazole dipeptides (IDPs), carnosine and anserine, are endogenous antioxidants. The metabolism and functions of IDPs have mainly been investigated in rodents. However, the blood of primates, such as humans, contains carnosinase (CN1), which hydrolyzes IDPs. In non-primates, CN1 is absent, allowing IDPs to be distributed throughout tissues. There are concerns about whether the results of animal experiments can be directly applied to humans. Therefore, we aimed to investigate the blood change in the concentration and tissue distribution of IDPs following their oral administration to golden hamsters, the only non-primates known to possess CN1. Methods: Plasma CN1 activity was compared between hamsters and humans. Hamsters were administered IDPs (an anserine/carnosine mixture) purified from chicken meat at a dose of 1000 mg/kg. Blood samples were collected at time points up to 6 h after administration. Tissue samples were collected at 6 h after administration to measure the concentrations of IDPs and related substances. Additionally, IDP levels in human and mice tissues from previous studies were compared with that of hamster tissues in this study. Results: Hamster plasma CN1 activity was more than 10 times higher than that in humans. Although IDPs were not detected in IDP-treated hamster plasma, constituent amino acids of IDPs increased up to 1–2 h and Nπ-methyl-histidine (m-His) remained at high levels up to 6 h after administration. IDP levels in control tissues (vehicle) were similar to those in human tissues. In the IDP group, tissue IDPs were higher than those in the vehicle and m-His increased in all tissues. Conclusions: This study indicated that m-His levels increase in hamster tissues following a single oral administration of IDPs and strongly suggest that hamsters should be used in functional studies of IDPs in humans, focusing on the functionality of m-His. Full article

Two novel cocrystals of zwitterionic trimethylglycine (TMG) with 2,6-dichlorophenol [TMG•2,6-dichlorophenol] (1:1) and 2,6-dibromophenol [TMG•2,6-dibromophenol] (1:2) are synthesized and structurally characterized using single crystal X-ray diffraction. To estimate the energy of various intermolecular interactions, periodic DFT calculations were performed followed by Bader analysis of the crystalline electron density. TMG molecules form dimers in [TMG•2,6-dichlorophenol] (1:1). Its supramolecular structure is governed by the primary charge-assisted H-bonds (~60 kJ/mol) and supported by C–H∙∙∙O contacts (~12 kJ/mol). Cl/Br substitution introduces a more potent halogen-bonding donor. The Br∙∙∙O⁻ interaction (~10 kJ/mol) is strong enough to reorganize the packing into a catemeric motif. As a result, TMG molecules form infinite chains in [TMG•2,6-dibromophenol] (1:2). This illustrates that “fine tuning” is not merely about changing distances, but about shifting the entire energy hierarchy of the crystal. Two-dimensional fingerprint diagrams (2D diagrams) obtained from the Hirshfeld surface and Bader’s analysis of the crystalline electron density give significantly different values of the contributions of the H∙∙∙H contacts, 28% vs. 5% respectively. The main reason for this discrepancy is the large number of relatively short intermolecular H∙∙∙H contacts without a critical bond point in trimethylglycine cocrystals. Full article

Background/Objectives: Acute kidney injury (AKI) remains a significant complication following cardiac surgery, associated with increased morbidity and mortality. The early detection of AKI is limited by the cost, availability, and unclear clinical utility of the current biomarkers. This study aimed to evaluate the red cell distribution width (RDW) on ICU admission as a predictor of postoperative AKI. Methods: We conducted a retrospective analysis of adult patients undergoing isolated coronary artery bypass grafting (CABG) or combined CABG and aortic valve surgery at a tertiary cardiac surgery centre (University Hospital of Siena, Italy) between January 2015 and December 2020. AKI was defined according to the KDIGO criteria. The RDW was measured preoperatively (T0), at ICU admission (T1), and at 24 (T2) and 48 h (T3) postoperatively. Temporal RDW changes (ΔRDW) were also calculated. Multivariate logistic regression identified independent predictors of AKI, and receiver operating characteristic (ROC) analysis evaluated the predictive accuracy. Results: A total of 456 patients were included, with an overall AKI incidence of 31%. Patients developing AKI exhibited significantly higher RDW at all measured time points, especially at ICU admission. Multivariate analysis identified age, RDW (OR 1.19, 95% CI: 1.03–1.37, p = 0.016) and serum creatinine at ICU admission, and elevated lactate at T2 as independent AKI predictors. In subgroup analyses, RDW at ICU admission remained significantly associated with AKI in patients who were not transfused, but not in patients who were. Conclusions: In this study, a high RDW at ICU admission represented an early postoperative marker independently associated with AKI after cardiac surgery, particularly in patients who did not receive transfusion. Full article

Spring vegetation phenology is highly sensitive to climate change; however, climate drivers and their threshold responses at the urban scale remain insufficiently and systematically quantified. Focusing on 31 provincial capitals and municipalities in mainland China, this study integrated MODIS MCD12Q2-derived start-of-season (SOS) for spring green-up and TerraClimate climate data (2001–2023) at a 500 m grid resolution. SOS trends were characterized using the Mann–Kendall test and the Theil–Sen slope estimator. Building on these trend metrics, we developed an XGBoost–SHAP framework using the interannual rate of temperature change (tem_slope) and the interannual rate of precipitation change (pre_slope) as input features, to quantify the nonlinear contributions of climate-change rates to SOS trends and to identify key thresholds. Results indicate that the multi-year mean SOS across China’s provincial capitals and municipalities is primarily distributed between approximately DOY 74 and 138, exhibiting a clear spatial pattern of earlier green-up in the south, later green-up in the north, and delayed green-up on plateaus, with pronounced shifts in distribution centers and dispersion among climatic zones and cities. At the city level, the mean SOS trend shows an overall advancing rate of 0.81 d·year⁻¹ (i.e., the average of city-mean Sen slopes across the 31 cities). Pixel-level trend analyses show that advancing and delaying trends commonly coexist within most cities; among pixels with significant or marginally significant SOS trends identified by the Mann–Kendall test (MK p < 0.10) across all cities, advancing and delaying SOS pixels account for 75.02% and 24.98%, respectively. At the city scale, the proportions of advancing versus delaying pixels vary markedly among cities, forming directional structures characterized by advance-dominant, delay-dominant, or bidirectional coexistence patterns. SHAP dependence relationships further reveal that the effects of tem_slope and pre_slope on SOS trends are generally nonlinear and piecewise, with substantial heterogeneity across climate zones and cities. The identified tipping points and associated sensitive ranges collectively delineate spatially differentiated climate-sensitive intervals, which define the nonlinear response boundaries of spring SOS to sustained warming and precipitation changes. This study provides quantitative evidence for regional differences in urban spring phenological responses to climate change across major Chinese cities and offers a methodological reference for identifying actionable climate thresholds in urban greening design and climate-adaptive management. Full article

Quantifying river surface flow velocity is essential for hydrodynamic modelling, flood forecasting, and water resource management. Traditional in situ methods provide accurate point measurements but are costly and limited in spatial coverage. Unmanned aerial vehicles (UAVs) offer a flexible, non-contact alternative for high-resolution monitoring. Optical flow is a tracer-independent technique for deriving velocity fields from RGB video, making it well suited to UAV-based surveys. However, its operational use is hindered by the limited availability of annotated datasets and by instability under low-texture or noisy conditions. This study combines a Finite element method (FEM)-based physical flow model with UAV video to generate reference datasets and introduces a modified Recurrent All-Pairs Field Transforms (RAFT) architecture based on multiframe sequences. A Gated Recurrent Unit fusion module (Fuse-GRU) is incorporated prior to correlation computation, improving robustness to illumination changes and surface homogeneity while maintaining computational efficiency. The proposed model delivers stable, physically consistent velocity estimates across multiple rivers and flow conditions. Accuracy improves with higher spatial resolution and moderate temporal spacing. Compared to field measurements, the average angular difference ranged from 8 to 15°. The high error values were mainly caused by inaccuracies in the physical model and by complex river features. These findings confirm that multiframe optical flow can reproduce realistic river flow patterns with accuracy comparable to physically-based simulations, thereby supporting UAV-based hydrometric monitoring and model validation. Full article

Generative artificial intelligence and foundation models have changed machine learning by allowing systems to produce readable text, realistic images, and other multimodal content with little direct input from a user. Foundation models are large neural networks trained on very large and varied datasets, and they form the core of many current generative AI (GenAI) systems. Their rapid development has led to major advances in areas like natural language processing, computer vision, multimodal learning, and robotics. Examples include GPT, LLaMA, and diffusion-based architectures, such as models often used for image generation. Systems such as Stable Diffusion show this shift by illustrating how AI can interpret information, draw basic inferences, and produce new outputs using more than one type of data. This review surveys common foundation model architectures and examines what they can do in generative tasks. It reviews Transformer, diffusion, and multimodal architectures, focusing on methods that support scaling and transfer across domains. The paper also reviews key approaches to pretraining and fine-tuning, including self-supervised learning, instruction tuning, and parameter-efficient adaptation, which support these systems’ ability to generalize across tasks. In addition to the technical details, this review discusses how GenAI is being used for text generation, image synthesis, robotics, and biomedical research. The study also notes continuing challenges, such as the high computing and energy demands of large models, ethical concerns about data bias and misinformation, and worries about privacy, reliability, and responsible use of AI in real settings. This review brings together ideas about model design, training methods, and social implications to point future research toward GenAI systems that are efficient, easy to interpret, and reliable, while supporting scientific progress and ethical responsibility. Full article

Photovoltaic (PV) power forecasting is strongly influenced by volatility, randomness, and changing meteorological conditions, while conventional point forecasting provides limited uncertainty information for engineering use. This study proposes a hybrid interval forecasting framework for PV prediction. Similar-day clustering first segments weather data into distinct scenarios (sunny, cloudy and overcast) to reduce noise and redundant information within sequences, enhancing stability and thereby providing a more refined feature space for deep learning. A BiLSTM–Transformer model is then used as the core forecaster, taking multiple meteorological variables as multi-feature time-series inputs. BiLSTM captures bidirectional temporal dependencies, and the Transformer enhances long-range feature extraction via attention. To improve robustness and stability, the Alpha Evolution (AE) algorithm is applied for hyperparameter optimization, balancing global exploration and local refinement. For probabilistic forecasting, Adaptive Bandwidth Kernel Density Estimation (ABKDE) is employed to construct prediction intervals, where the local bandwidth is determined by minimizing a local error function to adapt to data density and error distribution. Case studies utilizing a full-year, 5 min high-resolution dataset from the DKASC station demonstrate that the proposed AE-BiLSTM–Transformer achieves highly accurate point forecasts across diverse weather conditions, reducing the RMSE by 81.85%, 76.99%, and 72.26% under sunny, cloudy, and overcast scenarios, respectively, compared to the baseline LSTM. ABKDE further produces reliable and compact intervals; at the 90% confidence level on sunny days, it achieves PICP = 0.921 with PINAW = 0.0378, reducing PINAW by 75.16% relative to conventional KDE while maintaining comparable coverage. Full article

Vein graft disease remains a significant limitation to the long-term patency of venous conduits following coronary artery bypass grafting. Early oxidative stress, triggered by ischaemia–reperfusion injury and haemodynamic changes following the implantation of veins into the arterial circulation, disrupts endothelial integrity and initiates inflammation, apoptosis, and maladaptive remodelling. The KEAP1-NRF2 axis is a central regulator of cellular antioxidant responses; however, its role in the development of vein graft disease remains poorly defined. This narrative review aimed to summarise what is known about NRF2/KEAP1 signalling in modulating vein graft pathology. Methods: A systematic search of PubMed was conducted to identify original research studies examining the NRF2/KEAP1 pathway in human saphenous vein tissue in vivo or ex vivo. Narrative synthesis was performed due to limited evidential availability and study heterogeneity. Results: Only one study has directly evaluated NRF2 pathway activation directly in human saphenous vein tissue, and it demonstrated that Protandim (a herbal dietary supplement) treatment increased antioxidant enzyme activity and reduced oxidative stress markers, including superoxide and 4-hydroxynonenal, both known activators of MAPK-dependent smooth muscle proliferation. Adjacent studies in other cells and tissues reveal that NRF2 intersects with multiple pathways central to vein graft pathology: it suppresses NFκB-mediated inflammation, modulates eNOS-NO signalling, inhibits NADPH oxidase expression, regulates MAPK activation, and influences angiogenic responses. However, context-dependent activation of NRF2 under arterial cyclic stretch can paradoxically drive proliferation through p62-mediated KEAP1 sequestration and enhanced glutathione synthesis. Conclusions: The NRF2/KEAP1 pathway serves as a central integrator of oxidative stress responses that directly intersect with established mechanisms of intimal hyperplasia and pathological angiogenesis. Post-translational KEAP1 inhibition may offer a targeted intervention point to limit these processes. Critical gaps remain regarding our understanding of the role of NRF2 in human saphenous vein under physiological arterial conditions and sex-specific pathway regulation. Mechanistic studies in vein-specific models are essential for advancing our understanding and any potential therapeutic translation. Full article

Steroid-resistant nephrotic syndrome (SRNS) in childhood frequently reflects monogenic podocytopathies in which immunosuppression is ineffective. Biallelic variants in MYO1E, encoding the class I myosin Myo1E, cause a distinctive form of focal segmental glomerulosclerosis (FSGS) often accompanied by “Alport-like” multilamination of the glomerular basement membrane (GBM). Early recognition has therapeutic and prognostic implications. A previously healthy 4-year-old boy presented with generalized edema and nephrotic-range proteinuria. Glucocorticoids induced no remission; sequential calcineurin inhibition (cyclosporine, then tacrolimus) and a single dose of ofatumumab yielded only transient, partial reductions in proteinuria. A first biopsy elsewhere showed FSGS with nonspecific IgM/C3 trapping; electron microscopy (EM) was not performed. At age 10, repeat biopsy with EM revealed ~30% segmental foot-process effacement, focal GBM thickening (to 1740 nm), irregular lamina densa multilamination, and lamellar duplications without immune-complex deposits—features highly suggestive of hereditary GBM disease. Targeted sequencing identified compound-heterozygous MYO1E variants segregating in trans: a canonical splice-donor change (c.2785+1G>A) and a frameshift (c.3094_3097del; p.Thr1032Profs*73). Each parent was an unaffected heterozygous carrier; the sibling was negative. Supportive therapy with ramipril was continued. At last follow-up (January 2025), renal function was normal (serum creatinine 0.5 mg/dL; creatinine clearance 122 mL/min) with stable sub-nephrotic proteinuria (0.52 g/day; 16 mg/m² per hour) and normotension. This case broadens clinicopathologic recognition of MYO1E-associated nephropathy and highlights the teaching point that Alport-like GBM changes are not pathognomonic for type IV collagen disorders but may signal defects in podocyte cytoskeletal anchoring. Full article

Surgical resection remains a cornerstone in the multidisciplinary management of central nervous system (CNS) tumors, particularly diffuse gliomas. Traditionally, the role of surgery has been evaluated primarily through quantitative metrics such as extent of resection and its association with survival outcomes. However, despite maximal and radiologically complete resections, recurrence remains nearly universal in malignant CNS tumors, suggesting that surgical cytoreduction alone does not fully account for post-surgical disease dynamics. Emerging biological and molecular evidence indicates that surgery represents not merely a technical intervention, but a biologically active event that profoundly reshapes tumor evolution and treatment response. In this review, we propose a conceptual framework that redefines surgery as a key biological driver in CNS tumor progression. We synthesize evidence demonstrating that surgical trauma induces inflammation, hypoxia, vascular remodeling, immune modulation, and extracellular matrix reorganization, collectively reprogramming the residual tumor microenvironment. These changes create selective pressures that favor the survival and expansion of adaptive tumor cell subpopulations, including invasive and stem-like phenotypes. From an evolutionary perspective, surgical resection functions as an acute selective bottleneck acting on heterogeneous tumor ecosystems, contributing to clonal selection and molecular divergence at recurrence. We further examine the dissociation between surgical (anatomical) margins and molecular (biological) margins, highlighting how biologically active tumor cells infiltrate beyond radiologically defined boundaries. This discrepancy provides a biological explanation for marginal and distant recurrences and challenges anatomy-based paradigms of surgical completeness. Importantly, we discuss how surgery-induced biological changes influence postoperative radiotherapy and systemic therapies, affecting radiosensitivity, target delineation, and therapeutic vulnerability. Finally, we outline future directions toward surgery-integrated precision neuro-oncology, emphasizing the potential of spatial profiling, liquid biopsy, advanced imaging, and artificial intelligence to capture perioperative tumor evolution. By reframing surgery as a biological inflection point rather than a neutral prelude to adjuvant treatment, this review advocates for a dynamic, biology-driven continuum of care aimed at anticipating tumor adaptation and improving long-term disease control in CNS tumors. Full article

Accurate forecasting of equity returns remains fundamentally constrained by weak short-horizon predictability, pronounced noise, and structural non-stationarity. While deep learning models have been widely applied to financial time series, most studies prioritize point prediction and provide limited guidance on reliable uncertainty quantification, particularly in emerging markets. This study developed an uncertainty-aware forecasting framework for the South African equity market by integrating variational mode decomposition (VMD), gated recurrent units (GRUs), and temporal conformal prediction (TCP) to construct distribution-free prediction intervals with finite-sample coverage guarantees. Using daily returns from the FTSE/JSE All Share Index, we first confirmed that baseline recurrent models applied directly to raw returns exhibited negligible out-of-sample explanatory power, consistent with weak-form market efficiency. Incorporating VMD enhanced representation learning and improved point forecast accuracy by isolating latent frequency components. However, model-based predictive variance alone proved insufficient for reliable calibration. Embedding the models within a rolling conformal prediction framework restored near-nominal coverage across multiple confidence levels while allowing interval widths to adapt dynamically to changing volatility regimes. Robustness analyses, including walk-forward validation, stress-regime evaluation, and block permutation negative control experiments, indicated that the observed performance was not driven by temporal leakage or alignment artifacts. The results further highlight a trade-off between interval sharpness and tail-risk protection, particularly during extreme market events. Overall, the findings support a shift from return-level prediction toward calibrated uncertainty estimation as a more stable and economically meaningful objective in non-stationary financial environments. Full article

In recent years, social networks have shown a great influx of new users and traffic. As their popularity grows, so does the interest in researching ways to process the information available, in order to produce useful knowledge. One direction is making personalized recommendations based on users’ preferences and on their social behavior and related characteristics in general. Static recommendations, however, are proven to be highly inaccurate, since as time progresses, people tend to change their preferences, making different decisions than the ones predicted previously. This calls for an adaptive algorithm that shifts according to the changes in preferences and habits of the users. Handling the stream of information is challenging, as the new data can severely change the recommendations to many users. In this work, we propose a novel streaming Point-of-Interest recommendation algorithm that explicitly incorporates location-aware features into its dynamic update mechanism, enabling continuous adaptation to newly arriving data. The proposed approach is experimentally evaluated based on real-life data sets containing the network structure as well as check-in information. The results demonstrate high accuracy, achieving at the same time significant performance gains with respect to runtime costs compared to conventional approaches. Full article

Background/Objectives: Bone-anchored prostheses provide an alternative to socket prostheses, directly connecting the prosthesis to the residual limb via osseointegration. However, limited evidence exists on how spatiotemporal gait parameters and gait symmetry change over time following osseointegration in individuals with unilateral transfemoral amputation. This study aimed to examine changes in spatiotemporal and gait symmetry parameters before osseointegration and at 6 and 12 months post-surgery. Methods: Common spatiotemporal parameters were collected from six individuals with unilateral transfemoral amputation at baseline (with socket prosthesis) and at 6 and 12 months post-osseointegration using a motion analysis system. Group-level differences were assessed using repeated measures ANOVA. Gait symmetry was evaluated using selected spatiotemporal parameters. Results: Following osseointegration, individuals with unilateral transfemoral amputation experienced significant spatiotemporal changes over time. At the group level, walking velocity and stride length decreased at 6 months, with stride length increasing at 12 months. Step width and prosthetic-side step length increased at 12 months relative to 6 months, while intact-side step length decreased. Prosthetic-side toe-off timing was shorter at 12 months. Gait symmetry responses varied individually: some with poor baseline symmetry improved, while those with better baseline symmetry became more asymmetric, indicating heterogeneous outcomes. Conclusions: This study highlights longitudinal changes in gait biomechanics following osseointegration in individuals with unilateral transfemoral amputation. Gait adaptations were highly variable across individuals and time points. Future research should involve larger, more homogeneous samples and incorporate kinetic, muscle activity, and functional outcome measures to better understand the impact of bone-anchored prostheses on gait and mobility. Full article

Through the process of modernization, Turkish literature transcends aesthetics to reflect sociological and cultural changes. The tensions between the individual and society, tradition and modernity, and religion that emerged with Westernization are particularly reflected in the novel. Religious discourse takes different forms at each historical threshold during the modernization process. During the Tanzimat, Servet-i Fünûn, Milli Edebiyat and Socialist Realist periods, it served as a defensive or critical reference point in the face of debates on modernization and Westernization. With the secular policies of the Republic, its public function transformed, evolving into an arena for cultural and moral debate, and it increased its visibility within the multiparty political structure after 1950. From the 1980s onwards, Islamic discourse became an artistic and ideological force in both the social and literary spheres. This article examines the stages of Islamic discourse in Turkish novels within a historical framework, arguing that religious representations are not merely elements reflecting social change, but also play an active role in the reconstruction of identity formation and narrative aesthetics. The study analyzes the functions of religious elements using a text-centered approach. The findings show that religion is not merely a theme in literary texts, but a living element that transforms alongside society, influences identity formation, and shapes narrative aesthetics. Full article

Introduction: Over 100 studies demonstrate the efficacy of Emotional Freedom Techniques (EFT), an evidence-based therapeutic method. However, most research is on in-person delivery of EFT. Only a few studies examine EFT delivered virtually, and to date no research has provided a direct comparison of group virtual EFT to group in-person delivery. Objectives: Delivery of EFT shifted to online platforms in the wake of the 2020 COVID-19 pandemic. This makes a comparison of virtual delivery to in-person delivery timely. The research question of whether online group delivery is as effective as in-person group delivery is of high clinical relevance, given the increased access and convenience offered by virtual treatment options. Methods: Participants in the online group were a convenience sample of 172 participants drawn from four four-day virtual EFT training sessions. Changes in psychological and physiological symptoms were measured pre, post, and at six-month follow-up using the Patient Health Questionnaire (PHQ-4). The two-item Post Traumatic Stress Disorder (PTSD) Checklist (PCL), the Happiness Scale, and the QuickDASH pain scale. These results were then compared to those of a previously published study of in-person group EFT (n = 203) that used an identical training curriculum delivered face-to-face. Due to COVID restrictions, the physiological measures used in the face-to-face delivery could not be replicated in the virtual group. Results: Online group EFT demonstrated significant improvements in PTSD, anxiety, depression, pain, and happiness (all p < 0.001) pre to post EFT. These improvements were maintained at six-month follow-up for PTSD (p < 0.001), depression (p = 0.048), pain (p = 0.002), and happiness (p < 0.001). Although there was a reduction in anxiety in the online group at six-month follow-up, this did not reach significance (p = 0.102). When compared to the in-person group (pre-COVID), the percent change in symptoms, while still clinically and statistically significant, was for most conditions smaller in the virtual group (post COVID) at both post and follow-up time points. Conclusions: EFT is associated with significant improvements in psychological and physiological conditions including PTSD, anxiety, depression, pain, and happiness, whether delivered virtually in groups or in-person in groups. The psychological and physiological benefits identified in online treatment are similar to those found during in-person delivery, though not as large or clinically significant. This finding is consistent with the literature demonstrating that online treatment is an effective method of delivering psychological therapies. The results reinforce other studies showing COVID produced a significant increase in mental health symptoms. Published treatment guidelines already recommend in-person EFT as an efficient and potentially cost-effective first-line intervention in primary care; virtual group EFT can be similarly recommended. Full article