Search Results (18,097)

Diffusion-controlled processes play a critical role in the heat treatment and microstructural homogenization of β-titanium alloys containing multiple β-stabilizing elements. Adding β-phase stabilizing elements like Cr and Nb to titanium alloys can significantly improve the high-temperature strength and creep performance of the alloy. Their diffusion coefficients can be used to predict the risk of softening and creep failure in high-temperature components caused by diffusion. However, reliable diffusion kinetic data for the β phase in the Ti–Cr–Nb ternary system remain scarce, limiting quantitative process modeling and simulation. In this study, diffusion behavior in the BCC (β) region of the Ti–Cr–Nb system was investigated using diffusion couples combined with CALPHAD-based kinetic modeling. Twelve sets of diffusion couples were prepared and annealed at 1373 K for 48 h, 1423 K for 36 h, and 1473 K for 24 h. The corresponding composition–distance profiles were measured by electron probe microanalysis. Composition-dependent interdiffusion coefficients and atomic mobility parameters were determined using the numerical inverse method. The results revealed temperature and composition dependence of the main interdiffusion coefficients, with Nb exhibiting a stronger influence than Cr. The evaluated kinetic parameters provide an effective kinetic description for diffusion-controlled process simulations. Full article

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique that utilizes magnetic fields to induce cortical electric currents, enabling both the measurement and modulation of neuronal activity. Initially developed as a diagnostic tool, TMS now serves dual roles in clinical neurology, offering insight into neurophysiological dysfunctions and the therapeutic modulation of abnormal cortical excitability. This review examines key TMS outcome measures, including motor thresholds (MT), input–output (I/O) curves, cortical silent periods (CSP), and paired-pulse paradigms such as short-interval intracortical inhibition (SICI), short-interval intracortical facilitation (SICF), intracortical facilitation (ICF), long interval cortical inhibition (LICI), interhemispheric inhibition (IHI), and short-latency afferent inhibition (SAI). These biomarkers reflect underlying neurotransmitter systems and can aid in differentiating neurological conditions. Diagnostic applications of TMS are explored in Parkinson’s disease (PD), dystonia, essential tremor (ET), Alzheimer’s disease (AD), and mild cognitive impairment (MCI). Each condition displays characteristic neurophysiological profiles, highlighting the potential for TMS-derived biomarkers in early or differential diagnosis. Therapeutically, repetitive TMS (rTMS) has shown promise in modulating cortical circuits and improving motor and cognitive symptoms. High- and low-frequency stimulation protocols have demonstrated efficacy in PD, dystonia, ET, AD, and MCI, targeting the specific cortical regions implicated in each disorder. Moreover, the successful application of TMS in differentiating and treating AD and MCI underscores its clinical utility and translational potential across all neurodegenerative conditions. As research advances, increased attention and investment in TMS could facilitate similar diagnostic and therapeutic breakthroughs for other neurological disorders that currently lack robust tools for early detection and effective intervention. Moreover, this review also aims to underscore the importance of maintaining standardized TMS protocols. By highlighting inconsistencies and variability in outcomes across studies, we emphasize that careful methodological design is critical for ensuring the reproducibility, comparability, and reliable interpretation of TMS findings. In summary, this review emphasizes the value of TMS as a distinctive, non-invasive approach to probing brain function and highlights its considerable promise as both a diagnostic and therapeutic modality in neurology—roles that are often considered separately. Full article

Soil degradation and limited root-exploitable depth restrict maize productivity in Plinthosols of tropical regions. However, the combined effects of subsoiling and amendments derived from termite mound materials on soil functionality and yield remain insufficiently quantified. This study examines how variations in a functionally exploitable rooting depth, within a management system combining subsoiling and termite mound amendments, are associated with soil physicochemical properties and spatial variability of maize (Zea mays L.) grain yield in the Lubumbashi region of the Democratic Republic of the Congo. Spatial soil sampling and correlation analyses were used to identify the dominant pedological factors controlling yield variability. The results indicate a reduced vertical stratification of most nutrients within the explored depth, reflecting a more homogeneous distribution of soil properties within the managed profile, although direct causal attribution to specific practices cannot be established in the absence of untreated control plots. Improved rooting conditions were reflected by high and spatially variable productivity (2.3 to 11.1 t ha⁻¹ across blocks), accompanied by a moderate average gain between seasons (<1 t ha⁻¹), while extractable manganese emerged as a consistent negative predictor of yield. These patterns are consistent with a larger functionally exploitable rooting depth and an improved soil environment, although causal contributions of subsoiling and termite mound amendments cannot be isolated in the absence of control plots. Overall, the results highlight the importance of jointly considering structural and chemical soil properties when interpreting productivity gradients in Plinthosols and designing sustainable management strategies for degraded tropical soils. Full article

Background: Pseudomonas aeruginosa is one of the leading agents causing healthcare-associated infections (HAIs) due to its intrinsic resistance, its capacity to acquire resistance mechanisms, and its persistence in hospital environments. In Mexico, it ranks among the most frequently reported pathogens in national surveillance systems. The aim of this study was to characterize antimicrobial resistance profiles and the genetic determinants associated with MDR/XDR phenotypes in P. aeruginosa strains from HAIs at Hospital Juárez de México (HJM). Methods: Sixty-three strains from patients with HAIs were analyzed. Identification was confirmed by 16S rRNA gene sequencing. Antimicrobial susceptibility testing followed CLSI guidelines. MDR/XDR phenotypes were classified according to the Latin American consensus for categorizing MDR, XDR, and PDR pathogens. Screening for resistance mechanisms was carried out by PCR for the main β-lactamases circulating at HJM. Finally, mutations in the oprD gene were detected in imipenem-resistant isolates through amino acid sequence alignment. Results: Resistant phenotypes allowed the identification of MDR and XDR profiles. Only the metallo-β-lactamase bla_VIM was detected. Analysis of oprD porin sequences revealed recurrent mutations (S103T, T115K, L170F, G186P, and T189V) associated with imipenem resistance. Conclusions: In P. aeruginosa, the presence of bla_VIM and structural alterations in OprD confirms the multifactorial nature of carbapenem resistance. These findings underscore the need to strengthen microbiological surveillance programs and antimicrobial stewardship strategies to mitigate the impact and spread of MDR/XDR isolates. Full article

Driven by energy transition strategies, distributed resources are being extensively integrated into the distribution network (DN). However, sufficient coordination among these resources remains challenging due to their diverse ownership structures. To address this, a hybrid game-theoretic economic scheduling method for the distribution network based on grid–storage–load interaction is proposed. A two-layer game framework, “distribution network–shared energy storage–microgrid alliance (MGA)”, is established to enable coordinated utilization of flexible resources across the grid, storage, and load sides. The upper-layer distribution network determines time-of-use electricity prices to guide the energy strategies of storage and microgrid alliance. The lower-layer agents engage in a two-stage interaction: Stage 1, multiple microgrids (MGs) form an alliance to lease shared energy storage to smooth net-load profiles. The shared energy storage operator (SESO) then utilizes its surplus capacity to assist the distribution network in peak shaving, thereby maximizing its own revenue. Stage 2, the alliance facilitates mutual power support and implements demand response (DR), reducing its energy costs and assisting the system in peak shaving and valley filling. Case analysis demonstrates that, compared to baseline without coordination, the proposed method reduces the distribution network’s electricity procurement cost by 11.28% and lowers the system’s net load peak-to-valley difference rate by 56.53%. Full article

Recycling of 6xxx aluminum alloys, which are used extensively in the automotive industry, is important for ensuring a carbon-neutral future and the efficient use of resources on Earth. The sustainability of recycling in aluminum alloys is directly proportional to the correct classification of the scrap to be used. In this study, scrap stream from a novel scrap-sorting technology called MULTI-PICK has been used to validate. The 6063 and 6082 alloys produced with scrap stream, which are commonly used for structural parts in the automotive sector, are analyzed with hydrogen analysis and PREFIL. Cast billets are evaluated considering extrusion. After extrusion, microstructures of the profiles are investigated with scanning electron microscopy (SE), transmission electron microscopy (TE) and electron backscatter diffraction (EBSD). Their mechanical properties and anisotropic behaviors are investigated with tensile testing in different orientations. Additionally, an alternative alloy called 6111 has been studied to replace the target alloys with low critical raw material (CRM) content. According to the findings, highly recycled 6xxx alloys can be used in the automotive industry without losing their existing properties. Furthermore, using alternative feedstock and retrofitted systems can decrease carbon footprint below 4 kgCeq/kgAl. Full article

Soil erosion in the hilly and gully region of the middle reaches of the Yellow River is severe, threatening regional ecological security and the water–sediment balance of the Yellow River. The area features fragmented topography and significant spatial heterogeneity in soil thickness, forming a unique binary “soil–rock” structural system. The soil in the study area is characterized by silt-based loess, and the underlying bedrock is an interbedded Jurassic-Cretaceous sandstone and sandy shale. It has strong weathering, well-developed fissures, and good permeability, rather than dense impermeable rock layers. However, the spatiotemporal differentiation mechanism of soil moisture in this system remains unclear. This study focuses on the typical hilly and gully region—the Geqiugou watershed. Through field investigations, soil thickness sampling, multi-scale soil moisture monitoring, and analysis of meteorological data, it systematically examines the cascade relationships among microtopography, soil–rock combinations, soil moisture, and meteorological drivers. The results show that: (1) Based on the field survey of 323 sampling points in the study area, it was found that soil samples with a thickness of less than 50 cm accounted for 85%, which constituted the main structure of soil thickness in the region. Macrotopographic units control the spatial differentiation of soil thickness, forming a complete thickness gradient from erosional units (e.g., Gully and Furrow) to depositional units (e.g., Gently sloped terrace). Based on this, five typical soil–rock combination types with soil thicknesses of 10 cm, 30 cm, 50 cm, 70 cm, and 90 cm were identified. (2) Soil–rock combination structures regulate the vertical distribution and seasonal dynamics of soil moisture. In thin-layer combinations, soil moisture is primarily retained within the shallow soil profile with higher dynamics, whereas in thick-layer combinations, under conditions of substantial rainfall, moisture can percolate deeply and become notably stored within the fractured bedrock, sometimes exceeding the moisture content in the overlying soil. (3) The response of soil moisture to precipitation is hierarchical: light rain events only affect the surface layer, whereas heavy rainfall can infiltrate to depths below 70 cm. Under intense rainfall, the soil–rock interface acts as a rapid infiltration pathway. (4) The influence of meteorological drivers on soil moisture exhibits vertical differentiation and is significantly modulated by soil–rock combination types. This study reveals the critical role of microtopography-controlled soil–rock combination structures in the spatiotemporal differentiation of soil moisture, providing a scientific basis for the precise implementation of soil and water conservation measures and ecological restoration in the region. Full article

Background: Sarcomas are rare, aggressive malignancies with limited therapeutic options in advanced stages. This is the first real-world study in the MENA region evaluating the clinical utility of Next-Generation Sequencing (NGS) in guiding sarcoma treatment and improving outcomes. Methods: We retrospectively reviewed sarcoma patients who underwent NGS at a major referral center (2021–2024), comparing clinical and molecular outcomes between those who received NGS-based treatment adjustments (NBTA) and those who did not. Results: Seventy-eight patients were included (60% male; median age 44 years). Soft tissue sarcomas accounted for 70.5% of cases (n = 55), while bone sarcomas represented 29.5% (n = 23). Prior to NGS, 64.1% of patients had received a median of one line of systemic therapy. NGS was performed late in the disease course in 73% of cases. At least one mutation was detected in 87% (median 3 mutations). Targetable alterations were identified in 33% at the time of testing, rising to 42% with updated genomic knowledge and therapeutic advances. Overall, 20.5% received NBTA. Among non-NBTA patients, 67% had no actionable targets, 17% had no detectable mutations, and 16% were ineligible due to cost, limited access, or clinical deterioration. Tumor Mutational Burden was low in 79%, intermediate in 19%, and high in 2%, and all tumors were microsatellite stable. Patients receiving NBTA had a longer median Progression-Free Survival (9 vs. 2 months; p = 0.023). Median Overall Survival was longer in the NBTA group (74 vs. 48 months), though not statistically significant (p = 0.207). Genomic alterations were subtype-specific: EWSR1 rearrangements (Ewing and Desmoplastic small round cell tumors), CDK4 and MDM2 amplifications (Liposarcoma and Osteosarcoma), TP53 and RB1 mutations (Leiomyosarcoma), CDKN2A/B deletions (Undifferentiated Pleomorphic Sarcoma and Chondrosarcoma), and SS18 rearrangements (Synovial Sarcoma). Conclusions: Genomics-guided therapy in sarcoma is feasible and impactful. Expanding timely access to molecular profiling is essential for advancing precision oncology in the MENA region. Full article

Liver cancer, also known as hepatocellular carcinoma (HCC), remains a major global health concern, with high mortality driven by late-stage diagnosis, limited treatment efficacy, and frequent therapeutic resistance. Matrix metalloproteinases (MMPs), a large family of zinc-dependent endopeptidases, are central to the biological processes that drive liver tumor initiation and progression. By degrading and reorganizing extracellular matrix components, MMPs facilitate tumor expansion, tissue invasion, and metastatic dissemination. In addition, these enzymes regulate the availability of growth factors, cytokines, and chemokines, thereby influencing angiogenesis, inflammation, immune cell recruitment, and the development of an immunosuppressive tumor microenvironment. Aberrant expression or activity of multiple MMP family members is consistently associated with aggressive clinicopathologic features, including vascular invasion, increased metastatic potential, and reduced patient survival, highlighting their promise as prognostic markers and actionable therapeutic targets. Past attempts to modulate MMP activity were hindered by broad inhibition profiles and dose-limiting toxicities, underscoring the need for improved specificity and delivery strategies. Recent advances in molecular design, biologics engineering, and nanotechnology have revitalized interest in MMP targeting by enabling more selective, context-dependent modulation of proteolytic activity. Preclinical studies demonstrate that carefully tuned MMP inhibition can limit tumor invasion, enhance anti-angiogenic responses, and potentially improve the efficacy of existing systemic therapies, including immuno-oncology agents. This review synthesizes current knowledge on the multifaceted roles of MMPs in HCC pathobiology and evaluates emerging therapeutic strategies that may finally unlock the clinical potential of targeting these proteases. Full article

High-Resolution Range Profile (HRRP) represents the electromagnetic backscattering distribution of targets and plays a pivotal role in remote-sensing-based Automatic Target Recognition (RATR). However, in non-cooperative sensing scenarios, acquiring sufficient measured data is severely constrained by operational costs and physical limitations, leading to data scarcity that hampers model robustness. To overcome this, we propose SpecM-DDPM, a spectral-aware Denoising Diffusion Probabilistic Models (DDPM) tailored for generating high-fidelity HRRPs that preserve physical scattering properties. Unlike generic generative models, SpecM-DDPM incorporates radar signal physics into the diffusion process. Specifically, a parallel multi-scale block is designed to adaptively capture both local scattering centers and global target resonance structures. To ensure spectral fidelity, a spectral gating mechanism serves as a physics-constrained filter to calibrate the energy distribution in the frequency domain. Furthermore, a Frequency-Aware Curriculum Learning (FACL) strategy is introduced to guide the progressive reconstruction from low-frequency structural components to high-frequency scattering details. Experiments on measured aircraft data demonstrate that SpecM-DDPM generates samples with high physical consistency, significantly enhancing the generalization performance of radar recognition systems in data-limited environments. Full article

Regulatory T cells (Tregs), particularly their phenotypically distinct subpopulations, are critical for the establishment of maternal immune tolerance during embryo implantation. Despite advances in assisted reproductive technologies, implantation failure remains a frequent and often unexplained clinical challenge. Variations in Treg frequency and phenotype have been proposed to influence implantation success, particularly under differing hormonal conditions. This study aimed to investigate peripheral blood Treg levels and their subpopulations on the day of blastocyst transfer in both stimulated in vitro fertilization (IVF/ICSI) cycles involving controlled ovarian hyperstimulation (COH) and true natural cycles with frozen embryo transfer (FET), and to examine their associations with systemic hormone levels and anti-Müllerian hormone (AMH). A prospective observational study was conducted including women undergoing IVF/ICSI with fresh embryo transfer (ET) and women undergoing natural cycle FET. Peripheral blood samples were collected on the day of ET and analyzed using 13-colour flow cytometry, enabling detailed subdivision of Tregs into multiple subpopulations based on the expression of differentiation and chemokine markers, including CXCR5. In addition, because common $\gamma$-chain cytokines may influence pregnancy success by modulating the balance between suppressive Treg and non-Treg subsets, intracellular STAT5 signaling was assessed using phospho-specific flow cytometry. Serum estradiol, progesterone, FSH, LH, and AMH levels were measured in parallel. Significant differences were observed in Treg subpopulation distributions between women who conceived and those who did not. Higher frequencies of naïve CXCR5⁻ Tregs were associated with clinical pregnancy, independent of age, and correlated with serum progesterone levels. Moreover, both naïve Treg frequency and enhanced IL-7-dependent STAT5 signaling in naïve Tregs from women undergoing COH were associated with AMH levels, suggesting a link between ovarian reserve and Treg homeostasis mediated by signal transducer and activator of transcription 5 (STAT5) signaling. In conclusion, Treg subpopulations, particularly CXCR5⁻ naïve Tregs, appear to play a central role in implantation success following ET. Their distribution differs between stimulated and natural cycles and is influenced by systemic progesterone levels and STAT5 signaling. These findings suggest that peripheral Treg profiling may represent a potential biomarker of implantation competence and could inform personalized approaches in assisted reproduction. Full article

Automata and artificial intelligence (AI) have long occupied a central place in cultural and artistic imagination, and the recent proliferation of AI-generated artworks has intensified debates about authorship, creativity, and human agency. Empirical studies show that audiences often perceive AI-generated works as less authentic or emotionally resonant than human creations, with authorship attribution strongly shaping esthetic judgments. Yet little attention has been paid to how AI systems themselves evaluate creative authorship. This study investigates how large language models (LLMs) evaluate literary quality under different framings of authorship—Human, AI, or Human+AI collaboration. Using a questionnaire-based experimental design, we prompted four instruction-tuned LLMs (ChatGPT 4, Gemini 2, Gemma 3, and LLaMA 3) to read and assess three short stories in Italian, originally generated by ChatGPT 4 in the narrative style of Roald Dahl. For each story × authorship condition × model combination, we collected 100 questionnaire completions, yielding 3600 responses in total. Across esthetic, literary, and inclusiveness dimensions, the stated authorship systematically conditioned model judgments: identical stories were consistently rated more favorably when framed as human-authored or human–AI co-authored than when labeled as AI-authored, revealing a robust negative bias toward AI authorship. Model-specific analyses further indicate distinctive evaluative profiles and inclusiveness thresholds across proprietary and open-source systems. Our findings extend research on attribution bias into the computational realm, showing that LLM-based evaluations reproduce human-like assumptions about creative agency and literary value. We publicly release all materials to facilitate transparency and future comparative work on AI-mediated literary evaluation. Full article

Yeast biosensors represent a promising biotechnological innovation for ensuring the safety and quality of fermented beverages such as beer, wine, and kombucha. These biosensors employ genetically engineered yeast strains to detect specific contaminants, spoilage organisms, or hazardous compounds during fermentation or the final product. By integrating synthetic biology tools, researchers have developed yeast strains that can sense and respond to the presence of heavy metals (e.g., lead or arsenic), mycotoxins, ethanol levels, or unwanted microbial metabolites. When a target compound is detected, the biosensor yeast activates a reporter system, such as fluorescence, color change, or electrical signal, providing a rapid, visible, and cost-effective means of monitoring safety parameters. These biosensors offer several advantages: they can operate in real time, are relatively low-cost compared to conventional chemical analysis methods, and can be integrated directly into the fermentation system. Furthermore, as Saccharomyces cerevisiae is generally recognized as safe (GRAS), its use as a sensing platform aligns well with existing practices in beverage production. Yeast biosensors are being investigated for the early detection of contamination by spoilage microbes, such as Brettanomyces and lactic acid bacteria. These contaminants can alter the flavor profile and shorten the product’s shelf life. By providing timely feedback, these biosensor systems allow producers to intervene early, thereby reducing waste and enhancing consumer safety. In this work, we review the development and application of yeast-based biosensors as potential safeguards in fermented beverage production, with the overarching goal of contributing to the manufacture of safer and higher-quality products. Nevertheless, despite their substantial conceptual promise and encouraging experimental results, yeast biosensors remain confined mainly to laboratory-scale studies. A clear gap persists between their demonstrated potential and widespread industrial implementation, underscoring the need for further research focused on robustness, scalability, and regulatory integration. Full article

Background and Objectives: Oral Janus kinase (JAK) inhibitors have become an important therapeutic class in dermatology, with approved indications including atopic dermatitis and alopecia areata. Owing to their broad immunomodulatory effects and rapid onset of action, these agents are increasingly used off label for a variety of inflammatory skin disorders that are often refractory to standard therapies. The objective of this review was to provide a comprehensive overview of the published literature on the off-label dermatologic use of oral JAK inhibitors, summarizing clinical outcomes, safety profiles and treatment durations reported in real-world settings. Materials and Methods: A literature search was conducted in PubMed to identify case reports and case series describing off-label dermatologic use of baricitinib, abrocitinib, upadacitinib, and ritlecitinib. Extracted data included authorship and year, article type, treatment regimen, treatment duration and follow-up, prior systemic therapies, clinical outcomes, and reported adverse events. Results: A total of 136 articles were included, comprising 45 articles on abrocitinib (63 patients), 55 on upadacitinib (94 patients), 35 on baricitinib (45 patients), and 2 on ritlecitinib (2 patients). Across a wide spectrum of dermatological conditions, oral JAK inhibitors showed consistent clinical efficacy. Responses were frequently rapid and disease control was often maintained over several months of treatment. In many cases, dose reduction or treatment discontinuation did not lead to immediate relapse. Overall tolerability was favorable, with adverse events reported in a minority of patients and predominantly described as mild and transient. Conclusions: Although our data is limited to case-based literature, this review highlights the broad off-label therapeutic potential of oral JAK inhibitors in dermatology. Their rapid onset of action, sustained clinical responses, frequent maintenance of remission after dose tapering or discontinuation and generally acceptable safety profile support their consideration as treatment options in selected patients. Full article

Nanoplastics (NPs) pose significant risks due to their small size and ability to penetrate biological tissues. However, the molecular pathways and cellular mechanisms affected by NP exposure in marine teleosts remain poorly understood, especially in tropical reef fishes. This study examined the impact of short-term (7 days) waterborne exposure of 100 nm-carboxyl-modified polystyrene NPs on the false clownfish (Amphiprion ocellaris) exposed at two daily concentrations: low (20 µg/L, environmentally relevant) and high (2000 µg/L). A multidisciplinary approach, including biochemical and transcriptomic analyses, was conducted to assess toxic effects. Biochemical assays revealed limited changes in antioxidant defenses (CAT, GR, GST, TOSC). However, the Integrated Biomarker Response index (IBRv2i) suggested a compromised physiological condition, supported by transcriptomic data. Transcriptomic profiling revealed 409 significantly differentially expressed genes (DEGs) in the high-concentration and 354 DEGs in the low-concentration groups, with 120 shared DEGs mostly upregulated and indicative of a core molecular response. Collectively, the transcriptional profile of the low-concentration group resembled an early-warning, energy-reallocation strategy aimed at preserving essential sensory functions while minimizing expendable functions. The high-concentration group amplified the shared stress signature and recruited an additional 289 unique genes, resulting in pronounced enrichment of Gene Ontology terms related to “muscle contraction”, “oxygen transport”, “hydrogen-peroxide catabolism”, and “extracellular-matrix”. This study demonstrates that PS-NP exposure can alter gene expression and physiology in juvenile reef fish, even at environmentally relevant concentrations. Molecular responses varied with concentrations highlighting the role of exposure level in influencing biological systems and potential long-term impacts of NP pollution in marine environments. Full article