Search Results (1,454)

Background: Accurate post-treatment imaging assessment of hepatocellular carcinoma (HCC) is essential for guiding retreatment, transplantation eligibility, and prognosis. The Liver Imaging Reporting and Data System Treatment Response Algorithm (LI-RADS TRA) was updated in 2024, introducing refinements across contrast-enhanced ultrasound (CEUS), CT/MRI, and radiation-based therapies, including the TR-Nonprogressing category. We aimed to systematically review current evidence on the diagnostic performance, reproducibility, and clinical implications of LI-RADS TRA v2024 for post-treatment assessment of HCC across imaging modalities and locoregional therapies. Methods: A systematic search of PubMed, Embase, Scopus, Web of Science, and CENTRAL was conducted according to PRISMA 2020 guidelines. Original studies applying LI-RADS TRA v2024 (or comparisons with earlier versions or mRECIST) after locoregional therapies were included. Outcomes of interest comprised diagnostic accuracy metrics, inter-reader and inter-modality agreement, temporal behavior of TRA categories, and prognostic associations. Given substantial heterogeneity, results were synthesized narratively. Results: Six studies met inclusion criteria. After thermal ablation, CEUS applying the non-radiation TRA v2024 showed very high specificity (approximately 88–100%) and excellent negative predictive value (about 94–98%), with substantial-to-almost-perfect inter-reader agreement (κ up to 0.92) and excellent inter-modality agreement with CT/MRI (ICC ≈ 0.90). After transarterial chemoembolization, CEUS performance was time-dependent, with higher sensitivity at early follow-up (~15 days) and higher specificity at later assessment (~30 days). On MRI, non-radiation TRA v2024 combined with ancillary features improved sensitivity and, in some analyses, accuracy compared with v2017 and v2024 without ancillary features, while remaining more specific than mRECIST. In radiation-based therapies, the radiation TRA v2024 captured delayed-response patterns through the TR-Nonprogressing category, which demonstrated meaningful temporal evolution and prognostic separation from TR-Viable. Surgical validation confirmed preserved diagnostic performance against histology. Conclusions: Despite heterogeneous data, available evidence supports LI-RADS TRA v2024 as a clinically useful framework that improves clarity, reproducibility, and actionability of post-treatment HCC imaging. CEUS is particularly effective after ablation; timing is critical after TACE, ancillary features should be routinely applied on MRI, and TR-Nonprogressing appropriately reflects radiation biology while preserving prognostic value. Full article

Here, we present a single-operator push-cart platform equipped with a 16-beam LiDAR. A push-button interface controls data acquisition, and the data processing pipeline removes ground points, filters noise, performs 5-cm voxelization, and produces plot-level canopy metrics. We validated biomass estimation in hairy vetch (Vicia villosa) and corn (Zea mays) leaf- and whole-plant thinning experiments. In vetch, voxelized estimation of plant volume correlated strongly with destructively measured biomass (r² = 0.88), showing that the multi-beam LiDAR can produce biomass estimates comparable to previously reported methods. In corn, comparisons of perpendicular (0°) and multi-angle LiDAR beams showed significantly greater voxel counts in the upper canopy when angled beams were used (beam angle × height interaction, p < 0.001), demonstrating that multi-beam scanning provides greater penetration into the upper canopy than a single perpendicular scan plane. We also extended the suite of LiDAR-derived traits to include apparent leaf area index (LAI), mean tilt angle (MTA), persistent homology-based stand density, and plot-bounded foliage area density (FAD). The persistent homology algorithm distinguished between leaf-removal and plant-removal treatments (removal type × removal amount, p = 0.0039). LiDAR-derived LAI has been used to estimate canopy leaf area, but gap-fraction approaches do not fully exploit the ability of LiDAR to resolve distance. Plot-bounded FAD used ray length and interception distance within defined plot volumes and was more sensitive to plot-level treatments than apparent LAI or MTA, detecting differences associated with both the removal amount and removal type. These results show that a robust, portable, multi-beam LiDAR cart can reproduce plot-level canopy measurements and improve trait especially in research-sized plots. Full article

Microalgae of the genus Chlorella are widely used in biotechnology for biofuel production, wastewater treatment, and biomass generation. This study examined the effect of initial biomass concentration on the growth kinetics of Chlorella vulgaris cultivated in cylindrical photobioreactors. Experiments were performed in identical 4 L reactors under constant illumination (~300 µmol·m⁻²·s⁻¹), aeration (0.5 vvm), and atmospheric CO₂ (~0.04%). Four initial biomass concentrations (0.012, 0.053, 0.110, and 0.530 g·L⁻¹) were tested in duplicate. Growth curves were fitted using the logistic, Gompertz, and Baranyi–Roberts models. The best-performing Gompertz model was further extended by relating its kinetic parameters to the initial biomass concentration, allowing biomass productivity to be evaluated as a continuous function of cultivation time and inoculum level. Initial biomass strongly affected growth dynamics. Increasing the initial concentration from 0.012 to 0.110 g·L⁻¹ reduced the lag phase from 53.9 ± 5.1 h to 4.0 ± 6.9 h, while no distinct lag phase was observed at 0.530 g·L⁻¹. Meanwhile, the maximum specific growth rate decreased from 0.0507 to 0.0251 h⁻¹. The model-based analysis indicated that the optimal initial biomass concentration is time-dependent: higher values are preferable for short cultivations, whereas lower values become advantageous during prolonged cultivation. Although the predicted optimum partly lies between experimentally tested values and should be interpreted as exploratory rather than predictive, the proposed approach demonstrates the potential of model-assisted optimization for future process design, pending experimental validation. Full article

This study addresses the need for dark-current control and stable current response in planar high-purity germanium (HPGe) detectors for low-energy X-ray detection. A device fabrication strategy based on the coupled optimization of near-surface treatment, N/P junction formation, and guard-ring electrode design is proposed. Unlike previous studies that mainly focused on contact-layer fabrication, segmented electrode structures, low-noise readout, or response simulation, this work investigates low-damage near-surface construction, N-type and P-type contact-layer formation, and edge-related leakage-current regulation as an interconnected processing route. The relationship among the near-surface state, junction quality, electrode configuration, and edge-related leakage current is emphasized. Chemical mechanical polishing (CMP) reduced the surface roughness Sa of the HPGe crystal to 6.68 nm, providing a low-damage near-surface foundation for subsequent junction fabrication. On this basis, the optimized Li thermal diffusion process, namely 0.5 Å s⁻¹, 325 °C, and 5 min, formed an N-type contact layer with preserved lattice ordering and favorable electrical properties. B ion implantation combined with rapid thermal processing (RTP) achieved acceptor activation and implantation-damage recovery, and the condition with Rp = 198.1 nm showed relatively better structural recovery and electrical characteristics. After introducing the guard-ring electrode, the dark current of the device at −20 V decreased from 6.5 × 10⁻⁹ A to 2.03 × 10⁻⁹ A, and a stable switching current response was obtained under 12 keV monochromatic synchrotron X-ray irradiation. Geant4 simulations were further used as an auxiliary analysis to evaluate the effect of the guard-ring structure on the simulated response spectra and full-energy peak efficiency (FEPE) for low-energy X-rays. Overall, this study provides experimental evidence for process optimization of planar HPGe detectors with low dark current and stable low-energy current response. Full article

Pain biomarkers have been proposed as potential tools to improve patient stratification, treatment selection, and individualized therapeutic strategies in chronic pain. However, despite an increasing volume of research across neuroimaging, electrophysiological, and molecular domains, their translation into clinical practice remains limited. A central challenge lies in the conceptual and methodological misalignment between biomarker discovery and clinical applicability. Many studies labelled as “predictive” rely on measurements obtained during or after intervention, small sample sizes, or lack of external validation, limiting their ability to inform real-world decision-making. In addition, the distinction between predictive, monitoring, and mechanistic biomarkers is often blurred, further complicating interpretation and implementation. This Perspective examines why many candidate pain biomarkers, although biologically informative, have not yet become clinically actionable tools for treatment selection. We distinguish between associative, mechanistic, monitoring, preventive, and truly predictive biomarkers using clinically relevant examples from pain research, and we outline the methodological requirements needed to translate biomarker discovery into precision pain medicine. We argue that the field requires a more rigorous framework for defining and validating predictive biomarkers, encompassing appropriate timing of measurement, robust study design, external validation, and patient-relevant endpoints. Without this framework, pain biomarker research risks continuing to generate biologically informative but clinically non-actionable findings that do not advance individualized therapeutic decision-making. Full article

The application of a huge number of lithium-ion batteries (LIBs) to electric vehicles has produced much solid waste. If not disposed properly, the solid waste may cause environmental pollution and is, per se, a waste of resources. Therefore, recycling valuable metals from LIBs is considered an ideal option for preventing environmental pollution and alleviating waste. Taking sulfuric acid (H₂SO₄) as the leaching agent and glucose (C₆H₁₂O₆) as the reducing agent, the ultrasonic-assisted reducing leaching was used to recycle lithium (Li) and iron (Fe) from spent lithium iron phosphate (LFP) batteries. Based on experimental results of conventional leaching, the research aimed to examine the influence of ultrasonic treatment on leaching rates of Li and Fe. Results show that the leaching rates of Li and Fe are separately 96.53% and 96.8% when the concentration of H₂SO₄ is 2 mol/L, the concentration of C₆H₁₂O₆ is 2 mol/L, the liquid–solid ratio is 15 mL/g, leaching temperature is 70 °C, leaching time is 60 min, and ultrasonic power is 100 W. Compared with conventional leaching, the leaching rates of Li and Fe separately increase by 10.84% and 12.33% through ultrasonic-assisted leaching under the same experimental conditions. Kinetics analysis of ultrasonic-assisted reducing leaching indicates that the activation energies of Li and Fe are 10.84 kJ/mol and 16.24 kJ/mol, respectively. The ultrasonic-assisted reducing leaching process of Li and Fe from LFP batteries is controlled by diffusion. Full article

Acidic wastewater generated during sulfuric acid leaching of reduced tionite within the EUROTITAN process was treated using three low-cost adsorbents: fly ash, bentonite, and red mud slag. Tionite is a solid residue originating from the sulfate route of TiO₂ production, whereas the investigated wastewater is a secondary acidic stream produced during hydrometallurgical treatment of reduced tionite. The initial wastewater was characterized by low pH and elevated concentrations of Fe, Al, Ti, B, Cu, Mn, Pb, Cr, and Li. Batch adsorption experiments were carried out by varying contact time from 4 to 24 h and adsorbent dosage from 5 to 15 g/L. The results showed distinct selectivity depending on adsorbent type and solution chemistry. Bentonite exhibited the most stable performance, achieving nearly complete removal of Pb, Cu, B, and Li, while Fe and Al were only partially removed and Ti removal remained limited. Fly ash showed high affinity toward Pb and Cu, but its performance was strongly affected by dosage and contact time. Red mud slag demonstrated excellent Pb removal, high Cu removal, and time- and dosage-dependent Ti removal, although partial dissolution of Fe- and Al-bearing phases occurred under strongly acidic conditions. Overall, the results confirm that industrial by-products and natural clay materials can contribute to partial purification of acidic metallurgical wastewater, while additional neutralization or polishing steps are required for complete treatment. Full article

Cyclodextrins are cyclic carbohydrates capable of forming inclusion complexes with a wide range of molecules, thereby improving their solubility, stability, and bioavailability. Traditionally, cyclodextrins have been extensively applied in the food industry owing to their functionality and safety profile. However, their use in cosmeceuticals, a rapidly growing area that lies between cosmetics and pharmaceuticals, remains relatively underexplored. Given the increasing demand for scientifically validated, high-performance skincare formulations, cyclodextrins are emerging as promising compounds that can address several formulation challenges. The principal question is whether cyclodextrins represent a worthwhile investment for the future of cosmeceutical innovation. This article aims to provide a comprehensive, evidence-based overview of the current and potential roles of cyclodextrins as safe, effective, and multifunctional carriers in advanced skincare science. The current state of research on the application of cyclodextrins in cosmeceutical formulations is evaluated, with particular focus on active ingredients commonly used in dermatological care, such as vitamins A and C, coenzyme Q10, kojic acid, arbutin, and UV filters. For each of these compounds, relevant in vitro, in vivo, and clinical studies are reviewed in order to assess how cyclodextrin complexation influences key parameters, including solubility, stability, controlled release, skin penetration, and the reduction in adverse reactions. In addition, the use of cyclodextrins in the treatment of dermatological conditions such as acne, psoriasis, and rosacea is examined, highlighting their potential value, particularly in combination with azelaic acid and salicylic acid, well-known agents used to manage these conditions. Beyond their advantages, the limitations and challenges that currently restrict broader implementation of cyclodextrins in cosmeceuticals are also discussed, including cost variability, solubility constraints with certain substances, formulation incompatibilities, and regulatory considerations. Future perspectives are explored, particularly the development of novel modified and amphiphilic cyclodextrins, as well as their integration into nanotechnology-based systems and into intelligent, personalized skincare. Full article

Background: Gastric cancer remains a leading cause of cancer-related deaths worldwide. Although significant progress has been made in clinical diagnosis and treatment, the molecular mechanisms underlying gastric cancer have not yet been fully elucidated. To address this, this study employs a multi-omics approach to systematically analyze the molecular characteristics of gastric cancer. Methods: This case–control study enrolled 218 GC patients and 218 healthy controls, and adopted a multi-omics strategy combining inductively coupled plasma mass spectrometry (ICP-MS), element-related genome-wide association study (eGWAS), and untargeted metabolomics to explore the element-gene-metabolite regulatory axis in GC. Results: A total of nine plasma differential elements associated with gastric cancer were identified, with a combined diagnostic accuracy of 0.918. Specifically, elements such as Fe, Co, and Li showed significant correlations with 63 genes involved in key signaling pathways, including MAPK, SMAD, and Wnt. Genome-wide association studies (GWAS) revealed that gastric cancer-related genes were significantly enriched in cancer-associated pathways and signaling cascades such as Rap1. Metabolomic analysis further demonstrated that 20 elements in the gastric cancer cohort correlated with 94 metabolites, predominantly enriched in pyrimidine and glutathione metabolism pathways. Conclusions: These nine plasma differential elements showed high combined diagnostic efficacy and were associated with genes and metabolites enriched in cancer-related signaling, metabolic reprogramming, and DNA damage response pathways. Together, these findings suggest potential multi-level associations among plasma elemental alterations, genetic variation, and metabolic dysregulation in GC, providing candidate circulating biomarkers and mechanistic clues for future investigation. Full article

The mechanical properties, intergranular corrosion, and exfoliation corrosion of T6- and T8-aged Al–1.1Cu–2.4Li–X alloys (high Li content, Cu/Li ratio ≈ 0.46) were systematically examined. Microstructural analysis shows that T8 aging produces a higher number density of T1 (Al2CuLi) precipitates and a higher number density, as well as a finer and more uniform distribution of δ′ (Al3Li) compared to T6 aging. This results in yield and tensile strengths that are 90 MPa and 40 MPa higher, respectively, for the T8 condition. In terms of corrosion, the T6-aged alloy displays intergranular corrosion depths of 176.5–210.1 μm, while the T8-aged alloy exhibits much shallower depths of 67.2–95.8 μm. The inferior resistance to intergranular and exfoliation corrosion in the T6 temper is attributed to precipitation-free zones (PFZs) and secondary-phase particles at grain boundaries. Increasing T6’s aging time reduces the PFZ width and thus improves corrosion resistance. Conversely, prolonged T8 aging causes a gradual decrease in corrosion potential and an increase in corrosion current density, linked to a higher density of T1 precipitates, which signifies increased corrosion susceptibility. These findings provide a reference for understanding corrosion mechanisms and improving the corrosion resistance of high-Li Al–Li alloys. Full article

Brewery wastewater is a high-strength industrial effluent containing substantial organic, suspended, and colloidal fractions and therefore requires multistage treatment. This study evaluated sedimentation, prefiltration, coagulation, ceramic membrane filtration, and reverse osmosis (RO) polishing for improving the quality of actual brewery wastewater under short-term laboratory conditions. The acidic wastewater had chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), and dissolved organic carbon (DOC) values of 48,230 mg O₂/L, 34,160 mg O₂/L, and 6492 mg C/L, respectively. Three configurations were investigated: mechanical treatment; PIX 113 coagulation followed by ceramic microfiltration (MF), ultrafiltration (UF), or fine UF; and an integrated UF-RO system. Performance was assessed using contaminant removal, relative permeate flux (J/J₀), particle size analysis, dynamic light scattering, and zeta potential. Sedimentation and prefiltration provided limited treatment, whereas coagulation effectively destabilized colloids; a PIX 113 dosage of 2 mL/L was selected as a favorable compromise among the tested dosages. Among the ceramic membrane-based trains, the train ending with the 1 kDa membrane produced the highest-quality permeate, with overall COD, BOD₅, and DOC removals of 78.2%, 88.7%, and 49.8%, respectively. The tested sedimentation–prefiltration–coagulation-50 kDa UF-RO train achieved the highest overall removals: 97.9% COD, 98.6% BOD₅, and 94.0% DOC. The overall removals of chloride and nitrate ions in this train were 92.5% and 68.5%, respectively. The results indicate that coagulation-assisted ceramic membrane filtration followed by RO can substantially improve permeate quality. The novelty of the work lies in linking coagulation-assisted ceramic membrane filtration and RO polishing with particle-size and electrokinetic characterization, thereby clarifying the role of each treatment barrier and identifying an effective laboratory-scale train for upgrading high-strength brewery wastewater. Full article

MicroRNA (miRNA) dysregulation is a crucial pathogenic factor that extensively participates in the occurrence and progression of various human diseases, especially cancers. Identifying unknown miRNA–disease connections is essential for understanding disease pathogenesis and improving clinical treatment strategies. Traditional biological experiments are often expensive and technically restricted, so computational prediction has become a widely used auxiliary research tool. In this study, we develop a novel predictive model called Attribute-Aware Message Passing Graph Convolutional Network (AAMPGCN) to identify potential miRNA–disease associations. The advantage of AAMPGCN lies in integrating miRNA and disease attribute information into the message-passing process: it partitions the miRNA–disease heterogeneous graph that incorporates miRNA functional similarity, disease semantic similarity, and Gaussian interaction kernel similarity into attribute-homogeneous subgraphs, while restricting high-order message propagation within each subgraph. This mechanism effectively filters cross-attribute noise, preserves the discriminability of miRNA and disease embeddings during deep convolution, and is thus well-adapted to miRNA–disease heterogeneous networks. The AAMPGCN prioritizes miRNA and disease attributes, aggregating messages specifically among nodes with similar attribute characteristics that are relevant to miRNA–disease interactions. Experimental results show that the AAMPGCN model achieves AUC and AUPR values of 94.06 and 93.52 on the HMDD2.0 dataset, which outperforms existing methods. The proposed AAMPGCN provides a new and effective method for miRNA–disease association prediction, and also offers theoretical support for the research on disease molecular mechanisms and the screening of clinical therapeutic targets. Full article

Background/Objectives: Repetitive transcranial magnetic stimulation (rTMS) has been increasingly investigated as an adjunctive intervention in neurorehabilitation, particularly for motor recovery after stroke. However, conventional rTMS protocols remain limited by variability in target localization, inter-individual anatomical differences, lesion-related network reorganization, and limited reproducibility across treatment sessions. Neuronavigated repetitive transcranial magnetic stimulation (nrTMS) integrates structural neuroimaging with real-time coil tracking, enabling more precise and reproducible stimulation of patient-specific cortical targets. This approach may be especially relevant in patients with focal brain lesions, postoperative anatomical distortion, or functionally reorganized networks. Methods: This narrative review summarizes the biological rationale, current clinical evidence, practical workflow, and limitations of nrTMS in neurorehabilitation, with particular attention to the distinction between conventional rTMS and neuronavigated protocols. Results: The strongest evidence for rTMS-based rehabilitation remains in post-stroke motor recovery, although most studies have used non-navigated protocols. In contrast, postoperative neuro-oncological rehabilitation represents a clinically relevant but still investigational context for nrTMS, as preoperative functional mapping, postoperative deficits, and early rehabilitation can be integrated within a patient-specific therapeutic pathway. Early studies suggest feasibility when stimulation is combined with structured physiotherapy; however, the available evidence is based on small and heterogeneous cohorts, and clinically meaningful superiority over conventional rTMS or standard rehabilitation has not yet been established. Data in traumatic brain injury, multiple sclerosis, ataxias, and neurodegenerative disorders are still preliminary and heterogeneous. Conclusions: Neuronavigation should not be interpreted as an independent therapeutic breakthrough, but rather as a precision-enhancing component of rTMS-based rehabilitation. Its main potential value lies in improving targeting accuracy, session-to-session reproducibility, and integration with individualized neuroimaging and rehabilitation goals. Accordingly, nrTMS should currently be considered a precision-enhancing and hypothesis-generating framework rather than an established rehabilitation standard. Full article

Biochar water treatment stands at a decisive crossroads, where the promise of large-scale application meets the reality of laboratory trial-and-error. This study contends that the fundamental bottleneck to progress lies in the field’s persistent reliance on empirical experimentation and black-box data models. We therefore propose a conceptual research paradigm that aims to deeply integrate physics-informed machine learning (PIML) with life cycle assessment (LCA). The novelty of this framework lies in three dimensions: (i) the bidirectional information flow between PIML and LCA, enabling simultaneous material design and sustainability assessment; (ii) the embedding of fundamental physical laws (adsorption isotherms, kinetics, thermodynamics) directly into learning architectures to ensure physical consistency; and (iii) the extension to a water–energy–soil–food closed-loop system for holistic resource management. While the individual components of this framework have been demonstrated in other domains, their integrated application to biochar water treatment remains in early development stages. This perspective outlines potential pathways and identifies critical research gaps that must be addressed to realize this vision. The focus is on charting future directions rather than reporting established achievements. Through critical evaluation, we assess current integrated models under small-sample constraints and explicitly pinpoint explainability and cross-scale generalization as two indispensable gaps that industrial deployment demands be bridged. Building on this foundation, we outline a blueprint for a closed-loop system coupling water, energy, soil, and food, and present a three-phase roadmap for future research. This study seeks to offer a constructive perspective with the hope of supporting biochar technology toward more sustainable implementation. Full article

This work develops a locally adaptive isogeometric phase-field framework for two-dimensional quasi-static brittle fracture using cubic $C^1$ polynomial splines over hierarchical T-meshes (PHT-splines). The aim is not to introduce a new crack-density functional or a new degradation law, but to provide a consistent variational-to-discrete setting in which second- and fourth-order phase-field regularizations can be treated within the same locally refined spline framework. Starting from the energy functional, the formulation is carried through admissible weak forms to the corresponding discrete residual equations. The second-order formulation is posed in an $H^1(\mathrm{\Omega })$ setting, whereas the fourth-order model is treated directly through a Laplacian-based $H^2(\mathrm{\Omega })$-compatible approximation without auxiliary phase-field variables. The formulation combines history-field irreversibility, the tension–compression split of the elastic energy, and an adopted cubic degradation law with $s={10}^{-4}$, whose nonlinear tangent contribution is handled by a Taylor-stabilized staggered Newton scheme. Numerical tests on a single-edge notched tensile benchmark and a notched perforated beam under asymmetric bending show that local refinement captures the fracture zone while maintaining critical-load deviations of about $0.8\%$ and $0.3\%$, respectively, relative to the reference critical loads used for the two benchmark problems. The contribution therefore lies in the coherent coupling of higher-order regularity, admissible weak forms, local PHT-spline adaptivity, and stabilized nonlinear degradation treatment within a spline-based phase-field fracture implementation. Full article