Search Results (3,065)

Computed tomography (CT) images are stored at a 12-bit depth. However, many deep learning libraries and pre-trained models are designed for 8-bit images, requiring an intermediate compression step before restoring the original 12-bit physical range. This process causes information loss and can compromise image reliability. This study investigated the impact of two CT resampling methods (8-bit compression; 12-bit decompression) on dose calculation and image quality. Ten total marrow and lymphoid irradiation patients were selected. CT scans were resampled using linear and non-linear look-up tables (l_LUT/nl_LUT). Original and resampled CTs were evaluated considering: (i) Hounsfield unit (HU) root mean squared error (RMSE); (ii) dose-volume histogram (DVH) statistics for target volume and several organs; (iii) 3D gamma passing rate (GPR) with a 1%/1.25 mm criterion; (iv) lymph nodes contouring and diagnostic quality (scale 1–5). The RMSE for l_LUT vs. nl_LUT was 7 ± 1 vs. 10 ± 1 HU. Maximum differences in DVH statistics were 0.4%, with a 3D-GPR = 100% for all cases. CTs resampled with l_LUT exhibited evident brain pixelation (score = 1), whereas nl_LUT matched the original CT quality (score = 4). Both LUTs were acceptable for lymph nodes delineation. The nl_LUT optimized the CT resampling process, providing a more efficient method for possible deep learning applications in synthetic CT generation. Full article

Wheat is one of the world’s most important crops, cultivated across diverse ecogeographic zones on more than ~245 million hectares annually. Classified by vernalization requirement into spring, facultative, or winter types, the latter typically achieves higher yields due to its extended growing season, reaching ~18 t ha⁻¹ and 9–10 t ha⁻¹ as a national average for Western European countries such as Germany, France, and England, compared with the global average of barely above 3 t ha⁻¹. Despite this potential, winter wheat is largely confined to regions with relatively mild winters, while vast temperate zones with extremely cold winters rely on spring wheat. Breeding has traditionally targeted the vernalization–C-repeat Binding Factor (VRN–CBF) pathway, which confers tolerance to moderately severe winters but is insufficient for extreme cold, implying the need for additional layers of adaptive mechanisms. Using multiple genotypic datasets, we identified genomic regions underlying low-temperature tolerance. Genome- and chromosome-wide scans revealed strong differentiation on chromosome 5A (526–703 Mb), overlapping the VRN–CBF loci. SNP-level FST analysis between spring and winter cultivars highlighted the VRN-A1 (586–588 Mb) region and a locus spanning 549 and 559 Mb on chromosome 6A. Further comparisons between winter accessions adapted to extreme cold (≤−12 °C) and mild winters (>0 °C) revealed a differentiated region on chromosome 3B (561–564 Mb) harbouring two key genes conferring CBF-independent cold tolerance, TRAESCS3B02G351100 and TRAESCS3B02G354000, encoding diacylglycerol kinase1 (DGK1) and peroxidase 56 (PRX56), respectively. These findings underscore alternative pathways in shaping cold adaptation, highlighting the need to broaden breeding strategies for extreme environments. We further detected a pronounced haplotype divergence between Chinese and U.S. winter cultivars reflecting distinct breeding trajectories; notably, China, where ~90% of wheat production is of the winter type, achieves national yields >5 t ha⁻¹, compared with ~3 t ha⁻¹ in the United States, where over 70% of production is winter wheat. This contrast suggests that the haplotypes enriched in Chinese winter cultivars could represent valuable resources for enhancing winter wheat performance in other regions with comparable environments. Full article

This study presents the results of an investigation into the carbothermic synthesis of silicon carbide (SiC) from microsilica and petroleum coke. The research combines thermodynamic modeling with experimental validation conducted in an ore-thermal furnace. Thermodynamic calculations were performed using the HSC Chemistry 10 software package to evaluate the influence of temperature and the SiO₂/C ratio on phase formation and the conditions of SiC synthesis. The results show that the synthesis process exhibits a strong dependence on temperature and is largely governed by the carbon balance of the charge. At an SiO₂/C ratio of 1, the system is carbon-rich, which promotes effective reduction of silicon dioxide. However, at elevated temperatures, these conditions intensify gas-phase reactions and lead to increased silicon losses. The most favorable conditions for silicon carbide formation were achieved at an SiO₂/C ratio of 1.5, which is close to the stoichiometric value. This conclusion is confirmed by the maximum degree of SiC recovery obtained under experimental conditions. In contrast, at an SiO₂/C ratio of 2, carbon deficiency results in incomplete reduction in SiO₂ and a lower yield of the target product. The phase composition of the synthesized samples was analyzed by X-ray diffraction, revealing β-SiC as the dominant crystalline phase. The morphology and structure of the materials were examined using scanning electron microscopy, which confirmed the formation of SiC particles and aggregates with characteristic features. A comparison between calculated and experimental results demonstrates that thermodynamic modeling adequately describes the main trends of the process and can be effectively applied to optimize SiC synthesis conditions during the processing of technogenic silica-containing waste. Full article

This review highlights the rapidly evolving role of artificial intelligence (AI) in transforming lung cancer care, with a specific focus on its integrated applications across diagnosis, biomarker discovery, and drug development. The novelty of this work lies in its holistic examination of how AI bridges these traditionally separate domains, from radiology and pathology to genomics and clinical trials, to create a more cohesive and personalized oncology pipeline. We detail how AI algorithms significantly enhance early detection by improving the accuracy and efficiency of pulmonary nodule characterization on computed tomography scans and enable precise cancer subtyping via computational pathology. In biomarker discovery, AI-driven analysis of radiomic features and genomic data facilitates the non-invasive prediction of tumor genotype, PD-L1 expression, and immunotherapy response, moving beyond invasive tissue biopsies. Furthermore, AI is accelerating the drug development lifecycle by identifying novel therapeutic targets and optimizing patient selection for clinical trials. The review also explores AI’s critical role in personalizing treatment regimens, including predicting outcomes for radiotherapy and immunotherapy, thereby tailoring therapy to individual patient profiles. We critically address the challenges of clinical translation, including model interpretability, data standardization, and ethical considerations, which are pivotal for real-world implementation. Finally, we contend that the future of lung cancer management hinges on robust, multi-institutional validation of AI tools and the development of trustworthy, explainable systems. Full article

This study aims to establish diagnostic reference levels (DRLs) for common pediatric nuclear medicine (NM) procedures performed within the Dubai Health sector. The established DRLs will serve as a benchmark for pediatric NM practice, supporting standardized healthcare delivery and guiding ongoing quality improvement and internal audit activities. Patient dose survey data were collected from the solo NM center within the Dubai Health sector. The study included common scintigraphy procedures using gamma cameras and the hybrid positron emission tomography with computed tomography (PET/CT) procedures. Scintigraphy procedures include the dynamic and static renal scans, and ocular eye scans. The hybrid PET/CT procedures entail tumor/infection and neuroendocrine scans. Patient demographics, administered activities, CT doses, and study description were recorded. Both weight bands of <5, 5–<15, 15–<30, 30–<50, and 50–<80 kg, and age bands of <1, 1–<5, 5–<10, and 10–<15 years were considered. Statistical analysis was performed to determine the 25th percentile, median and 75th percentile of the dose distribution. The median value was used to establish the DRLs for the Dubai Health sector. The analyses revealed significant variation in the administered activities across the different pediatric NM procedures. The proposed DRLs for various pediatric NM procedures for the weight band 15–<30 kg are as follows: renal dynamic 98.4 MBq, renal static 96.2 MBq, ocular eyes 18.5 MBq, tumor/infection 155 MBq, and neuroendocrine 80 MBq. This work provides the first pediatric NM DRLs for the Dubai Health sector, offering a key reference for developing the local DRLs for the Emirate of Dubai. The findings indicate that achieving meaningful dose optimization will require systematic revision of existing imaging protocols, with targeted parameter adjustments informed by continuous dose monitoring and benchmarking to enhance patient safety and overall diagnostic quality. Full article

This paper explores the economic feasibility of Additive Manufacturing (AM) for producing prismatic battery cell housings, specifically targeting small production runs. A comprehensive cost analysis was conducted to compare AM with Tool-Based Manufacturing (TM) processes for battery cell caps and cans. This analysis takes various factors, including tooling, materials, machinery, labor, and part finishing costs, into account. The study demonstrates that AM offers significant economic advantages over TM for single-digit and low double-digit batch sizes, primarily due to the absence of expensive tooling costs associated with TM. AM-produced battery cell cans continue to be cost-effective even for medium-sized production runs. Additionally, AM allows for the integration of sensors directly within battery cell caps, providing enhanced real-time monitoring capabilities–an important benefit for development purposes. Further analysis, assuming a best-case scenario, indicated potential cost savings through the use of increased layer heights and faster recoating and scanning speeds, which enhances the economic appeal of AM. Overall, the findings suggest that AM is particularly beneficial for the production of battery cell housings in low- to mid-volume ranges, emphasizing its strategic importance for flexible manufacturing requirements and research-intensive applications. Full article

In this study, a targeted SSR (Simple Sequence Repeat) marker resource was developed based on genes and protein families associated with pathogen- and pest-related defense–resistance mechanisms in Camellia sinensis. Forty-one genes and protein families reported to show upregulation, increased expression, or functional validation under disease and pest stress were selected, and the corresponding 195 loci were mapped onto the Camellia sinensis cv. Shuchazao genome. SSR screening within gene bodies and gene-flanking regions (±5 kb) identified 5197 SSR loci. Putative QTL hotspot regions were defined using locus-based sliding-window analysis, Z-score calculations, and permutation tests, yielding 633 SSRs filtered at the 99% and 95% significance thresholds. Proteome-wide scans based on conserved amino acid motifs identified multiple loci within the WRKY, NAC, LRR, PRX, and CHI families, and Random Forest analysis was used to prioritize SSRs within these families. Finally, 386 SSR primer sets were designed and evaluated by in silico PCR across six tea genomes. Of these, 245 primers produced amplicons in more than one genome, and 124 exhibited polymorphic information content values greater than 0.500. Overall, the developed SSR panels represent a biologically contextualized and experimentally transferable marker resource targeting defense–resistance-associated genic and gene-proximal regions. Full article

Resource-limited settings continue to face challenges in the identification of COVID-19, bacterial pneumonia, viral pneumonia, and normal lung conditions because of the overlap of CT appearance and inter-observer variability. We justify a hybrid architecture of deep learning which combines hand-designed descriptors (Histogram of Oriented Gradients, Local Binary Patterns) and a 20-layer Convolutional Neural Network with dual self-attention. Handcrafted features were then trained with Support Vector Machines, and ensemble averaging was used to integrate the results with the CNN. The confidence level of 0.7 was used to mark suspicious cases to be reviewed manually. On a balanced dataset of 14,000 chest CT scans (3500 per class), the model was trained and cross-validated five-fold on a patient-wise basis. It had 97.43% test accuracy and a macro F1-score of 0.97, which was statistically significant compared to standalone CNN (92.0%), ResNet-50 (90.0%), multiscale CNN (94.5%), and ensemble CNN (96.0%). A further 2–3% enhancement was added by the self-attention module that targets the diagnostically salient lung regions. The predictions that were below the confidence limit amounted to only 5 percent, which indicated reliability and clinical usefulness. The framework provides an interpretable and scalable method of diagnosing multiclass lung disease, especially applicable to be deployed in healthcare settings with limited resources. The further development of the work will involve the multi-center validation, optimization of the model, and greater interpretability to be used in the real world. Full article

Background/Objectives: Maresin-1 (MaR1), a specialized pro-resolving mediator (SPM) derived from omega-3 fatty acids, has demonstrated potent anti-inflammatory and pro-resolving properties. However, its effects on depression-like behaviors and the associated dynamics of neuroinflammation, particularly in the context of chronic stress, are not yet fully understood. This study aimed to investigate the therapeutic potential of MaR1 in a chronic unpredictable stress (CUS) model and to monitor its dynamic effects on neuroimmune activity using longitudinal in vivo imaging. Methods: Adolescent male C57BL/6J mice were subjected to a 5-week CUS protocol. Mice exhibiting stable anhedonia were randomized to receive intraperitoneal injections of either MaR1 (5 µg/kg) or vehicle every other day for 4 weeks. During this period, CUS procedures were maintained. Depression-like behaviors were assessed using the sucrose preference test (SPT), tail suspension test (TST), and open field test (OFT). Dynamic changes in neuroinflammation were monitored via longitudinal [18F]DPA-714 positron emission tomography (PET) scans at baseline and after 2 and 4 weeks of treatment. Ex vivo analyses included immunofluorescence quantification of hippocampal microglia (ionized calcium-binding adaptor molecule 1, Iba1), astrocytes (glial fibrillary acidic protein, GFAP), and 18 kDa translocator protein (TSPO) co-expression, alongside quantitative polymerase chain reaction (qPCR) and Western blotting for inflammatory markers (IL-1β, IL-4, TSPO). Results: MaR1 treatment selectively alleviated depression-like behaviors, significantly reversing CUS-induced anhedonia in the SPT and improving locomotor activity, while its effect on despair-like behavior (TST) was not statistically significant. Longitudinal PET imaging revealed a biphasic neuroimmune response, characterized by an initial increase in [18F]DPA-714 standardized uptake value (SUV) at 2 weeks, followed by a return toward baseline at 4 weeks. Histologically, MaR1 reversed CUS-induced hippocampal microglial loss, resulting in a rebound of microglial numbers, and normalized astrocytic activation. At the molecular level, MaR1 dynamically modulated cytokine expression, culminating in a significant upregulation of the pro-resolving marker IL-4 and TSPO at 4 weeks. Conclusions: These findings indicate that Maresin-1 treatment is associated with behavioral improvement and dynamic modulation of glial activity and TSPO PET signals in the hippocampus. This study highlights the value of TSPO PET imaging for monitoring dynamic glial changes during therapeutic intervention and provides supportive evidence for targeting neuroimmune pathways in depression. Full article

Cancer is one of the leading causes of mortality worldwide, with breast and colon cancers being among the most common neoplasms in men and women, respectively. Despite significant advancements in treatment, there is a pressing need to enhance specificity and reduce systemic side effects. Importantly, a distinctive feature of cancer cells is their acidic extracellular environment, which profoundly influences cancer progression. In this study, we evaluated the anticancer activity of a pH-sensitive nanocomposite based on silver nanoparticles and pegylated carboxymethyl chitosan (AgNPs-CMC-PEG) in breast cancer (MCF-7) and colon cancer (HCT 116) cell lines. To achieve this, we synthesized and characterized the nanocomposite using UV-Vis spectroscopy, Dynamic Light Scattering (DLS), Fourier-Transform Infrared Spectroscopy (FT-IR), and Scanning Electron Microscopy (STEM-in-SEM). Furthermore, we assessed cytotoxic effects, apoptosis, and reactive oxygen species (ROS) generation using MTT, DAPI, and H2DCFDA assays. Additionally, we analyzed the expression of DNA methyltransferases (DNMT3a) and histone acetyltransferases (MYST4, GCN5) at the mRNA level using RT-qPCR, along with the acetylation and methylation of H3K9ac and H3K9me2 through Western blot analysis. The synthesized nanocomposite demonstrated an average hydrodynamic diameter of approximately 175.4 nm. In contrast, STEM-in-SEM analyses revealed well-dispersed nanoparticles with an average core size of about 14 nm. Additionally, Fourier-transform infrared (FTIR) spectroscopy verified the successful surface functionalization of the nanocomposite with polyethylene glycol (PEG), indicating effective conjugation and structural stability. The nanocomposite exhibited a pH and concentration dependent cytotoxic effect, with enhanced activity observed at an acidic pH 6.5 and at concentrations of 150 µg/ml, 75 µg/ml, and 37.5 µg/ml for both cell lines. Notably, the nanocomposite preferentially induced apoptosis accompanied by ROS generation. Moreover, expression analysis revealed a decrease in H3K9me2 and H3K9ac in both cell lines, with a more pronounced effect in MCF-7 at an acidic pH. Furthermore, the expression of DNMT3a at the mRNA level significantly decreased, particularly at acidic pH. Regarding histone acetyltransferases, GCN5 expression decreased in the HCT 116 line, while MYST4 expression increased in the MCF-7 line. These findings demonstrate that the AgNPs-CMC-PEG nanocomposite has therapeutic potential as a pH-responsive nanocomposite, capable of inducing significant cytotoxic effects and altering epigenetic markers, particularly under the acidic conditions of the tumor microenvironment. Overall, this study highlights the advantages of utilizing pH-sensitive materials in cancer therapy, paving the way for more effective and targeted treatment strategies. Full article

The management of non-small cell lung cancer (NSCLC), including lung adenocarcinomas (LUAD), has been revolutionized with the advent of precision oncology. While advanced cancers often carry poor prognosis, those harboring specific molecular alterations sensitive to targeted therapy (notably tyrosine kinase inhibitor [TKI]) have experienced improved response to treatment and survival outcomes. Consequently, detecting these alterations through molecular screening panel has become standard in several countries, although this necessitates high-quality tissue sampling to inform optimal therapeutic decisions. Oncologic imaging occupies a pivotal role in the routine care of patients, in particular at diagnosis, with a wealth of information gathered but underutilized, as medical imaging reflects the disease in its entirety at a given time point. Moreover, recent advancements in imaging quantitative analysis, including radiomics and artificial intelligence, could aid in better integration and understanding of this information that has been overlooked for years. Several radiological phenotypes (or radiophenotypes) have been linked to tumor genomic alterations, both in standard radiology relying on semantic features and metastatic patterns, and in radiomics. Ultimately, understanding the relationships between imaging and targetable genomic alterations via accurate imaging biomarkers could complement ambiguous tumor or liquid biopsy, detect emerging new alterations, and even substitute biopsy through ‘virtual biopsy’. During the past decade, there has been a surge in research focused on radiogenomic assessment of NSCLC and especially LUAD. However, due to the low prevalence of many oncogenic drivers, the scientific literature may lack clarity or present conflicting findings. This comprehensive review aims to provide a summary of the current state of this research, offering insights into the complex interplay between imaging and genomic alterations in lung adenocarcinoma. Full article

The carved lacquer horse-hoof-shaped box excavated from Yulin, Shaanxi Province, represents a typical example of lacquerware preservation in the arid environment of northern China, exhibiting multiple deterioration phenomena, including substrate deformation, lacquer film peeling, and pigment fading. To systematically analyze its structural composition and craftsmanship features, this study employed multiple analytical techniques, including ultra-depth microscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), confocal laser micro-Raman spectroscopy (Raman), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). Based on these analyses, a targeted conservation protocol was developed. Results revealed that the carved lacquer horse-hoof-shaped box has a wooden substrate structure, with the lacquer ash layer composed of mixed materials, including calcium carbonate (CaCO₃), quartz (SiO₂), and hydroxyapatite (Ca₁₀(PO₄)₆(OH)₂). The lacquer film layer contains Chinese lacquer and plant oils, with cinnabar applied as surface decoration. Based on these findings, a stratified reinforcement conservation strategy was proposed: under dynamic monitoring with optical fiber sensors and three-dimensional scanning, the wooden substrate was reinforced with moisture-curable polyurethane (MCPU), the lacquer ash layer was strengthened with acrylic emulsion (Primal AC33), aged areas were restored with nano calcium hydroxide (Ca(OH)₂) aqueous dispersion, and polyethylene glycol (PEG 400) poultice application was implemented to restore the flexibility of the lacquer film. This research significantly enhanced the integrity and stability of the carved lacquer horse-hoof-shaped box, providing practical evidence and technical references for the scientific conservation of lacquerware excavated from arid regions of northern China. Full article

Historically, systemic therapy has been the primary treatment for metastatic prostate cancer (MPC), with radiotherapy and surgery reserved for palliation. The recent literature suggests that adding local therapy (i.e., radiotherapy or surgery) to systemic therapy may improve survival for MPC patients with low metastatic burden (LMB). While some evidence supports the use of early intervention with local therapy targeting both the primary tumor and limited metastatic sites, the definition of LMB disease requires further clarification. Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scans play a vital role in staging MPC because they offer superior sensitivity and specificity compared to conventional imaging. PSMA PET thus improves patient selection and helps direct treatment planning. Local therapy in MPC can be separated into the treatment of primary and metastatic tumors. Furthermore, treatment of both the primary tumor and metastases can be managed using either radiotherapy or surgical intervention. Studies exploring the use of local therapy for both the primary tumor and oligometastatic sites have demonstrated promising clinical outcomes in patients with LMB or oligometastatic disease. This review provides a detailed description of the current optimal management of patients with metastatic prostate cancer with limited disease. Full article

Tyrosinase, encoded by Tyr, is a key rate-limiting enzyme in melanin biosynthesis. Knockout of Tyr results in a distinct albino phenotype, making it a widely used target for evaluating gene-editing efficiency. Here, we found that the tyrosinase-deficient skin melanophore lineage of Xenopus tropicalis (X. tropicalis) tadpoles shows strong autofluorescence under the GFP filter, which may interfere with in vivo fluorescence imaging. Through spectral scanning analysis, we characterized the emission spectrum of the autofluorescence under commonly used excitation wavelengths for fluorescent proteins. Based on this, we established a reference protocol for identifying and excluding such interference in Tyr-targeted knockin studies. Furthermore, knockout of the GTP cyclohydrolase 2 gene (Gch2) using CRISPR-Cas9 significantly reduced the fluorescence intensity induced by tyrosinase deficiency, indicating an essential role of the enzyme and its mediated pterine biosynthesis in the generation of the autofluorescence. This study systematically characterized these fluorescent mutant melanophores in X. tropicalis tadpoles, providing a practical basis for avoiding fluorescent interference in experimental science and a new perspective on pigment cell development and evolution. Full article

In this study, semi-interpenetrating polymer network (semi-IPN) hydrogels based on methacrylated dextran and native inulin were designed as biodegradable carriers for the colon-specific delivery of uracil as a model antitumor compound. The hydrogels were synthesized via free-radical polymerization, using diethylene glycol diacrylate (DEGDA) as a crosslinking agent at varying concentrations (5, 7.5, and 10 wt%), and their structural, thermal, and biological properties were systematically evaluated. Fourier transform infrared spectroscopy (FTIR) confirmed successful crosslinking and physical incorporation of uracil through hydrogen bonding. Concurrently, differential scanning calorimetry (DSC) revealed an increase in glass transition temperature (T_g) with increasing crosslinking density (149, 153, and 156 °C, respectively). Swelling studies demonstrated relaxation-controlled, first-order swelling kinetics under physiological conditions (pH 7.4, 37 °C) and high gel fraction values (84.75, 91.34, and 94.90%, respectively), indicating stable network formation. SEM analysis revealed that the hydrogel morphology strongly depended on crosslinking density and drug incorporation, with increasing crosslinker content leading to a more compact and wrinkled structure. Uracil loading further modified the microstructure, promoting the formation of discrete crystalline domains within the semi-IPN hydrogels, indicative of physical drug entrapment. All formulations exhibited high encapsulation efficiencies (>86%), which increased with increasing crosslinker content, consistent with the observed gel fraction values. Simulated in vitro gastrointestinal digestion showed negligible drug release under gastric conditions and controlled release in the intestinal phase, primarily governed by crosslinking density. Antimicrobial assessment against Escherichia coli and Staphylococcus epidermidis, used as an initial or indirect indicator of cytotoxic potential, revealed no inhibitory activity, suggesting low biological reactivity at the screening level. Overall, the results indicate that DEGDA-crosslinked dextran/inulin semi-interpenetrating (semi-IPN) hydrogels represent promising carriers for colon-targeted antitumor drug delivery. Full article