Search Results (3,956)

High-performance electromagnetic wave absorption materials are desperately needed due to the growing serious electromagnetic interference and pollution issues brought on by the quick growth of modern electronic technology and wireless communication. This work uses the organic–inorganic hybrid perovskite MAPbBr_xI_3−x as a model system to address the problem of restricted loss mechanisms and the challenges in changing the absorption bandwidth of single-component wave-absorbing materials. It achieves systematic tuning of electromagnetic wave absorption performance, especially within the effective working frequency spectrum, through accurate halogen site engineering. According to the study, MAPbI₃ (MPI), MAPbBr_1.5I_1.5 (MPIB), and MAPbBr₃ (MPB), which were synthesized using the anti-solvent approach, all demonstrated exceptional microwave absorption capability, with maximum reflection loss values exceeding −37 dB, among which MPB achieves a remarkable value of −42.41 dB at 16.60 GHz. More significantly, this work shows a distinct structure-property relationship between the effective absorption peak frequency range of this series of materials and their band structure: the strongest absorption peak shows a regular blue shift as the material bandgap widens and the bromine content rises. This finding suggests that focused tailoring of the operating frequency band in wave-absorbing materials can be achieved by manipulating the band structure of perovskites by varying the halogen concentration. In addition to confirming the significant application potential of organic–inorganic hybrid perovskites in the field of microwave absorption, this study offers a novel research perspective and material template for precisely and programmably controlling the absorption frequency band of wave-absorbing materials based on their basic electronic structures. Full article

Grassland fire is one of the major disasters threatening regional ecological security. Its occurrence, development, and spread are closely related to the spatial distribution and coverage of surface vegetation and snow cover across grassland areas. As the primary combustible fuel source, higher vegetation coverage increases fuel load and continuity, thereby directly determining grassland fire danger levels and accelerating fire spread velocity. In contrast, snow cover imposes an indirect regulatory effect on the spatiotemporal pattern of fire danger factors: it lowers surface temperature, raises near-surface humidity, and restricts the germination and growth of herbaceous vegetation in cold seasons, which effectively reduces available combustible materials and weakens regional fire hazard conditions. Therefore, accurately obtaining the coverage status of vegetation (direct combustible fuel factor) and snow cover (indirect fire-regulating factor) in complex grassland scenarios is the essential premise for reliable grassland fire danger monitoring, early warning, disaster prevention and control, and regional ecological management. Aiming at the practical problems in complex grassland scenarios (such as undulating terrain, uneven vegetation growth, large differences in snow depth, and complex lighting conditions), including difficulty in extracting vegetation and snow-covered areas, blurred and confusing boundaries, and low accuracy in coverage calculation, which seriously restrict the technical bottleneck of precise monitoring of grassland fire danger factors, this study takes near-ground images collected by grassland fire danger factor monitoring stations as the core data source, and proposes an improved UNet image segmentation model combined with image segmentation technology and deep learning methods to realize precise extraction of vegetation and snow-covered areas and efficient calculation of coverage in complex scenarios. To improve the model’s feature extraction ability, boundary localization accuracy, and reduce model parameters and computational overhead, the CBAM-ASPP (Convolutional Block Attention Module—Atrous Spatial Pyramid Pooling) module is integrated at the end of the encoding path. The attention mechanism is used to enhance the weight of key features, and the multi-scale receptive field of atrous spatial pyramid pooling is utilized to strengthen the model’s ability to fuse features of vegetation and snow areas of different scales. The residual attention mechanism is introduced in the upsampling stage to effectively alleviate the gradient disappearance problem, improve the model’s ability to accurately locate the boundaries of vegetation and snow areas, and reduce segmentation errors. In the training process, a dynamically weighted hybrid loss function is adopted to dynamically adjust the weights according to the segmentation difficulty of different types of samples during training, optimize the model training effect, and improve the segmentation accuracy and generalization ability. Experiments were conducted using near-ground images of typical complex grassland scenarios as the dataset, and the performance of the proposed model was verified through comparative experiments. The results show that in the vegetation segmentation task, the mean Intersection over Union (mIoU) of the model reaches 84.70%, and the accuracy rate is 91.28%, which are 1.48 and 1.58 percentage points higher than those of the standard UNet model, respectively. In the snow segmentation task, the mIoU of the model reaches 92.74%, and the accuracy rate is 94.19%, which are 2.39 and 2.36 percentage points higher than those of the standard UNet model, respectively. At the same time, the number of parameters of the model is reduced by 12.85% compared with the standard UNet. Also, its comprehensive performance is significantly better than that of mainstream image segmentation models such as FCN, SegNet, and DeepLabv3+. Based on the standardized time-series data retrieved by the optimized segmentation model, this study further constructs a Grassland Fire Risk Index (GFRI) using the Analytic Hierarchy Process (AHP). Pearson correlation verification confirms that the GFRI has an extremely significant positive correlation with historical fire frequency, accurately capturing the seasonal dynamic rhythm of regional grassland fire occurrence. This integrated framework of intelligent segmentation and fire risk quantification provides a reliable technical solution for grassland fire factor monitoring, dynamic fire risk assessment, early warning systems, and refined regional ecological management. Full article

Background: Prostate cancer (PCa) is the most commonly diagnosed malignancy in men and a leading cause of cancer-related mortality worldwide. Growing evidence indicates that metabolic syndrome components, including obesity, insulin resistance, and hyperglycemia, contribute to PCa development, and progression to more aggressive form. At the same time, standard treatments such as androgen deprivation therapy (ADT) and androgen receptor pathway inhibitors (ARPIs) significantly improve oncologic outcomes but are associated with adverse metabolic effects, including increased fat mass, insulin resistance, and sarcopenia, potentially worsening patients’ overall metabolic profile and quality of life. Tumor progression in PCa is strongly driven by androgen receptor (AR) signaling, which is closely linked to cellular metabolic reprogramming, highlighting metabolism as a potential therapeutic target. Aim: The aim of this study was to evaluate and synthesize current evidence on the role of the ketogenic diet (KD) in PCa, with particular emphasis on its interaction with hormonal therapies, underlying metabolic and endocrine mechanisms, and its potential application as an adjunctive strategy in integrated oncologic care. Results: The KD, characterized by high fat and very low carbohydrate intake, induces a metabolic state of ketosis that reduces circulating glucose, insulin, and insulin-like growth factor 1 (IGF-1), potentially counteracting metabolic alterations associated with PCa and its treatments. Preclinical studies consistently demonstrate that carbohydrate restriction and KD can slow tumor growth, modulate key oncogenic pathways such as PI3K/AKT/mTOR, reduce systemic insulin signaling, and enhance survival in prostate cancer models. Additionally, emerging evidence suggests possible synergistic effects when KD is combined with standard therapies, including ADT and immunotherapy. Clinical data, although limited, indicate that low-carbohydrate dietary interventions may improve metabolic parameters and could delay biochemical progression, as suggested by increased prostate-specific antigen (PSA) doubling time. However, results across studies remain heterogeneous, and robust evidence on long-term oncologic outcomes is lacking. Conclusions: Overall, the KD represents a promising but still experimental strategy in PCa management, requiring careful nutritional supervision to avoid adverse effects such as unintended weight loss or sarcopenia. Further well-designed randomized clinical trials are needed to clarify its safety, efficacy, and role in routine clinical practice. Full article

Tomato yellow leaf curl virus (TYLCV) is one of the most destructive viral diseases causing severe yield losses in tomato production worldwide. This study investigated the effects of TYLCV infection on plant growth, photosynthetic physiological responses, and yield formation in greenhouse-grown tomatoes and evaluated the applicability of physiological trait-based yield prediction models. Two large-fruited tomato cultivars widely cultivated in Korean protected horticulture systems, ‘Daphnis’ and ‘Pink Star’, were inoculated with TYLCV under greenhouse conditions, and their growth, physiological responses, and yield characteristics were compared under high- and low-temperature growing seasons. TYLCV infection significantly reduced leaf length, leaf width, and leaf area index (LAI), and decreased both flowering truss number and fruit-setting truss number, resulting in reduced total yield. Physiological analyses showed that infected plants exhibited decreases in the OJIP fluorescence rise curve and Fv/Fm values, indicating a reduced photochemical efficiency in photosystem II. In addition, A–Ci response curve analysis revealed a reduction in net photosynthetic rate, suggesting limited carbon assimilation capacity. Total yield showed significant positive correlations with maximum net photosynthetic rate (Amax), Fv/Fm, and Ci300. GGE and GT biplot analyses further indicated that yield was closely associated with photosynthetic performance and canopy development traits. A multiple regression model based on physiological traits and virus infection status explained a significant proportion of the variation in tomato yield (R² = 0.367), indicating that TYLCV infection acts as a key limiting factor for yield reduction. These findings demonstrate that TYLCV infection restricts tomato productivity through reduced photosynthetic efficiency and altered canopy structure. Moreover, physiological trait-based yield prediction approaches may provide a useful framework for evaluating productivity under viral infection conditions and for developing data-driven crop management strategies in greenhouse tomato production systems. Full article

Yeasts have attracted increasing attention as potential alternatives to traditional bacterial probiotic strains due to their physiological resilience and functional versatility. However, the probiotic potential of yeast strains associated with Mexican cocoa bean fermentation remains largely unexplored. Therefore, this study aimed to conduct a preliminary screening of physiological and surface-related traits associated with probiotic functionality in four autochthonous Saccharomyces cerevisiae strains (YCTA5, YCTA9, YCTA14, and YCTA16), previously isolated from cocoa fermentation, using Saccharomyces boulardii (Jarrow Formulas^®) as a reference strain. Evaluated parameters included tolerance to temperature, pH, and bile salts; hemolytic activity; survival in vitro under gastrointestinal (GI) conditions; bile salt hydrolase activity; auto-aggregation; co-aggregation; hydrophobicity; and response to antifungal agents (fluconazole, ciclopirox, nystatin, and clotrimazole). All yeast strains grew at 37 °C and at pH 4–8 and showed no hemolytic activity. All strains exhibited high auto-aggregation (>70%) and hydrophobicity values ranging from 55 to 88%. In the coaggregation assay, strains YCTA9, YCTA14, and YCTA16 showed moderate interactions with Escherichia coli, Bacillus cereus, and Listeria innocua, with some combinations exceeding 50%. Nevertheless, none of the yeast strains exhibited measurable growth at pH 2; bile salt tolerance was limited to 0.1% Oxgall, and viability decreased by approximately 54–56% after simulated gastrointestinal transit. These findings indicate that although some strains exhibited promising surface-related properties, significant physiological constraints restrict their probiotic potential under the tested conditions. Therefore, the studied yeast strains should be regarded as preliminary candidates requiring further validation. This work provides a first-stage evaluation for identifying functional yeast strains from Mexican cocoa bean fermentation, serving as a basis for future in vitro and in vivo studies. Full article

Albic soil is a typical low-yield and problematic soil in Northeast China, which severely restricts crop growth and yield. Through a three-year field experiment in the albic soil of China, soil three-phase ratio, soil bulk density (soil BD), soil total porosity (soil TP), size distribution and water stability of soil aggregates, and changes in maize yield under crop rotations were studied. The following three treatments were established: conventional fertilization (T0), conventional fertilization + soil amendment (T1), and conventional fertilization + soil amendment + bio-organic fertilizer (T2). The results indicated that, compared with T0, the soil three-phase ratio deviation value (R) of T1 and T2 decreased by 23.69–74.94%, and the generalized soil structure index (GSSI) increased by 4.75–15.41% in soil layers of 0–20 cm and 20–40 cm. Soil BD and soil TP changed significantly in the soil layer of 20–40 cm under treatment of T2 (decreased 12.82% and increased 18.31%, respectively). Content of aggregates >0.25 mm (R_0.25) increased significantly in the soil layer of 0–20 cm, with increases of 13.71% and 23.21% under treatments of T1 and T2. The mean weight diameter (MWD) and geometric mean diameter (GMD) increased significantly under treatment of T2. Compared with T0, maize yield increased 13.45% and 18.85% under treatments of T1 and T2. Correlation analysis showed that maize yield was significantly correlated with soil physical indexes and aggregate stability. In summary, the combined application of soil amendments and bio-organic fertilizer is not only important for albic soil improvement, but also crucial to stabilize the crop production capacity in albic soil regions. Full article

Background: Micro- and nano-plastics (MNPs) are pervasive environmental contaminants that accumulate in various tissues, including the placenta. Experimental and clinical studies suggest potential cytotoxic, oxidative, and inflammatory effects that may lead to placental dysfunction and adverse obstetric outcomes. However, high-quality evidence on the clinical relevance of MNPs exposure during pregnancy remains scarce, underscoring the need for systematic evaluation of their impact on maternal and fetal health. Methods: The databases PubMed, ScienceDirect, CENTRAL, Embase, MDPI and Google Scholar were searched for studies published up to September 2025 investigating the relationship between MNPs and obstetric outcomes. Results: Twelve studies were included in this review, with half employing an observational design in human subjects and the other half using experimental studies in murine models. Although the available evidence is limited, there are studies reporting the association between MNPs exposure and premature birth, low birth weight, intrauterine growth restriction, and miscarriage. The most prevalent polymer detected was polyethylene, and the most commonly used MNPs detection techniques were Raman microspectroscopy, digital microscopy, Fourier Transform Infrared, and Pyrolysis gas chromatography-mass spectrometry. Conclusions: This systematic review summarizes current limited insights on the potential effects of MNPs on obstetric outcomes, highlighting possible associations with low gestational age, low birth weight, intrauterine growth restriction, and miscarriage. Findings do not allow causal inference due to heterogeneity in study design, exposure assessment, contamination control, and analytical methodologies. Full article

Meningiomas are the most common intracranial tumours, yet the molecular programs underlying WHO grade 1 subtypes—particularly transitional diploid tumours—remain insufficiently defined, partly due to the scarcity of biologically faithful in vitro models. Here, we report the establishment of a long-term, genetically unmanipulated grade 1 meningioma cell line (H8T-MG) maintained under normoxic conditions in serum-containing, growth-factor-supplemented medium, together with a complementary long-term primary culture (H16T-MG), and provide an integrated descriptive and functional characterization of these models, combined with a subtype-restricted transcriptomic analysis of diploid transitional grade 1 tumours versus normal meninges. Both cultures preserved the dual meso-neuroectodermal identity characteristic of meningothelial cells, exhibiting stable adherent growth, preserved contact inhibition and a coherent immunocytochemical profile, expressing vimentin, α-SMA, nestin, connexin-43 and cannabinoid receptors—reported here for the first time in grade 1 meningioma cultures—highlighting cannabinoid-related pathways as potential targets for exploration. Transcriptomic analysis identified 51 differentially expressed genes, revealing a coherent inflammatory–metabolic programme characterised by downregulation of IL-17 and TNF signalling, cytokines and chemokines (IL6, CCL2, SELE, S100A8), together with reduced extracellular-matrix and cytoskeletal activity. In parallel, the enrichment of arachidonic acid metabolism, cytochrome-P450/xenobiotic pathways, retinol metabolism and oxidative/epoxygenase activity indicated a lipid/xenobiotic-oriented metabolic shift distinctive of this subtype. Protein–protein interaction analysis identified four hub genes—ASPN, SELE, ACKR1 and ABCB1—integrating ECM remodelling, endothelial–immune modulation and xenobiotic transport, reinforcing an immune-attenuated, metabolically adapted tumour landscape. Collectively, these findings provide the first integrated in vitro and transcriptomic characterisation of diploid transitional meningiomas, underscore the value of biologically stable models for early-stage meningioma research, and support the value of histological and ploidy stratification in grade 1 meningioma biology. Full article

The restriction of antimicrobial growth promoters in livestock production has intensified the search for nutritional strategies that support intestinal health while modulating inflammatory processes. Chronic or dysregulated inflammation can impair gut function and animal performance, highlighting the need for functional feed additives. Brown macroalgae are rich in bioactive compounds with immunomodulatory properties, though their mechanisms remain incompletely understood. In this study, the anti-inflammatory and barrier-protective effects of aqueous extracts from Ascophyllum nodosum (AN) and Fucus vesiculosus (FV) were investigated using complementary in vitro and in vivo models. Extracts were prepared by aqueous solid–liquid extraction and tested in lipopolysaccharide (LPS)-stimulated RAW264.7 and THP-1 macrophages, HEK-Blue TLR4 reporter cells, and Drosophila melanogaster models of intestinal inflammation and infection. Both extracts significantly reduced LPS-induced nitric oxide production in RAW264.7 macrophages in a concentration-dependent manner. In THP-1 macrophages, AN and FV attenuated secretion of inflammatory mediators, including TNF-α, IL-6, IL-33, CXCL9, CXCL10, CXCL11, and CCL7. Reporter assays demonstrated selective inhibition of TLR4-dependent NF-κB activation. In Drosophila melanogaster, supplementation reduced intestinal barrier disruption, mortality, and infection-induced immune activation. Overall, AN and FV attenuate inflammatory signaling and protect intestinal integrity via TLR4-dependent NF-κB inhibition, supporting their potential as functional feed additives to enhance gut health and resilience in livestock. Full article

Pathologic pregnancies including recurrent pregnancy loss, stillbirth, early-onset pre-eclampsia and early-onset fetal growth restriction form a continuous spectrum throughout gestation and have attracted wide attention. Autoimmune disorders and associated acquired thrombophilia are key etiological factors. However, because of the complicated associations between various clinical manifestations, laboratory examinations and treatments, the management of pathologic pregnancies with autoimmune disorders and associated acquired thrombophilia are difficult. This viewpoint article presents a comprehensive full gestation management strategy emphasizing early identification and multidisciplinary management to improve pregnancy outcomes in these patients. Future research should focus on novel biomarkers, therapeutic methods and crosstalk mechanisms between autoimmune disorders and thrombophilia to optimize clinical strategies. Full article

In osteopetrotic mice with homozygous inactivating mutations in the colony stimulating factor 1 (Csf1^op/op) or its receptor (Csf1r^−/−) gene, teeth fail to erupt due to severe reduction in osteoclastogenesis. Dental abnormalities have been described in the unerupted teeth of these models, but it remains unclear whether these defects arise from direct roles of CSF1R in odontogenesis or indirectly from impaired bone remodeling associated with failed eruption. Here, we examined the spatiotemporal expression of CSF1R during tooth development and inhibited CSF1R pharmacologically in utero using PLX5622 during early stages of tooth morphogenesis. Teeth and surrounding bone were analyzed at embryonic and postnatal stages using histology and high-resolution micro-computed tomography. Embryonic CSF1R inhibition resulted in reproducible abnormalities in incisor and molar morphology that were evident before and after birth and were associated with loss of normal bone remodeling at the tooth–bone interface. In contrast, postnatal CSF1R inhibition did not affect the structure or continuous growth of adult incisors. Together, these findings demonstrate a temporally restricted, indirect role for CSF1R in odontogenesis that is independent of tooth eruption and associated with remodeling of the bony crypts surrounding developing teeth by CSF1R-dependent cells. Full article

Background: Infection and inflammation are key contributors to spontaneous preterm birth (PTB), but the relationship between genitourinary microbial colonization and placental inflammatory pathology across preterm subgroups remains unclear. Methods: In this case–control study, women with PTB were compared with gestational age-matched controls. Urine cultures, Mycoplasma/Ureaplasma screening, inflammatory markers, and placental histopathology were analyzed. Early (24–33 weeks) and late (34–36 weeks) preterm births were evaluated separately. Results: Clinical risk factors were more common in PTB cases (87.0% vs. 68.7%, p = 0.001), particularly PPROM and fetal growth restriction. Conventional urine culture positivity did not differ between groups. Mycoplasma/Ureaplasma colonization was more frequent in controls (41.2% vs. 15.4%, p < 0.001). Early PTB was strongly associated with placental inflammation, including higher rates of histological chorioamnionitis, composite inflammatory lesions, placental culture positivity, and elevated CRP compared with late PTB. Conclusions: Early PTB may represent a distinct infection-associated phenotype characterized by prominent placental inflammation, whereas late PTB demonstrates a weaker inflammatory profile. Full article

Objectives: The dependence of non-small cell lung cancer (NSCLC) on glutamine has made targeting glutamine metabolism an attractive therapeutic approach. Dietary interventions are increasingly considered as adjuvant cancer therapies. This study aims to explore the relationship between glutamine starvation and ferroptosis in NSCLC and to elucidate the underlying molecular mechanisms. Methods: The effects of glutamine starvation were evaluated both in A549 and H460 NSCLC cell lines and in vivo using xenograft models in SCID mice. Assessments included cell viability, migration, clonogenic capacity, and the expression of key proteins. To gain mechanistic insight, AMPK was either overexpressed or inhibited, and key markers of ferritinophagy (including ULK1, BECN1, NCOA4, and LC3-II/I) and ferroptosis (such as ACSL4, GPX4, and xCT) were analyzed. Results: Glutamine starvation markedly suppressed tumor growth in both in vitro and in vivo settings, while also reducing cell migration and clonogenicity in cultured cells. This intervention activated AMPK, as indicated by increases in both total and phosphorylated forms, and upregulated PDZD8 expression. Mechanistically, AMPK activation played a critical role in driving ferritinophagy and ferroptosis—manipulation of AMPK consistently altered key markers of these processes. Furthermore, AMPK levels influenced PDZD8 protein expression. Notably, overexpressing PDZD8 alone was sufficient in promoting both ferritinophagy and ferroptosis, indicating that PDZD8 acts as a critical downstream mediator of AMPK in this pathway. Conclusions: Our findings reveal that glutamine starvation triggers ferroptosis in NSCLC via activation of ferritinophagy, mediated by the AMPK/PDZD8 signaling pathway. These results support the potential of dietary glutamine restriction as a novel therapeutic approach for NSCLC. Full article

Optimizing plant density and vegetative growth duration is important for improving productivity in controlled-environment medicinal cannabis cultivation. Although both factors strongly influence canopy development and yield, their combined effects under modern high-intensity LED lighting, and particularly their consequences for cannabinoid uniformity across the canopy, remain insufficiently characterized. This study examined how planting density and vegetative duration influence plant growth, yield, and cannabinoid concentration in Cannabis sativa L. (strain ‘Fat Banana’) grown under controlled environment conditions, high-intensity LED lighting and precision fertigation. Two vegetative durations (10 and 28 days) were evaluated in separate but identical controlled-environment chambers under broad-spectrum high-intensity LED lighting and automated precision fertigation on rockwool substrate. The 10-day regime compared 8, 14 and 18 plants m⁻²; the 28-day regime compared 6, 8 and 10 plants m⁻². Each combination was replicated across two independent cultivation cycles, and because density levels differed between regimes, direct between-regime comparisons were restricted to the shared density of 8 plants m⁻². Extending the vegetative phase from 10 to 28 days increased plant height, stem diameter and internodal length. Area-based yield increased strongly with density, reaching 1091 g m⁻² at 18 plants m⁻² under the 10-day regime and 1009 g m⁻² at 10 plants m⁻² under the 28-day regime. Apical biomass exceeded basal biomass, but total THC concentration did not differ significantly among planting densities, vegetative durations or canopy positions. Higher planting densities combined with shorter vegetative periods can therefore increase area-based productivity while maintaining stable THC concentration under high-intensity LED cultivation. Full article

This paper studies subset construction in NP-complete problems from the perspective of structured exploration of combinatorial search spaces. Classical approaches rely on exhaustive enumeration of subsets, which leads to exponential growth in time and memory requirements. To address this limitation, we introduce an indexed framework based on the correspondence between a finite set and its associated index set. Within this framework, subsets are represented as ordered index sequences, allowing subset construction to be reformulated as a constraint-guided search process over index space. Candidate subsets are characterized by numerical descriptors derived from their indices (referred to as index certificates), which guide and filter the construction process. Subset generation is further organized through admissible index intervals that restrict feasible transitions and reduce the effective search space. The framework is based on an index-based representation and structured traversal of pairwise index combinations. Computational experiments on representative instances illustrate the behavior of the indexed construction procedure and indicate its efficiency relative to classical enumeration-based methods for small and medium-sized instances. The proposed approach provides a structured perspective on combinatorial search and offers a basis for further development of algorithms based on constrained exploration of subset structures. Full article