Search Results (12,091)

Flammulina filiformis is one of the most important commercially cultivated species, and the assessment of strain quality is of paramount importance. The analysis measured physiological-biochemical indicators, morphological indicators, combined non-targeted metabolomics, and microbiomics in F. filiformis strains of different ages. The results indicate that, as the culture age increased, ergosterol content and catalase (CAT) activity declined continuously. The morphology of the mycelia gradually deteriorated, and yield continued to decrease. The relative content of lipids and lipid-like molecules decreased overall, while the proportion of organic acids and their derivatives increased; the oxidative phosphorylation pathway continued to be significantly enriched. The richness and diversity of the mycelium-associated bacterial community in the mycelia decreased significantly, and the microbial community structure changed. The community was dominated by the genus Acinetobacter from 15 to 60 days, whereas the genus Serratia was predominant in 90 days group. Correlation analysis revealed that the core differential signature metabolites MG 14:1_0:0_0:0, aspartic acid-threonine-aspartamide, and nicotinamide adenine dinucleotide (NAD⁺) were significantly correlated with multiple physiological-biochemical indicators. N-arachidonyl glycine showed significant correlations with 21 core bacterial genera; the dominant genera Acinetobacter and Serratia exhibited strong correlations with membrane homeostasis, core indicators of oxidative damage, and signature metabolites. These results indicate that the mycelial vitality of F. filiformis remains good within the first 15 days of cultivation, with significant ageing occurring after 60 days. These findings provide a theoretical basis for optimizing fungal strain preservation techniques and regulating mycelial ageing. Full article

X-band rainfall radar systems offer advantages such as high spatial resolution, flexible deployment options, and strong near-surface detection capabilities. However, due to the short electromagnetic wavelength in this band, the radar base data are highly susceptible to multiple coupled factors—including clutter from mountain vegetation, tall buildings, and other terrain features; electromagnetic interference from surrounding radio-frequency equipment; beam obstruction caused by complex topography; and attenuation of rainfall intensity along the precipitation path—resulting in pronounced distortion of raw echoes. This distortion significantly hinders the accuracy of quantitative precipitation estimation in mountainous regions and makes it difficult to meet the operational requirements for precise mountain torrent early warning systems. To address the problem, this study utilizes real-time observational data from field deployments of X-band rainfall radars in mountainous regions to construct a comprehensive, progressive quality control system comprising: refined removal of terrain clutter; electromagnetic interference pre-suppression; dynamic beam obstruction correction; and adaptive rainfall intensity attenuation correction. The terrain clutter suppression algorithm is optimized in this study, and an adaptive beam-blockage compensation algorithm based on the terrain-blockage fraction is further adopted. However, beam-blockage correction exhibits limited improvement in this case, which is likely attributed to the complementary observational coverage provided by higher-elevation radar scans. The echo-missing regions are dynamically corrected according to the terrain-blockage coverage ratio at different elevation angles and azimuths to realize differentiated compensation corresponding to blockage severity so as to effectively restore the true echo intensity obscured by terrain. Furthermore, considering the prominent rain-induced attenuation of radar electromagnetic waves along the propagation path, a dynamic attenuation correction scheme based on path-integrated reflectivity is introduced. The precipitation attenuation coefficient is dynamically calculated point by point from the variation characteristics of real-time echo intensity along the beam path to compensate echo loss, which addresses the limitation that fixed correction parameters cannot adapt to attenuation differences under variable rainfall intensities. Based on the Z-R power-law relationship, the radar echo-derived rainfall is inverted, using hourly measurements from dense ground-based rain gauges as the reference values, and precision is verified using the MB and RMSE—industry-standard meteorological evaluation metrics. Experimental results demonstrate that clutter suppression dominates RMSE reduction (7.37 to 1.91 mm/h). Beam blockage correction shows negligible impacts on RMSE and MB. Attenuation correction delivers marginal MB improvement (−0.52 to −0.51 mm/h) with no measurable RMSE response. After full-chain quality-control optimization, the aggregate RMSE between radar-derived rainfall and gauge observations is 1.91 mm h⁻¹, representing an approximately 74% reduction compared with the raw dataset (from 7.37 to 1.91 mm h⁻¹). Elevated RMSE values of 4.2–5.0 mm h⁻¹ are observed for rainfall intensities between 5 and 10 mm h⁻¹. In addition, the discrepancy between radar and gauge estimates grows as rainfall intensity increases. As the distance between radar and rain gauge increases, radar QPE systematically underestimates light precipitation, while persistent underestimation occurs across all ranges for heavy rainfall. This study enhances the differentiated quality control framework for X-band radar systems in complex mountainous regions, effectively improves the observation quality of radar-derived base data, and provides data support and technical references for dynamic monitoring of flash floods in mountainous river basins. Full article

Predicting air pollutant dispersion in complex urban environments traditionally relies on computationally intensive fluid dynamics simulations or empirical Gaussian models. This study explores whether topological network properties—originally derived from fluid flow concepts in pipe networks—can directly account for spatial concentration variations in an urban canopy. Using wind-tunnel measurement data from a representative urban setup, we construct a directed flow graph based on local velocity fields and compute key topological metrics, including node degree, betweenness centrality, and topological distances. A multiplicative regression model is then evaluated to assess the predictive capacity of these metrics against measured concentration distributions across multiple emission locations. Results show that graph-derived and geometric predictors capture a substantial portion of concentration variance (R² up to 0.83, mean 0.57), with geographic distance, node degree, and betweenness centrality emerging as the dominant drivers. Because geographic distance is not itself a topological metric, the reported explanatory power is attributed to the combined set of geometric and graph-derived predictors rather than to graph topology alone. These findings provide preliminary evidence that graph-derived and geometric descriptors of a sensor-space proximity graph are statistically associated with concentration in this dataset. Because geographic distance is a geometric rather than topological predictor, the explanatory power is attributed to the combined predictor set, not to graph topology alone. The results are source-dependent and should not be interpreted as an operational replacement for CFD or as direct design guidance. Further work with distance-only baselines and independent validation is needed. Full article

Fuel cell electric buses (FCEBs) are widely recognized as a promising low-carbon solution for long-distance public transportation. However, their adoption in intercity coach services remains limited, particularly at the demonstration stage, where multiple technological, economic, policy, and infrastructure factors interact. Prior research has predominantly examined these factors in isolation, with limited attention to their interrelationships. To address this gap, the present study proposes a hybrid multi-criteria decision-making (MCDM) framework that integrates a modified Delphi-based expert screening method, interval type-2 fuzzy sets (IT2FS), and the DEMATEL-based Analytic Network Process (DANP). Using the STEEP framework, twenty candidate criteria derived from the literature were screened by ten experts and refined to fifteen criteria relevant to the Taiwanese intercity coach context. A second panel of twelve experts then assessed the perceived directional influence relationships among the retained criteria using linguistic judgments modeled with IT2FS, and DANP was applied to derive network-adjusted priority weights. Expert assessments indicate that policy stability and long-term commitment, financial incentives and subsidy schemes, and infrastructure investment benefits received the highest priority weights in the current Taiwanese context. The perceived influence structure further indicates that the policy and technology dimensions primarily function as net influencing dimensions, whereas the economic and social dimensions are more strongly positioned as net-receiving dimensions within the expert-judgment network. These findings should be interpreted as context-specific, expert-based assessments rather than objectively established or statistically causal determinants of FCEB adoption. The results provide a structured decision-support perspective for governments, coach operators, and hydrogen supply-chain stakeholders when evaluating priorities for FCEB deployment in Taiwan and comparable demonstration-stage contexts. Full article

Transient pressure redistribution in ring gas pipelines is governed by both withdrawal intensity and spatial configuration, which determine circumferential flow redistribution and the location of the hydraulic junction. This study develops an analytical framework for transient pressure dynamics and hydraulic-junction localization in ring pipelines with multiple discrete withdrawals. A closed-form Fourier-series solution is derived and numerically verified against an independently implemented finite-difference model, demonstrating close analytical–numerical agreement. The hydraulic-junction coordinate is identified from the transient pressure-extremum condition, while a dimensionless localization factor is introduced to characterize its position relative to the geometric midpoint. Two contrasting ring configurations reveal distinct behaviors: For the investigated 30 km configuration, the hydraulic junction remains localized near the geometric midpoint under the considered proportional-withdrawal scenarios. In the second, increasing withdrawal loading causes progressive upstream migration toward a withdrawal-controlled limiting location. A steady balanced flow-reversal criterion provides a physical interpretation of the limiting junction position without being extended to globally unbalanced transient states. The results further show that efficient distributed withdrawal requires consideration of both pressure retention and hydraulic-junction behavior. The proposed framework provides a mathematically interpretable basis for assessing transient hydraulic states and withdrawal strategies in ring gas pipelines. Full article

Brain aging is a major risk factor for neurodegenerative disorders and is associated with a progressive loss of neuronal homeostasis. Rather than resulting from a single pathological event, brain aging involves coordinated changes across multiple biological processes, including neuroinflammation, proteostasis impairment, mitochondrial dysfunction, neurotransmission deficit, cellular senescence, gut microbiota dysbiosis, extracellular vesicle dysregulation, nutrient-sensing disturbances, and metabolic drift. These processes interact across molecular, cellular, and systemic levels and may progressively increase neuronal vulnerability to neurodegenerative pathology. Age-related biological alterations may increase susceptibility to Alzheimer’s disease and Parkinson’s disease. Disease-associated proteins, including amyloid-β, tau, and α-synuclein, may interact with age-related inflammation, metabolic dysfunction, and loss of proteostasis. This review examines the evidence supporting these mechanisms, their interactions, and their relevance to normal brain aging, Alzheimer’s disease, and Parkinson’s disease. Because much of the current mechanistic evidence derives from animal and cellular models, further longitudinal and human studies are needed to provide a more complete understanding of how these mechanisms operate during human brain aging and neurodegenerative diseases. Full article

Marine macroalgae constitutes an important source of structurally diverse secondary metabolites with significant pharmaceutical potential. In the present study, an untargeted liquid chromatography–mass spectrometry (LC-MS)-based metabolomic approach was integrated with biological screening to investigate the relationship between metabolite composition and antiproliferative activity in eight Mediterranean macroalgal species. Crude organic extracts were evaluated against the human colorectal cancer cell lines HT-29 and HCT-116, while the most active extracts were further investigated by flow cytometry to explore their cellular effects. Comparative metabolomic analysis revealed marked interspecific differences, with the brown algae Dictyota dichotoma and Rugulopteryx okamurae exhibiting metabolomes enriched in lipophilic diterpenoids and showing the highest cytotoxic activity. Although the bioactive compounds were not isolated, the antiproliferative effects were associated with diterpene-rich metabolite profiles containing tentatively annotated compounds such as dictyodial- and dilkamural-related diterpenoids tentatively. D. dichotoma displayed potent activity against both HT-29 and HCT-116 cells (GI₅₀ ≈ 4.5–5 μg mL⁻¹), whereas R. okamurae was markedly more active against HT-29 than HCT-116 cells, demonstrating that tumour genetic background substantially influences cellular susceptibility to macroalgal extracts and highlighting the importance of evaluating multiple cancer cell models during preliminary screening. Flow cytometry demonstrated increased intracellular reactive oxygen species (ROS), reduced metabolic viability, and decreased cell concentration following treatment with the most active extracts, whereas Annexin V/propidium iodide staining showed no detectable increase in apoptotic cell populations. These findings suggest that oxidative stress-associated metabolic impairment, rather than classical apoptosis, contributes to the observed antiproliferative activity. Overall, this study demonstrates the value of integrating untargeted metabolomics with comparative biological screening to identify promising marine macroalgae and metabolite classes for future bioassay-guided isolation and development of marine-derived anticancer agents. Full article

Background: Polycystic ovary syndrome (PCOS) is frequently associated with insulin resistance and dyslipidemia. Evidence regarding the metabolic effects of probiotics in PCOS remains inconsistent. This secondary analysis evaluated whether multispecies probiotic supplementation influenced glucose homeostasis, insulin resistance, and the lipid profile in women with PCOS. Methods: Data were derived from a 12-week randomized, double-blind, placebo-controlled study in which 50 women with PCOS were assigned to receive either a nine-strain probiotic (1.0 × 10⁹ CFU/day) or placebo. Fasting and 120 min glucose and insulin concentrations, HOMA-IR, total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides were assessed at baseline and follow-up. Treatment effects were evaluated using analysis of covariance adjusted for baseline values. The main analysis was based on participants with available follow-up data, and an intention-to-treat sensitivity analysis including all 50 randomized participants was performed using multiple imputation for missing follow-up measurements. Results: Forty-three participants were included in the complete-case analysis (probiotic, n = 19; placebo, n = 24); seven did not complete follow-up (six in the probiotic group, one in the placebo group). No statistically significant between-group differences were detected for glucose homeostasis, HOMA-IR, or lipid profile. The intention-to-treat sensitivity analysis yielded findings consistent with the complete-case analysis. Conclusions: Twelve weeks of multispecies probiotic supplementation did not result in statistically significant improvements in glucose metabolism, insulin resistance, or lipid profile compared with placebo. Given the relatively small sample size and limited precision of some estimates, clinically relevant effects cannot be excluded. Larger randomized controlled trials are warranted. Full article

Background: Pulmonary vein stenosis (PVS) is a progressive disease characterized by neointimal hyperplasia with poor outcomes. Clinical observations show that adjunctive therapy with imatinib mesylate and sirolimus is associated with improved survival and reduced rates of reintervention. In this study, we aimed to investigate the cellular mechanisms underlying PVS development and progression and to elucidate how these targeted therapies modulate these processes. Methods: We retrospectively analyzed cardiac catheterization and computed tomography, and lung scan data from three patients with PVS to estimate wall shear stress (WSS) at multiple time points. Tissue specimens resected during anatomical repair surgery were analyzed for tissue composition and fibrosis using hematoxylin and eosin staining, Masson’s trichrome staining, and flow cytometric analysis of endothelial cell (ECs) and fibroblast markers to determine endothelial-to-mesenchymal transition (EndMT). The safety and efficacy of imatinib mesylate and sirolimus were evaluated in healthy and PVS-derived ECs using cellular viability and proliferation assays, and by assessing fibrotic marker expression indicative of EndMT. Results: Patients exhibited severely elevated WSS estimates at multiple time points throughout disease progression. Disproportionate fibrotic remodeling driven by ECs transitioning into mesenchymal cells through EndMT was the cellular substrate of resected tissue in PVS. Targeted therapy with clinically relevant concentrations of imatinib mesylate and sirolimus was safe and significantly inhibited fibroproliferation and EndMT. At follow-up, all patients were alive and free of surgical and stent-based reintervention after anatomic repair surgery and adjunctive imatinib mesylate and sirolimus therapy. Conclusions: Fibroproliferative ECs undergoing EndMT are likely the cellular substrate underlying PVS development and progression. A multimodal approach consisting of anatomically focused surgical repair with adjunctive imatinib mesylate and sirolimus therapy may attenuate fibroproliferative remodeling. Full article

Near-infrared spectroscopy (NIRS) was applied to measure the moisture content (MC) of newly fallen deciduous leaves from four broadleaf tree species, namely Zelkova serrata (Keyaki), Quercus serrata (Konara), Quercus acutissima (Kunugi), and Fagus crenata (Buna), collected in 2016 and 2017. Leaves were sampled immediately after abscission, an ecologically important condition that has received direct measurement, providing initial MC data for litter decomposition research. Two multivariate calibration approaches were compared, partial least squares regression (PLSR) and random forest regression (RFR), each applied with and without spectral preprocessing (moving average, multiplicative scatter correction, second-order Norris Gap derivative, and mean centring), and both evaluated by leave-one-out cross-validation (LOOCV) for direct comparability. PLSR with preprocessing achieved R²cv = 0.75–0.86 and an RPD (the ratio of performance to deviation) = 2.01–2.70 across species and years; RFR without preprocessing yielded R²cv = 0.47–0.75 (RPD = 1.39–2.03), while RFR with preprocessing improved markedly to R²cv = 0.78–0.88 (RPD = 2.13–2.94). Wavelength importance, assessed by variable importance in projection (VIP) for PLSR under both preprocessing conditions, showed that preprocessed models concentrated importance sharply in the water combination band near 1900 nm, whereas non-preprocessed models distributed importance more broadly but still situated their single strongest wavelength within this same band in six of seven datasets. RFR feature importance shifted from the water absorption region (without preprocessing) toward the cellulose/lignin band near 2100–2300 nm (with preprocessing); a model-independent correlation analysis indicated that this shift corresponds, in most datasets, to a genuine change in the underlying MC–spectrum relationship rather than solely reflecting how RFR handles collinear wavelengths. Independent, bidirectional year-to-year prediction (2016-calibrated models tested on 2017 data, and vice versa) showed that the high within-year accuracy summarised above did not reliably transfer across years—most severely for Z. serrata, for which cross-year prediction failed in both directions—indicating that annual recalibration is advisable for operational use of this method. Full article

This work addresses the synthesis of constant-modulus (CM) radar waveforms whose range-Doppler behavior approximates a prescribed profile in the presence of multiple interference sources. Since the interference power at the matched-filter output amounts to an average of the slow-time ambiguity function (STAF) of the transmitted code evaluated at the interference range-Doppler bins, the design task is essentially one of shaping the STAF. The resulting formulation is high-dimensional and non-convex because of the CM requirement, which hampers conventional optimization tools in Euclidean space. To circumvent this difficulty, we recast the design as an unconstrained problem on a Riemannian manifold and tackle it directly with a trust-region scheme defined on that manifold. The Riemannian gradient and Hessian of the quartic cost are derived in closed form, the trust-region subproblem is solved by a truncated conjugate gradient procedure, and the computational complexity of each iteration is analyzed. Then an enhanced solver called Adaptive regularization with cubics (ARC) is developed, improving the performance based on the step-acceptance mechanism. Numerical results under two interference scenarios show that, compared with the existing method, the proposed approach produces deeper nulls at the interference locations while requiring less computation time. Full article

Cholesterol is increasingly recognized as a regulator of hematolymphoid malignancy biology, by influencing tumor proliferation, immune function, and therapeutic response. This review summarizes current evidence regarding the relationship between cholesterol metabolism and hematologic malignancies, integrating mechanistic studies with retrospective and emerging prospective clinical data. Cholesterol contributes to immune dysfunction by promoting CD8⁺ T-cell exhaustion within the tumor microenvironment. Clinical studies have reported associations between serum lipid profiles, statin use, and outcomes across multiple hematologic malignancies, although findings remain heterogeneous and are largely derived from retrospective analyses. Preclinical studies demonstrate that statins disrupt cholesterol-dependent signaling and inhibit tumor growth, whereas retrospective clinical studies generally support the safety of statin use and suggest possible therapeutic benefits in some lymphoma subtypes. Clinically, low high-density lipoprotein cholesterol (HDL) has been associated with advanced disease across multiple hematological malignancies. However, prospective, interventional data remain limited. Collectively, this review highlights the possible relationship between cholesterol metabolism and hematologic malignancy biology, with a focus on potential impacts on disease related outcomes. Full article

Background/Objectives: Patient-reported outcomes (PROs) capture important dimensions of inflammatory bowel disease (IBD), including fatigue, questionnaire-defined mood-related symptom burden, pain, sleep disturbance, bowel urgency and impaired health-related quality of life, yet these outcomes are incompletely explained by conventional inflammatory markers. Metabolite-related measures may capture host–microbe co-metabolism relevant to patient-reported burden. Methods: This critical narrative review synthesized adult IBD literature linking metabolite-related measures with patient-reported symptom domains. PubMed/MEDLINE, Embase.com, Scopus and Web of Science Core Collection were searched through 11 June 2026; purposive source selection supported critical narrative synthesis rather than exhaustive enumeration. Results: Our structured search identified only a small number of human studies, mainly in fatigue and questionnaire-defined mood-related symptom burden. Studies included serum, plasma or fecal metabolite measurements, exploratory multi-omics, inferred microbial metabolic functions and interventional pathway testing. Fatigue was associated with serum amino-acid-related changes, plasma lipidomic alterations and fecal untargeted metabolomic and microbiome differences; inferred microbial functional modules were also reported. Mood-related burden was associated with serum and fecal metabolomic changes, bile-acid profiles and microbiota-derived functional signals. Within our search and eligibility criteria, no human studies paired measured metabolites with sleep-, pain- or urgency-specific patient-reported outcome measures (PROMs); evidence for multidimensional clusters was insufficient. Conclusions: We did not identify a metabolite-related signature for the assessment of patient-reported burden that had undergone both analytical and clinical validation; findings support candidate associations and exploratory signatures. Future work requires longitudinal, phenotype-stratified cohorts, validated PROMs, rigorous metabolomics methodology, causal modeling, inflammatory and dietary metadata, multiple-testing control and independent validation for clinical translation. Full article

Background/Objectives: Sarcopenia contributes to frailty and functional decline in older adults; however, effective adjunctive strategies remain limited. Heat-killed Bifidobacterium breve B-3 (B-3HK), a postbiotic, has shown muscle-related effects in preclinical studies; however, clinical evidence in patients with established sarcopenia is scarce. This pilot trial aimed to evaluate these clinical effects. Methods: In this 24-week randomized, double-blind, placebo-controlled trial, adults aged 50–89 years with Asian Working Group for Sarcopenia (AWGS) 2019-defined sarcopenia received B-3HK (2 × 10¹⁰ cells/day) or placebo daily. The primary outcome was the change in knee extension strength at week 24. Secondary outcomes included body composition measured using bioelectrical impedance analysis (BIA), dual-energy X-ray absorptiometry (DXA), physical performance, Eating Assessment Tool-10 (EAT-10), serum biomarkers, gut microbiota, and safety. Secondary outcomes were exploratory with nominal p-values and no adjustment for multiple comparisons. Results: Fifty participants were randomized, and 49 were included in the full analysis set. Compared with placebo, B-3HK did not significantly improve knee extension strength. Exploratory analyses showed between-group differences favoring B-3HK in the BIA-derived skeletal muscle mass index, limb muscle mass, EAT-10 score, and serum insulin-like growth factor-1 and 25-hydroxyvitamin D levels. These differences were primarily driven by the attenuation of the decline in the placebo group and were not corroborated by DXA-derived indices or functional outcomes. The gut microbiota composition did not differ between groups. No serious adverse events were observed. Conclusions: B-3HK did not improve muscle strength in patients with sarcopenia. Exploratory analyses identified nominal between-group differences in body composition and endocrine outcomes; however, these findings were unadjusted for multiplicity and should be regarded as hypothesis-generating rather than confirmatory evidence of efficacy. These data may help inform the design of future adequately powered trials, but confirmation is required before any therapeutic benefit can be inferred. Full article

Hyperspectral image classification is an important task in remote sensing image interpretation. However, existing Mamba-based methods remain limited in exploiting shallow frequency information, preserving neighborhood continuity during spatial serialization, and protecting center-pixel semantics. To address these limitations, we propose a frequency-enhanced and center-pixel-guided dual-branch Mamba network (FCD-Mamba). First, the Frequency-Enhanced Multiscale Convolution Module (FEMSCM) applies serial Fourier filtering to enhance multiscale spatial features and calibrates spectral features using low-, middle-, and high-frequency DCT energy descriptors derived from the original spectrum of the center pixel. Second, the Spatial Center-Adaptive Mamba (SCA-Mamba) employs two orthogonal Hilbert curves and their reverse traversals to preserve spatial neighborhood continuity, while adaptively aggregating multi-path features using center and global representations. The Spectral Center-Preserving Mamba (SCP-Mamba) constructs center-preserved and global spectral sequences and models their complementary spectral dependencies through bidirectional scanning. Finally, the Center-Pixel-Guided Residual Fusion Module (CGRFM) exploits center-to-global discrepancies to calibrate dual-branch features and introduces auxiliary supervision to maintain the discriminability of each branch. Experiments on multiple public hyperspectral datasets demonstrate that FCD-Mamba achieves stable and competitive classification performance, validating the effectiveness of its constituent modules. Full article