Search Results (6,368)

CAR-T cell therapy remains ineffective in most solid tumours because effector cells infiltrate poorly, undergo exhaustion, and face antigen escape within an immunosuppressive microenvironment. To address this, we developed a hybrid framework that combines a mechanistic spatiotemporal model with machine learning for limited individual-level mechanistic personalisation under data constraints. At its core, we employed a reaction–diffusion–chemotaxis model describing functional and exhausted CAR-T cells, antigen-positive and antigen-negative tumour subpopulations, a chemoattractant, an immunosuppressive factor, and hypoxia. Gradient boosting combined with nested cross-validation was used to recover model-consistent latent-parameter pseudo-labels generated by a limited inverse problem. Within this surrogate-target setting, parameters characterising the tumour microenvironment and CAR-T cell exhaustion were reproduced most robustly, whereas antigen escape and individualised initial conditions were substantially less well constrained. As an auxiliary reference point, we also considered a direct empirical baseline for binary clinical outcomes. This baseline indicated that the observed clinical features contained a more stable signal for disease control than for objective response. A favourable response was associated with high CAR-T cell infiltration and cytotoxic potency, whereas resistance was linked to exhaustion, antigen escape, and a suppressive microenvironment. Overall, the proposed approach should be interpreted as an internally validated, hypothesis-generating proof-of-concept platform for mapping clinical features to mechanistically interpretable surrogate latent targets, rather than as evidence for validated recovery of true patient-specific biological parameters. Full article

Prolonged hospitalization in cardiac patients is associated with increased morbidity and healthcare resource utilization, yet early biological factors linked to extended length of stay remain insufficiently defined. This study aimed to explore an integrative framework combining oral health parameters and targeted gut microbial markers to identify factors associated with prolonged hospitalization in cardiac patients. A comparative observational design was applied, including patients with short-term hospitalization (1–4 days) and prolonged hospitalization (≥25 days). Oral health status was evaluated using a standardized dental protocol at admission and longitudinally in patients with prolonged hospitalization. Targeted qRT-PCR-based quantification of selected gut bacterial markers was performed at admission and reassessed after one and two weeks. Temporal changes were calculated relative to baseline, and multivariate logistic regression models adjusted for age, sex, and major cardiac diagnoses were used to explore associations with prolonged hospitalization. Short-term hospitalized patients (n = 27) exhibited minimal oral health variation (+2%) and stable marker profiles. In contrast, patients with prolonged hospitalization (n = 30 for oral health; n = 18 for microbial markers) showed progressive changes over time. Oral health impairment increased by 3% after one week and 16% after two weeks, while targeted microbial marker variation showed modest directional changes. Integrative models combining oral health parameters and targeted microbial markers suggested potential complementary information alongside clinical variables, within the limits of an exploratory framework and limited sample size. These findings support the relevance of multidomain clinical and biological monitoring in the early identification of patients at risk for prolonged hospitalization. Full article

To explore the regulatory mechanisms of different vegetation types on soil crust grain-size characteristics in sandy lands, this study focused on five typical plant species (Haloxylon ammodendron, Artemisia ordosica, Nitraria tangutorum, Agriophyllum squarrosum, and Phragmites australis) in an artificial vegetation restoration area on the northeastern edge of the Ulan Buh Desert. Using laser granulometry and graphical methods, we systematically determined the soil particle size composition and parameters of the crust (Layer A) and sub-crust (Layer B) layers, and analyzed their correlations with plant morphological parameters (crown width, plant height, basal diameter). The results showed that (1) different vegetation types significantly increased the content of soil fine particulate matter (silt and clay), with fine sand accounting for 42.85% and silt accounting for 23.64%; (2) there are significant differences in the impact of different vegetation types on particle size parameters. The average particle size of soil crust under Phragmites australis is the smallest (1.91), and the sorting is the worst (standard deviation 2.01). Under the vegetation type of Nitraria tangutorum, the average particle size of the soil crust layer is the largest (5.25), and the fractal dimension is the highest (2.46). (3) The crown width, plant height, and basal diameter of vegetation are negatively correlated with mean particle size, kurtosis, and fractal dimension (r= −0.62 to −0.45), and positively correlated with standard deviation and skewness (r = 0.51 to 0.68). (4) The frequency curve indicates that vegetation types broaden the distribution range of soil particles, and Phragmites australis and Artemisia ordosica exhibit bimodal characteristics. This study reveals the impact of vegetation restoration on soil grain size parameters in arid regions. These findings provide actionable strategies for optimizing vegetation configuration in actual desert restoration projects, notably proposing a “herbs first, shrubs follow” approach that can be directly applied to enhance restoration efficiency. Full article

Background/Objectives: Persistent gastrointestinal (GI) symptoms following oncologic treatment represent a major unmet need in survivorship care, often managed symptomatically without addressing underlying biological mechanisms. This study aimed to evaluate the clinical efficacy and biological correlates of an artificial intelligence (AI)-guided, personalized microbiome modulation strategy in oncology patients with chronic secondary GI dysfunction. Methods: We conducted a prospective, single-arm, open-label validation study including 29 adult female oncology patients with persistent GI symptoms lasting ≥3 months. Participants underwent baseline multidimensional assessment integrating shotgun metagenomic sequencing, inflammatory and nutritional biomarkers, and clinical symptom profiling. An AI-guided platform generated individualized dietary, supplement, and lifestyle recommendations. Outcomes were assessed at baseline and after a 3-month intervention, focusing on intra-individual changes in stool frequency (primary endpoint), self-reported energy, microbiome composition, and metabolic biomarkers. Paired statistical analyses, correlation testing, and multivariable regression were performed. Results: After three months, stool frequency significantly decreased (4.69 ± 2.41 to 2.07 ± 1.19 episodes/day; p < 0.0001), accompanied by a marked increase in energy levels (4.00 ± 1.04 to 7.24 ± 1.12; p < 0.0001). Microbiome analysis revealed consistent enrichment of butyrate-producing and barrier-supportive taxa, including Faecalibacterium prausnitzii, Eubacterium rectale, Roseburia intestinalis, Akkermansia muciniphila, and Bifidobacterium longum. Butyrate-related biomarkers and vitamin-associated parameters (B-complex, vitamin D) showed significant improvement, while lactate levels normalized. Changes in Bifidobacterium longum were independently associated with stool frequency reduction (β = −0.783, p = 0.0082). Conclusions: AI-guided personalized microbiome modulation was associated with significant clinical improvement and biologically coherent microbial and metabolic shifts in oncology patients with persistent GI symptoms. These findings support a precision supportive-care approach targeting microbiome restoration, warranting further validation in randomized controlled trials. Full article

Introduction: It is accepted that nano- and micro-plastic (NMP) pollutants threaten ecosystems and human health by their bioaccumulation but, interestingly, their toxicity is shape-dependent. However, a clear definition of irregular NMPs, as the dominant shape in environmental and biological samples, is currently lacking when compared to spherical and fibrous NMPs. Objectives: This study quantifies morphometric descriptors in order to develop a standardized definition for irregular NMPs. Methods: Hyperspectral images of 34 spherical, 50 fibrous, and 45 irregular NMPs were collected from the literature. All shape-related features reported previously were analyzed using a machine learning model. Using five-fold cross-validation, a decision tree-based ensemble classifier with fixed parameters and Gini coefficient was established to screen key morphometric descriptors and their optimal interval ranges. The model was independently validated, enabling the accurate distinction of irregular NMPs from spherical and fibrous NMPs. Results: Three morphometric descriptors, including circularity, roundness, and perimeter-to-area ratio, were identified using five-fold cross-validation as optimal indicators for NMP shape classification. Optimal interval ranges for irregular NMPs were as follows: circularity (0.388 ± 0.004–0.768 ± 0.004), roundness (0.248 ± 0.01–0.752 ± 0.06) and perimeter-to-area ratio (>11.608 ± 1.39). This approach generated a 96.0% macro-averaged accuracy across these NMPs, with 100% precision and 89.0% recall. Conclusions: Irregular NMPs may be characterized using three morphometric descriptors, such as circularity, roundness, and perimeter-to-area ratio. The three-descriptor combination has highly accurate discrimination from spherical and fibrous NMPs. Full article

Functional antibody-dependent enhancement (ADE) represents a fundamental and context-dependent characteristic of antiviral antibody responses, reflecting the dual capacity of antibodies to mediate both the neutralization and Fc receptor-dependent enhancement of infection. In flavivirus research, this duality complicates the interpretation of conventional serological metrics and limits the reliability of single-parameter correlates of immunity, particularly in populations with complex exposure histories. Over the past decade, functional ADE assays have evolved from specialized mechanistic tools into integrated immune assessment platforms supporting translational immunology, vaccine evaluation, and population-level immune surveillance. These platforms incorporate Fcγ receptor-relevant target cell systems, standardized viral inputs, dilution series-based profiling, quantitative enhancement metrics, and structured quality control frameworks to enable reproducible, comparable, and context-aware functional measurements across cohorts and laboratories. A central concept emerging from these developments is that ADE reflects a dynamic functional immune state rather than an intrinsic property of antibodies or a direct indicator of pathological risk. Accordingly, functional ADE platforms support the contextual interpretation of antibody activity across physiologically relevant conditions, facilitating discrimination between transient functional enhancement and clinically meaningful immunological risk. By integrating functional ADE metrics with serological, cellular, and epidemiological data, these platforms provide a structured framework for interpreting immune profiles in vaccine evaluation, booster strategy design, and population-level risk stratification. This review synthesizes the development, standardization, and global dissemination of functional ADE platforms and discusses key principles governing biological relevance, analytical robustness, and inter-site transferability. Emerging directions integrating functional ADE profiling with systems immunology, immunogenomics, and computational modeling are highlighted as pathways toward predictive, decision-support-oriented frameworks. By positioning ADE platforms as immune assessment infrastructures rather than isolated assays, this review underscores their value for mechanistic inquiry, translational interpretation, and preparedness-oriented responses to emerging viral threats in the absence of definitive correlates of protection. Full article

Aedes aegypti transmits viruses to millions of people worldwide. Despite the availability of vaccines, control and monitoring of mosquitoes is mandatory, which in turn requires knowledge of microevolutionary population genetics. Genetic techniques permit the assessment of biological parameters directly linked to the epidemiological importance of the insect (polymorphism, migration, fitness). However, these techniques are costly to most health surveillance services. Even for research laboratories, genotyping and estimation of variability may be unfeasible and time consuming. We conjectured that the wing geometry of Ae. aegypti could serve as an alternative indicator of genetic variability in mosquitoes, as wing shape is a useful taxonomic marker determined by quantitative heritage. We investigated this conjecture by testing if wild Ae. aegypti populations with high genetic variability had higher wing morphological diversity than inbred colonised populations. Using wing geometric morphometrics and microsatellite DNA genotyping of some populational samples, we confirmed this conjecture. The morphological diversity index was partly correspondent with genetic variability indexes such as theta, gene diversity and alleles per locus. Our findings, although circumscribed to the populational samples studied, indicate that wing geometry may be used as a cheap and quick semi-quantitative proxy for genetic variability. Full article

Artisanal fisheries in Mexico frequently operate with limited data, lacking historical catch and effort series. In this context, the population status of the dogfish (Rhizoprionodon terraenovae) was evaluated for the first time in Priority Marine Regions 45–46 and the area of influence of the Wetland of International Importance Playa Tortuguera Rancho Nuevo, Tamaulipas, using methods based on size frequencies. Between November 2018 and February 2020, 541 artisanal fishing organisms were analyzed in La Barra del Tordo using FISAT II. The von Bertalanffy growth parameters for combined sexes were: L∞ = 105 cm, k = 0.59 years⁻¹, t₀ = −0.195 years. Total (Z), natural (M) and fishing (F) mortalities were 4.13, 0.467 and 3.22 years⁻¹, respectively. The average exploitation rate (E = F/Z) was 0.78 (95% CI: 0.745–0.805), exceeding the reference point of 0.5 (G) indicating severe overexploitation. The parameters showed biological consistency (Ø′ = 3.81; M/k = 0.79), and natural mortality was within the range reported for the species. This finding, in a priority region for conservation under the regime of the Conservation Sector of the Marine Ecological Management Program, shows the urgent need to implement fisheries management with an ecosystem approach that guarantees the sustainability of the fishery and the integrity of the coastal ecosystem. The study demonstrates that, even with limited data, it is possible to obtain robust estimates to inform management decisions in natural protected areas Full article

The accumulation of microplastics in aquatic ecosystems poses a significant threat to fish physiology and welfare. This study investigated the impact of exposure to virgin polystyrene microplastics (15 µm) on energy balance and welfare in goldfish (Carassius auratus). Fish were exposed for 14 days, and the effects were assessed through an integrated analysis of behavioral, metabolic, neuroendocrine, and physiological parameters. Microplastic exposure significantly reduces feed intake and feed anticipatory activity, indicating a potent anorexigenic effect. This effect was driven by neuroendocrine disruption, characterized by the downregulation of orexigenic neuropeptides (npy, agrp, hcrt) and the upregulation of anorexigenic signaling (pomca, cartpt, lepa). Simultaneously, exposed fish exhibited increased oxygen consumption, suggesting elevated metabolic demands. These factors converged to impaired growth and reduced hepatosomatic index, suggesting altered energy allocation. Furthermore, microplastic exposure induced anxiety-like responses and increased plasma cortisol levels, confirming the activation of the physiological stress response. Overall, these findings demonstrate that microplastics disrupt energy homeostasis and trigger behavioral shifts that ultimately compromise fish welfare and the biological resilience of aquatic species. Full article

Objectives: To evaluate the effectiveness and durability of matrix-associated autologous chondrocyte implantation with periosteal flap (pMACI) in treating knee cartilage defects using clinical scores and MRI evaluations. Methods: Data were collected from 37 knees of 17 patients, with a mean follow-up of 5 years (range: 0.1–20 years). Clinical outcomes were assessed using the Lysholm Knee Scoring Scale (LKS) and Knee Injury and Osteoarthritis Outcome Score (KOOS). Tissue quality was quantitatively evaluated using MRI T1ρ and T2 mapping (biochemical) and MR observation of cartilage repair tissue: MOCART 2.0 (morphological). A linear mixed model was used to identify factors affecting outcomes, including etiology (trauma, OCD, OA), graft site, and defect size. Results: At the 20-year follow-up, clinical scores remained significantly improved from baseline (mean LKS: 55.6 to 86.5; KOOS: 37.8 to 70.8). The biochemical MRI parameters (T1ρ and T2 values) stabilized at levels comparable to native cartilage across all etiologies and sites (p = 0.326 and 0.412, respectively), indicating stable long-term tissue quality. In contrast, the MOCART 2.0 scores significantly declined over time (annual rate: −1.14 points; p < 0.001). Etiology was a significant factor; the OA group showed significantly lower clinical and MOCART scores compared to the trauma/OCD groups (p < 0.05). However, no significant differences were found in LKS and KOOS based on graft site (p = 0.489) or defect size (p > 0.05). Conclusions: pMACI may be a highly durable treatment capable of maintaining biological tissue quality and providing clinical benefits for two decades. The observed morphological deterioration after 20 years likely reflects joint-wide aging—especially in OA cases—rather than graft failure, highlighting the importance of long-term MRI monitoring. Full article

A comparative chemical analysis was conducted between P. aibuhitensis of orange and green body colors, evaluating their proximate composition, fatty acid profile, amino acid profile, astaxanthin content, lipidomic profile, and other biochemical parameters. Samples were categorized by body color into two groups, each with ten biological replicates. The samples were collected from the same local polychaete farm. The results revealed that the green phenotype had significantly higher moisture content but lower crude protein, crude lipid, and ash content compared to the orange phenotype. The orange polychaete was characterized by significantly higher concentrations of 16:0 and saturated fatty acids (SFAs), whereas the green one exhibited higher contents of n-6 polyunsaturated fatty acids (n-6 PUFAs) and a higher PUFA/SFA ratio. Regarding free amino acids, the orange polychaete had significantly higher threonine content, while the green ones had significantly higher levels of valine, isoleucine, leucine, phenylalanine, glutamate, alanine, histidine and proline. Additionally, the astaxanthin content was significantly higher in the orange phenotype. The bile acid level was significantly higher in the green phenotype compared to the orange one, but no significant differences were observed in other biochemical parameters such as total protein, total cholesterol, and triglyceride content. The lipidomic analysis revealed that glycerophospholipids were the most abundant lipid class in both phenotypes, followed by glycerolipids and sphingolipids. A total of 65 differentially abundant lipid molecules were identified between the two groups. Compared to the orange polychaete, the green one had higher levels of 59 lipids (predominantly ceramides) and lower levels of six lipids, including three triglycerides, one monogalactosyldiacylglycerol, and two phosphatidylserines. In general, the orange P. aibuhitensis showed a favorable nutritional profile for aquafeed and human nutrition, whereas the green ones had potential for targeted health applications owing to its specific lipid composition. However, direct validating experiments are required. Full article

The continuous monoculture in Populus × euramericana ‘Neva’ plantations is closely related to the accumulation of phenolic acids in the soil, and these phenolic compounds exert a certain influence on plant nitrogen uptake. Leguminous plants can replenish soil nitrogen through biological nitrogen fixation, which is of great significance for enhancing plant productivity. This study employed different concentrations of phenolic acid treatments (0T, 0.5T, 1.0T, 1.5T, 2.0T) to analyze the photosynthetic characteristics of five phenolic compounds in a poplar–soybean (Glycine max (L.) Merr.) intercropping system, thereby providing a basis for biological management strategies aimed at increasing the yield of poplar monoculture stands. The results indicate that (1) P_n in poplar monoculture, soybean monoculture, and soybean intercropping all decreased as phenolic acid concentration increased, whereas P_n in poplar intercropping increased with rising phenolic acid concentration. Under treatments ranging from 0T to 1.5T, the decrease in P_n in the pure poplar, pure soybean, and intercropped soybean systems was primarily due to stomatal limitations, whereas under treatments ranging from 1.5T to 2.0T, it was primarily due to non-stomatal limitations. (2) Poplar, soybean, and soybean-intercropped poplar adapted to environmental stress by dissipating excess light energy absorbed by PS II as heat. The intercropping system effectively optimized poplar fluorescence parameters and mitigated the damage caused by phenolic acid stress to its photosynthetic machinery. (3) Chlorophyll A, chlorophyll B, and total chlorophyll in poplar and soybean leaves were significantly inhibited. (4) The biomass of poplars grown in monoculture decreased as phenolic acid concentration increased, whereas the biomass of poplars in intercropping showed the opposite trend. It is evident that, under phenolic acid conditions, poplar–soybean intercropping can mitigate the effects of phenolic acid stress to a certain extent. Full article

The coffee berry borer (Hypothenemus hampei) is the primary pest of coffee crops worldwide. Sustainable management strategies increasingly rely on the integration of biological control and interventions activated by population thresholds. In this work, a comparative framework based on dynamical systems is presented, integrating three complementary mathematical models to analyze different management strategies for the coffee berry borer. First, a biologically structured three-dimensional model describes the interaction between adult and immature borers and predatory ants. Second, a two-dimensional formulation allows the maximum per capita consumption rate of the predator to be studied as a bifurcation parameter, identifying critical parameter values that delimit regions of coexistence or effective pest control. Finally, a piecewise-smooth dynamical system incorporates ethological control activated when infestation exceeds a predefined threshold, whose effectiveness depends on the capture intensity associated with the traps. Using stability theory, bifurcation analysis, and techniques from piecewise-smooth dynamical systems, parametric regions associated with persistence, coexistence, or significant pest reduction are characterized. The results show that biological control alone may be insufficient if a predation threshold is not exceeded, whereas its combination with early threshold-based interventions considerably enlarges the dynamical regions favorable to producers. This study provides a dynamical interpretation of the agricultural concept of intervention threshold and offers a quantitative framework to strengthen integrated management and the sustainability of coffee production. Full article

Thisarticle develops and analyzes a fractional-order Leslie–Gower prey–predator–parasite system incorporating two discrete delays and nonlocal spatial diffusion. The model’s central novelty lies in the simultaneous integration of three biologically realistic features that have not previously been combined: (i) fractional-order memory effects via a Caputo derivative of order $\alpha \in (0,1]$, (ii) two distinct biological delays—an infection transmission delay ${\tau }_1$ and a predator handling delay ${\tau }_2$—and (iii) nonlocal spatial dispersal modeled through fractional Laplacian operators ${(-\Delta )}^{\gamma /2}$. This triple integration enables the model to capture long-range temporal memory, delayed biological responses, and nonlocal spatial interactions simultaneously, offering insights into dynamics that are challenging to capture with classical integer-order or single-delay formulations. The fractional Laplacian generalizes classical diffusion by allowing long-range dispersal events (Lévy flights), where individuals can occasionally move over large distances with heavy-tailed step-size distributions—a phenomenon observed in many animal movement patterns but absent from standard diffusion models. We provide rigorous proofs of solution existence, uniqueness, non-negativity, and boundedness in both temporal and spatiotemporal settings. Local asymptotic stability conditions are derived for all feasible equilibrium states via characteristic equation analysis. The coexistence equilibrium undergoes a Hopf bifurcation when either delay crosses a critical threshold, with fractional order $\alpha$ modulating the bifurcation point and post-bifurcation oscillation frequency. A Lyapunov functional demonstrates global asymptotic stability of the infection-free equilibrium under biologically interpretable conditions. Turing instability analysis reveals conditions for spontaneous pattern formation, with the fractional exponent $\gamma$ controlling pattern wavelength and correlation length. Numerical simulations validate theoretical predictions, including spatial patterns, traveling waves, and chaos. To bridge theory with potential applications, we outline a statistical framework for parameter estimation and uncertainty quantification, suggesting that $\beta$, $\alpha$, and ${\tau }_1$ may be priority targets for parameter estimation. Full article

Background: This study aimed to assess the impact of PSMA-PET/CT fusion imaging on target volume delineation in prostate cancer RT and to evaluate its effects on dosimetric parameters and PSA response, including intraprostatic boost. Methods: This single-center, retrospective study included 138 prostate cancer patients treated with definitive RT. Patients were evaluated according to the use of PSMA-PET/CT fusion-based planning and an intraprostatic focal boost, and dosimetric parameters for target volumes and organs at risk were compared. Results: PSMA-PET/CT fusion-based planning significantly increased the minimum dose coverage of the prostate target volume (96.7% vs. 95.5%, p = 0.003) while reducing the maximum dose (104.8% vs. 106.1%, p < 0.001). At 1 year after RT, the median change in PSA from baseline was 0.08 ng/mL (range, −0.44–2.12) in patients who underwent PSMA PET imaging-based fusion planning compared with 0.01 ng/mL (range, −0.049–4.07) in those who did not (p = 0.010). In patients receiving the intraprostatic focal boost with PSMA-PET/CT fusion, rectal maximum dose percentages were significantly lower than in those without the boost (103.2% [98.9–106.7] vs. 103.8% [95.7–107.4], p = 0.026). Rectal V65 and V50 values were also significantly reduced in the fusion group (7.0% [0.7–19.8] vs. 5.2% [1.2–21.7], p = 0.007; and 13.6% [6.3–21.9] vs. 11.4% [4.4–29.2], p = 0.027, respectively). Bladder maximum dose percentages were significantly lower in patients receiving the PSMA-PET/CT fusion-guided intraprostatic boost compared with those without the boost (102.6% [99.7–107.9] vs. 104.5% [99.1–108.5], p = 0.001). Conclusions: PSMA-PET/CT fusion-based planning improves biologically guided target delineation and dose homogeneity and suggests potential for better early biochemical response while reducing normal tissue exposure, whereas the intraprostatic focal boost improves dose distribution but is not associated with a significant short-term (1-year) PSA benefit. Full article