Browse Articles

Carbon quantum dots and mycorrhizal fungi improve cadmium stress tolerance and essential oil production in grapefruit mint (Mentha suaveolens × piperita)

Community structure-regulation coupling reveals optimal information diffusion

Abstract Effective regulation of information diffusion in complex social systems requires balancing containment and intervention cost, yet how network community structure interacts with targeted interventions remains unclear. We develop a community structure-regulation coupling framework (COSREF) that integrates community structure with process-level regulation of transmission and show how their interplay governs diffusion. Tuning two regulation parameters governing within- and cross-community transmission yields three regimes: no, localized, and global diffusion, separated by abrupt transitions. This structure–regulation perspective reveals a low-cost intervention region where small, targeted adjustments contain spread, unifies topology and regulation within a single theoretical setting, and provides general principles for efficiently and robustly regulating modular systems. Analyses of large cross-platform real-world social networks confirm our analytical predictions and simulation results, demonstrating COSREF’s robustness across investigated topologies and its applicability to real information environments.

Multiple defects in macrophage antibacterial responses support intracellular survival of <i> <i>Mycobacterium</i> abscessus </i> in cystic fibrosis

The prevalence of Mycobacterium abscessus (MABS) infections in people with cystic fibrosis (pwCF) is increasing. Macrophages are key phagocytic cells that recognize bacteria via cell surface receptors, engulf them into phagosomes, and then utilize diverse killing strategies. Here, we used human primary monocyte-derived macrophages (MDMs) from healthy controls (HCs) and pwCF to investigate how they processed and killed MABS. Expression of phagocytosis-related pattern recognition receptors (TLR2, Dectin-1, Dectin-2, and MARCO), engulfment of MABS, and lysosomal acidity were all reduced in CF-MDMs. MABS-infected CF-MDMs also had reduced mitochondrial mass, mitochondrial reactive oxygen species (mitoROS) production, relative intracellular zinc levels and inducible mRNA expression of the antibacterial zinc transporters, SLC30A1 and SLC39A8. Stimulation of mitoROS production in HC-MDMs with antimycin A reduced intracellular loads of MABS, confirming that MABS are sensitive to this mechanism of killing and suggesting that the mitoROS defect in MABS-infected CF-MDMs compromises bacterial killing. Accordingly, CF-MDMs failed to control MABS infection, with these cells allowing significantly increased intracellular MABS survival and expansion over 6 d. While treatment with the CFTR modulator, elexacaftor–tezacaftor–ivacaftor (ETI) did increase CFTR channel function and corrected CF macrophage functions to some degree, this was not sufficient to increase MABS killing. Taken together, our findings suggest important roles for functional CFTR in internalization and killing of MABS within macrophages, with CFTR dysfunction supporting MABS survival and replication in macrophages. Under our experimental conditions, ETI treatment failed to fully restore macrophage functions against MABS, highlighting the need for alternative, host-targeted approaches for improving macrophage functions in CF.

A unified spatiotemporal–geometry framework for target classification and localisation in dual-static passive radar

Passive radar exploits ambient broadcast signals and requires no dedicated transmitter, making it attractive for covert surveillance and target monitoring. A fundamental difficulty arises at low signal-to-noise ratio (SNR) or when targets move slowly: the class decision (static vs. dynamic) and the geometry-based position estimate are solved in two independent steps by most existing methods, which can lead to inconsistent outputs. We propose a joint spatiotemporal–geometry framework for a dual-static passive radar operating on DVB-T broadcast signals at 650 MHz. The framework combines a spatiotemporal encoder with dilated convolutions and cross-attention, and a Cramér–Rao-weighted Levenberg–Marquardt bistatic solver. The two components are coupled through an iterative optimisation loop: the encoder class probability steers a physics-consistent velocity penalty inside the solver, while the updated solver state feeds back into the next class decision. Unlike prior joint methods that either operate on sequential tracks or incorporate physics only at training time, the proposed framework enforces the exact bistatic delay and Doppler equations as hard constraints at every test-time iteration while the encoder class probability actively steers the geometry penalty within the same optimisation loop. Across 500 Monte Carlo trials per SNR point and five independent evaluation seeds, the proposed method achieves a mean classification accuracy of 93.7 ± 0.8% with a weighted F1-score of 0.937 ± 0.007. The mean localisation error at −6 dB SNR is 1.15 ± 0.09 km, a 28.1% reduction compared with a geometry-only baseline. The joint optimisation converges in a mean of 4.1 ± 0.8 outer iterations. A sensitivity analysis confirms that all results are stable across a factor-of-two variation in any single hyperparameter. Within the simulated dual-static passive radar environment considered in this study, the proposed iterative approach consistently outperforms seven evaluated baseline methods in both classification accuracy and localisation error.

Tumor suppressor effects of miR-143 and miR-199 on the K562 myelogenous leukemia cell line by targeting the RNA-binding protein Musashi2

Self-assembled chamber-like cardiac organoids for modeling cardiac chamber formation and cardiotoxicity assessment

Long-term antibody dynamics challenge the paradigm of lifelong homotypic immunity to dengue virus

Immunity following infection with the four dengue virus serotypes (DENV1-4) remains difficult to define. Reports of individuals being reinfected with the same serotype challenge the paradigm that infection induces lifelong homotypic immunity. However, the frequency of these events and their importance for shaping immune profiles remain unknown. Here, we used data from three cohorts (N = 4,268 total participants) in two highly endemic settings (Cebu, Philippines, and Kamphaeng Phet, Thailand), which included long-term follow-up of individuals (mean follow-up of 8.8, 1.9, and 5.0 y). These data allowed us to elucidate age-specific patterns of infection and immunity, and to quantify individual long-term antibody titer dynamics following infection. We formulated mathematical models to explain these patterns, allowing for the possibility of progressive loss of immunity to homotypic reinfection. At the individual level, we found that, in the absence of subsequent infection, antibody titers exhibit a steady long-term decay following incident infections (half-life of 7 to 8 y), with the rate of decay slowing with increasing age. At the population level, incorporating homotypic reinfection was required to explain the age-specific dynamics of infection and immunity observed in our cohorts. We estimated that in highly endemic settings such as the Philippines, 60% of individuals have been homotypically reinfected by the age of 40 y. Our findings highlight homotypic reinfections as a key feature of endemic DENV settings and suggest that vaccines mimicking natural infection might not be expected to provide lifelong protection against infection.

Behavioral barriers in the management of spinal muscular atrophy: The role of procrastination, regret, and burnout

Background Decision-making in complex medical conditions is a cognitively demanding task influenced by clinician-specific behavioral factors. Procrastination, the voluntary delay of intended actions despite foreseeable adverse outcomes, is a self-regulation failure often exacerbated by high-stress clinical environments. This study evaluated the prevalence of procrastination among healthcare professionals (HCPs) managing spinal muscular atrophy (SMA) and analyzed its associations with burnout and healthcare-related regret. Methods We conducted a non-interventional, cross-sectional, web-based study of HCPs recruited through the Spanish CuidAME registry. Participants were assessed using a battery of validated instruments: the Pure Procrastination Scale (PPS), the Regret Intensity Scale (RIS-10), the Evidence-Based Practice Attitude Scale (EBPAS), and a single-item burnout measure. In addition to multivariate logistic regression, we employed a regression-based mediation analysis with bootstrap resampling to explore potential indirect effects of burnout on procrastination via regret intensity. Results Thirty-seven HCPs completed the study. Moderate-to-high procrastination was identified in 35.1% of the cohort. PPS scores correlated significantly with burnout (rho = 0.49, p = 0.002) and regret intensity (rho = 0.43, p = 0.007). Multivariate analysis identified burnout as the single independent factor associated with procrastination (OR: 8.17; 95%CI: 1.60–41.62; p = 0.011). Although burnout significantly predicted increased regret intensity, mediation analysis confirmed no significant indirect effect (beta = 0.98; 95%CI: −1.74 to 3.79). Burnout maintained a robust association with procrastination, independent of the mediator (beta = 5.11, p = 0.039). Conclusions Procrastination is a prevalent behavioral trait in SMA care. While procrastination correlates with healthcare-related regret, burnout serves as its primary independent predictor of this behavior. These exploratory findings suggest that targeted interventions to mitigate clinician burnout may facilitate the optimization of decision-making processes in complex neuromuscular care.

Upcycling waste iron into high-performance Fe3Si-SiC-NbC in-situ nanocomposites enhances multiple properties during carbothermal reactions

Abstract In this study, we are interested in reusing industrial waste to produce cost-effective Fe 3 Si intermetallic-based nanocomposites with excellent mechanical, thermal, and magnetic properties, fabricated through an in-situ carbothermal reaction during powder metallurgy sintering. Fe15Si5Nb (vol%) powder is milled with increasing proportions of activated carbon up to 8% using high-energy milling, then pressed into tablets and sintered in an inert gas. The microstructure and phase composition of the sintered sample were investigated with FESEM and XRD techniques. Moreover, physical, thermal, mechanical, and magnetic properties were studied. The results indicated that the particle size of the Fe 15 Si 5 Nb powder decreased with the addition of activated carbon during milling. After sintering, XRD results showed the formation of two phases: Fe₃Si and FeNb. Upon adding activated carbon, the FeNb phase dissolved, and ceramic phases, SiC and NbC, were formed. Furthermore, there was a marked improvement in both the thermal expansion coefficient (CTE) and mechanical properties, and also no breakdown of magnetic properties. The microhardness, strength, Young’s modulus, and CTE of the sample containing 8% activated carbon improved by approximately 69.81%, 33.95%, 21.77%, and 16.67%, respectively, compared to the base sample. Magnetization of the intermetallic base decreases from 28.12 to 26.20, 26.08, 23.65, and 21.98 emu/g, respectively, after incorporating 1%, 2%, 4%, and 8% activated carbon.

Histamine shapes the neurocomputational dynamics of human learning

Abstract Histamine was the first canonical monoamine identified in the mammalian brain, yet arguably remains the least understood in its mechanistic contributions to human behaviour. Using a first-in-class causal probe (H 3 R inverse agonist pitolisant), we show how elevating histamine shapes offline and online temporal–hippocampal dynamics — sustaining episodic learning-related activity and polarising retrieval computations. Beyond this, histamine adaptively shifts neurocomputational strategy under high working memory load, while stabilising value updates during aversive reinforcement learning. These findings uncover a mechanistically grounded influence of this underexplored system on human neurocomputation, supporting its therapeutic potential in psychiatry.

Lactylation of PD-L1 by a lactyltransferase HAT1 dictates its protein stability and tumor immune evasion

Lysine lactylation regulates protein fate and function across diverse biological processes. While PD-L1 has been widely studied posttranslationally, the role of its lactylation and the responsible enzyme have remained poorly studied. Here, we identify histone acetyltransferase 1 (HAT1) as a lactyltransferase that catalyzes programmed cell death ligand 1 (PD-L1) lactylation at residues K75 and K178 within its extracellular domain, thereby enhancing PD-L1 stability. Mechanistically, this glycosylation-dependent modification protects PD-L1 from endoplasmic reticulum (ER)-associated degradation and promotes ER-to-Golgi trafficking. Targeting PD-L1 lactylation by HAT1 knockdown, mutation of the lactylation sites or HAT1-PD-L1-interferring peptides suppresses tumor progression and enhances anti-PD-1 therapy efficacy. Clinically, lactylated PD-L1 strongly correlates with tumor progression. Together, these findings establish HAT1-mediated PD-L1 lactylation as a key mechanism of immune evasion and suggest that targeting this pathway could improve cancer immunotherapy outcomes.

A process-guided uncertainty-aware deep learning framework for reliable and interpretable industrial fault diagnosis

Timely fault detection is essential for safety, product quality, and energy efficiency in advanced industrial processes. However, many existing fault diagnosis methods insufficiently exploit process structure and sensor reliability, which limits their robustness and practical usefulness for process engineers. This study presents an improved framework SAU-PGA-CNN-BiLSTM that first couples Convolutional Neural Networks and Bidirectional Long Short-Term Memory layers to extract multivariate temporal dynamics and spatial correlations of the process data, secondly a process guided and sensor-aware attention mechanism is introduced which embeds process centrality, sequence level sensor reliability and uncertainty to the attention learning, to suppress unreliable channels and bias towards informative and stable sensors. In addition, Monte Carlo dropout with sensor prior-conditioning is used to provide calibrated confidence estimates that reflect both predictive uncertainty and sensor reliability. Finally, two lightweight sigmoid output heads perform fault detection and diagnosis combinedly, promoting mutual reinforcement between the tasks. Validated on the Tennessee Eastman Process benchmark, the proposed framework outperforms baselines model and achieves 93.6% multiclass diagnosis accuracy with 94.0% F1 score. After temperature scaling, the proposed model also demonstrates improved calibration compared with an otherwise identical model without sensor awareness, reducing negative log-likelihood from 0.197 to 0.182, Brier score from 0.101 to 0.095, and expected calibration error from 0.040 to 0.037. Attention visualizations further show that the model focuses on process-relevant and reliable sensors, supporting reliable industrial fault diagnosis.

Modeling soil water distribution under drip fertigation in chrysanthemum across soil types using HYDRUS-2D

Abstract Efficient water management is critical for sustainable chrysanthemum production under protected cultivation was conducted at Indian Agricultural Research Institute (IARI), New Delhi, India. While HYDRUS-based models are widely used for simulating soil water dynamics under drip irrigation, their application in floriculture crops remains limited, particularly for deriving crop-specific irrigation strategies. This study integrates field experimentation (2020–2023) with HYDRUS-2D simulations to evaluate soil water distribution under drip fertigation across multiple soil types. The effects of emitter discharge, irrigation scheduling, and soil hydraulic properties were analyzed to determine optimal root-zone moisture conditions. Results showed that soil moisture remained within the optimal range for up to 48 h after irrigation under appropriate scheduling. Among soil types, moisture retention followed the order: silt ≈ silty clay loam &gt; loam &gt; sandy clay loam &gt; sandy loam. Model validation demonstrated high accuracy (R 2  = 0.90–0.96; RMSE = 0.011–0.012; Ceff = 0.90–0.92), confirming the reliability of HYDRUS-2D. Simulation results indicated that an emitter discharge of 1.0 lph combined with a 48-hour irrigation interval maintained optimal root-zone moisture while minimizing deep percolation losses. The study highlights the potential of simulation-based approaches for optimizing irrigation design and improving water-use efficiency in greenhouse floriculture systems.

Rethinking the economics and flexibility of U.S. nuclear power through hydrogen integration and policy support

Interfacial electric fields create hyperalkaline shells on fatty acid–coated microdroplet aerosols

Aerosol acidity (pH) is a fundamental property governing atmospheric multiphase chemistry, as it influences pollutant partitioning, secondary organic aerosol formation, and trace metal solubility. Thermodynamic models typically assume the internal homogeneity of submicron particles; however, fresh aerosols produced via biomass burning often possess complex core–shell morphologies wherein an aqueous core is coated by organic surfactants. Here, we report that a size-dependent “alkaline shell” exists for aqueous ammonium sulfate microdroplets coated with stearic acid, a ubiquitous constituent of biomass burning. Using single-droplet surface-enhanced Raman spectroscopy and confocal fluorescence imaging, we identify a critical size regime (50 to 150 µm) where alignment of the surfactant monolayer generates strong interfacial electric fields (~10 8 V/m). This field drives local partitioning of protons and hydroxide ions, sustaining a hyperalkaline surface shell (pH ~9 to 11). We attribute this phenomenon to a feedback loop, distinct from bulk equilibria, involving surfactant dipole alignment, hydrophobic confinement of hydroxide, and interfacial charge transfer. These findings add critical nuance to bulk thermodynamic predictions, demonstrating that while the aerosol core remains acidic, the interface of organic-coated aerosols can act as a unique, high-pH microreactor in the atmosphere, potentially accelerating base-catalyzed reactions and altering the environmental fate of biomass emissions.

The role and targeting potential analysis of angiogenesis-related target THY1 in DSS-induced acute colitis in mice

Background Immune-driven inflammatory angiogenesis plays a crucial role in the pathogenesis of inflammatory bowel disease (IBD). However, the mechanism of chronic inflammation mediated by angiogenesis still remains unclear. This study aimed to investigate the crucial role and specific mechanism of the angiogenesis-related target THY1 in the development of acute colitis induced by dextran sulfate sodium (DSS) in mice. Methods Lentivirus-based systems were utilized to achieve both knockdown and overexpression of THY1 to explore the functional roles of THY1 in IBD development based on DSS-induced colitis mice model and co-culture system of intestinal epithelial cells and macrophages. Results THY1 significantly promotes DSS-induced colitis in the experimental mouse model. Silencing of the THY1 significantly reversed the inflammatory response, oxidative stress level, and angiogenic activity in DSS-induced colitis, whereas overexpression of THY1 further exacerbating the reactions related to inflammation, oxidative stress, and angiogenesis. Mechanism research showed that THY1 promotes the pathological process of DSS-induced colitis through inhibiting M2 macrophage polarization. In addition, THY1 promotes apoptosis through the Bcl-2/Bax/Cleaved caspase-3 pathway and promotes angiogenesis via upregulation of HIF-1α and VEGF expression in DSS-induced colitis. Conclusions THY1 promotes the occurrence and development of acute colitis induced by DSS in mice by regulating macrophage polarization, intestinal epithelial cell apoptosis, and inflammatory angiogenesis, providing a new perspective for the study of the pathogenesis of IBD. Furthermore, THY1 is expected to become a potential target molecule for the treatment of IBD.

Diagnostic performance of kinetic parameters of ultrafast breast MRI and their associations with immunohistopathological findings of breast carcinoma

Abstract This study aimed to assess diagnostic values of kinetic parameters in ultrafast dynamic contrast magnetic resonance imaging. The diagnostic performance of ultrafast kinetic parameters (time to enhancement [TTE], maximum slope [MS], time to peak, peak enhancement [PE], and wash-in slope [WIS]), and their correlations with the immunohistopathological findings of breast cancer were evaluated for 101 histologically proven breast lesions. We found that the areas under the curves of five ultrafast kinetic parameters in masses (0.69–0.81) and for MS, PE, and WIS in non-mass enhancement (NME) (0.91–0.94) were comparable to those of Breast Imaging Reporting and Data System (BI-RADS) categorizations (mass: 0.85, NME: 0.83) without statistically significant differences. Values of ultrafast kinetic parameters differed significantly according to invasiveness (invasive vs. non-invasive: TTE, p  = 0.029; MS, p  = 0.040; PE, p  = 0.032; and WIS, p  = 0.009), immunohistopathological findings (high vs. low Ki-67: TTE, p  = 0.020; MS, p  = 0.004; PE, p  = 0.003; and WIS, p  &lt; 0.001), hormone receptor (negative vs. positive: MS, p  = 0.033; and WIS, p  = 0.042), and triple-negative status (triple-negative vs. non-triple-negative: MS, p  = 0.028; and WIS, p  = 0.011) in breast cancer. In conclusion, ultrafast kinetic parameters demonstrate diagnostic performance comparable to that of BI-RADS categories for both mass and NME and may be associated with the immunohistopathological findings of breast cancer.

Network completeness enables angstrom-scale transport pathways in polymer membranes

Transition-state analysis of the arginine-specific human ADP-ribosyltransferase 1

The ADP-ribosylation of proteins is a versatile, reversible, posttranslational modification involved in the dynamic regulation of numerous cellular processes. Human ADP-ribosyltransferase 1 ( hs ART1, EC: 2.4.2.31) is a membrane-associated, GPI-anchored, mono-ADP-ribosyltransferase selective for mono-ADP ribosylation (MARylation) of L-arginine residues. Dysregulation of hs ART1 activity has been shown to permit immune cell evasion in non–small cell lung cancer (NSCLC) through elevated MARylation at Arg125 of the purinergic type 2 receptor (P2X7) in P2X7-positive T cells, resulting in NAD + -induced cell death (NICD) of tumor-penetrating immune cells. With hs ART1 emerging as an immunotherapy target in select cancers, there is a need to develop small-molecule inhibitors. The transition state (TS) for the MARylation of P2X7 peptide was determined from kinetic isotope effect (KIE) measurements of 3 H-, 14 C-, 18 O-, and 15 N-labeled NAD + substrates. Quantum mechanical (QM) calculations of the reaction coordinate, mapped with experimental KIEs, identify a TS geometry consistent with a highly dissociative, asymmetric, concerted mechanism with minimal contributions from the leaving group nicotinamide (NAM) and minor contributions from the incoming L-arginine guanidinium. The absence of a normal deuterium solvent isotope effect identifies a positively charged guanidinium nucleophile, leading to a dication N-ribosyltransferase mechanism. Together with the unusual, normal 18 O–O4 ′ KIE, we identified unique charge accumulation across the oxocarbenium at the TS caused by an increased bond order between the C1 ′ –C2 ′ , and decreased bond order between the C4 ′ –O4 ′ of the nicotinamide mononucleotide ribose. This is the first L-arginine-specific ADP-ribosylation TS to be characterized, a step toward the design of TS analogs.

Validation and evaluation of diagnostic tests for Schistosoma mansoni in Brazil: The ValidaXisto study protocol

The persistence of schistosomiasis as a serious public health problem can be attributed, in part, to the lack of more accurate diagnostic techniques, particularly in areas with low prevalence and low parasitic burden. Thus, an effective diagnostic tool with broad applicability for detecting active infections in both high- and low-prevalence settings, as well as for accurately monitoring cure after therapeutic interventions, represent an instrument of utmost importance for controlling disease transmission. Therefore, we propose evaluating different commercial tests for schistosomiasis diagnosis identified through a review of all tests registered to be used in Brazil by the Brazilian regulatory agency (ANVISA) and those registered by other regulatory agencies, as well as prototypes of tests under development. In addition, we propose the development and evaluation of molecular diagnostic methodologies for schistosomiasis using different biological samples (stool, blood, and urine) from individuals living in an endemic area. The Kato-Katz technique, with 18 slides per stool sample, will be used as the reference test for definition of schistosomiasis cases. The performance of the evaluated techniques will be compared with respect to sensitivity, specificity, accuracy, positive and negative likelihood ratios, agreement with the reference test, cost, time, and ease of execution. The effectiveness and feasibility of these diagnostic tests will be assessed to recommend their incorporation into the schistosomiasis surveillance actions of the Ministry of Health within the Brazilian Unified Health System (SUS) in the short to medium term, considering the conditions faced by surveillance programs within Primary Health Care.