搜索结果：Process

This study aimed to provide a comprehensive comparison of inhibitory control performance among children with Attention-Deficit/Hyperactivity Disorder (ADHD), Specific Learning Disorder (SLD), and comorbid ADHD+SLD, relative to typically developing peers. It sought to clarify whether inhibitory control deficits are generalized across tasks or specific to distinct types of inhibition. A total of 120 children (30 per group; aged 9-11 years) participated. Three tasks assessed different facets of inhibitory control: the Stroop Color-Word Test (interference suppression), the Cued Go/No-Go Task (prepotent response inhibition), and the Stop-Signal Task (cancellation of ongoing responses). Analyses controlled for baseline processing speed. Findings revealed distinct inhibitory profiles. Children with ADHD showed broad deficits across all tasks, most pronounced in the Cued Go/No-Go Task, indicating a core weakness in prepotent response inhibition. The SLD group demonstrated slower reaction times, particularly in the Cued Go/No-Go Task in the initial analysis. Slower responses reflect both processing-speed deficits and potential differences in motor planning and execution. However, after statistically controlling for these general speed effects, the SLD group's profile revealed a specific and significant deficit only in interference suppression, with no core impairment in prepotent response inhibition or action cancellation. The comorbid ADHD+SLD group exhibited the most severe and pervasive deficits across all measures, exceeding single-diagnosis groups, suggesting a synergistic impairment. These results support the multidimensional nature of inhibitory control and highlight disorder-specific neurocognitive signatures. The findings underscore the need for differentiated assessment and intervention approaches targeting distinct inhibitory processes and processing-speed deficits, particularly in children with comorbid conditions.

Digital twins of mammalian cell cultures hold great potential for predictive bioprocess modeling, yet their development is challenged by the nonlinear dynamics and metabolic complexity of these systems. We present a hybrid computational framework that integrates mechanistic and data-driven modeling to construct predictive digital twins for Chinese hamster ovary (CHO) cell cultures producing monoclonal antibodies. The framework couples ordinary differential equation (ODE) models with constraint-based metabolic modeling and machine learning components trained on Bayesian-estimated metabolic rates. Applied to 23 CHO fed-batch cultures, viable cell density, product titer, and key metabolite concentrations are accurately predicted under varying feeding and media conditions within a unified simulation engine, where empirical variability is incorporated through multivariate statistical constraints derived from experimental data. Cross-validation analyses demonstrated strong generalization across process variations, highlighting the framework's capacity to capture both biochemical constraints and adaptive cellular behavior. This hybrid modeling approach provides a mechanistically interpretable yet data-adaptive foundation for constructing bioprocess digital twins. By bridging statistical, mechanistic, and machine learning methodologies, it advances the computational representation of CHO cell culture systems and offers a generalizable strategy for predictive modeling in complex biological production processes.

Multimodal imaging has expanded treatment for patients with acute ischemic stroke with large vessel occlusion. Blood-brain barrier (BBB) disruption measured in the ischemic core is associated with hemorrhagic transformation. However, the associations between core BBB disruption (cBBBD) and baseline clinical/imaging variables, as well as 3-month outcome, have not been explored. This is a retrospective multicenter analysis of consecutive anterior circulation patients with acute ischemic stroke with large vessel occlusion, presenting over a 4-year time period, who were transferred from a primary to a comprehensive stroke center for possible endovascular therapy, with magnetic resonance imaging that included perfusion-weighted imaging before transfer. Magnetic resonance imaging scans were processed using RAPID software to generate penumbral imaging variables. Perfusion-weighted images were processed to detect and quantify contrast leakage; cBBBD was calculated as the average of all leaky voxels in the ischemic core. Poor functional outcome was defined as a modified Rankin Scale score of >2 at 3 months. Linear regression was used except for the outcome, which used logistic regression, controlling for age, stroke severity, and baseline functional status. Out of 411 patients transferred for endovascular therapy, 291 were included in this analysis with a median age of 74 years; 49% were female patients. The median National Institutes of Health Stroke Scale score was 13, the mean core volume was 32.3 mL, and the mean cBBBD was 2.1%. 71% of patients underwent endovascular therapy. Admission National Institutes of Health Stroke Scale score (P<0.001) and glucose level (P=0.033) were independently correlated with cBBBD. All imaging variables correlated strongly with cBBBD (P<0.001). The strongest correlation was 0.50, observed between cBBBD and mismatch ratio (r2=0.254). Increasing cBBBD was independently associated with poor functional outcome (adjusted odds ratio, 1.16 [CI, 1.03-1.32]; P=0.019; n=279), indicating that for every 1% increase in cBBBD, the odds of having a poor functional outcome increase by 16%. In acute ischemic stroke with large vessel occlusion, disruption of the BBB in the core lesion is independently associated with clinical outcome. cBBBD represents a new imaging profile for acute stroke that may help guide treatments.

Advancements in synthetic biology (SynBio) and other emerging and converging technologies, such as artificial intelligence (AI) additive manufacturing (3D printing), and nanotechnology are driving progress at an unprecedented pace. However, these promising and groundbreaking advances could also lead to novel biological risks, including the potential development of SynBio-enabled bioweapons (BW). Conducting a Delphi process, we consulted 13 experts from diverse relevant sectors. The multi-stage process included insights from literature reviews, expert interviews, two rounds of expert surveys, and two workshops. We identified consistent biological threat prioritizations and established consensus-driven policy recommendations. Based on this, we developed a novel hybrid governance framework. Our key proposal includes a multifaceted and integrative approach involving four sequential, iterative components: raising awareness; establishing robust training and monitoring systems to improve biosecurity measures; developing and implementing agile governance frameworks; and strengthening international treaties, such as the Biological Weapons Convention (BWC). We consider these integral, interconnected components to be interdependent and equally important. In an era of SynBio, AI-driven bioengineering, and democratization of biotechnology, implementing these recommendations will better safeguard against the potential misuse of these advancements in the context of the development and proliferation of BW.

Wheat starch composition and content significantly influence the processing and end-use quality of flour. In this study, we characterized a novel wheat mutant (M393) generated via &#x3b3;-ray mutagenesis, which exhibited altered starch content and superior bread-making performance compared to the wild type (WT). Comprehensive comparison analysis shows that the mutant M393 has longer dough stability time, higher tensile strength and better ductility than the wild type, and the volume of bread is larger, the texture of bread is finer, and the taste of bread is better. Microscopic observations, together with laser diffraction particle size analysis, revealed smaller starch granules and an increased proportion of B-type granules in M393.The total starch and amylose content of the mutant M393 were significantly decreased, while the amylopectin content was increased. Transcriptomic analyses revealed downregulated expression of the GBSS gene, which is responsible for amylose synthesis, while genes related to amylopectin synthesis (SBE, SS, and DBE) were upregulated, corresponding to the shifts in starch composition. In addition, a co-expression network of transcription factors and starch synthesis genes was constructed, and new transcription factors such as MYB89, SBP91, bHLH131, HD-ZIP67, and HD-ZIP66 were identified as putative regulators that may be involved in the expression of starch genes. The results of this study provide new insights into the transcriptional regulation of starch biosynthesis and provide a valuable theoretical basis for breeding wheat varieties with better processing quality.

Exosomes are nanometer-scale extracellular vesicles secreted by cells with a diameter of approximately 30-100 nanometers. Serving as essential messengers for intercellular communication, they play significant roles in both physiological and pathological processes. Their low immunogenicity, excellent tissue penetrability, and high biocompatibility have positioned them as a research focus for disease diagnostic biomarkers and drug delivery vehicles. Spinal cord injury (SCI) is a severe traumatic disorder of the nervous system, often leading to neuronal death, axonal disruption, glial scar formation, and dysregulated inflammatory responses, ultimately resulting in irreversible sensory and motor dysfunction. This review systematically elucidates the pivotal roles of exosomes derived from various cell sources in the repair of SCI. It focuses on how these exosomes target key cellular components including neurons, glial cells, vascular endothelial cells, and immune cells. This interaction modulates core pathological processes such as neuroinflammation, glial scar formation, axonal regeneration, angiogenesis, and apoptosis. By synthesizing current evidence, we aim to unravel the complex regulatory networks mediated by exosomes as intercellular signaling hubs within the SCI microenvironment. Furthermore, this review provides a theoretical foundation for their future development as novel diagnostic tools, regenerative therapeutic vectors, and targeted intervention strategies for SCI.

Mitochondrial ion channels are proteins of the inner and outer mitochondrial membranes that regulate ion flux and control various cellular processes, including calcium signaling, bioenergetic and metabolic functions, and cell death. Their precise regulation is essential to maintaining normal mitochondrial function and preventing pathological processes. Patch-clamp and planar lipid bilayer electrophysiology techniques have been used to measure ion flow directly across the membrane, thereby revealing the gating kinetics and pharmacological profile of ion channels in real time. Here, we describe a planar lipid bilayer electrophysiology approach for assessing mitochondrial ion channel conductance using mitochondrial inner membrane vesicles (IMVs). The comparative electrophysiology analysis between IMVs and purified mitochondrial proteins, ATP synthase, and the adenine nucleotide translocator (ANT), demonstrates that planar lipid bilayer electrophysiology is a robust tool for biophysical characterization of mitochondrial ion channels using IMVs. This approach is particularly valuable for investigating ion channel properties under controlled yet physiologically relevant conditions and for evaluating the direct modulatory effects of different pharmacological agents.

Second harmonic generation (SHG) is a widely used nonlinear optical process for frequency conversion and quantum information processing. However, existing approaches to enhance SHG in metasurfaces that are based on quasi-bound state in the continuum (quasi-BIC) resonances are often constrained by the limited second-order nonlinear susceptibilities of materials and the practical challenge of achieving high quality (Q) factors. Here, an alternative strategy is proposed to enhance SHG by increasing the absorptance (A) at the quasi-BIC resonance. Using temporal coupled mode theory (TCMT), an analytical expression is derived to link SHG intensity with both the resonance Q factor and absorptance, showing that strong SHG can be achieved even with finite Q when absorptance is properly optimized. To validate this concept, a 3R phase of molybdenum disulfide (3R-MoS2) metasurface is designed and fabricated by spectrally aligning a reflective resonance with a transmitted quasi-BIC mode, thereby enhancing absorptance at the target wavelength. The metasurface exhibits an SHG conversion efficiency of &#x223c;3 &#xd7; 10-5 at 9 GW cm-2, corresponding to more than 40-fold enhancement over an unpatterned flake. Despite the reduced damage threshold, the experimental results agree well with the theoretical model and establish a general design framework for absorptance-engineered metasurfaces for SHG.

We explored how systematic manipulation of the physical characteristics of the Kanizsa and Ebbinghaus illusions influences perceptual outcomes in the general population. Additionally, we investigated whether these effects on illusion processing are influenced by individual differences in autistic traits. Eighty-five adults aged 18 to 35&#xa0;years completed the Autism Spectrum Quotient (AQ) and participated in two illusion tasks in which the size, spacing, and direction of inducing elements were systematically manipulated. In addition to accuracy analysis, performance was assessed using the Balanced Integration Score (BIS), a metric that integrates accuracy and reaction time.Our results showed that, in the Kanizsa illusion, both the orientation of the illusory shape and the ratio of inducer size to spacing (i.e., support ratio) influenced perception. Similarly, in the Ebbinghaus illusion, both the size ratio of the two central circles (i.e., center ratio) and the relative size of the surrounding versus central circles (i.e., outer ratio) affected illusion strength. Autistic traits did not show consistent or robust modulation of the effects of physical stimulus characteristics across tasks. These findings suggest that illusion processing strength in the general population is primarily determined by stimulus geometry. Our findings suggest that predicted differences between within-object and between-object illusions with respect to autistic traits may not be evident in non-clinical samples.

The quantification of flow speed and -direction is key to many aerodynamic investigations. In case of large scale flow fields and outdoor environments optical techniques such as particle image velocimetry or Shake-the-Box are difficult to implement. Instead, a sufficient amount of point-wise measurements can be employed. Ultrasonic anemometers are a compelling solution due to their high accuracy and low drift even at low to moderate flow velocities. Commercial ultrasonic anemometers often lack a synchronization method and an analog output and most of the available products are closed source and therefore the algorithms employed have unknown characteristics such as time delay, error handling and filtering. The goal of this paper is to develop an ultrasonic anemometer that can measure flow velocities up to 35&#xa0;m&#xa0;s-1 and address the above issues while being low cost. The sensor is based on off-the-shelf electronic components, two custom printed circuit boards, and uses an STM32F4 microcontroller as its main processor. A semi-automated calibration and validation process was performed, achieving a mean flow speed magnitude accuracy of &#xb1; 0 . 3 m/s and an angle error of less than 1%.

Research on the neuropsychological outcomes of hemispherectomy in childhood has largely focused on the development of language after surgery to the left hemisphere. That work has highlighted both the positive aspects of neural plasticity in that language representation is transferred to the right hemisphere and the negative aspects - the crowding effect- in that aspects of visual-spatial processing may suffer. Less is known about the effects of right hemispherectomy on cognitive development, particularly on visuospatial processing, with existing studies including samples that vary considerably in etiology, age of seizure onset, duration of epilepsy, and age at surgery. This case report discusses neuropsychological development at ages 6 and 10&#xa0;years in a young boy who underwent a right hemispherectomy at 6&#xa0;months of age. Despite an extended period of seizure-free development of the left hemisphere, there was no evidence for reorganization of visuospatial function, as he remained impaired on tests assessing his ability in that domain. Findings suggest that the left hemisphere has limited capacity to assume the visual-spatial functions usually associated with the right hemisphere.

Synthetic cells, assembled from defined molecular components, are designed to mimic the features, form, and function of living cells. Light has emerged as a uniquely precise, biorthogonal, and non-invasive stimulus for regulating and energizing these systems, enabling chemical inhomogeneity and an out-of-equilibrium state central to many cellular processes. This review highlights the biological behaviors and functions that light has helped recreate in synthetic cells, including compartmentalization, energy supply and metabolism, protein synthesis, communication, growth, shape change and division, and motility. We survey the breadth of light-responsive components incorporated into synthetic cells, spanning photoswitchable and photocleavable small molecules, photoswitchable proteins, photocatalysts, nanoparticles, and photosynthetic organelles or organisms. Finally, we offer a perspective on key design considerations such as wavelength, reversibility, integration, biocompatibility, multicolor regulation, and biohybrid strategies. Together, these advances chart promising routes toward more dynamic, energy-autonomous, and programmable synthetic cells that will deepen our understanding of cellular functions and enable emerging biotechnological applications.

Diseases and health limitations associated with ageing often result in loss of mobility and reduced social participation. The ongoing demographic shift towards an increasingly ageing population, combined with a declining number of healthcare professionals, highlights the need to integrate digital assistive solutions to reduce workload and healthcare costs. Smart rollators (SRs) equipped with sensor-based assistance systems (SAS) are considered a promising innovation for enhancing safety, mobility, and independence in older adults. The aim of this study was to explore the needs, experiences, and perspectives of rollator users (RU) and healthcare professionals (HP) in order to identify and evaluate user-centred requirements for the iterative development of a smart rollator. As part of a broader research project, a design-based research (DBR) approach was applied. Five focus groups with a total of 30 participants (15 RU, 15 HP) were conducted using semi-structured interviews, which were analysed using qualitative content analysis. Data collection occurred in two phases: first, to explore user requirements, and subsequently, to evaluate an initial SR prototype. The analysis followed a content-structuring approach, conducted independently by two researchers. Three main categories emerged from the focus groups: use of the rollator in daily life, sensor-based assistance systems, and the application of digital assistive technologies. Participants generally assessed the integration of digital and sensor-based functions positively, provided that these increased perceived safety and remained easy to use. Desired features included navigation, environmental and fall detection, emergency call functionality, lighting, and haptic feedback. Barriers were primarily related to technological scepticism, limited digital literacy, and potential cognitive overload. Facilitating factors included training, simple user interfaces, and modular system structures. The findings indicate that participatory development processes are essential for improving the acceptance of smart rollators. Early involvement of users and nursing professionals ensures that technological innovations are designed to be practical, safe, and needs-oriented. The design-based research approach represents a suitable framework for the iterative development and evaluation of assistive technologies in healthcare settings.

The role of extracellular acidity in regulating parathyroid hormone (PTH) secretion in cultured mouse parathyroid glands (PTGs) has not studied to date, largely due to the technical difficulty of isolating mouse PTGs. We hypothesized that acidic extracellular pH directly stimulates PTH secretion through activation of a proton-sensing receptor, specifically ovarian cancer G protein-coupled receptor 1 (OGR1, also known as GPR68). To test this, we developed a method to reliably identify and isolate PTGs from male mice by administering 5-aminolevulinic acid (5-ALA), which induced selective fluorescence in these glands. Using this model, we demonstrate that acidic extracellular pH significantly stimulates PTH secretion in cultured mouse PTGs. Mechanistically, we identify OGR1 as the primary proton sensor mediating this response, as PTGs from OGR1 knockout mice failed to increase PTH secretion under acidic conditions, with no evidence of compensatory upregulation of other proton-sensing receptors. In addition, we found that low extracellular Ca2+ not only stimulates PTH secretion but also promotes extracellular acidification. Notably, low Ca2+ and acidic pH act synergistically to enhance PTH secretion in wild-type PTGs, an effect markedly attenuated in OGR1-deficient glands. Together, these findings establish a direct, OGR1-dependent mechanism by which extracellular acidity regulates PTH secretion and reveal an interaction between calcium and pH signaling in this process. This work provides a robust ex vivo model for studying PTG physiology and offers new insight into how metabolic acidosis may contribute to secondary hyperparathyroidism in chronic kidney disease, highlighting OGR1 signaling as a potential therapeutic target.

This study aimed to investigate the role of lactate in the progression of cardiac dysfunction after myocardial infarction (MI) and clarify the effect of aerobic exercise (AE) on improving post-infarction cardiac function by regulating lactate metabolism, so as to provide experimental evidence for the clinical improvement of cardiac function after MI. NIH 3&#x202f;T3 mouse embryonic fibroblasts and C57BL/6&#x202f;J mice were used as research subjects. In vitro, fibroblasts were treated with different concentrations of lactate, and the activation state of fibroblasts was evaluated by detecting the expression levels of Collagen I (COL I) and &#x3b1;-Smooth Muscle Actin (&#x3b1;-SMA). In vivo, four mouse models (SED-SHAM, AE-SHAM, SED-MI, and AE-MI) were established. Cardiac function was assessed by echocardiography for left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS). Lactate levels in cardiac tissue and serum were detected using a lactate assay kit, and serum metabolite changes mediated by lactate were analyzed via metabolomics technology. In vitro experiments confirmed that lactate could significantly induce fibroblast activation. Metabolomics results showed that elevated lactate levels after MI led to abnormal accumulation of arachidonoyl carnitine. In vivo experiments revealed that lactate levels in cardiac tissue and serum were significantly increased, while LVEF and LVFS were decreased in the SED-MI group. In contrast, lactate levels in cardiac tissue and serum were reduced, and LVEF and LVFS were elevated in the AE-SHAM group. Lactate levels in cardiac tissue and serum of the AE-MI group were lower than those of the SED-MI group but higher than those of the AE-SHAM group, and the LVEF and LVFS of the AE-MI group were significantly higher than those of the SED-MI group. This study confirmed that lactate accumulation is involved in the pathological process of cardiac dysfunction after myocardial infarction, and AE can improve cardiac function after MI by reducing lactate levels in cardiac tissue and serum. These findings provide new experimental evidence for the prevention and treatment of post-infarction cardiac dysfunction by targeting lactate metabolism, and also offer theoretical support for the application of AE in cardiac rehabilitation.

Drying river networks (DRNs) are globally expanding ecosystems where hydrological intermittence, including surface-flow cessation and habitat fragmentation, profoundly shapes biodiversity, ecological functions, and biogeochemical processes. Despite growing knowledge, the role of microbial communities inhabiting periphyton in tropical DRNs remains poorly understood. Here, we conducted the first spatiotemporal metabarcoding assessment (16S & 18S V4 amplicon sequencing) of bacteria, phototrophs, and fungi in stream periphyton across the Cube Drying River Network, located in Ecuador's Choc&#xf3;-Dari&#xe9;n biodiversity hotspot. We sampled 20 reaches spanning perennial and intermittent sites during six campaigns across an intermittence gradient. Microbial &#x3b1;-diversity increased with drying, peaking at the highest intermittence (45%), with phototrophs and fungi exhibiting significant gains compared to wetter phases. Community &#x3b2;-diversity declined as intermittence intensified, indicating homogenization of assemblages under sustained hydric stress and restricted dispersal due to disconnection of surface flow. Variation partitioning showed that major dissolved constituents (e.g., Ca2+, Mg2+, NO&#x2083;-, TOC) explained ~6% of compositional shifts, while environmental variables and trace elements accounted for smaller fractions. Co-occurrence network analyses revealed that interactions among microbial groups intensified with drying, culminating in highly connected yet low-modularity networks, which suggests reduced resilience under prolonged intermittence. Our results contrast with patterns reported in temperate and arid systems, where drying typically reduces microbial diversity, underscoring the particular dynamics of tropical DRNs, which are dominated by isolated pools and incomplete drying. These findings underscore the role of periphyton as critical microbial hubs that regulate ecosystem functioning under fluctuating flow regimes and emphasize the urgent need to integrate microbial dynamics into global assessments of river network resilience in the face of climate change.

Bioactive compounds derived from grape by-products support a circular economy approach and offer valuable opportunities for the nutraceutical and food industries. Among these by-products, grape seeds are of particular interest due to their high content of antioxidant proanthocyanidins (PAs). However, the aqueous solubility and chemical instability of PAs during processing, storage and consumption, limit their commercial viability. We hypothesize that an optimization in the PAs encapsulation would improve their physicochemical and biological performance, and the potential to be included in food formulations. In this study, we developed liposomes (Lip) as delivery systems for grape seed PAs and evaluated the effect of a chitosan (Cs) coating on their physicochemical properties, cellular responses, and rheological behavior. Both Lip and Cs/Lip formulations displayed high encapsulation efficiency (>90%) and presented particle sizes of 120-150&#x202f;nm with low polydispersity. Storage studies demonstrated excellent colloidal stability, PAs retention, and antioxidant activity. Viability assays in Caco-2 and SH-SY5Y (neuroblastoma) cell lines confirmed the safety of the formulations and revealed increased viability at the highest tested concentrations (50&#x202f;&#x3bc;g/mL in Caco-2: PAs-Lip increase 32% and PAs-Cs/Lip increase 24%; 1&#x202f;&#x3bc;g/mL in SH-SY5Y: PAs-Lip increase 27% and PAs-Cs/Lip increase 40%). Notably, PAs encapsulation reduced the cytotoxic effects induced by the oxidant agent tert-butyl hydroperoxide, with Cs/Lip exhibiting the strongest protective activity. In summary, the developed formulations, due to their safety, stability, potential to increase cell viability, and rheological compatibility with aqueous-based formulations, represent interesting ingredients to be included in food products and convert them into functional foods.

The electrocatalytic activity of metals is intrinsically governed by their surface chemical states, which, however, often degrades due to surface oxidation during electrocatalysis. Thus, enhancing oxidation resistance to improve the catalytic performance of metal materials is a pivotal challenge. Herein, we report a strategy to revive the catalytic activity of oxidized Au(111) facets via chemical reduction by highly reductive radicals in situ generated during electrocatalysis. Using electrochemiluminescence microscopy (ECLM), we achieved the real-time visualization of an anomalous signal fluctuation on Au(111) facets during ECL reactions, which arises from the continuous surface redox dynamics. In conjunction with electrochemiluminescence self-interference spectroscopy (ECLIS) and finite element simulations, we reveal that the lifetime of co-reactant radical cations strongly modulates the reduction kinetics of Au surface oxides and that the localized Au oxide reduction is governed by the surface distribution of co-reactant radicals. For the first time, we capture the ECLM-based real-time images of the surface redox processes on Au(111) facets during electrocatalysis with a temporal resolution of 100&#xa0;ms. This work underscores the potential of ECLM for in situ monitoring of electrocatalytic reactions and establishes a new strategy for reviving the catalytic activity of Au(111) using reaction-derived highly reductive radicals.