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Dementia represents a significant global health challenge, with early screening during the preclinical stage being crucial for effective management. Traditional diagnostic biomarkers for Alzheimer's Disease, the most common form of dementia, are limited by cost and invasiveness. Mild cognitive impairment (MCI), a precursor to dementia, is currently identified through neuropsychological tests like the Montreal Cognitive Assessment (MoCA), which are not suitable for large-scale screening. Eye-tracking technology, capturing and quantifying eye movements related to cognitive behavior, has emerged as a promising tool for cognitive assessment. Subtle changes in eye movements could serve as early indicators of MCI. However, the interpretation of eye-tracking data is challenging. This study introduced a dementia screening tool, VR Eye-tracking Cognitive Assessment (VECA), using eye-tracking technology, machine learning, and virtual reality (VR) to offer a non-invasive, efficient alternative capable of large-scale deployment. VECA was conducted with 201 participants from Shenzhen Baoan Chronic Hospital, utilizing eye-tracking data captured via VR headsets to predict MoCA scores and classify cognitive impairment across different educational backgrounds. The support vector regression model employed demonstrated a high correlation (0.9) with MoCA scores, significantly outperforming baseline models. Furthermore, it established optimal cut-off scores for identifying cognitive impairment with notable sensitivity (88.5%) and specificity (83%). This study underscores VECA's potential as a portable, efficient tool for early dementia screening, highlighting the benefits of integrating eye-tracking technology, machine learning, and VR in cognitive health assessments.
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Information exchange between brain regions is key to understanding information processing for social decision-making, but most analyses ignore its dynamic nature. New insights on this dynamic might help us to uncover the neural correlates of social cognition in the healthy population and also to understand the malfunctioning neural computations underlying dysfunctional social behavior in patients with mental disorders. In this work, we used a multi-round bargaining game to detect switches between distinct bargaining strategies in a cohort of 76 healthy participants. These switches were uncovered by dynamic behavioral modeling using the hidden Markov model. Proposing a novel model of dynamic effective connectivity to estimate the information flow between key brain regions, we found a stronger interaction between the right temporoparietal junction (rTPJ) and the right dorsolateral prefrontal cortex (rDLPFC) for the strategic deception compared with the social heuristic strategies. The level of deception was associated with the information flow from the Brodmann area 10 to the rTPJ, and this association was modulated by the rTPJ-to-rDLPFC information flow. These findings suggest that dynamic bargaining strategy is supported by dynamic reconfiguration of the rDLPFC-and-rTPJ interaction during competitive social interactions.
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Mapeo Encefálico , Interacción Social , Humanos , Encéfalo , Conducta Social , Corteza Prefrontal/diagnóstico por imagen , Imagen por Resonancia MagnéticaRESUMEN
Nitrous oxide (N2O) is an important greenhouse gas that plays a significant role in atmospheric photochemical reactions and contributes to stratospheric ozone depletion. Soils are the main sources of N2O emissions. In recent years, it has been demonstrated that soil is not only a source but also a sink of N2O uptake and consumption. N2O emissions at the soil surface are the result of gross N2O production, uptake, and consumption, which are co-occurring processes. Soil N2O uptake and consumption are complex biological processes, and their mechanisms are still worth an in-depth systematic study. This paper aimed to systematically address the current research progress on soil N2O uptake and consumption. Based on a bibliometric perspective, this study has highlighted the pathways of soil N2O uptake and consumption and their driving factors and measurement techniques. This systematic review of N2O uptake and consumption will help to further understand N transformations and soil N2O emissions.
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Gases de Efecto Invernadero , Suelo , Óxido Nitroso/análisis , Microbiología del SueloRESUMEN
Nitrogen losses in agricultural systems can be reduced through enhanced-efficiency fertilizers (EEFs), which control the physicochemical release from fertilizers and biological nitrogen transformations in soils. The adoption of EEFs by farmers requires evidence of consistent performance across soils, crops and climates, paired with information on the economic advantages. Here we show that the benefits of EEFs due to avoided social costs of nitrogen pollution considerably outweigh their costs-and must be incorporated in fertilizer policies. We outline new approaches to the design of EEFs using enzyme inhibitors with modifiable chemical structures and engineered, biodegradable coatings that respond to plant rhizosphere signalling molecules.
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Nitrification and immobilization compete for soil ammonium (NH4+); the relative dominance of these two processes has been suggested to reflect the potential risk of nitrogen loss from soils. Here, we compiled a database and developed a stochastic gradient boosting model to predict the global potential risk of nitrogen loss based on the ratio of nitrification to immobilization (N/I). We then conducted a meta-analysis to evaluate the effects of common management practices on the N/I ratio. The results showed that the soil N/I ratio varied with climate zones and land use. Soil total carbon, total nitrogen, pH, fertilizer nitrogen application rate, mean annual temperature, and mean annual precipitation are important factors of soil N/I ratio. Meta-analysis indicated that biochar, straw, and nitrification inhibitor application reduced the soil N/I ratio by 67, 64, and 78%, respectively. Returning plantation to forest and cropland to grassland decreased the soil N/I ratio by 88 and 45%, respectively. However, fertilizer nitrogen application increased the soil N/I ratio by 92%. Our study showed that the soil N/I ratio and its associated risk level of nitrogen loss were highly related to long-term soil and environmental properties with high spatial heterogeneity.
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Nitrificación , Nitrógeno , Fertilizantes/análisis , Bosques , Nitrógeno/análisis , Suelo , Microbiología del SueloRESUMEN
Triple network dysfunction theory of schizophrenia postulates that the interaction between the default-mode and the fronto-parietal executive network is disrupted by aberrant salience signals from the right anterior insula (rAI). To date, it is not clear how the proposed resting-state disruption translates to task-processing inefficiency in subjects with schizophrenia. Using a contiguous resting and 2-back task performance fMRI paradigm, we quantified the change in effective connectivity that accompanies rest-to-task state transition in 29 clinically stable patients with schizophrenia and 31 matched healthy controls. We found an aberrant task-evoked increase in the influence of the rAI to both executive (Cohen's d = 1.35, p = 2.8 × 10-6) and default-mode (Cohen's d = 1.22, p = 1.5 × 10-5) network regions occur in patients when compared to controls. In addition, the effective connectivity from middle occipital gyrus (dorsal visual cortex) to insula is also increased in patients as compared with healthy controls. Aberrant insula to executive network influence is pronounced in patients with more severe negative symptom burden. These findings suggest that control signals from rAI are abnormally elevated and directed towards both task-positive and task-negative brain regions, when task-related demands arise in schizophrenia. This aberrant, undiscriminating surge in salience signalling may disrupt contextually appropriate allocation of resources in the neuronal workspace in patients with schizophrenia.
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Esquizofrenia , Mapeo Encefálico , Corteza Cerebral/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética , Red Nerviosa/diagnóstico por imagen , Esquizofrenia/diagnóstico por imagenRESUMEN
In rabbit depressor nerve fibers, an on-off firing pattern, period-1 firing, and integer multiple firing with quiescent state were observed as the static pressure level was increased. A bursting pattern with bursts at the systolic phase of blood pressure, continuous firing, and bursting with burst at diastolic phase and quiescent state at systolic phase were observed as the mean level of the dynamic blood pressure was increased. For both static and dynamic pressures, the firing frequency of the first two firing patterns increased and of the last firing pattern decreased due to the quiescent state. If the quiescent state is disregarded, the spike frequency becomes an increasing trend. The instantaneous spike frequency of the systolic phase bursting, continuous firing, and diastolic phase bursting can reflect the temporal process of the systolic phase, whole procedure, and diastolic phase of the dynamic blood pressure signal, respectively. With increasing the static current corresponding to pressure level, the deterministic Hodgkin-Huxley (HH) model manifests a process from a resting state first to period-1 firing via a subcritical Hopf bifurcation and then to a resting state via a supercritical Hopf bifurcation, and the firing frequency increases. The on-off firing and integer multiple firing were here identified as noise-induced firing patterns near the subcritical and supercritical Hopf bifurcation points, respectively, using the stochastic HH model. The systolic phase bursting and diastolic phase bursting were identified as pressure-induced firings near the subcritical and supercritical Hopf bifurcation points, respectively, using an HH model with a dynamic signal. The firing, spike frequency, and instantaneous spike frequency observed in the experiment were simulated and explained using HH models. The results illustrate the dynamics of different firing patterns and the frequency and temporal coding mechanisms of aortic baroreceptor.