Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation.

Implicit adaptation has been regarded as a rigid process that automatically operates in response to movement errors to keep the sensorimotor system precisely calibrated. This hypothesis has been challenged by recent evidence suggesting flexibility in this learning process. One compelling line of evidence comes from work suggesting that this form of learning is context-dependent, with the rate of learning modulated by error history. Specifically, learning was attenuated in the presence of perturbations exhibiting high variance compared to when the perturbation is fixed. However, these findings are confounded by the fact that the adaptation system corrects for errors of different magnitudes in a non-linear manner, with the adaptive response increasing in a proportional manner to small errors and saturating to large errors. Through simulations, we show that this non-linear motor correction function is sufficient to explain the effect of perturbation variance without referring to an experience-dependent change in error sensitivity. Moreover, by controlling the distribution of errors experienced during training, we provide empirical evidence showing that there is no measurable effect of perturbation variance on implicit adaptation. As such, we argue that the evidence to date remains consistent with the rigidity assumption.

The Origin of Movement Biases During Reaching.

Goal-directed movements can fail due to errors in our perceptual and motor systems. While these errors may arise from random noise within these sources, they also reflect systematic motor biases that vary with the location of the target. The origin of these systematic biases remains controversial. Drawing on data from an extensive array of reaching tasks conducted over the past 30 years, we evaluated the merits of various computational models regarding the origin of motor biases. Contrary to previous theories, we show that motor biases do not arise from systematic errors associated with the sensed hand position during motor planning or from the biomechanical constraints imposed during motor execution. Rather, motor biases are primarily caused by a misalignment between eye-centric and the body-centric representations of position. This model can account for motor biases across a wide range of contexts, encompassing movements with the right versus left hand, proximal and distal effectors, visible and occluded starting positions, as well as before and after sensorimotor adaptation.

Can the aerosol pollution extreme events be revealed by global reanalysis products?

Extreme aerosol pollution poses significant risks to the climate, environment, and human health. To investigate the formation and impacts of aerosol pollution extreme events (APEE), the reanalysis product presents meticulous spatiotemporal information on the three-dimensional distribution of aerosols. However, there is a lack of comprehensive evaluation and information regarding the data quality of reanalysis products employed in APEE research, as well as limited understanding of their spatial and temporal distribution, variation, and long-term trends. To address this scientific gap, we conducted a global study for distribution and variation patterns of APEE using two widely-used reanalysis products, MERRA-2 (Modern-Era Retrospective Analysis for Research-2) and CAMS (Copernicus Atmospheric Monitoring Service). The APEE was defined here as a day when the daily aerosol optical depth (AOD) exceeding its 90th percentile for a given station and month. Eleven distinct land regions worldwide were selected for evaluation by comparing both reanalysis products with MODIS satellite products and ground-based observations in terms of frequency, intensity, and temporal trends of APEE. The analysis indicates that MERRA-2 and CAMS exhibit high matching rates (70 % and 80 %, respectively) in terms of occurrence timeline for APEE at monthly and seasonal scales, while also exhibiting strong monthly correlation coefficients (>0.65) with ground-based observations over selected regions. The total AOD (-0.002 âˆ¼ -0.123 decade-1), APEE AOD (-0.004 âˆ¼ -0.293 decade-1), and APEE frequency (-0.264 âˆ¼ -1.769 day month-1 decade-1) of both observations and reanalysis products in most regions showed a decreasing trend with various magnitude, except for some regions such as South Asia where the trend is increasing. Based on the aforementioned evaluation, it is evident that reanalysis products are effective and useful in identifying the temporal trends associated with APEE.

Advanced feedback enhances sensorimotor adaptation.

It is widely recognized that sensorimotor adaptation is facilitated when feedback is provided throughout the movement compared with when it is provided at the end of the movement. However, the source of this advantage is unclear: continuous feedback is more ecological, dynamic, and available earlier than endpoint feedback. Here, we assess the relative merits of these factors using a method that allows us to manipulate feedback timing independent of actual hand position. By manipulating the onset time of "endpoint" feedback, we found that adaptation was modulated in a non-monotonic manner, with the peak of the function occurring in advance of the hand reaching the target. Moreover, at this optimal time, learning was of similar magnitude as that observed with continuous feedback. By varying movement duration, we demonstrate that this optimal time occurs at a relatively fixed time after movement onset, an interval we hypothesize corresponds to when the comparison of the sensory prediction and feedback generates the strongest error signal.

A cerebellar population coding model for sensorimotor learning.

The cerebellum is crucial for sensorimotor adaptation, using error information to keep the sensorimotor system well-calibrated. Here we introduce a population-coding model to explain how cerebellar-dependent learning is modulated by contextual variation. The model consists of a two-layer network, designed to capture activity in both the cerebellar cortex and deep cerebellar nuclei. A core feature of the model is that within each layer, the processing units are tuned to both movement direction and the direction of movement error. The model captures a large range of contextual effects including interference from prior learning and the influence of error uncertainty and volatility. While these effects have traditionally been taken to indicate meta learning or context-dependent memory within the adaptation system, our results show that they are emergent properties that arise from the population dynamics within the cerebellum. Our results provide a novel framework to understand how the nervous system responds to variable environments.

Serial dependence in timing at the perceptual level being modulated by working memory.

Recent experiences bias the perception of following stimuli, as has been verified in various kinds of experiments in visual perception. This phenomenon, known as serial dependence, may reflect mechanisms to maintain perceptual stability. In the current study, we examined several key properties of serial dependence in temporal perception. Firstly, we examined the source of the serial dependence effect in temporal perception. We found that perception without motor reproduction is sufficient to induce the sequential effect; motor reproduction caused a stronger effect and is achieved by biasing the perception of the future target duration rather than directly influencing the subsequent movement. Secondly, we ask how working memory influences serial dependence in a temporal reproduction task. By varying the delay time between standard duration and the reproduction, we showed that the strength of serial dependence is enhanced as the delay increased. Those features of serial dependence are consistent with what has been observed in visual perceptual tasks, for example, orientation perception or location perception. The similarities between the visual and the timing tasks may suggest a similar neural coding mechanism of magnitude between the visual stimuli and the duration.

Neutrophil Extracellular Traps Formation and Citrullinated Histones 3 Levels in Patients with Kawasaki Disease.

Background: Kawasaki disease (KD) is a vasculitis associated with vascular injury and autoimmune response. Inflammatory factors stimulate neutrophils to produce web-like structures called neutrophil extracellular traps (NETs). Citrullinated histone 3 (H3Cit) is one of the main protein components of neutrophil extracellular traps involved in the process of NETosis. The levels of NETs and H3Cit in the KD are not known. Objective: To determine the changes in the levels of NETs and H3Cit in KD. Methods: Children with KD were recruited and divided into the acute KD and the sub-acute KD group according to the disease phase and whether intravenous immunoglobulin (IVIG) was used or not. Peripheral venous blood was taken before and after the IVIG administration and sent for the examination of NETs by flow cytometry. The level of H3Cit was measured by enzyme-linked immunosorbent assay (ELISA). Results: The counts of NETs in the acute KD group significantly increased compared with the healthy controls (p<0.01). The level of H3Cit was significantly higher in the acute KD group than in the healthy control subjects. Of note, both the counts of NETs and the level of H3Cit decreased in the KD patients treated with IVIG compared with the acute KD group (p<0.01). Conclusion: Acute KD is characterized by an increased formation of NETs and high levels of H3Cit. IVIG significantly inhibited NETs formation and also reduced the level of plasma H3Cit in children with KD.

The Transcription Factor MbWRKY46 in Malus baccata (L.) Borkh Mediate Cold and Drought Stress Responses.

The living environment of plants is not static; as such, they will inevitably be threatened by various external factors for their growth and development. In order to ensure the healthy growth of plants, in addition to artificial interference, the most important and effective method is to rely on the role of transcription factors in the regulatory network of plant responses to abiotic stress. This study conducted bioinformatics analysis on the MbWRKY46 gene, which was obtained through gene cloning technology from Malus baccata (L.) Borkh, and found that the MbWRKY46 gene had a total length of 1068 bp and encodes 355 amino acids. The theoretical molecular weight (MW) of the MbWRKY46 protein was 39.76 kDa, the theoretical isoelectric point (pI) was 5.55, and the average hydrophilicity coefficient was -0.824. The subcellular localization results showed that it was located in the nucleus. After conducting stress resistance studies on it, it was found that the expression of MbWRKY46 was tissue specific, with the highest expression level in roots and old leaves. Low temperature and drought had a stronger induction effect on the expression of this gene. Under low temperature and drought treatment, the expression levels of several downstream genes related to low temperature and drought stress (AtKIN1, AtRD29A, AtCOR47A, AtDREB2A, AtERD10, AtRD29B) increased more significantly in transgenic Arabidopsis. This indicated that MbWRKY46 gene can be induced to upregulate expression in Arabidopsis under cold and water deficient environments. The results of this study have a certain reference value for the application of M. baccata MbWRKY46 in low-temperature and drought response, and provide a theoretical basis for further research on its function in the future.

Implicit reward-based motor learning.

Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can induce explicit adjustments in movement strategy, it remains unclear if this type of feedback also induces implicit learning. We examined this question in a center-out reaching task by gradually moving an invisible reward zone away from a visual target to a final rotation of 7.5° or 25° in a between-group design. Participants received binary feedback, indicating if the movement intersected the reward zone. By the end of the training, both groups modified their reach angle by about 95% of the rotation. We quantified implicit learning by measuring performance in a subsequent no-feedback aftereffect phase, in which participants were told to forgo any adopted movement strategies and reach directly to the visual target. The results showed a small, but robust (2-3°) aftereffect in both groups, highlighting that binary feedback elicits implicit learning. Notably, for both groups, reaches to two flanking generalization targets were biased in the same direction as the aftereffect. This pattern is at odds with the hypothesis that implicit learning is a form of use-dependent learning. Rather, the results suggest that binary feedback can be sufficient to recalibrate a sensorimotor map.

Implicit reward-based motor learning.

Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can induce explicit adjustments in movement strategy, it remains unclear if this type of feedback also induce implicit learning. We examined this question in a center-out reaching task by gradually moving an invisible reward zone away from a visual target to a final rotation of 7.5° or 25° in a between-group design. Participants received binary feedback, indicating if the movement intersected the reward zone. By the end of the training, both groups modified their reach angle by about 95% of the rotation. We quantified implicit learning by measuring performance in a subsequent no-feedback aftereffect phase, in which participants were told to forgo any adopted movement strategies and reach directly to the visual target. The results showed a small, but robust (2-3°) aftereffect in both groups, highlighting that binary feedback elicits implicit learning. Notably, for both groups, reaches to two flanking generalization targets were biased in the same direction as the aftereffect. This pattern is at odds with the hypothesis that implicit learning is a form of use-dependent learning. Rather, the results suggest that binary feedback can be sufficient to recalibrate a sensorimotor map.

Quantitative phase imaging of living red blood cells combining digital holographic microscopy and deep learning.

Digital holographic microscopy as a non-contacting, non-invasive, and highly accurate measurement technology, is becoming a valuable method for quantitatively investigating cells and tissues. Reconstruction of phases from a digital hologram is a key step in quantitative phase imaging for biological and biomedical research. This study proposes a two-stage deep convolutional neural network named VY-Net, to realize the effective and robust phase reconstruction of living red blood cells. The VY-Net can obtain the phase information of an object directly from a single-shot off-axis digital hologram. We also propose two new indices to evaluate the reconstructed phases. In experiments, the mean of the structural similarity index of reconstructed phases can reach 0.9309, and the mean of the accuracy of reconstructions of reconstructed phases is as high as 91.54%. An unseen phase map of a living human white blood cell is successfully reconstructed by the trained VY-Net, demonstrating its strong generality.

A unitary mechanism underlies adaptation to both local and global environmental statistics in time perception.

Our duration estimation flexibly adapts to the statistical properties of the temporal context. Humans and non-human species exhibit a perceptual bias towards the mean of durations previously observed as well as serial dependence, a perceptual bias towards the duration of recently processed events. Here we asked whether those two phenomena arise from a unitary mechanism or reflect the operation of two distinct systems that adapt separately to the global and local statistics of the environment. We employed a set of duration reproduction tasks in which the target duration was sampled from distributions with different variances and means. The central tendency and serial dependence biases were jointly modulated by the range and the variance of the prior, and these effects were well-captured by a unitary mechanism model in which temporal expectancies are updated after each trial based on perceptual observations. Alternative models that assume separate mechanisms for global and local contextual effects failed to capture the empirical results.

Non-invasive detection of haemoglobin, platelets, and total bilirubin using hyperspectral cameras.

Hyperspectral imaging has emerged as a promising high-resolution and real-time imaging technology with potential applications in medical diagnostics and surgical guidance. In this study, we developed a high-speed hyperspectral camera by integrating a Fabry-Perot cavity filter on each CMOS pixel. We used it to non-invasively detect three blood components (haemoglobin, platelet, and total bilirubin). Specifically, we acquired transmission images of the subject's fingers, extracted spectral signals at each wavelength, and used dynamic spectroscopy to obtain non-invasive blood absorption spectra. The prediction models were established using the PLSR method and were modelled and validated based on the standard clinical-biochemical test values. The experimental results demonstrated excellent performance. The best predictions were obtained for haemoglobin, with a high related coefficient (R) of 0.85 or more in both the calibration and prediction sets and a mean absolute percentage error (MAPE) of only 5.7%. The results for total bilirubin were also ideal, with R values exceeding 0.8 in both sets and a MAPE of 10.6%. Although the prediction results for platelets were slightly less satisfactory, the error was still less than 15%, indicating that the results were also acceptable. Overall, our study highlights the potential of hyperspectral imaging technology for the development of portable and affordable devices for blood analysis, which can be used in various settings.

Switchable Fluorescent Light-Up Aptamers Based on Riboswitch Architectures.

Fluorescent light-up RNA aptamers (FLAPs) such as Spinach or Mango can bind small fluorogens and activate their fluorescence. Here, we adopt a switching mechanism otherwise found in riboswitches and use it to engineer switchable FLAPs that can be activated or repressed by trigger oligonucleotides or small metabolites. The fluorophore binding pocket of the FLAPs comprises guanine (G) quadruplexes, whose critical nucleotides can be sequestered by corresponding anti-FLAP sequences, leading to an inactive conformation and thus preventing association with the fluorophore. We modified the FLAPs with designed toehold hairpins that carry either an anti-FLAP or an anti-anti-FLAP sequence within the loop region. The addition of an input RNA molecule triggers a toehold-mediated strand invasion process that refolds the FLAP into an active or inactive configuration. Several of our designs display close-to-zero leak signals and correspondingly high ON/OFF fluorescence ratios. We also modified purine aptamers to sequester a partial anti-FLAP or an anti-anti-FLAP sequence to control the formation of the fluorogen-binding conformation, resulting in FLAPs whose fluorescence is activated or deactivated in the presence of guanine or adenine. We demonstrate that switching modules can be easily combined to generate FLAPs whose fluorescence depends on several inputs with different types of input logic.

Synchronous Phase-Shifting Interference for High Precision Phase Imaging of Objects Using Common Optics.

Quantitative phase imaging and measurement of surface topography and fluid dynamics for objects, especially for moving objects, is critical in various fields. Although effective, existing synchronous phase-shifting methods may introduce additional phase changes in the light field due to differences in optical paths or need specific optics to implement synchronous phase-shifting, such as the beamsplitter with additional anti-reflective coating and a micro-polarizer array. Therefore, we propose a synchronous phase-shifting method based on the Mach-Zehnder interferometer to tackle these issues in existing methods. The proposed method uses common optics to simultaneously acquire four phase-shifted digital holograms with equal optical paths for object and reference waves. Therefore, it can be used to reconstruct the phase distribution of static and dynamic objects with high precision and high resolution. In the experiment, the theoretical resolution of the proposed system was 1.064 µm while the actual resolution could achieve 1.381 µm, which was confirmed by measuring a phase-only resolution chart. Besides, the dynamic phase imaging of a moving standard object was completed to verify the proposed system's effectiveness. The experimental results show that our proposed method is suitable and promising in dynamic phase imaging and measurement of moving objects using phase-shifting digital holography.

Screening the effective components in treating dampness stagnancy due to spleen deficiency syndrome and elucidating the potential mechanism of Poria water extract.

Poria is an important medicine for inducing diuresis to drain dampness from the middle energizer. However, the specific effective components and the potential mechanism of Poria remain largely unknown. To identify the effective components and the mechanism of Poria water extract (PWE) to treat dampness stagnancy due to spleen deficiency syndrome (DSSD), a rat model of DSSD was established through weight-loaded forced swimming, intragastric ice-water stimulation, humid living environment, and alternate-day fasting for 21 days. After 14 days of treatment with PWE, the results indicated that PWE increased fecal moisture percentage, urine output, D-xylose level and weight; amylase, albumin, and total protein levels; and the swimming time of rats with DSSD to different extents. Eleven highly related components were screened out using the spectrum-effect relationship and LC-MS. Mechanistic studies revealed that PWE significantly increased the expression of serum motilin (MTL), gastrin (GAS), ADCY5/6, p-PKAα/ß/γ cat, and phosphorylated cAMP-response element binding protein in the stomach, and AQP3 expression in the colon. Moreover, it decreased the levels of serum ADH, the expression of AQP3 and AQP4 in the stomach, AQP1 and AQP3 in the duodenum, and AQP4 in the colon. PWE induced diuresis to drain dampness in rats with DSSD. Eleven main effective components were identified in PWE. They exerted therapeutic effect by regulating the AC-cAMP-AQP signaling pathway in the stomach, MTL and GAS levels in the serum, AQP1 and AQP3 expression in the duodenum, and AQP3 and AQP4 expression in the colon.

MbMYBC1, a M. baccata MYB transcription factor, contribute to cold and drought stress tolerance in transgenic Arabidopsis.

Cold and drought stress considerably suppress the development of plants. In this study, a new MYB (v-myb avian myeloblastosis viral)TF gene, MbMYBC1, was isolated from the M. baccata and located in nucleus. MbMYBC1 has a positive response to low temperature and drought stress. After being introduced into Arabidopsis thaliana, the physiological indicators of transgenic Arabidopsis had corresponding changes under these two stresses, the activities of catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) increased, electrolyte leakage rate (EL) and the content of proline increased, but the content of chlorophyll decreased. In addition, its overexpression can also activate the downstream expression of AtDREB1A, AtCOR15a, AtERD10B and AtCOR47 related to cold stress and AtSnRK2.4, AtRD29A, AtSOD1and AtP5CS1 related to drought stress. Based on these results, we speculate that MbMYBC1 can respond to cold and hydropenia signals, and can be used in transgenic technology to improve plant tolerance to low temperature and drought stress.

Method for retrieving range-resolved aerosol microphysical properties from polarization lidar measurements.

Aerosol microphysical properties, such as volume concentration (VC) and effective radius (ER), are of great importance to evaluate their radiative forcing and impacts on climate change. However, range-resolved aerosol VC and ER still cannot be obtained by remote sensing currently except for the column-integrated one from sun-photometer observation. In this study, a retrieval method of range-resolved aerosol VC and ER is firstly proposed based on the partial least squares regression (PLSR) and deep neural networks (DNN), combining polarization lidar and collocated AERONET (AErosol RObotic NETwork) sun-photometer observations. The results show that the measurement of widely-used polarization lidar can be reasonably used to derive the aerosol VC and ER, with the determination coefficient (R2) of 0.89 (0.77) for VC (ER) by use of the DNN method. Moreover, it is proven that the lidar-based height-resolved VC and ER at near-surface are well consistent with independent observations of collocated Aerodynamic Particle Sizer (APS). Additionally, we found that there are significant diurnal and seasonal variations of aerosol VC and ER in the atmosphere at Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). Compared with columnar ones from the sun-photometer observation, this study provides a reliable and practical way to obtain full-day range-resolved aerosol VC and ER from widely-used polarization lidar observation, even under cloud conditions. Moreover, this study also can be applied to long-term observations by current ground-based lidar networks and spaceborne CALIPSO lidar, aiming to further evaluate aerosol climatic effects more accurately.

Pollution in river tributaries restricts the water quality of ecological water replenishment in the Baiyangdian watershed, China.

Natural rivers often have complex water network structures, and the continuous water inflow from tributaries may have crucial impacts on the water quality of ecological water replenishment in the mainstream. This study selected two main inflow rivers of the largest lake in Hebei Province (Baiyangdian), the Fu River and Baigou River, to explore the influence of tributaries on the quality changes of ecological replenishment water in the mainstreams. In December 2020 and 2021, water samples were collected along the two river routes, and eutrophic parameters and heavy metals were determined. The results showed that the tributaries of the Fu River were all severely polluted. With the inflows of the tributaries, the comprehensive pollution index of eutrophication greatly increased along the replenished water route of the Fu River, and the replenished water in the lower reaches of the Fu River mainstream was mostly considered moderate to heavy pollution. Whereas, because the Baigou River's tributaries were only moderately polluted, the water quality in the Baigou River's replenished water was mostly better than moderate pollution. Due to the slight pollution of heavy metals in the tributaries, the replenished water in both the Fu and Baigou Rivers did not show any impact from heavy metal pollution. Correlation and principal component analysis indicated that the main sources of serious eutrophic pollution in the tributaries of the Fu and Baigou Rivers were related to domestic sewage, industrial wastewater, plant decay, and sediment release. This non-point source pollution then caused the decline in the quality of the replenished water in the mainstreams. This study exposed a long-standing but neglected problem in ecological water replenishment and provided a scientific foundation for conducting better water management to improve the inland water environment.

Genetic switches based on nucleic acid strand displacement.

Toehold-mediated strand displacement (TMSD) is an isothermal switching process that enables the sequence-programmable and reversible conversion of DNA or RNA strands between single- and double-stranded conformations or other secondary structures. TMSD processes have already found widespread application in DNA nanotechnology, where they are used to drive DNA-based molecular devices or for the realization of synthetic biochemical computing circuits. Recently, researchers have started to employ TMSD also for the control of RNA-based gene regulatory processes in vivo, in particular in the context of synthetic riboregulators and conditional guide RNAs for CRISPR/Cas. Here, we provide a review over recent developments in this emerging field and discuss the opportunities and challenges for such systems in in vivo applications.