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.

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.

Riboswitch-inspired toehold riboregulators for gene regulation in Escherichia coli.

Regulatory RNA molecules have been widely investigated as components for synthetic gene circuits, complementing the use of protein-based transcription factors. Among the potential advantages of RNA-based gene regulators are their comparatively simple design, sequence-programmability, orthogonality, and their relatively low metabolic burden. In this work, we developed a set of riboswitch-inspired riboregulators in Escherichia coli that combine the concept of toehold-mediated strand displacement (TMSD) with the switching principles of naturally occurring transcriptional and translational riboswitches. Specifically, for translational activation and repression, we sequestered anti-anti-RBS or anti-RBS sequences, respectively, inside the loop of a stable hairpin domain, which is equipped with a single-stranded toehold region at its 5' end and is followed by regulated sequences on its 3' side. A trigger RNA binding to the toehold region can invade the hairpin, inducing a structural rearrangement that results in translational activation or deactivation. We also demonstrate that TMSD can be applied in the context of transcriptional regulation by switching RNA secondary structure involved in Rho-dependent termination. Our designs expand the repertoire of available synthetic riboregulators by a set of RNA switches with no sequence limitation, which should prove useful for the development of robust genetic sensors and circuits.

MbWRKY53, a M. baccata WRKY Transcription Factor, Contributes to Cold and Drought Stress Tolerance in Transgenic Arabidopsis thaliana.

Apple is an important horticultural crop, but various adverse environmental factors can threaten the quality and yield of its fruits. The ability of apples to resist stress mainly depends on the rootstock. Malus baccata (L.) Borkh. is a commonly used rootstock in Northeast China. In this study, it was used as the experimental material, and the target gene MbWRKY53 was screened through transcriptome analysis and Real-Time Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) after cold and drought treatment. Bioinformatics analysis revealed that this transcription factor (TF) belonged to the WRKY TF family, and its encoded protein was localized in the nucleus. RT-qPCR showed that the gene was more easily expressed in roots and young leaves and is more responsive to cold and drought stimuli. Functional validation in Arabidopsis thaliana confirmed that MbWRKY53 can enhance plant tolerance to cold and drought stress. Furthermore, by analyzing the expression levels of genes related to cold and drought stress in transgenic Arabidopsis lines, it was inferred that this gene can regulate the expression of stress-related genes through multiple pathways such as the CBF pathway, SOS pathway, Pro synthesis pathway, and ABA-dependent pathways, enhancing the adaptability of transgenic Arabidopsis to cold and drought environments.

Overexpression of a Grape WRKY Transcription Factor VhWRKY44 Improves the Resistance to Cold and Salt of Arabidopsis thaliana.

Plants are often exposed to biotic or abiotic stress, which can seriously impede their growth and development. In recent years, researchers have focused especially on the study of plant responses to biotic and abiotic stress. As one of the most widely planted grapevine rootstocks, 'Beta' has been extensively proven to be highly resistant to stress. However, further research is needed to understand the mechanisms of abiotic stress in 'Beta' rootstocks. In this study, we isolated and cloned a novel WRKY transcription factor, VhWRKY44, from the 'Beta' rootstock. Subcellular localization analysis revealed that VhWRKY44 was a nuclear-localized protein. Tissue-specific expression analysis indicated that VhWRKY44 had higher expression levels in grape roots and mature leaves. Further research demonstrated that the expression level of VhWRKY44 in grape roots and mature leaves was highly induced by salt and cold treatment. Compared with the control, Arabidopsis plants overexpressing VhWRKY44 showed stronger resistance to salt and cold stress. The activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) were significantly increased, and the contents of proline, malondialdehyde (MDA) and chlorophyll were changed considerably. In addition, significantly higher levels of stress-related genes were detected in the transgenic lines. The results indicated that VhWRKY44 was an important transcription factor in 'Beta' with excellent salt and cold tolerance, providing a new foundation for abiotic stress research.

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.

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.

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.

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.

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.

VDE-Net: a two-stage deep learning method for phase unwrapping.

Phase unwrapping is a critical step to obtaining a continuous phase distribution in optical phase measurements and coherent imaging techniques. Traditional phase-unwrapping methods are generally low performance due to significant noise or undersampling. This paper proposes a deep convolutional neural network (DCNN) with a weighted jump-edge attention mechanism, namely, VDE-Net, to realize effective and robust phase unwrapping. Experimental results revealed that the weighted jump-edge attention mechanism, which is first proposed and simple to calculate, is useful for phase unwrapping. The proposed algorithm outperformed other networks or common attention mechanisms. In addition, an unseen wrapped phase image of a living red blood cell (RBC) was successfully unwrapped by the trained VDE-Net, thereby demonstrating its strong generalization capability.

miR-23b Ameliorates nonalcoholic steatohepatitis by targeting Acyl-CoA thioesterases 4.

Non-alcoholic fatty liver disease (NAFLD) and its more advanced stages, Non-alcoholic steatohepatitis and Cirrhosis, are the most common liver diseases in the worldwide, especially in developing countries. NAFLD is distinguished by the accumulation of triglycerides within hepatocytes. An increasing body of evidence suggests that hepatic MicroRNAs play an important role in NAFLD by controlling lipid metabolism, inflammation, and fibrosis. However, the precise causative functions of miRNA in NAFLD remain unknown. Here, we discovered that mice lacking MicroRNA-23b developed NAFLD-like phenotypes such as increased serum triglyceride and lipid droplet accumulation. In db/db mice fed a high fat diet, MicroRNA-23b overexpression reduced liver weight and alleviated liver inflammation, apoptosis, and fibrosis. MicroRNA-23b regulates the acyl-CoA metabolic process via Acyl-CoA thioesterase 4 (Acot4), which interacts with Acetyl CoA Carboxylase (ACC), according to the RNA-seq analysis.

Research on Nonlinear Compensation of the MEMS Gyroscope under Tiny Angular Velocity.

The Micro-Electro-Mechanical System (MEMS) gyroscope has been widely used in various fields, but the output of the MEMS gyroscope has strong nonlinearity, especially in the range of tiny angular velocity. This paper proposes an adaptive Fourier series compensation method (AFCM) based on the steepest descent method and Fourier series residual correction. The proposed method improves the Fourier series fitting method according to the output characteristics of the MEMS gyroscope under tiny angular velocity. Then, the optimal weights are solved by the steepest descent method, and finally the fitting residuals are corrected by Fourier series to further improve the compensation accuracy. In order to verify the effectiveness of the proposed method, the angle velocity component of the earth's rotation is used as the input of the MEMS gyroscope to obtain the output of the MEMS gyroscope under tiny angular velocities. Experimental characterization resulted in an input angular velocity between -0.0036°/s and 0.0036°/s, compared with the original data, the polynomial compensation method, and the Fourier series compensation method, and the output nonlinearity of the MEMS gyroscope was reduced from 1150.87 ppm, 641.13 ppm, and 250.55 ppm to 68.89 ppm after AFCM compensation, respectively, which verifies the effectiveness and superiority of the proposed method.

Deletion of the miR-25/93/106b cluster induces glomerular deposition of immune complexes and renal fibrosis in mice.

IgA nephropathy (IgAN), the most common form of primary glomerulonephritis, is caused by immune system dysfunction and affects only the kidneys. miRNA was involved in IgAN, in which their roles are still unknown. Herein, we found increased glomerular medulla size, proteinuria, kidney artery resistance, kidney fibrosis and immune complex deposition in 5-month miR-25/93/106b cluster knockout (miR-TKO) mice. In vitro, the inhibition of miR-25 cluster could promote cell proliferation and increase fibrosis-related protein and transferrin receptor (TFRC) expression in human renal glomerular mesangial cell (HRMC). Luciferase assay revealed that inhibition of miR-93/106b cluster could upregulate Ccnd1 expression through direct binding with the 3'UTR of Ccnd1. Conversely, inhibition of Ccnd1 expression prevented miR-93/106b-induced effect in HRMC. These findings suggested that miR-25 cluster played an important role in the progression of IgAN, which provided new insights into the pathogenesis and treatment of IgAN.

Implicit adaptation to mirror reversal is in the correct coordinate system but the wrong direction.

Learning in visuomotor adaptation tasks is the result of both explicit and implicit processes. Explicit processes, operationalized as reaiming an intended movement to a new goal, account for a significant proportion of learning. However, implicit processes, operationalized as error-dependent learning that gives rise to aftereffects, appear to be highly constrained. The limitations of implicit learning are highlighted in the mirror-reversal task, where implicit corrections act in opposition to performance. This is surprising given the mirror-reversal task has been viewed as emblematic of implicit learning. One potential issue not being considered in these studies is that both explicit and implicit processes were allowed to operate concurrently, which may interact, potentially in opposition. Therefore, we sought to further characterize implicit learning in a mirror-reversal task with a clamp design to isolate implicit learning from explicit strategies. We confirmed that implicit adaptation is in the wrong direction for mirror reversal and operates as if the perturbation were a rotation and only showed a moderate attenuation after 3 days of training. This result raised the question of whether implicit adaptation blindly operates as though perturbations were a rotation. In a separate experiment, which directly compared a mirror reversal and a rotation, we found that implicit adaptation operates in a proper coordinate system for different perturbations: adaptation to a mirror reversal and rotational perturbation is more consistent with Cartesian and polar coordinate systems, respectively. It remains an open question why implicit process would be flexible to the coordinate system of a perturbation but continue to be directed inappropriately.NEW & NOTEWORTHY Recent studies have found that implicit learning may operate inappropriately in some motor tasks, requiring explicit strategies to improve performance. However, this inappropriate adaptation could be attributable to competitive interactions between explicit and implicit processes. After isolating implicit processes, we found that implicit adaptation remained in the wrong direction for a mirror reversal, acting as if it were a rotation. Interestingly, however, the implicit system is sensitive to a particular coordinate system, treating mirror reversal and rotation differently.

Association between insomnia and type 2 diabetes mellitus in Han Chinese individuals in Shandong Province, China.

PURPOSE: Diabetes and sleep disorders are public health threats worldwide, but the potential association between them is still unclear. METHODS: We conducted a community-based cross-sectional study including 5078 participants (2665, 52.5% male) to determine the association between insomnia and diabetes mellitus prevalence. RESULTS: In patients with type 2 diabetes mellitus (T2DM) and nondiabetic controls, the prevalence of insomnia was 20.2% (68/377) and 12.2% (578/4741), respectively. The results showed that insomnia was associated with T2DM after adjusting for age, sex, BMI, smoking, alcohol consumption, presence of disease history (hypertension, dyslipidemia, stroke, cardiovascular diseases, cancers), and depression (odds ratio [OR] = 1.31, 95% confidence interval [CI] 1.03-1.66). After stratifying by age and sex, insomnia was significantly associated with diabetes mellitus only in the subgroup of middle-aged participants (40-59 years) (OR = 1.61, 95% CI 1.16-2.23) and males (OR = 1.48, 95% CI 1.08-2.03) after controlling for the above covariates. CONCLUSIONS: This study suggests that insomnia is independently and significantly associated with diabetes mellitus in the northern Chinese population, especially in the 40-59-year-old age group and in males.

A biomimetic enzyme modified electrode for H2O2 highly sensitive detection.

An efficient catalyst based on artificial bionic peroxidase was synthesized for electrocatalysis. A poly(ethyleneimine)/Au nanoparticle composite (PEI-AuNP) was prepared and it was then linked to hemin via a coupling reaction between carboxyl groups in hemin and amino groups in PEI without the activation of a carboxyl group by carbodiimide. Fourier transform infrared (FTIR) spectroscopy verified the formation of amido bonds within the structure. The presence of AuNPs contributed greatly in establishing the amido bonds within the composite. Transmission electron microscopy (TEM) and UV-visible spectroscopy were also used to characterize the PEI-AuNP-hemin catalyst. PEI-AuNP-hemin exhibited intrinsic peroxidase-like catalytic activities. The PEI-AuNP-hemin deposited on a glass carbon electrode had strong sensing for H2O2 with a well-defined linear relationship between the amperometric response and H2O2 concentration in the range from 1 µM to 0.25 mM. The detection limit was 0.247 nM with a high sensitivity of 0.347 mA mM(-1) cm(-2). The peroxidase-like catalytic activity of PEI-AuNP-hemin is discussed in relation to its microstructure. The study suggests that PEI-AuNP-hemin may have promising application prospects in biocatalysis and bioelectronics.

Multi-wavelength lasers with suppressed spectral linewidth of 10 kHz.

High coherent multi-wavelength or multi-tone light source are in high demand for optical density wavelength division multiplexed (DWDM) networks as the telecommunication capacity expands exponentially. However the linewidths of commercial multi-wavelength semiconductor lasers are typically a few MHz which is not acceptable when the frequency spacing of the multi-tones is 10 GHz. In this paper, a novel and simple method to suppress the linewidths of the multi-wavelength from ~6 MHz to ~10 kHz using an all-optical approach is proposed and demonstrated. The linewidths of the multi-wavelength are suppressed by a factor of 600 and the noise level of the multi-wavelength is decreased by nearly 20 dB. Each wavelength of the multi-wavelength operates in single longitudinal mode. Finally, more than 8 wavelengths over 10 nm are suppressed simultaneously through the approach and scheme presented in this work.

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.