Decreased wrist rotation imitation abilities in children with autism spectrum disorder.

Introduction: While meaningless gross motor imitation (GMI) is a common challenge for children diagnosed with autism spectrum disorder (ASD), this topic has not attracted much attention and few appropriate test paradigms have been developed. Methods: The current study proposed a wrist rotation imitation (WRI) task (a meaningless GMI assignment), and established a WRI ability evaluation system using low-cost wearable inertial sensors, which acquired the simultaneous data of acceleration and angular acceleration during the WRI task. Three metrics (i.e., total rotation time, rotation amplitude, and symmetry) were extracted from those data of acceleration and angular acceleration, and then were adopted to construct classifiers based on five machine learning (ML) algorithms, including k-nearest neighbors, linear discriminant analysis, naive Bayes, support vector machines, and random forests. To illustrate our technique, this study recruited 49 ASD children (aged 3.5-6.5 years) and 59 age-matched typically developing (TD) children. Results: Findings showed that compared with TD children, those with ASD may exhibit shorter total rotation time, lower rotation amplitude, and weaker symmetry. This implies that children with ASD might exhibit decreased WRI abilities. The classifier with the naive Bayes algorithm outperformed than other four algorithms, and achieved a maximal classification accuracy of 88% and a maximal AUC value of 0.91. Two metrics (i.e., rotation amplitude and symmetry) had high correlations with the gross and fine motor skills [evaluated by Gesell Developmental Schedules-Third Edition and Psychoeducational Profile-3 (PEP-3)]. While, the three metrics had no significant correlation with the visual-motor imitation abilities (evaluated by the subdomain of PEP-3) and the ASD symptom severity [evaluated by the Childhood Autism Rating Scale (CARS)] . Discussion: The strengths of this study are associated with the low-cost measurement system, correlation between the WRI metrics and clinical measures, decreased WRI abilities in ASD, and high classification accuracy.

SpeechMirror: A Multimodal Visual Analytics System for Personalized Reflection of Online Public Speaking Effectiveness.

As communications are increasingly taking place virtually, the ability to present well online is becoming an indispensable skill. Online speakers are facing unique challenges in engaging with remote audiences. However, there has been a lack of evidence-based analytical systems for people to comprehensively evaluate online speeches and further discover possibilities for improvement. This paper introduces SpeechMirror, a visual analytics system facilitating reflection on a speech based on insights from a collection of online speeches. The system estimates the impact of different speech techniques on effectiveness and applies them to a speech to give users awareness of the performance of speech techniques. A similarity recommendation approach based on speech factors or script content supports guided exploration to expand knowledge of presentation evidence and accelerate the discovery of speech delivery possibilities. SpeechMirror provides intuitive visualizations and interactions for users to understand speech factors. Among them, SpeechTwin, a novel multimodal visual summary of speech, supports rapid understanding of critical speech factors and comparison of different speech samples, and SpeechPlayer augments the speech video by integrating visualization of the speaker's body language with interaction, for focused analysis. The system utilizes visualizations suited to the distinct nature of different speech factors for user comprehension. The proposed system and visualization techniques were evaluated with domain experts and amateurs, demonstrating usability for users with low visualization literacy and its efficacy in assisting users to develop insights for potential improvement.

Improving Accuracy of ADHD Diagnosis with the Combination of Brain Imaging and Behavioral Measures.

Neuropsychological measures may improve Attention-deficit/hyperactivity disorder (ADHD) diagnostic accuracy and enhance treatment response detection. Highquality evaluation indicators are necessary for accurate diagnosis of ADHD. Due to the high complexity of the pathogenesis of ADHD, it may not be possible to accurately diagnose ADHD only by relying on behavioral assessment or brain imaging examination. Therefore, the authors propose a comprehensive index that combines brain imaging behavioral and measures. The results showed that the classification performance of the composite index was better than that of the single behavior or brain image index.Clinical Relevance- The results of this study help to remind practicing clinicians to consider the results of multiple clinical examinations when clinically diagnosing ADHD patients.

Scientific Problem Solving and Brain Symmetry Index: An exploratory EEG study.

Scientific problem solving has recently attracted fixation in the field of cognitive neuroscience and science education. Until now, there is very little evidence on the brain dynamics of scientific problem-solving processes. In this study, we were interested in exploring whether Brain Symmetry Index (BSI) would be an EEG index to reveal neural information. The present EEG study used two levels of complexity physics problems to research the neural mechanism of problem solving. Results indicated that relatively greater BSI found during difficult problem solving on the prefrontal theta and beta band. However, smaller BSI on the occipital alpha was found when solving difficult problems. There was no significant relationship between BSI and self-effort evaluation. The current study proposes an EEG index - BSI to reflect underlying brain functional characteristic.

Decreased frontal lobe complexity in left-behind children during joint attention: a fNIRS study with multivariable and multiscale sample entropy analysis.

Human brain development is shaped by experiences, especially during preschool, the critical period for cognitive and socioemotional development. This study employed the functional Near-Infrared Spectroscopy technique to explore the neural differences between left-behind children (LBC) and non-left-behind children (NLBC) on joint attention. Through collecting brain image data of 50 children (26 boys, aged 65.08 ± 6.28 months) and conducting multivariable and multiscale sample entropy (MMSE) analysis, the present study found that: (i) LBC showed lower brain complexity than NLBC in right prefrontal cortex; (ii) all participants demonstrated higher brain complexity in responding to joint attention conditions, compared to initiating joint attention ones; (iii) their brain complexity during joint attention was negatively associated with their emotional abilities. The findings advance our understanding of early brain development in LBC by providing evidence for the neural process characteristics of joint attention. Implications for early intervention to promote their brain development are also addressed.

Inhibitory control associated with the neural mechanism of joint attention in preschoolers: An fNIRS evidence.

Joint attention (JA) is fundamental to the development of children's social functioning; both its response and initiation are closely related to executive function (EF), but the relationship between JA and EF has been relatively rarely studied. The present study aimed to investigate the between-condition differences in brain activation and synchronization of JA under four conditions: (1) stranger-Initiating Joint Attention (Stranger-IJA); (2) teacher-Initiating Joint Attention (Teacher-IJA); (3) stranger-Responding to Joint Attention (Stranger-RJA); and (4) teacher-Responding to Joint Attention (Teacher-RJA). It also aimed to explore the relationships between neuroimaging data and children's inhibitory control levels. To address these two goals, the present study employed 41 (aged 58.61 ± 8.64 months, 24 boys) preschool children through behavioral and functional Near-Infrared Spectroscopy (fNIRS) brain imaging assessment to measure children's EF and brain function under JA, respectively. The results revealed that: (1) a significantly higher prefrontal cortex (PFC) activation was triggered in IJA than RJA; (2) a significantly higher brain activation was triggered in JA with a stranger than with a teacher; (3) a significantly higher index of synchronization asymmetry was evoked in the left and right PFC during interaction with the teacher than with the stranger; and (4) preschoolers' brain activation and synchronization were correlated with their inhibitory control level. The findings advance our understanding of preschoolers' social cognitive development with a biological aspect, offer an opportunity to understand the potential risk of the neural disorder in preschoolers, and provide a basis and insight for preventing neural developmental disorders.

Randomized, controlled trial of a mixed early start Denver model for toddlers and preschoolers with autism.

The early start Denver model (ESDM) has been extensively studied as a promising early intervention approach for young children with autism spectrum disorder (ASD). Various methodological drawbacks from earlier ESDM investigations must be rectified to expand the application scopes. For this purpose, the present study recruited a very large sample of 249 autistic children (aged 24-47 months), and used a randomized controlled design to compare outcomes from a mixed ESDM (M-ESDM) intervention with a mixed discrete trial teaching (M-DTT) intervention which remains one of the most commonly-used programming for early intervention. Over the course of a 12-week period, both groups (i.e., M-ESDM and M-DTT groups) received 25 h of intensive intervention per week using individual, group, and parent coaching techniques. Findings showed that: (i) the M-ESDM significantly outperformed the M-DTT in enhancing children's developmental abilities in gross motor and personal-social skills for toddlers and preschoolers, as well as in language for preschoolers with mild/moderate ASD and toddlers; and (ii) the M-ESDM dramatically reduced the severity of autistic symptoms in toddlers with severe ASD only, when compared to the M-DTT. However, the M-ESDM did not outperform the M-DTT in terms of improving children's developmental abilities in adaptability and fine motor for toddlers and preschoolers, as well as in language for preschoolers with severe ASD. In addition, when compared to the M-DTT, the M-ESDM did not show an advantage in reducing the severity of autistic symptoms in toddlers with mild/moderate ASD and preschoolers. Clinical Trial Registration: Chinese Clinical Trial Registry. Registration number ChiCTR200039492.

Nonlinear features of gaze behavior during joint attention in children with autism spectrum disorder.

Since children with autism spectrum disorder (ASD) might exhibit a variety of aberrant response to joint attention (RJA) behaviors, there is growing interest in identifying robust, reliable and valid eye-tracking metrics for determining differences in RJA behaviors between typically developing (TD) children and those with ASD. Previous eye-tracking studies have not been deeply investigated nonlinear features of gaze time-series during RJA. As a main motivation, this study aimed to extract three nonlinear features (i.e., complexity, long-range correlation, and local instability) of gaze time-series during RJA in children with ASD, which can be measured by fractal dimension (FD), Hurst exponent (H), and largest Lyapunov exponent (LLE), respectively. To illustrate our idea, this study adopted a publicly accessible database, including eye-tracking data collected during RJA from 19 children with ASD (7.74 ± 2.73) and 30 TD children (8.02 ± 2.89), and conducted a battery of nonparametric analysis of covariance (ANCOVA), where gender was used as covariable. Findings showed that gaze time-series during RJA in autistic children may generally have greater FD but lower H than that in TD controls. This implies that children with ASD possess more complex and unpredictable gaze behaviors during RJA than TD children. Furthermore, nonlinear metrics outperformed traditional eye-tracking metrics in obtaining higher identification performance with an accuracy of 82% and an AUC value of 0.81, distinguishing the differences between successful and failed RJA trails, and predicting the severity of ASD symptoms. Findings might bring some new insights into the understanding of the impairments in RJA behaviors for children with ASD.

Fine-Grained Video Retrieval With Scene Sketches.

Benefiting from the intuitiveness and naturalness of sketch interaction, sketch-based video retrieval (SBVR) has received considerable attention in the video retrieval research area. However, most existing SBVR research still lacks the capability of accurate video retrieval with fine-grained scene content. To address this problem, in this paper we investigate a new task, which focuses on retrieving the target video by utilizing a fine-grained storyboard sketch depicting the scene layout and major foreground instances' visual characteristics (e.g., appearance, size, pose, etc.) of video; we call such a task "fine-grained scene-level SBVR". The most challenging issue in this task is how to perform scene-level cross-modal alignment between sketch and video. Our solution consists of two parts. First, we construct a scene-level sketch-video dataset called SketchVideo, in which sketch-video pairs are provided and each pair contains a clip-level storyboard sketch and several keyframe sketches (corresponding to video frames). Second, we propose a novel deep learning architecture called Sketch Query Graph Convolutional Network (SQ-GCN). In SQ-GCN, we first adaptively sample the video frames to improve video encoding efficiency, and then construct appearance and category graphs to jointly model visual and semantic alignment between sketch and video. Experiments show that our fine-grained scene-level SBVR framework with SQ-GCN architecture outperforms the state-of-the-art fine-grained retrieval methods. The SketchVideo dataset and SQ-GCN code are available in the project webpage https://iscas-mmsketch.github.io/FG-SL-SBVR/.

Complex network of eye movements during rapid automatized naming.

Introduction: Although the method of visualizing eye-tracking data as a time-series might enhance performance in the understanding of gaze behavior, it has not yet been thoroughly examined in the context of rapid automated naming (RAN). Methods: This study attempted, for the first time, to measure gaze behavior during RAN from the perspective of network-domain, which constructed a complex network [referred to as gaze-time-series-based complex network (GCN)] from gaze time-series. Hence, without designating regions of interest, the features of gaze behavior during RAN were extracted by computing topological parameters of GCN. A sample of 98 children (52 males, aged 11.50 ± 0.28 years) was studied. Nine topological parameters (i.e., average degree, network diameter, characteristic path length, clustering coefficient, global efficiency, assortativity coefficient, modularity, community number, and small-worldness) were computed. Results: Findings showed that GCN in each RAN task was assortative and possessed "small-world" and community architecture. Additionally, observations regarding the influence of RAN task types included that: (i) five topological parameters (i.e., average degree, clustering coefficient, assortativity coefficient, modularity, and community number) could reflect the difference between tasks N-num (i.e., naming of numbers) and N-cha (i.e., naming of Chinese characters); (ii) there was only one topological parameter (i.e., network diameter) which could reflect the difference between tasks N-obj (i.e., naming of objects) and N-col (i.e., naming of colors); and (iii) when compared to GCN in alphanumeric RAN, GCN in non-alphanumeric RAN may have higher average degree, global efficiency, and small-worldness, but lower network diameter, characteristic path length, clustering coefficient, and modularity. Findings also illustrated that most of these topological parameters were largely independent of traditional eye-movement metrics. Discussion: This article revealed the architecture and topological parameters of GCN as well as the influence of task types on them, and thus brought some new insights into the understanding of RAN from the perspective of complex network.

Correlational Analysis of the Physicochemical Indexes, Volatile Flavor Components, and Microbial Communities of High-Temperature Daqu in the Northern Region of China.

Daqu is a microbial-rich baijiu fermentation starter. The high-temperature Daqu plays an essential role in the manufacturing of sauce-flavored baijiu. However, few studies have focused on three kinds of high-temperature Daqu (white, yellow, and black Daqu) in northern China. In this study, the physicochemical indexes, volatile flavor compounds, and microbial characteristics of the three different colors of high-temperature Daqu in northern China were comparatively analyzed to reveal their potential functions. White Daqu (WQ) exhibited the highest liquefying power and starch, and black Daqu (BQ) showed the highest saccharifying and esterifying powers. A total of 96 volatile components were identified in the three types of Daqu, and the contents of the volatile components of yellow Daqu (YQ) were the highest. The microbial community structure analysis showed that Bacillus and Byssochlamys were dominant in BQ, Kroppenstedtia and Thermoascus were dominant in WQ, and Virgibacillus and Thermomyces dominated the YQ. The RDA analysis revealed the correlation between the dominant microorganisms and different physicochemical indexes. The Spearman correlation analysis indicated that Oceanobacillus, Saccharopolyspora, Staphylococcus, Pseudogracilibacillus, Byssochlamys, and Thermomyces showed positive correlations with part of the majority of the key volatile flavor compounds. This work provides a scientific basis for the actual production of different colors of high-temperature Daqu in the northern region of China for sauce-flavored baijiu.

Recurrent 3D Hand Pose Estimation Using Cascaded Pose-Guided 3D Alignments.

3D hand pose estimation is a challenging problem in computer vision due to the high degrees-of-freedom of hand articulated motion space and large viewpoint variation. As a consequence, similar poses observed from multiple views can be dramatically different. In order to deal with this issue, view-independent features are required to achieve state-of-the-art performance. In this paper, we investigate the impact of view-independent features on 3D hand pose estimation from a single depth image, and propose a novel recurrent neural network for 3D hand pose estimation, in which a cascaded 3D pose-guided alignment strategy is designed for view-independent feature extraction and a recurrent hand pose module is designed for modeling the dependencies among sequential aligned features for 3D hand pose estimation. In particular, our cascaded pose-guided 3D alignments are performed in 3D space in a coarse-to-fine fashion. First, hand joints are predicted and globally transformed into a canonical reference frame; Second, the palm of the hand is detected and aligned; Third, local transformations are applied to the fingers to refine the final predictions. The proposed recurrent hand pose module for aligned 3D representation can extract recurrent pose-aware features and iteratively refines the estimated hand pose. Our recurrent module could be utilized for both single-view estimation and sequence-based estimation with 3D hand pose tracking. Experiments show that our method improves the state-of-the-art by a large margin on popular benchmarks with the simple yet efficient alignment and network architectures.

Invigorating spleen, replenishing qi and tonifying kidney method treatment of traditional Chinese medicine for myasthenia gravis: A protocol for systematic review and meta-analysis.

BACKGROUND: Myasthenia gravis (MG) is an autoimmune disease related to the production of autoantibodies. It is mediated by antibodies against acetylcholine receptor (AChR), muscle specific kinase (MuSK) or other AChR related proteins in the postsynaptic muscle membrane, which interfere with the transmission of signals at the neuromuscular junction, resulting in clinical symptoms of skeletal muscle weakness and fatigue, leading to the occurrence and development of MG. At present, the incidence rate of Mg is increasing year by year. At present, the method of invigorating spleen, replenishing qi and tonifying kidney in traditional Chinese medicine has been widely used in the clinical treatment of MG, and the effect is good. The purpose of this study was to systematically evaluate the efficacy and safety of the method of invigorating the spleen, supplementing qi and tonifying the kidney in the treatment of MG. METHODS: We will search from the following eight databases: PubMed, Cochrane Library, EMBASE, Web of Science, CNKI, Sinomed, Wanfang, and Vip. All randomized controlled trial (RCT) literature has been searched and classified since the establishment of the database to date. In this study, two researchers independently screened and evaluated the quality of the retrieved literature. Cochrane risk bias assessment tool was used to evaluate the risk of bias. The meta-analysis uses RevMan 5.3 software provided by Cochrane Collaboration Network for meta analysis. RESULTS: This study compared the main outcome indicators: clinical response rate, recurrence rate, incidence of adverse reactions, quantitative myasthenia gravis score (QMG). Secondary outcomes were clinical absolute score, quality of life score (QOL), levels of inflammatory factors such as IL-6, IL-10, and serum acetylcholine receptor antibody (AChR-Ab) levels. CONCLUSION: The purpose of this study was to evaluate the efficacy and safety of the method of invigorating the spleen, supplementing qi and tonifying the kidney in treating MG, and to provide evidence based medicine.

Features of eye movements during rapid automatized naming in Chinese children aged 7-11 years.

Rapid Automatized Naming (RAN) tests have been well-documented to predict reading abilities as well as a variety of neurobiological disorders (e.g., developmental dyslexia). Traditional measures of RAN tests only take into account the naming time and accuracy and cannot reflect temporal-spatial features during RAN tests. Although the eye tracking approach appears to be a promising tool for characterizing the essential temporal-spatial characteristics of RAN tests, no research has been conducted to investigate whether and how gender, age, and task-type alter those characteristics. Additionally, no study has examined eye movements during a Chinese adaptation of RAN in order to expand the applicability of RAN to developmental dyslexia in Chinese. To address the concerns stated above, this article recruited 408 children (206 males, aged 7-11 years) and adopted eight measures to quantify features of eye movements during a Chinese adaptation of RAN. Findings showed that: (1) eight eye-movement measures had the main effects of task-type and age, but only five of them had the main effect of gender (in particular, females outperformed males); (2) RAN abilities observed by eight eye-movement measures initially developed quickly before the age of 9, and then entered a relatively sluggish development phase; (3) non-alphanumeric RAN tasks generally required higher mental load (implying more fixation counts, saccade counts, and regression counts, smaller average saccade amplitude, fixation duration fluctuation and saccade amplitude fluctuation, and longer average fixation duration and total time of naming) than alphanumeric ones; (4) there were significant correlations between total time of naming (a widely-used behavioral parameter) and other eye-movement measures; and (5) there were significant correlation between eight eye-movement measures and three attention-related skills observed from a number cancellation task. The current study might offer some perspectives on the understanding of normative data of eye movements during RAN in Chinese school-aged children, as well as the applications (e.g., developmental dyslexia) associated with RAN.

Effectiveness and safety analysis of SanHanHuaShi granules for the treatment of coronavirus disease 2019: Study protocol and statistical analysis plan for a randomized, parallel-controlled, open-label clinical trial.

Background: Coronavirus disease 2019 (COVID-19) was declared a global pandemic in March 2020 by the World Health Organization (WHO). As of July 2, 2022, COVID-19 has caused more than 545 million infections and 6.3 million deaths worldwide, posing a significant threat to human health. Currently, there is still a lack of effective prevention and control strategies for the variation and transmission of SARS-CoV-2. Traditional Chinese medicine (TCM), which has a unique theoretical system, has treated various conditions for thousands of years. Importantly, recent studies have revealed that TCM contributed significantly to COVID-19. SanHanHuaShi (SHHS) granules, a Chinese herbal medicine, which has been included in Protocol for the Diagnosis and Treatment of Novel Coronavirus Disease 2019 (6th to 9th editions) issued by the National Health Commission of China and used to prevent and treat COVID-19 disease. A previous retrospective cohort study showed that SHHS could significantly reduce the severity of mild and moderate COVID-19. However, there is an absence of high-quality randomized controlled clinical studies to confirm the clinical effectiveness of SHHS. Therefore, a clinical study protocol and a statistical analysis plan were designed to investigate the efficacy and safety of SHHS for the prevention and treatment of COVID-19. This study will increase the integrity and data transparency of the clinical research process, which is of great significance for improving the practical application of SHHS granules in the future. Methods and analysis: The study was designed as a 7-day, randomized, parallel controlled, open-label, noninferiority clinical trial of positive drugs. A total of 240 patients with mild and moderate COVID-19 will be enrolled and randomly assigned to receive SanHanHuaShi granules or LianHuaQingWen granules treatment in a 1:1 ratio. Disease classification, vital signs, SARS-CoV-2 nucleic acid testing, symptoms, medications, adverse events, and safety evaluations will be recorded at each visit. The primary outcome will be the clinical symptom recovery rate. Secondary outcomes will include the recovery time of clinical symptoms, negative conversion time of SARS-CoV-2 nucleic acid test negative conversion rate, hospitalization time, antipyretic time, rate of conversion to severe patients, and time and rate of single symptom recovery. Adverse incidents and safety assessments will be documented. All data will be analyzed using a predetermined statistical analysis plan, including our method for imputation of missing data, primary and secondary outcome analyses, and safety outcomes. Discussion: The results of this study will provide robust evidence to confirm the effectiveness and safety of SHHS in the treatment of COVID-19. Clinical Trial Registration: http://www.chictr.org.cn. Trial number: ChiCTR2200058080. Registered on 29 March 2022.

Entropy of eye movement during rapid automatized naming.

Numerous studies have focused on the understanding of rapid automatized naming (RAN), which can be applied to predict reading abilities and developmental dyslexia in children. Eye tracking technique, characterizing the essential ocular activities, might have the feasibility to reveal the visual and cognitive features of RAN. However, traditional measures of eye movements ignore many dynamical details about the visual and cognitive processing of RAN, and are usually associated with the duration of time spent on some particular areas of interest, fixation counts, revisited fixation counts, saccadic velocities, or saccadic amplitudes. To cope with this drawback, we suggested an entropy-based method to measure eye movements for the first time, which first mapped eye movements during RAN in a time-series and then analyzed the time-series by a proper definition of entropy from the perspective of information theory. Our findings showed that the entropy was more sensitive to reflect small perturbation (e.g., rapid movements between focuses in the presence of skipping or omitting some stimulus during RAN) of eye movements, and thus gained better performance than traditional measures. We also verified that the entropy of eye movements significantly deceased with the age and the task complexity of RAN, and significantly correlated with traditional eye-movement measures [e.g., total time of naming (TTN)] and the RAN-related skills [e.g., selective attention (SA), cognitive speed, and visual-motor integration]. Our findings may bring some new insights into the understanding of both RAN and eye tracking technique itself.

SceneSketcher-v2: Fine-Grained Scene-Level Sketch-Based Image Retrieval Using Adaptive GCNs.

Sketch-based image retrieval (SBIR) is a long-standing research topic in computer vision. Existing methods mainly focus on category-level or instance-level image retrieval. This paper investigates the fine-grained scene-level SBIR problem where a free-hand sketch depicting a scene is used to retrieve desired images. This problem is useful yet challenging mainly because of two entangled facts: 1) achieving an effective representation of the input query data and scene-level images is difficult as it requires to model the information across multiple modalities such as object layout, relative size and visual appearances, and 2) there is a great domain gap between the query sketch input and target images. We present SceneSketcher-v2, a Graph Convolutional Network (GCN) based architecture to address these challenges. SceneSketcher-v2 employs a carefully designed graph convolution network to fuse the multi-modality information in the query sketch and target images and uses a triplet training process and end-to-end training manner to alleviate the domain gap. Extensive experiments demonstrate SceneSketcher-v2 outperforms state-of-the-art scene-level SBIR models with a significant margin.

Establishing Normative Data for the Number Cancelation Test Among Children in Kindergartens and Primary Schools in China.

This study aimed to suggest an attention assessment tool using a Digital Pen for measuring the temporal-spatial parameters during the Number Cancelation Test (NCT), and then to establish the normative data for the NCT among children in kindergartens and primary schools in China by recruiting a total of 989 children (496 males). Four measures, i.e., selective attention (SA), speed of cognitive processing (SpC), averaged time of circlings (ATC), and averaged circumference of circled curves (ACCC), were proposed to evaluate the NCT performance. They basically have a development trend with fast speed in the beginning before Grade 1 or 2 of primary schools, and then enter an extremely slow development period (with ceiling or floor effect). SA and SpC have gender and grade main effects, while ATC and ACCC have the grade main effect, only. In particular, females have higher SA scores than males in middle class of kindergarten, and Grade 2-Grade 5 of primary school, but no gender differences in other grades; females have higher SpC scores than males in middle class of kindergarten, and Grade 3-4 of primary school, but no gender differences in other grades. More importantly, in clinical practice, if SA or SpC measure of a child is below than the 5th centile (i.e., p5 level) of his/her grade-specific normative data, then this child may be predicted to have a high-risk of learning disabilities. Findings suggest that the proposed method can be used for early screening of learning disabilities by setting appropriate cut-off values.

Efficacy of Traditional Chinese Medicine on Animal Model of IgA Nephropathy: A Systematic Review and Meta-Analysis.

Objective: Traditional Chinese medicine (TCM) has a long history in the treatment of Immunoglobulin A nephropathy (IgAN). A large number of animal experiments focused on the TCM treatment of IgAN are conducted every year. The evidence for these preclinical studies is not clear. This study summarized and evaluated the results of animal experiments on TCM treatment for IgAN. Methods: We systematically searched animal studies from 6 databases from inception to August 30, 2022. We included Chinese studies from the key magazine of China technology. The quality of the included studies was evaluated with the SYRCLE animal experimental bias risk assessment tool and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Results: Out of 832 records identified in the initial search, 30 studies were selected. The results indicated that, compared with the control group, the TCM treatment group improved 24 h urine protein (24 h-UP) level (standardized mean difference (SMD) 3.57, 95% confidence interval (CI) 4.48 to 2.66, P < 0.001), urine red blood cell (U-RBC) (SMD 13.66, 95% CI 17.99 to 9.32, P < 0.001), serum creatinine (Scr) (mean difference (MD) 10.89, 95% CI 17.00 to 4.77, P < 0.001), blood urea nitrogen (BUN) (MD 2.44, 95% CI 3.42 to 1.47, P < 0.001), tumor necrosis factor-α (TNF-α) (MD 171.28 to 95% CI 323.68 to 18.88, P=0.03), transforming growth factor-ß1 (TGF-ß) (SMD 4.02, 95% CI 7.26 to 0.77, P=0.02), matrix metalloproteinase-9/tissue inhibitors of metalloproteinase-1(MMP-9/TIMP-1) (MD 0.03, 95% CI 0.00 to 0.06, P=0.02), nephrin mRNA (SMD 3.39, 95% CI 2.59 to 4.18, P < 0.001). However, there is no difference in albumin level (MD 1.10, 95% CI 0.06 to 2.26, P=0.06) and interleukin-6 (IL-6) (MD 170.77, 95% CI 365.3 to 23.75, P=0.09). Conclusions: TCM can improve 24 h-UP, U-RBC, Scr, BUN, MMP-9/TIMP-1, TNF-α, TGF-ß, and nephrin mRNA of IgAN animal models. Moreover, there is a need for rigorous reporting of preclinical research methodology, which is essential to support the quality of preclinical research. Registration. This review was registered with a systematic review record CRD42020171404 in the PROSPERO database.

Effect of Environmental Microorganisms on Fermentation Microbial Community of Sauce-Flavor baijiu.

The compositions of the microbial community in fermented grains of Sauce-flavor baijiu produced in different regions have diverse characteristics; however, the reasons for this remain unclear. The present study investigated the contributions of environmental microorganisms to the microbial community as well as the volatile compounds in the fermented grains of Sauce-flavor baijiu produced in the Beijing region using high-throughput sequencing combined with sourcetracker analysis, and compared the differences of environmental microorganism and their roles in the production process of Sauce-flavor baijiu from different regions.The results showed that the environmental microorganisms in the tools were the main contributors of the bacterial and fungal communities in fermented grains during heap fermentation and at the beginning of pit fermentation. At the end of pit fermentation, pit mud was the main environmental source of bacterial community in fermented grains, while tools and Daqu were the main environmental sources of fungal community in fermented grains.Environmental microorganisms thrived on the functional microorganisms in the fermented grains of Sauce-flavor baijiu produced in the Beijing region and thus shaped the profiles of volatile compounds. Environmental microorganisms of Sauce-flavor baijiu in the Guizhou province and the Beijing region differed significantly, which is partially responsible for the distinctive characteristics in the microbial community structure of Sauce-flavor baijiu-fermented grains from different regions.