Exploring Instructional and Institutional Opportunities and Challenges in a Newly-Formed Translanguaging Dual- Language School

Translanguaging pedagogy disrupts linguistic inequalities and creates transformative spaces for emergent bilingual students in dual language education (DLE) programs to leverage and expand students’ full linguistic repertoires. Guided by translanguaging theory and positioning theory, this case study presents an analysis of the opportunities and the challenges of implementing translanguaging pedagogy in a co-teaching Chinese-English dual language Pre-K school in China. Using the entire school as a case, this investigation is based on data from videos and field notes of class observations, interviews of teachers, school leaders and parents, audio recording of school meetings, and school documents. The study focuses on two main factors: First, how translanguaging pedagogy was implemented in the school including the individual or coordinated translanguaging practices of 34 Chinese and English teachers and the challenges they encountered; second, the institutional factors including teachers’ institutional positionality and the understanding of translanguaging among stakeholders (teachers, administrative leaders, and parents), which all influence the implementation of translanguaging pedagogy. The findings provide a rounded view of how the school’s translanguaging policy provided opportunities for teachers to legitimately navigate between two languages in teacher-student interactions and teachers’ co-teaching practices. Teachers employed various translanguaging strategies to construct three translanguaging components (translanguaging bridges, translanguaging assessments, and translanguaging showcases) through which emergent bilingual students’ full linguistic repertoire were validated and developed. The school’s child-initiated play pedagogy and stakeholders’ strong translanguaging stance supported the implementation of translanguaging pedagogy. The findings also reveal that the legitimizing position of translanguaging pedagogy did not eliminate all the challenges teachers encountered. These challenges stemmed from teachers’ insufficient experience of practicing translanguaging and their limited skills in translanguaging co-teaching design. Discrepancies between the institutional positions and co-teaching assignments, between language equivalency inside and outside the classroom, and between different stakeholders’ expectations created hindrances for the implementation of translanguaging pedagogy. This study adds to the growing research on translanguaging in early childhood education, as well as offering useful translanguaging strategies and examples for language teachers at Pre-K schools. This study explores the ideological boundary between two languages and reflects the core of translanguaging theory, which resonates with anti-bias education and conceptualizes the sociolinguistic reality and symbolic competence of emergent bilingual students. This study also provides insights about what kind of administrative and peripheral support is needed for translanguaging to occur and what obstacles may hinder teachers’ translanguaging practices in this specific DLE program. The findings can inform other schools to overcome challenges and enact an anti-bias and dynamic bilingual education based on the acknowledgment of the full linguistic capital students bring to the classroom

Average Consensus in Multiagent Systems with the Problem of Packet Losses When Using the Second-Order Neighbors’ Information

This paper mainly investigates the average consensus of multiagent systems with the problem of packet losses when both the first-order neighbors’ information and the second-order neighbors’ information are used. The problem is formulated under the sampled-data framework by discretizing the first-order agent dynamics with a zero-order hold. The communication graph is undirected and the loss of data across each communication link occurs at certain probability, which is governed by a Bernoulli process. It is found that the distributed average consensus speeds up by using the second-order neighbors’ information when packets are lost. Numerical examples are given to demonstrate the effectiveness of the proposed methods

Diurnal Variations in Neural Activity of Healthy Human Brain Decoded with Resting-State Blood Oxygen Level Dependent fMRI

It remains an ongoing investigation about how the neural activity alters with the diurnal rhythms in human brain. Resting-state functional magnetic resonance imaging (RS-fMRI) reflects spontaneous activities and/or the endogenous neurophysiological process of the human brain. In the present study, we applied the ReHo (regional homogeneity) and ALFF (amplitude of low frequency fluctuation) based on RS-fMRI to explore the regional differences in the spontaneous cerebral activities throughout the entire brain between the morning and evening sessions within a 24-h time cycle. Wide spread brain areas were found to exhibit diurnal variations, which may be attributed to the internal molecular systems regulated by clock genes, and the environmental factors including light-dark cycle, daily activities and homeostatic sleep drive. Notably, the diurnal variation of default mode network (DMN) suggests that there is an adaptation or compensation response within the subregions of DMN, implying a balance or a decoupling of regulation between these regions.National Natural Science Foundation of China [81371359]; National Basic Research Program of China [2015CB755500]; Basic Research Program of Shenzhen [JCYJ20160429191938883]SCI(E)[email protected]

STROBE-GnRHa pretreatment in frozen-embryo transfer cycles improves clinical outcomes for patients with persistent thin endometrium: A case-control study.

The well-prepared endometrium with appropriate thickness plays a critical role in successful embryo implantation. The thin endometrium is the main factor of frozen-embryo transfer (FET), resulting in the failure of implantation undergoing FET. Hormone treatment is suggested to improve endometrium thickness; however, among the larger numbers of cases, it cannot reach the sufficient thickness, which leads to a high cancelation rate of embryo transfer as well as waste high-quality embryos. Thus, it increases the burden to patients in both economic and psychological perspectives. We performed a retrospective observational study, which was composed with 2 cohorts, either with the conventional hormone replacement therapy (HRT) protocol or HRT with gonadotrophin-releasing hormone agonist (GnRHa) pretreatment to prepare the endometrium before FET. The measurements of endometrium thickness, hormone level, transfer cycle cancelation rate, pregnancy rate, and implantation rate were retrieved from the medical records during the routine clinic visits until 1 month after embryo transfer. The comparisons between 2 cohorts were performed by t-test or Mann-Whitney U test depending on the different attributions of data. In total, 49 cycles were under HRT with GnRHa pretreatment and 84 cycles were under the conventional HRT protocol. HRT with GnRHa pretreatment group improved the endometrial thickness (8.13 ± 1.79 vs 7.51 ± 1.45, P = .031), decreased the transfer cancelation rate (P = .003), and increased clinical pregnancy rate and implantation rate significantly (both P = .001). Additionally, luteinizing hormone level in pretreatment group was consistently lower than conventional HRT group (P < .05). Our study revealed HRT with GnRHa pretreatment efficiently improved the endometrial thickness, therefore, decreased the FET cycle cancelation. It also elevated the embryo implantation rate and clinical pregnancy rate by improving endometrial receptivity

A novel dual GLP-1/GIP receptor agonist alleviates cognitive decline by re-sensitizing insulin signaling in the Alzheimer icv. STZ rat model

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder, accompanied by memory loss and cognitive impairments, and there is no effective treatment for it at present. Since type 2 diabetes (T2DM) has been identified as a risk factor for AD, the incretins glucagon-like peptide 1 (GLP-1) and glucose dependent insulinotropic polypeptide (GIP), promising antidiabetic agents for the treatment of type 2 diabetes, have been tested in models of neurodegenerative disease including AD and achieved good results. Here we show for the first time the potential neuroprotective effect of a novel dual GLP-1/GIP receptor agonist (DA-JC4) in the icv. streptozotocin (STZ)-induced AD rat model. Treatment with DA-JC4 (10 nmol/kg ip.) once-daily for 14 days after STZ intracerebroventricular (ICV) administration significantly prevented spatial learning deficits in a Y- maze test and Morris water maze tests, and decreased phosphorylated tau levels in the rat cerebral cortex and hippocampus. DA-JC4 also alleviated the chronic inflammation response in the brain (GFAP-positive astrocytes, IBA1-positive microglia). Apoptosis was reduced as shown in the reduced ratio of pro-apoptotic BAX to anti- apoptotic Bcl-2 levels. Importantly, insulin signaling was re-sensitized as evidenced by a reduction of phospho-IRS1Ser1101 levels and phospho-AktSer473 up-regulation. In conclusion, the novel dual agonist DA-JC4 shows promise as a novel treatment for sporadic AD, and reactivating insulin signaling pathways may be a key mechanism that prevents disease progression in AD

Nonparametric Mean Shift Functional Detection in the Functional Space for Task and Resting-state fMRI

International audienceIn functional Magnetic Resonance Imaging (fMRI) data analysis, normalization of time series is an important and sometimes necessary preprocessing step in many widely used methods. The space of normalized time series with n time points is the unit sphere S^{n-2}, named the functional space. Riemannian framework on the sphere, including the geodesic, the exponential map, and the logarithmic map, has been well studied in Riemannian geometry. In this paper, by introducing the Riemannian framework in the functional space, we propose a novel nonparametric robust method, namely Mean Shift Functional Detection (MSFD), to explore the functional space. The first merit of the MSFD is that it does not need many assumptions on data which are assumed in many existing method, e.g. linear addition (GLM, PCA, ICA), uncorrelation (PCA), independence (ICA), the number and the shape of clusters (FCM). Second, MSFD takes into account the spatial information and can be seen as a multivariate extension of the functional connectivity analysis method. It is robust and works well for activation detection in task study even with a biased activation reference. It is also able to find the functional networks in resting-state study without a user-selected "seed" region. Third, it can enhance the boundary between different functional networks. Experiments were conducted on synthetic and real data to compare the performance of the proposed method with GLM and ICA. The experimental results validated the accuracy and robustness of MSFD, not only for activation detection in task study but also for functional network exploration in resting-state study

Effects of the Largest Lake of the Tibetan Plateau on the Regional Climate

Qinghai Lake is the largest lake in China. However, its influence on the local climate remains poorly understood. By using an atmosphere-lake coupled model, we investigated the impact of the lake on the local climate. After the adjustment of four key parameters, the model reasonably reproduced the lake-air interaction. Superimposed by the orographic effects on lake-land breeze circulation, the presence of the lake enhanced precipitation over the southern part of the lake and its adjacent land, while slightly reduced precipitation along the northern shore of the lake. The lake effect on local precipitation revealed a distinct seasonal and diurnal variability, reducing precipitation in May (-6.6%) and June (-4.5%) and increasing it from July (5.7%) to November (125.6%). During the open water season, the lake's daytime cooling effect weakened and the nighttime warming effect strengthened, affecting spatial distribution and intensity of lake-induced precipitation. In early summer, precipitation slightly decreased over the north part of the lake due to the lake's daytime cooling. In turn, lake-induced nighttime warming increased precipitation over the southern section of the lake and its adjacent land. With the start of the autumn cooling in September, heat and moisture fluxes from the lake resulted in precipitation increase in both daytime and nighttime over the entire lake. In October, the background atmospheric circulation coupled with the strong lake effects lead to a small amount but high proportion of lake-induced precipitation spreading evenly over the lake.Peer reviewe

Genome-wide comparison of DNA hydroxymethylation in mouse embryonic stem cells and neural progenitor cells by a new comparative hMeDIP-seq method

The genome-wide distribution patterns of the ‘6th base’ 5-hydroxymethylcytosine (5hmC) in many tissues and cells have recently been revealed by hydroxymethylated DNA immunoprecipitation (hMeDIP) followed by high throughput sequencing or tiling arrays. However, it has been challenging to directly compare different data sets and samples using data generated by this method. Here, we report a new comparative hMeDIP-seq method, which involves barcoding different input DNA samples at the start and then performing hMeDIP-seq for multiple samples in one hMeDIP reaction. This approach extends the barcode technology from simply multiplexing the DNA deep sequencing outcome and provides significant advantages for quantitative control of all experimental steps, from unbiased hMeDIP to deep sequencing data analysis. Using this improved method, we profiled and compared the DNA hydroxymethylomes of mouse ES cells (ESCs) and mouse ESC-derived neural progenitor cells (NPCs). We identified differentially hydroxymethylated regions (DHMRs) between ESCs and NPCs and uncovered an intricate relationship between the alteration of DNA hydroxymethylation and changes in gene expression during neural lineage commitment of ESCs. Presumably, the DHMRs between ESCs and NPCs uncovered by this approach may provide new insight into the function of 5hmC in gene regulation and neural differentiation. Thus, this newly developed comparative hMeDIP-seq method provides a cost-effective and user-friendly strategy for direct genome-wide comparison of DNA hydroxymethylation across multiple samples, lending significant biological, physiological and clinical implications

Bibliometric and visualization analysis of matrix metalloproteinases in ischemic stroke from 1992 to 2022

BackgroundMatrix metalloproteinases (MMPs) are important players in the complex pathophysiology of ischemic stroke (IS). Recent studies have shown that tremendous progress has been made in the research of MMPs in IS. However, a comprehensive bibliometric analysis is lacking in this research field. This study aimed to introduce the research status as well as hotspots and explore the field of MMPs in IS from a bibliometric perspective.MethodsThis study collected 1,441 records related to MMPs in IS from 1979 to 2022 in the web of science core collection (WoSCC) database, among them the first paper was published in 1992. CiteSpace, VOSviewer, and R package “bibliometrix” software were used to analyze the publication type, author, institution, country, keywords, and other relevant data in detail, and made descriptive statistics to provide new ideas for future clinical and scientific research.ResultsThe change in the number of publications related to MMPs in IS can be divided into three stages: the first stage was from 1992 to 2012, when the number of publications increased steadily; the second stage was from 2013 to 2017, when the number of publications was relatively stable; the third stage was from 2018 to 2022, when the number of publications began to decline. The United States and China, contributing more than 64% of publications, were the main drivers for research in this field. Universities in the United States were the most active institutions and contributed the most publications. STROKE is the most popular journal in this field with the largest publications as well as the most co-cited journal. Rosenberg GA was the most prolific writer and has the most citations. “Clinical,” “Medical,” “Neurology,” “Immunology” and “Biochemistry molecular biology” were the main research areas of MMPs in IS. “Molecular regulation,” “Metalloproteinase-9 concentration,” “Clinical translation” and “Cerebral ischemia–reperfusion” are the primary keywords clusters in this field.ConclusionThis is the first bibliometric study that comprehensively mapped out the knowledge structure and development trends in the research field of MMPs in IS in recent 30 years, which will provide a reference for scholars studying this field