Evaluation of Individual Contribution in Blended Collaborative Learning

With the deepening of classroom teaching reform, blended collaborative learning has become a common collaborative learning method, and its significance and value has been verified by many parties. However, there is still a lack of quantitative analysis and detailed insight into the internal interaction dynamics of the group at the individual level. There are limitations in the evaluation dimensions and methods of individual contribution in collaborative learning in previous studies, so it is difficult to obtain a comprehensive evaluation of individual contribution. The purpose of this study is to build an effective evaluation model of individual contribution in blended collaborative learning. Discussion recordings and text data in collaboration were collected in a non-invasive way to validate the model. Based on evaluation model, the characteristics and rules behind the data deeply were explored, the collaborative process of the blended collaborative learning was analyzed and mined, and the characteristics of learners\u27 contribution were summarized to support the development of blended collaborative learning

Blood pressure and expression of microRNAs in whole blood

Background: Blood pressure (BP) is a complex, multifactorial clinical outcome driven by genetic susceptibility, behavioral choices, and environmental factors. Many molecular mechanisms have been proposed for the pathophysiology of high BP even as its prevalence continues to grow worldwide, increasing morbidity and marking it as a major public health concern. To address this, we evaluated miRNA profiling in blood leukocytes as potential biomarkers of BP and BP-related risk factors. Methods: The Beijing Truck Driver Air Pollution Study included 60 truck drivers and 60 office workers examined in 2008. On two days separated by 1–2 weeks, we examined three BP measures: systolic, diastolic, and mean arterial pressure measured at both pre- and post-work exams for blood NanoString nCounter miRNA profiles. We used covariate-adjusted linear mixed-effect models to examine associations between BP and increased miRNA expression in both pooled and risk factor-stratified analyses. Results: Overall 43 miRNAs were associated with pre-work BP (FDR<0.05). In stratified analyses different but overlapping groups of miRNAs were associated with pre-work BP in truck drivers, high-BMI participants, and usual alcohol drinkers (FDR<0.05). Only four miRNAs were associated with post-work BP (FDR<0.05), in ever smokers. Conclusion: Our results suggest that many miRNAs were significantly associated with BP in subgroups exposed to known hypertension risk factors. These findings shed light on the underlying molecular mechanisms of BP, and may assist with the development of a miRNA panel for early detection of hypertension

LncRNA BCAR4, targeting to miR-665/STAT3 signaling, maintains cancer stem cells stemness and promotes tumorigenicity in colorectal cancer

Abstract Background Breast cancer anti-estrogen resistance 4 (BCAR4) is closely associated with colorectal cancer (CRC) initiation and propagation. However, the mechanisms underlying BCAR4 function in colon cancer remains largely unknown. In this study, we hypothesized that BCAR4 could regulate colon cancer stem/initiating cells (CSC) function and further facilitates the colon cancer progression. Methods qRT-PCR was used to examine the expression of BCAR4 and various CSC markers. FACS, acetaldehyde dehydrogenase (ALDH) activity and western blot assays were applicable to test the expression of CSC markers. CCK8, tumorsphere formation and transwell assays were adopted to examine the capacity of CRC cells proliferation, self-renewal and migration. Pull down assay was used to test the interaction between BCAR4 and miR-665. Luciferase reporter assay was used to examine the interaction of miR-665 and activators of transcription (STAT3). In vivo tumor xenograft study was used to verify the malignancy of CRC cells with inhibition of BCAR4. Results Breast cancer anti-estrogen resistance 4 was highly expressed in both CRC cells and stem/initiating cells. In addition, overexpression of BCAR4 facilitated the maintenance of ALDH positive cells (a type of cancer stem/initiating cells) stemness and promoted ALDH+ cells proliferation and migration. Inhibition of BCAR4 restricted ALDH+ cells proliferation and migration. We further proved that miR-665 was the target of BCAR4 and subsequently activated signal transducers and STAT3 signaling which is an important pathway in cancer stem cells self-renewal. Conclusions Breast cancer anti-estrogen resistance 4 promotes the CRC cells stemness through targeting to miR-665/STAT3 signaling and identification of the BCAR4 in CRC stem cells provides a new insight into CRC diagnosis, treatment, prognosis and next-step translational investigations

Evaluation of Reference Genes Suitable for Gene Expression during Root Enlargement in Cherry Radish Based on Transcriptomic Data

Reliable reference genes (RGs) are of great significance for the normalization of quantitative data. RGs are often used as a reference to ensure the accuracy of experimental results to detect gene expression levels by reverse transcription–quantitative real-time PCR (RT-qPCR). To evaluate the normalized RGs that are suitable for studying the expression of genes during the process of radish stele enlargement, based on the functional annotations and fragment per kilobase of transcript per million mapped reads (FPKM) values in the transcriptome data, three traditional RGs (GAPDH, 18SrRNA, and ACTIN7) and seven commonly used RGs (UBQ11, TUA6, TUB6, EF-1b1, EF-1a2, PP2A11, and SAND) were obtained. In the study, the results of geNorm, NormFinder, and BestKeeper from RefFinder comprehensively analyzed the stability ranking of candidate RGs. The results showed that compared with the traditional RGs, the common RGs show higher and more stable expression. Among the seven commonly used RGs, PP2A11 is recommended as the optimal RG for studying cherry radish stele enlargement. This research provides a useful and reliable RG resource for the accurate study of gene expression during root enlargement in cherry radishes and facilitates the functional genomics research on root enlargement

Investigation on the effects of an elliptical wall on the dynamic behaviors of a bubble restricted by two parallel plates

The present paper investigates the dynamic behaviors of a bubble restricted by two parallel plates near an elliptical wall. The typical experimental phenomena of the bubble are recorded employing the high-speed photography and a theoretical Kelvin impulse model is established. The impacts of the spatial position and the curvature of the wall on the bubble collapse behaviors are quantitatively investigated through the theoretical model and verified against the experimental results. The Kelvin impulse intensity and the direction during the bubble collapse process are compared and discussed for different elliptical-shaped walls. The main conclusions include: (1) During the bubble collapse process, the phenomenon of the bubble uneven splitting is discovered. (2) At different spatial positions and wall curvatures, the bubble collapse jet angle, movement distance, and velocity are in good agreement with the theoretical Kelvin impulse predictions. (3) As the short-to-long axis ratio increases, the differences in the distributions of the Kelvin impulse intensity and the direction near the elliptical wall gradually become larger, and the range of the influence of the impulse intensity expands

FNeXter: A Multi-Scale Feature Fusion Network Based on ConvNeXt and Transformer for Retinal OCT Fluid Segmentation

The accurate segmentation and quantification of retinal fluid in Optical Coherence Tomography (OCT) images are crucial for the diagnosis and treatment of ophthalmic diseases such as age-related macular degeneration. However, the accurate segmentation of retinal fluid is challenging due to significant variations in the size, position, and shape of fluid, as well as their complex, curved boundaries. To address these challenges, we propose a novel multi-scale feature fusion attention network (FNeXter), based on ConvNeXt and Transformer, for OCT fluid segmentation. In FNeXter, we introduce a novel global multi-scale hybrid encoder module that integrates ConvNeXt, Transformer, and region-aware spatial attention. This module can capture long-range dependencies and non-local similarities while also focusing on local features. Moreover, this module possesses the spatial region-aware capabilities, enabling it to adaptively focus on the lesions regions. Additionally, we propose a novel self-adaptive multi-scale feature fusion attention module to enhance the skip connections between the encoder and the decoder. The inclusion of this module elevates the model’s capacity to learn global features and multi-scale contextual information effectively. Finally, we conduct comprehensive experiments to evaluate the performance of the proposed FNeXter. Experimental results demonstrate that our proposed approach outperforms other state-of-the-art methods in the task of fluid segmentation

Differences in the depression and burnout networks between doctors and nurses: evidence from a network analysis

Abstract Background Previous studies have demonstrated a strong association between depression and job burnout among healthcare professionals, but the results have been inconsistent, and there is a lack of in-depth exploration of such a relationship among different healthcare professions. The present study aims to investigate the interrelationships between depression and burnout among Chinese healthcare professionals and whether there are differences in the networks of these symptoms between doctors and nurses. Methods The Maslach Burnout Inventory-General Survey and the 2-item Patient Health Questionnaire were employed to assess job burnout and depression among 3,684 healthcare professionals. The translation has been refined to ensure accuracy and academic suitability. Subsequently, network analysis was conducted on 2,244 participants with a higher level of job burnout to identify core symptoms and explore the associations between job burnout and depression. Results The present study showed a network association between lack of interest and pleasure in things and being exhausted from work, excessive tiredness facing work, tendency to collapse at work, and lack of passion for work than before among healthcare professionals, as well as a notable difference in the network association between lack of interest and pleasure in things and lack of passion for work than before between nurses and doctors. Conclusions The depression-burnout network structures differ between doctors and nurses, highlighting the need for targeted intervention measures for both groups

Cost-Effective Asymmetric Supercapacitors Based on Nickel Cobalt Oxide Nanoarrays and Biowaste-Derived Porous Carbon Electrodes

Two nanostructured electrode materials are fabricated and used to construct cost-effective asymmetric supercapacitors (ASCs). Hierarchical nickel cobalt oxide nanoarrays (NCO-NA) consisting of nanosheets (NCO-NS) or nanowires (NCO-NW) are uniformly grown on Ni foam by a simple, effective, and generally applicable method, while biowaste-derived hierarchical porous carbon (Bio-HPC) with an interconnected microstructure is fabricated by pretreatment with potassium hydroxide and followed by direct pyrolysis. Considering the mass of NiCo₂O₄, the maximum specific capacitance of the hierarchical NCO-NS and NCO-NW electrodes are 2300 and 2333 F g^–1, respectively, and the specific capacitance of the Bio-HPC electrode is 253.9 F g^–1 at a scan rate of 5 mV s^–1. NCO-NA, Bio-HPC, a piece of polypropylene membrane, and 30 wt % KOH solution are assembled into a high-performance, low-cost ASC with the capability of rapidly storing electrical energy. The NCO-NW//Bio-HPC ASC exhibits a higher energy density compared with NCO-NS//Bio-HPC ASC, while the latter shows better cycling performance (the capacitance still remains 91.12% after 2000 cycles)