Expression studies of the proteolytic p10 fragment of the neuronal Cdk5 activator in mammalian cells

Master'sMASTER OF SCIENC

Determinants of Air Quality in Building Environments: A Multi-Regression Analysis and Implications for Open Teaching Practices

In the ever-evolving educational milieu, the integration of innovative teaching methodologies is increasingly crucial to meet the changing needs of modern learners. This research meticulously explores the application of open teaching practices in the fields of building environment and energy application engineering. Through an in-depth examination of multi-regression data pertaining to various environmental factors, this study reveals significant correlations and patterns that are relevant to both educators and environmental specialists. Emphasis is placed on the student-centric ethos of this approach, combining the dual concepts of environmental science and pedagogical progression. The relationship between environmental variables, such as PM2.5, PM10, temperature, and humidity, and the air quality index (AQI) is rigorously analyzed. Such analysis underscores the educational improvements brought about by open teaching strategies. The presented findings not only offer nuanced insights into how the aforementioned variables influence air quality but also highlight the benefits and potential of open teaching methodologies in creating a more interactive and enlightening academic environment

Federated Learning with Extremely Noisy Clients via Negative Distillation

Federated learning (FL) has shown remarkable success in cooperatively training deep models, while typically struggling with noisy labels. Advanced works propose to tackle label noise by a re-weighting strategy with a strong assumption, i.e., mild label noise. However, it may be violated in many real-world FL scenarios because of highly contaminated clients, resulting in extreme noise ratios, e.g., $>$90%. To tackle extremely noisy clients, we study the robustness of the re-weighting strategy, showing a pessimistic conclusion: minimizing the weight of clients trained over noisy data outperforms re-weighting strategies. To leverage models trained on noisy clients, we propose a novel approach, called negative distillation (FedNed). FedNed first identifies noisy clients and employs rather than discards the noisy clients in a knowledge distillation manner. In particular, clients identified as noisy ones are required to train models using noisy labels and pseudo-labels obtained by global models. The model trained on noisy labels serves as a `bad teacher' in knowledge distillation, aiming to decrease the risk of providing incorrect information. Meanwhile, the model trained on pseudo-labels is involved in model aggregation if not identified as a noisy client. Consequently, through pseudo-labeling, FedNed gradually increases the trustworthiness of models trained on noisy clients, while leveraging all clients for model aggregation through negative distillation. To verify the efficacy of FedNed, we conduct extensive experiments under various settings, demonstrating that FedNed can consistently outperform baselines and achieve state-of-the-art performance. Our code is available at https://github.com/linChen99/FedNed.Comment: Accepted by AAAI 202

Prediction of DNA i-motifs via machine learning

i-Motifs (iMs), are secondary structures formed in cytosine-rich DNA sequences and are involved in multiple functions in the genome. Although putative iM forming sequences are widely distributed in the human genome, the folding status and strength of putative iMs vary dramatically. Much previous research on iM has focused on assessing the iM folding properties using biophysical experiments. However, there are no dedicated computational tools for predicting the folding status and strength of iM structures. Here, we introduce a machine learning pipeline, iM-Seeker, to predict both folding status and structural stability of DNA iMs. The programme iM-Seeker incorporates a Balanced Random Forest classifier trained on genome-wide iMab antibody-based CUT&Tag sequencing data to predict the folding status and an Extreme Gradient Boosting regressor to estimate the folding strength according to both literature biophysical data and our in-house biophysical experiments. iM-Seeker predicts DNA iM folding status with a classification accuracy of 81% and estimates the folding strength with coefficient of determination (R2) of 0.642 on the test set. Model interpretation confirms that the nucleotide composition of the C-rich sequence significantly affects iM stability, with a positive correlation with sequences containing cytosine and thymine and a negative correlation with guanine and adenine

Modification of HDL by reactive aldehydes alters select cardioprotective functions of HDL in macrophages

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154382/1/febs15034_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154382/2/febs15034.pd

Utilization of silicon dust to prepare Si3N4 used for steelmaking additives : thermodynamics and kinetics

DATA AVAILABIITY STATEMENT : Data are contained within the article.Please read abstract in the article.https://www.mdpi.com/journal/processeshj2024Materials Science and Metallurgical EngineeringSDG-09: Industry, innovation and infrastructur

Regulation of caveolin-1 membrane trafficking by the Na/K-ATPase

Here, we show that the Na/K-ATPase interacts with caveolin-1 (Cav1) and regulates Cav1 trafficking. Graded knockdown of Na/K-ATPase decreases the plasma membrane pool of Cav1, which results in a significant reduction in the number of caveolae on the cell surface. These effects are independent of the pumping function of Na/K-ATPase, and instead depend on interaction between Na/K-ATPase and Cav1 mediated by an N-terminal caveolin-binding motif within the ATPase α1 subunit. Moreover, knockdown of the Na/K-ATPase increases basal levels of active Src and stimulates endocytosis of Cav1 from the plasma membrane. Microtubule-dependent long-range directional trafficking in Na/K-ATPase–depleted cells results in perinuclear accumulation of Cav1-positive vesicles. Finally, Na/K-ATPase knockdown has no effect on processing or exit of Cav1 from the Golgi. Thus, the Na/K-ATPase regulates Cav1 endocytic trafficking and stabilizes the Cav1 plasma membrane pool

Effective Application of Solid Expandable Tubular During the Enhancement of Heavy Oil Recovery in China, Lessons Learned and Experience Shared

As the traditional thermal recovery became less effective in exploring the heavy oil reservoirs, some newly developed techniques such as chemical flooding, SAGD and HDCS are demonstrating their advantage in the recovery process in China. However, the ever increasingly used new techniques often compromised severely the well integrity as the flow of extremely high temperature fluid or gas caused quick damage to casing, leaving the wellbore less reliable. This compromise requires urgently a workover strategy that would maximize the well’s life span and guarantee the effectiveness of new techniques.Solid expandable tubular (SET) was field-proven in casing patching activities, but its application in the heavy oil recovery has not been attempted due to severe temperature challenge. We made innovations on the traditional structure of SET and got valuable results. The tubular after expansion was integrated with the original casing as a whole and the rubber was removed in-between, the wellbore size was maintained utmost and the casing was further strengthened. Meanwhile the expansion cone was put outside the tubular which is a big step forward in SET structure.Indoors experiments demonstrated sound performance of the new structure in the simulative temperature of 350 ℃, the plan for the field application was optimized based on the lessons collected in this experiment. High temperature well applications by SET were carried out in Liaohe oilfield which is famous for its heavy oil resource in China, and the detailed process as well as the outcome were compared and analyzed, finally the conclusions were drawn as a result of the whole study.We expect our work will help expand this enabling technology to better facilitate the enhancement of heavy oil recovery and maintain solid well integrity during the heavy oil production.Key words: Solid expandable tubular; Heavy oil recovery; Chin

Potential effective diagnostic biomarker in patients with primary and metastatic small intestinal neuroendocrine tumors

Background: Small intestinal neuroendocrine tumors (SI-NETs) are the most common malignant tumors of the small intestine, with many patients presenting with metastases and their incidence increasing. We aimed to find effective diagnostic biomarkers for patients with primary and metastatic SI-NETs that could be applied for clinical diagnosis.Methods: We downloaded GSE65286 (training set) and GSE98894 (test set) from the GEO database and performed differential gene expression analysis to obtain differentially expressed genes (DEGs) and differentially expressed long non-coding RNAs (DElncRNAs). The functions and pathways involved in these genes were further explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, a global regulatory network involving dysregulated genes in SI-NETs was constructed based on RNAInter and TRRUST v2 databases, and the diagnostic power of hub genes was identified by receiver operating characteristic curve (ROC).Results: A total of 2,969 DEGs and DElncRNAs were obtained in the training set. Enrichment analysis revealed that biological processes (BPs) and KEGG pathways were mainly associated with cancer. Based on gene set enrichment analysis (GSEA), we obtained five BPs (cytokinesis, iron ion homeostasis, mucopolysaccharide metabolic process, platelet degranulation and triglyceride metabolic process) and one KEGG pathway (ppar signaling pathway). In addition, the core set of dysregulated genes obtained included MYL9, ITGV8, FGF2, FZD7, and FLNC. The hub genes were upregulated in patients with primary SI-NETs compared to patients with metastatic SI-NETs, which is consistent with the training set. Significantly, the results of ROC analysis showed that the diagnostic power of the hub genes was strong in both the training and test sets.Conclusion: In summary, we constructed a global regulatory network in SI-NETs. In addition, we obtained the hub genes including MYL9, ITGV8, FGF2, FZD7, and FLNC, which may be useful for the diagnosis of patients with primary and metastatic SI-NETs