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The significant changes in the world of education after the coronavirus disease 2019 (COVID-19) pandemic have increased students' anxiety levels. This anxiety can trigger stress which can interfere with students' academic performance. Therefore, this condition is a critical problem that needs to be addressed immediately. However, researchers have not previously conducted much research to detect post-COVID stress levels. Apart from that, the existence of a system capable of carrying out this detection is still lacking. Therefore, this research focuses on building a system for detecting student stress levels. First, an exploration of the tree algorithm was carried out to find the most optimal method for recognizing student stress levels. Then a detection system is built using this optimal method. The research results show that the tree ID3 (Iterative Dichotomiser 3) algorithm achieves the highest accuracy value of 95% compared to other tree algorithms with the scenario of dividing training data into test data of 80%:20%. Moreover, this telegram bot-based detection system works well in recognizing three categories of stress, namely: light, moderate, and heavy stress based on black-box testing techniques. [ABSTRACT FROM AUTHOR]

Gene expression patterns are very sensitive to external influences and are reflected in phenotypic changes. It was previously described that transferring melanoma cells from a plastic surface to Matrigel led to formation of de novo vascular networks—vasculogenic mimicry—that are characteristic to a stemness phenotype in aggressive tumors. Up to now there was no detailed data about the gene signature accompanying this process. Here, we show that this transfer shortly led to extremely strong epigenetic changes in gene expression in the melanoma cells. We observed that on Matrigel numerous genes controlling ribosome biogenesis were upregulated. However, most of the activated genes were inhibitors of the differentiation genes (ID1, ID2, and ID3). At the same time, the genes that control differentiation were downregulated. Both the upregulated and the downregulated genes are simultaneously targeted by different transcription factors shaping sets of co-expressed genes. The specific group of downregulated genes shaping contacts with rDNA genes are also associated with the H3K27me3 mark and with numerous lincRNAs and miRNAs. We conclude that the stemness phenotype of melanoma cells is due to the downregulation of developmental genes and formation of dedifferentiated cells. [ABSTRACT FROM AUTHOR]

The present research explores the process of diagnosing thyroid disorders using two different methods: traditional and ensemble. The traditional method implements the ID3 decision tree algorithm on 4000 records after several preprocessing stages. This method is evaluated using various statistical approaches, which defines the proportion of true agreement between observed and predicted events. The partition accuracy for the traditional method ranges from 66% to 70%. The ensemble method relies on the Random Forest algorithm, which creates multiple trees on random datasets and integrates predictions through voting. The partition accuracy for the ensemble method, assessed using k-fold cross-validation, ranges from 68% to 74%, with a mean accuracy of 72%. The ensemble method demonstrates higher partition accuracy in diagnosing thyroid disorders compared to the traditional method. These findings suggest that ensemble machine learning techniques, particularly Random Forest, can significantly enhance diagnostic accuracy for thyroid disorders. Future research should focus on integrating these advanced algorithms into clinical diagnostic processes to improve patient outcomes and further optimize diagnostic techniques. [ABSTRACT FROM AUTHOR]

Extracting insights from educational data offers valuable business intelligence and web discovery solutions. Predicting student trajectories presents a significant challenge for higher education institutions today. They aim to determine which universities have the highest employment rates for their graduates and to understand if certain students are more likely to secure jobs than others. Accurate statistics are essential for planning, trend forecasting, and optimizing business processes. To tackle these challenges, we suggest an approach that employs historical data to classify the most suitable major for each student. This is achieved using the decision tree method and the Iterative Dichotomiser3 (ID3) algorithm. We've integrated a dashboard tailored specifically for Jordanian higher education institutions to visualize the knowledge derived from educational databases. Our research aims to assist higher education and training institutes in navigating the intricate shifts in the labor market. This paper emphasizes using the ID3 decision tree algorithm, a classification technique, to identify categories of workers. Such an approach aids companies in pinpointing the student groups with the highest likelihood of securing employment. [ABSTRACT FROM AUTHOR]

Tires serve as the critical interface between a vehicle and the road. Their condition significantly impacts road safety, vehicle performance, fuel efficiency, and operational costs. Developing a machine learning model for accurately and efficiently classifying tire conditions using tread depth measurements poses a critical challenge in enhancing automotive safety and maintenance. This research aims to address this challenge by leveraging machine learning techniques to categorize and assess tire conditions based on tread depth, thereby contributing to developing a robust and automated system for tire safety condition monitoring in diverse vehicle fleets. This article presents a novel ensemble method-based machine learning algorithm called EDT-STACK (Stacking Ensembles-Based Decision Tree) that combines several decision tree-based methods using a stacking ensemble technique. The model is trained and tested on a dataset of 500 tires (new and disposed) with different tread depths, The model achieves 99 % accuracy in all classes, demonstrating its efficacy in classifying tire conditions from tread depth data. The study also compares the performance of EDT-STACK with other algorithms. Its superior performance outshines other decision tree algorithms, such as XGBoost, AdaBoost, Random Forest, ID3, and Histogram-based Decision Tree, which achieve accuracies of 98 %, 78 %, 85 %, 98 %, and 98 %, respectively. This study concludes that EDT-STACK offers an innovative solution for tire condition assessment, which can enhance road safety, reduce environmental impacts, and optimize vehicle maintenance.

Cerebral amyloid angiopathy (CAA) is a degenerative vasculopathy. We have previously shown that transcription regulating proteins- inhibitor of DNA binding protein 3 (ID3) and the nuclear respiratory factor 1 (NRF1) contribute to vascular dysregulation. In this study, we have identified sex specific ID3 and NRF1-mediated gene networks in CAA patients diagnosed with Alzheimer's Disease (AD). High expression of ID3 mRNA coupled with low NRF1 mRNA levels was observed in the temporal cortex of men and women CAA patients. Low NRF1 mRNA expression in the temporal cortex was found in men with severe CAA. High ID3 expression was found in women with the genetic risk factor APOE4. Low NRF1 expression was also associated with APOE4 in women with CAA. Genome wide transcriptional activity of both ID3 and NRF1 paralleled their mRNA expression levels. Sex specific differences in transcriptional gene signatures of both ID3 and NRF1 were observed. These findings were further corroborated by Bayesian machine learning and the GeNIe simulation models. Dynamic machine learning using a Monte Carlo Markov Chain (MCMC) gene ordering approach revealed that ID3 was associated with disease severity in women. NRF1 was associated with CAA and severity of this disease in men. These findings suggest that aberrant ID3 and NRF1 activity presumably plays a major role in the pathogenesis and severity of CAA. Further analyses of ID3- and NRF1-regulated molecular drivers of CAA may provide new targets for personalized medicine and/or prevention strategies against CAA. [ABSTRACT FROM AUTHOR]

Chimeric antigen receptor (CAR) T cell therapy has achieved remarkable success in hematological malignancies but remains ineffective in solid tumors, due in part to CAR T cell exhaustion in the solid tumor microenvironment. To study dysfunction of mesothelin-redirected CAR T cells in pancreatic cancer, we establish a robust model of continuous antigen exposure that recapitulates hallmark features of T cell exhaustion and discover, both in vitro and in CAR T cell patients, that CAR dysregulation is associated with a CD8+ T-to-NK-like T cell transition. Furthermore, we identify a gene signature defining CAR and TCR dysregulation and transcription factors, including SOX4 and ID3 as key regulators of CAR T cell exhaustion. Our findings shed light on the plasticity of human CAR T cells and demonstrate that genetic downmodulation of ID3 and SOX4 expression can improve the efficacy of CAR T cell therapy in solid tumors by preventing or delaying CAR T cell dysfunction.

The quality of classroom interaction has received more and more attention as an important part of the teaching quality of English-specialized courses in colleges and universities. After completing the decision tree-based English classroom interaction analysis model based on the ID3 algorithm, this paper quantitatively analyzes the English classroom interaction rules and then designs the English classroom interaction enhancement strategies containing the three directions of teacher-teacher, teacher-student, and student-student on the basis of the derived rules and conducts a one-academic-year teaching experiment for English majors in a university in Guangzhou. It was found that the experimental class and the control class had the largest gap in two indicators: classroom discussion sessions (19.38% and 2.61%) and student manipulation techniques (9.07% and 0.41%). In the two classes at the beginning of the semester, the quality level scores of classroom interactions in both classes were below 30. In contrast, in the last two classes of the school year, the experimental class remained stable above 70 points until the end of classroom instruction. The control class remained below 30 points. After the beginning of the teaching experiment, the probability of students’ active speaking, group collaboration, or discussion in the experimental class increased rapidly. The probability of students’ active speaking stabilized at about 0.8 by the end of the 16th week. In contrast, the probability points of the control class were distributed more discretely in the course of the experiment, and the probability was basically below 0.4. In the experimental class, the English classroom interaction enhancement strategy proposed in this paper has yielded better results.

DNA binding inhibitory factor 3 (ID3) has been shown to have a key role in maintaining proliferation and differentiation. It has been suggested that ID3 may also affect mammalian ovarian function. However, the specific roles and mechanisms are unclear. In this study, the expression level of ID3 in cumulus cells (CCs) was inhibited by siRNA, and the downstream regulatory network of ID3 was uncovered by high-throughput sequencing. The effects of ID3 inhibition on mitochondrial function, progesterone synthesis, and oocyte maturation were further explored. The GO and KEGG analysis results showed that after ID3 inhibition, differentially expressed genes, including StAR, CYP11A1, and HSD3B1, were involved in cholesterol-related processes and progesterone-mediated oocyte maturation. Apoptosis in CC was increased, while the phosphorylation level of ERK1/2 was inhibited. During this process, mitochondrial dynamics and function were disrupted. In addition, the first polar body extrusion rate, ATP production and antioxidation capacity were reduced, which suggested that ID3 inhibition led to poor oocyte maturation and quality. The results will provide a new basis for understanding the biological roles of ID3 as well as cumulus cells. • Inhibition of ID3 reduces progesterone synthesis in bovine cumulus cells. • Inhibition of ID3 induces cumulus cell apoptosis. • Inhibition of ID3 affects mitochondrial dynamics in cumulus cells. • Inhibition of ID3 in cumulus cells reduces the quality of oocytes. [ABSTRACT FROM AUTHOR]

Identifying highly discriminating genes is a critical step in tumor recognition tasks based on microarray gene expression profile data and machine learning. Gene selection based on tree models has been the subject of several studies. However, these methods are based on a single-tree model, often not robust to ultra-highdimensional microarray datasets, resulting in the loss of useful information and unsatisfactory classification accuracy. Motivated by the limitations of single-tree-based gene selection, in this study, ensemble gene selection methods based on multiple-tree models were studied to improve the classification performance of tumor identification. Specifically, we selected the three most representative tree models: ID3, random forest, and gradient boosting decision tree. Each tree model selects top-n genes from the microarray dataset based on its intrinsic mechanism. Subsequently, three ensemble gene selection methods were investigated, namely multipletree model intersection, multiple-tree module union, and multiple-tree module cross-union, were investigated. Experimental results on five benchmark public microarray gene expression datasets proved that the multiple tree module union is significantly superior to gene selection based on a single tree model and other competitive gene selection methods in classification accuracy. [ABSTRACT FROM AUTHOR]

Abstract Objective To study the effect of inhibitor of differentiation 3 (ID3) on radiotherapy in patients with rectal cancer and to explore its primary mechanism. Methods Cell proliferation and clonogenic assays were used to study the relationship between ID3 and radiosensitivity. Co-immunoprecipitation and immunofluorescence were performed to analyze the possible mechanism of ID3 in the radiosensitivity of colorectal cancer. At the same time, a xenograft tumor model of HCT116 cells in nude mice was established to study the effect of irradiation on the tumorigenesis of ID3 knockdown colorectal cancer cells in vivo. Immunohistochemistry was performed to analyze the relationship between ID3 expression and the efficacy of radiotherapy in 46 patients with rectal cancer. Results Proliferation and clonogenic assays revealed that the radiosensitivity of colorectal cancer cells decreased with ID3 depletion through p53–independent pathway. With the decrease in ID3 expression, MDC1 was downregulated. Furthermore, the expression of ID3, MDC1, and γH2AX increased and formed foci after irradiation. ID3 interacted with PPARγ and form a positive feedback loop to enhance the effect of ID3 on the radiosensitivity of colorectal cancer. Irradiation tests in nude mice also confirmed that HCT116 cells with ID3 knockdown were more affected by irradiation. Immunohistochemical study showed that rectal cancer patients with low expression of ID3 had better radiotherapy efficacy. Conclusions ID3 and PPARγ influence the radiosensitivity of colorectal cancer cells by interacting with MDC1 to form a positive feedback loop that promotes DNA damage repair. Patients with low expression of ID3 who received neoadjuvant chemoradiotherapy can obtain a better curative effect.

Gestational diabetes mellitus occurs due to high glucose levels in the blood. Pregnant women are affected by this type of diabetes. A blood test is to be performed to identify diabetes. The Oral Glucose Tolerance Test (OGTT) is a blood test performed between the 24th and 28th week of pregnancy that is necessary to identify and overcome the side effects of GDM. The main objective of this work is to train a model by utilizing the training data, evaluate the trained model using the test data, and compare existing machine learning algorithms with a Gradient boosting machine (GBM) to achieve a better model for the effective prediction of gestational diabetes. In this work, the analysis was done with a few existing algorithms and the Extreme learning machine and Gradient boosting techniques. The k-fold cross-validation technique is applied with values of k as 3, 5, and 10 to obtain better performance. The existing algorithms implemented are the Naive Bayes classifier, Support Vector Machine, K-Nearest Neighbour, ID3, CART and J48. The proposed algorithms are Gradient boosting and ELM. These algorithms are implemented in R programming. The metrics like accuracy, kappa statistic, sensitivity/Recall, specificity, precision, f-measure and AUC are used to compare all the algorithms. GBM has obtained better performance than existing algorithms. Then finally, GBM is compared with the other proposed robust Machine Learning algorithm, namely the Extreme learning machine, and the GBM performed better. So, It is recommended to use a gradient-boosting algorithm to predict gestational diabetes effectively. [ABSTRACT FROM AUTHOR]

Abstract Background Dysregulation of inhibitor of differentiation/DNA binding (ID) genes is linked to cancer growth, angiogenesis, invasiveness, metastasis and patient survival. Nevertheless, few investigations have systematically determined the expression and prognostic value of ID genes in acute myeloid leukemia (AML). Methods The expression and clinical prognostic value of ID genes in AML were first identified by public databases and further validated by our research cohort. Results Using public data, the expression of ID1/ID3 was markedly downregulated in AML, and the expression of ID2 was greatly upregulated in AML, whereas ID4 showed no significant difference. Among the ID genes, only ID3 expression may be the most valuable prognostic biomarker in both total AML and cytogenetically normal AML (CN-AML) and especially in CN-AML. Clinically, reduced ID3 expression was greatly associated with higher white blood cell counts, peripheral blood/bone marrow blasts, normal karyotypes and intermediate cytogenetic risk. In addition, low ID3 expression was markedly related to FLT3 and NPM1 mutations as well as wild-type TP53. Despite these associations, multivariate Cox regression analysis revealed that ID3 expression was an independent risk factor affecting overall survival (OS) and disease free survival (DFS) in CN-AML patients. Biologically, a total of 839 mRNAs/lncRNAs and 72 microRNAs were found to be associated with ID3 expression in AML. Importantly, the expression of ID3 with discriminative value in AML was further confirmed in our research cohort. Conclusion The bioinformatics analysis and experimental verification demonstrate that low ID3 expression independently affects OS and DFS in patients with CN-AML, which might be seen as a potential prognostic indicator in CN-AML.

Objective: To study the effect of inhibitor of differentiation 3 (ID3) on radiotherapy in patients with rectal cancer and to explore its primary mechanism. Methods: Cell proliferation and clonogenic assays were used to study the relationship between ID3 and radiosensitivity. Co-immunoprecipitation and immunofluorescence were performed to analyze the possible mechanism of ID3 in the radiosensitivity of colorectal cancer. At the same time, a xenograft tumor model of HCT116 cells in nude mice was established to study the effect of irradiation on the tumorigenesis of ID3 knockdown colorectal cancer cells in vivo. Immunohistochemistry was performed to analyze the relationship between ID3 expression and the efficacy of radiotherapy in 46 patients with rectal cancer. Results: Proliferation and clonogenic assays revealed that the radiosensitivity of colorectal cancer cells decreased with ID3 depletion through p53–independent pathway. With the decrease in ID3 expression, MDC1 was downregulated. Furthermore, the expression of ID3, MDC1, and γH2AX increased and formed foci after irradiation. ID3 interacted with PPARγ and form a positive feedback loop to enhance the effect of ID3 on the radiosensitivity of colorectal cancer. Irradiation tests in nude mice also confirmed that HCT116 cells with ID3 knockdown were more affected by irradiation. Immunohistochemical study showed that rectal cancer patients with low expression of ID3 had better radiotherapy efficacy. Conclusions: ID3 and PPARγ influence the radiosensitivity of colorectal cancer cells by interacting with MDC1 to form a positive feedback loop that promotes DNA damage repair. Patients with low expression of ID3 who received neoadjuvant chemoradiotherapy can obtain a better curative effect. Highlights: • Depletion of ID3 enhances radiosensitivity of rectal cancer cells. • Interaction between ID3 and MDC1 promotes DNA damage repair. • Positive feedback loop between PPARγ and ID3 enhances the radiosensitivity of rectal cancer cells. • Patients with low expression of ID3 can obtain a better radiotherapy effect. [ABSTRACT FROM AUTHOR]

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Decision Trees are a common approach used for classifying unseen data into defined classes. The Information Gain is usually applied as splitting criteria in the node selection process for constructing the decision tree. However, bias in selecting the multi-variation attributes is a major limitation of using this splitting condition, leading to unsatisfactory classification performance. To deal with this problem, a new decision tree algorithm called “Knowledge-Based Decision Tree (KDT)” is proposed which exploits the knowledge in an ontology to assist the decision tree construction. The novelty of the study is that an ontology is applied to determine the attribute importance values using the PageRank algorithm. These values are used to modify the Information Gain to obtain appropriate attributes to be nodes in the decision tree. Four different datasets, Soybean, Heart disease, Dengue fever, and COVID-19 dataset, were employed to evaluate the proposed approach. The experimental results show that the proposed method is superior to the other decision tree algorithms, such as the traditional ID3 and the Mutual Information Decision tree (MIDT), and also performs better than a non-decision tree algorithm, e.g., the k-Nearest Neighbors.

Background & Aim: In folk medicine, red clover (Trifolium pratense) use to treat some diseases such as whooping cough, asthma, eczema, and some ophthalmic dysfunction. Due to its phytoestrogens and antioxidant-rich compounds, it is recommended to alleviate some cancers. This paper was conducted to study the anti-cancer and apoptosis effects of red clover extract (RCE) on the Raji cell line in Burkitt's lymphoma. Experimental: Red clover lyophilized powder (CAS = 85085-25-2) with a fixed ratio of Formononetin, Biochanin A, Daidzein, and Genistein was acquired from Sigma Aldrich German company. Raji cells were obtained from the Pasteur Institute of Iran-Tehran. Raji cells were treated with different concentrations of RCE, and viable cells were measured at an interval of 24, 48, and 72 hours incubation in three days by MTT assay. Agarose gel electrophoresis was used to determine the DNA degradation. Annexin V-FITC/PI kit and flow cytometry assay were used to determine the percent of apoptotic and necrotic treated Raji cells. Also, expression changes in cMYC, ID3, and P53 genes were measured by real-time PCR. Results: Red clover extract can prevent in vitro proliferation of the Raji cells in a time and dose-dependent manner. RCE, as well as c-MYC gene suppression and induction of ID3 and P53 genes, enters the Raji cells in the apoptosis stages with an acceptable percentage and has complication cure potential in Burkitt's lymphoma. Recommended applications/industries: The extract used in this study combines four components. The individual evaluation effects of Formononetin, Biochanin A, Daidzein, and Genistein on Raji cells are recommended.

During tumorigenesis, the recently identified tumor-specific memory T cells in draining lymph nodes (TdLN-T TSM cells) play a pivotal role in tumor repression that gives rise to progenitor exhausted T (T PEX) cells and further replenishes tumor-specific CD8+ T cells residing in the tumor microenvironment (TME). However, how T TSM cells are maintained in TdLN is largely unknown. Here, we show that the transcription regulator ID3 (inhibitor of DNA binding 3) is highly expressed by T TSM cells compared with other CD8+ T cell subsets. The deficiency of ID3 significantly interrupts the maintenance of T TSM and T PEX cells, resulting in decreased tumor-infiltrating CD8+ T cells and impaired tumor control. Consistent with this, overexpression of ID3 in CD8+ T cells increases the T TSM cell population and enhances the anti-tumor immune response. [Display omitted] • ID3 is highly expressed in TdLN-T TSM cells during tumorigenesis • The absence of ID3 in CD8+ T cells impairs tumor control • ID3 is crucial for the long-term maintenance of TdLN-T TSM and T PEX cells • ID3 overexpression increases TdLN-T TSM cells and enhances anti-tumor immune response Ran et al. highlight that deficiency of ID3 significantly disrupts the maintenance of TdLN-T TSM cells, resulting in impaired tumor control. [ABSTRACT FROM AUTHOR]

Diabetes can be defined as a chronic disease identified by high levels of blood glucose that result from issues in the way insulin is generated, the way insulin works, or both those reasons. The aim of this research is to propose a technique using the Decision Tree (ID3) and Naive Bayes to categorize diabetes and reduce classification errors by increasing the accuracy of the classification. The results of the proposed method were evaluated by comparing them with other results through the application of the proposed system to Pima India Diabetes data set, obtained from the UCI database site. The experimental results show that the ID3 recorded a precision ratio of 91% and the naive class corrected it to 94% for the same number of the test group.

Recurrent pregnancy loss (RPL) remains an unsolved problem in obstetrics and gynecology, and up to 50% of RPL cases are unexplained. Unexplained RPL (uRPL) is widely considered to be related to an aberrant endometrial microenvironment. BMP2 is an important factor involved in endometrial decidualization and embryo implantation, and intercellular adhesion molecule 1 (ICAM1) is a critical inflammatory regulator in the endometrium. In this study, we found that endometrial samples obtained from Unexplained RPL patients have significantly lower BMP2 and higher ICAM1 levels than fertile controls. For further research on the relationship between BMP2 and ICAM1 and the potential molecular mechanisms in Unexplained RPL, immortalized human endometrial stromal cells (HESCs) and primary human decidual stromal cells (HDSCs) were used as study models. Our results showed that BMP2 significantly decreased ICAM1 expression by upregulating DNA-binding protein inhibitor 3 (ID3) in both HESCs and HDSCs. Using kinase receptor inhibitors (dorsomorphin homolog 1 (DMH-1) and dorsomorphin) and siRNA transfection, it has been found that the upregulation of ID3 and the following downregulation of ICAM1 induced by BMP2 is regulated through the ALK3-SMAD4 signaling pathway. This research gives a hint of a novel mechanism by which BMP2 regulates ICAM1 in the human endometrium, which provides insights into potential therapeutics for unexplained RPL.

Antibody-mediated cancer immunotherapy targets inhibitory surface molecules, such as PD1, PD-L1, and CTLA-4, aiming to re-invigorate dysfunctional T cells. We purified and characterized tumor-infiltrating lymphocytes (TILs) and their patient-matched non-tumor counterparts from treatment-naïve NSCLC patient biopsies to evaluate the effect of PD1 expression on the functional and molecular profiles of tumor-resident T cells. We show that PD1+ CD8+ TILs have elevated expression of the transcriptional regulator ID3 and that the cytotoxic potential of CD8 T cells can be improved by knocking down ID3, defining it as a potential regulator of T cell effector function. PD1+ CD4+ memory TILs display transcriptional patterns consistent with both helper and regulator function, but can robustly facilitate B cell activation and expansion. Furthermore, we show that expanding ex vivo-prepared TILs in vitro broadly preserves their functionality with respect to tumor cell killing, B cell help, and TCR repertoire. Although purified PD1+ CD8+ TILs generally maintain an exhausted phenotype upon expansion in vitro, transcriptional analysis reveals a downregulation of markers of T-cell dysfunction, including the co-inhibitory molecules PD1 and CTLA-4 and transcription factors ID3, TOX and TOX2, while genes involved in cell cycle and DNA repair are upregulated. We find reduced expression of WNT signaling components to be a hallmark of PD1+ CD8+ exhausted T cells in vivo and in vitro and demonstrate that restoring WNT signaling, by pharmacological blockade of GSK3β, can improve effector function. These data unveil novel targets for tumor immunotherapy and have promising implications for the development of a personalized TIL-based cell therapy for lung cancer.

Background: Dysregulation of inhibitor of differentiation/DNA binding (ID) genes is linked to cancer growth, angiogenesis, invasiveness, metastasis and patient survival. Nevertheless, few investigations have systematically determined the expression and prognostic value of ID genes in acute myeloid leukemia (AML).Methods: The expression and clinical prognostic value of ID genes in AML were first identified by public databases and further validated by our research cohort.Results: Using public data, the expression of ID1/ID3 was markedly downregulated in AML, and the expression of ID2 was greatly upregulated in AML, whereas ID4 showed no significant difference. Among the ID genes, only ID3 expression may be the most valuable prognostic biomarker in both total AML and cytogenetically normal AML (CN-AML) and especially in CN-AML. Clinically, reduced ID3 expression was greatly associated with higher white blood cell counts, peripheral blood/bone marrow blasts, normal karyotypes and intermediate cytogenetic risk. In addition, low ID3 expression was markedly related to FLT3 and NPM1 mutations as well as wild-type TP53. Despite these associations, multivariate Cox regression analysis revealed that ID3 expression was an independent risk factor affecting overall survival (OS) and disease free survival (DFS) in CN-AML patients. Biologically, a total of 839 mRNAs/lncRNAs and 72 microRNAs were found to be associated with ID3 expression in AML. Importantly, the expression of ID3 with discriminative value in AML was further confirmed in our research cohort.Conclusion: The bioinformatics analysis and experimental verification demonstrate that low ID3 expression independently affects OS and DFS in patients with CN-AML, which might be seen as a potential prognostic indicator in CN-AML. [ABSTRACT FROM AUTHOR]

Treatment options for brain metastatic breast cancer are limited because the molecular mechanism for how breast cancer cells infiltrate the brain is not fully understood. For breast tumors to metastasize to the brain first, cells need to detach from the primary tumor, enter in the blood circulation, survive within the microvascular niche, and then cross the blood–brain barrier (BBB) to colonize into the brain. It is critical to understand how breast cancer cells transmigrate through the BBB to prevent brain metastasis. Nuclear respiratory factor 1 (NRF1) transcription factor has been reported to be highly active in several human cancers and its aberrant expression facilitates in the acquisition of breast cancer stem cells (BCSCs). Inhibitor of differentiation protein 3 (ID3), a transcription regulating protein, induces pluripotent endothelial stem cells (ESCs). Herein, we investigated if NRF1-induced BCSCs could cross a BBB model and guiding of BCSCs by ID3-induced ESCs across the BBB. BCSCs and ESCs were subjected to functional gain/loss experiments to determine if NRF1/ID3 contributed to lineage-specific BCSCs organ entry. First, we tested whether NRF1 promoted migration of breast cancer using a BBB model consisting of BCSCs or MDA-MB231 cells, brain endothelial cell layer, and astrocytes. NRF1 overexpression increased the propensity for BCSCs and NRF1-induced MDA-MB231 cells to adhere to brain endothelial cells and migrate across a human BBB model. Increased adhesion of NRF1-induced BCSCs to ESCsID3 was detected. NRF1-induced BCSCs crossed through the BBB model and this was promoted by ESCsID3. We also showed that environmental relevant exposure to PCBs (PCB153 and PCB77) produced differential effects. Treatment with PCB153 showed increased growth of NRF1-induced BCSCs tumor spheroids and increased in vivo migration of ESCsID3. Exosomal ID3 released from endothelial cells also supported the growth of NRF1-induced BCSCs and provide the basis for paracrine effects by ESCsID3 associated with breast tumors. Xenograft experiments showed that ID3 overexpressing brain ESCs not only supported the growth of BCSC tumor spheroids but guided them to the neural crest in zebrafish. These findings show for the first time a novel role for ID3 and NRF1 by which ESCsID3 help guide BCSCsNRF1 to distant metastatic sites where they most likely facilitate the colonization, survival, and proliferation of BCSCs. This knowledge is important for pre-clinical testing of NRF1/ID3 modifying agents to prevent the spread of breast cancer to the brain. [ABSTRACT FROM AUTHOR]

Vascular calcification (VC) poses significant challenges in cardiovascular health. This study employs single-cell transcriptome sequencing to dissect cellular dynamics in this process. We identify distinct cell subgroups, notably in vascular smooth muscle cells (VSMCs), and observe differences between calcified atherosclerotic cores and adjacent regions. Further exploration reveals ID3 as a key gene regulating VSMC function. In vitro experiments demonstrate ID3's interaction with USP1 and E12, modulating cell proliferation and osteogenic differentiation. Animal models confirm the critical role of the USP1/ID3/E12/P21 axis in VC. This study sheds light on a novel regulatory mechanism, offering potential therapeutic targets., Competing Interests: Declaration of competing interest The author declares no conflict of interest., (Copyright © 2024. Published by Elsevier Inc.)

During tumorigenesis, the recently identified tumor-specific memory T cells in draining lymph nodes (TdLN-T TSM cells) play a pivotal role in tumor repression that gives rise to progenitor exhausted T (T PEX ) cells and further replenishes tumor-specific CD8 + T cells residing in the tumor microenvironment (TME). However, how T TSM cells are maintained in TdLN is largely unknown. Here, we show that the transcription regulator ID3 (inhibitor of DNA binding 3) is highly expressed by T TSM cells compared with other CD8 + T cell subsets. The deficiency of ID3 significantly interrupts the maintenance of T TSM and T PEX cells, resulting in decreased tumor-infiltrating CD8 + T cells and impaired tumor control. Consistent with this, overexpression of ID3 in CD8 + T cells increases the T TSM cell population and enhances the anti-tumor immune response., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Abstract Background During pregnancy, trophoblast cell invasion needs to be finely controlled. Aberrant trophoblast cell invasion is associated with placental diseases. Epidermal growth factor (EGF) and its receptor, EGFR, are expressed in trophoblast cells. Although the pro-invasive effect of EGF on trophoblast cells has been reported, the underlying mechanism remains largely unknown. Results In the present study, we conducted an RNA sequencing (RNA-seq) to HTR-8/SVneo human trophoblast cells in response to EGF and identified KISS1 as a target gene of EGF. The human KISS1 gene encodes kisspeptin, also known as metastin, which can suppress tumor metastasis. Our results showed that EGF treatment downregulated KISS1 expression and secretion by activating the EGFR-mediated PI3K/AKT signaling pathway. In addition, the expression of inhibitor of DNA-binding protein 3 (ID3) was downregulated by EGF and that was required for the EGF-suppressed KISS1 expression. Functionally, transwell invasion assays demonstrated that EGF stimulated human trophoblast cell invasion by downregulating KISS1 expression. Preeclampsia (PE) is a placental disease characterized by insufficient trophoblast cell invasion. Our clinical results revealed that serum levels of EGF were downregulated while serum and placental levels of KISS1 were upregulated in PE patients. Conclusions This study demonstrates that downregulation of EGF can lead to poor trophoblast cell invasion by increasing KISS1 expression which subsequently contributes to the pathogenesis of PE. Video Abstract

T cells develop in the thymus from lymphoid primed multipotent progenitors or common lymphoid progenitors into ab and gd subsets. The basic helix-loophelix transcription factors, E proteins, play pivotal roles at multiple stages from T cell commitment to maturation. Inhibitors of E proteins, Id2 and Id3, also regulate T cell development while promoting ILC differentiation. Recent findings suggest that the thymus can also produce innate lymphoid cells (ILCs). In this review, we present current findings that suggest the balance between E and Id proteins is likely to be critical for controlling the bifurcation of T cell and ILC fates at early stages of T cell development. [ABSTRACT FROM AUTHOR]

Decision Trees are a common approach used for classifying unseen data into defined classes. The Information Gain is usually applied as splitting criteria in the node selection process for constructing the decision tree. However, bias in selecting the multi-variation attributes is a major limitation of using this splitting condition, leading to unsatisfactory classification performance. To deal with this problem, a new decision tree algorithm called “Knowledge-Based Decision Tree (KDT)” is proposed which exploits the knowledge in an ontology to assist the decision tree construction. The novelty of the study is that an ontology is applied to determine the attribute importance values using the PageRank algorithm. These values are used to modify the Information Gain to obtain appropriate attributes to be nodes in the decision tree. Four different datasets, Soybean, Heart disease, Dengue fever, and COVID-19 dataset, were employed to evaluate the proposed approach. The experimental results show that the proposed method is superior to the other decision tree algorithms, such as the traditional ID3 and the Mutual Information Decision tree (MIDT), and also performs better than a non-decision tree algorithm, e.g., the k-Nearest Neighbors. [ABSTRACT FROM AUTHOR]

Abstract Innate lymphoid cells (ILCs), comprising ILC1, 2, and 3 subpopulations, play unique roles in maintaining microbiome homeostasis, mucosal tissue integrity, and control of inflammation. So far, their characterization is dominantly based on tissue‐resident ILCs, whereas little information is available on circulating ILCs, in particular in newborns. In order to get a deeper understanding of neonatal innate immunity, we analyzed the transcriptomes and effector functions of cord blood (CB) ILCs. By RNAseq analysis, all ILC subsets could be clearly distinguished from each other. CB‐derived ILCs were generally closer related to neonatal T than natural killer (NK) cells and several factors shared by all three ILC subsets such as CD28, CCR4, and SLAMF1 are commonly expressed by T cells but lacking in NK cells. Notably, CB ILCs exhibited a unique signature of DNA binding inhibitor (ID) transcription factors (TF) with high ID3 and low ID2 expression distinct from PB‐ or tonsil‐derived ILCs. In vitro stimulation of sorted CB ILCs revealed distinct differences to tissue‐resident ILCs in that ILC1‐like and ILC3‐like cells were nonresponsive to specific cytokine stimulation, indicating functional immaturity. However, CB ILC3‐like cells expressed toll‐like receptors TLR1 and TLR2 and upon stimulation with the TLR2:1 ligand Pam3CSK4, responded with significantly increased proliferation and cytokine secretion. Together, our data provide novel insights into neonatal ILC biology with a unique TF signature of CB ILCs possibly indicating a common developmental pathway and furthermore a role of CB ILC3‐like cells in innate host defense.

T cells develop in the thymus from lymphoid primed multipotent progenitors or common lymphoid progenitors into αβ and γδ subsets. The basic helix-loop-helix transcription factors, E proteins, play pivotal roles at multiple stages from T cell commitment to maturation. Inhibitors of E proteins, Id2 and Id3, also regulate T cell development while promoting ILC differentiation. Recent findings suggest that the thymus can also produce innate lymphoid cells (ILCs). In this review, we present current findings that suggest the balance between E and Id proteins is likely to be critical for controlling the bifurcation of T cell and ILC fates at early stages of T cell development.

• ID3 remains a transcription factor that cannot be targeted for the prevention or treatment of cancer metastasis. • Milk thistle flavonolignan silibinin blocks the inducible activation of ID3 in brain endothelial cells. • Silibinin prevents the constitutive, acquired, and adaptive expression of ID3 in lung cancer cells. • Silibinin blocks ID3 transcription through BMP-responsive regulatory elements in ID3 gene enhancers. • Silibinin directly inhibits the kinase activity of the BMP receptors ACVRL1/ALK1 and BMPR2. • Silibinin suppresses ID3 overexpression in vivo at clinically relevant concentrations. ID3 (inhibitor of DNA binding/differentiation-3) is a transcription factor that enables metastasis by promoting stem cell-like properties in endothelial and tumor cells. The milk thistle flavonolignan silibinin is a phytochemical with anti-metastatic potential through largely unknown mechanisms. We have mechanistically investigated the ability of silibinin to inhibit the aberrant activation of ID3 in brain endothelium and non-small cell lung cancer (NSCLC) models. Bioinformatic analyses were performed to investigate the co-expression correlation between ID3 and bone morphogenic protein (BMP) ligands/BMP receptors (BMPRs) genes in NSCLC patient datasets. ID3 expression was assessed by immunoblotting and qRT-PCR. Luciferase reporter assays were used to evaluate the gene sequences targeted by silibinin to regulate ID3 transcription. In silico computational modeling and LanthaScreen TR-FRET kinase assays were used to characterize and validate the BMPR inhibitory activity of silibinin. Tumor tissues from NSCLC xenograft models treated with oral silibinin were used to evaluate the in vivo anti-ID3 effects of silibinin. Analysis of lung cancer patient datasets revealed a top-ranked positive association of ID3 with the BMP9 endothelial receptor ACVRL1/ALK1 and the BMP ligand BMP6. Silibinin treatment blocked the BMP9-induced activation of the ALK1-phospho-SMAD1/5-ID3 axis in brain endothelial cells. Constitutive, acquired, and adaptive expression of ID3 in NSCLC cells were all significantly downregulated in response to silibinin. Silibinin blocked ID3 transcription via BMP-responsive elements in ID3 gene enhancers. Silibinin inhibited the kinase activities of BMPRs in the micromolar range, with the lower IC 50 values occurring against ACVRL1/ALK1 and BMPR2. In an in vivo NSCLC xenograft model, tumoral overexpression of ID3 was completely suppressed by systematically achievable oral doses of silibinin. ID3 is a largely undruggable metastasis-promoting transcription factor. Silibinin is a novel suppressor of ID3 that may be explored as a novel therapeutic approach to interfere with the metastatic dissemination capacity of NSCLC. [Display omitted] [ABSTRACT FROM AUTHOR]

The main target of the work in this paper is to detect the gender and oldness of a person with an accurate decision and efficient time based on the number of facial outward attributes extracted using Linear-Discriminate Analysis to classify a person within a certain category according to his(her) gender and age. This work was deal with color facial images via the Iterative Dichotomiser3 algorithm as a classifier to detect the oldness of a person after gender detected. This paper used the Face-Gesture-Recognition-Research-Network aging dataset. All facial images in the dataset were categorizing into binary categories using k-means. This is followed by the process of dividing all samples according to age classes that belonging to each specific sex category. Thus, this division process enabled us to reach a quick and accurate decision. The results showed that the accuracy of the proposal was 90.93%, and F-measure was 89.4. [ABSTRACT FROM AUTHOR]

This research presents an effective method for automatically segmenting brain tumors using the proposed Optimized Thresholded Difference (OTD) and Rough Set Theory (RST). The tumor area is determined using the proposed two-level segmentation algorithm. The first level i.e., an overlay image is created, which is the intensity average of all the pixels of the brain area that were segmented in the initial stage. Then the second level, in which the process of the thresholded difference is applied between the brain area and the overlay image depending on the specified threshold. Features are extracted from the segmented images using the Gray-Level Co-occurrence Matrix (GLCM). To improve performance, an RST is employed with the extracted features. The completely automated methodology is validated using Figshare open dataset. [ABSTRACT FROM AUTHOR]

Bone morphogenetic protein (BMP) signaling has been shown to be intimately associated with adult neurogenesis in the subventricular zone (SVZ) and subgranular zone (SGZ). Adult neurogenesis declines in aging rodents and primates. However, the role of BMP signaling in the age-related neurogenesis decline remains elusive and the effect of BMP4 on adult SVZ neurogenesis remains controversial. Here, the expression of BMP4 and its canonical effector phosphorylated-Smad1/5/8 (p-Smad1/5/8) in the murine SVZ and SGZ were found to be increased markedly with age. We identified Id3 as a major target of BMP4 in neuronal stem cells (NSCs) of both neurogenic regions, which exhibited a similar increase during aging. Intracerebroventricular infusion of BMP4 activated Smad1/5/8 phosphorylation and upregulated Id3 expression, which further restrained NeuroD1, leading to attenuated neurogenesis in both neurogenic regions and defective differentiation in the SGZ. Conversely, noggin, a potent inhibitor of BMP4, demonstrated opposing effects. In support of this, BMP4 treatment or lentiviral overexpression of Id3 resulted in decreased NeuroD1 protein levels in NSCs of both neurogenic regions and significantly inhibited neurogenesis. Thus, our findings revealed that the increased BMP4 signaling with age inhibited adult neurogenesis in both SVZ and SGZ, which may be attributed at least in part, to the changes in the Id3-NeuroD1 axis. [ABSTRACT FROM AUTHOR]

Id3, an inhibitor of DNA binding protein, plays important roles in the function and homeostasis of effector and memory T cells. Recent evidence has shown that Id3 is also implicated in CD8 T cell exhaustion. However, whether and how Id3 might regulate effector function or exhaustion of CD8 T cells, especially in the tumor setting, is still unknown. Here, we first showed that Id3 expression was impaired in tumor-infiltrating CD8 T cells as liver cancer progressed, especially in PD-1 +Tim-3 + exhausted CD8 T cells. Enforced expression of Id3 in CD8 T cells resulted in repressed development of anti-tumor CTLs exhaustion, which offered better tumor control. And partially depletion of Id3 in CD8 T cells promoted the development of exhausted CD8 T cells. Furthermore, Id3hi CD8 T cells could respond to PD-1 blockade. Collectively, Id3 exerts protective functions in CD8 T cells for liver cancer. • Decreased expression of Id3 is associated with exhaustion CD8 T cells in liver cancer. Id3loCD8 T cells express high levels of inhibitory receptors. • Enforced Id3 expression prevented T cell exhaustion. • Low levels of Id3 expression is required for T cell exhaustion. • Id3lo CD8 T cells respond to PD-1 blockade. [ABSTRACT FROM AUTHOR]

Numerous studies have established the critical roles of microRNAs in regulating post-transcriptional gene expression in diverse biological processes. Here, we report on the role and mechanism of miR-24-3p in skeletal muscle differentiation and regeneration. miR-24-3p promotes myoblast differentiation and skeletal muscle regeneration by directly targeting high mobility group AT-hook 1 (HMGA1) and regulating it and its direct downstream target, the inhibitor of differentiation 3 (ID3). miR-24-3p knockdown in neonatal mice increases PAX7-positive proliferating muscle stem cells (MuSCs) by derepressing Hmga1 and Id3. Similarly, inhibition of miR-24-3p in the tibialis anterior muscle prevents Hmga1 and Id3 downregulation and impairs regeneration. These findings provide evidence that the miR-24-3p/HMGA1/ID3 axis is required for MuSC differentiation and skeletal muscle regeneration in vivo. [ABSTRACT FROM AUTHOR]

Artificial intelligence algorithms have an important and effective role in the medical field, especially in the field of diagnosing diseases. This research focuses on predicting the diagnosis of gestational diabetes by using the Iterative Dichotomiser3 (ID3) classifier algorithm, which is utilized to identify gestational diabetes; it was one of the most significant algorithms employed in this study. Training and testing are two critical phases of the research study. This study employed the Pima Indians Diabetes dataset, which comprised 768 women aged 21 and above with the eight reported traits. A feature selection stage, a discretization step, and using the classifier model for producing decision rules are all part of the Pima Indians diabetes data gathering process (Diabetes Dataset). In this study, the decision tree is employed to develop the classifier model, which is based on Diabetes training. The Iterative Dichotomiser3 (ID3) technique may be used to run the decision tree classification process. Diabetes is tested using decision rules, and the classifier implementation confusion matrix was retrieved from the testing portion. The system delivered high-quality results with a 94 percent accuracy rate. [ABSTRACT FROM AUTHOR]