Identification of Diagnostic Biomarkers and Therapeutic Targets in Sepsis-Associated ARDS via Combining Bioinformatics with Machine Learning Analysis by Liu T, Gao L, Li X

“…Differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis and immune infiltration analysis. …”
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Identification and predictive machine learning models construction of gut microbiota associated with lymph node metastasis in colorectal cancer by Yongzhi Wu, Chengen Deng, Zigui Huang, Yongqi Huang, Chuanbin Chen, Mingjian Qin, Zhen Wang, Fuhai He, Shenghai Liu, Rumao Zhong, Jun Liu, Chenyan Long, Jungang Liu, Weizhong Tang, Xiaoliang Huang

“…Furthermore, using transcriptome data from 23 CRC patients, we constructed an immune cell infiltration matrix to deeply explore the biological functions associated with LNM. Eventually, using the characteristics of the gut microbiota associated with LNM, we developed random forest (RF) and multilayer perceptron (MLP) machine learning models to predict the LNM status of CRC patients. …”
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning by Tao Zhou, Can Zhu, Wei Zhang, Qiongfang Wu, Mingqiang Deng, Zhiwei Jiang, Longfei Peng, Hao Geng, Zhouting Tuo, Zhouting Tuo, Ci Zou

“…The expression and biological functions of key genes in IC/BPS were further validated through in vitro experiments.ResultsA total of 87 DEGs were identified, comprising 43 up-regulated and 44 down-regulated genes. …”
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Development and clinical application of an automated machine learning-based delirium risk prediction model for emergency polytrauma patients by Zhenyi Liu, Yihao Huang, Long Li, Yisha Xu, Peng Wu, Zhigang Zhang, Tingyong Han, Liangjie Zhang, Ming Zhang

“…The SHapley Additive exPlanations (SHAP) framework quantified predictor contributions, and a MATLAB-based clinical decision support system (CDSS) was implemented for real-time risk stratification.ResultsThe improved algorithm significantly outperformed other algorithms on 12 standard test functions. The automated machine learning (AutoML) model achieved ROC-AUC and PR-AUC values of 0.9690 and 0.9611, respectively, on the training set, and 0.8929 and 0.8487, respectively, on the test set, both significantly higher than those of four other prediction models. …”
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Identifying Common Diagnostic Biomarkers and Therapeutic Targets between COPD and Sepsis: A Bioinformatics and Machine Learning Approach by Li X, Xiao Y, Yang M, Zhang X, Yuan Z, Zhang Z, Zhang H, Liu L, Zhao M

“…Differential expression gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were used to identify common genes. Functional enrichment analyses were conducted to explore the biological roles of these genes. …”
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Integrating proteomics and machine learning reveals characteristics and risks of lymph node-independent distant metastasis in colorectal cancer by Chenxiao Zheng, Baiwang Zhu, Yanyu Chen, Numan Shahid, Yiwang Hu, Hajar Mansoor Ahmed Ali Husain, Binbin Ou, Qiongying Zhang, Haobo Jin, Yating Zheng, Peng Li, Yifei Pan, Xiaodong Zhang, Xiaodong Zhang

“…Additionally, machine learning reveal ITGA11’s pivotal role in lymph node-independent metastasis. …”
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Reversed Effects of Intermittent Theta Burst Stimulation following Motor Training That Vary as a Function of Training-Induced Changes in Corticospinal Excitability by Tino Stöckel, Jeffery J. Summers, Mark R. Hinder

“…We conclude that iTBS has the potential to degrade prior motor learning as a function of training-induced CSE changes. …”
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Cannabidiol as a treatment for patients who are clinically at high risk of developing psychosis: learnings from the CANTOP-RCT by Sagnik Bhattacharyya, Cathy Davies, Ben Carter, Philip McGuire, Michael Brammer, Paolo Fusar-Poli, Matthew Broome, Stuart Watson, Jesus Perez, Alison Yung

“…Conclusions Here we summarise the events that led to this decision, reflect on the contributing factors and suggest potential learning points to help other researchers avoid such outcomes in future. …”
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Predictors of Occupational Adaptation in Individuals With Parkinson’s Disease by Jafar Haj Ghani, Ghorban Taghizadeh, Akram Azad, Seyed Amir Hasan Habibi

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Relationship between serum homocysteine, folate and vitamin B12 levels and cognitive function in patients with drug-naive obsessive-compulsive disorder by Yanru Ding, Shihao Lu, Shaoxia Wang, Yanrong Wang, Chujun Wu, Yunyun Du, Jianqun Fang

“…OCD symptom severity together with HCY and folate levels affect cognitive function.…”
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Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function by Imran Uddin, Dzati A. Ramli, Abdullah Khan, Javed Iqbal Bangash, Nosheen Fayyaz, Asfandyar Khan, Mahwish Kundi

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A High Accuracy Pedestrian Detection System Combining a Cascade AdaBoost Detector and Random Vector Functional-Link Net by Zhihui Wang, Sook Yoon, Shan Juan Xie, Yu Lu, Dong Sun Park

“…In order to overcome this problem, the authors propose an accurate pedestrian detection system based on two machine learning methods: cascade AdaBoost detector and random vector functional-link net. …”
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Effect of epigallocatechin-3-gallate (EGCG) on cognitive functioning and the expression of APP and BDNF in the hippocampus of rats with streptozotocin -induced Alzheimer-like disea... by Farnaz Ghayour Babaei, Ehsan Saburi, Fatemeh Forouzanfar, Mohadese Asgari, Zakieh Keshavarzi, Vahid Hajali

“…Real-time PCR assay was used for evaluating the expression of beta-amyloid precursor protein (APP) and brain-derived neurotrophic factor (BDNF) in the hippocampus of animals. STZ disrupted the function of animals in MWM acquisition phase by almost 65 % and all doses of EGCG could return the learning parameters to those of control animals. …”
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NNNPE: non-neighbourhood and neighbourhood preserving embedding by Kaizhi Chen, Chengpei Le, Shangping Zhong, Longkun Guo, Ge Xu

“…Second, we introduce the linear mapping to the objective function. Finally, the mapping matrix is calculated by the method of the fast learning Mahalanobis metric. …”
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Long Term Optimal DG Placement Considering Transmission System Reliability and Load Uncertainty by Ali Badri, Mahdy Norouzi

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A comparison of three executive function interventions on direct and far transfer in Chilean school children: a cluster-randomized controlled protocol by Nicholas Napolitano, Cristian A. Rojas-Barahona, Jorge Gaete, Ricardo Araya

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2023 Vision of Turkey, Public Library Policies and Çemişgezek : A Comparison of Public Libraries in Western Countries and Turkey with an Emphasis on Functional Aspects by Selma Alpay Aslan

“…However, it has been concluded that the full potential of the public libraries are not likely to be utilized because of the oversight of the gap in their service level compared to their European counterparts all these decades, and also because of emphasizing the cultural function of the public libraries rather than the role they can play in transitioning to knowledge society, contributing to closing the gap between the rich and the poor, helping with social inclusion and contributing to lifelong learning.…”
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Identification of Specific Abnormal Brain Functional Activity and Connectivity in Cancer Pain Patients: A Preliminary Resting-State fMRI Study by Hua Y, Geng Y, Liu S, Xia S, Liu Y, Cheng S, Chen C, Pang C, Zhao Z, Peng B, Dai Y, Ji J, Wu D

“…Through statistical analysis, differences in brain functional activity and connectivity between the cancer pain group and the healthy control group were investigated, followed by machine learning classification.Results: The results showed that compared to the normal group, reductions in the ALFF were primarily observed in the bilateral inferior temporal gyrus; ReHo increased in the right middle temporal gyrus and decreased in the left cerebellum Crus2. …”
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Hydra Radio Access Network (H-RAN): Multi-Functional Communications and Sensing Networks, Initial Access Implementation, and Task-2 Approach by Rafid I. Abd, Daniel J. Findley, Kwang Soon Kim

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Modeling Cross-Cultural Competence in Vocational Education Internationalization Using Neutrosophic SuperHyperFunctions and Big Data-Driven Cultural Clusters by Min Huang, Liang Zhang, Fenghua Li

“…This paper introduces a novel approach that models crosscultural competence using Neutrosophic SuperHyperFunctions. These functions allow for the representation of dynamic cultural clusters extracted from big data sources, including digital learning platforms and international student interactions. …”
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