Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing by Zehua Wang, Zhongxiao Zhang

“…Five hub genes (CDKN2A, VIM, TGFB1, CTSS, and CDC20) were biomarkers with area under the curve (AUC) values > 0.8, indicating high predictive performance. In vitro validation experiments demonstrated that the expressions of all five biomarkers in KIRC cells were elevated, and the knockdown of CTSS could inhibit the migration and invasion of KIRC cells. …”
Get full text

Scenario Modelling for Reproducing Investment Potential of Institutional Sectors in the Regions of the Siberian Federal District by I. V. Naumov, A. V. Trynov, A. O. Safonov

“…This model suggests systems of predictive scenarios for the reproduction and choosing the optimal one to achieve positive dynamics of the socio-economic development of the regions. …”
Get full text

Identification of exosome-related genes associated with prognosis and immune infiltration features in pancreatic cancer by Jie Wang, Ming Qing, Jie Gui, Pingyong Zhong, Hao Hua

“…An ERG_score was developed for forecasting overall survival and its predictive capacity was confirmed in PC cases. A precise nomogram was established to enhance the clinical utility of the ERG_score. …”
Get full text

Association of MTHFR Polymorphisms with H-Type Hypertension: A Systemic Review and Network Meta-Analysis of Diagnostic Test Accuracy by Yixuan Kong, Jinghui Zheng, Lijuan Li, Liying Lu, Jie Wang

“…The present result suggests that MTHFR C667T rs1801133 polymorphism is associated with H-HTN risk and may act as a promising predictive biomarker for H-HTN risk. However, further well-designed studies are warranted to confirm these results.…”
Get full text

Integrating taxonomic and phenotypic information through FISH-enhanced flow cytometry for microbial community dynamics analysis by Valérie Mattelin, Josefien Van Landuyt, Frederiek-Maarten Kerkhof, Yorick Minnebo, Nico Boon

“…As a reference to correlate increased distinction with the incorporation of taxonomic information, 16S rRNA gene sequencing was used. Finally, a predictive algorithm was trained to correctly classify samples in the differently treated groups. …”
Get full text

Psychometric properties of the German version of the Traumatic Grief Inventory-Self Report Plus (TGI-SR+) by Julia Treml, Viktoria Schmidt, Elmar Braehler, Matthias Morfeld, Anette Kersting

“…Despite the same name, both versions of PGD differ in symptom count, content, and diagnostic algorithm. A single instrument to screen for both PGD diagnoses is critical for bereavement research and care. …”
Get full text

Modeling and optimization of culture media for recombinant Helicobacter pylori vaccine antigen HpaA by Runqing Tan, Song Zhou, Min Sun, Yu Liu, Xiumei Ni, Jin He, Gang Guo, Kaiyun Liu

“…The artificial neural network linked genetic algorithm (ANN-GA) model exhibited superior predictive accuracy, achieving a rHpaA yield of 0.61 g/L, which represents a 93.2% increase compared to the initial medium. …”
Get full text

Parameter Sensitivity Analysis and Irrigation Regime Optimization for Jujube Trees in Arid Regions Using the WOFOST Model by Shihao Sun, Yingjie Ma, Pengrui Ai, Ming Hong, Zhenghu Ma

“…In this regard, the use of crop models can compensate for time-consuming and costly field trials to screen for better irrigation regimes, but their predictive accuracy is often compromised by parameter uncertainty. …”
Get full text

Prognostic value of gene signatures and proliferation in lymph-node-negative breast cancer. by Kristin Jonsdottir, Jörg Assmus, Aida Slewa, Einar Gudlaugsson, Ivar Skaland, Jan P A Baak, Emiel A M Janssen

“…<h4>Introduction</h4>The overall survival rate is good for lymph-node-negative breast cancer patients, but they still suffer from serious over- and some undertreatments. Prognostic and predictive gene signatures for node-negative breast cancer have a high number of genes related to proliferation. …”
Get full text

The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

“…The prognostic model incorporating these five genes demonstrated robust predictive power in both training and validation cohorts. …”
Get full text

A Novel Multi-Scale Joint Approach for Estimating Lithium-ion Battery Model Parameters and SOC Considering Hysteresis Effect and Temperature by Xinhui Zhang, Wenyuan Bai, Shuyu Xie, Jiatong Wang, Danny Sutanto, Kashem M. Muttaqi

“…Experimental validation under DST, US06, and FUDS conditions demonstrates the effectiveness of the proposed method, achieving a maximum voltage prediction error of 0.0650 and a maximum SOC estimation error of 0.0092 across the full temperature range.…”
Get full text

Climatic suitability and potential distribution of earleaf acacia and its candidate biological control agent Trichilogaster sp by Sara S. MacDonald, Emily J. Le Falchier, Lindsay P. Campbell, Ryan Zonneveld, Carey R. Minteer

“…Both models exhibit high predictive accuracy, with AUC values above 0.9. This study emphasizes the need for continued monitoring and management of ELA and evaluates areas in Florida predicted to have suitable climatic conditions for Trichilogaster sp. nov. …”
Get full text

Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
Get full text

Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…This framework is underpinned by a sophisticated model integrating advanced monitoring systems with a Hybrid Simulated Annealing Genetic Algorithm (H-SAGA), further enhanced by neural network-driven real-time predictions. …”
Get full text

Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…Furthermore, AI is being utilized to develop personalized treatment plans by analyzing large datasets to predict individual responses to therapies, thus optimizing patient outcomes and reducing healthcare costs. …”
Get full text

Rural Renewable Energy Resources Assessment and Electricity Development Scenario Simulation Based on the LEAP Model by Hai Jiang, Haoshuai Jia, Yong Qiao, Wenzhi Liu, Yijun Miao, Wuhao Wen, Ruonan Li, Chang Wen

“…The energy trends under different demand growth rates were predicted through the LEAP model, revealing that in the clean coal scenario of carbon capture (WSBC-CCS), clean coal power and renewable energy will dominate by 2030. …”
Get full text

Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…The integration of artificial intelligence (AI) with nanotechnology marks a new frontier in personalised care. AI algorithms can analyse individual patient data to adjust insulin doses and predict glucose fluctuations, paving the way for more responsive, customised treatment plans. …”
Get full text

Multi-Frequency Microwave Sensing System with Frequency Selection Method for Pulverized Coal Concentration by Haoyu Tian, Feng Gao, Yuwei Meng, Xiaoyan Jia, Rongdong Yu, Zhan Wang, Zicheng Liu

“…These results indicate that the system could quantitatively predict PCC and promptly detect PCC fluctuations, highlighting its immediacy and reliability.…”
Get full text

Development of Quantitative Structure–Anti-Inflammatory Relationships of Alkaloids by Cristian Rojas, Doménica Muñoz, Ivanna Cordero, Belén Tenesaca, Davide Ballabio

“…Because they can be labelled as active or inactive compounds against the inflammatory biological response, the aim of this work was to calibrate quantitative structure-activity relationships (QSARs) using machine learning classifiers to predict anti-inflammatory activity based on the molecular structures of alkaloids. …”
Get full text

The GAN Spatiotemporal Fusion Model Based on Multiscale Convolution and Attention Mechanism for Remote Sensing Images by Youping Xie, Jun Hu, Kang He, Li Cao, Kaijun Yang, Luo Chen

“…Different attention weights are assigned based on their contributions to the final output, resulting in more accurate predicted images. MSCAM-GAN was tested on the Coleambally irrigated area and lower Gwydir catchment datasets and compared with classic spatiotemporal fusion algorithms. …”
Get full text