Targeting PPARγ via SIAH1/2-mediated ubiquitin-proteasomal degradation as a new therapeutic approach in luminal-type bladder cancer by Chih-Chieh Tu, Tsung-Han Hsieh, Cheng-Ying Chu, Yu-Chen Lin, Bo-Jyun Lin, Chun-Han Chen

“…NMIBC is more frequently classified as a luminal subtype, in which increased PPARγ activity is a key feature in promoting tumor growth and evasion of immunosurveillance. …”
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Insulin resistance-induced mitochondrial dysfunction and pyroptosis in trophoblasts: protective role of metformin by Runyu Du, Yu Bai, Ling Li, Ying Shao, Na Wu

“…This study aimed to investigate the impact of IR, a key feature of GDM, on mitochondrial dysfunction and pyroptosis in trophoblasts and to evaluate the protective effects of metformin. …”
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Durability and FTIR Characteristics of Sustainable Bacterial Concrete with Mineral Admixtures by R. Porselvan, T. S. Lakshmi, Muniyandi Tholkapiyan

“…A novel “binary and ternary blended cementitious system” was developed, featuring twelve distinct mix proportions. M-sand was fully utilized as an acceptable aggregate substitute, with bacterial concentrations of (10–50)·105 cells/ml incorporated to mitigate crack formation. …”
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SHM System for Composite Material Based on Lamb Waves and Using Machine Learning on Hardware by Gracieth Cavalcanti Batista, Carl-Mikael Zetterling, Johnny Öberg, Osamu Saotome

“…To process the complex Lamb wave signals, the system incorporates well-known signal processing (DSP) techniques, including power spectrum density (PSD), wavelet transform, and Principal Component Analysis (PCA), for noise reduction, feature extraction, and data compression. These techniques enable the system to handle material anisotropy and mitigate the effects of edge reflections and mode conversions. …”
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Comprehensive Reservoir Architecture Dissection and Microfacies Analysis of the Chang 8 Oil Group in the Luo 1 Well Area, Jiyuan Oilfield by Jing Wang, Lixin Wang, Yanshu Yin, Pengfei Xie, Ge Xiong

“…Key findings reveal that the study area is characterized by a shallow-water deltaic depositional system, featuring three principal sedimentary microfacies: subaqueous distributary channels, sheet sands, and lacustrine muds. …”
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Dashboard‑Driven Machine Learning Analytics and Conceptual LLM Simulations for IIoT Education in Smart Steel Manufacturing by Mehdi Imani, Ali Imanifard, Babak Majidi, Abdolah Shamisa

“…Through advanced analytical models such as machine learning (ML) and, conceptually, Large Language Models (LLMs), this study explores how Industrial Internet of Things (IIoT) applications can transform educational experiences in the context of smart steel production. To mitigate the shortage of authentic industrial datasets for research, we developed an industry-validated IIoT educational dataset drawn from three months of operational records at a steel plant and enriched with domain-specific annotations—most notably distinct operational phases. …”
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FTIR-SpectralGAN: A Spectral Data Augmentation Generative Adversarial Network for Aero-Engine Hot Jet FTIR Spectral Classification by Shuhan Du, Yurong Liao, Rui Feng, Fengkun Luo, Zhaoming Li

“…This configuration progressively reduces feature dimensions and mitigates overfitting. During training, the generator learns the underlying distribution of spectral data, while the discriminator distinguishes between real and synthetic data and performs spectral classification. …”
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Technical solution for purifying emissions of climate-active gases by A. Yu. Briukhanov, E. V. Vasilev, S. A. Egorov

“…The system is equipped with digital sensors for monitoring and controlling the operational workflow. A special feature of the proposed system design is the use of replaceable filter cartridges and an active irrigation system. …”
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Coral reef detection using ICESat-2 and machine learning by Gabrielle A. Trudeau, Kim Lowell, Jennifer A. Dijkstra

“…Feature importance analysis identified satellite-derived bathymetry (SDB) depth as the most critical predictor of coral presence, followed by pseudo-rugosity, slope, and various other depth measurements. …”
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Single-Source and Multi-Source Cross-Subject Transfer Based on Domain Adaptation Algorithms for EEG Classification by Rito Clifford Maswanganyi, Chunling Tu, Pius Adewale Owolawi, Shengzhi Du

“…In this paper, domain adaptation algorithms, including two machine learning (ML) algorithms, are contrasted based on the single-source-to-single-target (STS) and multi-source-to-single-target (MTS) transfer paradigms, mainly to mitigate the challenge of immense inter-subject variations in EEG neural dynamics that lead to poor classification performance. …”
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Compressing Neural Networks on Limited Computing Resources by Seunghyun Lee, Dongjun Lee, Minju Hyun, Heeje Kim, Byung Cheol Song

“…Second, to minimize the computational cost of knowledge distillation, we introduce a synthetic teacher assistant that leverages precomputed fixed knowledge—referring to the stored feature maps/logits of the teacher network. By leveraging fixed knowledge, we mitigate the cost incurred by the teacher network and facilitate the transmission of fixed knowledge to the student via synthetic teacher assistants, thereby preventing distribution collapse. …”
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An enhanced lightweight model for apple leaf disease detection in complex orchard environments by Ge Wang, Wenjie Sang, Fangqian Xu, Yuteng Gao, Yue Han, Qiang Liu

“…To address the challenges of detecting small-target diseases on apple leaves in complex backgrounds and difficulty in mobile deployment, we propose an enhanced lightweight model, ELM-YOLOv8n.To mitigate the high consumption of computational resources in real-time deployment of existing models, we integrate the Fasternet Block into the C2f of the backbone network and neck network, effectively reducing the parameter count and the computational load of the model. …”
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Climate change impacts and sustainability integration among breast international group members by Seamus O'Reilly, Jessica Griffiths, Lisa Fox, Catherine S. Weadick, Nay My Oo, Lucy Murphy, Robert O'Leary, Theodora Goulioti, Virginie Adam, Evangelia D. Razis, Barbro Lindholm, Gustavo Werustsky, David Cameron, Judith Bliss

“…Methods: We assessed climate change impacts, existing sustainability engagement, and challenges and facilitators to climate change mitigation strategies among Breast International Group (BIG) members. …”
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Research Review and Prospect of Litchi Fruit Cracking by Xiwen LI, Haoshuang SUN, Xuequn PANG, Zhaoqi ZHANG

“…In this review, we introduce the phenomenon of litchi fruit cracking and the diversity of fruit cracking types, and emphasize the distinct feature of litchi fruit cracking along the suture line. …”
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Socioeconomic and demographic factors associated with anaemia among women of reproductive age in Zimbabwe: a supervised machine learning approach by Garikayi Chemhaka, Elliot Mbunge, Tafadzwa Dzinamarira, Godfrey Musuka, John Batani, Benhildah Muchemwa, Stephen Fashoto, Munyaradzi Mapingure, Rutendo Birri Makota, Ester Petrus

“…Predictive models can aid healthcare practitioners in identifying at-risk individuals and implementing timely interventions to mitigate the impact of anaemia.…”
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A pathology-attention multi-instance learning framework for multimodal classification of colorectal lesions by Fanglei Fu, Xuemei Zhang, Zhaoxuan Wang, Luxi Xie, Mingxi Fu, Jing Peng, Jianfeng Wu, Zhe Wang, Tian Guan, Yonghong He, Jin-Shun Lin, Lianghui Zhu, Wenbin Dai

“…On external datasets CRS-2024 and UniToPatho, the model reaches 95.78% and 84.09% accuracy, exceeding the best baselines by 2.22% and 5.68%, respectively.DiscussionThese results demonstrate that PAT-MIL effectively mitigates staining variability and enhances cross-center generalization through the collaborative modeling of visual and textual modalities. …”
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Foreground-Driven Contrastive Learning for Unsupervised Human Keypoint Detection by Shuxian Li, Hui Luo, Zhengwei Miao, Zhixing Wang, Qiliang Bao, Jianlin Zhang

“…Considering that keypoints vary due to changes in appearance and pose, we then introduce the contrastive loss to expand the feature space and enhance the network's robustness. …”
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Driving factors of fragmentation in urban landscapes: Local contributions, spatial relationships, and causal effects by Simin Jiang, Fei Feng, Xinna Zhang, Chengyang Xu, Baoquan Jia, Raffaele Lafortezza

“…The influence of impervious surface expansion intensity showed an inverted “U” shape over time in spatial correlation and causal effect, suggesting that while initial urban expansion increases fragmentation, advanced urbanization and green space restoration can mitigate these effects.…”
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Comparative Analysis of Hybrid Attention and Progressive Layering Through a Comprehensive Evaluation of ARU-Net and PLU-Net in Brain Tumour Segmentation by Noman Ahmed Siddiqui, Muhammad Tahir Qadri, Muhammad Ovais Akhter, Tahira Anwar, Fahad Farooq

“…ARU-Net mainly uses the methods of integrating the Convolutional Block Attention Modules (CBAM) and Squeeze-and-Excitation (SE) blocks, adding a regression-based output layer to generate continuous probability maps, which further focuses on feature recalibration and heterogeneity adaptation to tumour regions. …”
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Home-Based Lower Limb Exercises for Individuals with Diabetes: A Scoping Review by Sylwia Bęcławska, Michalina Błażkiewicz, Piotr Czyżewski, Tomasz Rutkowski, Jacek Wąsik

“…While conventional interventions such as specialized footwear and podiatric care can mitigate ulceration risks, they do not address the biomechanical factors contributing to ulcer recurrence. …”
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