Results 121 to 130 of about 356,775 (282)

The Arcsine Log-Logistic Distribution and Its Applications

European Journal of Mathematics and Statistics
This article introduces Arcsine Log-logistic (AL-L) distribution which is a member of Arcsine-G family proposed by Rahman. The different properties of AL-L distribution have been discussed. The distribution of various order statistics are obtained. Maximum Likelihood Estimation (MLE) technique is used to estimate the model parameters.
Md. Aftab Moral, Md. Shohel Rana, Md. Mahabubur Rahman   +2 more
openaire   +1 more source

Phosphatidic Acid‐TRIM59‐Olig2 Signaling Couples Metabolic Dysfunction to Myelination Failure in PWMI

Advanced Science, EarlyView.
PA accumulates after hypoxic‐ischemic injury and stabilizes the E3 ligase TRIM59 in OPCs. Stabilized TRIM59 enhances ubiquitination and degradation of Olig2, blocking differentiation and causing hypomyelination in PWMI. Modulating PA synthesis restores Olig2 levels, improves myelination, and ameliorates behavioral deficits, defining a metabolically ...
Xinyu Li, Yanan Liu, Meng Zhang, Yiwei Liu, Meiting Liu, Kaishen Zhu, Zhian Liu, Chao Ren, Ruiqin Yao   +8 more
wiley   +1 more source

New Generalized and Dual Generalized Order Statistics based Transmuted Log-Logistic Distributions

Journal of Statistical Theory and Applications (JSTA)
This paper introduces two extensions of the log-logistic distribution, namely the generalized order statistics transmuted log-logistic (GOSTLL) and the dual generalized order statistics transmuted log-logistic (DGOSTLL) distributions.
Manal Alharbi, Abdullah Almarashi, Muhammad Qaiser Shahbaz   +2 more
doaj   +1 more source

A New Artificial Intelligence Algorithm to Estimate the Survival Function  of the Modified Log-Logistic Distribution

Ibn Al-Haitham Journal for Pure and Applied Sciences
Survival analysis is a fundamental statistical tool for studying the period leading up to a specific event, such as patient death or device failure. Interest in this analysis has grown due to its ability to provide accurate insights into survival rates ...
Mohammed A.R. Hayoun, Bayda A. Kalaf, Erum Rehman   +2 more
doaj   +1 more source

Tumor‐Derived Exosomes Deliver Membrane‐Bound Fgl2 to Activate FcγRIIB‐Mediated Immunosuppression in Myeloid‐Derived Suppressor Cells

Advanced Science, EarlyView.
This study reveals that the Fgl2‐FcγRIIB signaling axis is a key mechanism by which MDSCs mediate tumor immune evasion. Tumor‐derived exosomes systemically activate MDSCs via this pathway, positioning this axis as a promising broad‐spectrum target for cancer immunotherapy.
Fenglin Lin, Dingqin Cai, Chunli Jian, Yaxian Qi, Linpeng Zheng, Qiao Yang, Longyao Zhang, Diangang Chen, Lingchen Li, Ping Cai, Lingyou Sun, Luping Zhang, Jianguo Sun   +12 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

ALKBH3 m1A Demethylase Deficiency Reduces Alzheimer's Amyloid‐β Pathology

Advanced Science, EarlyView.
This study identifies that ALKBH3‐driven m1A demethylation orchestrates Alzheimer's disease progression by disrupting mitochondrial and synaptic homeostasis. This epitranscriptomic mechanism suppresses PINK1‐mediated mitophagy via m1A erasure, leading to mitochondrial dysfunction, oxidative stress, elevated Aβ production, and impaired microglial ...
Yueyang Li, Sifei Yu, Kaidong Lu, Yujie Zhang, Mingjie Dong, Yan Peng, Liang Xue, Waleed Alam, Yuxuan Shui, Yi Zhou, Wuyunhan Ma, Meng Bao, Peiming Li, Peiyi Luo, Tiezhan Lu, Jiajia Li, Kang Zhang, Yuying Wang, Shuchen Yang, Nuoya Yin, Francesco Faiola, Zilong Gao, Jingfeng Zhou, Fei Zhao, Yali He, Magdalena J. Koziol   +25 more
wiley   +1 more source

Forecasting Root Rot Disease through Predictive Microbial Functional Profiling

Advanced Science, EarlyView.
Predicting soil‐borne disease moves beyond observation with a framework that elevates microbial functional genes into reliable forecasting biomarkers. By coupling targeted qPCR assays for core stress‐response genes with machine learning, this method detects root rot risks in pre‐symptomatic soils with over 80% accuracy.
Chuan You, Peng Ren, Ying Guan, Kai Gong, Zhen Hua, Wuxian Zhou, Xinlan Mei, Yikui Wang, Xiaofang Wang, Yangchun Xu, Qirong Shen, Zhong Wei   +11 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

A new and generalized family of heavy-tailed-Topp-Leone-type II exponentiated half logistic-G distribution with applications

Scientific African
We develop a novel family of distributions named heavy-tailed Topp-Leone-type II exponentiated half logistic distribution. Several mathematical properties including linear representation, Rényi entropy, quantile function, probability weighted moments ...
Oarabile Lekhane, Gomolemo Jacqueline Lekono, Broderick Oluyede, Lesego Gabaitiri   +3 more
doaj   +1 more source