Jiazhou Li^1,2, Mingyu Zhang¹, Xing Li^1,3, Fangbo Cao^1,2, Jiana Chen^1,2, Weiqin Wang^1,2, Huabin Zheng^1,2, Min Huang^1,2,4,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2025.075255 - 30 January 2026

Abstract Spikelet filling characteristics in early-season rice in southern China may be distinctive due to its exposure to high temperatures during the ripening period. However, limited information is currently available on these characteristics. This study aimed to characterize spikelet filling in early-season rice and identify the key factors contributing to its improvement. Field experiments were conducted over two years (2021 and 2022) to mainly investigate the proportions of fully-filled, partially-filled, and empty spikelets, along with the biomass-fertilized spikelet ratio and harvest index, in 11 early-season rice varieties. The results revealed significant varietal variation in spikelet filling,… More >

Menwa Alshammeri^1,2,*, Noshina Tariq³, NZ Jhanji^4,5, Mamoona Humayun⁶, Muhammad Attique Khan⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074627 - 29 January 2026

Abstract Artificial Intelligence (AI) is changing healthcare by helping with diagnosis. However, for doctors to trust AI tools, they need to be both accurate and easy to understand. In this study, we created a new machine learning system for the early detection of Autism Spectrum Disorder (ASD) in children. Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning. For this, we combined several different models, including Random Forest, XGBoost, and Neural Networks, into a single, more powerful framework. We used two different types More >

Vaskar Chakma^1,*, Md Jaheid Hasan Nerab¹, Abdur Rouf¹, Abu Sayed², Hossem Md Saim³, Md. Nournabi Khan³

Journal of Intelligent Medicine and Healthcare, Vol.4, pp. 1-35, 2026, DOI:10.32604/jimh.2026.074347 - 23 January 2026

Abstract Smoking continues to be a major preventable cause of death worldwide, affecting millions through damage to the heart, metabolism, liver, and kidneys. However, current medical screening methods often miss the early warning signs of smoking-related health problems, leading to late-stage diagnoses when treatment options become limited. This study presents a systematic comparative evaluation of machine learning approaches for smoking-related health risk assessment, emphasizing clinical interpretability and practical deployment over algorithmic innovation. We analyzed health screening data from 55,691 individuals, examining various health indicators including body measurements, blood tests, and demographic information. We tested three advanced… More >

Zongmeng Zhang^1,2,#, Cai Chen^3,#, Shaorui Rui³, Conghan Li³, Jiong Gu^3,*, Liang He^3,*

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.073085 - 23 January 2026

Abstract Objective: Hepatocellular carcinoma (HCC) ranks among the most prevalent malignant tumors globally. Metabolically associated fatty liver disease is a significant risk factor for HCC. Adiponectin, a key regulatory protein in glucolipid metabolism, presents potential as an anti-tumor target in HCC cells. The study focused on evaluating the anti-HCC properties of AdipoRon, an agonist of the adiponectin receptor. Method: Cell viability and proliferation were assessed using the cell counting kit-8 and colony formation assays, respectively. AdipoRon’s effect on HCC cell damage was evaluated via flow cytometry, apoptosis, and (lactate dehydrogenase) LDH assays. Mitochondrial function was evaluated… More >

Hang Zhang^1,#, Meng-Yuan Chu^1,#, Guohui Lv¹, You-Jie Li¹, Xuhang Liu², Fei Jiao^1,*, Yun-Fei Yan^1,*

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.068322 - 23 January 2026

Abstract Objectives: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality, with limited understanding of lncRNA-driven mechanisms in tumor progression. This study aimed to identify differentially expressed lncRNAs in NSCLC tissues and elucidate the functional role of the significantly upregulated RP3-340N1.2 in promoting malignancy. Methods: RNA sequencing was used to screen dysregulated lncRNAs. RP3-340N1.2 was functionally characterized via gain/loss-of-function assays in NSCLC cells, assessing proliferation, migration, and macrophage polarization. Mechanisms of interleukin 6 (IL-6) regulation were explored using cytokine profiling, Actinomycin D assays, and RNA Immunoprecipitation (RIP) assays to study RP3-340N1.2 interactions with… More >

Ruoxue Cai^1,#, Shuyi Hu^2,#, Feiyang Li², Huanhuan Sha^3,*, Guoren Zhou^2,*, Ying Fang³

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.070893 - 19 January 2026

Abstract Objective: To determine whether immunotherapy can bring new hope for patients with limited-stage small-cell lung cancer (LS-SCLC). We conducted this retrospective study to evaluate whether immunotherapy can achieve better efficacy in LS-SCLC patients. Methods: We evaluated 122 LS-SCLC patients who received concurrent chemoradiotherapy (CCRT) or sequential chemoradiotherapy (SCRT) (Group A) and immunotherapy combined with CCRT/SCRT followed by immunotherapy (Group B), to assess the objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). Factors affecting prognosis were also explored using Cox analysis. The prognosis of patients with type 2 diabetes and patients with… More >

Sai Xu^1,*, Jun Liu^1,*, Shengyu Huang¹, Zhi Li²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071865 - 12 January 2026

Abstract In scenarios where ground-based cloud computing infrastructure is unavailable, unmanned aerial vehicles (UAVs) act as mobile edge computing (MEC) servers to provide on-demand computation services for ground terminals. To address the challenge of jointly optimizing task scheduling and UAV trajectory under limited resources and high mobility of UAVs, this paper presents PER-MATD3, a multi-agent deep reinforcement learning algorithm with prioritized experience replay (PER) into the Centralized Training with Decentralized Execution (CTDE) framework. Specifically, PER-MATD3 enables each agent to learn a decentralized policy using only local observations during execution, while leveraging a shared replay buffer with More >

Chao Li^1,3,#, Jianing Wang^1,3,#, Caichang Ding^2,*, Zhiwei Ye^1,3

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071242 - 12 January 2026

Abstract Underwater images frequently suffer from chromatic distortion, blurred details, and low contrast, posing significant challenges for enhancement. This paper introduces AquaTree, a novel underwater image enhancement (UIE) method that reformulates the task as a Markov Decision Process (MDP) through the integration of Monte Carlo Tree Search (MCTS) and deep reinforcement learning (DRL). The framework employs an action space of 25 enhancement operators, strategically grouped for basic attribute adjustment, color component balance, correction, and deblurring. Exploration within MCTS is guided by a dual-branch convolutional network, enabling intelligent sequential operator selection. Our core contributions include: (1) a More >

Manaliben Amin^*

Journal on Artificial Intelligence, Vol.8, pp. 1-18, 2026, DOI:10.32604/jai.2026.073895 - 07 January 2026

Abstract Artificial intelligence (AI) is steadily making its way into pharmaceutical validation, where it promises faster documentation, smarter testing strategies, and better handling of deviations. These gains are attractive, but in a regulated environment speed is never enough. Regulators want assurance that every system is reliable, that decisions are explainable, and that human accountability remains central. This paper sets out a Human-in-the-Loop (HITL) AI approach for Computer System Validation (CSV) and Computer Software Assurance (CSA). It relies on explainable AI (XAI) tools but keeps structured human review in place, so automation can be used without creating… More >

Keiko Yanagihara^1,*, Masato Yoshida², Kensaku Awaji², Tamami Yamakawa¹, Sena Kato¹, Miki Tamura¹, Koji Nagata³

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.073891 - 30 December 2025

Abstract Background: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have transformed the management of hormone receptor–positive/HER2–negative (HR+/HER2–) advanced breast cancer, yet evidence for elderly or poor-performance patients remains limited. This study examined real-world outcomes of palbociclib plus endocrine therapy in Asian patients, with additional subgroup analyses by age and performance status. Methods: We retrospectively analyzed 46 consecutive Asian patients with recurrent or de novo HR+/HER2− breast cancer treated with first-line palbociclib plus ET between April 2021 and March 2025. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rate (ORR), disease control rate (DCR), and safety.… More >