Mariana Lopes^1,#, Carlos Vila Nova^2,3,#, Rui Caetano Oliveira^3,4, Fernando Schmitt⁵, Fernando Mendes^1,6,7,8,9,*, Diana Martins^1,6,7,8

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.074215 - 21 May 2026

Abstract Objectives: Triple-negative breast cancer (TNBC) accounts for approximately 15% of all invasive breast cancers and is characterized by aggressive behavior, limited therapeutic options, and poor clinical outcomes. Due to the absence of hormone receptors and HER2 expression, systemic treatment relies predominantly on chemotherapy, which is associated with high rates of early recurrence and mortality. Emerging evidence suggests that alterations in the microbiome can contribute to TNBC progression and influence therapeutic response, particularly affecting the efficacy of chemotherapy and immunotherapy through immune-mediated mechanisms; however, its role in TNBC remains incompletely understood. This systematic review aims to explore… More >

Minhyeok Choi¹, Imran Ahsan², Hyunwook Yu¹, Taeyoung Choe¹, Mucheol Kim^1,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079504 - 08 May 2026

Abstract Large language models (LLMs) are increasingly integrated into recommender systems to support semantic reasoning, natural language understanding, and user-adaptive personalization. However, their reliance on static parametric knowledge and fixed representations limits robustness in dynamic environments, particularly under long-tail and cold-start conditions. Retrieval-augmented architectures have emerged to address these limitations by grounding LLMs in external, non-parametric knowledge sources. This systematic literature review synthesizes 138 peer-reviewed studies published between 2023 and 2025 in conferences and journals, focusing on retrieval-augmented and LLM-enhanced recommendation. We analyze these works through a three-dimensional framework covering: (i) domain application, (ii) semantic feature… More >

Yahya Ghazwani^1,2,3, Mohammad Alghafees^1,2,3,*, Mishari Alshasha^1,2,3, Fahad Brayan^1,2,3, Abdulrahman Alsayyari^1,2,3, Ali Alyami^1,2,3

Canadian Journal of Urology, Vol.33, No.2, pp. 291-308, 2026, DOI:10.32604/cju.2026.077411 - 20 April 2026

Abstract Objectives: The emergence of artificial intelligence (AI) and predictive modeling offers prospects for clinical, anatomical, and imaging factor combination, like radiomics, to help with stone-free status (SFS) estimation and peroperative decision-making. The goal of this study was, therefore, to define the present performance range, determine sources of heterogeneity, and determine methodological practices permitting reliable implementation by varied circumstances. Methods: We searched six bibliographic databases through 19 September 2025. Studies deriving or validating AI/predictive models for SFS after ureteroscopy were eligible. Independent dual screening, duplicate data extraction, and risk-of-bias consideration using QUADAS-AI were conducted. Results: Five retrospective… More >

Yifan Huang^1,2,#, Bingzhi Han^2,#, Zikai Huang^1,2, Qianhao Huang², Tao Wang^2,*, Yuedong Chen^1,2,*

Canadian Journal of Urology, Vol.33, No.2, pp. 309-323, 2026, DOI:10.32604/cju.2026.070466 - 20 April 2026

Abstract Objectives: The external physical vibration lithecbole (EPVL) is a new device. It is clinically employed to improve the stone-free rate (SFR). However, it is not widely accepted in clinical practice due to the lack of high-level evidentiary support and a standard protocol. This study aimed to evaluate the effectiveness and safety of external physical vibration lithecbole (EPVL) as an adjunct to extracorporeal shock wave lithotripsy (ESWL) or retrograde intrarenal surgery (RIRS) for upper urinary tract stones. Methods: We systematically searched PubMed, Web of Science, Embase, the China National Knowledge Infrastructure (CNKI), and the Cochrane Library… More >

Hamed Alqahtani¹, Gulshan Kumar^2,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077367 - 09 April 2026

Abstract Large Language Models (LLMs) are becoming integral components of modern cybersecurity ecosystems, simultaneously strengthening defensive capabilities while giving rise to a new class of Artificial Intelligence–Generated Content (AIGC)-driven threats. This PRISMA-guided systematic review synthesises 167 peer-reviewed studies published between 2022 and 2025 and proposes a unified threat–defence–evaluation taxonomy as a central analytical framework to consolidate a previously fragmented body of research. Guided by this taxonomy, the review first examines AIGC-enabled threats, including automated and highly personalised phishing, polymorphic malware and exploit generation, jailbreak and adversarial prompting, prompt-injection attack vectors, multimodal deception, persona-steering attacks, and large-scale… More >

Muhammad Adnan Tariq¹, Sunawar Khan², Tehseen Mazhar^2,3, Tariq Shahzad⁴, Sahar Arooj⁵, Khmaies Ouahada⁶, Muhammad Adnan Khan^7,*, Habib Hamam^8,9,10,11

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.078672 - 30 March 2026

Abstract The contemporary smart cities, smart homes, smart buildings, and smart health care systems are the results of the explosive growth of Internet of Things (IoT) devices and deep learning. Yet the centralized training paradigms have fundamental issues in data privacy, regulatory compliance, and ownership silo alongside the scaled limitations of the real-life application. The concept of Federated Deep Learning (FDL) is a privacy-by-design method that will enable the distributed training of machine learning models among distributed clients without sharing raw data and is suitable in heterogeneous urban settings. It is an overview of the privacy-preserving… More >

M. Mohsin Raza^1,#, Muhammad Umair^1,#, Imran Arshad Choudhry¹, Muhammad Qasim¹, Muhammad Tahir Naseem^2,*, Mamoona Naveed Asghar³, Daniel Gavilanes^4,5,6,7, Manuel Masias Vergara^4,8,9, Imran Ashraf^10,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2025.074164 - 30 March 2026

Abstract Over the past decade, the landscape of cybersecurity has been increasingly shaped by the growing sophistication and frequency of malware attacks. Traditional detection techniques, while still in use, often fall short when confronted with modern threats that use advanced evasion strategies. This systematic review critically examines recent developments in malware detection, with a particular emphasis on the role of artificial intelligence (AI) and machine learning (ML) in enhancing detection capabilities. Drawing on literature published between 2019 and 2025, this study reviews 105 peer-reviewed contributions from prominent digital libraries including IEEE Xplore, SpringerLink, ScienceDirect, and ACM… More >

Jian Li^1,*, Yide Chen², Xinyi Zhao³, Eryong Xue^3,*

International Journal of Mental Health Promotion, Vol.28, No.3, 2026, DOI:10.32604/ijmhp.2026.073286 - 31 March 2026

Abstract Background: The mobility of people in rural areas may lead to more and more left-behind children (LBC) appearing, and being an LBC brings a lot of risks to mental health, which could greatly hinder children’s development and undermine their happiness and safety in life. Previous scholars have conducted plenty of studies that focused on Chinese rural LBCs’ mental health issues, such as what they exactly look like and some potential factors, but there remains a paucity of reviews about the relationship among certain mental health issues. We will try to figure out how the most common… More >

Francesco Chiari^1,*, Giovanni Motta², Daria Maria Filippini³, Claudio Donadio Caporale¹, Pierre Guarino¹

Oncology Research, Vol.34, No.4, 2026, DOI:10.32604/or.2026.073086 - 23 March 2026

Abstract Objective: Mucoepidermoid carcinoma (MEC) of the larynx is an extremely rare malignancy, accounting for less than 1% of primary laryngeal tumors. The optimal role of adjuvant therapy, particularly radiotherapy (RT), remains unclear due to limited evidence. This systematic review aimed to evaluate oncologic outcomes and the impact of adjuvant treatment in patients with early- and advanced-stage laryngeal MEC. Methods: A systematic literature search was performed according to PRISMA 2020 guidelines in PubMed/Embase, Scopus, and Cochrane for studies published up to 31 July 2025. Results: Twenty-two studies, encompassing 55 patients, were included. Early-stage (T1–T2) patients (n =… More >

Donatella Coradduzza^1,#, Anna La Salvia^2,#, Giuseppe Fanciulli³, Maria Rosaria De Miglio^3,*

Oncology Research, Vol.34, No.4, 2026, DOI:10.32604/or.2025.073045 - 23 March 2026

Abstract Background: An increasing number of studies have shown that ferroptosis is related to the initiation and development of small cell lung cancer (SCLC). The systematic review aimed to summarize the characteristics of ferroptosis from its pathogenetic role to translational therapeutic implications in SCLC. Methods: This systematic review, registered in PROSPERO (CRD420251090058), followed PRISMA 2020 guidelines. Comprehensive research of PubMed, Scopus, and Web of Science was performed for studies published between January 2010 and July 2025 investigating ferroptosis mechanisms, genetic or pharmacological modulation, or molecular profiling in SCLC. Two reviewers independently performed data extraction and quality… More >