Wen-Shou Tan^1,#, Hsuan Kuo^2,#, Chang-Ge Jiang¹, Mei-Han Lu¹, Yi-He Lu¹, Yung-Li Wang¹, Ching-Shuen Wang¹, Thi Thuy Tien Vo³, I-Ta Lee^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070871 - 30 December 2025

Abstract This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma (OSCC), a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis. Saliva has emerged as a noninvasive diagnostic medium capable of reflecting both local tumor activity and systemic physiological changes. Various salivary biomarkers, including microRNAs, cytokines, proteins, metabolites, and exosomes, have been linked to oncogenic signaling pathways involved in tumor progression, immune modulation, and therapeutic resistance. Advances in quantitative polymerase chain reaction, mass spectrometry, and next-generation sequencing have enabled comprehensive biomarker profiling, while point-of-care detection More >

Ashok Kumar Sah^1,*, Ranjay Kumar Choudhary^1,2, Velilyaeva Alie Sabrievna³, Karomatov Inomdzhon Dzhuraevich⁴, Anass M. Abbas⁵, Manar G. Shalabi⁵, Nadeem Ahmad Siddique⁶, Raji Rubayyi Alshammari⁷, Navjyot Trivedi⁸, Rabab H. Elshaikh¹

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.068238 - 30 December 2025

Abstract Male breast cancer (MBC) is rare, representing 0.5%–1% of all breast cancers, but its incidence is increasing due to improved diagnostics and awareness. MBC typically presents in older men, is human epidermal growth factor receptor 2 (HER2)-negative and estrogen receptor (ER)-positive, and lacks routine screening, leading to delayed diagnosis and advanced disease. Major risk factors include hormonal imbalance, radiation exposure, obesity, alcohol use, and Breast Cancer Gene 1 and 2 (BRCA1/2) mutations. Clinically, it may resemble gynecomastia but usually appears as a unilateral, painless mass or nipple discharge. Advances in imaging and liquid biopsy have More >

Ravita Chahar, Ashutosh Kumar Dubey^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-65, 2026, DOI:10.32604/cmc.2025.066990 - 10 November 2025

Abstract Objective: The increasing global prevalence of mental health disorders highlights the urgent need for the development of innovative diagnostic methods. Conditions such as anxiety, depression, stress, bipolar disorder (BD), and autism spectrum disorder (ASD) frequently arise from the complex interplay of demographic, biological, and socioeconomic factors, resulting in aggravated symptoms. This review investigates machine intelligence approaches for the early detection and prediction of mental health conditions. Methods: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework was employed to conduct a systematic review and analysis covering the period 2018 to 2025. The potential… More >

Mustansar Mubeen¹, Yasir Iftikhar^1,*, Ganesan Vadamalai^2,3, Muhammad Aasim⁴, Muhammad Faiq⁵, Uthman Balgith Algopishi⁶, Ahmed Ezzat Ahmed^6,7

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 3827-3843, 2025, DOI:10.32604/phyton.2025.071555 - 29 December 2025

Abstract Citrus viroids are small non-coding RNA pathogens that pose a significant threat to global citrus production by reducing fruit yield, quality, and tree longevity. Several viroids, including Citrus exocortis viroid (CEVd), Hop stunt viroid (HSVd), Citrus bent leaf viroid (CBLVd), and newly identified members such as Citrus Viroid VI (CVd-VI) and Citrus Viroid VII (CVd-VII) have been reported from diverse citrus-growing regions. These pathogens are transmitted mainly through vegetative propagation, contaminated tools, and occasionally via seed or pollen, making their management complex. This review synthesizes current knowledge on the biology, structural diversity, transmission, symptomatology, detection,… More >

Şeref Barbaros Arik^1,2,*, İnanç Güvenç^1,2

Canadian Journal of Urology, Vol.32, No.6, pp. 569-578, 2025, DOI:10.32604/cju.2025.068094 - 30 December 2025

Abstract Objectives: Differentiating benign from malignant testicular lesions is essential to avoid unnecessary surgery and ensure timely intervention. While conventional ultrasound remains the first-line imaging method, elastography and MRI provide additional functional and structural information. This study assesses the diagnostic utility of testicular elastography and magnetic resonance imaging (MRI) in differentiating benign and malignant testicular lesions. Methods: Patients with sonographically detected testicular masses were retrospectively evaluated using elastography, scrotal MRI, and tumor markers. Quantitative and qualitative imaging findings, lesion size, and laboratory values were recorded. Statistical analyses included Fisher’s exact test, logistic regression, Receiver operating characteristic… More >

Ilhong Son^1,2, Sun Jung Han², Dong Hwan Ho^1,3,*

BIOCELL, Vol.49, No.12, pp. 2283-2297, 2025, DOI:10.32604/biocell.2025.071119 - 24 December 2025

Abstract The potential of urinary biomarkers to facilitate non-invasive monitoring of Parkinson’s disease (PD) is a promising avenue, offering insights into the complex pathophysiology of the disease. The aggregation of α-synuclein, a central feature of PD, can be detected in urine, providing a diagnostic clue. Mutations in the LRRK2 gene, associated with increased kinase activity, can be estimated through the measurement of phosphorylated LRRK2 (pS1292) in urine. Oxidative stress, a hallmark of PD, is reflected in elevated levels of oxidized DJ-1 (oxDJ-1) in urine. Beyond these core biomarkers, other urinary components like DOPA decarboxylase, acetyl phenylalanine, More >

Huihui Yang¹, Saif Ur Rehman Khan^2,*, Omair Bilal², Chao Chen^1,*, Ming Zhao²

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2401-2434, 2025, DOI:10.32604/cmes.2025.072148 - 26 November 2025

Abstract Detecting Alzheimer’s disease is essential for patient care, as an accurate diagnosis influences treatment options. Classifying dementia from non-dementia in brain MRIs is challenging due to features such as hippocampal atrophy, while manual diagnosis is susceptible to error. Optimal computer-aided diagnosis (CAD) systems are essential for improving accuracy and reducing misclassification risks. This study proposes an optimized ensemble method (CEOE-Net) that initiates with the selection of pre-trained models, including DenseNet121, ResNet50V2, and ResNet152V2 for unique feature extraction. Each selected model is enhanced with the inclusion of a channel attention (CA) block to improve the feature… More >

Omar Sabri¹, Bassam Al-Shargabi^2,*, Abdelrahman Abuarqoub²

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2443-2486, 2025, DOI:10.32604/cmc.2025.066987 - 23 September 2025

Abstract This review comprehensively analyzes advancements in artificial intelligence, particularly machine learning and deep learning, in medical imaging, focusing on their transformative role in enhancing diagnostic accuracy. Our in-depth analysis of 138 selected studies reveals that artificial intelligence (AI) algorithms frequently achieve diagnostic performance comparable to, and often surpassing, that of human experts, excelling in complex pattern recognition. Key findings include earlier detection of conditions like skin cancer and diabetic retinopathy, alongside radiologist-level performance for pneumonia detection on chest X-rays. These technologies profoundly transform imaging by significantly improving processes in classification, segmentation, and sequential analysis across… More >

Jingxian Ni, Chaomeng Wang, Shiqi Sun, Yuxuan Sun, Gang Ma^*

Energy Engineering, Vol.122, No.9, pp. 3719-3736, 2025, DOI:10.32604/ee.2025.066971 - 26 August 2025

Abstract To improve the fault diagnosis accuracy of a PV grid-connected inverter, a PV grid-connected inverter data diagnosis method based on MPA-VMD-PSO-BiLSTM is proposed. Firstly, unlike the traditional VMD algorithm which relies on manual experience to set parameters (e.g., noise tolerance, penalty parameter, number of decompositions), this paper achieves adaptive optimization of parameters through MPA algorithm to avoid the problem of feature information loss caused by manual parameter tuning, and adopts the improved VMD algorithm for feature extraction of DC-side voltage data signals of PV-grid-connected inverters; and then, adopts the PSO algorithm for the Then, the… More >

Aya M. Al-Zoghby^1,2, Ahmed Ismail Ebada^1,*, Aya S. Saleh¹, Mohammed Abdelhay³, Wael A. Awad¹

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4155-4193, 2025, DOI:10.32604/cmc.2025.065571 - 30 July 2025

Abstract Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics, advancing precision medicine by enabling integration and learning from diverse data sources. The exponential growth of high-dimensional healthcare data, encompassing genomic, transcriptomic, and other omics profiles, as well as radiological imaging and histopathological slides, makes this approach increasingly important because, when examined separately, these data sources only offer a fragmented picture of intricate disease processes. Multimodal deep learning leverages the complementary properties of multiple data modalities to enable more accurate prognostic modeling, more robust disease characterization, and improved treatment decision-making. This review… More >