Sandra Pérez-Álvarez^1,*, Eduardo Fidel Héctor-Ardisana², Eduardo Sandoval Castro³, Erick H. Ochoa-Chaparro⁴, Luisa Patricia Uranga-Valencia¹

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 3749-3803, 2025, DOI:10.32604/phyton.2025.072135 - 29 December 2025

Abstract Grape (Vitis vinifera L.) cultivation has progressed from early domestication and clonal propagation to modern, data-driven breeding that is reshaping viticulture and wine quality. Yet climatic and biotic constraints still impose heavy losses—downy mildew can reduce yields by ≈75% in humid regions and gray mold by 20–50%—sustaining the need for resistant cultivars. Producer selection, interspecific crossing, and formal improvement programs have generated ~10,000 varieties, although only a few dozen dominate global acreage. Conventional breeding has delivered fungus-resistant “PIWI” cultivars that retain ≥85% of the V. vinifera genome; in Austria, national PIWI varieties are gaining acceptance for combined… More >

Federico Greco^1,2,*, Marco Cataldo³, Valerio D’Andrea^2,4, Luca Pugliese⁵, Andrea Panunzio⁶, Alessandro Tafuri⁶, Bruno Beomonte Zobel^2,4, Carlo Augusto Mallio^2,4

Canadian Journal of Urology, Vol.32, No.5, pp. 433-443, 2025, DOI:10.32604/cju.2025.068390 - 30 October 2025

Abstract Background: Radiogenomics offers a non-invasive approach to correlate imaging features with tumor molecular profiles. This study aims to identify computed tomography (CT) imaging characteristics associated with positive NIPA-like domain containing 4 (NIPAL4) expression in clear cell renal cell carcinoma (ccRCC) and to develop a radiogenomic predictive model to support personalized risk stratification. Methods: A retrospective analysis was conducted on 241 ccRCC patients from The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) databases. Clinical, pathological, and CT features were compared between NIPAL4-positive and NIPAL4-negative groups. A penalized logistic regression model was built to… More >

José Luis Rodríguez-Lorenzo¹, Bohuslav Janoušek¹, Emilio Cervantes^2,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2649-2667, 2025, DOI:10.32604/phyton.2025.068936 - 30 September 2025

Abstract Grapevine is unique among crops because its domestication resulted not only in new morphological characteristics, but also in altered reproductive mechanisms. Viticulture involves a change from a dioecious to a hermaphroditic mating system, which makes the reproductive system more efficient. In consequence and the fact that it is one of the oldest and most economically important cultivated plants, Vitis vinifera could be defined as an over-domesticated species. Here we review some key aspects in viticulture. The main areas of interest have remained consistent throughout history, including the origin and characterisation of cultivars, resistance to environmental conditions,… More >

HUAFANG HUANG^1,2,#, GUILIN WANG^3,#, DONGYUN ZENG^4,5, LUZ ANGELA TORRES-DE LA ROCHE², RUI ZHUO^1,2, RUDY LEON DE WILDE², WANWAN WANG⁶, ULF D. KAHLERT^7,*, WENJIE SHI^7,*

Oncology Research, Vol.33, No.3, pp. 631-640, 2025, DOI:10.32604/or.2024.054642 - 28 February 2025

Abstract Background: Neoadjuvant chemotherapy (NAC) significantly enhances clinical outcomes in patients with triple-negative breast cancer (TNBC); however, chemoresistance frequently results in treatment failure. Consequently, understanding the mechanisms underlying resistance and accurately predicting this phenomenon are crucial for improving treatment efficacy. Methods: Ultrasound images from 62 patients, taken before and after neoadjuvant therapy, were collected. Mitochondrial-related genes were extracted from a public database. Ultrasound features associated with NAC resistance were identified and correlated with significant mitochondrial-related genes. Subsequently, a prognostic model was developed and evaluated using the GSE58812 dataset. We also assessed this model alongside clinical factors… More >

Ahmed Zohair Ibrahim^1,*, P. Prakash², V. Sakthivel², P. Prabu³

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2447-2460, 2023, DOI:10.32604/csse.2023.030134 - 21 December 2022

Abstract In order to research brain problems using MRI, PET, and CT neuroimaging, a correct understanding of brainfunction is required. This has been considered in earlier times with the support of traditional algorithms. Deep learning process has also been widely considered in these genomics data processing system. In this research, brain disorder illness incliding Alzheimer’s disease, Schizophrenia and Parkinson’s diseaseis is analyzed owing to misdetection of disorders in neuroimaging data examined by means fo traditional methods. Moeover, deep learning approach is incorporated here for classification purpose of brain disorder with the aid of Deep Belief Networks More >

Muhammad Hamraz¹, Dost Muhammad Khan¹, Naz Gul¹, Amjad Ali¹, Zardad Khan¹, Shafiq Ahmad², Mejdal Alqahtani², Akber Abid Gardezi³, Muhammad Shafiq^4,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3663-3677, 2023, DOI:10.32604/cmc.2023.030064 - 31 October 2022

Abstract The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio (SNR). The proposed method utilizes the robust measures of location i.e., the “Median” as well as the measures of variation i.e., “Median absolute deviation (MAD) and Interquartile range (IQR)” in the SNR. By this way, two independent robust signal-to-noise ratios have been proposed. The proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio (RSNR).… More >

Halle Foss¹, Radhika Ragam¹, W. Kevin Kelly², Leonard G. Gomella¹

Canadian Journal of Urology, Vol.29, No.6, pp. 11399-11401, 2022

Abstract We report the case of a 61-year-old male with metastatic prostate cancer who presented with urinary retention secondary to subdermal penile and corpora cavernosa metastases with neuroendocrine transformation of his metastatic hormone sensitive prostate cancer. We highlight the presentation, diagnosis, and management of this rare condition. More >

Ala Saleh Alluhaidan^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5949-5962, 2022, DOI:10.32604/cmc.2022.022028 - 14 January 2022

Abstract Analysis of brain disorder in the neuroimaging of Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Computed Tomography (CT) needs to understand the functionalities of the brain and it has been performed using traditional methods. Deep learning algorithms have also been applied in genomics data processing. The brain disorder diseases of Alzheimer, Schizophrenia, and Parkinson are analyzed in this work. The main issue in the traditional algorithm is the improper detection of disorders in the neuroimaging data. This paper presents a deep learning algorithm for the classification of brain disorder using Deep Belief Network… More >

Cord J. Peters¹, Clesson E. Turner², Gregory T. Chesnut^3,4, Veda N. Giri^5,6, Leonard G. Gomella⁵, Craig D. Shriver^3,7, Albert Dobi³

Canadian Journal of Urology, Vol.28, No.3, pp. 10659-10667, 2021

Abstract Introduction: The objective of our review is to summarize the 2019 Philadelphia Prostate Cancer Genetic Consensus recommendations and discuss their implications to the US Military Health System.
Materials and methods: Literature review.
Results: Our fighting force and retired service members will significantly benefit from the Philadelphia Prostate Cancer Genetic Consensus recommendations. Moreover, the experience of the equal access US Military Health System may help advancing genetic testing for cancer at national levels.
Conclusions: Priorities recommended by the 2019 Consensus for more research on genetic predisposition to prostate cancer in racially diverse populations is a promising step. The US Military More >

MARGARET SIMONIAN^*

BIOCELL, Vol.45, No.6, pp. 1459-1463, 2021, DOI:10.32604/biocell.2021.017369 - 01 September 2021

Abstract Pediatric central nervous system tumors are the most common tumors in children, it constitute 15%–20% of all malignancies in children and are the leading cause of cancer related deaths in children. Proteogenomics is an emerging field of biological research that utilizes a combination of proteomics, genomics, and transcriptomics to aid in the discovery and identification of biomarkers for diagnosis and therapeutic purposes. Integrative proteogenomics analysis of pediatric tumors identified underlying biological processes and potential treatments as well as the functional effects of somatic mutations and copy number variation driving tumorigenesis. More >