Computer-assisted sperm analysis (CASA) and clustering analysis have enabled to study sperm subpopulations in mammals, but their use in fish sperm has been limited. We have used spermatozoa from Senegalese sole (Solea senegalensis) as a model for subpopulation analysis in teleostei using two different activating solutions. Semen from six males was activated using 1100 mOsm/kg solutions: artificial seawater (ASW) or sucrose solution (SUC). Motility was acquired at 15, 30, 45, and 60 s post-activation. CASA parameters were combined into two principal components, which were used in a non-hierarchical clustering analysis, obtaining four subpopulations (CL): CL1 (slow/non-linear), CL2 (slow/linear), CL3 (fast/non-linear), and CL4 (fast/linear). We detected spermatozoa lysis, especially in ASW. Sperm motility was higher for SUC and decreased with time. The subpopulation proportions varied with time and activating treatment, showing both an increase in CL1 and CL2 and a decrease in CL3 and CL4 with time. Both CL3 and CL4 were higher in samples activated with SUC, at least in early post-activation. Proportions of CL3 and CL4 at 15 s were associated with higher quality at 60 s and with lower lysis. A second clustering analysis was conducted, classifying the males accordingly to their motility subpopulations. This analysis showed a high heterogeneity between samples. Subpopulation analysis of CASA data can be applied to Solea spermatozoa, allowing identification of potentially interesting sperm subpopulations. Future studies might benefit from these techniques to establish the relationship of these subpopulations with fish sperm quality and fertility, helping to characterize males according to their reproductive potential.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1530/REP-07-0376 | DOI Listing |
JMIR Cancer
January 2025
Division of Radiology and Biomedical Engineering, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: The application of natural language processing in medicine has increased significantly, including tasks such as information extraction and classification. Natural language processing plays a crucial role in structuring free-form radiology reports, facilitating the interpretation of textual content, and enhancing data utility through clustering techniques. Clustering allows for the identification of similar lesions and disease patterns across a broad dataset, making it useful for aggregating information and discovering new insights in medical imaging.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Medical Biology, Albert Szent-Györgyi Medical School, University of Szeged, Somogyi u. 4, Szeged, 6720, Hungary.
In our research, we performed temporal transcriptomic profiling of host cells infected with Equid alphaherpesvirus 1 (EHV-1) by utilizing direct cDNA sequencing based on nanopore MinION technology. The sequencing reads were harnessed for transcript quantification at various time points. Viral infection-induced differential gene expression was identified through the edgeR package.
View Article and Find Full Text PDFSci Rep
January 2025
Ministry of Higher Education, Mataria Technical College, Cairo, 11718, Egypt.
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt.
View Article and Find Full Text PDFBMJ Open
January 2025
Centre for Cancer Screening, Prevention and Early Diagnosis, Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Background: Worldwide, lung cancer (LC) is the second most frequent cancer and the leading cause of cancer related mortality. Low-dose CT (LDCT) screening reduced LC mortality by 20-24% in randomised trials of high-risk populations. A significant proportion of those screened have nodules detected that are found to be benign.
View Article and Find Full Text PDFMod Pathol
January 2025
Department of Pathology and Medical Biology, University Medical Center Groningen, Groningen, the Netherlands; Department of Pathology, Amsterdam University Medical Center, Amsterdam, the Netherlands. Electronic address:
Fibro-osseous tumors of the craniofacial bones are a heterogeneous group of lesions comprising cemento-osseous dysplasia (COD), cemento-ossifying fibroma (COF), juvenile trabecular ossifying fibroma (JTOF), psammomatoid ossifying fibroma (PsOF), fibrous dysplasia (FD), and low-grade osteosarcoma (LGOS) with overlapping clinicopathological features. However, their clinical behavior and treatment differ significantly, underlining the need for accurate diagnosis. Molecular diagnostic markers exist for subsets of these tumors, including GNAS mutations in FD, SATB2 fusions in PsOF, mutations involving the RAS-MAPK signaling pathway in COD, and MDM2 amplification in LGOS.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!