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- de Vries, FAT, et al.
(författare)
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Mouse Sycp1 functions in synaptonemal complex assembly, meiotic recombination, and XY body formation
- 2005
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Ingår i: Genes & development. - : Cold Spring Harbor Laboratory. - 0890-9369 .- 1549-5477. ; 19:11, s. 1376-1389
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Tidskriftsartikel (refereegranskat)abstract
- In meiotic prophase, synaptonemal complexes (SCs) closely appose homologous chromosomes (homologs) along their length. SCs are assembled from two axial elements (AEs), one along each homolog, which are connected by numerous transverse filaments (TFs). We disrupted the mouse gene encoding TF protein Sycp1 to analyze the role of TFs in meiotic chromosome behavior and recombination. Sycp1-/- mice are infertile, but otherwise healthy. Sycp1-/- spermatocytes form normal AEs, which align homologously, but do not synapse. Most Sycp1-/- spermatocytes arrest in pachynema, whereas a small proportion reaches diplonema, or, exceptionally, metaphase I. In leptotene Sycp1-/- spermatocytes, γH2AX (indicative of DNA damage, including double-strand breaks) appears normal. In pachynema, Sycp1-/- spermatocytes display a number of discrete γH2AX domains along each chromosome, whereas γH2AX disappears from autosomes in wild-type spermatocytes. RAD51/DMC1, RPA, and MSH4 foci (which mark early and intermediate steps in pairing/recombination) appear in similar numbers as in wild type, but do not all disappear, and MLH1 and MLH3 foci (which mark late steps in crossing over) are not formed. Crossovers were rare in metaphase I of Sycp1-/- mice. We propose that SYCP1 has a coordinating role, and ensures formation of crossovers. Unexpectedly, Sycp1-/- spermatocytes did not form XY bodies.
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- Sturm, Bart, et al.
(författare)
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Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm
- 2022
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Ingår i: Diagnostics. - : MDPI. - 2075-4418. ; 12:2
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Tidskriftsartikel (refereegranskat)abstract
- An increasing number of pathology laboratories are now fully digitised, using whole slide imaging (WSI) for routine diagnostics. WSI paves the road to use artificial intelligence (AI) that will play an increasing role in computer-aided diagnosis (CAD). In melanocytic skin lesions, the presence of a dermal mitosis may be an important clue for an intermediate or a malignant lesion and may indicate worse prognosis. In this study a mitosis algorithm primarily developed for breast carcinoma is applied to melanocytic skin lesions. This study aimed to assess whether the algorithm could be used in diagnosing melanocytic lesions, and to study the added value in diagnosing melanocytic lesions in a practical setting. WSIs of a set of hematoxylin and eosin (H&E) stained slides of 99 melanocytic lesions (35 nevi, 4 intermediate melanocytic lesions, and 60 malignant melanomas, including 10 nevoid melanomas), for which a consensus diagnosis was reached by three academic pathologists, were subjected to a mitosis algorithm based on AI. Two academic and six general pathologists specialized in dermatopathology examined the WSI cases two times, first without mitosis annotations and after a washout period of at least 2 months with mitosis annotations based on the algorithm. The algorithm indicated true mitosis in lesional cells, i.e., melanocytes, and non-lesional cells, i.e., mainly keratinocytes and inflammatory cells. A high number of false positive mitosis was indicated as well, comprising melanin pigment, sebaceous glands nuclei, and spindle cell nuclei such as stromal cells and neuroid differentiated melanocytes. All but one pathologist reported more often a dermal mitosis with the mitosis algorithm, which on a regular basis, was incorrectly attributed to mitoses from mainly inflammatory cells. The overall concordance of the pathologists with the consensus diagnosis for all cases excluding nevoid melanoma (n = 89) appeared to be comparable with and without the use of AI (89% vs. 90%). However, the concordance increased by using AI in nevoid melanoma cases (n = 10) (75% vs. 68%). This study showed that in general cases, pathologists perform similarly with the aid of a mitosis algorithm developed primarily for breast cancer. In nevoid melanoma cases, pathologists perform better with the algorithm. From this study, it can be learned that pathologists need to be aware of potential pitfalls using CAD on H&E slides, e.g., misinterpreting dermal mitoses in non-melanotic cells.
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