Oocyte retrieval difficulties in women with ovarian endometriomas

Research question: What are the frequency, characteristics and consequences of technical diffiiculties encountered by physicians when carrying out oocyte retrieval in women with ovarian endometriomas? Design: We prospectively recruited women undergoing IVF and compared technical difficulties between women with (n = 56) and without (n = 227) endometriomas. Results: In exposed women, the cyst had to be transfixed in eight cases (14%, 95% CI 7 to 25%) and accidental contamination of the follicular fluid with the endometrioma content was recorded in nine women (16%, 95% CI 8 to 27%). Moreover, follicular aspiration was more frequently incomplete (OR 3.6, 95% CI 1.4 to 9.6). In contrast, the retrievals were not deemed to be more technically difficult by the physicians and the rate of oocytes retrieved per developed follicle did not differ. No pelvic infections or cyst ruptures were recorded (0%, 95% CI 0 to 5%). Conclusions: Oocyte retrieval in women with ovarian endometriomas is more problematic but the magnitude of these increased difficulties is modest

Qalb ta’ Tifel

Ġabra ta’ poeżiji u proża li tinkludi: Lil Malta ta’ Dun Karm – Fuq il-Fruntiera ta’ Dun Karm – Jum li jibqa’ jissemma ta’ Ġużè Chetcuti – Xbihet Malta ta’ Arthur V. Vassallo – Għanja ta’ Mħabba ta’ Ġużè Chetcuti – Żewġ Poeżijiet tal-kittieb Malti Antonio Calleja ta’ A. C. – Twettiqa ta’ Calleja – Lil Ħabib Għeluq Sninu ta’ Calleja – Taħt is-Salib ta’ R. M. B. – Lil Dun Karm ta’ Fran. Camilleri – Frak mill-weraq ta’ Byron ta’ A. C. – Irrid Immur Ta’ Xbiex ta’ Fran. Camilleri – Il-Cottonera fil-Ħamrun ta’ N. Biancardi – Qalb ta’ Tifel ta’ R. M. B.N/

Lill-kelb

Ġabra ta’ poeżiji u proża li tinkludi: Kemm hu kbir il-amar t’Alla! ta’ R. M. B. – Liż-żahrija ta’ V. M. B. – Il-Ġilju u l-warda ta’ P. P. M. B. – Sika trid tiżżewweġ.... ta’ R. M. B. – Qassis ġdid ta’ Dun Karm – Mhux dejjem tiġi żewġ ta’ T. Z. – Il-bandiera tagħna ta’ Mons. Gauci – Il-ħalliel tal-mejtin ta’ N. Biancardi – Lill-kelb ta’ Dun Karm.N/

Cases of albinism and leucism in amphibians in Italy : new reports

Findings of abnormally pigmented amphibian individuals provide interesting insights on intraspecific phenotypic variability as well as on variation among populations inhabiting different habitats. Amphibian coloration is determined by chromatophores (specific epidermal cells), and a variety of abnormalities related to them have been reported. In this study we reported cases of albinism and leucism in six species of Italian amphibians, including some endemic species. For some taxa, like Hydromantes sarrabusensis, H. flavus, H. supramontis and Bufo viridis, we describe the first observations of albinism and leucism

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation:A Multi-center, Multi-vendor, and Multi-disease Study

Background: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters.Purpose: Develop a generalizable CNN for lung segmentation in 1H-MRI, robust to pathology, acquisition protocol, vendor, and center.Study type: Retrospective.Population: A total of 809 1H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6–85); 42% females) and 31 healthy participants (median age (range): 34 (23–76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets.Field Strength/Sequence: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1H-MRI.Assessment: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance.Statistical Tests: Kruskal–Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland–Altman analyses assessed agreement with manually derived lung volumes. A P value of &lt;0.05 was considered statistically significant.Results: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880–0.987), Average HD of 1.63 mm (0.65–5.45) and XOR of 0.079 (0.025–0.240) on the testing set and a DSC of 0.973 (0.866–0.987), Average HD of 1.11 mm (0.47–8.13) and XOR of 0.054 (0.026–0.255) on external validation data.Data Conclusion: The 3D CNN generated accurate 1H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center.Evidence Level: 4.Technical Efficacy: Stage 1.</p