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The use of ultrasound (US) indicated cervical cerclage for short cervix in twin pregnancies is a controversial topic. All patients with coding diagnoses of short cervix (<25 mm on transvaginal US before 24 weeks' gestation) and twin pregnancies from 1/1/12 to 11/30/17 were included. [Extracted from the article]

Can VR technology be effectively used to bridge the gaps in training for surgeons? [ABSTRACT FROM AUTHOR]

This multicentric retrospective study reports long-term clinical outcomes of non-metastatic grade group 5 prostate cancers treated with external beam radiotherapy (EBRT) alone with long-term androgen deprivation therapy (ADT). Patients treated across 19 institutions were studied. The key endpoints that were evaluated were 5-year biochemical recurrence-free survival (bRFS), metastases-free survival (MFS), overall survival, together with EBRT-related acute and late toxicities. The impact of various prognostic factors on the studied endpoints was analysed using univariate and multivariate analyses. Among the 462 patients, 88% (405) had Gleason 9 disease and 31% (142) had primary Gleason pattern 5. A prostate-specific membrane antigen positron emission tomography-computed tomography scan was used for staging in 33% (153), 80% (371) were staged as T3/T4 and 30% (142) with pelvic nodal disease. The median ADT duration was 24 months; 66% received hypofractionated EBRT and 71.4% (330) received pelvic nodal irradiation. With a median follow-up of 56 months, the 5-year bRFS, MFS and overall survival were 73.1%, 77.4% and 90.5%, respectively. Primary Gleason pattern 5 was associated with worse bRFS, MFS and overall survival with hazard ratios of 0.51 (95% confidence interval 0.35 to 0.73, P < 0.001), 0.64 (95% confidence interval 0.43 to 0.96, P = 0.031) and 0.52 (95% confidence interval 0.28 to 0.97, P = 0.040), respectively, whereas pelvic nodal disease was associated with worse bRFS (hazard ratio 0.67, 95% confidence interval 0.46 to 0.98, P = 0.039) and MFS (hazard ratio 0.56, 95% confidence interval 0.37 to 0.85, P = 0.006). The acute and late radiation-related toxicities were low overall and pelvic nodal irradiation was associated with higher toxicities. Contemporary EBRT and long-term ADT led to excellent 5-year clinical outcomes and low rates of toxicity in this cohort of non-metastatic grade group 5 prostate cancers. Primary Gleason pattern 5 and pelvic node disease portends inferior clinical outcomes. • EBRT & ADT in non-metastatic GG5 cancers results in excellent 5-year outcomes. • 5-year bRFS, DMFS, OS and PCSM were 73.1%, 77.4%, 90.5% and 6.4% respectively. • Despite use of hypofractionation and pelvic nodal irradiation, toxicities were low. • Primary Gleason pattern 5 was associated with worse outcomes. • Pelvic nodal positivity was associated with worse bRFS and MFS. [ABSTRACT FROM AUTHOR]

Voltage-gated ion channels (VGICs) are pivotal in regulating electrical activity in excitable cells and are critical pharmaceutical targets for treating many diseases including cardiac arrhythmia and neuropathic pain. Despite their significance, challenges such as achieving target selectivity persist in VGIC drug development. Recent progress in deep learning, particularly diffusion models, has enabled the computational design of protein binders for any clinically relevant protein based solely on its structure. These developments coincide with a surge in experimental structural data for VGICs, providing a rich foundation for computational design efforts. This review explores the recent advancements in computational protein design using deep learning and diffusion methods, focusing on their application in designing protein binders to modulate VGIC activity. We discuss the potential use of these methods to computationally design protein binders targeting different regions of VGICs, including the pore domain, voltage-sensing domains, and interface with auxiliary subunits. We provide a comprehensive overview of the different design scenarios, discuss key structural considerations, and address the practical challenges in developing VGIC-targeting protein binders. By exploring these innovative computational methods, we aim to provide a framework for developing novel strategies that could significantly advance VGIC pharmacology and lead to the discovery of effective and safe therapeutics.