Three-dimensional (3D) reconstruction and examination of tissue at microscopic resolution have significant potential to enhance the study of both normal and disease processes, particularly those involving structural changes or those in which the spatial relationship of disease features is important. Although other methods exist for studying tissue in 3D, using conventional histopathological features has significant advantages because it allows for conventional histopathological staining and interpretation techniques. Until now, its use has not been routine in research because of the technical difficulty in constructing 3D tissue models. We describe a novel system for 3D histological reconstruction, integrating whole-slide imaging (virtual slides), image serving, registration, and visualization into one user-friendly package. It produces high-resolution 3D reconstructions with minimal user interaction and can be used in a histopathological laboratory without input from computing specialists. It uses a novel method for slice-to-slice image registration using automatic registration algorithms custom designed for both virtual slides and histopathological images. This system has been applied to >300 separate 3D volumes from eight different tissue types, using a total of 5500 virtual slides comprising 1.45 TB of primary image data. Qualitative and quantitative metrics for the accuracy of 3D reconstruction are provided, with measured registration accuracy approaching 120 μm for a 1-cm piece of tissue. Both 3D tissue volumes and generated 3D models are presented for four demonstrator cases.

Complex cytokine networks play an important role in a wide range of reproductive and pregnancy related processes. Here, we review the current knowledge concerning the impact of cytokines on uterine physiology and pathophysiology. Cytokines influence a range of uterine functions during the menstrual cycle, implantation, pregnancy and labour. The synergistic interactions between individual cytokines are intricate and dynamic, and modulated by pregnancy hormones. It is not surprising therefore, that perturbations to cytokine signalling are associated with adverse pregnancy outcomes, such as miscarriage, pre‐eclampsia, preterm labour and foetal brain injury. Further insight into the complexity of cytokine networks will be required to develop novel therapeutic strategies for the treatment of cytokine imbalances in pregnancy.

Variations in systemic inflammatory response biomarker levels have been associated with adverse clinical outcome in various malignancies. This study determined the prognostic significance of preoperative neutrophil:lymphocyte (NLR), platelet:lymphocyte (PLR) and monocyte:lymphocyte (MLR) ratios in endometrial cancer. Clinicopathological and 5-year follow-up data were obtained for a retrospective series of surgically treated endometrial cancer patients (n=605). Prognostic significance was determined for overall (OS) and cancer-specific survival (CSS) using Cox proportional hazards models and Kaplan-Meier analysis. Receiver-operator characteristic and log-rank functions were used to optimise cut-offs. NLR, PLR and MLR associations with clinicopathological variables were determined using non-parametric tests. Applying cut-offs of ⩾2.4 (NLR), ⩾240 (PLR) and ⩾0.19 (MLR), NLR and PLR (but not MLR) had independent prognostic significance. Combining NLR and PLR scores stratified patients into low (NLR-low and PLR-low), intermediate (NLR-high or PLR-high) and high risk (NLR-high and PLR-high) groups: multivariable hazard ratio (HR) 2.51; P<0.001 (OS); HR 2.26; P<0.01 (CSS) for high vs low risk patients. Increased NLR and PLR were most strongly associated with advanced stage (P<0.001), whereas increased MLR was strongly associated with older age (P<0.001). Both NLR and PLR are independent prognostic indicators for endometrial cancer, which can be combined to provide additional patient stratification.