Volumetric Reconstruction of a Human Retinal Pigment Epithelial Cell Reveals Specialized Membranes and Polarized Distribution of Organelles.

Purpose: Despite the centrality of the retinal pigment epithelium (RPE) in vision and retinopathy our picture of RPE morphology is incomplete. With a volumetric reconstruction of human RPE ultrastructure, we aim to characterize major membranous features including apical processes and their interactions with photoreceptor outer segments, basolateral infoldings, and the distribution of intracellular organelles. Methods: A parafoveal retinal sample was acquired from a 21-year-old male organ donor. With serial block-face scanning electron microscopy, a tissue volume from the inner-outer segment junction to basal RPE was captured. Surface membranes and complete internal ultrastructure of an individual RPE cell were achieved with a combination of manual and automated segmentation methods. Results: In one RPE cell, apical processes constitute 69% of the total cell surface area, through a dense network of over 3000 terminal branches. Single processes contact several photoreceptors. Basolateral infoldings facing the choriocapillaris resemble elongated filopodia and comprise 22% of the cell surface area. Membranous tubules and sacs of endoplasmic reticulum represent 20% of the cell body volume. A dense basal layer of mitochondria extends apically to partly overlap electron-dense pigment granules. Pores in the nuclear envelope form a distinct pattern of rows aligned with chromatin. Conclusions: Specialized membranes at the apical and basal side of the RPE cell body involved in intercellular uptake and transport represent over 90% of the total surface area. Together with the polarized distribution of organelles within the cell body, these findings are relevant for retinal clinical imaging, therapeutic approaches, and disease pathomechanisms.

Deep Learning-Based Segmentation of Cryo-Electron Tomograms.

Cryo-electron tomography (cryo-ET) allows researchers to image cells in their native, hydrated state at the highest resolution currently possible. The technique has several limitations, however, that make analyzing the data it generates time-intensive and difficult. Hand segmenting a single tomogram can take from hours to days, but a microscope can easily generate 50 or more tomograms a day. Current deep learning segmentation programs for cryo-ET do exist, but are limited to segmenting one structure at a time. Here, multi-slice U-Net convolutional neural networks are trained and applied to automatically segment multiple structures simultaneously within cryo-tomograms. With proper preprocessing, these networks can be robustly inferred to many tomograms without the need for training individual networks for each tomogram. This workflow dramatically improves the speed with which cryo-electron tomograms can be analyzed by cutting segmentation time down to under 30 min in most cases. Further, segmentations can be used to improve the accuracy of filament tracing within a cellular context and to rapidly extract coordinates for subtomogram averaging.

Application of Deep Learning Convolutional Neural Networks for Internal Tablet Defect Detection: High Accuracy, Throughput, and Adaptability.

Tablet defects encountered during the manufacturing of oral formulations can result in quality concerns, timeline delays, and elevated financial costs. Internal tablet cracking is not typically measured in routine inspections but can lead to batch failures such as tablet fracturing. X-ray computed tomography (XRCT) has become well-established to analyze internal cracks of oral tablets. However, XRCT normally generates very large quantities of image data (thousands of 2D slices per data set) which require a trained professional to analyze. A user-guided manual analysis is laborious, time-consuming, and subjective, which may result in a poor statistical representation and inconsistent results. In this study, we have developed an analysis program that incorporates deep learning convolutional neural networks to fully automate the XRCT image analysis of oral tablets for internal crack detection. The computer program achieves robust quantification of internal tablet cracks with an average accuracy of 94%. In addition, the deep learning tool is fully automated and achieves a throughput capable of analyzing hundreds of tablets. We have also explored the adaptability of the deep learning analysis program toward different products (e.g., different types of bottles and tablets). Finally, the deep learning tool is effectively implemented into the industrial pharmaceutical workflow.

British Menopause Society consensus statement on the management of estrogen deficiency symptoms, arthralgia and menopause diagnosis in women treated for early breast cancer.

This guidance document by the British Menopause Society provides an overview of the management of women experiencing estrogen deficiency symptoms and arthralgia following a breast cancer diagnosis. It is now recommended that breast cancer patients are referred to health care professionals with an expertise in menopause for the management of such symptoms, which in turn often involves liaison with patients' breast cancer teams. However, as many women initially present to primary health care professionals for advice, this statement is aimed to support the latter in such consultations by providing information about symptom aetiology, current management strategies and controversies and identifying useful practice points.

Anatomic dorsal and volar radioulnar ligament reconstruction with Mersilene augmentation for distal radioulnar joint instability.

Instability of the distal ulna is a fairly common problem after acute distal radius fracture (DRF), distal radius malunion, triangular fibrocartilage complex injury, and a host of other types of trauma. We present a new anatomic technique to stabilize the distal ulna with a tendon graft augmented with Mersilene tape, which has been used primarily to treat unidirectional (dorsal or volar) instability, but could be used for global instability as well. Of the 12 patients who underwent this procedure, 9 had stability fully restored and the remaining 3 had only mild instability after surgery. The procedure is an effective treatment for distal radioulnar joint instability and we believe that this surgical technique will be a valuable adjunct to the existing described procedures for hand surgeons. We present a retrospective single-surgeon case series with outcome measures.

Ligament reconstruction tendon interposition with mersilene augmentation.

Many surgical procedures have been described for the treatment of thumb basilar joint osteoarthritis. Augmentation of the standard ligament reconstruction tendon interposition procedure with the use of a Mersilene suture tape suspension-plasty, to recreate the stability provided by the anterior oblique ligament and increase pinch strength, will be described. Satisfaction with this procedure was evaluated through surveys completed by patients. In addition, independent physical assessments were performed to demonstrate stability, range of motion, and strength.

Structural clusters of evolutionary trace residues are statistically significant and common in proteins.

Given the massive increase in the number of new sequences and structures, a critical problem is how to integrate these raw data into meaningful biological information. One approach, the Evolutionary Trace, or ET, uses phylogenetic information to rank the residues in a protein sequence by evolutionary importance and then maps those ranked at the top onto a representative structure. If these residues form structural clusters, they can identify functional surfaces such as those involved in molecular recognition. Now that a number of examples have shown that ET can identify binding sites and focus mutational studies on their relevant functional determinants, we ask whether the method can be improved so as to be applicable on a large scale. To address this question, we introduce a new treatment of gaps resulting from insertions and deletions, which streamlines the selection of sequences used as input. We also introduce objective statistics to assess the significance of the total number of clusters and of the size of the largest one. As a result of the novel treatment of gaps, ET performance improves measurably. We find evolutionarily privileged clusters that are significant at the 5% level in 45 out of 46 (98%) proteins drawn from a variety of structural classes and biological functions. In 37 of the 38 proteins for which a protein-ligand complex is available, the dominant cluster contacts the ligand. We conclude that spatial clustering of evolutionarily important residues is a general phenomenon, consistent with the cooperative nature of residues that determine structure and function. In practice, these results suggest that ET can be applied on a large scale to identify functional sites in a significant fraction of the structures in the protein databank (PDB). This approach to combining raw sequences and structure to obtain detailed insights into the molecular basis of function should prove valuable in the context of the Structural Genomics Initiative.