Afghanistan is in a military conflict lasting more than 20 years and according to recent political development, in a downhill spiral towards a failed society. This scenario faces the question of the usefulness of international medical aid, especially morphological diagnostics in crisis situations. On the basis of ten years of experience from a telemedicine project, need, feasibility and results in Afghanistan will be discussed. General and country-specific problems and the sustainability of an international partnership are discussed. In summary our experience is: (1) Telemedicine is possible and necessary even in countries with high conflict potential. It is integrated into routine care by local medical care taker, (2) Accompanying video conferences are a significant improvement in telemedical diagnostics, (3) \"High level\" consultations can bridge the gap between sophisticated western diagnostics and medicine in the partner country in selected cases and (4) Scientific work is possible on the basis of the medical data collected on site and the image material generated.
UNASSIGNED: Afghanistan befindet sich in einem mehr als 20 Jahre dauernden militärischen Konflikt und nach der jüngsten politischen Entwicklung in einer Abwärtsspirale hin zu einer zerfallenden Gesellschaft. Dieses Szenario führt zur Frage der Sinnhaftigkeit internationaler medizinischer Hilfe, besonders der morphologischen Diagnostik, in Krisensituationen. Anhand der 10-jährigen Erfahrung mit einem Telemedizinprojekt in Afghanistan werden Notwendigkeit, Umsetzbarkeit und Ergebnisse sowie die Zukunftsfähigkeit beschrieben. Allgemeine und landesspezifische Probleme einer internationalen Partnerschaft werden erörtert. Das Fazit der Autoren gemäß ihren Erfahrungen lautet: (1) Telemedizin ist selbst in Ländern mit hohem Konfliktpotenzial möglich und nötig; sie wird von den örtlichen Ärzten in die Routineversorgung integriert. (2) Begleitende Videokonferenzen sind eine deutliche Verbesserung der telemedizinischen Diagnostik. (3) „High-Level-Konsultationen“ können in ausgesuchten Fällen die Kluft zwischen hochentwickelten westlicher Diagnostik und der Medizin im Partnerland überbrücken. (4) Wissenschaftliche Arbeiten sind auf der Basis der vor Ort erhobenen medizinischen Daten und des generierten Bildmaterials möglich.

Risk evaluation of lymph node metastasis (LNM) for endoscopically resected submucosal invasive (T1) colorectal cancers (CRC) is critical for determining therapeutic strategies, but interobserver variability for histologic evaluation remains a major problem. To address this issue, we developed a machine-learning model for predicting LNM of T1 CRC without histologic assessment. A total of 783 consecutive T1 CRC cases were randomly split into 548 training and 235 validation cases. First, we trained convolutional neural networks (CNN) to extract cancer tile images from whole-slide images, then re-labeled these cancer tiles with LNM status for re-training. Statistical parameters of the tile images based on the probability of primary endpoints were assembled to predict LNM in cases with a random forest algorithm, and defined its predictive value as random forest score. We evaluated the performance of case-based prediction models for both training and validation datasets with area under the receiver operating characteristic curves (AUC). The accuracy for classifying cancer tiles was 0.980. Among cancer tiles, the accuracy for classifying tiles that were LNM-positive or LNM-negative was 0.740. The AUCs of the prediction models in the training and validation sets were 0.971 and 0.760, respectively. CNN judged the LNM probability by considering histologic tumor grade.

The evolution of the diagnosis of infectious diseases began with the observation of the morphological characteristics of organisms such as ascaris and whipworms, followed by the use of the microscope and haematoxylin and eosin stains, which allowed recognition of microscopic characteristics undetectable with the naked eye, such as the viral cytopathic changes of herpes and the presence of fungi. Patterns of acute and chronic granulomatous inflammation were also observed; these were not specific to the exact aetiology of the disease, which led to the introduction of special methenamine stains for fungi and Ziehl-Neelsen for fungi and mycobacteria. Later, the use of immunohistochemistry was introduced, which acknowledged the use of antibodies to classify microorganisms and detect cases that were either difficult to interpret or in the midst of severe inflammatory processes. Currently, the use of molecular biology has made it possible to reach diagnoses that would have been very difficult to obtain through traditional methods; these techniques show key specific characteristics and facilitate the diagnosis of various infectious pathologies. These new techniques are based on the detection of antigens and nucleic acids of microorganisms, an important advance in the diagnosis of infectious diseases.

This review summarizes the current state of methods and results achievable by cryo-electron microscopy (cryo-EM) imaging for molecular, cell, and structural biologists who wish to understand what is required and how it might help to address their research questions. It covers some of the main issues in sample preparation, microscopes and data collection, image processing, three-dimensional (3D) reconstruction, and validation and interpretation of the resulting EM density maps and atomic models.

Tissue-clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here, we introduce NuMorph, a group of analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after clearing and imaging by light-sheet microscopy. We apply NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) model with a more subtle brain overgrowth phenotype. In each case, we identify differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of whole-brain imaging approaches, and the tools are widely applicable for studying brain structure phenotypes at cellular resolution.

Tissue clearing has become a powerful technique for studying anatomy and morphology at scales ranging from entire organisms to subcellular features. With the recent proliferation of tissue-clearing methods and imaging options, it can be challenging to determine the best clearing protocol for a particular tissue and experimental question. The fact that so many clearing protocols exist suggests there is no one-size-fits-all approach to tissue clearing and imaging. Even in cases where a basic level of clearing has been achieved, there are many factors to consider, including signal retention, staining (labeling), uniformity of transparency, image acquisition and analysis. Despite reviews citing features of clearing protocols, it is often unknown a priori whether a protocol will work for a given experiment, and thus some optimization is required by the end user. In addition, the capabilities of available imaging setups often dictate how the sample needs to be prepared. After imaging, careful evaluation of volumetric image data is required for each combination of clearing protocol, tissue type, biological marker, imaging modality and biological question. Rather than providing a direct comparison of the many clearing methods and applications available, in this tutorial we address common pitfalls and provide guidelines for designing, optimizing and imaging in a successful tissue-clearing experiment with a focus on light-sheet fluorescence microscopy (LSFM).

The renal pelvis (RP) is a funnel-shaped, smooth muscle structure that facilitates normal urine transport from the kidney to the ureter by regular, propulsive contractions. Regular RP contractions rely on pacemaker activity, which originates from the most proximal region of the RP at the pelvis-kidney junction (PKJ). Due to the difficulty in accessing and preserving intact preparations of the PKJ, most investigations on RP pacemaking have focused on single-cell electrophysiology and Ca2+ imaging experiments. Although important revelations on RP pacemaking have emerged from such work, these experiments have several intrinsic limitations, including the inability to accurately determine cellular identity in mixed suspensions and the lack of in situ imaging of RP pacemaker activity. These factors have resulted in a limited understanding of the mechanisms that underlie normal rhythmic RP contractions. In this paper, a protocol is described to prepare intact segments of mouse PKJ using a vibratome sectioning technique. By combining this approach with mice expressing cell-specific reporters and genetically encoded Ca2+ indicators, investigators may be able to more accurately study the specific cell types and mechanisms responsible for peristaltic RP contractions that are vital for normal urine transport.

Whether cardiac mucosa at the esophagogastric junction is normal or metaplastic is controversial. Studies attempting to resolve this issue have been limited by the use of superficial pinch biopsies, abnormal esophagi resected typically because of cancer, or autopsy specimens in which tissue autolysis in the stomach obscures histologic findings.
We performed histologic and immunohistochemical studies of the freshly fixed esophagus and stomach resected from 7 heart-beating, deceased organ donors with no history of esophageal or gastric disease and with minimal or no histologic evidence of esophagitis and gastritis.
All subjects had cardiac mucosa, consisting of a mixture of mucous and oxyntic glands with surface foveolar epithelium, at the esophagogastric junction. All also had unique structures we termed compact mucous glands (CMG), which were histologically and immunohistochemically identical to the mucous glands of cardiac mucosa, under esophageal squamous epithelium and, hitherto undescribed, in uninflamed oxyntic mucosa throughout the gastric fundus.
These findings support cardiac mucosa as a normal anatomic structure and do not support the hypothesis that cardiac mucosa is always metaplastic. However, they do support our novel hypothesis that in the setting of reflux esophagitis, reflux-induced damage to squamous epithelium exposes underlying CMG (which are likely more resistant to acid-peptic damage than squamous epithelium), and proliferation of these CMG as part of a wound-healing process to repair the acid-peptic damage could result in their expansion to the mucosal surface to be recognized as cardiac mucosa of a columnar-lined esophagus.

Tissue clearing is one of the most powerful strategies for a comprehensive analysis of disease progression. Here, we established an integrated pipeline that combines tissue clearing, 3D imaging, and machine learning and applied to a mouse tumour model of experimental lung metastasis using human lung adenocarcinoma A549 cells. This pipeline provided the spatial information of the tumour microenvironment. We further explored the role of transforming growth factor-β (TGF-β) in cancer metastasis. TGF-β-stimulated cancer cells enhanced metastatic colonization of unstimulated-cancer cells in vivo when both cells were mixed. RNA-sequencing analysis showed that expression of the genes related to coagulation and inflammation were up-regulated in TGF-β-stimulated cancer cells. Further, whole-organ analysis revealed accumulation of platelets or macrophages with TGF-β-stimulated cancer cells, suggesting that TGF-β might promote remodelling of the tumour microenvironment, enhancing the colonization of cancer cells. Hence, our integrated pipeline for 3D profiling will help the understanding of the tumour microenvironment.

Optical tissue clearing refers to physico-chemical treatments which make thick biological samples transparent by removal of refractive index gradients and light absorbing substances. Although tissue clearing was first reported in 1914, it was not widely used in light microscopy until 21th century, because instrumentation of that time did not permit to acquire and handle images of thick (mm to cm) samples as whole. Rapid progress in optical instrumentation, computers and software over the last decades made micrograph acquisition of centimeter-thick samples feasible. This boosted tissue clearing use and development. Numerous diverse protocols have been developed. They use organic solvents or water-miscible substances, such as detergents and chaotropic agents; some protocols require application of electric field or perfusion with special devices. There is no \'best-for-all\' tissue clearing method. Depending on the case, one or another protocol is more suitable. Most of protocols require days or even weeks to complete, thus choosing an unsuitable protocol may cause an important waste of time. Several inter-dependent parameters should be taken into account to choose a tissue clearing protocol, such as: (1) required image quality (resolution, contrast, signal to noise ratio etc), (2) nature and size of the sample, (3) type of labels, (4) characteristics of the available instrumentation, (5) budget, (6) time budget, and (7) feasibility. Present review focusses on the practical aspects of various tissue clearing techniques. It is aimed to help non-experts to choose tissue clearing techniques which are optimal for their particular cases.