Hasil untuk "Pathology"

K. Bera, K. Schalper, D. Rimm et al.

M. Humbert, C. Guignabert, S. Bonnet et al.

Clinical and translational research has played a major role in advancing our understanding of pulmonary hypertension (PH), including pulmonary arterial hypertension and other forms of PH with severe vascular remodelling (e.g. chronic thromboembolic PH and pulmonary veno-occlusive disease). However, PH remains an incurable condition with a high mortality rate, underscoring the need for a better transfer of novel scientific knowledge into healthcare interventions. Herein, we review recent findings in pathology (with the questioning of the strict morphological categorisation of various forms of PH into pre- or post-capillary involvement of pulmonary vessels) and cellular mechanisms contributing to the onset and progression of pulmonary vascular remodelling associated with various forms of PH. We also discuss ways to improve management and to support and optimise drug development in this research field. State of the art and research perspectives in the cellular and molecular basis and pathology of pulmonary vascular remodelling associated with various forms of pulmonary hypertension http://ow.ly/cjwp30mgzmH

Christina Ising, C. Venegas, Shuangshuang Zhang et al.

B. Abramoff, F. Caldera

K. Palikaras, E. Lionaki, Nektarios Tavernarakis

Neeraj Kumar, Ruchika Verma, Sanuj Sharma et al.

B. Dugger, D. Dickson

J. Epstein, L. Egevad, M. Amin et al.

K. Stark, S. Massberg

Thrombosis is the most feared complication of cardiovascular diseases and a main cause of death worldwide, making it a major health-care challenge. Platelets and the coagulation cascade are effectively targeted by antithrombotic approaches, which carry an inherent risk of bleeding. Moreover, antithrombotics cannot completely prevent thrombotic events, implicating a therapeutic gap due to a third, not yet adequately addressed mechanism, namely inflammation. In this Review, we discuss how the synergy between inflammation and thrombosis drives thrombotic diseases. We focus on the huge potential of anti-inflammatory strategies to target cardiovascular pathologies. Findings in the past decade have uncovered a sophisticated connection between innate immunity, platelet activation and coagulation, termed immunothrombosis. Immunothrombosis is an important host defence mechanism to limit systemic spreading of pathogens through the bloodstream. However, the aberrant activation of immunothrombosis in cardiovascular diseases causes myocardial infarction, stroke and venous thromboembolism. The clinical relevance of aberrant immunothrombosis, referred to as thromboinflammation, is supported by the increased risk of cardiovascular events in patients with inflammatory diseases but also during infections, including in COVID-19. Clinical trials in the past 4 years have confirmed the anti-ischaemic effects of anti-inflammatory strategies, backing the concept of a prothrombotic function of inflammation. Targeting inflammation to prevent thrombosis leaves haemostasis mainly unaffected, circumventing the risk of bleeding associated with current approaches. Considering the growing number of anti-inflammatory therapies, it is crucial to appreciate their potential in covering therapeutic gaps in cardiovascular diseases. In this Review, Stark and Massberg discuss how the interplay between innate immunity, platelet activation and coagulation, known as immunothrombosis, functions as a host defence mechanism to limit pathogen spreading, yet its aberrant activation, termed thromboinflammation, results in thrombotic complications, highlighting the therapeutic potential of anti-inflammatory strategies in cardiovascular pathologies. Inflammation and thrombosis are tightly connected processes that contribute to the containment of pathogen spreading in a host defence effector mechanism termed immunothrombosis. The dysregulated and excessive activation of immunothrombosis results in thromboinflammation, causing tissue ischaemia by microvascular and macrovascular thrombosis. The main factor in immunothrombosis and thromboinflammation is a vicious circle of platelet and innate immune cell activation, unleashing the complement system and coagulation cascade. Inflammatory conditions such as infection, chronic autoimmune diseases and clonal haematopoiesis of indeterminate potential are associated with an increased risk of thrombotic events, providing clinical evidence for the partnership between inflammation and thrombosis. Pulmonary immunothrombosis is a prominent feature of severe COVID-19, aggravating respiratory failure and correlating with a systemic prothrombotic phenotype. The inflammatory component of thrombosis is a therapeutic gap and a promising target for the prevention and treatment of cardiovascular diseases such as myocardial infarction, stroke and venous thromboembolism.

H. Jackson, Jana R Fischer, V. R. Zanotelli et al.

E. Stice

L. Racusen, K. Solez, R. Colvin et al.

BACKGROUND Standardization of renal allograft biopsy interpretation is necessary to guide therapy and to establish an objective end point for clinical trials. This manuscript describes a classification, Banff 97, developed by investigators using the Banff Schema and the Collaborative Clinical Trials in Transplantation (CCTT) modification for diagnosis of renal allograft pathology. METHODS Banff 97 grew from an international consensus discussion begun at Banff and continued via the Internet. This schema developed from (a) analysis of data using the Banff classification, (b) publication of and experience with the CCTT modification, (c) international conferences, and (d) data from recent studies on impact of vasculitis on transplant outcome. RESULTS Semiquantitative lesion scoring continues to focus on tubulitis and arteritis but includes a minimum threshold for interstitial inflammation. Banff 97 defines "types" of acute/active rejection. Type I is tubulointerstitial rejection without arteritis. Type II is vascular rejection with intimal arteritis, and type III is severe rejection with transmural arterial changes. Biopsies with only mild inflammation are graded as "borderline/suspicious for rejection." Chronic/sclerosing allograft changes are graded based on severity of tubular atrophy and interstitial fibrosis. Antibody-mediated rejection, hyperacute or accelerated acute in presentation, is also categorized, as are other significant allograft findings. CONCLUSIONS The Banff 97 working classification refines earlier schemas and represents input from two classifications most widely used in clinical rejection trials and in clinical practice worldwide. Major changes include the following: rejection with vasculitis is separated from tubulointerstitial rejection; severe rejection requires transmural changes in arteries; "borderline" rejection can only be interpreted in a clinical context; antibody-mediated rejection is further defined, and lesion scoring focuses on most severely involved structures. Criteria for specimen adequacy have also been modified. Banff 97 represents a significant refinement of allograft assessment, developed via international consensus discussions.

D. Schenk, R. Barbour, W. Dunn et al.

S. B. Whitaker

H. Braak, I. Alafuzoff, T. Arzberger et al.

Assessment of Alzheimer’s disease (AD)-related neurofibrillary pathology requires a procedure that permits a sufficient differentiation between initial, intermediate, and late stages. The gradual deposition of a hyperphosphorylated tau protein within select neuronal types in specific nuclei or areas is central to the disease process. The staging of AD-related neurofibrillary pathology originally described in 1991 was performed on unconventionally thick sections (100 μm) using a modern silver technique and reflected the progress of the disease process based chiefly on the topographic expansion of the lesions. To better meet the demands of routine laboratories this procedure is revised here by adapting tissue selection and processing to the needs of paraffin-embedded sections (5–15 μm) and by introducing a robust immunoreaction (AT8) for hyperphosphorylated tau protein that can be processed on an automated basis. It is anticipated that this revised methodological protocol will enable a more uniform application of the staging procedure.

I. Grundke‐Iqbal, K. Iqbal, Y. Tung et al.

A. Zimprich, A. Zimprich, S. Biskup et al.

V. Baxi, R. Edwards, M. Montalto et al.

Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision medicine have recently paved the way for the development of digital pathology-based approaches for quantitative pathologic assessments, namely whole slide imaging and artificial intelligence (AI)–based solutions, allowing us to explore and extract information beyond human visual perception. Within the field of immuno-oncology, the application of such methodologies in drug development and translational research have created invaluable opportunities for deciphering complex pathophysiology and the discovery of novel biomarkers and drug targets. With an increasing number of treatment options available for any given disease, practitioners face the growing challenge of selecting the most appropriate treatment for each patient. The ever-increasing utilization of AI-based approaches substantially expands our understanding of the tumor microenvironment, with digital approaches to patient stratification and selection for diagnostic assays supporting the identification of the optimal treatment regimen based on patient profiles. This review provides an overview of the opportunities and limitations around implementing AI-based methods in biomarker discovery and patient selection and discusses how advances in digital pathology and AI should be considered in the current landscape of translational medicine, touching on challenges this technology may face if adopted in clinical settings. The traditional role of pathologists in delivering accurate diagnoses or assessing biomarkers for companion diagnostics may be enhanced in precision, reproducibility, and scale by AI-powered analysis tools.

M. Cui, David Zhang

Data processing and learning has become a spearhead for the advancement of medicine, with pathology and laboratory medicine has no exception. The incorporation of scientific research through clinical informatics, including genomics, proteomics, bioinformatics, and biostatistics, into clinical practice unlocks innovative approaches for patient care. Computational pathology is burgeoning subspecialty in pathology that promises a better-integrated solution to whole-slide images, multi-omics data, and clinical informatics. However, computational pathology faces several challenges, including the ability to integrate raw data from different sources, limitation of hardware processing capacity, and a lack of specific training programs, as well as issues on ethics and larger societal acceptable practices that are still solidifying. The establishment of the entire industry of computational pathology requires far-reaching changes of the three essential elements connecting patients and doctors: the local laboratory, the scan center, and the central cloud hub/portal for data processing and retrieval. Computational pathology, unlocked through information integration and advanced digital communication networks, has the potential to improve clinical workflow efficiency, diagnostic quality, and ultimately create personalized diagnosis and treatment plans for patients. This review describes clinical perspectives and discusses the statistical methods, clinical applications, potential obstacles, and future directions of computational pathology. Data processing and learning has become a spearhead for the advancement of medicine. Computational pathology is burgeoning subspecialty that promises a better-integrated solution to whole-slide images, multi-omics data and clinical informatics as innovative approach for patient care. This review describes clinical perspectives and discusses the statistical methods, clinical applications, potential obstacles, and future directions of computational pathology.

Saba Shafi, Anil V. Parwani

Digital pathology (DP) is being increasingly employed in cancer diagnostics, providing additional tools for faster, higher-quality, accurate diagnosis. The practice of diagnostic pathology has gone through a staggering transformation wherein new tools such as digital imaging, advanced artificial intelligence (AI) algorithms, and computer-aided diagnostic techniques are being used for assisting, augmenting and empowering the computational histopathology and AI-enabled diagnostics. This is paving the way for advancement in precision medicine in cancer. Automated whole slide imaging (WSI) scanners are now rendering diagnostic quality, high-resolution images of entire glass slides and combining these images with innovative digital pathology tools is making it possible to integrate imaging into all aspects of pathology reporting including anatomical, clinical, and molecular pathology. The recent approvals of WSI scanners for primary diagnosis by the FDA as well as the approval of prostate AI algorithm has paved the way for starting to incorporate this exciting technology for use in primary diagnosis. AI tools can provide a unique platform for innovations and advances in anatomical and clinical pathology workflows. In this review, we describe the milestones and landmark trials in the use of AI in clinical pathology with emphasis on future directions.