Positive airway pressure longer than 24 h is associated with histopathological volutrauma in severe COVID-19 pneumonia—an ESGFOR based narrative case-control review

SARS-CoV-2; Post-mortem microbiology; VolutraumaSARS-CoV-2; Microbiología post mortem; VolutraumaSARS-CoV-2; Microbiologia post mortem; VolutraumaBackground and Objective: A thorough understanding of the pathogenic mechanisms elicited by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still requires further research. Until recently, only a restricted number of autopsies have been performed, therefore limiting the accurate knowledge of the lung injury associated with SARS-CoV-2. A multidisciplinary European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group of Forensic and Post-mortem Microbiology-ESGFOR team conducted a non-systematic narrative literature review among coronavirus 2019 disease (COVID-19) pneumonia cases assessing the histopathological (HP) effects of positive airways pressure. HP lung features were recorded and compared between mechanically ventilated (>24 hours) and control (ventilation <24 hours) patients. A logistic regression analysis was performed to identify associations between mechanical ventilation (MV) and HP findings. Methods: A PubMed and MEDLINE search was conducted in order to identify studies published between March 1st 2020 and June 30th 2021. Key Content and Findings: Seventy patients (median age: 69 years) from 24 studies were analysed, among whom 38 (54.2%) underwent MV longer than 24 hours. Overall, main HP features were: diffuse alveolar damage (DAD) in 53 (75.7%), fibrosis (interstitial/intra-alveolar) in 43 (61.4%), vascular damage—including thrombosis/emboli- in 41 (58.5%), and endotheliitis in only 8 (11.4%) patients. Association of DAD, fibrosis and vascular damage was detected in 30 (42.8%) patients. Multivariate analysis, adjusted by age and gender, identified MV >24 hours as an independent variable associated with DAD (OR =5.40, 95% CI: 1.48–19.62), fibrosis (OR =3.88, 95% CI: 1.25–12.08), vascular damage (OR =5.49, 95% CI: 1.78–16.95) and association of DAD plus fibrosis plus vascular damage (OR =6.99, 95% CI: 2.04–23.97). Conclusions: We identified that patients mechanically ventilated >24 hours had a significantly higher rate of pulmonary injury on histopathology independently of age and gender. Our findings emphasize the importance of maintaining a protective ventilator strategy when subjects with COVID-19 pneumonia undergo intubation

Bilateral duplicated crura of the thoracoabdominal diaphragm

Usually, the right crus of the diaphragm attach onto the upper and the left crus onto the upper two lumbar vertebrae. In the present case, bilateral duplication of the diaphragmatic crura was noted. The right crus duplicated into right medial crus which had the usual attachment and right lateral crus that attached to the fifth lumbar vertebra. The left crus also duplicated into left medial crus which had the usual attachment and left lateral crus that attached to the fifth lumbar vertebra. A retrocrural space separated the two duplications. A thorough knowledge of crural variations is necessary for the surgeons during surgical interventions

Content aware multi-focus image fusion for high-magnification blood film microscopy

Automated digital high-magnification optical microscopy is key to accelerating biology research and improving pathology clinical pathways. High magnification objectives with large numerical apertures are usually preferred to resolve the fine structural details of biological samples, but they have a very limited depth-of-field. Depending on the thickness of the sample, analysis of specimens typically requires the acquisition of multiple images at different focal planes for each field-of-view, followed by the fusion of these planes into an extended depth-of-field image. This translates into low scanning speeds, increased storage space, and processing time not suitable for high-throughput clinical use. We introduce a novel content-aware multi-focus image fusion approach based on deep learning which extends the depth-of-field of high magnification objectives effectively. We demonstrate the method with three examples, showing that highly accurate, detailed, extended depth of field images can be obtained at a lower axial sampling rate, using 2-fold fewer focal planes than normally required

Whole-Sample Mapping of Cancerous and Benign Tissue Properties

Structural and mechanical differences between cancerous and healthy tissue give rise to variations in macroscopic properties such as visual appearance and elastic modulus that show promise as signatures for early cancer detection. Atomic force microscopy (AFM) has been used to measure significant differences in stiffness between cancerous and healthy cells owing to its high force sensitivity and spatial resolution, however due to absorption and scattering of light, it is often challenging to accurately locate where AFM measurements have been made on a bulk tissue sample. In this paper we describe an image registration method that localizes AFM elastic stiffness measurements with high-resolution images of haematoxylin and eosin (H\&E)-stained tissue to within 1.5 microns. Color RGB images are segmented into three structure types (lumen, cells and stroma) by a neural network classifier trained on ground-truth pixel data obtained through k-means clustering in HSV color space. Using the localized stiffness maps and corresponding structural information, a whole-sample stiffness map is generated with a region matching and interpolation algorithm that associates similar structures with measured stiffness values. We present results showing significant differences in stiffness between healthy and cancerous liver tissue and discuss potential applications of this technique.Comment: Accepted at MICCAI201

IL-6 Trans-Signaling in the Brain Influences the Metabolic Phenotype of the 3xTg-AD Mouse Model of Alzheimer's Disease

Altres ajuts: Fundació La Marató de TV3 (20142210)Alzheimer's disease (AD) is a neurodegenerative disorder that causes the most prevalent dementia in the elderly people. Obesity and insulin resistance, which may cause major health problems per se, are risk factors for AD, and cytokines such as interleukin-6 (IL-6) have a role in these conditions. IL-6 can signal either through a membrane receptor or by trans-signaling, which can be inhibited by the soluble form of the co-receptor gp130 (sgp130). We have addressed the possibility that blocking IL-6 trans-signaling in the brain could have an effect in the triple transgenic 3xTg-AD mouse model of AD and/or in obesity progression, by crossing 3xTg-AD mice with GFAP-sgp130Fc mice. To serve as control groups, GFAP-sgp130Fc mice were also crossed with C57BL/6JOlaHsd mice. Seventeen-month-old mice were fed a control diet (18% kcal from fat) and a high-fat diet (HFD; 58.4% kcal from fat). In our experimental conditions, the 3xTg-AD model showed a mild amyloid phenotype, which nevertheless altered the control of body weight and related endocrine and metabolic factors, suggestive of a hypermetabolic state. The inhibition of IL-6 trans-signaling modulated some of these traits in both 3xTg-AD and control mice, particularly during HFD, and in a sex-dependent manner. These experiments provide evidence of IL-6 trans-signaling playing a role in the CNS of a mouse model of AD

Development and validation of a multivariate predictive model for rheumatoid arthritis mortality using a machine learning approach

We developed and independently validated a rheumatoid arthritis (RA) mortality prediction model using the machine learning method Random Survival Forests (RSF). Two independent cohorts from Madrid (Spain) were used: the Hospital Cl&iacute;nico San Carlos RA Cohort (HCSC-RAC; training; 1,461 patients), and the Hospital Universitario de La Princesa Early Arthritis Register Longitudinal study (PEARL; validation; 280 patients). Demographic and clinical-related variables collected during the first two years after disease diagnosis were used. 148 and 21 patients from HCSC-RAC and PEARL died during a median follow-up time of 4.3 and 5.0&nbsp;years, respectively. Age at diagnosis, median erythrocyte sedimentation rate, and number of hospital admissions showed the higher predictive capacity. Prediction errors in the training and validation cohorts were 0.187 and 0.233, respectively. A survival tree identified five mortality risk groups using the predicted ensemble mortality. After 1 and 7 years of follow-up, time-dependent specificity and sensitivity in the validation cohort were 0.79&ndash;0.80 and 0.43&ndash;0.48, respectively, using the cut-off value dividing the two lower risk categories. Calibration curves showed overestimation of the mortality risk in the validation cohort. In conclusion, we were able to develop a clinical prediction model for RA mortality using RSF, providing evidence for further work on external validation

Experience on how to implement a preanalytical and POCT unit in Madrid’s IFEMA field hospital during this unprecedented COVID-19 emergency

To fight the virus SARS-CoV-2 spread to Europe from China and to give support to the collapsed public health system, the Spanish Health Authorities developed a field hospital located in the facilities of Madrid exhibition centre (IFEMA) to admit and treat patients diagnosed with SARS-CoV-2 infectious disease (COVID-19). The Department of Laboratory Medicine of La Paz University Hospital in Madrid (LMD-HULP) was designated to provide laboratory services. Due to the emergency, the IFEMA field hospital had to be prepared for patient admission in less than 1 week and the laboratory professionals had to collaborate in a multidisciplinary group to assure that resources were available to start on time. The LMD-HULP participated together with the managers in the design of the tests portfolio and the integration of the healthcare information systems (IS) (hospital IS, laboratory IS and POCT management system). Laboratorians developed a strategy to quickly train clinicians and nurses on test requests, sample collection procedures and management/handling of the POCT blood gas analyser both by written materials and training videos. The IFEMA´s preanalytical unit managed 3782 requests, and more than 11,000 samples from March 27th to April 30th. Furthermore, 1151 samples were measured by blood gas analysers. In conclusion, laboratory professionals must be resilient and have to respond timely in emergencies as this pandemic. The lab’s personnel selection, design and monitoring indicators to maintain and further improve the quality and value of laboratory services is crucial to support medical decision making and provide better patient care