Frequent expression loss of Inter-alpha-trypsin inhibitor heavy chain (ITIH) genes in multiple human solid tumors: A systematic expression analysis

<p>Abstract</p> <p>Background</p> <p>The inter-alpha-trypsin inhibitors (ITI) are a family of plasma protease inhibitors, assembled from a light chain – bikunin, encoded by <it>AMBP </it>– and five homologous heavy chains (encoded by <it>ITIH1</it>, <it>ITIH2</it>, <it>ITIH3</it>, <it>ITIH4</it>, and <it>ITIH5</it>), contributing to extracellular matrix stability by covalent linkage to hyaluronan. So far, ITIH molecules have been shown to play a particularly important role in inflammation and carcinogenesis.</p> <p>Methods</p> <p>We systematically investigated differential gene expression of the <it>ITIH </it>gene family, as well as <it>AMBP </it>and the interacting partner <it>TNFAIP6 </it>in 13 different human tumor entities (of breast, endometrium, ovary, cervix, stomach, small intestine, colon, rectum, lung, thyroid, prostate, kidney, and pancreas) using cDNA dot blot analysis (Cancer Profiling Array, CPA), semiquantitative RT-PCR and immunohistochemistry.</p> <p>Results</p> <p>We found that <it>ITIH </it>genes are clearly downregulated in multiple human solid tumors, including breast, colon and lung cancer. Thus, <it>ITIH </it>genes may represent a family of putative tumor suppressor genes that should be analyzed in greater detail in the future. For an initial detailed analysis we chose <it>ITIH2 </it>expression in human breast cancer. Loss of <it>ITIH2 </it>expression in 70% of cases (n = 50, CPA) could be confirmed by real-time PCR in an additional set of breast cancers (n = 36). Next we studied ITIH2 expression on the protein level by analyzing a comprehensive tissue micro array including 185 invasive breast cancer specimens. We found a strong correlation (p < 0.001) between ITIH2 expression and estrogen receptor (ER) expression indicating that ER may be involved in the regulation of this ECM molecule.</p> <p>Conclusion</p> <p>Altogether, this is the first systematic analysis on the differential expression of <it>ITIH </it>genes in human cancer, showing frequent downregulation that may be associated with initiation and/or progression of these malignancies.</p

New prototype neuronavigation system based on preoperative imaging and intraoperative freehand ultrasound: system description and validation

Purpose: The aim of this report is to present IBIS (Interactive Brain Imaging System) NeuroNav, a new prototype neuronavigation system that has been developed in our research laboratory over the past decade that uses tracked intraoperative ultrasound to address surgical navigation issues related to brain shift. The unique feature of the system is its ability, when needed, to improve the initial patient-to-preoperative image alignment based on the intraoperative ultrasound data. Parts of IBIS Neuronav source code are now publicly available on-line. Methods: Four aspects of the system are characterized in this paper: the ultrasound probe calibration, the temporal calibration, the patient-to-image registration and the MRI-ultrasound registration. In order to characterize its real clinical precision and accuracy, the system was tested in a series of adult brain tumor cases. Results: Three metrics were computed to evaluate the precision and accuracy of the ultrasound calibration. 1) Reproducibility: 1.77 mm and 1.65 mm for the bottom corners of the ultrasound image, 2) point reconstruction precision 0.62-0.90 mm: and 3) point reconstruction accuracy: 0.49-0.74 mm. The temporal calibration error was estimated to be 0.82 ms. The mean fiducial registration error (FRE) of the homologous-point-based patient-to-MRI registration for our clinical data is 4.9 ± 1.1 mm. After the skin landmark-based registration, the mean misalignment between the ultrasound and MR images in the tumor region is 6.1 ± 3.4 mm. Conclusions: The components and functionality of a new prototype system are described and its precision and accuracy evaluated. It was found to have an accuracy similar to other comparable systems in the literature

Validation of a hybrid Doppler ultrasound vessel-based registration algorithm for neurosurgery

PURPOSE: We describe and validate a novel hybrid non-linear vessel registration algorithm for intraoperative updating of preoperative magnetic resonance (MR) images using Doppler ultrasound (US) images acquired on the dura for the correction of brain-shift and registration inaccuracies. We also introduce an US vessel appearance simulator that generates vessel images similar in appearance to that acquired with US from MR angiography data. METHODS: Our registration uses the minimum amount of preprocessing to extract vessels from the raw volumetric images. This prevents the removal of important registration information and minimizes the introduction of artifacts that may affect robustness, while reducing the amount of extraneous information in the image to be processed, thus improving the convergence speed of the algorithm. We then completed 3 rounds of validation for our vessel registration method for robustness and accuracy using (i)a large number of synthetic trials generated with our US vessel simulator, (ii)US images acquired from a real physical phantom made from polyvinyl alcohol cryogel (PVAc), and (iii)real clinical data gathered intraoperatively from 3 patients. RESULTS: Resulting target registration errors (TRE) of less than 2.5mm are achieved in more than 90% of the synthetic trials when the initial TREs are less than 20mm. TREs of less than 2mm were achieved when the technique was applied to the physical phantom, and TREs of less than 3mm were achieved on clinical data. CONCLUSIONS: These test trials show that the proposed algorithm is not only accurate but also highly robust to noise and missing vessel segments when working with US images acquired in a wide range of real-world conditions

Association of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19

Introduction: Acute kidney injury (AKI) has been identified as one of the most common and significant problems in hospitalized patients with COVID-19. However, studies examining the relationship between COVID-19 and AKI in low- and low-middle income countries (LLMIC) are lacking. Given that AKI is known to carry a higher mortality rate in these countries, it is important to understand differences in this population. Methods: This prospective, observational study examines the AKI incidence and characteristics of 32,210 patients with COVID-19 from 49 countries across all income levels who were admitted to an intensive care unit during their hospital stay. Results: Among patients with COVID-19 admitted to the intensive care unit, AKI incidence was highest in patients in LLMIC, followed by patients in upper-middle income countries (UMIC) and high-income countries (HIC) (53%, 38%, and 30%, respectively), whereas dialysis rates were lowest among patients with AKI from LLMIC and highest among those from HIC (27% vs. 45%). Patients with AKI in LLMIC had the largest proportion of community-acquired AKI (CA-AKI) and highest rate of in-hospital death (79% vs. 54% in HIC and 66% in UMIC). The association between AKI, being from LLMIC and in-hospital death persisted even after adjusting for disease severity. Conclusions: AKI is a particularly devastating complication of COVID-19 among patients from poorer nations where the gaps in accessibility and quality of healthcare delivery have a major impact on patient outcomes

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use