Estimated cumulative radiation dose from PET/CT in children with malignancies: a 5-year retrospective review

The increasing use of serial PET/CT scans in the management of pediatric malignancies raises the important consideration of radiation exposure in children. To estimate the cumulative radiation dose from PET/CT studies to children with malignancy and to compare with the data in literature. Two hundred forty-eight clinical PET/CT studies performed on 78 patients (50 boys/28 girls, 1.3 to 18 years old from December 2002 to October 2007) were retrospectively reviewed under IRB approval. The whole-body effective dose (ED) estimates for each child were obtained by estimating the effective dose from each PET/CT exam performed using the ImPACT Patient Dosimetry Calculator for CT and OLINDA for PET. The average number of PET/CT studies was 3.2 per child (range: 1 to 14 studies). The average ED of an individual CT study was 20.3 mSv (range: 2.7 to 54.2), of PET study was 4.6 mSv (range: 0.4 to 7.7) and of PET/CT study was 24.8 mSv (range: 6.2 to 60.7). The average cumulative radiation dose per patient from CT studies was 64.4 mSv (range: 2.7 to 326), from PET studies was 14.5 mSv (range: 2.8 to 73) and from PET/CT studies was 78.9 mSv (range: 6.2 to 399). The radiation exposure from serial PET/CT studies performed in pediatric malignancies was considerable; however, lower doses can be used for both PET and CT studies. The ALARA principle must be applied without sacrificing diagnostic information

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD

A swarm intelligence approach in undersampling majority class

Over the years, machine learning has been facing the issue of imbalance dataset. It occurs when the number of instances in one class significantly outnumbers the instances in the other class. This study investigates a new approach for balancing the dataset using a swarm intelligence technique, Stochastic Diffusion Search (SDS), to undersample the majority class on a direct marketing dataset. The outcome of the novel application of this swarm intelligence algorithm demonstrates promising results which encourage the possibility of undersampling a majority class by removing redundant data whist protecting the useful data in the dataset. This paper details the behaviour of the proposed algorithm in dealing with this problem and investigates the results which are contrasted against other techniques

Association between recurrence of acute kidney injury and mortality in intensive care unit patients with severe sepsis

Background: Acute kidney injury (AKI) occurs in more than half critically ill patients admitted in intensive care units (ICU) and increases the mortality risk. The main cause of AKI in ICU is sepsis. AKI severity and other related variables such as recurrence of AKI episodes may influence mortality risk. While AKI recurrence after hospital discharge has been recently related to an increased risk of mortality, little is known about the rate and consequences of AKI recurrence during the ICU stay. Our hypothesis is that AKI recurrence during ICU stay in septic patients may be associated to a higher mortality risk. Methods: We prospectively enrolled all (405) adult patients admitted to the ICU of our hospital with the diagnosis of severe sepsis/septic shock for a period of 30 months. Serum creatinine was measured daily. ?In-ICU AKI recurrence? was defined as a new spontaneous rise of ?0.3 mg/dl within 48 h from the lowest serum creatinine after the previous AKI episode. Results: Excluding 5 patients who suffered the AKI after the initial admission to ICU, 331 patients out of the 400 patients (82.8%) developed at least one AKI while they remained in the ICU. Among them, 79 (19.8%) developed ?2 AKI episodes. Excluding 69 patients without AKI, in-hospital (adjusted HR = 2.48, 95% CI 1.47?4.19), 90-day (adjusted HR = 2.54, 95% CI 1.55?4.16) and end of follow-up (adjusted HR = 1.97, 95% CI 1.36?2.84) mortality rates were significantly higher in patients with recurrent AKI, independently of sex, age, mechanical ventilation necessity, APACHE score, baseline estimated glomerular filtration rate, complete recovery and KDIGO stage. Conclusions: AKI recurred in about 20% of ICU patients after a first episode of sepsis-related AKI. This recurrence increases the mortality rate independently of sepsis severity and of the KDIGO stage of the initial AKI episode. ICU physicians must be aware of the risks related to AKI recurrence while multiple episodes of AKI should be highlighted in electronic medical records and included in the variables of clinical risk scores

Performance assessment of the database downscaled ocean waves (DOW) on Santa Catarina coast, South Brazil

ABSTRACT: This work presents a validation of wave parameters from the new sixty years Downscaled Ocean Waves (DOW) reanalysis database. This study compares quantiles of the Gumbel distribution of Hs (significant wave height) and Tp (peak period) from simulated data with an 11 months' time series obtained from a buoy moored seaward on the Santa Catarina coast. Analysis by means of Gumbel distribution quantiles allows more weight to be given to the highest values of the time series, which are especially important in design projects. The statistical parameters used to verify the fit between the measured and the modeled data included: RMSE, BIAS, Scatter Index and Pearson Correlation Coefficient. Mean direction (9m) validation was conducted qualitatively. The database showed good fit of the mean conditions, especially Hs which was well Reproduced by the wave model. Underestimation of Tp, related mainly to the low spatial and temporal resolution of wind data used to generate waves, highlights this general modeling problem. Based on calculated statistical parameters, DOW data were considered comparable to the values obtained by measurements; however, such data must be cautiously used for extreme events analysis and in areas of bimodal sea conditions, where major deficiencies in the database were observed.The authors are also thankful to the Brazilian government through the Ministério do Meio Ambiente (MMA) and the Agência Brasileira de Cooperação (ABC) for the financial support of this research (within the project Transference of Methodologies and Tools to Support the Brazilian Coastal Management)

Deep neural architectures for prediction in healthcare

This paper presents a novel class of systems assisting diagnosis and personalised assessment of diseases in healthcare. The targeted systems are end-to-end deep neural architectures that are designed (trained and tested) and subsequently used as whole systems, accepting raw input data and producing the desired outputs. Such architectures are state-of-the-art in image analysis and computer vision, speech recognition and language processing. Their application in healthcare for prediction and diagnosis purposes can produce high accuracy results and can be combined with medical knowledge to improve effectiveness, adaptation and transparency of decision making. The paper focuses on neurodegenerative diseases, particularly Parkinson’s, as the development model, by creating a new database and using it for training, evaluating and validating the proposed systems. Experimental results are presented which illustrate the ability of the systems to detect and predict Parkinson’s based on medical imaging information

Early prediction of cardiac resynchronization therapy response by non-invasive electrocardiogram markers

[EN] Cardiac resynchronization therapy (CRT) is an effective treatment for those patients with severe heart failure. Regrettably, there are about one third of CRT "non-responders", i.e. patients who have undergone this form of device therapy but do not respond to it, which adversely affects the utility and cost-effectiveness of CRT. In this paper, we assess the ability of a novel surface ECG marker to predict CRT response. We performed a retrospective exploratory study of the ECG previous to CRT implantation in 43 consecutive patients with ischemic (17) or non-ischemic (26) cardiomyopathy. We extracted the QRST complexes (consisting of the QRS complex, the S-T segment, and the T wave) and obtained a measure of their energy by means of spectral analysis. This ECG marker showed statistically significant lower values for non-responder patients and, joint with the duration of QRS complexes (the current gold-standard to predict CRT response), the following performances: 86% accuracy, 88% sensitivity, and 80% specificity. In this manner, the proposed ECG marker may help clinicians to predict positive response to CRT in a non-invasive way, in order to minimize unsuccessful procedures.This work was supported by MINECO under grants MTM2013-43540-P and MTM2016-76647-P.Ortigosa, N.; Pérez-Roselló, V.; Donoso, V.; Osca Asensi, J.; Martínez-Dolz, L.; Fernández Rosell, C.; Galbis Verdu, A. (2018). Early prediction of cardiac resynchronization therapy response by non-invasive electrocardiogram markers. Medical & Biological Engineering & Computing. 56(4):611-621. https://doi.org/10.1007/s11517-017-1711-1S611621564Boggiatto P, Fernández C, Galbis A (2009) A group representation related to the stockwell transform. 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Influenza A Virus Induces an Immediate Cytotoxic Activity in All Major Subsets of Peripheral Blood Mononuclear Cells

A replication defective influenza A vaccine virus (delNS1 virus) was developed. Its attenuation is due to potent stimulation of the innate immune system by the virus. Since the innate immune system can also target cancer cells, we reasoned that delNS1 virus induced immune-stimulation should also lead to the induction of innate cytotoxic effects towards cancer cells.Peripheral blood mononuclear cells (PBMCs), isolated CD56+, CD3+, CD14+ and CD19+ subsets and different combinations of the above subsets were stimulated by delNS1, wild type (wt) virus or heat inactivated virus and co-cultured with tumor cell lines in the presence or absence of antibodies against the interferon system. Stimulation of PBMCs by the delNS1 virus effectively induced cytotoxicity against different cancer cell lines. Surprisingly, virus induced cytotoxicity was exerted by all major subtypes of PBMCs including CD56+, CD3+, CD14+ and CD19+ cells. Virus induced cytotoxicity in CD3+, CD14+ and CD19+ cells was dependent on virus replication, whereas virus induced cytotoxicity in CD56+ cells was only dependent on the binding of the virus. Virus induced cytotoxicity of isolated cell cultures of CD14+, CD19+ or CD56+ cells could be partially blocked by antibodies against type I and type II (IFN) interferon. In contrast, virus induced cytotoxicity in the complete PBMC preparation could not be inhibited by blocking type I or type II IFN, indicating a redundant system of activation in whole blood.Our data suggest that apart from their well known specialized functions all main subsets of peripheral blood cells also initially exert a cytotoxic effect upon virus stimulation. This closely links the innate immune system to the adaptive immune response and renders delNS1 virus a potential therapeutic tool for viro-immunotherapy of cancer

Phosphoregulation of Ire1 RNase splicing activity.

Abstract Ire1 is activated in response to accumulation of misfolded proteins within the endoplasmic reticulum as part of the unfolded protein response (UPR). It is a unique enzyme, possessing both kinase and RNase activity that is required for specific splicing of Xbp1 mRNA leading to UPR activation. How phosphorylation impacts on the Ire1 splicing activity is unclear. In this study, we isolate distinct phosphorylated species of Ire1 and assess their effects on RNase splicing both in vitro and in vivo. We find that phosphorylation within the kinase activation loop significantly increases RNase splicing in vitro. Correspondingly, mutants of Ire1 that cannot be phosphorylated on the activation loop show decreased specific Xbp1 and promiscuous RNase splicing activity relative to wild-type Ire1 in cells. These data couple the kinase phosphorylation reaction to the activation state of the RNase, suggesting that phosphorylation of the activation loop is an important step in Ire1-mediated UPR activation.</jats:p