Epidemiologic features, seasonal variations and false positive rate of acute appendicitis in Shahr-e-Rey, Tehran

Introduction: Appendicitis is the most common acute surgical condition of the abdomen. Age, sex and seasonal variations have been observed in many studies. To describe and find the possible differences in the epidemiology of acute appendicitis in Shahr-e-Rey, we carried out a retrospective study of all patients with acute appendicitis admitted to Shohadaay-e Haftom-e Tir hospital as it is the only hospital in this restricted part of Tehran. Methods: Using hospital discharge abstract of patients who were admitted with the diagnosis of acute appendicitis from summer 1996 to spring 2004, we studied the demographic features, particularly age and sex, date of admission and final diagnosis of these patients. Results: During the observation period, 1093 cases were admitted with the diagnosis of acute appendicitis. Of these, 74.4 were males and 6.1 were not actually an acute appendicitis. The age-specific incidence of acute appendicitis has different patterns in male and female. The incidence was highest in males aged 20-29 years whereas in females the highest incidence was observed in 10-19 years age group. A significant seasonal effect was also observed, with the rate of acute appendicitis higher in the summer months (p < 0.006). The rate of false positive diagnosis was highest in the patients aged 0-9 years (p < 0.0001). Of those correctly diagnosed, 85.5 had uncomplicated acute appendicitis; 8.3 had perforation; and others (6.2) had acute appendicitis complicated with other situations. Conclusion: Appendicitis is more common in males, in those aged 20-29 years, and during the summer months. The age-specific incidence and sex ratio of acute appendicitis give the impression that epidemiologic features of acute appendicitis are different with worldwide data. However, the seasonal variation and false positive rate of acute appendicitis are in a good agreement with other studies. © 2006 Surgical Associates Ltd

Short-range order and precipitation in Fe-rich Fe-Cr alloys: Atomistic off-lattice Monte Carlo simulations

Short-range order (SRO) in Fe-rich Fe-Cr alloys is investigated by means of atomistic off-lattice Monte Carlo simulations in the semi-grand canonical ensemble using classical interatomic potentials. The SRO parameter defined by Cowley [Phys. Rev. B 77, 669 (1950)] is used to quantify the degree of ordering. In agreement with experiments a strong ordering tendency in the Cr distribution at low Cr concentrations (~< 5%) is observed, as manifested in negative values of the SRO parameters. For intermediate Cr concentrations (5% ~< c_Cr ~< 15%) the SRO parameter for the alpha-phase goes through a minimum, but at the solubility limit the alpha-phase still displays a rather strong SRO. In thermodynamic equilibrium for concentrations within the two-phase region the SRO parameter measured over the entire sample therefore comprises the contributions from both the alpha and alpha-prime phases. If both of these contributions are taken into account, it is possible to quantitatively reproduce the experimental results and interpret their physical implications. It is thereby shown that the inversion of the SRO observed experimentally is due to the formation of stable (supercritical) alpha-prime precipitates. It is not related to the loss of SRO in the alpha-phase or to the presence of unstable (subcritical) Cr precipitates in the alpha-phase.Comment: 9 pages, 8 figure

Statistical modeling of ground motion relations for seismic hazard analysis

We introduce a new approach for ground motion relations (GMR) in the probabilistic seismic hazard analysis (PSHA), being influenced by the extreme value theory of mathematical statistics. Therein, we understand a GMR as a random function. We derive mathematically the principle of area-equivalence; wherein two alternative GMRs have an equivalent influence on the hazard if these GMRs have equivalent area functions. This includes local biases. An interpretation of the difference between these GMRs (an actual and a modeled one) as a random component leads to a general overestimation of residual variance and hazard. Beside this, we discuss important aspects of classical approaches and discover discrepancies with the state of the art of stochastics and statistics (model selection and significance, test of distribution assumptions, extreme value statistics). We criticize especially the assumption of logarithmic normally distributed residuals of maxima like the peak ground acceleration (PGA). The natural distribution of its individual random component (equivalent to exp(epsilon_0) of Joyner and Boore 1993) is the generalized extreme value. We show by numerical researches that the actual distribution can be hidden and a wrong distribution assumption can influence the PSHA negatively as the negligence of area equivalence does. Finally, we suggest an estimation concept for GMRs of PSHA with a regression-free variance estimation of the individual random component. We demonstrate the advantages of event-specific GMRs by analyzing data sets from the PEER strong motion database and estimate event-specific GMRs. Therein, the majority of the best models base on an anisotropic point source approach. The residual variance of logarithmized PGA is significantly smaller than in previous models. We validate the estimations for the event with the largest sample by empirical area functions. etc

Fall Classification by Machine Learning Using Mobile Phones

Fall prevention is a critical component of health care; falls are a common source of injury in the elderly and are associated with significant levels of mortality and morbidity. Automatically detecting falls can allow rapid response to potential emergencies; in addition, knowing the cause or manner of a fall can be beneficial for prevention studies or a more tailored emergency response. The purpose of this study is to demonstrate techniques to not only reliably detect a fall but also to automatically classify the type. We asked 15 subjects to simulate four different types of falls–left and right lateral, forward trips, and backward slips–while wearing mobile phones and previously validated, dedicated accelerometers. Nine subjects also wore the devices for ten days, to provide data for comparison with the simulated falls. We applied five machine learning classifiers to a large time-series feature set to detect falls. Support vector machines and regularized logistic regression were able to identify a fall with 98% accuracy and classify the type of fall with 99% accuracy. This work demonstrates how current machine learning approaches can simplify data collection for prevention in fall-related research as well as improve rapid response to potential injuries due to falls

Adenosine A1 receptor: Functional receptor-receptor interactions in the brain

Over the past decade, many lines of investigation have shown that receptor-mediated signaling exhibits greater diversity than previously appreciated. Signal diversity arises from numerous factors, which include the formation of receptor dimers and interplay between different receptors. Using adenosine A1 receptors as a paradigm of G protein-coupled receptors, this review focuses on how receptor-receptor interactions may contribute to regulation of the synaptic transmission within the central nervous system. The interactions with metabotropic dopamine, adenosine A2A, A3, neuropeptide Y, and purinergic P2Y1 receptors will be described in the first part. The second part deals with interactions between A1Rs and ionotropic receptors, especially GABAA, NMDA, and P2X receptors as well as ATP-sensitive K+ channels. Finally, the review will discuss new approaches towards treating neurological disorders

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging

Novel insights in the role of Bcl-2 homolog Nr-13 (vNr-13) encoded by herpesvirus of turkeys in the virus replication cycle, mitochondrial networks and apoptosis inhibition

Bcl-2 (B cell lymphoma-2)-related gene Nr-13 plays a major role in the regulation of cell death in developing avian B-cells. With over 65% sequence similarity to the chicken Nr-13, herpesvirus of turkeys (HVT)-encoded HVT079 and HVT096 gene product &lt;jats:italic&gt;vNr-13&lt;/jats:italic&gt; is the first known alphaherpesvirus-encoded Bcl-2 homolog. HVT-infected cells were reported to be relatively more resistant to serum starvation, suggested that &lt;jats:italic&gt;vNr-13&lt;/jats:italic&gt; could be involved in protecting the cells. Here we describe CRISPR/Cas9-based editing of exon 1 of HVT079 and HVT096 genes from the HVT genome to generate the mutant HVT-&lt;jats:italic&gt;ΔvNr-13&lt;/jats:italic&gt; to gain insights into its functional roles. Overall, both wild type HVT and HVT&lt;jats:italic&gt;-ΔvNr-13&lt;/jats:italic&gt; showed similar growth kinetics; however, at early time points, HVT&lt;jats:italic&gt;-ΔvNr-13&lt;/jats:italic&gt; showed lower growth of 1.3- to 1.7-fold of cell-associated virus and 3- to 6.2- fold of cell-free virus. In the transfected cells, HVT &lt;jats:italic&gt;vNr-13&lt;/jats:italic&gt; mainly showed diffuse cytoplasmic distribution with faint nuclear staining. Further, &lt;jats:italic&gt;vNr-13&lt;/jats:italic&gt; localized to the mitochondria and endoplasmic reticulum (ER), and demonstrated to disrupt mitochondrial network morphology in the transfected cells. In the wildtype HVT-infected cells, &lt;jats:italic&gt;vNr-13&lt;/jats:italic&gt; expression appeared to be directly involved in the disruption of the mitochondrial network, as the mitochondrial network morphology was substantially restored in the HVT&lt;jats:italic&gt;-ΔvNr-13-&lt;/jats:italic&gt;infected cells. IncuCyte® S3 real time apoptosis monitoring demonstrated that &lt;jats:italic&gt;vNr-13&lt;/jats:italic&gt; unequivocally involved in the apoptosis inhibition, and it is associated with increase of PFU, especially at serum-free conditions of later stages of viral replication cycle. Furthermore, HVT blocks apoptosis in infected cells, but activates apoptosis in the non-infected bystander cells.&lt;/jats:p&gt; &lt;jats:p&gt;&lt;jats:bold&gt;Importance&lt;/jats:bold&gt;&lt;/jats:p&gt; Bcl-2 (B cell lymphoma-2)-related gene Nr-13 plays a major role in the regulation of cell death in developing avian B-cells. With over 65% sequence similarity to the chicken Nr-13, herpesvirus of turkeys (HVT)-encoded HVT079 and HVT096 gene product vNr-13 is the first known alphaherpesvirus-encoded Bcl-2 homolog. HVT-infected cells were reported to be relatively more resistant to serum starvation, suggested that vNr-13 could be involved in protecting the cells. Here we describe CRISPR/Cas9-based editing of exon 1 of HVT079 and HVT096 genes from the HVT genome to generate the mutant HVT-ΔvNr-13 to gain insights into its functional roles. Overall, both wild type HVT and HVT-ΔvNr-13 showed similar growth kinetics; however, at early time points, HVT-ΔvNr-13 showed lower growth of 1.3- to 1.7-fold of cell-associated virus and 3- to 6.2- fold of cell-free virus. In the transfected cells, HVT vNr-13 mainly showed diffuse cytoplasmic distribution with faint nuclear staining. Further, vNr-13 localized to the mitochondria and endoplasmic reticulum (ER), and demonstrated to disrupt mitochondrial network morphology in the transfected cells. In the wildtype HVT-infected cells, vNr-13 expression appeared to be directly involved in the disruption of the mitochondrial network, as the mitochondrial network morphology was substantially restored in the HVT-ΔvNr-13-infected cells. IncuCyte® S3 real time apoptosis monitoring demonstrated that vNr-13 unequivocally involved in the apoptosis inhibition, and it is associated with increase of PFU, especially at serum-free conditions of later stages of viral replication cycle. Furthermore, HVT blocks apoptosis in infected cells, but activates apoptosis in the non-infected bystander cells