ORGANO PHOSPHORUS COMPOUND POISONING, COMPLICATED ACUTE RENAL FAILURE AND DELAYED POST HYPOXIC ENCEPHALOPATHY - A CASE REPORT

Organophosphorus compound (OPC) poisoning is one of the most common poisons in rural India. We present a 27 year old female patient who came to us in altered sensorium and froathing from mouth with an alleged history of OPC intake about 2 hours back. The patient was intubated, connected to a mechanical ventilator and atropinized. On day 3 of admission patient had elevated renal parameters and was diagnosed as Acute Renal Failure due to acute tubular necrosis probably poison induced. On day 4 of admission she suffered an acute cardiac arrest and was resuscitated; following this she gradually improved and after 3weeks of intensive management her sensorium deteriorated. MRI Brain showed Diffuse Cerebral White Matter Leukodystrophy due to DEMYELINATION (Hypoxia induced). KEYWORDS: Organophosphorus compound poisoning; Acute renal failure; Demyelination; Leukoencephalopathy

ORGANO PHOSPHORUS COMPOUND POISONING, COMPLICATED ACUTE RENAL FAILURE AND DELAYED POST HYPOXIC ENCEPHALOPATHY - A CASE REPORT

Organophosphorus compound (OPC) poisoning is one of the most common poisons in rural India. We present a 27 year old female patient who came to us in altered sensorium and froathing from mouth with an alleged history of OPC intake about 2 hours back. The patient was intubated, connected to a mechanical ventilator and atropinized. On day 3 of admission patient had elevated renal parameters and was diagnosed as Acute Renal Failure due to acute tubular necrosis probably poison induced. On day 4 of admission she suffered an acute cardiac arrest and was resuscitated; following this she gradually improved and after 3weeks of intensive management her sensorium deteriorated. MRI Brain showed Diffuse Cerebral White Matter Leukodystrophy due to DEMYELINATION (Hypoxia induced). KEYWORDS: Organophosphorus compound poisoning; Acute renal failure; Demyelination; Leukoencephalopathy

Computational prediction of neural progenitor cell fates

Understanding how stem and progenitor cells choose between alternative cell fates is a major challenge in developmental biology. Efforts to tackle this problem have been hampered by the scarcity of markers that can be used to predict cell division outcomes. Here we present a computational method, based on algorithmic information theory, to analyze dynamic features of living cells over time. Using this method, we asked whether rat retinal progenitor cells (RPCs) display characteristic phenotypes before undergoing mitosis that could foretell their fate. We predicted whether RPCs will undergo a self-renewing or terminal division with 99% accuracy, or whether they will produce two photoreceptors or another combination of offspring with 87% accuracy. Our implementation can segment, track and generate predictions for 40 cells simultaneously on a standard computer at 5 min per frame. This method could be used to isolate cell populations with specific developmental potential, enabling previously impossible investigations.The computational aspects of this work were supported by the Center for Subsurface Sensing and Imaging Systems (NSF Grant EEC-9986821), by the Rensselaer Polytechnic Institute and by the University of Wisconsin-Milwaukee. This work was supported by grants from the Canadian Institutes of Health Research and the Foundation Fighting Blindness – Canada (to M.C). M.C. is a CIHR New Investigator and a W.K. Stell Scholar of the Foundation Fighting Blindness – Canada

Information diffusion in the U.S. real estate investment trust market

This study examines the information diffusion process in the U.S. Real Estate Investment Trust (REIT) market with a focus on the impacts of changing market environments, information supply, and information demand on the lead-lag effect. The results suggest that a significant lead-lag relationship exists between the lagged returns of big REITs and the current returns of small REITs. This relationship has slightly decreased along with policy and environment changes that occurred in the U.S. REIT market during the study period from 1986 to 2012, while still remaining significant in the most recent REIT market. The process of information diffusion is becoming unstable in recent years and the reverse lead-lag effect from small REITs to big REITs is observed especially when REIT market liquidity and return volatility are high. The lead-lag effect among REITs is driven largely by slow adjustment to negative information, which is magnified by a lack of information supply, especially as demand for such information increases. Finally, information flow from REITs with more media coverage to those with less media coverage becomes even more sluggish than the information flow from big REITs to small REITs

NetMets: software for quantifying and visualizing errors in biological network segmentation

One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization

Seasonal variations in the diagnosis of childhood cancer in the United States

Seasonal trends in month of diagnosis have been reported for childhood acute lymphoblastic leukaemia (ALL) and non-Hodgkin's lymphoma (NHL). This seasonal variation has been suggested to represent an underlying viral aetiology for these malignancies. Some studies have shown the highest frequency of diagnoses in the summer months, although this has been inconsistent. Data from the Children's Cancer Group and the Pediatric Oncology Group were analysed for seasonal incidence patterns. A total of 20 949 incident cancer cases diagnosed in the USA from 1 January 1989 through 31 December 1991 were available for analyses. Diagnosis-specific malignancies available for evaluation included ALL, acute myeloid leukaemia (AML), Hodgkin's disease, NHL, rhabdomyosarcoma, neuroblastoma, retinoblastoma, osteosarcoma, Wilms' tumour, retinoblastoma, Ewings' sarcoma, central nervous system (CNS) tumours and hepatoblastoma. Overall, there was no statistically significant seasonal variation in the month of diagnosis for all childhood cancers combined. For diagnosis-specific malignancies, there was a statistically significant seasonal variation for ALL (P = 0.01; peak in summer), rhabdomyosarcoma (P = 0.03; spring/summer) and hepatoblastoma (P = 0.01; summer); there was no seasonal variation in the diagnosis of NHL. When cases were restricted to latitudes greater than 40° (‘north’), seasonal patterns were apparent only for ALL and hepatoblastoma. Notably, 33% of hepatoblastoma cases were diagnosed in the summer months. In contrast, for latitudes less than 40° (‘south’), only CNS tumours demonstrated a seasonal pattern (P = 0.002; winter). Although these data provide modest support for a summer peak in the diagnosis of childhood ALL, any underlying biological mechanisms that account for these seasonal patterns are likely complex and in need of more definitive studies. © 1999 Cancer Research Campaig

Under- treatment and under diagnosis of hypertension: a serious problem in the United Arab Emirates

BACKGROUND: Hypertension, notably untreated or uncontrolled, is a major risk factor for cardiovascular diseases (CVD) morbidity and mortality. In countries in transition, little is known about the epidemiology of hypertension, and its biochemical correlates. This study was carried out in Al Ain, United Arab Emirates, to characterize self-reported (SR) normotensives and hypertensives in terms of actual hypertension status, demographic variables, CVD risk factors, treatment, and sequalae. METHODS: A sample, stratified by SR hypertensive status, of 349 SR hypertensives (Mean age ± SD; 50.8 ± 9.2 yrs; Male: 226) and 640 SR normotensives (42.9 ± 9.3 yrs, Male: 444) among nationals and expatriates was used. Hypertensives and normotensive subjects were recruited from various outpatient clinics and government organizations in Al-Ain city, United Arab Emirates (UAE) respectively. Anthropometric and demographic variables were measured by conventional methods. RESULTS: Both under-diagnosis of hypertension (33%) and under-treatment (76%) were common. Characteristics of undiagnosed hypertensives were intermediate between normotensives and SR hypertensives. Under-diagnosis of hypertension was more common among foreigners than among nationals. Risk factors for CVD were more prevalent among SR hypertensives. Obesity, lack of exercise and smoking were found as major risk factors for CVD among hypertensives in this population. CONCLUSION: Hypertension, even severe, is commonly under-diagnosed and under-treated in the UAE. Preventive strategies, better diagnosis and proper treatment compliance should be emphasized to reduce incidence of CVD in this population

Imported malaria among African immigrants: is there still a relationship between developed countries and their ex-colonies?

© 2009 Millet et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Patterns of care and survival for adolescents and young adults with acute leukaemia – a population-based study

We report a population-based study of patterns of care and survival for people with acute leukaemia diagnosed at age 15–29 years during 1984–94 in regions of England and Wales covered by specialist leukaemia registries. There were 879 patients: 417 with acute lymphoblastic leukaemia (ALL) and 462 with acute myeloid leukaemia (AML). For ALL, actuarial survival rates were 43% at 5 years after diagnosis and 37% at 10 years. Survival improved significantly between 1984–88 and 1989–94 for those aged 15–19 at diagnosis. Patients entered in national clinical trials and those not entered had similar survival rates. Survival rates were similar at teaching and non-teaching hospitals and at hospitals treating different numbers of study patients per year. For AML, survival rates were 42% at 5 years after diagnosis and 39% at 10 years. Survival improved significantly between 1984–88 and 1989–94. Patients entered in the Medical Research Council AML10 trial had a higher survival rate than those who were in the earlier AML9 trial. Survival did not vary with category of hospital. We conclude that survival has improved for adolescents and young adults with acute leukaemia but that there is at present no evidence that centralized treatment results in a survival benefit for patients in this age group. © 1999 Cancer Research Campaig