Hepatotoxicity Due To Mushroom Poisoning: A Case Report

Background: Although the majority of mushroom ingestions are benign, some result in significant toxicity and death. Of greatest concern is the hepatotoxic amatoxin-containing mushroom, which may be fatal even small ingestions. Identification of amatoxin poisoning can prove to be difficult due to delay in onset of symptoms and difficulty with identification of mushrooms.Case Report: We present one case of mushroom ingestion in Kerman, province what according to clinical course and laboratory finding, we believe to be an amanita species, treated with multiple dose of activated charcoal, N-acetylcysteine, high-dose penicillin and liver Gol (silymarin).Conclusion: We present the successful treatment a patient who ingested hepato-toxicity induced mushrooms, further, this case is evidence of a mushroom variety responsible for toxicity never previously implicated in the southeastern Iran

Prevalence and pattern of congenital malformations in newborn in Rafsanjan, Iran (2007-08)

Background and Objective: Congenital malformations are among important causes of morbidity and mortality in newborns. This study was done to determine the prevalence and pattern of congenital malformations in newborn. Materials and Methods: This descriptive study was done on 6089 newborns in maternity center in Rafsanjan, Iran during 2007-08. The newborns were examined by pediatricians and based on clinical examination the type of obvious of either minor or major malformations were recorded. Results: The 179 cases had at least a major or minor malformations. Over all the prevalence of malformations was 2.93%. The highest prevalence of obvious malformations was seen in the musculo-skeletal (43.5%), followed by genitourinary (22.9%) and cardiovascular systems (15.08%). There was significant relation between congenital malformations, gestational age and medicine used by mothers (P<0.05). Conclusion: The highest prevalence of obvious malformations was seen in the musculo-skeletal system

A 35-day old infant with COVID-19

In late 2019, a novel coronavirus named COVID-19 led to a large outbreak in China and many other countries. A few cases of pneumonia in newborns and infants with COVID-19 infection have been reported. The neonates and infants described as the cases of COVID-19 had been asymptomatic or have had mild symptoms. The target of the current report is a 35-day-old male infant with respiratory distress and cyanosis. The chest x-ray CT images revealed manifestation of lung infection. The upper respiratory sampling was done by pharyngeal swab and the results confirmed the COVID-19 infection. Considering the positive test results and the severity of the respiratory distress, a complex medication treatment was administered. As a result, the symptoms alleviated, and the patient was discharged after complete remission on the 11th day. Although rare cases of COVID-19 infection in infants have been reported, the transmission of disease from affected persons to infants can happen. Therefore, further studies for early diagnosis and management of the COVID-19 in newborns and infants are necessary. © 2020, Author(s)

Design, construction, and evaluation of �sensor lock�: an electromechanical stance control knee joint

Background and aim: Most currently-available stance control knee ankle foot orthoses (SCKAFOs) still need full knee extension to lock the knee joint, and they are still noisy, bulky, and heavy. Therefore, the aim of this study was to design, construct, and evaluate an original electromechanical SCKAFO knee joint that could feasibly solve these problems, and thus address the problems of current stance control knee joints with regards to their structure, function, cosmesis, and cost. Method: Ten able-bodied (AB) participants and two (knee ankle foot orthosis) KAFO users were recruited to participate in the study. A custom SCKAFO with the same set of components was constructed for each participant. Lower limb kinematics were captured using a 6-camera, video-based motion analysis system. Results: For AB participants, significant differences were found between normal walking and walking with the SCKAFO for temporal-spatial parameters and between orthoses with two modes of knee joints in the healthy subjects. Walking with stance control mode produced greater walking speed and step length, greater knee flexion during swing, and less pelvic obliquity than walking with a locked knee, for both AB and KAFO users. Conclusions: The feasibility of this new knee joint with AB people was demonstrated.Implications for rehabilitation Stance control knee ankle foot orthoses (SCKAFOs) are designed to stop knee flexion in stance phase and provide free knee movement during swing phase of walking. Due to their high cost, size, excessive weight, and poor performance, few SCKAFO were optimal clinically and commercially. The feasibility of the new knee joint with able-bodied people and poliomyelitis subjects was demonstrated. © 2017 Informa UK Limited, trading as Taylor & Francis Group

Design, construction, and evaluation of �sensor lock�: an electromechanical stance control knee joint

Background and aim: Most currently-available stance control knee ankle foot orthoses (SCKAFOs) still need full knee extension to lock the knee joint, and they are still noisy, bulky, and heavy. Therefore, the aim of this study was to design, construct, and evaluate an original electromechanical SCKAFO knee joint that could feasibly solve these problems, and thus address the problems of current stance control knee joints with regards to their structure, function, cosmesis, and cost. Method: Ten able-bodied (AB) participants and two (knee ankle foot orthosis) KAFO users were recruited to participate in the study. A custom SCKAFO with the same set of components was constructed for each participant. Lower limb kinematics were captured using a 6-camera, video-based motion analysis system. Results: For AB participants, significant differences were found between normal walking and walking with the SCKAFO for temporal-spatial parameters and between orthoses with two modes of knee joints in the healthy subjects. Walking with stance control mode produced greater walking speed and step length, greater knee flexion during swing, and less pelvic obliquity than walking with a locked knee, for both AB and KAFO users. Conclusions: The feasibility of this new knee joint with AB people was demonstrated.Implications for rehabilitation Stance control knee ankle foot orthoses (SCKAFOs) are designed to stop knee flexion in stance phase and provide free knee movement during swing phase of walking. Due to their high cost, size, excessive weight, and poor performance, few SCKAFO were optimal clinically and commercially. The feasibility of the new knee joint with able-bodied people and poliomyelitis subjects was demonstrated. © 2017 Informa UK Limited, trading as Taylor & Francis Group

Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach

Purpose: Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE). Methods: Six global graph measures are extracted from static and dynamic functional connectivity matrices using fMRI data of 35 unilateral TLE subjects. Alterations in the time trend of the graph measures are quantified. The random forest (RF) method is used for the determination of feature importance and selection of dynamic graph features including mean, variance, skewness, kurtosis, and Shannon entropy. The selected features are used in the support vector machine (SVM) classifier to identify the left and right epileptogenic sides in patients with TLE. Results: Our results for the performance of SVM demonstrate that the utility of dynamic features improves the classification outcome in terms of accuracy (88.5 for dynamic features compared with 82 for static features). Selecting the best dynamic features also elevates the accuracy to 91.5. Conclusion: Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE. © 2020, Fondazione Società Italiana di Neurologia