Solve the False-Positive Problem of the Mimic System Based on the Best Mimic Component Set

At present,there is a problem of false positives caused by the too vast mimic scope in mimic transformation technology.Previous studies have focused on the“compensation”method to deal with this problem,which is expensive and cannot fundamentally solve it.This paper provides new insights into coping with the situation.Firstly,this study summarizes the false-positive problem in the mimic transformation,analyzes its possible harm and the root causes.Secondly,three properties about the mimic scope are proposed.Based on the three properties and security quantification technology,the best mimic component set theory is put forward to solve the false-positive problem.There are two algorithms,the supplemental method and the subtraction method.The best mimic component set obtained by these two algorithms can fundamentally solve the mimic system’s false-positive problem but reduce the cost of mimic transformation.Thus make up for the lack of previous researches.

Postoperative reactive lymphadenitis: A potential cause of false-positive FDG PET/CT

A wide variety of surgical related uptake has been reported on F18-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography(FDG PET/CT) scan, most of which can be differentiated from neoplastic process based on the pattern of FDG uptake and/or anatomic appearance on the integrated CT in image interpretation. A more potential problem we may be aware is postoperative reactive lymphadenitis, which may mimic regional nodal metastases on FDG PET/CT. This review presents five case examples demonstrating that postoperative reactive lymphadenitis could be a false-positive source for regional nodal metastasis on FDG PET/CT. Surgical oncologists and radiologists should be aware of reactive lymphadenitis in interpreting postoperative restaging FDG PET/CT scan when FDG avid lymphadenopathy is only seen in the lymphatic draining location from surgical site.

An Efficient False-Positive Reduction System for Cerebral Microbleeds Detection

Cerebral Microbleeds(CMBs)are microhemorrhages caused by certain abnormalities of brain vessels.CMBs can be found in people with Traumatic Brain Injury(TBI),Alzheimer’s disease,and in old individuals having a brain injury.Current research reveals that CMBs can be highly dangerous for individuals having dementia and stroke.The CMBs seriously impact individuals’life which makes it crucial to recognize the CMBs in its initial phase to stop deterioration and to assist individuals to have a normal life.The existing work report good results but often ignores false-positive’s perspective for this research area.In this paper,an efficient approach is presented to detect CMBs from the Susceptibility Weighted Images(SWI).The proposed framework consists of four main phases(i)making clusters of brain Magnetic Resonance Imaging(MRI)using k-mean classifier(ii)reduce false positives for better classification results(iii)discriminative feature extraction specific to CMBs(iv)classification using a five layers convolutional neural network(CNN).The proposed method is evaluated on a public dataset available for 20 subjects.The proposed system shows an accuracy of 98.9%and a 1.1%false-positive rate value.The results show the superiority of the proposed work as compared to existing states of the art methods.

Hepatitis C virus infection and biological falsepositive syphilis test:a single-center experience

BACKGROUND:Rapid plasma regain positive and/or treponema pallidum hemagglutination negative [RPR(+)/TPHA(-)] results were designated as biologic false-positive (BFP).There are limited data about BFP reactions against syphilis in patients with hepatitis C virus (HCV) infection.This study aimed to determine the prevalence of BFP reactions for syphilis in patients with HCV infection in a large sample and assess the relationship between BFP reactions and HCV infection.METHODS:A total of 2656 patients with positive anti-HCV and 5600 healthy control subjects were enrolled in this study.Hepatitis C serology was determined by a second generation ELISA test for HCV antibody.Syphilis serology was determined by the RPR test.Those subjects with reactive RPR positive underwent the TPHA test.Demographics and laboratory data were collected by trained clinicians.RESULTS:Among 2656 patients,111 (4.2%) had a reactive RPR test.Of the 111 patients who were subjected to reactive RPR test,30 (27.0%) showed HCV(+)/RPR(+).Of 5600 healthy controls,80 (1.4%) had a reactive RPR test.Fourteen (17.5%) controls with HCV(-)/RPR(+) had a non-reactive TPHA test.These represented 1.1% of all HCV-positive and 0.3% of all HCV-negative subjects (P<0.001).A significantly increased prevalence shown by false-positive tests for syphilis was observed in elderly HCV-seropositive patients.BFP-HCV positive group had a higher prevalence of eosinophilia.The eosinophil abnormality was compared between the patients and controls (66.7% vs 21.4%,P=0.0043).No significant results were observed in antinuclear antibodies,antiphospholipid and complement (C3,C4) (P>0.05).CONCLUSIONS:The data of this study demonstrate that HCV infection is associated with a false-positive RPR test.In this study BFPs were significantly more common in HCV positive patients compared to HCV-negative ones.Eosinophil abnormality can be considered as a predictor for BFP.Excessive BFPs must be considered in assessing the frequency of syphilis in a HCV-positive population and the importance of the treponemal specific serologic test should be emphasized for a diagnosis of syphilis in such population.

Effects of historic wildfire and prescribed fire on site occupancy of bats in Shenandoah National Park,Virginia,USA

Given the likelihood of regional extirpation of several once-common bat species in eastern North America from white-nose syndrome,it is critical that the impacts of forest management activities,such as prescribed fire,are known in order to minimize potentially additive negative effects on bat populations.Historic wildfires may offer a suitable surrogate to assess long-term burn impacts on bats for planning,implementing and assessing burn programs.To examine the effects of historic fire on bats,we sampled bat activities at 24 transect locations in burned and unburned forest stands in the central Appalachian Mountains of Shenandoah National Park(SNP),Virginia,USA.There was limited evidence of positive fire effects over time on hoary bats(Lasiurus cinereus Beauvois)and big brown bats(Eptesicus fuscus Beauvois)occupancy.Overall,there were few or mostly equivocal relationships of bat occupancy relative to burn conditions or time since fire in SNP across species using a false-positive occupancy approach.Our results suggest that fire does not strongly affect bat site occupancy short-or long-term in the central Appalachians.

Case report of a healthy,elderly man with long-term high titers for anti-acetylcholine receptor antibody without myasthenia gravis

Anti-acetylcholine receptor antibodies （AAR） are considered pathognomonic and pathogenetic for myasthenia gravis （MG）. AAR detection confirms clinical diagnosis of MG. However, AAR is rarely detected in patients without MG. The underlying pathophysiological mechanisms in a normal subject without MG have not been adequately addressed in previous studies. The present study reports on a case study of a healthy, elderly man with high AAR titers for 14 years. Pathophysiological mechanisms could be due to AAR heterogeneity in specificity, affinity, and multiform, and to muscle variability in response to AAR.

Hybrid Semantic Service Matchmaking Method Based on a Random Forest

Semantic Service Matchmaking(SSM)can be leveraged for mining the most suitable service to accommodate a diversity of user demands.However,existing research on SSM mostly involves logical or non-logical matching,leading to unavoidable false-positive and false-negative problems.Combining different types of SSM methods is an effective way to improve this situation,but the adaptive combination of different service matching methods is still a difficult issue.To conquer this difficulty,a hybrid SSM method,which is based on a random forest and combines the advantages of existing SSM methods,is proposed in this paper.The result of each SSM method is treated as a multi-dimensional feature vector input for the random forest,converting the service matching into a two classification problem.Therefore,our method avoids the flaws found in manual threshold setting.Experimental results show that the proposed method achieves an outstanding performance.

Statistical considerations for high throughput screening data

High throughput screening(HTS)is a widely used effective approach in genome-wide association and large scale protein expression studies,drug discovery,and biomedical imaging research.How to accurately identify candidate‘targets’or biologically meaningful features with a high degree of confidence has led to extensive statistical research in an effort to minimize both false-positive and false-negative rates.A large body of literature on this topic with in-depth statistical contents is available.We examine currently available statistical methods on HTS and aim to summarize some selected methods into a concise,easy-tofollow introduction for experimental biologists.