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The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides interpretable features and its output is a fixed length vector irrespective of the number of input points or their sample times. In this paper we use the path signature to provide features for identifying people whose diagnosis subsequently converts to Alzheimer’s disease. In two separate classification tasks we distinguish converters from 1) healthy individuals, and 2) individuals with mild cognitive impairment. The data used are time-ordered measurements of the whole brain, ventricles and hippocampus from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We find two nonlinear interactions which are predictive in both cases. The first interaction is change of hippocampal volume with time, and the second is a change of hippocampal volume relative to the volume of the whole brain. While hippocampal and brain volume changes are well known in Alzheimer’s disease, we demonstrate the power of the path signature in their identification and analysis without manual feature selection. Sequential data is becoming increasingly available as monitoring technology is applied, and the path signature method is shown to be a useful tool in the processing of this data. [ABSTRACT FROM AUTHOR]

Objectives: The treatment of condylar fractures has long been controversial. In this paper, we established a database for accurate measurement, storage, management and analysis of patients’ data, in order to help determine the best treatment plan. Methods: First of all, the diagnosis and treatment database was established based on XNAT, including 339 cases of condylar fractures and their related information. Then image segmentation, registration and three-dimensional (3D) measurement were used to measure and analyze the condyle shapes. Statistical analysis was used to analyze the anatomical structure changes of condyle and the surrounding tissues at different stages before and after treatment. The processes of condylar fracture reestablishment at different stages were also dynamically monitored. Finally, based on all these information, the digital diagnosis and treatment plans for condylar fractures were developed. Results: For the patients less than 18 years old with no significant dislocation, surgical treatment and conservative treatment were equally effective for intracapsular fracture, and had no significant difference for neck and basal fractures. For patients above 18 years old, there was no significant difference between the two treatment methods for intracapsular fractures; but for condylar neck and basal fractures, surgical treatment was better than conservative treatment. When condylar fracture shift angle was greater than 11 degrees, and mandibular ramus height reduction was greater than 4mm, the patients felt the strongest pain, and their mouths opening was severely restricted. There were 170 surgical cases with condylar fracture shift angel greater than 11 degrees, and 118 of them (69.4%) had good prognosis, 52 of them (30.6%) had complications such as limited mouth opening. There were 173 surgical cases with mandibular ramus height reduction more than 4mm, and 112 of them (64.7%) had good prognosis, 61 of them (35.3%) had complications such as limited mouth opening. Conclusions: The establishment of XNAT condylar fracture database is helpful for establishing a digital diagnosis and treatment workflow for mandibular condylar fractures, providing new theoretical foundation and application basis for diagnosis and treatment of condylar fractures. [ABSTRACT FROM AUTHOR]

The identification of microbial species has depended predominantly upon culture-based techniques. However, the difficulty with which types of organisms are cultured implies that the grown species may be overrepresented by both cultivation and plate counts. In recent years, culture-independent analysis using high-throughput sequencing has been advocated for use as a point-of-care diagnostic tool. Although it offers a rapid and unbiased survey to characterize the pathogens in clinical specimens, its accuracy is reduced by the high level of contamination of human DNA. In this paper, we propose using a culture-independent analysis for a Klebsiella pneumoniae clinical strain within a liver abscess using nanopore sequencing. Owing to the highly-contaminated cell population within a liver abscess, we managed to reduce the confounding effects of human DNA through the use of DNase and differential centrifugation. Genomic DNA was sequenced through the use of Nanopore MinION sequencer and analyzed using a suite of bioinformatics approaches. K. pneumoniae was successfully identified along with antibiotic-resistant genes. Our results indicate that, by integrating real-time nanopore sequencing and bioinformatics software, real-time pathogen identification in a liver abscess can be achieved. [ABSTRACT FROM AUTHOR]

Objectives: Recently, improvements have been made to diagnostics for gambiense sleeping sickness control but their performance remains poorly documented and may depend on specimen processing prior to examination. In a prospective study in the Democratic Republic of the Congo, we compared the diagnostic performance of several parasite detection techniques, immune trypanolysis and of m18S PCR on whole blood stored in a stabilisation buffer or dried on filter paper. Methods: Individuals with CATT whole blood (WB) titer ≥1∶4 or with clinical signs indicative for sleeping sickness were examined for presence of trypanosomes in lymph node aspirate (LNA) and/or in blood. Blood was examined with Capillary Centrifugation Technique (CTC), mini-Anion Exchange Centrifugation Technique (mAECT) and mAECT on buffy coat (BC). PCR was performed on whole blood (i) stored in guanidine hydrochloride EDTA (GE) stabilisation buffer and (ii) dried on filter paper, and repeatability and reproducibility were assessed. Immune trypanolysis (TL) was performed on plasma. Results: A total of 237 persons were included. Among 143 parasitologically confirmed cases, 85.3% had a CATT-WB titre of ≥1/8, 39.2% were positive in LNA, 47.5% in CTC, 80.4% in mAECT-WB, 90.9% in mAECT-BC, 95.1% in TL and up to 89.5% in PCR on GE-stabilised blood. PCR on GE-stabilised blood showed highest repeatability (87.8%) and inter-laboratory reproducibility (86.9%). Of the 94 non-confirmed suspects, respectively 39.4% and 23.4% were TL or PCR positive. Suboptimal specificity of PCR and TL was also suggested by latent class analysis. Conclusion: The combination of LNA examination with mAECT-BC offered excellent diagnostic sensitivity. For PCR, storage of blood in stabilisation buffer is to be preferred over filter paper. TL as well as PCR are useful for remote diagnosis but are not more sensitive than mAECT-BC. For TL and PCR, the specificity, and thus usefulness for management of non-confirmed suspects remain to be determined. [ABSTRACT FROM AUTHOR]

Introduction: This paper investigates the role of Group II Secretory Phospholipase A2 (sPLA2-IIA) as a biomarker for the diagnosis of sepsis and bacterial infection in adults. Sepsis and bacterial infection are common problems encountered by patients in the hospital and often carry adverse outcomes if not managed early. Methods: Two independent reviewers conducted a comprehensive search using Ovid MEDLINE published from years 1993 to 2016 and SCOPUS published from year 1985 to 2017 to screen for relevant studies. The main inclusion criteria included adult subjects, patients with suspected or confirmed signs of infection and relevant outcomes which looked into the role of sPLA2-IIA in detecting the presence of sepsis and bacterial infection in the subjects. Results and discussion: Four studies met the inclusion criteria. SPLA2-IIA was found to be effective in detecting the presence of sepsis and bacterial infection in adults. The levels of serum sPLA2-IIA also correlated well with the presence of sepsis and bacterial infection. Conclusion: This systematic review highlights the role of sPLA2-IIA as a reliable tool to diagnose sepsis and bacterial infection in adult patients. Nonetheless, further studies should be done in the future to provide more compelling evidence on its application in the clinical setting. [ABSTRACT FROM AUTHOR]

Several studies on pregnancy-associated cancers have suggested an association with congenital anomalies in offspring. Previous studies have included maternal cancers diagnosed up to 2 years after pregnancy; however, long latency periods of some cancers mean that cancers diagnosed many years postpartum might have been present during pregnancy in a preclinical state. This paper considers the association between maternal cancers diagnosed from 2 years prior to pregnancy until the mother reaches 50 years of age, and congenital anomalies, as diagnosed at birth or within the first year of life. The current population-based study looks at associations of cancers in mothers with congenital anomalies in their children. Children were followed up from birth to diagnosis of a congenital anomaly, death, emigration or end of follow-up (whichever occurred first). A total of 56,016 children (2.6%) were considered exposed to a maternal cancer of any type; and they had a hazard ratio (HR) of 1.04 (95% confidence interval [CI]: 1.00, 1.09) compared with unexposed children. The greatest HR was seen among children whose mothers had been diagnosed with cancers before or during pregnancy (HR: 1.37, 95% CI: 1.07, 1.75). Similar results were seen when paternal cancers were used as a ‘negative control’. Statistically significant associations were seen for some specific congenital anomalies of organ systems (congenital anomalies of the musculoskeletal system [HR: 1.13, 95% CI: 1.02, 1.25]) and for some specific types of maternal cancer (leukaemia [HR: 1.31, 95% CI: 1.01, 1.61], The results of the main analyses suggest a small increase in risk of congenital anomalies in offspring of mothers diagnosed with cancer from 2 years before pregnancy, until the mother reaches 50 years of age; with the greatest increase seen for exposure in the pre-pregnancy and pregnancy period. These results may reflect shared causes for some cancers and some congenital anomalies. The similar results seen for paternal cancers indicate that the cause may be genetic or related to the families’ social and environmental conditions. [ABSTRACT FROM AUTHOR]

Early childhood anxiety disorders are common, impairing, and predictive of anxiety and mood disorders later in childhood. Epidemiological studies over the last decade find that the prevalence of impairing anxiety disorders in preschool children ranges from 0.3% to 6.5%. Yet, less than 15% of young children with an impairing anxiety disorder receive a mental health evaluation or treatment. One possible reason for the low rate of care for anxious preschoolers is the lack of affordable, timely, reliable and valid tools for identifying young children with clinically significant anxiety. Diagnostic interviews assessing psychopathology in young children require intensive training, take hours to administer and code, and are not available for use outside of research settings. The Preschool Age Psychiatric Assessment (PAPA) is a reliable and valid structured diagnostic parent-report interview for assessing psychopathology, including anxiety disorders, in 2 to 5 year old children. In this paper, we apply machine-learning tools to already collected PAPA data from two large community studies to identify sub-sets of PAPA items that could be developed into an efficient, reliable, and valid screening tool to assess a young child’s risk for an anxiety disorder. Using machine learning, we were able to decrease by an order of magnitude the number of items needed to identify a child who is at risk for an anxiety disorder with an accuracy of over 96% for both generalized anxiety disorder (GAD) and separation anxiety disorder (SAD). Additionally, rather than considering GAD or SAD as discrete/binary entities, we present a continuous risk score representing the child’s risk of meeting criteria for GAD or SAD. Identification of a short question-set that assesses risk for an anxiety disorder could be a first step toward development and validation of a relatively short screening tool feasible for use in pediatric clinics and daycare/preschool settings. [ABSTRACT FROM AUTHOR]

Pneumonia is the leading cause of infectious disease mortality in children. Currently, health care providers (HCPs) are trained to use World Health Organization Integrated Management of Childhood Illness (IMCI) paper-based protocols and manually assess respiratory rate to diagnose pneumonia in low-resource settings (LRS). However, this approach of relying on clinical signs alone has proven problematic. Hypoxemia, a diagnostic indicator of pneumonia severity associated with an increased risk of death, is not assessed because pulse oximetry is often not available in LRS. To improve HCPs’ ability to diagnose, classify, and manage pneumonia and other childhood illnesses, “mPneumonia” was developed. mPneumonia is a mobile health application that integrates a digital version of the IMCI algorithm with a software-based breath counter and a pulse oximeter. A design-stage qualitative pilot study was conducted to assess feasibility, usability, and acceptability of mPneumonia in six health centers and five community-based health planning and services centers in Ghana. Nine health administrators, 30 HCPs, and 30 caregivers were interviewed. Transcribed interview audio recordings were coded and analyzed for common themes. Health administrators reported mPneumonia would be feasible to implement with approval and buy-in from national and regional decision makers. HCPs felt using the mPneumonia application would be feasible to integrate into their work with the potential to improve accurate patient care. They reported it was “easy to use” and provided confidence in diagnosis and treatment recommendations. HCPs and caregivers viewed the pulse oximeter and breath counter favorably. Challenges included electricity requirements for charging and the time needed to complete the application. Some caregivers saw mPneumonia as a sign of modernity, increasing their trust in the care received. Other caregivers were hesitant or confused about the new technology. Overall, this technology was valued by users and is a promising innovation for improving quality of care in frontline health facilities. [ABSTRACT FROM AUTHOR]

Purpose: Visual Stress (VS) is a condition in which words appear blurred, in motion, or otherwise distorted when reading. Some people diagnosed with VS find that viewing black text on white paper through coloured overlays or precision tinted lenses (PTLs) reduces symptoms attributed to VS. The aim of the present study is to determine whether the choice of colour of overlays or PTLs is influenced by a patient’s gender. Methods: Records of all patients attending a VS assessment in two optometry practices between 2009 and 2014 were reviewed retrospectively. Patients who reported a significant and consistent reduction in symptoms with either overlay and or PTL were included in the analysis. Overlays and PTLs were categorized as stereotypical male, female or neutral colours based on gender preferences as described in the literature. Chi-square analysis was carried out to determine whether gender (across all ages or within age groups) was associated with overlay or PTL colour choice. Results: 279 patients (133 males and 146 females, mean age 17 years) consistently showed a reduction in symptoms with an overlay and were included. Chi-square analysis revealed no significant association between the colour of overlay chosen and male or female gender (Chi-square 0.788, p = 0.674). 244 patients (120 males and 124 females, mean age 24.5 years) consistently showed a reduction in symptoms with PTLs and were included. Chi-square analysis revealed a significant association between stereotypical male/female/neutral colours of PTLs chosen and male/female gender (Chi-square 6.46, p = 0.040). More males preferred stereotypical male colour PTLs including blue and green while more females preferred stereotypical female colour PTLs including pink and purple. Conclusions: For some VS patients, the choice of PTL colour is influenced not only by the alleviation of symptoms but also by other non-visual factors such as gender. [ABSTRACT FROM AUTHOR]

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control. [ABSTRACT FROM AUTHOR]

Purpose: Quantitative image analysis in previous research in obstructive sleep apnea syndrome (OSAS) has focused on the upper airway or several objects in its immediate vicinity and measures of object size. In this paper, we take a more general approach of considering all major objects in the upper airway region and measures pertaining to their individual morphological properties, their tissue characteristics revealed by image intensities, and the 3D architecture of the object assembly. We propose a novel methodology to select a small set of salient features from this large collection of measures and demonstrate the ability of these features to discriminate with very high prediction accuracy between obese OSAS and obese non-OSAS groups. Materials and Methods: Thirty children were involved in this study with 15 in the obese OSAS group with an apnea-hypopnea index (AHI) = 14.4 ± 10.7) and 15 in the obese non-OSAS group with an AHI = 1.0 ± 1.0 (p<0.001). Subjects were between 8–17 years and underwent T1- and T2-weighted magnetic resonance imaging (MRI) of the upper airway during wakefulness. Fourteen objects in the vicinity of the upper airways were segmented in these images and a total of 159 measurements were derived from each subject image which included object size, surface area, volume, sphericity, standardized T2-weighted image intensity value, and inter-object distances. A small set of discriminating features was identified from this set in several steps. First, a subset of measures that have a low level of correlation among the measures was determined. A heat map visualization technique that allows grouping of parameters based on correlations among them was used for this purpose. Then, through T-tests, another subset of measures which are capable of separating the two groups was identified. The intersection of these subsets yielded the final feature set. The accuracy of these features to perform classification of unseen images into the two patient groups was tested by using logistic regression and multi-fold cross validation. Results: A set of 16 features identified with low inter-feature correlation (< 0.36) yielded a high classification accuracy of 96% with sensitivity and specificity of 97.8% and 94.4%, respectively. In addition to the previously observed increase in linear size, surface area, and volume of adenoid, tonsils, and fat pad in OSAS, the following new markers have been found. Standardized T2-weighted image intensities differed between the two groups for the entire neck body region, pharynx, and nasopharynx, possibly indicating changes in object tissue characteristics. Fat pad and oropharynx become less round or more complex in shape in OSAS. Fat pad and tongue move closer in OSAS, and so also oropharynx and tonsils and fat pad and tonsils. In contrast, fat pad and oropharynx move farther apart from the skin object. Conclusions: The study has found several new anatomic bio-markers of OSAS. Changes in standardized T2-weighted image intensities in objects may imply that intrinsic tissue composition undergoes changes in OSAS. The results on inter-object distances imply that treatment methods should respect the relationships that exist among objects and not just their size. The proposed method of analysis may lead to an improved understanding of the mechanisms underlying OSAS. [ABSTRACT FROM AUTHOR]

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. [ABSTRACT FROM AUTHOR]

Background: Diaphragm weakness is the main reason for respiratory dysfunction in patients with Pompe disease, a progressive metabolic myopathy affecting respiratory and limb-girdle muscles. Since respiratory failure is the major cause of death among adult patients, early identification of respiratory muscle involvement is necessary to initiate treatment in time and possibly prevent irreversible damage. In this paper we investigate the suitability of dynamic MR imaging in combination with state-of-the-art image analysis methods to assess respiratory muscle weakness. Methods: The proposed methodology relies on image registration and lung surface extraction to quantify lung kinematics during breathing. This allows for the extraction of geometry and motion features of the lung that characterize the independent contribution of the diaphragm and the thoracic muscles to the respiratory cycle. Results: Results in 16 3D+t MRI scans (10 Pompe patients and 6 controls) of a slow expiratory maneuver show that kinematic analysis from dynamic 3D images reveals important additional information about diaphragm mechanics and respiratory muscle involvement when compared to conventional pulmonary function tests. Pompe patients with severely reduced pulmonary function showed severe diaphragm weakness presented by minimal motion of the diaphragm. In patients with moderately reduced pulmonary function, cranial displacement of posterior diaphragm parts was reduced and the diaphragm dome was oriented more horizontally at full inspiration compared to healthy controls. Conclusion: Dynamic 3D MRI provides data for analyzing the contribution of both diaphragm and thoracic muscles independently. The proposed image analysis method has the potential to detect less severe diaphragm weakness and could thus be used to determine the optimal start of treatment in adult patients with Pompe disease in prospect of increased treatment response. [ABSTRACT FROM AUTHOR]

Objectives: To determine the potential of intravoxel incoherent motion (IVIM) MR imaging for staging of hepatic fibrosis (HF). Methods: We searched PubMed and EMBASE from their inception to 31 July 2015 to select studies reporting IVIM MR imaging and HF staging. We defined F1-2 as non-advanced HF, F3-4 as advanced HF, F0 as normal liver, F1 as very early HF, and F2-4 as significant HF. Then we compared stage F0 with F1, F0-1 with F2-3, and F1-2 with F3-4 using IVIM-derived parameters (pseudo-diffusion coefficient D*, perfusion fraction f, and pure molecular diffusion parameter D). The effect estimate was expressed as a pooled weighted mean difference (WMD) with 95% confidence interval (CI), using the fixed-effects model. Results: Overall, we included six papers (406 patients) in this study. Significant differences in D* were observed between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 2.46, 95% CI 0.83–4.09, P = 0.006; WMD 13.10, 95% CI 9.53–16.67, P < 0.001; WMD 14.34, 95% CI 10.26–18.42, P < 0.001, respectively). Significant differences in f were also found between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 1.62, 95% CI 0.06–3.18, P = 0.027; WMD 5.63, 95% CI 2.74–8.52, P < 0.001; WMD 3.30, 95% CI 2.10–4.50, P < 0.001, respectively). However, D showed no differences between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 0.05, 95% CI -0.01─0.11, P = 0.105; WMD 0.04, 95% CI -0.01─0.10, P = 0.230; WMD 0.02, 95% CI -0.02─0.06, P = 0.378, respectively). Conclusions: IVIM MR imaging provides an effective method of staging HF and can distinguish early HF from normal liver, significant HF from normal liver or very early HF, and advanced HF from non-advanced HF. [ABSTRACT FROM AUTHOR]

Intravascular Ultrasound (IVUS) is one ultrasonic imaging technology to acquire vascular cross-sectional images for the visualization of the inner vessel structure. This technique has been widely used for the diagnosis and treatment of coronary artery diseases. The detection of the calcified plaque with acoustic shadowing in IVUS images plays a vital role in the quantitative analysis of atheromatous plaques. The conventional method of the calcium detection is manual drawing by the doctors. However, it is very time-consuming, and with high inter-observer and intra-observer variability between different doctors. Therefore, the computer-aided detection of the calcified plaque is highly desired. In this paper, an automated method is proposed to detect the calcified plaque with acoustic shadowing in IVUS images by the Rayleigh mixture model, the Markov random field, the graph searching method and the prior knowledge about the calcified plaque. The performance of our method was evaluated over 996 in-vivo IVUS images acquired from eight patients, and the detected calcified plaques are compared with manually detected calcified plaques by one cardiology doctor. The experimental results are quantitatively analyzed separately by three evaluation methods, the test of the sensitivity and specificity, the linear regression and the Bland-Altman analysis. The first method is used to evaluate the ability to distinguish between IVUS images with and without the calcified plaque, and the latter two methods can respectively measure the correlation and the agreement between our results and manual drawing results for locating the calcified plaque in the IVUS image. High sensitivity (94.68%) and specificity (95.82%), good correlation and agreement (>96.82% results fall within the 95% confidence interval in the Student t-test) demonstrate the effectiveness of the proposed method in the detection of the calcified plaque with acoustic shadowing in IVUS images. [ABSTRACT FROM AUTHOR]

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method. [ABSTRACT FROM AUTHOR]

Objectives: Although several studies have been conducted regarding Kaposi sarcoma (KS), its histogenesis still remains to be elucidated. The aim of our study was to analyze the immunophenotype of Kaposi sarcoma and to present a hypothesis about the histogenesis of this tumor, based on a case series and a review of relevant literature. Methods: In 15 cases of KSs diagnosed during 2000–2011, the clinicopathological features were correlated with the immunoexpression of c-Kit, SMA, CD34, CD31, vascular endothelial growth factor (VEGF), COX-2, c-KIT, smooth muscle antigen (SMA), and stem cell surface marker CD105. Results: Both CD105 and c-KIT rate of the spindle-shaped tumor cell positivity increased in parallel to the pathological stage. All cases displayed CD105 and weak c-KIT positivity in the endothelial cells. SMA, VEGF, and COX-2 were focally expressed in all cases. CD34 marked both endothelium and spindle-shaped tumor cells. No c-KIT expression was noticed in KS of the internal organs. Conclusions: KS seems to be a variant of myofibroblastic tumors that originates from the viral modified pluripotent mesenchymal cells of the connective tissue transformed in spindle-shaped KS cells, followed by a mesenchymal-endothelial transition and a myofibroblastic-like differentiation. This paper mailnly showed that KS cannot be considered a pure vascular tumor. [ABSTRACT FROM AUTHOR]

Introduction: There is no consensus on how to investigate men with negative transrectal ultrasound guided prostate biopsy (TRUS-B) but ongoing suspicion of cancer. Three strategies used are transperineal (TP-B), transrectal saturation (TS-B) and MRI-guided biopsy (MRI-B). We compared cancer yields of these strategies. Methods: Papers were identified by search of Pubmed, Embase and Ovid Medline. Included studies investigated biopsy diagnostic yield in men with at least one negative TRUS-B and ongoing suspicion of prostate cancer. Data including age, PSA, number of previous biopsy episodes, number of cores at re-biopsy, cancer yield, and Gleason score of detected cancers were extracted. Meta-regression analyses were used to analyse the data. Results: Forty-six studies were included; 12 of TS-B, 14 of TP-B, and 20 of MRI-B, representing 4,657 patients. Mean patient age, PSA and number of previous biopsy episodes were similar between the strategies. The mean number of biopsy cores obtained by TP-B and TS-B were greater than MRI-B. Cancer detection rates were 30·0%, 36·8%, and 37·6% for TS-B, TP-B, and MRI-B respectively. Meta-regression analysis showed that MRI-B had significantly higher cancer detection than TS-B. There were no significant differences however between MRI-B and TP-B, or TP-B and TS-B. In a sensitivity analysis incorporating number of previous biopsy episodes (36 studies) the difference between MRI-B and TP-B was not maintained resulting in no significant difference in cancer detection between the groups. There were no significant differences in median Gleason scores detected comparing the three strategies. Conclusions: In the re-biopsy setting, it is unclear which strategy offers the highest cancer detection rate. MRI-B may potentially detect more prostate cancers than other modalities and can achieve this with fewer biopsy cores. However, well–designed prospective studies with standardised outcome measures are needed to accurately compare modalities and define an optimum re-biopsy approach. [ABSTRACT FROM AUTHOR]

Cutaneous and mucosal leishmaniasis is widely distributed in Central and South America. Leishmania of the Viannia subgenus are the most frequent species infecting humans. L. (V.) braziliensis, L. (V.) panamensis are also responsible for metastatic mucosal leishmaniasis. Conventional or real time PCR is a more sensitive diagnostic test than microscopy, but the cost and requirement for infrastructure and trained personnel makes it impractical in most endemic regions. Primary health systems need a sensitive and specific point of care (POC) diagnostic tool. We developed a novel POC molecular diagnostic test for cutaneous leishmaniasis caused by Leishmania (Viannia) spp. Parasite DNA was amplified using isothermal Recombinase Polymerase Amplification (RPA) with primers and probes that targeted the kinetoplast DNA. The amplification product was detected by naked eye with a lateral flow (LF) immunochromatographic strip. The RPA-LF had an analytical sensitivity equivalent to 0.1 parasites per reaction. The test amplified the principal L. Viannia species from multiple countries: L. (V.) braziliensis (n = 33), L. (V.) guyanensis (n = 17), L. (V.) panamensis (n = 9). The less common L. (V.) lainsoni, L. (V.) shawi, and L. (V.) naiffi were also amplified. No amplification was observed in parasites of the L. (Leishmania) subgenus. In a small number of clinical samples (n = 13) we found 100% agreement between PCR and RPA-LF. The high analytical sensitivity and clinical validation indicate the test could improve the efficiency of diagnosis, especially in chronic lesions with submicroscopic parasite burdens. Field implementation of the RPA-LF test could contribute to management and control of cutaneous and mucosal leishmaniasis. [ABSTRACT FROM AUTHOR]