An interchangeable prion-like domain is required for Ty1 retrotransposition.

Retrotransposons and retroviruses shape genome evolution and can negatively impact genome function. Saccharomyces cerevisiae and its close relatives harbor several families of LTR-retrotransposons, the most abundant being Ty1 in several laboratory strains. The cytosolic foci that nucleate Ty1 virus-like particle (VLP) assembly are not well-understood. These foci, termed retrosomes or T-bodies, contain Ty1 Gag and likely Gag-Pol and the Ty1 mRNA destined for reverse transcription. Here, we report a novel intrinsically disordered N-terminal pr ion-like d omain (PrLD) within Gag that is required for transposition. This domain contains amino-acid composition similar to known yeast prions and is sufficient to nucleate prionogenesis in an established cell-based prion reporter system. Deleting the Ty1 PrLD results in dramatic VLP assembly and retrotransposition defects but does not affect Gag protein level. Ty1 Gag chimeras in which the PrLD is replaced with other sequences, including yeast and mammalian prionogenic domains, display a range of retrotransposition phenotypes from wildtype to null. We examine these chimeras throughout the Ty1 replication cycle and find that some support retrosome formation, VLP assembly, and retrotransposition, including the yeast Sup35 prion and the mouse PrP prion. Our interchangeable Ty1 system provides a useful, genetically tractable in vivo platform for studying PrLDs, complete with a suite of robust and sensitive assays, and host modulators developed to study Ty1 retromobility. Our work invites study into the prevalence of PrLDs in additional mobile elements. Significance: Retrovirus-like retrotransposons help shape the genome evolution of their hosts and replicate within cytoplasmic particles. How their building blocks associate and assemble within the cell is poorly understood. Here, we report a novel pr ion-like d omain (PrLD) in the budding yeast retrotransposon Ty1 Gag protein that builds virus-like particles. The PrLD has similar sequence properties to prions and disordered protein domains that can drive the formation of assemblies that range from liquid to solid. We demonstrate that the Ty1 PrLD can function as a prion and that certain prion sequences can replace the PrLD and support Ty1 transposition. This interchangeable system is an effective platform to study additional disordered sequences in living cells.

First molecular detection of Trypanosoma cruzi, T. rangeli and Leishmania spp. in capybaras.

Hydrochoerus hydrochaeris (capybara), is a widely distributed rodent in Latin America, with exploitation for food purposes and also used in leather industry products. The infection of this rodent by trypanosomatids may not be detected by parasitological methods, due to low parasitemias. The Capybaras blood samples from the Apure State were collected on filter paper, DNA was extracted and PCR was performed. The PCR technique was used for the detection of Trypanosoma cruzi satellite and kinetoplast DNA, T. rangeli miniexon, T. evansi RIME sequence, and DNA encoding ribosomal RNA and internal transcribed spacer 1 from Leishmania spp. Of the 16 evaluated samples, 12 (75%) were positive for T. cruzi, two for T. rangeli (12.5%), one for Leishmania spp. (6.3%) and none for T. evansi. Regarding coinfection, the two specimens infected with T. rangeli were also infected with T. cruzi (12.5%) and the positive sample for Leishmania spp. was also infected with T. cruzi (6.3%). The results shown in this study represent the first finding of T. cruzi infection, detected by molecular methods, world-wide and the first time that T. rangeli and Leishmania spp. have been found in capybaras. In addition, we report coinfections by T. cruzi/T. rangeli and T. cruzi/Leishmania spp. in H. hydrochaeris for the first time world-wide. Capybaras are widely managed as a source of animal protein, the results obtained require evaluating their possible role as a reservoir in trypanosomiasis and leishmaniasis. A 'One Health' approach through combination of ecological, veterinary and human health including the diagnosis and treatment of diseases of both humans and animals is essential for the development of more successful health programs.

Diminutive, degraded but dissimilar: Wolbachia genomes from filarial nematodes do not conform to a single paradigm.

Wolbachia are alpha-proteobacteria symbionts infecting a large range of arthropod species and two different families of nematodes. Interestingly, these endosymbionts are able to induce diverse phenotypes in their hosts: they are reproductive parasites within many arthropods, nutritional mutualists within some insects and obligate mutualists within their filarial nematode hosts. Defining Wolbachia 'species' is controversial and so they are commonly classified into 17 different phylogenetic lineages, termed supergroups, named A-F, H-Q and S. However, available genomic data remain limited and not representative of the full Wolbachia diversity; indeed, of the 24 complete genomes and 55 draft genomes of Wolbachia available to date, 84 % belong to supergroups A and B, exclusively composed of Wolbachia from arthropods. For the current study, we took advantage of a recently developed DNA-enrichment method to produce four complete genomes and two draft genomes of Wolbachia from filarial nematodes. Two complete genomes, wCtub and wDcau, are the smallest Wolbachia genomes sequenced to date (863 988 bp and 863 427 bp, respectively), as well as the first genomes representing supergroup J. These genomes confirm the validity of this supergroup, a controversial clade due to weaknesses of the multilocus sequence typing approach. We also produced the first draft Wolbachia genome from a supergroup F filarial nematode representative (wMhie), two genomes from supergroup D (wLsig and wLbra) and the complete genome of wDimm from supergroup C. Our new data confirm the paradigm of smaller Wolbachia genomes from filarial nematodes containing low levels of transposable elements and the absence of intact bacteriophage sequences, unlike many Wolbachia from arthropods, where both are more abundant. However, we observe differences among the Wolbachia genomes from filarial nematodes: no global co-evolutionary pattern, strong synteny between supergroup C and supergroup J Wolbachia, and more transposable elements observed in supergroup D Wolbachia compared to the other supergroups. Metabolic pathway analysis indicates several highly conserved pathways (haem and nucleotide biosynthesis, for example) as opposed to more variable pathways, such as vitamin B biosynthesis, which might be specific to certain host-symbiont associations. Overall, there appears to be no single Wolbachia-filarial nematode pattern of co-evolution or symbiotic relationship.

Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images.

We present the application of limited one-time sampling irregularity map (LOTS-IM): a fully automatic unsupervised approach to extract brain tissue irregularities in magnetic resonance images (MRI), for quantitatively assessing white matter hyperintensities (WMH) of presumed vascular origin, and multiple sclerosis (MS) lesions and their progression. LOTS-IM generates an irregularity map (IM) that represents all voxels as irregularity values with respect to the ones considered "normal". Unlike probability values, IM represents both regular and irregular regions in the brain based on the original MRI's texture information. We evaluated and compared the use of IM for WMH and MS lesions segmentation on T2-FLAIR MRI with the state-of-the-art unsupervised lesions' segmentation method, Lesion Growth Algorithm from the public toolbox Lesion Segmentation Toolbox (LST-LGA), with several well established conventional supervised machine learning schemes and with state-of-the-art supervised deep learning methods for WMH segmentation. In our experiments, LOTS-IM outperformed unsupervised method LST-LGA on WMH segmentation, both in performance and processing speed, thanks to the limited one-time sampling scheme and its implementation on GPU. Our method also outperformed supervised conventional machine learning algorithms (i.e., support vector machine (SVM) and random forest (RF)) and deep learning algorithms (i.e., deep Boltzmann machine (DBM) and convolutional encoder network (CEN)), while yielding comparable results to the convolutional neural network schemes that rank top of the algorithms developed up to date for this purpose (i.e., UResNet and UNet). LOTS-IM also performed well on MS lesions segmentation, performing similar to LST-LGA. On the other hand, the high sensitivity of IM on depicting signal change deems suitable for assessing MS progression, although care must be taken with signal changes not reflective of a true pathology.

Two New Species and New Records of Mites of the Genus Parichoronyssus (Acari: Macronyssidae) From South American Bats (Chiroptera), With a Key to the Known Species of the Genus.

Derived from exhaustive search of mites of the genus Parichoronyssus associated with South American Bats, we found two new species associated with Phyllostomid, Emballonurid, and Noctiniolid bats: Parichoronyssus alexanderfaini n. sp. associated with Rhinophylla pumilio Peters; Parichoronyssus gettingeri n. sp. associated with Rhynchonycteris naso Wied-Newied, and Noctilio leporinus Linneo. Herein we give the description of those new species, and additionally is included several new records for Parichoronyssus from the region, as well as providing a key to the 11 species of Parichoronyssus.

On two genera of spiny Pudicinae (Nematoda: Trichostrongylina) parasites of the spiny rat Proechimys simonsi (Mammalia: Echimyidae) from Peru.

A new species of trichostrongyloid nematode, Acanthostrongylus secundus is described. It differs from the other species of the genus in the structure of the caudal bursa. Squamasnema amazonica is redescribed correcting the synlophe structure and moving the genus from Heligmonellinae to Pudicinae. Both species were collected in Proechimys simonsi from Peru. [Zoobank URL: urn:lsid:zoobank.org:act:EEDBD925-8539-4F5D-A276-4F735464BA6F].

Impact of a Clinical Decision Support Tool on Dementia Diagnostics in Memory Clinics: The PredictND Validation Study.

BACKGROUND: Determining the underlying etiology of dementia can be challenging. Computer- based Clinical Decision Support Systems (CDSS) have the potential to provide an objective comparison of data and assist clinicians. OBJECTIVES: To assess the diagnostic impact of a CDSS, the PredictND tool, for differential diagnosis of dementia in memory clinics. METHODS: In this prospective multicenter study, we recruited 779 patients with either subjective cognitive decline (n=252), mild cognitive impairment (n=219) or any type of dementia (n=274) and followed them for minimum 12 months. Based on all available patient baseline data (demographics, neuropsychological tests, cerebrospinal fluid biomarkers, and MRI visual and computed ratings), the PredictND tool provides a comprehensive overview and analysis of the data with a likelihood index for five diagnostic groups; Alzheimer´s disease, vascular dementia, dementia with Lewy bodies, frontotemporal dementia and subjective cognitive decline. At baseline, a clinician defined an etiological diagnosis and confidence in the diagnosis, first without and subsequently with the PredictND tool. The follow-up diagnosis was used as the reference diagnosis. RESULTS: In total, 747 patients completed the follow-up visits (53% female, 69±10 years). The etiological diagnosis changed in 13% of all cases when using the PredictND tool, but the diagnostic accuracy did not change significantly. Confidence in the diagnosis, measured by a visual analogue scale (VAS, 0-100%) increased (ΔVAS=3.0%, p<0.0001), especially in correctly changed diagnoses (ΔVAS=7.2%, p=0.0011). CONCLUSION: Adding the PredictND tool to the diagnostic evaluation affected the diagnosis and increased clinicians' confidence in the diagnosis indicating that CDSSs could aid clinicians in the differential diagnosis of dementia.

Streblid bat flies (Diptera) and other ectoparasites on bats (Mammalia: Chiroptera) from French Guiana / Moscas estréblidas (Diptera) e outros ectoparasitos de morcegos (Mammalia: Chiroptera) na Guiana Francesa

Abstract: Recent field surveys of bats (Chiroptera) in various localities of French Guiana have been accompanied by the collection and preservation of ectoparasites, mainly bat flies (Diptera: Streblidae and Nycteribiidae). Most specimens of ectoparasites was collected haphazardly during the course of bats inventories, but systematic surveys on the whole chiropteran community were realized at five opportunities. Concerning Streblidae, 813 individuals have been examined, which represent 46 species and/or subspecies belonging to 15 genera and 6 taxa for confirmation and/or future description. For Nycteribiidae, 44 individuals of 3 identified species and 2 for confirmation and/or future description. Other ectoparasites have been found (Hemiptera and acarids), which are also listed with details on their bat-host, place and date of collect. For six species of bats in which at least 10 animals were carrying ectoparasites, a brief description of the frequencies of their ectoparasites provides some preliminary characteristics of their infracommunities.

Resumo: Pesquisas de campo recentes de morcegos (Chiroptera) em várias localidades da Guiana Francesa foram acompanhadas pela coleta e preservação de ectoparasitas, principalmente moscas ectoparasitas (Diptera: Streblidae e Nycteribiidae). A maioria dos espécimes de ectoparasitos foi coletada aleatoriamente durante o curso dos inventários de morcegos, mas pesquisas sistemáticas em toda a comunidade de quirópteros foram realizadas em cinco oportunidades. Sobre Streblidae, 813 indivíduos foram examinados, dos quais representam 46 espécies e/ou subespécies pertencentes a 15 gêneros e 6 táxons para posterior confirmação específica e/ou descrição. Para Nycterbiidae, 44 indivíduos de 3 espécies e 2 para posterior confirmação específica e/ou descrição. Outros ectoparasitos foram coletados (hemípteros polictenídeos e ácaros), os quais também foram listados com detalhes sobre seus hospedeiros, localidade e data de coleta. Para seis espécies de morcegos com mais de 10 morcegos infestados a descrição da composição de cada infracomunidade encontrada e sua frequência são apresentados.

Actualización en las inserciones anatómicas del ligamento anterolateral: revisión sistemática de la literatura / Update in the Anatomical Insertions of the Anterolateral Ligament: Systematic Review of Literature

Introducción Aunque las indicaciones para su reconstrucción aún son motivo de debate, desde su descripción, la anatomía del ligamento anterolateral ha sido estudiada extensivamente. Sus puntos de inserción se han modificado en los estudios más recientes y esto es importante en el momento de hacer una reconstrucción anatómica. Este estudio busca hacer una revisión sistemática de la literatura para establecer sus puntos de inserción en fémur y tibia. Materiales y métodos Revisión sistemática desde enero de 2012 hasta junio de 2017. Se buscaron publicaciones en Pubmed, Embase, Google Scholar y Cochrane. Se incluyeron estudios cadavéricos que evaluaran la anatomía del ligamento anterolateral y describieran sus puntos de inserción. Resultados Se encontraron 334 estudios con los términos de interés, que tras su evaluación llevó a incluir 13 artículos. El ligamento no estaba presente en el 100% de los especímenes evaluados en los diferentes artículos. Su inserción tibial se ha mantenido sin cambios desde la descripción inicial, en un punto intermedio entre la cabeza del peroné y el tubérculo de Gerdy, mientras que la femoral ha cambiado. Esta se ha modificado a un punto posterior y proximal al epicóndilo lateral del fémur y al origen del colateral externo, contrario a la ubicación inicial anterior y distal a estos. Discusión Actualmente se considera que la inserción del ligamento anterolateral es posterior y proximal al origen del ligamento colateral externo. Esto tiene importancia para su reconstrucción quirúrgica: el ligamento debería ser fijado cuando tiene su máxima longitud, entre 20-30° de flexión de la rodilla.

Introduction Although its anatomy has been extensively studied, there is still controversy in the medical literature as regards when the anterolateral ligament should be reconstructed. Its insertion points have been modified in the most recent studies and this might play an important role in its anatomical reconstruction. This study aims to conduct a systematic review of literature in order to establish insertion points of the anterolateral ligament in the femur and tibia. Materials and methods A systematic review of literature was conducted between January 2012 and June 2017. It included post-mortem studies of dissection of the anterolateral ligament in adult knees that reported its anatomical insertions. The following databases were searched: PubMed, Embase, Google Scholar and Cochrane. Results A total of 334 studies were found in the systematic review using the key words. After evaluating them, 13 papers fulfilled the eligibility criteria and were included in the study. The anterolateral ligament was not found in the 100% of the post-mortem knees. Its tibial insertion continued to be similar to the original description: between the fibula head and Gerdy's tubercle. The femoral insertion has changed, now being posterior and proximal to the lateral epicondyle and the insertion of the lateral collateral ligament, as opposed to its initial location of anterior and distal to these structures. Discussion The femoral insertion of the anterolateral ligament is currently considered to be proximal and posterior to the origin of the lateral collateral ligament. This is important for an anatomical surgical reconstruction, when the ligament should be fixed in its maximal length, between 20-30° of knee flexion.

Gut microbiota dynamics and functionality in Reticulitermes grassei after a 7-day dietary shift and ciprofloxacin treatment.

Gut microbial structure in animals depends on the host, dietary habits and local environment. A random event, dietary change or antibiotic treatment may alter the gut environment with possible repercussions for the bacterial community composition and functionality and ultimately host fitness. The present study was focused on the composition, structure and functionality of gut microbiota in Reticulitermes grassei and the data obtained was compared with sequence surveys of three other Reticulitermes species. Each Reticulitermes species had a significantly different bacterial gut microbiota (pairwise significance tests using the Kolmogorov-Smirnov test), but a similar pattern of distribution (P-test in weighted Unifrac). The core gut microbiota from the analyzed Reticulitermes species contained 16 bacterial operational taxonomic units. Enzymes (KO) were detected from 14 pathways related to carbohydrate metabolism. R. grassei and R. hesperus, based on relative abundance of KO, had the most similar carbohydrate pathway patterns. In addition, we described the gut microbiota and functionality pathways in R. grassei after a 7-day dietary shift and antibiotic (ciprofloxacin) treatment. Both factors, but above all the antibiotic, altered the relative abundance of certain microbial groups, although the changes were not statistically significant (P-test in weighted Unifrac). The cellulose diet enhanced the carbohydrate pathways related to propanoate, butanoate, ascorbate, and glyoxylate metabolism. The antibiotic treatment affected galactose metabolism, the citrate cycle and inositol phosphate metabolism. Those functional changes may be related to changes in the abundance of several bacterial groups. Our findings provide insights into the stability of the gut microbiota in R. grassei and a resilience response to dietary shift or antibiotic treatment disturbance after 7 days.

Personalized Gaussian Processes for Forecasting of Alzheimer's Disease Assessment Scale-Cognition Sub-Scale (ADAS-Cog13).

In this paper, we introduce the use of a personalized Gaussian Process pGP model to predict per-patient changes in ADAS-Cog13-a significant predictor of Alzheimer's Disease (AD) in the cognitive domain - using data from each patient's previous visits, and testing on future (held-out) data. We start by learning a population-level model using multi- modal data from previously seen patients using a base Gaussian Process (GP) regression. The pGP is then formed by adapting the base GP sequentially over time to a new (target) patient using domain adaptive GPs [1]. We extend this personalized approach to predict the values of ADAS-Cog13 over the future 6, 12, 18, and 24 months. We compare this approach to a GP model trained only on past data of the target patients tGP, as well as to a new approach that combines pGP with tGP. We find that this new approach (pGP+tGP) leads to significant improvements in accurately forecasting future ADAS-Cog13 scores.

Achatina fulica (Mollusca: Achatinidae) Naturally Infected with Caenorhabditis briggsae (Dougherty and Nigon, 1949) (Nematoda: Rhabditidae).

Specimens of the African snail Achatina fulica, collected in Bucaramanga, Colombia, were examined for parasites. Numerous specimens of Caenorhabditis briggsae were collected from the digestive tract of the snails and identified by the structure of male spiculum, caudal bursa, gubernaculum and precloacal lip in males, triangular tooth in metarhabdion, and protandrous hermaphrodites with a female:male ratio of 15:1 and with morphometry. DNA sequences of the ITS2 region of the ribosomal gene array from worms in this study matched with 99% similarity to published sequences of C. briggsae. A redescription of the species is provided. This is the first record of the species in South America.

Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database.

Magnetic resonance (MR) imaging is a powerful technique for non-invasive in-vivo imaging of the human brain. We employed a recently validated method for robust cross-sectional and longitudinal segmentation of MR brain images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Specifically, we segmented 5074 MR brain images into 138 anatomical regions and extracted time-point specific structural volumes and volume change during follow-up intervals of 12 or 24 months. We assessed the extracted biomarkers by determining their power to predict diagnostic classification and by comparing atrophy rates to published meta-studies. The approach enables comprehensive analysis of structural changes within the whole brain. The discriminative power of individual biomarkers (volumes/atrophy rates) is on par with results published by other groups. We publish all quality-checked brain masks, structural segmentations, and extracted biomarkers along with this article. We further share the methodology for brain extraction (pincram) and segmentation (MALPEM, MALPEM4D) as open source projects with the community. The identified biomarkers hold great potential for deeper analysis, and the validated methodology can readily be applied to other imaging cohorts.

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease.

Graphs are widely used as a natural framework that captures interactions between individual elements represented as nodes in a graph. In medical applications, specifically, nodes can represent individuals within a potentially large population (patients or healthy controls) accompanied by a set of features, while the graph edges incorporate associations between subjects in an intuitive manner. This representation allows to incorporate the wealth of imaging and non-imaging information as well as individual subject features simultaneously in disease classification tasks. Previous graph-based approaches for supervised or unsupervised learning in the context of disease prediction solely focus on pairwise similarities between subjects, disregarding individual characteristics and features, or rather rely on subject-specific imaging feature vectors and fail to model interactions between them. In this paper, we present a thorough evaluation of a generic framework that leverages both imaging and non-imaging information and can be used for brain analysis in large populations. This framework exploits Graph Convolutional Networks (GCNs) and involves representing populations as a sparse graph, where its nodes are associated with imaging-based feature vectors, while phenotypic information is integrated as edge weights. The extensive evaluation explores the effect of each individual component of this framework on disease prediction performance and further compares it to different baselines. The framework performance is tested on two large datasets with diverse underlying data, ABIDE and ADNI, for the prediction of Autism Spectrum Disorder and conversion to Alzheimer's disease, respectively. Our analysis shows that our novel framework can improve over state-of-the-art results on both databases, with 70.4% classification accuracy for ABIDE and 80.0% for ADNI.

Data-Driven Differential Diagnosis of Dementia Using Multiclass Disease State Index Classifier.

Clinical decision support systems (CDSSs) hold potential for the differential diagnosis of neurodegenerative diseases. We developed a novel CDSS, the PredictND tool, designed for differential diagnosis of different types of dementia. It combines information obtained from multiple diagnostic tests such as neuropsychological tests, MRI and cerebrospinal fluid samples. Here we evaluated how the classifier used in it performs in differentiating between controls with subjective cognitive decline, dementia due to Alzheimer's disease, vascular dementia, frontotemporal lobar degeneration and dementia with Lewy bodies. We used the multiclass Disease State Index classifier, which is the classifier used by the PredictND tool, to differentiate between controls and patients with the four different types of dementia. The multiclass Disease State Index classifier is an extension of a previously developed two-class Disease State Index classifier. As the two-class Disease State Index classifier, the multiclass Disease State Index classifier also offers a visualization of its decision making process, which makes it especially suitable for medical decision support where interpretability of the results is highly important. A subset of the Amsterdam Dementia cohort, consisting of 504 patients (age 65 ± 8 years, 44% females) with data from neuropsychological tests, cerebrospinal fluid samples and both automatic and visual MRI quantifications, was used for the evaluation. The Disease State Index classifier was highly accurate in separating the five classes from each other (balanced accuracy 82.3%). Accuracy was highest for vascular dementia and lowest for dementia with Lewy bodies. For the 50% of patients for which the classifier was most confident on the classification the balanced accuracy was 93.6%. Data-driven CDSSs can be of aid in differential diagnosis in clinical practice. The decision support system tested in this study was highly accurate in separating the different dementias and controls from each other. In addition to the predicted class, it also provides a confidence measure for the classification.

Self-Management and Health Care Transition Among Adolescents and Young Adults With Chronic Kidney Disease: Medical and Psychosocial Considerations.

Health care transition (HCT) is a process that requires preparation as a continuum from pediatric- to adult-focused services. For adolescents and young adults with chronic or ESRD, this process can be prolonged due to their physical, psychological, family, or ecological factors. HCT preparation is a matter of patient safety and patient rights as the consequences of poor preparation at the time of transfer to adult-focused services are great, including rejection of organs, disease relapse, or even death. We present a case to illustrate important points of HCT preparation, with suggestions for intervention by the interdisciplinary team members who serve (and will serve) these survivors of pediatric-onset health conditions. To monitor the HCT process, yearly measurements of skill mastery need to take place guide interventions.

Microfluidic multiplexing of solid-state nanopores.

Although solid-state nanopores enable electronic analysis of many clinically and biologically relevant molecular structures, there are few existing device architectures that enable high-throughput measurement of solid-state nanopores. Herein, we report a method for microfluidic integration of multiple solid-state nanopores at a high density of one nanopore per (35 µm2). By configuring microfluidic devices with microfluidic valves, the nanopores can be rinsed from a single fluid input while retaining compatibility for multichannel electrical measurements. The microfluidic valves serve the dual purpose of fluidic switching and electric switching, enabling serial multiplexing of the eight nanopores with a single pair of electrodes. Furthermore, the device architecture exhibits low noise and is compatible with electroporation-based in situ nanopore fabrication, providing a scalable platform for automated electronic measurement of a large number of integrated solid-state nanopores.

Biofilm formation and antibiotic susceptibility in dispersed cells versus planktonic cells from clinical, industry and environmental origins.

We examined the cell-surface physicochemical properties, the biofilm formation capability and the antibiotic susceptibility in dispersed cells (from an artificial biofilm of alginate beads) and compared with their planktonic (free-swimming) counterparts. The strains used were from different origins, such as clinical (Acinetobacter baumannii AB4), cosmetic industry (Klebsiella oxytoca EU213, Pseudomonas aeruginosa EU190), and environmental (Halomonas venusta MAT28). In general, dispersed cells adhered better to surfaces (measured as the "biofilm index") and had a greater hydrophobicity [measured as the microbial affinity to solvents (MATS)] than planktonic cells. The susceptibility to two antibiotics (ciprofloxacin and tetracycline) of dispersed cells was higher compared with that of their planktonic counterparts (tested by the "bactericidal index"). Dispersed and planktonic cells exhibited differences in cell permeability, especially in efflux pump activity, which could be related to the differences observed in susceptibility to antibiotics. At 1 h of biofilm formation in microtiter plates, dispersed cells treated with therapeutic concentration of ciprofloxacin yielded a lower biofilm index than the control dispersed cells without ciprofloxacin. With respect to the planktonic cells, the biofilm index was similar with and without the ciprofloxacin treatment. In both cases there were a reduction of the number of bacteria measured as viable count of the supernatant. The lower biofilm formation in dispersed cells with ciprofloxacin treatment may be due to a significant increase of biofilm disruption with respect to the biofilm from planktonic cells. From a clinical point of view, biofilms formed on medical devices such as catheters, cells that can be related to an infection were the dispersed cells. Our results showed that early treatment with ciprofloxacin of dispersed cells could diminishe bacterial dispersion and facilitate the partial elimination of the new biofilm formed.

Five-class differential diagnostics of neurodegenerative diseases using random undersampling boosting.

Differentiating between different types of neurodegenerative diseases is not only crucial in clinical practice when treatment decisions have to be made, but also has a significant potential for the enrichment of clinical trials. The purpose of this study is to develop a classification framework for distinguishing the four most common neurodegenerative diseases, including Alzheimer's disease, frontotemporal lobe degeneration, Dementia with Lewy bodies and vascular dementia, as well as patients with subjective memory complaints. Different biomarkers including features from images (volume features, region-wise grading features) and non-imaging features (CSF measures) were extracted for each subject. In clinical practice, the prevalence of different dementia types is imbalanced, posing challenges for learning an effective classification model. Therefore, we propose the use of the RUSBoost algorithm in order to train classifiers and to handle the class imbalance training problem. Furthermore, a multi-class feature selection method based on sparsity is integrated into the proposed framework to improve the classification performance. It also provides a way for investigating the importance of different features and regions. Using a dataset of 500 subjects, the proposed framework achieved a high accuracy of 75.2% with a balanced accuracy of 69.3% for the five-class classification using ten-fold cross validation, which is significantly better than the results using support vector machine or random forest, demonstrating the feasibility of the proposed framework to support clinical decision making.

Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images.

Accurate localization of anatomical landmarks is an important step in medical imaging, as it provides useful prior information for subsequent image analysis and acquisition methods. It is particularly useful for initialization of automatic image analysis tools (e.g. segmentation and registration) and detection of scan planes for automated image acquisition. Landmark localization has been commonly performed using learning based approaches, such as classifier and/or regressor models. However, trained models may not generalize well in heterogeneous datasets when the images contain large differences due to size, pose and shape variations of organs. To learn more data-adaptive and patient specific models, we propose a novel stratification based training model, and demonstrate its use in a decision forest. The proposed approach does not require any additional training information compared to the standard model training procedure and can be easily integrated into any decision tree framework. The proposed method is evaluated on 1080 3D high-resolution and 90 multi-stack 2D cardiac cine MR images. The experiments show that the proposed method achieves state-of-the-art landmark localization accuracy and outperforms standard regression and classification based approaches. Additionally, the proposed method is used in a multi-atlas segmentation to create a fully automatic segmentation pipeline, and the results show that it achieves state-of-the-art segmentation accuracy.