Snap evaporation of droplets on smooth topographies

Droplet evaporation on solid surfaces is important in many applications including printing, micro-patterning and cooling. While seemingly simple, the configuration of evaporating droplets on solids is difficult to predict and control. This is because evaporation typically proceeds as a “stick-slip” sequence—a combination of pinning and de-pinning events dominated by static friction or “pinning”, caused by microscopic surface roughness. Here we show how smooth, pinning-free, solid surfaces of non-planar topography promote a different process called snap evaporation. During snap evaporation a droplet follows a reproducible sequence of configurations, consisting of a quasi-static phase-change controlled by mass diffusion interrupted by out-of-equilibrium snaps. Snaps are triggered by bifurcations of the equilibrium droplet shape mediated by the underlying non-planar solid. Because the evolution of droplets during snap evaporation is controlled by a smooth topography, and not by surface roughness, our ideas can inspire programmable surfaces that manage liquids in heat- and mass-transfer applications

Autism as a disorder of neural information processing: directions for research and targets for therapy

The broad variation in phenotypes and severities within autism spectrum disorders suggests the involvement of multiple predisposing factors, interacting in complex ways with normal developmental courses and gradients. Identification of these factors, and the common developmental path into which theyfeed, is hampered bythe large degrees of convergence from causal factors to altered brain development, and divergence from abnormal brain development into altered cognition and behaviour. Genetic, neurochemical, neuroimaging and behavioural findings on autism, as well as studies of normal development and of genetic syndromes that share symptoms with autism, offer hypotheses as to the nature of causal factors and their possible effects on the structure and dynamics of neural systems. Such alterations in neural properties may in turn perturb activity-dependent development, giving rise to a complex behavioural syndrome many steps removed from the root causes. Animal models based on genetic, neurochemical, neurophysiological, and behavioural manipulations offer the possibility of exploring these developmental processes in detail, as do human studies addressing endophenotypes beyond the diagnosis itself

Natural course of fatty liver in 36,195 South Korean adults

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of liver disease, and yet the natural course remains unclear. Study population included 36,195 individuals who participated in a health-screening program and diagnosed with fatty liver by abdominal ultrasound. Participants were provided written information regarding fatty liver and advised to make lifestyle changes. Ultrasound was repeated after at least 6 months. After a mean follow up of 4.9 years (+/-3.4), 19.6% resolved their fatty liver. Individuals who resolved were more likely female (22.9% vs. 12.3%), thinner (body mass index [BMI], 25.2 +/- 2.7 vs. 26 +/- 2.7), and with lower HOMA-IR (1.4 vs. 1.7) (P .70.001). Decrease in BMI predicted resolution of fatty liver with 42% of those in the top quartile of BMI decline resolving compared with 5.7% in the lowest quartile (odds ratio [OR] (95% confidence interval [CI]) 15.65 (14.13-17.34), P < 0.001)). Baseline HOMA-IR also predicted resolution with those in the top quartile (most insulin resistant) being least likely to resolve (12%) vs. those in the lowest quartile (25%) (OR 0.36 [0.31-0.42], P < 0.001). Fatty liver disease is persistent. Individuals with higher degree of insulin resistance are also the most likely to have persistent steatosis at follow up

A method to improve protein subcellular localization prediction by integrating various biological data sources

<p>Abstract</p> <p>Background</p> <p>Protein subcellular localization is crucial information to elucidate protein functions. Owing to the need for large-scale genome analysis, computational method for efficiently predicting protein subcellular localization is highly required. Although many previous works have been done for this task, the problem is still challenging due to several reasons: the number of subcellular locations in practice is large; distribution of protein in locations is imbalanced, that is the number of protein in each location remarkably different; and there are many proteins located in multiple locations. Thus it is necessary to explore new features and appropriate classification methods to improve the prediction performance.</p> <p>Results</p> <p>In this paper we propose a new predicting method which combines two key ideas: 1) Information of neighbour proteins in a probabilistic gene network is integrated to enrich the prediction features. 2) Fuzzy k-NN, a classification method based on fuzzy set theory is applied to predict protein locating in multiple sites. Experiment was conducted on a dataset consisting of 22 locations from Budding yeast proteins and significant improvement was observed.</p> <p>Conclusion</p> <p>Our results suggest that the neighbourhood information from functional gene networks is predictive to subcellular localization. The proposed method thus can be integrated and complementary to other available prediction methods.</p

Real-world Prescription Patterns and Patient Satisfaction Regarding Maintenance Therapy of Gastroesophageal Reflux Disease: An Observational, Cross-sectional, Multicenter Study

Background/Aims Gastroesophageal reflux disease (GERD) is a common chronic gastrointestinal disorder that typically requires long-term maintenance therapy. However, little is known about patient preferences and satisfaction and real-world prescription patterns regarding maintenance therapy for GERD. Methods This observational, cross-sectional, multicenter study involved patients from 18 referral hospitals in Korea. We surveyed patients who had been prescribed proton pump inhibitors (PPIs) for GERD for at least 90 days with a minimum follow-up duration of 1 year. The main outcome was overall patient satisfaction with different maintenance therapy modalities. Results A total of 197 patients were enrolled. Overall patient satisfaction, patient preferences, and GERD health-related quality of life scores did not significantly differ among the maintenance therapy modality groups. However, the on-demand therapy group experienced a significantly longer disease duration than the continuous therapy group. The continuous therapy group demonstrated a lower level of awareness of potential adverse effects associated with PPIs than the on-demand therapy group but received higher doses of PPIs than the on-demand therapy group. The prescribed doses of PPIs also varied based on the phenotype of GERD, with higher doses prescribed for non-erosive reflux disease than erosive reflux disease. Conclusion Although overall patient satisfaction did not significantly differ among the different PPI maintenance therapy modality groups, awareness of potential adverse effects was significantly different between the on-demand and continuous therapy groups

An incremental approach to automated protein localisation

Tscherepanow M, Jensen N, Kummert F. An incremental approach to automated protein localisation. BMC Bioinformatics. 2008;9(1): 445.Background: The subcellular localisation of proteins in intact living cells is an important means for gaining information about protein functions. Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. Besides increasing our knowledge about intracellular processes, this information facilitates the development of innovative therapies and new diagnostic methods. In order to perform such a localisation, the proteins under analysis are usually fused with a fluorescent protein. So, they can be observed by means of a fluorescence microscope and analysed. In recent years, several automated methods have been proposed for performing such analyses. Here, two different types of approaches can be distinguished: techniques which enable the recognition of a fixed set of protein locations and methods that identify new ones. To our knowledge, a combination of both approaches – i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations afterwards – has not been presented yet. Furthermore, associated problems, e.g. the recognition of cells to be analysed, have usually been neglected. Results: We introduce a novel approach to automated protein localisation in living cells. In contrast to well-known techniques, the protein localisation technique presented in this article aims at combining the two types of approaches described above: After an automatic identification of unknown protein locations, a potential user is enabled to incorporate them into the pre-trained system. An incremental neural network allows the classification of a fixed set of protein location as well as the detection, clustering and incorporation of additional patterns that occur during an experiment. Here, the proposed technique achieves promising results with respect to both tasks. In addition, the protein localisation procedure has been adapted to an existing cell recognition approach. Therefore, it is especially well-suited for high-throughput investigations where user interactions have to be avoided. Conclusion: We have shown that several aspects required for developing an automatic protein localisation technique – namely the recognition of cells, the classification of protein distribution patterns into a set of learnt protein locations, and the detection and learning of new locations – can be combined successfully. So, the proposed method constitutes a crucial step to render image-based protein localisation techniques amenable to large-scale experiments

On-demand Versus Continuous Maintenance Treatment With a Proton Pump Inhibitor for Mild Gastroesophageal Reflux Disease: A Prospective Randomized Multicenter Study

Background/aims: It remains unclear which maintenance treatment modality is most appropriate for mild gastroesophageal reflux disease (GERD). We aimed to compare on-demand treatment with continuous treatment using a proton pump inhibitor (PPI) in the maintenance treatment for patients with non-erosive GERD or mild erosive esophagitis. Methods: Patients whose GERD symptoms improved after 4 weeks of standard dose PPI treatment were prospectively enrolled at 25 hospitals. Subsequently, the enrolled patients were randomly assigned to either an on-demand or a continuous maintenance treatment group, and followed in an 8-week interval for up to 24 weeks. Results: A total of 304 patients were randomized to maintenance treatment (continuous, n = 151 vs on-demand, n = 153). The primary outcome, the overall proportion of unwillingness to continue the assigned maintenance treatment modality, failed to confirm the non-inferiority of on-demand treatment (45.9%) compared to continuous treatment (36.1%). Compared with the on-demand group, the GERD symptom and health-related quality of life scores significantly more improved and the overall satisfaction score was significantly higher in the continuous treatment group, particularly at week 8 and week 16 of maintenance treatment. Work impairment scores were not different in the 2 groups, but the prescription cost was less in the on-demand group. Serum gastrin levels significantly elevated in the continuous treatment group, but not in the on-demand group. Conclusions: Continuous treatment seems to be more appropriate for the initial maintenance treatment of non-erosive GERD or mild erosive esophagitis than on-demand treatment. Stepping down to on-demand treatment needs to be considered after a sufficient period of continuous treatment

TESTLoc: protein subcellular localization prediction from EST data

Abstract Background The eukaryotic cell has an intricate architecture with compartments and substructures dedicated to particular biological processes. Knowing the subcellular location of proteins not only indicates how bio-processes are organized in different cellular compartments, but also contributes to unravelling the function of individual proteins. Computational localization prediction is possible based on sequence information alone, and has been successfully applied to proteins from virtually all subcellular compartments and all domains of life. However, we realized that current prediction tools do not perform well on partial protein sequences such as those inferred from Expressed Sequence Tag (EST) data, limiting the exploitation of the large and taxonomically most comprehensive body of sequence information from eukaryotes. Results We developed a new predictor, TESTLoc, suited for subcellular localization prediction of proteins based on their partial sequence conceptually translated from ESTs (EST-peptides). Support Vector Machine (SVM) is used as computational method and EST-peptides are represented by different features such as amino acid composition and physicochemical properties. When TESTLoc was applied to the most challenging test case (plant data), it yielded high accuracy (~85%). Conclusions TESTLoc is a localization prediction tool tailored for EST data. It provides a variety of models for the users to choose from, and is available for download at http://megasun.bch.umontreal.ca/~shenyq/TESTLoc/TESTLoc.html</p

Enhanced neuronal Met signalling levels in ALS mice delay disease onset

Signalling by receptor tyrosine kinases (RTKs) coordinates basic cellular processes during development and in adulthood. Whereas aberrant RTK signalling can lead to cancer, reactivation of RTKs is often found following stress or cell damage. This has led to the common belief that RTKs can counteract degenerative processes and so strategies to exploit them for therapy have been extensively explored. An understanding of how RTK stimuli act at cellular levels is needed, however, to evaluate their mechanism of therapeutic action. In this study, we genetically explored the biological and functional significance of enhanced signalling by the Met RTK in neurons, in the context of a neurodegenerative disease. Conditional met-transgenic mice, namely Rosa26LacZ−stop−Met, have been engineered to trigger increased Met signalling in a temporal and tissue-specific regulated manner. Enhancing Met levels in neurons does not affect either motor neuron (MN) development or maintenance. In contrast, increased neuronal Met in amyotrophic lateral sclerosis (ALS) mice prolongs life span, retards MN loss, and ameliorates motor performance, by selectively delaying disease onset. Thus, our studies highlight the properties of RTKs to counteract toxic signals in a disease characterized by dysfunction of multiple cell types by acting in MNs. Moreover, they emphasize the relevance of genetically assessing the effectiveness of agents targeting neurons during ALS evolution