Flexible neural probes have been pursued previously to minimize the mechanical mismatch between soft neural tissues and implants and thereby improve long-term performance. However, difficulties with insertion of such probes deep into the brain severely restricts their utility. We describe a solution to this problem using gallium (Ga) in probe construction, taking advantage of the solid-to-liquid phase change of the metal at body temperature and probe shape deformation to provide temperature-dependent control of stiffness over 5 orders of magnitude. Probes in the stiff state were successfully inserted 2 cm-deep into agarose gel "brain phantoms" and into rat brains under cooled conditions where, upon Ga melting, they became ultra soft, flexible, and stretchable *

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 (Mus musculus), Rat1 (Rattus norvegicus), Zebrafish1 (Danio rerio), Fruitfly1 (Drosophila melanogaster), and Worm1 (Caenorhabditis elegans). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer’s disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications.

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BackgroundGlobally, the World Health Organization reports that the chances of a child dying is highest in the first month of life, the neonatal period. The neonatal mortality rate in Cambodia is 18 per 1000 live births. In the province of Kampong Chhnang, that rate is the fifth highest among the 24 provinces of Cambodia at 27 per 1000 live births. We piloted a project to determine the feasibility of using a mHealth intervention (the use of mobile devices to improve health outcomes) to increase mothers’ awareness about neonatal care and promote the government policy ‘Safe Motherhood Protocols for Health Centres’ which are in line with WHO recommendations for neonatal care.MethodsBetween September and December 2013, we piloted an Interactive Voice Response system that sent pre-recorded messages to mothers of newborns using the theme ‘It takes a village to raise a baby’. Four hundred fifty-five mothers were registered onto this program and the intervention involved delivering seven periodic 60 to 90 s voice messages directly to the mobile phones of these mothers from day three of their neonate’s life to day 28. An evaluation of the pilot was conducted in December 2013. One hundred twenty-nine mothers were randomly selected from the 455 registered mothers and interviewed using a quantitative questionnaire. We also held two focus group discussions with three mothers and seven health workers.ResultsQuantitative and qualitative results of 126 respondents were included for analysis. They indicate that the intervention was well accepted. Seventy-one percent of respondents reported that they would recommend the intervention to other mothers, and 83% reported that they would be willing to pay for the service.ConclusionsThis type of mHealth intervention is an acceptable and feasible way of promoting the awareness of newborn care to rural Cambodian mothers.

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Caregivers generally understand the value of day care but several factors tip the balance in favor of non-use. These include culturally bound caregiving values and perceptions, and inadequacies in service delivery. Negative perceptions about services highlight the need to enhance the image and standards of day care and increase awareness of the benefits of day care for PWD beyond its custodial role.

Blood analysis is an indispensable means of detection in criminal investigation, customs security and quarantine, anti-poaching of wildlife, and other incidents. Detecting the species of blood is one of the most important analyses. In order to classify species by analyzing Raman spectra of blood, a recognition method based on deep learning principle is proposed in this paper. This method can realize multi-identification blood species, by constructing a onedimensional convolution neural network and establishing a Raman spectra database containing 20 kinds of blood. The network model is obtained through training, and then is employed to predict the testing set data. The average accuracy of blind detection is more than 97%. In this paper, we try to increase the diversity of data to improve the robustness of the model, optimize the network and adjust the hyperparameters to improve the recognition ability of the model. The evaluation results show that the deep learning model has high recognition performance to distinguish the species of blood.

PDMS thin-film transfer and enzyme microstamping enabled 3-in-1 Si/PDMS hybrid chemtrode for multi-analyte sensing and chemical delivery in vivo.