New type of microengine using internal combustion of hydrogen and oxygen

Microsystems become part of everyday life but their application is restricted by lack of strong and fast motors (actuators) converting energy into motion. For example, widespread internal combustion engines cannot be scaled down because combustion reactions are quenched in a small space. Here we present an actuator with the dimensions 100x100x5 um^3 that is using internal combustion of hydrogen and oxygen as part of its working cycle. Water electrolysis driven by short voltage pulses creates an extra pressure of 0.5-4 bar for a time of 100-400 us in a chamber closed by a flexible membrane. When the pulses are switched off this pressure is released even faster allowing production of mechanical work in short cycles. We provide arguments that this unexpectedly fast pressure decrease is due to spontaneous combustion of the gases in the chamber. This actuator is the first step to truly microscopic combustion engines.Comment: Paper and Supplementary Information (to appear in Scientific Reports

Two-dimensional amine and hydroxy functionalized fused aromatic covalent organic framework

Ordered two-dimensional covalent organic frameworks (COFs) have generally been synthesized using reversible reactions. It has been difficult to synthesize a similar degree of ordered COFs using irreversible reactions. Developing COFs with a fused aromatic ring system via an irreversible reaction is highly desirable but has remained a significant challenge. Here we demonstrate a COF that can be synthesized from organic building blocks via irreversible condensation (aromatization). The as-synthesized robust fused aromatic COF (F-COF) exhibits high crystallinity. Its lattice structure is characterized by scanning tunneling microscopy and X-ray diffraction pattern. Because of its fused aromatic ring system, the F-COF structure possesses high physiochemical stability, due to the absence of hydrolysable weak covalent bonds

Homonymous Quadrantanopsia as the First Manifestation of Cerebral Metastasis of Invasive Mole: a case report

<p>Abstract</p> <p>Introduction</p> <p>Homonymous quadrantanopsia results from retrochiasmal lesions in the visual pathway. Invasive mole is a benign tumor that arises from myometrial invasion of a hydatidiform mole via direct extension through tissue or venous channels. Cerebral metastasis of invasive mole is rare and there has been no report demonstrating homonymous quadrantanopsia as the first manifestation of metastasis in any trophoblastic neoplasms.</p> <p>Case presentation</p> <p>We report the case of a 31-year-old Asian woman who presented with right homonymous inferior quadrantanopsia from the mass effect of a solitary cerebral metastasis from an invasive mole. A magnetic resonance image (MRI) of the brain showed a metastatic tumor in the left occipital lobe. The visual field improved slightly after chemotherapy. There was a reduction in the tumor size and the surrounding edema. This is the first case report demonstrating that homonymous quadrantanopsia should be included in the manifestations of the metastasis of an invasive mole.</p> <p>Conclusions</p> <p>The presentation of homonymous quadrantanopsia must alert ophthalmologists to conduct a complete medical history and arrange specialist consultation.</p

Basal Ganglia Pathways Associated With Therapeutic Pallidal Deep Brain Stimulation for Tourette Syndrome

BACKGROUND: Deep brain stimulation (DBS) targeting the globus pallidus internus (GPi) can improve tics and comorbid obsessive-compulsive behavior (OCB) in patients with treatment-refractory Tourette syndrome (TS). However, some patients’ symptoms remain unresponsive, the stimulation applied across patients is variable, and the mechanisms underlying improvement are unclear. Identifying the fiber pathways surrounding the GPi that are associated with improvement could provide mechanistic insight and refine targeting strategies to improve outcomes. METHODS: Retrospective data were collected for 35 patients who underwent bilateral GPi DBS for TS. Computational models of fiber tract activation were constructed using patient-specific lead locations and stimulation settings to evaluate the effects of DBS on basal ganglia pathways and the internal capsule. We first evaluated the relationship between activation of individual pathways and symptom improvement. Next, linear mixed-effects models with combinations of pathways and clinical variables were compared in order to identify the best-fit predictive models of tic and OCB improvement. RESULTS: The best-fit model of tic improvement included baseline severity and the associative pallido-subthalamic pathway. The best-fit model of OCB improvement included baseline severity and the sensorimotor pallidosubthalamic pathway, with substantial evidence also supporting the involvement of the prefrontal, motor, and premotor internal capsule pathways. The best-fit models of tic and OCB improvement predicted outcomes across the cohort and in cross-validation. CONCLUSIONS: Differences in fiber pathway activation likely contribute to variable outcomes of DBS for TS. Computational models of pathway activation could be used to develop novel approaches for preoperative targeting and selecting stimulation parameters to improve patient outcomes

Tuning the binding affinity and selectivity of perfluoroaryl-stapled peptides by cysteine-editing.

A growing number of approaches to 'staple' α-helical peptides into a bioactive conformation using cysteine cross-linking are emerging. Here we explore the replacement of L-cysteine with 'cysteine analogues' in combinations of different stereochemistry, side chain length and beta-carbon substitution, to examine the influence that the thiol-containing residue(s) has on target protein-binding affinity in a well explored model system, p53-MDM2/MDMX. In some cases, replacement of one or more L-cysteine residues afforded significant changes in the measured binding affinity and target selectivity of the peptide. Computationally constructed homology models indicate that some modifications, such as incorporating two D-cysteines favourably alter the positions of key functional amino acid side chains, which is likely to cause changes in binding affinity, in agreement with measured SPR data

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Evidence for validity and reliability of a french version of the FAAM

BACKGROUND: The Foot and Ankle Ability Measure (FAAM) is a self reported questionnaire for patients with foot and ankle disorders available in English, German, and Persian. This study plans to translate the FAAM from English to French (FAAM-F) and assess the validity and reliability of this new version.METHODS: The FAAM-F Activities of Daily Living (ADL) and sports subscales were completed by 105 French-speaking patients (average age 50.5 years) presenting various chronic foot and ankle disorders. Convergent and divergent validity was assessed by Pearson's correlation coefficients between the FAAM-F subscales and the SF-36 scales: Physical Functioning (PF), Physical Component Summary (PCS), Mental Health (MH) and Mental Component Summary (MCS). Internal consistency was calculated by Cronbach's Alpha (CA). To assess test re-test reliability, 22 patients filled out the questionnaire a second time to estimate minimal detectable changes (MDC) and intraclass correlation coefficients (ICC).RESULTS: Correlations for FAAM-F ADL subscale were 0.85 with PF, 0.81 with PCS, 0.26 with MH, 0.37 with MCS. Correlations for FAAM-F Sports subscale were 0.72 with PF, 0.72 with PCS, 0.21 with MH, 0.29 with MCS. CA estimates were 0.97 for both subscales. Respectively for the ADL and Sports subscales, ICC were 0.97 and 0.94, errors for a single measure were 8 and 10 points at 95% confidence and the MDC values at 95% confidence were 7 and 18 points.CONCLUSION: The FAAM-F is valid and reliable for the self-assessment of physical function in French-speaking patients with a wide range of chronic foot and ankle disorders

Projected WIMP sensitivity of the LUX-ZEPLIN dark matter experiment

LUX-ZEPLIN (LZ) is a next-generation dark matter direct detection experiment that will operate 4850 feet underground at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. Using a two-phase xenon detector with an active mass of 7 tonnes, LZ will search primarily for low-energy interactions with weakly interacting massive particles (WIMPs), which are hypothesized to make up the dark matter in our galactic halo. In this paper, the projected WIMP sensitivity of LZ is presented based on the latest background estimates and simulations of the detector. For a 1000 live day run using a 5.6-tonne fiducial mass, LZ is projected to exclude at 90% confidence level spin-independent WIMP-nucleon cross sections above 1.4×10-48 cm2 for a 40 GeV/c2 mass WIMP. Additionally, a 5σ discovery potential is projected, reaching cross sections below the exclusion limits of recent experiments. For spin-dependent WIMP-neutron(-proton) scattering, a sensitivity of 2.3×10-43 cm2 (7.1×10-42 cm2) for a 40 GeV/c2 mass WIMP is expected. With underground installation well underway, LZ is on track for commissioning at SURF in 2020