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Transport in topological matter has shown a variety of novel phenomena over the past decade. Although numerous transport studies have been conducted on three-dimensional topological insulators (TIs), study of ballistic motion and thus exploration of potential landscapes on a hundred nanometer scale is for the prevalent TI materials almost impossible due to their low carrier mobility. Therefore, it is unknown whether helical Dirac electrons in TIs, bound to interfaces between topologically distinct materials, can be manipulated on the nanometer scale by local gates or locally etched regions. Here we impose a submicron periodic potential onto a single surface of Dirac electrons in high-mobility strained mercury telluride (HgTe), which is a strong TI. Pronounced geometric resistance resonances constitute the clear-cut observation of a ballistic effect in three-dimensional TIs. Ballistic motion on nanometer scale of topological surface states has rarely been studied. Here, Maier et al. report pronounced geometric resistance resonances of high-mobility Dirac electrons in strained HgTe, suggesting a ballistic effect in three-dimensional topological insulators.

In the original version of this Article, the second and third sentences of the first paragraph of the “Gate voltage and antidot period dependencies” section of the Results originally incorrectly read “The characteristic evolution of the sheet resistance ρ □ = ρ □ ( B =0) with V g shown for three antidot samples and an unpatterned reference sample in Fig. 3a. The maxima of ρ xx , located between V g ~0.5 and 1 V, reflect the charge neutrality point (CNP), corresponding to an E F position located slightly in the valence band (see band structure in Fig. 3b).” In the corrected version, “ ρ □ = ρ □ ( B = 0 ) ” is replaced by “ ρ □ = ρ xx ( B = 0 ) ”, and “The maxima of ρ xx ” is replaced by “The maxima of ρ □ ”.

To assess the safety and efficacy of changing to the travoprost/timolol fixed combination (TTFC) from other mono- or adjunctive therapies. A prospective, open-label, observational cohort of primary open-angle glaucoma and ocular hypertensive patients whose intraocular pressure (IOP) was uncontrolled on prior therapy or was not on target. Patients were changed from prior mono- or adjunctive treatment at Day 0 to TTFC dosed every evening and underwent active treatment efficacy and safety evaluations at Week 12. In 474/522 (91%) patients who completed this trial an IOP (mm Hg) of 21.9 +/- 2.0 on prior treatment was reduced by TTFC at Month 3: from all prior treatments 5.6 +/- 2.6; from monotherapy 5.9 +/- 2.3; from adjunctive treatments 4.5 +/- 2.9; and from several of the most frequent individual treatments: timolol 5.7 +/- 2.2; latanoprost 6.3 +/- 2.6; and latanoprost/timolol fixed combination 4.4 +/- 1.9. Ocular hyperemia was the most frequent adverse effect (n = 21, 4%). Both patients and physicians preferred TTFC compared to all prior and common individual treatments. The solicited symptom survey showed, following a modified Bonferroni correction (alpha/5), a reduced incidence with TTFC of ocular pain (P = 0.01) while the prior medicine had a lower incidence of burning on instillation (P < 0.001). Changing patients from prior mono- or adjunctive therapy to TTFC can provide on average a further reduction in IOP while demonstrating a favorable safety profile and a high patient preference.

To compare the diurnal intraocular pressure (IOP)-lowering efficacy and safety of travoprost 0.004% and tafluprost 0.0015% administered to patients with primary open-angle glaucoma or ocular hypertension. This was a randomized, double-masked, active-controlled, crossover design trial, in which patients were randomized to either travoprost or tafluprost monotherapy administered once daily in the evening for six weeks and then crossed over to the alternative treatment for another six weeks. Diurnal IOP was measured (8 am to 8 pm, every two hours) and a solicited symptom survey was administered at the end of both six-week periods, as was conjunctival hyperemia and visual acuity assessment, slit-lamp biomicroscopy, and adverse event solicitation. Fifty-one patients were randomized and 48 patients completed the study. The 12-hour mean diurnal IOP was significantly lower with travoprost therapy than with tafluprost therapy (P = 0.01), and a significantly lower IOP was also reported for travoprost at five of the seven individual time points (P < 0.05). Neither therapy produced a significant increase from baseline in any of the individual patient-reported symptom scores, except for hyperemia (P ≤ 0.01), which was increased with both treatments. Investigator-observed hyperemia was also increased from baseline with both therapies (P < 0.01), although the increase with travoprost therapy was significantly smaller than with tafluprost (P < 0.01). No additional safety concerns were noted from slit-lamp biomicroscopy or visual acuity results, and no difference was noted in patient-reported tolerability of the two medications. Travoprost 0.004% monotherapy produced lower diurnal IOP than tafluprost 0.0015% in patients with primary open-angle glaucoma or ocular hypertension and exhibited a similar safety profile.

Transport in topological matter has shown a variety of novel phenomena over the last decade. Although numerous transport studies have been conducted on three-dimensional topological insulators (3D-TIs), study of ballistic motion and thus exploration of potential landscapes on a hundred nanometer scale is for the prevalent TI materials almost impossible due to their low carrier mobility. Therefore it is unknown whether helical Dirac electrons in TIs, bound to interfaces between topologically distinct materials, can be manipulated on the nanometer scale by local gates or locally etched regions. Here we impose a submicron periodic potential onto a single surface of Dirac electrons in high mobility strained mercury telluride (HgTe), which is a strong TI. Pronounced geometric resistance resonances constitute the first observation of a ballistic effect in 3D-TIs.

Nanowires with helical surface states represent key prerequisites for observing and exploiting phase-coherent topological conductance phenomena, such as spin-momentum locked quantum transport or topological superconductivity. We demonstrate in a joint experimental and theoretical study that gated nanowires fabricated from high-mobility strained HgTe, known as a bulk topological insulator, indeed preserve the topological nature of the surface states, that moreover extend phase-coherently across the entire wire geometry. The phase-coherence lengths are enhanced up to 5 \\(\\)m when tuning the wires into the bulk gap, so as to single out topological transport. The nanowires exhibit distinct conductance oscillations, both as a function of the flux due to an axial magnetic field, and of a gate voltage. The observed \\(h/e\\)-periodic Aharonov-Bohm-type modulations indicate surface-mediated quasi-ballistic transport. Furthermore, an in-depth analysis of the scaling of the observed gate-dependent conductance oscillations reveals the topological nature of these surface states. To this end we combined numerical tight-binding calculations of the quantum magneto-conductance with simulations of the electrostatics, accounting for the gate-induced inhomogenous charge carrier densities around the wires. We find that helical transport prevails even for strongly inhomogenous gating and is governed by flux-sensitive high-angular momentum surface states that extend around the entire wire circumference.

Brain extraction from magnetic resonance imaging (MRI) is crucial for many neuroimaging workflows. Current methods demonstrate good results on non-enhanced T1-weighted images, but struggle when confronted with other modalities and pathologically altered tissue. In this paper we present a 3D convolutional deep learning architecture to address these shortcomings. In contrast to existing methods, we are not limited to non-enhanced T1w images. When trained appropriately, our approach handles an arbitrary number of modalities including contrast-enhanced scans. Its applicability to MRI data, comprising four channels: non-enhanced and contrast-enhanced T1w, T2w and FLAIR contrasts, is demonstrated on a challenging clinical data set containing brain tumors (N=53), where our approach significantly outperforms six commonly used tools with a mean Dice score of 95.19. Further, the proposed method at least matches state-of-the-art performance as demonstrated on three publicly available data sets: IBSR, LPBA40 and OASIS, totaling N=135 volumes. For the IBSR (96.32) and LPBA40 (96.96) data set the convolutional neuronal network (CNN) obtains the highest average Dice scores, albeit not being significantly different from the second best performing method. For the OASIS data the second best Dice (95.02) results are achieved, with no statistical difference in comparison to the best performing tool. For all data sets the highest average specificity measures are evaluated, whereas the sensitivity displays about average results. Adjusting the cut-off threshold for generating the binary masks from the CNN's probability output can be used to increase the sensitivity of the method. Of course, this comes at the cost of a decreased specificity and has to be decided application specific. Using an optimized GPU implementation predictions can be achieved in less than one minute. The proposed method may prove useful for large-scale studies and clinical trials. •Fast Deep Learning architecture for brain extraction in MRI images•Trained appropriately, it handles multi-modal MRI data including contrast-enhanced scans.•Matches at least state-of-the-art performance on publicly available data sets•Superior performance for a multi-modal clinical data set of brain tumors

Opioid use for pain management has dramatically increased, with little assessment of potential pathophysiological consequences for the primary pain condition. Here, a short course of morphine, starting 10 d after injury in male rats, paradoxically and remarkably doubled the duration of chronic constriction injury (CCI)-allodynia, months after morphine ceased. No such effect of opioids on neuropathic pain has previously been reported. Using pharmacologic and genetic approaches, we discovered that the initiation and maintenance of this multimonth prolongation of neuropathic pain was mediated by a previously unidentified mechanism for spinal cord and pain—namely, morphine-induced spinal NOD-like receptor protein 3 (NLRP3) inflammasomes and associated release of interleukin-1β (IL-1β). As spinal dorsal horn microglia expressed this signaling platform, these cells were selectively inhibited in vivo after transfection with a novel Designer Receptor Exclusively Activated by Designer Drugs (DREADD). Multiday treatment with the DREADD-specific ligand clozapine-N-oxide prevented and enduringly reversed morphine-induced persistent sensitization for weeks to months after cessation of clozapine-N-oxide. These data demonstrate both the critical importance of microglia and that maintenance of chronic pain created by early exposure to opioids can be disrupted, resetting pain to normal. These data also provide strong support for the recent “two-hit hypothesis” of microglial priming, leading to exaggerated reactivity after the second challenge, documented here in the context of nerve injury followed by morphine. This study predicts that prolonged pain is an unrealized and clinically concerning consequence of the abundant use of opioids in chronic pain.

Almost any warm-blooded creature can be an intermediate host for Toxoplasma gondii . However, sexual reproduction of T . gondii occurs only in felids, wherein fertilisation of haploid macrogametes by haploid microgametes, results in diploid zygotes, around which a protective wall develops, forming unsporulated oocysts. Unsporulated oocysts are shed in the faeces of cats and meiosis gives rise to haploid sporozoites within the oocysts. These, now infectious, sporulated oocysts contaminate the environment as a source of infection for people and their livestock. RNA-Seq analysis of cat enteric stages of T . gondii uncovered genes expressed uniquely in microgametes and macrogametes. A CRISPR/Cas9 strategy was used to create a T . gondii strain that exhibits defective fertilisation, decreased fecundity and generates oocysts that fail to produce sporozoites. Inoculation of cats with this engineered parasite strain totally prevented oocyst excretion following infection with wild-type T . gondii , demonstrating that this mutant is an attenuated, live, transmission-blocking vaccine.

Health nudge interventions to steer people into healthier lifestyles are increasingly applied by governments worldwide, and it is natural to look to such approaches to improve health by altering what people choose to eat. However, to produce policy recommendations that are likely to be effective, we need to be able to make valid predictions about the consequences of proposed interventions, and for this, we need a better understanding of the determinants of food choice. These determinants include dietary components (e.g. highly palatable foods and alcohol), but also diverse cultural and social pressures, cognitive-affective factors (perceived stress, health attitude, anxiety and depression), and familial, genetic and epigenetic influences on personality characteristics. In addition, our choices are influenced by an array of physiological mechanisms, including signals to the brain from the gastrointestinal tract and adipose tissue, which affect not only our hunger and satiety but also our motivation to eat particular nutrients, and the reward we experience from eating. Thus, to develop the evidence base necessary for effective policies, we need to build bridges across different levels of knowledge and understanding. This requires experimental models that can fill in the gaps in our understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that encapsulate scientific knowledge from diverse disciplines, and which embed understanding in a way that enables policy-relevant predictions to be made. Here we review recent developments in these areas.