Nitrogen-vacancy (NV) centers in diamond are appealing nanoscale quantum sensors for temperature, strain, electric fields, and, most notably, magnetic fields. However, the cryogenic temperatures ...required for low-noise single-shot readout that have enabled the most sensitive NV magnetometry reported to date are impractical for key applications, e.g., biological sensing. Overcoming the noisy readout at room temperature has until now demanded the repeated collection of fluorescent photons, which increases the time cost of the procedure, thus reducing its sensitivity. Here, we show how machine learning can process the noisy readout of a single NV center at room temperature, requiring on average only one photon per algorithm step, to sense magnetic-field strength with a precision comparable to those reported for cryogenic experiments. Analyzing large datasets from NV centers in bulk diamond, we report absolute sensitivities of60nTs1/2including initialization, readout, and computational overheads. We show that dephasing times can be simultaneously estimated and that time-dependent fields can be dynamically tracked at room temperature. Our results dramatically increase the practicality of early-term single-spin sensors.
Summary
The disease burden of hepatitis C virus (HCV) is expected to increase as the infected population ages. A modelling approach was used to estimate the total number of viremic infections, ...diagnosed, treated and new infections in 2013. In addition, the model was used to estimate the change in the total number of HCV infections, the disease progression and mortality in 2013–2030. Finally, expert panel consensus was used to capture current treatment practices in each country. Using today's treatment paradigm, the total number of HCV infections is projected to decline or remain flat in all countries studied. However, in the same time period, the number of individuals with late‐stage liver disease is projected to increase. This study concluded that the current treatment rate and efficacy are not sufficient to manage the disease burden of HCV. Thus, alternative strategies are required to keep the number of HCV individuals with advanced liver disease and liver‐related deaths from increasing.
CONTEXTSulphur is one of the most abundant elements in the Universe. Surprisingly, sulphuretted molecules are not as abundant as expected in the interstellar medium and the identity of the main ...sulphur reservoir is still an open question.AIMSOur goal is to investigate the H2S chemistry in dark clouds, as this stable molecule is a potential sulphur reservoir.METHODSUsing millimeter observations of CS, SO, H2S, and their isotopologues, we determine the physical conditions and H2S abundances along the cores TMC 1-C, TMC 1-CP, and Barnard 1b. The gas-grain model Nautilus is used to model the sulphur chemistry and explore the impact of photo-desorption and chemical desorption on the H2S abundance.RESULTSOur modeling shows that chemical desorption is the main source of gas-phase H2S in dark cores. The measured H2S abundance can only be fitted if we assume that the chemical desorption rate decreases by more than a factor of 10 when n H > 2 × 104. This change in the desorption rate is consistent with the formation of thick H2O and CO ice mantles on grain surfaces. The observed SO and H2S abundances are in good agreement with our predictions adopting an undepleted value of the sulphur abundance. However, the CS abundance is overestimated by a factor of 5 - 10. Along the three cores, atomic S is predicted to be the main sulphur reservoir.CONCLUSIONSThe gaseous H2S abundance is well reproduced, assuming undepleted sulphur abundance and chemical desorption as the main source of H2S. The behavior of the observed H2S abundance suggests a changing desorption efficiency, which would probe the snowline in these cold cores. Our model, however, highly overestimates the observed gas-phase CS abundance. Given the uncertainty in the sulphur chemistry, we can only conclude that our data are consistent with a cosmic elemental S abundance with an uncertainty of a factor of 10.
While molecular subgrouping has revolutionized medulloblastoma classification, the extent of heterogeneity within subgroups is unknown. Similarity network fusion (SNF) applied to genome-wide DNA ...methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes. After integration of somatic copy-number alterations, and clinical features specific to each cluster, we identify 12 different subtypes of medulloblastoma. Integrative analysis using SNF further delineates group 3 from group 4 medulloblastoma, which is not as readily apparent through analyses of individual data types. Two clear subtypes of infants with Sonic Hedgehog medulloblastoma with disparate outcomes and biology are identified. Medulloblastoma subtypes identified through integrative clustering have important implications for stratification of future clinical trials.
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•Medulloblastoma comprises 12 subtypes; 2 WNT, 4 SHH, 3 group 3, and 3 group 4 groups•Heterogeneity within subgroups accounts for previously unexplained variation•Groups 3 and 4 medulloblastoma are molecularly distinct entities•Clinically and biologically relevant subtypes exist for each subgroup
Cavalli et al. analyze 763 primary medulloblastoma samples using the similarity network fusion approach. They identify subtypes that have distinct somatic copy-number aberrations, activated pathways, and clinical outcomes within each of the four known subgroups and further delineate group 3 from group 4 MB.
Patients with schizophrenia have patterns of brain deficits including reduced cortical thickness, subcortical gray matter volumes, and cerebral white matter integrity. We proposed the regional ...vulnerability index (RVI) to translate the results of Enhancing Neuro Imaging Genetics Meta‐Analysis studies to the individual level. We calculated RVIs for cortical, subcortical, and white matter measurements and a multimodality RVI. We evaluated RVI as a measure sensitive to schizophrenia‐specific neuroanatomical deficits and symptoms and studied the timeline of deficit formations in: early (≤5 years since diagnosis, N = 45, age = 28.8 ± 8.5); intermediate (6–20 years, N = 30, age 43.3 ± 8.6); and chronic (21+ years, N = 44, age = 52.5 ± 5.2) patients and healthy controls (N = 76, age = 38.6 ± 12.4). All RVIs were significantly elevated in patients compared to controls, with the multimodal RVI showing the largest effect size, followed by cortical, white matter and subcortical RVIs (d = 1.57, 1.23, 1.09, and 0.61, all p < 10−6). Multimodal RVI was significantly correlated with multiple cognitive variables including measures of visual learning, working memory and the total score of the MATRICS consensus cognitive battery, and with negative symptoms. The multimodality and white matter RVIs were significantly elevated in the intermediate and chronic versus early diagnosis group, consistent with ongoing progression. Cortical RVI was stable in the three disease‐duration groups, suggesting neurodevelopmental origins of cortical deficits. In summary, neuroanatomical deficits in schizophrenia affect the entire brain; the heterochronicity of their appearance indicates both the neurodevelopmental and progressive nature of this illness. These deficit patterns may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter these neuroanatomical deficit patterns.
We developed the regional vulnerability index (RVI) to quantify individual similarity to the expected schizophrenia deficits patterns derived from large‐scale meta‐analyses performed by Enhancing Neuro Imaging Genetics Meta‐Analysis (ENIGMA) consortium. RVIs for cortical, subcortical, and white matter measurements and a cross‐modality RVI showed significant association with illness duration, cognitive deficits and symptoms. The similarity to expected disorder patterns captured by RVI may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter the formation of neuroanatomical deficits.
Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast doubt on its ...practicability for near-term, nonfault tolerant, quantum devices. Here we report experimental results demonstrating that this intuition need not be true. We implement a recently proposed adaptive Bayesian approach to quantum phase estimation and use it to simulate molecular energies on a silicon quantum photonic device. The approach is verified to be well suited for prethreshold quantum processors by investigating its superior robustness to noise and decoherence compared to the iterative phase estimation algorithm. This shows a promising route to unlock the power of quantum phase estimation much sooner than previously believed.
This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA ...(Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder‐related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.
With the advent of wireless sensors, there has been an increasing amount of research in the area of energy harvesting, particularly from vibration, to power these devices. An interesting application ...is the possibility of harvesting energy from the track-side vibration due to a passing train, as this energy could be used to power remote sensors mounted on the track for strutural health monitoring, for example. This paper describes a fundamental study to determine how much energy could be harvested from a passing train. Using a time history of vertical vibration measured on a sleeper, the optimum mechanical parameters of a linear energy harvesting device are determined. Numerical and analytical investigations are both carried out. It is found that the optimum amount of energy harvested per unit mass is proportional to the product of the square of the input acceleration amplitude and the square of the input duration. For the specific case studied, it was found that the maximum energy that could be harvested per unit mass of the oscillator is about 0.25J/kg at a frequency of about 17Hz. The damping ratio for the optimum harvester was found to be about 0.0045, and the corresponding amplitude of the relative displacement of the mass is approximately 5mm.
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•A fundamental investigation into the energy harvested from a train-induced vibration.•Excitation is time-limited so the transient in the induced vibration is important.•Simple expressions are derived and a strategy is proposed to optimize the harvester.•For the specific case, a maximum energy of 0.25J/kg can be harvested at 17Hz.
Altered structural brain asymmetry in autism spectrum disorder (ASD) has been reported. However, findings have been inconsistent, likely due to limited sample sizes. Here we investigated 1,774 ...individuals with ASD and 1,809 controls, from 54 independent data sets of the ENIGMA consortium. ASD was significantly associated with alterations of cortical thickness asymmetry in mostly medial frontal, orbitofrontal, cingulate and inferior temporal areas, and also with asymmetry of orbitofrontal surface area. These differences generally involved reduced asymmetry in individuals with ASD compared to controls. Furthermore, putamen volume asymmetry was significantly increased in ASD. The largest case-control effect size was Cohen's d = -0.13, for asymmetry of superior frontal cortical thickness. Most effects did not depend on age, sex, IQ, severity or medication use. Altered lateralized neurodevelopment may therefore be a feature of ASD, affecting widespread brain regions with diverse functions. Large-scale analysis was necessary to quantify subtle alterations of brain structural asymmetry in ASD.
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