Application of operando X-ray diffraction and Raman spectroscopies in elucidating the behavior of cathode in lithium-ion batteries

With the advances in characterization techniques, various operando/in-situ methods were applied in studying rechargeable batteries in order to improve the electrochemical properties of electrode materials, prolonging the battery life and developing new battery materials. In the present review, we focus on the characterization of electrode materials with operando/in-situ X-ray diffraction and Raman spectroscopies. By correlating the results obtained via these two techniques in different electrode chemistry: (a) intercalation materials, such as layered metal oxides and (b) conversion materials, such as elemental sulfur. We demonstrate the importance of using operando/in-situ techniques in examining the microstructural changes of the electrodes under various operating conditions, in both macro and micro-scales. These techniques also reveal the working and the degradation mechanisms of the electrodes and the possible side reactions involved. The comprehension of these mechanisms is fundamental for ameliorating the electrode materials, enhancing the battery performance and lengthening its cycling life

Endothelins are vascular-derived axonal guidance cues for developing sympathetic neurons

During development, sympathetic neurons extend axons along a myriad of distinct trajectories, often consisting of arteries, to innervate one of a large variety of distinct final target tissues. Whether or not subsets of neurons within complex sympathetic ganglia are predetermined to innervate select end-organs is unknown. Here we demonstrate in mouse embryos that the endothelin family member Edn3 (ref. 1), acting through the endothelin receptor EdnrA (refs 2, 3), directs extension of axons of a subset of sympathetic neurons from the superior cervical ganglion to a preferred intermediate target, the external carotid artery, which serves as the gateway to select targets, including the salivary glands. These findings establish a previously unknown mechanism of axonal pathfinding involving vascular-derived endothelins, and have broad implications for endothelins as general mediators of axonal growth and guidance in the developing nervous system. Moreover, they suggest a model in which newborn sympathetic neurons distinguish and choose between distinct vascular trajectories to innervate their appropriate end organs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62906/1/nature06859.pd

Somatostatin subtype-2 receptor-targeted metal-based anticancer complexes

Conjugates of a dicarba analogue of octreotide, a potent somatostatin agonist whose receptors are overexpressed on tumor cells, with [PtCl 2(dap)] (dap = 1-(carboxylic acid)-1,2-diaminoethane) (3), [(η 6-bip)Os(4-CO 2-pico)Cl] (bip = biphenyl, pico = picolinate) (4), [(η 6-p-cym)RuCl(dap)] + (p-cym = p-cymene) (5), and [(η 6-p-cym)RuCl(imidazole-CO 2H)(PPh 3)] + (6), were synthesized by using a solid-phase approach. Conjugates 3-5 readily underwent hydrolysis and DNA binding, whereas conjugate 6 was inert to ligand substitution. NMR spectroscopy and molecular dynamics calculations showed that conjugate formation does not perturb the overall peptide structure. Only 6 exhibited antiproliferative activity in human tumor cells (IC 50 = 63 ± 2 μ in MCF-7 cells and IC 50 = 26 ± 3 μ in DU-145 cells) with active participation of somatostatin receptors in cellular uptake. Similar cytotoxic activity was found in a normal cell line (IC 50 = 45 ± 2.6 μ in CHO cells), which can be attributed to a similar level of expression of somatostatin subtype-2 receptor. These studies provide new insights into the effect of receptor-binding peptide conjugation on the activity of metal-based anticancer drugs, and demonstrate the potential of such hybrid compounds to target tumor cells specifically. © 2012 American Chemical Society

A copper diimine‐based honeycomb‐like porous network as an efficient reduction catalyst

Nitrophenols are among the widely used industrial chemicals worldwide; however, their hazardous effects on environment are a major concern nowadays. Therefore, the conversion of environmentally detrimental p‐nitrophenol (PNP) to industrially valuable p‐aminophenol (PAP), a prototype reaction, is an important organic transformation reaction. However, the traditional conversion of PNP to PAP is an expensive and environmentally unfriendly process. Here, we report a honeycomb‐like porous network with zeolite‐like channels formed by the self‐organization of copper, 1,10‐phenanthroline, 4,4′‐bipyridine, and water. This porous network effectively catalyzed the transformation of hazardous PNP to pharmaceutically valued PAP. In the presence of complex, PNP to PAP conversion occurred in a few minutes, which is otherwise a very sluggish process. To assess the kinetics, the catalytic conversion of PNP to PAP was studied at five different temperatures. The linearity of lnCt/Co versus temperature plot indicated pseudo‐first‐order kinetics. The copper complex with zeolite like channels may find applications as a reduction catalyst both on laboratory and industrial scales and in green chemistry for the remediation of pollutants

How Are Adolescents Sleeping? Adolescent Sleep Patterns and Sociodemographic Differences in 24 European and North American Countries.

PURPOSE:Insufficient and poor sleep patterns are common among adolescents worldwide. Up to now, the evidence on adolescent sleep has been mostly informed by country-specific studies that used different measures and age groups, making direct comparisons difficult. Cross-national data on adolescent sleep that could inform nations and international discussions are lacking. We examined the sleep patterns of adolescents across 24 countries and by gender, age, and affluence groups. METHODS:We obtained sleep data on 165,793 adolescents (mean age 13.5 years; 50.5% girls) in 24 European and North American countries from the recent cross-sectional Health Behaviour in School-aged Children surveys (2013-2014 and 2017-2018). For each country, we calculated the age-standardized mean in sleep duration, timing, and consistency and the proportions meeting sleep recommendations on school and nonschool days from self-reported bedtimes and wake times. We conducted stratified analyses by gender, age, and family affluence group. RESULTS:Adolescent sleep patterns varied cross-nationally. The average sleep duration ranged between 7:47 and 9:07 hours on school days and between 9:31 and 10:22 hours on nonschool days, and the proportion of adolescents meeting sleep recommendations ranged between 32% and 86% on school days and between 79% and 92% on nonschool days. Sleep patterns by gender and affluence groups were largely similar, but older adolescents slept less and went to bed later on school days than younger adolescents in all countries. CONCLUSIONS:The sleep patterns of adolescents vary across countries and sociodemographic groups. Insufficient sleep on school days is common in many countries. Public health and policy efforts to promote healthy adolescent sleep are encouraged

Gender differences in the association between adiposity and probable major depression: a cross-sectional study of 140,564 UK Biobank participants

<b>Background</b><p></p> Previous studies on the association between adiposity and mood disorder have produced contradictory results, and few have used measurements other than body mass index (BMI). We examined the association between probable major depression and several measurements of adiposity: BMI, waist circumference (WC), waist-hip-ratio (WHR), and body fat percentage (BF%).<p></p> <b>Methods</b><p></p> We conducted a cross-sectional study using baseline data on the sub-group of UK Biobank participants who were assessed for mood disorder. Multivariate logistic regression models were used, adjusting for potential confounders including: demographic and life-style factors, comorbidity and psychotropic medication.<p></p> <b>Results</b><p></p> Of the 140,564 eligible participants, evidence of probable major depression was reported by 30,145 (21.5%). The fully adjusted odds ratios (OR) for obese participants were 1.16 (95% confidence interval (CI) 1.12, 1.20) using BMI, 1.15 (95% CI 1.11, 1.19) using WC, 1.09 (95% CI 1.05, 1.13) using WHR and 1.18 (95% CI 1.12, 1.25) using BF% (all p <0.001). There was a significant interaction between adiposity and gender (p = 0.001). Overweight women were at increased risk of depression with a dose response relationship across the overweight (25.0-29.9 kg/m2), obese I (30.0-34.9 kg/m2), II (35.0-39.9 kg/m2) and III (≥40.0 kg/m2) categories; fully adjusted ORs 1.14, 1.20, 1.29 and 1.48, respectively (all p < 0.001). In contrast, only obese III men had significantly increased risk of depression (OR 1.29, 95% CI 1.08, 1.54, p = 0.006).<p></p> <b>Conclusion</b><p></p> Adiposity was associated with probable major depression, irrespective of the measurement used. The association was stronger in women than men. Physicians managing overweight and obese women should be alert to this increased risk

Neural network identification of people hidden from view with a single-pixel, single-photon detector

Light scattered from multiple surfaces can be used to retrieve information of hidden environments. However, full three-dimensional retrieval of an object hidden from view by a wall has only been achieved with scanning systems and requires intensive computational processing of the retrieved data. Here we use a non-scanning, single-photon single-pixel detector in combination with a deep convolutional artificial neural network: this allows us to locate the position and to also simultaneously provide the actual identity of a hidden person, chosen from a database of people (N = 3). Artificial neural networks applied to specific computational imaging problems can therefore enable novel imaging capabilities with hugely simplified hardware and processing times

Photon-efficient imaging with a single-photon camera

Reconstructing a scene's 3D structure and reflectivity accurately with an active imaging system operating in low-light-level conditions has wide-ranging applications, spanning biological imaging to remote sensing. Here we propose and experimentally demonstrate a depth and reflectivity imaging system with a single-photon camera that generates high-quality images from ∼1 detected signal photon per pixel. Previous achievements of similar photon efficiency have been with conventional raster-scanning data collection using single-pixel photon counters capable of ∼10-ps time tagging. In contrast, our camera's detector array requires highly parallelized time-to-digital conversions with photon time-tagging accuracy limited to ∼ns. Thus, we develop an array-specific algorithm that converts coarsely time-binned photon detections to highly accurate scene depth and reflectivity by exploiting both the transverse smoothness and longitudinal sparsity of natural scenes. By overcoming the coarse time resolution of the array, our framework uniquely achieves high photon efficiency in a relatively short acquisition time