Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning.

Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of parameter settings, the autocorrelation velocimetry methods based on clutter filtering are prone to incorrectly filter out the near-wall blood flow signal, resulting in poor velocimetric accuracy. In addition, the Doppler coherent compounding acts as a low-pass filter, which also leads to low values of blood flow velocity estimated by the above methods. Motivated by this status quo, here we propose a deep learning estimator that combines clutter filtering and blood flow velocimetry based on the adaptive property of one-dimensional convolutional neural network (1DCNN). The estimator is operated by first extracting the blood flow signal from the original Doppler echo signal through an affine transformation of the 1D convolution, and then converting the extracted signal into the desired blood flow velocity using a linear transformation function. The effectiveness of the proposed method is verified by simulation as well as in vivo carotid artery data. Compared with typical velocimetry methods such as high-pass filtering (HPF) and singular value decomposition (SVD), the results show that the normalized root means square error (NRMSE) obtained by 1DCNN is reduced by 54.99 % and 53.50 % for forward blood flow velocimetry, and 70.99 % and 69.50 % for reverse blood flow velocimetry, respectively. Consistently, the in vivo measurements demonstrate that the goodness-of-fit of the proposed estimator is improved by 8.72 % and 4.74 % for five subjects. Moreover, the estimation time consumed by 1DCNN is greatly reduced, which costs only 2.91 % of the time of HPF and 12.83 % of the time of SVD. In conclusion, the proposed estimator is a better alternative to the current blood flow velocimetry, and is capable of providing more accurate diagnosis information for vascular diseases in clinical applications.

Binary Polyamide-Imide Fibrous Superelastic Aerogels for Fire-Retardant and High-Temperature Air Filtration.

Fibrous air filtration materials are highly desirable for particle removal from high-temperature emission sources. However, the existing commercial filter materials suffer from either low filtration efficiency or high pressure drop, due to the difficulty in achieving small fiber diameter and high porosity simultaneously. Herein, we report a facile strategy to fabricate mechanical robust fibrous aerogels by using dual-scale sized PAI/BMI filaments and fibers, which are derived from wet spinning and electrospinning technologies, respectively. The creativity of this design is that PAI/BMI filaments can serve as the enhancing skeleton and PAI/BMI fibers can assemble into high-porosity interconnected networks, enabling the improvement of both mechanical property and air filtration performance. The resultant dual-scale sized PAI/PBMI fibrous aerogels show a compressive stress of 8.36 MPa, a high filtration efficiency of 90.78% (particle diameter of 2.5 µm); for particle diameter over 5 µm, they have 99.99% ultra-high filtration efficiency, a low pressure drop of 20 Pa, and high QF of 0.12 Pa-1, as well as thermostable and fire-retardant properties (thermal decomposition temperature up to 342.7 °C). The successive fabrication of this material is of great significance for the govern of industrial dust.

Correction: Altered gut metabolome contributes to depression-like behaviors in rats exposed to chronic unpredictable mild stress.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An integrated assessment and spatial-temporal variation analysis of neonicotinoids in pollen and honey from noncrop plants in Zhejiang, China.

Recent studies have shown that neonicotinoids in pollen and honey (collected by honeybees) are likely to pose risks to honeybees. However, data on the integrated residue and spatial-temporal variation of neonicotinoids from noncrop plants, the principle sources of pollen for honey bees, are very limited, especially in China. In this study, we employed a novel assessment method based on the relative potency factor to calculate the integrated residue of seven neonicotinoids in pollen and honey samples collected from noncrop plants in 12 stations of Zhejiang province in three consecutive months. The integrated concentration of neonicotinoids (IMIRPF) ranged from no detected (ND) to 34.93 ng/g in pollen and ND to 8.51 ng/g in honey. Acetamiprid showed the highest detection frequency of 41.7%, followed by clothianidin (33.3%) and dinotefuran (22.2%). The highest IMIRPF occurred in April for stations in the fringe areas of Zhejiang province, whereas for stations in the central areas of Zhejiang province, the IMIRPF in May was relatively higher than the other two months. In terms of spatial change, the pollution variation of pollen samples in Lin'an-Tonglu-Pujiang was relative highly polluted-lightly polluted-highly polluted. For honey samples, spatial variation showed a single trend, and peak values were found in Wenzhou, which may be attributed to the local climate and farming practices. This fundamental information will be helpful to understand the effects of neonicotinoids on honeybees foraging habits.

Altered gut metabolome contributes to depression-like behaviors in rats exposed to chronic unpredictable mild stress.

The gut microbiota has been increasingly correlated with depressive disorder. It was recently shown that the transplantation of the gut microbiota from depressed patients to animals can produce depressive-like behaviors, suggesting that the gut microbiota plays a causal role in the development of depression. In addition, metabolic disorder, which is strongly associated with depression, is exacerbated by changes in the composition of the gut microbiota and is alleviated by treatment with antidepressants. However, the key players and pathways that link the gut microbiota to the pathogenesis of depression remain largely unknown. To evaluate the relationships between depression and metabolic disorders in feces and plasma, we monitored changes in fecal and plasma metabolomes during the development of depressive-like behaviors in rats exposed to chronic unpredictable mild stress (CUMS). In these animals, the fecal metabolome was altered first and subjected to changes in the plasma metabolome. Changes in the abundance of fecal metabolites were associated with depressive-like behaviors and with altered levels of neurotransmitters in the hippocampus. Furthermore, the analysis of the fecal metabolome and the fecal microbiota in CUMS rats demonstrated consistent changes in the levels of several amino acids, including L-threonine, isoleucine, alanine, serine, tyrosine, and oxidized proline. Finally, we observed significant correlations between these amino acids and the altered fecal microbiota. The results of this study suggest that changes in amino acid metabolism by the gut microbiota contribute to changes in circulating amino acids and are associated with the behavior indices of depression.

HiTAD: detecting the structural and functional hierarchies of topologically associating domains from chromatin interactions.

A current question in the high-order organization of chromatin is whether topologically associating domains (TADs) are distinct from other hierarchical chromatin domains. However, due to the unclear TAD definition in tradition, the structural and functional uniqueness of TAD is not well studied. In this work, we refined TAD definition by further constraining TADs to the optimal separation on global intra-chromosomal interactions. Inspired by this constraint, we developed a novel method, called HiTAD, to detect hierarchical TADs from Hi-C chromatin interactions. HiTAD performs well in domain sensitivity, replicate reproducibility and inter cell-type conservation. With a novel domain-based alignment proposed by us, we defined several types of hierarchical TAD changes which were not systematically studied previously, and subsequently used them to reveal that TADs and sub-TADs differed statistically in correlating chromosomal compartment, replication timing and gene transcription. Finally, our work also has the implication that the refinement of TAD definition could be achieved by only utilizing chromatin interactions, at least in part. HiTAD is freely available online.

Fast solution-combustion synthesis of nitrogen-modified Li4Ti5O12 nanomaterials with improved electrochemical performance.

A series of nitrogen-modified Li4Ti5O12 (N-LTO) nanomaterials with hierarchical micro/nanoporous structures are first synthesized via a facile one-step combustion process using thermal decomposition of urea. Successful deposition of a TiN thin layer onto the LTO surface was confirmed by transmission electron microscopy with energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy, Raman spectroscopy, and thermogravimetric measurements. The electrochemical performances of the N-LTO nanomaterials are also investigated in this work. Compared with pristine LTO, the N-LTO nanomaterial with 1.1 wt % nitrogen exhibits a higher rate capability and better reversibility. At charge/discharge rates of 1, 2, 8, and 15 C, the discharge capacities of the N-LTO electrode were 159, 150, 128, and 108 mAh g(-1), respectively. After 200 cycles at 1 C, its capacity retention was 98.5% with almost no capacity fading.

Raising the cycling stability of aqueous lithium-ion batteries by eliminating oxygen in the electrolyte.

Aqueous lithium-ion batteries may solve the safety problem associated with lithium-ion batteries that use highly toxic and flammable organic solvents, and the poor cycling life associated with commercialized aqueous rechargeable batteries such as lead-acid and nickel-metal hydride systems. But all reported aqueous lithium-ion battery systems have shown poor stability: the capacity retention is typically less than 50% after 100 cycles. Here, the stability of electrode materials in an aqueous electrolyte was extensively analysed. The negative electrodes of aqueous lithium-ion batteries in a discharged state can react with water and oxygen, resulting in capacity fading upon cycling. By eliminating oxygen, adjusting the pH values of the electrolyte and using carbon-coated electrode materials, LiTi(2)(PO(4))(3)/Li(2)SO(4)/LiFePO(4) aqueous lithium-ion batteries exhibited excellent stability with capacity retention over 90% after 1,000 cycles when being fully charged/discharged in 10 minutes and 85% after 50 cycles even at a very low current rate of 8 hours for a full charge/discharge offering an energy storage system with high safety, low cost, long cycling life and appropriate energy density.