11 research outputs found
Transcriptome analysis reveals dynamic changes in coxsackievirus A16 infected HEK 293T cells
Individual Differences in Holistic Processing Predict Face Recognition Ability
Why do some people recognize faces easily and others frequently make mistakes in recognizing faces? Classic behavioral work has shown that faces are processed in a distinctive holistic manner that is unlike the processing of objects. In the study reported here, we investigated whether individual differences in holistic face processing have a significant influence on face recognition. We found that the magnitude of face-specific recognition accuracy correlated with the extent to which participants processed faces holistically, as indexed by the composite-face effect and the whole-part effect. This association is due to face-specific processing in particular, not to a more general aspect of cognitive processing, such as general intelligence or global attention. This finding provides constraints on computational models of face recognition and may elucidate mechanisms underlying cognitive disorders, such as prosopagnosia and autism, that are associated with deficits in face recognition
Expression of manB Gene from Escherichia coli in Lactococcus lactis and Characterization of Its Bifunctional Enzyme, Phosphomannomutase
Variable density points pressure sensor with wide sensing range and spatial pressure mapping
Wearable flexible pressure sensors are a novel class of human activity detection device. However, the preparation of pressure sensors with high sensitivity and wide sensing range still faces great challenges. This study reveals an flexible heat-resistant variable density point pressure sensing array (PSA) with ultra-wide sensing range based on Ti3C2Tx-MXene. MXene containing polar oxygen-containing functional groups coated polyester fiber fabricated the pressure sensing layer while a stainless steel wire core is used as a flexible electrode for signal collection. The signal processing device rapidly converts the mechanical signal into electrical signal output to increase the transmission speed and range. Experimental results show that the PSA can effectively sense dynamic and static pressures with high sensitivity (0.14–0.87 kPa−1 over a pressure range of 7.2 Pa–2000 kPa), a wide sensing range (0–15000 kPa), fast response time (80 ms), 10,000 cycles (2000 kPa) stability and maintains a 81.25% current response. The noval fully woven structural flexible PSA exhibited larger area, of which the weave density is varied to control resolution and the pressure mapping is referenced to each pixel point to qualitatively and quantitatively analyze shape and pressure distribution. Variable density points pressure sensor with wide sensing range and spatial pressure mappinghas promising applications in healthcare
Extraction, Isolation and Identification of Low Molecular Weight Peptides in Human Milk
Human milk contains numerous free low molecular weight peptides (LMWPs), which may play an important role in infant health and growth. The bioactivities of LMWPs are determined by their structures, especially the amino acid sequences. In the present study, 81 human milk samples were collected and purified by cation-exchange solid-phase extraction (SPE). Ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used for the separation and detection of free LMWPs in human milk. A total of 56 LMWPs were identified and quantified. These LMWPs were mainly derived from 3 regions of β-casein, which were the amino acid fragments of 16–40, 85–110, and 205–226. The predominant LMWPs were RETIESLSSSEESITEYK, RETIESLSSSEESITEYKQKVEKVK, ETIESLSSSEESITEYK, TQPLAPVHNPIS, and QPLAPVHNPISV with molecular weights of 2247.9573, 2860.2437, 2091.8591, 1372.7666, and 1271.7212, respectively. The results indicated that the technique based on SPE and UPLC-QTOF-MS might greatly facilitate the analysis of LMWPs in human milk
Individual Differences in Holistic Processing Predict Face Recognition Ability
Why do some people recognize faces easily and others frequently make mistakes in recognizing faces? Classic behavioral work has shown that faces are processed in a distinctive holistic manner that is unlike the processing of objects. In the study reported here, we investigated whether individual differences in holistic face processing have a significant influence on face recognition. We found that the magnitude of face-specific recognition accuracy correlated with the extent to which participants processed faces holistically, as indexed by the composite-face effect and the whole-part effect. This association is due to face-specific processing in particular, not to a more general aspect of cognitive processing, such as general intelligence or global attention. This finding provides constraints on computational models of face recognition and may elucidate mechanisms underlying cognitive disorders, such as prosopagnosia and autism, that are associated with deficits in face recognition
Improving the enzyme property of ornithine transcarbamylase from Lactobacillus brevis through site-directed mutation
Additional file 1: of Transcriptome analysis reveals dynamic changes in coxsackievirus A16 infected HEK 293T cells
RNA-Seq saturation curves. The horizontal axis represents number of reads. The left vertical axis represents the number of genes, and the right vertical axis represents the correlation coefficient. Saturation test results showed that the sequencing data were sufficient for analysis of differences in gene expression. (PPTX 49 kb
Observed changes in China's methane emissions linked to policy drivers.
China is set to actively reduce its methane emissions in the coming decade. A comprehensive evaluation of the current situation can provide a reference point for tracking the country's future progress. Here, using satellite and surface observations, we quantify China's methane emissions during 2010-2017. Including newly available data from a surface network across China greatly improves our ability to constrain emissions at subnational and sectoral levels. Our results show that recent changes in China's methane emissions are linked to energy, agricultural, and environmental policies. We find contrasting methane emission trends in different regions attributed to coal mining, reflecting region-dependent responses to China's energy policy of closing small coal mines (decreases in Southwest) and consolidating large coal mines (increases in North). Coordinated production of coalbed methane and coal in southern Shanxi effectively decreases methane emissions, despite increased coal production there. We also detect unexpected increases from rice cultivation over East and Central China, which is contributed by enhanced rates of crop-residue application, a factor not accounted for in current inventories. Our work identifies policy drivers of recent changes in China's methane emissions, providing input to formulating methane policy toward its climate goal