It is remarkably desirable and challenging to design a stretchable conductive material with tunable electromagnetic‐interference (EMI) shielding and heat transfer for applications in flexible electronics. However, the existing materials sustained a severe attenuation of performances when largely stretched. Here, a super‐stretchable (800% strain) liquid metal foamed elastomer composite (LMF‐EC) is reported, achieving super‐high electrical (≈104 S cm−1) and thermal (17.6 W mK−1) conductivities under a large strain of 400%, which also exhibits unexpected stretching‐enhanced EMI shielding effectiveness of 85 dB due to the conductive network elongation and reorientation. By varying the liquid and solid states of LMF, the stretching can enable a multifunctional reversible switch that simultaneously regulates the thermal, electrical, and electromagnetic wave transport. Novel flexible temperature control and a thermoelectric system based on LMF‐EC is furthermore developed. This work is a significant step toward the development of smart electromagnetic and thermal regulator for stretchable electronics.
Background: The diagnosis performance of B-mode ultrasound (US) for focal liver lesions (FLLs) is relatively limited. We aimed to develop a deep convolutional neural network of US (DCNN-US) for aiding radiologists in classification of malignant from benign FLLs. Materials and methods: This study was conducted in 13 hospitals and finally 2143 patients with 24,343 US images were enrolled. Patients who had non-cystic FLLs with pathological results were enrolled. The FLLs from 11 hospitals were randomly divided into training and internal validations (IV) cohorts with a 4:1 ratio for developing and evaluating DCNN-US. Diagnostic performance of the model was verified using external validation (EV) cohort from another two hospitals. The diagnosis value of DCNN-US was compared with that of contrast enhanced computed tomography (CT)/magnetic resonance image (MRI) and 236 radiologists, respectively. Findings: The AUC of Model LBC for FLLs was 0.924 (95% CI: 0.889À0.959) in the EV cohort. The diagnostic sensitivity and specificity of Model LBC were superior to 15-year skilled radiologists (86.5% vs 76.1%, p = 0.0084 and 85.5% vs 76.9%, p = 0.0051, respectively). Accuracy of Model LBC was comparable to that of contrast enhanced CT (both 84.7%) but inferior to contrast enhanced MRI (87.9%) for lesions detected by US. Interpretation: DCNN-US with high sensitivity and specificity in diagnosing FLLs shows its potential to assist less-experienced radiologists in improving their performance and lowering their dependence on sectional imaging in liver cancer diagnosis.
High levels of c-aminobutyric acid (GABA) accumulate in plant tissues under various stresses and exogenous additives. The purpose of this research is to provide an effective finding that can prove a rapid accumulation of GABA in germinated soybean (Glycine max L.) in response to different additives under hypoxia. Hypoxia-induced GABA accumulation in soybean embryo resulted in part from polyamine oxidation. Response to different concentration of glutamate (Glu), pyridoxal phosphate, arginine, CuCl 2 , NaCl, and CaCl 2 , a significant difference including GABA accumulation, changes of Glutamate decarboxylase (GAD), and Diamine oxidase activity (DAO) activity in germinated soybean under hypoxia occurred (p \ 0.05) and the maximum accumulation of GABA were 4.07, 3.02, 3.50, 3.26, 4.00, and 3.30 g kg -1 DW respectively, which were significantly higher than those germinated soybean under normal culture (CK) and hypoxia culture (CK 0 ) (p \ 0.05). The GAD and DAO have different distributions in cotyledon and embryo of germinated soybean, and the enzyme activity mainly located in embryo of germinated soybean. Germinated soybean is a good resource of GABA-rich food. Different additives have significant effects on GABA production, among which Glu and NaCl are ideal material for GABA accumulation.
The cecal microbiota plays important roles in host food digestion and nutrient absorption, which may in part affect feed efficiency (
FE
). To investigate the composition and functional differences of cecal microbiota between high (n = 30) and low (n = 29) feed conversion ratio (
FCR
; metric for FE) groups, we performed 16S rRNA gene sequencing and predicted the metagenome function using Phylogenetic Investigation of Communities by Reconstruction of Unobserved Species in yellow broilers. The results showed that the 2 groups had the same prominent microbes but with differing abundance.
Firmicutes
,
Bacteroidetes
, and
Actinobacteria
were 3 prominent bacterial phyla in the cecal microbial community. Although there were no differences in microbial diversity, compositional differences related to FCR were found via linear discriminant analysis (
LDA
) effect size; the genus
Bacteroides
had a significantly higher abundance (LDA >2) in the high FE (
HFE
) group than in the low FE group. Furthermore, genus
Bacteroides
had a negative FCR-associated correlation (
P
< 0.05).
Oscillospira
was positively correlated with
Bacteroides
in both groups, whereas
Dorea
was negatively correlated with
Bacteroides
in the HFE group. Predictive functional analysis revealed that metabolic pathways such as “starch and sucrose metabolism,” “phenylalanine, tyrosine and tryptophan biosynthesis,” and “carbohydrate metabolism” were significantly enriched in the HFE group. The relatively subtle differences in FE-associated cecal microbiota composition suggest a possible link between cecal microbiota and FE. Moreover,
Bacteroides
may potentially be used as biomarkers for FE to improve growth performance in yellow broilers.
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