Attractive forces slow contact formation between deformable bodies underwater.

Thermodynamics tells us to expect underwater contact between two hydrophobic surfaces to result in stronger adhesion compared to two hydrophilic surfaces. However, the presence of water changes not only energetics but also the dynamic process of reaching a final state, which couples solid deformation and liquid evacuation. These dynamics can create challenges for achieving strong underwater adhesion/friction, which affects diverse fields including soft robotics, biolocomotion, and tire traction. Closer investigation, requiring sufficiently precise resolution of film evacuation while simultaneously controlling surface wettability, has been lacking. We perform high-resolution in situ frustrated total internal reflection imaging to track underwater contact evolution between soft-elastic hemispheres of varying stiffness and smooth-hard surfaces of varying wettability. Surprisingly, we find the exponential rate of water evacuation from hydrophobic-hydrophobic (adhesive) contact is three orders of magnitude lower than that from hydrophobic-hydrophilic (nonadhesive) contact. The trend of decreasing rate with decreasing wettability of glass sharply changes about a point where thermodynamic adhesion crosses zero, suggesting a transition in mode of evacuation, which is illuminated by three-dimensional spatiotemporal height maps. Adhesive contact is characterized by the early localization of sealed puddles, whereas nonadhesive contact remains smooth, with film-wise evacuation from one central puddle. Measurements with a human thumb and alternatively hydrophobic/hydrophilic glass surface demonstrate practical consequences of the same dynamics: adhesive interactions cause instability in valleys and lead to a state of more trapped water and less intimate solid-solid contact. These findings offer interpretation of patterned texture seen in underwater biolocomotive adaptations as well as insight toward technological implementation.

A colorimetric sensor for Staphylococcus aureus detection based on controlled click chemical-induced aggregation of gold nanoparticles and immunomagnetic separation.

Staphylococcus aureus (S. aureus) is a pathogen closely associated with foodborne diseases. We prepared a reliable colorimetric sensor to detect S. aureus using click chemical reaction and immunomagnetic separation. Aptamer-functionalized and ALP-labeled Fe3O4 NPs act as separation and signal transduction elements. Under the optimized conditions, the Cu+ generated by signal transduction triggers a click chemistry reaction, which causes the aggregation of azides and alkyne-AuNPs and a color change. The net extinction ratio of Δ(A530/A760) was linearly correlated with the S. aureus concentration from 10 to 106 cfu mL-1, and the limit detection was 2.4 cfu mL-1. The recoveries were 91.15 ~ 106.36% for the analysis of spiked food and water samples without pre-enrichment. Therefore, we believe that the detection platform can be easily and accurately used for S. aureus detection, providing a broad prospect for on-site visual detection.

Factors Associated with Age-Related Changes in Non-Smoking Urban Men and Women in China Determined by Low-Dose Computed Tomography Imaging.

BACKGROUND Respiratory function usually worsens in the elderly with aging. This study aimed to retrospectively investigate tracheal changes caused by "normal aging" through use of low-dose CT (LDCT) in non-smoking asymptomatic urban residents and the related factors influencing tracheal changes. MATERIAL AND METHODS A total of 733 Chinese subjects who underwent LDCT were recruited. The trachea shape, width, and calcification degree of the tracheal wall were measured and compared between males and females and among different age groups. The effects of age, sex, trachea morphology, BMI, BP, GLU, TC, TG, HDL, and LDL on the width and calcification of tracheal wall were analyzed by multiple linear regression. RESULTS Significant sex differences in trachea shape were found, as type II and type I were found mainly in the males and females, respectively. The values of anterior-posterior inner diameter (AP), left-right inner diameter (LR), width, and calcification score of tracheae in the males were higher than that in the females. In both males and females, trachea AP, wall width, and calcification scores increased with age, but this trend was not observed in tracheal LR. Age, sex, and trachea shape had significant effects on the width and calcification scores of tracheal walls, and trachea calcification was one of the factors influencing tracheal wall width. CONCLUSIONS Tracheal aging can be evaluated by measuring trachea shape, thickness, and the degree of calcification of the tracheal wall by LDCT, while sex and age should be taken into consideration comprehensively for judging normal trachea aging. In addition, obesity may aggravate trachea aging.

Multicolor colorimetric visual detection of Staphylococcus aureus based on Fe3O4-Ag-MnO2 composites nano-oxidative mimetic enzyme.

Novel Fe3O4-Ag-MnO2 composites were successfully synthesized. It was noteworthy that the obtained Fe3O4-Ag-MnO2 composites were found to possess three types of enzyme-mimicking activities, including peroxidase-like, catalase-like and oxidase-like activities. Taking advantage of the oxidase properties of Fe3O4-Ag-MnO2, the direct oxidation of TMB could be catalyzed to generate blue oxidation products without H2O2. The oxidase-like activity of Fe3O4-Ag-MnO2 were carefully studied. Based on the Fe3O4-Ag-MnO2-TMB system, a fast, sensitive and intuitive multicolor colorimetric method for Staphylococcus aureus (S. aureus) detection was established under the optimized conditions. The proposed method allows the detection of S. aureus with a detection limit of 3.7 cfu mL-1 and a linear range of 10-106 cfu mL-1. This new colorimetric method has been successfully proved to be applicable to the detection S. aureus of food samples.

Nitrogen deposition enhances the deterministic process of the prokaryotic community and increases the complexity of the microbial co-network in coastal wetlands.

Global nitrogen deposition has increased significantly in recent years. At present, research on the effects of different amounts and types of nitrogen deposition on soil microorganisms in coastal wetlands is scarce. In this study, based on 7 years of simulated nitrogen deposition at multiple levels (low, medium, high) and of multiple types (NH4NO3, NH4Cl, KNO3), the effects of different nitrogen deposition conditions on the diversity, community assembly processes, co-networks, and community function of soil prokaryotes in coastal wetlands were examined. The results showed that, compared with that in control, the microbial α diversity increased significantly under nitrogen deposition (P < 0.05). However, it decreased significantly in the high-NH4NO3 and high-NH4Cl treatments (P < 0.05). The deterministic process of community assembly was strengthened under the different types of nitrogen deposition. Compared with that under NH4+-N deposition, the microbial co-network under NO3--N deposition was more complex. Network stability significantly decreased under different NH4+-N deposition levels. In addition, the results of FAPROTAX functional prediction showed that microbial community functional groups associated with carbon and nitrogen cycling changed significantly (P < 0.05). In conclusion, our results emphasize that nitrogen deposition environments cause changes in soil microbial community structure and interactions, and may also affect soil carbon and nitrogen cycling, but the effects of different forms and levels of nitrogen deposition are not consistent. This study provides new insights for evaluating the changes in soil microbial communities in coastal wetlands caused by different types of long-term nitrogen deposition, and has scientific significance for assessing the ecological effects of long-term nitrogen deposition.

Peripheral interstitial lung abnormalities on LDCT in an asymptomatic, nonsmoking Chinese urban cohort.

To retrospectively investigate the imaging features and the related influencing factors of peripheral interstitial lung abnormalities (PILA) that caused "normal aging" by low-dose computed tomography (LDCT) in an nonsmoking, asymptomatic Chinese urban cohort. The clinical data of 733 subjects who underwent chest LDCT were retrospectively collected. The computed tomography (CT) signs of PILA (interlobular septal thickening [ILST], intralobular interstitial thickening [ILIT], ground-glass opacity [GGO], reticular shadow [RS], subpleural line [SL]) were evaluated at 6 levels and statistically analyzed. The effects of age, sex, body mass index (BMI), blood pressure (BP), and blood biochemistry parameters on ILST, ILIT, and RS were analyzed by Binary Logistic regression analysis. Significant age differences in PILA were found. None of the 5 PILA CT signs (GGO, ILST, ILIT, RS, and SL) was observed in subjects under 40 years old, while in subjects over 40 years old, the incidence of PILA increased with age. All 5 CT signs of PILA were significantly different among the subjects aged 18 to 49, 50 to 69, and 70 to 79 (P < .05). There was no significant sex difference in PILA. Among age, sex, BMI, BP, and laboratory biochemistry parameters, only age had a significant effect on ILST, ILIT, and RS. LDCT can be used as a noninvasive method to evaluate the PILA. PILA were mainly affected by age, while sex, BMI, BP, and laboratory biochemistry parameters had little effect on PILA. PILA observed before the age of 40 years should be considered an abnormal finding, whereas it is common in individuals over 70.

Phase Prediction of High-Entropy Alloys by Integrating Criterion and Machine Learning Recommendation Method.

The comprehensive properties of high-entropy alloys (HEAs) are highly-dependent on their phases. Although a large number of machine learning (ML) algorithms has been successfully applied to the phase prediction of HEAs, the accuracies among different ML algorithms based on the same dataset vary significantly. Therefore, selection of an efficient ML algorithm would significantly reduce the number and cost of the experiments. In this work, phase prediction of HEAs (PPH) is proposed by integrating criterion and machine learning recommendation method (MLRM). First, a meta-knowledge table based on characteristics of HEAs and performance of candidate algorithms is established, and meta-learning based on the meta-knowledge table is adopted to recommend an algorithm with desirable accuracy. Secondly, an MLRM based on improved meta-learning is engineered to recommend a more desirable algorithm for phase prediction. Finally, considering poor interpretability and generalization of single ML algorithms, a PPH combining the advantages of MLRM and criterion is proposed to improve the accuracy of phase prediction. The PPH is validated by 902 samples from 12 datasets, including 405 quinary HEAs, 359 senary HEAs, and 138 septenary HEAs. The experimental results shows that the PPH achieves performance than the traditional meta-learning method. The average prediction accuracy of PPH in all, quinary, senary, and septenary HEAs is 91.6%, 94.3%, 93.1%, and 95.8%, respectively.

Machine learning in the development of targeting microRNAs in human disease.

A microRNA is a small, single-stranded, non-coding ribonucleic acid that plays a crucial role in RNA silencing and can regulate gene expression. With the in-depth study of miRNA in development and disease, miRNA has become an attractive target for novel therapeutic strategies. Exploring miRNA targeting therapy only through experiments is expensive and laborious, so it is essential to develop novel and efficient computational methods to narrow down the search. Recent advances in machine learning applied in biomedical informatics provide opportunities to explore miRNA-targeting drugs, thus promoting miRNA therapeutics. This review provides an overview of recent advancements in miRNA targeting therapeutic using machine learning. First, we mainly describe the basics of predicting miRNA targeting drugs, including pharmacogenomic data resources and data preprocessing. Then we present primary machine learning algorithms and elaborate their application in discovering relationships among miRNAs, drugs, and diseases. Along with the progress of miRNA targeting therapeutics, we finally analyze and discuss the current challenges and opportunities that machine learning confronts.

Sirt1 Mediates Vitamin D Deficiency-Driven Gluconeogenesis in the Liver via mTorc2/Akt Signaling.

As an active form of vitamin D (VD), 1,25-dihydroxyvitamin D (1,25(OH)2D3) is involved in the development of many metabolic diseases, such as diabetes, autoimmune diseases, and tumours. While prospective epidemiological studies have consistently implicated VD deficiency in the regulation of glucose metabolism and insulin sensitivity, the specific mechanism remains unclear. Here, we generated 1α(OH)ase-null mice (targeted ablation of the 25-hydroxyvitamin D 1α hydroxylase enzyme) and found that these mice developed hepatic glucose overproduction, glucose intolerance, and hepatic insulin resistance accompanied by reduced Sirtuin 1 (Sirt1) expression. The chromatin immunoprecipitation (ChIP) and a luciferase reporter assay revealed that 1,25(OH)2D3-activated VD receptor (VDR) directly interacted with one VD response element (VDRE) in the Sirt1 promoter to upregulate Sirt1 transcription, triggering a cascade of serine/threonine kinase (AKT) phosphorylation at S473 and FOXO1 phosphorylation at S256. This phosphorylation cascade reduced the expression of gluconeogenic genes, eventually attenuating glucose overproduction in the liver. In addition, a signaling pathway was found to modulate gluconeogenesis involving VDR, Sirt1, Rictor (a component of mTOR complex 2 [mTorc2]), AKT, and FOXO1, and Sirt1 and FOXO1 were identified as key modulators of dysregulated gluconeogenesis due to VD deficiency.

Keap1-Nrf2 signaling activation by Bardoxolone-methyl ameliorates high glucose-induced oxidative injury in human umbilical vein endothelial cells.

In cultured human umbilical vein endothelial cells (HUVECs) high glucose (HG) stimulation will lead to significant cell death. Bardoxolone-methyl (BARD) is a NF-E2 p45-related factor 2 (Nrf2) agonist. In this study we show that BARD, at only nM concentrations, activated Nrf2 signaling in HUVECs. BARD induced Keap1-Nrf2 disassociation, Nrf2 protein stabilization and nuclear translocation, increasing expression of antioxidant response element (ARE) genes. BARD pretreatment in HUVECs inhibited HG-induced reactive oxygen species production, oxidative injury and cell apoptosis. Nrf2 shRNA or knockout (using a CRISPR/Cas9 construct) reversed BARD-induced cytoprotection in HG-stimulated HUVECs. Conversely, forced activation of Nrf2 cascade by Keap1 shRNA mimicked BARD's activity and protected HUVECs from HG. Importantly, BARD failed to offer further cytoprotection against HG in the Keap1-silened HUVECs. Taken together, Keap1-Nrf2 cascade activation by BARD protects HUVECs from HG-induced oxidative injury.

Peripheral vessel and air bronchograms for detecting the pathologic patterns of subsolid nodules.

PURPOSE: To assess the relationships of subsolid nodules (SSNs) with peripheral vessels and aerated bronchi using computed tomography (CT), and to correlate the imaging features with the benign/malignant pathological diagnoses. METHODS: This study retrospectively analyzed data from 83 patients with a solitary SSN (January 2008 to December 2016). SSNs were imaged (LightSpeed 64-slice spiral CT, General Electric, USA), their mean diameter determined, and the relationship with peripheral vessels (types I-IV) and aerated bronchi (types I-V) were classified. Pathologic diagnoses were obtained from the surgical specimens. RESULTS: SSNs were diagnosed as benign (n = 29), pre-invasive (n = 9), micro-invasive adenocarcinoma (n = 7) and invasive adenocarcinoma (n = 38). SSN size, peripheral vessel class and aerated bronchus class differed between pathologic types (P < 0.05). For benign SSNs, peripheral vessel type II (58.6%) was most common, followed by III (20.7%) and IV (6.9%). Aerated bronchus type V (65.5%) was most frequent, followed by IV (27.6%); type I aerated bronchus was not observed. No cases of micro-invasive or invasive adenocarcinoma were peripheral vessel type I or aerated bronchus type V. For invasive adenocarcinoma, 92.1% were peripheral vessel types III + IV while 71.8% were aerated bronchus types I + II. CONCLUSIONS: SSN pathologic types differ with regard to peripheral vessel and aerated bronchus types. Type I peripheral vessel and type V aerated bronchus (both least involved) suggest a benign lesion, whereas type III/IV peripheral vessel and type I/II aerated bronchus (both most involved) suggest malignancy.