The evaporation of water/ethanol drops with different mixing ratios was investigated at controlled vapor pressure of water (relative humidity) and ethanol in the background gas. Therefore, a drop of about 1 microL was deposited on a hydrophobized silicon substrate at room temperature in a closed cell. With a microscope camera we monitored the contact angle, the volume and the contact radius of the drops as function of time. Pure water drops evaporated in constant contact angle mode. The evaporation rate of water decreased with increasing humidity. In mixed drops ethanol did not evaporate completely at first, but a fraction still remained in the drop until the end of evaporation. Depending on ethanol concentration in the drop and on relative humidity in the background gas, water vapor condensed at the beginning of the evaporation of mixed drops. Also, at a high vapor pressure of ethanol, ethanol condensed at the beginning of the evaporation. The presence of ethanol vapor accelerated the total evaporation time of water drops.

Condensation on soft elastic surfaces differs significantly from condensation on hard surfaces. On polymeric substrates with varying cross-linking density, we investigate the nucleation and the growth of condensing water drops. With increasing softness of the substrates, we find (1) increasing nucleation density, (2) longer relaxation times for drop shape equilibration after merging of two drops, and (3) prevention of merging on very soft surfaces. These effects lead to higher surface coverage and overall condensed volume on soft surfaces.

Pyrene derivatives can absorb onto the surface of carbon nanotubes and graphite particles through pi-pi interactions to functionalize these inorganic building blocks with organic surface moieties. Using single molecule force spectroscopy, we have demonstrated the first direct measurement of the interaction between pyrene and a graphite surface. In particular, we have connected a pyrene molecule onto an AFM tip via a flexible poly(ethylene glycol) (PEG) chain to ensure the formation of a molecular bridge. The pi-pi interaction between pyrene and graphite is thus indicated to be approximately 55 pN with no hysteresis between the desorption and adhesion forces.

These authors contributed equally to this work. SUMMARYDespite the importance of host-microbe interactions in natural ecosystems, agriculture and medicine, the impact of long-term (especially decades or longer) microbial colonization on the dynamics of host genomes is not well understood. The vegetable crop 'Jiaobai' with enlarged edible stems was domesticated from wild Zizania latifolia (Oryzeae) approximately 2000 years ago as a result of persistent infection by a fungal endophyte, Ustilago esculenta. Asexual propagation via infected rhizomes is the only means of Jiaobai production, and the Z. latifolia-endophyte complex has been maintained continuously for two centuries. Here, genomic analysis revealed that cultivated Z. latifolia has a significantly smaller repertoire of immune receptors compared with wild Z. latifolia. There are widespread gene losses/mutations and expression changes in the plant-pathogen interaction pathway in Jiaobai. These results show that continuous long-standing endophyte association can have a major effect on the evolution of the structural and transcriptomic components of the host genome.

We have synthesized a new kind of poly(2-acrylamido-2-methylpropanesulfonic acid) with crown ether and studied comparatively the single molecule force spectroscopy of the polymers with and without crown ether, in terms of desorption and elongation. The smooth desorption process enabled us to calculate the loading rate of the stretching process. For the two polymers, desorption forces were loading rate independent and ionic strength insensitive. Interestingly, the desorption forces of the two polymers were undistinguishable in all conditions. These findings demonstrate (1) the polymer chains adopt a trainlike (flat) conformation at the interface with a high adsorption/desorption rate, (2) the spacer, which separates the charged group from the hydrophobic backbone and combines the two properties together, should account for the retained desorption force at high salt concentration, and (3) the 20% less in linear charge density does not affect the desorption force remarkably since hydrophobic interaction dominates the adhesion force. In deionized water, PAMPS-co-crown is less rigid than PAMPS since the uncharged side groups separate the charged groups, and thus the repulsion between adjacent charged groups is reduced. As the salt concentration increased, the rigidity of the two polymers both decreased, suggesting that the external salt would screen the charges of the polyelectrolytes. The linear charge density and the ionic strength affect only the rigidity of single polyelectrolyte chain but not the adhesion force, which is another result of the "spacer effect". This fundamental finding, which reveals the nonelectrostatic origin of the interfacial interaction of polyelectrolytes, sheds new light on the understanding of polyelectrolytes, especially for those containing spacers.

The development of metastasis is the leading cause of death and an enormous therapeutic challenge in cases of non-small cell lung cancer. To better understand the molecular mechanisms underlying the metastasis process and to discover novel potential clinical markers for non-small cell lung cancer, comparative proteomic analysis of two non-small cell lung cancer cell lines with different metastatic potentials, the non-metastatic CL1-0 and highly metastatic CL1-5 cell lines, was carried out using two-dimensional electrophoresis followed by matrix-assisted laser desorption ionization-time of flight mass spectrometry and tandem mass spectrometry. Thirty-three differentially expressed proteins were identified unambiguously, among which 16 proteins were significantly upregulated and 17 proteins were downregulated in highly metastatic CL1-5 cells compared with non-metastatic CL1-0 cells. Subsequently, 8 of 33 identified proteins were selected for further validation at the mRNA level using real-time quantitative polymerase chain reaction, and three identified proteins, S100A11, PGP 9.5 and HSP27, were confirmed by western blotting. The protein S100A11 displaying significant differential expression at both the protein and mRNA levels was further analyzed by immunohistochemical staining in 65 primary non-small cell lung cancer tissues and 10 matched local positive lymph node specimens to explore its relationship with metastasis. The results indicated that the upregulation of S100A11 expression in non-small cell lung cancer tissues was significantly associated with higher tumor-nodemetastasis stage (P = 0.001) and positive lymph node status (P = 0.011), implying that S100A11 might be an important regulatory molecule in promoting invasion and metastasis of non-small cell lung cancer. (Cancer Sci 2007; 98: 1265-1274) L ung cancer is the leading cause of cancer-related mortality worldwide. In some countries it has become the number one cancer killer, accounting for more deaths than prostate cancer, breast cancer and colorectal cancer combined.(1) NSCLC, the most common histological subtype, represents 85% of all lung cancers and often develops metastases resulting in incurable disease at the time of diagnosis. Because of the lack of accurate early stage detection measures and efficient methods for preventing metastasis, the 5-year survival rate for all stages combined is only 15%, and only 16% of lung cancers are diagnosed at an early stage.(2) Therefore, investigations into the mechanisms of metastasis are required urgently for the early diagnosis and therapy of NSCLC.Metastasis is a complex multistep process that includes invasion of tumor cells into the surrounding stroma, passage through the endothelial lining and into the vasculature, escape from blood vessels, and then colonization of distant organs. During the devastating process a series of changes occur in the tumor cells, providing them with the potential for invasion and subsequent localization at a secondary site. It is therefore quite difficult to attribute the m...

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality rate, and it induces other diseases. Since there are no obvious symptoms during the early stages of CKD, patients often fail to notice the disease. Early detection of CKD enables patients to receive timely treatment to ameliorate the progression of this disease. Machine learning models can effectively aid clinicians achieve this goal due to their fast and accurate recognition performance. In this study, we propose a machine learning methodology for diagnosing CKD. The CKD data set was obtained from the University of California Irvine (UCI) machine learning repository, which has a large number of missing values. KNN imputation was used to fill in the missing values, which selects several complete samples with the most similar measurements to process the missing data for each incomplete sample. Missing values are usually seen in real-life medical situations because patients may miss some measurements for various reasons. After effectively filling out the incomplete data set, six machine learning algorithms (logistic regression, random forest, support vector machine, k-nearest neighbor, naive Bayes classifier and feed forward neural network) were used to establish models. Among these machine learning models, random forest achieved the best performance with 99.75% diagnosis accuracy. By analyzing the misjudgments generated by the established models, we proposed an integrated model that combines logistic regression and random forest by using perceptron, which could achieve an average accuracy of 99.83% after ten times of simulation. Hence, we speculated that this methodology could be applicable to more complicated clinical data for disease diagnosis. INDEX TERMS Chronic kidney disease, machine learning, KNN imputation, integrated model.

We propose a simple method to isolate polymer chains individually at the quartz surface by utilizing the defects in the self-assembled monolayers of organosilane. This method allows us to measure the desorption force of a single polyelectrolyte chain from a substrate directly.