Xi'an Jiaotong University

About: Xi'an Jiaotong University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Heat transfer & Dielectric. The organization has 85440 authors who have published 99682 publications receiving 1579683 citations. The organization is also known as: '''Xi'an Jiaotong University''' & Xi'an Jiao Tong University.

Cell volume change through water efflux impacts cell stiffness and stem cell fate.

Abstract: Cells alter their mechanical properties in response to their local microenvironment; this plays a role in determining cell function and can even influence stem cell fate. Here, we identify a robust and unified relationship between cell stiffness and cell volume. As a cell spreads on a substrate, its volume decreases, while its stiffness concomitantly increases. We find that both cortical and cytoplasmic cell stiffness scale with volume for numerous perturbations, including varying substrate stiffness, cell spread area, and external osmotic pressure. The reduction of cell volume is a result of water efflux, which leads to a corresponding increase in intracellular molecular crowding. Furthermore, we find that changes in cell volume, and hence stiffness, alter stem-cell differentiation, regardless of the method by which these are induced. These observations reveal a surprising, previously unidentified relationship between cell stiffness and cell volume that strongly influences cell biology.

Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting

Abstract: Current deep neural networks (DNNs) can easily overfit to biased training data with corrupted labels or class imbalance. Sample re-weighting strategy is commonly used to alleviate this issue by designing a weighting function mapping from training loss to sample weight, and then iterating between weight recalculating and classifier updating. Current approaches, however, need manually pre-specify the weighting function as well as its additional hyper-parameters. It makes them fairly hard to be generally applied in practice due to the significant variation of proper weighting schemes relying on the investigated problem and training data. To address this issue, we propose a method capable of adaptively learning an explicit weighting function directly from data. The weighting function is an MLP with one hidden layer, constituting a universal approximator to almost any continuous functions, making the method able to fit a wide range of weighting functions including those assumed in conventional research. Guided by a small amount of unbiased meta-data, the parameters of the weighting function can be finely updated simultaneously with the learning process of the classifiers. Synthetic and real experiments substantiate the capability of our method for achieving proper weighting functions in class imbalance and noisy label cases, fully complying with the common settings in traditional methods, and more complicated scenarios beyond conventional cases. This naturally leads to its better accuracy than other state-of-the-art methods.

Immune-Related Adverse Events Associated with Anti-PD-1/PD-L1 Treatment for Malignancies: A Meta-Analysis.

Abstract: Background: Treatment of cancers with programmed cell death protein 1 (PD-1) pathway inhibitors can lead to immune-related adverse events (irAEs), which could be serious and even fetal. Therefore, clinicians should be aware of the characteristics of irAEs associated with the use of such drugs. Methods: The MEDLINE, EMBASE, and Cochrane databases were searched to find potential studies using the following strategies: anti-PD-1/PD-L1 treatment; irAEs; and cancer. R© package Meta was used to pool incidence. Results: Forty-six studies representing 12,808 oncologic patients treated with anti-PD-1/PD-L1 agents were included in the meta-analysis. The anti-PD-1/PD-L1 agents included nivolumab, pembrolizumab, atezolizumab, durvalumab, avelumab, and BMS-936559. The tumor types were melanomas, Hodgkin lymphomas, urothelial carcinomas, breast cancers, non-small cell lung cancers, renal cell carcinomas (RCC), colorectal cancers, and others. We described irAEs according to organ systems, namely, the skin (pruritus, rash, maculopapular rash, vitiligo, and dermatitis), endocrine system (hypothyroidism, hyperthyroidism, hypophysitis, thyroiditis, and adrenal insufficiency), digestive system (colitis, diarrhea, pancreatitis, and increased AST/ALT/bilirubin), respiratory system (pneumonitis, lung infiltration, and interstitial lung disease), and urinary system (increased creatinine, nephritis, and renal failure). In patients treated with the PD-1 signaling inhibitors, the overall incidence of irAEs was 26.82% (95% CI, 21.73-32.61; I2, 92.80) in any grade and 6.10% (95% CI, 4.85-7.64; I2, 52.00) in severe grade, respectively. The development of irAEs was unrelated to the dose of anti-PD-1/PD-L1 agents. The incidence of particular irAEs varied when different cancers were treated with different drugs. The incidence of death due to irAEs was around 0.17%. Conclusion: The occurrence of irAEs was organ-specific and related to drug and tumor types.

Donor polymer design enables efficient non-fullerene organic solar cells.

Abstract: In organic photovoltaics, electron acceptors are developed to replace fullerenes, and new donors need to be designed to match these acceptors Here, the authors show that a polymer with strong temperature dependent aggregation and intentionally reduced crystallinity matches non-fullerene acceptors