Measurement of the Near-Bed Turbulence in a Laboratory Surf Zone

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

CCN2 Enhances Resistance to Cisplatin-Mediating Cell Apoptosis in Human Osteosarcoma

Osteosarcoma (OS) is the most common form of malignant bone tumor and is an aggressive malignant neoplasm exhibiting osteoblastic differentiation. Cisplatin is one of the most efficacious antitumor drugs for osteosarcoma patients. However, treatment failures are common due to the development of chemoresistance. CCN2 (also known as CTGF), is a secreted protein that binds to integrins, modulates the invasive behavior of certain human cancer cells. However, the effect of CCN2 in cisplatin-mediated chemotherapy is still unknown. Here, we found that CCN2 was upregulated in human osteosarcoma cells after treatment with cisplatin. Moreover, overexpression of CCN2 increased the resistance to cisplatin-mediated cell apoptosis. In contrast, reduction of CCN2 by CCN2 shRNA promoted the chemotherapeutic effect of cisplatin. We also found that CCN2 provided resistance to cisplatin-induced apoptosis through upregulation of Bcl-xL and survivin. Knockdown of Bcl-xL or survivin removed the CCN2-mediated resistance to apoptosis induced by cisplatin. On the other hand, CCN2 also promoted FAK, MEK, and ERK survival signaling pathways to enhance tumor survival during cisplatin treatment. In a mouse xenograft model, overexpression of CCN2 promoted resistance to cisplatin. However, knockdown of CCN2 increased the therapeutic effect of cisplatin. Therefore, our data suggest that CCN2 might be a critical oncogene of human osteosarcoma for cisplatin-resistance and supported osteosarcoma cell growth in vivo and in vitro

A new regularized least squares support vector regression for gene selection

<p>Abstract</p> <p>Background</p> <p>Selection of influential genes with microarray data often faces the difficulties of a large number of genes and a relatively small group of subjects. In addition to the curse of dimensionality, many gene selection methods weight the contribution from each individual subject equally. This equal-contribution assumption cannot account for the possible dependence among subjects who associate similarly to the disease, and may restrict the selection of influential genes.</p> <p>Results</p> <p>A novel approach to gene selection is proposed based on kernel similarities and kernel weights. We do not assume uniformity for subject contribution. Weights are calculated via regularized least squares support vector regression (RLS-SVR) of class levels on kernel similarities and are used to weight subject contribution. The cumulative sum of weighted expression levels are next ranked to select responsible genes. These procedures also work for multiclass classification. We demonstrate this algorithm on acute leukemia, colon cancer, small, round blue cell tumors of childhood, breast cancer, and lung cancer studies, using kernel Fisher discriminant analysis and support vector machines as classifiers. Other procedures are compared as well.</p> <p>Conclusion</p> <p>This approach is easy to implement and fast in computation for both binary and multiclass problems. The gene set provided by the RLS-SVR weight-based approach contains a less number of genes, and achieves a higher accuracy than other procedures.</p

The Arabidopsis Malectin-Like/LRR-RLK IOS1 is Critical for BAK1-Dependent and BAK1-Independent Pattern-Triggered Immunity

Plasma membrane-localized pattern recognition receptors (PRRs) such as FLAGELLIN SENSING2 (FLS2), EF-TU RECEPTOR (EFR) and CHITIN ELICITOR RECEPTOR KINASE 1 (CERK1) recognize microbe-associated molecular patterns (MAMPs) to activate pattern-triggered immunity (PTI). A reverse genetics approach on genes responsive to the priming agent beta-aminobutyric acid (BABA) revealed IMPAIRED OOMYCETE SUSCEPTIBILITY1 (IOS1) as a critical PTI player. Arabidopsis thaliana ios1 mutants were hyper-susceptible to Pseudomonas syringae bacteria. Accordingly, ios1 mutants showed defective PTI responses, notably delayed up-regulation of the PTI-marker gene FLG22-INDUCED RECEPTOR-LIKE KINASE1 (FRK1), reduced callose deposition and mitogen-activated protein kinase activation upon MAMP treatment. Moreover, Arabidopsis lines over-expressing IOS1 were more resistant to bacteria and showed a primed PTI response. In vitro pull-down, bimolecular fluorescence complementation, co-immunoprecipitation, and mass spectrometry analyses supported the existence of complexes between the membrane-localized IOS1 and BRASSINOSTEROID INSENSITIVE1-ASSOCIATED KINASE1 (BAK1)-dependent PRRs FLS2 and EFR, as well as with the BAK1-independent PRR CERK1. IOS1 also associated with BAK1 in a ligand-independent manner, and positively regulated FLS2-BAK1 complex formation upon MAMP treatment. In addition, IOS1 was critical for chitin-mediated PTI. Finally, ios1 mutants were defective in BABA-induced resistance and priming. This work reveals IOS1 as a novel regulatory protein of FLS2-, EFR- and CERK1-mediated signaling pathways that primes PTI activation

Development of Rifampicin-Indocyanine Green-Loaded Perfluorocarbon Nanodroplets for Photo-Chemo-Probiotic Antimicrobial Therapy

Acne vulgaris, generally resulted from overgrowth of Propionibacterium acnes (P. acnes), is one of the most difficult-to-treat facial dermatoses and more than 90% of adolescents experienced the disease worldwide. Because the innate non-lymphoid immune system cannot effectively eliminate excessive P. acnes from the skin surface, so far the therapy of acne vulgaris is still mainly dependent on antibiotic treatment. However, long-term or overdose of antibiotics may initiate microbial drug resistance and/or generate unexpected side effects that seriously hamper the use of antibiotics in the clinic. To overcome the aforementioned challenges, the novel rifampicin (RIF)-indocyanine green (ICG)-loaded perfluorocarbon (PFC) nanodroplets (RIPNDs) that may offer combined photo-, chemo-, and probiotic efficacies to P. acnes eradication were developed in this study. The RIPND was first characterized as a sphere-like nanoparticle with surface charge of −20.9 ± 2.40 mV and size of 240.7 ± 6.73 nm, in which the encapsulation efficiencies of RIF and ICG were 54.0 ± 10.5% and 95.0 ± 4.84%, respectively. In comparison to the freely dissolved ICG, the RIPNDs conferred an enhanced thermal stability to the entrapped ICG, and were able to provide a comparable hyperthermia effect and markedly increased production of singlet oxygen under near infrared (NIR; 808 nm, 6 W/cm2) exposure. Furthermore, the RIPNDs were able to induce fermentation of S. epidermidis but not P. acnes, indicating that the RIPNDs may serve as a selective fermentation initiator for the target probiotics. Based on the microbial population index analyses, P. acnes with 1 × 106 cells/mL can be completely eradicated by 12-h co-culture with S. epidermidis fermentation products followed by treatment of RIPNDs (≥20-μM ICG/3.8-μM RIF) + NIR for 5 min, whereby the resulted microbial mortality was even higher than that caused by using 16-fold enhanced amount of loaded RIF alone. Overall these efforts show that the RIPNDs were able to provide improved ICG stability, selective fermentability to S. epidermidis, and enhanced antimicrobial efficacy compared to equal dosage of free RIF and/or ICG, indicating that the developed nanodroplets are highly potential for use in the clinical anti-P. acne treatment with reduced chemotoxicity

Prediagnosis of Obstructive Sleep Apnea via Multiclass MTS

Obstructive sleep apnea (OSA) has become an important public health concern. Polysomnography (PSG) is traditionally considered an established and effective diagnostic tool providing information on the severity of OSA and the degree of sleep fragmentation. However, the numerous steps in the PSG test to diagnose OSA are costly and time consuming. This study aimed to apply the multiclass Mahalanobis-Taguchi system (MMTS) based on anthropometric information and questionnaire data to predict OSA. Implementation results showed that MMTS had an accuracy of 84.38% on the OSA prediction and achieved better performance compared to other approaches such as logistic regression, neural networks, support vector machine, C4.5 decision tree, and rough set. Therefore, MMTS can assist doctors in prediagnosis of OSA before running the PSG test, thereby enabling the more effective use of medical resources