Explore the vast range of titles available.

We develop a procedure for analyzing multivariate nonstationary time series using the SLEX library (smooth localized complex exponentials), which is a collection of bases, each basis consisting of waveforms that are orthogonal and time-localized versions of the Fourier complex exponentials. Under the SLEX framework, we build a family of multivariate models that can explicitly characterize the time-varying spectral and coherence properties. Every model has a spectral representation in terms of a unique SLEX basis. Before selecting a model, we first decompose the multivariate time series into nonstationary components with uncorrelated (nonredundant) spectral information. The best SLEX model is selected using the penalized log energy criterion, which we derive in this article to be the Kullback-Leibler distance between a model and the SLEX principal components of the multivariate time series. The model selection criterion takes into account all of the pairwise cross-correlation simultaneously in the multivariate time series. The proposed SLEX analysis gives results that are easy to interpret, because it is an automatic time-dependent generalization of the classical Fourier analysis of stationary time series. Moreover, the SLEX method uses computationally efficient algorithms and hence is able to provide a systematic framework for extracting spectral features from a massive dataset. We illustrate the SLEX analysis with an application to a multichannel brain wave dataset recorded during an epileptic seizure.

Cell surface carbohydrate antigens sialyl Lewis X (sLeX) and Lewis Y (LeY) are paramount glycoconjugates and are abundantly expressed in the receptive endometrium. Furthermore, among the important biological functions of both antigens is their role in leukocytes adhesion and extravasation. Interleukin-1 beta (IL-1β) is involved in the process of human embryo implantation and placenta development. Here, we used an in vitro model to investigate whether sLeX and LeY are playing a role in the embryo implantation process mediated by IL-1β. Our results are showing that the expression of cell surface sLeX was enhanced in endometrial RL95-2 cells after exposure to IL-1β. RT-qPCR detection indicated that the transcript level of glycosyltransferase gene fucosyltransferase 3 (FUT3) was significantly elevated and that of FUT4/7 and ST3 beta-galactoside alpha-2,3-sialyltransferase 3/4 (ST3GAL3/4) were decreased by treatment with IL-1β. Modulatory role of glycosyltransferase FUT3 on sLeX biosynthesis was determined by FUT3 siRNA transfection in RL95-2 cells. Results showed that the expression level of sLeX was suppressed, but no change was observed in regard to LeY. Moreover, IL-1β promoted the HTR-8/SVneo trophoblast spheroids attachment to the RL95-2 endometrial monolayer, which was partially blocked by anti-sLeX antibody and FUT3 knockdown. Gene expression analysis of the RNA-seq transcriptome data from human secretory endometrium demonstrated a significantly higher level of FUT3 in the mid-secretory phase compared to the early secretory phase, which was correlated with the expression of IL1B. In summary, the inflammatory microenvironment at the fetomaternal interface can regulate the glycosylation pattern of endometrial cells at the time of implantation. SLeX can be significantly induced by IL-1β via increasing FUT3 expression, which facilitates the trophoblast adhesion during embryo implantation. Summary Sentence sLeX can be significantly induced by IL-1β via increasing FUT3 expression, which facilitates trophoblast adhesion during human embryo implantation. Graphical Abstract

Expression of sialyl Lewis X (SLeX) is a well-documented event during malignant transformation of cancer cells, and largely associates with their invasive and metastatic properties. Glycoproteins and glycolipids are the main carriers of SLeX, whose biosynthesis is known to be performed by different glycosyltransferases, namely by the family of β-galactoside-α2,3-sialyltransferases (ST3Gals). In this study, we sought to elucidate the role of ST3GalIV in the biosynthesis of SLeX and in malignant properties of gastrointestinal (GI) cancer cells. By immunofluorescent screening, we selected SLeX-positive GI cancer cell lines and silenced ST3GalIV expression via CRISPR/Cas9. Flow cytometry, immunofluorescence and western blot analysis showed that ST3GalIV KO efficiently impaired SLeX expression in most cancer cell lines, with the exception of the colon cancer cell line LS174T. The impact of ST3GalIV KO in the biosynthesis of SLeX isomer SLeA and non sialylated Lewis X and A were also evaluated and overall, ST3GalIV KO led to a decreased expression of SLeA and an increased expression in both LeX and LeA. In addition, the abrogation of SLeX on GI cancer cells led to a reduction in cell motility. Furthermore, ST3GalVI KO was performed in LS174T ST3GalIV KO cells, resulting in the complete abolishment of SLeX expression and consequent reduced motility capacity of those cells. Overall, these findings portray ST3GalIV as the main, but not the only, enzyme driving the biosynthesis of SLeX in GI cancer cells, with a functional impact on cancer cell motility.

Background Nasopharyngeal carcinoma (NPC) is a type of head and neck malignant tumor with a high incidence in specific regional distribution, and its traditional therapies face some challenges. It has become an urgent need to seek new therapeutic strategies without or with low toxicity and side effects. At present, more and more researchers has been attracting attention by nanotheranostic platform. Therefore, our team synthesized the polyethylene glycol-coated ultrasmall superparamagnetic iron oxide nanoparticles-coupled sialyl Lewis X (USPIO-PEG-sLe x ) nanotheranostic platform with high temperature pyrolysis. Results The USPIO-PEG-sLe x nanoparticles had excellent photothermal conversion property, and the temperature of USPIO-PEG-sLe x nanoparticles solution increased with its concentration and power density of near-infrared (NIR) on 808 nm wavelengths. Five USPIO-PEG-sLe x nanoparticles with different concentrations of 0 mg/ml, 0.025 mg/ml, 0.05 mg/ml, 0.1 mg/ml and 0.2 mg/ml were prepared. The biological toxicity results showed that the viability of NPC 5-8F cells is related to the concentration of USPIO-PEG-sLe x nanoparticles and the culture time (P < 0.001). The results of photothermal therapy (PTT) in vitro indicated that the viability of 5-8F cells decreased significantly with the concentration of USPIO-PEG-sLe x nanoparticles increases (P < 0.001), and the viability of NPC 5-8F cells were 91.04% ± 5.20%, 77.83% ± 3.01%, 73.48% ± 5.55%, 59.50% ± 10.98%, 17.11% ± 3.14%, respectively. The USPIO-PEG-sLe x nanoparticles could target the tumor area, and reduce the T2* value of tumor tissue. The T2* values of tumor pre- and post-injection were 30.870 ± 5.604 and 18.335 ± 4.351, respectively (P < 0.001). In addition, USPIO-PEG-sLe x nanoparticles as a photothermal agent for PTT could effectively inhibit tumor progression. The ratio of volume change between tail vein injection group, control group, nanoparticles without laser irradiation group and blank group after 5 treatments were 3.04 ± 0.57, 5.80 ± 1.06, 8.09 ± 1.96, 7.89 ± 2.20, respectively (P < 0.001). Conclusions Our synthesized USPIO-PEG-sLe x nanotheranostic platform, and it may be become a new strategy for the treatment of NPC. Graphic Abstract

We propose a new method for analyzing bivariate nonstationary time series. The proposed method is a statistical procedure that automatically segments the time series into approximately stationary blocks and selects the span to be used to obtain the smoothed estimates of the time-varying spectra and coherence. It is based on the smooth localized complex exponential (SLEX) transform, which forms a library of orthogonal complex-valued transforms that are simultaneously localized in time and frequency. We show that the smoothed SLEX periodograms are consistent estimators, report simulation results, and apply the method to a two-channel electroencephalogram dataset recorded during an epileptic seizure.

Despite decades of intensive attention directed to creation of genetically altered cells (e.g., as in development of chimeric antigen receptor (CAR) T-cells) and/or to achieve requisite accumulation of desired immunologic effectors (e.g., elaboration of virus-specific T cells, expansion of NK cells, differentiation of dendritic cells, isolation, and propagation of Tregs, etc.), there has been essentially no interest in the most fundamental of all hurdles: assuring tissue-specific delivery of administered therapeutic cells to sites where they are needed. With regards to use of CAR T-cells, the absence of information on the efficacy of cell delivery is striking, especially in light of the clear association between administered cell dose and adverse events, and the obvious fact that pertinent cell acquisition/expansion costs would be dramatically curtailed with more efficient delivery of the administered cell bolus. Herein, based on information garnered from studies of human leukocytes and adult stem cells, the logic underlying the use of cell surface glycoengineering to enforce E-selectin ligand expression will be conveyed in the context of how this approach offers strategies to enhance delivery of CAR T-cells to marrow and to tumor beds. This application of glycoscience principles and techniques with intention to optimize cell therapeutics is a prime example of the emerging field of \"translational glycobiology.\"

In this study, a new water and alkaline‐soluble polysaccharide (ALP), with an average molecular weight of 6.63 × 104 Da, was successfully purified from the rhizomes of Atractylodes lancea. GC analysis demonstrated that ALP was a kind of glucan. The effect of the ALP on the interaction between E‐selectin and sialyl Lewis X (sLex) was examined in human osteosarcoma U‐2 OS cells. It was obvious that the expression of sLex antigen on the surface of U‐2 OS cells was visible under fluorescence microscopy. The addition of ALP (0.5, 1 and 2 mg/mL) resulted in a marked inhibition on the adhesion, migration and invasion of U‐2 OS cells to human umbilical vein endothelial cells (HUVECs), which was achieved by the decreased sLex expression on U‐2 OS cells. Additionally, the induction of apoptosis can be observed in U‐2 OS cells following ALP treatment using TUNEL staining and Annexin V‐FITC/PI double‐staining analysis on flow cytometry. In conclusion, these results indicated that ALP exerted anti‐metastatic activity towards osteosarcoma cells via inhibition of sLex/E‐selectin binding, which suggested that ALP could be a potent agent for human osteosarcoma intervention.

Accurate clustering of time series is a challenging problem for data arising from areas such as financial markets, biomedical studies, and environmental sciences, especially when some, or all, of the series exhibit nonlinearity and nonstationarity. When a subset of the series exhibits nonlinear characteristics, frequency domain clustering methods based on higher-order spectral properties, such as the bispectra or trispectra are useful. While these methods address nonlinearity, they rely on the assumption of series stationarity. We propose the Bispectral Smooth Localized Complex EXponential (BSLEX) approach for clustering nonlinear and nonstationary time series. BSLEX is an extension of the SLEX approach for linear, nonstationary series, and overcomes the challenges of both nonlinearity and nonstationarity through smooth partitions of the nonstationary time series into stationary subsets in a dyadic fashion. The performance of the BSLEX approach is illustrated via simulation where several nonstationary or nonlinear time series are clustered, as well as via accurate clustering of the records of 16 seismic events, eight of which are earthquakes and eight are explosions. We illustrate the utility of the approach by clustering S&P 100 financial returns.

The complex implantation process is initiated by the recognition and adhesion between the embryo and uterine endometrial epithelium. The expression and interactions between the adhesive molecules from both fetal and maternal sides are crucial for the successful implantation. In this study, we aimed to investigate the expression and adhesive function of sLeX on the trophoblasts and L-selectin on uterine epithelial cells mediated the adhesion at the fetal-maternal interface, and to further explore whether this adhesion system could induce endometrial apoptosis, using in vitro implantation model consisting of the human trophoblast cell line (JAR) and human uterine epithelial cell line (RL95-2). The results showed that sLeX was expressed on JAR cells by indirect immunofluorescence staining. After transfection of JAR cells with fucosyltransferase VII (FUT7) which is the key enzyme for sLeX synthesis, the expression of FUT7 and sLeX synthesis were increased, and the percent adhesion of trophoblast cells to RL95-2 cell monolayer was significantly increased (P < 0.01). L-selectin was strongly expressed but not E- and P-selectin on epithelial RL95-2 cells by RT-PCR, Western blot. Blocking L-selectin with specific antibody or heparin pretreatment in RL95-2 cells inhibited the adhesion of JAR cells to RL95-2 cell monolayer. Furthermore, regulating the expression of sLeX on JAR cells or blocking L-selectin on RL95-2 cells could activate the apoptosis of uterine epithelial cells. These results suggest the sLeX/L-selectin adhesion system at fetal-maternal interface not only mediates the adhesion of embryo to uterine epithelium, but also effectively induces the apoptosis in uterine epithelium. The study supplies a molecular basis for the elucidation of the initial recognition and adhesion during embryo implantation.

Statistical discrimination for nonstationary random processes is important in many applications. Our goal was to develop a discriminant scheme that can extract local features of the time series, is consistent, and is computationally efficient. Here, we propose a discriminant scheme based on the SLEX (smooth localized complex exponential) library. The SLEX library forms a collection of Fourier-type bases that are simultaneously orthogonal and localized in both time and frequency domains. Thus, the SLEX library has the ability to extract local spectral features of the time series. The first step in our procedure, which is the feature extraction step based on work by Saito, is to find a basis from the SLEX library that can best illuminate the difference between two or more classes of time series. In the next step, we construct a discriminant criterion that is related to the Kullback-Leibler divergence between the SLEX spectra of the different classes. The discrimination criterion is based on estimates of the SLEX spectra that are computed using the SLEX basis selected in the feature extraction step. We show that the discrimination method is consistent and demonstrate via finite sample simulation studies that our proposed method performs well. Finally, we apply our method to a seismic waves dataset with the primary purpose of classifying the origin of an unknown seismic recording as either an earthquake or an explosion.