Immobilization of dye-decolorizing peroxidase on magnetic nanoparticles: A dual- functional biocatalyst for mycotoxins degradation and hydrogen peroxide detection

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A Meta-Learning Based Gradient Descent Algorithm for MU-MIMO Beamforming

Multi-user multiple-input multiple-output (MU-MIMO) beamforming design is typically formulated as a non-convex weighted sum rate (WSR) maximization problem that is known to be NP-hard. This problem is solved either by iterative algorithms, which suffer from slow convergence, or more recently by using deep learning tools, which require time-consuming pre-training process. In this paper, we propose a low-complexity meta-learning based gradient descent algorithm. A meta network with lightweight architecture is applied to learn an adaptive gradient descent update rule to directly optimize the beamformer. This lightweight network is trained during the iterative optimization process, which we refer to as \emph{training while solving}, which removes both the training process and the data-dependency of existing deep learning based solutions.Extensive simulations show that the proposed method achieves superior WSR performance compared to existing learning-based approaches as well as the conventional WMMSE algorithm, while enjoying much lower computational load

Spleen-Yang-deficiency patients with polycystic ovary syndrome have higher levels of visfatin

AbstractObjectiveTo study serum visfatin levels in women with polycystic ovary syndrome (PCOS) grouped by Traditional Chinese Medicine (TCM) patterns. To study the correlations of serum visfatin levels with homeostatic model assessment insulin resistance (HOMA-IR), fasting plasma glucose (FPG), fasting insulin (FINS), body mass index (BMI), testosterone (T), total cholesterol (TC), and triglycerides (TG).MethodsTwo hundred and twelve PCOS patients were placed into the following TCM pattern subgroups: Kidney-Yang deficiency (KYD) group, Spleen-Yang deficiency (SYD) group, stagnant Liver-Qi transforming into heat (SLQTH) group, and Kidney-Yin deficiency (KYIND) group. The correlations between serum visfatin levels and HOMA-IR, FPG, FINS, BMI, T, TC, and TG were analyzed.ResultsOf all patients with PCOS, there were 82 in the KYD group (38.6%), 67 in the SYD group (31.6%), 37 in the SLQTH group (17.5%), and 26 in the KYIND group (12.3%). Visfatin levels in all PCOS subgroups were higher than those in the control group (P<0.01 or P<0.05). Among these subgroups, the visfatin levels in the SYD group were significantly higher than those in the other three TCM pattern groups (P<0.05). There were no statistical differences among the remaining three pattern groups. The levels of BMI, FINS, HOMA-IR, T, and TG were significantly higher in all subgroups than those in the control group (P<0.05). There were no significant differences in FPG and TC between all PCOS subgroups and the control group (P>0.05). The SYD group had higher levels of FINS and HOMA-IR compared with the KYD, SLQTH, and KYIND groups (P<0.05). In all subgroups, after controlling for BMI, TG, TC, and age, visfatin was positively correlated with FINS (r= 0.197, P=0.015) and HOMA-IR (r=0.173, P=0.033), and was not correlated with T.ConclusionKYD and SYD patterns are most common in PCOS patients. Increased visfatin is a common pathophysiologic manifestation in PCOS patients. The SYD group had the highest levels of visfatin, and visfatin was positively correlated with FINS and HOMA-IR

Timestamp-supervised Wearable-based Activity Segmentation and Recognition with Contrastive Learning and Order-Preserving Optimal Transport

Human activity recognition (HAR) with wearables is one of the serviceable technologies in ubiquitous and mobile computing applications. The sliding-window scheme is widely adopted while suffering from the multi-class windows problem. As a result, there is a growing focus on joint segmentation and recognition with deep-learning methods, aiming at simultaneously dealing with HAR and time-series segmentation issues. However, obtaining the full activity annotations of wearable data sequences is resource-intensive or time-consuming, while unsupervised methods yield poor performance. To address these challenges, we propose a novel method for joint activity segmentation and recognition with timestamp supervision, in which only a single annotated sample is needed in each activity segment. However, the limited information of sparse annotations exacerbates the gap between recognition and segmentation tasks, leading to sub-optimal model performance. Therefore, the prototypes are estimated by class-activation maps to form a sample-to-prototype contrast module for well-structured embeddings. Moreover, with the optimal transport theory, our approach generates the sample-level pseudo-labels that take advantage of unlabeled data between timestamp annotations for further performance improvement. Comprehensive experiments on four public HAR datasets demonstrate that our model trained with timestamp supervision is superior to the state-of-the-art weakly-supervised methods and achieves comparable performance to the fully-supervised approaches.Comment: Under Review (submitted to IEEE TMC

Combination of capecitabine and ludartin inhibits colon cancer growth in mice

Purpose: To investigate the efficacy of capecitabine and ludartin in the treatment of colon cancer in mice.Methods: Mice model of colon cancer was used in this study. Quantitative real-time polymerase chain reaction (Qrt-PCR) was used to quantify the expression of vascular endothelial growth factor (VEGF) mRNA. Micro-vessel density was assessed using immunohistochemical analysis.Results: When administered separately, capecitabine and ludartin treatments significantly suppressed tumor growth in the mice model of colon cancer for 4 weeks, compared to control group. Coadministration of capecitabine and ludartin significantly inhibited tumor growth for 6 weeks (p &lt; 0.05). Symptoms of colon cancer such as weight loss, skin discoloration and leukopenia were observed in untreated control group. However, these symptoms were completely absent in the group treated with combination of capecitabine and ludartin. The combined treatment also prevented colon cancer-induced increase in white blood cell (WBC) count, and increased median survival time of colon cancer mice from 38 to 55 days. Expression of VEGF in combination (capecitabine + ludartin) treatment group was significantly lower than in the control, i.e., untreated group (p ˂ 0.05). The combination treatment group also had significantly lower micro-vessel density in the tumor tissues, compared to the  ntreated control mice (p &lt; 0.05).Conclusion: These results show that a combination treatment of capecitabine and ludartin effectively inhibits colon tumor growth and angiogenesis in mice via a mechanism involving suppression of VEGF expression. Thus, capecitabine and ludartin combination is a potentially  uitable treatment for colon cancer.Keywords: Colon cancer, Mice, Ludartin, Leukopenia, VEGF expression, Angiogenesi

Effect of rosiglitazone on rabbit model of myocardial ischemia-reperfusion injury

AbstractObjectiveTo explore mechanism and protective effect of rosiglitazone on myocardial ischemia reperfusion (I/R) injury.MethodsA total of 48 male Japanese white big-ear rabbits were randomly divided into control group (A), I/R group (B), low dose of rosiglitazone group (C), high dose of rosiglitazone group (D). Plasma concentration of and also reduced the concentration of plasma serum creatine kinase (CK), CK-MB, high-sensitivity C-reactive protein (hsCRP), ultra-superoxide dismutase (SOD), malondialdehyde (MDA), lactic acid glutathione skin peroxidase (GSH-PX), nitric oxide (NO) and endothelin (ET) were measured 1 h later after I/R. Twenty-four hours after I/R the hearts were harvested for pathological and ultrastructural analysis. Area of myocardial infarction were tested.ResultsPlasma concentration of CK, CK-MB, hsCRP, NO, MDA and ET were decreased in C, D group compared with group B. Plasma concentration of T-SOD and GSH-Px were increased significantly in C, D group compared with group B. Compared with group B, pathological and ultrastructural changes in C and D group were slightly. There was significant difference in myocardial infarction area between group C, D and group B (P<0.05). Myocardial infarction area and arrhythmia rate were lower in group C, D compare with group B.ConclusionsRosiglitazone may protect myocardium from I/R injury by enhancing T-SOD and GSH-Px concentration, inhibit inflammatory reaction, and improve endothelial function

Ethyl 3,4-dimethyl-5-[(E)-(phenyl­imino)­meth­yl]-1H-pyrrole-2-carboxyl­ate

In the title compound, C16H18N2O2, the mol­ecule adopts an E conformation about the C=N double bond. The dihedral angle between the pyrrole and phenyl rings is 41.55 (8)°. In the crystal structure, pairs of inter­molecular N—H⋯O hydrogen bonds link the mol­ecules into centrosymmetric dimers. In the dimer, the two pyrrole rings are almost coplanar and the two phenyl rings are parallel to each other