Construction of Thioamide Peptide via Sulfur-Involved Amino Acids/Amino Aldehydes Coupling

A sulfur-involved ligation for thioamide quasi-peptides was developed via amino acids and amino aldehydes coupling. The key to the transformation was the chelation of copper with imines for chiral activation and fixation. In this environment, linear polysulfur decreased the alkalinity of single sulfur anions to prevent racemization caused by the interaction between sulfur and sodium sulfide. Dipeptides, tripeptides, tetrapeptides, and the linkage between the drug and amino acids were successfully obtained

Coupling of oxidative stress responses to tricarboxylic acid cycle and prostaglandin E₂ alterations in <i>Caenorhabditis elegans</i> under extremely low-frequency electromagnetic field

Purpose: With all-pervasive presence of extremely low-frequency electromagnetic field (ELF-EMF) in modern life, ELF-EMF has been regarded as an essential factor which may induce changes in many organisms. The objective of the present study was to investigate the physiological responses of Caenorhabditis elegans (C. elegans) to 50 Hz, 3 mT ELF-EMF exposure. Materials and methods: Worms were exposed to ELF-EMF from the egg stage until reaching the fourth larva (L4) stage. After exposure, expressions of the tricarboxylic acid (TCA) cycle enzymes were examined by qRT-PCR and western blot analysis. Two lipid metabolites were detected by GC-MS. Reactive oxygen species (ROS) level was detected by dichlorofluorescein staining and worm antioxidant system was investigated by enzymatic activity analysis, including detection of the superoxide dismutase and catalase (CAT) activity and the total antioxidant capacity (T-AOC). Results: The TCA cycle enzyme, fumarase was found with decreased expression under ELF-EMF exposure. And arachidonic acid (ArA) and prostaglandin E2(PGE2) showed elevated concentrations, with increased expression of prostaglandin E2 synthase (PGES-2) in ELF-EMF exposed worms. Significant elevation of ROS level was identified accompanied with the significant depression of T-AOC in response to ELF-EMF. Conclusions: Our results suggested that exposure to 50 Hz, 3 mT ELF-EMF in C. elegans can elicit disruptions of the TCA cycle metabolism and PGE2 formation, coupling ELF-EMF-induced oxidative stress responses. Our study probably will attract increasing attentions to the controllable application of ELF-EMF associated with health and disease.</p

Secondary metabolites isolated from the deep sea-derived fungus <i>Aspergillus sydowii</i> C1-S01-A7

Two novel compounds, 2-hydroxy-6-formyl-vertixanthone (1) and 12-O-acetyl-sydowinin A (2), were obtained from the culture of a deep sea-derived fungus Aspergillus sydowii C1-S01-A7, together with twenty-two known compounds (3–24). Their structures were elucidated based on extensive spectroscopic methods. Compounds 4, 8 and 12 showed antibacterial activities against Vibrio rotiferianus and Vibrio vulnificus. Compounds 1, 2, 7, 8, 11 and 12 exhibited antibacterial activity against methicillin-resistant Staphylococcus aureus. Remarkably, compound 8 displayed selectively cytotoxic activity against A549 and strongest cytotoxic activities for both A549 and HepG2 in comparison to the remaining compounds.</p

Characteristics of included studies (Ordered by the subgroup).

Characteristics of included studies (Ordered by the subgroup).</p

Additional file 1 of Acceptance of COVID-19 vaccination and influencing factors among people living with HIV in Guangxi, China: a cross-sectional survey

Additional file 1: Univariate and multivariate analysis for the other factors on the willingness to vaccination among PLWH

The ACF and PACF graphs of transformed hepatitis incidence series.

ACF = the autocorrelation function graph and PACF = partial autocorrelation graph. The possible values of q and Q were 1, 2, 3 and 1 basic on the ACF graph, and the possible values of p and P were 1, 2, 3 and 1 basic on the PACF graph.</p

The forecasting curves of the three models and the actual hepatitis incidence series.

ARIMA = the autoregressive integrated moving average; GRNN = the generalized regression neural network.</p

Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China

<div><p>Background</p><p>Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease.</p><p>Methods</p><p>The autoregressive integrated moving average (ARIMA) model and the generalized regression neural network (GRNN) model were used to fit the incidence data from the Heng County CDC (Center for Disease Control and Prevention) from January 2005 to December 2012. Then, the ARIMA-GRNN hybrid model was developed. The incidence data from January 2013 to December 2013 were used to validate the models. Several parameters, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and mean square error (MSE), were used to compare the performance among the three models.</p><p>Results</p><p>The morbidity of hepatitis from Jan 2005 to Dec 2012 has seasonal variation and slightly rising trend. The ARIMA(0,1,2)(1,1,1)₁₂ model was the most appropriate one with the residual test showing a white noise sequence. The smoothing factor of the basic GRNN model and the combined model was 1.8 and 0.07, respectively. The four parameters of the hybrid model were lower than those of the two single models in the validation. The parameters values of the GRNN model were the lowest in the fitting of the three models.</p><p>Conclusions</p><p>The hybrid ARIMA-GRNN model showed better hepatitis incidence forecasting in Heng County than the single ARIMA model and the basic GRNN model. It is a potential decision-supportive tool for controlling hepatitis in Heng County.</p></div

The funnel plots for publication bias.

<p>The red solid circle represents for PCR-based RDTMs, blue for ELISA-based RDTMs and green for other RDTMs. The areas of the circles stand for the number of cases. The Deek test was not significant (p = 0.69).</p

Monthly incidence of hepatitis from January 2005 to December 2012.

<p>Monthly incidence of hepatitis from January 2005 to December 2012.</p