Liquid Chicken Oil Could Be a Healthy Dietary Oil.

Liquid chicken oil is similar to the human lipid ratio, and is similar to the ideal fatty acids ratio suggested by Hayes, but its benefits remain unclear (Hwang, K.N.; Tung, H.P.; Shaw, H.M. J. Oleo. Sci. 69, 199-206 (2020)). Using soybean oil as a control, liquid chicken oil, coconut oil, lard oil, and olive oil, were tested on SD rats with the rodent diet 5001 plus 1% of high cholesterol addition and moderate 10 % of test oils. Positive results showed that a 10% liquid chicken oil diet reduced LDL and triglycerides, atherogenic index while increasing superoxide dismutase more than the soybean oil control (0.05 ≦ p < 0.10). Moreover, increment of hepatic endogenous glutathione peroxidase was found to be significantly different from the soybean oil control (p < 0.05). In this study, liquid chicken oil had more benefits than vegetable soybean dietary oil, with little evidence of hyperlipidemia. Comparison of the test oils with categories of fatty acids to the idea ratio SFA : MUFA : PUFA = 1 : 1.5 : 1, scored by its average weight implied a parallel trend of lipidemia and hepatic antioxidant activity to its score. It is difficult to use the test of rat to reflect human physiology, it remain 19% different of the fatty acids ratio from human ratio, however, this study reveal that the healthiness of a dietary oil seems relate well to its compatibility to the idea ratio or the host oil ratio, in this case, it is the human ratio.

Rbm24 Regulates Alternative Splicing Switch in Embryonic Stem Cell Cardiac Lineage Differentiation.

The transition of embryonic stem cell (ESC) pluripotency to differentiation is accompanied by an expansion of mRNA and proteomic diversity. Post-transcriptional regulation of ESCs is critically governed by cell type-specific splicing. However, little is known about the splicing factors and the molecular mechanisms directing ESC early lineage differentiation. Our study identifies RNA binding motif protein 24 (Rbm24) as a key splicing regulator that plays an essential role in controlling post-transcriptional networks during ESC transition into cardiac differentiation. Using an inducible mouse ESC line in which gene expression could be temporally regulated, we demonstrated that forced expression of Rbm24 in ESCs dramatically induced a switch to cardiac specification. Genome-wide RNA sequencing analysis identified more than 200 Rbm24-regulated alternative splicing events (AS) which occurred in genes essential for the ESC pluripotency or differentiation. Remarkably, AS genes regulated by Rbm24 composed of transcriptional factors, cytoskeleton proteins, and ATPase gene family members which are critical components required for cardiac development and functionality. Furthermore, we show that Rbm24 regulates ESC differentiation by promoting alternative splicing of pluripotency genes. Among the Rbm24-regulated events, Tpm1, an actin filament family gene, was identified to possess ESC/tissue specific isoforms. We demonstrated that these isoforms were functionally distinct and that their exon AS switch was essential for ESC differentiation. Our results suggest that ESC's switching into the differentiation state can be initiated by a tissue-specific splicing regulator, Rbm24. This finding offers a global view on how an RNA binding protein influences ESC lineage differentiation by a splicing-mediated regulatory mechanism. Stem Cells 2016;34:1776-1789.

An accurate and efficient method to predict the electronic excitation energies of BODIPY fluorescent dyes.

Recently, the extreme learning machine neural network (ELMNN) as a valid computing method has been proposed to predict the nonlinear optical property successfully (Wang et al., J. Comput. Chem. 2012, 33, 231). In this work, first, we follow this line of work to predict the electronic excitation energies using the ELMNN method. Significantly, the root mean square deviation of the predicted electronic excitation energies of 90 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivatives between the predicted and experimental values has been reduced to 0.13 eV. Second, four groups of molecule descriptors are considered when building the computing models. The results show that the quantum chemical descriptions have the closest intrinsic relation with the electronic excitation energy values. Finally, a user-friendly web server (EEEBPre: Prediction of electronic excitation energies for BODIPY dyes), which is freely accessible to public at the web site: http://202.198.129.218, has been built for prediction. This web server can return the predicted electronic excitation energy values of BODIPY dyes that are high consistent with the experimental values. We hope that this web server would be helpful to theoretical and experimental chemists in related research.

A promising tool to achieve chemical accuracy for density functional theory calculations on Y-NO homolysis bond dissociation energies.

A DFT-SOFM-RBFNN method is proposed to improve the accuracy of DFT calculations on Y-NO (Y = C, N, O, S) homolysis bond dissociation energies (BDE) by combining density functional theory (DFT) and artificial intelligence/machine learning methods, which consist of self-organizing feature mapping neural networks (SOFMNN) and radial basis function neural networks (RBFNN). A descriptor refinement step including SOFMNN clustering analysis and correlation analysis is implemented. The SOFMNN clustering analysis is applied to classify descriptors, and the representative descriptors in the groups are selected as neural network inputs according to their closeness to the experimental values through correlation analysis. Redundant descriptors and intuitively biased choices of descriptors can be avoided by this newly introduced step. Using RBFNN calculation with the selected descriptors, chemical accuracy (≤1 kcal·mol(-1)) is achieved for all 92 calculated organic Y-NO homolysis BDE calculated by DFT-B3LYP, and the mean absolute deviations (MADs) of the B3LYP/6-31G(d) and B3LYP/STO-3G methods are reduced from 4.45 and 10.53 kcal·mol(-1) to 0.15 and 0.18 kcal·mol(-1), respectively. The improved results for the minimal basis set STO-3G reach the same accuracy as those of 6-31G(d), and thus B3LYP calculation with the minimal basis set is recommended to be used for minimizing the computational cost and to expand the applications to large molecular systems. Further extrapolation tests are performed with six molecules (two containing Si-NO bonds and two containing fluorine), and the accuracy of the tests was within 1 kcal·mol(-1). This study shows that DFT-SOFM-RBFNN is an efficient and highly accurate method for Y-NO homolysis BDE. The method may be used as a tool to design new NO carrier molecules.

Differential protein profile in zebrafish (Danio rerio) brain under the joint exposure of methyl parathion and cadmium.

As different chemicals, methyl parathion (MP) and cadmium (Cd) can induce neurotoxicity on the brain of aquatic ecosystems. This study aims to explore the differential expression proteins in the brain induced by their joint stress and their joint effects, which are poorly reported, and devotes finding novel biomarkers for monitoring their contamination in water and assessing their neurological effects. The bioaccumulation of MP and Cd in tissues after 96 h of exposure was first analyzed by GC and inductively coupled plasma-MS to provide insights into the interaction. Protein profile changes in the brains of the zebrafish (Danio rerio) exposed to MP and Cd were further investigated using the proteomic approach. The correlation of gene expression on the transcription level of mRNA and the translation level of protein was examined by real-time quantitative PCR and Western blotting analysis. It showed that Cd and MP have an interaction on their bioaccumulation, which suggests that their joint effect over 96 h might be antagonistic. Proteomics revealed that 22 protein spots changed their expression levels under stress, of which 16 proteins were identified using MS. These proteins were involved in oxidation/reduction, metabolism, energy production, receptor activity, and cytoskeleton assembly. Among them, five proteins with a remarkable abundance change are significantly suggested to play important roles in the joint effect. This work demonstrates that there exists an interaction between MP and Cd toxicities, which may aid in our understanding of the mechanism of neurotoxicity induced by joint stress. The results may also provide the possibility of the establishment of candidate biomarkers for monitoring MP and Cd contamination in water.

Improving the accuracy of Density Functional Theory (DFT) calculation for homolysis bond dissociation energies of Y-NO bond: generalized regression neural network based on grey relational analysis and principal component analysis.

We propose a generalized regression neural network (GRNN) approach based on grey relational analysis (GRA) and principal component analysis (PCA) (GP-GRNN) to improve the accuracy of density functional theory (DFT) calculation for homolysis bond dissociation energies (BDE) of Y-NO bond. As a demonstration, this combined quantum chemistry calculation with the GP-GRNN approach has been applied to evaluate the homolysis BDE of 92 Y-NO organic molecules. The results show that the ull-descriptor GRNN without GRA and PCA (F-GRNN) and with GRA (G-GRNN) approaches reduce the root-mean-square (RMS) of the calculated homolysis BDE of 92 organic molecules from 5.31 to 0.49 and 0.39 kcal mol(-1) for the B3LYP/6-31G (d) calculation. Then the newly developed GP-GRNN approach further reduces the RMS to 0.31 kcal mol(-1). Thus, the GP-GRNN correction on top of B3LYP/6-31G (d) can improve the accuracy of calculating the homolysis BDE in quantum chemistry and can predict homolysis BDE which cannot be obtained experimentally.

[Comparative pharmacokinetic analysis based on nonlinear mixed effect model].

Comparative pharmacokinetic (PK) analysis is often carried out throughout the entire period of drug development, the common approach for the assessment of pharmacokinetics between different treatments requires that the individual PK parameters, which employs estimation of 90% confidence intervals for the ratio of average parameters, such as AUC and Cmax, these 90% confidence intervals then need to be compared with the pre-specified equivalent interval, and last we determine whether the two treatments are equivalent. Unfortunately in many clinical circumstances, some or even all of the individuals can only be sparsely sampled, making the individual evaluation difficult by the conventional non-compartmental analysis. In such cases, nonlinear mixed effect model (NONMEM) could be applied to analyze the sparse data. In this article, we simulated a sparsely sampling design trial based on the dense sampling data from a truly comparative PK study. The sparse data were analyzed with NONMEM method, and the original dense data were analyzed with non-compartment analysis. Although the trial design and analysis methods are different, the 90% confidence intervals for the ratio of PK parameters based on 1000 Bootstrap are very similar, indicated that the analysis based on NONMEM is a reliable method to treat with the sparse data in the comparative pharmacokinetic study.

[In vitro pharmacodynamic interactions of antitumor effect of the combination of adriamycin and curcumin evaluated by the parameter method and the response surface].

The paper aimed to find the optimal combination and evaluation of the interactions of antitumor effect of the curcumin (Cur) and adriamycin (ADM) in vitro. According to the factorial design and data characteristics, the parameter method combined with the response surface approach were used to analyze the pharmacodynamic interactions of in vitro antitumor effects of the combination of Cur and ADM at different dosages. The results showed that the dose-effect relationship of the combination with the ratio of ADM-Cur 1:3 showed significant differences in comparison with either used alone. The dose-effect curve was shift left in combination. The combination of adriamycin (ADM, 0.693-2.132 micromol L(-1)) and curcumin (Cur, 2.047-6.304 micromol L(-1)) with a fixed ratio (1:3) showed a synergism. With increasing doses of the combination, there is an additive effect. Computer simulation showed a trend of decreasing difference between the observed and expected effects with the dose increasing in Cur from 6.304 to 16.0 micromol L(-1) and ADM from 2.132 to 5.3 micromol L(-1). The response surface analysis showed the optimal combination to be Cur 18.50 micromol L(-1) and ADM 3.89 micromol L(-1) with a ratio of 5:1. This study suggests that the parameter method combined with the response surface analysis provides richer and more reasonable information, and is helpful for quantitative design of drug combination therapy and to describe the nature and degree of drug interaction.

Improving the accuracy of low level quantum chemical calculation for absorption energies: the genetic algorithm and neural network approach.

The combination of genetic algorithm and back-propagation neural network correction approaches (GABP) has successfully improved the calculation accuracy of absorption energies. In this paper, the absorption energies of 160 organic molecules are corrected to test this method. Firstly, the GABP1 is introduced to determine the quantitative relationship between the experimental results and calculations obtained by using quantum chemical methods. After GABP1 correction, the root-mean-square (RMS) deviations of the calculated absorption energies reduce from 0.32, 0.95 and 0.46 eV to 0.14, 0.19 and 0.18 eV for B3LYP/6-31G(d), B3LYP/STO-3G and ZINDO methods, respectively. The corrected results of B3LYP/6-31G(d)-GABP1 are in good agreement with experimental results. Then, the GABP2 is introduced to determine the quantitative relationship between the results of B3LYP/6-31G(d)-GABP1 method and calculations of the low accuracy methods (B3LYP/STO-3G and ZINDO). After GABP2 correction, the RMS deviations of the calculated absorption energies reduce to 0.20 and 0.19 eV for B3LYP/STO-3G and ZINDO methods, respectively. The results show that the RMS deviations after GABP1 and GABP2 correction are similar for B3LYP/STO-3G and ZINDO methods. Thus, the B3LYP/6-31G(d)-GABP1 is a better method to predict absorption energies and can be used as the approximation of experimental results where the experimental results are unknown or uncertain by experimental method. This method may be used for predicting absorption energies of larger organic molecules that are unavailable by experimental methods and by high-accuracy theoretical methods with larger basis sets. The performance of this method was demonstrated by application to the absorption energy of the aldehyde carbazole precursor.

An accurate density functional theory calculation for electronic excitation energies: the least-squares support vector machine.

Support vector machines (SVMs), as a novel type of learning machine, has been very successful in pattern recognition and function estimation problems. In this paper we introduce least-squares (LS) SVMs to improve the calculation accuracy of density functional theory. As a demonstration, this combined quantum mechanical calculation with LS-SVM correction approach has been applied to evaluate the electronic excitation energies of 160 organic molecules. The newly introduced LS-SVM approach reduces the root-mean-square deviation of the calculated electronic excitation energies of 160 organic molecules from 0.32 to 0.11 eV for the B3LYP/6-31G(d) calculation. Thus, the LS-SVM correction on top of B3LYP/6-31G(d) is a better method to correct electronic excitation energies and can be used as the approximation of experimental results which are impossible to obtain experimentally.

[Expression of the soluble human Fas ligand in Dictyostelium discoideum].

An expression system is described for high-yield production of recombinant soluble human FasL (shFasL) in Dictyostelium discoideum cells. DNA encoding amino acids 141 - 281 of hFasL was PCR amplified from cDNA derived from activated human neutrophils. The resulting product was fused with a DNA fragment encoding hCG-beta signal peptide and cloned in the expression vector pMB12neo. Dictyostelium strain AX3 was transfected with this plasmid, yielding a recombinant strain called AX3-pCESFL95-H3. In order to improve the shFasL expression level, pMB12neo was optimized by replacing its transcriptional terminator/ polyadenylation segment of the 2H3 gene with an actin8 terminator/polyadenylation segment, yielding derived expression vector pMB74. The recombinant Dictyostelium strain called AX3-pLu8 was generated with this new plasmid. When the recombinant cells were cultivated in a complex HL-5C medium, a cell density of (1.5 - 2) x 10(7)/mL was reached, and the shFasL level expressed by strains AX3-pCESFL95-H3 and AX3-pLu8 was 23.5 microg/L and 206 microg/L, respectively. By using a newly developed synthetic medium called SIH as culture medium, higher cell density of (4 - 5) x 10(7)/mL was achieved. Correspondently, 111 microg/L and 420 microg/L shFasL were secreted by recombinant strains AX3-pCESFL95-H3 and AX3-pLu8, respectively.

[Observation of course of placental separation by continuous dynamic ultrasonography during third stage of labor].

OBJECTIVE: To investigate the physiologic course of third stage of labor, and to judge the optimal time of natural placental separation permitted. METHODS: To observe and record the course of third stage of labor by continuous dynamic ultrasonography and to estimate the total amount of blood loss from placental separation within two hours after delivery by the method of weighing lost blood. RESULTS: Third stage of labor can be divided into four phases: the latent phase (4.37 +/- 3.78) min, the contraction phase (1.48 +/- 0.97) min, the detachment phase (0.50 +/- 0.00) min, and the expulsion phase (0.62 +/- 2.23) min. In 85% of the puerperas the third stage of labor takes about 10 minutes (average 6.94 minutes). The amount of postpartum hemorrhage and the risk of the patient increased prominently if the time of stage of labor was longer than 10 minutes (P < 0.01). CONCLUSION: The third stage of labor must be limited in 10 minutes to prevent postpartum hemorrhage.

[Uptake of nickel from industrial wastewater by genetically engineered Escherichia coli JM109].

Heavy metal wastewater poses a serious threat to the environment. In comparison to the existing methods of chemical precipitation, ion exchange and carbon adsorption, biosorption is an attractive alternative for the recovery of heavy metals from industrial effluents. However, nickel ion, different from other heavy metal ions, is a more recalcitrant pollutant and has low affinity to many metal tolerant microorganisms. In this study, Escherichia coli JM109 was genetically engineered to simultaneously express a Ni2+ transport system (the product of nixA gene) andoverexpress metallothionein (MT). NixA protein has a high affinity for Ni2+, and metallothioneins (MTs) are capable of binding a variety of heavy metals including Ni2+ . The Ni2+ bioaccumulation performance of the genetically engineered E. coli JM109 was evaluated. Time-course test showed that the bioaccumulation rate was rapid, and 95% of the accumulation was achieved within the first 10 minutes. The maximum Ni2+ bioaccumulation by genetically engineered E. coli cells was dramatically increased from 1.54 mg/g to 10.11mg/g, a more than five-fold increase than that of the original E. coli strain. The isotherm was of Langmuir type. Within the tested pH range (pH 4-10), the engineered cells displayed more resistance to pH variation, retaining up to 80% of the Ni2+ binding capacity at pH 4, while the original E. coli host cells lost 80% of Ni2+ binding capacity at pH 4. The presence of Na+ and Ca2+ affected Ni2+ bioaccumulation, but the effects were not serious, as 71% and 66% of the Ni2+ binding capacities were retained respectively at the concentrations of 1000 mg/L Na+ and 1000 mg/L Ca2+ . However, Mg2+ exerted a severe adverse effect on Ni2+ bioaccumulation, 83% of Ni2+ accumulating capacity was lost when Mg2+ concentration reached 200 mg/L. The effects of different kinds of heavy metals on Ni2+ accumulating were different. The genetically engineered E. coli cell lost less than 45% of its Ni2+ bioaccumulation activity in the presence of 50 mg/L lead or cadmium, 66% in the presence of 25mg/L mercury and 84% in the presence of 40 mg/L copper. The presence of glucose did not improve Ni2+ uptake. Our study suggests that the genetically engineered E. coli JM109 has potential application for effective and efficient recovery of nickel from aqueous solutions.