Polysaccharides Obtained from Cordyceps militaris Alleviate Hyperglycemia by Regulating Gut Microbiota in Mice Fed a High-Fat/Sucrose Diet.

Polysaccharides isolated from fungus Cordyceps militaris display multi-biofunctions, such as immunostimulation, down-regulation of hyperlipidemia, and anti-cancer function. The occurrence of obesity and metabolic syndrome is related to the imbalance of gut microbiota. In this study, the effects of C. militaris and its fractions on modifying metabolic syndrome in mice were evaluated. Mice were fed a high-fat/high-sucrose diet (HFSD) for 14 weeks to induce body weight increase and hyperlipidemia symptoms in mice, and then the mice were simultaneously given a HFSD and C. militaris samples for a further 8 weeks. The results indicated that the fruit body, polysaccharides, and cordycepin obtained from C. militaris had different efficacies on regulating metabolic syndrome and gut microbiota in HFSD-treated mice. Polysaccharides derived from C. militaris decreased the levels of blood sugar and serum lipids in mice fed HFSD. In addition, C. militaris-polysaccharide treatment obviously improved intestinal dysbiosis through promoting the population of next generation probiotic Akkermansia muciniphila in the gut of mice fed HFSD. In conclusion, polysaccharides derived from C. militaris have the potential to act as dietary supplements and health food products for modifying the gut microbiota to improve the metabolic syndrome.

The applications of Lactobacillus plantarum-derived extracellular vesicles as a novel natural antibacterial agent for improving quality and safety in tuna fish.

Bacteria release membrane vesicles into the extracellular environment but which activity is unclear. We investigated the applications of extracellular vesicles (EVs) isolated from probiotic Lactobacillus plantarum to protect tuna fish against spoilage and quality loss in this study. A significant difference was found in EVs size obtained from L. plantarum after 8, 24, and 48 hr incubation. The L. plantarum-derived EVs were collected and used to confirm the anti-bacterial activity versus Shewanella putrefaciens. Finally, the tuna fish was stored at 4 °C for 5 days after coating with EVs or sodium erythorbate, and the quality indexes were assayed. Results indicated that EVs markedly inhibited oxidation reaction, total volatile base nitrogen (TVBN), peroxide value (PV), malondialdehyde (MDA), and bacteria levels. These results finding out that EVs from L. plantarum may have potential for application in food storage technology. Overall, we indicated this new material may be developed as an anti-bacterial agent for prolonging the shelf life of tuna fish.

Comparison and improvement of the predictability and interpretability with ensemble learning models in QSPR applications.

Ensemble learning helps improve machine learning results by combining several models and allows the production of better predictive performance compared to a single model. It also benefits and accelerates the researches in quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR). With the growing number of ensemble learning models such as random forest, the effectiveness of QSAR/QSPR will be limited by the machine's inability to interpret the predictions to researchers. In fact, many implementations of ensemble learning models are able to quantify the overall magnitude of each feature. For example, feature importance allows us to assess the relative importance of features and to interpret the predictions. However, different ensemble learning methods or implementations may lead to different feature selections for interpretation. In this paper, we compared the predictability and interpretability of four typical well-established ensemble learning models (Random forest, extreme randomized trees, adaptive boosting and gradient boosting) for regression and binary classification modeling tasks. Then, the blending methods were built by summarizing four different ensemble learning methods. The blending method led to better performance and a unification interpretation by summarizing individual predictions from different learning models. The important features of two case studies which gave us some valuable information to compound properties were discussed in detail in this report. QSPR modeling with interpretable machine learning techniques can move the chemical design forward to work more efficiently, confirm hypothesis and establish knowledge for better results.

Random Forest Model with Combined Features: A Practical Approach to Predict Liquid-crystalline Property.

Quantitative structure-property relationships were developed to predict the liquid crystalline (LC) of a large dataset of aromatic organic compounds using machine learning algorithms and different molecular descriptors. The aim of this study was to find appropriate models and descriptors for the prediction of a large variety of liquid crystalline behaviors. Furthermore, descriptor calculations based on LC structural templates were proposed to understand the structural effects on the LC behaviors. The results suggest that random forest classifier and combined features which consists of structural templates were usable for LC behavior prediction. The best performance of prediction models showed high accuracy and F1 score (90 % and 93 %). Furthermore, the random forest has strong abilities to large input feature, quick training and easy model-tuning for constructing LC prediction model. Therefore, the prediction model allows experimentalists to seek the synthesis of a predicted molecule that would exhibit the desired LC properties to accelerate the progress in the discovery of new LC materials.

Random Forest Approach to QSPR Study of Fluorescence Properties Combining Quantum Chemical Descriptors and Solvent Conditions.

The Quantitative Structure - Property Relationship (QSPR) approach was performed to study the fluorescence absorption wavelengths and emission wavelengths of 413 fluorescent dyes in different solvent conditions. The dyes included the chromophore derivatives of cyanine, xanthene, coumarin, pyrene, naphthalene, anthracene and etc., with the wavelength ranging from 250 nm to 800 nm. An ensemble method, random forest (RF), was employed to construct nonlinear prediction models compared with the results of linear partial least squares and nonlinear support vector machine regression models. Quantum chemical descriptors derived from density functional theory method and solvent information were also used by constructing models. The best prediction results were obtained from RF model, with the squared correlation coefficients [Formula: see text] of 0.940 and 0.905 for λabs and λem, respectively. The descriptors used in the models were discussed in detail in this report by comparing the feature importance of RF.

Direct observation of Ru-alkylidene forming into ethylene in ring-closing metathesis from hyperpolarized 1H NMR.

Ring-closing metathesis was monitored using real-time NMR of 1H hyperpolarized olefins at room temperature. By applying a selective saturation to an observable intermediate, its protons were found to transfer to ethylene. The intermediate was thus identified as a Ru-alkylidene species, which appears in the ethylene formation pathway.

Intermolecular interactions determined by NOE build-up in macromolecules from hyperpolarized small molecules.

The nuclear Overhauser effect (NOE) is a primary means to characterize intermolecular interactions using modern NMR spectroscopy. Multiple experiments measured using different mixing time can be used for quantifying NOE buildup and measuring cross-relaxation rates. However, this approach using conventional multi-dimensional NMR is time consuming. Hyperpolarization by dissolution dynamic nuclear polarization (D-DNP) can generate deviations from equilibrium spin polarization by orders of magnitude, thereby enhancing signals and allowing to characterize NOE build up in real-time. Since most small molecules can be hyperpolarized using D-DNP, this method is applicable to the study of intermolecular interactions between small molecules and macromolecules. This application is demonstrated using a model system for host-guest interactions including the third generation polyamidoamine dendrimer (G3 PAMAM) and the pharmaceutical phenylbutazone (PBZ). After mixing 1H hyperpolarized PBZ with PAMAM, the NOE build up is directly observed at different sites of the dendrimer in series of one-dimensional NMR spectra. Cross-relaxation rates specific to individual source and target spins are determined from the build up curves. Further, the polarization enhancement is shown to be sufficiently large to allow identification of cross-peaks not observed in a conventional 2D-NOESY spectrum. The improved signal-to-noise ratio provided by hyperpolarization allows for characterizing the intermolecular interaction in an almost instantaneous measurement, opening an application to macromolecular and biomacromolecular NMR.

Milli-tesla NMR and spectrophotometry of liquids hyperpolarized by dissolution dynamic nuclear polarization.

Hyperpolarization methods offer a unique means of improving low signal strength obtained in low-field NMR. Here, simultaneous measurements of NMR at a field of 0.7mT and laser optical absorption from samples hyperpolarized by dissolution dynamic nuclear polarization (D-DNP) are reported. The NMR measurement field closely corresponds to a typical field encountered during sample injection in a D-DNP experiment. The optical spectroscopy allows determination of the concentration of the free radical required for DNP. Correlation of radical concentration to NMR measurement of spin polarization and spin-lattice relaxation time allows determination of relaxivity and can be used for optimization of the D-DNP process. Further, the observation of the nuclear Overhauser effect originating from hyperpolarized spins is demonstrated. Signals from (1)H and (19)F in a mixture of trifluoroethanol and water are detected in a single spectrum, while different atoms of the same type are distinguished by J-coupling patterns. The resulting signal changes of individual peaks are indicative of molecular contact, suggesting a new application area of hyperpolarized low-field NMR for the determination of intermolecular interactions.

In Situ Determination of Tacticity, Deactivation, and Kinetics in [rac-(C2H4(1-Indenyl)2)ZrMe][B(C6F5)4] and [Cp2ZrMe][B(C6F5)4]-Catalyzed Polymerization of 1-Hexene Using (13)C Hyperpolarized NMR.

The stereochemistry, kinetics, and mechanism of olefin polymerization catalyzed by a set of zirconium-based metallocenes was studied by NMR using dissolution dynamic nuclear polarization (DNP). Hyperpolarized 1-hexene was polymerized in situ with a C2 symmetric catalyst, [(EBI)ZrMe][B(C6F5)4] (EBI = rac-(C2H4(1-indenyl)2)), and a C2v symmetric catalyst, [(Cp)2ZrMe][B(C6F5)4] (Cp = cyclopentadienyl). Hyperpolarized (13)C NMR spectra were used to characterize product tacticity following initiation of the reaction. At the same time, a signal gain of 3 orders of magnitude from (13)C hyperpolarization enabled the real time observation of catalyst-polymeryl species and deactivation products, such as vinylidene and a Zr-allyl complex. The compounds appearing in the reaction provide evidence for the existence of ß-hydride elimination and formation of a dormant site via a methane-generating mechanism. The presence of a deactivating mechanism was incorporated in a model used to determine kinetic parameters of the reaction. On this basis, rate constants were measured between 0.8 and 6.7 mol % of catalyst. The concentration dependence of the rate constants obtained indicates a second-order process for polymerization concomitant with a first-order process for deactivation. The simultaneous observation of both processes in the time evolution of (13)C NMR signals over the course of several seconds underlines the utility of hyperpolarized NMR for quantifying early events in polymerization reactions.

Asymmetric synthesis of bis-tetrahydrofuran cores in annonaceous acetogenins.

The bis-THF cores of annonaceous acetogenins were synthesized using (3R,4R)-1,5-hexadiene-3,4-diol (1) as the sole source of carbon atoms. The methylene acetal function was applied as a new linker/tether to facilitate the ring-closing metathesis.

Effects of open burning of rice straw on concentrations of atmospheric polycyclic aromatic hydrocarbons in central Taiwan.

The sizes and concentrations of 21 atmospheric polycyclic aromatic hydrocarbons (PAHs) were measured at Jhu-Shan (a rural site) and Sin-Gang (a town site) in central Taiwan in October and December 2005. Air samples were collected using semi-volatile sampling trains (PS-1 sampler) over 16 days for rice-straw burning and nonburning periods. These samples were then analyzed using a gas chromatograph with a flame-ionization detector (GC/FID). Particle-size distributions in the particulate phase show a bimode, peaking at 0.32-0.56 microm and 3.2-5.6 microm at the two sites during the nonburning period. During the burning period, peaks also appeared at 0.32-0.56 microm and 3.2-5.6 microm at Jhu-Shan, with the accumulation mode (particle size between 0.1 and 3.2 microm) accounting for approximately 74.1% of total particle mass. The peaks at 0.18-0.32 microm and 1.8-3.2 microm at Shin-Gang had an accumulation mode accounting for approximately 70.1% of total particle mass. The mass median diameter (MMD) of 3.99-4.35 microm in the particulate phase suggested that rice-straw burning generated increased numbers of coarse particles. The concentrations of total PAHs (sum of 21 gases + particles) at the Jhu-Shan site (Sin-Gang site) were 522.9 +/- 111.4 ng/ml (572.0 +/- 91.0 ng/ml) and 330.1 +/- 17.0 ng/ml (or 427.5 +/- 108.0 ng/ml) during burning and nonburning periods, respectively, accounting for a roughly 58% (or 34%) increase in the concentrations of total PAHs due to rice-straw burning. On average, low-weight PAHs (about 87.0%) represent the largest proportion of total PAHs, followed by medium-weight PAHs (7.1%), and high-weight PAHs (5.9%). Combustion-related PAHs during burning periods were 1.54-2.57 times higher than those during nonburning periods. The results of principal component analysis (PCA)/absolute principal component scores (APCS) suggest that the primary pollution sources at the two sites are similar and include vehicle exhaust, coal/wood combustion, incense burning, and incineration emissions. Open burning of rice straw was estimated to contribute approximately 5.0-33.5% to the total atmospheric PAHs at the two sites.

Acute idiopathic syringomyelia: a case report.

There have been isolated reports in the literature of the natural history and less than complete knowledge of the epidemiology and pathophysiology of syringomyelia. This article describes a clinically acute-onset abnormal patient with localized dilatation of the central canal of the spinal cord who had no evidence of present or prior Chiari's malformation, trauma, infection, tumor, or other predisposing pathologic condition. It is suggested that this distinct condition be labeled "acute idiopathic syringomyelia".