Structural Characteristics and Antioxidative Capability of the Soluble Polysaccharides Present in Dictyophora indusiata

Dictyophora indusiata (Vent. ex Pers.) Fish Phallaceae (Chinese name Zhu-Sūn, the bamboo fungi) has been used as a medicinal mushroom to treat many inflammatory, gastric and neural diseases since 618 AD in China. We hypothesize that the soluble polysaccharides (SP) present in D. indusiata and their monosaccharide profiles can act as an important role affecting the antioxidative capability, which in turn would influence the biological activity involving anti-inflammatory, immune enhancing and anticancer. We obtained six SP fractions and designated them as D1, a galactoglucan; D2, a galactan; D3, the isoelectrically precipitated riboglucan from 2% NaOH; D4, a myoinositol; D5 and D6, the mannogalactans. The total SP accounted for 37.44% w/w, their molecular weight (MW) ranged within 801–4656 kDa. D3, having the smallest MW 801 kDa, exhibited the most potent scavenging effect against the α,α-diphenyl-β-picrylhydrazyl, •OH−, and •O2− radicals, yielding IC50 values 0.11, 1.02 and 0.64 mg mL−1, respectively. Thus we have confirmed our hypothesis that the bioactivity of D. indusiata is related in majority, if not entirely, to its soluble polysaccharide type regarding the MW and monosaccharide profiles

Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network

The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC) patients undergoing resection between artificial neural network (ANN) and logistic regression (LR) models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. We constructed a prognostic model for 434 patients with 21 potential input variables by Cox regression model. Model performance was measured by numbers of significant predictors and predictive accuracy. The results indicated that ANN had double to triple numbers of significant predictors at 1-, 3-, and 5-year survival models as compared with LR models. Scores of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of 1-, 3-, and 5-year survival estimation models using ANN were superior to those of LR in all the training sets and most of the validation sets. The study demonstrated that ANN not only had a great number of predictors of mortality variables but also provided accurate prediction, as compared with conventional methods. It is suggested that physicians consider using data mining methods as supplemental tools for clinical decision-making and prognostic evaluation

Isolation, Culture and Characterization of Hirsutella sinensis Mycelium from Caterpillar Fungus Fruiting Body

The caterpillar fungus Ophiocordyceps sinensis (previously called Cordyceps sinensis) has been used for centuries in Asia as a tonic to improve health and longevity. Recent studies show that O. sinensis produces a wide range of biological effects on cells, laboratory animals and humans, including anti-fatigue, anti-infection, anti-inflammatory, antioxidant, and anti-tumor activities. In view of the rarity of O. sinensis fruiting bodies in nature, cultivation of its anamorph mycelium represents a useful alternative for large-scale production. However, O. sinensis fruiting bodies harvested in nature harbor several fungal contaminants, a phenomenon that led to the isolation and characterization of a large number of incorrect mycelium strains. We report here the isolation of a mycelium from a fruiting body of O. sinensis and we identify the isolate as O. sinensis’ anamorph (also called Hirsutella sinensis) based on multi-locus sequence typing of several fungal genes (ITS, nrSSU, nrLSU, RPB1, RPB2, MCM7, β-tubulin, TEF-1α, and ATP6). The main characteristics of the isolated mycelium, including its optimal growth at low temperature (16°C) and its biochemical composition, are similar to that of O. sinensis fruiting bodies, indicating that the mycelium strain characterized here may be used as a substitute for the rare and expensive O. sinensis fruiting bodies found in nature

Ganoderma Lucidum Stimulates Autophagy-Dependent Longevity Pathways in Caenorhabditis Elegans and Human Cells

The medicinal fungus Ganoderma lucidum is used as a dietary supplement and health tonic, but whether it affects longevity remains unclear. We show here that a water extract of G. lucidum mycelium extends lifespan of the nematode Caenorhabditis elegans. The G. lucidum extract reduces the level of fibrillarin (FIB-1), a nucleolar protein that correlates inversely with longevity in various organisms. Furthermore, G. lucidum treatment increases expression of the autophagosomal protein marker LGG-1, and lifespan extension is abrogated in mutant C. elegans strains that lack atg-18, daf-16, or sir-2.1, indicating that autophagy and stress resistance pathways are required to extend lifespan. In cultured human cells, G. lucidum increases concentrations of the LGG-1 ortholog LC3 and reduces levels of phosphorylated mTOR, a known inhibitor of autophagy. Notably, low molecular weight compounds (\u3c10 kDa) isolated from the G. lucidum water extract prolong lifespan of C. elegans and the same compounds induce autophagy in human cells. These results suggest that G. lucidum can increase longevity by inducing autophagy and stress resistance

Role of the CCAAT-Binding Protein NFY in SCA17 Pathogenesis

Spinocerebellar ataxia 17 (SCA17) is caused by expansion of the polyglutamine (polyQ) tract in human TATA-box binding protein (TBP) that is ubiquitously expressed in both central nervous system and peripheral tissues. The spectrum of SCA17 clinical presentation is broad. The precise pathogenic mechanism in SCA17 remains unclear. Previously proteomics study using a cellular model of SCA17 has revealed reduced expression of heat shock 70 kDa protein 5 (HSPA5) and heat shock 70 kDa protein 8 (HSPA8), suggesting that impaired protein folding may contribute to the cell dysfunction of SCA17 (Lee et al., 2009). In lymphoblastoid cells, HSPA5 and HSPA8 expression levels in cells with mutant TBP were also significantly lower than that of the control cells (Chen et al., 2010). As nuclear transcription factor Y (NFY) has been reported to regulate HSPA5 transcription, we focused on if NFY activity and HSPA5 expression in SCA17 cells are altered. Here, we show that TBP interacts with NFY subunit A (NFYA) in HEK-293 cells and NFYA incorporated into mutant TBP aggregates. In both HEK-293 and SH-SY5Y cells expressing TBP/Q61∼79, the level of soluble NFYA was significantly reduced. In vitro binding assay revealed that the interaction between TBP and NFYA is direct. HSPA5 luciferase reporter assay and endogenous HSPA5 expression analysis in NFYA cDNA and siRNA transfection cells further clarified the important role of NFYA in regulating HSPA5 transcription. In SCA17 cells, HSPA5 promoter activity was activated as a compensatory response before aggregate formation. NFYA dysfunction was indicated in SCA17 cells as HSPA5 promoter activity reduced along with TBP aggregate formation. Because essential roles of HSPA5 in protection from neuronal apoptosis have been shown in a mouse model, NFYA could be a target of mutant TBP in SCA17

Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network

Background: A database for hepatocellular carcinoma (HCC) patients who had received hepatic resection was used to develop prediction models for 1-, 3- and 5-year disease-free survival based on a set of clinical parameters for this patient group. Methods: The three prediction models included an artificial neural network (ANN) model, a logistic regression (LR) model, and a decision tree (DT) model. Data for 427, 354 and 297 HCC patients with histories of 1-, 3- and 5-year disease-free survival after hepatic resection, respectively, were extracted from the HCC patient database. From each of the three groups, 80 % of the cases (342, 283 and 238 cases of 1-, 3- and 5-year disease-free survival, respectively) were selected to provide training data for the prediction models. The remaining 20 % of cases in each group (85, 71 and 59 cases in the three respective groups) were assigned to validation groups for performance comparisons of the three models. Area under receiver operating characteristics curve (AUROC) was used as the performance index for evaluating the three models. Conclusions: The ANN model outperformed the LR and DT models in terms of prediction accuracy. This study demonstrated the feasibility of using ANNs in medical decision support systems for predicting disease-free survival based on clinical databases in HCC patients who have received hepatic resection

What is at stake in a war? A prospective evaluation of the Ukraine and Russia conflict for business and society

War produces devastating impacts on humankind, especially in terms of lives and livelihoods. While war is a widely studied topic in history, it remains relatively understudied in business. To address this gap, this article explores the impact of war for business and society. To do so, this article undertakes a prospective evaluation of the Ukraine and Russia conflict as a recent case of war. In doing so, this article reveals that a war can impact society within (e.g., limit access to basic necessities and monetary resources, increase unemployment and reduce purchasing power, and increase asylum seekers and refugees) and outside (e.g., supply shortage and inflation and threat of false information) as well as business within(e.g., threat of cyberattacks, threat to digital and sustainable growth, and short-term and long-term sanctions and support) and outside (e.g., test of business ethics and moral obligations and test of brand management) war-torn countries. The article concludes with an agenda for future research involving war, business, and society

A Machine Learning-Based Prediction Model of LCCO2 for Building Envelope Renovation in Taiwan

In 2015, Taiwan’s government announced the “Greenhouse Gas Reduction and Management Act”, the goal of which was a 50% reduction in carbon emissions by 2050, compared with 2005. The residential and commercial sectors produce approximately one third of all carbon emissions in Taiwan, and the number of construction renovation projects is much larger than that of new construction projects. In this paper, we considered the life-cycle CO2 (LCCO2) of a building envelope renovation project in Tainan and focused on local construction methods for typical row houses. The LCCO2 of 744 cases with various climate zones, orientations, and insulation and glazing types was calculated via EnergyPlus, SimaPro, and a local database (LCBA database), and the results were then used to develop a machine learning model. Our findings showed that the machine learning model was capable of predicting annual energy consumption and LCCO2. With regard to annual energy consumption, the RMSE was 227.09 kW·h (per year) and the R2 was 0.992. For LCCO2, the RMSE was 2792.47 kgCO2eq and the R2 was 0.989, which indicates a high-confidence process for decision making in the early stages of building design and renovation

Proteomic Profiling of Outer Membrane Vesicles Released by Escherichia coli LPS Mutants Defective in Heptose Biosynthesis

Escherichia coli releases outer membrane vesicles (OMVs) into the extracellular environment. OMVs, which contain the outer membrane protein, lipopolysaccharides (LPS), and genetic material, play an important role in immune response modulation. An isobaric tag for relative and absolute quantitation (iTRAQ) analysis was used to investigate OMV constituent proteins and their functions in burn trauma. OMV sizes ranged from 50 to 200 nm. Proteomics and Gene Ontology analysis revealed that ΔrfaC and ΔrfaG were likely involved in the upregulation of the structural constituent of ribosomes for the outer membrane and of proteins involved in protein binding and OMV synthesis. ΔrfaL was likely implicated in the downregulation of the structural constituent of the ribosome, translation, and cytosolic large ribosomal subunit. Kyoto Encyclopedia of Genes and Genomes analysis indicated that ΔrfaC and ΔrfaG downregulated ACP, ACEF, and ADHE genes; ΔrfaL upregulated ACP, ACEF, and ADHE genes. Heat map analysis demonstrated upregulation of galF, clpX, accA, fabB, and grpE and downregulation of pspA, ydiY, rpsT, and rpmB. These results suggest that RfaC, RfaG, and RfaL proteins were involved in outer membrane and LPS synthesis. Therefore, direct contact between wounds and LPS may lead to apoptosis, reduction in local cell proliferation, and delayed wound healing