Cytosolic HMGB1 Mediates Autophagy Activation in an Emulsified Isoflurane Anesthesia Cell Model

Neurochemical Research - Inhalation anesthetic isoflurane may cause an increased risk of cognitive impairment. Previous studies have indicated that this cognitive decline is associated with...     

A cross-talk between epithelium and endothelium mediates human alveolar–capillary injury during SARS-CoV-2 infection

COVID-19, caused by SARS-CoV-2, is an acute and rapidly developing pandemic, which leads to a global health crisis. SARS-CoV-2 primarily attacks human alveoli and causes severe lung infection and damage. To better understand the molecular basis of this disease, we sought to characterize the responses of alveolar epithelium and its adjacent microvascular endothelium to viral infection under a co-culture system. SARS-CoV-2 infection caused massive virus replication and dramatic organelles remodeling in alveolar epithelial cells, alone. While, viral infection affected endothelial cells in an indirect manner, which was mediated by infected alveolar epithelium. Proteomics analysis and TEM examinations showed viral infection caused global proteomic modulations and marked ultrastructural changes in both epithelial cells and endothelial cells under the co-culture system. In particular, viral infection elicited global protein changes and structural reorganizations across many sub-cellular compartments in epithelial cells. Among the affected organelles, mitochondrion seems to be a primary target organelle. Besides, according to EM and proteomic results, we identified Daurisoline, a potent autophagy inhibitor, could inhibit virus replication effectively in host cells. Collectively, our study revealed an unrecognized cross-talk between epithelium and endothelium, which contributed to alveolar–capillary injury during SARS-CoV-2 infection. These new findings will expand our understanding of COVID-19 and may also be helpful for targeted drug development.Subject terms: Mechanisms of disease, Viral infection     

Interaction of ethanol with opiate receptors

Addition of ethanol to rat brain homogenate containing opiate receptors inhibits at a concentration of 50 mM the stereospecific binding of 3H-naloxone at 37 degrees C but not at 0 degree C, with the ID50 being 462 mM under these conditions. The temperature-dependent inhibition of the ligand binding suggests that ethanol does not compete with naloxone for specific binding sites of opiate receptors and changes the structure of lipids in biological membranes. Scatchard's analysis has demonstrated that apart from a decrease in the number of highly affinity binding sites of 3H-naloxone, the total amount of the binding sites remains unchanged both in the presence and absence of ethanol and constitutes 453 and 549 fmol/mg protein. It is assumed that ethanol might interconvert highly and low-affinity binding sites. Analysis of the effect of ethanol on 3H-naloxone binding with opiate receptors contained by synaptic membranes obtained from animals with varying predisposition to voluntary alcoholization has shown that ethanol inhibits to a greater degree ligand binding with membranes obtained from rats predisposed to alcoholization. The possibility of the involvement of receptors in the biochemical mechanisms by which the initial alcoholic motivation is effected is under discussion.     

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province,China

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D²H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D²H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well.     

Measurement of 7-dehydrocholesterol and cholesterol in hair can be used in the diagnosis of Smith-Lemli-Opitz syndrome

7-dehydrocholesterol (7-DHC) and cholesterol (CHOL) are biomarkers of Smith-Lemli-Opitz Syndrome (SLOS), a congenital autosomal recessive disorder characterized by elevated 7-DHC level in patients. Hair samples have been shown to have great diagnostic and research value, which has long been neglected in the SLOS field. In this study, we sought to investigate the feasibility of using hair for SLOS diagnosis. In the presence of antioxidants (2,6-ditert-butyl-4-methylphenol and triphenylphosphine), hair samples were completely pulverized and extracted by micro-pulverized extraction in alkaline solution or in n-hexane. After microwave-assisted derivatization with N,O-Bis(trimethylsilyl)trifluoroacetamide, the analytes were measured by GC-MS. We found that the limits of determination for 7-DHC and CHOL were 10 ng/mg and 8 ng/mg, respectively. In addition, good linearity was obtained in the range of 50–4000 ng/mg and 30–6000 ng/mg for 7-DHC and CHOL, respectively, which fully meets the requirement for SLOS diagnosis and related research. Finally, by applying the proposed method to real hair samples collected from 14 healthy infants and two suspected SLOS patients, we confirmed the feasibility of hair analysis as a diagnostic tool for SLOS. In conclusion, we present an optimized and validated analytical method for the simultaneous determination of two SLOS biomarkers using human hair.     

Structural Insight of a Trimodular Halophilic Cellulase with a Family 46 Carbohydrate-Binding Module

Cellulases are the key enzymes used in the biofuel industry. A typical cellulase contains a catalytic domain connected to a carbohydrate-binding module (CBM) through a flexible linker. Here we report the structure of an atypical trimodular cellulase which harbors a catalytic domain, a CBM46 domain and a rigid CBM_X domain between them. The catalytic domain shows the features of GH5 family, while the CBM46 domain has a sandwich-like structure. The catalytic domain and the CBM46 domain form an extended substrate binding cleft, within which several tryptophan residues are well exposed. Mutagenesis assays indicate that these residues are essential for the enzymatic activities. Gel affinity electrophoresis shows that these tryptophan residues are involved in the polysaccharide substrate binding. Also, electrostatic potential analysis indicates that almost the entire solvent accessible surface of CelB is negatively charged, which is consistent with the halophilic nature of this enzyme.     

Solving the N-Queens problem with a binary Hopfield-type network

The application of a discrete Hopfield-type neural network to solving the NP-Hard optimization problem — the N-Queens Problem (NQP) — is presented. The applied network is binary, and at every moment each neuron potential is equal to either 0 or 1. The network can be implemented in the asynchronous mode as well as in the synchronous one with n parallel running processors. In both cases the convergence rate is up to 100%, and the experimental estimate of the average computational complexity is polynomial. Based on the computer simulation results and the theoretical analysis, the proper network parameters are established. The behaviour of the network is explained.     

Modeling the Role of Negative Cooperativity in Metabolic Regulation and Homeostasis

A significant proportion of enzymes display cooperativity in binding ligand molecules, and such effects have an important impact on metabolic regulation. This is easiest to understand in the case of positive cooperativity. Sharp responses to changes in metabolite concentrations can allow organisms to better respond to environmental changes and maintain metabolic homeostasis. However, despite the fact that negative cooperativity is almost as common as positive, it has been harder to imagine what advantages it provides. Here we use computational models to explore the utility of negative cooperativity in one particular context: that of an inhibitor binding to an enzyme. We identify several factors which may contribute, and show that acting together they can make negative cooperativity advantageous.