Identification of eight genomic protective alleles for mitochondrial diabetes by Kinship-graph convolutional network.

AIMS: Nearly 85% of maternally inherited diabetes and deafness (MIDD) are caused by the m.3243A>G mutation in the mitochondrial DNA. However, the clinical phenotypes of MIDD may also be influenced by the nuclear genome, this study aimed to investigate nuclear genome variants that influence clinical phenotypes associated with m.3243A>G mutation in MIDD based on whole-genome sequencing of the patients belonging to pedigrees. MATERIALS AND METHODS: We analyzed a whole-genome sequencing (WGS) dataset from blood samples of 38 MIDD patients with the m.3243A > G mutation belonging to 10 pedigrees, by developing a Kinship-graph convolutional network approach, called Ki-GCN, integrated with the conventional genome-wide association study (GWAS) methods. RESULTS: We identified eight protective alleles in the nuclear genome that have protective effects against the onset of MIDD, related deafness, and also type 2 diabetes. Based on these eight protective alleles, we constructed an effective logistic regression model to predict the early or late onset of MIDD patients. CONCLUSIONS: There are protective alleles in the nuclear genome that are associated with the onset-age of MIDD patients and might also provide protective effects on the deafness derived from MIDD patients.

Transcriptome Analysis of Protocatechualdehyde against Listeria monocytogenes and Its Effect on Chicken Quality Characteristics.

The development of natural antimicrobial agents offers new strategies for food preservation due to the health hazards associated with the spoilage of meat products caused by microbial contamination. In this paper, the inhibitory mechanism of protocatechualdehyde (PCA) on Listeria monocytogenes was described, and its effect on the preservation of cooked chicken breast was evaluated. The results showed that the minimal inhibitory concentration (MIC) of PCA on L. monocytogenes was 0.625 mg/mL. Secondly, PCA destroyed the integrity of the L. monocytogenes cell membrane, which was manifested as a decrease in membrane hyperpolarization, intracellular ATP level, and intracellular pH value. Field emission gun scanning electron microscopy (FEG-SEM) observed a cell membrane rupture. Transcriptome analysis showed that PCA may inhibit cell growth by affecting amino acid, nucleotide metabolism, energy metabolism, and the cell membrane of L. monocytogenes. Additionally, it was discovered that PCA enhanced the color and texture of cooked chicken breast meat while decreasing the level of thiobarbituric acid active substance (TBARS). In conclusion, PCA as a natural antibacterial agent has a certain reference value in extending the shelf life of cooked chicken breast.

Single-cell entropy network detects the activity of immune cells based on ribosomal protein genes.

We developed a new computational method, Single-Cell Entropy Network (SCEN) to analyze single-cell RNA-seq data, which used the information of gene-gene associations to discover new heterogeneity of immune cells as well as identify existing cell types. Based on SCEN, we defined association-entropy (AE) for each cell and each gene through single-cell gene co-expression networks to measure the strength of association between each gene and all other genes at a single-cell resolution. Analyses of public datasets indicated that the AE of ribosomal protein genes (RP genes) varied greatly even in the same cell type of immune cells and the average AE of RP genes of immune cells in each person was significantly associated with the healthy/disease state of this person. Based on existing research and theory, we inferred that the AE of RP genes represented the heterogeneity of ribosomes and reflected the activity of immune cells. We believe SCEN can provide more biological insights into the heterogeneity and diversity of immune cells, especially the change of immune cells in the diseases.

Evaluation of Kratom Opioid Derivatives as Potential Treatment Option for Alcohol Use Disorder.

Background and Purpose: Mitragyna speciosa extract and kratom alkaloids decrease alcohol consumption in mice at least in part through actions at the δ-opioid receptor (δOR). However, the most potent opioidergic kratom alkaloid, 7-hydroxymitragynine, exhibits rewarding properties and hyperlocomotion presumably due to preferred affinity for the mu opioid receptor (µOR). We hypothesized that opioidergic kratom alkaloids like paynantheine and speciogynine with reduced µOR potency could provide a starting point for developing opioids with an improved therapeutic window to treat alcohol use disorder. Experimental Approach: We characterized paynantheine, speciociliatine, and four novel kratom-derived analogs for their ability to bind and activate δOR, µOR, and κOR. Select opioids were assessed in behavioral assays in male C57BL/6N WT and δOR knockout mice. Key Results: Paynantheine (10 mg∙kg-1, i.p.) produced aversion in a limited conditioned place preference (CPP) paradigm but did not produce CPP with additional conditioning sessions. Paynantheine did not produce robust antinociception but did block morphine-induced antinociception and hyperlocomotion. Yet, at 10 and 30 mg∙kg-1 doses (i.p.), paynantheine did not counteract morphine CPP. 7-hydroxypaynantheine and 7-hydroxyspeciogynine displayed potency at δOR but limited µOR potency relative to 7-hydroxymitragynine in vitro, and dose-dependently decreased voluntary alcohol consumption in WT but not δOR in KO mice. 7-hydroxyspeciogynine has a maximally tolerated dose of at least 10 mg∙kg-1 (s.c.) at which it did not produce significant CPP neither alter general locomotion nor induce noticeable seizures. Conclusion and Implications: Derivatizing kratom alkaloids with the goal of enhancing δOR potency and reducing off-target effects could provide a pathway to develop novel lead compounds to treat alcohol use disorder with an improved therapeutic window.

The Meta-Position of Phe4 in Leu-Enkephalin Regulates Potency, Selectivity, Functional Activity, and Signaling Bias at the Delta and Mu Opioid Receptors.

As tool compounds to study cardiac ischemia, the endogenous δ-opioid receptors (δOR) agonist Leu5-enkephalin and the more metabolically stable synthetic peptide (d-Ala2, d-Leu5)-enkephalin are frequently employed. However, both peptides have similar pharmacological profiles that restrict detailed investigation of the cellular mechanism of the δOR's protective role during ischemic events. Thus, a need remains for δOR peptides with improved selectivity and unique signaling properties for investigating the specific roles for δOR signaling in cardiac ischemia. To this end, we explored substitution at the Phe4 position of Leu5-enkephalin for its ability to modulate receptor function and selectivity. Peptides were assessed for their affinity to bind to δORs and µ-opioid receptors (µORs) and potency to inhibit cAMP signaling and to recruit ß-arrestin 2. Additionally, peptide stability was measured in rat plasma. Substitution of the meta-position of Phe4 of Leu5-enkephalin provided high-affinity ligands with varying levels of selectivity and bias at both the δOR and µOR and improved peptide stability, while substitution with picoline derivatives produced lower-affinity ligands with G protein biases at both receptors. Overall, these favorable substitutions at the meta-position of Phe4 may be combined with other modifications to Leu5-enkephalin to deliver improved agonists with finely tuned potency, selectivity, bias and drug-like properties.

Dependence of Initial Value on Pattern Formation for a Logistic Coupled Map Lattice.

The logistic coupled map lattices (LCML) have been widely investigated as well as their pattern dynamics. The patterns formation may depend on not only fluctuations of system parameters, but variation of the initial conditions. However, the mathematical discussion is quite few for the effect of initial values so far. The present paper is concerned with the pattern formation for a two-dimensional Logistic coupled map lattice, where any initial value can be linear expressed by corresponding eigenvectors, and patterns formation can be determined by selecting the corresponding eigenvectors. A set of simulations are conducted whose results demonstrate the fact. The method utilized in the present paper could be applied to other discrete systems as well.