Urine microRNA-7977/G6PD level in DKD patients and its association with dysfunction of albumin-induced autophagy in proximal epithelial tubular cells.

Studies have shown that decreased expression of glucose-6-phosphate dehydrogenase (G6PD) play an important role in DKD. However, the upstream and downstream pathways of G6PD downregulation leading to DKD have not been elucidated.We conducted a series of studies including clinical study, animal studies, and in vitro studies to explore this. Firstly, a total of 90 subjects were evaluated. The urinary G6PD activity and its association with the clinical markers were analyzed. Then, urine differentially microRNAs that can bind and degrade G6PD were screened and verified in DKD patients. After that, high glucose (HG)-cultured Human kidney cells (HK-2) and Zucker diabetic fatty (ZDF) rats were used to test the roles of miR-7977/G6PD/albumin-induced autophagy in DKD. The plasma and urinary G6PD activity were decreased significantly in patients with DKD, accompanied by increased urinary mir-7977 level. The fasting plasma glucose (FPG), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and urinary albumin excretion were independent predictors of urinary G6PD activity by multiple linear regression analysis.The increased expression of miR-7977 and decreased expression of G6PD were also found in the kidney of ZDF rats with early renal tubular damage.In HK-2 cells cultured with normal situation, low level of albumin could induce autophagy along with the stimulation of G6PD although this was impaired under high glucose. Overexpression of G6PD reversed albumin-induced autophagy in HK2 cells under high glucose.Inhibition mir-7977 expression led to significantly increased expression of G6PD and reversed the effects of high glucose on albumin induced autophagy.Our study supports a new mechanism of G6PD downregulation in DKD.

Benzoxazinoids Biosynthetic Gene Cluster Identification and Expression Analysis in Maize under Biotic and Abiotic Stresses.

Benzoxazinoids (BXs) are unique bioactive metabolites with protective and allelopathic properties in maize in response to diverse stresses. The production of BXs involves the fine regulations of BXs biosynthetic gene cluster (BGC). However, little is known about whether and how the expression pattern of BGC members is impacted by biotic and abiotic stresses. Here, maize BGC was systemically investigated and 26 BGC gene members were identified on seven chromosomes, for which Bin 4.00-4.01/4.03-4.04/7.02 were the most enriched regions. All BX proteins were clearly divided into three classes and seven subclasses, and ten conserved motifs were further identified among these proteins. These proteins were localized in the subcellular compartments of chloroplast, endoplasmic reticulum, or cytoplasmic, where their catalytic activities were specifically executed. Three independent RNA-sequencing (RNA-Seq) analyses revealed that the expression profiles of the majority of BGC gene members were distinctly affected by multiple treatments, including light spectral quality, low-temperature, 24-epibrassinolide induction, and Asian corn borer infestation. Thirteen differentially expressed genes (DEGs) with high and specific expression levels were commonly detected among three RNA-Seq, as core conserved BGC members for regulating BXs biosynthesis under multiple abiotic/biotic stimulates. Moreover, the quantitative real-time PCR (qRT-PCR) verified that six core conserved genes in BGC were significantly differentially expressed in leaves of seedlings upon four treatments, which caused significant increases in 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) content under darkness and wound treatments, whereas a clear decrease in DIMBOA content was observed under low-temperature treatment. In conclusion, the changes in BX metabolites in maize were regulated by BGC gene members in multiple stress presences. Therefore, the identification of key genes associated with BX accumulation under biotic/abiotic stresses will provide valuable gene resources for breeding maize varieties with enhanced capability to adapt to environmental stresses.

Application of metagenomic next-generation sequencing for rapid molecular identification in spinal infection diagnosis.

Objective: This study aimed to determine the sensitivity and specificity of metagenomic next-generation sequencing (mNGS) for detecting pathogens in spinal infections and to identify the differences in the diagnostic performance between mNGS and targeted next-generation sequencing (tNGS). Methods: A total of 76 consecutive patients with suspected spinal infections who underwent mNGS, culture, and histopathological examinations were retrospectively studied. The final diagnosis of the patient was determined by combining the clinical treatment results, pathological examinations, imaging changes and laboratory indicators. The sensitivity and specificity of mNGS and culture were determined. Results: The difference between the two detection rates was statistically significant (p < 0.001), with mNGS exhibiting a significantly higher detection rate (77.6% versus 18.4%). The average diagnosis time of mNGS was significantly shorter than that of bacterial culture (p < 0.001, 1.65 versus 3.07 days). The sensitivity and accuracy of mNGS were significantly higher than that of the culture group (p < 0.001, 82.3% versus 17.5%; 75% versus 27.6%), whereas the specificity of mNGS (42.9%) was lower than that of the culture group (p > 0.05, 42.9% versus 76.9%). The sensitivity, specificity, accuracy, and positive predictive value (PPV) of pus were higher than those of tissue samples for mNGS, whereas for culture, the sensitivity, specificity, accuracy, and PPV of tissue samples were higher than those of pus. tNGS demonstrated higher sensitivity and accuracy in diagnosing tuberculosis (TB) than mNGS (80% versus 50%; 87.5% versus 68.8%). Conclusion: mNGS for spinal infection demonstrated better diagnostic value in developing an antibiotic regimen earlier, and it is recommended to prioritize pus samples for testing through mNGS. Moreover, tNGS outperformed other methods for diagnosing spinal TB and identifying antibiotic-resistance genes in drug-resistant TB.

Penicianstinoids F-K, six undescribed meroterpenoids from the marine algicolous fungus Penicillium sp. RR-DL-1-7.

Six previously undescribed meroterpenoids, penicianstinoids F-K (1-6), together with four known analogues, dehydroaustinol (7), dehydroaustin (8), penicianstinoid A (9), and furanoaustinol (10), were isolated from the cultures of the algicolous fungus Penicillium sp. RR-DL-1-7, derived from the red alga Rhodomela confervoides. Their structures and relative configuration were established by detailed spectroscopic analysis of NMR and HR-MS experiments, and the absolute configurations were assigned by X-ray diffraction and ECD spectral analysis. None of the isolates showed obvious growth inhibitory effects against five plankton and four bacteria species tested.

A physiologically based pharmacokinetic model of diethyl phthalates in humans.

Phthalates are a family of industrial and consumer product chemicals, among which diethyl phthalate (DEP) has been widely used. DEP is metabolized into the active metabolite monoethyl phthalate (MEP) and exposure to DEP may induce male reproductive toxicity, developmental toxicity and hepatotoxicity. To better assess the toxicity of DEP and MEP, it is important to understand and predict their internal concentrations, especially in reproductive organs. Here we present a human physiologically based pharmacokinetic (PBPK) model of DEP. Implemented in R, the PBPK model consists of seven tissue compartments, including blood, gut, liver, fat, skin, gonad, and rest of body (RB). In the blood both DEP and MEP partition into free and bound forms, and tissue distribution is considered as blood flow-limited. DEP is metabolized in the gut and liver into MEP which is further glucuronidated and cleared through the urine. The chemical-specific parameters of the model were predicted in silico or estimated based on published human urinary MEP data after exposure to DEP in the air at 250 or 300 µg/m3 for 3 or 6 h through inhalation and dermal absorption. Sensitivity analysis identified important parameters including partition coefficients of DEP for fat, RB, and skin compartments, and the rate constants for glucuronidation of MEP and urinary excretion, with regard to Cmax, area under the curve (AUC), and clearance half-lives of DEP and MEP. A subset of the sensitive parameters was then included in hierarchical population Bayesian Markov chain Monte Carlo (MCMC) simulations to characterize the uncertainty and variability of these parameters. The model is consistent with the notion that dermal absorption represents a significant route of exposure to DEP in ambient air and clothing can be an effective barrier. The developed human PBPK model can be utilized upon further refinement as a quantitative tool for DEP risk assessment.