Adjuvant Lipoic acid Injection in Sepsis treatment in China (ALIS study): protocol for a randomised, single-blind, placebo-controlled trial.

INTRODUCTION: Sepsis is a life-threatening immune disorder resulting from an dysregulated host response to infection. Adjuvant therapy is a valuable complement to sepsis treatment. Lipoic acid has shown potential in attenuating sepsis-induced immune dysfunction and organ injury in vivo and in vitro studies. However, clinical evidence of lipoic acid injection in sepsis treatment is lacking. Hence, we devised a randomised controlled trial to evaluate the efficacy and safety of lipoic acid injection in improving the prognosis of sepsis or septic shock patients. METHODS AND ANALYSIS: A total of 352 sepsis patients are planned to be recruited from intensive care units (ICUs) at eight tertiary hospitals in China for this trial. Eligible participants will undergo randomisation in a 1:1 ratio, allocating them to either the control group or the experimental group. Both groups received routine care, with the experimental group also receiving lipoic acid injection and the control group receiving placebo. The primary efficacy endpoint is 28-day all-cause mortality. The secondary efficacy endpoints are as follows: ICU and hospital mortality, ICU and hospital stay, new acute kidney injury in ICU, demand and duration of life support, Sequential Organ Failure Assessment (SOFA)/Acute Physiology and Chronic Health Evaluation II (APACHE II) and changes from baseline (ΔSOFA/ΔApache II), arterial blood lactate (LAC) and changes from baseline (ΔLAC), blood procalcitonin, high-sensitivity C-reactive protein, interleukin-2 (IL-2), IL-4, IL-6, IL-10, tumour necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) and changes from baseline on day 1 (D1), D3, D5 and D7. Clinical safety will be assessed through analysis of adverse events. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of Maoming People's Hospital (approval no. PJ2020MI-019-01). Informed consent will be obtained from the participants or representatives. The findings will be disseminated through academic conferences or journal publications. TRIAL REGISTRATION: ChiCTR2000039023.

High-Fat Diets with Differential Fatty Acids Induce Obesity and Perturb Gut Microbiota in Honey Bee.

HFD (high-fat diet) induces obesity and metabolic disorders, which is associated with the alteration in gut microbiota profiles. However, the underlying molecular mechanisms of the processes are poorly understood. In this study, we used the simple model organism honey bee to explore how different amounts and types of dietary fats affect the host metabolism and the gut microbiota. Excess dietary fat, especially palm oil, elicited higher weight gain, lower survival rates, hyperglycemic, and fat accumulation in honey bees. However, microbiota-free honey bees reared on high-fat diets did not significantly change their phenotypes. Different fatty acid compositions in palm and soybean oil altered the lipid profiles of the honey bee body. Remarkably, dietary fats regulated lipid metabolism and immune-related gene expression at the transcriptional level. Gene set enrichment analysis showed that biological processes, including transcription factors, insulin secretion, and Toll and Imd signaling pathways, were significantly different in the gut of bees on different dietary fats. Moreover, a high-fat diet increased the relative abundance of Gilliamella, while the level of Bartonella was significantly decreased in palm oil groups. This study establishes a novel honey bee model of studying the crosstalk between dietary fat, gut microbiota, and host metabolism.

Generation of Fluorinated Amychelin Siderophores against Pseudomonas aeruginosa Infections by a Combination of Genome Mining and Mutasynthesis.

Pioneering microbial genomic surveys have revealed numerous untapped biosynthetic gene clusters, unveiling the great potential of new natural products. Here, using a combination of genome mining, mutasynthesis, and activity screening in an infection model comprising Caenorhabditis elegans and Pseudomonas aeruginosa, we identified candidate virulence-blocking amychelin siderophore compounds from actinomycetes. Subsequently, we developed unreported analogs of these virulence-blocking siderophores with improved potency by exploiting an Amycolatopsis methanolica strain 239T chorismate to salicylate a biosynthetic subpathway for mutasynthesis. This allowed us to generate the fluorinated amychelin, fluoroamychelin I, which rescued C. elegans from P. aeruginosa-mediated killing with an EC50 value of 1.4 µM, outperforming traditional antibiotics including ceftazidime and meropenem. In general, this paper describes an efficient platform for the identification and production of classes of anti-microbial compounds with potential unique modes of action.

[Establishment of chromatographic fingerprint of Squama Manis and its applications in animal source identification and quality grade discrimination].

Squama Manis, or "Chuanshanjia" in Chinese, is a traditional Chinese medicine (TCM) for promoting blood circulation and reducing swelling and discharge; the only animal source used in TCM is the scales of Manis pentadactyla. However, in today's pharmaceutical market, there are many scales from other species of the same genus that are difficult to distinguish from Squama Manis. High-quality and low-quality scales are also severely confused. To solve the above problems, various analytical methods have been developed, such as thin-layer chromatography, mass spectrometry and DNA detection. Owing to their low resolving ability, high equipment cost, and inconvenient operation, none of these methods are appropriate for routine identification of Squama Manis. A chromatographic fingerprint can comprehensively reflect the synergic action of multiple chemical compositions in TCM and has been widely used for the quality control of TCM. In the present study, we established a fingerprint of Squama Manis and explored its feasibility in identifying the origin and quality grade of scales. First, Squama Manis powder was hydrolyzed by hydrochloric acid (1 mol/L). Next, the extract was analyzed on a Symmetry 300 C18 column by linear gradient elution, using 0.1% trifluoroacetic acid (v/v) in water and 0.1% trifluoroacetic acid (v/v) in acetonitrile as the mobile phase and 280 nm as the detection wavelength. The established method was systematically validated, demonstrating good precision, repeatability and sample stability (relative standard deviation (RSD)<5%). Subsequently, samples of different sources and quality grades were distinguished by similarity evaluation and discrimination analysis based on the fingerprint data. In the similarity evaluation, the reference fingerprint was defined as the average fingerprint of twelve first-class samples, and seventeen chromatographic peaks were identified as common peaks. Similarities between the reference fingerprint and fingerprints with different base sources and quality grades were calculated using the absolute area of common peaks as original data. The similarities between Squama Manis and scales from other animals were all less than 0.776, while the similarities between Squama Manis of different grades overlapped significantly, varying from 0.988 to 0.996 for first-class samples and 0.950 to 0.995 for general samples. The results reflected the feasibility of similarity evaluation for discriminating base source and its limitation in the distinguishing between quality grades. Nonetheless, first-class scales showed higher average similarity and lower RSD than general scales, which indicates some level of revelation between fingerprint similarity and quality grade. Thus, a better algorithm or discriminant model is required to distinguish between quality grades. Therefore, a supervised chemometric technique, kernel-based support vector machine (SVM), was applied to construct predictive models. The SVM is a common discriminant model that classifies samples by constructing a separate hyperplane in n-dimensional space, maximizing the margin between classes. Combination with a kernel function can effectively avoid "dimension disaster" when dealing with nonlinear data. In the model, the quality grade was defined as a sample label, and the absolute peak areas constituted the data matrix. Verified by 10-fold cross-validation, the unbiased prediction accuracy was up to 95.83%. The predicted results were highly consistent with the actual classifications. The results indicate the high feasibility of the established model for determining quality grade, as it performed significantly better than the similarity evaluation. Samples from batches A and B were completely discriminated and only two samples from batch S were incorrectly classified. Given the batch bias, we believe that model error may have been caused by man-made tag errors rather than the model itself. In conclusion, we established a chromatographic fingerprint for Squama Manis quality analysis and demonstrated its feasibility in animal source identification and quality determination by combining different data analysis methods. The established strategy may provide a new method for improving the the validity and accuracy of Squama Manis in clinical use.