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In a multi-omics analysis, bacterial polyynes are found to act as antifungal agents by inhibiting the Candida albicans polyyne resistance gene ERG10, the homolog of MasL encoding acetyl-CoA acetyltransferase.

Abstract Background and Aims Regorafenib has demonstrated its survival benefit for unresectable hepatocellular carcinoma (uHCC) patients in a phase III clinical trial. We aimed to assess the efficacy and tolerability of regorafenib and the predictors of treatment outcomes in Taiwanese patients. Methods We analyzed the survival, best overall response, predictors of treatment outcomes, and safety for uHCC patients who had tumor progression on sorafenib therapy and received regorafenib as salvage therapy between March 2018 and November 2020. Results Eighty‐six patients with uHCC were enrolled (median age, 66.5 years; 76.7% male). The median regorafenib treatment duration was 4.0 months (95% confidence interval [CI], 3.6–4.6). The most frequently reported adverse events were hand‐foot skin reaction (44.2%), diarrhea (36.0%), and fatigue (29.1%). No unpredictable toxicity was observed during treatment. The median overall survival (OS) with regorafenib was 12.4 months (95% CI, 7.8–17.0) and the median progression‐free survival (PFS) was 4.2 months (95% CI, 3.7–4.7). Of 82 patients with regorafenib responses assessable, 4 patients (4.9%) achieved a partial response, and 33 (40.2%) had stable disease, leading to a disease control rate (DCR) of 45.1% (n = 37). Patients possessing baseline AFP 10% reduction at 4 weeks or >20% reduction at 8 weeks after regorafenib administration) exhibited comparable treatment outcomes to those with baseline AFP

Beauveria bassiana is a globally distributed entomopathogenic fungus that produces various secondary metabolites to support its pathogenesis in insects. Two polyketide synthase genes, pks14 and pks15, are highly conserved in entomopathogenic fungi and are important for insect virulence. However, understanding of their mechanisms in insect pathogenicity is still limited. Here, we overexpressed these two genes in B. bassiana and compared the metabolite profiles of pks14 and pks15 overexpression strains to those of their respective knockout strains in culture and in vivo using tandem liquid chromatography-mass spectrometry (LC-MS/MS) with Global Natural Products Social Molecular Networking (GNPS). The pks14 and pks15 clusters exhibited crosstalk with biosynthetic clusters encoding insect-virulent metabolites, including beauvericins, bassianolide, enniatin A, and the intracellular siderophore ferricrocin under certain conditions. These secondary metabolites were upregulated in the pks14-overexpressing strain in culture and the pks15-overexpressing strain in vivo. These data suggest that pks14 and pks15, their proteins or their cluster components might be directly or indirectly associated with key pathways in insect pathogenesis of B. bassiana, particularly those related to secondary metabolism. Information about interactions between the polyketide clusters and other biosynthetic clusters improves scientific understanding about crosstalk among biosynthetic pathways and mechanisms of pathogenesis.

Due to its advantages of high customization and rapid production, metal laser melting manufacturing (MAM) has been widely applied in the medical industry, manufacturing, aerospace and boutique industries in recent years. However, defects during the selective laser melting (SLM) manufacturing process can result from thermal stress or hardware failure during the selective laser melting (SLM) manufacturing process. To improve the product’s quality, the use of defect detection during manufacturing is necessary. This study uses the process images recorded by powder bed fusion equipment to develop a detection method, which is based on the convolutional neural network. This uses three powder-spreading defect types: powder uneven, powder uncovered and recoater scratches. This study uses a two-stage convolutional neural network (CNN) model to finish the detection and segmentation of defects. The first stage uses the EfficientNet B7 to classify the images with/without defects, and then to locate the defects by evaluating three different instance segmentation networks in second stage. Experimental results show that the accuracy and Dice measurement of Mask-R-CNN network with ResNet 152 backbone can reach 0.9272 and 0.9438. The computational time of an image only takes approximately 0.2197 sec. The used CNN model meets the requirements of the early detected defects, regarding the SLM manufacturing process.

Traditional Chinese medicine (TCM) has been applied to improve human health for millennia. In the TCM system, "medicinal property" ( yao xing; hot and cold properties) is a core concept used to describe the influences of medicinal materials on human physiological conditions, and metabolites are believed to be one of the major ingredients of TCMs that affect their medicinal property. However, due to a lack of comprehensive analyses of TCM metabolomes, information about the relationships between TCM metabolite composition and medicinal property remains limited. In this pilot study, a mass spectral molecular networking-based platform was established and applied to systematically profile the metabolome of 24 TCMs with various medicinal properties. The molecular networks were built based on the liquid chromatography-tandem mass spectrometry (LC-MS/MS) data from 50% EtOH extracts of 24 TCMs. The results showed that various classes of metabolites were clustered in the molecular networks, and the potential medicinal propertyassociated molecular families were filtered by screening the medicinal property and the diversity of TCM sources. For example, some specific types of flavonoids were identified in the representative cold-property (han xing) molecular families. In contrast, due to the limited sample size, the representative and universal hot-property (re xing) molecular family has not been well revealed. In summary, this study provides methodology and information on the potential relationships between the metabolite composition and the concept of medicinal property in TCM. Furthermore, the results can serve as a foundation for mass spectral molecular networking-based analysis of TCM metabolomes, facilitating TCM research and development. [ABSTRACT FROM AUTHOR]