Tongue texture may contribute to the assessment of malignant risk of thyroid nodules.

In the present study, it was aimed to evaluate whether there is an objective tongue image indicator that could be used to evaluate malignant risk of thyroid nodules through a cross sectional study. From December 2018 to December 2020, the TFDA-1 digital tongue-face diagnostic instrument was used to collect the tongue images. TDAS 2.0 software was used for tongue image analysis. A standardized database was constructed by combining patient physical examination results and tongue image analysis results. The relationship between tongue image index and TI-RADS classification of thyroid nodules was tested. A total of 5,900 cases were collected and 4,615 cases were included in the present study after excluding 154 cases due to incomplete information, 1,221 cases with thyroid nodules were separated into 417 cases TI-RADS 2 group, 693 cases in TI-RADS 3 group and 111 cases in TI-RADS 4 group. Without considering confounding factors, tongue image indexes zhiCon, zhiASM, zhiENT, zhiMEAN, zhiClrB, zhiClrR, zhiClrG, zhiClrI, zhiClrL and zhiClrY were significantly different among the three groups (P<0.05). Excluding the influence of age, sex, body mass index, smoking and drinking, the results of one-way variance linear trend analysis showed that the values of zhiCon, zhiENT and zhiMEAN increased with the increasing TI-RADS category, while the values of zhiASM decreased with the increase of TI-RADS category. Tongue texture index may be helpful for differentiating the benign and malignant of thyroid nodules.

Assessment of the anti-rheumatoid arthritis activity of Gastrodia elata (tian-ma) and Radix aconitic lateralis preparata (fu-zi) via network pharmacology and untargeted metabolomics analyses.

AIM: Gastrodia elata and Radix aconiti lateralis preparrata are respectively named as Tian-Ma and Fu-Zi (TF) in Chinese. We explored the active components against rheumatoid arthritis (RA) from an extensively used couplet of Chinese herbs, Gastrodia elata and Radix aconiti lateralis preparata (TF) via untargeted metabolomics and network pharmacological approaches. METHODS: Water extracts of TF were mixed at ratios 1:1, 3:2 and 2:3 (w/w). Ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) was then utilized as metabolomics screening. Human Metabolome (http://www.hmdb.ca/) and Lipidmaps (http://www.lipidmaps.org/) databases were used to annotate detected compounds. Further identification of vital genes and important pathways associated with the anti-RA properties of the TF preparations was done via network pharmacology, and verified by real-time quantitative polymerase chain reaction (RT-qPCR). RESULTS: Four key compounds involved in unsaturated fatty acid biosynthesis and isoflavonoid biosynthesis were identified through metabolomics analyses. Three key components of TF associated with anti-RA activity were linoleic acid, daidzein, and daidzin. Results of RT-qPCR revealed that all 3 tested TF couplets (1:1, 3:2, and 2:3) markedly suppressed the transcription of PTGS2. These results were consistent with our network pharmacological predictions. CONCLUSIONS: The anti-RA properties of Tian-Ma and Fu-Zi are associated with the inhibition of arachidonic acid metabolism pathway.

Source and risk assessment of PCBs in sediments of Fenhe reservoir and watershed, China.

The concentrations of polychlorinated biphenyls (PCBs) in sediments from the Fenhe reservoir and watershed were detected at 28 sites in wet and dry seasons. The ∑(123)PCBs ranged from n.d. to 126.49 ng g(-1) dw. The dominated congeners were tri-PCBs (34.29%) and tetra-PCBs (24.05%). In the Fenhe reservoir, ∑(123)PCBs presented a decreasing trend, while percentages of low chlorinated congeners showed an increasing trend. For the temporal variations, PCBs homologues profiles of sediment samples and spatial distribution of ∑(123)PCBs for the two periods were similar (with CD = 0.021 and r(2) = 0.999 respectively), although PCBs concentrations in the wet season were significantly higher than in the dry season. PCA was applied to analyze the possible sources for PCBs, suggesting that PCBs might be mainly influenced by Aroclor 1016 and 1242. Compared with 3 established sediment quality guidelines, levels of PCBs in sediments of the investigated watershed might have a potential biological impact, especially in the wet season.