Assessment of bidirectional relationships between depression and rheumatoid arthritis among adults: a two-sample Mendelian randomization study.

OBJECTIVE: Increasing evidence shows that depression is associated with rheumatoid arthritis (RA). However, the causality and direction of this association remain unclear, because links between the two diseases might be caused by shared environmental confounding factors. Our study aims to understand a putative causal link between the two diseases. METHODS: We retrieved summary statistics from meta-analyses of non-overlapping genome-wide association studies (GWASes) for depression (n = 807,553, 246,363 cases and 561,190 controls) and RA (n = 58,284, 14,361 cases and 42,923 controls). We combined Mendelian randomization (MR) estimates from each genetic instrument using inverse-variance weighted (IVW) meta-analysis, with alternate methods (e.g., simple median approach, weighted median approach, and MR-Egger regression) and conducted sensitivity analyses to assess the robustness of MR analyses. RESULTS: We found no evidence of causal relationships between depression and RA across all MR methods (IVW OR, 1.028 for RA; 95% CI, 0.821-1.287; P = 0.810) or vice versa (IVW OR, 0.999 for depression; 95% CI, 0.984-1.014; P = 0.932), indicating the links between the two diseases might be due to confounders. CONCLUSION: Despite the results, to optimize treatment outcomes of RA patients, we still emphasize depression should be managed as part of routine clinical care to optimize treatment outcomes of RA.

Data-mining-based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID-19.

Traditional Chinese Medicine (TCM) plays a role in preventing and treating COVID-19 in China. Based on the manifestations and symptoms of COVID-19, our study used the data mining method to summarize related therapeutic experience left by predecessors who used TCM to treat epidemics in their eras. Initially, we collected abundant medical records with similar manifestations of COVID-19 in Chinese ancient times. The key words including wen (), yi (), li (), and zhang () were searched in ZhongyiZhiku (https://www.zk120.com/) from Warring States Period (475 BC-221 BC) to the Republic of China era (1912-1949) to locate ancient medical records according to inclusion criteria and exclusion criteria. Moreover, COVID-19-related manifestations and corresponding medications in those records were categorized. Eventually, Traditional Chinese Medicine Inheritance Support System version 2.5 was used to build a medical record database of TCM treating COVID-19. Our study collected 263 epidemic medical records comprising COVID-19 related manifestations and found that Chinese Materia Medica (CMM) combinations excavated from ancient medical records included Ren Shen Bai Du San, Wu Ling San, Xiao Chai Hu Tang, Da Cheng Qi Tang, Da Chai Hu Tang, Ling Gui Zhu Gan Tang, and Qing Wen Bai Du Yin. The recurrent CMMs with a high frequency for treating COVID-19 manifestations were Scutellariae Radix (Huang Qin), Paeoniae Alba Radix (Bai Shao), Poria (Fu Ling), and Bupleuri Radix (Chai Hu). Our study suggests that TCM might offer new therapeutic strategies for COVID-19.

Determination of the activity of alkaline phosphatase based on aggregation-induced quenching of the fluorescence of copper nanoclusters.

A rapid method is described for synthesis of copper nanoclusters (CuNCs) by utilizing L-histidine as the stabilizer and ascorbic acid (AA) as the reductant. The CuNCs display blue-green fluorescence with excitation/emission peaks at 390/485 nm. A sensitive fluorometric assay was worked out for determination of alkaline phosphatase (ALP) activity. If the ALP substrate p-nitrophenylphosphate (PNPP) is enzymatically hydrolyzed, it forms p-nitrophenol (PNP) which reduces the fluorescence of CuNCs because its absorption band at 410 nm overlaps the excitation peak of CuNCs at 390 nm. In addition, the amino groups and imidazole groups on the surface of CuNCs possibly form a complex with the phenol groups of PNP. This induces aggregation-induced quenching of the fluorescence of CuNCs. The fluorescent probe has a linear analytical range that extends from 0.5 mU·mL-1 to 40 mU·mL-1 and a detection limit of 45 µU·mL-1. Graphical abstract Schematic illustration of a fluorometric assay for alkaline phosphatase (ALP) activity that uses L-histidine protected copper nanoclusters (CuNCs), aggregation-induced quenching, and the inner filter effect between PNP and CuNCs.

Poly(styrene-4-sulfonate)-protected copper nanoclusters as a fluorometric probe for sequential detection of cytochrome c and trypsin.

Stable copper nanoclusters (CuNCs) were prepared by utilizing D-penicillamine as both the stabilizer and reductant. The emission of the CuNCs (with excitation/emission peaks at 390/645 nm) is largely stabilized by coating with poly(sodium-p-styrenesulfonate) (PSS). Cytochrome c (Cyt c) quenches the fluorescence of the PSS-coated CuNCs, and this effect was exploited to design a quenchometric fluorometric assay for Cyt c. If trypsin is added to the loaded CuNCs, it will hydrolyze Cyt c to form peptide fragments, and fluorescence is gradually restored. A highly sensitive and fluorometric turn-off-on assay was constructed for sequential detection of Cyt c and trypsin. The linear ranges for Cyt c and trypsin are from 8.0 nM to 680 nM, and from 0.1 to 6.0 µg mL-1, and the lower detection limits are 0.83 nM and 20 ng mL-1 for Cyt c and trypsin, respectively. Graphical abstract Schematic illustration of the fluorometric assay for trypsin based on the electron transfer between poly(p-styrenesulfonate)-protected copper nanoclusters (PSS-CuNCs) and cytochrome c (Cyt c).