RESUMEN
A plant can be thought of as a colony comprising numerous growth buds, each developing to its own rhythm. Such lack of synchrony impedes efforts to describe core principles of plant morphogenesis, dissect the underlying mechanisms, and identify regulators. Here, we use the minimalist known angiosperm to overcome this challenge and provide a model system for plant morphogenesis. We present a detailed morphological description of the monocot Wolffia australiana, as well as high-quality genome information. Further, we developed the plant-on-chip culture system and demonstrate the application of advanced technologies such as single-nucleus RNA-sequencing, protein structure prediction, and gene editing. We provide proof-of-concept examples that illustrate how W. australiana can decipher the core regulatory mechanisms of plant morphogenesis.
RESUMEN
BACKGROUND: Line probe assays (LPAs) are PCR-based assays used for the rapid diagnosis of Mycobacterium tuberculosis (MTB) and drug-resistant tuberculosis (DR-TB). But studies on its performance are insufficient. Thus, in this study, we conducted a systematic review and meta-analysis to evaluate the effect of LPAs in the detection of MTB and drug-resistant TB in comparison with the traditional culture and DST methods. METHODS: A systemic literature search was conducted on the Web of Science, Embase, PubMed, the Cochrane Library, Scopus, and OVID databases. All the included studies were classified according to different detecting objects. Sensitivity, specificity, Positive Likely Ratio (PLR), Negative Likely Ratio (NLR), Diagnostic Odds Ratio (DOR), corresponding 95% confidence interval, Area Under Curve (AUC), Deeks' funnel plot, and Bivariate Boxplot was used to do the evaluation. RESULTS: 147 studies included 491 datasets, with 182,448 samples, were incorporated into our analysis. The sensitivity (95% CI), specificity (95% CI), PLR, NLR, DOR and AUC for MTB were 0.89 (0.86 to 0.92), 0.94 (0.90 to 0.97), 15.70, 0.11, 139 and 0.96, respectively; for rifampicin-resistant TB were 0.96 (0.95 to 0.97), 0.99 (0.98 to 0.99), 82.9, 0.04, 1994 and 1.00, respectively; for isoniazid-resistant TB were 0.91 (0.89 to 0.93), 0.99 (0.98 to 0.99), 83.4, 0.09, (0.99 to 1.00), 195.7, 0.07, 2783 and 1.00, respectively; for Multi-drug resistant TB (MDR-TB) were 0.93 (0.90 to 0.95), 1.00 (0.99 to 1.00), 195.7, 0.07, 2783 and 1.00, respectively; for extensively drug-resistant TB (XDR-TB) were 0.60 (0.33 to 0.82), 1.00 (0.95 to 1.00), 291.3, 0.4, 726 and 0.95, respectively; for (second-line drug-resistant TB) SLID-TB were 0.83 (0.78 to 0.87), 0.98 (0.97 to 0.99), 44.6, 0.17, 262 and 0.98, respectively. Sensitivity in pre-extensively drug-resistant TB (Pre-XDR-TB) was 0.67, specificity was 0.91. No publication bias existed according to Deeks' funnel plot. CONCLUSION: High diagnosis performance was confirmed in LPAs for the diagnosis of MTB and drug-resistant TB. LPAs might be a good alternative to culture and DST in detecting MTB, RR-TB, INH-TB, XDR-TB, SLID-TB, and MDR-TB. While more studies were still needed to explore the diagnosis performance of LPAs for Pre-XDR TB.