Plasmodiophora brassicae, the causal agent of clubroot disease of the Brassica crops, is widespread in the world. Quantitative trait loci (QTLs) for partial resistance to 4 different isolates of P. brassicae (Pb2, Pb4, Pb7, and Pb10) were investigated using a BC1F1 population from a cross between two subspecies of Brassica rapa, i.e. Chinese cabbage inbred line C59-1 as a susceptible recurrent parent and turnip inbred line ECD04 as a resistant donor parent. The BC1F2 families were assessed for resistance under controlled conditions. A linkage map constructed with simple sequence repeats (SSR), unigene-derived microsatellite (UGMS) markers, and specific markers linked to published clubroot resistance (CR) genes of B. rapa was used to perform QTL mapping. A total of 6 QTLs residing in 5 CR QTL regions of the B. rapa chromosomes A01, A03, and A08 were identified to account for 12.2 to 35.2% of the phenotypic variance. Two QTL regions were found to be novel except for 3 QTLs in the respective regions of previously identified Crr1, Crr2, and Crr3. QTL mapping results indicated that 1 QTL region was common for partial resistance to the 2 isolates of Pb2 and Pb7, whereas the others were specific for each isolate. Additionally, synteny analysis between B. rapa and Arabidopsis thaliana revealed that all CR QTL regions were aligned to a single conserved crucifer blocks (U, F, and R) on 3 Arabidopsis chromosomes where 2 CR QTLs were detected in A. thaliana. These results suggest that some common ancestral genomic regions were involved in the evolution of CR genes in B. rapa.

With the increasing pressure of energy exhaustion and environmental degradation, environmental regulation is considered as a strategy to achieve sustainable development. This paper specifically analyzes the mechanism of multi-dimensional environmental regulations on energy- and environment-biased technological progress, and empirically detects the differentiated impacts using China’s panel data from the period 2000–2016, employing the generalized method of moments (GMM) and a dynamic threshold model. The results reveal that: (1) command-and-control regulation (CCR) promotes energy-saving and pollution abatement technological progress. Market-based regulation (MBR) stimulates energy-saving technological progress, while informal regulation (IR) only accelerates environment conservation technological progress. (2) There are threshold effects on the relationship of environmental regulations and biased technological progress. With economic developments, CCR and MBR have positive effects on energy- and environment-related technological progress, whilst IR fails to promote backstop and pollution abatement technological progress. The clear diversity in the impacts of different environment regulations on biased technological progress provides new insights for the optimal future policy design.

Crystallization is one of the important unit operations for the separation and purification of solid products in the chemical, pharmaceutical, and pesticide industries, especially for realizing high-end, high-value solid products. The precise control of the solution crystallization process determines the polymorph, crystal shape, size, and size distribution of the crystal product, which is of great significance to improve product quality and production efficiency. In order to develop the crystallization process in a scientific method that is based on process parameters and data, process analysis technology (PAT) has become an important enabling platform. In this paper, we review the development of PAT in the field of crystallization in recent years. Based on the current research status of drug crystallization process control, the monitoring methods and control strategies of feedback control in the crystallization process were systematically summarized. The focus is on the application of model-free feedback control strategies based on the solution and solid information collected by various online monitoring equipment in product engineering, including improving particle size distribution, achieving polymorphic control, and improving purity. In this paper, the challenges of feedback control strategy in the crystallization process are also discussed, and the development trend of the feedback control strategy has been prospected.

N 6 -methyladenosine (m 6 A) is the most abundant form of mRNA modification and controls many aspects of RNA metabolism including gene expression. However, the mechanisms by which m 6 A regulates cell- and condition-specific gene expression are still poorly understood, partly due to a lack of tools capable of identifying m 6 A sites that regulate gene expression under different conditions. Here we develop m 6 A-express , the first algorithm for predicting condition-specific m 6 A regulation of gene expression (m 6 A-reg-exp) from limited methylated RNA immunoprecipitation sequencing (MeRIP-seq) data. Comprehensive evaluations of m 6 A-express using simulated and real data demonstrated its high prediction specificity and sensitivity. When only a few MeRIP-seq samples may be available for the cellular or treatment conditions, m 6 A-express is particularly more robust than the log-linear model. Using m 6 A-express , we reported that m 6 A writers, METTL3 and METTL14, competitively regulate the transcriptional processes by mediating m 6 A-reg-exp of different genes in Hela cells. In contrast, METTL3 induces different m 6 A-reg-exp of a distinct group of genes in HepG2 cells to regulate protein functions and stress-related processes. We further uncovered unique m 6 A-reg-exp patterns in human brain and intestine tissues, which are enriched in organ-specific processes. This study demonstrates the effectiveness of m 6 A-express in predicting condition-specific m 6 A-reg-exp and highlights the complex, condition-specific nature of m 6 A-regulation of gene expression.