Automatic detection of low surface brightness galaxies from SDSS images

Low surface brightness (LSB) galaxies are galaxies with central surface brightness fainter than the night sky. Due to the faint nature of LSB galaxies and the comparable sky background, it is difficult to search LSB galaxies automatically and efficiently from large sky survey. In this study, we established the Low Surface Brightness Galaxies Auto Detect model (LSBG-AD), which is a data-driven model for end-to-end detection of LSB galaxies from Sloan Digital Sky Survey (SDSS) images. Object detection techniques based on deep learning are applied to the SDSS field images to identify LSB galaxies and estimate their coordinates at the same time. Applying LSBG-AD to 1120 SDSS images, we detected 1197 LSB galaxy candidates, of which 1081 samples are already known and 116 samples are newly found candidates. The B-band central surface brightness of the candidates searched by the model ranges from 22 mag arcsec $^ {- 2}$ to 24 mag arcsec $^ {- 2}$, quite consistent with the surface brightness distribution of the standard sample. 96.46\% of LSB galaxy candidates have an axis ratio ($b/a$) greater than 0.3, and 92.04\% of them have $fracDev\_r$\textless 0.4, which is also consistent with the standard sample. The results show that the LSBG-AD model learns the features of LSB galaxies of the training samples well, and can be used to search LSB galaxies without using photometric parameters. Next, this method will be used to develop efficient algorithms to detect LSB galaxies from massive images of the next generation observatories.Comment: 11 pages, 9 figures,accepted to be published on MNRA

The Development of Molecular Biology of Osteoporosis

Osteoporosis is one of the major bone disorders that affects both women and men, and causes bone deterioration and bone strength. Bone remodeling maintains bone mass and mineral homeostasis through the balanced action of osteoblasts and osteoclasts, which are responsible for bone formation and bone resorption, respectively. The imbalance in bone remodeling is known to be the main cause of osteoporosis. The imbalance can be the result of the action of various molecules produced by one bone cell that acts on other bone cells and influence cell activity. The understanding of the effect of these molecules on bone can help identify new targets and therapeutics to prevent and treat bone disorders. In this article, we have focused on molecules that are produced by osteoblasts, osteocytes, and osteoclasts and their mechanism of action on these cells. We have also summarized the different pharmacological osteoporosis treatments that target different molecular aspects of these bone cells to minimize osteoporosis

Shared recycling model for waste electrical and electronic equipment based on the targeted responsibility system in the context of China

Abstract The formal recycling of waste electrical and electronic equipment (WEEE) has long faced collection difficulties owing to the inadequate recycling system and insufficient collection capacity under China’s fund-based recycling model. The government has introduced the recycling Target Responsibility System (TRS) to motivate producers to develop and share recycling systems, yet without clear incentive mechanisms. In this study, we provide a “1 + N” shared recycling model referring to the theory of the sharing economy, and we propose a credit mechanism with a deposit system and a penalty mechanism for dishonesty to constrain the opportunistic behavior of sharing. In addition, according to the TRS, we design a “reduction-penalty-subsidy” fund policy to incentivize producers and recyclers to achieve recycling targets. On this basis, we apply evolutionary game theory and system dynamics approach to analyze the collaborative mechanism of shared recycling and the incentive effect of the funding policy. Game analysis yields the evolution of shared recycling from the developing stage to the mature stage. The system simulation results indicate that the government’s “penalty” and “subsidy” strategies provide evident incentives for producers and recyclers, respectively, in the developing stage, whereas endogenous dynamics derived from economies of scale under market mechanisms promote the multi-agent collaborative implementation of shared recycling in the mature stage

Roles of African swine fever virus structural proteins in viral infection

African swine fever virus (ASFV) is a large, double-stranded DNA virus and the sole member of the Asfarviridae family. ASFV infects domestic pigs, wild boars, warthogs, and bush pigs, as well as soft ticks (Ornithodoros erraticus), which likely act as a vector. The major target is swine monocyte-macrophage cells. The virus can cause high fever, haemorrhagic lesions, cyanosis, anorexia, and even fatalities in domestic pigs. Currently, there is no vaccine and effective disease control strategies against its spread are culling infected pigs and maintaining high biosecurity standards. African swine fever (ASF) spread to Europe from Africa in the middle of the 20th century, and later also to South America and the Caribbean. Since then, ASF has spread more widely and thus is still a great challenge for swine breeding. The genome of ASFV ranges in length from about 170 to 193 kbp depending on the isolate and contains between 150 and 167 open reading frames (ORFs). The ASFV genome encodes 150 to 200 proteins, around 50 of them structural. The roles of virus structural proteins in viral infection have been described. These proteins, such as pp220, pp62, p72, p54, p30, and CD2v, serve as the major component of virus particles and have roles in attachment, entry, and replication. All studies on ASFV proteins lay a good foundation upon which to clarify the infection mechanism and develop vaccines and diagnosis methods. In this paper, the roles of ASFV structural proteins in viral infection are reviewed

α-Cyclodextrins Polyrotaxane Loading Silver Sulfadiazine

As a drug carrier, polyrotaxane (PR) has been used for targeted delivery and sustained release of drugs, whereas silver sulfadiazine (SD-Ag) is an emerging antibiotic agent. PR was synthesized by the use of α-cyclodextrin (CD) and poly(ethylene glycol) (PEG), and a specific antibacterial material (PR-(SD-Ag)) was then prepared by loading SD-Ag onto PR with different mass ratios. The loading capacity and the encapsulation efficiency were 90% at a mass ratio of 1:1 of PR and SD-Ag. SD-Ag was released stably and slowly within 6 d in vitro, and its cumulative release reached more than 85%. The mechanism of PR loading SD-Ag might be that SD-Ag attached to the edge of α-CD through hydrogen bonding. PR-(SD-Ag) showed a higher light stability than SD-Ag and held excellent antibacterial properties against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus)

From Plant to Yeast—Advances in Biosynthesis of Artemisinin

Malaria is a life-threatening disease. Artemisinin-based combination therapy (ACT) is the preferred choice for malaria treatment recommended by the World Health Organization. At present, the main source of artemisinin is extracted from Artemisia annua; however, the artemisinin content in A. annua is only 0.1–1%, which cannot meet global demand. Meanwhile, the chemical synthesis of artemisinin has disadvantages such as complicated steps, high cost and low yield. Therefore, the application of the synthetic biology approach to produce artemisinin in vivo has magnificent prospects. In this review, the biosynthesis pathway of artemisinin was summarized. Then we discussed the advances in the heterologous biosynthesis of artemisinin using microorganisms (Escherichia coli and Saccharomyces cerevisiae) as chassis cells. With yeast as the cell factory, the production of artemisinin was transferred from plant to yeast. Through the optimization of the fermentation process, the yield of artemisinic acid reached 25 g/L, thereby producing the semi-synthesis of artemisinin. Moreover, we reviewed the genetic engineering in A. annua to improve the artemisinin content, which included overexpressing artemisinin biosynthesis pathway genes, blocking key genes in competitive pathways, and regulating the expression of transcription factors related to artemisinin biosynthesis. Finally, the research progress of artemisinin production in other plants (Nicotiana, Physcomitrella, etc.) was discussed. The current advances in artemisinin biosynthesis may help lay the foundation for the remarkable up-regulation of artemisinin production in A. annua through gene editing or molecular design breeding in the future

A Mechanistic Model for Estimating Rice Photosynthetic Capacity and Stomatal Conductance from Sun-Induced Chlorophyll Fluorescence

Enhancing the photosynthetic rate is one of the effective ways to increase rice yield, given that photosynthesis is the basis of crop productivity. At the leaf level, crops’ photosynthetic rate is mainly determined by photosynthetic functional traits including the maximum carboxylation rate (Vcmax) and stomatal conductance (gs). Accurate quantification of these functional traits is important to simulate and predict the growth status of rice. In recent studies, the emerging sun-induced chlorophyll fluorescence (SIF) provides us an unprecedented opportunity to estimate crops’ photosynthetic traits, owing to its direct and mechanistic links to photosynthesis. Therefore, in this study, we proposed a practical semimechanistic model to estimate the seasonal Vcmax and gs time-series based on SIF. We firstly generated the coupling relationship between the open ratio of photosystem II (qL) and photosynthetically active radiation (PAR), then estimate the electron transport rate (ETR) based on the proposed mechanistic relationship between SIF and ETR. Finally, Vcmax and gs were estimated by linking to ETR based on the principle of evolutionary optimality and the photosynthetic pathway. Validation with field observations showed that our proposed model can estimate Vcmax and gs with high accuracy (R2 > 0.8). Compared to simple linear regression model, the proposed model could increase the accuracy of Vcmax estimates by >40%. Therefore, the proposed method effectively enhanced the estimation accuracy of crops’ functional traits, which sheds new light on developing high-throughput monitoring techniques to estimate plant functional traits, and also can improve our understating of crops’ physiological response to climate change

A chromosome-level genome assembly and annotation of the medicinal plant Lepidium apetalum

Abstract Objectives As a traditional Chinese medicine, Lepidium apetalum is commonly used for purging the lung, relieving dyspnea, alleviating edema, and has the significant pharmacological effects on cardiovascular disease, hyperlipidemia, etc. In addition, the seeds of L. apetalum are rich in unsaturated fatty acids, sterols, glucosinolates and have a variety of biological activity compounds. To facilitate genomics, phylogenetic and secondary metabolite biosynthesis studies of L. apetalum, we assembled the high-resolution genome of L. apetalum. Data description We completed chromosome-level genome assembly of the L. apetalum genome (2n = 32), using Illumina HiSeq and PacBio Sequel sequencing platform as well as high-throughput chromosome conformation capture (Hi-C) technique. The assembled genome was 296.80 Mb in size, 34.41% in GC content, and 23.89% in repeated sequence content, including 316 contigs with a contig N50 of 16.31 Mb. Hi-C scaffolding resulted in 16 chromosomes occupying 99.79% of the assembled genome sequences. A total of 46 584 genes and 105 pseudogenes were predicted, 98.37% of which can be annotated to Nr, GO, KEGG, TrEMBL, SwissPort, Pfam and KOG databases. The high-quality reference genome generated by this study will provide accurate genetic information for the molecular biology research of L. apetalum