Beyond genome: Advanced omics progress of Panax ginseng.

Ginseng is a perennial herb of the genus Panax in the family Araliaceae as one of the most important traditional medicine. Genomic studies of ginseng assist in the systematic discovery of genes related to bioactive ginsenosides biosynthesis and resistance to stress, which are of great significance in the conservation of genetic resources and variety improvement. The transcriptome reflects the difference and consistency of gene expression, and transcriptomics studies of ginseng assist in screening ginseng differentially expressed genes to further explore the powerful gene source of ginseng. Protein is the ultimate bearer of ginseng life activities, and proteomic studies of ginseng assist in exploring the biosynthesis and regulation of secondary metabolites like ginsenosides and the molecular mechanism of ginseng adversity adaptation at the overall level. In this review, we summarize the current status of ginseng research in genomics, transcriptomics and proteomics, respectively. We also discuss and look forward to the development of ginseng genome allele mapping, ginseng spatiotemporal, single-cell transcriptome, as well as ginseng post-translational modification proteome. We hope that this review will contribute to the in-depth study of ginseng and provide a reference for future analysis of ginseng from a systems biology perspective.

Social media unveils the hidden but high magnitude of human-mediated biological invasions in China.

Humans are responsible for the release of many non-native animals into the wild. However, these releases occur randomly and are difficult to monitor. Here, using two of the worst invasive herpetofauna as model taxa, we applied an iEcology approach and found a high magnitude of human-mediated releases in China, suggesting this approach can be used to monitor introductions and advise management bodies in a timely manner.

Bioresorbable thin-film silicon diodes for the optoelectronic excitation and inhibition of neural activities.

Neural activities can be modulated by leveraging light-responsive nanomaterials as interfaces for exerting photothermal, photoelectrochemical or photocapacitive effects on neurons or neural tissues. Here we show that bioresorbable thin-film monocrystalline silicon pn diodes can be used to optoelectronically excite or inhibit neural activities by establishing polarity-dependent positive or negative photovoltages at the semiconductor/solution interface. Under laser illumination, the silicon-diode optoelectronic interfaces allowed for the deterministic depolarization or hyperpolarization of cultured neurons as well as the upregulated or downregulated intracellular calcium dynamics. The optoelectronic interfaces can also be mounted on nerve tissue to activate or silence neural activities in peripheral and central nervous tissues, as we show in mice with exposed sciatic nerves and somatosensory cortices. Bioresorbable silicon-based optoelectronic thin films that selectively excite or inhibit neural tissue may find advantageous biomedical applicability.

Patterned cPCDH expression regulates the fine organization of the neocortex.

The neocortex consists of a vast number of diverse neurons that form distinct layers and intricate circuits at the single-cell resolution to support complex brain functions1. Diverse cell-surface molecules are thought to be key for defining neuronal identity, and they mediate interneuronal interactions for structural and functional organization2-6. However, the precise mechanisms that control the fine neuronal organization of the neocortex remain largely unclear. Here, by integrating in-depth single-cell RNA-sequencing analysis, progenitor lineage labelling and mosaic functional analysis, we report that the diverse yet patterned expression of clustered protocadherins (cPCDHs)-the largest subgroup of the cadherin superfamily of cell-adhesion molecules7-regulates the precise spatial arrangement and synaptic connectivity of excitatory neurons in the mouse neocortex. The expression of cPcdh genes in individual neocortical excitatory neurons is diverse yet exhibits distinct composition patterns linked to their developmental origin and spatial positioning. A reduction in functional cPCDH expression causes a lateral clustering of clonally related excitatory neurons originating from the same neural progenitor and a significant increase in synaptic connectivity. By contrast, overexpression of a single cPCDH isoform leads to a lateral dispersion of clonally related excitatory neurons and a considerable decrease in synaptic connectivity. These results suggest that patterned cPCDH expression biases fine spatial and functional organization of individual neocortical excitatory neurons in the mammalian brain.

Boronate Affinity-Based Electrochemical Aptasensor for Point-of-Care Glycoprotein Detection.

As a class of oligosaccharide chain-containing proteins, glycoproteins are of great value in screening and early diagnosis of malignant tumors and other major diseases. Herein, we report a universal boronate affinity-based electrochemical aptasensor for point-of-care glycoprotein detection. Aptasensing of glycoproteins involves the specific recognition and capture of target glycoproteins by end-tethered nucleic acid aptamers and the site-specific labeling of ferrocene tags via the phenylboronic acid (PBA)-based boronate affinity interactions because the cis-diol sites of oligosaccharide chains on glycoproteins can selectively react with the PBA receptor groups to form cyclic phenylborates in aqueous basic media. Due to the presence of hundreds to thousands of cis-diol sites on a glycoprotein, a large number of ferrocene tags can be recruited for the signal-on aptasensing of glycoproteins at a low-abundance level, eliminating the need for extra amplification strategies. As a result, the boronate affinity-based electrochemical aptasensor is highly sensitive and selective for glycoprotein detection and tolerant to the false-positive results. The detection limit for α-fetoprotein (AFP) is 0.037 ng/mL, with a linear response ranging from 0.1 to 100 ng/mL. In addition to the merits of simple operation, short assay time, and low detection cost, the aptasensor is applicable to the detection of glycoproteins in serum samples and the point-of-care detection using disposable flexible electrodes. Overall, this work provides a universal and promising platform for the point-of-care detection of glycoproteins, holding great potential in screening and early diagnosis of glycoprotein-related malignant tumors and other major diseases.

Multicriteria analysis on environmental impacts of accelerated vehicle retirement program from a life-cycle perspective: A case study of Beijing.

The environmental benefits of accelerated vehicle retirement programs (AVRPs), which have been extensively adopted in many countries, are highlighted by the proponents. However, the methods for evaluating their environmental effects are lacking of considering material and water criteria as well as continuous improvement in vehicle fuel efficiency and emission control. Additionally, the studies on Chinese case only considered air pollutants during vehicle usage and assumed a fixed remaining lifetime of old vehicles. This study therefore proposed a multicriteria life-cycle analysis model, which embeds not only vehicle lifetime distribution but also dynamics of vehicle fuel efficiency and emission factors, to examine the environmental effects of AVRP more comprehensively in terms of material, water, and energy consumption as well as emission of greenhouse gas, air pollutants and water pollutants. The assessment of the AVRP in Beijing, China, shows that short-term environmental benefits can be hardly gained from a life-cycle perspective, and energy consumption, greenhouse gases and other pollutants (except for volatile organic compound) decrease only when the users keep their new vehicles for 3 years or more. In the medium term, the AVRP would slightly increase material, energy and water consumption, sulfur-oxide, greenhouse gas and water pollutants, but significantly or moderately reduce other air pollutants. Moreover, the results reveal that merely considering the phase of vehicle usage may also lead underestimating some environmental benefits of AVRP by ignoring the phase of fuel production, whilst promoting vehicle fuel efficiency standards and the environmental regulations on vehicle and fuel supply chains may minimize the environmental benefits of AVRP or even have adverse effects.

Biologically Mediated RAFT Polymerization for Electrochemical Sensing of Kinase Activity.

The assay of kinase activity with ultrahigh sensitivity is important to medical diagnostics and drug discovery. Herein, we report the biologically mediated RAFT polymerization (BMRP) and its potential use as an efficient amplification strategy in the ultrasensitive electrochemical sensing of kinase activity. In BMRP, the reversible addition-fragmentation chain-transfer (RAFT) process is initiated and sustained by the reduced form of coenzyme I (i.e., NADH), which can efficiently mediate the direct fragmentation of thiocarbonylthio (TCT) compounds (or the TCT-capped dormant chains) to produce an initiating/propagating radical under mild conditions. Due to the absence of exogenous radicals, the notorious radical termination in RAFT equilibrium can be greatly suppressed. For the sensing of kinase activity, the recognition peptides, without carboxyl groups, are immobilized via the Au-S self-assembly. After phosphorylation, TCT compounds (as RAFT agents) are tethered to the enzymatically generated phosphate groups via the carboxylate-Zr(IV)-phosphate (CZP) linkage. Subsequently, the BMRP of ferrocenylmethyl methacrylate (FcMMA) results in the labeling of each phosphate group with hundreds to thousands of Fc tags, thereby greatly amplifying the sensing signal. Obviously, the BMRP-based strategy is biologically friendly, highly efficient, uncomplicated, and quite low-cost. The detection limit of 1.85 mU/mL has been achieved toward the selective sensing of the cAMP-dependent protein kinase (PKA). Moreover, the proposed kinase sensor is applicable to inhibitor screening and kinase activity sensing in serum samples. By virtue of its low cost, high sensitivity and selectivity, and uncomplicated operation, the proposed kinase sensor holds great potential in medical diagnostics and drug discovery.

Ecological balance emerges in implementing the water-energy-food security nexus in well-developed countries in Africa.

Although many African countries have made significant progress towards universal access to water, energy, and food resources (WEF), assessing the ecological response to the increasing productivity of these resources is not well researched, which carries the risk of ecological deficit, resource degradation, and inefficient policy responses to resource management. This study seeks to assess the ecological sustainability response to the high increase demand for WEF resources in well-developed African countries. The study developed new measurement metrics for the WEF production system, including three indicators of ecological footprint (EF), ecological biocapacity (EBC), and eco-balance. The overall analysis considers data from four distinct types of water and energy use activities, and eight distinct types of food consumption, in nine African countries with the highest WEF nexus performance. An evaluation tool for the Water, Energy, Food and Ecological Balance (WEFEB) nexus index is proposed as one of the study's outcomes. Despite having 100% access to WEF resources related to the SDG targets. The results reveal the significant levels of imbalance and large ecological deficits existing in many of the concerned countries, especially North Africa, Mauritius, and South Africa, which need to rethink their economic models. Projecting a sustained increase in resource demand so that each country achieves at least 1700 m3/capita/year as the minimum amount of water needed, most countries would suffer from a steady increase in ecological imbalance. According to the results, managing the ecological imbalances with increasing demand for WEF resources in well-developed African countries may require well-designed policies to effectively reduce certain types of human demand that have a large ecological footprint.

Raman spectroscopy combined with machine learning algorithms to detect adulterated Suichang native honey.

Zhejiang Suichang native honey, which is included in the list of China's National Geographical Indication Agricultural Products Protection Project, is very popular. This study proposes a method of Raman spectroscopy combined with machine learning algorithms to accurately detect low-concentration adulterated Suichang native honey. In this study, the native honey collected by local beekeepers in Suichang was selected for adulteration detection. The spectral data was compressed by Savitzky-Golay smoothing and partial least squares (PLS) in sequence. The PLS features taken for further analysis were selected according to the contribution rate. In this study, three classification modeling methods including support vector machine, probabilistic neural network and convolutional neural network were adopted to correctly classify pure and adulterated honey samples. The total accuracy was 100%, 100% and 99.75% respectively. The research result shows that Raman spectroscopy combined with machine learning algorithms has great potential in accurately detecting adulteration of low-concentration honey.

Design, implementation, and evaluation of an Internet of Things (IoT) network system for restaurant food waste management.

Catering companies around the world generate tremendous amounts of waste; those in China are no exception. The paper discusses the design, implementation, and evaluation of a sensor-based Internet of Things (IoT) network technology for improving the management of restaurant food waste (RFW) in the city of Suzhou, China. This IoT-based system encompasses the generation, collection, transportation and final disposal of RFW. The Suzhou case study comprised four steps: (1) examination of the required functionality of an IoT-enabled system in the specific context of Suzhou; (2) configuration of the system architecture, both software and hardware components, according to the identified functionality; (3) installation of the components of the IoT system at the facilities of the stakeholders across the RFW generation-collection-transportation-disposal value chain; and (4) evaluation of the performance of the entire system, based on data from three years of operation. The results show that the system had a strong impact. Positive results include: (1) better management of RFW generation, as evidenced by a 20.5% increase in RFW collected via official channels and a 207% increase in the number of RFW generators under official contract; (2) better law enforcement in response to RFW malpractice, enabled by the monitoring capabilities of the IoT system; and (3) an overall reduction in illicit RFW activities and better process optimization across the RFW value chain. Negative results include: (1) Radio-frequency identification (RFID) tags need to be renewed often due to the frequent handling of waste bins, thus increasing operating costs; (2) dynamic/automatic weight sensors had a higher degree of error than the more time-consuming static/manual weighing method; and (3) there were disagreements between the city's government agencies about how to interpret data from the IoT system, which led to some inefficiencies in management. In sum, the Suzhou IoT system enabled data-driven management of RFW and had a net positive impact for the stakeholders involved.