Optimization of the morphological, structural, and physicochemical properties of maize starch using straw returning and nitrogen fertilization in Northeast China.

The combination of straw returning and nitrogen (N) fertilization is a popular tillage mode and essential strategy for achieving stable yield and high quality. However, the optimal combination strategy and the influence of tillage mode on the morphological, crystalline, and molecular structures of maize starch remain unclear. We conducted a long-term field experiment over 7 years in Northeast China using two tillage modes, rotary tillage with straw returning (RTS) and plow tillage with straw returning (PTS), and four N application rates. The relative crystallinity, 1045/1022 cm-1 value, and B2 and B3 chains of maize starch were higher under RTS than under PTS, resulting in increased stability of starch and improvements in gelatinization enthalpy and temperature. The surface of the starch granules induced by N fertilizer was smoother than that under the N0 (0 kg N ha-1) treatment. The proportion of amylose content, solubility, swelling power, and light transmittance increased under N2 (262 kg N ha-1) treatment, along with improvement in starch pasting properties. These results suggest that RTS combined with N2 treatment can regulate the morphological, structural, and physicochemical characteristics of maize starch, providing an essential reference for improving the quality of maize starch from an agronomic point of view.

A New Monitoring Technology for Bearing Fault Detection in High-Speed Trains.

In this work, a new monitoring system is developed for bearing fault detection in high-speed trains. Firstly, a data acquisition system is developed to collect vibration and other related signals wirelessly. Secondly, a new multiple correlation analysis (MCA) technique is proposed for bearing fault detection. The MCA technique consists of the three processing steps: (1) the collected vibration signal is decomposed by variational modal decomposition (VMD) to formulate the representative intrinsic mode functions (IMFs); (2) the MCA is used to process and identify the characteristic features for signal analysis; (3) bearing fault is diagnosed by examining bearing characteristic frequency information on the envelope power spectrum. The effectiveness of the proposed MCA fault detection technique is verified by experimental tests corresponding to different bearing conditions.

The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives.

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has become a powerful tool for describing cell subpopulation classification and cell heterogeneity by achieving high-throughput and multidimensional analysis of individual cells and circumventing the shortcomings of traditional sequencing for detecting the average transcript level of cell populations. It has been applied to life science and medicine research fields such as tracking dynamic cell differentiation, revealing sensitive effector cells, and key molecular events of diseases. This review focuses on the recent technological innovations in scRNA-Seq, highlighting the latest research results with scRNA-Seq as the core technology in frontier research areas such as embryology, histology, oncology, and immunology. In addition, this review outlines the prospects for its innovative application in traditional Chinese medicine (TCM) research and discusses the key issues currently being addressed by scRNA-Seq and its great potential for exploring disease diagnostic targets and uncovering drug therapeutic targets in combination with multiomics technologies.

A new strategy for the rapid identification and validation of direct toxicity targets of psoralen-induced hepatotoxicity.

The interaction between small-molecule compounds of traditional Chinese medicine and their direct targets is the molecular initiation event, which is the key factor for toxicity efficacy. Psoralen, an active component of Fructus Psoraleae, is toxic to the liver and has various pharmacological properties. Although the mechanism of psoralen-induced hepatotoxicity has been studied, the direct target of psoralen remains unclear. Thus, the aim of this study was to discover direct targets of psoralen. To this end, we initially used proteomics based on drug affinity responsive target stability (DARTS) technology to identify the direct targets of psoralen. Next, we used surface plasmon resonance (SPR) analysis and verified the affinity effect of the 'component-target protein'. This method combines molecular docking technology to explore binding sites between small molecules and proteins. SPR and molecular docking confirmed that psoralen and tyrosine-protein kinase ABL1 could be stably combined. Based on the above experimental results, ABL1 is a potential direct target of psoralen-induced hepatotoxicity. Finally, the targets Nrf2 and mTOR, which are closely related to the hepatotoxicity caused by psoralen, were predicted by integrating proteomics and network pharmacology. The direct target ABL1 is located upstream of Nrf2 and mTOR, Nrf2 can influence the expression of mTOR by affecting the level of reactive oxygen species. Immunofluorescence experiments and western blot results showed that psoralen could affect ROS levels and downstream Nrf2 and mTOR protein changes, whereas the ABL1 inhibitor imatinib and ABL1 agonist DPH could enhance or inhibit this effect. In summary, we speculated that when psoralen causes hepatotoxicity, it acts on the direct target ABL1, resulting in a decrease in Nrf2 expression, an increase in ROS levels and a reduction in mTOR expression, which may cause cell death. We developed a new strategy for predicting and validating the direct targets of psoralen. This strategy identified the toxic target, ABL1, and the potential toxic mechanism of psoralen.

Functional metabolome profiling may improve individual outcomes in colorectal cancer management implementing concepts of predictive, preventive, and personalized medical approach.

Objectives: Colorectal cancer (CRC) is one of the most common solid tumors worldwide, but its diagnosis and treatment are limited. The objectives of our study were to compare the metabolic differences between CRC patients and healthy controls (HC), and to identify potential biomarkers in the serum that can be used for early diagnosis and as effective therapeutic targets. The aim was to provide a new direction for CRC predictive, preventive, and personalized medicine (PPPM). Methods: In this study, CRC patients (n = 30) and HC (n = 30) were recruited. Serum metabolites were assayed using an ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Subsequently, CRC cell lines (HCT116 and HCT8) were treated with metabolites to verify their function. Key targets were identified by molecular docking, thermal shift assay, and protein overexpression/inhibition experiments. The inhibitory effect of celastrol on tumor growth was also assessed, which included IC50 analysis, nude mice xenografting, molecular docking, protein overexpression/inhibition experiments, and network pharmacology technology. Results: In the CRC group, 15 serum metabolites were significantly different in comparison with the HC group. The level of glycodeoxycholic acid (GDCA) was positively correlated with CRC and showed high sensitivity and specificity for the clinical diagnostic reference (AUC = 0.825). In vitro findings showed that GDCA promoted the proliferation and migration of CRC cell lines (HCT116 and HCT8), and Poly(ADP-ribose) polymerase-1 (PARP-1) was identified as one of the key targets of GDCA. The IC50 of celastrol in HCT116 cells was 121.1 nM, and the anticancer effect of celastrol was supported by in vivo experiments. Based on the potential of GDCA in PPPM, PARP-1 was found to be significantly correlated with the anticancer functions of celastrol. Conclusion: These findings suggest that GDCA is an abnormally produced metabolite of CRC, which may provide an innovative molecular biomarker for the predictive identification and targeted prevention of CRC. In addition, PARP-1 was found to be an important target of GDCA that promotes CRC; therefore, celastrol may be a potential targeted therapy for CRC via its effects on PARP-1. Taken together, the pathophysiology and progress of tumor molecules mediated by changes in metabolite content provide a new perspective for predictive, preventive, and personalized medical of clinical cancer patients based on the target of metabolites in vivo.Clinical trials registration number: ChiCTR2000039410. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-021-00269-8.

Development of a Smart Clinical Bluetooth Thermometer Based on an Improved Low-Power Resistive Transducer Circuit.

Smart sensors have been used in many engineering monitoring and control applications. This work focuses on the development of a new type of clinical Bluetooth thermometer, based on an improved low-power resistive transducer circuit. Most existing resistive transducers use relatively complicated circuits with higher cost and power consumption. To tackle these problems, especially in real applications, an improved low-power resistive transducer circuit is proposed in this work and is used to develop smart Bluetooth thermometers. The parameters of the resistive transducer circuit are selected by quantitative analysis and optimization to improve the performance of the low-power resistive transducer circuit. The effectiveness of the proposed design technology was verified by tests. The temperature measurement error of the new smart Bluetooth thermometer is less than 0.1 °C, which can not only meet the clinical use requirements but also has lower cost and power consumption.

Power-Saving Design of Radio Frequency Identification Sensor Networks in Bus Seatbelt Monitoring Systems.

Seatbelt state monitoring is important in intercity buses for passenger safety. This paper discusses the issues and challenges in power-saving design of radio frequency identification (RFID) sensor networks in bus seatbelt monitoring. A new design approach is proposed in this work for low-power layout and parameter setting in RFID sensor nodes in hardware and software design. A one-to-many pairing registration method is suggested between the concentrator and the seat nodes. Unlike using extra computer software to write seat identification (ID) into an integrated circuit (IC) card, the node ID in this project can be stored into the concentrator directly, which can reduce intermediate operations and reduce development costs. The effectiveness of the proposed low-power design approach is verified by some experimental tests.