CRISPR/Cas9 targeted editing of UDP-rhamnose: Rhamnosyltransferase gene decreases its functions in acteoside biosynthesis and pest resistance in Rehmarmia glutinosa.

UDP-rhamnose: rhamnosyltransferases (URTs)in Rehmarmia glutinosa (RgURT1-RgURT4)may catalyze two key downstream steps of acteoside biosynthesis. Moreover, they were identified from Rehmarmia glutinosa and preliminarily characterized, but their bioinformatics analysis and functions remain to be further explored. The present study mainly focused on investigating their bioinformatics function prediction, genotype-dependent expression, and roles for acteoside biosynthesis and pest resistance with CRISPR/Cas9 technology.Some key findings were as follows:they had a low identity but a typical PSPG box of rhamnosyltransferases, belonging to Glycosyltansferase-GTB type superfamily; They could be expressed depending on genotype,but RgURT4 expression is the highest; Based on RgURT4, two sgRNAs were designed and cloned into pBWA(V)HS-zmpl vector to construct a pBWA(V)HS-Cas9-RgURT vector. It was transferred to Rehmarmia glutinosa using Agrobacterium-mediated transformation so that hygromycin-resistant R. glutinosa plants were obtained. Sequencing indicated that CRISPR/Cas9 targeted editing resulted in base replacements in RgURT4,while its expression was decreased among these edited plants; A few of them had yellower leaves with white dots, lower acteoside and a little higher decaffeoylacteoside than WTs; Tetranychus cinnbarinus among them was observed by stereomicroscope. The results demonstrated that CRISPR/Cas9-mediated RgURT4 editing reduced the acteoside content and pest resistance but decaffeoylacteoside content of Rehmarmia glutinosa. This study will contribute to the function analyses of rhamnosyltransferases gene and downstream steps of acteoside biosynthesis as well as its CRISPR-Cas9-based molecular breeding.

Social-emotional problems in 3-to 5-year-old children: a cross-sectional study of highly educated migrants in a Chinese urban area.

Background: Previous research has primarily examined the mental well-being of children from labor migrant families, yet there is a lack of understanding regarding the mental well-being of children from highly educated migrant backgrounds. This study investigated the social-emotional problems of 3-5-year-olds from highly educated migrant families residing in an urban area of China, as well as explored potential differences in demographic variables. Methods: A cross-sectional study was conducted in Qiantang District, Hangzhou, China, with 1,494 (53.3% boys) children selected via a convenient sampling method. The Ages & Stages Questionnaires: social-Emotional, Second Edition (ASQ:SE-2) was used to measure social-emotional problems. Results: The results showed that 23.6% of the children were at risk for social-emotional problems. More boys (26.7%) than girls (20.1%) had scores above the cut-off. Additionally, more children in the low socioeconomic status (29.9%) had scores above the cut-off than those in the high socioeconomic status (18.9%). There were three common issues among all age groups: "being more active than others," "excessive attachment to parents," and "being overly friendly with strangers. Conclusion: The social-emotional development of children from highly educated migrant families is a significant aspect that deserves recognition, contributing valuable insights to the existing literature on this topic.

Small extracellular vesicle CA1 as a promising diagnostic biomarker for nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC), a malignant cancer originating from the epithelial cells of the nasopharynx, presents diagnostic challenges with current methods such as plasma Epstein-Barr virus (EBV) DNA testing showing limited efficacy. This study focused on identifying small extracellular vesicle (sEV) proteins as potential noninvasive biomarkers to enhance NPC diagnostic accuracy. We isolated sEVs from plasma and utilized 4D label-free proteomics to identify differentially expressed proteins (DEPs) among healthy controls (NC = 10), early-stage NPC (E-NPC = 10), and late-stage NPC (L-NPC = 10). Eighteen sEV proteins were identified as potential biomarkers. Subsequently, parallel reaction monitoring (PRM) proteomic analysis preliminarily confirmed sEV carbonic anhydrase 1 (CA1) as a highly promising biomarker for NPC, particularly in early-stage diagnosis (NC = 15; E-NPC = 10; L-NPC = 15). To facilitate this, we developed an automated, high-throughput and highly sensitive CA1 immune-chemiluminescence chip technology characterized by a broad linear detection range and robust controls. Further validation in an independent retrospective cohort (NC = 89; E-NPC = 39; L-NPC = 172) using this technology confirmed sEV CA1 as a reliable diagnostic biomarker for NPC (AUC = 0.9809) and E-NPC (AUC = 0.9893), independent of EBV-DNA testing. Notably, sEV CA1 exhibited superior diagnostic performance compared to EBV-DNA, with a significant incremental net reclassification improvement of 27.61 % for NPC and 72.11 % for E-NPC detection. Thus, this study identifies sEV CA1 as an innovative diagnostic biomarker for NPC and E-NPC independent of EBV-DNA. Additionally, it establishes an immune-chemiluminescence chip technology for the detection of sEV CA1 protein, paving the way for further validation and clinical application.

An Improved Two-Shot Tracking Algorithm for Dynamics Analysis of Natural Killer Cells in Tumor Contexts.

Natural killer cells (NKCs) are non-specific immune lymphocytes with diverse morphologies. Their broad killing effect on cancer cells has led to increased attention towards activating NKCs for anticancer immunotherapy. Consequently, understanding the motion characteristics of NKCs under different morphologies and modeling their collective dynamics under cancer cells has become crucial. However, tracking small NKCs in complex backgrounds poses significant challenges, and conventional industrial tracking algorithms often perform poorly on NKC tracking datasets. There remains a scarcity of research on NKC dynamics. In this paper, we utilize deep learning techniques to analyze the morphology of NKCs and their key points. After analyzing the shortcomings of common industrial multi-object tracking algorithms like DeepSORT in tracking natural killer cells, we propose Distance Cascade Matching and the Re-Search method to improve upon existing algorithms, yielding promising results. Through processing and tracking over 5000 frames of images, encompassing approximately 300,000 cells, we preliminarily explore the impact of NKCs' cell morphology, temperature, and cancer cell environment on NKCs' motion, along with conducting basic modeling. The main conclusions of this study are as follows: polarized cells are more likely to move along their polarization direction and exhibit stronger activity, and the maintenance of polarization makes them more likely to approach cancer cells; under equilibrium, NK cells display a Boltzmann distribution on the cancer cell surface.

Factors predicting complications following open reduction and internal fixation of intra-articular distal radius fracture.

Objective: This study aimed to determine the incidence and predictors of the complications after open reduction and internal fixation (ORIF) of intra-articular distal radius fracture (IADRF) with a minimum follow-up of 12 months. Methods: Medical records and outpatient follow-up records were retrospectively reviewed to collect medical, surgical, and complication data on consecutive patients who had undergone an ORIF procedure for an IADRF between January 2019 and June 2022. Data included demographics, comorbidities, injury, surgical characteristics, and laboratory findings on admission. A multivariate logistic regression model was constructed to identify the significant predictors, with a composite of any complications occurring within 12 months after the operation as the outcome variable and potentially a range of clinical data as the independent variables. The magnitude of the relationship was indicated by the odds ratio (OR) and the 95% confidence interval (CI). Results: During the study period, 474 patients were included, and 64 had documented complications (n = 73), representing an accumulated rate of 13.5%. Among them, carpal tunnel syndrome was the most common, followed by tenosynovitis caused by tendon irritation/rupture, superficial or deep wound infection, complex regional pain syndrome (CRPS) type 1, radial shortening (≥4 mm), plate/screw problems, and others. The multivariate results showed the following factors significantly associated with increased risk of complications: experience of DRF surgery with <30 cases (OR: 2.2, 95% CI: 1.6-3.5), AO type C fracture (OR: 1.7, 95% CI: 1.2-2.9), initial lunate facet collapse of ≥5 mm (OR: 4.2, 95% CI: 1.4-8.9), and use of temporary external fixation before index surgery (OR: 2.4, 95% CI: 1.5-4.3). Conclusions: These findings may aid in patient counseling and quality improvement initiatives, and IADRF should be directed by an experienced surgeon.

Efficacy of early administration of sacubitril/valsartan after coronary artery revascularization in patients with acute myocardial infarction complicated by moderate-to-severe mitral regurgitation: a randomized controlled trial.

Effects of angiotensin receptor/neprilysin inhibitors (ARNI) on ventricular remodeling in patients with heart failure, especially heart failure with reduced ejection fraction (HFrEF), are better than those of angiotensin-converting enzyme inhibitors (ACEI). Acute myocardial infarction (AMI) complicated by mitral regurgitation exacerbates ventricular remodeling and increases the risk of heart failure. There is limited evidence on the effects of early administration of ARNI in patients with AMI complicated by mitral regurgitation. The aim of this trial was to examine the effectiveness and the safety of early administration of sacubitril/valsartan after coronary artery revascularization in patients with AMI complicated by moderate-to-severe mitral regurgitation. This was a randomized, single-blind, parallel-group, controlled trial. From June 2021 to June 2022, we enrolled 142 consecutive patients with AMI complicated by moderate-to-severe mitral regurgitation and followed them for 12 months. The patients received standard treatment for AMI and were randomly assigned to receive ARNI or benazepril. The primary efficacy end points were the differences in mitral regurgitant jet area (MRJA), mitral regurgitant volume (MRV), concentration of n-terminal pro-brain natriuretic peptide (NT-proBNP), left ventricular ejection fraction (LVEF), and left ventricular end-diastolic volume and end-systolic volume (LVEDV and LVESV) between groups and within groups at baseline, 1, 3, 6, and 12 months. Secondary end points included the rates of heart failure hospitalization, all-cause mortality, refractory angina, malignant arrhythmias, recurrent myocardial infarction, and stroke. Safety end points included the rates of hyperkalemia, renal dysfunction, hypotension, angioedema, and cough. The ARNI group had significantly lower NT-proBNP levels than the benazepril group at 1 month and later (P < 0.001). MRJA and MRV significantly improved in the ARNI group compared with the benazepril group at 12 months (MRJA: - 3.21 ± 2.18 cm2 vs. - 1.83 ± 2.81 cm2, P < 0.05; MRV: - 27.22 ± 15.22 mL vs. - 13.67 ± 21.02 mL, P < 0.001). The ARNI group also showed significant reductions in LVEDV and LVESV (P < 0.05) and improvement in LVEF (P < 0.05). Secondary end point analysis showed a significantly higher rate of heart failure hospitalization in the benazepril group compared with the ARNI group (HR = 2.03, 95% CI 1.12-3.68, P = 0.021). Safety end point analysis showed a higher rate of hypotension in the ARNI group (P < 0.05). Early use of sacubitril/valsartan after coronary artery revascularization in patients with AMI complicated by moderate-to-severe mitral regurgitation can significantly reduce mitral regurgitation, improve ventricular remodeling, and decrease heart failure hospitalization. Nevertheless, caution is needed to avoid hypotension. Chinese Clinical Trial Registry (ChiCTR2100054255) registered on December 11, 2021.

Transcriptomic and targeted metabolome analyses revealed the regulatory mechanisms of the synthesis of bioactive compounds in Citrus grandis 'tomentosa'.

Exocarpium Citri Grandis is a popular Chinese herbal medicine prepared from Citrus grandis 'tomentosa', and it is rich in several bioactive compounds, including flavonoids, coumarins, and volatile oils. However, studies are yet to elucidate the mechanisms of synthesis and regulation of these active components. Therefore, the present study examined the profiles of flavonoids and volatile oil bioactive compounds in plant petals, fruits, and tender leaves, and then performed RNA sequencing on different tissues to identify putative genes involved in the synthesis of bioactive compounds. The results show that the naringin, naringenin, and coumarin contents of the fruitlets were significantly higher than those of the tender leaves and petals, whereas the tender leaves had significantly higher levels of rhoifolin and apigenin. A total of 49 volatile oils, of which 10 were mainly found in flowers, 15 were mainly found in fruits, and 18 were mainly found in leaves, were identified. RNA sequencing identified 9,942 genes that were differentially expressed in different tissues. Further analysis showed that 20, 15, and 74 differentially expressed genes were involved in regulating flavonoid synthesis, regulating coumarin synthesis, and synthesis and regulation of terpenoids, respectively. CHI1 (Cg7g005600) and 1,2Rhat gene (Cg1g023820) may be involved in the regulation of naringin synthesis in C. grandis fruits. The HDR (Cg8g006150) gene, HMGS gene (Cg5g009630) and GGPS (Cg1g003650) may be involved in the regulation and synthesis of volatile oils in C. grandis petals. Overall, the findings of the present study enhance our understanding of the regulatory mechanisms of secondary metabolites in C. grandis, which could promote the breeding of C. grandis with desired characteristics.

Historical variability of cotton yield and response to climate and agronomic management in Xinjiang, China.

Cotton is the primary fibre crop in the world with high economic value, and its yield can be affected by climate and agronomic management. Xinjiang, the largest cotton-producing province in China, contributes to approximately 90 % of the national and over 20 % of global production. Earlier studies focused on cotton yield variability and/or drivers on the site scale, for only one to several counties or cities within Xinjiang, in several years before 2000, or provincial production for a short period. It remains poorly understood how and why cotton yields change in Xinjiang. This study analyzes the spatiotemporal variability of cotton yields at the provincial and county (73 counties) levels from 1989 to 2017 using yield statistics, and identifies the dominant climate and agronomic management factors as well as their optimal ranges, historical states, and interaction effects using the geographical detector method (Geodetector). The results show that the Xinjiang cotton yield has increased markedly over the past decades, with the long-term trend outweighing the interannual variability. High yields are mostly found in southern and northwestern Xinjiang. Yield has increased significantly in over 95.6 % of cotton-planting areas, primarily in the west. Nitrogen fertilization is the leading driver of cotton yield changes, mainly impacting long-term trends. The combination of nitrogen fertilization and agricultural mechanization enhances the explanatory power in a bivariate way and is the strongest in the interaction effect between factors. Temperature variability has the greatest influence on detrended yield variability, and the explanatory power is enhanced and the highest when combined with precipitation. In addition, historical states of these factors are generally lower than their optimal ranges, indicating potential for cotton yield enhancement through improved agronomic management practices and in the context of global warming. This study could enhance understanding of cotton Xinjiang yield variability and drivers, and provides scientific guidance for local cotton cultivation.

Efficacy of Platelet-Rich Plasma in the Treatment of Diabetic Foot Ulcers: A Systematic Review and Meta-Analysis.

BACKGROUND: The probiological healing effect of platelet-rich plasma (PRP) during tissue repair has recently gathered much attention. This study aimed to conduct a systematic review and meta-analysis of patients with diabetic foot ulcer (DFU) receiving PRP or conventional treatment to evaluate their efficacy. METHODS: PubMed, Excerpta Medica Database (EMBASE), Cochrane Library, and China National Knowledge Infrastructure (CNKI) databases were comprehensively searched by 2 independent reviewers following PRISMA guidelines for the inclusion of randomized controlled trials (RCTs) comparing PRP with conventional treatments for DFUs. The primary measurements of healing rate and healing time, the methodological quality and extracted data were assessed using Review Manager 5.3. Statistical significance was set at P < 0.05. RESULTS: A total of 10 RCTs involving 550 patients were included in this study, PRP was observed to significantly improve the healing rate (risk ratio [RR] = 1.38, 95% confidence interval [CI] 1.05-1.82, P = 0.02) and shorten the healing time (mean difference [MD] = -23.23, 95% CI -45.97 to -0.49, P = 0.05) of patients with DFU when compared to the conventional treatment. CONCLUSIONS: Compared to conventional treatment, PRP effectively promoted the healing of patients with DFU by evidently improving the healing rate and healing time.

Association between parents' concerns about eating and sleeping problems and social-emotional development in Chinese children aged 3 to 6 years.

Background: Parents' parenting beliefs have a major influence on their children's eating and sleeping problems and emotional socialization. However, the relationship between parent's concerns about eating or sleeping problems and social-emotional development is unclear. Methods: We used a convenience sampling method to investigate 997 parents of preschool children aged 3 to 6 in Hangzhou, China, and asked them to complete the "Ages & Stages Questionnaire: Social-Emotional (2nd Edition)" (ASQ: SE-2) and the Survey of Concerns about Children's Eating and Sleeping Problems. To examine the relationship between children's social-emotional development and their parents' concerns about their eating or sleeping problems, binary logistic regression was used. Results: There were 218 children (21.9%) with a suspected social-emotional development delay, and 273 parents (27.4%) were concerned about their children's eating or sleeping problems, which mainly focused on ill-balanced eating, bad eating habits, and difficulty falling asleep. The rate of suspected social-emotional development delay in children with the co-occurrence of eating and sleeping problems (37.8%) was significantly higher than those with only eating problems (29.7%), only sleeping problems (24.4%), and those with no eating or sleeping problems (18.8%) (p < 0.05). A binary logistic regression analysis showed that parents' concerns about the co-occurrence of eating and sleeping problems (OR = 2.52, p = 0.01) and only eating problems (OR = 1.71, p = 0.004) were risk factors for children's social-emotional development. In addition, boys were more likely than girls to have suspected social-emotional development delay (OR = 1.49, p = 0.01). Conclusion: Children whose parents were concerned about only eating or the co-occurrence of eating and sleeping problems were linked to have a higher risk of suspected social-emotional development delay.

Fucoxanthin triggers ferroptosis in glioblastoma cells by stabilizing the transferrin receptor.

Glioblastoma (GBM) is the most common and lethal tumor in the world, possessing high stemness, aggressiveness and resistance. Fucoxanthin is a bio-active compound extracted from seaweeds that shows anti-tumor effects to different types of tumors. Here, we show that fucoxanthin inhibits the survival of GBM cells by triggering ferroptosis, a ferric ion and reactive oxygen species (ROS) dependent cell death and ferrostatin-1 could block it. Furthermore, we identified that fucoxanthin targets the transferrin receptor (TFRC). Fucoxanthin is able to block degradation and maintain high levels of TFRC, and similarly inhibits the growth of GBM xenografts in vivo, downregulates the expression of proliferating cell nuclear antigen (PCNA) and upregulates the levels of TFRC in tumor tissues. In conclusion, we demonstrate that fucoxanthin has a significant anti-GBM effect by triggering ferroptosis.

Classification and recognition of milk somatic cell images based on PolyLoss and PCAM-Reset50.

Somatic cell count (SCC) is a fundamental approach for determining the quality of cattle and bovine milk. So far, different classification and recognition methods have been proposed, all with certain limitations. In this study, we introduced a new deep learning tool, i.e., an improved ResNet50 model constructed based on the residual network and fused with the position attention module and channel attention module to extract the feature information more effectively. In this paper, macrophages, lymphocytes, epithelial cells, and neutrophils were assessed. An image dataset for milk somatic cells was constructed by preprocessing to increase the diversity of samples. PolyLoss was selected as the loss function to solve the unbalanced category samples and difficult sample mining. The Adam optimization algorithm was used to update the gradient, while Warm-up was used to warm up the learning rate to alleviate the overfitting caused by small sample data sets and improve the model's generalization ability. The experimental results showed that the classification accuracy, precision rate, recall rate, and comprehensive evaluation index F value of the proposed model reached 97%, 94.5%, 90.75%, and 92.25%, respectively, indicating that the proposed model could effectively classify the milk somatic cell images, showing a better classification performance than five previous models (i.e., ResNet50, ResNet18, ResNet34, AlexNet andMobileNetv2). The accuracies of the ResNet18, ResNet34, ResNet50, AlexNet, MobileNetv2, and the new model were 95%, 93%, 93%, 56%, 37%, and 97%, respectively. In addition, the comprehensive evaluation index F1 showed the best effect, fully verifying the effectiveness of the proposed method in this paper. The proposed method overcame the limitations of image preprocessing and manual feature extraction by traditional machine learning methods and the limitations of manual feature selection, improving the classification accuracy and showing a strong generalization ability.

Ebracteolatain A exerts anti-proliferation of breast cancer by inhibiting Protein kinase D 1 in MEK/ERK and PI3K/AKT signaling pathways.

BACKGROUND: Ebracteolatain A (EA) is an acetyl-phloroglucinol compound extracted from Euphorbiae Ebracteolatae Radix, which has been shown to have antitumor activity. PURPOSE: Current research addressed the antitumor activity of EA in breast cancer and further clarified its mechanism. STUDY DESIGN: Based on the pharmacodynamic evaluation in breast cancer cells and animal models, the antitumor effects of EA will be validated in vitro and in vivo. METHODS: Breast cancer cells were processed with increasing concentrations of EA. CCK-8 and colony formation assays were employed to examine the effects of EA on proliferation and survival. Flow cytometry detected the blocking function of EA on the cell cycle. The specific mechanism of EA in breast cancer was studied by transfection experiments and Western Blot analysis. Finally, a nude mice xenograft tumor model was constructed to assess the therapeutic and potential mechanism of EA. RESULTS: We proved that EA caused a dose-dependent inhibition on MCF-7 and MDA-MB-415 cells with IC50 of 6.164 and 6.623 µmol/l, respectively. While EA reduced cell proliferation and clone formation, and markedly arrested cells in the G0/G1 phase. In vivo, EA remarkably suppressed the tumor weight and volume in xenograft nude mice. Besides, PKD1 reversed the inhibition of EA on breast cancer cell proliferation, clone formation, and cycle arrest, and restored tumor growth in xenograft nude mice. Western Blot confirmed that EA regulates breast cancer by suppressing PKD1 in MEK/ERK and PI3K/AKT signaling pathways. CONCLUSION: Herein, we first confirmed EA exerts anti-proliferation by inhibiting PKD1 in MEK/ERK and PI3K/AKT signaling pathways, indicating that EA is a prodigious breast cancer drug candidate.

An improved nonnegative matrix factorization with the imputation method model for pollution source apportionment during rainstorm events.

Data scarcity caused by extreme conditions during storms adds difficulties in performing pollution source apportionment. This study integrated nonnegative matrix factorization with the imputation method (NMF-IM) to fill in missing data (NAs) and conduct source apportionment. A total of 367 river samples and 35 runoff samples were taken from the Banqiao and Nanfei River basins located in Hefei, China, during four rainfall events from June to August 2020. Sixteen indicators were quantified and used for source diagnostics using NMF-IM. The results showed that total phosphorus (TP) had higher concentrations and more violent fluctuations than total nitrogen (TN) in river samples taken from rain. NMF-IM was shown to recover the value distribution of NAs approximately. The source profiles and contribution rates calculated by NMF-IM with NAs were close to the original results calculated by NMF without NAs, with root mean square error of less than 2.3% and differences less than 9.5%. Multiple forms of nitrogen and phosphorus indicators benefit reaching reasonable source diagnostics results. At least four indicators were needed to reach the same contribution rates as 16 indicator diagnostics. The two good indicator combination groups are nitrate (NO3-N), nitrite (NO2-N), ammonia nitrogen (NH3-N), and total suspended solids (TSS) and NO3-N, NO2-N, phosphorus (PO4-P), and TSS. The pollution source contributions changed with the Antecedent dry period (ADPs) of rain events. Treated tailwater and untreated sewage were major sources, contributing more than 80% of the total pollution of the rainstorm events with short ADPs. Dust wash became the dominant contributor after 60 min and contributed 36% of the total pollution of rainstorm events with long ADPs. The average source contribution rates for rainfall events in the Banqiao River were treated tailwater (41%) > untreated sewage (27%) > dust wash (19%) > other sources (16%). The pollution source diagnostics results were verified to be reasonable by simulation using tested run-off data and literature results.

Multitarget and Multipathway Regulation of Zhenqi Fuzheng Granule against Non-Small Cell Lung Cancer Based On Network Pharmacology and Molecular Docking.

Background and Objective. The morbidity and mortality rates of non-small cell lung cancer (NSCLC) remain high. Zhenqi Fuzheng (ZQFZ) granule, which consists of Astragali Radix and Ligustri Lucidi Fructus, is commonly used to improve the immunity of cancer patients. However, the mechanism of ZQFZ granule against NSCLC is still unclear. In this study, the network pharmacology and molecular docking approaches were used to investigate the potential mechanism of ZQFZ granule on NSCLC. Methods. The ingredients in the ZQFZ granule were considered in one study based on UPLC, and the potential targets were predicted in the SwissTargetPrediction database. NSCLC targets were gathered from GeneCards, OMIM, and TTD databases. The ingredient-target-NSCLC network was drawn by Cytoscape. The protein-protein interaction was obtained from the STRING database, and the gene function and biological pathways were analyzed by Metascape. AutoDock Vina was used to verify the molecular docking between the key compounds and core targets, and PyMol visualized the results. Results. 244 targets were related to 13 candidate compounds and 1904 targets were related to NSCLC, of which a total of 106 anti-NSCLC targets were predicted. The compound-target-NSCLC network indicated that sinapinic acid, ferulic acid, asiatic acid, pratensein, and glycitein might be the key components for treating NSCLC. The 41 vital targets (out of 106 targets) above the median calculated by PPI degree were selected for bioinformatics analysis. The top 10 targets out of 41 ranked by MCC were IL-6, SRC, CTNNB1, STAT3, CASP3, TNF, EGFR, MAPK8, HSP90AA1, and PTGS2. ZQFZ granule treatment for NSCLC involved many pathways through KEGG analyses, which included pathways in cancer (hsa05200), proteoglycans in cancer (hsa05205), endocrine resistance (hsa01522), microRNAs in cancer (hsa05206), PI3K-Akt signaling pathway (hsa04151), and IL-17 signaling pathway (hsa04657). Molecular docking studies revealed that sinapinic acid, ferulic acid, asiatic acid, pratensein, and glycitein had good infinity with most core targets. Conclusions. This study indicated that ZQFZ granule with multicompounds could treat NSCLC through multitargets and multipathways.

Selection of internal reference gene for normalization of reverse transcription-quantitative polymerase chain reaction analysis in Mycoplasma hyopneumoniae.

Mycoplasma hyopneumoniae is the etiological agent of swine enzootic pneumonia (EP), which resulting in considerable economic losses in pig farming globally. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is a major tool for gene expression studies. However, no internal reference genes for normalization of RT-qPCR data of M. hyopneumoniae have been reported. The aim of this study was to screen the most stable genes for RT-qPCR analysis in M. hyopneumoniae under different conditions. Therefore, a total of 13 candidate internal reference genes (rpoC, Lipo, sgaB, oppB, hypo621, oppF, gyrB, uvrA, P146, prfA, proS, gatB, and hypo499) of M. hyopneumoniae filtered according to the reported quantitative proteomic analysis and the 16S rRNA internal reference gene frequently used in other bacteria were selected for RT-qPCR analysis. The mRNAs from different virulence strains (168, 168 L, J, NJ, and LH) at five different growth phases were extracted. The corresponding cycle threshold (Ct) values of the 25 reverse transcribed cDNAs using the 14 candidate genes were determined. Different internal reference genes or combinations were then screened for expression stability analysis using various statistical tools and algorithms, including geNorm, BestKeeper, and NormFinder software, to ensure the reliability of the analysis. Through further comprehensive evaluation of the RefFinder software, it is concluded that the gatB gene was the most suitable internal reference gene for samples of the different virulence strains in different growth phases for M. hyopneumoniae, followed by prfA, hypo499, and gyrB.

The Effects of NAA on the Tuberous Root Yield and Quality of Rehmannia glutinosa and Its Regulatory Mechanism by Transcriptome and Metabolome Profiling.

Naphthylacetic acid (NAA) was used to increase the tuberous root yield of Rehmannia glutinosa, but the differences between its NAA-treated and control tuberous roots (NT and CG) and the regulatory mechanism of NAA effect remain unclear. In order to investigate them, NTs and CGs were used as materials, and both yield-related indices were measured; the metabolomics and transcriptomics were used to capture differentially accumulated metabolites (DAM) and to validate them via mining differentially expressed genes (DEGs), respectively. The effects of NAA treatment: increased NT mass per plant by 21.14%, through increasing the number of roots and increasing the mean root diameter; increased catalpol content by 1.2234% (p < 0.05); up-regulated 11DAMs and 596DEGs; and down-regulated 18 DAMs and 517DEGs. In particular, we discovered that NAA regulated its DAMs and biomass via 10 common metabolic pathways, and that the number of NAA-down-regulated DAMs was more than that of NAA-up-regulated DAMs in its tuberous root. Furthermore, HPLC validated the changes of several DAMs and 15 DEGs (4CL, ARF, CCoAOMT, ARGOS, etc.) associated with the yield increase and DAMs were verified by RT-qPCR. This study provided some valuable resources, such as tuberous root indices, key genes, and DAMs of Rehmannia glutinosa in response to NAA for distinguishing the CGs from NTs, and novel insights into the regulatory mechanism of NAA effects on both at the transcriptomic and metabolomic levels, so it will lay a theoretical foundation for NAA-regulated plant yield and quality, and provide references for prohibiting the uses of NAA as a swelling agent in medicinal tuber plants in China.

Human liver microsomes study on the inhibitory effect of plantainoside D on the activity of cytochrome P450 activity.

BACKGROUND: Plantainoside D is widely existed in the herbs and possesses various pharmacological activities, making it possible to co-administrate with other herbs. Its effect on cytochrome P450 enzymes (P450) is a risk factor for inducing adverse drug-drug interactions. To assess the effect of plantainoside D on the activity of major P450 isoenzymes in human liver microsomes. METHODS: The Cocktail method was conducted in human liver microsomes in the presence of probe substrates. The activity of P450 isoenzymes was evaluated by the production of corresponding metabolites. The concentration-dependent and time-dependent inhibition assays were performed in the presence of 0, 2.5, 5, 10, 25, 50, and 100 µM plantainoside D to characterize the inhibitory effect of plantainoside D. RESULTS: Significant inhibition was observed in the activity of CYP1A2, 2D6, and 3A, which was concentration-dependent with the IC50 values of 12.83, 8.39, and 14.66 µM, respectively. The non-competitive manner and competitive manner were observed in the CYP3A inhibition (Ki = 7.16 µM) and CYP1A2 (Ki = 6.26 µM) and 2D6 inhibition (Ki = 4.54 µM), respectively. Additionally, the inhibition of CYP3A was found to be time-dependent with the KI of 1.28 µM-1 and Kinact of 0.039 min-1. CONCLUSIONS: Weak inhibitory effects of plantainoside D on the activity of CYP1A2, 2D6, and 3A were revealed in vitro, implying its potential of inducing interactions with CYP1A2-, 2D6-, and 3A-metabolized drugs. Although further in vivo validations are needed, the feasibility of the Cocktail method in evaluating P450 activity has been verified.

Influence of emotion on purchase intention of electric vehicles: a comparative study of consumers with different income levels.

Promoting electric vehicles (EVs) adoption has become one of the important paths for countries around the world to address climate change and accelerate the transformation of energy system for achieving sustainable development. As one of the important psychological factors, the research on the explanatory power of emotions to EVs purchase intention is still insufficient. This paper collected 400 valid questionnaires all around China. By incorporating emotions and moral norms into the Theory of Planned Behavior (TPB) model, this study used structural equation model to estimate the impact of positive anticipated emotion (PAE), negative anticipated emotion (NAE), and moral norms together with TPB elements on EVs purchase intention. In order to explore the heterogeneity effect of the above factors on EVs purchase intention among consumers of different income groups, we divided the total sample into high-income subsample and low-income subsample according to the household monthly disposable income. We concluded as follows: for the total sample, PAE has the greatest impact on EVs purchase intention, followed by attitude, NAE, and perceived behavioral control (PBC). In particular, the purchase intention of high-income consumers mainly depends on NAE, while the purchase intention of low-income consumers mainly depends on PAE. Additionally, PBC has more significant impact on EVs purchase intention of high-income group. Finally, targeted policy implications are proposed to promote EVs purchase.

Recognition of bovine milk somatic cells based on multi-feature extraction and a GBDT-AdaBoost fusion model.

Traditional laboratory microscopy for identifying bovine milk somatic cells is subjective, time-consuming, and labor-intensive. The accuracy of the recognition directly through a single classifier is low. In this paper, a novel algorithm that combined the feature extraction algorithm and fusion classification model was proposed to identify the somatic cells. First, 392 cell images from four types of bovine milk somatic cells dataset were trained and tested. Secondly, filtering and the K-means method were used to preprocess and segment the images. Thirdly, the color, morphological, and texture features of the four types of cells were extracted, totaling 100 features. Finally, the gradient boosting decision tree (GBDT)-AdaBoost fusion model was proposed. For the GBDT classifier, the light gradient boosting machine (LightGBM) was used as the weak classifier. The decision tree (DT) was used as the weak classifier of the AdaBoost classifier. The results showed that the average recognition accuracy of the GBDT-AdaBoost reached 98.0%. At the same time, that of random forest (RF), extremely randomized tree (ET), DT, and LightGBM was 79.9, 71.1, 67.3 and 77.2%, respectively. The recall rate of the GBDT-AdaBoost model was the best performance on all types of cells. The F1-Score of the GBDT-AdaBoost model was also better than the results of any single classifiers. The proposed algorithm can effectively recognize the image of bovine milk somatic cells. Moreover, it may provide a reference for recognizing bovine milk somatic cells with similar shape size characteristics and is difficult to distinguish.