High blood glucose variability may predict poor outcomes in patients with spontaneous cerebellar hemorrhage undergoing surgical operation: a retrospective study.

BACKGROUND: Elevated blood glucose (BG) variability has been reported as an independent risk factor for poor prognosis in a variety of diseases. This study aimed to investigate the association between BG variability and clinical outcomes in patients with spontaneous cerebellar hemorrhage (SCH) undergoing surgical operation. METHODS: This retrospective cohort study of the consecutive patients admitted to the department of Neurosurgery, the Affiliated Hospital of Qingdao University between January 2014 and June 2022 with the diagnosis of SCH underwent surgical intervention. BG analysis was continuously and routinely performed. BG variability was represented by the standard deviation (SD) of the serial measurements within the first 7 days. The general characteristics, imageological information, blood glucose level, and surgical information were reviewed and compared through medical records. RESULTS: A total of 115 patients (65 male and 50 female) were enrolled. Out of all 115 patients, the overall clinical outcomes according to the modified Rankin Scale (mRS) were poor (mRS 3-6) in 31 patients (26.96%) and good (mRS 0-2) in 84 patients (73.04%). Twelve of the 115 patients died during hospitalization, and the mortality rate was 10.43%. Multivariate logistic regression analysis showed that SD of BG (odds ratio (OR), 4.717; 95% confidence interval (CI), 1.054-21.115; P = 0.043), GCS (OR, 0.563; 95% CI, 0.330-0.958; P = 0.034), and hematoma volume (OR, 1.395; 95% CI, 1.118-1.748; P = 0.003) were significant predictors. The area under the ROC curve of SD of BG was 0.911 (95% CI, 0.850-0.973; P < 0.001) with a sensitivity and specificity of 90.3% and 83.3%, respectively, and the cut-off value was 1.736. CONCLUSIONS: High BG Variability is independently correlated with the 6-month poor outcomes in patients with SCH undergoing surgical operation.

The anti-breast cancer therapeutic potential of 1,2,3-triazole-containing hybrids.

Breast cancer, as one of the most common invasive malignancies and the leading cause of cancer-related deaths in women globally, poses a significant challenge in the world health system. Substantial advances in diagnosis and treatment have significantly improved the survival rate of breast cancer patients, but the number of incidences and deaths of breast cancer are projected to increase by 40% and 50%, respectively, by 2040. Chemotherapy is one of the principal treatments for breast cancer therapy, but multidrug resistance and severe side effects remain the major obstacles to the success of treatment. Hence, there is a vital need to develop novel chemotherapeutic agents to combat this deadly disease. 1,2,3-Triazole, which can be effectively constructed by click chemistry, not only can serve as a linker to connect different anti-breast cancer pharmacophores but also is a valuable pharmacophore with anti-breast cancer potential and favorable properties such as hydrogen bonding, moderate dipole moment, and enhanced water solubility. Particularly, 1,2,3-triazole-containing hybrids have demonstrated promising in vitro and in vivo anti-breast cancer potential against both drug-sensitive and drug-resistant forms and possessed excellent selectivity by targeting different biological pathways associated with breast cancer, representing privileged scaffolds for the discovery of novel anti-breast cancer candidates. This review concentrates on the latest advancements of 1,2,3-triazole-containing hybrids with anti-breast cancer potential, including work published between 2020 and the present. The structure-activity relationships (SARs) and mechanisms of action are also reviewed to shed light on the development of more effective and multitargeted candidates.

Mechanism of dexmedetomidine protection against cisplatin induced acute kidney injury in rats.

OBJECTIVE: This study explored the molecular mechanisms by which dexmedetomidine (Dex) alleviates cisplatin (CP)-induced acute kidney injury (AKI) in rats. METHODS: CP-induced AKI models were established, and Dex was intraperitoneally injected at different concentrations into rats in the model groups. Subsequently, rats were assigned to the control, CP, CP + Dex 10 µg/kg, and CP + Dex 25 µg/kg groups. After weighing the kidneys of the rats, the kidney arterial resistive index was calculated, and CP-induced AKI was evaluated. In addition, four serum biochemical indices were measured: histopathological damage in rat kidneys was detected; levels of inflammatory factors, interleukin (IL)-1ß, IL-18, IL-6, and tumor necrosis factor alpha, in kidney tissue homogenate of rats were assessed through enzyme-linked immunosorbent assay (ELISA); and levels of NLRP-3, caspase-1, cleaved caspase-1, gasdermin D (GSDMD), and GSDMD-N in kidney tissues of rats were determined via western blotting. RESULTS: Dex treatment reduced nephromegaly and serum clinical marker upregulation caused by CP-induced AKI. In addition, hematoxylin and eosin staining revealed that Dex treatment relieved CP-induced kidney tissue injury in AKI rats. ELISA analyses demonstrated that Dex treatment reduced the upregulated levels of proinflammatory cytokines in the kidney tissue of AKI rats induced by CP, thereby alleviating kidney tissue injury. Western blotting indicated that Dex alleviated CP-induced AKI by inhibiting pyroptosis mediated by NLRP-3 and caspase-1. CONCLUSION: Dex protected rats from CP-induced AKI, and the mechanism may be related to NLRP-3/Caspase-1-mediated pyroptosis.

Twist-Angle and Thickness-Ratio Tuning of Plasmon Polaritons in Twisted Bilayer van der Waals Films.

Stacking bilayer structures is an efficient way to tune the topology of polaritons in in-plane anisotropic films, e.g., by leveraging the twist angle (TA). However, the effect of another geometric parameter, the film thickness ratio (TR), on manipulating the plasmon topology in bilayers is elusive. Here, we fabricate bilayer structures of WTe2 films, which naturally host in-plane hyperbolic plasmons in the terahertz range. Plasmon topology is successfully modified by changing the TR and TA synergistically, manifested by the extinction spectra of unpatterned films and the polarization dependence of the plasmon intensity measured in skew ribbon arrays. Such TR- and TA-tunable topological transitions can be well explained based on the effective sheet optical conductivity by adding up those of the two films. Our study demonstrates TR as another degree of freedom for the manipulation of plasmonic topology in nanophotonics, exhibiting promising applications in biosensing, heat transfer, and the enhancement of spontaneous emission.

RGS5 augments astrocyte activation and facilitates neuroinflammation via TNF signaling.

Astrocytes contribute to chronic neuroinflammation in a variety of neurodegenerative diseases, including Parkinson's disease (PD), the most common movement disorder. However, the precise role of astrocytes in neuroinflammation remains incompletely understood. Herein, we show that regulator of G-protein signaling 5 (RGS5) promotes neurodegenerative process through augmenting astrocytic tumor necrosis factor receptor (TNFR) signaling. We found that selective ablation of Rgs5 in astrocytes caused an inhibition in the production of cytokines resulting in mitigated neuroinflammatory response and neuronal survival in animal models of PD, whereas overexpression of Rgs5 had the opposite effects. Mechanistically, RGS5 switched astrocytes from neuroprotective to pro-inflammatory property via binding to the receptor TNFR2. RGS5 also augmented TNFR signaling-mediated pro-inflammatory response by interacting with the receptor TNFR1. Moreover, interrupting RGS5/TNFR interaction by either RGS5 aa 1-108 or small molecular compounds feshurin and butein, suppressed astrocytic cytokine production. We showed that the transcription of astrocytic RGS5 was controlled by transcription factor early B cell factor 1 whose expression was reciprocally influenced by RGS5-modulated TNF signaling. Thus, our study indicates that beyond its traditional role in G-protein coupled receptor signaling, astrocytic RGS5 is a key modulator of TNF signaling circuit with resultant activation of astrocytes thereby contributing to chronic neuroinflammation. Blockade of the astrocytic RGS5/TNFR interaction is a potential therapeutic strategy for neuroinflammation-associated neurodegenerative diseases.

Electrochemical Synthesis of α-Thiocyanated/Methoxylated Ketones Using Enol Acetates.

We have developed the synthesis of α-substituted ketone compounds with enol acetates in an electrochemical way. By using cheap NH4SCN and MeOH as the radical sources, a series of valuable α-thiocyanates/methoxy ketones were synthesized under mild electrolysis conditions in acceptable yields with diverse functional group compatibility. Additionally, the scale-up experiment and synthetic transformations reveal potential applications in organic synthesis.

Systemic immune-inflammation index may predict the acute kidney injury and prognosis in patients with spontaneous cerebral hemorrhage undergoing craniotomy: a single-center retrospective study.

BACKGROUND: The systemic immune-inflammation index (SII) is an emerging prognostic marker of cancer. We aimed to explore the predictive ability of the SII on acute kidney injury (AKI) and prognosis in patients with spontaneous cerebral hemorrhage (SCH) who underwent craniotomy. METHODS: Patients with SCH who underwent craniotomy between 2014 and 2021 were enrolled in this study. The epidemiology and predictive factors for AKI after SCH were analyzed. The prognostic factors for clinical outcomes in patients with SCH and AKI were further investigated. The prognostic factors were then analyzed using a logistic regression model and a receiver operating characteristic curve. RESULTS: In total, 305 patients were enrolled in this study. Of these, 129 (42.3%) patients presented with AKI, and 176 (57.7%) patients were unremarkable. The SII (odds ratio [OR], 1.261; 95% confidence interval [CI], 1.036-1.553; P = 0.020) values and serum uric acid levels (OR, 1.004; 95% CI, 1.001-1.007; P = 0.005) were significant predictors of AKI after SCH craniotomy. The SII cutoff value was 1794.43 (area under the curve [AUC], 0.669; 95% CI, 0.608-0.730; P < 0.001; sensitivity, 65.9%; specificity, 65.1%). Of the patients with AKI, 95 and 34 achieved poor and good outcomes, respectively. SII values (OR, 2.667; 95% CI, 1.167-6.095; P = 0.020), systemic inflammation response index values (OR, 1.529; 95% CI, 1.064-2.198; P = 0.022), and Glasgow Coma Scale (GCS) scores on admission (OR, 0.593; 95% CI, 0.437-0.805; P = 0.001) were significant in the multivariate logistic regression analysis. The cutoff SII value was 2053.51 (AUC, 0.886; 95% CI, 0.827-0.946; P < 0.001; sensitivity, 78.9%; specificity, 88.2%). CONCLUSIONS: The SII may predict AKI in patients with SCH who underwent craniotomy and may also predict the short-term prognosis of these patients.

Machine Learning Modeling for Spatial-Temporal Prediction of Geohazard.

Geohazards, such as landslides, rock avalanches, debris flow, ground fissures, and ground subsidence, pose significant threats to people's lives and property [...].

Pd-Enriched-Core/Pt-Enriched-Shell High-Entropy Alloy with Face-Centred Cubic Structure for C1 and C2 Alcohol Oxidation.

High-entropy alloy nanoparticles (HEA NPs) have aroused great interest globally with their unique electrochemical, catalytic, and mechanical properties, as well as diverse activity and multielement tunability for multi-step reactions. Herein, a facile low-temperature synthesis method at atmospheric pressure is employed to synthesize Pd-enriched-HEA-core and Pt-enriched-HEA-shell NPs with a single phase of face-centred cubic structure. Interestingly, the lattice of both Pd-enriched-HEA-core and Pt-enriched-HEA-shell enlarge during the formation process of HEA, with tensile strains included in the core and shell of HEA. The as-obtained PdAgSn/PtBi HEA NPs show excellent electrocatalytic activity and durability for methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR). The specific (mass) activity of PdAgSn/PtBi HEA NPs for MOR is 4.7 mA cm-2 (2874 mA mg(Pd+Pt) -1 ), about 1.7 (5.9) and 1.5 (4.8) times higher than that of commercial Pd/C and Pt/C catalysts, respectively. Additional to high-entropy effect, Pt sites and Pd sites on the interface of the HEA act synergistically to facilitate the multi-step process towards EOR. This study offers a promising way to find a feasible route for scalable HEA manufacturing with promising applications.

Chromatin assembly factor 1B critically controls the early development but not function acquisition of invariant natural killer T cells in mice.

CD4+ CD8+ double-positive thymocytes give rise to both conventional TCRαß+ T cells and invariant natural killer T cells (iNKT cells), but these two kinds of cells display different characteristics. The molecular mechanism underlying iNKT cell lineage development and function acquisition remain to be elucidated. We show that the loss of chromatin assembly factor 1B (CHAF1b) maintains the normal development of conventional TCRαß+ T cells but severely impairs early development of iNKT cells. This dysregulation is accompanied by the impairment in chromatin activation and gene transcription at Vα14-Jα18 locus. Notably, ectopic expression of a Vα14-Jα18 TCR rescues Chaf1b-deficient iNKT cell developmental defects. Moreover, cytokine secretion and antitumor activity are substantially maintained in Vα14-Jα18 TCR transgene-rescued Chaf1b-deficient iNKT cells. Our study identifies CHAF1b as a critical factor that controls the early development but not function acquisition of iNKT cells via lineage- and stage-specific regulation.

Plants Mitigate Nitrous Oxide Emissions from Antibiotic-Contaminated Agricultural Soils.

Vegetable production systems are hotspots of nitrous oxide (N2O) emissions and antibiotic pollution. However, little is known about the interconnections among N2O emissions, vegetable growth, and antibiotic contamination. To understand how plants regulate N2O emissions from enrofloxacin (ENR)-contaminated soils, in situ N2O emissions were measured in pot experiments with cherry radish and pakchoi. Gross N2O production and consumption processes were discriminated based on an acetylene inhibition experiment. Results indicated that vegetable growth decreased the cumulative N2O flux from 0.71 to -0.29 kg ha-1 and mitigated the ENR-induced increase in N2O emissions. Radish displayed better mitigation of N2O emissions than pakchoi. By combining the analysis of N2O flux with soil physicochemical and microbiological properties, we demonstrated that growing vegetables could either promote gross N2O consumption or decrease gross N2O production, primarily by interacting with soil nitrate, clade II nosZ (nosZII)-carrying bacteria, and Deinococcus-Thermus. ENR inhibited N2O consumption more than N2O production, with the nosZII-carrying bacteria, represented by Gemmatimonadetes, as the main inhibition target. However, increasing nosZII-carrying bacteria by growing radish offsets the inhibitory effect of ENR. These findings provide new insights into N2O emissions and antibiotic pollution in vegetable-soil ecosystems and broaden the options for mitigating N2O emissions.

Scientometric Analysis of Artificial Intelligence (AI) for Geohazard Research.

Geohazard prevention and mitigation are highly complex and remain challenges for researchers and practitioners. Artificial intelligence (AI) has become an effective tool for addressing these challenges. Therefore, for decades, an increasing number of researchers have begun to conduct AI research in the field of geohazards leading to rapid growth in the number of related papers. This has made it difficult for researchers and practitioners to grasp information on cutting-edge developments in the field, thus necessitating a comprehensive review and analysis of the current state of development in the field. In this study, a comprehensive scientometric analysis appraising the state-of-the-art research for geohazard was performed based on 9226 scientometric records from the Web of Science core collection database. Multiple types of scientometric techniques, including coauthor analysis, co-citation analysis, and cluster analysis were employed to identify the most productive researchers, institutions, and hot research topics. The results show that research related to the application of AI in the field of geohazards experienced a period of rapid growth after 2000, with major developments in the field occurring in China, the United States, and Italy. The hot research topics in this field are ground motion, deep learning (DL), and landslides. The commonly used AI algorithms include DL, support vector machine (SVM), and decision tree (DT). The obtained visualization on research networks offers valuable insights and an in-depth understanding of the key researchers, institutions, fundamental articles, and salient topics through animated maps. We believe that this scientometric review offers useful reference points for early-stage researchers and provides valuable in-depth information to experienced researchers and practitioners in the field of geohazard research. This scientometric analysis and visualization are promising for reflecting the global picture of AI-based geohazard research comprehensively and possess potential for the visualization of the emerging trends in other research fields.

Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach.

Slope failures lead to large casualties and catastrophic societal and economic consequences, thus potentially threatening access to sustainable development. Slope stability assessment, offering potential long-term benefits for sustainable development, remains a challenge for the practitioner and researcher. In this study, for the first time, an automated machine learning (AutoML) approach was proposed for model development and slope stability assessments of circular mode failure. An updated database with 627 cases consisting of the unit weight, cohesion, and friction angle of the slope materials; slope angle and height; pore pressure ratio; and corresponding stability status has been established. The stacked ensemble of the best 1000 models was automatically selected as the top model from 8208 trained models using the H2O-AutoML platform, which requires little expert knowledge or manual tuning. The top-performing model outperformed the traditional manually tuned and metaheuristic-optimized models, with an area under the receiver operating characteristic curve (AUC) of 0.970 and accuracy (ACC) of 0.904 based on the testing dataset and achieving a maximum lift of 2.1. The results clearly indicate that AutoML can provide an effective automated solution for machine learning (ML) model development and slope stability classification of circular mode failure based on extensive combinations of algorithm selection and hyperparameter tuning (CASHs), thereby reducing human efforts in model development. The proposed AutoML approach has the potential for short-term severity mitigation of geohazard and achieving long-term sustainable development goals.

Calcium leaching characteristics in landfill leachate collection systems from bottom ash of municipal solid waste incineration.

Calcium leaching is a critical factor in the clogging of leachate collection systems (LCS), a phenomenon that affects landfill stability and operation. The bottom ash (BA) of municipal solid waste (MSW) incineration plants contains large quantities of calcium-based compounds. Landfilling is the main disposal method for BA in China that intensifies the consequences of LCS clogging. The factors influencing BA calcium leaching were investigated using simulated leachate. The results showed that fine BA particles, low pH values, high temperature, and ratios of leachate to BA solids were conducive to calcium leaching. Calcium leaching was found to be higher in actual leachate than in simulated leachate. At pH = 5, the cumulative calcium dissolution ratios (CDRs) were 83.36% and 31.49% after 20 days of leaching in the actual and simulated leachate, respectively; at pH = 6, the values were 50.67% and 12.06%, respectively. The introduction of landfill gas could decrease the calcium dissolution and leaching rates. When the ratio of leachate to BA solid was 20:1 mL/g, the accumulative CDR values were 45.98% (pH = 6) and 5.80% (pH = 8) without landfill gases, and 4.59% (pH = 6) and 0.48% (pH = 8) with landfill gases. These results provide the scientific basis for clogging risk prediction with respect to calcium leaching in the LCS of landfills. BA landfilling in old landfill areas with relatively high leachate pH and low chemical oxygen demand, as well as when leachate mixed with an appropriate amount of landfill gases, could be feasible measures to reduce calcium leaching and further prevent clogging in LCS.

Visible-Light-Induced Palladium-Catalyzed Carbocyclization of Unactivated Alkyl Bromides with Alkenes Involving C-I or C-B Coupling.

A palladium-catalyzed, photochemical tandem cyclization/dicarbofunctionalization of unactivated alkyl halides containing an alkene moiety offers an appealing route to produce five- or six-membered rings in a redox-neutral fashion. Multisubstituted carbo- and heterocyclic compounds were prepared through the formation of new C-B or C-O bonds, which provides a convenient synthetic route for further transformations. This protocol is characterized by the reaction of alkene regio- and stereoselectivities, good functional group compatibility, wide substrate scope, and mild reaction conditions.

Fungal community composition change and heavy metal accumulation in response to the long-term application of anaerobically digested slurry in a paddy soil.

Anaerobically digested slurry (ADS) has been widely used as a liquid fertilizer in agroecosystems. However, there is scant information on the effects of successive ADS applications on heavy metals (HMs) accumulation and fungal community composition in paddy soils. In this study, we conducted a field experiment over 10 years to assess the changes in soil HMs and fungal community composition under the long-term application of ADS in a paddy field. The four treatments were (1) no fertilizer (CK); (2) mineral fertilizer and 270 kg N ha-1 from urea (MF); (3) 270 kg N ha-1 from ADS (ADS1); and (4) 540 kg N ha-1 from ADS (ADS2). The results revealed that ADS application improved paddy soil fertility compared to that under the MF treatment by increasing soil organic C (SOC), total N (TN) and available potassium (AK). Long-term application of ADS significantly increased soil total and available Zn (TZn and AZn) concentrations as compared to those under the MF treatment. However, there were no significant differences in the total and available Cu concentrations or the total Pb concentration between the ADS and MF treatments. Sequence analysis showed that application of ADS increased the fungal richness indexes (Chao1 and ACE) compared to MF treatment. Principal coordinate analysis (PCoA) showed that the soil fungal community compositions were significantly separated by high levels of ADS application. Long-term application of ADS increased the relative abundance of classes Sordariomycetes, Dothideomycetes and Agaricomycetes by 20.8-29.0%, 107.3-141.4% and 289.5-387.5%, respectively, but decreased that of Pezizomycetes by 14.0-33.0% compared to that under the MF treatment. At the genus level, compared to those under the MF treatment, the relative abundances of Pyrenochaetopsis and Myrothecium were significantly increased by the application of ADS, but those of Mrakia and Tetracladium were significantly decreased. Redundancy analysis (RDA) revealed that SOC, AZn and AP were the three most important factors affecting the fungal community composition of the paddy soil. Our findings suggested that fungal community composition could be affected by changes in the chemical properties and heavy metal contents of paddy soil under high application of ADS in the long term.

Experimental Investigation of the Physical Properties and Microstructure of Slate under Wetting and Drying Cycles Using Micro-CT and Ultrasonic Wave Velocity Tests.

Cyclic wetting and drying processes have been considered as important factors that accelerate the weathering process and have deteriorative effects on rock properties. In the present study, a fully nondestructive and noninvasive testing approach utilizing micro-CT and ultrasonic wave velocity tests was employed to investigate the microstructure of slate under wetting and drying cycles. We studied variations in the physical properties, including the dry weight and the velocities of P- and S-waves versus the number of wetting and drying cycles. The internal microstructural distributions were visualized and quantified by the 3D reconstruction and hybrid image segmentation of CT images. The degree of deterioration caused by wetting and drying cycles was reflected by exponential decreases of physical properties, including dry weight and velocities of the P- and S-waves. Parameters relating to the microfracture diameter, volume, etc. were quantified. The nondestructive and noninvasive testing approach utilizing micro-CT and ultrasonic wave velocity tests has potential for the detection and visualization of the internal microstructure of rock under wetting and drying cycles.

A Hybrid Landslide Displacement Prediction Method Based on CEEMD and DTW-ACO-SVR-Cases Studied in the Three Gorges Reservoir Area.

Accurately predicting the surface displacement of the landslide is important and necessary. However, most of the existing research has ignored the frequency component of inducing factors and how it affects the landslide deformation. Therefore, a hybrid displacement prediction model based on time series theory and various intelligent algorithms was proposed in this paper to study the effect of frequency components. Firstly, the monitoring displacement of landslide from the Three Gorges Reservoir area (TGRA) was decomposed into the trend and periodic components by complete ensemble empirical mode decomposition (CEEMD). The trend component can be predicted by the least square method. Then, time series of inducing factors like rainfall and reservoir level was reconstructed into high frequency components and low frequency components with CEEMD and t-test, respectively. The dominant factors were selected by the method of dynamic time warping (DTW) from the frequency components and other common factors (e.g., current monthly rainfall). Finally, the ant colony optimization-based support vector machine regression (ACO-SVR) is utilized for prediction purposes in the TGRA. The results demonstrate that after considering the frequency components of landslide-induced factors, the accuracy of the displacement prediction model based on ACO-SVR is better than that of other models based on SVR and GA-SVR.

Metal(loid) bioaccessibility and children's health risk assessment of soil and indoor dust from rural and urban school and residential areas.

This study focused on the oral bioaccessibility and children health risks of metal(loid)s (As, Cd, Cr, Cu, Ni, Pb and Zn) in soil/indoor dust of school and households from Lanzhou, China. The simple bioaccessibility extraction test method was applied to assess bioaccessibility, and children's health risk was assessed via statistical modeling (hazard quotients, hazard index and incremental lifetime carcinogenic risk). Metal(loid) content and bioaccessibility in indoor dust samples were significantly higher than those in corresponding soil samples (p < 0.05). The order for mean values of bioaccessibility of the elements in soil was as follows: Cd (57.1%) > Zn (44.6%) > Pb (39.9%) > Cu (33.2%) > Ni (12.4%) > Cr (5.3%) > As (4.4%), while for indoor dust, the order was: As (73.0%) > Cd (68.4%) > Pb (63.3%) > Zn (60.4%) > Cu (36.5%) > Ni (25.2%) > Cr (13.6%). The Pearson correlation coefficient showed that metal(loid) bioaccessibility was in general significantly negatively correlated to the Al, Fe and Mn contents. Neither noncarcinogenic nor carcinogenic risks exceeded the tolerance interval for 3-5- and 6-9-year-old children for all elements. They both were mostly attributed to As considering metal(loid)s types and to school indoor dust considering sources. Therefore, maintaining interior sanitation would be an effective measure to reduce the potential health effects of indoor dust on children.

[Transcriptomic data analyses of wild and cultivated Angelica sinensis root by high-throughput sequencing technology].

The root of Angelica sinensis is known throughout Asia for its traditional efficacy in invigorating and promoting blood circulation. The wild germplasm resources of A. sinensis was in short supply, and most of the commercial medicinal materials come from cultivation. To obtain the differences in the transcriptional levels of wild and cultivated of A. sinensis, the full-length transcriptome of A. sinensis was analyzed using PacBio SMRT three-generation high-throughput sequencing technology. Using the high-throughput sequencing platform Illumina HiSeq X Ten PE150, a root transcriptome dataset of wild and cultivated A.sinensis was obtained. The transcriptome sequencing analyses obtained 16.5 Gb database in wild and cultivated A.sinensis, after assembly steps, we obtain 113 906 transcript sequences(insfroms) with an average length of 1 466 nt. BLAST analysis indicated that 109 113(accounting for 95.79% of the total insfroms), 93 276(81.89%),60 638(53.24%),48 928(42.95%),42 876(37.64%)isofroms were successfully annotated in the NR, Swiss-port, GO, KO and KOG databases, respectively. The annotation information can be classified into three categories of biological processes, cellular components and molecular functions of GO classification, involving 128 KEGG standard metabolic pathways. Analysis of 25 463 differential insfroms, 15 090 higher expression in wild A. sinensis, and 10 373 higher in cultivated A. sinensis. In the enrichment analysis of GO and KEGG, differential insfroms were concentrated on the pathway of plant-pathogen interaction, MAPK signaling pathway-plant and plant hormone signal transduction. In this study, high-throughput sequencing was used to obtain the full-length transcription information of A. sinensis, and the overall characteristics of A. sinensis genetic information were clarified. By comparing the differential expression of wild and cultivated A. sinensis at the genetic level, it provides basic information for further screening and breeding of A. sinensis germplasm resources, resistance research and secondary metabolic pathway analysis.