Au- ZnFe2O4 hollow microspheres based gas sensor for detecting the mustard gas simulant 2-chloroethyl ethyl sulfide.

Mustard gas, a representative of blister agents, poses a severe threat to human health. Although the structure of 2-chloroethyl ethyl sulfide (2-CEES) is similar to mustard gas, 2-CEES is non-toxic, rendering it a commonly employed simulant in related research. ZnFe2O4-based semiconductor gas sensors exhibit numerous advantages, including structural stability, high sensitivities, and easy miniaturization. However, they exhibit insufficient sensitivity at low concentrations and require high operating temperatures. Owing to the effect of electronic and chemical sensitization, the gas-sensing performance of a sensor may be remarkably enhanced via the sensitization method of noble metal loading. In this study, based on the morphologies of ZnFe2O4 hollow microspheres, a solvothermal method was adopted to realize different levels of Au loading. Toward 1 ppm of 2-CEES, the gas sensor based on 2 wt.% Au-loaded ZnFe2O4 hollow microspheres exhibited a response sensitivity twice that of the gas sensor based on pure ZnFe2O4; furthermore, the response/recovery times decreased. Additionally, the sensor displayed excellent linear response to low concentrations of 2-CEES, outstanding selectivity in the presence of several common volatile organic compounds, and good repeatability, as well as long-term stability. The Au-loaded ZnFe2O4-based sensor has considerable potential for use in detecting toxic chemical agents and their simulants.

A genome-wide cross-trait analysis identifies shared loci and causal relationships of obesity and lipidemic traits with psoriasis.

Background: Obesity and dyslipidemia, major global health concerns, have been linked to psoriasis, but previous studies faced methodological limitations and their shared genetic basis remains unclear. This study examines various obesity-related and lipidemic traits as potential contributors to psoriasis development, aiming to clarify their genetic associations and potential causal links. Methods: Summary statistics from genome-wide association studies (GWAS) conducted for obesity-related traits (body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-hip ratio adjusted for the body mass index (WHRadjBMI)) and lipidemic traits (high-density lipoprotein (HDL), LDL, triglyceride (TG), total Cholesterol (TC), apolipoprotein A1 (apoA1), apolipoprotein B (apoB), and apolipoprotein E (apoE)) and psoriasis, all in populations of European ancestry, were used. We quantified genetic correlations, identified shared loci and explored causal relationship across traits. Results: We found positive genetic correlation between BMI and psoriasis (rg=0.22, p=2.44×10-18), and between WHR and psoriasis (rg=0.19, p=1.41×10-12). We further found the positive genetic correlation between psoriasis and WHRadjBMI(rg=0.07, p=1.81×10-2) the genetic correlation, in while the effect of BMI was controlled for. We identified 14 shared loci underlying psoriasis and obesity-related traits and 43 shared loci between psoriasis and lipidemic traits via cross-trait meta-analysis. Mendelian randomization (MR) supported the causal roles of BMI (IVW OR=1.483, 95%CI=1.333-1.649), WHR (IVW OR=1.393, 95%CI=1.207-1.608) and WHRadjBMI (IVW OR=1.18, 95%CI=1.047-1.329) in psoriasis, but not observe any significant association between lipidemic traits and the risk of psoriasis. Genetic predisposition to psoriasis did not appear to affect the risk of obesity and lipidemic traits. Conclusions: An intrinsic link between obesity-related traits and psoriasis has been demonstrated. The genetic correlation and causal role of obesity-related traits in psoriasis highlight the significance of weight management in both the prevention and treatment of this condition.

Anti-psoriasis effect of 18ß-glycyrrhetinic acid by breaking CCL20/CCR6 axis through its vital active group targeting GUSB/ATF2 signaling.

BACKGROUND: Psoriasis is an immune-mediated chronic inflammatory skin disease. Current research suggests that the long-term persistence and recurrence of psoriasis are closely related to the feedback loop formed between keratinocytes and immune cells, especially in Th 17 or DC cells expressing CCR6. CCL20 is the ligand of CCR6. Therefore, drugs that block the expression of CCL20 or CCR6 may have a certain therapeutic effect on psoriasis. Glycyrrhetinic acid (GA) is the main active ingredient of the plant drug licorice and is often used to treat autoimmune diseases, including psoriasis. However, its mechanism of action is still unclear. METHODS: Psoriasis like skin lesion model was established by continuously applying imiquimod on the back skin of normal mice and CCR6-/- mice for 7 days. The therapeutic and preventive effects of glycyrrhetinic acid (GA) on the model were observed and compared. The severity of skin injury is estimated through clinical PASI scores and histopathological examination. qRT-PCR and multiple cytoline assay were explored to detect the expression levels of cytokines in animal dorsal skin lesions and keratinocyte line HaCaT cells, respectively. The dermis and epidermis of the mouse back were separated for the detection of CCL20 expression. Transcription factor assay was applied to screen, and luciferase activity assay to validate transcription factors regulated by GA. Technology of surface plasmon laser resonance with LC-MS (SPR-MS), molecular docking, and enzyme activity assay were used to identified the target proteins for GA. Finally, we synthesized different derivatives of 18beta-GA and compared their effects, as well as glycyrrhetinic acid (GL), on the skin lesion of imiquimod-induced mice to evaluate the active groups of 18beta-GA. RESULTS: 18ß-glycyrrhetinic acid (GA) improved IMQ-induced psoriatic lesions, and could specifically reduce the chemokine CCL20 level of the epidermis in lesion area, especially in therapeutic administration manner. The process was mainly regulated by transcription factor ATF2 in the keratinocytes. In addition, GUSB was identified as the primary target of 18ßGA. Our findings indicated that the subject on molecular target research of glycyrrhizin should be glycyrrhetinic acid (GA) instead of glycyrrhizic acid (GL), because GL showed little activity in vitro or in vivo. Apart from that, α, ß, -unsaturated carbonyl in C11/12 positions was crucial or unchangeable to its activity of 18ßGA, while proper modification of C3 or C30 position of 18ßGA may vastly increase its activity. CONCLUSION: Our research indicates that 18ßGA exerted its anti-psoriasis effect mainly by suppressing ATF2 and downstream molecule CCL20 predominately through α, ß, -unsaturated carbonyl at C11/12 position binding to GUSB in the keratinocytes, and then broke the feedback loop between keratinocytes and CCR6-expressing immune cells. GA has more advantages than GL in the external treatment of psoriasis. A highlight of this study is to investigate the influence of special active groups on the pharmacological action of a natural product, inspired by the molecular docking result.

Comparing the removal efficiency of diisobutyl phthalate by Bacillariophyta, Cyanophyta and Chlorophyta.

The utilization of microalgae for both removing phthalate esters (PAEs) from wastewater and producing bioenergy has become a popular research topic. However, there is a lack of studies comparing the effectiveness of different types of microalgae in removing these harmful compounds. Therefore, the present study aimed to evaluate and compare the efficiency of various processes, such as hydrolysis, photolysis, adsorption, and biodegradation, in removing diisobutyl phthalate (DiBP) using six different species of microalgae. The study indicated that the average removal efficiency of DiBP (initial concentrations of 5, 0.5, and 0.05 mg L-1) by all six microalgae (initial cell density of 1 × 106 cells mL-1) was in the order of Scenedesmus obliquus (95.39 %) > Chlorella vulgaris (94.78 %) > Chroococcus sp. (91.16 %) > Cyclotella sp. (89.32 %) > Nitzschia sp. (88.38 %) > Nostoc sp. (84.33 %). The results of both hydrolysis and photolysis experiments revealed that the removal of DiBP had minimal impact, with respective removal efficiencies of only 0.89 % and 1.82 %. The adsorption efficiency of all six microalgae decreased significantly with increasing initial DiBP concentrations, while the biodegradation efficiency was elevated. Chlorella vulgaris and Chroococcus sp. demonstrated the highest adsorption and biodegradation efficiencies among the microalgae tested. Scenedesmus obliquus was chosen for the analysis of the degradation products of DiBP due to its exceptional ability to remove DiBP. The analysis yielded valuable results, identifying monoisobutyl phthalate (MiBP), phthalic acid (PA), and salicylic acid (SA) as the possible degradation products of DiBP. The possible degradation pathways mainly included dealkylation, the addition of hydroxyl groups, and decarboxylation. This study lays a theoretical foundation for the elimination of PAEs in the aquatic environment.

Design of multi-frequency point, high-isolation switches for micro-channel plate data acquisition.

In order to replace the phosphor screen of a proximity-gated x-ray framing camera with a readout circuit using a time-interleaved structure, this paper carries out the design of a high-isolation RF switch. In this paper, a Metal-Oxide-Semiconductor Field Effect Tube (MOSFET) switching circuit is designed to achieve high isolation and low insertion loss at 0.5-3 GHz. This solves the problem that the switching circuit cannot be turned off properly due to the parasitic capacitance of MOSFETs in the process of RF signal transmission, resulting in signal feedthrough. It also ensures that the input signal can be transmitted to the output intact when the switching circuit is turned on. High isolation is achieved by using parallel resonance to increase the voltage division and series resonance to leak the current. The switch achieves 76 dB isolation and 0.07 dB insertion loss at 1 GHz frequency. Isolation is increased by adding parallel branches near the 2 and 3 GHz frequency points, achieving greater than 33 dB isolation from 0.5 to 3 GHz.

Investigation of dissolved organic matter's influence on the toxicity of cadmium to the cyanobacterium Microcystis aeruginosa by biochemical and molecular assays.

Rapid economic development has increased the accumulation of dissolved organic matter (DOM) and heavy metals in aquatic environments. In addition, Microcystis aeruginosa can cause the outbreak of cyanobacteria bloom and can produce microcystin, which poses a threat to human water safety. Therefore, this study analyzed the biochemical and molecular assays of DOM (0, 1, 3, 5, 8, 10 mg C L-1) extracted from four different sources on the toxicity of cadmium (Cd) to M. aeruginosa. The results showed that the addition of different concentrations of DOM from sediment, biochar, and humic acid alleviated the toxicity of Cd to M. aeruginosa. But the addition of rice hulls DOM at high concentrations (8 and 10 mg L-1) significantly reduced the normal growth and metabolic activities of M. aeruginosa. DOM from four different sources promoted the expression level of microcystin-related gene mcyA and the production of microcystin-leucine-arginine (MC-LR), and mcyA was positively correlated with MC-LR. DOM from biochar, sediment, and humic acid were able to bind Cd through complexation. The results will help to understand the toxic effects of heavy metals on toxic-producing cyanobacteria in the presence of DOM, and provide certain reference for the evaluation of water environmental health.

Systematical construction of rice flavor types based on HS-SPME-GC-MS and sensory evaluation.

Rice is one of the main staple foods of Chinese people and its quality requirements are also improving. Aroma is one of the evaluation factors of rice quality, rice with better aroma quality is often more accepted by consumers. A universal aroma descriptive lexicon was established and four flavor types were formed based on samples from 9 representative rice cultivation regions. The key variables affecting the sensory quality of Chinese rice flavor were screened. It was found that the hexanal and nonanal with the highest content had no effect on the flavor properties, which suggests that volatile organic compounds (VOCs) content is not necessarily related to the influence of flavor properties. According to the aroma analysis of different rice flavor types, it can provide guidance for other flavor research.

Volatile metabolomics and chemometric study provide insight into the formation of the characteristic cultivar aroma of Hemerocallis.

Due to its ornamental, edible, and medicinal value, Hemerocallis has been historically loved and used in China. However, the current understanding of the aromatic profiles of this flower is rather limited. This work aimed to evaluate and classify the aromatic profiles of Hemerocallis flowers from 10 cultivars, the volatiles of which were analyzed using solid-phase microextraction-gas chromatography-mass spectrometry. Sensory evaluation, odor activity value and relative odor activity value calculations, and chemometric analysis were also performed, the result showed that a total of 81 volatile components were identified. Linalool, 3-furanmethanol, indole, phenylacetonitrile, nerolidol, benzaldehyde, nonanal, geranial, (E)-ß-ocimene, and volatile components specific to the different types were found to have an essential role in identifying these 10 varieties. The findings presented in this thesis add to our understanding of Hemerocallis.

Deep regression using 99mTc-DTPA dynamic renal imaging for automatic calculation of the glomerular filtration rate.

OBJECTIVES: To develop and evaluate an artificial intelligence (AI) system that can automatically calculate the glomerular filtration rate (GFR) from dynamic renal imaging without manually delineating the regions of interest (ROIs) of kidneys and the corresponding background. METHODS: This study was a single-center retrospective analysis of the data of 14,634 patients who underwent 99mTc-DTPA dynamic renal imaging. Two systems based on convolutional neural networks (CNN) were developed and evaluated: sGFRa predicts the radioactive counts of ROIs and calculates GFR using the Gates equation and sGFRb directly predicts GFR from dynamic renal imaging without using other information. The root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R2 were used to evaluate the performance of our approach. RESULTS: sGFRa achieved an RMSE of 5.05, MAE of 4.03, MAPE of 6.07%, and R2 of 0.93 for total GFR while sGFRb achieved an RMSE of 7.61, MAE of 5.92, MAPE of 8.92%, and R2 of 0.85 for total GFR. The accuracy of sGFRa and sGFRb in determining the stage of chronic kidney disease was 87.41% and 82.44%, respectively. CONCLUSIONS: The findings of sGFRa show that automatic GFR calculation based on CNN and using dynamic renal imaging is feasible and efficient and, additionally, can aid clinical diagnosis. Furthermore, the promising results of sGFRb demonstrate that CNN can predict GFR from dynamic renal imaging without additional information. KEY POINTS: • Our CNN-based AI systems can automatically calculate GFR from dynamic renal imaging without manually delineating the ROIs of kidneys and the corresponding background. • sGFRa accurately predicted the radioactive counts of ROIs and calculated GFR using the Gates method. • sGFRb-predicted GFR directly without any parameters related to the Gates equation.

[Nitric Oxide Emissions from Chinese Upland Cropping Systems and Mitigation Strategies: A Meta-analysis].

Agroecosystems are a significant source of nitric oxide (NO), a potent atmospheric pollutant. It has been well documented that the NO emissions from upland cropping systems and their emission factors are large relative to those from paddy fields. However, a clear understanding of their uncertainty and regulating factors is still lacking. To date, various field experiments have been conducted to investigate NO emissions and mitigation, providing an opportunity for a Meta-analysis. The aims of this study were to 1 investigate the uncertainty and regulating factors of NO emissions and emission factors from maize-winter wheat rotations, non-waterlogging period in rice-winter wheat rotations, vegetable fields, tea plantations, and fruit orchards across China by extracting data from peer-reviewed publications, and 2 quantify the mitigation potential of management practices, such as reducing nitrogen fertilizer input, organic substitution with chemical fertilizers, and application of enhanced-efficiency nitrogen fertilizers or biochar by performing a pairwise Meta-analysis. A total of 49 references (published from 2006 to 2021) were collected. The results showed that annual NO emissions from the maize-winter wheat rotations, tea plantations, and fruit orchards averaged 1.44, 7.45, and 0.92 kg·hm-2, respectively, with significant differences among the three cropping systems (P<0.05). The seasonal NO emissions from the non-waterlogging period in rice-winter wheat rotations and vegetable fields within a single growth period averaged 2.13 kg·hm-2 and 2.09 kg·hm-2, respectively. The NO emissions positively related to nitrogen inputs in the maize-winter wheat rotations, non-waterlogging period in rice-winter wheat rotations, and tea plantations (P<0.01) but not in the vegetable fields and fruit orchards. The emission factors averaged 0.31%, 0.71%, 0.96%, 1.74%, and 0.13% in the maize-winter wheat rotations, non-waterlogging period in rice-winter wheat rotations, vegetable fields, tea plantations, and fruit orchards, respectively, with significant differences among the cropping systems (P<0.01), except between the maize-winter wheat rotations and non-waterlogging period in rice-winter wheat rotations or vegetable fields (P>0.05). Considering the substantial differences in emission factors among the cropping systems, a specific emission factor for each system should be applied when estimating an agricultural NO budget at a regional or national scale. Reducing nitrogen input only mitigated NO emissions (by 36%) at a reducing nitrogen ratio above 25% but did not impact emission factors. An optimal reducing nitrogen ratio has to be further evaluated without crop productivity penalties. Organic substitution in soils with organic carbon content<15 g·kg-1 or pH<7 and application of enhanced-efficiency fertilizers in the maize-winter wheat rotation simultaneously mitigated NO emissions (by -46%- -38%) and emission factors (by -62%- -45%). By contrast, biochar amendment had no significant effects on either NO emissions or emission factors. These findings highlight a possibility of choosing an effective NO mitigation strategy under specific field conditions.

An automatic fine-grained skeleton segmentation method for whole-body bone scintigraphy using atlas-based registration.

PURPOSE: Whole-body bone scintigraphy (WBS) is one of the common imaging methods in nuclear medicine. It is a time-consuming, tedious, and error-prone issue for physicians to determine the location of bone lesions which is important for the qualitative diagnosis of bone lesions. In this paper, an automatic fine-grained skeleton segmentation method for WBS is developed. METHOD: The proposed method contains four steps. In the first step, a novel denoising method is proposed to remove the noise from WBS which benefits the location of the skeleton. In the second step, a restoration method based on gray probability distribution is developed to repair the partial contamination caused by the high local density of radionuclide. Then, the standardization for WBS is performed by the exact histogram matching. Finally, the deformation field between the atlas and the input WBS is calculated by registration, and the segmentation mask of the input WBS is obtained by wrapping the segmentation mask of the atlas with the deformation field. RESULTS: The experimental results show that the proposed method outperforms the traditional registration (Morphon): mean square error decreased from [Formula: see text] to [Formula: see text], peak signal-to-noise ratio increased from 21.26 to 26.92, and mean structural similarity increased from 0.9986 to 0.9998. CONCLUSIONS: Our experiments show that the proposed method can achieve robust and fine-grained results which outperform the traditional registration method, indicating it could be helpful in clinical application. To the best of our knowledge, this is the first work that implements a fully automated fine-grained skeleton segmentation method for WBS.

Crosstalk of LncRNA HOTAIR and SP1-mediated repression of PDK1 contributes to ß-Elemene-inhibited proliferation of hepatocellular carcinoma cells.

ETHNOPHARMACOLOGICAL RELEVANCE: Hepatocellular carcinoma (HCC) is a liver malignancy which lacks effective treatment and has a poor prognosis. ß-Elemene refers to a natural Curcuma wenyujin-derived single molecular entity, which exhibits various biological activities, and is especially well-known for it's antitumor properties. AIM OF THE RESEARCH: LncRNA HOTAIR, SP1, and PDK1 have displayed oncogenic roles in many tumors, participating in the initiation and progression of cancers by mediating multiple signaling pathways. However, there are only a few reports about their roles and mutual relationship in the growth of HCC cells. Therefore, this study aimed to investigate the expression of LncRNA HOTAIR, SP1, and PDK1 and their interaction with ß-Elemene in HCC cells. MATERIALS AND METHODS: MTT, a Colony formation assay, and flow cytometry were employed to evaluate the growth of HCC and LO2 cells under ß-Elemene. LncRNA HOTAIR, SP1 and PDK1 plasmids were transfected into HCC cells by a transient transfection assay, and the expression and interaction of LncRNA HOTAIR, SP1 and PDK1 were assessed via qRT-PCR and western blotting. RESULTS: ß-Elemene suppressed HCC cell growth through the downregulation of LncRNA HOTAIR, SP1 and PDK1. The results demonstrated a reciprocal interaction among LncRNA HOTAIR, SP1 and PDK1. Exogenous overexpression LncRNA HOTAIR or SP1 eliminated the suppressive effects of ß-Elemene on them, and both of which regulated PDK1 expression in HCC cells. Additionally, exogenously overexpressed SP1 or LncRNA HOTAIR prevented ß-Elemene inhibition of the protein-level expression of PDK1, whereas overexpressing PDK1 had no effect on SP1, though it still weakened the inhibition of cell growth and LncRNA HOTAIR expression by ß-Elemene. CONCLUSION: ß-Elemene suppresses HCC cell proliferation via through the regulation of LncRNA HOTAIR, SP1, PDK1 and their interaction.

Automatic differentiation of thyroid scintigram by deep convolutional neural network: a dual center study.

BACKGROUND: 99mTc-pertechnetate thyroid scintigraphy is a valid complementary avenue for evaluating thyroid disease in the clinic, the image feature of thyroid scintigram is relatively simple but the interpretation still has a moderate consistency among physicians. Thus, we aimed to develop an artificial intelligence (AI) system to automatically classify the four patterns of thyroid scintigram. METHODS: We collected 3087 thyroid scintigrams from center 1 to construct the training dataset (n = 2468) and internal validating dataset (n = 619), and another 302 cases from center 2 as external validating datasets. Four pre-trained neural networks that included ResNet50, DenseNet169, InceptionV3, and InceptionResNetV2 were implemented to construct AI models. The models were trained separately with transfer learning. We evaluated each model's performance with metrics as following: accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), recall, precision, and F1-score. RESULTS: The overall accuracy of four pre-trained neural networks in classifying four common uptake patterns of thyroid scintigrams all exceeded 90%, and the InceptionV3 stands out from others. It reached the highest performance with an overall accuracy of 92.73% for internal validation and 87.75% for external validation, respectively. As for each category of thyroid scintigrams, the area under the receiver operator characteristic curve (AUC) was 0.986 for 'diffusely increased,' 0.997 for 'diffusely decreased,' 0.998 for 'focal increased,' and 0.945 for 'heterogeneous uptake' in internal validation, respectively. Accordingly, the corresponding performances also obtained an ideal result of 0.939, 1.000, 0.974, and 0.915 in external validation, respectively. CONCLUSIONS: Deep convolutional neural network-based AI model represented considerable performance in the classification of thyroid scintigrams, which may help physicians improve the interpretation of thyroid scintigrams more consistently and efficiently.

Automatic identification of suspicious bone metastatic lesions in bone scintigraphy using convolutional neural network.

BACKGROUND: We aimed to construct an artificial intelligence (AI) guided identification of suspicious bone metastatic lesions from the whole-body bone scintigraphy (WBS) images by convolutional neural networks (CNNs). METHODS: We retrospectively collected the 99mTc-MDP WBS images with confirmed bone lesions from 3352 patients with malignancy. 14,972 bone lesions were delineated manually by physicians and annotated as benign and malignant. The lesion-based differentiating performance of the proposed network was evaluated by fivefold cross validation, and compared with the other three popular CNN architectures for medical imaging. The average sensitivity, specificity, accuracy and the area under receiver operating characteristic curve (AUC) were calculated. To delve the outcomes of this study, we conducted subgroup analyses, including lesion burden number and tumor type for the classifying ability of the CNN. RESULTS: In the fivefold cross validation, our proposed network reached the best average accuracy (81.23%) in identifying suspicious bone lesions compared with InceptionV3 (80.61%), VGG16 (81.13%) and DenseNet169 (76.71%). Additionally, the CNN model's lesion-based average sensitivity and specificity were 81.30% and 81.14%, respectively. Based on the lesion burden numbers of each image, the area under the receiver operating characteristic curve (AUC) was 0.847 in the few group (lesion number n ≤ 3), 0.838 in the medium group (n = 4-6), and 0.862 in the extensive group (n > 6). For the three major primary tumor types, the CNN-based lesion identifying AUC value was 0.870 for lung cancer, 0.900 for prostate cancer, and 0.899 for breast cancer. CONCLUSION: The CNN model suggests potential in identifying suspicious benign and malignant bone lesions from whole-body bone scintigraphic images.

Fuzhenghefuzhiyang Formula (FZHFZY) Improves Epidermal Differentiation via Suppression of the Akt/mTORC1/S6K1 Signalling Pathway in Psoriatic Models.

Psoriasis is a chronic proliferative skin disorder characterised by abnormal epidermal differentiation. The Fuzhenghefuzhiyang (FZHFZY) formula created by Chuanjian Lu, a master of Chinese medicine in dermatology, has been external used in the Guangdong Provincial Hospital of Chinese Medicine for the treatment of psoriasis, but its mechanisms of action against psoriasis remain poorly understood. This study involved an exploration of the effects of FZHFZY on epidermal differentiation and its underlying mechanisms in interleukin (IL)-17A/IL-22/interferon (IFN)-γ/tumour necrosis factor (TNF)-α-stimulated HaCaT cells and in a mouse model of imiquimod (IMQ)-induced psoriasis. Cell viability was assessed by MTT assay. Epidermal differentiation was detected by reverse-transcription polymerase chain reaction and western blotting. Histological evaluation of the skin tissue was performed via haematoxylin and eosin staining, and the Akt/mTORC1/S6K1 pathway was analysed by western blotting. FZHFZY inhibited proliferation and improved epidermal differentiation in IL-17A/IL-22/IFN-γ/TNF-α-induced HaCaT cells. FZHFZY ameliorated symptoms of psoriasis, regulated epidermal differentiation and inhibited phosphorylation of the Akt/mTORC1/S6K1 pathway in the skin of mice with imiquimod-induced psoriasis. Our results suggest that FZHFZY may exhibit therapeutic action against psoriasis by regulating epidermal differentiation via inhibition of the Akt/mTORC1/S6K1 pathway.

Metabonomics Study on the Infertility Treated With Zishen Yutai Pills Combined With In Vitro Fertilization-embryo Transfer.

Zishen Yutai Pills (ZYP) is a safe and well quality-controlled TCM preparation with promising effects in many fields of reproduction, including prevention of miscarriage, increase of pregnancy rate during in vitro fertilization-embryo transfer (IVF-ET). The plasma of patients was collected from a clinical trial, namely, "Effect of Traditional Chinese Medicine vs placebo on live births among women undergoing in vitro fertilization, a multi-center randomized controlled trial." Plasma samples were analyzed with metabonomics method. UPLC-MS technology was used to establish the plasma metabolic fingerprint. Multivariate statistical analysis was applied for comparing the differences of plasma metabolites between ZYP group and placebo group, 44 potential metabolites were screen out and identified. Pathway analysis was conducted with database mining. Compared with placebo, chemicals were found to be significantly down-regulated on HCG trigger day and 14 days after embryo transplantation, including trihexosylceramide (d18:1/26:1), glucosylceramide(d18:1/26:0), TG(22:6/15:0/22:6), TG(22:4/20:4/18:4). Compared with placebo, some chemicals were found to be significantly up-regulated on HCG trigger day and 14 days after embryo transplantation, i.e., PIP3(16:0/16:1), PIP2(18:1/18:1), tauroursodeoxycholic acid, L-asparagine, L-glutamic acid, kynurenic acid, 11-deoxycorticosterone, melatonin glucuronide, hydroxytyrosol. These metabolites were highly enriched in pathways including sphingolipid metabolism, alanine, aspartic acid and glutamic acid metabolism, aminoacyl tRNA biosynthesis, taurine and hypotaurine metabolism. This study revealed metabolic differences between subjects administered with ZYP and placebo. Relating metabolites were identified and pathways were enriched, providing basis on the exploration on the underlying mechanisms of ZYP combined with IVF-ET in the treatment of infertility.

[Research progress of microextraction by packed sorbent and its application in microvolume sample extraction].

Microextraction is a rapidly developing sample preparation technology in the field of analytical chemistry, which is seeing widespread application. Accurate sample preparation can not only save time but also improve the efficiency of analysis, determination, and data quality. At present, sample pretreatment methods must be rapid, allow for miniaturization, automation, and convenient online connection with analytical instruments. To meet the requirements of green analytical methods and improve the extraction efficiency, microextraction techniques have been introduced as suitable replacements to conventional sample preparation and extraction methods. Microextraction using a packed sorbent (MEPS) is a new type of sample preparation technology. The MEPS equipment was prepared using microsyringe with a volume of 50-500 µL, including MEPS syringes and MEPS adsorption beds (barrel insert and needle, BIN), which is essentially similar to a miniaturized solid phase extraction device. The BIN contains the adsorbent and is built into the syringe needle. A typical MEPS extraction procedure involves repeatedly pumping the sample solution in two directions (up and down) through the adsorbent multiple times in the MEPS syringe. The specific operation course of MEPS includes conditioning, loading, washing, elution, and introduction into the analysis instrument. The conditioning process is adopted to infiltrate the dry sorbent and remove bubbles between the filler particles. The adsorption process is accomplished by pulling the liquid plunger of the syringe so that the sample flows through the adsorbent in both directions multiple times. The washing process involves rinsing the sorbent to remove unwanted components after the analyte is retained. The elution process involves the use of an eluent to ensure that the sample flows through the adsorbent in both directions multiple times, so that elution can be realized by the pumping-pushing action. The target analyte is eluted with the eluent, which can be directly used for chromatographic analysis. However, when processing complex biological matrix samples by MEPS, pretreatment steps such as dilution of the sample and removal of proteins are commonly required. At present, the operation modes of the MEPS equipment are classified into three types: manual, semi-automated, and fully automated. This increase in the degree of automation is highly conducive to processing extremely low or extremely high sample volumes. Critical factors affecting the MEPS performance have been investigated in this study. The conditions for MEPS optimization are the operating process parameters, including sample flow rate, sample volume, number of sample extraction cycles, type and volume of the adsorbent, and elution solvents. It is also necessary to consider the effect of the sample matrix on the performance of MEPS. The MEPS sorbent should be cleaned by a solvent to eliminate carryover and reuse. The sorbent is a core aspect of MEPS. Several types of commercial and non-commercial sorbents have been used in MEPS. Commercial sorbents include silica-based sorbents such as unmodified silica (SIL), C2, C8, and C18. Unmodified silicon-based silica is a normal phase adsorption material, which is highly polar and can be used to retain polar analytes. C18, C8, and C2 materials are suitable for reversed-phase adsorption, while SCX, SAX, APS, and M1 (C8+SCX) adsorbents are suitable for the mixed-mode and ion-exchange modes. Noncommercial sorbents include molecularly imprinted materials, restricted-access molecularly imprinted materials, graphitized carbon, conductive polymer materials, modified silicon materials, and covalent-organic framework materials. The performance of MEPS has recently been illustrated by online with LC-MS and GC-MS assays for the analysis of biological matrices, environmental samples, and food samples. Pretreatment in MEPS protocols includes dilution, protein precipitation, and centrifugation in biological fluid matrices. Because of the small sample size, fast operation, etc., MEPS is expected to be more widely used in the analysis of bio-matrix samples. MEPS devices could also play an important role in field pretreatment and analysis.

Rapid detection of sulfur mustard hydrolysis products based on microextraction by packed sorbent combined with nano-electrospray ionization mass spectrometry.

RATIONALE: Sulfur mustard is a blister agent prohibited by the Chemical Weapons Convention, and the detection of its hydrolysis product, thiodiglycol (TDG), is an important indicator of blister agent contamination. Due to the poor volatility and low extraction efficiency of TDG, derivatization gas chromatography or liquid chromatography is required for conventional methods, and the detection process is cumbersome and time-consuming. METHODS: A microextraction by packed sorbent (MEPS) device and a nano-electrospray ionization (nano-ESI) device were used. The central composite design (CCD) model of Response Surface Methodology was used to optimize the elution procedure; the variance analysis under equal repeated trials with multiple factors was used to quantitatively analyze the significance of the impact of related factors on the nano-ESI efficiency. The MEPS-nano-ESI-MS experimental conditions were optimized. RESULTS: A new detection method of sulfur mustard hydrolysis products in water based on MEPS-nano-ESI-MS was established; the detection limit was 1 ng/mL and was linear between 5 ng/mL and 100 ng/mL (R2 = 0.9911) with a precision of ≤7.2%, and the recovery rate was 107.89% when the sample concentration was 40 ng/mL. CONCLUSIONS: The experimental results showed that the proposed method could quickly detect the contaminated water samples without chromatographic separation and derivatization, thereby verifying the contamination of sulfur mustard on site.

Anti-Angiogenic Efficacy of PSORI-CM02 and the Associated Mechanism in Psoriasis In Vitro and In Vivo.

Psoriasis is a chronic proliferative autoimmune dermatologic disease characterised by abnormal angiogenesis. Thus, regulating angiogenesis in the skin is an important treatment strategy for psoriasis. PSORI-CM02, an empirical Chinese medicine formula optimised from Yin Xie Ling, was created by the Chinese medicine specialist, Guo-Wei Xuan. Clinical studies have shown that PSORI-CM02 is safe and effective for the treatment of psoriasis. However, its anti-psoriatic mechanisms remain to be further explored. In this study, we investigated the effects of PSORI-CM02 on angiogenesis in the skin and the underlying mechanisms in IL-17A-stimulated human umbilical vein endothelial cells (HUVECs) and a murine model of imiquimod (IMQ)-induced psoriasis. In vitro, PSORI-CM02 significantly inhibited the proliferation and migration of IL-17A-stimulated HUVECs in a dose-dependent manner. Further, it markedly regulated the antioxidative/oxidative status and inflammation; suppressed the expression of VEGF, VEGFR1, VEGFR2, ANG1, and HIF-1α; and reduced the phosphorylation of MAPK signalling pathway components in IL-17A-stimulated HUVECs. In vivo studies showed that PSORI-CM02 markedly reduced angiogenesis in the skin of mice with IMQ-induced psoriasis, while significantly rebalancing antioxidant/oxidant levels; inhibiting the production of IL-6, TNF-α, IL-17A, and IL-17F; and repressing the synthesis of angiogenic mediators. In addition, PSORI-CM02 markedly reduced the activation of the MAPK signalling pathway in psoriatic skin tissue. Taken together, our results demonstrated that PSORI-CM02 inhibited psoriatic angiogenesis by reducing the oxidative status and inflammation, suppressing the expression of angiogenesis-related molecules, and inhibiting the activation of the MAPK signalling pathway in vitro and in vivo.

The Gene Expression Analysis of Peripheral Blood Monocytes From Psoriasis Vulgaris Patients With Different Traditional Chinese Medicine Syndromes.

Psoriasis is chronic skin disease and an important health concern. Traditional Chinese Medicine (TCM) has shown great promise in the treatment of psoriasis. However, the correlation between TCM Syndromes and genomics of psoriasis has not been evaluated. Here, we analyzed gene expression profiling of monocytes from psoriasis vulgaris patients with different TCM syndrome types to reveal the molecular basis of different psoriasis syndromes. Of the 62 cases of psoriasis vulgaris recruited, 16, 23, and 23 cases were of blood-heat syndrome, blood stasis syndrome, and blood-dryness syndrome, respectively; 10 healthy controls were recruited as controls. Affymertix's Gene Chip ®clariom D gene chip was used to detect the gene expression profile of peripheral blood monocytes collected from recruited individuals. Compared with the healthy control group, 1570 genes were up-regulated and 977 genes were down-regulated in the psoriasis vulgaris patients group; 798 genes and 108 genes were up- and down-regulated in the blood-heat syndrome group respectively; 319 and 433 genes were up- and down-regulated in the blood-dryness syndrome group, respectively; and 502 and 179 genes were up-and down-regulated in the blood-stasis syndrome group. Our analyses indicated not only common differential genes and pathways between psoriasis syndrome groups and healthy controls, but also syndrome-specific genes and pathways. The results of this study link the three syndromes at the gene level and will be useful for clarifying the molecular basis of TCM syndromes of psoriasis. Clinical Trial Registration: (http://www.chictr.org.cn/showproj.aspx?proj=4390), identifier (ChiCTR-TRC-14005185).