Time-Dependent Extension of Grimme's Continuous Chirality Measure for Electronic Chirality Flips in Femto- and Attosecond Time Domains.

Grimme's Continuous Chirality Measure ( C C M ${CCM}$ ) was developed for comparisons of the chirality of the electronic wave functions of molecules, typically in their ground states. For example, C C M = 14 . 5 ${CCM=14.5}$ , 1 . 2 ${1.2}$ and 0 . 0 ${0.0}$ for alanine, hydrogen-peroxide, and for achiral molecules, respectively. Well-designed laser pulses can excite achiral molecules from the electronic ground state to time-dependent chiral superposition states, with chirality flips in the femto- or even attosecond (fs or as) time domains. Here we provide a time-dependent extension C C M t ${CCM\left(t\right)}$ of Grimme's C C M ${CCM}$ for trailing the electronic chirality flips. As examples, we consider two laser driven electronic wavefunctions which represent flips between opposite electronic enantiomers of oriented NaK within 4 . 76 f s ${4.76\ {\rm f}{\rm s}}$ and 433 a s ${433\ {\rm a}{\rm s}}$ . The corresponding C C M t ${CCM\left(t\right)}$ vary respectively from 14 . 5 ${14.5}$ or from 13 . 3 ${13.3}$ to 0 . 0 ${0.0}$ , and back.

Viscoelasticity measured by shear wave elastography in a rat model of nonalcoholic fatty liver disease: comparison with dynamic mechanical analysis.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is rapidly becoming one of the most common liver diseases. Ultrasound elastography has been used for the diagnosis of NAFLD. However, clinical research on steatosis by elastography technology has mainly focused on steatosis with fibrosis or non-alcoholic steatohepatitis (NASH), while steatosis without fibrosis has been poorly studied. Moreover, the relationship between liver viscoelasticity and steatosis grade is not clear. In this study, we evaluated the degree of liver steatosis in a simple steatosis rat model using shear wave elastography (SWE). RESULTS: The viscoelasticity values of 69 rats with hepatic steatosis were measured quantitatively by SWE in vivo and validated by a dynamic mechanical analysis (DMA) test. Pathological sections were used to determine the steatosis grade for each rat. The results showed that the elasticity values µ obtained by the two methods followed the same trend, and µ is significantly correlated with liver steatosis. The Pearson's correlation coefficients indicate that [Formula: see text] obtained by SWE is positively linear correlated with DMA (r = 0.628, p = 7.85 × 10-9). However, the viscosity values [Formula: see text] obtained by SWE were relatively independent of those obtained by DMA with a correlation coefficient of - 0.01. The combined Voigt elasticity measurements have high validity in the prediction of steatosis (S0 vs. S1-S4), with an AUROC of 0.755 (95% CI 0.6175-0.8925, p < 0.01) and the optimal cutoff value was 2.08 kPa with a sensitivity of 78% and specificity of 63%. CONCLUSION: SWE might have the feasibility to be introduced as an auxiliary technique for NAFLD patients in clinical settings. However, the viscosity results measured by SWE and DMA are significantly different, because the two methods work in different frequency bands.

Biological evaluation and SAR analysis of novel covalent inhibitors against fructose-1,6-bisphosphatase.

Fructose-1,6-bisphosphatase (FBPase) is an attractive target for affecting the GNG pathway. In our previous study, the C128 site of FBPase has been identified as a new allosteric site, where several nitrovinyl compounds can bind to inhibit FBPase activity. Herein, a series of nitrostyrene derivatives were further synthesized, and their inhibitory activities against FBPase were investigated in vitro. Most of the prepared nitrostyrene compounds exhibit potent FBPase inhibition (IC50 < 10 µM). Specifically, when the substituents of F, Cl, OCH3, CF3, OH, COOH, or 2-nitrovinyl were installed at the R2 (meta-) position of the benzene ring, the FBPase inhibitory activities of the resulting compounds increased 4.5-55 folds compared to those compounds with the same groups at the R1 (para-) position. In addition, the preferred substituents at the R3 position were Cl or Br, thus compound HS36 exhibited the most potent inhibitory activity (IC50 = 0.15 µM). The molecular docking and site-directed mutation suggest that C128 and N125 are essential for the binding of HS36 and FBPase, which is consistent with the C128-N125-S123 allosteric inhibition mechanism. The reaction enthalpy calculations show that the order of the reactions of compounds with thiol groups at the R3 position is Cl > H > CH3. CoMSIA analysis is consistent with our proposed binding mode. The effect of compounds HS12 and HS36 on glucose production in primary mouse hepatocytes were further evaluated, showing that the inhibition was 71% and 41% at 100 µM, respectively.

Modelling the impacts of climate and land use changes on soil water erosion: Model applications, limitations and future challenges.

The world is experiencing serious soil losses. Soil erosion has become an important environmental problem in certain regions and is strongly affected by climate and land use changes. By selecting and reviewing 13 extensively used soil water erosion models (SWEMs) from the published literature, we summarize the current model-based knowledge on how climate factors (e.g., rainfall, freeze-thaw cycles, rainstorms, temperature and atmospheric CO2 concentrations) and land use change impact soil erosion worldwide. This study also provides a critical review of the application of these 13 SWEMs. By comparing model structures, features, prediction accuracies, and erosion processes, we recommend the most suitable SWEMs for different regions of the globe (Asia, Europe, Africa and the America) based on the evaluations of 13 SWEMs. Future soil erosion could be simulated using the RUSLE, LISEM, WEPP v2010.1, SWAT, EPIC, KINEROS and AGNPS models in Asia; the RUSLE, WEPP v2010.1, SWAT, EPIC, WATEM-SEDEM, MEFIDIS, AGNPS and AnnAGNPS models in Europe; the RUSLE, LISEM, SWAT, and AGNPS models in Africa; and the WEPP v2010.1, SWAT, EPIC, KINEROS, AGNPS and AnnAGNPS models in America. Finally, the limitations and challenges of the 13 SWEMs are highlighted.

Noninvasive assessment of age-related stiffness of crystalline lenses in a rabbit model using ultrasound elastography.

BACKGROUND: The pathological or physiological changes of a crystalline lens directly affect the eye accommodation and transmittance, and then they increase the risk of presbyopia and cataracts for people in the middle and old age groups. There is no universally accepted quantitative method to measure the lens' mechanical properties in vivo so far. This study aims to investigate the possibility of assessing the age-related stiffness change of crystalline lens by acoustic-radiation-force-based ultrasound elastography (ARF-USE) in a rabbit model in vivo. METHODS: There were 13 New Zealand white rabbits that were divided into four groups and fed normally until they were 60 (n = 4), 90 (n = 2), 120 (n = 4), and 150 (n = 3) days old, respectively. An ARF-USE platform was built based on the Verasonics™ Vantage 256 system. The shear waves were excited and traced in the lens by a linear ultrasound probe after a rabbit was anaesthetized. RESULTS: The average group velocities were 1.38 ± 0.2 m/s, 2.06 ± 0.3 m/s, 2.07 ± 0.29 m/s, and 2.30 ± 0.28 m/s, respectively, for the four groups of rabbits. The results shows that the group velocity has a strong correlation with the day age (r = 0.84, p < 1 × 10-7) and the weight (r = 0.83, p < 1×10-7) of the rabbits while the maximum displacement has no correlations with the day age (r = 0.27, p > 0.1) and the weight (r = 0.32, p > 0.1). CONCLUSION: This study demonstrated that the group velocity measured by ARF-USE had a strong correlation with age-related stiffness in a rabbit model, suggesting that group velocity is a good biomarker to characterize the stiffness of a crystalline lens. This study also demonstrated the feasibility of using this USE technique to assess the mechanical properties of the lens in vivo for clinical or research purposes.

[Epidemiological survey and risk factor analysis of asthma in children in urban districts of Zhengzhou, China].

OBJECTIVE: To study the epidemiological features, treatment status, and risk factors for asthma in children in Zhengzhou, China. METHODS: Questionnaires for primary screening were issued using the method of multi-stage stratified sampling. Suspected asthmatic children were given a second questionnaire, physical examination, medical history review, and auxiliary examination to confirm the diagnosis. Age- and sex-matched non-asthmatic children were randomly recruited to the control group. RESULTS: The number of valid questionnaires was 10 616 (5 444 males and 5 172 females). There were 308 confirmed asthma cases and the overall prevalence was 2.90%. The prevalence in boys was higher than that in girls (3.4% vs 2.4%). The prevalence in children under 3 years of age was 10.2%, which was higher than that in other age groups. The top three triggers for asthma attack in children were respiratory infection (94.2%), weather changes (89.0%), and exercise (35.1%). The most common asthma attack was moderate (71.8%), followed by mild (22.7%). Inhaled corticosteroids, systemic corticosteroids, and antibiotics were applied to 94.8% (292 cases), 74.7% (230 cases), and 90.9% (280 cases) of all patients, respectively. Multivariate logistic regression analysis indicated the following major risk factors for asthma: history of allergic rhinitis (OR=150.285, 95% CI: 31.934-707.264), history of eczema (OR=10.600, 95% CI: 1.054-106.624), history of atopic dermatitis (OR=31.368, 95% CI: 3.339-294.683), food allergies (OR=27.373, 95% CI: 2.670-280.621), method of birth (OR=2.853, 95% CI: 1.311-6.208), age of first antibiotic use (OR=0.384, 95% CI: 0.172-0.857), frequency of antibiotic use within 1 year of age (OR=9.940, 95% CI: 6.246-15.820), use of wall decorating materials (OR=2.108, 95% CI: 1.464-3.036), and use of heat supply in winter (OR=6.046, 95% CI: 1.034-35.362). CONCLUSIONS: The prevalence of childhood asthma is associated with age and gender in Zhengzhou. Most asthma attacks are moderate, often triggered by respiratory infection. Treatment of asthma has been standardized, but still needs further improvement. History of allergic rhinitis, eczema, atopic dermatitis and food allergies, cesarean delivery, frequent use of antibiotics within 1 year of age, use of decorating materials on the wall, and use of heating in winter may increase risk for asthma, and use of antibiotics in older age is a protective factor against asthma in children.

miR­1343­3p inhibits autophagy by directly targeting ATG7 in multiple myeloma cells.

Multiple myeloma (MM) is the second most common type of hematological malignancy globally. Despite application of several new drugs, such as daratumumab, bortezomib/lenalidomide/dexamethasone, in combination with hematopoietic stem cell transplantation, overall prognosis remains poor and the pathological mechanism of MM is still unknown. The present study used TargetScan to predict autophagy-related 7 (ATG7) as a candidate target gene of microRNA (miR)-1343-3p and confirmed the interaction between miR-1343-3p and the ATG7 3' untranslated region (3'UTR) using a dual-luciferase reporter assay. In U266 and RPMI-8226 MM cell lines, miR-1343-3p mimic transfection decreased mRNA and protein levels of ATG7, while miR-1343-3p inhibition increased ATG7 expression levels using reverse transcription-qPCR and western blot analysis. miR-1343-3p mimic transfection inhibited U266 and RPMI-8226 cell survival. Finally, miR-1343-3p regulated ATG7 and autophagy in MM cells using western blot analysis. The present findings suggested that miR-1343-3p may regulate ATG7 and autophagy by directly targeting the 3'UTR of ATG7. To the best of our knowledge, there are no direct data showing the roles of miR-1343-3p in development of MM; however, miR-1343-3p may be considered a potential target for MM treatment.

Efficacy and safety of nab-paclitaxel or combined nab-paclitaxel and immune checkpoint inhibitors in relapsed small-cell lung cancer.

Background: Most patients with small-cell lung cancer (SCLC) experience disease progression after first-line chemotherapy. Notably, nab-paclitaxel monotherapy has antitumor activity in relapsed SCLC. Objective: This study evaluated the efficacy and safety of combined of nab-paclitaxel and immune checkpoint inhibitors (ICIs) in relapsed SCLC. Design: We retrospectively analyzed patients with relapsed SCLC who received nab-paclitaxel or combined nab-paclitaxel and ICIs (anti-programmed death-1, PD-1 or anti-programmed cell death 1 ligand, PD-L1) between February 2017 and September 2021. Methods: Efficacy and safety data were collected from electronic health records. Progression-free survival (PFS) and overall survival (OS) were assessed using the Kaplan-Meier method and a standard log-rank test. Results: We included 56 patients with relapsed SCLC, of which 29 received nab-paclitaxel alone (Group A), and 27 received combined nab-paclitaxel and ICIs (Group B). Baseline characteristics were similar between the two groups. Group B had a numerically higher objective response rate than Group A (40.7% versus 17.2%; p = 0.052). However, combined nab-paclitaxel and ICIs failed to demonstrate survival superiority over nab-paclitaxel monotherapy [median PFS: 3.2 months versus 2.8 months (p = 0.5225); median OS: 11.0 months versus 9.3 months (p = 0.7298)]. The safety profiles of Groups A and B were both tolerable. Conclusion: This study indicated that compared with nab-paclitaxel monotherapy, combined nab-paclitaxel and ICIs failed to improve survival in relapsed SCLC.

Few-Shot Partial Multi-View Learning.

It is often the case that data are with multiple views in real-world applications. Fully exploring the information of each view is significant for making data more representative. However, due to various limitations and failures in data collection and pre-processing, it is inevitable for real data to suffer from view missing and data scarcity. The coexistence of these two issues makes it more challenging to achieve the pattern classification task. Currently, to our best knowledge, few appropriate methods can well-handle these two issues simultaneously. Aiming to draw more attention from the community to this challenge, we propose a new task in this paper, called few-shot partial multi-view learning, which focuses on overcoming the negative impact of the view-missing issue in the low-data regime. The challenges of this task are twofold: (i) it is difficult to overcome the impact of data scarcity under the interference of missing views; (ii) the limited number of data exacerbates information scarcity, thus making it harder to address the view-missing issue in turn. To address these challenges, we propose a new unified Gaussian dense-anchoring method. The unified dense anchors are learned for the limited partial multi-view data, thereby anchoring them into a unified dense representation space where the influence of data scarcity and view missing can be alleviated. We conduct extensive experiments to evaluate our method. The results on Cub-googlenet-doc2vec, Handwritten, Caltech102, Scene15, Animal, ORL, tieredImagenet, and Birds-200-2011 datasets validate its effectiveness. The codes will be released at https://github.com/zhouyuan888888/UGDA.

MS²-GNN: Exploring GNN-Based Multimodal Fusion Network for Depression Detection.

Major depressive disorder (MDD) is one of the most common and severe mental illnesses, posing a huge burden on society and families. Recently, some multimodal methods have been proposed to learn a multimodal embedding for MDD detection and achieved promising performance. However, these methods ignore the heterogeneity/homogeneity among various modalities. Besides, earlier attempts ignore interclass separability and intraclass compactness. Inspired by the above observations, we propose a graph neural network (GNN)-based multimodal fusion strategy named modal-shared modal-specific GNN, which investigates the heterogeneity/homogeneity among various psychophysiological modalities as well as explores the potential relationship between subjects. Specifically, we develop a modal-shared and modal-specific GNN architecture to extract the inter/intramodal characteristics. Furthermore, a reconstruction network is employed to ensure fidelity within the individual modality. Moreover, we impose an attention mechanism on various embeddings to obtain a multimodal compact representation for the subsequent MDD detection task. We conduct extensive experiments on two public depression datasets and the favorable results demonstrate the effectiveness of the proposed algorithm.

Comparability of JAK2 p.V617F allele burden in peripheral blood and that in bone marrow in patients with suspected myeloproliferative neoplasms: a single-center prospective study.

PURPOSE: To detect JAK2 p.V617F and measure allele burden in peripheral blood (PB) and bone marrow (BM) aspirates in patients with suspected myeloproliferative neoplasms (MPNs). METHODS: Patients with suspected MPNs were prospectively enrolled between August 2017 and May 2019, and their PB and BM were collected during the same period. Quantitative fluorescence polymerase chain reaction (PCR) was used to detect the copy number of JAK2 wild type and the V617F mutant; the JAK2 V617F proportion was also calculated. The JAK2 p.V617F proportion in PB was compared to that in BM by Chi-square test. RESULTS: Among 54 patients with suspected MPNs, 43 of them were eligible for analysis. The JAK2 p.V617F in PB had the same sensitivity and specificity as BM (all P>0.05). The Chi-square test suggested that the JAK2 p.V617F allele burden of PB was comparable to that of BM (Spearman Correlation =0.986; P=0.000). CONCLUSION: PB could be used as an alternative to BM for JAK2 p.V617F measurement in patients with suspected MPNs.

A systematic review and meta-analysis on the risk factors of acute myeloid leukemia.

Background: Acute myeloid leukemia (AML) is one of the main types of leukemia that threatens the life and health of patients. A large number of clinical studies have been conducted on the etiology of the disease. However, there are few evidence-based medical studies and no definitive treatment guidelines. Methods: Related articles were searched from Medline, Excerpta Medica Database (EMBASE), EBSCO, OVID, Chinese Biology Medicine Disc (CBMDISC), and Wanfang databases. The search time limit was from the establishment of the database to September 2021. The search terms were as follows: acute myeloid leukemia, AML, electromagnetic field, case-control study, cohort study, and risk factors. All literatures were included according to PICOS standards, and the risk of deviation and literature quality were assessed. RevMan 5.3 software was used for meta-analysis. Results: The 10 articles included were of high quality and low bias risk. The research results showed that compared with healthy people, among the risk factors for AML, family tumor history [risk ratio (RR) =0.98; 95% confidence interval (CI): (0.57, 1.69); Z=0.08; P=0.94] and the hepatitis B virus (HBV) infection rate [odds ratio (OR) =1.34; 95% CI: (0.57, 3.13); Z=0.68; P=0.50] showed no significant differences, but the hepatitis C virus (HCV) infection rate [OR =1.60; 95% CI: (1.17, 2.19); Z=2.92; P=0.003] and environmental exposure rate [OR =1.49; 95% CI: (1.01, 2.21); Z=2.02; P=0.04] increased significantly. Conclusions: A total of 10 articles were included to analyze AML risk factors and related content. The results suggested that HCV infection and environmental exposure history such as home decoration were risk factors for AML.

Hierarchical Prototype Refinement With Progressive Inter-Categorical Discrimination Maximization for Few-Shot Learning.

Metric-based few-shot learning categorizes unseen query instances by measuring their distance to the categories appearing in the given support set. To facilitate distance measurement, prototypes are used to approximate the representations of categories. However, we find prototypical representations are generally not discriminative enough to represent the discrepancy of inter-categorical distribution of queries, thereby limiting the classification accuracy. To overcome this issue, we propose a new Progressive Hierarchical-Refinement (PHR) method, which effectively refines the discrimination of prototypes by conducting the Progressive Discrimination Maximization strategy based on the hierarchical feature representations. Specifically, we first encode supports and queries into the representation space of spatial level, global level, and semantic level. Then, the refining coefficients are constructed by exploring the metric information contained in these hierarchical embedding spaces simultaneously. Under the guidance of the refining coefficients, the meta-refining loss progressively maximizes the discrimination degree of inter-categorical prototypical representations. In addition, the refining vectors are adopted to further enhance the representations of prototypes. In this way, the metric-based classification can be more accurate. Our PHR method shows the competitive performance on the miniImagenet, CIFAR-FS, FC100, and CUB datasets. Moreover, PHR presents good compatibility. It can be incorporated with other few-shot learning models, making them more accurate.

Real-Time Semantic Segmentation via Spatial-Detail Guided Context Propagation.

Nowadays, vision-based computing tasks play an important role in various real-world applications. However, many vision computing tasks, e.g., semantic segmentation, are usually computationally expensive, posing a challenge to the computing systems that are resource-constrained but require fast response speed. Therefore, it is valuable to develop accurate and real-time vision processing models that only require limited computational resources. To this end, we propose the spatial-detail guided context propagation network (SGCPNet) for achieving real-time semantic segmentation. In SGCPNet, we propose the strategy of spatial-detail guided context propagation. It uses the spatial details of shallow layers to guide the propagation of the low-resolution global contexts, in which the lost spatial information can be effectively reconstructed. In this way, the need for maintaining high-resolution features along the network is freed, therefore largely improving the model efficiency. On the other hand, due to the effective reconstruction of spatial details, the segmentation accuracy can be still preserved. In the experiments, we validate the effectiveness and efficiency of the proposed SGCPNet model. On the Cityscapes dataset, for example, our SGCPNet achieves 69.5% mIoU segmentation accuracy, while its speed reaches 178.5 FPS on 768 x 1536 images on a GeForce GTX 1080 Ti GPU card. In addition, SGCPNet is very lightweight and only contains 0.61 M parameters. The code will be released at https://github.com/zhouyuan888888/SGCPNet.

Clinical value of alveolar lavage supernatant specimens in the detection of the EGFR gene mutation in patients with non-small cell lung carcinoma.

Background: This study sought to compare the consistency of the epidermal growth factor receptor (EGFR) gene mutation detection results in the supernatant of alveolar lavage specimens to the tissue sample results, and the consistency of the blood EGFR gene mutation detection results to the tissue detection results. Methods: In total, 29 patients with non-small cell lung carcinoma (NSCLC) were selected, and their bronchoalveolar lavage fluid (BALF) was collected. The supernatant and precipitate were separated by centrifugation. Deoxyribonucleic acid (DNA) was extracted from the supernatant, and blood and tumor tissues were collected to detect patients' EGFR gene mutation status. Results: Of the 29 enrolled patients, 12 of the 23 tissue-biopsy patients (52.2%) were positive for EGFR mutations, 11 of the 28 blood-test patients (39.2%) were positive for EGFR mutations, and 13 of the 29 cases of the BALF-test patients (44.8%) were positive for EGFR mutations. The most common mutations were the exon 19 deletion mutation and the L858R point mutation. The EGFR gene mutation rate was higher in female, young, non-smoker, and stage IIIB patients (than stage IV patients), but the differences were not statistically significant (all P>0.05). Of the 29 NSCLC patients tested for the EGFR gene mutation, the BALF supernatant and blood results were the same for 27 patients (coincidence rate: 93.10%). Of the 23 of the 29 enrolled patients tested for the EGFR gene mutation, the BALF supernatant and tissue test results were the same for 21 patients (coincidence rate: 91.30%). Further, the blood-test and the tissue test results were the same for 20 patients (coincidence rate: 86.96%). Conclusions: The EGFR gene mutation rate was high in NSCLC patients. The coincidence rate of the EGFR gene mutation detection results between BALF supernatant and tumor tissues was slightly higher than that of the blood and tumor tissue EGFR gene mutation detection results.

FGF2 is overexpressed in asthma and promotes airway inflammation through the FGFR/MAPK/NF-κB pathway in airway epithelial cells.

BACKGROUND: Airway inflammation is the core pathological process of asthma, with the key inflammatory regulators incompletely defined. Recently, fibroblast growth factor 2 (FGF2) has been reported to be an inflammatory regulator; however, its role in asthma remains elusive. This study aimed to investigate the immunomodulatory role of FGF2 in asthma. METHODS: First, FGF2 expression was characterised in clinical asthma samples and the house dust mite (HDM)-induced mouse chronic asthma model. Second, recombinant mouse FGF2 (rm-FGF2) protein was intranasally delivered to determine the effect of FGF2 on airway inflammatory cell infiltration. Third, human airway epithelium-derived A549 cells were stimulated with either HDM or recombinant human interleukin-1ß (IL-1ß) protein combined with or without recombinant human FGF2. IL-1ß-induced IL-6 or IL-8 release levels were determined using enzyme-linked immunosorbent assay, and the involved signalling transduction was explored via Western blotting. RESULTS: Compared with the control groups, the FGF2 protein levels were significantly upregulated in the bronchial epithelium and alveolar areas of clinical asthma samples (6.70 ± 1.79 vs. 16.32 ± 2.40, P = 0.0184; 11.20 ± 2.11 vs. 21.00 ± 3.00, P = 0.033, respectively) and HDM-induced asthmatic mouse lung lysates (1.00 ± 0.15 vs. 5.14 ± 0.42, P < 0.001). Moreover, FGF2 protein abundance was positively correlated with serum total and anti-HDM IgE levels in the HDM-induced chronic asthma model (R2 = 0.857 and 0.783, P = 0.0008 and 0.0043, respectively). Elevated FGF2 protein was mainly expressed in asthmatic bronchial epithelium and alveolar areas and partly co-localised with infiltrated inflammatory cell populations in HDM-induced asthmatic mice. More importantly, intranasal instillation of rm-FGF2 aggravated airway inflammatory cell infiltration (2.45 ± 0.09 vs. 2.88 ± 0.14, P = 0.0288) and recruited more subepithelial neutrophils after HDM challenge [(110.20 ± 29.43) cells/mm2 vs. (238.10 ± 42.77) cells/mm2, P = 0.0392] without affecting serum IgE levels and Th2 cytokine transcription. In A549 cells, FGF2 was upregulated through HDM stimulation and promoted IL-1ß-induced IL-6 or IL-8 release levels (up to 1.41 ± 0.12- or 1.44 ± 0.14-fold change vs. IL-1ß alone groups, P = 0.001 or 0.0344, respectively). The pro-inflammatory effect of FGF2 is likely mediated through the fibroblast growth factor receptor (FGFR)/mitogen-activated protein kinase (MAPK)/nuclear factor kappa B (NF-κB) pathway. CONCLUSION: Our findings suggest that FGF2 is a potential inflammatory modulator in asthma, which can be induced by HDM and acts through the FGFR/MAPK/NF-κB pathway in the airway epithelial cells.

The impact of pharmacist oriented mode on risk control in a Chinese centralized intravenous admixture service centre.

Centralized intravenous admixture service (CIVAS) centres, which are pharmaceutical departments found in Chinese hospitals, provide high-quality intravenous fluids and pharmaceutical services for patients, and errors in their working procedures can lead to adverse consequences. Pharmacists, the primary CIVAS centre personnel, play a role in risk control; however, to date, the effect of pharmacists' participation in risk management has not been reported. The main aim of this study was to evaluate the pharmacist's role in risk control and evaluate its impact. A retrospective observational study was designed to assess the principal working process in the CIVAS centre of a provincial healthcare setting. Errors in the main working process were identified, and intervention measures were formulated. The pharmacist intervention effect was evaluated by assessing the identification rate of improper prescriptions; the incidence rate of drug preparation, compounding, packaging and delivery process errors; and expenditures on wasteful drugs. There was a higher identification rate for improper prescriptions after the intervention (P < 0.05), while the incidence of drug preparation (P < 0.05), admixture (P < 0.05), and packaging and delivery errors (P < 0.01) was significantly lower; the total wasteful medication expenditure was also dramatically reduced. The potential creativity of pharmacists in error control can provide dependable intravenous drugs for patients and reduce the running expenditures for CIVAS.

Identifying Genomic Alterations in Small Cell Lung Cancer Using the Liquid Biopsy of Bronchial Washing Fluid.

Objective: With the rapid development of cancer genomics and immunomics, some new treatments of small cell lung cancer (SCLC) are emerging. However, there are limitations to the clinical use of tumor tissue. Our study aimed to evaluate the potential use of bronchial washing fluid (BWF) in the liquid biopsy of SCLC. Methods: Twenty-one extensive SCLC (ES-SCLC) patients were enrolled in this study. For all patients, four sample types, BWF supernatant (BWFs), BWF precipitate (BWFp), plasma and tumor tissue, were collected before receiving chemotherapy, and one type, plasma, was collected after chemotherapy. All samples were conducted to NGS using the 1021-gene panel. The concordance rates of genomic profiling using NGS in the four types of samples were evaluated. Multiple clinical information was analyzed for correlation. Results: We successfully tested 20 BWFs samples, 21 BWFp samples, 21 tumor tissue samples, 20 pre-treatment plasma, and 13 post-treatment plasma of these 21 patients. The detectability of somatic mutations was 100% for BWFs, BWFp, tumor tissues, and post-treatment plasma, and only one pre-treatment plasma was absent with any mutation. Matched tumor tissue, BWFs, BWFp, and pre-treatment plasma samples were subsistent for 19 patients. For these patients, 204 genomic alterations were identified in tissue samples, while 189 (92.6%), 175 (85.5%), and 163 (79.9%) alterations were detected in the matched BWFs, BWFp, and pre-treatment plasma, respectively. Moreover, we found that the three tumor markers associated with SCLC have a lower sensitivity than genomic alterations. The endocrine resistance pathway was found enriched in hyponatremia patients which may be related to the hyponatremia. The TMBs of BWF, BWFp, and pre-treatment plasma samples all had a strong correlation with that of tissue samples. Both the VAF and the MVAF of mutations in post-treatment plasma were less than those in pre-treatment plasma, which was in accordance with the evaluation of curative effect. Conclusions: For ES-SCLC patients, the liquid biopsy of BWF showed a highly potential advantage to identify DNA alterations, which suggested that genomic analysis of BWF liquid biopsy may have clinical value as a supplement for tissue and blood detection. Through the restricted validation, it can be widely used in routine clinical practice.

miR­140­5p inhibits cervical cancer cell phenotypes via downregulating FEN1 to halt the cell cycle.

Cervical cancer (CC) is a frequently occurring cancer in women with a high mortality rate. Despite improvements to therapeutic strategies, the survival outcome for patients with CC remains poor. Therefore, the present study aimed to investigate the molecular mechanism underlying CC inhibition involving microRNA (miR)­140­5p and flap structure­specific endonuclease 1 (FEN1). Bioinformatics analysis was conducted, which identified that FEN1 was associated with CC cell cycle progression. Subsequently, 3'untranslated region reporter assays were performed to assess the regulatory relationship between FEN1 mRNA and miR­140­5p. Functional assays, including EdU staining assay, flow cytometry, and wound healing assays, were conducted to observe CC cell phenotypes induced by alterations to miR­140­5p and FEN1 expression levels. FEN1 expression was high and miR­140­5p expression was low in CC tissues and cell lines compared with adjacent healthy tissues and a normal cervical epithelial cell line, respectively. miR­140­5p knockdown reversed small interfering RNA­FEN1­mediated suppressive effects on CC cell phenotypes, potentially via inducing cell cycle arrest at the G1 phase. Therefore, the present study suggested that miR­140­5p may serve as an antitumorigenesis factor in CC by targeting FEN1 mRNA.

Multi-Atlas Segmentation of Anatomical Brain Structures Using Hierarchical Hypergraph Learning.

Accurate segmentation of anatomical brain structures is crucial for many neuroimaging applications, e.g., early brain development studies and the study of imaging biomarkers of neurodegenerative diseases. Although multi-atlas segmentation (MAS) has achieved many successes in the medical imaging area, this approach encounters limitations in segmenting anatomical structures associated with poor image contrast. To address this issue, we propose a new MAS method that uses a hypergraph learning framework to model the complex subject-within and subject-to-atlas image voxel relationships and propagate the label on the atlas image to the target subject image. To alleviate the low-image contrast issue, we propose two strategies equipped with our hypergraph learning framework. First, we use a hierarchical strategy that exploits high-level context features for hypergraph construction. Because the context features are computed on the tentatively estimated probability maps, we can ultimately turn the hypergraph learning into a hierarchical model. Second, instead of only propagating the labels from the atlas images to the target subject image, we use a dynamic label propagation strategy that can gradually use increasing reliably identified labels from the subject image to aid in predicting the labels on the difficult-to-label subject image voxels. Compared with the state-of-the-art label fusion methods, our results show that the hierarchical hypergraph learning framework can substantially improve the robustness and accuracy in the segmentation of anatomical brain structures with low image contrast from magnetic resonance (MR) images.