Search

Since the impoundment of Three Gorges Reservoir (TGR) in 2003, numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall. One case is the Outang landslide, a large-scale and active landslide, on the south bank of the Yangtze River. The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics. Data mining technology, including the two-step clustering and Apriori algorithm, is then used to identify the dominant triggers of landslide movement. In the data mining process, the two-step clustering method clusters the candidate triggers and displacement rate into several groups, and the Apriori algorithm generates correlation criteria for the cause-and-effect. The analysis considers multiple locations of the landslide and incorporates two types of time scales: long-term deformation on a monthly basis and short-term deformation on a daily basis. This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors. The data mining results reveal different dominant triggering factors depending on the monitoring frequency: the monthly and bi-monthly cumulative rainfall control the monthly deformation, and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide. It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslide-prone areas.

BackgroundIn recent years, the position of PCSK9 inhibitors as adjuvant therapy to statins in guidelines has further improved. However, there remained a dearth of direct comparative studies among different PCSK9 inhibitors. Therefore, this study aimed to conduct a network meta-analysis to evaluate the efficacy and safety of different PCSK9 inhibitors combined with statins.MethodsA comprehensive literature search was conducted from the study's inception to 12 November 2023, encompassing multiple online databases including PubMed, Embase, Cochrane Central, Web of Science, and ClinicalTrials.gov to obtain relevant randomized controlled trials. Frequentist network meta-analysis was employed to compare the efficacy and safety of different PCSK9 inhibitors. The efficacy endpoints were low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (ApoB), and lipoprotein (a) (Lp(a)). The safety endpoints were any adverse events (AE), severe adverse events (SAE), AE leading to treatment discontinuation, and injection-site reaction.ResultsCompared with placebo and ezetimibe, all PCSK9 inhibitors demonstrated significant reductions in LDL-C levels. Notably, evolocumab exhibited the most pronounced effect with a treatment difference of −63.67% (−68.47% to −58.87%) compared with placebo. Regarding dosage selection for evolocumab, the regimen of 140 mg Q2W (−69.13%, −74.55% to −63.72%) was superior to 420 mg QM (−61.51%, −65.97% to −57.05%). Based on rankings and P-scores analysis, tafolecimab 150 mg Q2W demonstrated superior efficacy in reducing ApoB levels (−61.70%, −84.38% to −39.02%) and Lp(a) levels (−43%, 30%, −68%, 81% to −17%, 79%). Furthermore, the safety profile of PCSK9 inhibitors was favorable with no increase in the incidence of AE, SAE, or AE leading to treatment discontinuation; however, alirocumab, inclisiran, and tafolecimab may potentially entail a potential risk associated with injection-site reactions.ConclusionCompared with placebo and ezetimibe, PCSK9 inhibitors can significantly reduce LDL-C, ApoB, and Lp(a) when combined with statins to treat hypercholesterolemia. Furthermore, PCSK9 inhibitors and ezetimibe exhibit similar safety profiles.Systematic Review Registration[PROSPERO], identifier [CRD42023490506].

Soil moisture (SM) plays an essential role in the hydrological cycle, drought monitoring, and water resources management. However, passive microwave remote sensing products offer coarse spatial resolutions (approximately 25–40 km), greatly limiting their applications. In this study, we considered vegetation memory and increased the amount of vegetation data by spatiotemporal fusion, integrated lagged vegetation index and fusion data as model inputs, and downscaled the spatial resolution of SMAP SM using the Random Forest (RF) model as well as multi-source remote sensing data. The downscaled SM was validated with 30 in situ SM measurements and daily precipitation data and explored the contributions of NDVIlagged and NDVIfused in downscaling. The results show that the downscaled SM is highly consistent with the in situ SM measurements. The correlation ranges from 0.628 to 0.849 with an average of 0.689. The root mean square error (RMSE) ranges from 0.024 to 0.094 m3/m3 with an average of 0.057 m3/m3. The proposed method leverages the strengths of the RF model, fusion vegetation data, and lagged vegetation data to improve high-resolution SM accuracy.

BackgroundTislelizumab is the first PD-1 inhibitor in China to demonstrate superior efficacy in second-line or third-line treatment of patients with advanced or metastatic non-small-cell lung cancer (NSCLC). This study aimed to evaluate the cost-effectiveness of tislelizumab compared to docetaxel from a Chinese healthcare system perspective.MethodsA dynamic Markov model was developed to evaluate the cost-effectiveness of tislelizumab in comparison to docetaxel in second or third-line treatment. The efficacy data utilized in the model were derived from the RATIONALE-303 clinical trial, while cost and utility values were obtained from the drug data service platform and published studies. The primary outcomes of the model encompassed quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to validate the robustness of the base case analysis results.ResultsThe tislelizumab group demonstrated a cost increase of CNY 117,473 and a gain of 0.58 QALYs compared to the docetaxel group, resulting in an ICER value of CNY 202,927 per QALY gained.ConclusionThe administration of tislelizumab in patients with advanced or metastatic NSCLC not only extends the progression-free survival (PFS) and overall survival (OS). Moreover, this treatment demonstrates a favorable cost-effectiveness profile across the Chinese population.

The H9N2 subtype avian influenza viruses mainly cause respiratory symptoms, reduce the egg production and fertility of poultry, and result in secondary infections, posing a great threat to the poultry industry and human health. Currently, all H9N2 avian influenza commercial vaccines are inactivated vaccines, which provide protection for immunized animals but cannot inhibit the spread of the virus and make it difficult to distinguish between the infected animals and vaccinated animals. In this study, a trimeric consensus H9 hemagglutinin (HA) subunit vaccine for the H9N2 subtype avian influenza virus based on a baculovirus expression system was first generated, and then the effects of three molecular adjuvants on the H9 HA subunit vaccine, Cholera toxin subunit B (CTB), flagellin, and granulocyte-macrophage colony-stimulating factor (GM-CSF) fused with H9 HA, and one synthetic compound, a polyinosinic–polycytidylic acid (PolyI:C) adjuvant, were evaluated in mice by intranasal administration. The results showed that these four adjuvants enhanced the immunogenicity of the H9 HA subunit vaccine for avian influenza viruses, and that GM-CSF and PolyI:C present better mucosal adjuvant activity for the H9 HA subunit vaccine. These results demonstrate that we have developed a potential universal H9 HA mucosal subunit vaccine with adjuvants in a baculovirus system that would be helpful for the prevention and control of H9N2 subtype avian influenza viruses.

Currently, there is an absence of an exhaustive elucidation regarding the long-term spatiotemporal characteristics of meteorological droughts in China. Previous studies have predominantly fixated on the lower-dimensional (temporal or spatial) facets of drought events, overlooking critical spatiotemporal details. This paper proposes an integrated processing framework that employs a three-dimensional clustering algorithm to discern drought events and quantifies the spatiotemporal patterns and dynamic attributes of China’s meteorological droughts during 1950–2021 from a three-dimensional perspective encompassing longitude, latitude, and time, capturing comprehensive spatiotemporal information. Additionally, the cross wavelet transform is harnessed to elucidate the impact of teleconnection factors on meteorological drought. The findings underscore that prolonged and extensive meteorological drought events, characterized by heightened severity, primarily manifest during the 1950 s, 1960 s, and 2010 s in temporal, predominantly within the central and western China spatially. From 1950 onwards, the severity, duration, and affected area of meteorological droughts in China exhibit a discernible pattern of initial decline followed by escalation. Into the 2010 s, meteorological droughts became more severe and active. China's meteorological drought displays two relatively prevailing spatial migration patterns: an overarching eastward and westward migration. In the former, the most frequent migration occurs to the east and northeast during its monthly evolution, while the latter involves migration primarily towards the west, southwest, and northwest. The impact of teleconnection factors on meteorological drought shows a spatiotemporal heterogeneity, with ENSO exhibiting a relatively substantial and intricate influencer. This research unearths the latest long-term spatiotemporal dynamics of meteorological drought in China, which contributes to an improved comprehension of drought patterns and behaviors.

The skin is the outer layer of the human body, and it is crucial in defending against injuries and damage. The regenerative capacity of aging and damaged skin caused by exposure to external stimuli is significantly impaired. Currently, the rise in average life expectancy and the modern population’s aesthetic standards have sparked a desire for stem-cell-based therapies that can address skin health conditions. In recent years, mesenchymal stem cells (MSCs) as therapeutic agents have provided a promising and effective alternative for managing skin regeneration and rejuvenation, attributing to their healing capacities that can be applied to damaged and aged skin. However, it has been established that the therapeutic effects of MSC may be primarily mediated by paracrine mechanisms, particularly the release of exosomes (Exos). Exosomes are nanoscale extracellular vesicles (EVs) that have lipid bilayer and membrane structures and can be naturally released by different types of cells. They influence the physiological and pathological processes of recipient cells by transferring a variety of bioactive molecules, including lipids, proteins, and nucleic acids such as messenger RNAs (mRNAs) and microRNAs (miRNAs) between cells, thus playing an important role in intercellular communication and activating signaling pathways in target cells. Among them, miRNAs, a type of endogenous regulatory non-coding RNA, are often incorporated into exosomes as important signaling molecules regulating protein biosynthesis. Emerging evidence suggests that exosomal miRNAs from MSC play a key role in skin regeneration and rejuvenation by targeting multiple genes and regulating various biological processes, such as participating in inflammatory responses, cell migration, proliferation, and apoptosis. In this review, we summarize the recent studies and observations on how MSC-derived exosomal miRNAs contribute to the regeneration and rejuvenation of skin tissue, with particular attention to the applications of bioengineering methods for manipulating the miRNA content of exosome cargo to improve their therapeutic potential. This review can provide new clues for the diagnosis and treatment of skin damage and aging, as well as assist investigators in exploring innovative therapeutic strategies for treating a multitude of skin problems with the aim of delaying skin aging, promoting skin regeneration, and maintaining healthy skin.

Introduction: Tocilizumab and baricitinib are recommended treatment options for COVID-19 patients with hyperinflammatory response; however, there is a lack of systematic review directly evaluating their efficacy and safety.Objective: This review was conducted to evaluate the efficacy and safety of tocilizumab and baricitinib in the treatment of hospitalized patients with COVID-19.Methods: Relevant databases were searched for studies that compared the effect or safety of baricitinib or tocilizumab in hospitalized patients with COVID-19. The mortality was the main outcome. The hospital length of stay or adverse drug reactions were taken into consideration as secondary endpoints. The analyses were performed in Revman 5.3 or Stata 16.0. The protocol and analysis plan were pre-registered in PROSPERO, with the registration number CRD42023408219.Results: In total, 10 studies with 2,517 patients were included. The overall pooled data demonstrated that, there was no statistically significant difference in the 28-day mortality rate and the hospital length of stay between the tocilizumab and baricitinib (OR = 1.10, 95% CI = 0.80–1.51, p = 0.57; OR = −0.68, 95% CI = −2.24–0.87, p = 0.39). The adverse reactions including secondary infection rate, thrombotic and bleeding events, and acute liver injury of tocilizumab were significantly higher than that of baricitinib. (OR = 1.49, 95% CI = 1.18–1.88, p < 0.001,OR = 1.52, 95% CI = 1.11–2.08, p = 0.009; OR = 1.52, 95% CI = 1.11–2.08, p = 0.009; OR = 2.24, 95% CI = 1.49–3.35, p < 0.001).Conclusion: In patients hospitalized with COVID-19, no discernible difference in therapeutic efficacy was observed between tocilizumab and baricitinib; however, the group treated with baricitinib demonstrated a significantly lower incidence of adverse effects.

BackgroundMycoplasma pneumoniae pneumonia (MPP) is common among children, but the impact of atopy on MPP severity in children is unknown. This study investigated whether atopic vs. nonatopic children had greater MPP severity.MethodsRetrospective analysis was conducted on 539 (ages 3–14 years) patients who were hospitalized in the First Affiliated Hospital of Anhui Medical University for MPP between January 2018 and December 2021, 195 were atopic and 344 were nonatopic. Of them, 204 had refractory MPP, and 335 had general MPP. And of atopic children, 94 had refractory MPP, and 101 had general MPP. Data on demographic and clinical characteristics, laboratory findings, clinical treatments were analyzed.ResultsSignificantly more boys with MPP were atopic than nonatopic (P

In the research of automatic interpretation of remote sensing images, semantic segmentation based on deep convolutional neural networks has been rapidly developed and applied, and the feature segmentation accuracy and network model generalization ability have been gradually improved. However, most of the network designs are mainly oriented to the three visible RGB bands of remote sensing images, aiming to be able to directly borrow the mature natural image semantic segmentation networks and pre-trained models, but simultaneously causing the waste and loss of spectral information in the invisible light bands such as near-infrared (NIR) of remote sensing images. Combining the advantages of multispectral data in distinguishing typical features such as water and vegetation, we propose a novel deep neural network structure called the multispectral semantic segmentation network (MSNet) for semantic segmentation of multi-classified feature scenes. The multispectral remote sensing image bands are split into two groups, visible and invisible, and ResNet-50 is used for feature extraction in both coding stages, and cascaded upsampling is used to recover feature map resolution in the decoding stage, and the multi-scale image features and spectral features from the upsampling process are fused layer by layer using the feature pyramid structure to finally obtain semantic segmentation results. The training and validation results on two publicly available datasets show that MSNet has competitive performance. The code is available: https://github.com/taochx/MSNet.

External causes like changes in reservoir level and intense rainfall can cause reservoir landslides. Exploring the factors that govern landslide deformation and analyzing its stability evolution is essential in mitigating the associated risks. The Sanzhouxi landslide, which has experienced ongoing movements and has been implemented a professional monitoring system, is chosen for analysis in this paper. A combination of geological survey and analysis of monitoring data is utilized to explore landslide deformation characteristics. A data mining method, grey relation analysis (GRA), is subsequently performed to determine the causes of landslide deformation. Furthermore, the stability of the Sanzhouxi landslide in response to reservoir level fluctuation and rainfall for each day over an entire year is assessed using the Morgenstern-Price (MP) approach in 2D GeoStudio software. Such a process illustrates clearly how the landslide stability alters with external triggers changing. The findings reveal that the landslide deforms variably in spatial and temporal. The reservoir level rising contributes to landslide deformation primarily, while rainfall has a secondary impact. The factor of safety (FS) of the Sanzhouxi landslide drops from 1.17 to 1.07 during high reservoir water level periods and remain the same or increase in other periods except for some transitory moments while decreasing only by about 2% under the effect of rainfall. The daily FS results validate the dominant influence of reservoir level fluctuation on the stability of the landslide. The comprehensive understanding of landslide movement based on deformation characteristics, triggering factor identification, and daily stability validation, contributes to realizing nearly real-time prediction and evaluating the risk due to slope movements in similar geological settings worldwide.

Summary objectiveTo assess the clinical features and outcomes of hematological disease patients with Candida tropicalis bloodstream infections and determine the antifungal susceptibility of C. tropicalis.MethodsThis is a retrospective, single-center, observational study conducted in the Department of Hematology at The First Affiliated Hospital of Guangxi Medical University from January 2013 to December 2021. A total of 26 hematological disease patients with C. tropicalis bloodstream infections were enrolled, and their clinical features, treatment plans, and prognoses were assessed. Univariate analysis was performed by Kaplan–Meier analysis and multivariate analysis was conducted using a Cox regression model. The antifungal susceptibility of C. tropicalis was determined from patient blood cultures.ResultsThe patients had a mean age of 35 years (range: 10–65 years), 50% were male (13/26) and 88.5% had hematologic malignancies (23/26) while the remaining three patients included two cases of severe aplastic anemia and one case of β-thalassemia. All patients had neutropenia. Seven patients were initially given azole alone (26.9%), five of whom failed treatment and died (71.4%). Fifteen patients were treated with echinocandin (57.7%), three of whom failed treatment and died (20.0%), and eight patients were treated with amphotericin B (30.8%), two of whom failed treatment and died (25.0%). The total and attributable mortality rates were 42.3 and 34.6%, respectively. Univariate analysis showed that there are six risk factors for attributable deaths among hematological disease patients with C. tropicalis blood infections. These risk factors included septic shock, Pitt bacteremia scores ≥4, procalcitonin levels ≥10 ng/mL, positive plasma (1,3)- β-D glucan assay, serum albumin levels

A cantilever block wall-panel attachment strip (CBW) flexible connection node was designed to connect precast concrete (PC) exterior wall panels to steel frames. To investigate the performance of the CBW flexible connection node and PC exterior wall panels during earthquakes, a partial two-storey steel frame was extracted from an actual engineering structure, and a full-scale steel frame–exterior wall panel shaking-table model was designed. Two sets of shaking-table tests were conducted under seismic intensity 7, 8, and 9 (Chinese Seismic Intensity Scale) earthquakes. The acceleration and displacement responses of the composite wall panel, open window panel, and integral wall panel along the in-plane and out-of-plane motions were analysed. The acceleration amplification factors of the PC exterior wall panels ranged from 0.753 to 1.400 (in-plane) and from 0.998 to 2.199 (out-of-plane). The CBW flexible connection node had a deformation capacity that could coordinate the deformation of the exterior wall panel and prevent severe damage. The surfaces of the PC exterior wall panels remained intact during a very strong seismic intensity 9 earthquake.

Landslide displacement prediction has garnered significant recognition as a pivotal component in realizing successful early warnings and implementing effective control measures. This task remains challenging as landslide deformation involves not only temporal dependency within time series data but also spatial dependence across various regions within landslides. The present study proposes a landslide spatiotemporal displacement forecasting model by introducing attention-based deep learning algorithms based on spatiotemporal analysis. The Maximal Information Coefficient (MIC) approach is employed to quantify the spatial and temporal correlations within the daily data of Global Navigation Satellite System (GNSS) observations. Based on the quantitative spatiotemporal analysis, the proposed prediction model combines a convolutional neural network (CNN) and long short-term memory (LSTM) network to capture spatial and temporal dependencies individually. Spatial–temporal attention mechanisms are implemented to optimize the model. Additionally, we develop a single-point prediction model using LSTM and a multiple-point prediction model using the CNN-LSTM without an attention mechanism to compare the forecasting capabilities of the attention-based CNN-LSTM model. The Outang landslide in the Three Gorges Reservoir Area (TGRA), characterized by a large and active landslide equipped with an advanced monitoring system, is taken as a studied case. The temporal MIC results shed light on the response times of monitored daily displacement to external factors, showing a lagging duration of between 10 and 50 days. The spatial MIC results indicate mutual influence among different locations within the landslide, particularly in the case of nearby sites experiencing significant deformation. The attention-based CNN-LSTM model demonstrates an impressive predictive performance across six monitoring stations within the Outang landslide area. Notably, it achieves a remarkable maximum coefficient of determination (R2) value of 0.9989, accompanied by minimum values for root mean squared error (RMSE), absolute mean error (MAE), and mean absolute percentage error (MAPE), specifically, 1.18 mm, 0.99 mm, and 0.33%, respectively. The proposed model excels in predicting displacements at all six monitoring points, whereas other models demonstrate strong performance at specific individual stations but lack consistent performance across all stations. This study, involving quantitative deformation characteristics analysis and spatiotemporal displacement prediction, holds promising potential for a more profound understanding of landslide evolution and a significant contribution to reducing landslide risk.

BackgroundSeveral randomized controlled trials (RCTs) have confirmed the favorable clinical benefit of pembrolizumab in advanced non-small cell lung cancer (NSCLC). However, considering the strict inclusion and exclusion criteria in clinical research, there are certain differences between patients in the real-world, it is unclear whether the findings of clinical trials are fully representative of the treatment efficacy in patients who will eventually use it. Therefore, to further comprehensively assess the efficacy and safety of pembrolizumab in NSCLC, we conducted a systematic review and meta-analysis based on the latest RCTs and real-world studies (RWSs).MethodsWe systematically searched PubMed, Embase, The Cochrane Library, The Web of Science, and clinical trials.gov as of December 2021. RCTs and RWSs of patients receiving pembrolizumab monotherapy or in combination with chemotherapy for advanced NSCLC were included.ResultsThe meta-analysis ultimately included 11 RCTs and 26 RWSs with a total of 10,695 patients. The primary outcomes of this study were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), serious adverse events (SAEs), the incidence of severe pneumonia reactions, and drug-related mortality. Direct meta-analysis results showed that in RCTs, pembrolizumab in combination with chemotherapy was superior to chemotherapy in terms of OS (HR=0.60, 95%CI:0.50-0.73), PFS (HR=0.47, 95%CI:0.38-0.58) and ORR (OR=3.22, 95%CI:2.57-4.03); pembrolizumab monotherapy was superior to chemotherapy in terms of OS (HR=0.73, 95%CI:0.66-0.80) and ORR (OR=1.90, 95%CI:1.17-3.09), but comparable to chemotherapy in terms of PFS (HR=0.83, 95%CI:0.66-1.04). The ORR values in retrospective single-arm studies were 45% (40%-51%).ConclusionIn RCTs, pembrolizumab monotherapy or in combination with chemotherapy is more effective and safer than chemotherapy for advanced NSCLC. In RWSs, ECOG PS 0-1 was shown to correlate with PFS and OS for patients with NSCLC.

Study region: Ten major river basins in China. Study focus: The spatial and temporal distribution of terrestrial water storage (TWS) in China is significantly affected by global climate change and increased human activity. In this study, we analyzed the spatial and temporal variability of TWS in ten Chinese basins based on data of the Gravity Recovery and Climate Experiment (GRACE). To discuss the driving force of TWS, we assessed the relative contributions and time lags of precipitation (P), evapotranspiration (ET), and runoff (R) to TWS using Spearman correlation analysis and partial least squares regression (PLS). New hydrological insights for the region: Results indicate that: (1) TWS generally shows a reduction trend at a rate of 1.58 ± 0.067 mm/a from 2003 to 2020, with the most significant decreasing trend in September (−2.77 ± 0.070 mm/a). (2) The relative contributions of P, ET, and R to the TWS in China are 29.89 ± 6.98%, 31.03 ± 6.92% and 39.09 ± 10.82%, respectively, and are more prominent in low-latitude regions than in high-latitude regions. (3) The best-correlated lag times were 1–2 months between the P and TWS responses. (4) Melting snow, ice and groundwater extraction may have weakened the response of the northern TWS to the climate. The results provide insight into the spatial and temporal variation in water storage, which can provide a basis for the scientific and effective management of water resources.

Objective To identify coronary heart disease risk factors in young and middle-aged persons and develop a tailored risk prediction model. Methods A retrospective cohort study was used in this research. From January 2017 to January 2020, 553 patients in the Department of Cardiology at a tertiary hospital in Anhui Province were chosen as research subjects. The research subjects were separated into two groups based on the results of coronary angiography performed during hospitalization (n = 201) and non-coronary heart disease (n = 352). R software (R 3.6.1) was used to analyze the clinical data of the two groups. A logistic regression prediction model and three machine learning models, including BP neural network, Extreme gradient boosting (XGBoost), and random forest, were built, and the best prediction model was chosen based on the relevant parameters of the different machine learning models. Results Univariate analysis identified a total of 24 indexes with statistically significant differences between coronary heart disease and non-coronary heart disease groups, which were incorporated in the logistic regression model and three machine learning models. The AUCs of the test set in the logistic regression prediction model, BP neural network model, random forest model, and XGBoost model were 0.829, 0.795, 0.928, and 0.940, respectively, and the F1 scores were 0.634, 0.606, 0.846, and 0.887, indicating that the XGBoost model’s prediction value was the best. Conclusion The XGBoost model, which is based on coronary heart disease risk factors in young and middle-aged people, has a high risk prediction efficiency for coronary heart disease in young and middle-aged people and can help clinical medical staff screen young and middle-aged people at high risk of coronary heart disease in clinical practice.

Hypertrophic scar (HS) is an undesirable skin abnormality following deep burns or operations. Although intralesional multi-injection with the suspension of triamcinolone acetonide (TA) and 5-fluorouracil (5-Fu) has exhibited great promise to HS treatment in clinical, the difference of metabolic behavior between TA and 5-Fu remarkably compromised the treatment efficacy. Besides, the traditional injection with great pain is highly dependent on the skill of the experts, which results in poor compliance. Herein, a bilayer dissolving microneedle (BMN) containing TA and 5-Fu (TA-5-Fu-BMN) with biphasic release profile was designed for HS therapy. Equipped with several micro-scale needle tips, the BMN could be self-pressed into the HS with uniform drug distribution and less pain. Both in vitro permeation and in vivo HS retention tests revealed that TA and 5-Fu could coexist in the scar tissue for a sufficient time period due to the well-designed biphasic release property. Subsequently, the rabbit ear HS model was established to assess therapeutic efficacy. The histological analysis showed that TA-5-Fu-BMN could significantly reduce abnormal fibroblast proliferation and collagen fiber deposition. It was also found that the value of scar elevation index was ameliorated to a basal level, together with the downregulation of mRNA and protein expression of Collagen I (Col I) and transforming growth factor-β1 (TGF-β1) after application of TA-5-Fu-BMN. In conclusion, the BMN with biphasic release profiles could serve as a potential strategy for HS treatment providing both convenient administrations as well as controlled drug release behavior.

Dissolving microneedles (MNs) have emerged as a promising transdermal delivery system, as they integrate the advantages of both injection and transdermal preparations. However, the low drug-loading and limited transdermal delivery efficiency of MNs severely hinder their clinical applications. Microparticle-embedded gas-propelled MNs were developed to simultaneously improve drug-loading and transdermal delivery efficiency. The effects of mold production technologies, micromolding technologies, and formulation parameters on the quality of gas-propelled MNs were systematically studied. Three-dimensional printing technology was found to prepare male mold with the highest accuracy, while female mold made from the silica gel with smaller Shore hardness could obtain a higher demolding needle percentage (DNP). Vacuum micromolding with optimized pressure was superior to centrifugation micromolding in preparing gas-propelled MNs with significantly improved DNP and morphology. Moreover, the gas-propelled MNs could achieve the highest DNP and intact needles by selecting polyvinylpyrrolidone K30 (PVP K30), polyvinyl alcohol (PVA), and potassium carbonate (K2CO3): citric acid (CA) = 0.15:0.15 (w/w) as the needle skeleton material, drug particle carrier, and pneumatic initiators, respectively. Moreover, the gas-propelled MNs showed a 1.35-fold drug loading of the free drug-loaded MNs and 1.19-fold cumulative transdermal permeability of the passive MNs. Therefore, this study provides detailed guidance for preparing MNs with high productivity, drug loading, and delivery efficiency.

Abstract Background Circular RNAs (circRNAs) have been demonstrated to play significant roles in regulating gene expression in tumorigenesis, including breast cancer (BC). This study was designed to explore the role and underlying molecular mechanisms of circMMP11 in BC. Methods The real-time quantitative polymerase chain reaction (RT-qPCR) assay was used for examining expression of circMMP11, microRNA-625-5p (miR-625-5p), and Zinc finger E-box binding homeobox-2 (ZEB2). The protein expression of ZEB2, Vimentin, and E-cadherin was assessed by western blot assay. The proliferation ability of BC cells was determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazol-3-ium bromide (MTT) and colony-forming assays. The transwell assay was used to measure migration and invasion of BC cells. The apoptotic cells were examined by flow cytometry assay. The interaction association among circMMP11, miR-625-5p, and ZEB2 was confirmed by RNA pull-down and dual-luciferase report assays. A xenograft experiment was established to clarify the role of circMMP11 silencing in vivo. Results We found that circMMP11 and ZEB2 were overexpressed in BC tissues and cells compared with controls. The suppression of circMMP11 or ZEB2 repressed proliferation, migration, and invasion while induced apoptosis of BC cells. Additionally, miR-625-5p, interacted with ZEB2, was a target of circMMP11 in BC cells. CircMMP11 regulated the expression of ZEB2 by targeting miR-625-5p. Knockdown of circMMP11-mediated effects on BC cells could be abolished by overexpression of ZEB2. Consistently, silencing of circMMP11 impeded the tumor growth in vivo. Conclusions CircMMP11/miR-625-5p/ZEB2 axis affected proliferation, migration, invasion, and apoptosis of BC cells through the mechanism of competing endogenous RNAs (ceRNA), indicating that circMMP11 was an oncogenic circRNA in BC.

Soil moisture (SM) is an indispensable variable in drought monitoring and weather forecast. L-band is found to be the most suitable band for retrieving surface SM. Here, we evaluate two L-band passive microwave SM products Soil Moisture Active and Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) in Inner Mongolia. The collected in-situ data from 24 measured sites and the triple collocation (TC) analysis method (using Global Land Data Assimilation System (GLDAS) Noah and the Advanced Scatterometer (ASCAT) SM data as a reference dataset) are used to evaluate SMAP and SMOS SM products. In the validation based on in-situ SM, SMAP shows the highest correlation with the in-situ SM, followed by GLDAS and SMOS. The root mean square error (RMSE) and bias value of SMAP is the lowest. The validation results of each in-situ station show that the median correlation coefficient of ASCAT is the highest, followed by SMAP, GLDAS, and SMOS. The median RMSE and bias of SMAP are the lowest, while SMOS performs the worst among the three products. TC analysis results show that SMAP has better performance with the majority of the random errors distributed between 0.02 and 0.03 m3/m3. The average random error of SMAP is small, while SMOS has relatively large random errors. Simultaneously, SMAP performs better than GLDAS and SMOS in grassland and low vegetation coverage areas. The research results and analysis of this paper are expected to provide some insights for improving the quality of SM products.

Abstract It was well-known that Berberine, a major bioactive compound extracted from natural plants Coptis chinensis, has anti-diabetic effects for decades in china. Other types of pharmacological activities, such as anti-inflammatory, antimicrobial, hypolipidemic, and anti-cancer effects, have also been examined. At cellular level, these pharmacological activities were mostly an inhibitory effect. However, the cytoprotective effect of berberine was also observed in various types of cells, such as neurons, endothelial cells, fibroblasts, and β-cells. The paradoxical result may be closely associated with characteristics and distribution of berberine within cells, and they can be explained mechanically by mitohormesis, one particular form of hormesis. Here, we reviewed the mitohormetic response and assessed the berberine-induced effects and the possible signaling pathway involved. These findings may contribute to better clinical applications of berberine and indicate that some mitochondria-targeted conventional drugs should be considered carefully in clinical application.

When using HBase to store tiles of remote sensing images, the spatial position of a tile is often used as the first part of the tile's rowkey so that tiles with high spatial correlations are stored close together to improve query efficiency. We refer to this storage method as the Geo-First model. However, Geo-First models have two problems: the load between nodes is unbalanced, and the accumulation of time-series remote sensing images has a negative impact on storage and query efficiency. Considering these two problems, we proposed a method for storing remote sensing images based on Google S2 and HBase. In our method, two strategies are adopted to eliminate these problems: the balanced placement strategy (BPS) and the periodic storage strategy (PSS). We evaluated our method by focusing on the effectiveness of BPS and PSS. The results show that our method achieves higher tile storage and query efficiency than three Geo-First models based on latitude and longitude, Geohash code, and Google S2 code. BPS effectively balances the load between nodes, while PSS alleviates the negative impact of the accumulation of time-series remote sensing images. Both BPS and PSS greatly improve tile storage and query efficiency.

In the era of rapid data expansion and computer technology development, discrete storage, multiband push and fuzzy query remote sensing data management methods are no longer suitable for the data analysis needs of users, including the needs for long time series, global regions and multidata fusion. After analyzing traditional data management techniques, this paper discusses the existing achievements and development trends of current technologies. This paper aims to solve the problem of data sharing difficulties and organizational inconsistency caused by the use of different formats for the same spatial object. Based on a discrete global grid, this paper studies the blocky division method and coding specification of Google S2 and then accomplishes the layered storage of remote sensing data in HBase. Finally, Kylin is used to build a cube model to discuss the information mining analysis changes in the new data management model. Experiments show that the blocky and layered management schema (BLMS) can realize the unified management of global remote sensing data with multisource, heterogeneous, multiscale, and long-term characteristics and provide accurate data services on demand.

Natural selenium (Se)-rich areas in China are generally characterized by high geological background of cadmium (Cd). However, the interaction between Se and Cd in the soil-rice-human continuum in such areas remains elusive. The concentrations, bioaccessibilities, and biomarkers of Se and Cd in a typical Se-Cd rich area were determined through chemical analysis, in vitro digestion model and cross-sectional study, respectively. The results showed that the molar ratio of available Se/Cd in the soil was averaged at 0.55 and soil Se did not reduce Cd accumulation and transportation in rice. Se bioaccessibility increased from the gastric phase to the intestinal phase, but the opposite was the case for Cd bioaccessibility. Moreover, bioaccessible concentration of Cd was positively correlated to corresponding total concentration in rice but negatively associated with the logarithm of molar ratio of Se/Cd. The risk of Cd-induced nephrotoxicity for the exposure group was not higher than the reference group, which could be ascribed to the mitigative effect of Se. Males and elders were at higher risk of Cd-induced injury owing to higher urinary Cd (U-Cd) and β2-microglobulin (U-β2-MG), and lower urinary Se (U-Se). Our results suggested that Cd-induced health risk should be assessed from a soil-rice-human perspective and the interaction between Se and Cd should be taken into account.

Objective To examine the efficacy and safety of a sequential combination of chemotherapy and autologous cytokine-induced killer (CIK) cell treatment in triple-negative breast cancer (TNBC) patients.Methods A total of 294 post-surgery TNBC patients participated in the research from January 1, 2009 to January 1, 2015. After adjuvant chemotherapy, autologous CIK cells were introduced in 147 cases (CIK group), while adjuvant chemotherapy alone was used to treat the remaining 147 cases (control group). The major endpoints of the investigation were the disease-free survival (DFS) and overall survival (OS). Additionally, the side effects of the treatment were evaluated.Results In the CIK group, the DFS and OS intervals of the patients were significantly longer than those of the control group (DFS: P = 0.047; OS: P = 0.007). The multivariate analysis demonstrated that the TNM (tumor-node-metastasis) stage and adjuvant CIK treatment were independent prognostic factors for both DFS [hazard ratio (HR) = 0.520, 95% confidence interval (CI):0.271-0.998, P = 0.049; HR = 1.449, 95% CI:1.118-1.877, P = 0.005, respectively] and OS (HR=0.414, 95% CI:0.190-0.903, P = 0.027; HR = 1.581, 95% CI:1.204-2.077, P = 0.001, respectively) in patients with TNBC. Additionally, longer DFS and OS intervals were associated with increased number of CIK treatment cycles (DFS: P = 0.020; OS: P = 0.040). The majority of the patients who benefitted from CIK cell therapy were relatively early-stage TNBC patients.Conclusion Chemotherapy in combination with adjuvant CIK could be used to lower the relapse and metastasis rate, thus effectively extending the survival time of TNBC patients, especially those at early stages.

Abstract Our study presents the genetic landscape betel quid chewing‐associated tongue carcinomas (BQ‐TCs). We compared the genetic landscape and mutational signatures of 15 BQ‐TCs, five nonbetel quid chewing‐associated tongue carcinomas (nBQ‐TCs), and 82 tongue carcinomas in general population from the TCGA (TCGA‐TCs) project. The highlights of this research mainly include: (a) The genetic landscape of BQ‐TC was characterized with frequent mutations in RASA1 gene and in CpG islands throughout the genome. (b) The BQ‐TC had a distinct mutational signature from that of nBQ‐TC and tongue carcinomas in the general population, and this signature was associated with the mutations in RASA1 and in CpG islands. (c) Our study indicates that betel quid (BQ) chewing classifies a distinct group of tongue carcinoma. The BQ chewing might not contribute to the tumorigenesis of tongue carcinomas as a mutagen.

Abstract Electrochemical sensors have the high sensitivity, fast response, and simple operation for applications in biological, medical, and chemical detection, but limited by the poor stability and high cost of the electrode materials. In this work, we used PtNi lagged-like nanowire for caffeic acid (CA) electrochemical detection. The removal of outer layer Ni during reaction process contributed to the rehabilitation of active Pt sites at the surface, leading to the excellent electrocatalytic behavior of CA sensing. Carbon-supported PtNi-modified glassy carbon electrode (PtNi/C electrode) showed a broad CA detecting range (from 0.75 to 591.783 μM), a low detection limit (0.5 μM), and excellent stability. The electrode preserved high electrocatalytic performance with 86.98% of the initial oxidation peak current retained after 4000 potential cycles in 0.5 mM caffeic acid solution. It also demonstrates excellent anti-interference capability and is ready for use in the real sample analysis.

A self-healing epoxy coating is creatively prepared by employing expired cefalexin loaded into mesoporous silica nanomaterials (MSNs) for corrosion protection of 304 stainless steel (304SS). A series of physical characterizations, including transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectrometer, and N2 adsorption–desorption isotherms, verified that the cefalexin successfully filled porous MSN. The corrosion resistance of the epoxy (EP) coating incorporated with the cefalexin@MSNs is investigated using a Tafel polarization curve and electrochemical impedance spectra (EIS) in a 3.5 wt.% NaCl solution. It is found that the EP-Cefalexin@MSNs coating has a higher self-corrosion voltage and a lower self-corrosion current density than EP coating. Moreover, the charge transfer resistance (Rct) value of Cefalexin@MSNs coating is twice that of EP coating after immersion for 24 h, indicating that the cefalexin@MSNs significantly enhance the corrosion resistance of the coating under long-duration immersion. The improved corrosion resistance is attributed to the densified adsorption of the cefalexin inhibiting the cathode corrosion reaction, providing a self-healing long-duration corrosion protection for 304SS.

Fracture energy, as an important characteristic parameter of the fracture properties of materials, has been extensively studied by scholars. However, less research has been carried out on ubiquitiformal fracture energy and the main method used by scholars is the uniaxial tensile test. In this paper, based on previous research, the first Brazilian splitting test was used to study the ubiquitiformal crack extension of slate and granite, and the complexity and ubiquitiformal fracture energy of rock material were obtained. The heterogeneity of the material was then characterized by the Weibull statistical distribution, and the cohesive model is applied to the ABAQUS numerical software to simulate the effect of heterogeneity on the characteristics of ubiquitiformal cracks. The results demonstrate that the ubiquitiformal complexity of slate ranges from 1.54 to 1.60, and that of granite ranges from 1.58 to 1.62. The mean squared deviations of the slate and granite ubiquitiformal fracture energy are the smallest compared with the other fracture energies, which are 0.038 and 0.037, respectively. When the homogeneity of the heterogeneous model is less than 1.5, its heterogeneity has a greater influence on the Brazilian splitting strength, and the heterogeneity of the rock is obvious. However, when the homogeneity is greater than five, the effect on the Brazilian splitting strength is much less, and the Brazilian splitting strength tends to be the average strength. Therefore, it is particularly important to study the fracture problem of cracks from the nature of the material structure by combining the macroscopic and mesoscopic views through the ubiquitiform theory.

The neonatal or infant period is a critical stage for the development of brain neuroplasticity. Early life stresses in the neonatal period, including neonatal maternal separation (NMS), have adverse effects on an increased risk of psychiatric disorders in juveniles and adults. However, the underlying molecular mechanisms are not largely understood. Here, we found that juvenile rats subjected to 4 h daily NMS during postnatal days 1 to 20 exhibited autistic-like behavioral deficits without impairments in learning and memory functions. Molecular mechanism studies showed that oxytocin receptor (OXTR) in the medial prefrontal cortex of NMS rats was evidently downregulated when compared with control pups, especially in neurons. Erk/MAPK signaling, the downstream coupling signaling of OTXR, was also inhibited in NMS juvenile rats. Treatment with oxytocin could relieve NMS-induced social deficit behaviors and activated phosphorylation of Erk/MAPK signaling. Furthermore, medication with the inhibitor of H3K4 demethylase alleviated the abnormal behaviors in NMS rats and increased the expression of OXTR in the medial prefrontal cortex, which showed an epigenetic mechanism underlying social deficits induced by NMS. Taken together, these findings identified a molecular mechanism by which disruptions of mother–infant interactions influenced later displays of typical social behaviors and suggested the potential for NMS-driven epigenetic tuning of OXTR expression.

Visceral pain is one of the leading causes for abdominal pain in gastroenterological diseases and is still hard to treat effectively. Bulleyaconitine A (BAA) is an aconitine analog and has been used for the treatment of pain. Our previous work suggested that BAA exerted analgesic effects on neuropathic pain through stimulating the expression of dynorphin A in spinal microglia. Here, we investigated the inhibitory effect of BAA on visceral pain and examined whether the expression of dynorphin A in spinal microglia was responsible for its effects. We found that BAA produced significant antivisceral pain effect induced by acetic acid through stimulating dynorphin A expression in spinal microglia. In addition, anxiety and chronic visceral pain are highly prevalent comorbid conditions in clinical research, which is still a problem to be solved. We also aimed to evaluate the effects of BAA on anxiety. A comorbidity model with characteristics of both chronic visceral pain and anxiety was developed by colorectal injection of 2,4,6-trinitrobenzene sulfonic acid and the induction of heterotypic intermittent chronic stress protocol. In comorbid animals, BAA exerted great antianxiety effects. Meanwhile, the antianxiety mechanism of BAA was different with the antivisceral pain mechanism of BAA. In conclusion, our study demonstrated, for the first time, that BAA exerted marked antivisceral pain and antianxiety effects, which expands the analgesic spectrum and clinical application of BAA. Furthermore, it also it provides a better guidance for the clinical use of BAA.

The EGFR-targeting cancer therapies are commonly facing drug resistance, mostly due to mutations. Gene therapy with artificial microRNA targeting EGFR conserved sequence may avoid such problem. In this study, we constructed a recombinant adenovirus expressing EGFR-targeting artificial microRNA and active revCASP3 (Ad-EC), under the control of tumor-specific SLPI promoter, and evaluated its inhibitory effect on HEP-2 cancer cells both in vitro and in vivo. MTT assay showed that cell growth inhibition rate at 72h was 44.0% in Ad-EC group at MOI 50, while the rate was 7.7% in the control virus Ad-GFP group and 3.6% in Cetuximab (500 μg/ml) group respectively. Flow cytometry analysis revealed the late apoptotic cells rate was 36.1% in Ad-EC group, significantly higher than 6.5% of Ad-GFP group (p < 0.001). When Ad-EC (MOI 50) was combined with CDDP (0.25 μg/ml), late apoptotic cells rate increased to 61.2%, significantly higher than each monotherapy group (P < 0.001). The real-time xCELLigence system recorded an effective cell growth inhibition in Ad-EC and CDDP groups, and more enhanced effect in Ad-EC plus CDDP group. Western blot revealed that Ad-EC could inhibit the activation of AKT pathway and ERK1/2 pathway, while Cetuximab had the AKT pathway over-activated. In vivo experiments with HEP-2 xenograft in nude mice confirmed the tumor inhibition in Ad-EC, CDDP and Ad-EC plus CDDP groups compared with PBS group (P < 0.01). Collectively, these data support the effective inhibition of cancer cells by this novel gene therapy strategy.

It is crucial to predict landslide displacement accurately for establishing a reliable early warning system. Such a requirement is more urgent for landslides in the reservoir area. The main reason is that an inaccurate prediction can lead to riverine disasters and secondary surge disasters. Machine learning (ML) methods have been developed and commonly applied in landslide displacement prediction because of their powerful nonlinear processing ability. Recently, deep ML methods have become popular, as they can deal with more complicated problems than conventional ML methods. However, it is usually not easy to obtain a well-trained deep ML model, as many hyperparameters need to be trained. In this paper, a deep ML method—the gated recurrent unit (GRU)—with the advantages of a powerful prediction ability and fewer hyperparameters, was applied to forecast landslide displacement in the dam reservoir. The accumulated displacement was firstly decomposed into a trend term, a periodic term, and a stochastic term by complementary ensemble empirical mode decomposition (CEEMD). A univariate GRU model and a multivariable GRU model were employed to forecast trend and stochastic displacements, respectively. A multivariable GRU model was applied to predict periodic displacement, and another two popular ML methods—long short-term memory neural networks (LSTM) and random forest (RF)—were used for comparison. Precipitation, reservoir level, and previous displacement were considered to be candidate-triggering factors for inputs of the models. The Baijiabao landslide, located in the Three Gorges Reservoir Area (TGRA), was taken as a case study to test the prediction ability of the model. The results demonstrated that the GRU algorithm provided the most encouraging results. Such a satisfactory prediction accuracy of the GRU algorithm depends on its ability to fully use the historical information while having fewer hyperparameters to train. It is concluded that the proposed model can be a valuable tool for predicting the displacements of landslides in the TGRA and other dam reservoirs.

Abstract Frameshift mutations frequently occur in colorectal cancer (CRC) with microsatellite instability (MSI), but the nature and biological function of many MSI‐associated mutations remain elusive. Here, an MSI frameshift mutation is identified in glioma tumor suppressor candidate region gene 1 (GLTSCR1) that produces two C‐terminal‐truncated proteins. Additionally, GLTSCR1 is verified as a tumor suppressor that inhibits CRC metastasis. Through binding to bromodomains and the phosphorylation‐dependent interaction domain of bromodomain protein 4 (BRD4) via the C‐terminus, GLTSCR1 blocks oncogenic transcriptional elongation. However, truncated GLTSCR1 translocates into the cytoplasm and loses BRD4 binding domain, which induces the phosphorylation of RNA Pol II at Ser2 and dephosphorylation at Ser5, then increases oncogenic transcriptional elongation. Importantly, GLTSCR1 deficiency decreases sensitivity to bromodomain and extra terminal domain inhibitors. This study highlights the molecular mechanism of the GLTSCR1‐BRD4 interaction, which is a potential therapeutic target for CRC.

It is well-known that platinum (Pt) is still the preferred material of anode catalyst in ethanol oxidation, however, the prohibitive high cost and CO poisoning of Pt metal impede the commercialization of fuel cells. Therefore, improving the utilization rate of catalysts and reduce the cost of catalyst become one of the most concerned focus in the construction of fuel cells. In this work, the Pt-based catalysts are synthesized by using different content of sodium dodecyl sulfate (SDS) modified-Ti3C2Tx support, and the dispersion regulation function of SDS modified-Ti3C2Tx supported on Pt nanoparticles is investigated. The structure, composition and morphology of different catalysts are characterized by X-ray diffraction (XRD), X-ray spectroscopy (EDX), transmission electron microscopy (TEM) and high-resolution TEM, respectively. It is found that the Pt nanoparticles in pure Ti3C2Tx surface are serious aggregated and show poor dispersion, whereas the Pt nanoparticles in SDS modified-Ti3C2Tx have a better dispersion. The electrochemical results revealed that SDS modified-Ti3C2Tx supported Pt nanoparticles has higher electrocatalytic activity and stability in both acidic and alkaline ethanol oxidation when the dosage of SDS increases to 100 mg. These findings indicate that the SDS-Ti3C2Tx/Pt catalysts show a promising future of potential applications in fuel cells with modification of Ti3C2Tx support.

The objective of this study was to develop a novel anhydrous reverse micelle nanoparticles (ARM-NPs) system to overcome the sedimentation instability of peptide-containing pressurized metered-dose inhalers (pMDIs). A bottom-up method was utilized to fabricate ARM-NPs. Tertiary butyl alcohol (TBA)/water system, freeze-drying and lipid inversion method were successively used to produce the ARM-NPs for pMDI. Various characteristics of ARM-NPs were investigated including particle size, morphology, secondary structure of the peptide drug, aerosolization properties and storage stability. As revealed by the results, ARM-NPs with spherical shape possessed 147.7 ± 2.0 nm of particle size with 0.152 ± 0.021 PdI. The ARM-NPs for pMDI had satisfactory fine particle fraction (FPF) value of 46.99 ± 1.33%, while the secondary structure of the peptide drug was unchanged. Stability tests showed no pronounced sedimentation instability for over 12 weeks at 4–6 °C. Furthermore, a hypothesis was raised to explain the formation mechanism of ARM-NPs, which was verified by the differential scanning calorimetry analysis. The lecithin employed in the reverse micelle vesicles could serve as a steric barrier between peptide drugs and bulk propellant, which prevented the instability of peptide drugs in hydrophobic environment. Homogenous particle size could avoid Ostwald ripening phenomenon of particles in pMDIs. It was concluded that the ARM-NPs for pMDI could successfully overcome sedimentation instability by the steric barrier effect and homogeneous particle size.

Astrocytes, as the largest population of glial subtype, play crucial roles in normal brain function and pathological conditions, such as Parkinson’s disease (PD). Restoring the functions of astrocyte is a promising new therapeutic target for PD. Astrocytes can express multiple types of neurotransmitter receptors, including functional α7 nicotinic acetylcholine receptor (α7nAChR). Previously, we found that a non-selective α7nAChR agonist nicotine exerted a protective effect against H2O2-induced astrocyte apoptosis via an α7nAChR-dependent pathway. However, the molecular mechanism of the antiapoptotic response of astroglial α7nAChR has not been studied. In the present study, using pharmacological inhibition and genetic knockout of α7nAChR, we assessed the antiapoptotic effects of an α7nAChR agonist PNU-282987 in primary cultured astrocytes treated with 1-methyl-4-phenylpyridinium (MPP+). PNU-282987 promoted the viability of astrocytes, alleviated MPP+ induced apoptosis, and decreased the number of GFAP+/TUNEL+ cells. Meanwhile, PNU-282987 upregulated the expression of the antiapoptotic protein Bcl-2 and downregulated the expression of the apoptotic protein Bax and cleaved-caspase-3. Moreover, the suppression of the JNK-p53-caspase-3 signaling may underlie the neuroprotective property of PNU-282987. Therefore, PNU-282987 ameliorates astroglial apoptosis induced by MPP+ through α7nAChR-JNK-p53 signaling. Our findings suggest that PNU-282987 may be a potential drug for restoring astroglial functions in the treatment of PD.

Deep learning technology has achieved great success in the field of remote sensing processing. However, the lack of tools for making deep learning samples with remote sensing images is a problem, so researchers have to rely on a small amount of existing public data sets that may influence the learning effect. Therefore, we developed an add-in (LabelRS) based on ArcGIS to help researchers make their own deep learning samples in a simple way. In this work, we proposed a feature merging strategy that enables LabelRS to automatically adapt to both sparsely distributed and densely distributed scenarios. LabelRS solves the problem of size diversity of the targets in remote sensing images through sliding windows. We have designed and built in multiple band stretching, image resampling, and gray level transformation algorithms for LabelRS to deal with the high spectral remote sensing images. In addition, the attached geographic information helps to achieve seamless conversion between natural samples, and geographic samples. To evaluate the reliability of LabelRS, we used its three sub-tools to make semantic segmentation, object detection and image classification samples, respectively. The experimental results show that LabelRS can produce deep learning samples with remote sensing images automatically and efficiently.

The enantiomers separation of eight pharmaceutical racemates collected in Chinese Pharmacopoeia 2010 (Ch.P2010), including nitrendipine, felodipine, omeprazole, praziquantel, sulpiride, clenbuterol hydrochloride, verapamil hydrochloride and chlorphenamine maleate, was performed on chiral stationary phase of amylose ramification by high performance liquid chromatography (HPLC) on Chiralpak AD-H column and Chiralpak AS-H column with the mobile phase consisted of isopropanol and n-hexane. The detection wavelength and the flow rate were set at 254 nm and 0.7 mL/min, respectively. The effects of proportion of organic additives, alcohol displacer and temperature on the separation were investigated. The results indicated that eight chiral drugs were separated on chiral stationary phase of amylase ramification in normal phase chromatographic system. The chromatographic retention and resolution of enantiomers were adjusted by factors, including the changes of the concentration of alcohol displacer in mobile phase, organic alkaline modifier and column temperature. It was shown that the resolution was improved with reducing concentration of alcohol displacer. When the concentration of organic alkaline modifier was 0.2%, the resolution and the peak shape were fairly good. Most racemates mentioned above had the best resolution at column temperature of 25 °C. The best temperature should be kept unchanged in the process of separation so as to obtain stable separation results.

To assess biodegradable nasal packing effectiveness for improving postoperative symptoms and mucosal healing after endoscopic sinonasal surgery as compared with conventional/non-packing groups.Relevant articles were searched on PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials. We included randomized controlled trials (RCTs) that compared biodegradable packings with conventional packings or no packing, reporting postoperative symptoms and/or mucosal healing outcomes.This review included 19 studies, of which 11 compared biodegradable packings with conventional packings. Meta-analysis found that biodegradable packings significantly improved postoperative symptoms: bleeding at removal, pain at removal, pain in situ, and nasal blockage. Mucosal healing outcomes were inconsistent within studies, with no data could be pooled. Eight studies compared biodegradable packings with non-packing group. Postoperative symptom data in this comparison could not be pooled: A protective or equal effect on postoperative bleeding was reported in different studies; no difference was reported in pain status and nasal blockage. As for mucosal healing, meta-analysis showed that two arms of comparison had similar effect on synechiae, edema, infection and granulation at each time point.The limiting evidence suggests that biodegradable nasal packings are statistically better than conventional packings in postoperative symptoms, and probably comparable to non-packing group, as in this comparison we could not carry out meta-analysis. No beneficial or detrimental effect on postoperative mucosal healing could be determined based on existing evidence.