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Soil salinization–alkalization is a major hindrance to agricultural development globally. Tea crabapple is widely used in China. However, little remains known regarding the molecular mechanisms used to withstand mixed saline–alkali stress (MSAS). Herein, we exposed tea crabapple seedlings to MSAS, and RNA-seq was performed for the transcriptome analysis of roots. Between 43.26 million and 43.37 million clean reads were thus obtained. In comparison with the control group (day 0), 2931, 2335, and 3746 genes were differentially expressed at day 1, day 3, and day 6 of MSAS exposure, respectively, and 1022 genes were common in the three comparison groups. On functional annotation, we observed that numerous differentially expressed genes were involved in "global and overview maps"; "carbohydrate metabolism"; "folding, sorting, and degradation"; "biosynthesis of other secondary metabolites"; "environmental adaptation"; and "signal transduction." Heat shock proteins, cytochrome P450s, disease-resistant proteins, non-specific lipid-transfer proteins, pectate lyase, and beta-glucosidases were also induced in response to MSAS, in addition to nitrogen, phosphorus, and potassium absorption and metabolism-related genes. Transcription factor-coding genes appear to regulate the response of tea crabapple roots to MSAS by participating in, for example, plant hormone signal transduction and heat shock response. We also performed quantitative real-time PCR to validate the expression of six differentially expressed genes. Our findings provide new insights into the molecular mechanisms used by tea crabapple to cope with MSAS. [ABSTRACT FROM AUTHOR]

Velvet ash (Fraxinus velutina Torr.) is a dioecious tree species, which is widely used as a part of urban greeneries in saline land of North China. Female and male trees have different nutrient allocation trade-offs in dioecious species. As the fruit production consumes a lot of nutrients, female F. velutina plants grow slowly and are vulnerable to insects and diseases. Ecological stoichiometry can be used to study the physiological mechanism of the growth difference between female and male plants. The purpose of this study was to compare the seasonal patterns of C, N and P stoichiometry and their trade-offs in different organs of female and male F. velutina plants planted in urban green spaces. The fruit C, N and P contents of female F. velutina plants were all lower than those of leaves in the early growing season, but higher than those of leaves in the middle and late growing season. During most months, the leaf C and P contents of females were higher than those of males, while the leaf N content was lower than that of males, which was consistent with the sex-specific resource requirements for reproduction (i.e., high carbon requirements for ovules and high nitrogen demands for pollen). Compared to the females, there were more significant correlations between the stoichiometric indices (element contents and their ratios) of branches and leaves in male plants, and this difference may be related to the fact that the male plants were not involved in nutritional allocation for fruits. The leaf N/P of F. velutina was lower than 14 in the whole growing season, which indicated N limitation. The female and male plants of F. velutina had different sex-specific resource requirements for sex organ formation. [ABSTRACT FROM AUTHOR]

Purpose: As a novel antiangiogenic multi-target tyrosine kinase inhibitor recently approved in China, anlotinib has exhibited promising anticancer efficacy and acceptable safety profile in the salvage treatment of small cell lung cancer (SCLC) in clinical trials. Here we retrospectively investigated the efficacy and safety of anlotinib as third- or further-line treatment in patients with refractory SCLC. Patients and methods: A total of 40 patients with refractory SCLC treated with anlotinib monotherapy were included in this study. The clinicopathological data, treatment information, survival data and safety data were retrospectively collected. Survival curves were constructed using the Kaplan–Meier method. Univariate analysis was performed by log-rank testing. Results: Altogether, 40 patients of extensive-stage SCLC or progressive limited-stage SCLC received anlotinib monotherapy as third- or further-line treatment from July 2018 to June 2020. Four patients achieved partial response (PR), 14 patients achieved stable disease (SD), no complete response (CR) was recorded, and 22 patients experienced progressive disease (PD). The disease control rate (DCR) was 45.0%. The median progression-free survival (PFS) was 3.0 months (95% CI 2.241–3.759), and the median overall survival (OS) was 7.8 months (95% CI 3.190–12.410). The common adverse effects (AEs) included hypertension, fatigue, anorexia, cough, rash and nausea. Grade 3 treatment-related AEs occurred in 3 (7.5%) patients. One patient interrupted anlotinib treatment due to repeated grade 1 epistaxis. Univariate analysis revealed that patients without liver metastases, previously treated with radiotherapy or with Eastern Cooperative Oncology Group (ECOG) scores of 0 or 1 had longer OS with anlotinib treatment. Cox regression analysis demonstrated that patients without liver metastases and patients with ECOG score ≤ 1 had longer PFS, while patients without liver metastases had longer OS. Conclusion: Anlotinib is beneficial to refractory SCLC as third- or further-line treatment, especially in patients without liver metastasis and with better physical status. Related adverse effects are tolerable and manageable. [ABSTRACT FROM AUTHOR]

Employee counterproductive work behavior (ECWB) in the workplace has caused serious harm to the organization, and its recessive occurrence creates difficulty for the organization to guard against it. This study aims to explore the influence of high-performance work systems (HPWS) on the two sides of ECWB with employees and the internal influence path. It also aims to combine resource conservation and affective events theories to build an HPWS five-level model. It provides human resource management measures for enterprises to reduce and prevent the ECWB effectively. This study adopts a quantitative analysis method to conduct a questionnaire survey among employees in 366 enterprises in China. The results show that HPWS has a significant two-sided impact on ECWB. For employees with positive emotions, HPWS improved employee performance and inhibited ECWB. Meanwhile, for employees with negative emotions, HPWS reduces employees' work input and increases employees' counterproductive behaviors. For negative employees, the positive effect of HPWS is more significant than the negative effect of positive employees. In addition, organizational commitment has a moderating effect on the counterproductive behavior of negative employees. Therefore, when implementing HPWS, enterprises should consider the impact of both sides of HPWS on ECWB and adopt a more humane management method. In this study, a practical five-level HPWS model is constructed, which complements the existing research model and provides a theoretical basis and practical guidance for enterprises to scientifically and effectively promote employees to achieve high performance. [ABSTRACT FROM AUTHOR]

Background: As a novel irreversible pan-ErbB inhibitor recently approved in China, pyrotinib has exhibited promising anticancer efficacy and acceptable safety profile in HER2-positive metastatic breast cancer (mBC). The aim of this retrospective study was to estimate the efficacy and safety of pyrotinib treatment in Chinese mBC patients. Methods: We retrospectively reviewed the real-world clinicopathological and treatment data of HER2-positive mBC patients receiving pyrotinib-based treatment from August 2018 to July 2019 in Qilu Hospital of Shandong University and other medical centers of Shandong Province in China. Results: A total of 64 patients treated with pyrotinib were included for analysis, and the median follow-up duration was 260 days (interquartile range, 199.0 to 339.0 days). Fifty-nine (92.2%) patients had been previously treated with trastuzumab and/or T-DM1, while 11 (17.2%) patients had been exposed to lapatinib. The objective response rate (ORR) of all patients was 73.4%, and the disease control rate (DCR) was 98.4%, with a clinical benefit rate (CBR) of 87.5%. Patients with exposure to lapatinib responded well to pyrotinib-based treatment, although the ORR was significantly lower compared with that of patients without exposure to lapatinib (44.1% vs 77.5%, p=0.037). Previous lapatinib exposure was negatively associated with the objective response of pyrotinib treatment (odds ratio [OR]=0.248, 95% confidence interval [CI]  0.063– 0.970, p=0.045). The median progression-free survival (mPFS) for patients with previous lapatinib exposure and patients with visceral metastasis was 299 days (95% CI 240.1– 357.9 days) and 359 days (95% CI 258.3– 459.7 days), respectively. But the mPFS of the whole cohort has not been reached until the cut-off date. Cox multivariate analysis revealed that only visceral metastasis was an independent predictor of significantly shorter PFS (p=0.041) but not previous exposure to lapatinib (p=0.092). Diarrhea (28.1%), hand-foot syndrome (17.2%), and neutropenia (9.4%) were the most common grade 3 adverse events associated with pyrotinib treatment. Conclusion: Pyrotinib is highly beneficial to HER2-positive metastatic breast cancer patients, even in patients with previous lapatinib exposure. Pyrotinib is a feasible replacement of lapatinib in combination with chemotherapeutic drugs or as a monotherapy. Adverse effects are tolerable and easily manageable. [ABSTRACT FROM AUTHOR]

This study introduces four heterogeneous ensemble-learning techniques, that is, stacking, blending, simple averaging, and weighted averaging, to predict landslide susceptibility in Yanshan County, China. These techniques combine several state-of-the-art classifiers of convolutional neural network, recurrent neural network, support vector machine, and logistic regression in specific ways to produce reliable results and avoid problems with the model selection. The study consists of three main steps. The first step establishes a spatial database consisting of 16 landslide conditioning factors and 380 historical landslide locations. The second step randomly selects training (70% of the total) and test (30%) datasets out of grid cells corresponding to landslide and non-slide locations in the study area. The final step constructs the proposed heterogeneous ensemble-learning methods for landslide susceptibility mapping. The proposed ensemble-learning methods show higher prediction accuracy than the individual classifiers mentioned above based on statistical measures. The blending ensemble-learning method achieves the highest overall accuracy of 80.70% compared to the other ensemble-learning methods. [ABSTRACT FROM AUTHOR]

Background: Microsatellite stable (MSS) or mismatch repair proficient (pMMR) metastatic colorectal cancer (mCRC) is resistant to immune checkpoint inhibitors. However, a recent Japanese trial showed that regorafenib plus nivolumab had encouraging anti-cancer activity in MSS or pMMR mCRCs. Materials and Methods: We retrospectively reviewed the efficacy and safety data of combination therapy with regorafenib plus anti-PD-1 antibody in patients with refractory MSS or pMMR mCRC in the medical centers of Shandong Province in China. Results: Twenty-three patients with MSS or pMMR mCRC received regorafenib plus anti-PD-1 antibody. Eighteen (78.3%) patients experienced stable disease as best response, five (21.7%) patients had progressive disease, and no partial response was observed. The disease control rate (DCR) was 78.3% (18/23), and the median progression-free survival (PFS) was 3.1 months (95% CI, 2.32-3.89). Four of five (80.0%) patients with progressive disease had baseline liver metastasis, while nine of 18 (50.0%) patients with stable disease displayed no liver metastasis. One patient receiving radiofrequency ablation treatment for liver and abdominal wall metastases prior to combination treatment experienced a remarkably prolonged PFS of 9.2 months with SD. Neither liver metastasis status nor previous exposure to regorafenib was associated with treatment outcome. Treatment-related grade 3 toxicities were observed in 5/23 (21.7%) patients. Conclusion: No objective response was observed with the combination of regorafenib plus anti-PD-1 antibody, suggesting its little clinical activity in unselected Chinese patients with pMMR/MSS mCRC. Meanwhile, it exhibited some potential benefit in this cohort in terms of DCR and PFS. Adverse events were generally tolerable and manageable. Prospective studies with large sample sizes are needed to verify the findings. This combination strategy plus local ablative therapy might be worthy of further exploration. [ABSTRACT FROM AUTHOR]

Background: The novel coronavirus disease 2019 (COVID-19) outbreak started in Wuhan, Hubei, China since Dec 2019 and cases of infection have been continuously reported in various countries. It is now clear that the SARS-COV-2 coronavirus is transmissible from human to human. Nucleic acid detection is considered as the gold standard for the diagnosis of COVID-19. In this case report, we describe our experience in detection of SARS-COV-2 from a confirmed patient using nucleic acid test of bronchoalveolar-lavage fluid (BALF) samples but not nasopharyngeal swabs.Case Presentation: We present a case of severely ill SARS-COV-2 infected 46-year-old man with fever, coughing and chest tightness. We performed viral detection using his BALF samples and imaging method (CT) for confirmation. The patient received combination of interferonalfa-1b and ribavirin, lopinavir and ritonavir for antiviral treatment at different stages. Other medication was also given to him in combination for anti-inflammation, intestinal microbial regulation, phlegm elimination, liver protection and pulmonary fibrosis prevention purposes. We provided oxygen supply to him using BIPAP ventilator and high-flow humidification oxygen therapy instrument to facilitate respiration. The patient was cured and discharged.Conclusion: This case report described an effective supportive medication scheme to treat SARS-COV-2 infected patient and emphasized the necessity of detection of the viral genome using BALF samples and its significance in the diagnosis and prognosis of the disease. [ABSTRACT FROM AUTHOR]

This work was to generate landslide susceptibility maps for the Three Gorges Reservoir (TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree (GBDT), random forest (RF) and information value (InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area, 28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic (ROC) curves, the sensitivity, specificity, overall accuracy (OA), and kappa coefficient (KAPPA). The results showed that the GBDT, RF and InV models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR. [ABSTRACT FROM AUTHOR]

Understanding the relationships between the pore structure and bulk properties such as irreducible water saturation (S wir) and permeability (k) of rocks is a crucial problem in geoscience. In this study, two types of fractal dimension were determined from nuclear magnetic resonance (NMR) T 2 relaxation time distribution and models for estimating S wir and k using fractal theory were proposed. In view of the data of sandstone samples from upper Paleozoic formation in China, we found a good agreement between the predicted S wir values based on fractal analysis and the experimental measurements, and the estimated k values based on the proposed model are within one order of magnitude of measured k. Additionally, another four frequently used k estimation models were compared with our proposed model, and the result support that the proposed approach has great potential in investigating k while certain limitation still exists. This procedure was applied on another set of sandstone samples collected from a different location, and the predicted permeability values are reliable. Our study suggests that the proposed S wir estimation model using NMR T 2 data and fractal dimensions provides useful insights into characterizing the pore space properties of sedimentary rocks. Our work demonstrates that we can use NMR data to infer S wir directly, and the estimated S wir value can be well integrated in permeability prediction model, which improves the applications of NMR in characterizing the properties related to rock pores. [ABSTRACT FROM AUTHOR]

In infants, hepatitis B virus (HBV) infections are mainly acquired by mother-to-child transmission (MTCT). Current tests for the presence of HBV markers at birth can neither confirm nor exclude MTCT. The aim of this study was to find an early diagnostic marker of HBV MTCT. From 2011 to 2016, we studied a total of 5999 pregnant women who gave birth at our hospital in Shenzhen City, China. HBsAg-positive mothers and their offspring (n=386 pairs) were tested at birth for HBV markers, and 207 infants were followed up at 7-12 months after birth. The HBsAg-seropositive rate of the pregnant women was 12.5%. Additionally, 28.0%, 36.0%, 98.5% and 6.6% of umbilical cord (UC) blood samples of neonates were found to be positive for HBsAg, HBeAg, anti-HBc and HBV-DNA, respectively, whereas for neonatal femoral venous (FV) blood, the percentages were 16.2%, 38.0%, 98.8% and 2.6%, respectively. Mothers with high HBV DNA loads and those who were HBeAg positive were the most likely to have HBV-positive offspring. Immunoprophylaxis failed in five infants: the difference in median HBV DNA titer between UC blood from infants with and without HBV MTCT was statistically significant, and there was no significant difference in HBV DNA titer between UC blood and in peripheral blood of infants with HBV MTCT. In conclusion, we found that HBeAg positivity and high HBV loads are strong risk factors for MTCT of HBV and that the HBV DNA titer in the UC is a good predictor for HBV MTCT. [ABSTRACT FROM AUTHOR]

Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13–24 h prediction tasks (MAPE = 31.47%). [ABSTRACT FROM AUTHOR]

• Plant water consumption was sensitive to the deep soil water. • Middle and deep layer soil water was utilized during high water consumption. • Mixed-species plantations were not necessarily conducive to enhancing drought resistance in arid regions. • Mixing of tree species with the same water use strategy could cause a soil desiccation. Water is a crucial factor limiting artificial vegetation growth in arid and semi-arid regions. The water availability and plant utilization patterns reflect the ecosystem's response to environmental water conditions. In arid and semi-arid areas, it was considered that mixed-species plantations, particularly arbors mixed with shrubs, were conducive to enhancing drought resistance. However, inappropriate artificial vegetation and exorbitant productivity could have accelerated soil desiccation in range and intensity, demonstrating adverse effects on soil water cycle and further influencing vegetation's growth and natural succession. In this study, we investigated the water use strategies of mixed tree planting (Elaeagnus angustifolia) with shrubs (Caragana korshinskii) in the sandy land of the east Yellow River, China. Our findings demonstrated that Elaeagnus angustifolia consumed more than 1.2 times more water than Caragana korshinskii. Elaeagnus angustifolia and Caragana korshinskii primarily used the middle and deep layer soil water during high water consumption. During the lower water consumption season, Elaeagnus angustifolia and Caragana korshinskii utilized the shallow layer soil water. In most cases, the two species have overlapping niches in space and time and compete while sharing water resources. In very few cases, the two species responded to seasonal droughts primarily through spatial differences in water use. The soil water deficit and water consumption rate in deep layers of the mixed plantation of Elaeagnus angustifolia and Caragana korshinskii were 260 mm and 19 mm/year, which were significantly higher than those in the pure plantation of Elaeagnus angustifolia and Caragana korshinskii. The mixed forest of Elaeagnus angustifolia and Caragana korshinskii might lead to the soil moisture environment in the study area to show a drought trend, resulting in soil desiccation. These findings could provide the scientific basis for restoring regional vegetation and stand structure optimization allocation of shelter forests. [ABSTRACT FROM AUTHOR]

This study analysed the response in the size of wetlands to a sudden turn from drought to flood along the Yangtze River system in China. The wetlands and their spatial distributions in the provinces of Hubei, Hunan, Jiangxi, Anhui and Jiangsu for three periods (April and May 2010, April and May 2011 and June and July 2011) were identified by the artificial visual interpretation of charge-coupled device images obtained in 2010 and 2011 by the HJ-1A and HJ-1B satellites. The sizes of the wetland areas of all five provinces in the three periods were 30,087.10, 23,427.68 and 31,346.49 km2, respectively, with the largest changes occurring in Jiangxi. Changes in the mean standardized precipitation index (SPI) and its patterns of spatial distribution had similar trends to the changes in the size of the wetlands of each province in the three periods. SPI was positively correlated (R2 = 0.360, p < 0.05) with changes in the proportions of the wetlands during the drought. The mean SPI of the final period after the flood was positively correlated (R2 = 0.406, p < 0.01) with changes in the proportions of wetlands. Poyang Lake and Dongting Lake were impacted most by the flood, and Hongze Lake and Caohu Lake were the least affected. [ABSTRACT FROM AUTHOR]

Land-use allocation is of great importance for rapid urban planning and natural resource management. This article presents an improved artificial bee colony (ABC) algorithm to solve the spatial optimization problem. The new approach consists of a heuristic information-based pseudorandom initialization (HIPI) method for initial solutions and pseudorandom search strategy based on a long-chain (LC) mechanism for neighborhood searches; together, these methods substantially improve the search efficiency and quality when handling spatial data in large areas. We evaluated the approach via a series of land-use allocation experiments and compared it with particle swarm optimization (PSO) and genetic algorithm (GA) methods. The experimental results show that the new approach outperforms the current methods in both computing efficiency and optimization quality. [ABSTRACT FROM PUBLISHER]

There has been rapid economic development in China in recent decades, and demand for energy has consequently been increasing rapidly. Development and utilisation of clean and renewable energy has been promoted by the Chinese government to help sustain long-term and stable development. Sugarcane is being increasingly used in several countries as feedstock for renewable energy products, and is a major and expanding crop in southern China. In this paper, we discuss the potential of sugarcane as a feedstock for bioenergy production in China. It includes a review of (1) the existing sugarcane industry in China and key bio-physical factors affecting the extent to which sugarcane-based industries could supply feedstock for renewable energy production in China, (2) the economic and policy factors which are likely to affect production of bioenergy from sugarcane in China, and (3) recommendations on actions and policies that may assist with appropriate development of bioenergy production from sugarcane in China. Existing and expected future economic conditions are unlikely to favour production of biofuel from the sugar component in cane. However, the fibre component of cane remains an under-utilised resource component. A conclusion is made that sugarcane fibre has potential to contribute towards renewable electricity production in China. However, at present, favourable incentives do not exist to encourage this production. It is suggested that policies to facilitate cost-effective production of renewable electricity by sugar mills, consistent with national objectives regarding production of renewable energy, be considered by governments. Priorities for future research are in improving biomass yields per unit area of land and technologies for low-cost conversion of lignocellulosic biomass into biofuel. [ABSTRACT FROM AUTHOR]

Abstract: This paper aims to develop a novel hybrid model for assessing landslide susceptibility at the regional scale using multisource data to produce a landslide susceptibility map of the Zigui–Badong area near the Three Gorges Reservoir, China. This area is subject to anthropogenic influences because the reservoir's water level fluctuates cyclically between 145 and 175m; in addition, the area suffers from extreme rainfall events due to the local climate. The area has experienced significant and widespread landslide events in recent years. In our study, a novel hybrid model is proposed to produce landslide susceptibility maps using geographical information systems (GIS) and remote sensing. The hybrid model is based on rough set (RS) theory and a support vector machine (SVM). RS theory is employed as an attribute reduction tool to identify the significant environmental parameters of a landslide, and an SVM is used to predict landslide susceptibility. Four data domains were considered in this research: geological, geomorphological, hydrology, and land cover. The original group of 20 environmental parameters and 202 landslides were used as the inputs to produce a landslide susceptibility map. According to the map, 19.7% of the study area was identified as medium- and high-susceptibility zones encompassing 89.5% of the historical landslides. The results indicate high levels of landslide hazard in and around the main inhabited areas, such as Badong County and other towns, as well as in rural residential areas and transportation areas along the Yangtze River and its tributaries. The predicted map indicates a good correlation between the classified high hazard areas and slope failures confirmed in the field. Furthermore, the quality of the proposed model was comprehensively evaluated, including the degree of model fit, the robustness of the model, the uncertainty associated with the probabilistic estimate, and the model prediction skill. The proposed model was also compared with the general SVM, which demonstrated that the hybrid model has superior prediction skill and higher reliability and confirmed the usefulness of the proposed model for landslide susceptibility mapping at a regional scale. [Copyright &y& Elsevier]

In the Three Gorges of China, there are frequent landslides, and the potential risk of landslides is tremendous. An efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of lives and properties caused by these landslides. This paper presents landslide susceptibility mapping on the Zigui-Badong of the Three Gorges, using rough sets and back-propagation neural networks (BPNNs). Landslide locations were obtained from a landslide inventory map, supported by field surveys. Twenty-two landslide-related factors were extracted from the 1:10,000-scale topographic maps, 1:50,000-scale geological maps, Landsat ETM + satellite images with a spatial resolution of 28.5 m, and HJ-A satellite images with a spatial resolution of 30 m. Twelve key environmental factors were selected as independent variables using the rough set and correlation coefficient analysis, including elevation, slope, profile curvature, catchment aspect, catchment height, distance from drainage, engineering rock group, distance from faults, slope structure, land cover, topographic wetness index, and normalized difference vegetation index. The initial, three-layered, and four-layered BPNN were trained and then used to map landslide susceptibility, respectively. To evaluate the models, the susceptibility maps were validated by comparing with the existing landslide locations according to the area under the curve. The four-layered BPNN outperforms the other two models with the best accuracy of 91.53 %. Approximately 91.37 % of landslides were classified as high and very high landslide-prone areas. The validation results show sufficient agreement between the obtained susceptibility maps and the existing landslide locations. [ABSTRACT FROM AUTHOR]

China's unprecedented urbanization and economic modernization have brought about significant growth and land use changes in cities and their surroundings. Traditional analyses of the relationship between urbanization and land use change have not fully incorporated important factors like city function or developmental stage. We define and apply a new visualization and analysis tool-an evolution tree-showing how an understanding of evolutionary pathways taken by growing cities contributes to visualization and forecasting of urban development and spatial expansion. We clustered 253 Chinese cities by type and developmental stage, arranging them in a 'tree' structure, with types grouped as branches and leaf position along branches reflecting developmental stage. Urban growth rates are higher for business-oriented, manufacturing-oriented, and functionally comprehensive cities than for those oriented toward tourism. Extent of spatial growth is dominated by city type and developmental stage. Cities evolve along typical pathways, punctuated by occasional leap developments across functional types. [ABSTRACT FROM AUTHOR]

This study presents a new ensemble framework to predict landslide susceptibility by integrating decision trees (DTs) with the rotation forest (RF) ensemble technique. The proposed framework mainly includes four steps. First, training and validation sets are randomly selected according to historical landslide locations. Then, landslide conditioning factors are selected and screened by the gain ratio method. Next, several training subsets are produced from the training set and a series of trained DTs are obtained by using a DT as a base classifier couple with different training subsets. Finally, the resultant landslide susceptibility map is produced by combining all the DT classification results using the RF ensemble technique. Experimental results demonstrate that the performance of all the DTs can be effectively improved by integrating them with the RF ensemble technique. Specifically, the proposed ensemble methods achieved the predictive values of 0.012–0.121 higher than the DTs in terms of area under the curve (AUC). Furthermore, the proposed ensemble methods are better than the most popular ensemble methods with the predictive values of 0.005–0.083 in terms of AUC. Therefore, the proposed ensemble framework is effective to further improve the spatial prediction of landslides. [ABSTRACT FROM AUTHOR]

In this study, 52 Streptococcus suis isolates from pigs in southern China were divided into four known sequence types (STs) and six new STs, using multilocus sequence typing. Ten representative isolates were selected from 10 STs for the analysis of whole genome sequences. Virulence was assessed in 10 isolates, which were classified into three pathogenic groups. The prevalence of virulence-associated factors in the moderately pathogenic group was higher than that in the highly pathogenic group. The isolates from ST1 complex and serotype 2 were allocated to the moderately pathogenic group, while the isolates from the highly pathogenic group belonged to the non-ST1 complex and non-serotype 2. Three clusters were obtained based on multilocus sequence typing sequences: cluster III isolates from the nasal cavity of healthy pigs were classified into the highly pathogenic group and showed many peculiarities compared with cluster I and II isolates in virulence genotypes, genetic typing and pathogenesis, indicating a potential independent evolutionary line. Our results suggest that S. suis infections in China are becoming more complicated with constantly mutating isolates, which makes it difficult to distinguish their virulence by recognized typing methods. Thus, increased investigation and monitoring of these infections should be a priority for the swine industry in China. [ABSTRACT FROM AUTHOR]

• B. velezensis HC-8 isolated from honeysuckle plant can control honeysuckle powdery mildew. • B. velezensis HC-8 showed the maximum PV values by spraying prior to pathogen inoculation. • B. velezensis HC-8 populations persisted in plant leaves. • B. velezensis HC-8 increased defense-related enzyme activities in honeysuckle plant. • B. velezensis HC-8 may be a promising agent for biocontrol of powdery mildew. Powdery mildew caused by Erysiphe lonicerae var. lonicerae is a serious disease that causes significant loss to honeysuckle production in China. This disease is difficult to control by chemical measures, thus biological control may constitute a powerful alternative strategy. To develop an environmentally friendly microbial agent for biocontrol of powdery mildew, we screened strains of Bacillus spp. for biocontrol potential. One of the 102 isolates, strain HC-8, demonstrated high antifungal activity against three phytopathogenic fungi and efficiently suppressed the conidia germination of E. lonicerae under in vitro conditions. This isolate, which offered significant biocontrol of powdery mildew disease in honeysuckle, was identified as belonging to Bacillus velezensis. After challenge inoculation with E. lonicerae , honeysuckle plants treated with a concentration of 1 × 108 CFU/ml showed the highest protection value (PV). Biocontrol efficacy was highest when strain HC-8 was applied prior to pathogen inoculation, and the minimum PV was recorded when HC-8 was used 1 day after pathogen inoculation. Populations of the GFP-tagged strain HC-8- gfp persisted on honeysuckle leaves up to 25 days after spraying. In addition, we found that B. velezensis HC-8 induced defense-related enzyme activities in the leaves of honeysuckle. Thus, the present study provides a potential high-efficiency strategy for the biological control of powdery mildew disease and shows that B. velezensis HC-8 has significant potential as a biocontrol agent for honeysuckle production. [ABSTRACT FROM AUTHOR]

High mountains may serve as condensers for persistent organic pollutants (POPs) and the ice/snow core can provide long-term records of atmospheric deposition of pollutants. In this study, organochlorine pesticides (OCPs) and polycyclic aromatic hydrocarbons (PAHs) in firn core from Dasuopu Glacier were analyzed and the seasonal variation and deposition flux of these pollutants were investigated. PCB 28 was always detected in samples from different firn core layers and concentrations of PCB 28 were in the range of 0.09–0.3 ng/l. Hexachlorobenzene (HCB) and total DDTs (p-p''-DDD and p-p''-DDT) were not always detected and were only present in some samples. No p-p''-DDE and hexachlorocyclohexane (HCH) were detected above the level of determination limits. Concentrations of HCB ranged from 0.04 to 0.07 ng/l, and total DDTs were in the range of 0.15–0.3 ng/l. Total glacier PAHs was below 26 ng/l. The levels of OCPs and PAHs in Dasuopu glacier were roughly similar to values from the European mountain areas but lower than those from Lys glacier (Italy) and glacier from Rocky Mountain. Hg concentration (2–35 ng/l) in firn core samples was higher than that of remote region of Arctic. PCB 28 didn''t show obvious variation in different seasons, however for major PAH compounds higher values were observed in summer than in winter. With regard to Hg, it displayed winter maximum. Deposition flux of OCPs, PAHs and mercury showed similar results with maximum flux occurring in the 2000s. After 2000/2001, deposition flux decreased and reflected the possible decrease of emissions of these atmospheric pollutants in the adjacent region. [Copyright &y& Elsevier]

• LSTM is considered for flood susceptibility prediction in a sequence perspective. • An appropriate feature engineering method is integrated with the LSTM network. • A reliable flood susceptibility map can be obtained by using the LSS-LSTM method. • The proposed method can achieve better performance than benchmark methods. Identifying floods and producing flood susceptibility maps are crucial steps for decision-makers to prevent and manage disasters. Plenty of studies have used machine learning models to produce reliable susceptibility maps. Nevertheless, most research ignores the importance of developing appropriate feature engineering methods. In this study, we propose a local spatial sequential long short-term memory neural network (LSS-LSTM) for flood susceptibility prediction in Shangyou County, China. The three main contributions of this study are summarized below. First of all, it is a new perspective to use the deep learning technique of LSTM for flood susceptibility prediction. Second, we integrate an appropriate feature engineering method with LSTM to predict flood susceptibility. Third, we implement two optimization techniques of data augmentation and batch normalization to further improve the performance of the proposed method. The LSS-LSTM method can not only capture the attribution information of flood conditioning factors and the local spatial information of flood data, but also has powerful sequential modelling capabilities to deal with the spatial relationship of floods. The experimental results demonstrate that the LSS-LSTM method achieves satisfactory prediction performance (93.75% and 0.965) in terms of accuracy and area under the receiver operating characteristic (ROC) curve. [ABSTRACT FROM AUTHOR]

Landslides are regarded as one of the most common geological hazards in a wide range of geo-environment. The aim of this study is to assess landslide susceptibility by integrating convolutional neural network (CNN) with three conventional machine learning classifiers of support vector machine (SVM), random forest (RF) and logistic regression (LR) in the case of Yongxin Country, China. To this end, 16 predisposing factors were first selected for landslide modelling. Then, a total of 364 landslide historical locations were randomly divided into training (70%; 255) and verification (30%; 109) sets for modelling process and assessment. Next, the training set was used for building three hybrid methods of CNN-SVM, CNN-RF and CNN-LR. In the following, the trained models were used for landslide susceptibility mapping. Finally, several objective measures were employed to compare and validate the performance of these methods. The experimental results demonstrated that the performance of the machine learning classifiers previously mentioned can be effectively improved by integrating the CNN technique. Therefore, the proposed hybrid methods can be recommended for landslide spatial modelling in other prone areas with similar geo-environmental conditions. • Landslide susceptibility prediction based on CNN and machine learning models. • CNN is used to extract useful features from landslide raw data. • Accuracy of single classifiers are improved using the CNN for feature extraction. • Reliable landslide susceptibility maps are obtained by using the hybrid methods. [ABSTRACT FROM AUTHOR]

Background: Patients with cancer are a high-risk population in the COVID-19 pandemic. We aimed to describe clinical characteristics and outcomes of patients with cancer and COVID-19, and examined risk factors for mortality in this population.Methods: We did a retrospective, multicentre, cohort study of 205 patients with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and with a pathological diagnosis of a malignant tumour in nine hospitals within Hubei, China, from Jan 13 to March 18, 2020. All patients were either discharged from hospitals or had died by April 20, 2020. Clinical characteristics, laboratory data, and cancer histories were compared between survivors and non-survivors by use of χ2 test. Risk factors for mortality were identified by univariable and multivariable logistic regression models.Findings: Between Jan 13 and Mar 18, 2020, 205 patients with cancer and laboratory-confirmed SARS-CoV-2 infection were enrolled (median age 63 years [IQR 56-70; range 14-96]; 109 [53%] women). 183 (89%) had solid tumours and 22 (11%) had haematological malignancies. The median duration of follow-up was 68 days (IQR 59-78). The most common solid tumour types were breast (40 [20%] patients), colorectal (28 [14%]), and lung cancer (24 [12%]). 54 (30%) of 182 patients received antitumour therapies within 4 weeks before symptom onset. 30 (15%) of 205 patients were transferred to an intensive care unit and 40 (20%) died during hospital admission. Patients with haematological malignancies had poorer prognoses than did those with solid tumours: nine (41%) of 22 patients with haematological malignancies died versus 31 (17%) of 183 patients with solid tumours (hazard ratio for death 3·28 [95% CI 1·56-6·91]; log rank p=0·0009). Multivariable regression analysis showed that receiving chemotherapy within 4 weeks before symptom onset (odds ratio [OR] 3·51 [95% CI 1·16-10·59]; p=0·026) and male sex (OR 3·86 [95% CI 1·57-9·50]; p=0·0033) were risk factors for death during admission to hospital.Interpretation: Patients with cancer and COVID-19 who were admitted to hospital had a high case-fatality rate. Unfavourable prognostic factors, including receiving chemotherapy within 4 weeks before symptom onset and male sex, might help clinicians to identify patients at high risk of fatal outcomes.Funding: National Natural Science Foundation of China. [ABSTRACT FROM AUTHOR]

We analyzed the distribution and bioaccumulation of six heavy metals (Cu, Pb, Zn, Cr, Cd and Hg) in marine organisms, water, and sediments from China's Hainan and Zhoushan coastal regions. In all marine organism, seawater, and sediment samples, Zn and Hg had the highest and lowest concentrations, respectively. Heavy metals in marine organisms varied by region and species, with concentrations being higher in Zhoushan than in Hainan (except for Zn) and in crab than in fish. Marine organisms' ability to digest and eliminate heavy metals (bioaccumulation ability), based on bioaccumulation factors, was significantly higher for heavy metals in seawater than in sediment. Higher sediment background values may explain the higher heavy metal concentrations in crab. Generally, marine organisms' bioaccumulation ability was higher for Cu and Zn and lower for Pb. Findings specific to the coastal environments may be generalizable to other coastal areas in China or worldwide. Image 1 • Across all samples, Zn and Hg had the highest and lowest concentrations, respectively. • Heavy metal concentrations (except for Zn) were higher in Zhoushan than in Hainan. • Heavy metal concentrations were higher in crab than in fish. • BAFs of organisms for heavy metals were higher in seawater than in sediment. • BAFs of organisms were higher for Cu and lower for Pb. [ABSTRACT FROM AUTHOR]

This paper aims to use recurrent neural networks (RNNs) to perform landslide susceptibility mapping in Yongxin County, China. The two main contributions of this study are summarized as follows. First, the regular RNN is compared to its three variants in the case study of landslide susceptibility mapping for the first time, including long short term memory, gated recurrent unit and simple recurrent unit. Second, a sequential data representation method is proposed to fully explore the predicting potential of RNNs. The study area consists of 364 historical landslide locations that were divided into two parts: 255 (70%) for training and 109 (30%) for validation, and 16 landslide influencing factors were considered for spatial prediction. To validate the effectiveness of these RNN-related methods, several objective measures of accuracy, recall, F-measure, Matthews correlation coefficient and the receiver operating characteristic were used for evaluation. Experimental results demonstrate that very high and high susceptible areas are concentrated in the northwest and south of Yongxin County, while landslides in the central area are less prone to occur. Based on quantitative results, all the RNN-related methods achieved area under the curve values above 0.83 and produced accurate prediction results with the optimized parameters. Therefore, the RNN framework can be used as a useful tool for the landslide susceptibility mapping task to mitigate and manage landslides. • Landslide susceptibility mapping based on recurrent neural networks. • Sequential landslide data are constructed for modelling. • Regular recurrent neural network is compared with its three variants. • Reliable landslide susceptibility maps can be achieved in the study area. [ABSTRACT FROM AUTHOR]

• CNNs are considered for dealing with the flood susceptibility mapping task. • Two different CNN frameworks of classification and feature extraction are presented. • Three data presentation forms are designed for the proposed CNN frameworks. • Reliable flood susceptibility maps can be obtained by using the proposed CNNs. • Prediction performance of SVM can be improved using the CNNs for feature extraction. Flood is a very destructive natural disaster in the world, which seriously threatens the safety of human life and property. In this paper, the most popular convolutional neural network (CNN) is introduced to assess flood susceptibility in Shangyou County, China. The main contributions of this study are summarized as follows. First, the CNN technique is used for flood susceptibility mapping through two different CNN classification and feature extraction frameworks. Second, three data presentation methods are designed in the CNN architecture to fit the two proposed frameworks. To construct the proposed CNN-based methods, 13 flood triggering factors related to historical flood events in the study area were prepared. The performance of these CNN-based methods was evaluated using several objective criteria in comparison to the conventional support vector machine (SVM) classifier. Experiments results demonstrate that all the CNN-based methods can produce more reliable and practical flood susceptibility maps. For example, the proposed CNN-based classifiers were 0.022–0.054 higher than SVM in terms of area under the curve (AUC). In addition, in the classification process, CNN-based feature extraction can effectively improve the prediction capability of SVM by 0.021–0.051 in terms of AUC. Therefore, the proposed CNN frameworks can help mitigate and manage floods. [ABSTRACT FROM AUTHOR]

Aim: Repetitive negative thinking (RNT) as a cognitive process in multiple mental disorders is a key risk factor for mental disorders. It is associated with the development and maintenance of the illness. The perseverative thinking questionnaire (PTQ) is an instrument to evaluate RNT with excellent reliability and validity. Nevertheless, a Chinese version of the perseverative thinking questionnaire (C-PTQ) is lack of validation in Chinese college students. The study aimed to establish a C-PTQ, explore its psychometric properties in college students., Methods: After translating PTQ into Chinese, we investigated 696 college students. We conducted exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to examine the psychometric properties and factor structures of the C-PTQ. Content validity was assessed using the content validity index and internal consistency was assessed using the Cronbach's α and McDonald's Omega ω. Multi-variable linear regressions explored the relationships between variables. We used receiver operating characteristic (ROC) curves to determine the ability of C-PTQ in identifying depression and anxiety., Results: The EFA showed a one-factor structure, which explained 52.227% of the total variance. The CFA showed that both one-factor structure in this research and three-factor structure of original demonstrated eligible model fits. The content validity index of 0.93. Results demonstrated good internal consistency (Cronbach's α = 0.934, McDonald's Omega ω = 0.934) and convergent validity. The PTQ is a useful tool in identifying depression (sensitivity = 85.5%, specificity = 64.6%) and anxiety (sensitivity = 84.6%, specificity = 68.5%)., Conclusions: The C-PTQ has good psychometric properties, which is valid and reliable for assessing RNT in Chinese college students., (© 2024 John Wiley & Sons Australia, Ltd.)

Objectives: Recent mpox outbreaks highlight diverse transmission modes, with sexual behavior prominent in China's IIb strain. Nevertheless, despite HPV being a common sexually transmitted pathogen, there is a paucity of research into its coexistence and genotype distribution within this patients population., Methods: We conducted a study at the Third People's Hospital of Shenzhen from May to September 2023. We collected information on mpox patients, including their sociodemographic and clinical characteristics. Anal swabs were collected for HPV genotyping., Results: Among 73 MSM mpox cases, HIV positivity was 56.2 % (41/73) and HPV positivity 80.4 % (41/51). Multiple HPV infections were prevalent (56.9 %, 29/51), especially among HIV-positive (93 %, 27/29). HPV16 (29.3 %, 12/41) was the most common high-risk genotype, followed by HPV59 (26.8 %, 10/41), HPV42 (19.5 %, 8/41), HPV6 (14.6 %, 6/41), and HPV54 (14.6 %, 6/41). HPV infection was significantly associated with HIV infection (p = 0.001). Additionally, HIV infection (p = 0.001) and PCR-detected positive sites for mpox (p = 0.047) were associated with high-risk HPV infection., Conclusions: In this study, most of the mpox patients were found to be infected with HPV, mostly with high-risk types and multiple infections. Therefore, it is strongly recommended that mpox-infected individuals intensify HPV-related screening, prevention, and treatment measures., Competing Interests: Declaration of Competing Interest The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

With climate change and anthropic influence on the coastal ecosystems, mangrove ecosystems are disappearing at an alarming rate. Accordingly, it becomes important to track, study, record and store the mangrove microbial community considering their ecological importance and potential for biotechnological applications. Here, we provide information on mangrove fungal community composition and diversity in mangrove ecosystems with different plant species and from various locations differing in relation to anthropic influences. We describe twelve newly assembled genomes, including four chromosomal-level genomes of fungal isolates from the mangrove ecosystems coupled with functional annotations. We envisage that these data will be of value for future studies including comparative genome analysis and large-scale temporal and/or spatial research to elucidate the potential mechanisms by which mangrove fungal communities assemble and evolve. We further anticipate that the genomes represent valuable resources for bioprospecting related to industrial or clinical uses., (© 2024. The Author(s).)

Background: Increasing evidence points to hyperhomocysteinemia as an independent risk factor for coronary artery disease in addition to traditional cardiovascular risks, but few have studied the association between hyperhomocysteinemia and total coronary artery occlusion (TCAO). To understand the risk factors for TCAO, we investigated the potential relationship between hyperhomocysteinemia and TCAO, and the interactions between cardiovascular risk factors and hyperhomocysteinemia., Methods: A total of 890 adult patients from Southwest China participated in this cross-sectional study between February 2018 and February 2021. TCAO was defined as complete occlusion of more than one of the 15 coronary segments. Hyperhomocysteinemia was defined as serum homocysteine levels ≥15 μmol/L. Multivariable logistic regression models were used to determine the relationship between hyperhomocysteinemia and TCAO. The relationship between homocysteine as a continuous variable and TCAO was also analyzed. Subgroup analyses by sex, age, weight, smoking, hypertension, diabetes, and dyslipidemia were done, and interactions between subgroup variables and hyperhomocysteinemia were performed., Results: Individuals with hyperhomocysteinemia showed an increased risk for TCAO. The adjusted odds ratio for TCAO in individuals with hyperhomocysteinemia was 1.74 (95% confidence interval, 1.28-2.36). When analyzed as a continuous variable, homocysteine was associated with an increased risk for TCAO. Subgroup analysis showed that the association between hyperhomocysteinemia and TCAO was statistically significant in men, elderly, overweight, smokers, and non-diabetic people. Interaction analysis showed no significant interactions between hyperhomocysteinemia and group variables., Conclusions: In Southwest China, hyperhomocysteinemia was significantly associated with TCAO. This association was particularly significant in men, elderly, overweight, smokers, and non-diabetic people., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Radiation recall pneumonitis (RRP) is unpredictable but associated with severe radiation damage in previously irradiated fields. Chemotherapy and targeted drugs have been reported to contribute to RRP. Here we report a case of a patient with non-small cell lung cancer (NSCLC) who developed RRP following administration of immune checkpoint inhibitor (ICI) 18 months after the end of re-irradiation., Case Presentation: A 69-year-old man received adjuvant chemoradiotherapy post-operatively. He underwent thoracic re-irradiation for oligometastatic NSCLC. On second recurrence, pembrolizumab combined with nab-paclitaxel were administered. After six months, he developed symptoms of persistent cough and dyspnea, with consistent pneumonitis on CT images. The clinical time frame and significant radiographic evidence raised suspicion for RRP. Symptoms resolved after steroids., Conclusions: RRP is a rare occurrence. Patients undergoing immunotherapy after prior irradiation may be at increased risk of this rare radiation pneumonitis., (© 2022. The Author(s).)

Based on the meteorological data of 143 meteorological site, we calculated aridity index (AI) with the potential evaporation formulated by FAO-56 Penman-Monteith and precipitation in Northwest China during 1989-2019. Mann-Kendall trend analysis, wavelet analysis and partial differential equation were used to examine the AI change trend, variation cycle, and contribution rate of main climate impact factors to AI. The results showed that there was a non-significant decreasing trend of AI in Northwest China on the whole, a significant decreasing trend of AI in Qinghai, and a non-significant increasing trend of AI in Xinjiang during 1989-2019. There was an abrupt change of AI in the study area in 2010. There was a primary 17-year periodicity in the change of AI in Northwest China. The spatial distribution of AI was shown as a larger AI in the middle of Northwest China and a smaller AI in the Southeast and Northwest in Northwest China. The tendency rates of AI were -1.27, -1.17·(10 a) -1 , -0.41, -0.49, -1.77 and -2.73·(10 a) -1 in Northwest China, Gansu, Ningxia, Shanxi, Qinghai, and Xinjiang, respectively. The possibility of drought risk was higher in Xiaozaohuo, Korla, Aksu, and Turpan region. Precipitation and actual water vapor pressure were the dominant factors of AI changes in Gansu, Ningxia, Qinghai, and Shaanxi. But the potential evapotranspiration, solar radiation, and average temperature were the main climate factors for AI changes in Xinjiang.

Background: The COVID-19 pandemic is a significant worldwide health crisis. Breast cancer patients with COVID-19 are fragile and require particular clinical care. This study aimed to identify the clinical characteristics of breast cancer patients with COVID-19 and the risks associated with anti-cancer treatment., Methods: The medical records of breast cancer patients with laboratory-confirmed COVID-19 were collected among 9559 COVID-19 patients from seven designated hospitals from 13th January to 18th March 2020 in Hubei, China. Univariate and multivariate analyses were performed to assess risk factors for COVID-19 severity., Results: Of the 45 breast cancer patients with COVID-19, 33 (73.3%) developed non-severe COVID-19, while 12 (26.7%) developed severe COVID-19, of which 3 (6.7%) patients died. The median age was 62 years, and 3 (6.7%) patients had stage IV breast cancer. Univariate analysis showed that age over 75 and the Eastern Cooperative Oncology Group (ECOG) score were associated with COVID-19 disease severity (P < 0.05). Multivariate analysis showed that patients who received chemotherapy within 7 days had a significantly higher risk for severe COVID-19 (logistic regression model: RR = 13.886, 95% CI 1.014-190.243, P = 0.049; Cox proportional hazards model: HR = 13.909, 95% CI 1.086-178.150, P = 0.043), with more pronounced neutropenia and higher LDH, CRP and procalcitonin levels than other patients (P < 0.05)., Conclusions: In our breast cancer cohort, the severity of COVID-19 could be associated with baseline factors such as age over 75 and ECOG scores. Chemotherapy within 7 days before symptom onset could be a risk factor for severe COVID-19, reflected by neutropenia and elevated LDH, CRP and procalcitonin levels., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Coronavirus disease 2019 (COVID-19) has spread worldwide, causing significant stress on the medical system. We explored the risk factors for condition changes in COVID-19 pneumonia patients after admission.The patients diagnosed with COVID-19 pneumonia at 2 medical centers in Hunan Province were studied, and those whose conditions changed after admission were compared. Their clinical characteristics and experimental indicators were compared using SPSS software and R language to build a disease risk prediction model.Patients with condition changes after admission were older and had more blood cell abnormalities and impaired organ function (decreased albumin, elevated D-dimer) than normal patients. We found that age, neutrophil ratio, D-dimer, chest Computed tomograpgy (CT) changes, and glucocorticoid use were risk factors for COVID-19 pneumonia after admission.Elderly patients are more susceptible to disease changes after COVID-19 pneumonia; COVID-19 pneumonia patients who develop disease changes after admission have higher neutrophil ratios, increased D-dimer levels, chest imaging changes, and glucocorticoid usage. Additional research is needed.

We examined the effects of biochar and effective mircoorganisms (EM) application on growth and photosynthetic characteristics of Sesbania cannabina in the Yellow River Delta, by a pot experiment with different EM treatments (without EM addition, EM-; with EM addition, EM+) and a gradient of biochar treatments (0, B 0 ; 0.5%, B 1 ; 1.5%, B 2 ; 3%, B 3 ; biochar weight/soil weight). The growth parameters, photosynthetic light response curve and chlorophyll fluorescence characteristics of S. cannabina were measured. The results showed that the EM+B 3 treatment had the best effect among all the treatments. Compared with the EM-B 0 treatment, the EM+B 3 treatment increased height, stem diameter, and total biomass by 69.5%, 90.0% and 141.1%, respectively. Biochar and EM significantly improved photosynthetic capacity. Compared with the EM-B 0 treatment, the EM+B 3 treatment significantly enhanced the maximum light response of net photosynthetic rate, transpiration rate, water use efficiency, and stomatal conductance by 93.8%, 35.1%, 43.4%, and 34.8%, respectively. Biochar and EM improved the parameters of chlorophyll fluorescence. Compared with the EM-B 0 treatment, the EM+B 3 treatment significantly increased the potential photochemical efficiency, the actual photochemical efficiency, the apparent electron transport rate and the non-photochemical quenching coefficient by 25.8%, 31.5%, 37.2%, and 56.8%, respectively. The parameters of growth, photosynthesis and chlorophyll fluorescence increased with the increasing biochar under EM+ treatments, whereas the B 3 treatment had negative effect under EM- treatments. The co-addition of EM and 3% biochar (EM+B 3 ) could improve the photosynthetic capacity and chlorophyll fluorescence characteristics of S. cannabina , broaden light ecological amplitude, boost the water retention and drought resistance property, and promote the growth of S. cannabina .

During the COVID-19 era, Chinese hospitals have developed a system that enables vulnerable cancer patients to continue to receive high-quality medical care, optimising their survival whilst protecting them. This includes use of digital quick codes, fever clinics and optimal scheduling. We wish to share our experiences working with patients during the pandemic.

Mother-to-child transmission of hepatitis B virus (HBV) is the main route of transmission in Asia, and characterization of HBV quasispecies is needed to further understand virus evolution and adaptation. To understand changes in HBV during mother-to-child transmission, we enrolled nine pairs of mothers and children in the study, including a set of twins. Three groups were infected with HBV genotype C, and six groups were infected with HBV genotype B. The full-length HBV genome was amplified by PCR from serum samples before antiviral treatment, the whole viral genomes from each pair were sequenced, and the complexity and diversity of the quasispecies were analyzed. The entropy of transmitted HBV in children was found to be lower than their mothers, suggesting that there was a bottleneck effect during HBV transmission from the mother to the child. Selective evolution was shown by calculating πN and πS in the whole genomes, and the highest values were obtained for the X gene, which plays a role in viral replication and immune escape. All genotype C patients and only one genotype B pair had a πN/πS greater than 1 ratio, indicating that positive selection had occurred. In addition, quasispecies were found to be different between the twin children despite having the same mother, indicating that virus evolution is host-specific.

Background: In December 2019, an outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was reported in Wuhan, Hubei province, China, which has subsequently affected more than 200 countries worldwide including Europe, North America, Oceania, Africa and other places. The number of infected people is rapidly increasing, while the diagnostic method of COVID-19 is only by nucleic acid testing., Objective: To explain the epidemiological characteristics, clinical features, imaging manifestations and to judge diagnostic value of COVID-19 by analyzing the clinical data of COVID-19 suspected and confirmed patients in a non-outbreak, Shanghai, China. To clarify the early epidemiology and clinical characteristics about COVID-19., Methods: Cross-sectional, single-center case reports of the 86 patients screened at Zhoupu Hospital in Pudong New District, Shanghai, China, from January 23 to February 16, 2020. Epidemiology, demography, clinical, laboratory and chest CTs were collected and analyzed. The screened patients were divided into COVID-19 and non-COVID-19 based on nucleic acid test results., Results: Of the 86 screened patients, 11 were confirmed (12.8%) by nucleic acid testing (mean age 40.73 ± 11.32, 5 males). No significant differences were found in clinical symptoms including fever, cough, dyspnea, sore throat, and fatigue (P > 0.05). No statistical difference was observed in plasma C-reactive protein (CRP) between the two groups (COVID-19 and non-COVID-19 ) of patients (P = 0.402), while the white blood cell count and lymphocyte count of the confirmed patients were slightly lower than those of the suspected patients (P < 0.05). Some non-COVID-19 chest CTs also showed subpleural lesions, such as ground-glass opacities (GGO) combined with bronchiectasis; or halo nodules distributed under the pleura with focal GGO; consolidation of subpleural distribution or combined with air bronchi sign and vascular bundle sign, etc., Conclusion: The early clinical manifestations and imaging findings of COVID-19 are not characteristic in non-outbreak areas. Etiological testing should be performed as early as possible for clinically suspected patients., (© 2020 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

Introduction: This study aimed to develop a new model on the basis of the National Early Warning Score to predict intensive care unit admission and the mortality of patients with acute pancreatitis., Methods: Patients diagnosed with acute pancreatitis in the emergency department were enrolled. The values of the National Early Warning Score, Modified Early Warning Score, and Bedside Index of Severity in Acute Pancreatitis in predicting intensive care unit admission and mortality of patients with acute pancreatitis were evaluated., Results: A total of 379 patients with acute pancreatitis were enrolled; 77 patients (20.3%) were admitted to the intensive care unit and 14 (3.7%) died. The National Early Warning Score and calcium level were identified as independent risk factors of intensive care unit admission. Serum calcium exhibited a moderate correlation with National Early Warning Score (r = -0.46; P < 0.001), Modified Early Warning Score (r = -0.37; P < 0.001), and Bedside Index of Severity in Acute Pancreatitis (r = -0.39; P < 0.001). A new model called National Early Warning Score-calcium was developed by combining National Early Warning Score and calcium blood test result, which had larger areas under the curve for predicting intensive care unit admission and mortality than the other 3 scoring systems., Discussion: A new model developed by combining National Early Warning Score and calcium exhibited better value in predicting the prognosis of acute pancreatitis than the models involving National Early Warning Score, Modified Early Warning Score, and Bedside Index of Severity in Acute Pancreatitis alone., (Copyright © 2019 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.)

Purpose: To discuss postoperative thrombocytopenia in the treatment of hepatocellular carcinoma (HCC) through transcatheter arterial chemoembolization (TACE) with single application of Lobaplatin as chemotherapy drug., Methods: The study retrospectively analyzed 1,945 HCC patients treated with TACE in our hospital from May 2013 to May 2018. The number of first-time users of lobaplatin reached 128, the second-time users reached 417, the third-time and above users 239. The analysis examined various items of patients, including gender, age, multiple preoperative examination indicators (platelet level, liver function tests, AFP level), ascites, preoperative presence of peptic ulcer at the initial (3-7 days) and long-term (21-90 days) postoperative stages. Platelet levels were evaluated according to the WHO Grading System for Hematologic Toxicity for side effects of anticancer drugs., Results: For HCC patients with normal pre-intervention platelet level, the incidences of mild decrease, moderate decrease and severe decrease after intervention were 16.50%, 10.47% and 4.88% respectively, the incidences of long-term platelet reduction after intervention were 13.25%, 4.73% and 1.65% respectively. The level of post-intervention thrombocytopenia was not correlated with the cycles of lobaplatin use. The initial thrombocytopenia was more obvious in female patients after intervention. The presence or absence of peptic ulcer and ascites before the intervention had an effect on the initial thrombocytopenia after the intervention. Platelet level before intervention was correlated with that after intervention. The liver function grading before intervention had no effect on the two levels of thrombocytopenia after intervention. There was a correlation between AFP level grouping before intervention and initial thrombocytopenia after intervention., Conclusions: The long-term incidence of thrombocytopenia after interventional therapy was not high in TACE patients with HCC treated with LPT alone, which was relatively safe. Besides, the occurrence of thrombocytopenia after intervention had certain characteristics, which can be used to guide clinical practice, so as to reduce the incidence of thrombocytopenia or provide targeted symptomatic support treatment.

Aerator is an indispensable tool in aquaculture, and China is one of the largest aquaculture countries in the world. So, the intelligent control of the aerator is of great significance to energy conservation and environmental protection and the prevention of the deterioration of dissolved oxygen. There is no intelligent aerator related work in practice and research. In this paper, we mainly study the intelligent aerator control based on deep learning, and propose a dissolved oxygen prediction algorithm with long and short term memory network, referred as DopLSTM. The prediction results are used to the intelligent control design of the aerator. As a result, it is proved that the intelligent control of the aerator can effectively reduce the power consumption and prevent the deterioration of dissolved oxygen.

Aims: This study aimed to assess whether neutrophil gelatinase-associated lipocalin (NGAL) and fibroblast growth factor 23 (FGF23) could be reliable biomarkers for early diagnosis of contrast-induced nephropathy (CIN)., Methods: 202 patients who underwent percutaneous coronary intervention (PCI) were included in the research. All subjects were divided into CIN group and non-CIN group. Serum NGAL and FGF23 were evaluated before and 0, 1, and 2 days after PCI. Serum levels of these two markers were compared intra-group and among groups. Receiver-operating characteristic (ROC) analysis and logistic regression models were conducted to assess the diagnostic performance of NGAL and FGF23 in detecting CIN., Results: When compared with baseline values, serum levels of both NGAL and FGF23 in all subjects increased after PCI, and the values peaked 1 day after PCI, but the changing was greater in CIN group. There were obvious differences between two groups in serum NGAL after 1, 2 days, and similar differences present in serum FGF23 after 1 day. ROC analysis showed that the area under the curve (AUC) of relative values (percent change from the baseline) in NGAL after 1 day was 0.899 (95% CI: 0.834-0.964, p = .000), the optimum cutoff was 49% (sensitivity = 80%, specificity = 92.4%). And the AUC in FGF23 was 0.814 (95% CI: 0.733-0.894, p = .000), the optimum cutoff was 20% (sensitivity = 73.3%, specificity = 87.6%). Both serum NGAL and serum FGF23 could improve the clinical models in identifying CIN., Conclusions: NGAL and FGF23 may have certain value in early diagnosis of CIN.

Tooth development is a complex process that involves precise and time-dependent orchestration of multiple genetic, molecular, and cellular interactions. Ameloblastin (AMBN, also named "amelin" or "sheathlin") is the second most abundant enamel matrix protein known to have a key role in amelogenesis. Amelogenesis imperfecta (AI [MIM: 104500]) refers to a genetically and phenotypically heterogeneous group of conditions characterized by inherited developmental enamel defects. The hereditary dentin disorders comprise a variety of autosomal-dominant genetic symptoms characterized by abnormal dentin structure affecting either the primary or both the primary and secondary teeth. The vital role of Ambn in amelogenesis has been confirmed experimentally using mouse models. Only two cases have been reported of mutations of AMBN associated with non-syndromic human AI. However, no AMBN missense mutations have been reported to be associated with both human AI and dentin disorders. We recruited one kindred with autosomal-dominant amelogenesis imperfecta (ADAI) and dentinogenesis imperfecta/dysplasia characterized by generalized severe enamel and dentin defects. Whole exome sequencing of the proband identified a novel heterozygous C-T point mutation at nucleotide position 1069 of the AMBN gene, causing a Pro to Ser mutation at the conserved amino acid position 357 of the protein. Exfoliated third molar teeth from the affected family members were found to have enamel and dentin of lower mineral density than control teeth, with thinner and easily fractured enamel, short and thick roots, and pulp obliteration. This study demonstrates, for the first time, that an AMBN missense mutation causes non-syndromic human AI and dentin disorders.

In order to define the effects of fruit crop load on the distribution and utilization of carbon and nitrogen in dwarf apple trees, we conducted three crop load levels (High-crop load, 6 fruits per trunk cross-sectional area (cm 2 , TCA)), Medium-crop load (4 fruits cm -2 TCA), Low-crop load (2 fruits cm -2 TCA)) in 2014 and 2015. The results indicated that the 15 N derived from fertilizer (Ndff) values of fruits decreased with the reduction of crop load, but the Ndff values of annual branches, leaves and roots increased. The plant 15 N-urea utilization rates on Medium and Low-crop load were 1.12-1.35 times higher than the High-crop load. With the reduction of crop load, the distribution rate of 13 C and 15 N in fruits was gradually reduced, but in contrast, the distribution of 13 C and 15 N gradually increased in annual branches, leaves and roots. Compared with High-crop load, the Medium and Low-crop load significantly improved fruit quality p < 0.05. Hence, controlling fruit load effectively regulated the distribution of carbon and nitrogen in plants, improved the nitrogen utilization rate and fruit quality. The appropriate crop load level for mature M.26 interstocks apple orchards was deemed to be 4.0 fruits cm -2 TCA.