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Background The warming of the 21st century has made high temperatures a major threat to the global population. Health problems associated with increased ambient temperatures have become a growing public health problem worldwide.Aim To study the attribute to high, low, and non-optimum temperatures of road injuries in 21 regions and global stratified by sex, age, geographic location and socio-demographic status from 1990 to 2019.Methods We used the Global Burden of Disease Study (GBD) Results Tool to examine the age-standardized death rates and disability-adjusted life years (DALYs) due to road injuries in 2019 by Join-point. Moreover, we report that high, low, and non-optimum temperatures exposure on road injuries for different groups by sex, age, region, and disease. In addition, we examined temporal trends in the burden of road disease caused by high, low, and non-optimum temperatures from 1990 to 2019. Trend analyzes were conducted for major socio-demographic index (SDI) regions.Results Globally, both the age-standardized death rate (ASDR) and DALY declined from 1990 to 2019, with average annual percent change (AAPC) values of −1.3% and −1.2%, respectively. In 2019, the indicators (death, and DALYs) steadily declined with SDI quintile increased in most regions. And road injuries related death and DALYs rate attributed to high temperatures were 0.17 and 8.50 respectively in 2019. From 1990 to 2019, DALYs for road injuries caused by low temperatures showed the most significant upward trend in most regions, especially in low-latitude countries.Conclusions This study provides a comprehensive understanding of the road injury burden caused by high, low, and non-optimum temperatures, which remains high in regions with low SDI. Therefore, special attention should be paid to road injuries in poor countries or in areas with extreme temperatures.

Purpose It is of great significance to accurately identify the KRAS gene mutation status for patients in tumor prognosis and personalized treatment. Although the computer-aided diagnosis system based on deep learning has gotten all-round development, its performance still cannot meet the current clinical application requirements due to the inherent limitations of small-scale medical image dataset and inaccurate lesion feature extraction. Therefore, our aim is to propose a deep learning model based on T2 MRI of colorectal cancer patients to identify whether KRAS gene is mutated. Methods In this research, a multi-task attentive model is proposed to identify KRAS gene mutations in patients, which is mainly composed of a segmentation sub-network and an identification sub-network. Specifically, at first, the features extracted by the encoder of segmentation model are used as guidance information to guide the two attention modules in the identification network for precise activation of the lesion area. Then the original image of the lesion and the segmentation result are concatenated for feature extraction. Finally, features extracted from the second step are combined with features activated by the attention modules to identify the gene mutation status. In this process, we introduce the inter-layer loss function to encourage the similarity of the two sub-network parameters and ensure that the key features are fully extracted to alleviate the overfitting problem caused by small dataset to some extent. Results The proposed identification model is benchmarked primarily using 15-fold cross validation. 382 images from 36 clinical cases were used to test the model. For the identification of KRAS mutation status, the average accuracy is 89.95±1.23%, the average sensitivity is 89.29±1.79%, the average specificity is 90.53±2.45%, and the average AUC is 95.73±5.02%. For segmentation of lesions, the average dice is 88.11 ± 0.86% CONCLUSIONS: We developed a novel deep learning-based model to identify the KRAS status in colorectal cancer. We demonstrated the excellent properties of the proposed identification through comparison with ground truth gene mutation status of 36 clinical cases. And all these results show that the novel method has great potential for clinical application. This article is protected by copyright. All rights reserved.

It was widely known that crystallization kinetics are the basis for crystallization behavior and crystallizer scale-up design. Cooling crystallization of potassium chloride was an essential unit operation in recycling industry. Some researchers have proposed the strategy of adding seed crystals for the intermittent cooling crystallization process to control the particle size and distribution of the target product. This paper studied the complex function relation between particle size and growth rate of KCI in the crystallization process in a continuous mixed-suspension mixed-product-removal (MSMPR) crystallizer at a steady state. Using the crystallization kinetics data, the mathematical models of coupling crystallization were established based on the population balance equations and mass balance equations. Since population density distributions of products behave multiform under different conditions, based on diffusion theory. The growth rate was obtained by a least square method for the multivariate linear regression, and the reliability of the kinetics model was validated experimentally. Fitting results indicated that some classical models, including several size-independent growth models and size-dependent growth models, such as Bransom, C-R, MJ2, ASL, and MJ3, could not model the size-dependent growth accurately. Based on this situation, an exponential growth model was proposed and confirmed to describe the size-dependent growth behavior. It was found that the model parameters have definite meanings and were strongly related to particle size. Compared with the classical models, this model showed good pertinency and adaptability to experimental results when used to describe the population density distribution and the size-dependent growth rate of KCI. This research could provide a theoretical guide for optimizing the crystallization process and designing industrial crystallizers.

Background Predicting the mutation statuses of 2 essential pathogenic genes [epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma (KRAS)] in non-small cell lung cancer (NSCLC) based on CT is valuable for targeted therapy because it is a non-invasive and less costly method. Although deep learning technology has realized substantial computer vision achievements, CT imaging being used to predict gene mutations remains challenging due to small dataset limitations. Methods We propose a multi-channel and multi-task deep learning (MMDL) model for the simultaneous prediction of EGFR and KRAS mutation statuses based on CT images. First, we decomposed each 3D lung nodule into 9 views. Then, we used the pre-trained inception-attention-resnet model for each view to learn the features of the nodules. By combining 9 inception-attention-resnet models to predict the types of gene mutations in lung nodules, the models were adaptively weighted, and the proposed MMDL model could be trained end-to-end. The MMDL model utilized multiple channels to characterize the nodule more comprehensively and integrate patient personal information into our learning process. Results We trained the proposed MMDL model using a dataset of 363 patients collected by our partner hospital and conducted a multi-center validation on 162 patients in The Cancer Imaging Archive (TCIA) public dataset. The accuracies for the prediction of EGFR and KRAS mutations were, respectively, 79.43% and 72.25% in the training dataset and 75.06% and 69.64% in the validation dataset. Conclusions The experimental results demonstrated that the proposed MMDL model outperformed the latest methods in predicting EGFR and KRAS mutations in NSCLC.

Chinese newborns have been screened for inborn errors of metabolism (IEM) for over 20 years. Although China features 56 different ethnic groups, there are no specific data describing the incidence of such genetic errors across difference ethnicities. To understand the ethnic preference distribution of the incidence and variants of IEM in the Ningxia Hui Autonomous Region of China, 189,354 newborns from 2016 to 2019 were screened by tandem mass spectrometry, including 87,482 from the Han ethnic population, 88,229 from the Hui population, 1,103 from other ethnicities, and 12,540 infants without ethnic registration. Suspected cases then underwent specific genetic profiling by targeted next generation sequencing. In total, 160 patients were diagnosed with 17 types of IEM, with a significant higher incidence in Hui infants (1/1,003) than in Han infants (1/1,232). Five diseases (eight patients) were specifically detected in Han infants, while three were exclusively diagnosed in six Hui infants. For shared diseases, the variants of keys genes also showed ethnic preference. Our findings enhance our understanding of the genetics underlying IEM, thus promoting the development of treatment plans for patients from different areas or ethnicities in China.

Background: There is still a lack of systematic investigation to explore the exact contribution of activities of daily living (ADL) to subjective well-being (SWB). This study aimed to estimate the association between ADL and SWB among Chinese older adults.Methods: The study included 13,010 participants from the Chinese Longitudinal Healthy Longevity Survey. SWB was measured by eight items, covering self-life satisfaction, positive emotions (optimism, consciousness, self-control, and happiness), and negative emotions (anxiety, loneness, and unusefulness). ADL was divided into basic activities of daily living (BADL) and instrumental activities of daily living (IADL), which were assessed by the adapted Katz index and Lawton scale, respectively. We applied Spearman correlation and logistic regression analysis to analyze the association between different ADL and older people’s SWB.Results: The differences in different levels of SWB among older adults in terms of gender, age, residence, region, ethnicity, occupation, living arrangement, education level, marital, economic, health status, smoking and drinking status, scores of BADL, and IADL were significant(Pr=-0.137 vs r=-0.268, PConclusions: Both BADL and IADL were significantly associated with SWB amongolder Chinese adults.

Background The exposure to risk factors (Smoking, High fasting plasma glucose and High BMI) are considered a major health concern. However, previous studies focused on changes in the global age-specific incidence and mortality, failed to distinguish between cohort and period effects, and did not discuss risk factors separately. Methods This study to estimate the burden of Alzheimer's disease and other dementias stratified by gender, age, locations, and social-demographic status for 21 regions across the world from 1990 to 2019. Besides, trend analyzes were conducted for major regions and risk factors for DALYs were also analyzed using age-period-cohort model and Join-point model. Results Globally, the age standardized incidence rate(ASIR), age standardized death rate(ASDR), and age standardized DALY rates for Alzheimer's disease have an upward trend from 1990 to 2019.(percentage change: 1.5%,3.0%,3.5%, respectively) with average annual percent change. In most regions, indicators (incidence, mortality, and DALYs) increased steadily with SDI increased. By APC analysis, substantially increasing age effects were presented for Alzheimer's disease and other dementias from 40 to 95 years. The cohort effects RRs had a rapid reduction attribute to Smoking, High fasting plasma glucose and High BMI. Conclusions As the burden of Alzheimer's disease remains high in areas with low SDI. Therefore, rapid and effective government responses are needed to tackle and control dementia risk factors to reduce the disease burden in middle-low and low SDI countries.

Background and Objective: Identifying the KRAS mutation status accurately in medical images is very important for the diagnosis and treatment of colorectal cancer. Despite the substantial progress achieved by existing methods, it remains challenging due to limited annotated dataset, large intra-class variances, and a high degree of inter-class similarities. Methods: To tackle these challenges, we propose a spatial-frequency dual-branch attention model (SF-DBAM) to determine the KRAS mutation status of colorectal cancer patients using a limited T2-weighted MRI dataset. The dataset contains 169 wild-type patients (2151 images) and 137 mutation-type patients (1666 images). The first branch utilizes part of the pre-trained Xception model to capture spatial-domain information and alleviate the small-scale dataset problem. The second branch builds frequency-domain information into cube columns using block-based discrete cosine transform and channel rearrangement. Then the cube columns are fed into convolutional long short-term memory (convLSTM) to explore the effective information between the reconstructed frequency-domain channels. Also, we design a channel enhanced attention module (CEAM) at the end of each branch to make them focus on the lesion areas. Finally, we concatenate the two branches and output the classified results through fully connected layers. Results: The proposed method achieves 88.03% overall accuracy with AUC of 94.27% and specificity of 90.75% in 10-fold cross-validation, which is better than the current non-invasive methods for determining KRAS mutation status. Conclusions: We believe that the proposed method can assist physicians to diagnose the KRAS mutation status in patients with colorectal cancer, and other medical problems can benefit from the spatial and frequency domains information.

Ursolic acid (UA) shows an effect on obesity and related metabolic diseases, but its mechanism of action remains unclear. We found that UA clearly reduced the body weight and adipose tissue mass and improved the glucose tolerance and insulin sensitivity in obese male mice. UA treatment significantly reduced the volume and weights of the epididymal white adipose tissue (eWAT) and inguinal subcutaneous white adipose tissue (igSWAT) of HFD-fed mice, respectively. UA also decreased the expression of genes involved in adipocyte differentiation and lipogenesis in igSWAT. Real-time PCR and immunohistochemistry showed that the expression of beiging-related genes 4-1BB factor (CD137), T-box transcription factor 1 (TBX1), and transmembrane protein 26 (TMEM26) were significantly increased in the UA treatment group. UA treatment significantly reduced the weight of gastrocnemius muscle (GM) and lipid droplets in the GM. UA treatment significantly upregulated the expression of PR domain-containing 16 (PRDM16), peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α), and fibronectin type 3 domain-containing protein 5 (FNDC5) in GM and igSWAT. UA also stimulated irisin secretion in the serum. In conclusion, these results indicate that UA plays an anti-obesogenic role by increasing the secretion of irisin and promoting the beiging of WAT.

Ovarian cancer (OC), the third common gynecologic malignancy, contributes to the most cancer-caused mortality in women. However, 70% of patients with OC are diagnosed at an advanced stage, of which the 5-year survival is less than 30%. Long noncoding RNAs (long ncRNAs or lncRNA), a type of RNA with exceeding 200 nucleotides in length but no protein-coding capability, have been demonstrated to involve the pathogenesis of various cancers and show considerable potential in the diagnosis of OC. In this study, we found that the LINC00909 expression in tumor and serum specimens of OC patients was elevated, determined by real-time quantitative, and droplet digital PCR. In receiver operating characteristic (ROC) analysis, our results revealed that serum LINC00909 distinguished cancers from normal ovarian tissue with 87.8% of sensitivity and 69.6% of specificity (AUC, 81.2%) and distinguished serous ovarian cancer from normal ovarian tissue with 90.0% of sensitivity and 75.9% of specificity (AUC, 84.5%). Furthermore, we observed that the tumor and serum LINC00909 level was positively associated with the International Federation of Gynecology and Obstetrics (FIGO) stage and the Eastern Cooperative Oncology Group (ECOG) score (reflecting patients’ performance status). Also, patients with low serum LINC00909 level showed a longer overall (hazard ratio, HR = 1.874 , p = 0.0004 ) and progression-free ( HR = 1.656 , p = 0.0017 ) survival. Functional assays indicated that the elevation of LINC00909 expression contributes to cell proliferation, migration, and invasion capability of ovarian cancer cells. Besides, we demonstrated that LINC00909 functions as a competing endogenous RNA (ceRNA) of MRC2 mRNA by sponging miR-23-3p, and thereby promotes epithelial-to-mesenchymal transition (EMT) of ovarian cancer cells. Therefore, we highlight that the LINC00909/miR-23b-3p/MRC2 axis is implicated in the pathogenesis of ovarian cancer, and serum LINC00909 may be a promising biomarker for the diagnosis of OC.

Exacum affine Balf.f. ex Regel is a traditional medicinal plant in Yemen and also a popular potted plant. In this study, we sequenced the complete chloroplast genome of E. affine on the Illumina HiSeq Platform. The plastome sequence is 153,311 bp in length with a typical quadripartite structure, containing a pair of inverted repeated (IR) regions of 26,079 bp that are separated by a large single copy (LSC) region of 83,724 bp, and a small single copy (SSC) region of 17,509 bp. The GC content of the whole cp genome was 43.14%. A total of 132 functional genes were annotated, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The complete plastome sequence of E. affine will provide genetic and genomic information to promote its horticulture, officinal utilisation and systematics research of Gentianaceae (especially the tribe Exaceae).

A thermophoretic motion system with a variable heat transmission factor is investigated, which describes wrinkling soliton propagation in a substrate-supported graphene sheet. Analytic multiple-lump wave solutions are constructed via the Hirota bilinear method and symbolic computation. A numerical simulation shows that the system exhibits breaking lump waves. The system parameters control the open width and number of breaking gaps. These results should contribute to a better understanding of the propagation characteristics of wrinkling solitons in a complex graphene thermophoretic motion system.

This study analyzes a thermophoretic motion system with a variable heat transmission which models the nonlinear wrinkle motions in substrate-supported graphene sheets. Through symbolic computation, the analytic N-soliton solutions are obtained for the system. The N-soliton solutions can be used to describe the multiple wrinkles in graphene sheets. Furthermore, wrinkle propagation and interaction are discussed. Snake-, V- and Z-like wrinkles are observed graphically by choosing the heat transmission function as three specific functions. A collision between wrinkles is elastic. Before and after the collision, wrinkle energy and propagation direction remain unchanged. But at collision points, the energy carried by the larger wrinkles will be subtracted. The research contributes to a deeper understanding to the structures, characteristics and propagation behavior of the wrinkles in the grapheme sheets, and has potential applications in graphene materials.

MicroRNAs (miRs) have been frequently reported dysregulating in tumors and playing a crucial role in tumor development and progression. However, the expression of miR-155 and its role in gastric cancer (GC) are still obscure. qRT-PCR was applied to detect miR-155 expression in 60 matched GC samples and four GC cell lines, and the relationship between miR-155 levels and clinicopathological features of GC was analyzed. Next, the effects of miR-155 on GC cell growth were evaluated by gain- and loss-of-function analysis. Finally, the target gene(s) of miR-155 in GC cells were explored. Our results revealed that miR-155 levels were significantly lower in both GC tissues and GC cell lines than in their normal controls, and its expression inversely correlated with tumor size and the pathologic stage. Moreover, our study showed that enforced expression of miR-155 impaired GC cell proliferation, promoted G1 phase arrest and induced apoptosis in vitro. In addition, we identified cyclin D1 as the direct target of miR-155, and knockdown of cyclin D1 partially phenocopied the role of miR-155 in GC cells. Our findings suggest that miR-155 may act as a potential diagnostic marker for early-stage GC and may represent a novel therapeutic target for GC treatment.

The absorption spectra of chromophoric dissolved organic matter (CDOM), along with general physical, chemical and biological variables, were determined in the Bohai Bay, China, in the springs of 2011 and 2012. The absorption coefficient of CDOM at 350 nm ( a 350 ) in surface water ranged from 1.00 to 1.83 m − 1 (mean: 1.35 m − 1 ) in May 2011 and from 0.78 to 1.92 m − 1 (mean: 1.19 m − 1 ) in April 2012. Little surface-bottom difference was observed due to strong vertical mixing. The a 350 was weakly anti-correlated to salinity but positively correlated to chlorophyll a (Chl- a ) concentration. A shoulder over 260–290 nm, suggestive of biogenic molecules, superimposed the overall pattern of exponentially decreasing CDOM absorption with wavelength. The wavelength distribution of the absorption spectral slope manifested a pronounced peak at ca. 300 nm characteristic of algal-derived CDOM. All a 250 / a 365 ratios exceeded 6, corresponding to CDOM molecular weights ( M w ) of less than 1 kDa. Spectroscopically, CDOM in the Bohai Bay differed substantively from that in the Haihe River, the bay's dominant source of land runoff; photobleaching of the riverine CDOM enlarged the difference. Results point to marine biological production being the principal source of CDOM in the Bohai Bay during the sampling seasons. Relatively low runoff, fast dilution, and selective photodegradation are postulated to be among the overarching elements responsible for the lack of terrigenous CDOM signature in the bay water.

A new variable separation in the (G′/G)-expansion algorithm is introduced to obtain the solutions for a nonlinear Broer-Kaup system with variable coefficient. Control based on the variable coefficient is studied for the system. Different variable coefficient functions greatly influence the traveling way, velocity and amplitude of the solutions. Visualized effects are plotted.

Based on the non-traveling wave solution with variable separation for the (1+1)-dimensional Vakhnenko equation, selecting the arbitrary function properly, some exotic loop-like soliton structures are excited.

By selecting proper functions involved in the known non-traveling wave solution with variable separation, a class of fractal soliton structure is investigated for a nonlinear Broer-Kaup system. The fractal soliton structure can hold its similarity in different scales.

The exact soliton solutions are constructed by extending the (G'/G)-expansion method for a nonlinear system. The soliton controls are investigated. The soliton shapes can be under the controls of the parameters in the soliton solutions.

The exact soliton solutions are constructed by extending the (G'/G)-expansion method for the nonlinear (2+1)-dimensional Sasa-Satsuma system. The soliton controls are studied. The soliton can vary in shapes and amplitudes under the control of the parameters in the soliton solutions for the system.

In an intelligent and autonomous multi-agent system, agents often need to work together and achieve common and individual goals under the environment where are limited or scarce resources. How to allocate these resources efficiently is critical in proceeding of cooperation and competition. This paper advances and investigates a mathematically computable approach to solve the problems by introducing auction theory. An agent-based multi-item auction model is studied as negotiation method so as to get some precious resources for buyer agents and allocate them for vendor agents. Some attributes and impacts for the agents about parameters are showed through simulating experience such as buying power, item number required by buyer agent, number of buyer agents, rules of auction and so on. All this is beneficial for the future mechanisms design both in agent-based software engineering and various distributed system, especially Internet-based commerce applications

A class model of rational auction negotiation for multi-agent in which time is related. In a creative way, time parameter is introduced into the process of the rational negotiation in multi-agent system. Buyer agents are able to choose several bidding ways like time-dependent tactics, behavior-dependent tactics. As the result, agents can receive different utilities.