Incorporating preoperative frailty to assist in early prediction of postoperative pneumonia in elderly patients with hip fractures: an externally validated online interpretable machine learning model.

BACKGROUND: This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians. METHODS: Employing clinical data from elderly patients with hip fractures, we derived and externally validated machine learning models for predicting POP. Model derivation utilized a registry from Nanjing First Hospital, and external validation was performed using data from patients at the Fourth Affiliated Hospital of Nanjing Medical University. The derivation cohort was divided into the training set and the testing set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used for feature screening. We compared the performance of models to select the optimized model and introduced SHapley Additive exPlanations (SHAP) to interpret the model. RESULTS: The derivation and validation cohorts comprised 498 and 124 patients, with 14.3% and 10.5% POP rates, respectively. Among these models, Categorical boosting (Catboost) demonstrated superior discrimination ability. AUROC was 0.895 (95%CI: 0.841-0.949) and 0.835 (95%CI: 0.740-0.930) on the training and testing sets, respectively. At external validation, the AUROC amounted to 0.894 (95% CI: 0.821-0.966). The SHAP method showed that CRP, the modified five-item frailty index (mFI-5), and ASA body status were among the top three important predicators of POP. CONCLUSION: Our model's good early prediction ability, combined with the implementation of a network risk calculator based on the Catboost model, was anticipated to effectively distinguish high-risk POP groups, facilitating timely intervention.

The efficacy of different nimodipine administration route for treating subarachnoid hemorrhage: A network meta-analysis.

BACKGROUND: A systematic review and network meta-analysis (NMA) were conducted to explore the optimal administration route of nimodipine for treatment subarachnoid hemorrhage. METHODS: Electronic databases (Pubmed, Embase, Web of Science and Cochrane databases) were systematically searched to identify randomized controlled trials evaluating different administration route of nimodipine (intravenous and enteral) versus placebo for treatment subarachnoid hemorrhage. Outcomes included case fatality at 3 months, poor outcome measured at 3 months (defined as death, vegetative state, or severe disability), incidence of delayed cerebral ischemia (DCI), delayed ischemic neurological deficit. A random-effect Bayesian NMA was conducted for outcomes of interest, and results were presented as odds ratios (ORs) and 95% credible intervals. The NMA was performed using R Software with a GeMTC package. A Bayesian NMA was performed and relative ranking of agents was assessed using surface under the cumulative ranking (SUCRA) probabilities. RESULTS: Nine randomized controlled trials met criteria for inclusion and finally included in this NMA. There was no statistically significant between intravenous and enteral in terms of case fatality, the occurrence of DCI, delayed ischemic neurologic deficit and poor outcomes (P > .05). Both intravenous and enteral could reduce case fatality, the occurrence of DCI, delayed ischemic neurologic deficit and poor outcomes (P < .05). The SUCRA shows that enteral ranked first, intravenous ranked second and placebo ranked the last for case fatality, the occurrence of DCI and poor outcomes. The SUCRA shows that intravenous ranked first, enteral ranked second and placebo ranked the last for delayed ischemic neurologic deficit. CONCLUSIONS: It is possible that both enteral and intravenous nimodipine have comparable effectiveness in preventing poor outcomes, DCI, and delayed ischemic neurological deficits. However, further investigation may be necessary to determine the exact role of intravenous nimodipine in current clinical practice.

Spatio-temporal dynamic change mechanism analysis of traffic conflict risk based on trajectory data.

Analyzing risk dynamic change mechanism under spatio-temporal effects can provide a better understanding of traffic risk, which helps reinforce the safety improvement. Traditionally, spatio-temporal studies based on crash data were mostly conducted to explore crash risk evolution mechanism from a macroscopic perspective. Dynamic change mechanism of short-term risk within a small-scale area deserves exploration, which cannot be captured in macroscopic crash-based studies. It is practical to analyze traffic conflict risk as a surrogate safety measure, which can preferably overcome the limitations of crash-based studies. This study aims to explore the spatio-temporal dynamic change mechanism of conflict risk based on trajectory data. Both conflict frequency and severity are integrated and assessed by applying fuzzy logic theory to develop the whole risk indicator. Trajectories on U.S. Highway101 from NGSIM dataset are utilized and aggregated. A two-step framework is proposed to analyze the risk dynamic change mechanism. The spatial Markov model is firstly applied to explore the transition probability of risk level, and then the panel regression approach is employed to quantify the relationship between spatio-temporal risk and traffic characteristics. Modeling results show that (1) the dynamic change trend of safety states differs under different spatial lag conditions, and it can be well depicted by the spatial Markov model; (2) dynamic spatial panel data modeling method performs better than the model that only considers temporal or spatial dependency. The novel proposed framework promotes a systematic exploration of conflict risk from a mesoscopic perspective, which contributes to assess the real-time road safety more comprehensively.

Convolutional Neural Network Models Combined with Kansei Engineering in Product Design.

This study aims to combine deep learning technology and user perception to propose an efficient design method that can meet the perceptual needs of users and enhance the competitiveness of products in the market. Firstly, the application development of sensory engineering and the research on sensory engineering product design by related technologies are discussed, and the background is provided. Secondly, the Kansei Engineering theory and the algorithmic process of the convolutional neural network (CNN) model are discussed, and theoretical and technical support is provided. A perceptual evaluation system is established for product design based on the CNN model. Finally, taking a picture of the electronic scale as an example, the testing effect of the CNN model in the system is analyzed. The relationship between product design modeling and sensory engineering is explored. The results show that the CNN model improves the "logical depth" of perceptual information of product design and gradually increases the abstraction degree of image information representation. There is a correlation between the user perception impression of electronic weighing scales of different shapes and the design effect of product design shapes. In conclusion, the CNN model and perceptual engineering have in-depth application significance in the image recognition of product design and the perceptual combination of product design modeling. Combined with the CNN model of perceptual engineering, product design is studied. From the perspective of product modeling design, perceptual engineering has been deeply explored and analyzed. In addition, the product perception based on the CNN model can accurately analyze the correlation between product design elements and perceptual engineering and reflect the rationality of the conclusion.

Development of a composite regional vulnerability index and its relationship with the impacts of the COVID-19 pandemic.

The interactions between vulnerability and human activities have largely been regarded in terms of the level of risk they pose, both internally and externally, for certain groups of disadvantaged individuals and regions/areas. However, to date, very few studies have attempted to develop a comprehensive composite regional vulnerability index, in relation to travel, housing, and social deprivation, which can be used to measure vulnerability at an aggregated level in the social sciences. Therefore, this research aims to develop a composite regional vulnerability index with which to examine the combined issues of travel, housing and socio-economic vulnerability (THASV index). It also explores the index's relationship with the impacts of the COVID-19 pandemic, reflecting both social and spatial inequality, using Greater London as a case study, with data analysed at the level of Middle Layer Super Output Areas (MSOAs). The findings show that most of the areas with high levels of composite vulnerability are distributed in Outer London, particularly in suburban areas. In addition, it is also found that there is a spatial correlation between the THASV index and the risk of COVID-19 deaths, which further exacerbates the potential implications of social deprivation and spatial inequality. Moreover, the results of the multiscale geographically weighted regression (MGWR) show that the travel and socio-economic indicators in a neighbouring district and the related vulnerability indices are strongly associated with the risk of dying from COVID-19. In terms of policy implications, the findings can be used to inform sustainable city planning and urban development strategies designed to resolve urban socio-spatial inequalities and the potential related impacts of COVID-19, as well as guiding future policy evaluation of urban structural patterns in relation to vulnerable areas.

Genetic Architecture of Abdominal Fat Deposition Revealed by a Genome-Wide Association Study in the Laying Chicken.

Fat has a high energy density, and excessive fatness has been recognized as a problem for egg production and the welfare of chickens. The identification of a genetic polymorphism controlling fat deposition would be helpful to select against excessive fatness in the laying hen. This study aimed to estimate genomic heritability and identify the genetic architecture of abdominal fat deposition in a population of chickens from a Dongxiang blue-shelled local breed crossbred with the White Leghorn. A genome-wide association study was conducted on abdominal fat percentage, egg production and body weights using a sample of 1534 hens genotyped with a 600 K Chicken Genotyping Array. The analysis yielded a heritability estimate of 0.19 ± 0.04 for abdominal fat percentage; 0.56 ± 0.04 for body weight at 72 weeks; 0.11 ± 0.03 for egg production; and 0.24 ± 0.04 for body weight gain. The genetic correlation of abdominal fat percentage with egg production between 60 and 72 weeks of age was -0.35 ± 0.18. This implies a potential trade-off between these two traits related to the allocation of resources. Strong positive genetic correlations were found between fat deposition and weight traits. A promising locus close to COL12A1 on chromosome 3, associated with abdominal fat percent, was found in the present study. Another region located around HTR2A on chromosome 1, where allele substitution was predicted to be associated with body weight gain, accounted for 2.9% of phenotypic variance. Another region located on chromosome 1, but close to SOX5, was associated with egg production. These results may be used to influence the balanced genetic selection for laying hens.

Histological study of platelet-rich fibrin combined with MTA for direct pulp capping of rabbit teeth / 口腔疾病防治

Objective @# To investigate the outcomes of a novel direct pulp capping agent containing platelet-rich fibrin (PRF) and mineral trioxide aggregate (MTA). @*Methods @# A total of 32 New Zealand rabbits were randomly divided into 4 groups, namely, the PRF+MTA group (P+M group), PRF group (P group), MTA group (M group) and blank control group (BC group), with 8 rabbits per group. Dental pulp exposure and direct pulp capping were performed, and complete crown square sealing was performed on 2 mandibular central incisor teeth of each rabbit. Four rabbits from each group were euthanized after each observation period (7 and 28 days). The experimental teeth were subjected to HE staining. Inflammatory cell infiltration, calcified bridge formation and pulp tissue disorganization were observed and graded. @*Results@#Inflammatory cell infiltration: on the 7th day, group P+M and group M were lighter than group BC (P<0.05); on the 28th day, group P+M was lighter than group P and group BC (P<0.05); group P+M and group M did not significantly differ (P>0.05). Calcified bridge formation: on the 7th and 28th days, group P+M was lighter than group P, group M and group BC (P<0.05); on the 28th day, group M was higher than group BC (P<0.05). Under microscope, the calcified bridge contained cellular components and was surrounded by odontoblast-like cells, sharing a structure resembled osteodentin; dentin tubule-like structure could not be observed in calcified bridge, and the calcified bridge resembled certain points of osteodentin. Pulp tissue disorganization: on the 7th day, group P+M and group M were lighter than group BC (P<0.05); on the 28th day, group P+M was lighter than group P and group BC (P<0.05). group P+M and group M did not significantly differ (P>0.05). @*Conclusion @# The combination of PRF and MTA for direct pulp capping provided light inflammatory cell infiltration, stable pulp status and a strong ability of pulp tissue to form calcified bridge, and the calcified bridge resembled certain points of osteodentin.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets

PurposeEsophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC.MethodsAfter comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1–C4) based on the gene sets of 28 immune cell subpopulations. The discrepancies in prognostic value, clinical features, drug sensitivity, and tumor components between the immunotypes were individually analyzed.ResultsThe ranking of immune infiltration is C1 > C4 > C3 > C2. These subtypes are characterized by high and low expression of immune checkpoint proteins, enrichment and insufficiency of immune-related pathways, and differential distribution of immune cell subgroups. Poorer survival was observed in the C1 subtype, which we hypothesized could be caused by an immunosuppressive cell population. Fortunately, C1’s susceptibility to anti-PD-1 therapy offers hope for patients with poor prognosis in advanced stages. On the other hand, C4 is sensitive to docetaxel, which may offer novel treatment strategies for ESCC in the future. It is worth noting that immunophenotyping is tightly bound to the abundance of stromal components and stem cells, which could explain the tumor immune escape to some extent. Ultimately, determination of hub genes based on the C1 subtypes provides a reference for the discovery of immunotarget drugs against ESCC.ConclusionThe identification of immunophenotypes in our study provides new therapeutic strategies for patients with ESCC.

Soft Magnetic Microrobot Doped with Porous Silica for Stability-Enhanced Multimodal Locomotion in a Nonideal Environment.

As an emerging field of robotics, magnetic-field-controlled soft microrobot has broad application prospects for its flexibility, locomotion diversity, and remote controllability. Magnetic soft microrobots can perform multimodal locomotion under the control of a magnetic field, which may have potential applications in precision medicine. However, previous research studies mainly focus on new locomotion in a relatively ideal environment, lacking exploration on the ability of magnetic microrobot locomotion to resist external disturbances and proceed in a nonideal environment. Here, a porous silica-doped soft magnetic microrobot is constructed for enhanced stability of multimodal locomotion in the nonideal biological environment. Porous silica spheres are doped into a NdFeB-silicone elastomer base, improving adhesion properties and refining the comprehensive mechanical properties of the microrobot. Multimodal locomotions are achieved, and the influence of porous silica doping on the stability of each locomotion in a nonideal environment is explored in depth. Motions in nonideal circumstances such as climbing, loading, current rushing, wind blowing, and obstacle hindering are conducted successfully with porous silica doping. Such a stability-enhanced multimodal locomotion system can be used in biocatalysis and thrombus removal, and its prospect for precision medicine is highlighted by in vivo demonstration of multimodal locomotion with nonideal disturbance.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets.

PURPOSE: Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC. METHODS: After comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1-C4) based on the gene sets of 28 immune cell subpopulations. The discrepancies in prognostic value, clinical features, drug sensitivity, and tumor components between the immunotypes were individually analyzed. RESULTS: The ranking of immune infiltration is C1 > C4 > C3 > C2. These subtypes are characterized by high and low expression of immune checkpoint proteins, enrichment and insufficiency of immune-related pathways, and differential distribution of immune cell subgroups. Poorer survival was observed in the C1 subtype, which we hypothesized could be caused by an immunosuppressive cell population. Fortunately, C1's susceptibility to anti-PD-1 therapy offers hope for patients with poor prognosis in advanced stages. On the other hand, C4 is sensitive to docetaxel, which may offer novel treatment strategies for ESCC in the future. It is worth noting that immunophenotyping is tightly bound to the abundance of stromal components and stem cells, which could explain the tumor immune escape to some extent. Ultimately, determination of hub genes based on the C1 subtypes provides a reference for the discovery of immunotarget drugs against ESCC. CONCLUSION: The identification of immunophenotypes in our study provides new therapeutic strategies for patients with ESCC.

A high-resolution trajectory data driven method for real-time evaluation of traffic safety.

Real-time safety evaluation is essential for developing proactive safety management strategy and improving the overall traffic safety. This paper proposes a method for real-time evaluation of road safety, in which traffic states and conflicts are combined to explore the internal relationship based on high-resolution trajectory data. In order to assess the real-time traffic safety at a lane level, the trajectory data of the HighD dataset from Germany are utilized to collect lane-based dataset. A surrogate safety measure, time-to-collision (TTC) index, is used for the conflict identification. A binary logistic regression model is employed to quantify the relationship between traffic states and conflicts. Moreover, machine learning methods, including support vector machine, decision tree, random forest, and gradient boosting decision tree, are applied for real-time evaluation. A total of 24 models are trained using the selected four classifier algorithms, and random forest achieves the best performance with 0.85 of the overall accuracy. The results show that the conflict risk can be well estimated by the proposed method. The findings of this study contribute to the high-precision evaluation of real-time traffic safety and the development of proactive safety management.

Three-dimensional self-powered DNA walking machine based on catalyzed hairpin assembly energy transfer strategy.

Herein, catalyzed hairpin assembly is implemented as an automated strategy, which can respond in living cells to detect specific target DNA. Using the principle of catalyzed hairpin assembly (CHA), the auxiliary chain connects the fuel and starting chain to form a triple-stranded DNA to complete such a single system. Hundreds of single systems are modified on gold nanoparticles as DNA orbitals. Through the specific recognition of base complementation, the target DNA can realize the automatic walking of the three-dimensional fluorescence machine. This is a novel walking nanomachine that has a simple structure and can independently exist in cells to achieve automatic operation.

Study of pulp blood flow in normal adult first molars detected by laser Doppler flowmetry / 口腔疾病防治

Objective @#To explore the "clinical normal reference range" of pulpal blood flow (PBF) in the physiological state in an effort to provide a reference for clinical diagnosis and treatment.@* Methods@# According to the working principle and operational considerations of laser Doppler flowmetry (LDF), the PBF blood flow value of the first molars of the upper and lower mandibles of normal adults was detected by LDF, and the clinical reference value range under physiological conditions was analyzed and calculated. The differences in PBF values by sex, dental position and location (left and right side, upper and lower jaw) were analyzed. @*Results @#A total of 200 normal adult participants with an average age of (22.76 ± 3.26) years were included. The cohort included 95 males and 105 females, with a total of 800 first molars. Neither the PBF values of the left and right first molars nor the PBF values of the upper and lower first molars in males or females significantly differed (P>0.05). The PBF value for females was higher than that of males. Specifically, the clinical reference PBF values for males and females were (8.56 ± 3.25) PU and (9.51 ± 3.47) PU, respectively.@*Conclusion @#The PBF values of normal adult first molars in healthy subjects were higher in females than in males, and in the PBF values of first molars of the same sex did not significantly differ between the left side and right side or upper and lower jaw; these values could be used as a reference for the selection of control teeth.

The Impact of Load Style Variation on Gait Recognition Based on sEMG Images Using a Convolutional Neural Network.

Surface electromyogram (sEMG) signals are widely employed as a neural control source for lower-limb exoskeletons, in which gait recognition based on sEMG is particularly important. Many scholars have taken measures to improve the accuracy of gait recognition, but several real-time limitations affect its applicability, of which variation in the load styles is obvious. The purposes of this study are to (1) investigate the impact of different load styles on gait recognition; (2) study whether good gait recognition performance can be obtained when a convolutional neural network (CNN) is used to deal with the sEMG image from sparse multichannel sEMG (SMC-sEMG); and (3) explore whether the control system of the lower-limb exoskeleton trained by sEMG from part of the load styles still works efficiently in a real-time environment where multiload styles are required. In addition, we discuss an effective method to improve gait recognition at the levels of the load styles. In our experiment, fifteen able-bodied male graduate students with load (20% of body weight) and using three load styles (SBP = backpack, SCS = cross shoulder, SSS = straight shoulder) were asked to walk uniformly on a treadmill. Each subject performed 50 continuous gait cycles under three speeds (V3 = 3 km/h, V5 = 5 km/h, and V7 = 7 km/h). A CNN was employed to deal with sEMG images from sEMG signals for gait recognition, and back propagation neural networks (BPNNs) and support vector machines (SVMs) were used for comparison by dealing with the same sEMG signal. The results indicated that (1) different load styles had remarkable impact on the gait recognition at three speeds under three load styles (p < 0.001); (2) the performance of gait recognition from the CNN was better than that from the SVM and BPNN at each speed (84.83%, 81.63%, and 83.76% at V3; 93.40%, 88.48%, and 92.36% at V5; and 90.1%, 86.32%, and 85.42% at V7, respectively); and (3) when all the data from three load styles were pooled as testing sets at each speed, more load styles were included in the training set, better performance was obtained, and the statistical analysis suggested that the kinds of load styles included in training set had a significant effect on gait recognition (p = 0.002), from which it can be concluded that the control system of a lower-limb exoskeleton trained by sEMG using only some load styles is not sufficient in a real-time environment.

Long non-coding RNA NHEG1/hsa-miR-665/HMGB1 axis is involved in the regulation of neuroblastoma progression.

Long non-coding (lncRNA) neuroblastoma highly expressed 1 (NHEG1) has been reorganized as a prognostic factor in neuroblastoma (NB), but the molecular mechanisms in the suppression of neuroblastoma remain to be elucidated. In our study, we explored the functional roles of lncRNA NHEG1 in neuroblastoma and the underlying molecular mechanism. We collected NB tumor samples and adjacent normal tissues to compare lncRNA NHEG1 expression. Through bioinformatic target prediction, we selected potential downstream effectors of lncRNA NHEG1 for functional validation in NB cell lines. We observed that lncRNA NHEG1 was significantly upregulated in NB tissues as compared to the normal tissues. In NB tissues, lncRNA NHEG1 expression showed an inverse correlation with hsa-miR-665 (miR-655), but a positive correlation with high mobility group box 1 (HMGB1). In NB cell lines, lncRNA NHEG1 knockdown caused the upregulation of miR-665 and the downregulation of HMGB1. Through a series of functional assays, we further demonstrated that lncRNA Nheg1 knockdown suppressed cell proliferation, migration and invasion of NB cells, which could be rescued by miR-665 inhibitor and HMGB1 overexpression. Together, our data demonstrated that lncRNA NHEG1 serves as a competitive partner to negatively regulate the activity of miR-665, which relieves the inhibition on HMGB1 expression and promotes the aggressive phenotype of neuroblastoma cells. Our study indicates that lncRNA NHEG1/miR-665/HMGB1 axis may play an important role in regulating the aggressiveness and the progression of neuroblastoma.

Effects of Energy-Restricted Feeding during Rearing on the Performance, Uniformity, and Development of Rugao Layer Breeders at the Initiation of the Laying Period.

The aim of this study was to assess the effects of energy-restricted feeding during rearing on the performance, uniformity, and development of layer breeders at the initiation of the laying period. A total of 2400 8-week-old Rugao layer breeders were randomly assigned to one of five groups (480 pullets per group) with eight replicates and were fed one of five diets that were nutritionally equal with the exception of apparent metabolizable energy corrected for nitrogen (AMEn) content (2850, 2750, 2650, 2550, and 2450 kcal AMEn/kg) from 8 to 18 weeks of age. The daily amount of feed was restricted to the absolute quantity of the diet consumed by laying hens fed 2850 kcal AMEn per kg diet ad libitum (control). From 18 to 21 weeks of age, all hens were fed a basal diet ad libitum. The body weight (BW) of the laying pullets decreased linearly with increasing energy restriction (p < 0.001) but recovered within 3 weeks of ad libitum feeding (p = 0.290). A gradual increase in the degree of energy restriction resulted in a gradual decrease in average daily weight gain (ADG) and a gradual increase in the feed conversion ratio (FCR) and energy conversion ratio (ECR) from 8 to 18 weeks of age (p < 0.001, p < 0.001, p = 0.008). In contrast, the ADG and ADFI (p < 0.001, p < 0.001) gradually increased, while the FCR and ECR (p < 0.001, p < 0.001) gradually improved from 18 to 21 weeks of age. From 8 to 21 weeks of age, ECR improved (p = 0.005) with an increasing degree of energy restriction. The energy-restricted feeding for 6 weeks to the end of the trial improved BW uniformity (p < 0.05). The relative length and circumference of tarsus (p < 0.001, p < 0.001), and the relative weights and lengths of the small intestine, duodenum, jejunum, ileum, and caeca increased linearly (p < 0.001, p = 0.012, p < 0.007, p = 0.012, p = 0.040; p < 0.001, p = 0.003, p = 0.032, p = 0.029, p = 0.040) with increasing energy restriction at 18 weeks of age. After switching to ad libitum feeding for 3 weeks, the relative weights and lengths of the small intestine, duodenum, and jejunum of laying pullets increased linearly with increasing energy restriction (p < 0.001, p = 0.016, p = 0.011; p = 0.009, p = 0.028, p = 0.032). In conclusion, moderate energy restriction (85.97%, 2450 vs. 2850 kcal AMEn/kg) from 8 to 18 weeks of age and switching to ad libitum feeding from 18 to 21 weeks of age can be used to improve BW uniformity and stimulate the development of the duodenum and jejunum of native layer breeders at the initiation of the laying period without compromising BW.

Epidemiology and outcomes of bloodstream infections in severe burn patients: a six-year retrospective study.

BACKGROUND: Infection is the leading cause of morbidity and mortality among burn patients, and bloodstream infection (BSI) is the most serious. This study aimed to evaluate the epidemiology and clinical outcomes of BSI in severe burn patients. METHODS: Clinical variables of all patients admitted with severe burns (≥ 20% total body surface area, %TBSA) were analyzed retrospectively from January 2013 to December 2018 at a teaching hospital. The Kaplan-Meier method was utilized for plotting survival curves. Multivariate logistic regression and Cox regression model were also performed. RESULTS: A total of 495 patients were evaluated, of whom 136 (27.5%) had a BSI. The median time from the patients being burned to BSI was 8 days. For BSI onset in these patients, 47.8% (65/136) occurred in the first week. The most frequently isolated causative organism was A. baumannii (22.7%), followed by methicillin-resistant Staphylococcus aureus (18.7%) and K. pneumoniae (18.2%), in patients with BSI. Multivariate logistic regression analysis showed that %TBSA (p = 0.023), mechanical ventilation (p = 0.019), central venous catheter (CVC) (p < 0.001) and hospital length of stay (27d vs 50d, p < 0.001) were independent risk factors associated with BSI. Cox regression model showed that acute kidney injury (HR, 12.26; 95% CI 2.31-64.98; p = 0.003) and septic shock (HR, 4.36; 95% CI 1.16-16.34; p = 0.031) were identified as independent predictors of 30-day mortality of BSI in burn patients. CONCLUSIONS: Multidrug resistant gram-negative bacteria were the main pathogens of BSI in severe burn patients. Accurate evaluation of risk factors for BSI and the mortality of BSI in severe burn patients may improve early appropriate management.

Lipolytic gene DAGLA is targeted by miR-223 in chicken hepatocytes.

miR-223 is an important miRNA. It plays important roles in lipid metabolism by targeting related genes in mammals. It may be related to fatty liver in laying hens and its functions and target genes need further study. Through bioinformatics, we found that 349 genes were predicted as target genes of miR-223. Lipid-related gene DAGLA was among the predicted target genes. Dual-luciferase reporter assays showed that DAGLA was the target gene of miR-223 and the site mutation assays validated the target site of miR-223 in DAGLA. Overexpression of miR-223 in chicken hepatocytes LMH decreased the mRNA and protein expression of DAGLA, while knockdown of miR-223 increased expression of DAGLA in LMH cells, further indicating that miR-223 targets DAGLA and downregulates its expression. Since the target site of miR-223 in chicken DAGLA is not conserved, these findings suggest that miR-223 plays a specific role in chicken liver by regulating expression of target gene DAGLA.

Identification of prognostic biomarkers associated with tumor microenvironment in ceRNA network for esophageal squamous cell carcinoma: a bioinformatics study based on TCGA database.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer in the world with high incidence rate and poor prognosis. Infiltrated immune and stromal cells are vital components of tumor microenvironment (TME) and have a significant impact on the progression of ESCC. The competitive endogenous RNA (ceRNA) hypothesis has been proved important in the molecular biological mechanisms of tumor development. However, there are few studies on the relationship between ceRNA and ESCC TME. METHODS: The proportion of tumor-infiltrating immune cells and the amount of stromal and immune cells in ESCC cases were calculated from The Cancer Genome Atlas database using the CIBERSORT and ESTIMATE calculation methods. After stratified identification of differentially expressed genes, WGCNA and miRNA prediction system were applied to construct ceRNA network. Finally, PPI network and survival analysis were selected to discriminate prognostic signature. And the results were verified in two independent groups from Gene Expression Omnibus and Lanzhou, China. RESULTS: We found that high Stromal and ESTIMATE scores were significantly associated with poor overall survival. Three TME-related key prognostic genes were screened, namely, LCP2, CD86, SLA. And the expression of them was significantly correlated with infiltrated immunocytes. It is also found that ESTIMATE Score and the expression of CD86 were both related to TNM system of ESCC. CONCLUSIONS: We identified three novel TME-related prognostic markers and their lncRNA-miRNA-mRNA pathway in ESCC patients, which may provide new strategies for the targeted therapy.

Decreased expression of m6A demethylase FTO in ovarian aging.

PURPOSE: N6-methyladenosine (m6A) and demethylase fat mass and obesity-associated protein (FTO) were reported to be associated with oocyte development and maturation. But the relationship between FTO and ovarian aging was still unclear. This study was aimed at investigating the FTO expression level and the m6A content during ovarian aging. METHODS: The expression level of FTO and the content of m6A RNA methylation in human follicular fluid (FF), granulosa cells (GCs) and mouse ovary from different age groups were studied by ELISA, WB, qRT-PCR, IHC and m6A Colorimetric. RESULTS: Human FF ELISA quantified that the level of FTO protein decreased with age (P = 0.025). QRT-PCR results showed that the relative expression of FTO in human GCs was lower in the elderly group than in the young group (P = 0.012). FTO mRNA and protein expression levels were lower in the ovary of 32-week-old mice than in 3- and 8-week-old mice (P < 0.05). Immunohistochemistry showed FTO was relatively decreased in 32-week-old mice (P < 0.05). The m6A content in total RNA from old human GCs and ovary from 32-week-old mice was significantly higher compared with the younger ones. CONCLUSIONS: In human FF, GCs and mouse ovary, the expression of FTO decreased while the content of m6A increased with aging. However, the inner mechanism still needs further investigation.