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Meiyu precipitation of Zhejiang province was abnormally less than usual in 2018.During the Meiyu period， mean feature of large-scale circulation in mid-high latitude on 500 hPa exhibited a “trough-ridge-trough” pattern， while in low latitude， western Pacific subtropical High （WPSH） marched eastward and northward.Moreover， the upper-layer westerly jet over East Asia located northward and low-level jet supply south of Zhejiang was not sufficient.All the factors above worked together to form weak Meiyu.Inadequate moisture transport in the first and second ten days of June， inferior convergence of north and south flows， southward-placed westerly jet over East Asia， stronger South China Sea summer monsoon （SCSSM）， and weaker Indian monsoon acted jointly to cause a late Zhejiang Meiyu.There were three rainfall processes （process I， process II， and process III） and a time with few precipitation during the entire Meiyu stage.The formation of process I and II could be attributed to meeting of northward and southward air flows， while the essence of process III was typhoon-induced convection.The spatiotemporal variation of large-scale circulation associated with different processes was investigated comprehensively， and the result indicated that compared to process I， precipitation intensity of process II was very limited because of the forceless cold air invasion， more powerful SCSSM， and feeble transport of southwest moisture.Furthermore， the impact of precursory oceanic， atmospheric， and land signals on Meiyu was analyzed， and found that the primary climate characteristics were positive Niño index and negative North Pacific sea surface temperature （SST） anomaly in winter and spring， warm SST over southwest Indian Ocean in winter， decreased sea ice for the Kara-Barents Sea in spring， and Southern Annular Mode and Arctic Oscillation in the positive and negative phases respectively during April-May.Based on the monitoring time-series of Zhejiang Meiyu， the stable or strengthened climatic factors from winter to spring were extracted with two indices of correlation coefficient and ratio of the same sign， and moreover， winter and spring Meiyu prediction model were constructed using three methods of multivariable linear regression， multi-factors composite assess， and combined diagnosis.Generally speaking， all the linear statistical models were able to predict Meiyu precipitation anomaly over Zhejiang province well， especially for the negative anomaly cases.

Abstract Introduction Declining physical activity among university students has become a concern, with increasingly poor dietary behaviors and other unfavorable factors having an impact on the occurrence of psychological symptoms. Previous studies have analyzed the association between moderate-to-vigorous physical activity (MVPA) and psychological symptoms, but few studies have investigated the association between soy product consumption and these symptoms. In addition, the associations between physical activity and soy product consumption with psychological symptoms have not been investigated. Methods In this study, 7267 university students from different regions of China were surveyed regarding physical activity, soy product consumption, and psychological symptoms. Binary logistic regression was used to analyze the associations among MVPA, soy product consumption, and psychological symptoms. A generalized linear model (GLM) was applied to further analyze the associations of MVPA and soy product consumption with psychological symptoms in this population. Results The detection rate of psychological symptoms among Chinese university students was 17.9%, with the rate among female students (18.9%) higher than that among male students (16.6%). The proportion of university students with MVPA 60 min/d was 76.1%, 19.3%, and 4.6%, respectively, and the proportion with soy product consumption ≤ 2 times/wk, 3–5 times/wk, and ≥ 5 times/wk was 25.8%, 42.4%, and 31.7%, respectively. The GLM showed that compared with university students who had MVPA 60 min/d and soy product consumption ≥ 6 times/week (OR = 0.198, 95% CI: 0.100–0.393, P 60 min/d and soy product consumption 3–5 times/week (OR = 0.221, 95% CI: 0.102–0.479, P

Porous asphalt (PA) have attracted considerable interest due to their functional advantages such as significant water permeability and noise attenuation properties. Nevertheless, its vulnerability to damage significantly hinders its widespread application. Therefore, this paper aims to investigate the damage characteristics of PA's high- and low-temperature performance under the coupled effects of moisture and temperature. Firstly, Hamburg Wheel-Tracking Test (HWTT) and three-point bending tests were conducted on PA under different coupling conditions. Subsequently, its damage characteristics were analyzed using the three-stage permanent deformation model, logistic model, and two-way analysis of variance (ANOVA) method. The findings indicate that under dry conditions, PA-13 exhibits a linear decrease in rutting resistance within the temperature range of 40–60 °C, followed by a significant decrease at 70 °C. During immersion in water, PA-13 undergoes a second and third-stage rutting evolution process, with an accelerated creep rate observed at 70°C. High temperatures exacerbate the viscoelastic damage of PA-13, while multi-field coupling promotes the simultaneous occurrence of viscoelastic damage and stripping damage. Furthemore, the results of the two-way ANOVA indicate that moisture has a more significant impact on high-temperature performance damage. In addition, in a dry environment, the low-temperature crack resistance of PA-13 deteriorates with decreasing temperature, but there is little difference at −20 °C and −30 °C. This is attributed to PA-13 exhibiting flexible cracking at 0 °C and −10 °C, while undergoing brittle cracking at −20 °C and −30 °C. Additionally, the coupled effect of temperature and moisture reduces the damage tolerance of PA-13 and accelerates its cracking process. The results of the two-way ANOVA indicate that both low temperature and treatment methods have a statistically significant impact on low-temperature performance, with treatment methods having a higher degree of influence. The findings of this paper contribute to an in-depth understanding of the damage mechanism of PA-13.

Breast cancer is rare in men and is managed using strategies similar to those for breast cancer in women. This study retrospectively analyzed the clinicopathological features, treatment, and survival of male breast cancer (MBC). A total of 66 patients with MBC admitted into Xijing Hospital from August 2006 to March 2024 were reviewed. Data were collected from patients’ hospital records and breast cancer database of Xijing Hospital. The incidence of MBC tended to increase from 2018, with affected individuals being older than those with female breast cancer (FBC). The most common histological type of MBC was invasive carcinoma, with positive hormone receptor status. A total of 62 (93.9%) patients with MBC underwent modified radical mastectomy. Chemotherapy was administered to 39 (59.1%) patients, while endocrine therapy was received by 14 patients (21.2%) and radiotherapy by nine patients (13.6%). Survival analysis indicated that the median overall survival (OS) of patients with MBC was 46.7 months (0.9–184.8 months). As of the latest data, 58 patients (87.9%) with MBC are alive. Factors significantly associated with survival included age (χ 2 = 3.856, p = .050), estrogen receptor (χ 2 = 10.427, p = .005), molecular types (χ 2 = 10.641, p = .031), P63 (χ 2 = 2.631, p

ObjectiveAlthough the impact of the variants of COVID-19 on the general population is diminishing, there is still a certain mortality rate for severe and critically ill patients, especially for the elderly with comorbidities. The present study investigated whether the D-dimer to albumin ratio (DAR) can predict the severity of illness and mortality in COVID-19 patients.MethodsA total of 1,993 patients with COVID-19 were retrospectively reviewed and the association of DAR with severe or critical illness or death during hospitalization was analyzed. The area under the ROC curve was used to screen the best indicators, Chi-square test, rank sum test, and univariate and multivariate binary logistic regression analysis were used to calculate the mean value of difference and adjusted odds ratio (aORs) with their 95% CI, and finally, survival was analyzed using Kaplan–Meier (KM) curves.ResultsAmong 1,993 patients with COVID-19, 13.4% were severely ill, and the mortality rate was 2.3%. The area under the curve (AUC) using DAR to predict severe and critically ill patients was higher than that using other parameters. The best cut-off value of DAR was 21 in the ROC with a sensitivity of 83.1% and a specificity of 68.7%. After adjusting age, gender, comorbidities, and treatment, the binary logistic regression analysis showed that elevated DAR was an independent risk factor for severely ill and mortality of COVID-19 patients. The KM curve suggested that patients with a higher DAR was associated with worse survival. The negative predictive value of DAR (21) for adverse prognosis and death was 95.98 and 99.84%, respectively, with a sensitivity of 80.9 and 95.65%, respectively.ConclusionThe DAR may be an important predictor for severe illness and mortality in COVID-19 patients.

Abstract Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844 bounding boxes. On the basis of this dataset, a deep-learning-based framework was developed to identify and localize 14 common abnormalities and calculate the cardiothoracic ratio (CTR) simultaneously. The mean average precision values obtained by the model for 14 abnormalities reached 0.572-0.631 with an intersection-over-union threshold of 0.5, and the intraclass correlation coefficient of the CTR algorithm exceeded 0.95 on the held-out, multicentre and prospective test datasets. This framework shows an excellent performance, good generalization ability and strong clinical applicability, which is superior to senior radiologists and suitable for routine clinical settings.

This study aimed to convert wastes generated during the extraction of oil from Camellia oleifera seeds, including the fruit shell (COFS) and seed cake (COSC), into fermentable feedstocks using pretreatment and enzymatic hydrolysis processes. The application of a green acid catalyst in the thermochemical pretreatment of the COFS and COSC mixture yielded the highest sugar of 28 g/L. Solid-state fermentation (SSF) was conducted on-site using various waste biomass substrates to produce enzymes for the saccharification process. This study found that COFS was the ideal substrate for generating SSF enzymes capable of breaking down lignocellulosic biomass. A novel enzymatic hydrolysis strategy was developed to minimize water consumption and enhance substrate utilization efficiency. By fine-tuning the enzymatic hydrolysis process, an additional sugar of 20.58 g/L was achieved using thermochemically pretreated solid residues and SSF enzymes. Standard techniques were used to analyze the raw materials, residual solids, and hydrolysates to assess the efficiency of each processing step. In general, the use of SSF enzymes and green pretreatment methods, reduction of water consumption in the process, and implementation of an efficient biomass utilization approach, enhance the overall efficiency and eco-friendliness of this study.

Abstract Currently, there are three main shortcomings in meteorological drought indices: first, they rely on historical climate probability functions; second, the timescale used in calculations has a certain degree of subjectivity; third, the same index value may correspond to vastly different levels of actual drought in different climate types of regions. The purpose of this article is to establish a meteorological drought index that does not rely on historical meteorological element probability functions. Through theoretical derivation, four drought‐level maintenance lines are established on the cumulative precipitation‐cumulative water surface evaporation coordinate plane, and the coordinate quadrant is divided into five drought‐level areas. Through forward daily rolling accumulation, the maximum distance point is selected from the dynamically changing coordinate points to determine the corresponding cumulative precipitation and cumulative evaporation. The meteorological drought index is established by the distance from the selected coordinate point to each drought‐level maintenance line. Using daily precipitation and evaporation data from meteorological observation stations, the index is calculated based on the established meteorological drought index model, and compared with actual drought evolution and drought disaster records. The results show that the index can capture the development of drought well, and its changes are very consistent with drought disaster records. The index is of great significance for drought monitoring or assessment, and can provide guidance for water resource allocation, crop layout, and urban planning. Furthermore, it can also provide a way of thinking that does not rely on historical element probabilities for future drought research.

BackgroundAcute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpretability. ObjectiveThis study aims to establish an explainable deep learning model to provide individualized in-hospital mortality prediction and risk factor assessment for patients with AMI. MethodsIn this retrospective multicenter study, we used data for consecutive patients hospitalized with AMI from the Chongqing University Central Hospital between July 2016 and December 2022 and the Electronic Intensive Care Unit Collaborative Research Database. These patients were randomly divided into training (7668/10,955, 70%) and internal test (3287/10,955, 30%) data sets. In addition, data of patients with AMI from the Medical Information Mart for Intensive Care database were used for external validation. Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to explain the model with the highest area under the receiver operating characteristic curve in both the internal test and external validation data sets to quantify and visualize the features that drive predictions. ResultsA total of 10,955 patients with AMI who were admitted to Chongqing University Central Hospital or included in the Electronic Intensive Care Unit Collaborative Research Database were randomly divided into a training data set of 7668 (70%) patients and an internal test data set of 3287 (30%) patients. A total of 9355 patients from the Medical Information Mart for Intensive Care database were included for independent external validation. In-hospital mortality occurred in 8.74% (670/7668), 8.73% (287/3287), and 9.12% (853/9355) of the patients in the training, internal test, and external validation cohorts, respectively. The Self-Attention and Intersample Attention Transformer model performed best in both the internal test data set and the external validation data set among the 9 prediction models, with the highest area under the receiver operating characteristic curve of 0.86 (95% CI 0.84-0.88) and 0.85 (95% CI 0.84-0.87), respectively. Older age, high heart rate, and low body temperature were the 3 most important predictors of increased mortality, according to the explanations of the Self-Attention and Intersample Attention Transformer model. ConclusionsThe explainable deep learning model that we developed could provide estimates of mortality and visual contribution of the features to the prediction for a patient with AMI. The explanations suggested that older age, unstable vital signs, and metabolic disorders may increase the risk of mortality in patients with AMI.

Abstract Currently, the precise and detailed anatomical data of the normal uterus, especially the myometrium thickness in various parts of the uterus, are lacking. This study aims to provide normal references for uterine size in healthy reproductive-aged Chinese women to facilitate the application of hysteroscopic surgery. A total of 298 women of reproductive age with normal uterine were included. Parity was significantly correlated with uterine measurements (P 0.05). There was a positive correlation between body mass index (BMI) and extrauterine measurements as well as myometrial thickness (P

Currently, few studies explore the internal phases of styrene-butadiene-styrene (SBS) modified bitumen at the nanoscale, though the surface phases of SBS modified bitumen have been deeply understood through a lot of research. The present study uses the atomic force microscopy (AFM) peak force quantitative nanomechanical mode (PF-QNM) to investigate the nanomechanical properties of the interior of linear SBS modified bitumen and corresponding mastics at the nanoscale. Firstly, the suitable experimental methods for the interior of bitumen and mastics are explored. Then, the phase relationship between surfaces and interiors of linear SBS modified bitumen is determined by analyzing nanomechanical properties. On this basis, in comparison with the internal phases of base bitumen, the effect of modifiers on phases is deeply investigated. Finally, the internal phases of linear SBS modified bituminous mastics are further investigated. The results reveal that the interior of linear SBS modified bitumen only has two phases, which form in a manner like periphase and paraphase on the surface. In contrast to base bitumen, linear SBS modified bitumen does not create new phases and change the properties of original phases in the interior, but affects the proportion of A-phase and B-phase and presents the homogenization. Furthermore, due to the influence of preparation methods, only the bitumen area away from the fillers can be imaged by AFM PF-QNM. It can be found that the addition of mineral fillers also slightly changes the internal phase distribution of linear SBS modified bitumen, while the effect is less than that of fillers on base bitumen.

This work investigated the aging effects on the rheological properties of high viscosity modified asphalt (HVMA). First, the high- and low-temperature rheological properties were measured by a dynamic shear rheometer and a bending beam rheometer, respectively. The aging mechanism was then tested using an Fourier transform infrared spectroscopy and a scanning electron microscope. Besides, a study was performed to compare the aging effects on the rheological properties of HVMA, crumb rubber modified asphalt (CRMA), and neat asphalt (SK-90). The experimental results showed that the effects of the long-term aging on HVMA exceeded those of short-term aging. The complex shear modulus of the HVMA was improved by the aging in the whole frequency range. The complex shear modulus of the HVMA after the long-term aging was larger than after the short-term aging. Thus, the aging improved the high-temperature viscoelastic performance of HVMA. With a decrease in temperature from −12 °C to −24 °C, the low-temperature viscoelastic performance of HVMA decreased since its stiffness modulus and low continuous grading temperature increase. Both of the short- and long-term aging of HVMA were caused by an oxidation reaction, while modifier swelling also happened after long-term aging. Compared to CRMA and SK-90, aging had a limited influence on the high- and low-temperature rheological properties of HVMA.

ABSTRACT Among various environmental stresses, the depletion of inorganic phosphate, which is an important signaling molecule that modulates virulence production, is notable. In our previous study, we demonstrated that lapA, encoding alkaline phosphatase, plays a key role in Pseudomonas aeruginosa biofilm formation in porcine skin explants, an ex vivo chronic wound model. However, the mechanism by which lapA participates in the virulence and biofilm formation of P. aeruginosa remains unclear. In the present study, the lapA deletion mutant was constructed in P. aeruginosa PAO1, and the phenotypic characterization was assessed. Our data demonstrated that phosphate depletion stress significantly enhanced elastase activity, hemolysis, rhamnolipid production, swarming and swimming motilities, and 3-oxo-C12-homoserine lactone (HSL) production in P. aeruginosa. Moreover, phosphate starvation evidently induced the virulence of P. aeruginosa in Caenorhabditis elegans (C. elegans) through fast-kill and slow-kill infections. Deletion of the lapA gene led to broad phenotypic changes, including reduced elastase activity, swimming motility, C4-HSL, and 3-oxo-C12-HSL production, as well as increased chitinase activity and rhamnolipid production under phosphate depletion stress, which was unrelated to C4-HSL. Deletion of the lapA gene also significantly inhibited PAO1 biofilm formation in porcine skin explants by reducing the expression levels of las and rhl quorum sensing systems and extracellular polymeric substance synthesis. Finally, lapA deletion also reduced the virulence of PAO1 in C. elegans in fast-kill and slow-kill infection assays. Thus, the findings suggest that targeting lapA can help control biofilm formation and reduce virulence in nonhealing-infected wounds, where P. aeruginosa is a persistent problem. IMPORTANCE Our previous study demonstrated that the expression of lapA was induced under phosphate depletion conditions, but its roles in virulence and biofilm formation by Pseudomonas aeruginosa remain largely unknown. This study presents a systematic investigation of the roles of lapA in virulence induction and biofilm formation by constructing a lapA-deficient strain with P. aeruginosa PAO1. The results showed that deletion of the lapA gene evidently reduced elastase activity, swimming motility, C4-HSL, and 3-oxo-C12-HSL production, and increased rhamnolipid production under phosphate depletion stress. Moreover, lapA gene deletion inhibited PAO1 biofilm formation in porcine skin explants by reducing the expression levels of las and rhl quorum sensing systems and extracellular polymeric substance synthesis. Finally, lapA gene deletion also reduced the virulence of PAO1 in Caenorhabditis elegans in fast-kill and slow-kill infection assays. This study provides insights into the roles of lapA in modulating P. aeruginosa virulence and biofilm formation under phosphate depletion stress.

IntroductionA large-sample study focusing on VIN lesions of a more precise thickness is needed to help guide clinical treatment. This study aimed to investigate the depth of vulvar intraepithelial neoplasia (VIN) and involved skin appendages to provide evidence for laser surgery.MethodsThe study retrospectively enrolled and analyzed the clinical characteristics of VIN patients in the obstetrics and gynecology department of a university hospital between January 1, 2019 and December 30, 2021. The study further explored the thickness of epithelium and skin appendages of 285 women with low-grade VIN (VIN1) and 285 women with high-grade VIN (VIN2/3).ResultsThe study included 1,139 (80%) VIN1 and 335 (20%) VIN2/3 cases. The VIN1 and VIN2/3 groups showed a significant difference in human papillomavirus infection (P

RationaleCOVID-19 pandemic has imposed tremendous stress and burden on the economy and society worldwide. There is an urgent demand to find a new model to estimate the deterioration of patients inflicted by Omicron variants.ObjectiveThis study aims to develop a model to predict the deterioration of elderly patients inflicted by Omicron Sub-variant BA.2.MethodsCOVID-19 patients were randomly divided into the training and the validation cohorts. Both Lasso and Logistic regression analyses were performed to identify prediction factors, which were then selected to build a deterioration model in the training cohort. This model was validated in the validation cohort.Measurements and main resultsThe deterioration model of COVID-19 was constructed with five indices, including C-reactive protein, neutrophil count/lymphocyte count (NLR), albumin/globulin ratio (A/G), international normalized ratio (INR), and blood urea nitrogen (BUN). The area under the ROC curve (AUC) showed that this model displayed a high accuracy in predicting deterioration, which was 0.85 in the training cohort and 0.85 in the validation cohort. The nomogram provided an easy way to calculate the possibility of deterioration, and the decision curve analysis (DCA) and clinical impact curve analysis (CICA)showed good clinical net profit using this model.ConclusionThe model we constructed can identify and predict the risk of deterioration (requirement for ventilatory support or death) in elderly patients and it is clinically practical, which will facilitate medical decision making and allocating medical resources to those with critical conditions.

ObjectiveThe aim of the present study is to assess the utility of C-reactive protein to Lymphocyte Ratio (CLR) in predicting short-term clinical outcomes of patients infected by SARS-CoV-2 BA.2.2.MethodsThis retrospective study was performed on 1,219 patients with laboratory-confirmed SARS-CoV-2 BA.2.2 to determine the association of CLR with short-term clinical outcomes. Independent Chi square test, Rank sum test, and binary logistic regression analysis were performed to calculate mean differences and adjusted odds ratios (aORs) with their 95% CI, respectively.ResultsOver 8% of patients admitted due to SARS-CoV-2 BA.2.2. were critically ill. The best cut-off value of CLR was 21.25 in the ROC with a sensitivity of 72.3% and a specificity of 86%. After adjusting age, gender, and comorbidities, binary logistic regression analysis showed that elevated CLR was an independent risk factor for poor short-term clinical outcomes of COVID-19 patients.ConclusionC-reactive protein to Lymphocyte Ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 inflicted patients.

Litsea cubeba is a characteristic woody oil resource in Hunan. As a solid waste of woody oil resources, Litsea cubeba kernels are rich in Litsea cubeba kernel oil with a carbon chain length of C10–12 fatty acid. In this work, aliphatic hydroxamic acids (AHAs) with carbon chain lengths of C10–12 were prepared from Litsea cubeba kernel oil via methylation and hydroximation reactions. The adsorption and hydrophobicity mechanism of AHA towards wolframite was explored by contact angle, zeta potential, Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). The flotation results demonstrated that AHA was a superior collector than the traditional collector such as benzoyl hydroxamic acid (BHA). Zeta potential and contact angle results have shown that AHA was adsorbed on the surface of the Fe(III)-activated wolframite in its anionic form, which significantly improved the surface hydrophobicity of wolframite. FTIR and XPS revealed that AHA was chemically adsorbed on the surface of Fe(III)-activated wolframite in the form of a five-member ring, which made the hydrophobic chain reach into the solution, come in contact with bubbles, and achieve flotation separation.

ObjectiveBy identifying the clinicopathological characteristics and prognostic influences of patients with triple-positive breast cancer (TPBC) at Xijing Hospital in China compared with those in the United States, this study aims to construct a nomogram model to forecast the overall survival rate (OS) of TPBC patients.MethodThe Surveillance, Epidemiology, and End Results (SEER) database was used to screen 5769 patients as the training cohort, and 191 patients from Xijing Hospital were used as the validation cohort. Cox risk-proportional model was applied to select variables and the nomogram model was constructed based on the training cohort. The performance of the model was evaluated by calculating the C-index and generating calibration plots in the training and validation cohorts.ResultsCox multifactorial analysis showed that age, chemotherapy, radiotherapy, M-stage, T-stage, N-stage, and the mode of surgery were all independent risk factors for the prognosis of TPBC patients (all P

Abstract In order to solve the problem of uncontrollable cutting depth and the rough incision edge of the cornea with manual trephine in lamellar keratoplasty, an ultrasonic‐assisted corneal trephination method has been proposed for the first time in accordance with the advantage of ultrasonic vibration cutting, and the corresponding robotic system has been designed and researched. According to the traditional process of lamellar keratoplasty, the requirements of the surgical robotic system were first proposed. On this basis, the robotic system was designed and its schematic diagram was introduced. Second, the key components of the robotic body such as the eccentric adjusting mechanism and the end‐effector of ultrasonic scalpel were illustrated, which can realise corneal trephination of different incision diameters without scalpel replacement. Then the operation flow chart of a robot‐assisted lamellar keratoplasty was put forward. Finally, the preliminary verified experiments were performed using a grape and a porcine eyeball, respectively, in vitro with the prototype system. The results show that the robotic system can basically satisfy the operation requirements of lamellar keratoplasty. Owing to the less cutting force and smoother corneal incision edge of ultrasonic‐assisted lamellar keratoplasty compared with manual trephine, it was proved to be more feasible and superior.

The blending behavior of aged and virgin asphalt binder is one of the most critical problems in the mixing process of hot recycling. To accurately measure the participation degree of aged asphalt and optimize the mixing process of hot recycling, a series of laboratory tests were designed by using magnetite aggregate and thin-layer chromatography with flame ionization detection (TLC-FID) for the first time. In this study, 24 different lab-mixing conditions were deliberately adopted to investigate the impact on the DoB of aged and virgin asphalt binders, including mixing amount of RAP, mixing amount of rejuvenating agent, mixing time, mixing temperature, mixing orders and the thickness of asphalt film. The results indicated that the aged and virgin asphalt cannot be completely blended in the mixing process and DoB is only about 40–60 % in general. The DoB decreases with the increase of asphalt film thickness and it decreases by 30 % when asphalt film thickness is 9 µm. DOB increased with the content of RAP and rejuvenating agent up to 70 % which same as mixing sequence. Although the mixing time and temperature can promote DOB, the mixing time and temperature should be controlled within 240 s and 170 °C, otherwise the accuracy of DOB will be affected.

PurposeCuprotosis is a newly discovered form of non-apoptotic regulated cell death and is characterized by copper-dependent and associated with mitochondrial respiration. However, the prognostic significance and function of cuprotosis-related genes (CRGs) in hepatocellular carcinoma (HCC) are unknown. This study aims to develop cuprotosis-mediated patterns-related gene (CMPRG) prediction models for the prognosis of patients with HCC, exploring the functional underlying the CRGs on the influence of tumor microenvironment (TME) features.Experimental designThis study obtained transcriptome profiling and the corresponding clinical information from the TCGA and GEO databases. Besides, the Cox regression model with LASSO was implemented to build a multi-gene signature, which was then validated in an internal validation set and two external validation sets through Kaplan-Meier, DCA, and ROC analyses.ResultsAccording to the LASSO analysis, we screened out a cuprotosis-mediated pattern 5-gene combination (including PBK; MMP1; GNAZ; GPC1 and AKR1D1). A nomogram was constructed for the presentation of the final model. The ROC curve assessed the model’s predictive ability, which resulted in an area under the curve (AUC) values ranging from 0.604 to 0.787 underwent internal and two external validation sets. Meanwhile, the risk score divided the patients into two groups of high and low risk, and the survival rate of high-risk patients was significantly lower than that of low-risk patients (P

Based on ship navigational requirements and safety in foggy conditions and with a particular emphasis on avoiding ship collisions and improving navigational abilities, we constructed a fog navigation dataset along with a new method for enhancing foggy images and perceived visibility using a discriminant deep learning architecture and the EfficientNet neural network by replacing the SE module and incorporating a convolution block attention module and focal loss function. The accuracy of our model exceeded 95%, which meets the needs of an intelligent ship navigation environment in foggy conditions. As part of our research, we also determined the best enhancement algorithm for each type of fog according to its classification.

Abstract Background We developed a computational model integrating clinical data and imaging features extracted from contrast-enhanced computed tomography (CECT) images, to predict lymph node (LN) metastasis in patients with pancreatic ductal adenocarcinoma (PDAC). Methods This retrospective study included 159 patients with PDAC (118 in the primary cohort and 41 in the validation cohort) who underwent preoperative contrast-enhanced computed tomography examination between 2012 and 2015. All patients underwent surgery and lymph node status was determined. A total of 2041 radiomics features were extracted from venous phase images in the primary cohort, and optimal features were extracted to construct a radiomics signature. A combined prediction model was built by incorporating the radiomics signature and clinical characteristics selected by using multivariable logistic regression. Clinical prediction models were generated and used to evaluate both cohorts. Results Fifteen features were selected for constructing the radiomics signature based on the primary cohort. The combined prediction model for identifying preoperative lymph node metastasis reached a better discrimination power than the clinical prediction model, with an area under the curve of 0.944 vs. 0.666 in the primary cohort, and 0.912 vs. 0.713 in the validation cohort. Conclusions This pilot study demonstrated that a noninvasive radiomics signature extracted from contrast-enhanced computed tomography imaging can be conveniently used for preoperative prediction of lymph node metastasis in patients with PDAC.

Hyperspectral compressed sensing (HCS) is a new imaging method that effectively reduces the power consumption of data acquisition. In this article, we present a novel HCS algorithm by incorporating spatial-spectral hybrid compressed sensing, followed by a reconstruction based on spectral unmixing. At the sampling stage, the measurements are acquired by a spatial-spectral hybrid compressive sampling scheme to preserve the necessary information for the following spectral unmixing, where spatial compressive sampling mainly retains the endmember information, and spectral compressive sampling mainly retains the abundance information. Due to the limitations of the traditional linear mixed model, an improved mixed model is proposed for HCS reconstruction, which considers spectral variability, nonlinear mixing, and other factors. At the reconstruction stage, based on the improved mixed model, semi-nonnegative matrix factorization is introduced to realize spectral unmixing on the measurements to achieve the final reconstruction by using an alternate iteration manner. The proposed algorithm is tested on real hyperspectral data, and the selection of parameters is fully analyzed. Experimental results demonstrate that the proposed algorithm can significantly outperform state-of-the-art HCS algorithms in terms of reconstruction performance.

The efficacy and safety of early renal replacement therapy (eRRT) for critically ill patients with acute kidney injury (AKI) remain controversial. Therefore, the purpose of our study was to perform an up-to-date meta-analysis with the trial sequential analysis (TSA) of randomized controlled trials (RCTs) to evaluate the therapeutic effect of eRRT on patients in an intensive care unit (ICU). We extensively searched MEDLINE, EMBASE, LILACS, the Cochrane Central Register of Controlled Trials and ClinicalTrials.gov, Gray Literature Report, and Bielefeld Academic Search Engine (BASE), and conducted an updated search on December 27, 2021. The included studies were RCTs, which compared the efficacy and safety of eRRT and delayed renal replacement therapy (dRRT) on critically ill patients with AKI. We adopted TSA and sensitivity analysis to strengthen the robustness of the results. About 12 RCTs with a total of 5,423 participants were included. Patients receiving eRRT and dRRT had the similar rate of all-cause mortality at day 28 (38.7% vs. 38.9%) [risk ratio (RR), 1.00; 95%CI, 0.93–1.07, p = 0.93, I2 = 0%, p = 0.93]. A sensitivity and subgroup analysis produced similar results for the primary outcome. TSA showed that the required information size was 5,034, and the cumulative Z-curve crossed trial sequential monitoring boundaries for futility. Patients receiving eRRT had a higher rate of renal replacement therapy (RRT) (RR, 1.50, 95% CI: 1.28–1.76, p < 0.00001, I2 = 96%), and experienced more adverse events comparing to those receiving dRRT (RR: 1.41, 95% CI: 1.22–1.63, p < 0.0001, heterogeneity not applied). The most remarkable and important experimental finding is that, to our knowledge, the current meta-analysis included the largest sample size from the RCTs, which were published in the past 10 years to date, show that eRRT had no significant survival benefit for ill patients with AKI compared with dRRT and TSA indicating that no more studies were needed to confirm it.Trial RegistrationINPLASY, INPLASY2020120030. Registered 04 December 2020.

According to the advantages of ultrasonic vibration cutting, an ultrasound-assisted corneal trepanation robotic system is developed to improve the accuracy of corneal trephination depth and corneal incision quality in corneal trephination operations. Firstly, we analyzed the reasons for the difficulty in controlling the depth of trephination in corneal transplantations from the perspective of the biomechanical properties of the cornea. Based on the advantages of ultrasonic vibration cutting, we introduced an ultrasonic-vibration-assisted cutting method for corneal trephination and analyzed the cutting mechanism. Secondly, we described the surgical demands of corneal trephination and listed the design requirements of a robotic system. Thirdly, we introduced the design details of said system, including the system’s overall structure, the ultrasound-assisted end effector, the key mechanisms of the robotic system, and the human–machine interaction interface. We designed the end effector based on ultrasonic vibration cutting and its eccentric adjustment system in an innovative way. Additionally, we then presented a procedure for robot-assisted corneal trephination. Finally, we performed several cutting experiments on grapes and porcine eyeballs in vitro. The results show that, compared with manual trephine, ultrasound-assisted corneal trephination has a better operation effect on the accuracy of corneal trephination depth and corneal incision quality.

Pancreatic adenocarcinoma (PAAD) is characterized by high malignancy, frequent metastasis, and recurrence with an unfavorable prognosis. This study is aimed at constructing a prognostic model for tumor-infiltrating immune cells and a competing endogenous RNA (ceRNA) network in PAAD and analyzing susceptibilities of chemotherapy and immunotherapy of PAAD. Gene expression profiles and clinical information of PAAD were downloaded from The Cancer Genome Atlas (TCGA) database and divided into the tumor group and the normal group. A total of five PAAD survival-related key genes in the ceRNA network and three survival-related immune infiltrating cells were uncovered, and two survival risk models and nomograms were constructed. The efficiency and performance of the two models were verified using multi-index area under the curve analysis at different time points, decision curve analysis, and calibration curves. Co-expression analysis showed that LRRC1, MIR600HG, and RNF166 in the ceRNA network and tumor-infiltrating immune cells including CD8 T cells and M1 macrophages were likely related to the PAAD prognosis, and the expression of key ceRNA-related genes was experimently validated in tissues and cell lines by RT-qPCR. Patients with low risk scores for key genes in the ceRNA network displayed a positive response to anti-programmed death-1 (PD-1) treatment and greater sensitivity to chemotherapeutic drugs such as docetaxel, lapatinib, and paclitaxel. More importantly, our results suggested that the IC50 values of gemcitabine in PAAD were not significantly different between the high and low risk groups. The expression levels of immune checkpoints were significantly different in the high-risk and low-risk groups. The prognostic model, nomogram, and drug analysis may provide an essential reference for PAAD patient management in the clinic.

Abstract Background To determine the relevance of the single or combination mutations of BRAF V600E, TERT, and NRAS genes and the clinicopathologic relationship in papillary thyroid cancer (PTC). Methods Patients with PTC were enrolled into the study between February 2018 and April 2019. Based on the number of mutant genes, we classified the participants into single BRAF V600E mutation group, double mutations group and no mutation group. Single factor and multiple logistic regression analyses were applied to explore the independent factors. Review Manager 5.3 was used for meta-analysis to review the clinical efficacy of gene co-mutations. Results Finally, 483 patients were enrolled into the study and 419 (86.7%) of them harbored BRAF V600E mutation. TERT or NRAS mutation was likely to coexist with BRAF V600E mutation in PTC. BRAF V600E and NRAS promoter co-mutations was identified in 6 patients, with a prevalence of 1.2%. Prevalence of BRAF V600E and TERT coexistence in PTC was 2.1%. Significant differences were found among age, pathology, multifocality, bilateral lesions, lymph node metastasis, and 131I radiotherapy, P

Hepatocellular carcinoma (HCC) is the most common gastrointestinal tumor with a poor prognosis, which is associated with poor differentiation of tumor cells. However, the potential value of cell differentiation-related molecules in predicting the benefit and prognosis of immune checkpoint inhibitors (ICI) therapy remains unknown. Herein, to investigate the differentiation trajectory of HCC cells and their clinical significance, a differentiation-related gene prognostic index (DRGPI) based on HCC differentiation-related genes (HDRGs) was constructed to elucidate the immune characteristics and therapeutic benefits of ICI in the HCC subgroup defined by DRGPI. Single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from four HCC samples were integrated for bioinformatics analysis. Then, PON1, ADH4, SQSTM1, HSP90AA1, and STMN1 were screened out to construct a DRGPI. More intriguingly, RT-qPCR validation of the expression of these genes yielded consistent results with the TCGA database. Next, the risk scoring (RS) constructed based on DRGPI suggested that the overall survival (OS) of the DRGPI-high patients was significantly worse than that of the DRGPI-low patients. A nomogram was constructed based on DRGPI-RS and clinical characteristics, which showed strong predictive performance and high accuracy. The comprehensive results indicated that a low DRGPI score was associated with low TP53 mutation rates, high CD8 T cell infiltration, and more benefit from ICI therapy. Homoplastically, the high DRGPI score reflected the opposite results. Taken together, our study highlights the significance of HCC cell differentiation in predicting prognosis, indicating immune characteristics, and understanding the therapeutic benefits of ICI, and suggests that DRGPI is a valuable prognostic biomarker for HCC.

Objective: Hypoperfusion is an important factor determining the prognosis of ischemic stroke patients. The present study aimed to investigate possible predictors of hypoperfusion on MRI of ischemic stroke patients within 7 days of stroke onset.Methods: Ischemic stroke patients, admitted to the comprehensive Stroke Center of Shanghai Fourth People's Hospital affiliated to Tongji University within 7 days of onset between January 2016 and June 2017, were recruited to the present study. Magnetic resonance imaging (MRI), including both diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI), was performed within 7 days of the symptom onset. Time to maximum of the residue function (Tmax) maps were automatically evaluated using the RAPID software. The volume of hypoperfusion was measured outside the infarct area based on ADC < 620 × 10−6 mm2/s. The 90 d mRS score was assessed through either clinic visits or telephone calls. Multivariate step-wise analysis was used to assess the correlation between MR findings and clinical variables, including the demographic information, cardio-metabolic characteristics, and functional outcomes.Results: Among 635 patients admitted due to acute ischemic stroke within 7 days of onset, 241 met the inclusion criteria. Hypoperfusion volume of 38 ml was the best cut-off value for predicting poor prognosis of patients with cerebral infarction (90 d-mRS score ≥ 2). The incidences of MR perfusion Tmax > 4–6 s maps with a volume of 0–38 mL or >38 mL were 51.9% (125/241) and 48.1% (116/241), respectively. Prior stroke and vascular stenosis (≥70%) were associated with MR hypoperfusion. Multivariate step-wise analysis showed that prior stroke and vascular stenosis (≥70%) were risk factors of Tmax > 4–6 s maps, and the odds ratios (OR) were 3.418 (adjusted OR 95% CI: 1.537–7.600), and 2.265 (adjusted OR, 95% CI: 1.199–4.278), respectively.Conclusion: Our results suggest that prior stroke and vascular stenosis (≥70%) are strong predictors of hypoperfusion in patients with acute ischemic stroke within 7 days of stroke onset.

Background. Multiple organ failure (MOF) may lead to an increased mortality rate of moderately severe (MSAP) or severe acute pancreatitis (SAP). This study is aimed to use machine learning to predict the risk of MOF in the course of disease. Methods. Clinical and laboratory features with significant differences between patients with and without MOF were screened out by univariate analysis. Prediction models were developed for selected features through six machine learning methods. The models were internally validated with a five-fold cross-validation, and a series of optimal feature subsets were generated in corresponding models. A test set was used to evaluate the predictive performance of the six models. Results. 305 (68%) of 455 patients with MSAP or SAP developed MOF. Eighteen features with significant differences between the group with MOF and without it in the training and validation set were used for modeling. Interleukin-6 levels, creatinine levels, and the kinetic time were the three most important features in the optimal feature subsets selected by K-fold cross-validation. The adaptive boosting algorithm (AdaBoost) showed the best predictive performance with the highest AUC value (0.826; 95% confidence interval: 0.740 to 0.888). The sensitivity of AdaBoost (80.49%) and specificity of logistic regression analysis (93.33%) were the best scores among the six models in the test set. Conclusions. A predictive model of MOF complicated by MSAP or SAP was successfully developed based on machine learning. The predictive performance was evaluated by a test set, for which AdaBoost showed a satisfactory predictive performance. The study is registered with the China Clinical Trial Registry (Identifier: ChiCTR1800016079).

Objectives. The present study is aimed at investigating the frequency and associated factors of asymmetrical prominent veins (APV) in patients with acute ischemic stroke (AIS). Methods. Consecutive patients with AIS admitted to the Comprehensive Stroke Center of Shanghai Fourth People’s Hospital between January 2013 and December 2017 were enrolled. MRI including diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), and susceptibility-weighted imaging (SWI) was performed within 12 hours of symptom onset. The volume of asymmetrical prominent veins (APV) was evaluated using the Signal Processing In nuclear magnetic resonance software (SPIN, Detroit, Michigan, USA). Multivariate analysis was used to assess relationships between APV findings and medical history, clinical variables as well as cardio-metabolic indices. Results. Seventy-six patients met the inclusion criteria. The frequency of APV≥10 mL was 46.05% (35/76). Multivariate analyses showed that proximal artery stenosis or occlusion (≥50%) (P

Abstract Background More than 50% of metastatic melanoma patients have a specific mutation in the serine/threonine kinase BRAF. This results in constitutive activation of the RAS-RAF-MEK-ERK-MAP kinase pathway, which causes uncontrolled cell growth. Vemurafenib (PLX4032) is an oral chemotherapeutic agent that targets the specific mutation V600E in the BRAF protein. Initial response rates are high in patients with BRAF mutant melanoma treated with a BRAF inhibitor such as vemurafenib, but resistance nearly always develops and disease progression ensues. There are several different mechanisms by which melanoma develops BRAF inhibitor resistance. One potential component of resistance is increased drug efflux. Overexpressed ABCB5 (ATP-binding cassette transporter, subfamily B, member 5) has been shown to efflux anti-cancer drugs from cancer cells. The purpose of this study is to determine whether ABCB5 is highly expressed in BRAF inhibitor-resistant melanoma cells and to evaluate whether ABCB5 is involved in the development of resistance to BRAF inhibitors in cutaneous melanoma. Methods We established three BRAF inhibitor-resistant melanoma cell lines with BRAF mutation. The expression level of ABCB5 in PLX-resistant cell lines was checked by real-time PCR and Western blot analysis. SK-MEL-2 melanoma cells with wild-type BRAF were used for comparison. The association of different levels of ABCB5 with the changes of ERK, p-ERK, Akt and p-Akt was also assessed by Western blotting. Re-sensitization of melanoma cells to PLX was tested by p-ERK inhibitor PD58059 and ABCB5 knockdown by ABCB5 siRNA, respectively. Results We showed that ABCB5 was overexpressed in SK-MEL-28PLXr and A2058PLXr cells but not in A375PLXr cells. ABCB5 overexpression is associated with activation of p-ERK status but not Akt. Inhibition of p-ERK re-sensitized SK-MEL-28PLXr and A2058PLXr cells to PLX treatment, but knockdown of ABCB5 did not re-sensitize A2058 PLXr and SK-MEL-28 PLXr cells to PLX treatment. Conclusion These results confirm that, even though ABCB5 was overexpressed in SK-MEL-28 and A2058 melanoma cells that develop resistance to BRAF inhibitors, ABCB5 may not be a major targetable contributor to BRAF resistance. p-ERK inhibition may play important roles in BRAF resistance in these two melanoma cell lines.

The accelerated life testing is a common tool to achieve lifetime prediction and reliability analysis for light-emitting diodes (LEDs). Currently, all popular accelerated methods, either offline or online, employ a large volume, energy-consuming temperature chamber, which will cause the instruments inside worse, and the methods are usually incapable of controlling the junction temperature online. In this paper, we propose a multifunctional online system that controls the temperature of heat sink directly by a heating plate integrated to electrical-current-stress fixture. The combinations of spectrometer with optical multiplexer and current source with electrical matrix switch are adopted to fulfill the comprehensive real-time testing of LEDs, including optical, electrical, colorimetric, and thermal properties. In particular, junction temperature is monitored and controlled online by pulse-voltage method, which raises the accuracy and reliability of lifetime analysis and prediction. A new file format-HDF5 is applied to process huge quantities of experimental data, which are helpful to analyze the failure mechanism.

BACKGROUND:Vascular endothelial growth factor (VEGF) is commonly overexpressed in a variety of tumor types including lung cancer. As a key regulator of angiogenesis, it promotes tumor survival, growth, and metastasis through the activation of the downstream protein kinase B (AKT) and extracellular signal-regulated kinase (ERK 1/2) activation. The VEGF promoter contains a 36 bp guanine-rich sequence (VEGFq) which is capable of forming quadruplex (four-stranded) DNA. This sequence has been implicated in the down-regulation of both basal and inducible VEGF expression and represents an ideal target for inhibition of VEGF expression. RESULTS:Our experiments demonstrate sequence-specific interaction between a G-rich quadruplex-forming oligonucleotide encoding a portion of the VEGFq sequence and its double stranded target sequence, suggesting that this G-rich oligonucleotide binds specifically to its complementary C-rich sequence in the genomic VEGF promoter by strand invasion. We show that treatment of A549 non-small lung cancer cells (NSCLC) with this oligonucleotide results in decreased VEGF expression and growth inhibition. The VEGFq oligonucleotide inhibits proliferation and invasion by decreasing VEGF mRNA/protein expression and subsequent ERK 1/2 and AKT activation. Furthermore, the VEGFq oligonucleotide is abundantly taken into cells, localized in the cytoplasm/nucleus, inherently stable in serum and intracellularly, and has no effect on non-transformed cells. Suppression of VEGF expression induces cytoplasmic accumulation of autophagic vacuoles and increased expression of LC3B, suggesting that VEGFq may induce autophagic cell death. CONCLUSION:Our data strongly suggest that the G-rich VEGFq oligonucleotide binds specifically to the C-rich strand of the genomic VEGF promoter, via strand invasion, stabilizing the quadruplex structure formed by the genomic G-rich sequence, resulting in transcriptional inhibition. Strand invading oligonucleotides represent a new approach to specifically inhibit VEGF expression that avoids many of the problems which have plagued the therapeutic use of oligonucleotides. This is a novel approach to specific inhibition of gene expression.

In this paper, based on the theoretical research of structural modal analysis, different types of phonon crystal modal structures are designed for the first time, and the characteristics and the generation mechanism of the bandgap were studied through theoretical calculations and experiments. According to the phenomenon in the experimental results, we can find that the vibration transmission characteristics of phonon crystal structure α 3 are the best, and it is also superior to that of phonon crystal structure α 10 (full period structure). Therefore, the comparison of theoretical analysis with experimental phenomena shows that the bandgap generation mechanism should be modal resonance instead of local resonance in the finite periodic structure. The profound reason lies in there is no separate Z direction local vibration mode of periodic structure in the vibration mode of finite structure, and the bandgap of finite structure is the mode superposition torsional resonance mechanism between scatterer and substrate mode.

During the last decades, the ionic polymer-metal composite (IPMC) received much attention because of its potential capabilities, such as large displacement and flexible bending actuation. In this paper, a biomimetic flapping air vehicle was proposed by combining the superiority of ionic polymer metal composite with the bionic beetle flapping principle. The blocking force was compared between casted IPMC and IPMC. The flapping state of the wing was investigated and the maximum displacement and flapping angle were measured. The flapping displacement under different voltage and frequency was tested. The flapping displacement of the wing and the support reaction force were measured under different frequency by experiments. The experimental results indicate that the high voltage and low frequency would get large flapping displacement.

BackgroundThere is increasing interest in the concept of atrial cardiomyopathy, but the underlying molecular and mechanistic determinants remain poorly defined. We identified a family with heritable atrial cardiomyopathy manifesting as progressive atrial‐selective electromechanical dysfunction, tachyarrhythmias, and bradyarrhythmias requiring pacemaker implantation. Myosin light‐chain 4 (MYL4), encoding the atrial‐selective essential myosin light chain, was identified as a candidate gene. We used genetically modified rat models to investigate the role of MYL4 in atrial cardiomyopathy. Methods and ResultsExome sequencing and systematic bioinformatic analyses identified a rare missense variant of MYL4 (c.31G>A [p.E11K]) in a large multiplex atrial cardiomyopathy family pedigree. The mutation cosegregated with atrial standstill (selected as the principal presenting trait) with a logarithm of the odds score of 5.3. The phenotype of rats with MYL4 mutation knock‐in confirmed the causative role of the mutation. MYL4 knockout rats showed a similar atrial cardiomyopathy phenotype, whereas rats with an adjacent 4‐amino‐acid deletion showed no phenotype. Both MYL4 p.E11K knock‐in rats and MYL4 knockout rats showed progressive atrial electrophysiological, contractile, and fibrotic abnormalities, similar to affected patients. Biochemical analyses of MYL4 p.E11K mutation rats showed activation of proapoptotic and profibrotic signaling, along with increased atrial‐cardiomyocyte terminal deoxynucleotidyl transferase dUTP nick end labeling staining, suggesting enhanced apoptotic cell death, findings that were mimicked by in vitro adenoviral transfer of the mutant gene to neonatal‐rat cardiomyocytes. ConclusionsLoss‐of‐function MYL4 gene variants cause progressive atrial cardiomyopathy in humans and rats. Our findings identify MYL4 as a key gene required for atrial contractile, electrical and structural integrity. These results improve our understanding of the molecular basis of atrial cardiomyopathy and introduce new models for further mechanistic analysis.

Toll-like receptor 4 is overexpressed in various tumors, including cervical carcinoma. However, the role of Toll-like receptor 4 in cervical cancer remains controversial, and the underlying mechanisms are largely elusive. Therefore, Toll-like receptor 4 in cervical cancer and related mechanisms were investigated in this study. Quantitative reverse transcription polymerase chain reaction and western blot analyses were used to detect messenger RNA and protein levels in HeLa, Caski, and C33A cells with different treatments. Proliferation was quantified using Cell Counting Kit-8. Cell cycle distribution and apoptosis were assessed by flow cytometry. Higher levels of Toll-like receptor 4 expression were found in human papillomavirus–positive cells compared to human papillomavirus–negative cells. Proliferation of HeLa and Caski cells was promoted in lipopolysaccharide-stimulated groups but suppressed in short hairpin RNA–transfected groups. Apoptosis rates were lower in lipopolysaccharide-stimulated groups relative to short hairpin RNA–transfected groups. In addition, G2-phase distribution was enhanced when Toll-like receptor 4 was downregulated. Moreover, the pNF-κBp65 level was positively correlated with the Toll-like receptor 4 level in HeLa and Caski cells, though when an nuclear factor-κB inhibitor was applied to lipopolysaccharide-stimulated groups, the patterns of proliferation and apoptosis were opposite to those of the lipopolysaccharide-stimulated groups without inhibitor treatment. In conclusion, these data suggest that Toll-like receptor 4 promotes proliferation and apoptosis resistance in human papillomavirus–related cervical cancer cells at least in part through the Toll-like receptor 4/nuclear factor-κB pathway, which may be correlated with the occurrence and development of cervical carcinoma.

In this study, we have investigated the trade-off between the color rendering index (CRI, Ra) and the scotopic/photopic ratio (S/P) for color-tunable phosphor-coated white light-emitting diodes (LEDs) at two CRI limitations (Ra ≥ 70 and Ra ≥ 96). First, luminescent spectra measurements have been conducted to determine experimental results of Ra and S/P under various correlated color temperatures (CCTs). Then, a nonlinear programming method has been adopted for the optimization of Ra and S/P by varying spectral shapes through adjusting spectral parameters, such as peak wavelengths, full-width at half-maxima, and relative intensities. Therefore, polynomial curves of optimal S/P versus CCT at two Ra limitations have been discovered, enabling users to obtain optimal S/P under arbitrary CCTs within [2700 K, 6500 K]. In addition, a comparison study between the present work and our previous work has also been conducted at Ra = 70, and a fair agreement of optimal S/P has been observed.

Congenital contractural arachnodactyly (CCA, OMIM 121050), also known as Beals-Hecht syndrome, is an autosomal dominant disorder of connective tissue. CCA is characterized by arachnodactyly, dolichostenomelia, pectus deformities, kyphoscoliosis, congenital contractures and a crumpled appearance of the helix of the ear. The aim of this study is to identify the genetic cause of a 4-generation Chinese family of Tujia ethnicity with congenital contractural arachnodactyly by exome sequencing. The clinical features of patients in this family are consistent with CCA. A novel missense mutation, c.3769T>C (p.C1257R), in the fibrillin 2 gene (FBN2) was identified responsible for the genetic cause of our family with CCA. The p.C1257R mutation occurs in the 19th calcium-binding epidermal growth factor-like (cbEGF) domain. The amino acid residue cysteine in this domain is conserved among different species. Our findings suggest that exome sequencing is a powerful tool to discover mutation(s) in CCA. Our results may also provide new insights into the cause and diagnosis of CCA, and may have implications for genetic counseling and clinical management.

To optimize irrigation and provide a technical guide on agricultural production, the water-saving irrigation meteorological grading indexes of different development stages of maize were built in this paper, based on the principle of farmland water balance, the theories of insufficient irrigation and regulated deficit irrigation, and by using multidimensional information including day-by-day meteorological data in 1961-2008 from 500 meteorological stations, soil moisture data in ten-day periods in 1993-2008 from 239 agro-meteorological stations (of which, the data in 1980-2008 came from 68 agro-meteorological stations),irrigation amount and yield data were collected to analyze the relationship between the moisture deficiency rates, the quantity of water deficit and yield reduction rates at sowing-jointing stage, jointing-heading stage, heading-mature stage and the whole growth stage of maize referring to the product-water function(FAO-1979). Results indicated that water-saving irrigation meteorological grading indexes from I-III levels of moisture deficiency rate and the quantity of water deficit (secondary indicators) were [10%, 25%), [25%, 40%) and >40%, corresponding to 1-2 irrigations (600m3 hm–2 each time), 2-3 irrigations and >3 irrigations for the whole growth stage of maize, respectively. For sowing-jointing stage, the indicators were [15%, 30%), [30%, 45%) and >45%, corresponding to 0.5 irrigation, 1 irrigations and >1 irrigation, respectively. For jointing-heading stage, the indicators were [15%,30%), [30%, 45%) and >45%, corresponding to 0.5 irrigation, 1 irrigation and >1 irrigation, respectively. For heading-mature stage, the indicators were [15%, 30%), [30%, 50%) and >50%, corresponding to 1 irrigation, 1-2 irrigations and >2 irrigations, respectively. These indices could supply scientific support for the optimization of irrigation, and give guidance to agricultural production.

Autosomal recessive cerebellar ataxias are a group of neurodegenerative disorders that are characterized by complex clinical and genetic heterogeneity. Although more than 20 disease-causing genes have been identified, many patients are still currently without a molecular diagnosis. In a two-generation autosomal recessive cerebellar ataxia family, we mapped a linkage to a minimal candidate region on chromosome 16p13.3 flanked by single-nucleotide polymorphism markers rs11248850 and rs1218762. By combining the defined linkage region with the whole-exome sequencing results, we identified a homozygous mutation (c.493CT) in CHIP (NM_005861) in this family. Using Sanger sequencing, we also identified two compound heterozygous mutations (c.389AT/c.441GT; c.621C>G/c.707GC) in CHIP gene in two additional kindreds. These mutations co-segregated exactly with the disease in these families and were not observed in 500 control subjects with matched ancestry. CHIP colocalized with NR2A, a subunit of the N-methyl-D-aspartate receptor, in the cerebellum, pons, medulla oblongata, hippocampus and cerebral cortex. Wild-type, but not disease-associated mutant CHIPs promoted the degradation of NR2A, which may underlie the pathogenesis of ataxia. In conclusion, using a combination of whole-exome sequencing and linkage analysis, we identified CHIP, encoding a U-box containing ubiquitin E3 ligase, as a novel causative gene for autosomal recessive cerebellar ataxia.

Considering the high energy consumption of image acquisition, computation, and transmission in wireless multimedia sensor networks (WMSNs), two-tier network structure is usually used to lighten the energy consumption burden on camera sensors. Thus, a camera sensor can only be actuated when an event is detected by scalar sensors within its field of view (FoV). In this paper, we study the event-driven camera actuation problem and propose a distributed collaborative camera actuation scheme based on sensing-region management (DCCA-SM). The basic idea of this scheme is to divide the whole sensing field into many sensing regions which are covered by different sets of camera sensors. During the running of the network, by forming a cluster of the scalar sensors in each sensing region, the events occurring in each sensing region can be managed by the scalar cluster head. Therefore, by hearing from the scalar cluster heads, each camera sensor can know the exact coverage overlaps without changing information with the neighboring camera sensors. Meanwhile, sensing-region management avoids repeatedly event reporting from scalar sensors. In order to show the performance of the DCCA-SM, a simulation has been conducted. The comparative performance evaluations demonstrate effectiveness and energy efficiency of the proposed scheme.