POLQ inhibition attenuates the stemness and ferroptosis resistance in gastric cancer cells via downregulation of dihydroorotate dehydrogenase.

Gastric cancer (GC) contains subpopulations of cancer stem cells (CSCs), which are described as the main contributors in tumor initiation and metastasis. It is necessary to clarify the molecular mechanism underlying CSCs phenotype and develop novel biomarkers and therapeutic targets for gastric cancer. Here, we show that POLQ positively regulates stem cell-like characteristics of gastric cancer cells, knockdown of POLQ suppressed the stemness of GC cells in vitro and in vivo. Further mechanistic studies revealed that POLQ knockdown could downregulate the expression of dihydroorotate dehydrogenase (DHODH). DHODH overexpression rescued the reduced stemness resulted by POLQ knockdown. Furthermore, we found that POLQ expression correlated with resistance to ferroptosis, and POLQ inhibition renders gastric cancer cells more vulnerable to ferroptosis. Further investigation revealed that POLQ regulated DHODH expression via the transcription factors E2F4, thereby regulating ferroptosis resistance and stemness of gastric cancer cells. Given the importance of POLQ in stemness and ferroptosis resistance of GC, we further evaluated the therapeutic potential of POLQ inhibitor novobiocin, the results show that novobiocin attenuates the stemness of GC cells and increased ferroptosis sensitivity. Moreover, the combination of POLQ inhibitor and ferroptosis inducer synergistically suppressed MGC-803 xenograft tumor growth and diminished metastasis. Our results identify a POLQ-mediated stemness and ferroptosis defense mechanism and provide a new therapeutic strategy for gastric cancer.

MonoAux: Fully Exploiting Auxiliary Information and Uncertainty for Monocular 3D Object Detection.

Monocular 3D object detection plays a pivotal role in autonomous driving, presenting a formidable challenge by requiring the precise localization of 3D objects within a single image, devoid of depth information. Most existing methods in this domain fall short of harnessing the limited information available in monocular 3D detection tasks. They typically provide only a single detection outcome, omitting essential uncertainty analysis and result post-processing during model inference, thus limiting overall model performance. In this paper, we propose a comprehensive framework that maximizes information extraction from monocular images while encompassing diverse depth estimation and incorporating uncertainty analysis. Specifically, we mine additional information intrinsic to the monocular 3D detection task to augment supervision, thereby addressing the information scarcity challenge. Moreover, our framework handles depth estimation by recovering multiple sets of depth values from calculated visual heights. The final depth estimate and 3D confidence are determined through an uncertainty fusion process, effectively reducing inference errors. Furthermore, to address task weight allocation in multi-task training, we present a versatile training strategy tailored to monocular 3D detection. This approach leverages measurement indicators to monitor task progress, adaptively adjusting loss weights for different tasks. Experimental results on the KITTI and Waymo dataset confirm the effectiveness of our approach. The proposed method consistently provides enhanced performance across various difficulty levels compared to the original framework while maintaining real-time efficiency.

Causal Relationship Between Immune Cells/Cytokines and Dilated Cardiomyopathy.

To date, whether there is any causal relationship between dilated cardiomyopathy (DCM) and the changes in the levels/expression of immune cells/cytokines is still unclear. This study aimed to investigate the causal relationship between the levels of various types of immune cells/cytokines and DCM. Herein, two-sample Mendelian randomization (MR) (TSMR) using R software was conducted. Single nucleotide polymorphisms (SNPs) related to the levels of various types of immune cells/cytokines and DCM were screened based on the genome-wide association studies (GWAS) obtained from open-source databases. The TSMR was conducted using inverse variance weighted (IVW), method, MR-Egger regression, weighted median method, and simple estimator based on mode to explore the causal association between the levels of each immune cell/cytokine and DCM. Sensitivity analysis was conducted using MR-Egger regression and a leave-one-out sensitivity test. A total of 1816 SNPs related to host immune status and DCM were identified. The IVW results showed a relationship between DCM and the circulating levels of basophils/eosinophils, total eosinophils-basophils, lymphocytes, and C-reactive protein (CRP). Increased lymphocytes levels (odds ratio (OR) = 0.91, 95% confidence interval (CI): 0.84-0.97, P = 0.005) were seen as protective against DCM, whereas increased basophil (OR = 1.18, 95% CI: 1.04-1.33, P = 0.022), eosinophil (OR = 1.1, 95% CI: 1.03-1.17, P = 0.007), eosinophil-basophil (OR = 1.09, 95% CI: 1.02-1.17, P = 0.014), and CRP (OR = 1.1, 95% CI: 1.03-1.18, P = 0.013) levels were associated with an increased risk of DCM. These analyses revealed that there may be a relationship between immune cells/select cytokine status and the onset of DCM. Future studies are required to further validate these outcomes in animal models and clinical trials.

Coupled thermo-mechanical interaction on a multi-layered skin tissue with temperature-dependent physical properties irradiated by a pulse laser.

A detailed understanding of the coupled thermo-mechanical interaction on the biological tissue irradiated by a pulse laser is essential for the existed therapeutic methods constructed on the photo-thermal effect, which will contribute to the design, characterization and optimization of strategies for delivering better treatment. The aim of present work is to explore the coupled thermo-mechanical behavior of a multi-layered skin tissue with temperature-dependent physical properties under the pulsed laser irradiation. A layered theoretical model involved variable physical parameters with temperature has been proposed firstly according to the generalized theory of thermo-elasticity with dual-phase lag mechanism. The numerical method based on an explicit finite difference scheme is then employed to predict the temporal and spatial distributions of the temperature, thermal deformation and stresses experienced to a short-pulse laser irradiation. On this basis, the effect of variable thermal and mechanical physical parameters of skin tissue on the coupled thermo-mechanical behavior and relative thermal damage has been evaluated.

Knowledge-Embedded Mutual Guidance for Visual Reasoning.

Visual reasoning between visual images and natural language is a long-standing challenge in computer vision. Most of the methods aim to look for answers to questions only on the basis of the analysis of the offered questions and images. Other approaches treat knowledge graphs as flattened tables to search for the answer. However, there are two major problems with these works: 1) the model disregards the fact that the world we surrounding us interlinks our hearing and speaking of natural language and 2) the model largely ignores the structure of the acrlong KG. To overcome these challenging deficiencies, a model should jointly consider two modalities of vision and language, as well as the rich structural and logical information embedded in knowledge graphs. To this end, we propose a general joint representation learning framework for visual reasoning, namely, knowledge-embedded mutual guidance. It realizes mutual guidance not only between visual data and natural language descriptions but also between knowledge graphs and reasoning models. In addition, it exploits the knowledge derived from the reasoning model to boost knowledge graphs when applying the visual relation detection task. The experimental results demonstrate that the proposed approach performs dramatically better than state-of-the-art methods on two benchmarks for visual reasoning.

Tumor-targeting hydroxyapatite nanoparticles for remodeling tumor immune microenvironment (TIME) by activating mitoDNA-pyroptosis pathway in cancer.

In recent years, immunotherapy has emerged as a promising strategy for treating solid tumors, although its efficacy remains limited to a subset of patients. Transforming non-responsive "cold" tumor types into immuno-responsive "hot" ones is critical to enhance the efficacy of immune-based cancer treatments. Pyroptosis, a programmed cell death mechanism, not only effectively eliminates tumor cells but also triggers a potent inflammatory response to initiate anti-tumor immune activities. This sheds light on the potential of pyroptosis to sensitize tumors to immune therapy. Hence, it is urgent to explore and develop novel treatments (e.g., nanomedicines) which are capable of inducing pyroptosis. In this study, we constructed tumor-targeting nanoparticles (CS-HAP@ATO NPs) by loading atorvastatin (ATO) onto chondroitin sulfate (CS) modified hydroxyapatite (HAP) nanoparticles (CS-HAP). CS was strategically employed to target tumor cells, while HAP exhibited the capacity to release calcium ions (Ca2+) in response to the tumor microenvironment. Moreover, ATO disrupted the mitochondrial function, leading to intracellular energy depletion and consequential changes in mitochondrial membrane permeability, followed by the influx of Ca2+ into the cytoplasm and mitochondria. CS and HAP synergetically augmented mitochondrial calcium overload, inciting the production of substantial amount of reactive oxygen species (ROS) and the subsequent liberation of oxidized mitochondrial DNA (OX-mitoDNA). This intricate activation process promoted the assembly of inflammasomes, most notably the NLRP3 inflammasome, followed by triggering caspase-1 activation. The activated caspase-1 was able to induce gasderminD (GSDMD) protein cleavage and present the GSDM-N domain, which interacted with phospholipids in the cell membrane. Then, the cell membrane permeability was raised, cellular swelling was observed, and abundant cell contents and inflammatory mediators were released. Ultimately, this orchestrated sequence of events served to enhance the anti-tumor immunoresponse within the organism.

A high sensitivity cross-capacitive sensor for water droplets and bubble detection in hydraulic oil.

The presence of moisture and air in hydraulic oil will seriously affect the reliability of machines. This paper proposes a new cross-capacitive oil pollution detection sensor, which is based on the Thompson and Lampard theorem. The sensing unit consists of four identical copper electrodes with infinitesimally small gaps. The sensor can effectively distinguish water droplets and air bubble pollutants mixed in the oil through the pulse direction of the signal. Compared with traditional capacitive sensors, the sensor has a significant improvement in detection accuracy and detection throughput. In this paper, the relationship between the cross-capacitance value with the dielectric constant and the frequency in an alternating electric field was deduced, and the best excitation frequency was chosen as 1.9 MHz. Experiments show that the sensor can effectively detect water droplets of 140-160 µm and bubbles of 170-190 µm and has good linearity for detecting water droplets and air bubbles of different sizes. The sensor provides a new method for machine condition monitoring of hydraulic systems.

Exploring the diagnostic and prognostic value of the C-reactive protein/lymphocyte ratio for dilated cardiomyopathy based on a real-world study.

To determine the risk factors for dilated cardiomyopathy (DCM) and construct a risk model for predicting HF in patients with DCM, We enrolled a total of 2122 patients, excluding those who did not meet the requirements. A total of 913 patients were included in the analysis (611 males and 302 females) from October 2012 to May 2020, and data on demographic characteristics, blood biochemical markers, and cardiac ultrasound results were collected. Patients were strictly screened for DCM based on the diagnostic criteria. First, these patients were evaluated using propensity score matching (PSM). Next, unconditional logistic regression was used to assess HF risk. Furthermore, receiver operating characteristic (ROC) curve analysis was conducted to determine diagnostic efficiency, and a nomogram was developed to predict HF. Finally, the Kaplan‒Meier survival curve was plotted. Of the initial 2122 patients, the ejection fraction (EF) in males was worse. We included 913 patients after the final DCM diagnosis. The results showed that the levels of NT-proBNP, WBC, PLT, neutrophils, lymphocytes, eosinophils, and IL-6, C-reactive protein (CRP) and the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and CRP/lymphocyte ratio (CLR) were higher in males than in females (P < 0.001-0.009). The nomogram showed that factors such as sex, WBC, neutrophils, PLR, and CLR could predict the risk of worsening cardiac function in patients with DCM before and after PSM (P < 0.05). The ROC curve showed that CLR with an 85.6% area demonstrated higher diagnostic efficacy than the NLR (77.0%) and PLR (76.6%, P < 0.05). Survival analysis showed a higher mortality risk in females with higher CLR levels (P < 0.001-0.009). However, high CLR levels indicated a higher mortality risk (P < 0.001) compared to sex. Male EF is lower in DCM patients. CLR could predict the risk of declined cardiac function in patients with DCM. The mortality in females with higher CLR levels was highest; however, the exact mechanism should be investigated.

Searching for Intrinsic Causality between Colonic Dysbiosis and Non-Ischemic Cardiomyopathy: A Mendelian Randomization-Based Analysis.

Objective: Little is known about gut microbiota (GM) and cardiomyopathy. Their causal relationship was explored using two-sample Mendelian randomization (TSMR) performed by R software. Methods: The single nucleotide polymorphisms (SNPs) were further screened based on the genome-wide association studies (GWAS) of gut microbiota and cardiomyopathy obtained from an open database. TSMR was performed using an MR-Egger regression, simple estimator based on mode, weighted median method, inverse variance weighted (IVW), weighted estimator and CML-MA-BIC to explore the causal association. And the sensitivity analysis was carried out using an MR-Egger regression and the leave-one-out sensitivity test. Results: As for 211 GM taxa, IVW results confirmed that the class Actinobacteria (OR = 0.81, p = 0.021) and genus Coprobacter (OR = 0.85, p = 0.033) were protective factors for cardiomyopathy. The phylum Firmicutes (OR = 0.87, p < 0.01), family Acidaminococcaceae (OR = 0.89, p < 0.01), genus Desulfovibrio (OR = 0.92, p = 0.030) and genus Prevotella9 (OR = 0.93, p = 0.029) were protective factors for ischemic cardiomyopathy. The family Rhodospirillaceae (OR = 1.06, p = 0.036) and genus Turicibacter (OR = 1.09, p = 0.019) were risk factors for ischemic cardiomyopathy. The genus Olsenella (OR = 0.91, p = 0.032) was a protective factor for non-ischemic cardiomyopathy. The order Rhodospirillales (OR = 1.14, p = 0.024), family Rikenellaceae (OR = 1.21, p = 0.012) and genus Gordonibacter (OR = 1.12, p = 0.019) were risk factors for non-ischemic cardiomyopathy. The robustness of MR results was reflected in the heterogeneity (p > 0.05) and pleiotropy (p > 0.05) analyses. Conclusions: A potential causal relationship of cardiomyopathy with some GM taxa has been confirmed in the current study.

Webly Supervised Knowledge-Embedded Model for Visual Reasoning.

Visual reasoning between visual images and natural language remains a long-standing challenge in computer vision. Conventional deep supervision methods target at finding answers to the questions relying on the datasets containing only a limited amount of images with textual ground-truth descriptions. Facing learning with limited labels, it is natural to expect to constitute a larger scale dataset consisting of several million visual data annotated with texts, but this approach is extremely time-intensive and laborious. Knowledge-based works usually treat knowledge graphs (KGs) as static flattened tables for searching the answer, but fail to take advantage of the dynamic update of KGs. To overcome these deficiencies, we propose a Webly supervised knowledge-embedded model for the task of visual reasoning. On the one hand, vitalized by the overwhelming successful Webly supervised learning, we make much use readily available images from the Web with their weakly annotated texts for an effective representation. On the other hand, we design a knowledge-embedded model, including the dynamically updated interaction mechanism between semantic representation models and KGs. Experimental results on two benchmark datasets demonstrate that our proposed model significantly achieves the most outstanding performance compared with other state-of-the-art approaches for the task of visual reasoning.

Integration of miRNA and mRNA analysis reveals the role of ribosome in to anti-artificial aging in sweetcorn.

Sweetcorn is a kind of maize with high sugar content and has poor seed aging tolerance, which seriously limits its production. However, few studies have explored the artificial aging (AA) tolerance by miRNA-mRNA integration analysis in sweetcorn. Here, we characterized the physiological, biochemical and transcriptomic changes of two contrasting lines K62 and K107 treated with AA during time series. Both the germination indexes and antioxidant enzymes showed significant difference between two lines. The MDA content of AA-tolerant genotype K62 was significantly lower than that of K107 on the fourth and sixth day. Subsequently, 157 differentially expressed miRNAs (DEMIs) and 8878 differentially expressed mRNAs (DEMs) were identified by RNA-seq analysis under aging stress. The "ribosome" and "peroxisome" pathways were enriched to respond to aging stress, genes for both large units and small ribosomal subunits were significantly upregulated expressed and higher translation efficiency might exist in K62. Thirteen pairs of miRNA-target genes were obtained, and 8 miRNA-mRNA pairs might involve in ribosome protein and translation process. Our results elucidate the mechanism of sweetcorn response to AA at miRNA-mRNA level, and provide a new insight into sweetcorn AA response to stress.

Bio-thermal response and thermal damage in biological tissues with non-equilibrium effect and temperature-dependent properties induced by pulse-laser irradiation.

Comprehension of thermal behavior underlying the living biological tissues helps successful applications of current heat therapies. The present work is to explore the heat transport properties of irradiated tissue during tis thermal treatment, in which the local thermal non-equilibrium effect as well as temperature-dependent properties arose from complicated anatomical structure, is considered. Based on the generalized dual-phase lag (GDPL) model, a non-linear governing equation of tissue temperature with variable thermal physical properties is proposed. The effective procedure constructed on an explicit finite difference scheme is then developed to predict numerically the thermal response and thermal damage irradiated by a pulse laser as a therapeutic heat source. The parametric study on variable thermal physical parameters including the phase lag times, heat conductivity, specific heat capacity and blood perfusion rate has been performed to evaluate their influence on temperature distribution in time and space. On this basis, the thermal damage with different laser variables such as laser intensity and exposure time are further analyzed.

Patient satisfaction after nipple-sparing mastectomy with intraoperative radiotherapy and breast reconstruction for breast cancer.

INTRODUCTION: The use of nipple-sparing mastectomy (NSM) combined with breast reconstruction is increasing in breast cancer surgeries despite its controversial safety profile. To reduce the recurrence rate of tumors in the nipple-areola complex (NAC), we used intraoperative radiotherapy (IORT). The purpose of this study was to explore patients' feedback on this novel treatment strategy. PATIENTS AND METHODS: From January 2014 to May 2018, eligible patients with breast cancer were enrolled in this study and separated into 2 groups. Patients in the NSM group underwent IORT to the NAC flap, and patients in the skin-sparing mastectomy (SSM) group underwent SSM and breast reconstruction. The postoperative satisfaction was collected and assessed using the Breast-Q reconstruction questionnaire and a standardized questionnaire; this was compared between the 2 groups. RESULTS: There were 46 patients (52 NSMs) in the NSM group and 20 patients (22 SSMs) in the SSM group. The breast-Q scores were higher in the NSM group than the SSM group, with trends for a 'higher satisfaction with breasts' (67.39 ± 20.59 vs. 55.00 ± 19.33; p = 0.026) and 'higher sexual well-being' (61.74 ± 22.24 vs. 49.50 ± 20.12; p = 0.039). All the patients recognized the importance of nipple preservation. Thirty-seven women (80.40%) were satisfied or very satisfied with the appearance and shape of the NAC in the NSM group, while 38/46 women (82.60%) were very unsatisfied or unsatisfied with the sensitivity of the nipples. CONCLUSIONS: The Breast-Q scores showed great satisfaction with breasts and sexual well-being in the NSM group. However, more effort should be made in improving postoperative NAC sensitivity.

Carbonation Resistance and Pore Structure of Mixed-Fiber-Reinforced Concrete Containing Fine Aggregates of Iron Ore Tailings.

The disposal of industrial by-product tailings has become an important issue in solving environmental pollution. In this study, 15%, 30%, 50%, and 70% iron tailings were used to replace the natural sand in concrete, and 1.5% steel fiber and 0-0.75% PVA fibers were added to the iron tailings concrete. The effects of the iron tailings replacement rate and the fiber content on the mechanical properties, carbonization depth, and concrete porosity were studied in a carbonization environment. The results demonstrated that the compressive and splitting tensile strengths of concrete first increased and subsequently decreased with an increase in the iron tailings replacement rate, while the carbonation depth and porosity initially decreased and subsequently increased. When the replacement rate of iron tailings was 30%, the compressive strength and split tensile strength were increased by 7.6% and 17.7%, respectively, and the porosity was reduced by 8.9%. The compressive strength, carbonation depth and porosity of single-doped steel-fiber concrete were superior to those of ordinary iron tailings concrete. However, compared with single-doped steel fiber, the performance of steel-PVA fiber was further improved. Based on the mechanical properties, the carbonation depth test results of the three aforementioned types of concrete, the mathematical expression of the uniaxial compression stress-strain curve of iron tailings concrete, and the prediction equation of the carbonation depth of mixed-fiber iron tailings concrete were proposed. This study provides a reference for the application and popularization of fiber-reinforced iron tailings concrete in carbonization environments.

Safety, pharmacokinetics and pharmacodynamics of a novel γ-aminobutyric acid (GABA) receptor potentiator, HSK3486, in Chinese patients with hepatic impairment.

BACKGROUND: The primary objective of this study was to investigate if hepatic impairment alters the safety, pharmacokinetics, and pharmacodynamics of HSK3486. RESEARCH DESIGN AND METHODS: This was a clinical trial of HSK3486 in subjects with normal hepatic function (n = 8), and mild (Child-Pugh A; n = 8), or moderate (Child-Pugh B; n = 8) hepatic impairment. Each subject received an IV bolus dose of 0.4 mg/kg HSK3486 for 1 min, immediately followed by a maintenance infusion of 0.4 mg/kg/h HSK3486 for 30 min. RESULTS: In total, 24 subjects were enrolled and completed the study. HSK3486 was generally well tolerated by all subjects. There were no serious AEs and no deaths reported during the study. The incidence of AEs was numerically highest in subjects with moderate hepatic impairment. The exposure (AUC) of HSK3486 increased gradually with the decrease in hepatic function; however, degree of hepatic impairment had little effect on HSK3486 PD (MOAA/S and BIS). CONCLUSIONS: Overall, there were no clinically relevant differences in HSK3486 exposure or PD in subjects with mild or moderate hepatic impairment compared to normal control. These data imply that HSK3486 dose adjustment is not warranted in subjects with mild or moderate hepatic impairment. TRIAL REGISTRATION: The trial is registered at ClinicalTrials.gov (CT.gov identifier: NCT04145596).Key MessageHSK3486 at an IV bolus dose of 0.4 mg/kg and a maintenance infusion of 0.4 mg/kg/h was safe and well tolerated by all mild or moderate hepatic impairment subjects and normal hepatic function subjects.There were no clinically relevant differences in HSK3486 exposure or PD in subjects with mild or moderate hepatic impairment compared to subjects with normal hepatic function.HSK3486 dose adjustment is not required in subjects with mild or moderate hepatic impairment.

Slight flow volume rises increase nitrogen loading to nitrogen-rich river, while dramatic flow volume rises promote nitrogen consumption.

Concentrated rainfall and water transfer projects result in slight and dramatic increases in flow volume over short periods of time, causing nitrogen recontamination in the water-receiving areas of nitrogen-rich rivers. This study coupled hydrodynamic and biochemical reaction models to construct a model for quantifying diffusive transport and transformation fluxes of nitrogen across the water-sediment interface and analysed possible changes in the relative abundance of microbial functional genes using high-throughput sequencing techniques. In this study, the processes of ammonium (NH4+-N) and nitrate (NO3--N) nitrogen release and sedimentation with resuspended particles, as well as mineralisation, nitrification, and denitrification processes were investigated at the water-sediment interface in the Fu River during slight and dramatic increases in flow volume caused by concentrated rainfall and water diversion projects. Specifically, a slight flow volume rise increased the release of NH4+-N from the sediment, inhibited sedimentation of NO3--N, decreased the mineralisation rate, increased the nitrification rate, and had little effect on the denitrification process, ultimately increasing the nitrogen load to the river water. A dramatic increase in flow volume simultaneously increased NH4+-N and NO3--N exchange fluxes, inhibited the mineralisation process, promoted nitrification-denitrification processes, and increased inorganic nitrogen consumption in the river. This study provides a solution for the re-pollution of rivers that occurs during the implementation of reservoir management and water diversion projects. Furthermore, these results indicate a potential global nitrogen sink that may have been overlooked.

Research on Mechanical and Carbonization Properties of Hybrid Fiber Iron Tailings Concrete Based on Deep Learning.

Iron tailings sand is a kind of mineral waste, and open-air storage is a common treatment method for iron tailings, which not only has a huge impact on the ecological environment but also occupies a lot of land resources. Therefore, the preparation of high-ductility fiber reinforced iron tailings concrete and its application in practical engineering structures have good application prospects. This paper is based on the deep learning research on the mechanical and carbonization properties of hybrid fiber iron tailings concrete. Therefore, tailings sands with different substitution rates, single-mixed steel fiber, and mixed steel-PVA fiber concrete were prepared in this paper. Its compressive strength, split tensile strength, axial compressive strength, elastic modulus, strain, and carbonization depth were tested. Through the existing concrete compressive stress-strain curve equations, the nonlinear calculation of each group of concrete compressive stress-strain curve equations in this paper is carried out, some parameters are determined, and the carbonation depth equation is established. The results show that, with the increase of tailings content, the properties of concrete increase first and then decrease and the addition of fibers can effectively improve the strength, elastic modulus, peak strain, and carbonization depth of concrete. However, with the increase of PVA fiber content, its performance enhancement effect decreased.

A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer.

Patients with hormone receptor (HR)-positive tumors breast cancer usually experience a relatively low pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Here, we derived a 10-microRNA risk score (10-miRNA RS)-based model with better performance in the prediction of pCR and validated its relation with the disease-free survival (DFS) in 755 HR-positive breast cancer patients (273, 265, and 217 in the training, internal, and external validation sets, respectively). This model, presented as a nomogram, included four parameters: the 10-miRNA RS found in our previous study, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, and volume transfer constant (Ktrans). Favorable calibration and discrimination of 10-miRNA RS-based model with areas under the curve (AUC) of 0.865, 0.811, and 0.804 were shown in the training, internal, and external validation sets, respectively. Patients who have higher nomogram score (>92.2) with NAC treatment would have longer DFS (hazard ratio=0.57; 95%CI: 0.39-0.83; P=0.004). In summary, our data showed the 10-miRNA RS-based model could precisely identify more patients who can attain pCR to NAC, which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HR-positive breast cancer.

A novel method for identifying geomechanical parameters of rock masses based on a PSO and improved GPR hybrid algorithm.

In view of the shortcomings of existing artificial neural network (ANN) and support vector regression (SVR) in the application of three-dimensional displacement back analysis, Gaussian process regression (GPR) algorithm is introduced to make up for the shortcomings of existing intelligent inversion methods. In order to improve the generality of the standard GPR algorithm with single kernel function, an improved Gaussian process regression (IGPR) algorithm with combined kernel function is proposed by adding two single kernel functions. In addition, in the training process of IGPR model, the particle swarm optimization (PSO) is combined with the IGPR model (PSO-IGPR) to optimize the parameters of the IGPR model. After the IGPR model can accurately map the relationship between geomechanical parameters and rock mass deformation, the PSO algorithm is directly used to search the best geomechanical parameters to match the deformation calculated by igpr model with the measured deformation of rock mass. The application case of Beikou tunnel shows that the combined kernel function GPR has higher identification accuracy than the single kernel function GPR and SVR model, the IGPR model with automatic correlation determination (ARD) kernel function can obtain higher identification accuracy than the IGPR model with isotropic (ISO) kernel function, and the PSO-IGPR hybrid model based on ARD kernel function has the highest identification accuracy. Therefore, this paper proposes a displacement back analysis method of the PSO-IGPR hybrid algorithm based on ARD kernel function, which can be used to identify the geomechanical parameters of rock mass and solve other engineering problems.

High mobility group box 1 and homocysteine as preprocedural predictors for contrast-induced acute kidney injury after percutaneous coronary artery intervention.

PURPOSE: High mobility group box 1 (HMGB1) and homocysteine (Hcy) play important roles in contrast-induced acute kidney injury (CI-AKI). We compared HMGB1 to Hcy as preprocedural predictors for CI-AKI in coronary artery disease (CAD) patients after percutaneous coronary artery intervention (PCI). METHODS: We included 257 eligible patients who were categorized into CI-AKI ( +) and CI-AKI ( -) group. The differences in clinical characteristics and biochemical indexes between two groups were analyzed. RESULTS: We observed that thirty-eight (14.8%) of 257 eligible CAD patients developed CI-AKI. HMGB1 (14.65 [11.13-24.89] vs 10.88 [7.94-13.23], p < 0.001) and Hcy (14.07 [12.07-17.31] vs 12.09 [10.71-13.47], p < 0.001) increased significantly in CI-AKI ( +) group. Both age (r = 0.210, p = 0.001), serum creatinine (r = 0.509, p < 0.001), eGFR (r = - 0.459, p < 0.001) and Hcy (r = 0.531, p < 0.001) were significantly correlated with HMGB1. Among all patients, HMGB1 (OR 1.181, 95% CI 1.081-1.290, p < 0.001) and Hcy (OR 1.260, 95% CI 1.066-1.489, p = 0.007) were independent predictors for the development of CI-AKI. We built the propensity score matching (PSM) using 38 pairs of patients. After adjustment, HMGB1 (OR 1.169, 95% CI 1.035-1.322, p = 0.012) and Hcy (OR 1.457, 95% CI 1.064-1.997, p = 0.019) were also independent predictors for the development of CI-AKI. Both HMGB1 (AUC: 0.704, 95% CI: 0.588-0.819, p = 0.002) and Hcy (AUC: 0.708, 95% CI: 0.593-0.823, p = 0.002) had predictive values for CI-AKI. CONCLUSION: There is a significant positive association between HMGB1 and Hcy in CAD patients. Both HMGB1 and Hcy are potential preprocedural predictors of CI-AKI after PCI.