Among population-based metaheuristics, both Differential Evolution (DE) and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) perform outstanding for real parameter single objective ...optimization. Compared with DE, CMA-ES stagnates much earlier in many occasions. In this paper, we propose CMA-ES with individuals redistribution based on DE, IR-CMA-ES, to address stagnation in CMA-ES. We execute experiments based on two benchmark test suites to compare our algorithm with nine peers. Experimental results show that our IR-CMA-ES is competitive in the field of real parameter single objective optimization.
Metabolic dysfunction-associated fatty liver disease (MAFLD) and chronic kidney disease (CKD) present notable health challenges, however, abdominal obesity has received scant attention despite its ...potential role in exacerbating these conditions. Thus, we conducted a retrospective cohort study using the National Health and Nutrition Examination Surveys III (NHANES III) of the United States from 1988 to 1994 including 9161 participants, and mortality follow-up survey in 2019. Statistical analyze including univariable and multivariable Logistic and Cox regression models, and Mediation effect analyze were applied in study after adjustment for covariates. Our findings revealed that individuals with both abdominal obesity and MAFLD were more likely to be female, older and exhibit higher prevalence of advanced liver fibrosis (7.421% vs. 2.363%, p < 0.001), type 2 diabetes mellitus (T2DM) (21.484% vs. 8.318%, p < 0.001) and CKD(30.306% vs. 16.068%, p < 0.001) compared to those with MAFLD alone. MAFLD (adjusted OR: 1.392, 95% CI 1.013-1.913, p = 0.041), abdominal obesity (adjusted OR 1.456, 95% CI 1.127-1.880, p = 0.004), abdominal obesity with MAFLD (adjusted OR 1.839, 95% CI 1.377-2.456, p < 0.001), advanced fibrosis(adjusted OR 1.756, 95% CI 1.178-2.619, p = 0.006) and T2DM (adjusted OR 2.365, 95% CI 1.758-3.183, p < 0.001) were independent risk factors of CKD. The abdominal obese MAFLD group had the highest all-cause mortality as well as mortality categorized by disease during the 30-year follow-up period. Indices for measuring abdominal obesity, such as waist circumference (WC), waist-hip ratio (WHR), and lipid accumulation product (LAP), elucidated a greater mediation effect of MAFLD on CKD compared to BMI on CKD (proportion mediation 65.23%,70.68%, 71.98%, respectively vs. 32.63%). In conclusion, the coexistence of abdominal obesity and MAFLD increases the prevalence and mortality of CKD, and abdominal obesity serves as a mediator in the association between MAFLD and CKD.
Pancreatic carcinoma (PC) is a lethal cancer. Gut microbiota is associated with some risk factors of PC, e.g. obesity and types II diabetes. However, the specific gut microbial profile in clinical PC ...in China has never been reported. This prospective study collected 85 PC and 57 matched healthy controls (HC) to analyze microbial characteristics by MiSeq sequencing. The results showed that gut microbial diversity was decreased in PC with an unique microbial profile, which partly attributed to its decrease of alpha diversity. Microbial alterations in PC featured by the increase of certain pathogens and lipopolysaccharides-producing bacteria, and the decrease of probiotics and butyrate-producing bacteria. Microbial community in obstruction cases was separated from the un-obstructed cases.
was associated with the bile. Furthermore, 23 microbial functions e.g. Leucine and LPS biosynthesis were enriched, while 13 functions were reduced in PC. Importantly, based on 40 genera associated with PC, microbial markers achieves a high classification power with AUC of 0.842. In conclusion, gut microbial profile was unique in PC, providing a microbial marker for non-invasive PC diagnosis.
The transverse relaxation time (T2) is an important indicator to determine the fundamental sensitivity limit of alkali-metal atomic magnetometers. We propose a method based on the principle of ...longitudinal field modulation that obtains T2 by scanning the transverse static magnetic field. The previous technique of extracting T2 from the linewidth of the modulation frequency and the traditional magnetic-resonance-broadening-fitting method are also described. The T2 measurements of Cesium (Cs) atoms are carried out through these three methods, whose operating environments are applicable to different atomic magnetometers, respectively. The method that we propose can be used for obtaining the T2 of Cs atoms as well as detecting the transverse static magnetic field and is customized for the study of the Cs–Xenon ensemble for the construction of nuclear magnetic resonance gyroscopes. Moreover, the relationship between the limit sensitivities and cell temperatures is further studied in the experiment.
Available treatments for hepatocellular carcinoma (HCC), a common human malignancy with a low survival rate, remain unsatisfactory. Macropinocytosis (MPC), a type of endocytosis that involves the ...non-specific uptake of dissolved molecules, has been shown to contribute to HCC pathology; however, its biological mechanism remains unknown.
The current study identified 27 macropinocytosis-related genes (MRGs) from 71 candidate genes using bioinformatics. The R software was used to create a prognostic signature model by filtering standardized mRNA expression data from HCC patients and using various methods to verify the reliability of the model and indicate immune activity.
The prognostic signature was constructed using seven MPC-related differentially expressed genes,
,
,
,
,
,
, and
, through LASSO Cox regression. The risk score was acquired from the expression of these genes and their corresponding coefficients. HCC patients in the discovery and validation cohorts were stratified, and the survival of low-risk score patients was improved in both cohorts. Time-dependent ROC analysis indicated that the model's prediction reliability was the highest in the short term. Subsequent immunologic analysis, including KEGG, located the immune action pathway of the differentially expressed genes in the direction of the cancer pathway, etc. Immune infiltration and immune checkpoint tests provided valuable guidance for future follow-up experiments.
A risk model with MRGs was constructed to effectively predict HCC patient prognoses and suggest changes in the immune microenvironment during the disease process. The findings should benefit the development of a prognostic stratification and treatment strategy for HCC.
While single-cell mass spectrometry can reveal cellular heterogeneity and the molecular mechanisms of intracellular biochemical reactions, its application is limited by the insufficient detection ...sensitivity resulting from matrix interference and sample dilution. Herein, we propose an intact living-cell electrolaunching ionization mass spectrometry (ILCEI-MS) method. A capillary emitter with a narrow-bore, constant-inner-diameter ensures that the entire living cell enters the MS ion-transfer tube. Inlet ionization improves sample utilization, and no solvent is required, preventing sample dilution and matrix interference. Based on these features, the detection sensitivity is greatly improved, and the average signal-to-noise (S/N) ratio is about 20:1 of single-cell peaks in the TIC of ILCEI-MS. A high detection throughput of 51 cells per min was achieved by ILCEI-MS for the single-cell metabolic profiling of multiple cell lines, and 368 cellular metabolites were identified. Further, more than 4000 primary single cells digested from the fresh multi-organ tissues of mice were detected by ILCEI-MS, demonstrating its applicability and reliability.
A novel living-cell mass spectrometry method allows a whole cell to enter entirely into the MS inlet and ionize with almost no sample dilution and matrix interference, which greatly improves the sensitivity of single-cell metabolite detection.
Background and aim
Nonalcoholic fatty liver disease (NAFLD) is becoming the leading cause of chronic liver disease in China. The early identification and management of patients at risk are essential. ...We aimed to develop a novel clinical and laboratory-based nomogram (CLN) model to predict NAFLD with high accuracy.
Methods
We designed a retrospective cross-sectional study and enrolled 21,468 participants (16,468 testing and 5000 validation). Clinical information and laboratory/imaging results were retrieved. Significant variables independently associated with NAFLD were identified by a logistic regression model, and a NAFLD prediction CLN was constructed. The CLN was then compared with four existing NAFLD-related prediction models: the fatty liver index (FLI), the hepatic steatosis index (HSI), the visceral adiposity index (VAI) and the triglycerides and glucose (TyG) index. Area under the receiver operator characteristic curve (AUROC) and decision curve analysis (DCA) were performed.
Results
A total of 6261/16,468 (38.02%) and 1759/5000 (35.18%) participants in the testing and validation datasets, respectively, had ultrasound-proven NAFLD. Six variables were selected to build the CLN: body mass index (BMI), diastolic blood pressure (DBP), uric acid (UA), fasting blood glucose (FBG), triglyceride (TG), and alanine aminotransferase (ALT). The diagnostic accuracy of the CLN for NAFLD (AUROC 0.857, 95% CI 0.852–0.863) was significantly superior to that of the FLI (AUROC 0.849, 95% CI 0.843–0.855), the VAI (AUROC 0.752, 95% CI 0.745–0.760), the HSI (AUROC 0.828, 95% CI 0.822–0.834), and the TyG index (AUROC 0.774, 95% CI 0.767–0.781) (all
p
< 0.001). DCA confirmed the clinical utility of the CLN.
Conclusions
This physical examination and laboratory test-based, nonimage-assisted novel nomogram has better performance in predicting NAFLD than the FLI, the VAI, the HSI and the TyG index alone. This model can be used as a quick screening tool to assess NAFLD in the general population.
With the accumulation and storage of remote sensing images in various satellite data centers, the rapid detection of objects of interest from large-scale remote sensing images is a current research ...focus and application requirement. Although some cutting-edge object detection algorithms in remote sensing images perform well in terms of accuracy, their inference speed is slow and requires high hardware requirements that are not suitable for real-time object detection in large-scale remote sensing images. To address this issue, we propose a fast inference framework for object detection in large-scale remote sensing images. On the one hand, we introduce <inline-formula><tex-math notation="LaTeX">\alpha</tex-math></inline-formula>-IoU Loss on the YWCSL model to implement adaptive weighted loss and gradient, which achieves 64.62% and 79.54% mAP on DIOR-R and DOTA test sets, respectively. More importantly, the inference speed of the YWCSL model reaches 60.74 FPS on a single NVIDIA GeForce RTX 3080Ti, which is 2.87 times faster than the current state-of-the-art one-stage detector S<inline-formula><tex-math notation="LaTeX">^{2}</tex-math></inline-formula>A-Net. On the other hand, we build a distributed inference framework to enable fast inference on large-scale remote sensing images. Specifically, we save the images on HDFS for distributed storage and deploy the YWCSL model to the Spark cluster. When using 5 nodes, the speedup of the cluster reaches 9.54, which is 90.80% higher than the theoretical linear speedup (5.00). Our distributed inference framework for large-scale remote sensing images significantly reduces the dependence of object detection on expensive hardware resources, which has important research significance for the wide application of object detection in remote sensing images.
Historical earth observation (EO) data have played an important role in long-term scientific and environmental monitoring. The effective organization of large-scale and long-term remote-sensing data ...to achieve efficient retrieval and access has become one of the important issues. However, inherent big data characteristics, such as a large scale, and asymmetrical temporal and spatial distributions, have caused problems with the efficiency of data retrieval and access. Therefore, this study proposes an efficient data organization method for use in a cloud-computing environment that has two aims. First, it addresses the problem of low retrieval efficiency. An asymmetrical index model for the image metadata is constructed that is based on a unified spatio-temporal grid coding; a prepartitioning mechanism under the HBase architecture is established to realize the uniform storage of the metadata with an asymmetrical spatiotemporal distribution and to avoid retrieval efficiency bottlenecks caused by a load imbalance. Second, it addresses low access efficiency. By dividing the remote-sensing image into tiles, a unified spatio-temporal code is established for each tile, and a consistent hash operation is performed; tiles with similar hash values are stored in the same or adjacent Hadoop Distributed File System nodes. In this way, tiles with temporal or spatial correlations can be gathered and stored, and lots of disk seeks can be avoided during retrieval, thereby greatly improving the data access efficiency. Comparative experiments showed that the data organization method can effectively improve the retrieval and access efficiencies of large-scale and long time-series remote-sensing data in a cloud-computing environment.
MicroRNAs (miRNAs) are critical regulators in organ development. Among them, miR-191 is known to be regulated in early embryogenesis and dysregulated in cancer. This role in undifferentiated tissues ...suggests a possible part of miR-191 also in bone marrow derived mesenchymal stem cells (BMSCs) physiology. Here, we report that miR-191 decreased MMP expression and migration of BMSCs. Conditioned media of miR-191 overexpressing BMSCs block VEGF expression, and inhibit angiogenesis of HUVECs. Under osteogenic culture conditions, inhibition of miR-191 significantly induces bone formation. Moreover, our studies showed miR-191 might influence chondrogenesis of BMSCs by directly targeting CCAAT Enhancer Binding Protein Beta (CEBPB). Taken together, here we demonstrate the role of miR-191 in differentiation, migration and paracrine function of BMSCs.
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