Differential evolution-assisted salp swarm algorithm with chaotic structure for real-world problems

There is a new nature-inspired algorithm called salp swarm algorithm (SSA), due to its simple framework, it has been widely used in many fields. But when handling some complicated optimization problems, especially the multimodal and high-dimensional optimization problems, SSA will probably have difficulties in convergence performance or dropping into the local optimum. To mitigate these problems, this paper presents a chaotic SSA with differential evolution (CDESSA). In the proposed framework, chaotic initialization and differential evolution are introduced to enrich the convergence speed and accuracy of SSA. Chaotic initialization is utilized to produce a better initial population aim at locating a better global optimal. At the same time, differential evolution is used to build up the search capability of each agent and improve the sense of balance of global search and intensification of SSA. These mechanisms collaborate to boost SSA in accelerating convergence activity. Finally, a series of experiments are carried out to test the performance of CDESSA. Firstly, IEEE CEC2014 competition fuctions are adopted to evaluate the ability of CDESSA in working out the real-parameter optimization problems. The proposed CDESSA is adopted to deal with feature selection (FS) problems, then five constrained engineering optimization problems are also adopted to evaluate the property of CDESSA in dealing with real engineering scenarios. Experimental results reveal that the proposed CDESSA method performs significantly better than the original SSA and other compared methods.

Evolving kernel extreme learning machine for medical diagnosis via a disperse foraging sine cosine algorithm

Kernel extreme learning machine (KELM) has been widely used in the fields of classification and identification since it was proposed. As the parameters in the KELM model have a crucial impact on performance, they must be optimized before the model can be applied in practical areas. In this study, to improve optimization performance, a new parameter optimization strategy is proposed, based on a disperse foraging sine cosine algorithm (DFSCA), which is utilized to force some portions of search agents to explore other potential regions. Meanwhile, DFSCA is integrated into KELM to establish a new machine learning model named DFSCA-KELM. Firstly, using the CEC2017 benchmark suite, the exploration and exploitation capabilities of DFSCA were demonstrated. Secondly, evaluation of the model DFSCA-KELM on six medical datasets extracted from the UCI machine learning repository for medical diagnosis proved the effectiveness of the proposed model. At last, the model DFSCA-KELM was applied to solve two real medical cases, and the results indicate that DFSCA-KELM can also deal with practical medical problems effectively. Taken together, these results show that the proposed technique can be regarded as a promising tool for medical diagnosis.

BI-RADS Reading of Non-Mass Lesions on DCE-MRI and Differential Diagnosis Performed by Radiomics and Deep Learning

Background

A wide variety of benign and malignant processes can manifest as non-mass enhancement (NME) in breast MRI. Compared to mass lesions, there are no distinct features that can be used for differential diagnosis. The purpose is to use the BI-RADS descriptors and models developed using radiomics and deep learning to distinguish benign from malignant NME lesions.

Materials and Methods

A total of 150 patients with 104 malignant and 46 benign NME were analyzed. Three radiologists performed reading for morphological distribution and internal enhancement using the 5th BI-RADS lexicon. For each case, the 3D tumor mask was generated using Fuzzy-C-Means segmentation. Three DCE parametric maps related to wash-in, maximum, and wash-out were generated, and PyRadiomics was applied to extract features. The radiomics model was built using five machine learning algorithms. ResNet50 was implemented using three parametric maps as input. Approximately 70% of earlier cases were used for training, and 30% of later cases were held out for testing.

Results

The diagnostic BI-RADS in the original MRI report showed that 104/104 malignant and 36/46 benign lesions had a BI-RADS score of 4A–5. For category reading, the kappa coefficient was 0.83 for morphological distribution (excellent) and 0.52 for internal enhancement (moderate). Segmental and Regional distribution were the most prominent for the malignant group, and focal distribution for the benign group. Eight radiomics features were selected by support vector machine (SVM). Among the five machine learning algorithms, SVM yielded the highest accuracy of 80.4% in training and 77.5% in testing datasets. ResNet50 had a better diagnostic performance, 91.5% in training and 83.3% in testing datasets.

Conclusion

Diagnosis of NME was challenging, and the BI-RADS scores and descriptors showed a substantial overlap. Radiomics and deep learning may provide a useful CAD tool to aid in diagnosis.

Enzyme-induced morphological transformation of drug carriers: Implications for cytotoxicity and the retention time of antitumor agents

Nanocarriers have been widely employed to deliver chemotherapeutic drugs for cancer treatment. However, the insufficient accumulation of nanoparticles in tumors is an important reason for the poor efficacy of nanodrugs. In this study, a novel drug delivery system with a self-assembled amphiphilic peptide was designed to respond specifically to alkaline phosphatase (ALP), a protease overexpressed in cancer cells. The amphiphilic peptide self-assembled into spherical and fibrous nanostructures, and it easily assembled into spherical drug-loaded peptide nanoparticles after loading of a hydrophobic chemotherapeutic drug. The cytotoxicity of the drug carriers was enhanced against tumor cells over time. These spherical nanoparticles transformed into nanofibers under the induction of ALP, leading to efficient release of the encapsulated drug. This drug delivery strategy relying on responsiveness to an enzyme present in the tumor microenvironment can enhance local drug accumulation at the tumor site. The results of live animal imaging showed that the residence time of the morphologically transformable drug-loaded peptide nanoparticles at the tumor site was prolonged in vivo, confirming their potential use in antitumor therapy. These findings can contribute to a better understanding of the influence of drug carrier morphology on intracellular retention.

Reactive-oxygen-species-scavenging nanomaterials for resolving inflammation

Reactive oxygen species (ROS) mediate multiple physiological functions; however, the over-accumulation of ROS causes premature aging and/or death and is associated with various inflammatory conditions. Nevertheless, there are limited clinical treatment options that are currently available. The good news is that owing to the considerable advances in nanoscience, multiple types of nanomaterials with unique ROS-scavenging abilities that influence the temporospatial dynamic behaviors of ROS in biological systems have been developed. This has led to the emergence of next-generation nanomaterial-controlled strategies aimed at ameliorating ROS-related inflammatory conditions. Accordingly, herein we reviewed recent progress in research on nanotherapy based on ROS scavenging. The underlying mechanisms of the employed nanomaterials are emphasized. Furthermore, important issues in developing cross-disciplinary nanomedicine-based strategies for ROS-based inflammatory conditions are discussed. Our review of this increasing interdisciplinary field will benefit ongoing studies and clinical applications of nanomedicine based on ROS scavenging.

Doppler-based predictive model for methotrexate resistance in low-risk gestational trophoblastic neoplasia with myometrial invasion: prospective study of 147 patients

OBJECTIVES

This prospective clinical study aimed to evaluate the vascularization characteristics of low-risk gestational trophoblastic neoplasia (GTN) using Doppler imaging and to develop a predictive model for resistance to methotrexate (MTX).

METHODS

Patients with low-risk GTN receiving primary MTX treatment were enrolled from the Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China, from September 2012 to August 2018. The primary endpoint was to develop and internally validate a predictive model for resistance to MTX therapy in these patients. In the training set, clinical features and Doppler hemodynamic parameters before MTX therapy were analyzed using logistic regression to identify independent predictors of MTX resistance, which were integrated into the model. The predictive performance of the model was evaluated by leave-one-out cross-validation in the training dataset and internal validation in an independent-sample test dataset.

RESULTS

The entire imaging protocol was completed by 147 eligible patients, of which 110 comprised the training set and 37 the test set. In the training set, cases with myometrial invasion (81.8%; 90/110) showed vascular-enriched areas in the myometrium and high velocity and low impedance ratios of the uterine artery (UtA) compared to cases without myometrial invasion (18.2%; 20/110). On multivariate logistic regression analysis, time-averaged mean velocity in UtA (UtA-TAmean) and the International Federation of Gynecology and Obstetrics (FIGO) score were identified as independent predictors (P = 0.009 and P = 0.043, respectively) of MTX resistance. The Doppler-based predictive model, developed based on the 90 cases with myometrial invasion, was y = -2.95332 + 0.41696 × FIGO score + 0.03551 × UtA-TAmean. The model showed an area under the curve of 0.757 (95% CI, 0.653-0.862) and the optimal cut-off value was 0.50622, which had 45.2% sensitivity and 96.6% specificity. The model stratified patients with low-risk GTN into low (< 10%), intermediate (10-90%) and high (> 90%) probability of MTX resistance, based on the threshold values of -1.59544 and 0.10046. The model had an accuracy of 74.4% (95% CI, 64.5-82.3%) in the cross-validation and 72.7% (95% CI, 55.8-84.9%) in the internal validation.

CONCLUSIONS

The Doppler-based predictive model, combining a non-invasive marker of tumor vascularity with the FIGO scoring system, can differentiate cases with low from those with high probability of developing MTX resistance and therefore has the potential to guide treatment options in patients with low-risk GTN and myometrial invasion. © 2020 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Upregulation of miR-146b promotes porcine ovarian granulosa cell apoptosis by attenuating CYP19A1

MicroRNAs (miRNAs) are 21- to 24-nucleotide long small noncoding RNAs, which play an important role in follicular atresia and granulosa cell (GC) apoptosis in the mammalian ovary. Here, we report that miR-146b, a conserved and ovary-enriched miRNA, modulates estradiol (E2) secretion, GC apoptosis, and follicular atresia in pigs. Genome-wide analysis and quantitative real-time PCR revealed that miR-146b was significantly upregulated during follicular atresia, and fluorescence-activated cell sorting showed that miR-146b functioned as a proapoptotic factor to induce GC apoptosis. MicroRNA-mRNA network analysis and luciferase reporter assays showed that CYP19A1, the pivotal enzyme for E2 synthesis signaling, was directly targeted by miR-146b. Furthermore, miR-146b interacted with the 3'untranslated region of CYP19A1 to prevent translation, thereby regulating CYP19A1-mediated E2 secretion and GC apoptosis. However, miR-146b was not regulated by the transcription factor SMAD4 or oxidative stress, both of which are critical regulators of CYP19A1. We, thus, conclude that miR-146b is a novel epigenetic factor regulating GC functions, follicular development, and female reproduction.

[Value of ALBI grade on precised estimation liver reserve function of patients with hepatocellular carcinoma]

Précised liver reserve function estimation is of great significance for predicting the survival time, post-hepatectomy liver failure and individualized comprehensive treatment strategies in hepatocellular carcinoma (HCC) patients. Currently, the widely used Child-Pugh (CP) classification and indocyanine green 15-minute retention rate (ICGR 15) have certain flaws and limitations. The albumin-bilirubin (ALBI) grading especially makes up for the deficiency of CP classification, and can provide an objective, simple, accurate and evidence-based method to estimate and guide the liver reserve function of HCC patients. This paper follows up and summarizes the research progress of ALBI grading estimation at home and abroad on liver reserve function of HCC patients.

The association between napping and the risk of cardiovascular disease and all-cause mortality: a systematic review and dose-response meta-analysis

Background

Napping is a habit prevalent worldwide and occurs from an early age. Some sleep specialists have suggested it as a potential public health tool due to the prevalence of sleep disorder. However, the association between napping and the risk of cardiovascular disease (CVD) and all-cause mortality remains unclear.

Purpose

To assess the association between napping and the risk of CVD and all-cause mortality.

Methods

We conducted a systematic search of Medline, Embase and Cochrane databases from inception through December 2019 for prospective cohort studies investigating the association between napping and the risk of CVD and/or all-cause mortality. Overall estimates were calculated using random effect models with inverse variance weighting. Dose-response meta-analysis was performed using restricted cubic spline models. The results were reported as hazard ratio (HR) and 95% confidence interval (CI).

Results

A total of 313651 participants (57.8% female, 38.9% took naps) from 20 cohort studies were included in the analysis. Overall, pooled analysis detected no association between daytime nap and CVD (HR 1.13, 95% CI 0.99–1.28). However, in subgroup analysis including only participants who were female (HR 1.31, 95% CI 1.09–1.58), older (age&gt;65 years) (HR 1.36, 95% CI 1.07–1.72), or took a longer nap (nap time&gt;60 minutes) (HR 1.34, 95% CI 1.05–1.63), napping was significantly associated with a higher risk of CVD comparing to not napping. All-cause mortality was associated with napping overall (HR 1.19, 95% CI 1.12–1.26), and effect sizes were even more pronounced in females (HR 1.22, 95% CI 1.13–1.31), older participants (HR 1.27, 95% CI 1.11–1.45) and those who took a long nap (HR 1.30, 95% CI 1.12–1.47). Furthermore, after stratifying participants by night sleep time (&lt;6 and &gt;6h/day), no significant association was detected except those who slept &gt;6h/day at night and took a long nap (HR 1.13, 95% CI 1.03–1.24). Dose-response analysis showed a J-curve relation between nap time and CVD (Figure 1). The HR decreased from 0 to 25 min/day, followed by a sharp increase in the risk at longer times. A positive linear relationship between nap time and all-cause mortality was also observed.

Conclusion

Long napping over 60 minutes per day is associated with increased risks of CVD and all-cause mortality. Night sleep duration may play a role in the relation between napping and all-cause mortality. Further, large-scale prospective cohort studies need to confirm our conclusion and investigate the underlying mechanisms driving these associations.

Funding Acknowledgement

Type of funding source: None

Assessing the impact of drinking water iodine concentrations on the iodine intake of Chinese pregnant women living in areas with restricted iodized salt supply

PURPOSE

The supply of non-iodized salt and the water improvement project have been conducted to reduce the iodine concentration in drinking water in areas with elevated water iodine. We aimed to assess the impact of water iodine concentration (WIC) on the iodine intake of pregnant women in areas with restricted iodized salt supply, and determine the cutoff values of WIC in areas with non-iodized salt supply.

METHODS

Overall, 534 pregnant women who attended routine antenatal outpatient visits in Zibo Maternal and Child Health Hospital in Gaoqing County were recruited. The 24-h urine iodine excretion (UIE) in 534 samples and the iodine concentration in 534 drinking water samples were estimated. Urinary iodine excretion, daily iodine intake, and daily iodine intake from drinking water (WII) were calculated. The relationship between WIC and daily iodine take was analyzed.

RESULTS

The median WIC, spot urine iodine concentration (UIC), and 24-h UIE were 17 (6, 226) μg/L, 145 (88, 267) μg/L, and 190 (110, 390) μg/day, respectively. A significant positive correlation was found between WIC and UIE (R² = 0.265, p < 0.001) and UIC (R² = 0.261, p < 0.001). The contribution rate of WII to total iodine intake increased from 3.0% in the group with WIC of < 10 μg/L to 45.7% in the group with WIC of 50-99 μg/L.

CONCLUSION

The iodine content in drinking water is the major iodine source in pregnant women living in high-water iodine areas where iodized salt supply is restricted. The contribution rate of daily iodine intake from drinking water increases with the increase in water iodine concentration.

Elevated microRNA-125b inhibits cytotrophoblast invasion and impairs endothelial cell function in preeclampsia

Preeclampsia (PE) is a life-threatening disorder of human pregnancy affecting 5-8% of all pregnancies. Currently, PE remains an elusive complicated and heterogenous medical condition with no early marker or symptoms is recognized for this serious pregnancy complications. Here, we profiled the plasma miRNA expression patterns associated with preeclampsia and found 16 miRNAs were deregulated (p < 0.01) in patients who later developed PE. Circulating hsa-miR-125b was aberrantly upregulated in early pregnancy and significantly reduced after delivery in preeclampsia. We then investigated the underlying molecular mechanisms between miR-125b and PE in vitro. We found that upregulated miR-125b can target KCNA1 to inhibit trophoblast invasion in human trophoblast cells. Moreover, overexpression of miR-125b in HUVECs impaired endothelial cell function through GPC1. The findings indicated that upregulated miR-125b leads to impaired placentation, and an increased risk of preeclampsia, Our studies provide novel insights into the underlying mechanisms on the association of miR-125b in early pregnancy and risk of PE, miR-125b might be a more specific predictive marker and a safe therapeutic target for treating patients with PE.

Broadband, millimeter-wave antireflection coatings for large-format, cryogenic aluminum oxide optics

We present two prescriptions for broadband ($ {\sim} 77 - 252\;{\rm GHz} $), millimeter-wave antireflection coatings for cryogenic, sintered polycrystalline aluminum oxide optics: one for large-format (700 mm diameter) planar and plano-convex elements, the other for densely packed arrays of quasi-optical elements-in our case, 5 mm diameter half-spheres (called "lenslets"). The coatings comprise three layers of commercially available, polytetrafluoroethylene-based, dielectric sheet material. The lenslet coating is molded to fit the 150 mm diameter arrays directly, while the large-diameter lenses are coated using a tiled approach. We review the fabrication processes for both prescriptions, then discuss laboratory measurements of their transmittance and reflectance. In addition, we present the inferred refractive indices and loss tangents for the coating materials and the aluminum oxide substrate. We find that at 150 GHz and 300 K the large-format coating sample achieves $ (97 \pm 2)\% $ transmittance, and the lenslet coating sample achieves $ (94 \pm 3)\% $ transmittance.

Mechanical Changes and Microfilament Reorganization Involved in Microcystin-LR-Promoted Cell Invasion in DU145 and WPMY Cells

Microcystin-leucine arginine (MC-LR) is a potent tumor initiator that can induce malignant cell transformation. Cellular mechanical characteristics are pivotal parameters that are closely related to cell invasion. The aim of this study is to determine the effect of MC-LR on mechanical parameters, microfilament, and cell invasion in DU145 and WPMY cells. Firstly, 10 μM MC-LR was selected as the appropriate concentration via cell viability assay. Subsequently, after MC-LR treatment, the cellular deformability and viscoelastic parameters were tested using the micropipette aspiration technique. The results showed that MC-LR increased the cellular deformability, reduced the cellular viscoelastic parameter values, and caused the cells to become softer. Furthermore, microfilament and microfilament-associated proteins were examined by immunofluorescence and Western blot, respectively. Our results showed that MC-LR induced microfilament reorganization and increased the expression of p-VASP and p-ezrin. Finally, the impact of MC-LR on cell invasion was evaluated. The results revealed that MC-LR promoted cell invasion. Taken together, our results suggested that mechanical changes and microfilament reorganization were involved in MC-LR-promoted cell invasion in DU145 and WPMY cells. Our data provide novel information to explain the toxicological mechanism of MC-LR.

Rice momilactone gene cluster: transcriptional response to barnyard grass (Echinochloa crus-galli)

Expression of genes involved in diterpene biosynthesis, especially momilactone and gibberellins (GAs), in rice plants (Oryza sativa L.) in response to barnyard grass (Echinochloa crus-galli) stress was examined. The three analyzed class II diterpene synthases had the highest fold change expression. Transcription patterns of genes for two homologs of momilactone synthases, OsMAS and OsMAS2, suggests their distinct roles in response to the presence of barnyard grass.

Dual roles of misshapen/NIK-related kinase (MINK1) in osteoarthritis subtypes through the activation of TGFβ signaling

OBJECTIVE

To identify the role of misshapen/NIK-related kinase (MINK1) in age-related Osteoarthritis (OA) and injury-induced OA, and the effects of enhanced TGFβ signaling in these progresses.

DESIGN

The effect of MINK1 was analyzed with MINK1 knock out (Mink1-/-) mice and C57BL/6J mice. OA progress was studied in age-related OA and instability-associated OA (destabilization of the medial meniscus, DMM) models. The murine knee joint was evaluated through histological staining, Osteoarthritis Research Society International (OARSI) scores, immunohistochemistry, and μCT analysis. Primary chondrocytes were isolated from wild type and Mink1-/- mice and subjected to osteogenic induction and Western blot analysis.

RESULTS

MINK1 is highly expressed during cartilage development and in normal cartilage. Mink1-/- mice displayed markedly lower OARSI scores, aggrecan degradation neoepitope positive cells and increased Safranin O and pSMAD2 staining in aging-related OA model. However, in injury-induced OA, loss of MINK1 accelerates extracellular matrix (ECM) destruction, osteophyte formation, and subchondral bone sclerosis. Accelerated subchondral bone remodeling in Mink1-/- mice was accompanied with increased numbers of nestin-positive mesenchymal stem cells (MSCs) and osterix-positive osteoprogenitors. pSMAD2 staining was increased in the subchondral bone marrow of Mink1-/- mice and overexpression of MINK1 inhibited SMAD2 phosphorylation in vitro.

CONCLUSIONS

This study shows for the first time that activation of TGFβ/SMAD2 by MINK1 deficiency plays opposite roles in aging-related and injury-induced OA. MINK1 deficiency protects cartilage from degeneration in aging joints through increased SMAD2 activation in chondrocytes, while accelerating OA progress in injury-induced model through enhanced osteogenesis of MSCs in the subchondral bone. These findings provide insights for developing precision OA therapeutics targeting TGFβ/SMAD2 signaling.

Functional expression of the Spodoptera exigua chitinase to examine the virtually screened inhibitor candidates

Chitinase is responsible for insect chitin hydrolyzation, which is a key process in insect molting and pupation. However, little is known about the chitinase of Spodoptera exigua (SeChi). In this study, based on the SeChi gene (ADI24346) identified in our laboratory, we constructed the recombinant baculovirus P-Chi for the expression of recombinant SeChi (rSeChi) in Hi5 cells. The rSeChi was purified by chelate affinity chromatography, and the purified protein showed activity comparable with that of a commercial SgChi, suggesting that we harvested active SeChi for the first time. The purified protein was subsequently tested for enzymatic properties and revealed to exhibit its highest activity at pH 8 and 40 C. Using homology modeling and molecular docking techniques, the three-dimensional model of SeChi was constructed and screened for inhibitors. In two rounds of screening, twenty compounds were selected. With the purified rSeChi, we tested each of the twenty compounds for inhibitor activity against rSeChi, and seven compounds showed obvious activity. This study provided new information for the chitinase of beet armyworm and for chitinase inhibitor development.

Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning With Consideration of Peritumor Tissue

BACKGROUND

Computer-aided methods have been widely applied to diagnose lesions detected on breast MRI, but fully-automatic diagnosis using deep learning is rarely reported.

PURPOSE

To evaluate the diagnostic accuracy of mass lesions using region of interest (ROI)-based, radiomics and deep-learning methods, by taking peritumor tissues into consideration.

STUDY TYPE

Retrospective.

POPULATION

In all, 133 patients with histologically confirmed 91 malignant and 62 benign mass lesions for training (74 patients with 48 malignant and 26 benign lesions for testing).

FIELD STRENGTH/SEQUENCE

3T, using the volume imaging for breast assessment (VIBRANT) dynamic contrast-enhanced (DCE) sequence.

ASSESSMENT

3D tumor segmentation was done automatically by using fuzzy-C-means algorithm with connected-component labeling. A total of 99 texture and histogram parameters were calculated for each case, and 15 were selected using random forest to build a radiomics model. Deep learning was implemented using ResNet50, evaluated with 10-fold crossvalidation. The tumor alone, smallest bounding box, and 1.2, 1.5, 2.0 times enlarged boxes were used as inputs.

STATISTICAL TESTS

The malignancy probability was calculated using each model, and the threshold of 0.5 was used to make a diagnosis.

RESULTS

In the training dataset, the diagnostic accuracy was 76% using three ROI-based parameters, 84% using the radiomics model, and 86% using ROI + radiomics model. In deep learning using the per-slice basis, the area under the receiver operating characteristic (ROC) was comparable for tumor alone, smallest and 1.2 times box (AUC = 0.97-0.99), which were significantly higher than 1.5 and 2.0 times box (AUC = 0.86 and 0.71, respectively). For per-lesion diagnosis, the highest accuracy of 91% was achieved when using the smallest bounding box, and that decreased to 84% for tumor alone and 1.2 times box, and further to 73% for 1.5 times box and 69% for 2.0 times box. In the independent testing dataset, the per-lesion diagnostic accuracy was also the highest when using the smallest bounding box, 89%.

DATA CONCLUSION

Deep learning using ResNet50 achieved a high diagnostic accuracy. Using the smallest bounding box containing proximal peritumor tissue as input had higher accuracy compared to using tumor alone or larger boxes.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2.