A Novel Steganography Method for Infrared Image Based on Smooth Wavelet Transform and Convolutional Neural Network.

Infrared images have been widely used in many research areas, such as target detection and scene monitoring. Therefore, the copyright protection of infrared images is very important. In order to accomplish the goal of image-copyright protection, a large number of image-steganography algorithms have been studied in the last two decades. Most of the existing image-steganography algorithms hide information based on the prediction error of pixels. Consequently, reducing the prediction error of pixels is very important for steganography algorithms. In this paper, we propose a novel framework SSCNNP: a Convolutional Neural-Network Predictor (CNNP) based on Smooth-Wavelet Transform (SWT) and Squeeze-Excitation (SE) attention for infrared image prediction, which combines Convolutional Neural Network (CNN) with SWT. Firstly, the Super-Resolution Convolutional Neural Network (SRCNN) and SWT are used for preprocessing half of the input infrared image. Then, CNNP is applied to predict the other half of the infrared image. To improve the prediction accuracy of CNNP, an attention mechanism is added to the proposed model. The experimental results demonstrate that the proposed algorithm reduces the prediction error of the pixels due to full utilization of the features around the pixel in both the spatial and the frequency domain. Moreover, the proposed model does not require either expensive equipment or a large amount of storage space during the training process. Experimental results show that the proposed algorithm had good performances in terms of imperceptibility and watermarking capacity compared with advanced steganography algorithms. The proposed algorithm improved the PSNR by 0.17 on average with the same watermark capacity.

Investigations on coronary artery plaque detection and subclassification using machine learning classifier.

Coronary artery diseases are one of the high-risk diseases, which occur due to the insufficient blood supply to the heart. The different types of plaques formed inside the artery leads to the blockage of the blood stream. Understanding the type of plaques along with the detection and classification of plaques supports in reducing the mortality of patients. The objective of this study is to present a novel clustering method of plaque segmentation followed by wavelet transform based feature extraction. The extracted features of all different kinds of calcified and sub calcified plaques are applied to first train and test three machine learning classifiers including support vector machine, random forest and decision tree classifiers. The bootstrap ensemble classifier then decides the best classification result through a voting method of three classifiers. A training dataset including 64 normal CTA images and 73 abnormal CTA images is used, while a testing dataset consists of 111 normal CTA images and 103 abnormal CTA images. The evaluation metrics shows better classification rate and accuracy of 97.7%. The Sensitivity and Specificity rates are 97.8% and 97.5%, respectively. As a result, our study results demonstrate the feasibility and advantages of developing and applying this new image processing and machine learning scheme to assist coronary artery plaque detection and classification.

Objective functional assessment using the "Timed Up and Go" test in patients with lumbar spinal stenosis.

OBJECTIVEPatient-reported outcome measures (PROMs) are standard of care for the assessment of functional impairment. Subjective outcome measures are increasingly complemented by objective ones, such as the "Timed Up and Go" (TUG) test. Currently, only a few studies report pre- and postoperative TUG test assessments in patients with lumbar spinal stenosis (LSS).METHODSA prospective two-center database was reviewed to identify patients with LSS who underwent lumbar decompression with or without fusion. The subjective functional status was estimated using PROMs for pain (visual analog scale [VAS]), disability (Roland-Morris Disability Index [RMDI] and Oswestry Disability Index [ODI]), and health-related quality of life (HRQoL; 12-Item Short-Form Physical Component Summary [SF-12 PCS] and the EQ-5D) preoperatively, as well as on postoperative day 3 (D3) and week 6 (W6). Objective functional impairment (OFI) was measured using age- and sex-standardized TUG test results.RESULTSSixty-four patients (n = 32 [50%] male, mean age 66.8 ± 11.7 years) were included. Preoperatively, they reported a mean VAS back pain score of 4.1 ± 2.7, VAS leg pain score of 5.4 ± 2.7, RMDI of 10.4 ± 5.3, ODI of 41.9 ± 16.2, SF-12 PCS score of 32.7 ± 8.3, and an EQ-5D index of 0.517 ± 0.226. The preoperative rates of severe, moderate, and mild OFI were 4.7% (n = 3), 12.5% (n = 8), and 7.8% (n = 5), respectively, and the mean OFI T-score was 116.3 ± 23.7. At W6, 60 (93.8%) of 64 patients had a TUG test result within the normal population range (no OFI); 3 patients (4.7%) had mild and 1 patient (1.6%) severe OFI. The mean W6 OFI T-score was significantly decreased (103.1 ± 13.6; p < 0.001). Correspondingly, the PROMs showed a decrease in subjective VAS back pain (1.6 ± 1.7, p < 0.001) and leg pain (1.0 ± 1.8, p < 0.001) scores, disability (RMDI 5.3 ± 4.7, p < 0.001; ODI 21.3 ± 16.1, p < 0.001), and increase in HRQoL (SF-12 PCS 40.1 ± 8.3, p < 0.001; EQ-5D 0.737 ± 0.192, p < 0.001) at W6. The W6 responder status (clinically meaningful improvement) ranged between 81.3% (VAS leg pain) and 29.7% (EQ-5D index) of patients.CONCLUSIONSThe TUG test is a quick and easily applicable tool that reliably measures OFI in patients with LSS. Objective tests incorporating longer walking time should be considered if OFI is suspected but fails to be proven by the TUG test, taking into account that neurogenic claudication may not clinically manifest during the brief TUG examination. Objective tests do not replace the subjective PROM-based assessment, but add valuable information to a comprehensive patient evaluation.

The effect of low intensity shockwave treatment (Li-SWT) on human myoblasts and mouse skeletal muscle.

BACKGROUND: Transplanting myogenic cells and scaffolds for tissue engineering in skeletal muscle have shown inconsistent results. One of the limiting factors is neovascularization at the recipient site. Low intensity shockwave therapy (Li-SWT) has been linked to increased tissue regeneration and vascularization, both integral to survival and integration of transplanted cells. This study was conducted to demonstrate the response of myoblasts and skeletal muscle to Li-SWT. METHOD: Primary isolated human myoblasts and explants were treated with low intensity shockwaves and subsequently cell viability, proliferation and differentiation were tested. Cardiotoxin induced injury was created in tibialis anterior muscles of 28 mice, and two days later, the lesions were treated with 500 impulses of Li-SWT on one of the legs. The treatment was repeated every third day of the period and ended on day 14 after cardiotoxin injection.. The animals were followed up and documented up to 21 days after cardiotoxin injury. RESULTS: Li-SWT had no significant effect on cell death, proliferation, differentiation and migration, the explants however showed decreased adhesion. In the animal experiments, qPCR studies revealed a significantly increased expression of apoptotic, angiogenic and myogenic genes; expression of Bax, Bcl2, Casp3, eNOS, Pax7, Myf5 and Met was increased in the early phase of regeneration in the Li-SWT treated hind limbs. Furthermore, a late accumulative angiogenic effect was demonstrated in the Li-SWT treated limbs by a significantly increased expression of Angpt1, eNOS, iNOS, Vegfa, and Pecam1. CONCLUSION: Treatment was associated with an early upregulation in expression of selected apoptotic, pro-inflammatory, angiogenic and satellite cell activating genes after muscle injury. It also showed a late incremental effect on expression of pro-angiogenic genes. However, we found no changes in the number of PAX7 positive cells or blood vessel density in Li-SWT treated and control muscle. Furthermore, Li-SWT in the selected doses did not decrease survival, proliferation or differentiation of myoblasts in vitro.

The amino acid's backup bone - storage solutions for proteomics facilities.

Proteomics methods, especially high-throughput mass spectrometry analysis have been continually developed and improved over the years. The analysis of complex biological samples produces large volumes of raw data. Data storage and recovery management pose substantial challenges to biomedical or proteomic facilities regarding backup and archiving concepts as well as hardware requirements. In this article we describe differences between the terms backup and archive with regard to manual and automatic approaches. We also introduce different storage concepts and technologies from transportable media to professional solutions such as redundant array of independent disks (RAID) systems, network attached storages (NAS) and storage area network (SAN). Moreover, we present a software solution, which we developed for the purpose of long-term preservation of large mass spectrometry raw data files on an object storage device (OSD) archiving system. Finally, advantages, disadvantages, and experiences from routine operations of the presented concepts and technologies are evaluated and discussed. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Efficient inhibition of growth of metastatic cancer cells after resection of primary colorectal cancer by soluble Flt-1.

Removal of primary tumors often leads to increases in growth of metastatic tumor cells. Thus, development of an efficient treatment to inhibit the growth of metastatic tumor cells after resection of primary tumors appears to be critical for cancer therapy. Here, we reported that administration of a Chinese medicine Shiquandabutao (SQDBT) after removal of the primary cancer significantly inhibited the growth of metastatic cancer cells in mouse liver. Further analyses showed that the effect of SQDBT resulted from one of its main component, Siwutang (SWT), rather than from another main component, Sijunzitang (SJZT). Moreover, we found that the soluble Flt-1 from SWT neutralized the increased placental growth factor (PLGF) secreted by the metastatic cancer cells after primary cancer resection and subsequently inhibited the cancer neovascularization to suppress the metastatic cancer growth. Thus, our study reveals an essential role of SQDBT in inhibiting the growth of metastatic cancer after removal of primary cancer and further highlights PLGF as a potential target for metastatic cancer treatment.

High-resolution crystal structure reveals a HEPN domain at the C-terminal region of S. cerevisiae RNA endonuclease Swt1.

Swt1 is an RNA endonuclease that plays an important role in quality control of nuclear messenger ribonucleoprotein particles (mRNPs) in eukaryotes; however, its structural details remain to be elucidated. Here, we report the crystal structure of the C-terminal (CT) domain of Swt1 from Saccharomyces cerevisiae, which shares common characteristics of higher eukaryotes and prokaryotes nucleotide binding (HEPN) domain superfamily. To study in detail the full-length protein structure, we analyzed the low-resolution architecture of Swt1 in solution using small angle X-ray scattering (SAXS) method. Both the CT domain and middle domain exhibited a good fit upon superimposing onto the molecular envelope of Swt1. Our study provides the necessary structural information for detailed analysis of the functional role of Swt1, and its importance in the process of nuclear mRNP surveillance.

Clinical improvement and resorption of calcifications in calcific tendinitis of the shoulder after shock wave therapy at 6 months' follow-up: a systematic review and meta-analysis.

OBJECTIVES: To evaluate the effectiveness of shock wave therapy (SWT) for functional improvement and the reduction of pain in patients with calcific tendinitis of the shoulder, and to determine the rate of disappearance of calcifications after therapy at 6 months' follow-up. DATA SOURCES: Articles were searched from the Cochrane Library, MEDLINE, Embase, CINAHL, and Ovid database. STUDY SELECTION: We included randomized controlled trials from 1992 to 2011, and their quality was assessed using the Physiotherapy Evidence Database (PEDro) scale. DATA EXTRACTION: Studies were evaluated by 2 independent reviewers for their methodologic quality. Disagreements were settled by a third reviewer. Data were then extracted and cross-checked for accuracy. The reviewers were not blinded to the authors of the articles. DATA SYNTHESIS: In 4 of the 6 studies included for review, the resorption of calcifications was evaluated using meta-analysis because the studies had 2 treatment groups, while the other 2 studies were analyzed descriptively because they had 3 treatment groups. Fixed- and random-effects models were used to meta-analyze total and partial resorption ratios, and I(2) statistics were calculated to assess heterogeneity. CONCLUSIONS: We found a clinical improvement with a pooled total resorption ratio of 27.19 (95% confidence interval [CI], 7.20-102.67) and a pooled partial resorption ratio of 16.22 (95% CI, 3.33-79.01). SWT increases shoulder function, reduces pain, and is effective in dissolving calcifications. These results were maintained over the following 6 months.

Heartbeat detection from high-density EMG electrodes on the upper arm at different EMG intensity levels using Zephlet.

BACKGROUND AND OBJECTIVES: A significant number of global deaths caused by cardiac arrhythmias can be prevented with accurate and immediate identification. Wearable devices can play a critical role in such identification by continuously monitoring cardiac activity using electrocardiogram (ECG). The existing body of research has focused on extracting cardiac information from the body surface by investigating various electrode locations and algorithm development for ECG interpretation. The present study was designed for heartbeat detection using the signals recorded from the upper arm. METHODS: Firstly, optimal electrode locations on the upper arm were identified for Rest and elbow flexion (EF) conditions. Next, a synthesized ECG was generated using the selected electrodes with generalized weights over subjects and trials, and then zero-phase wavelet (Zephlet) was applied for feature extraction. Heartbeat detection was finally performed using the extracted detail coefficients incorporated with a multiagent detection scheme (MDS). RESULTS: The F1-score for heartbeat detection was 0.94  ±  0.16, 0.86  ±  0.22, 0.79  ±  0.26, and 0.67  ±  0.31 for Rest and EF with three different levels of muscle contraction (C1 to C3), respectively. Changing the acceptable distance between the detected and actual heartbeats from 50 ms to 20 ms, the F1-score changed to 0.81  ±  0.20, 0.66  ±  0.26, 0.57  ±  0.26,  and 0.44  ±  0.26 for Rest and C1 to C3, respectively. CONCLUSION: These findings make several contributions to the current literature, summarized as precise and consistent electrode localization for various muscle contraction levels and accurate heartbeat detection method development for each of these conditions.

Savonius wind turbine blade design and performance evaluation using ANN-based virtual clone: A new approach.

The drag based Savonius wind turbine (SWT) has shown immense potential for renewable power generation in built-up areas under complex urban wind conditions. While a series of studies have been conducted on improving SWT's efficiency, optimal performance has yet to be achieved using traditional design approaches such as experimental and/or computational fluid dynamics methods. Recently, artificial intelligence and machine learning have been widely used in design optimization. As such, an ANN-based virtual clone can be an alternative to traditional design methods for wind turbine performance determination. Therefore, the main goal of this study is to investigate whether ANN-based virtual clones are capable of determining the performance of SWTs with a shorter timeframe and minimal resources compared to traditional methods. To achieve the objective, an ANN-based virtual clone model is developed. Two sets of data (computational and experimental) are used to validate and determine the efficacy of the proposed ANN-based virtual clone model. Using experimental data, the model's fidelity is over 98%. The proposed model produces results in one-fifth the time of the existing simulation (based on the combined ANN + GA metamodel) method. The model also reveals the location of the dataset's optimized point for augmenting the turbine's performance.

Improvement of pixel classification by the simultaneous use of spectral and spatial information in the framework of spectroscopic imaging.

Hyperspectral imaging technology is developing in a very fast way. We find it today in many analytical developments using different spectroscopies for sample classification purposes. Instrumental developments allow us to acquire more and more data in shorter and shorter periods of time while improving their quality. Therefore, we are going in the right direction as far as the measure is concerned. On the other hand, we can make a more mixed assessment for the hyperspectral imaging data processing. Indeed, the data acquired in spectroscopic imaging have the particularity of encoding both spectral and spatial information. Unfortunately, in chemometrics, almost all classification approaches today only use spectral information from three-dimensional hyperspectral data arrays. To be more precise, an approach encompassing the unfolding/refolding of such arrays is often applied beforehand because the majority of algorithms for analysing these data are not capable of handling them in their original structure. Spatial information is therefore lost during the chemometric exploration. The study of the spectral part of the acquired data array alone is clearly a limitation that we propose to overcome in this work. 2-D Stationary Wavelet Transform will be used in the data preprocessing phase to ensure the joint use of spectral and spatial information. Two spectroscopic datasets will then be used to evaluate the potential of our approach in the context of supervised classification.

Application of artificial intelligence based on synchrosqueezed wavelet transform and improved deep extreme learning machine in water quality prediction.

Water quality prediction is the basis for the prevention and control of water pollution. In this paper, to address the problem of low prediction accuracy of existing empirical models due to the non-smoothness and nonlinearity of water quality series, a novel water quality forecasting model integrating synchrosqueezed wavelet transform and deep extreme learning machine optimized with the sparrow search algorithm (SWT-SSA-DELM) was proposed. First, the water quality series was denoised by SWT to reduce the non-stationarity and randomness of water quality series. Then, construct DELM by combining ELM and an autoencoder, and an innovative metaheuristic algorithm, SSA, was used to optimize the hyperparameters of the DELM. Finally, the constructed feature vector was used as the input of the DELM, and the proposed water quality prediction model SWT-SSA-DELM was trained and tested with the data sets of Xinchengqiao and Xiaolangdi in the Yellow River Basin, China. Models such as ELM and DELM alone, as well as their improved form based on ensemble learning, long short-term memory network (LSTM), autoregressive integrated moving average (ARIMA) were adopted as comparison models. The results make it evident that the model presented, linking the ability to ensure convergence to the global optima of the SSA with the nonlinear mapping of the DELM, outperforms similar models in terms of predictive performance, with average MAE, MAPE, and RMSE of 0.15, 2.02%, and 0.21 in the test stage, which is 72.82%, 72.88%, and 74.32% lower than the baseline ELM model, respectively.

Circ-SWT1 Ameliorates H2O2-Induced Apoptosis, Oxidative Stress and Endoplasmic Reticulum Stress in Cardiomyocytes via miR-192-5p/SOD2 Axis.

Acute myocardial infarction (AMI) is a most serious cardiovascular disease. Increasing findings have indicated that circular RNAs (circRNAs) serve as competent biomarkers in the process of AMI. Herein, our study aimed to probe the functions of circ-SWT1 in cardiomyocyte injury after AMI. H2O2-induced human cardiomyocyte cell line AC16 were used for expression and function analyses. The levels of genes and proteins were detected by qRT-PCR and western blotting. Cell apoptosis was analyzed by flow cytometry and caspase3 activity analysis. The oxidative stress injury was evaluated by detecting the levels of reactive oxygen species (ROS), malondialdehyde and superoxide dismutase (SOD). Western blotting was used to detect the expressions of apoptosis-related markers and endoplasmic reticulum stress (ERS) markers. Dual-luciferase reporter, RIP and pull-down assays were applied to confirm the interaction between miR-192-5p and circ-SWT1 or SOD2. H2O2 treatment significantly decreased circ-SWT1 expression in cardiomyocytes, functionally, ectopic expression of circ-SWT1 attenuated H2O2-triggered apoptosis, oxidative stress and endoplasmic reticulum (ER) stress in cardiomyocytes in vitro. Mechanistically, circ-SWT1 competitively bound to miR-192-5p to relieve the repression of miR-192-5p on its target SOD2. Further rescue experiments showed that miR-192-5p upregulation reversed the inhibitory effects of circ-SWT1 on H2O2-induced cardiomyocyte injury. Moreover, miR-192-5p inhibition protected cardiomyocytes against H2O2-evoked apoptosis, oxidative stress and ER stress, which were abolished by SOD2 silencing. Circ-SWT1 ameliorates H2O2-induced apoptosis, oxidative stress and ER stress in cardiomyocytes via miR-192-5p/SOD2 axis, suggesting the potential involvement of circ-SWT1 in AMI process.

Elucidating the pharmacological mechanism by which Si-Wu-Tang induces cellular senescence in breast cancer via multilevel data integration.

Traditional Chinese medicine (TCM) is a promising strategy for effectively treating cancer by inducing cellular senescence with minimal side effects. Si-Wu-Tang (SWT) is a TCM composed of four herbs that is commonly used in China for the treatment of gynecological diseases; SWT can prevent breast cancer (BC), but the molecular mechanism by which SWT induces cellular senescence and its clinical application value remain unknown. We identified 335 differentially expressed genes (DEGs) in SWT-treated MCF-7 cells through Gene Expression Omnibus (GEO) dataset analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed the enrichment of biological processes and key signaling pathways including cellular senescence, the cell cycle, the MAPK signaling pathway, and the p53 signaling pathway. Additionally, SWT induced BC cell senescence by upregulating the expression of 33 aging/senescence-induced genes (ASIGs). According to LASSO regression analysis, NDRG1, ERRFI1, SOCS1, IRS2, IGFBP4, and BIRC3 levels were associated with BC prognosis and were used to develop risk scores. ERRFI1, SOCS1, IRS2, IGFBP4, and BIRC3 were identified as protective factors (P < 0.05, HR < 1), while NDRG1 was identified as a risk factor (P < 0.05, HR > 1). Notably, patients with low risk scores had increased senescence-associated secretory phenotypes (SASPs) and immune cell infiltration. Overall, we systematically integrated biological databases and biocomputational methods to reveal the mechanisms by which SWT induces senescence in breast cancer and its clinical value.

Domestication and improvement genes reveal the differences of seed size- and oil-related traits in soybean domestication and improvement.

To address domestication and improvement studies of soybean seed size- and oil-related traits, a series of domesticated and improved regions, loci, and candidate genes were identified in 286 soybean accessions using domestication and improvement analyses, genome-wide association studies, quantitative trait locus (QTL) mapping and bulked segregant analyses in this study. As a result, 534 candidate domestication regions (CDRs) and 458 candidate improvement regions (CIRs) were identified in this study and integrated with those in five and three previous studies, respectively, to obtain 952 CDRs and 538 CIRs; 1469 loci for soybean seed size- and oil-related traits were identified in this study and integrated with those in Soybase to obtain 433 QTL clusters. The two results were intersected to obtain 245 domestication and 221 improvement loci for the above traits. Around these trait-related domestication and improvement loci, 7 domestication and 7 improvement genes were found to be truly associated with these traits, and 372 candidate domestication and 87 candidate improvement genes were identified using gene expression, SNP variants in genome, miRNA binding, KEGG pathway, DNA methylation, and haplotype analysis. These genes were used to explain the trait changes in domestication and improvement. As a result, the trait changes can be explained by their frequencies of elite haplotypes, base mutations in coding region, and three factors affecting their expression levels. In addition, 56 domestication and 15 improvement genes may be valuable for future soybean breeding. This study can provide useful gene resources for future soybean breeding and molecular biology research.

Nephrectomy Delay of More than 10 Weeks from Diagnosis Is Associated with Decreased Overall Survival in pT3 RCC.

In this study, we aimed to evaluate the impact of surgical wait time (SWT) on outcomes of patients with renal cell carcinoma (RCC), and to investigate risk factors associated with prolonged SWT. Using the National Cancer Database, we retrospectively reviewed the records of patients with pT3 RCC treated with radical or partial nephrectomy between 2004 and 2014. The cohort was divided based on SWT. The primary outcome was 5-year overall survival (OS). Logistic regression analysis was used to investigate the risk factors associated with delayed surgery. Cox proportional hazards models were fitted to assess relations between SWT and 5-year OS after adjusting for confounding factors. A total of 22,653 patients were included in the analysis. Patients with SWT > 10 weeks had higher occurrence of upstaging. Using logistic regression, we found that female patients, African-American or Spanish origin patients, treatment in academic or integrated network cancer center, lack of insurance, median household income of <$38,000, and the Charlson-Deyo score of ≥1 were more likely to have prolonged SWT. SWT > 10 weeks was associated with decreased 5-year OS (hazard ratio [HR], 1.24; 95% confidence interval [CI], 1.15-1.33). This risk was not markedly attenuated after adjusting for confounding variables, including age, gender, race, insurance status, Charlson-Deyo score, tumor size, and surgical margin status (adjusted HR, 1.13; 95% CI, 1.04-1.24). In conclusion, the vast majority of patients underwent surgery within 10 weeks. There is a statistically significant trend of increasing SWT over the study period. SWT > 10 weeks is associated with decreased 5-year OS.

Virtual screening of the multi-gene regulatory molecular mechanism of Si-Wu-tang against non-triple-negative breast cancer based on network pharmacology combined with experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: Si-Wu-Tang (SWT), a prestigious herbal formula from China, has been extensively used for centuries for female-related diseases. It has been documented that SWT has a significant inhibitory effect on non-triple-negative breast cancer (non-TNBC) cells. However, there has been limited comprehensive analysis of the targeted effects of the anticancer components of SWT and its exact biological mechanism. AIM OF THE STUDY: This study aims to uncover the mechanism by which SWT treats non-TNBC by applying a network pharmacological method combined with experimental validation. MATERIALS AND METHODS: First, SWT compounds were collected from the Traditional Chinese Medicines Systems Pharmacology database (TCMSP) and The Encyclopedia of Traditional Chinese Medicine (ETCM), and then the targets related to SWT were obtained from the TCMSP and SwissTarget databases. Second, a target data set of non-TNBC proteins was established by using the Online Mendelian Inheritance in Man (OMIM), GeneCards and Gene Expression Omnibus (GEO) databases. Third, based on the overlap of targets between SWT and non-TNBC, a protein-protein interaction (PPI) network was built to analyse the interactions among these targets, which focused on screening for hub targets by topology. On these hub genes, we conducted a meta-analysis and survival analysis to screen the best match targets, ESR1, PPARG, CAT, and PTGS2, which had a strong correlation with the ingredients of SWT in our verification by molecular docking. In vitro experiments further proved the reliability of the network pharmacology findings. Finally, FunRich software and the ClusterProfiler package were utilized for the enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data. RESULTS: A total of 141 active ingredients and 116 targets of SWT were selected. GO enrichment analysis showed that the biological processes through which SWT acted against non-TNBC (FDR<0.01) mainly involved modulating energy metabolism and apoptosis. According to RT-qPCR and Western blotting, the mRNA and protein expression of ESR1, PPARG and PTGS2 were upregulated (P < 0.01), and the mRNA and protein levels of CAT were downregulated (P < 0.01), suggesting a multi-gene regulatory molecular mechanism of SWT against non-triple-negative breast cancer. CONCLUSIONS: This research explored the multi-gene pharmacological mechanism of action of SWT against non-TNBC through network pharmacology and in vitro experiments. The findings provide new ideas for research on the mechanism of action of Chinese medicine against breast cancer.

Fusing spectral and spatial information with 2-D stationary wavelet transform (SWT 2-D) for a deeper exploration of spectroscopic images.

Nowadays, it is clear that there is an increasing importance in spectroscopic imaging in all fields of science. Obviously, one bulk analysis can no longer be satisfactory, as the interest focuses more on the chemical nature and the location of the compounds present within a given complex matrix. This is, evidently, due to the fact that for a more comprehensive exploration of complex samples, one single acquired hyperspectral data cube can provide both spectral and spatial information simultaneously. Although many techniques were proposed by the chemometric community in explorations of these specific datasets, unfortunately, they are almost always focusing on spectral information, even if chemical images were ultimately observed. In other words, spatial information is not well exploited, and therefore lost during the actual chemometric calculation phase. The goal of this short communication is to present a very simple and fast spectral/spatial fusion approach based on 2-D stationary wavelet transform (SWT 2-D) which is able to improve the obtainable information, compared with a classical data analysis, in which the spatial domain would not be considered nor used.

Motor Impairment and Its Influence in Gait Velocity and Asymmetry in Community Ambulating Hemiplegic Individuals.

OBJECTIVES: To determine the most important motor impairments that are predictors of gait velocity and spatiotemporal symmetrical ratio in patients with stroke. DESIGN: Cross-sectional, descriptive analysis study. SETTING: Human performance laboratory of the University of Santo Tomas. PARTICIPANTS: Individuals with chronic stroke (N=55; 34 men, 21 women) who are community dwellers. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The gait velocity and spatiotemporal symmetrical ratio (step length; step, stance, swing, single-leg support, and double-leg support stance times) was determined using Vicon motion capture. We also calculated motor impairment of the leg and foot using Brunnstrom's stages of motor recovery, evaluated muscle strength using the scoring system described by Collin and Wade, and assessed spasticity using by the modified Ashworth Scale. RESULTS: Regression analysis showed that plantarflexor strength is a predictor of gait velocity and all temporospatial symmetry ratio. Knee flexor and extensor strength are predictors in single-leg support time and double-leg support time symmetry ratio, respectively. On the other hand, hip adductor and quadriceps spasticity are predictors of swing time and step length symmetry ratio. CONCLUSION: Different motor impairments are predictors of stroke gait abnormality. Interventions should be focused on these motor impairments to allow for optimal gait rehabilitation results.

Retrospective comparison of focused shockwave therapy and radial wave therapy for men with erectile dysfunction.

BACKGROUND: Low-intensity shockwave therapy (SWT) is an emerging treatment for erectile dysfunction (ED). Devices used for SWT include focused shockwave therapy (fSWT) or radial wave therapy (rWT), which differ in how the waves are generated, their tissue penetration, and the shape of their pressure waves. Most studies of SWT for ED to date have utilized fSWT. Although widely used, the efficacy of rWT for ED is unknown. Our objective is to compare the efficacy of rWT and fSWT for ED at our institution. METHODS: A retrospective chart review was performed to identify all men with ED treated by fSWT or rWT. Men with history suggesting non-vasculogenic ED were excluded. All men received 6 consecutive weekly treatments. The fSWT group received 3,000 shocks per treatment at 0.09 mJ/mm2. The rWT group received 10,000 shocks per treatment at 90 mJ and 15 Hz. Pre-treatment and 6-week post-treatment Sexual Health Inventory in Men (SHIM) scores were measured. Treatment response was categorized on a scale of 1-3 (1 if no improvement, 2 if erections sufficient for intercourse with phosphodiesterase 5 inhibitors (PDE5i), or 3 if sufficient erections without PDE5i). Primary endpoint was self-reported improvement score of 2 or greater. RESULTS: A total of 48 men were included: 24 treated by fSWT and 24 by rWT. There were no significant differences in age, duration of ED, pre-treatment PDE5i use, or pre-treatment SHIM scores between the groups. Following treatment with rWT, the mean SHIM score improved from 9.3 to 16.1 (P<0.001). The mean SHIM following fSWT improved from 9.3 to 15.5 (P<0.001). The mean improvement in SHIM score did not differ between rWT (6.8) and fSWT (6.2) (P=0.42). 54% of men treated by fSWT experienced a significant clinical improvement (≥ grade 2 response) compared to 75% in the rWT group (P=0.42). There were no reported side effects with either device. CONCLUSIONS: In our patient population, both fSWT and rWT were moderately effective treatments for arteriogenic ED with no observable difference in efficacy between the two modalities.