Cognitive protection and brain entropy changes from omega-3 polyunsaturated fatty acids supplement in late-life depression: A 52-week randomized controlled trial.

BACKGROUND: Late-life depression (LLD) is associated with risk of dementia, yet intervention of LLD provides an opportunity to attenuate subsequent cognitive decline. Omega-3 polyunsaturated fatty acids (PUFAs) supplement is a potential intervention due to their beneficial effect in depressive symptoms and cognitive function. To explore the underlying neural mechanism, we used resting-state functional MRI (rs-fMRI) before and after omega-3 PUFAs supplement in older adults with LLD. METHODS: A 52-week double-blind randomized controlled trial was conducted. We used multi-scale sample entropy to analyze rs-fMRI data. Comprehensive cognitive tests and inflammatory markers were collected to correlate with brain entropy changes. RESULTS: A total of 20 patients completed the trial with 11 under omega-3 PUFAs and nine under placebo. While no significant global cognitive improvement was observed, a marginal enhancement in processing speed was noted in the omega-3 PUFAs group. Importantly, participants receiving omega-3 PUFAs exhibited decreased brain entropy in left posterior cingulate gyrus (PCG), multiple visual areas, the orbital part of the right middle frontal gyrus, and the left Rolandic operculum. The brain entropy changes of the PCG in the omega-3 PUFAs group correlated with improvement of language function and attenuation of interleukin-6 levels. LIMITATIONS: Sample size is small with only marginal clinical effect. CONCLUSION: These findings suggest that omega-3 PUFAs supplement may mitigate cognitive decline in LLD through anti-inflammatory mechanisms and modulation of brain entropy. Larger clinical trials are warranted to validate the potential therapeutic implications of omega-3 PUFAs for deterring cognitive decline in patients with late-life depression.

Radiotranscriptomics of non-small cell lung carcinoma for assessing high-level clinical outcomes using a machine learning-derived multi-modal signature.

BACKGROUND: Multi-omics research has the potential to holistically capture intra-tumor variability, thereby improving therapeutic decisions by incorporating the key principles of precision medicine. The purpose of this study is to identify a robust method of integrating features from different sources, such as imaging, transcriptomics, and clinical data, to predict the survival and therapy response of non-small cell lung cancer patients. METHODS: 2996 radiomics, 5268 transcriptomics, and 8 clinical features were extracted from the NSCLC Radiogenomics dataset. Radiomics and deep features were calculated based on the volume of interest in pre-treatment, routine CT examinations, and then combined with RNA-seq and clinical data. Several machine learning classifiers were used to perform survival analysis and assess the patient's response to adjuvant chemotherapy. The proposed analysis was evaluated on an unseen testing set in a k-fold cross-validation scheme. Score- and concatenation-based multi-omics were used as feature integration techniques. RESULTS: Six radiomics (elongation, cluster shade, entropy, variance, gray-level non-uniformity, and maximal correlation coefficient), six deep features (NasNet-based activations), and three transcriptomics (OTUD3, SUCGL2, and RQCD1) were found to be significant for therapy response. The examined score-based multi-omic improved the AUC up to 0.10 on the unseen testing set (0.74 ± 0.06) and the balance between sensitivity and specificity for predicting therapy response for 106 patients, resulting in less biased models and improving upon the either highly sensitive or highly specific single-source models. Six radiomics (kurtosis, GLRLM- and GLSZM-based non-uniformity from images with no filtering, biorthogonal, and daubechies wavelets), seven deep features (ResNet-based activations), and seven transcriptomics (ELP3, ZZZ3, PGRMC2, TRAK1, ATIC, USP7, and PNPLA2) were found to be significant for the survival analysis. Accordingly, the survival analysis for 115 patients was also enhanced up to 0.20 by the proposed score-based multi-omics in terms of the C-index (0.79 ± 0.03). CONCLUSIONS: Compared to single-source models, multi-omics integration has the potential to improve prediction performance, increase model stability, and reduce bias for both treatment response and survival analysis.

[Identification of quality markers of Gei Herba based on analytic hierarchy process-entropy weight method and network pharmacology].

Analytic hierarchy process(AHP)-entropy weight method(EWM) and network pharmacology were employed to identify the potential quality markers(Q-markers) of Gei Herba. According to the new concept of Q-markers in traditional Chinese medicine(TCM), the AHP-EWM was applied to quantitatively identify the Q-markers of Gei Herba. The AHP was used for the weight analysis of primary indicators(factor layer), and the EWM for the analysis of literature and experimental data of secondary indicators(control layer). In addition, network pharmacology was employed to build the "component-target-disease-efficacy" network for Gei Herba, and the components showing strong associations with the Qi-replenishing, spleen-invigorating, blood-tonifying, Yin-nourishing, lung-moistening, and phlegm-resolving effects of Gei Herba were screened out. According to the results of AHP-EWM and network pharmacology, four components, i.e., ellagic acid, gallic acid, gemin G, and gemin C, were finally identified as potential Q-markers of Gei Herba. In this study, the AHP-EWM and network pharmacology were employed to screen the Q-markers of Gei Herba, which provided ideas for the quantitative evaluation and identification of Q-markers of TCM.

[Optimization of extraction process for classic prescription Yihuang Decoction based on Box-Behnken design-response surface methodology, standard relation, and analytic hierarchy process combined with entropy weight method].

Based on the concept of quality by design(QbD), the Box-Behnken design-response surface methodology combined with standard relation(SR) and analytic hierarchy process(AHP)-entropy weight method(EWM) was applied to optimize the extraction process of the classic prescription Yihuang Decoction. The content of geniposidic acid, phellodendrine hydrochloride, and berberine hydrochloride in Yihuang Decoction, the extract yield, and fingerprint similarity were used as the critical quality attributes(CQAs) of the extraction process. The extraction time, water addition, and extraction times were used as the critical process parameters(CPPs). After determining the levels of each factor and level through single-factor experiments, response surface experiments were designed according to the Box-Behnken principle, and the experimental results were analyzed. The SR between each sample and the reference sample under various evaluation indicators of different extraction parameters was calculated. The weights of the five evaluation indicators were determined using AHP-EWM, followed by comprehensive evaluation. A function model between CPPs and CQAs characterized by comprehensive scores was established to predict the optimal extraction process parameters. In the final comprehensive weight coefficients, the yield rate accounted for 43.1%, and the content of berberine hydrochloride, phellodendrine hydrochloride, and geniposidic acid accounted for 35.1%, 6.3%, and 15.5%, respectively. After comprehensive score analysis with SR, the established second-order polynomial model was statistically significant(P<0.01, and the lack of fit was not significant). The predicted optimal extraction conditions for Yihuang Decoction were determined as follows: 8-fold volume of water, extraction time of 1.5 h, and extraction once. The mean comprehensive score of the validation experiment was 85.77, with an RSD of 0.99%, and it met the quality control stan-dards for the reference sample of Yihuang Decoction. The results indicate that the optimized extraction process for Yihuang Decoction is stable and reliable, and the water extract is close in quality attributes to the reference sample. This can serve as a foundation for the research and development of granules in the future. Box-Behnken design-response surface methodology combined with SR and AHP-EWM can provide references for the modern extraction process research of other classic prescriptions.

Traditional Chinese Medicine studies for Alzheimer's disease via network pharmacology based on entropy and random walk.

Alzheimer's disease (AD) is a common neurodegenerative disease having complex pathogenesis, approved drugs can only alleviate symptoms of AD for a period of time. Traditional Chinese medicine (TCM) contains multiple active ingredients that can act on multiple targets simultaneously. In this paper, a novel algorithm based on entropy and random walk with the restart of heterogeneous network (RWRHE) is proposed for predicting active ingredients for AD and screening out the effective TCMs for AD. First, Six TCM compounds containing 20 herbs from the AD drug reviews in the CNKI (China National Knowledge Internet) are collected, their active ingredients and targets are retrieved from different databases. Then, comprehensive similarity networks of active ingredients and targets are constructed based on different aspects and entropy weight, respectively. A comprehensive heterogeneous network is constructed by integrating the known active ingredient-target association information and two comprehensive similarity networks. Subsequently, bi-random walks are applied on the heterogeneous network to predict active ingredient-target associations. AD related targets are selected as the seed nodes, a random walk is carried out on the target similarity network to predict the AD-target associations, and the associations of AD-active ingredients are inferred and scored. The effective herbs and compounds for AD are screened out based on their active ingredients' scores. The results measured by machine learning and bioinformatics show that the RWRHE algorithm achieves better prediction accuracy, the top 15 active ingredients may act as multi-target agents in the prevention and treatment of AD, Danshen, Gouteng and Chaihu are recommended as effective TCMs for AD, Yiqitongyutang is recommended as effective compound for AD.

Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method.

The processing of toxic ethnomedicines is of great significance for their safe clinical application. Thus, the limitations of traditional processing should be addressed, and the processing method of ethnomedicines should be standardized using modern research methods. In this study, the processing technology of a commonly used Tibetan medicine Tiebangchui (TBC), the dried root of Aconitum pendulum Busch, processed with highland barley wine was optimized. Diester-diterpenoid alkaloid (DDA) (aconitine, 3-deoxyaconitine, 3-acetylaconitine) and monoester-diterpenoid alkaloid (MDA) (benzoylaconine) content were used as evaluation indicators, and the weight coefficient of each evaluation index was determined by the entropy method. The single factor test and Box-Behnken design were used in investigating the influence of the ratio between highland barley wine and TBC, slice thickness of TBC, and processing time. Comprehensive scoring was performed according to the objective weight of each index determined by the entropy method. The optimal processing conditions of TBC with highland barley wine were as follows: the amount of highland barley wine is five times that of TBC, a soaking time of 24 h, and a TBC thickness of 1.5 cm. The results showed that the relative standard deviation between the verification test and predicted value was less than 2.55% and the optimized processing technology of TBC processed with highland barley wine is simple, feasible, and stable, and so can provide a reference for industrial production.

[Quality evaluation of Huocao based on UPLC fingerprint and multi-component content determination].

Huocao(a traditional Chinese herbal medicine) moxibustion is a characteristic technology in Yi medicine suitable for cold-dampness diseases. Huocao, as the moxibustion material, is confusedly used in clinical practice and little is known about its quality control. In this study, UPLC method was used to establish the chemical fingerprint of non-volatile components in Huocao, and the contents of eight phenolic acids such as chlorogenic acid were determined. Multivariate statistical analysis was performed to obtain the indicator components of Huocao for quality evaluation, and thus a comprehensive evaluation system for the quality of Huocao was built. The UPLC fingerprints of 49 batches of Huocao were established, and there were 20 common peaks, of which eight phenolic acids including neochlorogenic acid and chlorogenic acid were identified. Except for three batches of Huocao, the similarity of the other 46 batches was higher than 0.89, suggesting that the established fingerprint method could be used for quality control of the medicinal herb. The correlation coefficient between entropy weight score of the eight phenolic acids and comprehensive fingerprint score in Huocao was 0.875(P<0.01), which indicated that the eight phenolic acids could be used as indicator components for the quality evaluation of Huocao. Furthermore, in multivariate statistical analysis on the common peaks of fingerprint and the contents of the eight phenolic acids, chlorogenic acid, isochlorogenic acid A and isochlorogenic acid C were screened to be the indicator components. The results revealed that the proposed method achieved a simple and accurate quality control of Huocao based on UPLC fingerprint and multi-component content determination, which provided useful data for establishing the quality standard of Huocao.

Comprehensive quality evaluation of Tangwei capsule based on HPLC-QAMS multi-index quantitative determination combined with chemometrics and EW-TOPSIS method. / é«˜æ•ˆæ¶²ç›¸ä¸€æµ‹å¤šè¯„æ³•å¤šæŒ‡æ ‡æˆåˆ†å®šé‡è”åˆåŒ–å­¦è®¡é‡å­¦ã€ç†µæƒä¼˜åŠ£è§£è·ç¦»æ³•ç”¨äºŽç³–ç»´èƒ¶å›Šç»¼åˆè´¨é‡è¯„ä»·.

OBJECTIVES: To detect the contents of Tangwei capsule main components with high performance liquid chromatography-quantitative analysis of multicomponents by single marker (HPLC-QAMS) method and to evaluate the quality with chemometrics and entropy weight-technique for order preference by similarity to an ideal solution (EW-TOPSIS). METHODS: A symmetry C18 column and 0.1% formic acid-acetonitrile as mobile phase were used for HPLC of Tangwei capsule. The contents of 3'-hydroxypuerarin, puerarin, 3'-methoxypuerarin, methylnissolin-3-O-glucoside, calycosin, formononetin, rosmarinic acid, salvianolic acid B, dihydrotanshinone Ⅰ, cryptotanshinone, tanshinone Ⅰ, tanshinone ⅡA and cucurbitacin B in 15 batches of Tangwei capsule were determined simultaneously. The quality differences of 15 batches of samples were analyzed by chemometrics and EW-TOPSIS. RESULTS: The HPLC-UV showed that 13 components had good linear relationships in corresponding concentration ranges (r≥0.9991). The relative standard deviations (RSD) of precision, repeatability and stability were all less than 2.00%. The average recovery rates were between 96.86% and 100.13%, and RSD were all less than 2.00%. Cluster analysis showed that 15 batches of samples were clustered into 3 groups. Partial least squares-discriminant analysis showed that salvianolic acid B, formononetin, puerarin, 3'-methoxypuerarin and rosmarinic acid were the main potential markers affecting the quality of Tangwei capsule. EW-TOPSIS analysis showed that the quality of S12-S15 was superior. CONCLUSIONS: The analytical method established in this study can be used for the comprehensive evaluation of the quality of Tangwei capsule to provide laboratory support for its quality control and overall evaluation.

Detection of motor imagery based on short-term entropy of time-frequency representations.

BACKGROUND: Motor imagery is a cognitive process of imagining a performance of a motor task without employing the actual movement of muscles. It is often used in rehabilitation and utilized in assistive technologies to control a brain-computer interface (BCI). This paper provides a comparison of different time-frequency representations (TFR) and their Rényi and Shannon entropies for sensorimotor rhythm (SMR) based motor imagery control signals in electroencephalographic (EEG) data. The motor imagery task was guided by visual guidance, visual and vibrotactile (somatosensory) guidance or visual cue only. RESULTS: When using TFR-based entropy features as an input for classification of different interaction intentions, higher accuracies were achieved (up to 99.87%) in comparison to regular time-series amplitude features (for which accuracy was up to 85.91%), which is an increase when compared to existing methods. In particular, the highest accuracy was achieved for the classification of the motor imagery versus the baseline (rest state) when using Shannon entropy with Reassigned Pseudo Wigner-Ville time-frequency representation. CONCLUSIONS: Our findings suggest that the quantity of useful classifiable motor imagery information (entropy output) changes during the period of motor imagery in comparison to baseline period; as a result, there is an increase in the accuracy and F1 score of classification when using entropy features in comparison to the accuracy and the F1 of classification when using amplitude features, hence, it is manifested as an improvement of the ability to detect motor imagery.

Whole-brain network transitions within the framework of ignition and transfer entropy following VIM-MRgFUS in essential tremor patients.

Magnetic resonance-guided focused ultrasound (MRgFUS) lesioning of the ventralis intermedius nucleus (VIM) has shown promise in treating drug-refractory essential tremor (ET). It remains unknown whether focal VIM lesions by MRgFUS have broader restorative effects on information flow within the whole-brain network of ET patients. We applied an information-theoretical approach based on intrinsic ignition and the concept of transfer entropy (TE) to assess the spatiotemporal dynamics after VIM-MRgFUS. Eighteen ET patients (mean age 71.44 years) underwent repeated 3T resting-state functional magnetic resonance imaging combined with Clinical Rating Scale for Tremor (CRST) assessments one day before (T0) and one month (T1) and six months (T2) post-MRgFUS, respectively. We observed increased whole brain ignition-driven mean integration (IDMI) at T1 (p < 0.05), along with trend increases at T2. Further, constraining to motor network nodes, we identified significant increases in information-broadcasting (bilateral supplementary motor area (SMA) and left cerebellar lobule III) and information-receiving (right precentral gyrus) at T1. Remarkably, increased information-broadcasting in bilateral SMA was correlated with relative improvement of the CRST in the treated hand. In addition, causal TE-based effective connectivity (EC) at T1 showed an increase from right SMA to left cerebellar lobule crus II and from left cerebellar lobule III to right thalamus. In conclusion, results suggest a change in information transmission capacity in ET after MRgFUS and a shift towards a more integrated functional state with increased levels of global and directional information flow.

Information flow dynamics between geopolitical risk and major asset returns.

We quantify information flows between geopolitical risk (GPR) and global financial assets such as equity, bonds, and commodities, with a focus on the Russian-Ukrainian conflict. We combine transfer entropy and the I-CEEMDAN framework to measure information flows at multi-term scales. Our empirical results indicate that (i) in the short term, crude oil and Russian equity show opposite responses to GPR; (ii) in the medium and long term, GPR information increases the risk in the financial market; and (iii) the efficiency of the financial asset markets can be confirmed on a long-term scale. These findings have important implications for market participants, such as investors, portfolio managers, and policymakers.

Monitoring Level of Hypnosis Using Stationary Wavelet Transform and Singular Value Decomposition Entropy With Feedforward Neural Network.

Classifying the patient's depth of anesthesia (LoH) level into a few distinct states may lead to inappropriate drug administration. To tackle the problem, this paper presents a robust and computationally efficient framework that predicts a continuous LoH index scale from 0-100 in addition to the LoH state. This paper proposes a novel approach for accurate LoH estimation based on Stationary Wavelet Transform (SWT) and fractal features. The deep learning model adopts an optimized temporal, fractal, and spectral feature set to identify the patient sedation level irrespective of age and the type of anesthetic agent. This feature set is then fed into a multilayer perceptron network (MLP), a class of feed-forward neural networks. A comparative analysis of regression and classification is made to measure the performance of the chosen features on the neural network architecture. The proposed LoH classifier outperforms the state-of-the-art LoH prediction algorithms with the highest accuracy of 97.1% while utilizing minimized feature set and MLP classifier. Moreover, for the first time, the LoH regressor achieves the highest performance metrics ( [Formula: see text], MAE = 1.5) as compared to previous work. This study is very helpful for developing highly accurate monitoring for LoH which is important for intraoperative and postoperative patients' health.

[Clinical application of acupuncture-moxibustion for the treatment of spirit based on approximate entropy of electrooculogram signal].

According to the theory of acupuncture-moxibustion for the treatment of spirit, starting from the relationship between eye movement and spirit, the application of electrooculogram (EOG) signal acquisition and analysis technology for the clinical treatment of spirit by acupuncture-moxibustion is discussed. Based on the nonlinear dynamic characteristics of EOG signals, it is proposed to apply the approximate entropy algorithm to extract the EOG signal characteristics in autism spectrum disorder children under different behavior states, which could realize the preliminary exploration of the correlation between EOG signals and cognitive activities. This could provide a possibility to objectively reflect the patient' s current mental state, and could be used as a potential method to grasp spirit in clinical acupuncture- moxibustion treatment. Furthermore, considering the characteristics of acupoint stimulation on the body surface, the EOG signal acquisition and analysis technology could further be combined with biofeedback technology, and a new idea for clinical acupuncture-moxibustion to treat spirit guided by biofeedback of EOG is proposed.

Clinical application of acupuncture-moxibustion for the treatment of spirit based on approximate entropy of electrooculogram signal / 中国针灸

According to the theory of acupuncture-moxibustion for the treatment of spirit, starting from the relationship between eye movement and spirit, the application of electrooculogram (EOG) signal acquisition and analysis technology for the clinical treatment of spirit by acupuncture-moxibustion is discussed. Based on the nonlinear dynamic characteristics of EOG signals, it is proposed to apply the approximate entropy algorithm to extract the EOG signal characteristics in autism spectrum disorder children under different behavior states, which could realize the preliminary exploration of the correlation between EOG signals and cognitive activities. This could provide a possibility to objectively reflect the patient' s current mental state, and could be used as a potential method to grasp spirit in clinical acupuncture- moxibustion treatment. Furthermore, considering the characteristics of acupoint stimulation on the body surface, the EOG signal acquisition and analysis technology could further be combined with biofeedback technology, and a new idea for clinical acupuncture-moxibustion to treat spirit guided by biofeedback of EOG is proposed.

Quality evaluation of Huocao based on UPLC fingerprint and multi-component content determination / 中国中药杂志

Huocao(a traditional Chinese herbal medicine) moxibustion is a characteristic technology in Yi medicine suitable for cold-dampness diseases. Huocao, as the moxibustion material, is confusedly used in clinical practice and little is known about its quality control. In this study, UPLC method was used to establish the chemical fingerprint of non-volatile components in Huocao, and the contents of eight phenolic acids such as chlorogenic acid were determined. Multivariate statistical analysis was performed to obtain the indicator components of Huocao for quality evaluation, and thus a comprehensive evaluation system for the quality of Huocao was built. The UPLC fingerprints of 49 batches of Huocao were established, and there were 20 common peaks, of which eight phenolic acids including neochlorogenic acid and chlorogenic acid were identified. Except for three batches of Huocao, the similarity of the other 46 batches was higher than 0.89, suggesting that the established fingerprint method could be used for quality control of the medicinal herb. The correlation coefficient between entropy weight score of the eight phenolic acids and comprehensive fingerprint score in Huocao was 0.875(P<0.01), which indicated that the eight phenolic acids could be used as indicator components for the quality evaluation of Huocao. Furthermore, in multivariate statistical analysis on the common peaks of fingerprint and the contents of the eight phenolic acids, chlorogenic acid, isochlorogenic acid A and isochlorogenic acid C were screened to be the indicator components. The results revealed that the proposed method achieved a simple and accurate quality control of Huocao based on UPLC fingerprint and multi-component content determination, which provided useful data for establishing the quality standard of Huocao.

Thermodynamic analysis of an entropically driven, high-affinity nanobody-HIV p24 interaction.

Protein-protein interactions are fundamental to life processes. Complementary computational, structural, and biophysical studies of these interactions enable the forces behind their specificity and strength to be understood. Antibody fragments such as single-chain antibodies have the specificity and affinity of full antibodies but a fraction of their size, expediting whole molecule studies and distal effects without exceeding the computational capacity of modeling systems. We previously reported the crystal structure of a high-affinity nanobody 59H10 bound to HIV-1 capsid protein p24 and deduced key interactions using all-atom molecular dynamics simulations. We studied the properties of closely related medium (37E7) and low (48G11) affinity nanobodies, to understand how changes of three (37E7) or one (48G11) amino acids impacted these interactions; however, the contributions of enthalpy and entropy were not quantified. Here, we report the use of qualitative and quantitative experimental and in silico approaches to separate the contributions of enthalpy and entropy. We used complementary circular dichroism spectroscopy and molecular dynamics simulations to qualitatively delineate changes between nanobodies in isolation and complexed with p24. Using quantitative techniques such as isothermal titration calorimetry alongside WaterMap and Free Energy Perturbation protocols, we found the difference between high (59H10) and medium (37E7) affinity nanobodies on binding to HIV-1 p24 is entropically driven, accounted for by the release of unstable waters from the hydrophobic surface of 59H10. Our results provide an exemplar of the utility of parallel in vitro and in silico studies and highlight that differences in entropic interactions between amino acids and water molecules are sufficient to drive orders of magnitude differences in affinity.

Comprehensive quality evaluation of Tangwei capsule based on HPLC-QAMS multi-index quantitative determination combined with chemometrics and EW-TOPSIS method / 浙江大学学报·医学版

OBJECTIVES@#To detect the contents of Tangwei capsule main components with high performance liquid chromatography-quantitative analysis of multicomponents by single marker (HPLC-QAMS) method and to evaluate the quality with chemometrics and entropy weight-technique for order preference by similarity to an ideal solution (EW-TOPSIS).@*METHODS@#A symmetry C18 column and 0.1% formic acid-acetonitrile as mobile phase were used for HPLC of Tangwei capsule. The contents of 3'-hydroxypuerarin, puerarin, 3'-methoxypuerarin, methylnissolin-3-O-glucoside, calycosin, formononetin, rosmarinic acid, salvianolic acid B, dihydrotanshinone Ⅰ, cryptotanshinone, tanshinone Ⅰ, tanshinone ⅡA and cucurbitacin B in 15 batches of Tangwei capsule were determined simultaneously. The quality differences of 15 batches of samples were analyzed by chemometrics and EW-TOPSIS.@*RESULTS@#The HPLC-UV showed that 13 components had good linear relationships in corresponding concentration ranges (r≥0.9991). The relative standard deviations (RSD) of precision, repeatability and stability were all less than 2.00%. The average recovery rates were between 96.86% and 100.13%, and RSD were all less than 2.00%. Cluster analysis showed that 15 batches of samples were clustered into 3 groups. Partial least squares-discriminant analysis showed that salvianolic acid B, formononetin, puerarin, 3'-methoxypuerarin and rosmarinic acid were the main potential markers affecting the quality of Tangwei capsule. EW-TOPSIS analysis showed that the quality of S12-S15 was superior.@*CONCLUSIONS@#The analytical method established in this study can be used for the comprehensive evaluation of the quality of Tangwei capsule to provide laboratory support for its quality control and overall evaluation.

Correlations between B-mode ultrasound image texture features and tissue temperatures in hyperthermia.

PURPOSE: The noninvasive monitoring of mild hyperthermia or thermal ablation is important to guarantee therapeutic safety and efficacy. The potential of ultrasound B-mode image texture features in monitoring temperature or coagulation zones studied in this article. MATERIALS AND METHODS: The experiments carried out on eighteen in vitro porcine liver samples heated from 20°C to 60°C in the water bath. The ultrasound radiofrequency signal at different temperature collected to reconstruct B-mode ultrasound images. The texture features based on gray level histogram (GLH), gray level co-occurrence matrix (GLCM), and gray level-gradient co-occurrence matrix (GGCM) extracted, respectively. Accordingly, we analyze the correlations between these texture features and temperature based on the experiment results. RESULTS: The results showed that five texture feature parameters closely related to temperature, including mean gray scale of GLH, homogeneity of GLCM, hybrid entropy, inverse difference moment, and correlation of GGCM. Some of these feature parameters have correlation coefficients larger than 0.9 within the temperature range of 20°C to 60°C. CONCLUSIONS: The above-mentioned five feature parameters expected to apply for noninvasive monitoring of MH or TA.

The improved entropy weighting model in water quality evaluation based on the compound function.

Entropy weight model (EWM) is widely used in water quality evaluation. In the conventional EWM, the weight is a monotone increasing function of the dispersion degree. However, this weighting principle often neglects the heavily polluted indicators. To solve this problem, an improved EWM is designed, in which the weight of the indicator is a compound function of its dispersion degree and pollution degree. In the clean domain, the weight increases with the dispersion degree, while in the polluted domain, the weight decreases with the dispersion degree. And for the same dispersion degree, the larger the pollution degree is, the higher the weight is, and vice versa. Subsequently, the improved EWM is applied to the water quality evaluation of Wucheng Wetland in Poyang Lake, China. Results are as follows: (i) For TP, CODMn, and NH3-N, their dispersion degrees are 0.001, 0.158, and 0.084; and their pollution degrees are 0.971, 0.277, and 0.281, respectively. (ii) According to the improved EWM, the weights of TP, CODMn, and NH3-N are 0.613, 0.197, and 0.190, respectively. (iii) The comprehensive water quality indices of estuary region, wetland region, and the central lake area are 32.5, 30.9, and 35.6, respectively, all of which belong to a "bad" grade. The water environment of Wucheng Wetland suffered serious damage of phosphorus, and the ecosystem faced a high threat. (iv) Compared with the conventional EWM, the improved EWM highlights the importance of polluted indicators, which makes the comprehensive evaluation results more rigorous and reasonable.

The network signature of constellation line figures.

In traditional astronomies across the world, groups of stars in the night sky were linked into constellations-symbolic representations rich in meaning and with practical roles. In some sky cultures, constellations are represented as line (or connect-the-dot) figures, which are spatial networks drawn over the fixed background of stars. We analyse 1802 line figures from 56 sky cultures spanning all continents, in terms of their network, spatial, and brightness features, and ask what associations exist between these visual features and culture type or sky region. First, an embedded map of constellations is learnt, to show clusters of line figures. We then form the network of constellations (as linked by their similarity), to study how similar cultures are by computing their assortativity (or homophily) over the network. Finally, we measure the diversity (or entropy) index for the set of constellations drawn per sky region. Our results show distinct types of line figures, and that many folk astronomies with oral traditions have widespread similarities in constellation design, which do not align with cultural ancestry. In a minority of sky regions, certain line designs appear universal, but this is not the norm: in the majority of sky regions, the line geometries are diverse.