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Motivation Dropout events bring challenges in analyzing single-cell RNA sequencing data as they introduce noise and distort the true distributions of gene expression profiles. Recent studies focus on estimating dropout probability and imputing dropout events by leveraging information from similar cells or genes. However, the number of dropout events differs in different cells, due to the complex factors, such as different sequencing protocols, cell types, and batch effects. The dropout event differences are not fully considered in assessing the similarities between cells and genes, which compromises the reliability of downstream analysis. Results This work proposes a hybrid Generative Adversarial Network with dropouts identification to impute single-cell RNA sequencing data, named AGImpute. First, the numbers of dropout events in different cells in scRNA-seq data are differentially estimated by using a dynamic threshold estimation strategy. Next, the identified dropout events are imputed by a hybrid deep learning model, combining Autoencoder with a Generative Adversarial Network. To validate the efficiency of the AGImpute, it is compared with seven state-of-the-art dropout imputation methods on two simulated datasets and seven real single-cell RNA sequencing datasets. The results show that AGImpute imputes the least number of dropout events than other methods. Moreover, AGImpute enhances the performance of downstream analysis, including clustering performance, identifying cell-specific marker genes, and inferring trajectory in the time-course dataset. Availability and implementation The source code can be obtained from https://github.com/xszhu-lab/AGImpute. [ABSTRACT FROM AUTHOR]

Spatial transcriptome (ST) technology provides both the spatial location and transcriptional profile of spots, as well as tissue images. ST data can be utilized to construct gene regulatory networks, which can help identify gene modules that facilitate the understanding of biological processes such as cell communication. Correlation measurement is the core basis for constructing a gene regulatory network. However, due to the high noise and sparsity in ST data, common correlation measurement methods such as the Pearson correlation coefficient (PCC) and Spearman correlation coefficient (SPCC) are not suitable. In this work, a new gene correlation measurement method called STgcor is proposed. STgcor defines vertexes as spots in a two-dimensional coordinate plane consisting of axes X and Y from the gene pair (X and Y). The joint probability density of Gaussian distribution of the gene pair (X and Y) is calculated to identify and eliminate outliers. To overcome sparsity, the degree, trend, and location of the distribution of vertexes are used to measure the correlation between gene pairs (X, Y). To validate the performance of the STgcor method, it is compared with the PCC and SPCC in a weighted coexpression network analysis method using two ST datasets of breast cancer and prostate cancer. The gene modules identified by these methods are then compared and analyzed. The results show that the STgcor method detects some special gene modules and cancer-related pathways that cannot be detected by the other two methods. [ABSTRACT FROM AUTHOR]

Objective: Cancer-related cognitive impairments (CRCI) are frequently reported among cancer survivors, and attention is the most frequently assessed cognitive domain in CRCI. However, there is no consensus as to whether attention is impaired. We suggest that a major reason for this lack of agreement is a lack of construct validity for neuropsychological attention tests. We propose to assess the construct validity of neuropsychological attention tests with respect to experimental paradigms from cognitive psychology.Methods: Self-reported cancer survivors (N = 314) completed an online battery comprising six experimental attention paradigms and eight neuropsychological tests. Confirmatory factor analysis was used to evaluate the fit of five models derived from a general population sample (N = 636) in a previous study (M. Treviño, Cogn Res Princ Implic, in press). We then subjected the best-fitting model to a measurement invariance analysis.Results: The best-fitting model was a six intercorrelated factor structure, comprising Capacity, Search, Digit Span, Arithmetic, Sustained Attention, and Flanker Interference factors. Configural and weak invariance held, indicating that the factor loadings were invariant across groups. Strong invariance, indicating that intercepts were also invariant, held except for the Approximate Number Sense test.Conclusions: According to our factor model, Spatial Span and Digit Symbol Coding measure attentional capacity, while the Trail Making Test (A&B) and Letter Cancellation tests measure visual search ability. However, Digit Span and Arithmetic tests do not measure attention. We hope that these results will lead to better scientific models, better patient education, and, ultimately, improved outcomes for survivors. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNA-seq) can present cellular heterogeneity at higher resolution when measuring the gene expression in an individual cell. However, there are still some computational problems in scRNA-seq data, including high dimensionality, high sparseness, and high noise. To solve them, dimensionality reduction is essential as it reduces dimensions and also removes most of the zeros and noise. Therefore, we propose a hybrid dimensionality reduction algorithm for scRNA-seq data by integrating binning-based entropy and a denoising autoencoder, named ScEDA. In ScEDA, a novel binning-based entropy estimation method is performed to select efficient genes, while removing noise. For each gene, binning-based entropy is designed to describe the differences in its expression across all cells, that is, the distribution of expression of each gene in all cells. Genes are regarded as inefficient and removed when they achieve low binning-based entropy. Moreover, by combining Kullback–Leibler (KL) divergence with the autoencoder, the objective function is reconstructed to maximize the similarity in distribution between input data and reconstructed data. Furthermore, by adding Poisson-distributed noise to the original input data, the denoising autoencoder is used to improve robustness. Compared with three other clustering methods, ScEDA provides superior average performance on 16 real scRNA-seq datasets, with obvious enhancement in large-scale datasets. [ABSTRACT FROM AUTHOR]

Sodium-ion batteries (SIBs) have drawn ever-increasing attention for scalable electrical energy storage owing to the inexhaustible sources and wide distribution of sodium. However, to develop feasible anode materials still remains a great challenge for the practical application of SIBs. Here, we report hard carbons derived from a plentiful and deserted biomass of rice husk through a facile acid treatment and subsequent pyrolysis. The investigation illustrates that the electrochemical properties of the rice husk-derived hard carbons (RHHCs) are significantly influenced by the pyrolysis temperature because of the discrepancy in their microstructure. The RHHC pyrolyzed at 1300 °C (RHHC-1300) shows the highest reversible capacity of 372 mAh g −1 and good cycling stability and rate performance due to its large interlayer distance and suitable oxygen content. Moreover, full sodium-ion batteries are assembled to examine the application prospect using Na 3 V 2 (PO 4 ) 2 F 3 /C and RHHC-1300 as cathode and anode materials, respectively, delivering a high-energy density of 185 Wh kg −1 and stable cycling performance. This work could intensify the fundamental understanding of the sodium storage mechanism in biomass-derived hard carbons. [ABSTRACT FROM AUTHOR]

Many randomized experiments in the social sciences allocate subjects to treatment arms at the time the subjects enroll. Desirable features of the mechanism used to assign subjects to treatment arms are often (1) equal numbers of subjects in intervention and control arms, (2) balanced allocation for population subgroups and across covariates, (3) ease of use, and (4) inability for a site worker to predict the treatment arm for a subject before he or she has been assigned. In general, a trade-off must be made among these features: Many mechanisms that achieve high balance do so at the cost of high predictability. In this article, we review methods for randomized assignment of individuals that have been discussed in the literature, evaluating the performance of each with respect to the desirable design features. We propose a method for controlling the amount of predictability in a study while achieving high balance across subgroups and covariates. The method is applicable when a database containing the subgroup membership and covariates of each potential participant is available in advance. We use simple simulation and graphical methods to evaluate the balance and predictability of randomization mechanisms when planning the study and describe a computer program implemented in the R statistical software package that prospectively evaluates candidate randomization methods. [ABSTRACT FROM AUTHOR]

Biclustering algorithm is to cluster in the horizontal and vertical directions simultaneously in matrix. This algorithm identifies a set of sub-matrix by adopting a greedy iterative strategy, which employs the mean squared residue to measure the element consistency of a sub-matrix. Biclustering algorithm is widely applied in large and complex data. However, different versions of biclustering algorithm always have the problem that with the increasing of data size, more irrelevant rows or columns are involved in clustering which results in the poor performance of clustering. Therefore, this paper proposes a new algorithm, which combines fuzzy member matrix and comprehensive evaluation in fuzzy mathematics with multi-objective optimization algorithm to improve the performance of biclustering algorithm. In order to validate the effectiveness of the new algorithm, the performance the new algorithm and other three mainstream algorithms are compared on three gene/protein expression datasets. The results show the new algorithm has better element consistency, and sub-matrix capacity than other algorithms. [ABSTRACT FROM AUTHOR]

K nearest neighbors ( k NN) is an efficient lazy learning algorithm and has successfully been developed in real applications. It is natural to scale the k NN method to the large scale datasets. In this paper, we propose to first conduct a k -means clustering to separate the whole dataset into several parts, each of which is then conducted k NN classification. We conduct sets of experiments on big data and medical imaging data. The experimental results show that the proposed k NN classification works well in terms of accuracy and efficiency. [ABSTRACT FROM AUTHOR]

Objective. This systematic review was conducted to evaluate the clinical effectiveness and safety of herbal medicine (HM) as an alternative management for hot flushes induced by endocrine therapy in breast cancer patients. Methods. Key English and Chinese language databases were searched from inception to July 2015. Randomized Controlled Trials (RCTs) evaluating the effects of HM on hot flushes induced by endocrine therapy in women with breast cancer were retrieved. We conducted data collection and analysis in accordance with the Cochrane Handbook for Systematic Reviews of Interventions. Statistical analysis was performed with the software (Review Manager 5.3). Results. 19 articles were selected from the articles retrieved, and 5 articles met the inclusion criteria for analysis. Some included individual studies showed that HM can relieve hot flushes as well as other menopausal symptoms induced by endocrine therapy among women with breast cancer and improve the quality of life. There are minor side effects related to HM which are well tolerated. Conclusion. Given the small number of included studies and relatively poor methodological quality, there is insufficient evidence to draw positive conclusions regarding the objective benefit of HM. Additional high quality studies are needed with more rigorous methodological approach to answer this question. [ABSTRACT FROM AUTHOR]

Herein, a novel type of carbon-coated SnO 2 nanotubes has been designed and synthesized through a facile two-step hydrothermal approach by using ZnO nanorods as templates. During the synthetic route, SnO 2 nanocrystals and carbon layer have been uniformly deposited on the rod-like templates in sequence, meanwhile ZnO nanorods could be in situ dissolved owing to the generated alkaline and acidic environments during hydrothermal coating of SnO 2 nanocrystals and hydrothermal carbonization of glucose, respectively. When utilized as an anode material in lithium-ion batteries, the carbon-coated SnO 2 nanotubes manifests markedly enhanced Li-storage capabilities in terms of specific capacity and cycling stability in comparison with bare SnO 2 nanocrystals. [ABSTRACT FROM AUTHOR]

Background: With increasing multidisciplinary care strategies, palliative medicine practitioner perceptions toward acupuncture integration are significant. Objective: To evaluate acupuncture availability and acceptability in Australian palliative care. Outcomes: (1) Domains of the survey included participant characteristics, (2) workplace availability, (3) personal attitudes, and (4) recommendation likelihood. Design: An online REDCap survey of Australian palliative medicine practitioners was administered. Results: Acupuncture was mostly not available/permitted at workplaces (45.2%) due to cost/funding (57.1%) and limited evidence (57.1%). When available by workplace (24.2%) or affiliated service (4.8%), doctors mostly administered acupuncture (66.7%). Respondents were not up to date with current research (71.4%). Referral likelihood increased with confidence in provider (80.0%), workplace availability (77.1%), and patient prior/current use (77.1%). Patient acupuncture discussions were rare (62.9%) with barriers of effectiveness uncertainty (71.4%) and limited knowledge of availability (57.1%). Conclusion: Despite available integrative services and acceptability by Australian palliative medicine practitioners, utilization is low. Further research into acupuncture effectiveness for palliative symptoms, feasibility, and patient acceptability is required. [ABSTRACT FROM AUTHOR]

Huge amounts of genes in single-cell RNA sequencing (scRNA-seq) data may influence the performance of data clustering. To obtain high-quality genes for data clustering, the study proposes a novel gene selection algorithm based on Fisher score and genetic algorithms with dynamic crossover (abbreviated as FDCGA). To reduce time and space complexity, FDCGA first employs Fisher score to gain the preliminary candidate genes and then utilizes genetic algorithms with dynamic crossover to select beneficial genes to data clustering and analysis. The experimental results conducted on several publicly real-world scRNA-seq datasets demonstrate that FDCGA outperforms the other several competitors in terms of both NMI and ARI metrics and possesses significant optimization performances. The experimental convergence shows that the fitness of FDCGA can increase and converge to a fixed state versus the number of iterations. The statistical analysis demonstrates that FDCGA statistically significantly outperforms the other competing methods. [ABSTRACT FROM AUTHOR]

In MOPSO (multiobjective particle swarm optimization), to maintain or increase the diversity of the swarm and help an algorithm to jump out of the local optimal solution, PAM (Partitioning Around Medoid) clustering algorithm and uniform design are respectively introduced to maintain the diversity of Pareto optimal solutions and the uniformity of the selected Pareto optimal solutions. In this paper, a novel algorithm, the multiobjective particle swarm optimization based on PAM and uniform design, is proposed. The differences between the proposed algorithm and the others lie in that PAM and uniform design are firstly introduced to MOPSO. The experimental results performing on several test problems illustrate that the proposed algorithm is efficient. [ABSTRACT FROM AUTHOR]

A novel electrode material for supercapacitor composed of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT) and graphitic-phase C 3 N 4 (g-C 3 N 4 ) was prepared by a layer-by-layer assembly method. The resulting composite of PEDOT/g-C 3 N 4 represented excellent electrochemical stability in neutral electrolyte and enhanced electrochemical performance of capacitance and average energy density in comparison with single PEDOT. The specific capacitance was 137 F g −1 in H 2 SO 4 and 200 F g −1 in Na 2 SO 4 at a current density of 2 A g −1 , respectively. More significantly, the average energy density was 9.65 W h kg −1 at an average power density of 4001.86 W kg −1 in H 2 SO 4 . While in Na 2 SO 4 , the average energy density reached 17.5 W h kg −1 at an average power density of 5000 W kg −1 . More than 89% and 96.5% of capacitance were retained in H 2 SO 4 and Na 2 SO 4 respectively, suggesting that PEDOT/g-C 3 N 4 possessed an excellent cycling stability in view of capacity performance as electrode materials. The property improvement was attributed to the synergistic effects of the two components in the composite. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2 ) enrichment are widely reported to stimulate the plant growth. However, those relative studies in the horticultural plants are quite limited, particularly about the interaction of CO 2 and the physiological phenomenon “midday depression”. Herein, daytime (T1, 7:00–19:00) and morning (T2, 7:00–12:00) CO 2 enrichment treatments (800 ± 50 μmol mol −1 ) were conducted in open-top plastic greenhouses to investigate their effects on photosynthesis and growth in Gerbera jamesonii , compared to the atmospheric CO 2 concentration (CK, approximately 400 μmol mol −1 ). The results showed that the leaf net photosynthetic rate (Pn) of G. jamesonii was averagely increased 52 ± 17% in T1 and 66 ± 8% in T2 by CO 2 enrichment, which remarkably higher ( P < 0.05) in T2 than that in T1 in the later period of the experiment (30–150 d). CO 2 enrichment also significantly increased ( P < 0.01) the contents of photoassimilates (soluble sugar, starch, and chlorophyll), but decreased the contents of soluble proteins ( P < 0.05). The biomass determination in T1 and T2 revealed that plant dry weight was raised 40 ± 9% and 32 ± 6% on 150 days, respectively. In addition, CO 2 enrichment enhanced the quantities and qualities of flowers ( P < 0.05), such as augmented the flower number and size, extended the peduncle length, accumulated anthocyanin concentrations, and prolonged the flower vase life. Even though there were no significant differences between day and morning CO 2 enrichment on the basis of the statistical data, the morning CO 2 enrichment exhibited more favorable cost savings. According to these positive responses, we considered that the morning CO 2 enrichment has a potential application in commential production of G. jamesonii . [ABSTRACT FROM AUTHOR]

The development of single cell RNA sequencing (scRNA-seq) has provided new perspectives to study biological problems at the single cell level. One of the key issues in scRNA-seq data analysis is to divide cells into several clusters for discovering the heterogeneity and diversity of cells. However, the existing scRNA-seq data are high-dimensional, sparse, and noisy, which challenges the existing single-cell clustering methods. In this study, we propose a joint learning framework (JLONMFSC) for clustering scRNA-seq data. In our method, the dimension of the original data is reduced to minimize the effect of noise. In addition, the graph regularized matrix factorization is used to learn the local features. Further, the Low-Rank Representation (LRR) subspace clustering is utilized to learn the global features. Finally, the joint learning of local features and global features is performed to obtain the results of clustering. We compare the proposed algorithm with eight state-of-the-art algorithms for clustering performance on six datasets, and the experimental results demonstrate that the JLONMFSC achieves better performance in all datasets. The code is avalable at https://github.com/lanbiolab/JLONMFSC. • Single-cell sequencing data clustering is critical for exploring the heterogeneity and diversity of unknown cell groups. • We propose a joint learning framework for single-cell data clustering based on the factorization of graph regularization matrix and low rank representation subspace clustering. • The experimental results show that our method outperformances than other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Genes are the basic functional units of heredity. Differences in genes can lead to various congenital physical conditions. One kind of these differences is caused by genetic variations named single nucleotide polymorphisms (SNPs). An SNP is a variation in a single nucleotide that occurs at a specific position in the genome. Some SNPs can affect splice sites and protein structures and cause gene abnormalities. SNPs on paired chromosomes may lead to fatal diseases so that a fertilized embryo cannot develop into a normal fetus or the people born with these abnormalities die in childhood. The distributions of genotypes on these SNP sites are different from those on other sites. Based on this idea, we present a novel statistical method to detect the abnormal distributions of genotypes and locate the potentially lethal genes. The test was performed on HapMap data and 74 suspicious SNPs were found. Ten SNP maps "reviewed" genes in the NCBI database. Among them, 5 genes were related to fatal childhood diseases or embryonic development, 1 gene can cause spermatogenic failure, and the other 4 genes were associated with many genetic diseases. The results validated our method. The method is very simple and is guaranteed by a statistical test. It is an inexpensive way to discover potentially lethal genes and the mutation sites. The mined genes deserve further study. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNA-seq) has recently brought new insight into cell differentiation processes and functional variation in cell subtypes from homogeneous cell populations. A lack of prior knowledge makes unsupervised machine learning methods, such as clustering, suitable for analyzing scRNA-seq. However, there are several limitations to overcome, including high dimensionality, clustering result instability, and parameter adjustment complexity. In this study, we propose a method by combining structure entropy and k nearest neighbor to identify cell subpopulations in scRNA-seq data. In contrast to existing clustering methods for identifying cell subtypes, minimized structure entropy results in natural communities without specifying the number of clusters. To investigate the performance of our model, we applied it to eight scRNA-seq datasets and compared our method with three existing methods (nonnegative matrix factorization, single-cell interpretation via multikernel learning, and structural entropy minimization principle). The experimental results showed that our approach achieves, on average, better performance in these datasets compared to the benchmark methods. [ABSTRACT FROM AUTHOR]

Clustering analysis of gene expression data is essential for understanding complex biological data, and is widely used in important biological applications such as the identification of cell subpopulations and disease subtypes. In commonly used methods such as hierarchical clustering (HC) and consensus clustering (CC), holistic expression profiles of all genes are often used to assess the similarity between samples for clustering. While these methods have been proven successful in identifying sample clusters in many areas, they do not provide information about which gene sets (functions) contribute most to the clustering, thus limiting the interpretability of the resulting cluster. We hypothesize that integrating prior knowledge of annotated gene sets would not only achieve satisfactory clustering performance but also, more importantly, enable potential biological interpretation of clusters. Here we report ClusterMine, an approach that identifies clusters by assessing functional similarity between samples through integrating known annotated gene sets in functional annotation databases such as Gene Ontology. In addition to the cluster membership of each sample as provided by conventional approaches, it also outputs gene sets that most likely contribute to the clustering, thus facilitating biological interpretation. We compare ClusterMine with conventional approaches on nine real-world experimental datasets that represent different application scenarios in biology. We find that ClusterMine achieves better performances and that the gene sets prioritized by our method are biologically meaningful. ClusterMine is implemented as an R package and is freely available at: www.genemine.org/clustermine.php [ABSTRACT FROM AUTHOR]

Highlights • By in situ growth, Au-WS 2 nanocomposites was prepared, of which enhanced ECL was observed for the first time. • Au-WS 2 nanocomposites only facilitated but not participated in the redox reactions of the ECL processes. • The ECL analytical interface was non-destructive and able to accomplish repeated detection. • Release of dopamine from cells was controlled by K+ and nifidipine, and further monitored by the ECL interface. Abstract Quantification of cell-released dopamine (DA) is essential to understand various biological processes. However, concentration of DA outside living cells may increase and decrease in a short time. Thus, approaches used to detect cell-released DA should meet higher demands. Herein, a simple and green method is employed to in situ growth of gold nanoparticles on the surface of WS 2 nanosheets. The defects of prepared Au-WS 2 nanocomposites may accelerate electron transfer and facilitate the absorption of dissolved oxygen. As a result, Au-WS 2 nanocomposites-enhanced electrochemiluminescence (ECL) is observed for the first time, and is further used to fabricate a non-destructive and label-free analytical interface. The ECL interface can selectively detect DA in a range of 5.0 nM–200 μM with a detection limit of 3.23 nM. Meanwhile, since the architecture on the ECL interface is not destroyed during the detection procedure, DA can be quantified continuously at least six times after one fabrication. In addition, the proposed ECL interface can accurately monitor the release of DA from PC12 cells manipulated by K+ and nifidipine, indicating great potential of this ECL sensor for surveying DA-related investigations. [ABSTRACT FROM AUTHOR]

An abstract of the study "Impact of Chinese Herbal Medicine on Survival, Relapse and Metastasis in Women with Breast Cancer: A Systematic Review of Randomized Controlled Trial" by Xun Li and colleagues is presented.

Objectives: We examined the effect of changing treatment timing and the use of manual, electro acupuncture on the symptoms of primary dysmenorrhea. Methods: A randomised controlled trial was performed with four arms, low frequency manual acupuncture (LF-MA), high frequency manual acupuncture (HF-MA), low frequency electro acupuncture (LF-EA) and high frequency electro acupuncture (HF-EA). A manualised trial protocol was used to allow differentiation and individualized treatment over three months. A total of 74 women were randomly assigned to one of the four groups (LF-MA n = 19, HF-MA n = 18, LF-EA n = 18, HF-EA n = 19). Twelve treatments were performed over three menstrual cycles, either once per week (LF groups) or three times in the week prior to menses (HF groups). All groups received a treatment in the first 48 hours of menses. The primary outcome was the reduction in peak menstrual pain at 12 months from trial entry. Results: During the treatment period and nine month follow-up all groups showed statistically significant (p < .001) reductions in peak and average menstrual pain compared to baseline but there were no differences between groups (p > 0.05). Health related quality of life increased significantly in six domains in groups having high frequency of treatment compared to two domains in low frequency groups. Manual acupuncture groups required less analgesic medication than electro-acupuncture groups (p = 0.02). HF-MA was most effective in reducing secondary menstrual symptoms compared to both–EA groups (p<0.05). Conclusion: Acupuncture treatment reduced menstrual pain intensity and duration after three months of treatment and this was sustained for up to one year after trial entry. The effect of changing mode of stimulation or frequency of treatment on menstrual pain was not significant. This may be due to a lack of power. The role of acupuncture stimulation on menstrual pain needs to be investigated in appropriately powered randomised controlled trials. [ABSTRACT FROM AUTHOR]

Objective. The goal was to investigate the connection between neuroinflammation in the brain and serum inflammatory markers as Alzheimer's disease progressed. We also sought to determine whether electroacupuncture had an effect on inflammatory markers found in blood and other brain regions. Methods. As an animal model for AD, we used senescence-accelerated mouse prone 8 (SAMP8) mice. To examine the effects and probable mechanism of electroacupuncture, we used HE staining, immunofluorescence staining, western blotting, and enzyme-linked immunosorbent assay. Results. Electroacupuncture therapy protected neurons, significantly downregulated the Iba-1 level in the hippocampus (p value was 0.003), frontal lobe cortex (p value was 0.042), and temporal lobe cortex (p value was 0.013) of the AD animal model, all of which had significantly lower levels of IL-6 (p value was 0.001), IL-1β (p value was 0.001), and TNF-α (p value was 0.001) in their serum. Conclusion. The amounts of IL-6, IL-1β, and TNF-α detected in the serum were strongly linked to the levels discovered in the hippocampus and the frontal lobes of the brain, respectively. A better understanding of the electroacupuncture process as well as the course of Alzheimer's disease and the therapeutic benefits of electroacupuncture may be gained by using biomarkers such as serum inflammatory marker biomarkers. [ABSTRACT FROM AUTHOR]

Hollow porous structures of Pt–Pd bimetallic alloy possess unique compositional and structural superiorities for catalytic and electrocatalytic applications, and are thus anticipated to manifest novel properties and/or enhanced performance compared with their monometallic counterparts. Herein, a general electrostatic-attraction-directed layer-by-layer assembly approach has been developed for the construction of a novel type of hollow porous Pt–Pd alloy nanospheres (Pt–Pd HPNSs) using SiO 2 nanospheres as templates. Moreover, the Pt–Pd HPNSs with controllable shell thickness are prepared and their comparative electrocatalytic performances toward methanol oxidation reaction (MOR) are investigated. It's found that optimized Pt–Pd HPNSs manifests markedly enhanced catalytic activity and durability in comparison with both commercial Pt black and Pd black catalysts. [ABSTRACT FROM AUTHOR]

The hypothesis that extracellular polymeric substances (EPS) affect the formation of biofilms for subsequent enhanced biodegradation of polycyclic aromatic hydrocarbons was tested. Controlled formation of biofilms on humin particles and biodegradation of phenanthrene and pyrene were performed with bacteria and EPS-extracted bacteria of Micrococcus sp. PHE9 and Mycobacterium sp. NJS-P. Bacteria without EPS extraction developed biofilms on humin, in contrast the EPS-extracted bacteria could not attach to humin particles. In the subsequent biodegradation of phenanthrene and pyrene, the biodegradation rates by biofilms were significantly higher than those of EPS-extracted bacteria. Although, both the biofilms and EPS-extracted bacteria showed increases in EPS contents, only the EPS contents in biofilms displayed significant correlations with the biodegradation efficiencies of phenanthrene and pyrene. It is proposed that the bacterial-produced EPS was a key factor to mediate bacterial attachment to other surfaces and develop biofilms, thereby increasing the bioavailability of poorly soluble PAH for enhanced biodegradation. [ABSTRACT FROM AUTHOR]

The hydrogen evolution reaction (HER), an appealing solution for future energy supply, requires efficient and inexpensive electrocatalysts with abundant active surface sites. Although crystalline MoS 2 and WS 2 are promising candidates, their activity is dominated by edge sites. Amorphous tungsten sulfide prepared so far lacks the required active sites and its application has thus been hampered. In this work, nickel and cobalt incorporated amorphous tungsten sulfide synthesized by a thermolytic process is demonstrated to enhance the HER efficiency dramatically. The amorphous nickel tungsten sulfide (amorphous NiWS) annealed at 210 °C delivers the best HER performance in this system boasting a Tafel slope of 55 mV per decade and current density of 8.6 mA cm −2 at 250 mV overpotential in a sustained test for 24 h. The introduction of Ni or Co into the catalyst and subsequent thermal treatment alters the porous structure and chemical bonding states thereby increasing the density of active sites on the surface. [ABSTRACT FROM AUTHOR]

Objective: To determine the acceptability and feasibility of acupuncture for the treatment of endometriosis-related chronic pelvic pain. Design: A prospective, randomized controlled feasibility study. Setting: Outpatient setting in Sydney, Australia. Subjects: Participants who were aged 18–45 years, had a confirmed laparoscopic diagnosis of endometriosis in the past 5 years, and had regular menstrual periods and mean pelvic pain scores ≥4/10. Interventions: Sixteen acupuncture treatments delivered by registered acupuncturists using a standardized point protocol over 8 weeks, twice per week plus usual care compared with usual care alone. Outcome measures: Primary outcome measures were feasibility, safety, and acceptability of the acupuncture intervention. Secondary outcomes were changes in self-reported pelvic pain scores, changes in quality of life as measured by the Endometriosis Health Profile (EHP-30), changes in descending pain modulation, and changes in systemic inflammation (plasma interleukin [IL-6] concentrations). Results: Twenty-nine participants were eligible to participate, with 19 participants completing the trial. There was unequal withdrawals between groups; the acupuncture group had a withdrawal rate of 14% compared with 53% in usual care. Adverse events were uncommon (6.7%) and generally mild. A 1.9 point decrease in median nonmenstrual pain scores and a 2.0 decrease in median menstrual pain scores between baseline and end of trial were observed in the acupuncture group only. Improvements in all domains of the EHP-30 were seen in the acupuncture group, with no changes seen in usual care. There was no difference between baseline and end of treatment in IL-6 concentrations for either group. Conclusions: Acupuncture was an acceptable, well-tolerated treatment and it may reduce pelvic pain and improve quality of life; however, usual care was not an acceptable control group. Trial Registration: anzctr.org.au: ACTRN12617000053325. Prospectively registered January 11, 2017. [ABSTRACT FROM AUTHOR]

Objective: To assess the effectiveness and safety of Zao Ren An Shen (ZRAS), a Chinese herbal medicine formula, for the treatment of insomnia.Methods: Seven databases (ie, EMBASE, PubMed, the Cochrane library, and PsycINFO, Chinese National Knowledge Infrastructure, Wanfang and Chongqing VIP) were searched from their inception to 6 November 2018. Controlled trials comparing the effectiveness or safety of ZRAS to conventional treatments, a placebo or no-treatment in an insomnia population were selected. Primary outcomes were: sleep quality (assessed with the Pittsburgh Sleep Quality Index, PSQI), and the number of adverse events at post-treatment. The risk of bias was assessed with the Cochrane Collaboration's tool and meta-analyses were performed using RevMan 5.3.Results: A total of 19 studies (1780 participants) were included. The effect of ZRAS on sleep quality (mean difference) was found to be superior compared to placebo in the sole placebo-controlled study located [-0.90 (-1.56, -0.24; 95% CI), p = 0.007] and similar to Benzodiazepine Receptor Agonists (BzRAs) [0.17 (-0.29, 0.64); 95% CI, p = 0.46]. The number of adverse events (relative risk) was lower for ZRAS than BzRAs [0.16 (0.12, 0.23; 95% CI), p < 0.001]. An overall high risk of bias was found in the selected studies.Conclusions: The results favor ZRAS against BzRAs and placebo for the treatment of insomnia. However, the poor methodology of the studies prevents strong recommendations for ZRAS. Clinical trials with higher quality designs are required. [ABSTRACT FROM AUTHOR]

Sodium-ion batteries (SIBs) have long been recognized as a potential substitute for lithium-ion batteries, while their practical application is greatly hindered owing to the absence of suitable cathode materials with improved rate capability and prolonged cycling life. Na 3 V 2 (PO 4) 3 (NVP) has drawn extensive attention among the cathode materials for SIBs because of its fast Na+-transportable framework which enables high-speed charge transfer, but the poor electric conductivity of NVP significantly restricts the Na+ diffusion. To tackle this issue, in this work, porous NVP/reduced graphene oxide hollow spheres (NVP/rGO HSs) are constructed via a spray drying strategy. Due to the unique porous hollow architecture, the synthesized compound manifests a high reversible capacity of 116 mAh g−1 at 1 C (1 C = 118 mA g−1), an outstanding high-rate capability of 107.5 mAh g−1 at 10 C and 98.5 mAh g−1 at 20 C, as well as a stable cycling performance of 109 mAh g−1 after 400 cycles at 1 C and 73.1 mAh g−1 after 1000 cycles at 10 C. Moreover, galvanostatic intermittent titration technique demonstrates that the Na+ diffusion coefficient of NVP/rGO HSs is an order of magnitude larger than the pristine NVP. The remarkable electrochemical properties of NVP/rGO HSs in full cells further enable it a potential cathode for SIBs. [ABSTRACT FROM AUTHOR]

Background: Chemotherapy-related fatigue (CRF) is a common symptom in non-small cell lung cancer (NSCLC) patients. A Chinese herbal formula cream for oral application, called Jianpishengsui (JPSS), is extensively used in the First Affiliated Hospital of Guangzhou University of Chinese Medicine as an internal preparation for CRF and is associated with a promising response. Due to the lack of high-quality clinical evidence, a randomized placebo-controlled trial is required to assess the efficacy and safety of JPSS.Methods/design: The efficacy and safety of JPSS herbal formula cream will be evaluated through a prospective, randomized, placebo-controlled trial conducted in the First Affiliated Hospital of Guangzhou University of Chinese Medicine. NSCLC patients with CRF will be randomized into two groups at a ratio of 1:1. Each group will receive either 15 g of the oral JPSS herbal formula cream or placebo twice a day from day 6 to day 20 during two courses of paclitaxel + platinum/docetaxel + platinum/pemetrexed + platinum (TP/DP/AP) chemotherapy. The primary endpoint is the difference in the degree of fatigue between baseline (the day before the start of the intervention) and day 42, which will be assessed by the Revised Piper Fatigue Scale score. The secondary endpoints are quality of life (measured by the 43-item European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Lung Cancer C43), Eastern Cooperative Oncology Group Performance Status, and Traditional Chinese Medicine syndrome score. The toxicity of the treatments will also be evaluated at the same time. All outcomes will be measured at baseline, day 6, day 21, and day 42 of the treatment.Discussion: This randomized trial will investigate the efficacy and safety of JPSS applied for CRF in patients with NSCLC.Trial Registration: Chinese Clinical Trial Registry, ChiCTR1900023451. Registered on 28 May 2019. [ABSTRACT FROM AUTHOR]

The brain has the most complex structures and functions in living organisms, and brain networks can provide us an effective way for brain function analysis and brain disease detection. In brain networks, there exist some important neural unit modules, which contain many meaningful biological insights. It is appealing to find the neural unit modules and obtain their affiliations. In this study, we present a novel method by integrating the uniform design into the particle swarm optimization to find community modules of brain networks, abbreviated as UPSO. The difference between UPSO and the existing ones lies in that UPSO is presented first for detecting community modules. Several brain networks generated from functional MRI for studying autism are used to verify the proposed algorithm. Experimental results obtained on these brain networks demonstrate that UPSO can find community modules efficiently and outperforms the other competing methods in terms of modularity and conductance. Additionally, the comparison of UPSO and PSO also shows that the uniform design plays an important role in improving the performance of UPSO. [ABSTRACT FROM AUTHOR]

Abstract Na-superionic conductor-structured Na 3 V 2 (PO 4) 3 is extensively investigated as a promising cathode material for sodium-ion batteries. Unfortunately, the Na 3 V 2 (PO 4) 3 cathode suffers from low rate capability due to its inherent low electric conductivity. One of the general solutions to this dilemma is to embed the Na 3 V 2 (PO 4) 3 nanoparticles uniformly within carbon matrix, however, the effect of carbon matrix categories on the sodium storage performance of Na 3 V 2 (PO 4) 3 is unclear. Here we systematically compare the influence of different carbon matrix on the electrochemical properties of the Na 3 V 2 (PO 4) 3 cathode and find that expanded graphite outperforms carbon nanotubes and carbon black as carbon matrix. As a result, the as-synthesized Na 3 V 2 (PO 4) 3 /expanded graphite composite delivers a high reversible capacity of 111.4 mAh g−1 at 1C, superior rate capability (105 mAh g−1 at 50C), and ultralong cycle life (48 mAh g−1 after 20,000 cycles at 50C), which are better than most Na 3 V 2 (PO 4) 3 -based composites reported previously. Moreover, the remarkable electrochemical performance of Na 3 V 2 (PO 4) 3 /expanded graphite in symmetric cells further advances the practical application of sodium-ion batteries. Graphical abstract Image 1 Highlights • NVP/C composites are synthesized by freeze drying, ball milling, and annealing. • A systematic study of the influence of different carbon matrix are carried out. • Excellent rate capability and ultralong cycle life are demonstrated by NVP/EG. • Superior electrochemical properties of NVP/EG in symmetric cells are revealed. [ABSTRACT FROM AUTHOR]

Graphical abstract Using acetone and antimony acetate as the starting materials, 2D porous hybrid nanosheets with ultrathin antimony nanoplates (∼0.5 nm thick) being anchored on graphene-like carbon porous nanosheets were facily constructed with outstanding electrochemical performances as anode materials for sodium-ion batteries. Abstract Rational design and facile synthesis of two-dimensional (2D) materials still remain a great challenge. Herein, a facile process was proposed to construct 2D porous hybrid nanosheets, with ultrathin antimony nanoplates (with a thickness of ca. 0.5 nm) being anchored on acetone-derived graphene-like carbon porous nanosheets, by an aldol reaction and subsequent carbothermal reduction method using acetone and antimony acetate as the starting raw materials. The novel structural and compositional characteristics afford the 2D porous hybrid nanosheets with impressive boosting electrochemical sodium storage properties in terms of excellent cycling stability, high reversible specific capacity, and superior rate performance. The present work would provide significant value for the development of both synthetic methodology of 2D materials and their application as electrode active materials for energy storage and conversion. [ABSTRACT FROM AUTHOR]

Purpose. Many patients with advanced non-small-cell lung cancer (NSCLC) seek help from Chinese herbal medicine (CHM). The purpose of this study was to investigate the survival between CHM and chemotherapy (CT) treatment of patients aged ≥60 years with advanced Epidermal Growth Factor Receptor (EGFR) wild type NSCLC and Karnofsky Performance Status (KPS) ≥ 60. Methods. We extracted individual data of all eligible patients from 1 randomized control trial and 2 cohort studies and performed a pooled analysis. Survival outcomes of patients were compared between CHM group and CT group using Cox regression model stratified for study. Results. A total of 486 patients were included in the study, including 262 patients in the CHM group and 224 patients in the CT group. The median overall survival time was 10.9 (95% confidence intervals [CI]: 8.9-13.0) months in CHM group and 9.8 (95% CI: 8.1-11.5) days in CT group (p=0.592). The adjusted hazard ratio (HR) and 95% CI for CHM compared to CT are 0.98 (0.87, 1.10, p=0.751) in the stratified Cox regression model. Stratified analysis showed a trend that previously treated elderly patients with EGFR wild type advanced NSCLC probably gain greater survival benefit from CHM (adjusted HR:0.83, 95% CI: 0.68-1.01, p=0.063). Conclusions. There might be no significant difference in survival for elderly patients with advanced EGFR wild type NSCLC between the CHM and CT groups in the current study. And previously treated elderly patients with advanced NSCLC probably receive greater benefit from CHM. However, limited by the design and unpreplanned study hypothesis, the results must be confirmed by randomized control trial before making a conclusion. [ABSTRACT FROM AUTHOR]

Herein, a very simple and cost-effective solid state reaction method is employed to obtain, for the first time, the antimony nanoparticles embedded within reduced graphene oxide matrices (designated as Sb/rGO). By directly grinding antimony chloride and sodium hydroxide together at room temperature in the presence of graphene oxide (GO), Sb 4 O 5 Cl 2 precursor was quickly obtained, which is evenly incorporated in the graphene oxide matrices. After subsequent chemical reduction by NaBH 4 , the Sb/rGO composite was successfully synthesized. The as-prepared Sb/rGO composite consists of uniform Sb nanoparticles of sub-20 nm, all of which have been wrapped in and protected by the rGO matrices. The Sb nanoparticles serve as a sufficient sodium ion reservoir while the rGO matrices provide highly efficient pathways for transport of sodium ions and electrons. Moreover, the volume expansion of Sb during sodiation can be buffered in the rGO matrices. As a result, the Sb/rGO composite exhibits excellent electrochemical performance in sodium-ion batteries (SIBs), including an enhanced cycling stability with a highly reversible charge capacity of 455 mA h g −1 after 45 cycles at 100 mA g −1 , and a coulombic efficiency exceeding 98% during cycling. The findings in the present work pave the way to not only synthesize the designated promising electrode materials for high performance SIBs, but also thoroughly understand the solid-state reaction. [ABSTRACT FROM AUTHOR]

Background. The aim of this study was to examine the reliability of a scale to assess the methodological quality of acupuncture administered in clinical research. Methods. We invited 36 acupuncture researchers and postgraduate students to participate in the study. Firstly, participants rated two articles using the scale. Following this initial stage, modifications were made to scale items and the exercise was repeated. Interrater reliability was assessed for individual items using the Fleiss kappa statistic, whilst the overall scale used the intraclass correlation coefficient statistic. A threshold agreement of ≥0.61 was acceptable. Results. We received 26 responses and a 72% response rate. The first phase of testing found moderate reliability with intraclass correlation coefficients of 0.46 and 0.55 for the articles. The interrater reliability of the scales varied between and within the researchers (0.35, 0.60) and was more consistent with the postgraduate students (0.54, 0.54). Five items on the scale scored below the threshold and were revised for further testing. In this phase the intraclass correlation coefficient demonstrated variability between articles but improved to achieve reliability above the agreed threshold. Conclusion. This study provides evidence of the reliability of the NICMAN scale although improvements to a small number of items remain. [ABSTRACT FROM AUTHOR]

Antimony has received a great deal of attention as a promising anode material for sodium-ion batteries (SIBs) due to its high theoretical capacity of 660 mAh g −1 . However, this application is significantly hampered by inherent large volume change and sluggish kinetics. To address these issues, an antimony−cyano-based ionic liquid-derived nitrogen-doped carbon (Sb CNC) hybrid is proposed and synthesized by ball-milling and subsequent pyrolysis treatment. As an anode material for SIBs, the as-synthesized Sb CNC hybrid delivers reversible capacities of 475 mAh g −1 at a current density of 100 mA g −1 and 203 mAh g −1 at 5000 mA g −1 , and a 92.4% capacity retention based on the first-cycle capacity after 150 cycles at 100 mA g −1 . Using ex situ X-ray photoelectron spectroscopy and elemental mapping techniques, we attribute the good structural integrity to the formation of Sb N C bonds between Sb and the cyano-based ionic liquid-derived N-doped carbon matrix. Moreover, the presence of N-doped carbon network in the hybrid material serves as a robust protective cover and an electrical highway, buffering the substantial volume expansion of Sb nanoparticles and ensuring the fast electron transport for stable cycling operation. [ABSTRACT FROM AUTHOR]

Recently, many multi-objective differential evolution versions (MODEs) have been developed by incorporating the search engine of differential evolution (DE) and multi-objective processing mechanisms. However, most existing MODEs perform poorly in solving multi-objective optimization problems (MOPs) with variable linkages. The cause of this poor performance is the rotational variability of binomial crossover operator (BCO), which is not conducive to making simultaneous progress across all variables within a solution vector in the search for such MOPs. To alleviate the limitation, dynamic covariance matrix learning (DCML) based on the information distribution of the entire or a portion of the population is proposed to establish a proper coordinate system for the BCO by eigen decomposition. In this method, the rotational invariance of DE can be enhanced to a certain extent by releasing the interactions among the variables; thus, it is useful for MODEs to better balance their exploration and exploitation abilities. By integrating the DCML into existing MODEs, a class of new MODEs, which are called MODEs + DCML for short, are presented in this study. For comparison purposes, the proposed DCML strategy is applied to four commonly used MODEs. Twenty-nine benchmark problems with variable linkages are selected as the test suite to evaluate the performance of the proposed MODEs + DCML. The experimental results show that the proposed DCML can significantly improve the performance of the state-of-the-art MODEs in most test functions. [ABSTRACT FROM AUTHOR]

Herein, we develop a new kind of carbon supported gold-phosphorus (Au-P/C) electrocatalyst for the alkaline ethanol oxidation reaction (EOR). The Au-P/C catalysts with different Au/P ratio (i.e., AuP/C, Au 3 P 2 /C and Au 4 P 3 /C) can be obtained by a facile and novel hot-reflux method with white phosphorus (P 4 ) as reductant and ethanol as solvent. The crystal structure, composition and particle-size of the Au-P/C catalysts are investigated by X-ray diffraction (XRD), Energy Dispersive Spectrometer (EDS), scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS), etc. The results demonstrate that Au-P/C catalysts present an alloy phase with the high content of P, ultrafine particle-size and high dispersity on carbon support, which results in excellent electrocatalytic activity and stability towards the EOR compared with that of the free-phosphorus Au/C catalyst. In addition, among the various Au-P/C catalysts with different Au/P ratio, the AuP/C sample exhibits the best electrocatalytic performance in comparison with other Au 3 P 2 /C and Au 4 P 3 /C samples. [ABSTRACT FROM AUTHOR]

Our study aimed to explore whether San Huang Decoction (SHD) inhibited the development of breast cancer by regulating Aurora A. Human breast cancer cell lines MCF-7 and MDA-MB-231 were cultured and SHD extract was prepared. Cell growth assay and apoptosis analysis were respectively performed to detect the effects of SHD on breast cancer cells. In addition, the effects of SHD on the expression of Aurora A and p53 were determined by RT-PCR and western blot. Besides, we used Aurora A siRNA to knock down Aurora A. We then co-administrated SHD and tamoxifen or epirubicin to detect the effect of SHD on chemosensitivity to tamoxifen or epirubicin. SHD treatment significantly inhibited cell growth in a dose-dependent manner. Moreover, SHD treatment resulted in a marked decrease in Aurora A expression and obvious increase in p53 expression. In addition, knockdown of Aurora A induced cell growth inhibition, which was similar to the effect of SHD treatment. Besides, SHD exerted an additive effect on cell growth inhibition and apoptosis induction when breast cancer cells were co-administration of SHD with tamoxifen or epirubicin. Our study indicates that SHD treatment may inhibit cell growth and enhance chemosenstivity to other anti-tumor drugs in breast cancer via down-regulation of Aurora A. [ABSTRACT FROM AUTHOR]

The facet-dependent properties of SnO 2 are of fundamental and practical importance. In this study, by adjusting the deposition temperature during chemical vapor deposition, octahedral SnO 2 with the exposed (1 0 1) facet and two other kinds of SnO 2 polyhedrons with (1 0 1) and (1 0 0) facets with different ratios are fabricated controllably based on the vapor–solid growth mechanism. A slight increase in the deposition temperature from 1030 to 1070 °C decreases the surface energy of the reduced (1 0 1) facet with Sn termination, leading to the formation of polyhedrons with different area ratios of (1 0 1) to (1 0 0) facets. By adopting the terephthalic acid fluorescent method, the SnO 2 octahedrons are demonstrated to have the strongest photocatalytic activity due to the formation of surface states induced by 5s electrons of bivalent Sn on the (1 0 1) surface. The results reveal that the photocatalytic properties of SnO 2 microcrystals can be enhanced by facet-controlled synthesis. [ABSTRACT FROM AUTHOR]

In situ growth of Pd–Pt alloy nanoflowers on host reduced graphene oxide (Pd–Pt ANFs/RGO) nanosheets by one–pot polyallylamine hydrochloride-assisted co–chemical reduction method, is developed. Compared with the common approaches to assembly of nanocatalysts in selected substrates based on pre-synthesized catalyst nanoparticles, the in situ fabrication is more facile, cost-effective and environment-friendly, allowing effective control of the location, distribution and uniformity of the supported Pd–Pt nanoflowers through the entire matrix. The detailed morphology, composition and structure of Pd–Pt ANFs/RGO nanocomposites are investigated by transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), selected-area electron diffraction (SAED), energy dispersive spectrum (EDS), and nitrogen adsorption–desorption isotherms (SADI). TEM images show that Pd–Pt ANFs are directly grown on RGO with porous structure and good dispersion. Against commercial Pd/C catalyst, Pd–Pt ANFs/RGO nanocomposites show superior electrocatalytic activity, stability and satisfactory CO tolerance towards methanol oxidation reaction in basic electrolyte. [ABSTRACT FROM AUTHOR]

Herein, a novel type of graphene-wrapped SnO 2 nanotubes (SnO 2 -NTs/G) nanohybrid has been designed and constructed through a facile Sn-nanorod-templated self-assembly approach. The as-prepared SnO 2 -NTs/G nanohybrid has been utilized as an anode material in lithium-ion batteries, and demonstrates remarkable cycling stability, high reversible capacities, and rate capability by virtue of its unique structural features. [ABSTRACT FROM AUTHOR]

The direct electron transfer and electrocatalysis of hemoglobin (Hb) immobilized on the phosphonate functionalized multi-walled carbon nanotubes (MWCNTs) are investigated. Fourier transform infrared (FT-IR) spectra, UV–vis spectra and cyclic voltammetry (CV) analyses reveal that the phosphonate functionalized MWCNTs have good biocompatibility for Hb immobilization, and promote the electron communication between Hb and electrode. The immobilized Hb shows a pair of redox peak with a formal potential of −406±10mV (vs. SCE) and the electrochemical behavior of Hb was a surface-controlled process in a pH 7.0 phosphate buffer solution. And the immobilized Hb can act in an electrocatalytic manner in the electrochemical reduction of nitric oxide (NO). Accordingly, an unmediated NO electrochemical biosensor is constructed. Under optimized experimental conditions, the NO electrochemical biosensor shows the fast response (less than 3s), the wide linear range (1.5×10−7 to 2.7×10−4 M) and the low detection limit (1.5×10−8 M), which is attributed to the good mass transport, the large Hb loading per unit area and the fast electron transfer rate of Hb. [ABSTRACT FROM AUTHOR]

A nonenzymatic iron(iii) diethylenetriaminepentaacetic acid (FeIII-DETPA) complex based amperometric sensor for the analytical determination of hydrogen peroxide was developed. By combining the electrostatic interaction between the FeIII-DETPA complex and polyallylamine (PAH) functionalized multiwalled carbon nanotubes (MWCNTs) as well as the ionotropic crosslinking interaction between PAH and ethylenediamine-tetramethylene phosphonic acid (EDTMP), the electroactive FeIII-DETPA complex was successfully incorporated within the MWCNT matrix, and firmly immobilized on the Au substrate electrode. The fabricated electrochemical sensor was characterized with scanning electron microscopy (SEM), transmission electron microscopy (TEM) and electrochemical methods. The influences of solution pH and ionic strength on the electrochemical sensor were investigated. The prepared electrochemical sensor had a fast response to hydrogen peroxide (＜3 s) and an excellent linear range of concentration from 1.25 × 10−8 to 4.75 × 10−3 M with a detection limit of 6.3 × 10−9 M under the optimum conditions. [ABSTRACT FROM AUTHOR]

Background: Quality acupuncture influences the outcomes of clinical research, and issues associated with effective administration of acupuncture in randomized controlled trials need to be addressed when appraising studies. Objective: The study objective was to achieve consensus on domains and items for inclusion in a rating scale to assess quality acupuncture administered in clinical research. Study design and subjects: An active group of Australian acupuncture researchers initially identified a pool of items assessing quality. The Delphi consensus process was then used to select and reduce the number of items, and an additional expert panel of 42 researchers were invited to participate. Participants initially ranked items along a five-point scale for the first Delphi round, and indicated an agree or disagree response during the second round. For an item to be retained into the second round, an item had to attain greater than 80% agreement that the item described a dimension of quality acupuncture and related study design. Results: Thirty-two (32) experts agreed to participate in the study. After two rounds of the Delphi process, consensus was reached on 14 domains and 26 items relating to quality acupuncture. Domains, items, and minimum standards related to study design; rationale of the intervention; criteria relating to needling stimulation either manual or electrostimulation; duration and frequency of treatment; and practitioner training. Conclusions: Items for inclusion in an instrument to assess quality acupuncture in clinical research were identified. Further development of the instrument including relative weighting of items and reliability testing is under way. [ABSTRACT FROM AUTHOR]

Presents a monograph that describes the toxicity of Herba Asari, a Chinese medicinal herb. List of other terms for the herb; Major constituents; Formulae in which the herb is used as one of the ingredients.

Presents a monograph that describes the toxicity of Radix Sophorae Flavescentis, a Chinese herbal medicine. List of other terms for the herb; Major constituents; Potential toxicity grade.

Whilst the popular use of herbal medicine globally, it poses challenges in managing potential drug-herb interaction. There are two folds of the drug-herb interaction, a beneficial interaction that may improve therapeutic outcome and minimise the toxicity of drug desirably; by contrast, negative interaction may evoke unwanted clinical consequences, especially with drugs of narrow therapeutic index. Scutellaria baicalensis Georgi is one of the most popular medicinal plants used in Asian countries. It has been widely used for treating various diseases and conditions such as cancer, diabetes, inflammation, and oxidative stress. Studies on its extract and bioactive compounds have shown pharmacodynamic and pharmacokinetic interactions with a wide range of pharmaceutical drugs as evidenced by plenty of in vitro , in vivo and clinical studies. Notably, S. baicalensis and its bioactives including baicalein, baicalin and wogonin exhibited synergistic interactions with many pharmaceutical drugs to enhance their efficacy, reduce toxicity or overcome drug resistance to combat complex diseases such as cancer, diabetes and infectious diseases. On the other hand, S. baicalensis and its bioactives also affected the pharmacokinetic profile of many drugs in absorption, distribution, metabolism and elimination via the regulatory actions of the efflux pumps and cytochrome P450 enzymes. This review provides comprehensive references of the observed pharmacodynamic and pharmacokinetic drug interactions of Scutellaria baicalensis and its bioactives. We have elucidated the interaction with detailed mechanistic actions, identified the knowledge gaps for future research and potential clinical implications. Such knowledge is important for the practice of both conventional and complementary medicines, and it is essential to ensure the safe use of related herbal medicines. The review may be of great interest to practitioners, consumers, clinicians who require comprehensive information on the possible drug interactions with S. baicalensis and its bioactives. [Display omitted] • S. baicalensis promoted the anti-cancer effect of cisplatin and fluorouracil. • Baicalein enhanced anti-diabetic activity of metformin. • Baicalein and baicalin sensitised the anti-bacterial effect of many antibiotics. • S. baicalensis affected pharmacokinetic profiles of numerous pharmaceutical drugs. [ABSTRACT FROM AUTHOR]

As a most promising low-cost substitute for the current lithium-ion batteries technology, sodium-ion batteries (SIBs) have aroused particular attentions over the past few years. However, the performance of SIBs is still far from our expectations due to the lack of suitable electrode materials with excellent electrical conductivity, high energy density, long-term cycling stability, and high-rate performance. Herein, ultrafine ZnSe nanoparticles homogeneously confined within N,Se-codoped carbon matrix were constructed via a facile solid state reaction route. By directly using zinc acetate dihydrate, o -vanillin and o -phenylenediamine as starting raw materials, a self-assembly solid state reaction occurred to give rise to a bis-Schiff base complex with zinc (II) at room temperature. After subsequent calcination in the presence of selenium powder at elevated temperature, simultaneous carbonization and selenization took place, resulting to the in-situ formation of ultrafine ZnSe nanoparticles (∼6.5 nm) encapsulated in N,Se-codoped carbon matrix (named as ZnSe⊂NSeC). The unique ZnSe⊂NSeC hybrid demonstrated an impressive sodium storage performance in terms of long-term cycling stability (282 mA h g−1 of charging capacity after 500 cycles at 0.1 A g−1) and excellent rate capability (198 mA h g−1 of charging capacity at 5 A g−1). More importantly, a superb stable charging capacity of 238 mA h g−1 still maintained even after 1200 cycles at 1.0 A g−1. Such strategy may also be used to explore other nanocomposites to boost their energy storage performance. • The ZnSe⊂NSeC hybrid was readily in-situ fabricated via ambient temperature solid state reaction followed by subsequent calcination. • Ultrafine ZnSe NPs were evenly encapsulated in the N,Se-codoped carbon matrix in the ZnSe⊂NSeC hybrid before and after prolonged charge/discharge cycles. • The ZnSe⊂NSeC hybrid exhibited exceptional electrochemical performance for sodium storage. [ABSTRACT FROM AUTHOR]