Showing papers by "Hong Kong Baptist University published in 2016"

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

The Visual Object Tracking VOT2016 Challenge Results

Abstract: The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).

The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent

Abstract: The alternating direction method of multipliers (ADMM) is now widely used in many fields, and its convergence was proved when two blocks of variables are alternatively updated. It is strongly desirable and practically valuable to extend the ADMM directly to the case of a multi-block convex minimization problem where its objective function is the sum of more than two separable convex functions. However, the convergence of this extension has been missing for a long time--neither an affirmative convergence proof nor an example showing its divergence is known in the literature. In this paper we give a negative answer to this long-standing open question: The direct extension of ADMM is not necessarily convergent. We present a sufficient condition to ensure the convergence of the direct extension of ADMM, and give an example to show its divergence.

The Effect of Information Communication Technology Interventions on Reducing Social Isolation in the Elderly: A Systematic Review.

Abstract: Background: The aging of the population is an inexorable change that challenges governments and societies in every developed country. Based on clinical and empirical data, social isolation is found to be prevalent among elderly people, and it has negative consequences on the elderly’s psychological and physical health. Targeting social isolation has become a focus area for policy and practice. Evidence indicates that contemporary information and communication technologies (ICT) have the potential to prevent or reduce the social isolation of elderly people via various mechanisms. Objective: This systematic review explored the effects of ICT interventions on reducing social isolation of the elderly. Methods: Relevant electronic databases (PsycINFO, PubMed, MEDLINE, EBSCO, SSCI, Communication Studies: a SAGE Full-Text Collection, Communication & Mass Media Complete, Association for Computing Machinery (ACM) Digital Library, and IEEE Xplore) were systematically searched using a unified strategy to identify quantitative and qualitative studies on the effectiveness of ICT-mediated social isolation interventions for elderly people published in English between 2002 and 2015. Narrative synthesis was performed to interpret the results of the identified studies, and their quality was also appraised. Results: Twenty-five publications were included in the review. Four of them were evaluated as rigorous research. Most studies measured the effectiveness of ICT by measuring specific dimensions rather than social isolation in general. ICT use was consistently found to affect social support, social connectedness, and social isolation in general positively. The results for loneliness were inconclusive. Even though most were positive, some studies found a nonsignificant or negative impact. More importantly, the positive effect of ICT use on social connectedness and social support seemed to be short-term and did not last for more than six months after the intervention. The results for self-esteem and control over one’s life were consistent but generally nonsignificant. ICT was found to alleviate the elderly’s social isolation through four mechanisms: connecting to the outside world, gaining social support, engaging in activities of interests, and boosting self-confidence. Conclusions: More well-designed studies that contain a minimum risk of research bias are needed to draw conclusions on the effectiveness of ICT interventions for elderly people in reducing their perceived social isolation as a multidimensional concept. The results of this review suggest that ICT could be an effective tool to tackle social isolation among the elderly. However, it is not suitable for every senior alike. Future research should identify who among elderly people can most benefit from ICT use in reducing social isolation. Research on other types of ICT (eg, mobile phone–based instant messaging apps) should be conducted to promote understanding and practice of ICT-based social-isolation interventions for elderly people. [J Med Internet Res 2016;18(1):e18]

Osteoclast-derived exosomal miR-214-3p inhibits osteoblastic bone formation

Abstract: Emerging evidence indicates that osteoclasts direct osteoblastic bone formation. MicroRNAs (miRNAs) have a crucial role in regulating osteoclast and osteoblast function. However, whether miRNAs mediate osteoclast-directed osteoblastic bone formation is mostly unknown. Here, we show that increased osteoclastic miR-214-3p associates with both elevated serum exosomal miR-214-3p and reduced bone formation in elderly women with fractures and in ovariectomized (OVX) mice. Osteoclast-specific miR-214-3p knock-in mice have elevated serum exosomal miR-214-3p and reduced bone formation that is rescued by osteoclast-targeted antagomir-214-3p treatment. We further demonstrate that osteoclast-derived exosomal miR-214-3p is transferred to osteoblasts to inhibit osteoblast activity in vitro and reduce bone formation in vivo. Moreover, osteoclast-targeted miR-214-3p inhibition promotes bone formation in ageing OVX mice. Collectively, our results suggest that osteoclast-derived exosomal miR-214-3p transfers to osteoblasts to inhibit bone formation. Inhibition of miR-214-3p in osteoclasts may be a strategy for treating skeletal disorders involving a reduction in bone formation.

Action2Activity: Recognizing Complex Activities from Sensor Data

Abstract: As compared to simple actions, activities are much more complex, but semantically consistent with a human's real life. Techniques for action recognition from sensor generated data are mature. However, there has been relatively little work on bridging the gap between actions and activities. To this end, this paper presents a novel approach for complex activity recognition comprising of two components. The first component is temporal pattern mining, which provides a mid-level feature representation for activities, encodes temporal relatedness among actions, and captures the intrinsic properties of activities. The second component is adaptive Multi-Task Learning, which captures relatedness among activities and selects discriminant features. Extensive experiments on a real-world dataset demonstrate the effectiveness of our work.

Acetate functions as an epigenetic metabolite to promote lipid synthesis under hypoxia.

Abstract: Besides the conventional carbon sources, acetyl-CoA has recently been shown to be generated from acetate in various types of cancers, where it promotes lipid synthesis and tumour growth. The underlying mechanism, however, remains largely unknown. We find that acetate induces a hyperacetylated state of histone H3 in hypoxic cells. Acetate predominately activates lipogenic genes ACACA and FASN expression by increasing H3K9, H3K27 and H3K56 acetylation levels at their promoter regions, thus enhancing de novo lipid synthesis, which combines with its function as the metabolic precursor for fatty acid synthesis. Acetyl-CoA synthetases (ACSS1, ACSS2) are involved in this acetate-mediated epigenetic regulation. More importantly, human hepatocellular carcinoma with high ACSS1/2 expression exhibit increased histone H3 acetylation and FASN expression. Taken together, this study demonstrates that acetate, in addition to its ability to induce fatty acid synthesis as an immediate metabolic precursor, also functions as an epigenetic metabolite to promote cancer cell survival under hypoxic stress.

Cooperative data scheduling in hybrid vehicular ad hoc networks: VANET as a software defined network

Abstract: This paper presents the first study on scheduling for cooperative data dissemination in a hybrid infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communication environment. We formulate the novel problem of cooperative data scheduling (CDS). Each vehicle informs the road-side unit (RSU) the list of its current neighboring vehicles and the identifiers of the retrieved and newly requested data. The RSU then selects sender and receiver vehicles and corresponding data for V2V communication, while it simultaneously broadcasts a data item to vehicles that are instructed to tune into the I2V channel. The goal is to maximize the number of vehicles that retrieve their requested data. We prove that CDS is NP-hard by constructing a polynomial-time reduction from the Maximum Weighted Independent Set (MWIS) problem. Scheduling decisions are made by transforming CDS to MWIS and using a greedy method to approximately solve MWIS. We build a simulation model based on realistic traffic and communication characteristics and demonstrate the superiority and scalability of the proposed solution. The proposed model and solution, which are based on the centralized scheduler at the RSU, represent the first known vehicular ad hoc network (VANET) implementation of software defined network (SDN) concept.

The Signaling Effect of Corporate Social Responsibility in Emerging Economies

Abstract: What signals do firms in emerging economies send to stakeholders when they adopt corporate social responsibility (CSR) practices? We argue that in emerging economies, firms that adopt CSR practices positively signal investors that their firms have superior capabilities for filling institutional voids. From an institution-based view, we hypothesize that the institutional environment moderates the signaling effect of CSR on a firm’s financial performance. Based on a sample of firms from ten Asian emerging economies, we find a positive relationship between CSR practices and financial performance. This positive relationship is stronger in the less developed capital market than in the more developed one. The financial benefits of CSR practices are also more salient in the low information diffusion market than in the high one. We emphasize that signaling theory and the institution-based view can jointly contribute to the CSR literature.

Astragalus membranaceus: A review of its protection against inflammation and gastrointestinal cancers

Abstract: Astragalus membranaceus is a major medicinal herb commonly used in many herbal formulations in the practice of traditional Chinese medicine (TCM) to treat a wide variety of diseases and body disorders. Among its diversified clinical applications, the potential use of this herb and its chemical constituents in treatments of inflammatory diseases and cancers has been actively investigated in recent years. Astragalus-based treatments have demonstrated significant amelioration of the toxicity induced by other concurrently administered orthodox drugs (e.g., immunosuppressants and cancer chemotherapeutics). The major components of Astragalus membranaceus are polysaccharides, flavonoids, and saponins. Contemporary use of Astragalus membranaceus mainly focuses on its immunomodulating, anti-oxidant, and anti-inflammatory, as well as anticancer effects. In this paper, we summarize the properties of Astragalus membranaceus and its major constituents in the biological system based on experimental and clinical studies. The antitumorigenic mechanisms of a novel Astragalus saponins extract called AST in treating various gastrointestinal cancers are highlighted. We discuss in detail how the Astragalus herb and AST influence the immune system, modulate various cancer signaling pathways, and interact with specific transcription molecules during protection against gastrointestinal inflammation and cancers. This information could help clinicians and scientists develop novel target-specific and effective therapeutic agents that are deprived of major systemic side effects, so as to establish a better treatment regimen in the battle against inflammatory diseases and cancers of the gut.

Benchmarking State-of-the-Art Deep Learning Software Tools

Abstract: Deep learning has been shown as a successful machine learning method for a variety of tasks, and its popularity results in numerous open-source deep learning software tools coming to public. Training a deep network is usually a very time-consuming process. To address the huge computational challenge in deep learning, many tools exploit hardware features such as multi-core CPUs and many-core GPUs to shorten the training and inference time. However, different tools exhibit different features and running performance when they train different types of deep networks on different hardware platforms, making it difficult for end users to select an appropriate pair of software and hardware. In this paper, we present our attempt to benchmark several state-of-the-art GPU-accelerated deep learning software tools, including Caffe, CNTK, TensorFlow, and Torch. We focus on evaluating the running time performance (i.e., speed) of these tools with three popular types of neural networks on two representative CPU platforms and three representative GPU platforms. Our contribution is two-fold. First, for end users of deep learning software tools, our benchmarking results can serve as a reference to selecting appropriate hardware platforms and software tools. Second, for developers of deep learning software tools, our in-depth analysis points out possible future directions to further optimize the running performance.

Aligning users across social networks using network embedding

Abstract: In this paper, we adopt the representation learning approach to align users across multiple social networks where the social structures of the users are exploited. In particular, we propose to learn a network embedding with the followership/ followee-ship of each user explicitly modeled as input/output context vector representations so as to preserve the proximity of users with "similar" followers/followees in the embedded space. For the alignment, we add both known and potential anchor users across the networks to facilitate the transfer of context information across networks. We solve both the network embedding problem and the user alignment problem simultaneously under a unified optimization framework. The stochastic gradient descent and negative sampling algorithms are used to address scalability issues. Extensive experiments on real social network datasets demonstrate the effectiveness and efficiency of the proposed approach compared with several state-of-the-art methods.

Facets of the Fundamental Content Dimensions: Agency with Competence and Assertiveness-Communion with Warmth and Morality.

Abstract: Agency (A) and communion (C) are fundamental content dimensions. We propose a facet-model that differentiates A into assertiveness (AA) and competence (AC) and C into warmth (CW) and morality (CM). We tested the model in a cross-cultural study by comparing data from Asia, Australia, Europe, and the USA (overall N = 1.808). Exploratory and confirmatory factor analyses supported our model. Both the two-factor model and the four-factor model showed good fit indices across countries. Participants answered additional measures intended to demonstrate the fruitfulness of distinguishing the facets. The findings support the model's construct validity by positioning the fundamental dimensions and their facets within a network of self-construal, values, impression management, and the Big Five personality factors: In all countries, A was related to independent self-construal and to agentic values, C was related to interdependent self-construal and to communal values. Regarding the facets, AA was always related to A values, but the association of AC with A values fell below our effect size criterion in four of the five countries. A (both AA and AC) was related to agentic impression management. However, C (both CW and CM) was neither related to communal nor to agentic impression management. Regarding the Big Five personality factors, A was related to emotional stability, to extraversion, and to conscientiousness. C was related to agreeableness and to extraversion. AA was more strongly related to emotional stability and extraversion than AC. CW was more strongly related to extraversion and agreeableness than CM. We could also show that self-esteem was more related to AA than AC; and that it was related to CM, but not to CW. Our research shows that (a) the fundamental dimensions of A and C are stable across cultures; and (b) that the here proposed distinction of facets of A and C is fruitful in analyzing self-perception. The here proposed measure, the AC-IN, may be a useful tool in this research area. Applications of the facet model in social perception research are discussed.

TargetNet: a web service for predicting potential drug–target interaction profiling via multi-target SAR models

Abstract: Drug–target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug–drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naive Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user’s molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75–100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug–drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

Antidiabetic Effects of Simple Phenolic Acids: A Comprehensive Review

Abstract: Diabetes mellitus (DM) has become a major public health threat across the globe. Current antidiabetic therapies are based on synthetic drugs that very often have side effects. It has been widely acknowledged that diet plays an important role in the management of diabetes. Phenolic acids are widely found in daily foods such as fruits, vegetables, cereals, legumes, and wine and they provide biological, medicinal, and health properties. Simple phenolic acids have been shown to increase glucose uptake and glycogen synthesis, improve glucose and lipid profiles of certain diseases (obesity, cardiovascular diseases, DM, and its complication). The current review is an attempt to list out the antidiabetic effects of simple phenolic acids from medicinal plants and botanical foods.

Linkers Having a Crucial Role in Antibody-Drug Conjugates.

Abstract: Antibody-drug conjugates (ADCs) comprised of a desirable monoclonal antibody, an active cytotoxic drug and an appropriate linker are considered to be an innovative therapeutic approach for targeted treatment of various types of tumors and cancers, enhancing the therapeutic parameter of the cytotoxic drug and reducing the possibility of systemic cytotoxicity. An appropriate linker between the antibody and the cytotoxic drug provides a specific bridge, and thus helps the antibody to selectively deliver the cytotoxic drug to tumor cells and accurately releases the cytotoxic drug at tumor sites. In addition to conjugation, the linkers maintain ADCs' stability during the preparation and storage stages of the ADCs and during the systemic circulation period. The design of linkers for ADCs is a challenge in terms of extracellular stability and intracellular release, and intracellular circumstances, such as the acid environment, the reducing environment and cathepsin, are considered as the catalysts to activate the triggers for initiating the cleavage of ADCs. This review discusses the linkers used in the clinical and marketing stages for ADCs and details the fracture modes of the linkers for the further development of ADCs.

Highly Selective Two-Photon Fluorescent Probe for Ratiometric Sensing and Imaging Cysteine in Mitochondria

Abstract: A novel ratiometric mitochondrial cysteine (Cys)-selective two-photon fluorescence probe has been developed on the basis of a merocyanine as the fluorophore and an acrylate moiety as the biothiol reaction site. The biocompatible and photostable acrylate-functionalized merocyanine probe shows not only a mitochondria-targeting property but also highly selective detection and monitoring of Cys over other biothiols such as homocysteine (Hcy) and glutathione (GSH) and hydrogen sulfide (H2S) in live cells. In addition, this probe exhibits ratiometric fluorescence emission characteristics (F518/F452), which are linearly proportional to Cys concentrations in the range of 0.5–40 μM. More importantly, the probe and its released fluorophore, merocyanine, exhibit strong two-photon excited fluorescence (TPEF) with two-photon action cross-section (Φσmax) of 65.2 GM at 740 nm and 72.6 GM at 760 nm in aqueous medium, respectively, which is highly desirable for high contrast and brightness ratiometric two-photon fluoresce...

Transketolase counteracts oxidative stress to drive cancer development

Abstract: Cancer cells experience an increase in oxidative stress. The pentose phosphate pathway (PPP) is a major biochemical pathway that generates antioxidant NADPH. Here, we show that transketolase (TKT), an enzyme in the PPP, is required for cancer growth because of its ability to affect the production of NAPDH to counteract oxidative stress. We show that TKT expression is tightly regulated by the Nuclear Factor, Erythroid 2-Like 2 (NRF2)/Kelch-Like ECH-Associated Protein 1 (KEAP1)/BTB and CNC Homolog 1 (BACH1) oxidative stress sensor pathway in cancers. Disturbing the redox homeostasis of cancer cells by genetic knockdown or pharmacologic inhibition of TKT sensitizes cancer cells to existing targeted therapy (Sorafenib). Our study strengthens the notion that antioxidants are beneficial to cancer growth and highlights the therapeutic benefits of targeting pathways that generate antioxidants.

Capacity Estimation for Vehicle-to-Grid Frequency Regulation Services With Smart Charging Mechanism

Abstract: Due to various green initiatives, renewable energy will be massively incorporated into the future smart grid. However, the intermittency of the renewables may result in power imbalance, thus adversely affecting the stability of a power system. Frequency regulation may be used to maintain the power balance at all times. As electric vehicles (EVs) become popular, they may be connected to the grid to form a vehicle-to-grid (V2G) system. An aggregation of EVs can be coordinated to provide frequency regulation services. However, V2G is a dynamic system where the participating EVs come and go independently. Thus, it is not easy to estimate the regulation capacities for V2G. In a preliminary study, we modeled an aggregation of EVs with a queueing network, whose structure allows us to estimate the capacities for regulation-up and regulation-down separately. The estimated capacities from the V2G system can be used for establishing a regulation contract between an aggregator and the grid operator, and facilitating a new business model for V2G. In this paper, we extend our previous development by designing a smart charging mechanism that can adapt to given characteristics of the EVs and make the performance of the actual system follow the analytical model.

Multifunctional polymetallaynes: properties, functions and applications.

Abstract: Insertion of transition metal elements into organic polymeric scaffolds enables a nice coupling of the intriguing physical traits of metal complexes such as electronic, optical and magnetic properties with the solution processability of carbon-based macromolecules. The propensity of these metal-based polymers towards exhibiting metal–metal interactions can also provide additional means for manipulating the structural order and electronic coupling in the molecules. Among these metallopolymers, rigid-rod transition metal σ-acetylide polymers, or polymetallaynes in short, are of much current interest. These organometallic polymers are important functional materials showing unique characteristics including electrical semiconductivity, photo-/electroluminescence, non-linear optical properties, liquid crystallinity, chemosensing capability and photovoltaic effect. Recently, there has been an impressive progress of functional polymetallaynes consisting of a variety of conjugated organic bridging moieties and transition metals. In this review, we summarize the structure–property–function relationships of polymetallaynes of different transition metals, with a major focus on the effect of transition metals and the structural modification of ligands in activating their multifunctional properties. Different emerging applications can thus be realized, for example, as the converters for both light/electricity signals, sensor protectors against intense laser beam and patternable precursors to magnetic metal alloy nanoparticles for data storage, etc.

High-performance polymer solar cells based on a 2D-conjugated polymer with an alkylthio side-chain

Abstract: Two new two-dimension (2D)-conjugated copolymers (PBDTT-S-TT-CF and PBDTT-O-TT-CF) were designed and synthesized for the application as donor materials in polymer solar cells (PSCs) and for further investigation of the effect of alkylthio side chains on the photovoltaic performance of 2D-conjugated polymers. The two copolymers were prepared by the copolymerization of alkylthio- or alkoxy-thienyl-benzodithiophene (BDTT-S or BDTT-O) and thienothiophene with carbonyl and fluorine substituents (TT-CF), and they demonstrated strong and broad absorption spectra in the wavelength region from 450 nm to ca. 800 nm. The HOMO energy level of PBDTT-S-TT-CF was further down-shifted to −5.44 eV by alkylthio substitution on thiophene conjugated side chain of BDT unit and the carbonyl and fluorine substitution on TT unit. The inverted-structured PSCs based on PBDTT-S-TT-CF:PC70BM exhibited a high PCE of 9.58% with a remarkably high Voc of 0.89 V and a high FF of 71.0%. The PCE of the PSCs based on PBDTT-O-TT-CF also reached a high value of 8.68% with a Voc = 0.78 V and a higher Jsc = 16.5 mA cm−2, which is benefited from the broad absorption of PBDTT-O-TT-CF. The results further confirm the unique advantages of the alkylthio side chain in the design of state-of-the-art polymer donor materials for high performance PSCs with high Voc.

Conjugating a groove-binding motif to an Ir(III) complex for the enhancement of G-quadruplex probe behavior

Abstract: In this study, the reported G-quadruplex groove binder benzo[d,e]isoquinoline was linked to a cyclometallated Ir(iii) complex to generate a highly selective DNA probe 1 that retains the favorable photophysical properties of the parent complex. The linked complex 1 showed advantages of both parent complex 2 and groove binder 3. Similar to 3, the conjugated complex 1 exhibits a superior affinity and selectivity for G-quadruplex DNA over other conformations of DNA or proteins, with the fold enhancement ratio obviously improved compared with parent complex 2. The molecular modelling revealed a groove-binding mode between complex 1 and G-quadruplex. Meanwhile 1 also possesses the prominent advantages of transition metal complex probes such as a large Stokes shift and long lifetime phosphorescence, which could be recognized in strong fluorescence media through time-resolved emission spectroscopy (TRES). We then employed 1 to develop a detection assay for AGR2, a potential cancer biomarker, as a "proof-of-principle" demonstration of the application of a linked complex for DNA-based detection in diluted fetal bovine serum. We anticipate that this conjugation method may be further employed in the development of DNA probes and have applications in label-free DNA-based diagnostic platforms.

Gut microbiota-involved mechanisms in enhancing systemic exposure of ginsenosides by coexisting polysaccharides in ginseng decoction

Abstract: Oral decoctions of traditional Chinese medicines (TCMs) serve for therapeutic and prophylactic management of diseases for centuries. Small molecules and polysaccharides are the dominant chemicals co-occurred in the TCM decoction. Small molecules are well-studied by multidisciplinary elaborations, whereas the role of polysaccharides remains largely elusive. Here we explore a gut microbiota-involved mechanism by which TCM polysaccharides restore the homeostasis of gut microbiota and consequently promote the systemic exposure of concomitant small molecules in the decoction. As a case study, ginseng polysaccharides and ginsenosides in Du-Shen-Tang, the decoction of ginseng, were investigated on an over-fatigue and acute cold stress model. The results indicated that ginseng polysaccharides improved intestinal metabolism and absorption of certain ginsenosides, meanwhile reinstated the perturbed holistic gut microbiota, and particularly enhanced the growth of Lactobacillus spp. and Bacteroides spp., two major metabolic bacteria of ginsenosides. By exploring the synergistic actions of polysaccharides with small molecules, these findings shed new light on scientization and rationalization of the classic TCM decoctions in human health care.

Inferring a personalized next point-of-interest recommendation model with latent behavior patterns

Abstract: In this paper, we address the problem of personalized next Point-of-interest (POI) recommendation which has become an important and very challenging task in location-based social networks (LBSNs), but not well studied yet. With the conjecture that, under different contextual scenario, human exhibits distinct mobility patterns, we attempt here to jointly model the next POI recommendation under the influence of user's latent behavior pattern. We propose to adopt a third-rank tensor to model the successive check-in behaviors. By incorporating softmax function to fuse the personalized Markov chain with latent pattern, we furnish a Bayesian Personalized Ranking (BPR) approach and derive the optimization criterion accordingly. Expectation Maximization (EM) is then used to estimate the model parameters. Extensive experiments on two large-scale LBSNs datasets demonstrate the significant improvements of our model over several state-of-the-art methods.

Hypoxia causes transgenerational impairments in reproduction of fish.

Abstract: Hypoxia is amongst the most widespread and pressing problems in aquatic environments. Here we demonstrate that fish (Oryzias melastigma) exposed to hypoxia show reproductive impairments (retarded gonad development, decrease in sperm count and sperm motility) in F1 and F2 generations despite these progenies (and their germ cells) having never been exposed to hypoxia. We further show that the observed transgenerational reproductive impairments are associated with a differential methylation pattern of specific genes in sperm of both F0 and F2 coupled with relevant transcriptomic and proteomic alterations, which may impair spermatogenesis. The discovered transgenerational and epigenetic effects suggest that hypoxia might pose a dramatic and long-lasting threat to the sustainability of fish populations. Because the genes regulating spermatogenesis and epigenetic modifications are highly conserved among vertebrates, these results may also shed light on the potential transgenerational effects of hypoxia on other vertebrates, including humans.