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Houttuynia cordata (H. cordata) is a popular vegetable in Asian countries and is also used extensively as herbal medicine in treating various diseases. H. cordata contains aristolactams, which have a similar Chinese name as aristolochic acids (AAs); hence, an emerging concern in the greater China region has arisen about the potential linkage between H. cordata and aristolochic acid nephropathy (AAN). However, only a single study has tested for the presence of AAs in H. cordata samples, and the analysis was limited by the analytical sensitivity of the method. Thus, further analysis of AAs in H. cordata using analytical method of higher sensitivity is needed to alleviate public anxiety over the use of this popular vegetable. In this study, a liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was used to analyze H. cordata samples for the natural existence of aristolochic acid I (AA‐I) and aristolochic acid II (AA‐II), which are the most carcinogenic and nephrotoxic compounds in the AA family. After evaluating the method performance by fortifying blank samples with three concentrations of AAs, the validated method was applied to identify AA‐I and AA‐II in both fresh and sun‐dried H. cordata samples (n = 20) collected from different cities in China. The LC–MS/MS method achieved method detection limits (MDLs) as low as 2 ng/g of AAs in H. cordata. Analysis of the collected fresh and sun‐dried H. cordata samples revealed that AA‐I and AA‐II either do not exist naturally in H. cordata or exist at concentrations below the MDLs. Therefore, it is not very likely that consumption of H. cordata will result in AAN because AA‐I and AA‐II, the nephrotoxic and carcinogenic culprits of AAN, are not produced naturally in the plant or are produced at levels that do not pose a risk of AAN. [ABSTRACT FROM AUTHOR]

Rationale: Over the past six decades, residents of farming villages in multiple countries of the Balkan peninsula have been suffering from a unique type of chronic renal disease, Balkan endemic nephropathy (BEN). It was speculated that environmental pollution by aristolochic acids (AAs) produced naturally by Aristolochia clematitis L., a weed that grows in the area, was causing the disease. However, the human exposure pathway to this class of phytotoxin remains obscure. Knowledge of the sink and stability of AAs in the environment would assist in the formulation of policy reducing exposure risk. Methods: Using our newly developed liquid chromatography/tandem mass spectrometry method of high sensitivity and selectivity, we analysed over 130 soil samples collected from cultivation fields in southern Serbia for the presence of AAs. The environmental stability of AAs was also investigated by incubating soil samples spiked with AAs at various temperatures. Results: The analysis detected AA‐I in over two‐fifths of the tested samples at sub‐μg/kg to μg/kg levels, with higher concentrations observed in more acidic farmland soil. Furthermore, analysis of soil samples incubated at various temperatures revealed half‐lives of over 2 months, indicating that AAs are relatively resistant to degradation. Conclusions: Cultivation soil in southern Serbia is being extensively contaminated with AAs released from the decomposition of A. clematitis weeds. Since AAs are resistant to degradation, it is possible that AAs could have been taken up by root absorption and transported to the edible part of food crops. Prolonged exposure to AA‐contaminated food grown from polluted soil could be one of the main aetiological mechanisms of BEN observed in the area. [ABSTRACT FROM AUTHOR]

In an artificial society where agents repeatedly interact with one another, effective coordination among agents is generally a challenge. This is especially true when the participating agents are self-interested, and that there is no central authority to coordinate, and direct communication or negotiation are not possible. Recently, the problem was studied in a paper by Hao and Leung, where a new repeated game mechanism for modeling multi-agent interactions as well as a new reinforcement learning based agent learning method were proposed. In particular, the game mechanism differs from traditional repeated games in that the agents are anonymous, and the agents interact with randomly chosen opponents during each iteration. Their learning mechanism allows agents to coordinate without negotiations. The initial results had been promising. However, extended simulation also reveals that the outcomes are not stable in the long run in some cases, as the high level of cooperation is eventually not sustainable. In this work, we revisit he problem and propose a new learning mechanism as follows. First, we propose an enhanced Q-learning-based framework that allows the agents to better capture both the individual and social utilities that they have learned through observations. Second, we propose a new concept of \social attitude" for determining the action of the agents throughout the game. Simulation results reveal that this approach can achieve higher social utility, including close-to-optimal results in some scenarios, and more importantly, the results are sustainable with social norms emerging. [ABSTRACT FROM AUTHOR]

It is challenging to design effective scheduling algorithms for multimedia transmissions over wireless channels that employ adaptive modulation and coding (AMC). On the one hand, it is desirable for the overall system throughput to be enhanced by taking advantage of multi-user diversity. On the other hand, fairness or QoS guarantees need to be maintained for individual users, especially in the case of multimedia applications that have strict delay requirements. In this paper, we propose a novel scheduling algorithm called QoS-based cross-layer scheduling (QoS-CLS) to achieve a good design tradeoff. To maximize the system throughput, the algorithm takes into account the information on both the physical layer and the data link layer to schedule user transmissions. Using cross-layer information, the scheduling problem is formulated as a Markov Decision Process and the optimal decision policy (based on the channel status, traffic state, and buffer status of each traffic flow) is pre-calculated by linear programming. This policy is then stored in the system for scheduling in real-time. Simulation results show that QoS-CLS can greatly enhance the channel throughput compared to existing algorithms because of its cross-layer QoS consideration and the optimization method. Moreover, it can provide QoS guarantees while achieving efficient resource sharing among different traffic flows. [ABSTRACT FROM AUTHOR]

Aristolochic acids (AAs) are nitrophenanthrene carboxylic acids naturally produced by Aristolochia plants. These plants were widely used to prepare herbal remedies until AAs were observed to be highly nephrotoxic and carcinogenic to humans. Although the use of AA-containing Aristolochia plants in herbal medicine is prohibited in countries worldwide, emerging evidence nevertheless has indicated that AAs are the causative agents of Balkan endemic nephropathy (BEN), an environmentally derived disease threatening numerous residents of rural farming villages along the Danube River in countries of the Balkan Peninsula. This perspective updates recent findings on the identification of AAs in food as a result of the root uptake of free AAs released from the decayed seeds of Aristolochia clematitis L., in combination with their presence and fate in the environment. The potential link between AAs and the high prevalence of chronic kidney diseases in China is also discussed. [ABSTRACT FROM AUTHOR]