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Molecular-level security devices have raised ever-increasing interest in recent years to protect data and information from illegal invasion. Prior molecular keypad locks have an output signal dependent upon not only the appropriate combination but also the exact sequence of inputs, but it cannot be reset or reprogrammed. Here, a DNA-based security system with reset and never-reported reprogram function is successfully developed in proof-of-principle, with which one can change the password in case that the system is cracked. The previous password becomes invalid in the reprogrammed security system. Interestingly, more than one password is designed to permit multiple users to access. By harnessing the intrinsic merit of the different passwords, the system can distinguish different user who is endowed with prior authority. The intelligent device is addressed on solid support and facilitates electronic processes, avoiding chemical accumulation in the system by simple removal of the electrode from the input solution and indicating a main avenue for its further development.

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Endophytic fungi associated with three bryophyte species in the Fildes Region, King George Island, maritime Antarctica, that is, the liverwort Barbilophozia hatcheri, the mosses Chorisodontium aciphyllum and Sanionia uncinata, were studied by culture-dependent method. A total of 128 endophytic fungi were isolated from 1329 tissue segments of 14 samples. The colonization rate of endophytic fungi in three bryophytes species were 12.3%, 12.1%, and 8.7%, respectively. These isolates were identified to 21 taxa, with 15 Ascomycota, 5 Basidiomycota, and 1 unidentified fungus, based on morphological characteristics and sequence analyses of ITS region and D1/D2 domain. The dominant fungal endophyte was Hyaloscyphaceae sp. in B. hatcheri, Rhizoscyphus sp. in C. aciphyllum, and one unidentified fungus in S. uncinata; and their relative frequencies were 33.3%, 32.1%, and 80.0%, respectively. Furthermore, different Shannon-Weiner diversity indices (0.91-1.99) for endophytic fungi and low endophytic fungal composition similarities (0.19-0.40) were found in three bryophyte species. Growth temperature tests indicated that 21 taxa belong to psychrophiles (9), psychrotrophs (11), and mesophile (1). The results herein demonstrate that the Antarctic bryophytes are an interesting source of fungal endophytes and the endophytic fungal composition is different among the bryophyte species, and suggest that these fungal endophytes are adapted to cold stress in Antarctica.

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Background: Alpiniae Oxyphyllae Fructus (Yizhi in Chinese) have been widely used as an herbal medicine for the treatment of diuresis, enuresis and diarrhea in China. Many studies have deciphered some potential underlying mechanisms for its anti-diarrheal effects. However, tissue distribution of Yizhi constituents is warranted because pharmacological receptors are frequently located in tissues. Moreover, it is also interesting to know about the potential correlation between behavior in drug distribution and the observed pharmacological response. The aim of this study is to investigate tissue distribution behaviors of Yizhi constituents after oral administration of Yizhi extract to rats, focusing on 10 active principles. Methods: Twenty four male Sprague Dawley rats were given orally the Yizhi extract and fourteen tissue samples were collected after being killed by bleeding from the abdominal aorta under ether anesthesia at different time-points. The resulting tissues were excised and homogenized. Based on our previous reports, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) was used to quantify the target analytes, as well as phase II metabolites, in the various biosamples. Results: Almost all the targeted Yizhi active principles and some glucuronidated metabolites were qualitatively measured in rat stomach, small intestine, large intestine, as well as liver. Nootkatone, yakuchinone A and tectochrysin were observed in the rat brain. In other rat tissues, these analytes had lower exposure or could not be detected. Consistently, quantitative analysis revealed that the Yizhi active principles dominantly distributed into gastrointestinal tissues followed by liver, the overall exposure levels ranking as follows: stomach > small intestine > large intestine > liver. Tissue concentrationtime profiles of the test active principles in rat stomach, small intestine, and large intestine were bimodal with two concentration peaks occurring at 0.5 and 4h after oral administration, respectively. The exposure levels in rat kidney and bladder were quite low. Conclusion: The active principles of Yizhi were specially distributed into gastrointestinal tissues after oral administration of its ethanol extract to rats. The tissue distribution behaviors partly supported its anti-diarrheal effects from a pharmacokinetic opinion. This paper will be useful as the starting point for studying the pharmacological activities of this traditional herb.

Wireless Body area Sensor Network (WBSN) is a recent concept that can dramatically benefit healthcare applications through advances in wireless technology. Physiological and biokinetic parameters that require continuous monitoring are sensed by small and lightweight body sensors that transmit the values of these parameters over wireless links for monitoring at the other end. The sensors employed in WBSNs are limited in resources, with battery power being at the premium. Conservation of energy used by the network has a direct bearing on the longevity of the network. Therefore, there is no need to send data periodically and need to transmit selectively when needed. This paper presents a dual framework for predicting when to transfer physiological parameters in such a network that could save energy consumption while maintaining error to minimum level. The framework utilizes an artificial neural network (ANN) for prediction that not only saves energy, but also does it with lesser error than popular prediction algorithms. A comparison of performance of five data prediction algorithms in predicting physiological data is presented. The amount of network energy saved as a result of prediction is also considered in detail.