Development and validation of a sensitive enzyme-linked immunosorbent assay for clonidine hydrochloride in pig urine and pork samples

Clonidine hydrochloride (CLO) is a new substitute for a traditionally used adrenergic agonist. The illegal use of CLO in the livestock industry possess potential harm to human health. Hence, it is an urgent need for the rapid detection of CLO residues. Here, we prepared a highly sensitive and specific monoclonal antibody (mAb) and it used to develop an indirect competitive ELISA (ic-ELISA) for the rapid screening of CLO residues. The limit of detection and limit of quantification values of ic-ELISA were as follows: 0.033 and 0.054 ng/mL for pig urine and 0.061 and 0.096 ng/mL for pork, respectively. Recovery experiment indicated that the ic-ELISA posed outstanding accuracy and precision. Furthermore, the results of ic-ELISA were strongly correlated to the results of HPLC. Thus, the ic-ELISA provided a sensitive and rapid on-site detection of CLO residues in pig urine and pork samples

Solvothermal synthesis and thermoelectric properties of indium telluride nanostring-cluster hierarchical structures

A simple solvothermal approach has been developed to successfully synthesize n-type α-In2Te3 thermoelectric nanomaterials. The nanostring-cluster hierarchical structures were prepared using In(NO3)3 and Na2TeO3 as the reactants in a mixed solvent of ethylenediamine and ethylene glycol at 200°C for 24 h. A diffusion-limited reaction mechanism was proposed to explain the formation of the hierarchical structures. The Seebeck coefficient of the bulk pellet pressed by the obtained samples exhibits 43% enhancement over that of the corresponding thin film at room temperature. The electrical conductivity of the bulk pellet is one to four orders of magnitude higher than that of the corresponding thin film or p-type bulk sample. The synthetic route can be applied to obtain other low-dimensional semiconducting telluride nanostructures

Integrative Generalized Master Equation: A Theory to Study Long-timescale Biomolecular Dynamics via the Integrals of Memory Kernels

The generalized master equation (GME) provides a powerful approach to study biomolecular dynamics via non-Markovian dynamic models built from molecular dynamics (MD) simulations. Previously, we have implemented the GME for biomolecular dynamics, namely the quasi Markov State Model (qMSM), where we explicitly calculate the memory kernel and propagate protein dynamics using a discretized GME. qMSM can be constructed with much shorter MD simulation trajectories than the Markov State Model (MSM). However, since qMSM needs to explicitly compute the time-dependent memory kernels, it is heavily affected by the numerical fluctuations of simulation data when applied to study complicated conformational changes of biomolecules. This can lead to numerical instability of predicted long-time dynamics, greatly limiting the applicability of the qMSM in complicated molecules. In this paper, we propose a new theory, the Integrative GME (IGME), to overcome the challenges of the qMSM by using the time integrations of memory kernels. The IGME avoids the numerical instability induced by explicit computation of time-dependent memory kernel functions, giving more robust predictions of long-time dynamics. Using our analytical solution of the IGME, we propose a new approach to compute memory kernels and long-time dynamics in a numerically stable, accurate and efficient way. To demonstrate its effectiveness, we have applied the IGME in three biomolecules: the alanine dipeptide, the FIP35 WW domain, and Taq RNAP. In each system, the IGME achieves significantly smaller fluctuations for both memory kernels and long-time dynamics compared to the qMSM. We anticipate that the IGME can be widely applied to investigate complex conformational changes of biomolecules

Active query caching for database web servers

Abstract. A substantial portion of web traffic consists of queries to database web servers. Unfortunately, a common technique to improve web scalability, proxy caching, is ineffective for database web servers because existing web proxy servers cannot cache queries. To address this problem, we modify a recently proposed enhanced proxy server, called an active proxy, to enable Active Query Caching. Our approach works by having the server send the proxy a query applet, which can process simple queries at the proxy. This enables the proxy server to share the database server workload as well as to reduce the network traffic. We show both opportunities and limitations of this approach through a performance study. Keywords:Active query caching, proxy caching, database web servers, query containment.

A Step-by-step Guide on How to Construct quasi-Markov State Models to Study Functional Conformational Changes of Biological Macromolecules

Conformational changes play an important role for many biomolecules to perform their functions. In recent years, Markov State Model (MSM) has become a powerful tool to investigate these functional conformational changes by predicting long time-scale dynamics from many short molecular dynamics (MD) simulations. In MSM, dynamics are modelled by a first-order master equation, in which a biomolecule undergoes Markovian transitions among conformational states at discrete time intervals, called lag time. The lag time has to be sufficiently long to build a Markovian model, but this parameter is often bound by the length of MD simulations available for estimating the frequency of interstate transitions. To address this challenge, we recently employed the generalized master equation (GME) formalism (e.g., the quasi-Markov State Model or qMSM) to encode the non-Markovian dynamics in a time-dependent memory kernel. When applied to study protein dynamics, our qMSM can be built from MD simulations that are an order-of-magnitude shorter than MSM would have required. The construction of qMSM is more complicated than that of MSMs, as time-dependent memory kernels need to be properly extracted from the MD simulation trajectories. Here, we present a step-by-step guide on how to build qMSM from MD simulation datasets, and the materials accompanying this protocol are publicly available on Github: https://github.com/ykhdrew/qMSM_tutorial. We hope this protocol is useful for researchers who want to apply qMSM and study functional conformational changes in biomolecules

Use of DNA metabarcoding of bird pellets in understanding raptor diet on the Qinghai-Tibetan Plateau of China

Background: Diet analysis is essential to understanding the functional role of large bird species in food webs. Morphological analysis of regurgitated bird pellet contents is time intensive and may underestimate biodiversity. DNA metabarcoding has the ability to circumvent these issues, but has yet to be done. Methods: We present a pilot study using DNA metabarcoding of MT-RNR1 and MT-CO1 markers to determine the species of origin and prey of 45 pellets collected in Qinghai and Gansu Provinces, China. Results: We detected four raptor species [Eurasian Eagle Owl (Bubo bubo), Saker Falcon (Falco cherrug), Steppe Eagle (Aquila nipalensis), and Upland Buzzard (Buteo hemilasius)] and 11 unique prey species across 10 families and 4 classes. Mammals were the greatest detected prey class with Plateau Pika (Ochotona curzoniae) being the most frequent. Observed Shannon’s and Simpson’s diversity for Upland Buzzard were 1.089 and 0.479, respectively, while expected values were 1.312 ± 0.266 and 0.485 ± 0.086. For Eurasian Eagle Owl, observed values were 1.202 and 0.565, while expected values were 1.502 ± 0.340 and 0.580 ± 0.114. Interspecific dietary niche partitioning between the two species was not detected. Conclusions: Our results demonstrate successful use of DNA metabarcoding for understanding diet via a novel noninvasive sample type to identify common and uncommon species. More work is needed to understand how raptor diets vary locally, and the mechanisms that enable exploitation of similar dietary resources. This approach has wide ranging applicability to other birds of prey, and demonstrates the power of using DNA metabarcoding to study species noninvasively