Effectiveness of 10 polymorphic microsatellite markers for parentage and pedigree analysis in plateau pika (Ochotona curzoniae)

<p>Abstract</p> <p>Background</p> <p>The plateau pika <it>(Ochotona curzoniae) </it>is an underground-dwelling mammal, native to the Tibetan plateau of China. A set of 10 polymorphic microsatellite loci has been developed earlier. Its reliability for parentage assignment has been tested in a plateau pika population. Two family groups with a known pedigree were used to validate the power of this set of markers.</p> <p>Results</p> <p>The error in parentage assignment using a combination of these 10 loci was very low as indicated by their power of discrimination (0.803 - 0.932), power of exclusion (0.351 - 0.887), and an effectiveness of the combined probability of exclusion in parentage assignment of 99.999%.</p> <p>Conclusion</p> <p>All the offspring of a family could be assigned to their biological mother; and their father or relatives could also be identified. This set of markers therefore provides a powerful and efficient tool for parentage assignment and other population analyses in the plateau pika.</p

A multiple hashing approach to complete identification of missing RFID tags

PublishedJournal ArticleOwing to its superior properties, such as fast identification and relatively long interrogating range over barcode systems, Radio Frequency Identification (RFID) technology has promising application prospects in inventory management. This paper studies the problem of complete identification of missing RFID tag, which is important in practice. Time efficiency is the key performance metric of missing tag identification. However, the existing protocols are ineffective in terms of execution time and can hardly satisfy the requirements of real-time applications. In this paper, a Multi-hashing based Missing Tag Identification (MMTI) protocol is proposed, which achieves better time efficiency by improving the utilization of the time frame used for identification. Specifically, the reader recursively sends bitmaps that reflect the current slot occupation state to guide the slot selection of the next hashing process, thereby changing more empty or collision slots to the expected singleton slots. We investigate the optimal parameter settings to maximize the performance of the MMTI protocol. Furthermore, we discuss the case of channel error and propose the countermeasures to make the MMTI workable in the scenarios with imperfect communication channels. Extensive simulation experiments are conducted to evaluate the performance of MMTI, and the results demonstrate that this new protocol significantly outperforms other related protocols reported in the current literature. © 2014 IEEE.This work was supported by NSFC (Grant No.s 60973117, 61173160, 61173162, 60903154, and 61321491), New Century Excellent Talents in University (NCET) of Ministry of Education of China, the National Science Foundation for Distinguished Young Scholars of China (Grant No. 61225010), and the Project funded by China Postdoctoral Science Foundation

Multi-objective Black Widow Algorithm Guided by Competitive Mechanism and Pheromone Mechanism

Black widow optimization algorithm (BWOA) is a swarm intelligence optimization algorithm, which has the advantages of fast convergence and high precision. However, the update strategy adopted by BWOA is too simple, and it is easy to fall into the local optimal solution. Moreover, the search ability in multi-dimensional space is lacking, the population structure is single, and the convergence and diversity of the algorithm need to be improved.&nbsp; In order to improve the comprehensive performance of BWOA and make it applicable to multi-objective optimization problems, this paper proposes a multi-objective black widow optimization algorithm (MBWOA) guided by a competition mechanism and an improved pheromone mechanism. MBWOA adopts the method of dynamic allocation of populations, which divides the populations into two in the iterative process and uses different competition mechanisms to enhance the diversity of the populations in the iterative process and improve the convergence of the algorithm. At the same time, it uses the improved pheromone mechanism to guide offspring individuals that have gone through the competition mechanism to optimize in the direction of population gap, improve the distribution of population, and enhance the convergence ability of the algorithm. Using MBWOA and four comparison algorithms to conduct comparative experiments on three indicators of IGD, HV and Spread respectively, the results show that MBWOA has better convergence accuracy, convergence speed and diversity. Finally, the effectiveness of the used mechanism is confirmed by the experiments of MBWOA and the comparison algorithms on three indicators

Effects of climate change and anthropogenic activity on ranges of vertebrate species endemic to the Qinghai - Tibet Plateau over 40 years

Over the past 40 years, the climate has been changing and human disturbance has increased in the vast Qinghai¿Tibet Plateau (QTP). These 2 factors are expected to affect the distribution of a large number of endemic vertebrate species. However, quantitative relationships between range shifts and climate change and human disturbance of these species in the QTP have rarely been evaluated. We used occurrence records of 19 terrestrial vertebrate species (birds, mammals, amphibians, and reptiles) occurring in the QTP from 1980 to 2020 to quantify the effects of climate change and anthropogenic impacts on the distribution of these 4 taxonomic groups and estimated species range changes in each species. The trend in distribution changes differed among the taxonomic groups, although, generally, ranges shifted to central QTP. Climate change contributed more to range variation than human disturbance (the sum of the 4 climatic variables contributed more than the sum of the 4 human disturbance variables for all 4 taxonomic groups). Suitable geographic range increased for most mammals, amphibians, and reptiles (+27.6%, +18.4%, and +27.8% on average, respectively), whereas for birds range decreased on average by 0.9%. Quantitative evidence for climate change and human disturbance associations with range changes for endemic vertebrate species in the QTP can provide useful insights into biodiversity conservation under changing environments.This project was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (2019QZKK0501); the Strategic Priority Research Program of Chinese Academy of Sciences (CAS) (XDB31000000); the National Natural Science Foundation of China (32070410; 32100396); the Youth Innovation Promotion Association of CAS (2021370); and the Sichuan Science and Technology Program (2023NSFSC0197)INTRODUCTION METHODS Species distribution data Statistical analyses RESULTS DISCUSSION ACKNOWLEDGMENT

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase&nbsp;chain&nbsp;reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of&nbsp;prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics

METSP: A Maximum-Entropy Classifier Based Text Mining Tool for Transporter-Substrate Identification with Semistructured Text

The substrates of a transporter are not only useful for inferring function of the transporter, but also important to discover compound-compound interaction and to reconstruct metabolic pathway. Though plenty of data has been accumulated with the developing of new technologies such as in vitro transporter assays, the search for substrates of transporters is far from complete. In this article, we introduce METSP, a maximum-entropy classifier devoted to retrieve transporter-substrate pairs (TSPs) from semistructured text. Based on the high quality annotation from UniProt, METSP achieves high precision and recall in crossvalidation experiments. When METSP is applied to 182,829 human transporter annotation sentences in UniProt, it identifies 3942 sentences with transporter and compound information. Finally, 1547 confidential human TSPs are identified for further manual curation, among which 58.37% pairs with novel substrates not annotated in public transporter databases. METSP is the first efficient tool to extract TSPs from semistructured annotation text in UniProt. This tool can help to determine the precise substrates and drugs of transporters, thus facilitating drug-target prediction, metabolic network reconstruction, and literature classification

Solutions to No-Wait Flow Shop Scheduling Problem Using the Flower Pollination Algorithm Based on the Hormone Modulation Mechanism

A flower pollination algorithm is proposed based on the hormone modulation mechanism (HMM-FPA) to solve the no-wait flow shop scheduling problem (NWFSP). This algorithm minimizes the maximum accomplished time. Random keys are encoded based on an ascending sequence of components to make the flower pollination algorithm (FPA) suitable for the no-wait flow shop scheduling problem. The hormone modulation factor is introduced to strengthen information sharing among the flowers and improve FPA cross-pollination to enhance the algorithm global search performance. A variable neighborhood search strategy based on dynamic self-adaptive variable work piece blocks is constructed to improve the local search quality. Three common benchmark instances are applied to test the proposed algorithm. The result verifies that this algorithm is effective

Chicken Swarm Optimization Based on Elite Opposition-Based Learning

Chicken swarm optimization is a new intelligent bionic algorithm, simulating the chicken swarm searching for food in nature. Basic algorithm is likely to fall into a local optimum and has a slow convergence rate. Aiming at these deficiencies, an improved chicken swarm optimization algorithm based on elite opposition-based learning is proposed. In cock swarm, random search based on adaptive t distribution is adopted to replace that based on Gaussian distribution so as to balance the global exploitation ability and local development ability of the algorithm. In hen swarm, elite opposition-based learning is introduced to promote the population diversity. Dimension-by-dimension greedy search mode is used to do local search for individual of optimal chicken swarm in order to improve optimization precision. According to the test results of 18 standard test functions and 2 engineering structure optimization problems, this algorithm has better effect on optimization precision and speed compared with basic chicken algorithm and other intelligent optimization algorithms

Effects of thermal ablation on Treg/Th17 in hepatocellular carcinoma of mice

The study was aimed to explore the possible function of thermal ablation treatment on T helper 17 (Th17) cells and regulatory T (Treg) cells in transplantation of hepatocellular carcinoma in mice. In total, 60 male C57BL/6 mice were divided into control group, model group, and treat group. Flow cytometry was used to detect the frequency of Th17 and Treg cells in peripheral blood. The levels of interleukin (IL)-17, IL-23, IL-10, and transforming growth factor beta (TGF-β) in serum were detected by enzyme-linked immunosorbent assay (ELISA).The levels of IL-17, RORγt, Foxp3, and TGF-β mRNA in tumor tissues were detected by real-time fluorescence quantitative PCR (qRT-PCR). Compared with the model group, tumor size was significantly decreased after thermal ablation treatment. After treatment, the frequency of Th17 cells in peripheral blood was significantly decreased, while the frequency of Treg cells was profoundly increased ( P  < 0.05). The levels of IL-17 and IL-23 were significantly downregulated, while IL-10 and TGF-β levels were upregulated ( P  < 0.05). IL-17 and RORγt mRNA levels in tumor tissues were significantly decreased ( P  < 0.05), and Foxp3 and TGF-β mRNA levels were significantly increased ( P  < 0.05). Thermal ablation treatment plays a positive role in the treatment of hepatoma in mice through affecting the imbalance of Th17/Treg cells