On the Generation of Medical Question-Answer Pairs

Question answering (QA) has achieved promising progress recently. However, answering a question in real-world scenarios like the medical domain is still challenging, due to the requirement of external knowledge and the insufficient quantity of high-quality training data. In the light of these challenges, we study the task of generating medical QA pairs in this paper. With the insight that each medical question can be considered as a sample from the latent distribution of questions given answers, we propose an automated medical QA pair generation framework, consisting of an unsupervised key phrase detector that explores unstructured material for validity, and a generator that involves a multi-pass decoder to integrate structural knowledge for diversity. A series of experiments have been conducted on a real-world dataset collected from the National Medical Licensing Examination of China. Both automatic evaluation and human annotation demonstrate the effectiveness of the proposed method. Further investigation shows that, by incorporating the generated QA pairs for training, significant improvement in terms of accuracy can be achieved for the examination QA system.Comment: AAAI 202

Integrated Filtering Microstrip Duplex Antenna Array with High Isolation

This paper presents a 2 × 1 integrated filtering microstrip duplex antenna array with high isolation and same polarization. The antenna consists of two radiating patches fed by two T-shaped probes and a power distributing duplex network (PDDN). The PDDN is composed of two bandstop filters and a 180-degree phase shift power divider. And the PDDN is designed to achieve the functions of power division, frequency selectivity, and port isolation. A Transmission Line (TL) model is adopted to design the PDDN, and the detailed synthesis procedure is presented. For demonstration, the proposed antenna is designed and fabricated. The implemented antenna achieves an average gain of 10 dBi, a cross-polarization ratio of 20 dB, and an isolation of 35 dB within the operation band

Microbial characterization based on multifractal analysis of metagenomes

IntroductionThe species diversity of microbiomes is a cutting-edge concept in metagenomic research. In this study, we propose a multifractal analysis for metagenomic research.Method and ResultsFirstly, we visualized the chaotic game representation (CGR) of simulated metagenomes and real metagenomes. We find that metagenomes are visualized with self-similarity. Then we defined and calculated the multifractal dimension for the visualized plot of simulated and real metagenomes, respectively. By analyzing the Pearson correlation coefficients between the multifractal dimension and the traditional species diversity index, we obtain that the correlation coefficients between the multifractal dimension and the species richness index and Shannon diversity index reached the maximum value when q = 0, 1, and the correlation coefficient between the multifractal dimension and the Simpson diversity index reached the maximum value when q = 5. Finally, we apply our method to real metagenomes of the gut microbiota of 100 infants who are newborn and 4 and 12 months old. The results show that the multifractal dimensions of an infant's gut microbiomes can distinguish age differences.Conclusion and DiscussionThere is self-similarity among the CGRs of WGS of metagenomes, and the multifractal spectrum is an important characteristic for metagenomes. The traditional diversity indicators can be unified under the framework of multifractal analysis. These results coincided with similar results in macrobial ecology. The multifractal spectrum of infants’ gut microbiomes are related to the development of the infants

A Hybrid Artificial Bee Colony Algorithm for Flexible Job Shop Scheduling Problems

In this paper, we propose a hybrid Pareto-based artificial bee colony (HABC) algorithm for solving the multi-objective flexible job shop scheduling problem. In the hybrid algorithm, each food sources is represented by two vectors, i.e., the machine assignment vector and the operation scheduling vector. The artificial bee is divided into three groups, namely, employed bees, onlookers, and scouts bees. Furthermore, an external Pareto archive set is introduced to record non-dominated solutions found so far. To balance the exploration and exploitation capability of the algorithm, the scout bees in the hybrid algorithm are divided into two parts. The scout bees in one part perform randomly search in the predefined region while each scout bee in another part randomly select one non-dominated solution from the Pareto archive set. Experimental results on the well-known benchmark instances and comparisons with other recently published algorithms show the efficiency and effectiveness of the proposed algorithm

The Deacetylase HDAC6 Mediates Endogenous Neuritic Tau Pathology

The initiating events that promote tau mislocalization and pathology in Alzheimer's disease (AD) are not well defined, partly because of the lack of endogenous models that recapitulate tau dysfunction. We exposed wild-type neurons to a neuroinflammatory trigger and examined the effect on endogenous tau. We found that tau re-localized and accumulated within pathological neuritic foci, or beads, comprised of mostly hypo-phosphorylated, acetylated, and oligomeric tau. These structures were detected in aged wild-type mice and were enhanced in response to neuroinflammation in vivo, highlighting a previously undescribed endogenous age-related tau pathology. Strikingly, deletion or inhibition of the cytoplasmic shuttling factor HDAC6 suppressed neuritic tau bead formation in neurons and mice. Using mass spectrometry-based profiling, we identified a single neuroinflammatory factor, the metalloproteinase MMP-9, as a mediator of neuritic tau beading. Thus, our study uncovers a link between neuroinflammation and neuritic tau beading as a potential early-stage pathogenic mechanism in AD

Homology-Driven Proteomics of Dinoflagellates with Unsequenced Genomes Using MALDI-TOF/TOF and Automated De Novo Sequencing

This study developed a multilayered, gel-based, and underivatized strategy for de novo protein sequence analysis of unsequenced dinoflagellates using a MALDI-TOF/TOF mass spectrometer with the assistance of DeNovo Explorer software. MASCOT was applied as the first layer screen to identify either known or unknown proteins sharing identical peptides presented in a database. Once the confident identifications were removed after searching against the NCBInr database, the remainder was searched against the dinoflagellate expressed sequence tag database. In the last layer, those borderline and nonconfident hits were further subjected to de novo interpretation using DeNovo Explorer software. The de novo sequences passing a reliability filter were subsequently submitted to nonredundant MS-BLAST search. Using this layer identification method, 216 protein spots representing 158 unique proteins out of 220 selected protein spots from Alexandrium tamarense, a dinoflagellate with unsequenced genome, were confidently or tentatively identified by database searching. These proteins were involved in various intracellular physiological activities. This study is the first effort to develop a completely automated approach to identify proteins from unsequenced dinoflagellate databases and establishes a preliminary protein database for various physiological studies of dinoflagellates in the future

Identification and Characterization of Cell Wall Proteins of a Toxic Dinoflagellate Alexandrium catenella

The cell wall is an important subcellular component of dinoflagellate cells with regard to various aspects of cell surface-associated ecophysiology, but the full range of cell wall proteins (CWPs) and their functions remain to be elucidated. This study identified and characterized CWPs of a toxic dinoflagellate, Alexandrium catenella, using a combination of 2D fluorescence difference gel electrophoresis (DIGE) and MALDI TOF-TOF mass spectrometry approaches. Using sequential extraction and temperature shock methods, sequentially extracted CWPs and protoplast proteins, respectively, were separated from A. catenella. From the comparison between sequentially extracted CWPs labeled with Cy3 and protoplast proteins labeled with Cy5, 120 CWPs were confidently identified in the 2D DIGE gel. These proteins gave positive identification of protein orthologues in the protein database using de novo sequence analysis and homology-based search. The majority of the prominent CWPs identified were hypothetical or putative proteins with unknown function or no annotation, while cell wall modification enzymes, cell wall structural proteins, transporter/binding proteins, and signaling and defense proteins were tentatively identified in agreement with the expected role of the extracellular matrix in cell physiology. This work represents the first attempt to investigate dinoflagellate CWPs and provides a potential tool for future comprehensive characterization of dinoflagellate CWPs and elucidation of their physiological functions

Metaproteomic characterization of dissolved organic matter in the water column of the South China Sea

Ministry of Science and Technology [2009CB421203]; National Natural Science Foundation of China [40821063, 40776068, 40876059]; University of ChinaWe characterized dissolved organic matter (DOM; < 0.7 mu m in size) collected from the surface (10-m and 75-m) and bathypelagic (3000-m) layers in the South China Sea using the shotgun proteomic approach. A total of 182 proteins matched by 286 unique peptides were identified from three DOM samples. The number of proteins in the large DOM (LDOM; 0.2-0.7-mu m fraction) was significantly greater than that in the small DOM (SDOM; 5-kD-0.2-mu m fraction). There was no remarkable difference in the number of proteins between the surface and bathypelagic SDOMs. The sources of dissolved proteins were diverse in surface DOM, including various bacterial and phytoplankton groups as well as Oomycetes, whereas the Archaea, Proteobacteria, and some phytoplankton groups were the major contributors to bathypelagic DOM. Proteins involved in cytoskeleton, energy production and conversion, posttranslational modification, protein turnover, and chaperones presented high abundance in surface LDOM, whereas proteins involved in translation, ribosomal structure, and biogenesis were more abundant in bathypelagic LDOM. Proteins involved in transport and metabolism, cell wall or membrane or envelope biogenesis, and photosynthesis were abundant in the 75-m LDOM. A urea ABC transporter assigned to amino acid transport and metabolism was the most abundant protein in the 10-m SDOM, whereas methylenetetrahydromethanopterin reductase involved in energy production and conversion dominated the protein profiles in the 75- and 3000-m SDOMs. The dissolved proteins in the water column are diverse and dynamic, with each layer characterized by unique proteins, and only a very minor amount of proteins from the surface are protected and transferred to the deep sea