131 research outputs found

    Serum anti-Mullerian hormone predicts ovarian response in (Macaca fascicularis) monkeys

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    AMH as a promising predictor of ovarian response has been studied extensively in women undergoing assisted reproductive technology treatment, but little is known about its prediction value in monkeys undergoing ovarian stimulation. In the current study, a total of 380 cynomolgus monkeys ranging from 5 to 12 years received 699 ovarian stimulation cycles. Serum samples were collected for AMH measure with enzyme-linked immunosorbent assay. It was found that serum AMH levels were positive correlated with the number of retrieved oocytes (P < 0.01) in the first, second and third stimulation cycles. In the first cycles, area under the curve (ROCAUC) of AMH is 0.688 for low response and 0.612 for high response respectively, indicating the significant prediction values (P = 0.000 and P = 0.005). The optimal AMH cutoff value was 9.68 ng/mL for low ovarian response and 15.88 ng/mL for high ovarian response prediction. In the second stimulation cycles, the significance of ROCAUC of AMH for high response rather than the low response was observed (P = 0.001 and P = 0.468). The optimal AMH cutoff value for high ovarian response was 15.61 ng/mL. In the third stimulation cycles, AMH lost the prediction value with no significant ROCAUC. Our data demonstrated that AMH, not age, is a cycle-dependent predictor for ovarian response in form of oocyte yields, which would promote the application of AMH in assisted reproductive treatment (ART) of female cynomolgus monkeys. AMH evaluation would optimize candidate selection for ART and individualize the ovarian stimulation strategies, and consequentially improve the efficiency in monkeys

    A longitudinal resource for population neuroscience of school-age children and adolescents in China

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    During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013–2022), the first ten-year stage of the lifespan CCNP (2013–2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0–17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the “Chinese Data-sharing Warehouse for In-vivo Imaging Brain” in the Chinese Color Nest Project (CCNP) – Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank

    Haplotype-resolved genome assembly and allele-specific gene expression in cultivated ginger

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    Ginger (Zingiber officinale) is one of the most valued spice plants worldwide; it is prized for its culinary and folk medicinal applications and is therefore of high economic and cultural importance. Here, we present a haplotype-resolved, chromosome-scale assembly for diploid ginger anchored to 11 pseudochromosome pairs with a total length of 3.1 Gb. Remarkable structural variation was identified between haplotypes, and two inversions larger than 15 Mb on chromosome 4 may be associated with ginger infertility. We performed a comprehensive, spatiotemporal, genome-wide analysis of allelic expression patterns, revealing that most alleles are coordinately expressed. The alleles that exhibited the largest differences in expression showed closer proximity to transposable elements, greater coding sequence divergence, more relaxed selection pressure, and more transcription factor binding site differences. We also predicted the transcription factors potentially regulating 6-gingerol biosynthesis. Our allele-aware assembly provides a powerful platform for future functional genomics, molecular breeding, and genome editing in ginger.https://www.nature.com/hortreshj2022BiochemistryGeneticsMicrobiology and Plant Patholog

    Prevalence and trend of hepatitis C virus infection among blood donors in Chinese mainland: a systematic review and meta-analysis

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    <p>Abstract</p> <p>Background</p> <p>Blood transfusion is one of the most common transmission pathways of hepatitis C virus (HCV). This paper aims to provide a comprehensive and reliable tabulation of available data on the epidemiological characteristics and risk factors for HCV infection among blood donors in Chinese mainland, so as to help make prevention strategies and guide further research.</p> <p>Methods</p> <p>A systematic review was constructed based on the computerized literature database. Infection rates and 95% confidence intervals (95% CI) were calculated using the approximate normal distribution model. Odds ratios and 95% CI were calculated by fixed or random effects models. Data manipulation and statistical analyses were performed using STATA 10.0 and ArcGIS 9.3 was used for map construction.</p> <p>Results</p> <p>Two hundred and sixty-five studies met our inclusion criteria. The pooled prevalence of HCV infection among blood donors in Chinese mainland was 8.68% (95% CI: 8.01%-9.39%), and the epidemic was severer in North and Central China, especially in Henan and Hebei. While a significant lower rate was found in Yunnan. Notably, before 1998 the pooled prevalence of HCV infection was 12.87% (95%CI: 11.25%-14.56%) among blood donors, but decreased to 1.71% (95%CI: 1.43%-1.99%) after 1998. No significant difference was found in HCV infection rates between male and female blood donors, or among different blood type donors. The prevalence of HCV infection was found to increase with age. During 1994-1995, the prevalence rate reached the highest with a percentage of 15.78% (95%CI: 12.21%-19.75%), and showed a decreasing trend in the following years. A significant difference was found among groups with different blood donation types, Plasma donors had a relatively higher prevalence than whole blood donors of HCV infection (33.95% <it>vs </it>7.9%).</p> <p>Conclusions</p> <p>The prevalence of HCV infection has rapidly decreased since 1998 and kept a low level in recent years, but some provinces showed relatively higher prevalence than the general population. It is urgent to make efficient measures to prevent HCV secondary transmission and control chronic progress, and the key to reduce the HCV incidence among blood donors is to encourage true voluntary blood donors, strictly implement blood donation law, and avoid cross-infection.</p

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    A Feedback System Supporting Students Approaching a High-Level Programming Course

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    This study analyzes the mistakes students are prone to make in programming and uses the GDB and Valgrind tools to implement dynamic analysis techniques for their eventual application to programs created by students. In the analysis process, spectral error localization technology is used to strengthen the dynamic analysis to find errors more accurately. The analyzed results are sorted and corresponding feedback is given to students in order for them to better understand the content of errors when revising the program and classifying and counting the types of errors made. This study sorts mistakes frequently made by students and topics in which students are likely to make certain mistakes. The developed system was implemented in experiments including students from a programming course who were divided into two groups, namely the experimental group and the control group. A system for both groups of students to upload and submit assignments and a code analysis and feedback improvement system were used. Students in the control group only used the assignment uploading and submitting system for basic assignment uploading, verification, and the comparison of test data. After the program was entered, declarative sentence disassembly and dynamic slicing were suggested. Data were sent to GNU Debugger (GDB) and Valgrind for spectral error location; the classification and recording of error types; and the interpretation of the number of error lines, error types, and related variables. Feedback and a generated report were sent back to the student interface to provide effective and useful feedback to the students in the experimental group for them to revise their homework and record the types and number of errors they made in that week’s homework in the database. The answers provided by the students to the questions were recorded. The analysis of the pass rates of the students in the experimental and control groups for each homework test aided the understanding of the differences in the learning success of the two groups of students each week. The weekly pass rates and the numbers of measured errors in the experimental group compared with in the control group were input into a distribution map to allow us to better understand whether there was any positive correlation between the detected information, feedback to the students, pass rates of the tests, and other related data. The system statistically obtained feedback and the degree of improvement of homework programs; then, it distributed specially designed questionnaires to all students to directly obtain and quantify their feedback and perceived benefits of this system, thereby verifying the effectiveness of the system and its practicality

    A Feedback System Supporting Students Approaching a High-Level Programming Course

    No full text
    This study analyzes the mistakes students are prone to make in programming and uses the GDB and Valgrind tools to implement dynamic analysis techniques for their eventual application to programs created by students. In the analysis process, spectral error localization technology is used to strengthen the dynamic analysis to find errors more accurately. The analyzed results are sorted and corresponding feedback is given to students in order for them to better understand the content of errors when revising the program and classifying and counting the types of errors made. This study sorts mistakes frequently made by students and topics in which students are likely to make certain mistakes. The developed system was implemented in experiments including students from a programming course who were divided into two groups, namely the experimental group and the control group. A system for both groups of students to upload and submit assignments and a code analysis and feedback improvement system were used. Students in the control group only used the assignment uploading and submitting system for basic assignment uploading, verification, and the comparison of test data. After the program was entered, declarative sentence disassembly and dynamic slicing were suggested. Data were sent to GNU Debugger (GDB) and Valgrind for spectral error location; the classification and recording of error types; and the interpretation of the number of error lines, error types, and related variables. Feedback and a generated report were sent back to the student interface to provide effective and useful feedback to the students in the experimental group for them to revise their homework and record the types and number of errors they made in that week&rsquo;s homework in the database. The answers provided by the students to the questions were recorded. The analysis of the pass rates of the students in the experimental and control groups for each homework test aided the understanding of the differences in the learning success of the two groups of students each week. The weekly pass rates and the numbers of measured errors in the experimental group compared with in the control group were input into a distribution map to allow us to better understand whether there was any positive correlation between the detected information, feedback to the students, pass rates of the tests, and other related data. The system statistically obtained feedback and the degree of improvement of homework programs; then, it distributed specially designed questionnaires to all students to directly obtain and quantify their feedback and perceived benefits of this system, thereby verifying the effectiveness of the system and its practicality

    Ghost Synthetic Aperture with Computational Wavefront Shaping

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    Although optical synthetic aperture has been generally accepted as preferred technique to achieve very large pupil, the optical cophase of all the gaint subapertures is still a difficult task currently. Besides, the associated adaptive optics combatting the atmospheric turbulence presents hard to conduct. Here we demonstrate an incoherent optical synthetic aperture based on lensless ghost imaging method, in which diffraction-limited imaging can be performed even when the distributed sub-sources is non-cophased. Better yet, the wavefront shaping is computationally implement via an iterative algorithm, rather than actual optical modulation process. These enhancement makes the presented technique far easy under current techniques, and promising in many optcial sensing applications.Comment: there are some typos and notation problems, which is adverse for the preprint to be accessible for a wide audienc
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