220 research outputs found
Cross-Scale Cost Aggregation for Stereo Matching
Human beings process stereoscopic correspondence across multiple scales.
However, this bio-inspiration is ignored by state-of-the-art cost aggregation
methods for dense stereo correspondence. In this paper, a generic cross-scale
cost aggregation framework is proposed to allow multi-scale interaction in cost
aggregation. We firstly reformulate cost aggregation from a unified
optimization perspective and show that different cost aggregation methods
essentially differ in the choices of similarity kernels. Then, an inter-scale
regularizer is introduced into optimization and solving this new optimization
problem leads to the proposed framework. Since the regularization term is
independent of the similarity kernel, various cost aggregation methods can be
integrated into the proposed general framework. We show that the cross-scale
framework is important as it effectively and efficiently expands
state-of-the-art cost aggregation methods and leads to significant
improvements, when evaluated on Middlebury, KITTI and New Tsukuba datasets.Comment: To Appear in 2013 IEEE Conference on Computer Vision and Pattern
Recognition (CVPR). 2014 (poster, 29.88%
MATCHCLIP: locate precise breakpoints for copy number variation using CIGAR string by matching soft clipped reads
Copy number variations (CNVs) are associated with many complex diseases. Next generation sequencing data enable one to identify precise CNV breakpoints to better under the underlying molecular mechanisms and to design more efficient assays. Using the CIGAR strings of the reads, we develop a method that can identify the exact CNV breakpoints, and in cases when the breakpoints are in a repeated region, the method reports a range where the breakpoints can slide. Our method identifies the breakpoints of a CNV using both the positions and CIGAR strings of the reads that cover breakpoints of a CNV. A read with a long soft clipped part (denoted as S in CIGAR) at its 3ā²(right) end can be used to identify the 5ā²(left)-side of the breakpoints, and a read with a long S part at the 5ā² end can be used to identify the breakpoint at the 3ā²-side. To ensure both types of reads cover the same CNV, we require the overlapped common string to include both of the soft clipped parts. When a CNV starts and ends in the same repeated regions, its breakpoints are not unique, in which case our method reports the left most positions for the breakpoints and a range within which the breakpoints can be incremented without changing the variant sequence. We have implemented the methods in a C++ package intended for the current Illumina Miseq and Hiseq platforms for both whole genome and exon-sequencing. Our simulation studies have shown that our method compares favorably with other similar methods in terms of true discovery rate, false positive rate and breakpoint accuracy. Our results from a real application have shown that the detected CNVs are consistent with zygosity and read depth information. The software package is available at http://statgene.med.upenn.edu/softprog.html
Collaborative decoding of critical tokens for boosting factuality of large language models
The most common training pipeline for large language models includes
pretraining, finetuning and aligning phases, with their respective resulting
models, such as the pretrained model and the finetuned model. Finetuned and
aligned models show improved abilities of instruction following and safe
generation, however their abilities to stay factual about the world are
impacted by the finetuning process. Furthermore, the common practice of using
sampling during generation also increases chances of hallucination. In this
work, we introduce a collaborative decoding framework to harness the high
factuality within pretrained models through the concept of critical tokens. We
first design a critical token classifier to decide which model to use for the
next token, and subsequently generates the next token using different decoding
strategies. Experiments with different models and datasets show that our
decoding framework is able to reduce model hallucination significantly,
showcasing the importance of the collaborative decoding framework.Comment: work in progres
Daidzin decreases blood glucose and lipid in streptozotocin-induced diabetic mice
Purpose: To investigate the ameliorative effect of daidzin (DZ) on diabetes in streptozotocin (STZ)- induced diabetic Institute of Cancer Research (ICR) mice, with a view to determining its usefulness in the treatment of diabetes.Methods: The effect of DZ (100, 200 and 400 mg/kg) on blood glucose was investigated in both normal and STZ-induced diabetic mice with glibenclamide (3 mg/kg) and metformin (400 mg/kg) as positive control, respectively. Serum or hepatic levels of lipid, proinflammatory factors, malondialdehyde (MDA) and superoxide dismutase (SOD) were measured. Glucosidase activity assay and glucose uptake by C2C12 myotubes were performed in vitro and the expression of glucose transporter 4 (GLUT4) in C2C12 cells was determined by western blot.Results: DZ (200 and 400 mg/kg) did not decrease fasting blood glucose in normal mice but inhibited starch-induced postprandial glycemia. Oral administration of 400 mg/kg of DZ for 14 days significantly decreased mouse blood glucose (p < 0.01), as well as serum total cholesterol (TC, p < 0.01), triglycerides (TG, p < 0.01), low-density lipoprotein cholesterol (LDL-c, p < 0.01) levels in STZ-induced hyperglycemic mice and improved oral glucose tolerance. The serum and hepatic activity of SOD was enhanced (p < 0.01 and p < 0.001, respectively) while MDA level decreased (p < 0.001). Blood concentrations of interleukin-6 (IL-6, p < 0.001), tumor necrosis factor Ī± (TNF-Ī±, p < 0.01), monocyte chemotactic protein 1 (MCP-1, p < 0.01) were also significantly reduced. In vitro glucosidase activity results showed that DZ inhibited Ī±-glucosidase with IC50 values of 82, 98 and 389 Ī¼g/mL for Ī±- glucosidase from S. cerevisiae, Rhizopus sp. and rat intestines, respectively. It also stimulated glucose uptake and GLUT4 membrane translocation in C2C12 myotubes at 20 Ī¼M (p < 0.05).Conclusion: Oral administration of DZ is effective in alleviating diabetic hyperglycemia, dyslipidemia and inflammation. Inhibition of Ī±-glucosidase and stimulation of glucose consumption by muscles may account for its inhibitory effect on blood glucose.Keywords: Daidzin, Diabetes, Inflammation, Superoxide dismutase (SOD), Malondialdehyde (MDA), Glucosidase, C2C12 myotubes, Glucose transporte
Acetylation-defective mutant of PparĪ³ is associated with decreased lipid synthesis in breast cancer cells.
In our prior publications we characterized a conserved acetylation motif (K(R)xxKK) of evolutionarily related nuclear receptors. Recent reports showed that peroxisome proliferator activated receptor gamma (PPARĪ³) deacetylation by SIRT1 is involved in delaying cellular senescence and maintaining the brown remodeling of white adipose tissue. However, it still remains unknown whether lysyl residues 154 and 155 (K154/155) of the conserved acetylation motif (RIHKK) in PparĪ³1 are acetylated. Herein, we demonstrate that PparĪ³1 is acetylated and regulated by both endogenous TSA-sensitive and NAD-dependent deacetylases. Acetylation of lysine 154 was identified by mass spectrometry (MS) while deacetylation of lysine 155 by SIRT1 was confirmed by in vitro deacetylation assay. An in vivo labeling assay revealed K154/K155 as bona fide acetylation sites. The conserved acetylation sites of PparĪ³1 and the catalytic domain of SIRT1 are both required for the interaction between PparĪ³1 and SIRT1. Sirt1 and PparĪ³1 converge to govern lipid metabolism in vivo. Acetylation-defective mutants of PparĪ³1 were associated with reduced lipid synthesis in ErbB2 overexpressing breast cancer cells. Together, these results suggest that the conserved lysyl residues K154/K155 of PparĪ³1 are acetylated and play an important role in lipid synthesis in ErbB2-positive breast cancer cells
Toward more accurate variant calling for āpersonal genomesā
To date, researchers and clinicians use widely different methods for detecting and reporting human genetic variation. As the size of academic and private databases grow and as the use of the existing genomic techniques expand, researchers and clinicians stand to greatly benefit from the standardization of data generating approaches and analysis methodologies. To successfully implement genomic analyses in the clinic, it will be critically important to optimize the existing pipelines for attaining a higher sensitivity and specificity for more accurate and consistent variant calling
Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing
BACKGROUND: To facilitate the clinical implementation of genomic medicine by next-generation sequencing, it will be critically important to obtain accurate and consistent variant calls on personal genomes. Multiple software tools for variant calling are available, but it is unclear how comparable these tools are or what their relative merits in real-world scenarios might be. METHODS: We sequenced 15 exomes from four families using commercial kits (Illumina HiSeq 2000 platform and Agilent SureSelect version 2 capture kit), with approximately 120X mean coverage. We analyzed the raw data using near-default parameters with five different alignment and variant-calling pipelines (SOAP, BWA-GATK, BWA-SNVer, GNUMAP, and BWA-SAMtools). We additionally sequenced a single whole genome using the sequencing and analysis pipeline from Complete Genomics (CG), with 95% of the exome region being covered by 20 or more reads per base. Finally, we validated 919 single-nucleotide variations (SNVs) and 841 insertions and deletions (indels), including similar fractions of GATK-only, SOAP-only, and shared calls, on the MiSeq platform by amplicon sequencing with approximately 5000X mean coverage. RESULTS: SNV concordance between five Illumina pipelines across all 15 exomes was 57.4%, while 0.5 to 5.1% of variants were called as unique to each pipeline. Indel concordance was only 26.8% between three indel-calling pipelines, even after left-normalizing and intervalizing genomic coordinates by 20 base pairs. There were 11% of CG variants falling within targeted regions in exome sequencing that were not called by any of the Illumina-based exome analysis pipelines. Based on targeted amplicon sequencing on the MiSeq platform, 97.1%, 60.2%, and 99.1% of the GATK-only, SOAP-only and shared SNVs could be validated, but only 54.0%, 44.6%, and 78.1% of the GATK-only, SOAP-only and shared indels could be validated. Additionally, our analysis of two families (one with four individuals and the other with seven), demonstrated additional accuracy gained in variant discovery by having access to genetic data from a multi-generational family. CONCLUSIONS: Our results suggest that more caution should be exercised in genomic medicine settings when analyzing individual genomes, including interpreting positive and negative findings with scrutiny, especially for indels. We advocate for renewed collection and sequencing of multi-generational families to increase the overall accuracy of whole genomes
- ā¦