A genome-wide regulatory network identifies key transcription factors for memory CD8+ T-cell development

Memory CD8[superscript +] T-cell development is defined by the expression of a specific set of memory signature genes. Despite recent progress, many components of the transcriptional control of memory CD8[superscript +] T-cell development are still unknown. To identify transcription factors and their interactions in memory CD8[superscript +] T-cell development, we construct a genome-wide regulatory network and apply it to identify key transcription factors that regulate memory signature genes. Most of the known transcription factors having a role in memory CD8[superscript +] T-cell development are rediscovered and about a dozen new ones are also identified. Sox4, Bhlhe40, Bach2 and Runx2 are experimentally verified, and Bach2 is further shown to promote both development and recall proliferation of memory CD8[superscript +] T cells through Prdm1 and Id3. Gene perturbation study identifies the interactions between the transcription factors, with Sox4 positioned as a hub. The identified transcription factors and insights into their interactions should facilitate further dissection of molecular mechanisms underlying memory CD8[superscript +] T-cell development.Singapore-MIT AllianceNational Institutes of Health (U.S.) (Grant AI69208)National Cancer Institute (U.S.) (Koch Institute Support (core) Grant P30-CA14051

Localization of just noticeable difference for image compression

The just noticeable difference (JND) is the minimal difference between stimuli that can be detected by a person. The picture-wise just noticeable difference (PJND) for a given reference image and a compression algorithm represents the minimal level of compression that causes noticeable differences in the reconstruction. These differences can only be observed in some specific regions within the image, dubbed as JND-critical regions. Identifying these regions can improve the development of image compression algorithms. Due to the fact that visual perception varies among individuals, determining the PJND values and JND-critical regions for a target population of consumers requires subjective assessment experiments involving a sufficiently large number of observers. In this paper, we propose a novel framework for conducting such experiments using crowdsourcing. By applying this framework, we created a novel PJND dataset, KonJND++, consisting of 300 source images, compressed versions thereof under JPEG or BPG compression, and an average of 43 ratings of PJND and 129 self-reported locations of JND-critical regions for each source image. Our experiments demonstrate the effectiveness and reliability of our proposed framework, which is easy to be adapted for collecting a large-scale dataset. The source code and dataset are available at https://github.com/angchen-dev/LocJND.</p

Localization of Just Noticeable Difference for Image Compression

The just noticeable difference (JND) is the minimal difference between stimuli that can be detected by a person. The picture-wise just noticeable difference (PJND) for a given reference image and a compression algorithm represents the minimal level of compression that causes noticeable differences in the reconstruction. These differences can only be observed in some specific regions within the image, dubbed as JND-critical regions. Identifying these regions can improve the development of image compression algorithms. Due to the fact that visual perception varies among individuals, determining the PJND values and JND-critical regions for a target population of consumers requires subjective assessment experiments involving a sufficiently large number of observers. In this paper, we propose a novel framework for conducting such experiments using crowdsourcing. By applying this framework, we created a novel PJND dataset, KonJND++, consisting of 300 source images, compressed versions thereof under JPEG or BPG compression, and an average of 43 ratings of PJND and 129 self-reported locations of JND-critical regions for each source image. Our experiments demonstrate the effectiveness and reliability of our proposed framework, which is easy to be adapted for collecting a large-scale dataset. The source code and dataset are available at https://github.com/angchen-dev/LocJND

DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM

SLAM systems based on NeRF have demonstrated superior performance in rendering quality and scene reconstruction for static environments compared to traditional dense SLAM. However, they encounter tracking drift and mapping errors in real-world scenarios with dynamic interferences. To address these issues, we introduce DDN-SLAM, the first real-time dense dynamic neural implicit SLAM system integrating semantic features. To address dynamic tracking interferences, we propose a feature point segmentation method that combines semantic features with a mixed Gaussian distribution model. To avoid incorrect background removal, we propose a mapping strategy based on sparse point cloud sampling and background restoration. We propose a dynamic semantic loss to eliminate dynamic occlusions. Experimental results demonstrate that DDN-SLAM is capable of robustly tracking and producing high-quality reconstructions in dynamic environments, while appropriately preserving potential dynamic objects. Compared to existing neural implicit SLAM systems, the tracking results on dynamic datasets indicate an average 90% improvement in Average Trajectory Error (ATE) accuracy.Comment: 11pages, 4figure

Defining species specific genome differences in malaria parasites

<p>Abstract</p> <p>Background</p> <p>In recent years a number of genome sequences for different <it>plasmodium </it>species have become available. This has allowed the identification of numerous conserved genes across the different species and has significantly enhanced our understanding of parasite biology. In contrast little is known about species specific differences between the different genomes partly due to the lower sequence coverage and therefore relatively poor annotation of some of the draft genomes particularly the rodent malarias parasite species.</p> <p>Results</p> <p>To improve the current annotation and gene identification status of the draft genomes of <it>P. berghei</it>, <it>P. chabaudi </it>and <it>P. yoelii</it>, we performed genome-wide comparisons between these three species. Through analyses via comparative genome hybridizations using a newly designed pan-rodent array as well as in depth bioinformatics analysis, we were able to improve on the coverage of the draft rodent parasite genomes by detecting orthologous genes between these related rodent parasite species. More than 1,000 orthologs for <it>P. yoelii </it>were now newly associated with a <it>P. falciparum </it>gene. In addition to extending the current core gene set for all plasmodium species this analysis also for the first time identifies a relatively small number of genes that are unique to the primate malaria parasites while a larger gene set is uniquely conserved amongst the rodent malaria parasites.</p> <p>Conclusions</p> <p>These findings allow a more thorough investigation of the genes that are important for host specificity in malaria.</p

Selection of long oligonucleotides for gene expression microarrays using weighted rank-sum strategy

<p>Abstract</p> <p>Background</p> <p>The design of long oligonucleotides for spotted DNA microarrays requires detailed attention to ensure their optimal performance in the hybridization process. The main challenge is to select an optimal oligonucleotide element that represents each genetic locus/gene in the genome and is unique, devoid of internal structures and repetitive sequences and its Tm is uniform with all other elements on the microarray. Currently, all of the publicly available programs for DNA long oligonucleotide microarray selection utilize various combinations of cutoffs in which each parameter (uniqueness, Tm, and secondary structure) is evaluated and filtered individually. The use of the cutoffs can, however, lead to information loss and to selection of suboptimal oligonucleotides, especially for genomes with extreme distribution of the GC content, a large proportion of repetitive sequences or the presence of large gene families with highly homologous members.</p> <p>Results</p> <p>Here we present the program OligoRankPick which is using a weighted rank-based strategy to select microarray oligonucleotide elements via an integer weighted linear function. This approach optimizes the selection criteria (weight score) for each gene individually, accommodating variable properties of the DNA sequence along the genome. The designed algorithm was tested using three microbial genomes <it>Escherichia coli</it>, <it>Saccharomyces cerevisiae </it>and the human malaria parasite species <it>Plasmodium falciparum</it>. In comparison to other published algorithms OligoRankPick provides significant improvements in oligonucleotide design for all three genomes with the most significant improvements observed in the microarray design for <it>P. falciparum </it>whose genome is characterized by large fluctuations of GC content, and abundant gene duplications.</p> <p>Conclusion</p> <p>OligoRankPick is an efficient tool for the design of long oligonucleotide DNA microarrays which does not rely on direct oligonucleotide exclusion by parameter cutoffs but instead optimizes all parameters in context of each other. The weighted rank-sum strategy utilized by this algorithm provides high flexibility of oligonucleotide selection which accommodates extreme variability of DNA sequence properties along genomes of many organisms.</p

Phase I study of azacitidine and oxaliplatin in patients with advanced cancers that have relapsed or are refractory to any platinum therapy.

BackgroundDemethylation process is necessary for the expression of various factors involved in chemotherapy cytotoxicity or resistance. Platinum-resistant cells may have reduced expression of the copper/platinum transporter CTR1. We hypothesized that azacitidine and oxaliplatin combination therapy may restore platinum sensitivity. We treated patients with cancer relapsed/refractory to any platinum compounds (3 + 3 study design) with azacitidine (20 to 50 mg/m(2)/day intravenously (IV) over 15 to 30 min, D1 to 5) and oxaliplatin (15 to 30 mg/m(2)/day, IV over 2 h, D2 to 5) (maximum, six cycles). Platinum content, LINE1 methylation (surrogate of global DNA methylation), and CTR1 expression changes (pre- vs. post-treatment) were assessed. Drug pharmacokinetics were analyzed.ResultsThirty-seven patients were treated. No dose-limiting toxicity (DLT) was noted at the maximum dose. The most common adverse events were anemia and fatigue. Two (5.4%) patients had stable disease and completed six cycles of therapy. Oxaliplatin (D2) and azacitidine (D1 and 5) mean systemic exposure based on plasma AUCall showed dose-dependent interaction whereby increasing the dose of oxaliplatin reduced the mean azacitidine exposure and vice versa; however, no significant differences in other non-compartmental modeled parameters were observed. Blood samples showed universal reduction in global DNA methylation. In tumor samples, hypomethylation was only observed in four out of seven patients. No correlation between blood and tumor demethylation was seen. The mean cytoplasmic CTR1 score decreased. The pre-dose tumor oxaliplatin levels ranged from &lt;0.25 to 5.8 μg/g tumor. The platinum concentration increased 3- to 18-fold. No correlation was found between CTR1 score and oxaliplatin level, which was found to have a trend toward correlation with progression-free survival.ConclusionsOxaliplatin and azacitidine combination therapy was safe. CTR1 expression was not correlated with methylation status or tissue platinum concentration

Subjective assessment of global picture-wise just noticeable difference

The picture-wise just noticeable difference (PJND) for a given image and a compression scheme is a statistical quantity giving the smallest distortion that a subject can perceive when the image is compressed with the compression scheme. The PJND is determined with subjective assessment tests for a sample of subjects. We introduce and apply two methods of adjustment where the subject interactively selects the distortion level at the PJND using either a slider or keystrokes. We compare the results and times required to those of the adaptive binary search type approach, in which image pairs with distortions that bracket the PJND are displayed and the difference in distortion levels is reduced until the PJND is identified. For the three methods, two images are compared using the flicker test in which the displayed images alternate at a frequency of 8 Hz. Unlike previous work, our goal is a global one, determining the PJND not only for the original pristine image but also for a sequence of compressed versions. Results for the MCL-JCI dataset show that the PJND measurements based on adjustment are comparable with those of the traditional approach using binary search, yet significantly faster. Moreover, we conducted a crowdsourcing study with side-by-side comparisons and forced choice, which suggests that the flicker test is more sensitive than a side-by-side comparison