VARIATIONS IN MICROARRAY BASED GENE EXPRESSION PROFILING: IDENTIFYING SOURCES AND IMPROVING RESULTS

Two major issues hinder the application of microarray based gene expression profiling in clinical laboratories as a diagnostic or prognostic tool. The first issue is the sheer volume and high-dimensionality of gene expression data from microarray experiments, which require advanced algorithms to extract meaningful gene expression patterns that correlate with biological impact. The second issue is the substantial amount of variation in microarray gene expression data, which impairs the performance of analysis method and makes sharing or integrating microarray data very difficult. Variations can be introduced by all possible sources including the DNA microarray technology itself and the experimental procedures. Many of these variations have not been characterized, measured, or linked to the sources. In the first part of this dissertation, a decision tree learning method was demonstrated to perform as well as more popularly accepted classification methods in partitioning cancer samples with microarray data. More importantly, results demonstrate that variation introduced into microarray data by tissue sampling and tissue handling compromised the performance of classification methods. In the second part of this dissertation, variations introduced by the T7 based in vitro transcription labeling methods were investigated in detail. Results demonstrated that individual amplification methods significantly biased gene expression data even though the methods compared in this study were all derivatives of the T7 RNA polymerase based in vitro transcription labeling approach. Variations observed can be partially explained by the number of biotinylated nucleotides used for labeling and the incubation time of the in vitro transcription experiments. These variations can generate discordant gene expression results even using the same RNA samples and cannot be corrected by post experiment analysis including advanced normalization techniques. Studies in this dissertation stress the concept that experimental and analytical methods must work together. This dissertation also emphasizes the importance of standardizing the DNA microarray technology and experimental procedures in order to optimize gene expression analysis and create quality standards compatible with the clinical application of this technology. These findings should be taken into account especially when comparing data from different platforms, and in standardizing protocols for clinical applications in pathology

Structures and Anomalies of Water

Introduction of the principles of the asymmetrical, short-range O:H-O coupled oscillater pair and the basic rule for water ice, which reconciles the structure and anomalies of water ice.Comment: 20 pages. In Chines

Calibrating Multimodal Learning

Multimodal machine learning has achieved remarkable progress in a wide range of scenarios. However, the reliability of multimodal learning remains largely unexplored. In this paper, through extensive empirical studies, we identify current multimodal classification methods suffer from unreliable predictive confidence that tend to rely on partial modalities when estimating confidence. Specifically, we find that the confidence estimated by current models could even increase when some modalities are corrupted. To address the issue, we introduce an intuitive principle for multimodal learning, i.e., the confidence should not increase when one modality is removed. Accordingly, we propose a novel regularization technique, i.e., Calibrating Multimodal Learning (CML) regularization, to calibrate the predictive confidence of previous methods. This technique could be flexibly equipped by existing models and improve the performance in terms of confidence calibration, classification accuracy, and model robustness

Deep sequencing discovery of novel and conserved microRNAs in trifoliate orange (Citrus trifoliata)

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play a critical role in post-transcriptional gene regulation and have been shown to control many genes involved in various biological and metabolic processes. There have been extensive studies to discover miRNAs and analyze their functions in model plant species, such as <it>Arabidopsis </it>and rice. Deep sequencing technologies have facilitated identification of species-specific or lowly expressed as well as conserved or highly expressed miRNAs in plants.</p> <p>Results</p> <p>In this research, we used Solexa sequencing to discover new microRNAs in trifoliate orange (<it>Citrus trifoliata</it>) which is an important rootstock of citrus. A total of 13,106,753 reads representing 4,876,395 distinct sequences were obtained from a short RNA library generated from small RNA extracted from <it>C. trifoliata </it>flower and fruit tissues. Based on sequence similarity and hairpin structure prediction, we found that 156,639 reads representing 63 sequences from 42 highly conserved miRNA families, have perfect matches to known miRNAs. We also identified 10 novel miRNA candidates whose precursors were all potentially generated from citrus ESTs. In addition, five miRNA* sequences were also sequenced. These sequences had not been earlier described in other plant species and accumulation of the 10 novel miRNAs were confirmed by qRT-PCR analysis. Potential target genes were predicted for most conserved and novel miRNAs. Moreover, four target genes including one encoding IRX12 copper ion binding/oxidoreductase and three genes encoding NB-LRR disease resistance protein have been experimentally verified by detection of the miRNA-mediated mRNA cleavage in <it>C. trifoliata</it>.</p> <p>Conclusion</p> <p>Deep sequencing of short RNAs from <it>C. trifoliata </it>flowers and fruits identified 10 new potential miRNAs and 42 highly conserved miRNA families, indicating that specific miRNAs exist in <it>C. trifoliata</it>. These results show that regulatory miRNAs exist in agronomically important trifoliate orange and may play an important role in citrus growth, development, and response to disease.</p

Fairness-guided Few-shot Prompting for Large Language Models

Large language models have demonstrated surprising ability to perform in-context learning, i.e., these models can be directly applied to solve numerous downstream tasks by conditioning on a prompt constructed by a few input-output examples. However, prior research has shown that in-context learning can suffer from high instability due to variations in training examples, example order, and prompt formats. Therefore, the construction of an appropriate prompt is essential for improving the performance of in-context learning. In this paper, we revisit this problem from the view of predictive bias. Specifically, we introduce a metric to evaluate the predictive bias of a fixed prompt against labels or a given attributes. Then we empirically show that prompts with higher bias always lead to unsatisfactory predictive quality. Based on this observation, we propose a novel search strategy based on the greedy search to identify the near-optimal prompt for improving the performance of in-context learning. We perform comprehensive experiments with state-of-the-art mainstream models such as GPT-3 on various downstream tasks. Our results indicate that our method can enhance the model's in-context learning performance in an effective and interpretable manner

Effects of parenteral nutrition of ω-3 polyunsaturated fatty acid, arginine and glutamine on cellular immune status of patients following liver cancer surgery

Purpose: To study the effects of parenteral nutrition (TPN), ω-3  polyunsaturated fatty acid (PUFA), Larginine (Arg), and glutamine on cellular immunity of patients who have done the liver cancer (LC) surgery.Methods: Seventy-five (75) LC patients were randomly divided into 5  groups (A - E; 15 cases each), group A, B, C, D and E, in which patients were treated with TPN, TPN + fish oil, TPN + Arg, TPN + glutamine, and TPN + ω-3 PUFA + Arg + glutamine, respectively. Before and after surgery, CD3 +, CD4 + and CD8 + were measured by antibody-sensitized erythrocyte rosette test, and IL-6, IL-10 and TNF-a were assayed with double-antibody sandwich enzyme-linked immunoassay (DAS-ELISA). IgA and IgM were measured nephelometrically.Results: The levels of CD3 +, CD4 + and CD8 + in group A showed no  obvious change after surgery (p &gt; 0.05). However, CD3 + and CD4 +  increased in groups B, C and D, while CD8 + decreased in group E (p &lt; 0.05). IL-6 in group E was lower than that in any of the other four groups (p &lt; 0.05). IL-10 in group A was lower than that in groups B, C and D, but lower than in group E (p &lt; 0.05). The levels of TNF-a in groups B and C were lower than those in group A, but higher than that in group E (p &lt; 0.05) but lower than in group D. IgA in group E was higher than in the other groups (p &lt; 0.05), while IgM level in group E was lower than in groups A, B and C (p &lt; 0.05).Conclusion: Immunosuppressive status and cellular immunity of patients  after liver cancer surgery may be improved by a combination therapy of TPN, ω-3 PUFAs, Arg and glutamine.Keywords: Polyunsaturated fatty acid, Arginine, Glutamine, Parenteral nutrition, Hepatoma, Cellular immunit

Crohn\u27s disease-associated ATG16L1 T300A genotype is associated with improved survival in gastric cancer

BACKGROUND: A non-synonymous single nucleotide polymorphism of the ATG16L1 gene, T300A, is a major Crohn\u27s disease (CD) susceptibility allele, and is known to be associated with increased apoptosis induction in the small intestinal crypt base in CD subjects and mouse models. We hypothesized that ATG16L1 T300A genotype also correlates with increased tumor apoptosis and therefore could lead to superior clinical outcome in cancer subjects. METHODS: T300A genotyping by Taqman assay was performed for gastric carcinoma subjects who underwent resection from two academic medical centers. Transcriptomic analysis was performed by RNA-seq on formalin-fixed paraffin-embedded cancerous tissue. Tumor apoptosis and autophagy were determined by cleaved caspase-3 and p62 immunohistochemistry, respectively. The subjects\u27 genotypes were correlated with demographics, various histopathologic features, transcriptome, and clinical outcome. FINDINGS: Of the 220 genotyped subjects, 163 (74%) subjects carried the T300A allele(s), including 55 (25%) homozygous and 108 (49%) heterozygous subjects. The T300A/T300A subjects had superior overall survival than the other groups. Their tumors were associated with increased CD-like lymphoid aggregates and increased tumor apoptosis without concurrent increase in tumor mitosis or defective autophagy. Transcriptomic analysis showed upregulation of WNT/β-catenin signaling and downregulation of PPAR, EGFR, and inflammatory chemokine pathways in tumors of T300A/T300A subjects. INTERPRETATION: Gastric carcinoma of subjects with the T300A/T300A genotype is associated with repressed EGFR and PPAR pathways, increased tumor apoptosis, and improved overall survival. Genotyping gastric cancer subjects may provide additional insight for clinical stratification