Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance

Multi-objective learning (MOL) problems often arise in emerging machine learning problems when there are multiple learning criteria or multiple learning tasks. Recent works have developed various dynamic weighting algorithms for MOL such as MGDA and its variants, where the central idea is to find an update direction that avoids conflicts among objectives. Albeit its appealing intuition, empirical studies show that dynamic weighting methods may not always outperform static ones. To understand this theory-practical gap, we focus on a new stochastic variant of MGDA - the Multi-objective gradient with Double sampling (MoDo) algorithm, and study the generalization performance of the dynamic weighting-based MoDo and its interplay with optimization through the lens of algorithm stability. Perhaps surprisingly, we find that the key rationale behind MGDA -- updating along conflict-avoidant direction - may hinder dynamic weighting algorithms from achieving the optimal ${\cal O}(1/\sqrt{n})$ population risk, where $n$ is the number of training samples. We further demonstrate the variability of dynamic weights on the three-way trade-off among optimization, generalization, and conflict avoidance that is unique in MOL

Employees’ Collaborative Use of Green Information Systems

Green information system (GIS) plays an important role in the sustainable development of organizations, especially for those in emerging economy that face both economic and environmental pressures. To fulfill the purpose, employees need to work together on tasks using all kinds of GIS functions such as online collaboration and remote meeting. Researchers study GIS adoption at either the organizational level or the individual level, but few examine such technology-enabled collaboration as a cross-level phenomenon. Extending the belief-action-outcome (BAO) framework, this study investigates the motivation, effort and performance of collaborative GIS use. In particular, there are two aspects of motivation: GIS strategy as extrinsic motivation and GIS belief as intrinsic motivation, as well as two types of performance: tangible environmental performance and intangible green image. Collective GIS effort mediates the relationships between motivation and performance variables. Empirical evidence based on survey observations collected in China supports most hypothesized relationships. The findings provide helpful insights on the best practices to promote the collaborative use of GIS for corporate sustainability

PDCD6 is an independent predictor of progression free survival in epithelial ovarian cancer

<p>Abstract</p> <p>Background</p> <p>Programmed cell death 6 (PDCD6) beside its known proapoptotic functions may be a player in survival pathways in cancer. The purpose of this study is to further explore the roles of PDCD6 in epithelial ovarian cancer.</p> <p>Methods</p> <p>Lentiviral vector with shRNA for PDCD6 was used to investigate the effects of PDCD6 knockdown on cell growth, cell cycle, apoptosis and motility in ovarian cancer cells. Two hundred twelve epithelial ovarian cancer tissues were analyzed for mRNA expression of <it>PDCD6 </it>using RT-PCR. Associations of its expression with clinical pathological factors, progression free and overall survival were evaluated.</p> <p>Results</p> <p>PDCD6 is highly expressed in metastatic ovarian cancer cells and positively regulates cell migration and invasion. Significantly, the level of <it>PDCD6 </it>expression in epithelial ovarian cancer correlates with clinical progression. Patients with medium or high levels of <it>PDCD6 </it>mRNA were at higher risk for disease progression, compared to those with low levels (HR, 1.29; <it>P </it>= 0.024 for medium levels; and HR, 1.57; <it>P </it>= 0.045 for high levels) after adjusting for age, disease stage, tumor grade, histologic type and residual tumor size. Kaplan-Meier survival analysis demonstrated similar results. However, no association was found between <it>PDCD6 </it>expression and overall survival.</p> <p>Conclusions</p> <p>PDCD6 seems to play an important role in ovarian cancer progression and it may be an independent predictor of progression free survival in epithelial ovarian cancer. Further studies are needed to more completely elucidate the molecular mechanisms of PDCD6 involve in ovarian cancer progression.</p

Activation of MET signaling by HDAC6 offers a rationale for a novel ricolinostat and crizotinib combinatorial therapeutic strategy in diffuse large B‐cell lymphoma

Some histone deacetylases (HDACs) promote tumor cell growth and pan‐ or selective HDAC inhibitors are active in some cancers; however, the pivotal HDAC enzyme and its functions in human diffuse large B‐cell lymphoma (DLBCL) remain largely unknown. Using NanoString nCounter assays, we profiled HDAC mRNA expression and identified HDAC6 as an upregulated HDAC family member in DLBCL tissue samples. We then found that HDAC6 plays an oncogenic role in DLBCL, as evidenced by its promotion of cell proliferation in vitro and tumor xenograft growth in vivo. Mechanistically, the interaction between HDAC6 and HR23B downregulated HR23B expression, thereby reducing the levels of casitas B‐lineage lymphoma (c‐Cbl), an E3 ubiquitin ligase for hepatocyte growth factor receptor (MET), which resulted in the inhibition of MET ubiquitination‐dependent degradation. In addition, enhanced HDAC6 expression and decreased HR23B expression were correlated with poor overall survival rates among patients with DLBCL. Taken together, these results establish an HDAC6–HR23B–MET axis and indicate that HDAC6 is a potent promoter of lymphomagenesis in DLBCL. Thus, a therapeutic strategy based on HDAC6 inhibitors in combination with MET inhibitors is promising. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146400/1/path5108_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146400/2/path5108.pd

Oncogenic state and cell identity combinatorially dictate the susceptibility of cells within glioma development hierarchy to IGF1R targeting

Glioblastoma is the most malignant cancer in the brain and currently incurable. It is urgent to identify effective targets for this lethal disease. Inhibition of such targets should suppress the growth of cancer cells and, ideally also precancerous cells for early prevention, but minimally affect their normal counterparts. Using genetic mouse models with neural stem cells (NSCs) or oligodendrocyte precursor cells (OPCs) as the cells‐of‐origin/mutation, it is shown that the susceptibility of cells within the development hierarchy of glioma to the knockout of insulin‐like growth factor I receptor (IGF1R) is determined not only by their oncogenic states, but also by their cell identities/states. Knockout of IGF1R selectively disrupts the growth of mutant and transformed, but not normal OPCs, or NSCs. The desirable outcome of IGF1R knockout on cell growth requires the mutant cells to commit to the OPC identity regardless of its development hierarchical status. At the molecular level, oncogenic mutations reprogram the cellular network of OPCs and force them to depend more on IGF1R for their growth. A new‐generation brain‐penetrable, orally available IGF1R inhibitor harnessing tumor OPCs in the brain is also developed. The findings reveal the cellular window of IGF1R targeting and establish IGF1R as an effective target for the prevention and treatment of glioblastoma

Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas

The evolution of DNA methylome and methylation intra-tumor heterogeneity (ITH) during early carcinogenesis of lung adenocarcinoma has not been systematically studied. We perform reduced representation bisulfite sequencing of invasive lung adenocarcinoma and its precursors, atypical adenomatous hyperplasia, adenocarcinoma in situ and minimally invasive adenocarcinoma. We observe gradual increase of methylation aberrations and significantly higher level of methylation ITH in later-stage lesions. The phylogenetic patterns inferred from methylation aberrations resemble those based on somatic mutations suggesting parallel methylation and genetic evolution. De-convolution reveal higher ratio of T regulatory cells (Tregs) versus CD8 + T cells in later-stage diseases, implying progressive immunosuppression with neoplastic progression. Furthermore, increased global hypomethylation is associated with higher mutation burden, copy number variation burden and AI burden as well as higher Treg/CD8 ratio, highlighting the potential impact of methylation on chromosomal instability, mutagenesis and tumor immune microenvironment during early carcinogenesis of lung adenocarcinomas

Consideration of influences of soil parameters on compaction behavior with soil/water/air coupled F. E. code

Background: The essential amino acid methionine can be used for protein synthesis but also serves as a precursor for homocysteine and cysteine. Objective: The objective of this study was to determine the minimal obligatory methionine requirement of infants in the presence of excess cysteine (91 mg · k

Immune evolution from preneoplasia to invasive lung adenocarcinomas and underlying molecular features

The mechanism by which anti-cancer immunity shapes early carcinogenesis of lung adenocarcinoma (ADC) is unknown. In this study, we characterize the immune contexture of invasive lung ADC and its precursors by transcriptomic immune profiling, T cell receptor (TCR) sequencing and multiplex immunofluorescence (mIF). Our results demonstrate that anti-tumor immunity evolved as a continuum from lung preneoplasia, to preinvasive ADC, minimally-invasive ADC and frankly invasive lung ADC with a gradually less effective and more intensively regulated immune response including down-regulation of immune-activation pathways, up-regulation of immunosuppressive pathways, lower infiltration of cytotoxic T cells (CTLs) and anti-tumor helper T cells (Th), higher infiltration of regulatory T cells (Tregs), decreased T cell clonality, and lower frequencies of top T cell clones in later-stages. Driver mutations, chromosomal copy number aberrations (CNAs) and aberrant DNA methylation may collectively impinge host immune responses and facilitate immune evasion, promoting the outgrowth of fit subclones in preneoplasia into dominant clones in invasive ADC