Combine and conquer: representation learning from multmodal data

Supervised learning, which involves training a model using a labelled dataset, is becoming less popular due to its high cost and various issues with generalization and robustness. This is unsurprising, as data such as images and language are complex and cannot be accurately represented by a single label. When models are trained using this method, they often learn features that spuriously correlate with the label, resulting in poor performance when deployed in the real world. This thesis explores representation learning using multiple sources of data, such as images and language or photos and sketches. We demonstrate through both generative and discriminative models that extracting common abstract concepts between multiple modalities or domains can lead to more accurate and generalisable representations. In addition, we investigate ways to improve the data efficiency of these models, including using fewer multimodal pairs through contrastivestyle objectives and generating multimodal pairs through masked image modeling. Finally, we systematically evaluate the robustness of different learning objectives on distribution shift tasks in order to understand their usefulness in the real world

Shared immunotherapeutic approaches in HIV and hepatitis B virus: combine and conquer

Purpose of review: The aim of this study was to identify similarities, differences and lessons to be shared from recent progress in HIV and hepatitis B virus (HBV) immunotherapeutic approaches. Recent findings: Immune dysregulation is a hallmark of both HIV and HBV infection, which have shared routes of transmission, with approximately 10% of HIV-positive patients worldwide being coinfected with HBV. Immune modulation therapies to orchestrate effective innate and adaptive immune responses are currently being sought as potential strategies towards a functional cure in both HIV and HBV infection. These are based on activating immunological mechanisms that would allow durable control by triggering innate immunity, reviving exhausted endogenous responses and/or generating new immune responses. Recent technological advances and increased appreciation of humoral responses in the control of HIV have generated renewed enthusiasm in the cure field. Summary: For both HIV and HBV infection, a primary consideration with immunomodulatory therapies continues to be a balance between generating highly effective immune responses and mitigating any significant toxicity. A large arsenal of new approaches and ongoing research offer the opportunity to define the pathways that underpin chronic infection and move closer to a functional cure

Combine and conquer: challenges for targeted therapy combinations in early phase trials.

Our increasing understanding of cancer biology has led to the development of molecularly targeted anticancer drugs. The full potential of these agents has not, however, been realised, owing to the presence of de novo (intrinsic) resistance, often resulting from compensatory signalling pathways, or the development of acquired resistance in cancer cells via clonal evolution under the selective pressures of treatment. Combinations of targeted treatments can circumvent some mechanisms of resistance to yield a clinical benefit. We explore the challenges in identifying the best drug combinations and the best combination strategies, as well as the complexities of delivering these treatments to patients. Recognizing treatment-induced toxicity and the inability to use continuous pharmacodynamically effective doses of many targeted treatments necessitates creative intermittent scheduling. Serial tumour profiling and the use of parallel co-clinical trials can contribute to understanding mechanisms of resistance, and will guide the development of adaptive clinical trial designs that can accommodate hypothesis testing, in order to realize the full potential of combination therapies

What information could the main actors of liquid biopsy provide? A representative case of non-small cell lung cancer (NSCLC)

In non-small cell lung cancer (NSCLC), there is a consensus regarding the use of liquid biopsy, generally, to detect "druggable" mutations and, in particular, to monitor tyrosine kinase inhibitor (TKI) treatments. However, whether circulating tumor cells (CTCs) are better tools than cell-free DNA (cfDNA), is still a matter of debate, mainly concerning which antigen(s) we should use to investigating simultaneously both epithelial and epithelial-to-mesenchymal transient (EMT) phenotype in the same sample of CTCs. To address this item, we exploited here a single-tube liquid biopsy, to detect both epithelial cell adhesion molecule (EpCAM)-positive CTCs and EpCAM-low/negative CTCs, because down-modulation of EpCAM is considered the first step in EMT. Furthermore, we analyzed the DNA from CTCs of four different phenotypes (ctcDNA), according to their EpCAM expression and cytokeratin pattern, and circulating tumor DNA (ctDNA) by droplet digital PCR (ddPCR), in order to disclose activating and resistancedriving mutations. Liquid biopsy reflected spatial and temporal heterogeneity of the tumor under treatment pressure. We provide the proof-of-concept that the complementary use of ctDNA and ctcDNA represents a reliable, minimally invasive and dynamic tool for a more comprehensive view of tumor evolution

Divide and Conquer

The maxim “divide and conquer” (divide et impera) is invoked frequently in law, history, and politics, but often in a loose or undertheorized way. We suggest that the maxim is a placeholder for a complex of ideas related by a family resemblance, but differing in their details, mechanisms and implications. We provide an analytic taxonomy of divide and conquer mechanisms in the settings of a Stag Hunt Game and an indefinitely-repeated Prisoners' Dilemma. A number of applications are considered, including labor law, bankruptcy, constitutional design and the separation of powers, imperialism and race relations, international law, litigation and settlement, and antitrust law. Conditions under which divide and conquer strategies reduce or enhance social welfare, and techniques that policy makers can use to combat divide and conquer tactics, are also discussed

Use of (Q)SAR genotoxicity predictions and fuzzy multicriteria decision-making for priority ranking of ethoxyquin transformation products

Ethoxyquin (EQ; 6-ethoxy-2,2,4-trimethyl-1,2-dihydroquinoline) has been used as an antioxidant in feed for pets and food-producing animals, including farmed fish such as Atlantic salmon. In Europe, the authorization for use of EQ as a feed additive was suspended, due to knowledge gaps concerning the presence and toxicity of EQ transformation products (TPs). Recent analytical studies focusing on the detection of EQ TPs in farmed Atlantic salmon feed and fillets reported the detection of a total of 27 EQ TPs, comprising both known and previously not described EQ TPs. We devised and applied an in silico workflow to rank these EQ TPs according to their genotoxic potential and their occurrence data in Atlantic salmon feed and fillet. Ames genotoxicity predictions were obtained applying a suite of five (quantitative) structure–activity relationship ((Q)SAR) tools, namely VEGA, TEST, LAZAR, Derek Nexus and Sarah Nexus. (Q)SAR Ames genotoxicity predictions were aggregated using fuzzy analytic hierarchy process (fAHP) multicriteria decision-making (MCDM). A priority ranking of EQ TPs was performed based on combining both fAHP ranked (Q)SAR predictions and analytical occurrence data. The applied workflow prioritized four newly identified EQ TPs for further investigation of genotoxicity. The fAHP-based prioritization strategy described here, can easily be applied to other toxicity endpoints and groups of chemicals for priority ranking of compounds of most concern for subsequent experimental and mechanistic toxicology analyses.publishedVersio

Short- and long-term evolution in our arms race with cancer: Why the war on cancer is winnable.

Human society is engaged in an arms race against cancer, which pits one evolutionary process-human cultural evolution as we develop novel cancer therapies-against another evolutionary process-the ability of oncogenic selection operating among cancer cells to select for lineages that are resistant to our therapies. Cancer cells have a powerful ability to evolve resistance over the short term, leading to patient relapse following an initial period of apparent treatment efficacy. However, we are the beneficiaries of a fundamental asymmetry in our arms race against cancer: Whereas our cultural evolution is a long-term and continuous process, resistance evolution in cancer cells operates only over the short term and is discontinuous - all resistance adaptations are lost each time a cancer patient dies. Thus, our cultural adaptations are permanent, whereas cancer's genetic adaptations are ephemeral. Consequently, over the long term, there is good reason to expect that we will emerge as the winners in our war against cancer

Earnings Prediction with Deep Leaning

In the financial sector, a reliable forecast the future financial performance of a company is of great importance for investors' investment decisions. In this paper we compare long-term short-term memory (LSTM) networks to temporal convolution network (TCNs) in the prediction of future earnings per share (EPS). The experimental analysis is based on quarterly financial reporting data and daily stock market returns. For a broad sample of US firms, we find that both LSTMs outperform the naive persistent model with up to 30.0% more accurate predictions, while TCNs achieve and an improvement of 30.8%. Both types of networks are at least as accurate as analysts and exceed them by up to 12.2% (LSTM) and 13.2% (TCN).Comment: 7 pages, 4 figures, 2 tables, submitted to KI202