Survival prediction, central to the analysis of clinical trials, has the potential to be transformed by the availability of RNA-seq data as it reveals the underlying molecular and genetic mechanisms for disease and outcomes. However, the amount of RNA-seq samples available for understudied or rare diseases is often limited. To address this, leveraging data across different cancer types can be a viable solution, necessitating the application of self-supervised learning techniques. Yet, this wealth of data often comes in a tabular format without a known structure, hindering the development of a generally effective augmentation method for survival prediction.While traditional methods have been constrained by a one cancer-one model philosophy or have relied solely on a single modality, our approach, Guided-STab, on the contrary, offers a comprehensive approach through pretraining on all available RNA-seq data from various cancer types while guiding the representation by incorporating sparse clinical features as auxiliary tasks. With a multitask-guided self-supervised representation learning framework, we maximize the potential of vast unlabeled datasets from various cancer types, leading to genomic-driven survival predictions. These auxiliary clinical tasks then guide the learned representations to enhance critical survival factors. Extensive experiments reinforce the promise of our approach, as Guided-STab consistently outperforms established benchmarks on TCGA dataset.

3566 Background: Clinical biomarker studies are often hindered by the availability of tissue specimens of sufficient quality and quantity. While RNA-Seq is often considered the gold standard for measuring mRNA expression levels in cancer tissue, it typically requires multiple formalin-fixed paraffin-embedded (FFPE) tissue sections to extract a sufficient amount of quality RNA for subsequent gene expression profiling analysis. The HTG EdgeSeq technology is a gene expression profiling platform that combines quantitative nuclease protection assay technology with next-generation sequencing detection. Unlike RNA-Seq, the HTG EdgeSeq technology does not require RNA extraction, and can use small amounts of tissue material, typically several mm2, to generate reproducible gene expression profiles. Methods: This study compares the performance of RNA-Seq and HTG's profiling panel, the HTG EdgeSeq Precision Immuno-Oncology Panel (PIP), which is designed to measure expression levels of 1,392 genes focused on tumor/immune interaction. Approximately 1,200 samples from three tumor indications (gastric cancer, colorectal cancer and ovarian cancer) were tested using both technologies. Results: Up to four FFPE slides were used for RNA extraction to support RNA-Seq testing; out of the 1,202 samples processed, 1,099 generated extracted RNA of sufficient quality and quantity (as measured by RNA concentration, RIN score and %DV200) to proceed to sequencing, which resulted in a pass rate of 91.4% for RNA-Seq. The HTG EdgeSeq PIP panel resulted in a pass rate of 97.3% (samples passing QC metrics) when the same 1,200 samples were tested, and required only a single FFPE section owing to the small sample requirement. The t-SNE (a non-linear dimensionality reduction method) analysis of the common 1,358 genes revealed similar clustering of the three cancer indications between the two methods. Correlations across individual genes by sample resulted in the mean Spearman correlation coefficient of 0.73 (95% confidence interval of 0.61 - 0.80). Additionally, gene-wise comparisons across all samples were also evaluated. Conclusions: These data demonstrate that HTG EdgeSeq gene expression panels can be used as a competitive alternative to RNA-Seq, generating equivalent gene expression results, while offering the added benefits of a small sample size requirement, lack of RNA extraction bias, and fully automated data analysis pipeline.

2593 Background: A multiparameter tumor inflammation assay based on gene expression profiling (TIA-GEP) can extend the utility of IHC to interrogate the tumor microenvironment (TME). Using CD8 expression assessed by IHC (CD8-IHC) as a surrogate for inflammation, statistical modelling was used to develop a specific gene signature on the TIA-GEP panel to predict CD8-IHC. The correlation between TIA-GEP and CD8-IHC and the prevalence of inflammation were explored across multiple tumor types. Methods: Levels of inflammation were measured by CD8-IHC and TIA-GEP on 1778 procured samples across 12 tumor types. Quality control metrics involved sample input quality, technical errors, and inter-run variability. Generalized linear models were used to identify an inflammation score that predicts the CD8-IHC score in melanoma and SCCHN tissue. The predictive accuracy of this signature was also examined in 10 additional tumor types. Results: Assessment of TME inflammation by CD8-IHC was consistent with that observed by TIA-GEP in multiple tumor types. The range of inflammation varied across different tumor types, with relatively lower inflammation range and scores in SCLC, ovarian, and prostate cancers, and higher values in NSCLC, melanoma, SCCHN, and gastric cancers. R2 x 100 values reflecting percent variation in CD8-IHC associated with TIA-GEP ranged from 62.4% to 79.2% ( P < 0.0001) for all tumor types except prostate cancer (32.5%). Low correlation in prostate cancer may be a result of low prevalence of inflammation by CD8-IHC. Estimated linear regression slopes between CD8-IHC and TIA-GEP ranged from 0.74 in SCLC to 1.27 in gastric cancer. Conclusions: The results suggest that the inflammation signature is a robust potential diagnostic tool predicting inflammation in the TME. The inflammation signature not only correlates with CD8-IHC for multiple tumor types, but also leverages the alternative benefits associated with TIA-GEP, which include information related to tumor inflammation-associated biomarkers and flexibility in exploring the value of other genomic signatures.

Quantitative systems pharmacology (QSP) has emerged as an innovative approach in model‐informed drug discovery and development, supporting program decisions from exploratory research through late‐stage clinical trials. In this commentary, we discuss the unique value of disease‐scale “platform” QSP models that are amenable to reuse and repurposing to support diverse clinical decisions in ways distinct from other pharmacometrics strategies.

Hexagonal boron nitride (hBN) growth was carried out on (111) Si substrates at a temperature of 1350 °C using a cold wall chemical vapor deposition system. The hBN phase of the deposited films was identified by the characteristic Raman peak at 1370 cm−1 with a full width at half maximum of 25 cm−1, corresponding to the in-plane stretch of B and N atoms. Chemical bonding states and composition of the hBN films were analyzed by X-ray photoelectron spectroscopy; the extracted B/N ratio was 1.03:1, which is 1:1 within the experimental error. The fabricated metal-hBN-metal devices demonstrate a strong deep UV (DUV) response. Further, the hBN growth on the vertical (111) surfaces of parallel trenches fabricated in (110) Si was explored to achieve a thermal neutron detector. These results demonstrate that hBN-based detectors represent a promising approach towards the development of DUV photodetectors and efficient solid-state thermal neutron detectors.

We report on the design, fabrication, and performance of solid-state neutron detector based on three-dimensional honeycomb-like silicon micro-structures. The fabricated detectors use boron filled deep holes with aspect ratio of over 12 and showed a very low leakage current density of ∼7 × 10−7 A/cm2 at −1 V for device sizes varying from 2 × 2 to 5 × 5 mm2. A thermal neutron detection efficiency of 4.5% ± 0.5% with discrimination setting of 500 keV and gamma to neutron sensitivity of (1.1 ± 0.1) × 10−5 for single layer was measured without external bias for these devices. Monte-Carlo simulation predicts a maximum efficiency of 45% for such devices filled with 95% enriched 10boron.

RNA interference (RNAi) has generated significant interest as a strategy to suppress viral infection, but in some cases antiviral activity of unmodified short-interfering RNA (siRNA) has been attributed to activation of innate immune responses. We hypothesized that immunostimulation by unmodified siRNA could mediate both RNAi as well as innate immune stimulation depending on the mode of drug delivery. We investigated the potential of immunostimulatory RNAs (isRNAs) to suppress influenza A virus in vivo in the mouse lung. Lipidoid 98N12-5(1) formulated with unmodified siRNA targeting the influenza nucleoprotein gene exhibited antiviral activity. Formulations were optimized to increase antiviral activity, but the antiviral activity of lipidoid-delivered siRNA did not depend on sequence homology to the influenza genome as siRNA directed against unrelated targets also suppressed influenza replication in vivo. This activity was primarily attributed to enhancement of innate immune stimulation by lipidoid-mediated delivery, which indicates increased toll-like receptor (TLR) activation by siRNA. Certain chemical modifications to the siRNA backbone, which block TLR7/8 activation but retain in vitro RNAi activity, prevented siRNA-mediated antiviral activity despite enhanced lipidoid-mediated delivery. Here, we demonstrate that innate immune activation caused by unmodified siRNA can have therapeutically relevant effects, and that these non-RNAi effects can be controlled through chemical modifications and drug delivery.

We recently described a strategy for intracellular delivery of macromolecules, utilizing pH-responsive "core-shell" structured gel particles. These cross-linked hydrogel particles disrupt endosomes with low toxicity by virtue of physical sequestration of an endosome-disrupting "proton sponge" core inside a nontoxic hydrophilic shell. Here we tested the efficacy of this system for cytosolic delivery of a broad range of macromolecular cargos, and demonstrate the delivery of proteins, whole viral particles, or siRNA oligonucleotides into the cytosol of dendritic cells and epithelial cells via core-shell particles. We assessed the functional impact of particle delivery for vaccine applications and found that cytosolic delivery of protein antigens in dendritic cells via the core-shell particles promotes priming of CD8(+) T-cells at 100-fold lower doses than soluble protein. Functional gene knockdown following delivery of siRNA using the particles was demonstrated in epithelial cells. Based on these findings, these materials may be of interest for a broad range of biomedical applications.

A key challenge for therapeutic application of RNA interference is to efficiently deliver synthetic small interfering RNAs (siRNAs) into target cells that will lead to the knockdown of the target transcript (functional siRNA delivery). To facilitate rational development of nonviral carriers, we have investigated by imaging, pharmacological and genetic approaches the mechanisms by which a cationic lipid carrier mediates siRNA delivery into mammalian cells. We show that ∼95% of siRNA lipoplexes enter the cells through endocytosis and persist in endolysosomes for a prolonged period of time. However, inhibition of clathrin-, caveolin-, or lipid-raft-mediated endocytosis or macropinocytosis fails to inhibit the knockdown of the target transcript. In contrast, depletion of cholesterol from the plasma membrane has little effect on the cellular uptake of siRNA lipoplexes, but it abolishes the target transcript knockdown. Furthermore, functional siRNA delivery occurs within a few hours and is gradually inhibited by lowering temperatures. These results demonstrate that although endocytosis is responsible for the majority of cellular uptake of siRNA lipoplexes, a minor pathway, probably mediated by fusion between siRNA lipoplexes and the plasma membrane, is responsible for the functional siRNA delivery. Our findings suggest possible directions for improving functional siRNA delivery by cationic lipids.

RNA interference (RNAi) has generated significant interest as a strategy to suppress viral infection, but in some cases antiviral activity of unmodified short-interfering RNA (siRNA) has been attributed to activation of innate immune responses. We hypothesized that immunostimulation by unmodified siRNA could mediate both RNAi as well as innate immune stimulation depending on the mode of drug delivery. We investigated the potential of immunostimulatory RNAs (isRNAs) to suppress influenza A virus in vivo in the mouse lung. Lipidoid 98N12-5(1) formulated with unmodified siRNA targeting the influenza nucleoprotein gene exhibited antiviral activity. Formulations were optimized to increase antiviral activity, but the antiviral activity of lipidoid-delivered siRNA did not depend on sequence homology to the influenza genome as siRNA directed against unrelated targets also suppressed influenza replication in vivo. This activity was primarily attributed to enhancement of innate immune stimulation by lipidoid-mediated delivery, which indicates increased toll-like receptor (TLR) activation by siRNA. Certain chemical modifications to the siRNA backbone, which block TLR7/8 activation but retain in vitro RNAi activity, prevented siRNA-mediated antiviral activity despite enhanced lipidoid-mediated delivery. Here, we demonstrate that innate immune activation caused by unmodified siRNA can have therapeutically relevant effects, and that these non-RNAi effects can be controlled through chemical modifications and drug delivery.

Biochemical reaction networks are commonly described by non-linear ODE systems. Model parameters such as rate and equilibrium constants may be unknown or inaccessible and have to be identified from time-series measurements of chemical species. However, parameter identification is an ill-posed inverse problem in the sense that its solution lacks certain stability properties. In particular, modeling errors and measurement noise can be amplified considerably. These problems can be overcome by the use of so-called regularization methods. More specifically, parameter identification can be formulated in a stable way as a minimization problem with a data mismatch and a regularization term. On a benchmark problem, we demonstrate the stabilizing effect of Tikhonov regularization, i.e. we are able to identify the parameters from noisy measurements in a stable and accurate manner. In the algorithmic realization, we use the adjoint technique to efficiently compute the gradient of the data mismatch. Furthermore, we have developed a software package which allows the identification of parameters in valid SBML models of biochemical reaction networks. ∗ stefan.mueller@oeaw.ac.at Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences, Altenberger Straße 69, 4040 Linz, Austria Industrial Mathematics Institute, Johannes Kepler University Linz, Altenberger Straße 69, 4040 Linz, Austria Rector’s Office, University of Vienna, Dr.-Karl-Lueger-Ring 1, 1010 Wien, Austria

Purpose. Low efficiency and toxicity are two major drawbacks of current non-viral gene delivery vectors. Since DNA delivery to mammalian cells is a multi-step process, generating and searching combinatorial libraries of vectors employing high-throughput synthesis and screening methods is an attractive strategy for the development of new improved vectors because it increases the chance of identifying the most overall optimized vectors.Materials and Methods. Based on the rationale that increasing the effective molecular weight of small PEIs, which are poor vectors compared to the higher molecular weight homologues but less toxic, raises their transfection efficiency due to better DNA binding, we synthesized a library of 144 biodegradable derivatives from two small PEIs and 24 bi- and oligo-acrylate esters. A 423-Da linear PEI and its 1: 1 (w/w) mixture with a 1.8-kDa branched PEI were cross-linked with the acrylates at three molar ratios in DMSO. The resulting polymers were screened for their efficiency in delivering a beta-galactosidase expressing plasmid to COS-7 monkey kidney cells. Selected most potent polymers from the initial screen were tested for toxicity in A549 human lung cancer cells, and in vivo in a systemic gene delivery model in mice employing a firefly luciferase expressing plasmid.Results. Several polycations that exhibited high potency and low toxicity in vitro were identified from the library. The most potent derivative of the linear 423-Da PEI was that cross-linked with tricycle[5.2.1.0]-decane- dimethanol diacrylate (diacrylate 14), which exhibited an over 3,600-fold enhancement in efficiency over the parent. The most potent mixed PEI was that cross-linked with ethylene glycol diacrylate (diacrylate 4) which was over 850-fold more efficient than the physically mixed parent PEIs. The relative efficiencies of these polymers were even up to over twice as high as that of the linear 22-kDa PEI, considered the "gold standard" for in vitro and systemic gene delivery. The potent cross-linked polycations identified were also less toxic than the 22-kDa PEI. The optimal vector in vivo was the mixed PEI cross-linked with propylene glycol glycerolate diacrylate ( diacrylate 7); it mediated the highest gene expression in the lungs, followed by the spleen, with the expression in the former being 53-fold higher compared to the latter. In contrast, the parent PEIs mediated no gene expression at all under similar conditions, and injection of the polyplexes of the 22-kDa PEI at its optimal N/P of 10 prepared under identical conditions killed half of the mice injected.Conclusions. High-throughput synthesis and transfection assay of a cross-linked library of biodegradable PEIs was proven effective in identifying highly transfecting vectors. The identified vectors exhibited dramatically superior efficiency compared to their parents both in vitro and in an in vivo systemic gene delivery model. The majority of these vectors mediated preferential gene delivery to the lung, and their in vivo toxicity paralleled that in vitro.

With the strong support of the World Tourism Organisation (UNWTO), the School of Hotel and Tourism Management of The Hong Kong Polytechnic University (PolyU) recently hosted the First International Forum on Tourism Education and the Fourth China Tourism Forum with peer institutions in China. Each of the forum attracted over 200 attendance, including participants from around the world and Mainland China. As a leading hospitality and tourism education institution in China, PolyU's School of Hotel and Tourism Management was proud to pioneer the First International Forum on Tourism Education with the support of UNWTO and the Government of Guangxi Zhuang Autonomous Region, the Tourism Bureau of Guangxi Zhuang Autonomous Region, Guilin Tourism Bureau and Guilin Institute of Tourism in the city of Guilin, Guangxi, China on 12 - 13 December 2007. With an aim to enhance the international competitiveness of tourism education in China, the Forum provided a platform for academics and practitioners to exchange views and research outputs related to this important topic. The issues explored in the Forum included the impact of the trend of tourism development on tourism education; the modes of training tourism professionals; work-integrated education; research on the programme structure and profession of tourism education; students' understanding and experience on tourism education; and the development trend and future prospect of tourism education.

SiRNAs exert their biological effect by guiding the degradation of their cognate mRNA sequence, thereby shutting down the corresponding protein production (gene silencing by RNA interference or RNAi). Due to this property, siRNAs are emerging as promising therapeutic agents for the treatment of inherited and acquired diseases, as well as research tools for the elucidation of gene function in both health and disease. Because of their lethality and prevalence, lung diseases have attracted particular attention as targets of siRNA-mediated cures. In addition, lung is accessible to therapeutic agents via multiple routes, e.g., through the nose and the mouth, thus obviating the need for targeting and making it an appealing target for RNAi-based therapeutic strategies. The clinical success of siRNA-mediated interventions critically depends upon the safety and efficacy of the delivery methods and agents. Delivery of siRNAs relevant to lung diseases has been attempted through multiple routes and using various carriers in animal models. This review focuses on the recent progress in non-viral delivery of siRNAs for the treatment of lung diseases, particularly infectious diseases. The rapid progress will put siRNA-based therapeutics on fast track to the clinic.

In conventional avionics system design process, changing the avionics system architecture involves a large team of engineers and requires months to years of redesign time. This paper describes the Avionics Architecture Tool (AST) developed by JPL that can automatically synthesize architecture for the avionics-system-on-a-chip. As the synthesis is based on Genetic Algorithm and driven by requirements that are imposed by the environment, the synthesized architecture can quickly adapt to environmental changes. Furthermore, the AST can also guarantee that the synthesized architecture is viable and workable through the use of Viability Tree.

Influenza A viruses cause epidemics and pandemics in both poultry and humans, inflicting enormous suffering and economical loss. Currently, two strategies, vaccines and small molecule therapeutics, are utilized to control the spread of influenza. Vaccination offers limited protection and requires accurate prediction of future circulating strains and production of sufficient quantities of vaccine for large populations in a short time. There are four antiviral drugs for treatment and/or prophylaxis of influenza.

Influenza A virus causes one of the most prevalent infections in humans. In a typical year, 10 – 20% of the population of the US is infected by influenza virus, resulting in up to 40,000 deaths and 200,000 hospitalisations. Vaccination is the most effective preventative measure that can protect 70 – 90% of healthy adults aged < 65; however, the protection rate is much lower in those most susceptible to infection, namely infants, the elderly and individuals with weakened immune systems. Although four drugs have been approved by the FDA for use as prophylaxis and/or treatment of influenza, concerns about their side effects and the emergence of drug-resistant viruses persist. RNA interference (RNAi), an emerging method of post transcriptional gene silencing, appears ideal for the prevention and treatment of influenza. RNAi in mammals can be mediated by short interfering RNAs (siRNAs) of ∼21– 27 nucleotides in length. The authors have previously shown that si-RNAs specific for conserved regions of the influenza virus genome are potent inhibitors of influenza virus replication in both cell lines and chicken embryos. This review discusses the recent progress in the invivo inhibition of influenza virus by the delivery of siRNAs mediated by non-viral vectors, and the prospects of this strategy for prophylaxis and treatment of influenza infection in humans.

*It is acknowledged that an earlier version of this paper was presented at the 2nd APacCHRIE Conference and 2nd Biennial Conference on Tourism in Asia, held in Phuket, Thailand, on 27–29 May 2004.