Robustness Enhancement in Neural Networks with Alpha-Stable Training Noise

With the increasing use of deep learning on data collected by non-perfect sensors and in non-perfect environments, the robustness of deep learning systems has become an important issue. A common approach for obtaining robustness to noise has been to train deep learning systems with data augmented with Gaussian noise. In this work, we challenge the common choice of Gaussian noise and explore the possibility of stronger robustness for non-Gaussian impulsive noise, specifically alpha-stable noise. Justified by the Generalized Central Limit Theorem and evidenced by observations in various application areas, alpha-stable noise is widely present in nature. By comparing the testing accuracy of models trained with Gaussian noise and alpha-stable noise on data corrupted by different noise, we find that training with alpha-stable noise is more effective than Gaussian noise, especially when the dataset is corrupted by impulsive noise, thus improving the robustness of the model. The generality of this conclusion is validated through experiments conducted on various deep learning models with image and time series datasets, and other benchmark corrupted datasets. Consequently, we propose a novel data augmentation method that replaces Gaussian noise, which is typically added to the training data, with alpha-stable noise

Immunogenicity and therapeutic effects of a Mycobacterium tuberculosis rv2190c DNA vaccine in mice

The Excel data file [FOLT] Figshare, [DOI: 10.6084/m9.figshare.4668148 and https://figshare.com/s/bd46c22986c673579bb6 ] includes all datasets supporting the conclusions of this article: IFN-Îł in spleen lymphocyte culture supernatants, IL-4 in spleen lymphocyte culture supernatants, CD4+ T cell subsets expressing intracellular IFN-Îł or IL-4, CFU in the lungs and spleens.. (XLS 143 kb

Cost-effectiveness analysis of elacestrant versus standard endocrine therapy for second-/third-line treatment of patients with HR+/HER2- advanced or metastatic breast cancer: a US payer perspective

BackgroundThis study evaluated the cost-effectiveness of elacestrant (ELA) and standard-of-care (SOC) as second-/third-line treatment for pretreated estrogen receptor (ER)– positive/human epidermal growth factor receptor 2 (HER2)–negative advanced or metastatic breast cancer (A/MBC) in the US.MethodsThe 3 health states partitioned survival model (PSM) was conducted from the perspective of the US third-party payers. The time horizon for the model lasted 10 years. Effectiveness and safety data were derived from the EMERALD trial (NCT03778931). Costs were derived from the pricing files of Medicare and Medicaid Services, and utility values were derived from published studies. One-way sensitivity analysis as well as probabilistic sensitivity analysis were performed to observe model stability.ResultELA led to an incremental cost-effectiveness ratio (ICER) of $8,672,360/quality-adjusted life year (QALY) gained compared with SOC in the overall population and$2,900,560/QALY gained compared with fulvestrant (FUL) in the ESR1(estrogen receptor 1) mutation subgroup. The two ICERs of ELA were significantly higher than the willingness-to-pay (WTP) threshold values of $150,000/QALY.ConclusionsELA was not cost-effective for the second-/third-line treatment of patients with ER+/HER2–A/MBC compared with SOC in the US

Implications of inflammatory cell death-related IFNG and co-expressed RNAs (AC006369.1 and CCR7) in breast carcinoma prognosis, and anti-tumor immunity

Objective: Interferon-γ (IFN-γ) encoded by IFNG gene is a pleiotropic molecule linked with inflammatory cell death mechanisms. This work aimed to determine and characterize IFNG and co-expressed genes, and to define their implications in breast carcinoma (BRCA).Methods: Transcriptome profiles of BRCA were retrospectively acquired from public datasets. Combination of differential expression analysis with WGCNA was conducted for selecting IFNG-co-expressed genes. A prognostic signature was generated through Cox regression approaches. The tumor microenvironment populations were inferred utilizing CIBERSORT. Epigenetic and epitranscriptomic mechanisms were also probed.Results: IFNG was overexpressed in BRCA, and connected with prolonged overall survival and recurrence-free survival. Two IFNG-co-expressed RNAs (AC006369.1, and CCR7) constituted a prognostic model that acted as an independent risk factor. The nomogram composed of the model, TNM, stage, and new event owned the satisfying efficacy in BRCA prognostication. IFNG, AC006369.1, and CCR7 were closely linked with the tumor microenvironment components (e.g., macrophages, CD4/CD8 T cells, NK cells), and immune checkpoints (notably PD1/PD-L1). Somatic mutation frequencies were 6%, and 3% for CCR7, and IFNG, and high amplification potentially resulted in their overexpression in BRCA. Hypomethylated cg05224770 and cg07388018 were connected with IFNG and CCR7 upregulation, respectively. Additionally, transcription factors, RNA-binding proteins, and non-coding RNAs possibly regulated IFNG and co-expressed genes at the transcriptional and post-transcriptional levels.Conclusion: Collectively, our work identifies IFNG and co-expressed genes as prognostic markers for BRCA, and as possible therapeutic targets for improving the efficacy of immunotherapy

An mHealth-based school health education system designed to scale up salt reduction in China (EduSaltS): A development and preliminary implementation study

BackgroundHigh-salt diet is an important risk factor for several non-communicable diseases. School-based health education has been found effective in reducing salt intake among children and their families in China. However, no such interventions have been scaled up in the real world. For this purpose, a study was launched to support the development and scale-up of an mHealth-based system (EduSaltS) that integrated routine health education and salt reduction and was delivered through primary schools. This study aims to elaborate the framework, development process, features, and preliminary scaling-up of the EduSaltS system.MethodsThe EduSaltS system evolved from previously successfully tested interventions to reduce family salt intake by empowering schoolchildren through school health education. EduSaltS was designed by following the WHO’s conceptual framework for developing a scaling-up strategy which accounted for the nature of the innovation, the capacity of the implementing organizations, the characteristics of the environment, the resources available, and type of scaling up. The system was then developed step by step from determination of online platform architecture, definition of component interventions and activities, development of specific educational materials and tools, to the development of the online/offline hybridized system. The system was tested and refined by a pilot in two schools and a preliminary scale-up in two cities in China.ResultsEduSaltS was developed as an innovative health education system, including an online WeChat-based education platform, a set of offline activities, and an actual administrative website showing the progress and setting the system. The WeChat platform could be installed on users’ smartphones to automatically deliver 20 sessions of five-minute well-structured cartoon video classes, followed by other online interactive activities. It also helps support project implementation and real-time performance evaluation. As a first-stage roll-out, a one-year course has been successfully implemented among 54,538 children and their families from 209 schools in two cities, and the average course completion rate was 89.1%.ConclusionAs an innovative mHealth-based health education system, EduSaltS was developed based on successfully tested interventions and an appropriate framework for scaling up. The early-stage roll-out has shown its preliminary scalability, and further evaluation is ongoing

Research on photostability for infrared thin films of chalcogenide glasses

The photostability, photo-bleaching and photo-darkening behavior of twelve film samples of Ge-As-Se thin films with different chemical compositions are investigated when the films are exposed at irradiation of 656 nm by thermal evaporation deposition. Th

HGT-Finder: A New Tool for Horizontal Gene Transfer Finding and Application to Aspergillus genomes

Horizontal gene transfer (HGT) is a fast-track mechanism that allows genetically unrelated organisms to exchange genes for rapid environmental adaptation. We developed a new phyletic distribution-based software, HGT-Finder, which implements a novel bioinformatics algorithm to calculate a horizontal transfer index and a probability value for each query gene. Applying this new tool to the Aspergillus fumigatus, Aspergillus flavus, and Aspergillus nidulans genomes, we found 273, 542, and 715 transferred genes (HTGs), respectively. HTGs have shorter length, higher guanine-cytosine (GC) content, and relaxed selection pressure. Metabolic process and secondary metabolism functions are significantly enriched in HTGs. Gene clustering analysis showed that 61%, 41% and 74% of HTGs in the three genomes form physically linked gene clusters (HTGCs). Overlapping manually curated, secondary metabolite gene clusters (SMGCs) with HTGCs found that 9 of the 33 A. fumigatus SMGCs and 31 of the 65 A. nidulans SMGCs share genes with HTGCs, and that HTGs are significantly enriched in SMGCs. Our genome-wide analysis thus presented very strong evidence to support the hypothesis that HGT has played a very critical role in the evolution of SMGCs. The program is freely available at http://cys.bios.niu.edu/HGTFinder/ HGTFinder.tar.gz