Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability

Training deep neural networks (DNNs) takes significant time and resources. A practice for expedited deployment is to use pre-trained deep neural networks (PTNNs), often from model zoos.collections of PTNNs; yet, the reliability of model zoos remains unexamined. In the absence of an industry standard for the implementation and performance of PTNNs, engineers cannot confidently incorporate them into production systems. As a first step, discovering potential discrepancies between PTNNs across model zoos would reveal a threat to model zoo reliability. Prior works indicated existing variances in deep learning systems in terms of accuracy. However, broader measures of reliability for PTNNs from model zoos are unexplored. This work measures notable discrepancies between accuracy, latency, and architecture of 36 PTNNs across four model zoos. Among the top 10 discrepancies, we find differences of 1.23%-2.62% in accuracy and 9%ś131% in latency. We also find mismatches in architecture for well-known DNN architectures (e.g., ResNet and AlexNet). Our findings call for future works on empirical validation, automated tools for measurement, and best practices for implementation

An Experimental Study on the Establishment of Pulmonary Hypertension Model in Rats induced by Monocrotaline

Pulmonary hypertension is called PH for short. It is caused by the pulmonary artery vascular disease leading to pulmonary vascular resistance, and the increase right lung compartment load, which resulting in weakening or even collapse of the right ventricular function. The establishment of rat PH model under the action of monocrotaline is a repeatable, simple and accessible operation technique, which has been widely used in the treatment of pulmonary hypertension. This paper discusses the principle and properties of the PH model on rats under the monocrotaline action

Highly branched poly(β-amino ester) delivery of minicircle DNA for transfection of neurodegenerative disease related cells

Current therapies for most neurodegenerative disorders are only symptomatic in nature and do not change the course of the disease. Gene therapy plays an important role in disease modifying therapeutic strategies. Herein, we have designed and optimized a series of highly branched poly(β-amino ester)s (HPAEs) containing biodegradable disulfide units in the HPAE backbone (HPAESS) and guanidine moieties (HPAESG) at the extremities. The optimized polymers are used to deliver minicircle DNA to multipotent adipose derived stem cells (ADSCs) and astrocytes, and high transfection efficiency is achieved (77% in human ADSCs and 52% in primary astrocytes) whilst preserving over 90% cell viability. Furthermore, the top-performing candidate mediates high levels of nerve growth factor (NGF) secretion from astrocytes, causing neurite outgrowth from a model neuron cell line. This synergistic gene delivery system provides a viable method for highly efficient non-viral transfection of ADSCs and astrocytes

Perfluorocarbon nanodrug induced oxygen self-enriching sonodynamic therapy improves cancer immunotherapy after insufficient radiofrequency ablation

Residual lesions and undetectable metastasis after insufficient radiofrequency ablation (iRFA) are associated with earlier new metastases and poor survival in cancer patients, for induced aggressive tumor phenotype and immunosuppression. Programmed cell death protein 1(PD-1) blockade has been reported to enhance the radiofrequency ablation-elicited antitumor immunity, but its ability to eliminate incompletely ablated residual lesions has been questioned. Here, we report a combined treatment modality post iRFA based on integrating an oxygen self-enriching nanodrug PFH-Ce6 liposome@O2 nanodroplets (PCL@O2)-augmented noninvasive sonodynamic therapy (SDT) with PD-1 blockade. PCL@O2 containing Ce6 as the sonosensitizer and PFH as O2 reservoir, was synthesized as an augmented SDT nanoplatform and showed increased ROS generation to raise effective apoptosis of tumor cells, which also exposed more calreticulin to induce stronger immunogenic cell death (ICD). Combining with PD-1 blockade post iRFA, this optimized SDT induced a better anti-tumor response in MC38 tumor bearing mouse model, which not only arrested residual primary tumor progression, but also inhibited the growth of distant tumor, therefore prolonging the survival. Profiling of immune populations within the tumor draining lymph nodes and tumors further revealed that combination therapy effectively induced ICD, and promoted the maturation of dendritic cells, tumor infiltration of T cells, as well as activation of cytotoxic T lymphocytes. While iRFA alone could result in an increase of regulatory T cells (Tregs) in the residual tumors, SDT plus PD-1 blockade post iRFA reduced the number of Tregs in both primary and distant tumors. Moreover, the combined treatment could significantly initiate long-term immune memory, manifesting as elevated levels of CD8+ and CD4+ central memory cells. Therefore, this study establishes the preclinical proof of concept to apply oxygen self-enriching SDT to augment cancer immunotherapy after iRFA

Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations

Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10-7 to 2.46×10-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding