Comprehensive Analysis of N6-methyladenosine Modification Patterns Associated With Multiomic Characteristics of Bladder Cancer

Purpose: To comprehensively analyze N6-methyladenosine modification patterns in bladder tumors and to further systematically explore the inherent relationships between these modification patterns and multiomic tumor characteristics.Materials and Methods: A total of 901 bladder tumor samples, including 405 samples from TCGA database, 188 samples from GSE13507 and 308 samples from GSE32894, were included in this systematic analysis. The N6-methyladenosine modification patterns were identified utilizing unsupervised clustering analysis. To quantify N6-methyladenosine modification patterns, the m6Ascore of individual sample was developed using principal component analysis algorithms. Relationships among immune infiltration, tumor mutation burden, various clinical characteristics, molecular subtypes, and the m6Ascore were systematically analyzed. The guiding value of m6Ascore in immunotherapy was further validated in an external trial cohort. Genomics of Drug Sensitivity in Cancer expression references were also utilized to perform drug sensitivity analysis for patients with distinct m6A modification patterns.Results: We determined three different N6-methyladenosine modification patterns for 901 bladder tumors. The quantitative m6Ascore of individual sample derived from N6-methyladenosine modification patterns could play a significant role in predicting overall survival, immune cell infiltration, and classic oncogene mutations. A low m6Ascore combined with high tumor mutation burden indicated better survival outcomes (p < 0.001). A higher m6Ascore also indicated a higher grade, higher T and N stage, elder ages, higher death rate, and higher PD1/PDL1/CTLA4 expressions (p < 0.01). The Basal type tended to exhibit significantly higher m6Ascores than the Luminal and Neuronal subtypes. External immunotherapy cohorts demonstrated that no difference in therapeutic effects was noted between the high and low m6Ascore groups when anti-PD1 immunotherapy was exclusively administered. When anti-PD1 and anti-CTLA4 immunotherapy were simultaneously administered, the high m6Ascore group had a significantly better prognosis than the low m6Ascore group (p < 0.001). High m6A groups were potentially sensitive to various medical treatments including Bleomycin, Bortezomib, Cisplatin, Cyclopamine, Dasatinib, Docetaxe, Rapamycin, and Vinblastine in this study.Conclusions: This study systematically revealed the important roles of m6A methylation modification patterns in bladder tumors. Detailed quantification of m6A modification patterns could improve our understanding of the bladder tumor microenvironments and could provide guidance for future immunotherapy strategies.

A Specific Emitter Identification Algorithm under Zero Sample Condition Based on Metric Learning

With the development of information technology in modern military confrontation, specific emitter identification has become a hot and difficult topic in the field of electronic warfare, especially in the field of electronic reconnaissance. Specific emitter identification requires a historical reconnaissance signal as the matching template. In order to avoid being intercepted by enemy electronic reconnaissance equipment, modern radar often has multiple sets of working parameters, such as pulse width and signal bandwidth, which change when performing different tasks and training. At this time, the collected fingerprint features cannot fully match the fingerprint template in the radar database, making the traditional specific emitter identification algorithm ineffective. Therefore, when the working parameters of enemy radar change, that is, when there is no such variable working parameter signal template in our radar database, it is a bottleneck problem in the current electronic reconnaissance field to realize the specific emitter identification. In order to solve this problem, this paper proposes a network model based on metric learning. By learning deep fingerprint features and learning a deep nonlinear metric between different sample signals, the same individual sample signals under different working parameters can be associated. Even if there are no samples under a certain kind of working parameter signal, it can still be associated with the original individual through this network model, so as to achieve the purpose of specific emitter identification. As opposed to the situation in which the traditional specific emitter identification algorithm cannot be associated with the original individual when the signal samples of changing working parameters are not collected, the algorithm proposed in this paper can better solve the problem of changing working parameters and zero samples.

Pooling Nasopharyngeal Swab Specimens to Improve Testing Capacity for SARS-CoV-2 by Real-Time RT-PCR

Background The detection of SARS-CoV-2 using qRT-PCR with the pooling of samples can reduce workload and costs especially when the prevalence rate of COVID-19 in a population is low. To analyse the effect of pooling samples on the sensitivity of RT-qPCR for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection, we compared the cycle threshold (Ct) values of pools of 5 and 10 that tested positive with Ct values of individual samples that tested positive in that pool. Twenty positive nasopharyngeal (NP) specimens with low to high viral load were selected and pooled individually with four and nine negative NP. Results In NP specimens, the sensitivity of pools of 5 and 10 were 90 and 85%, compared to individual sample testing, respectively. The RT-qPCR sensitivity of pools of 5 and 10 against individual testing were not significantly different (p > 0.05). Detection of positive samples with low Ct values (< 36) was consistently achieved in pools of 5 and 10. However, there were higher false negatives when samples with high ct values (> 36) were pooled and tested. The mean Ct values obtained with the 5-sample pooled testing exceeded individual sample testing by 1.85 ± 1.09 cycles, while Ct values obtained with the 10-sample pooling exceeded individual sample testing by 3.4 ± 1.65 cycles. Conclusions In a low prevalence setting, testing capacity can be increased by pooling 5 or 10 samples, but the risk of additional false negatives needs to be considered

Design of a High-Throughput Real-Time PCR System for Detection of Bovine Respiratory and Enteric Pathogens

Bovine respiratory and enteric diseases have a profound negative impact on animal, health, welfare, and productivity. A vast number of viruses and bacteria are associated with the diseases. Pathogen detection using real-time PCR (rtPCR) assays performed on traditional rtPCR platforms are costly and time consuming and by that limit the use of diagnostics in bovine medicine. To diminish these limitations, we have developed a high-throughput rtPCR system (BioMark HD; Fluidigm) for simultaneous detection of the 11 most important respiratory and enteric viral and bacterial pathogens. The sensitivity and specificity of the rtPCR assays on the high-throughput platform was comparable with that of the traditional rtPCR platform. Pools consisting of positive and negative individual field samples were tested in the high-throughput rtPCR system in order to investigate the effect of an individual sample in a pool. The pool tests showed that irrespective of the size of the pool, a high-range positive individual sample had a high influence on the cycle quantification value of the pool compared with the influence of a low-range positive individual sample. To validate the test on field samples, 2,393 nasal swab and 2,379 fecal samples were tested on the high-throughput rtPCR system as pools in order to determine the occurrence of the 11 pathogens in 100 Danish herds (83 dairy and 17 veal herds). In the dairy calves, Pasteurella multocida (38.4%), rotavirus A (27.4%), Mycoplasma spp. (26.2%), and Trueperella pyogenes (25.5%) were the most prevalent pathogens, while P. multocida (71.4%), Mycoplasma spp. (58.9%), Mannheimia haemolytica (53.6%), and Mycoplasma bovis (42.9%) were the most often detected pathogens in the veal calves. The established high-throughput system provides new possibilities for analysis of bovine samples, since the system enables testing of multiple samples for the presence of different pathogens in the same analysis test even with reduced costs and turnover time.

Adjusting the Cut-Off and Maximum Pool Size in RT-qPCR Pool Testing for SARS-CoV-2

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) to detect SARS-CoV-2 RNA is an essential test to monitor the occurrence of COVID-19. A methodology is proposed for the determination of maximum pool size and adjustments of cut-off values of cycle threshold (Ct in RT-qPCR pool testing, to compensate for the dilution caused by pooling. The trade-off between pool size and test sensitivity is stated explicitly. The procedure was designed to ensure that samples that would be detectable in individual testing remain detectable in pool testing. The proposed relaxation in cut-off is dependent on the pool size, allowing a relatively tight correction to avoid loss of detection of positive samples. The methodology was evaluated in a study of pool testing of adults attending a public emergency care unit, reference for COVID-19 in Belo Horizonte, Brazil, and presenting flu-like symptoms. Even samples on the edge of detectability in individual testing were detected correctly. The proposed procedure enhances the consistency of RT-qPCR pool testing by enforcing that the scales of detectability in pool processing and in individual sample processing are compatible. This may enhance the contribution of pool testing to large-scale testing for COVID-19.

Supplemental Material: Recalibrating Rodinian rifting in the northwestern United States

Individual sample detrital zircon results, alternative maximum depositional age calculations, conventional laser-ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) methodology, rapid LA-ICP-MS methodology, sample locations, and detrital zircon U-Pb/Lu-Hf results for all analyses and compiled U-Pb data.<br>

Supplemental Material: Recalibrating Rodinian rifting in the northwestern United States

Individual sample detrital zircon results, alternative maximum depositional age calculations, conventional laser-ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) methodology, rapid LA-ICP-MS methodology, sample locations, and detrital zircon U-Pb/Lu-Hf results for all analyses and compiled U-Pb data.<br>

Supplemental Material: Recalibrating Rodinian rifting in the northwestern United States

Individual sample detrital zircon results, alternative maximum depositional age calculations, conventional laser-ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) methodology, rapid LA-ICP-MS methodology, sample locations, and detrital zircon U-Pb/Lu-Hf results for all analyses and compiled U-Pb data.<br>