Efficient Monitoring of Parametric Context Free Patterns

Recent developments in runtime verification and monitoring show that parametric regular and temporal logic specifications can be efficiently monitored against large programs. However, these logics reduce to ordinary finite automata, limiting their expressivity. For example, neither can specify structured properties that refer to the call stack of the program. While context-free grammars (CFGs) are expressive and well-understood, existing techniques of monitoring CFGs generate massive runtime overhead in real-life applications. This paper shows for the first time that monitoring parametric CFGs is practical (on the order of 10% or lower for average cases, several times faster than the state-of-the-art). We present a monitor synthesis algorithm for CFGs based on an LR(1) parsing algorithm, modified with stack cloning to account for good prefix matching. In addition, a logic-independent mechanism is introduced to support partial matching, allowing patterns to be checked against fragments of execution traces

BCL11B is required for positive selection and survival of double-positive thymocytes

Transcriptional control of gene expression in double-positive (DP) thymocytes remains poorly understood. We show that the transcription factor BCL11B plays a critical role in DP thymocytes by controlling positive selection of both CD4 and CD8 lineages. BCL11B-deficient DP thymocytes rearrange T cell receptor (TCR) α; however, they display impaired proximal TCR signaling and attenuated extracellular signal-regulated kinase phosphorylation and calcium flux, which are all required for initiation of positive selection. Further, provision of transgenic TCRs did not improve positive selection of BCL11B-deficient DP thymocytes. BCL11B-deficient DP thymocytes have altered expression of genes with a role in positive selection, TCR signaling, and other signaling pathways intersecting the TCR, which may account for the defect. BCL11B-deficient DP thymocytes also presented increased susceptibility to spontaneous apoptosis associated with high levels of cleaved caspase-3 and an altered balance of proapoptotic/prosurvival factors. This latter susceptibility was manifested even in the absence of TCR signaling and was only partially rescued by provision of the BCL2 transgene, indicating that control of DP thymocyte survival by BCL11B is nonredundant and, at least in part, independent of BCL2 prosurvival factors

Prolonged drought regulates the silage quality of maize (Zea mays L.): Alterations in fermentation microecology

Prolonged drought stress caused by global warming poses a tremendous challenge to silage production of maize. Drought during maize growth and development resulted in altered micro-environment for silage fermentation. How fermentation of silage maize responds to moisture scales remains uncharted territory. In this research, Maize water control trials were conducted and the silage quality and microbial community of drought-affected maize were determined. The results showed that drought stress significantly reduced the dry matter but increased root-to-shoot ratio, soluble sugar and malonaldehyde content in maize. Before fermentation, the crude protein, crude ash and acid detergent fiber contents were significantly increased but the ether extract content was decreased under drought. The crude protein and acid detergent fiber were significantly decreased in the drought affected group after fermentation. Furthermore, water stress at maize maturity stage greatly reduced the number of total bacteria in silage fermentation but increased the proportion of the lactobacillus and lactic acid content of silage. Drought stress alters the microbial ecosystem of the fermentation process and reconstitutes the diversity of the bacterial community and its metabolites. This study provides a theoretical basis for the study of changes in silage fermentation as affected by abiotic stresses

Risk factors associated with postoperative respiratory failure after esophagectomy for esophageal cancer

Aim: Respiratory failure is common after esophagectomy for esophageal cancer (EC). This study aimed to identify the risk factors associated with postoperative respiratory failure following esophagectomy for EC. Methods: A single-center observational study from China was conducted on 262 patients with EC who underwent thoracoscopic esophagectomy between April 2014 and June 2016. The patients were divided into two groups: group I (respiratory failure) and group II (without respiratory failure). Demographic and perioperative variables, tumor-related factors, surgical factors, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, and clinical course were compared between the groups. Univariable and multivariable logistic regression analyses were performed to assess the risk factors of postoperative respiratory failure after esophagectomy. Results: Among the 262 patients, 24 (9.2%) developed respiratory failure. Univariable analysis revealed several risk factors, including age, smoking, comorbidities, partial pressure of oxygen (PO2), partial pressure of carbon dioxide (PCO2), forced vital capacity (FVC), FVC percentage (FVC%), urine volume during surgery, and APACHE II score. Multivariable analysis showed that age, comorbidities of diabetes mellitus (DM), FVC%, urine volume during surgery, and APACHE II score were independent predictors of respiratory failure. Specifically, elderly patients (> 65 years) with comorbidities of DM, lower FVC%, higher urine volume during surgery, and elevated APACHE II score were found to be more susceptible to respiratory failure, resulting in prolonged hospitalization and increased healthcare burden. These findings emphasize the importance of considering these factors in the management and care of patients at risk of respiratory failure. Conclusions: As a common complication following esophagectomy for EC. Respiratory failure is significantly associated with age, comorbidities of DM, FVC%, urine volume during surgery, and APACHE II score in the dataset. The findings will contribute to the evaluation of the risk of respiratory failure and guide early intervention strategies in clinical decision-making

Listen to genes : dealing with microarray data in the frequency domain

Background: We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes. Methodology: Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail. Conclusions: We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers

Fine mapping and identification of the fuzzless gene GaFzl in DPL972 (Gossypium arboreum).

peer reviewedKEY MESSAGE: The fuzzless gene GaFzl was fine mapped to a 70-kb region containing a GIR1 gene, Cotton_A_11941, responsible for the fuzzless trait in Gossypium arboreum DPL972. Cotton fiber is the most important natural textile resource. The fuzzless mutant DPL972 (Gossypium arboreum) provides a useful germplasm resource to explore the molecular mechanism underlying fiber and fuzz initiation and development. In our previous research, the fuzzless gene in DPL972 was identified as a single dominant gene and named GaFzl. In the present study, we fine mapped this gene using F2 and BC1 populations. By combining traditional map-based cloning and next-generation sequencing, we mapped GaFzl to a 70-kb region containing seven annotated genes. RNA-Sequencing and re-sequencing analysis narrowed these candidates to two differentially expressed genes, Cotton_A_11941 and Cotton_A_11942. Sequence alignment uncovered no variation in coding or promoter regions of Cotton_A_11942 between DPL971 and DPL972, whereas two single-base mutations in the promoter region and a TTG insertion in the coding region were detected in Cotton_A_11941 in DPL972. Cotton_A_11941 encoding a homologous gene of GIR1 (GLABRA2-interacting repressor) in Arabidopsis thaliana is thus the candidate gene most likely responsible for the fuzzless trait in DPL972. Our findings should lead to a better understanding of cotton fuzz formation, thereby accelerating marker-assisted selection during cotton breeding

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Efficient Formalism-Independent Monitoring of Parametric Properties

Efficient monitoring of parametric properties, in spite of increasingly growing interest thanks to applications such as testing and security, imposes a highly non-trivial challenge on monitoring approaches due to the potentially huge number of parameter instances. A few solutions have been proposed, but most of them compromise their expressiveness for performance or vice versa. In this paper, we propose a generic, in terms of specification formalisms, yet efficient, solution to monitoring parametric specifications. Our approach is based on a general semantics for slicing parametric traces and makes use of knowledge about the property to monitor. The needed knowledge is not specific to the underlying formalism and can be easily computed when generating monitoring code from the property. An extensive evaluation shows that the monitoring code generated by our algorithm is still faster than other state-of-art techniques optimized for particular logics or properties