Cytological and proteomic analyses of horsetail (Equisetum arvense L.) spore germination

Spermatophyte pollen tubes and root hairs have been used as single-cell-type model systems to understand the molecular processes underlying polar growth of plant cells. Horsetail (Equisetum arvense L.) is a perennial herb species in Equisetopsida, which creates separately growing spring and summer stems in its life cycle. The mature chlorophyllous spores produced from spring stems can germinate without dormancy. Here we report the cellular features and protein expression patterns in five stages of horsetail spore germination (mature spores, rehydrated spores, double-celled spores, germinated spores, and spores with protonemal cells). Using 2-DE combined with mass spectrometry, 80 proteins were found to be abundance changed upon spore germination. Among them, proteins involved in photosynthesis, protein turnover, and energy supply were over-represented. Thirteen proteins appeared as proteoforms on the gels, indicating the potential importance of post-translational modification. In addition, the dynamic changes of ascorbate peroxidase, peroxiredoxin, and dehydroascorbate reductase implied that reactive oxygen species homeostasis is critical in regulating cell division and tip-growth. The diverse expression patterns of proteins in photosynthesis, energy supply, lipid and amino acid metabolism indicated that heterotrophic and autotrophic metabolism were necessary in light-dependent germination of the spores. Twenty-six proteins were involved in protein synthesis and fate, indicating that protein turnover is vital to spore germination. Furthermore, the altered abundance of small G protein Ran, 14-3-3 protein, actin, and Caffeoyl-CoA O-methyltransferase revealed that signaling transduction, vesicle trafficking, cytoskeleton dynamics, and cell wall modulation were critical to cell division and polar growth. These findings lay a foundation toward understanding the molecular mechanisms underlying fern spore asymmetric division and rhizoid polar growth

Prognostic value of MRI-derived masticator space involvement in IMRT-treated nasopharyngeal carcinoma patients

OBJECTIVES: This retrospective study reassessed nasopharyngeal carcinoma (NPC) patients treated with intensity-modulated radiation therapy (IMRT), to determine the significance how magnetic resonance imaging (MRI)-derived masticator space involvement (MSI) affected patients’ prognosis. METHODS: One thousand one hundred ninety seven NPC patients who had complete set of MRI and medical records were enrolled. Basing on their MRI findings, the T-categories of tumors were identified according to the seventh edition of American Joint Committee on Cancer staging system, which considers MSI a prognostic indicator for NPCs. Rates of overall survival (OS), local relapse-free survival (LRFS), regional relapse-free survival (RRFS) and distant metastasis-free survival (DMFS) were analyzed by the Kaplan-Meier method, and the Log-Rank test compared their differences. Cox regression analysis was employed to evaluate various prognostic factors systematically. Statistical analyses were conducted with SPSS 18.0 software, P value < 0.05 was considered statistically significant. RESULTS: Medial pterygoid muscle (MPM) was involved in 283 (23.64 %) cases, of which lateral pterygoid muscle (LPM) was concurrently affected in 181 (15.12 %) and infratemporal fossa (ITF) in 19 (1.59 %). Generally, MSI correlated with an OS, LRFS, and DMFS consistent with a T4-stage diagnosis (P > 0.05). Although different degrees of MSI presented a similar OS and DMFS (P > 0.1), tumors involving LPM had a relatively poorer LRFS than those affected the MPM only (P = 0.027), even for subgroup of patients composed of T3 and T4 classifications (P = 0.035). A tumor involving MPM brought an LRFS consistent with a T2 or T3-stage disease (P > 0.1). If the tumor affected LPM or ITF concurrently, the survival outcomes were more consistent with a T4-stage disease (P > 0.1). Nevertheless, compared to tumor infiltrating MPM, those invading LPM or ITF more frequently spread into other concurrent sites that earned higher T-staging categories. Moreover, multivariate analyses indicated the degree of MSI was a significant prognostic factor for the OS of NPCs (P = 0.036). CONCLUSIONS: Degree of MSI is a significant prognosticator for the OS of IMRT-treated NPCs, and the prognosis of patients with lateral MSI extension (LPM and ITF) were shown to be significantly worse than those affected only MPM or the T3-stage disease. Thus, it is highly recommended that lateral MSI extension be a higher T-staging category

Mild thermal treatment assists fungal preprocessing of softwood sawdust for production of fermentable sugar

Preheating with hot air at 85 - 125 degrees C was evaluated for its effectiveness in removing terpenes and terpenoids in softwood sawdust, thereby enhancing fungal preprocessing and subsequent saccharification of softwood-based mushroom substrates. Sawdust from pine (Pinus sylvestris L.) and spruce (Picea abies (L.) H. Karst.) was preheated prior to shiitake (Lentinula edodes (Berk.) Pegler) cultivation. Preheating removed up to 96 % of terpenes in pine- based substrates and up to 50 % in spruce-based substrates. Additionally, preheating decreased total terpenoids content in spruce by up to 78 %. For the pine-based substrate, the mild heating generally led to faster colonisation and improved mushroom yield, with the fastest mycelia colonisation and highest yield observed for 105 degrees C treatment. This temperature was associated with the lowest content of total terpenes and absence of major monoterpenes. The content of terpenes and terpenoids continued to decrease during cultivation, alongside fungal degradation of lignocellulose. As a result of more extensive lignin degradation, the enzymatic digestibility of cellulose was higher for spruce-based spent mushroom substrate than for pine-based one (up to 89 % vs. 49 % conversion). Enzymatic digestibility showed a negative correlation with the alpha-pinene content, and a positive correlation with increasing preheating temperatures

Analysis of weighted co-regulatory networks in maize provides insights into new genes and regulatory mechanisms related to inositol phosphate metabolism

Sub-network 1 and 2 of “magenta2”, node annotation. (XLSX 10 kb

Multi-level Explanation of Deep Reinforcement Learning-based Scheduling

Dependency-aware job scheduling in the cluster is NP-hard. Recent work shows that Deep Reinforcement Learning (DRL) is capable of solving it. It is difficult for the administrator to understand the DRL-based policy even though it achieves remarkable performance gain. Therefore the complex model-based scheduler is not easy to gain trust in the system where simplicity is favored. In this paper, we give the multi-level explanation framework to interpret the policy of DRL-based scheduling. We dissect its decision-making process to job level and task level and approximate each level with interpretable models and rules, which align with operational practices. We show that the framework gives the system administrator insights into the state-of-the-art scheduler and reveals the robustness issue in regards to its behavior pattern.Comment: Accepted in the MLSys'22 Workshop on Cloud Intelligence / AIOp

Functional linear regression: dependence and error contamination

Functional linear regression is an important topic in functional data analysis. It is commonly assumed that samples of the functional predictor are independent realizations of an underlying stochastic process, and are observed over a grid of points contaminated by iid measurement errors. In practice, however, the dynamical dependence across different curves may exist and the parametric assumption on the error covariance structure could be unrealistic. In this article, we consider functional linear regression with serially dependent observations of the functional predictor, when the contamination of the predictor by the white noise is genuinely functional with fully nonparametric covariance structure. Inspired by the fact that the autocovariance function of observed functional predictors automatically filters out the impact from the unobservable noise term, we propose a novel autocovariance-based generalized method-of-moments estimate of the slope function. We also develop a nonparametric smoothing approach to handle the scenario of partially observed functional predictors. The asymptotic properties of the resulting estimators under different scenarios are established. Finally, we demonstrate that our proposed method significantly outperforms possible competing methods through an extensive set of simulations and an analysis of a public financial dataset

Enabling efficient bioconversion of birch biomass by Lentinula edodes regulatory roles of nitrogen and bark additions on mushroom production and cellulose saccharification

Pretreatment with edible white-rot fungi has advantages in low inputs of energy and chemicals for reducing the recalcitrance of woody biomass for bioethanol production while harvesting protein-rich food. The effectiveness of fungal pretreatment may vary with substrate composition. In this study, birch with or without bark and nitrogen additives were experimentally studied for their effects on shiitake production, substrate lignocellulosic degradation and enzymatic convertibility with cellulolytic enzymes. Whey was added as protein nitrogen and led to successful outcomes, while non-protein nitrogen urea and ammonium-nitrate resulted in mortality of fungal mycelia. The mushroom yields of one harvest were generally comparable between the treatments, averaging 651 g fresh weight per kilogram dry substrate, and high enough as to be profitable. Nitrogen loading (0.5-0.8%, dry mass) negatively affected lignin degradation and enzymatic convertibility and prolonged cultivation/pretreatment time. The added bark (0-20%) showed quadratic correlation with degradation of lignin, xylan and glucan as well as enzymatic digestibility of glucan. Nitrogen loading of < 0.6% led to maximal mass degradation of xylan and lignin at bark ratios of 4-9% and 14-19%, respectively, peak saccharification of glucan at 6-12% and the shortest pretreatment time at 8-13% bark. The designed substrates resulted in 19-35% of glucan mass loss after fungal pretreatment, less than half of the previously reported values. Nitrogen and bark additions can regulate lignocellulose degradation and saccharification of birch-based substrates. The designed substrate composition could considerably reduce cellulose consumption during fungal pretreatment, thus improving bioconversion efficiency

Shiitake cultivation as biological preprocessing of lignocellulosic feedstocks – Substrate changes in crystallinity, syringyl/guaiacyl lignin and degradation-derived by-products

Formulation of substrates based on three hardwood species combined with modulation of nitrogen content by whey addition (0–2%) was investigated in an experiment designed in D-optimal model for their effects on biological preprocessing of lignocellulosic feedstock by shiitake mushroom (Lentinula edodes) cultivation. Nitrogen loading was shown a more significant role than wood species for both mushroom production and lignocellulose degradation. The fastest mycelial colonization occurred with no nitrogen supplementation, but the highest mushroom yields were achieved when 1% whey was added. Low nitrogen content resulted in increased delignification and minimal glucan consumption. Delignification was correlated with degradation of syringyl lignin unit, as indicated by a significant reduction (41.5%) of the syringyl-to-guaiacyl ratio after cultivation. No significant changes in substrate crystallinity were observed. The formation of furan aldehydes and aliphatic acids was negligible during the pasteurization and fungal cultivation, while the content of soluble phenolics increased up to seven-fold.publishedVersio

Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas

DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 cancer types. Mutations with accompanying loss of heterozygosity were observed in over 1/3 of DDR genes, including TP53 and BRCA1/2. Other prevalent alterations included epigenetic silencing of the direct repair genes EXO5, MGMT, and ALKBH3 in ∼20% of samples. Homologous recombination deficiency (HRD) was present at varying frequency in many cancer types, most notably ovarian cancer. However, in contrast to ovarian cancer, HRD was associated with worse outcomes in several other cancers. Protein structure-based analyses allowed us to predict functional consequences of rare, recurrent DDR mutations. A new machine-learning-based classifier developed from gene expression data allowed us to identify alterations that phenocopy deleterious TP53 mutations. These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy