KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data.

Kinases as important enzymes can transfer phosphate groups from high-energy and phosphate-donating molecules to specific substrates and play essential roles in various cellular processes. Existing algorithms for kinase activity from phosphorylated proteomics data are often costly, requiring valuable samples. Moreover, methods to extract kinase activities from bulk RNA sequencing data remain undeveloped. In this study, we propose a computational framework KinPred-RNA to derive kinase activities from bulk RNA-sequencing data in cancer samples. KinPred-RNA framework, using the extreme gradient boosting (XGBoost) regression model, outperforms random forest regression, multiple linear regression, and support vector machine regression models in predicting kinase activities from cancer-related RNA sequencing data. Efficient gene signatures from the LINCS-L1000 dataset were used as inputs for KinPred-RNA. The results highlight its potential to be related to biological function. In conclusion, KinPred RNA constitutes a significant advance in cancer research by potentially facilitating the identification of cancer.

Integrated analysis of differently expressed microRNAs and mRNAs at different postnatal stages reveals intramuscular fat deposition regulation in goats (Capra hircus).

Intramuscular fat refers to the adipose tissue distributed in the muscle. It is an important indicator that affects the quality of goat meat, and can directly affect the tenderness and flavor of goat meat. Our previous study revealed the mRNA that may be crucial for intramuscular fat deposition during goat growth; however, how the microRNAs (miRNAs) are involved in the process is largely unclear. In the present study, a total of 401 known miRNAs and 120 goat novel miRNAs, including 110 differentially expressed (DE) miRNAs, were identified among longissimus dorsi from three growth stages (2, 9, and 24 months) by miRNA sequencing. Combining analysis of the DE mRNAs and DE miRNAs was then performed by miRDB and miRwalk, and miR-145-5p and FOXO1, miR-487b-3p, and PPARG coactivator 1 α (PPARGC1A), miR-345-3p, and solute carrier family 2 member 4 (SLC2A4), etc. were shown to closely associate with lipid metabolism, which was then validated by a correlation analysis. The final DE mRNAs were significantly enriched in fatty acid transmembrane transport, fatty acid homeostasis, apelin signaling pathway, glucagon signaling pathway, insulin signaling pathway, and AMPK signaling pathway by gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Besides, miR-145-5p showed a certain effect on goat intramuscular fat metabolism by acting on the possible target gene Forkhead Box O1 (FOXO1). These data provide some theoretical support for improving the quality of goat meat.

By Carrot or by Stick: The Influence of Encouraging and Discouraging Facial Feedback on Implicit Rule Learning.

Implicit learning refers to the process of unconsciously learning complex knowledge through feedback. Previous studies investigated the influences of different types of feedback (e.g., social and non-social feedback) on implicit learning. This study focused on the social information presented in the learning situation and tried to explore the effects of different social feedback on implicit rule learning. We assigned participants randomly into an encouraging facial feedback group (happy expression for correct answer, neutral but not negative expression for incorrect answer) and a discouraging facial feedback group (neutral but not happy expression for correct answer, negative expression for incorrect answer). The implicit learning task included four difficulty levels, and social feedback was presented in the learning phase but not the testing phase in two experiments. The only difference between the two experiments was that the sad face used as negative feedback in Experiment 1 was replaced with an angry face in Experiment 2 to enhance the ecological validity of the discouraging facial feedback group. These two experiments yielded consistent results: the performances in the encouraging facial feedback group were more accurate in both the learning and the testing phases at all difficulty levels. These findings indicated that the influence of encouraging social feedback for a better implicit learning achievement was stable and established a new groundwork for future research on incentive-based education, making it critical to investigate the impact of various forms of encouraging-based education on learning.

Resveratrol inhibits respiratory syncytial virus replication by targeting heparan sulfate proteoglycans.

Resveratrol, renowned as an antioxidant, also exhibits significant potential in combatting severe respiratory infections, particularly the respiratory syncytial virus (RSV). Nevertheless, the specific mechanism underlying its inhibition of RSV replication remains unexplored. Heparan sulfate proteoglycans (HSPGs) play a pivotal role as attachment factors for numerous viruses, offering a promising avenue for countering viral infections. Our research has unveiled that resveratrol effectively curbs RSV infection in a dose-dependent manner. Remarkably, resveratrol disrupts the early stages of RSV infection by engaging with HSPGs, rather than interacting with RSV surface proteins like fusion (F) protein and glycoprotein (G). Resveratrol's affinity appears to be predominantly directed towards the negatively charged sites on HSPGs, thus impeding the binding of viral receptors. In an in vivo study involving RSV-infected mice, resveratrol demonstrates its potential by ameliorating pulmonary pathology. This improvement is attributed to the inhibition of pro-inflammatory cytokine expression and a reduction in viral load within the lungs. Notably, resveratrol specifically alleviates inflammation characterized by an abundance of neutrophils in RSV-infected mice. In summation, our data first shows how resveratrol combats RSV infection through interactions with HSPGs, positioning it as a promising candidate for innovative drug development targeting RSV infections. Our study provides insight into the mechanism of resveratrol antiviral infection.

The Role of In-Group and Out-Group Facial Feedback in Implicit Rule Learning.

Implicit learning refers to the fact that people acquire new knowledge (structures or rules) without conscious awareness. Previous studies have shown that implicit learning is affected by feedback. However, few studies have investigated the role of social feedback in implicit learning concretely. Here, we conducted two experiments to explore how in-group and out-group facial feedback impact different difficulty levels of implicit rule learning. In Experiment 1, the Chinese participants in each group could only see one type of facial feedback, i.e., either in-group (East Asian) or out-group (Western) faces, and learned the implicit rule through happy and sad facial expressions. The only difference between Experiment 2 and Experiment 1 was that the participants saw both the in-group and out-group faces before group assignment to strengthen the contrast between the two group identities. The results showed that only in Experiment 2 but not Experiment 1 was there a significant interaction effect in the accuracy of tasks between the difficulty levels and groups. For the lowest difficulty level, the learning accuracy of the in-group facial feedback group was significantly higher than that of the out-group facial feedback group, whereas this did not happen at the two highest levels of difficulty. In conclusion, when the contrast of group identities was highlighted, out-group feedback reduced the accuracy of the least difficult task; on the contrary, there was no accuracy difference between out-group and in-group feedback conditions. These findings have extensively important implications for our understanding of implicit learning and improving teaching achievement in the context of educational internationalization.

p53-regulated lncRNAs in cancers: from proliferation and metastasis to therapy.

Long non-coding RNAs (lncRNAs) have been identified as master gene regulators through various mechanisms such as transcription, translation, protein modification and RNA-protein complexes. LncRNA dysregulation is frequently associated with a variety of biological functions and human diseases including cancer. The p53 network is a key tumor-suppressive mechanism that transcriptionally activates target genes to suppress cellular proliferation in human malignancies. Recent research indicates that lncRNAs play an important role in the p53 signaling pathway. In this review, we summarize the current knowledge of lncRNAs in p53-relevant functions and provide an overview of how these altered lncRNAs contribute to tumor initiation and progression. We also discuss the association between lncRNA and up- or downstream genes of p53. These findings imply that lncRNAs can help identify cellular vulnerabilities that may prove to be promising potential biomarkers and therapeutic targets for cancer treatment.

Expression Variation of CPT1A Induces Lipid Reconstruction in Goat Intramuscular Precursor Adipocytes.

Intramuscular fat (IMF) deposition is one of the most important factors affecting meat quality and is closely associated with the expression of carnitine palmitoyl transferase 1A (CPT1A) which facilitates the transfer of long-chain fatty acids (LCFAs) into the mitochondria. However, the role of how CPT1A regulates the IMF formation remains unclear. Herein, we established the temporal expression profile of CPT1A during the differentiation of goat intramuscular precursor adipocytes. Functionally, the knockdown of CPT1A by siRNA treatment significantly increased the mRNA expression of adipogenic genes and promoted lipid deposition in goat intramuscular precursor adipocytes. Meanwhile, a CPT1A deficiency inhibited cell proliferation and promoted cell apoptosis significantly. CPT1A was then supported by the overexpression of CPT1A which significantly suppressed the cellular triglyceride deposition and promoted cell proliferation although the cell apoptosis also was increased. For RNA sequencing, a total of 167 differential expression genes (DEGs), including 125 upregulated DEGs and 42 downregulated DEGs, were observed after the RNA silencing of CPT1A compared to the control, and were predicted to enrich in the focal adhesion pathway, cell cycle, apoptosis and the MAPK signaling pathway by KEGG analysis. Specifically, blocking the MAPK signaling pathway by a specific inhibitor (PD169316) rescued the promotion of cell proliferation in CPT1A overexpression adipocytes. In conclusion, the expression variation of CPT1A may reconstruct the lipid distribution between cellular triglyceride deposition and cell proliferation in goat intramuscular precursor adipocyte. Furthermore, we demonstrate that CPT1A promotes the proliferation of goat adipocytes through the MAPK signaling pathway. This work widened the genetic regulator networks of IMF formation and delivered theoretical support for improving meat quality from the aspect of IMF deposition.

DeepAFP: An effective computational framework for identifying antifungal peptides based on deep learning.

Fungal infections have become a significant global health issue, affecting millions worldwide. Antifungal peptides (AFPs) have emerged as a promising alternative to conventional antifungal drugs due to their low toxicity and low propensity for inducing resistance. In this study, we developed a deep learning-based framework called DeepAFP to efficiently identify AFPs. DeepAFP fully leverages and mines composition information, evolutionary information, and physicochemical properties of peptides by employing combined kernels from multiple branches of convolutional neural network with bi-directional long short-term memory layers. In addition, DeepAFP integrates a transfer learning strategy to obtain efficient representations of peptides for improving model performance. DeepAFP demonstrates strong predictive ability on carefully curated datasets, yielding an accuracy of 93.29% and an F1-score of 93.45% on the DeepAFP-Main dataset. The experimental results show that DeepAFP outperforms existing AFP prediction tools, achieving state-of-the-art performance. Finally, we provide a downloadable AFP prediction tool to meet the demands of large-scale prediction and facilitate the usage of our framework by the public or other researchers. Our framework can accurately identify AFPs in a short time without requiring significant human and material resources, and hence can accelerate the development of AFPs as well as contribute to the treatment of fungal infections. Furthermore, our method can provide new perspectives for other biological sequence analysis tasks.

[Diagnosis and treatment of rare malignant temporal bone tumors].

Objective:To analyze the diagnosis, treatment and prognosis of patients with rare malignant tumors of the temporal bone. Methods:Four cases of rare temporal bone malignant tumors in our hospital between March 2014 and December 2020 were reviewed, including two cases of chondrosarcoma, one case of fibrosarcoma and one case of endolymphatic cystic papillary adenocarcinoma. There were three males and one female, ages between 28 and 56 years at the time of surgery. Common symptoms included hearing loss, facioplegia, tinnitus, and headache. All patients underwent imaging examinations to evaluate the extent of the lesions. Tumors were removed by subtotal temporal bone resection or infratemporal fossa approach, and postoperative adjuvant radiotherapy was applied if necessary. Results:One of the two chondrosarcoma patients was cured by complete resection of the tumor for 75 months, the other one recurred after the first excision of the tumor and underwent infratemporal fossa approach resection of skull base mass again with no recurrence found yet for 112 months. One patient with fibrosarcoma survived for 28 months after surgery with a positive margin and post-operative radiotherapy. One patient with endolymphatic cystic papillary adenocarcinoma recurred 12 months after subtotal lithotomy, and underwent subtotal temporal bone resection again, combined with radiotherapy. No recurrence was found for 63 months. Conclusion:The incidence of rare temporal bone malignant tumors is extremely low, the location is hidden, and the symptoms are atypical. Attention should be paid for early detection and early treatment. Surgical resection is the main treatment, and radiotherapy can be supplemented in the advanced stage or with a positive margin.

Long non-coding RNA HIF1A-As2 and MYC form a double-positive feedback loop to promote cell proliferation and metastasis in KRAS-driven non-small cell lung cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide. KRAS is the main oncogenic driver in lung cancer that can be activated by gene mutation or amplification, but whether long non-coding RNAs (lncRNAs) regulate its activation remains unknown. Through gain and loss of function approaches, we identified that lncRNA HIF1A-As2, a KRAS-induced lncRNA, is required for cell proliferation, epithelial-mesenchymal transition (EMT) and tumor propagation in non-small cell lung cancer (NSCLC) in vitro and in vivo. Integrative analysis of HIF1A-As2 transcriptomic profiling reveals that HIF1A-As2 modulates gene expression in trans, particularly regulating transcriptional factor genes including MYC. Mechanistically, HIF1A-As2 epigenetically activates MYC by recruiting DHX9 on MYC promoter, consequently stimulating the transcription of MYC and its target genes. In addition, KRAS promotes HIF1A-As2 expression via the induction of MYC, suggesting HIF1A-As2 and MYC form a double-regulatory loop to strengthen cell proliferation and tumor metastasis in lung cancer. Inhibition of HIF1A-As2 by LNA GapmeR antisense oligonucleotides (ASO) significantly improves sensitization to 10058-F4 (a MYC-specific inhibitor) and cisplatin treatment in PDX and KRASLSLG12D-driven lung tumors, respectively.

Integrated metabolomics and lipidomics analyses suggest the temperature-dependent lipid desaturation promotes aflatoxin biosynthesis in Aspergillus flavus.

Temperature is one of the main factors affecting aflatoxin (AF) biosynthesis in Aspergillus flavus. Previous studies showed that AF biosynthesis is elevated in A. flavus at temperatures between 28°C-30°C, while it is inhibited at temperatures above 30°C. However, little is known about the metabolic mechanism underlying temperature-regulated AF biosynthesis. In this study, we integrated metabolomic and lipidomic analyses to investigate the endogenous metabolism of A. flavus across 6 days of mycelia growth at 28°C (optimal AF production) and 37°C (no AF production). Results showed that both metabolite and lipid profiles were significantly altered at different temperatures. In particular, metabolites involved in carbohydrate and amino acid metabolism were up-regulated at 37°C on the second day but down-regulated from days three to six. Moreover, lipidomics and targeted fatty acids analyses of mycelia samples revealed a distinct pattern of lipid species and free fatty acids desaturation. High degrees of polyunsaturation of most lipid species at 28°C were positively correlated with AF production. These results provide new insights into the underlying metabolic changes in A. flavus under temperature stress.

Environmentally Friendly and Broad-Spectrum Antibacterial Poly(hexamethylene guanidine)-Modified Polypropylene and Its Antifouling Application.

Biological fouling is one of the main reasons that limits the application of traditional polypropylene (PP) fishing nets in aquaculture. Here, a new environmentally friendly and broad-spectrum antibacterial agent called cationic poly(hexamethylene guanidine) (PHMG) was grafted onto PP molecular chains via permanent chemical bonding to inhibit the biological fouling. The antibacterial monofilaments were obtained by blending different contents of PP-g-PHMG with PP by melt spinning. FTIR results found PHMG to be stably present in the mixed monofilaments after high-temperature melt spinning molding. The crystallinity, relaxation behavior, mechanical properties, water absorptivity, and antibacterial and antifouling efficiencies of the PP-g-PHMG/PP blends were strongly dependent on PP-g-PHMG. The crystallinity increased with increasing PP-g-PHMG content. Adding PP-g-PHMG improved the breaking strength, knotting strength, and elongation at the break for all ratios of PP-g-PHMG/PP blends. However, the water absorption caused by PHMG is low, ranging between 2.48% and 3.45% for the PP-g-PHMG/PP monofilaments. The monofilaments showed excellent nonleaching antimicrobial activities against Staphylococcus aureus and Escherichia coli. The electrostatic adsorption of the negatively charged bacteria and the destruction of their cell membrane allowed the growth inhibition to reach 99.69% with a PP-g-PHMG content of 40%. The marine fish farming experiment also showed a long-term antifouling effect.

Dual-signal fluorescent test strips for spoilage sensing of packaged seafood: Visual monitoring of volatile basic nitrogens.

With the food safety issues abounding, exploring reliable and efficient methods for evaluating food safety is crucial. Herein, a ratiometric test strip was proposed by using green-yellow fluorescent d-penicillamine capped silver nanocluster (DPA-AgNCs) as indicator and red-emitting bimetallic gold/silver nanoclusters (AuAgNCs) as an internal reference, providing a real-time and visual monitoring system for food freshness. Results showed that the as-prepared DPA-AgNCs displayed an excellent response and good sensitivity for volatile basic nitrogens (VBNs), with a limit of detection (LOD) of 0.51 µM and 0.08 ppm for spermidine and ammonia hydroxide, respectively. Subsequently, a ratiometric test strip was developed to visually monitor ammonia vapour, displaying an obvious fluorescence colour variation from mustard to deep-red. Moreover, the presented ratiometric test strip was successfully applied for non-contact and visual evaluating and monitoring VBNs in the shrimp sample, showing high potential for in-situ monitoring.

Simultaneous sensing of ammonia and temperatures using a dual-mode freshness indicator based on Au/Cu nanoclusters for packaged seafood.

Seafood is highly perishable and monitoring its freshness this thus an important issue. For the first time, the current study developed a dual-mode freshness indicator based on d-penicillamine capped bimetallic gold/copper nanoclusters (DPA-Au/CuNCs) as a response probe for simultaneous monitoring of ammonia and temperatures to assess seafood freshness. Results indicated that the prepared DPA-Au/CuNCs have good sensitivity toward ammonia, with a limit of detection of 0.14 ppm. The indicator as a gas sensor for ammonia vapour detection exhibited highly recognizable fluorescence colour changes and the variations from white to yellow were observed with increasing storage temperature under natural light. For confirming its practical applications, the indicator was used to simultaneously monitor ammonia and temperatures during the storage of shrimp and fish, showing good potential for practical applications in evaluating seafood freshness for the food industry.

Diel dynamics of multi-omics in elkhorn fern provide new insights into weak CAM photosynthesis.

Crassulacean acid metabolism (CAM) has high water-use efficiency (WUE) and is widely recognized to have evolved from C3 photosynthesis. Different plant lineages have convergently evolved CAM, but the molecular mechanism that underlies C3-to-CAM evolution remains to be clarified. Platycerium bifurcatum (elkhorn fern) provides an opportunity to study the molecular changes underlying the transition from C3 to CAM photosynthesis because both modes of photosynthesis occur in this species, with sporotrophophyll leaves (SLs) and cover leaves (CLs) performing C3 and weak CAM photosynthesis, respectively. Here, we report that the physiological and biochemical attributes of CAM in weak CAM-performing CLs differed from those in strong CAM species. We investigated the diel dynamics of the metabolome, proteome, and transcriptome in these dimorphic leaves within the same genetic background and under identical environmental conditions. We found that multi-omic diel dynamics in P. bifurcatum exhibit both tissue and diel effects. Our analysis revealed temporal rewiring of biochemistry relevant to the energy-producing pathway (TCA cycle), CAM pathway, and stomatal movement in CLs compared with SLs. We also confirmed that PHOSPHOENOLPYRUVATE CARBOXYLASE KINASE (PPCK) exhibits convergence in gene expression among highly divergent CAM lineages. Gene regulatory network analysis identified candidate transcription factors regulating the CAM pathway and stomatal movement. Taken together, our results provide new insights into weak CAM photosynthesis and new avenues for CAM bioengineering.

A ratiometric fluorescent tag based on dual-emissive hydrophobic carbon dots for in-situ monitoring of seafood freshness.

A ratiometric fluorescent tag based on dual-emissive hydrophobic carbon dots (H-CDs) with well volatile base nitrogens (VBNs)-response was fabricated, offering the in-situ, real-time, and visual evaluation of seafood freshness. The presented H-CDs aggregates exhibited a sensitive response to VBNs, with a limit of detection of 7 µM and 137 ppb for spermine and ammonia hydroxide, respectively. Subsequently, a ratiometric tag was successfully fabricated by depositing dual-emissive CDs on cotton paper. Upon the treatment with ammonia vapour, the presented tag exhibited highly recognizable colour variations from red to blue under UV light. In addition, the cytotoxicity was explored by CCK8 assay, and the results proved the nontoxicity of the presented H-CDs. To our knowledge, this is the first ratiometric tag based on dual-emissive CDs with aggregation-induced emission properties for recognition of VBNs and seafood freshness in a real-time and visual manner.

Multikink quantile regression for longitudinal data with application to progesterone data analysis.

Motivated by investigating the relationship between progesterone and the days in a menstrual cycle in a longitudinal study, we propose a multikink quantile regression model for longitudinal data analysis. It relaxes the linearity condition and assumes different regression forms in different regions of the domain of the threshold covariate. In this paper, we first propose a multikink quantile regression for longitudinal data. Two estimation procedures are proposed to estimate the regression coefficients and the kink points locations: one is a computationally efficient profile estimator under the working independence framework while the other one considers the within-subject correlations by using the unbiased generalized estimation equation approach. The selection consistency of the number of kink points and the asymptotic normality of two proposed estimators are established. Second, we construct a rank score test based on partial subgradients for the existence of the kink effect in longitudinal studies. Both the null distribution and the local alternative distribution of the test statistic have been derived. Simulation studies show that the proposed methods have excellent finite sample performance. In the application to the longitudinal progesterone data, we identify two kink points in the progesterone curves over different quantiles and observe that the progesterone level remains stable before the day of ovulation, then increases quickly in 5 to 6 days after ovulation and then changes to stable again or drops slightly.

Effects of Surgical Timing of Facial Nerve Decompression for Patients With Severe Bell's Palsy.

Context: Bell's palsy is a form of idiopathic, facial nerve palsy. Initial treatment includes the use of oral corticosteroids and/or antiviral agents, but facial paralysis may persist. Some surgeons suggest that surgical decompression of the facial nerve can be a beneficial, but the optimal surgical approach, extent of nerve decompression, and timing of surgery remain unclear. Objective: This study intended to evaluate the efficacy of delayed, facial nerve decompression for severe Bell's palsy (BP) and to explore the relationship of opportunity timing for operations, with postoperative recovery for facial nerve function. Design: The research team performed a retrospective study. Setting: The study took place at Beijing Tiantan Hospital of Capital Medical University in Beijing, China. Participants: Participants were 45 patients who had been diagnosed with BP between 2015 and 2021 and who had undergone facial nerve decompression using the transmastoid approach, between 30 and 180 days after the onset of BP. According to the operation's timing, the research team divided the participants into three groups, consisting of participants who underwent surgery: (1) at 30-60-days after BP onset-19 participants, (2) at 61-90 days after BP onset-18 participants, and (3) at more than 90 days after BP onset-8 participants. Outcome Measures: The research team: (1) analyzed participants' demographic and preoperative and postoperative clinical characteristics, (2) compared the surgical outcomes with participants' House-Brackmann (HB) scales, and (3) analyzed the factors affecting the recovery of facial nerve function using logistic regression. Results: Decompression surgery was effective for 29 participants (64.4%), with similar rates for participants who underwent surgery after 30-60 days (73.7%) and 61-90 days (77.8%), but the surgery' success was significantly higher for those groups than for participants who underwent surgery after >90 days (12.5%), with P = .008 and P = .003, respectively. Multivariate logistic regression analysis showed that disease duration was the only factor significantly associated with the effectiveness of surgery (odds ratio = 120.337; 95% confidence interval 2.997-4832.267, P = .011). Conclusions: For patients with severe Bell's palsy with ineffective conservative treatment, surgery performed 30 to 90 days after the onset of paralysis can have therapeutic benefits, whereas surgery performed after 3 months is relatively ineffective.

Linolenic Acid-Derived Oxylipins Inhibit Aflatoxin Biosynthesis in Aspergillus flavus through Activation of Imizoquin Biosynthesis.

Oxylipins play important signaling roles in aflatoxin (AF) biosynthesis in Aspergillus flavus. We previously showed that exogenous supply of autoxidated linolenic acid (AL) inhibited AF biosynthesis in A. flavus via oxylipins, but the molecular mechanism is still unknown. Here, we performed multiomics analyses of A. flavus grown in media with or without AL. Targeted metabolite analyses and quantitative reverse transcription (qRT)-polymerase chain reaction (PCR) showed that the imizoquin (IMQ) biosynthetic pathway was distinctly upregulated in the presence of AL. 13C-glucose labeling confirmed in parallel that the tricarboxylic acid cycle was also enhanced by AL, consistent with observed increases in mycelial growth. Moreover, we integrated thermal proteome profiling and molecular dynamics simulations to identify a potential receptor of AL; AL was found to interact with a transporter (ImqJ) located in the IMQ gene cluster, primarily through hydrophobic interactions. Further analyses of strains with an IMQ pathway transcription factor overexpressed or knocked out confirmed that this pathway was critical for AL-mediated inhibition of AF biosynthesis. Comparison of 22 assembled A. flavus and Aspergillus oryzae genomes showed that genes involved in the IMQ pathway were positively selected in A. oryzae. Taken together, the results of our study provide novel insights into oxylipin-mediated regulation of AF biosynthesis and suggest potential methods for preventing AF contamination of crops.

Identification of Nonlinear Soil Properties from Downhole Array Data Using a Bayesian Model Updating Approach.

An accurate seismic response simulation of civil structures requires accounting for the nonlinear soil response behavior. This, in turn, requires understanding the nonlinear material behavior of in situ soils under earthquake excitations. System identification methods applied to data recorded during earthquakes provide an opportunity to identify the nonlinear material properties of in situ soils. In this study, we use a Bayesian inference framework for nonlinear model updating to estimate the nonlinear soil properties from recorded downhole array data. For this purpose, a one-dimensional finite element model of the geotechnical site with nonlinear soil material constitutive model is updated to estimate the parameters of the soil model as well as the input excitations, including incident, bedrock, or within motions. The seismic inversion method is first verified by using several synthetic case studies. It is then validated by using measurements from a centrifuge test and with data recorded at the Lotung experimental site in Taiwan. The site inversion method is then applied to the Benicia-Martinez geotechnical array in California, using the seismic data recorded during the 2014 South Napa earthquake. The results show the promising application of the proposed seismic inversion approach using Bayesian model updating to identify the nonlinear material parameters of in situ soil by using recorded downhole array data.