Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis

<p>Abstract</p> <p>Background</p> <p>Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public.</p> <p>Results</p> <p>In this paper, we report an open source software tool, Automics, which is specifically designed for NMR-based metabonomics studies. Automics is a highly integrated platform that provides functions covering almost all the stages of NMR-based metabonomics studies. Automics provides high throughput automatic modules with most recently proposed algorithms and powerful manual modules for 1D NMR spectral processing. In addition to spectral processing functions, powerful features for data organization, data pre-processing, and data analysis have been implemented. Nine statistical methods can be applied to analyses including: feature selection (Fisher's criterion), data reduction (PCA, LDA, ULDA), unsupervised clustering (K-Mean) and supervised regression and classification (PLS/PLS-DA, KNN, SIMCA, SVM). Moreover, Automics has a user-friendly graphical interface for visualizing NMR spectra and data analysis results. The functional ability of Automics is demonstrated with an analysis of a type 2 diabetes metabolic profile.</p> <p>Conclusion</p> <p>Automics facilitates high throughput 1D NMR spectral processing and high dimensional data analysis for NMR-based metabonomics applications. Using Automics, users can complete spectral processing and data analysis within one software package in most cases. Moreover, with its open source architecture, interested researchers can further develop and extend this software based on the existing infrastructure.</p

SyzTrust: State-aware Fuzzing on Trusted OS Designed for IoT Devices

Trusted Execution Environments (TEEs) embedded in IoT devices provide a deployable solution to secure IoT applications at the hardware level. By design, in TEEs, the Trusted Operating System (Trusted OS) is the primary component. It enables the TEE to use security-based design techniques, such as data encryption and identity authentication. Once a Trusted OS has been exploited, the TEE can no longer ensure security. However, Trusted OSes for IoT devices have received little security analysis, which is challenging from several perspectives: (1) Trusted OSes are closed-source and have an unfavorable environment for sending test cases and collecting feedback. (2) Trusted OSes have complex data structures and require a stateful workflow, which limits existing vulnerability detection tools. To address the challenges, we present SyzTrust, the first state-aware fuzzing framework for vetting the security of resource-limited Trusted OSes. SyzTrust adopts a hardware-assisted framework to enable fuzzing Trusted OSes directly on IoT devices as well as tracking state and code coverage non-invasively. SyzTrust utilizes composite feedback to guide the fuzzer to effectively explore more states as well as to increase the code coverage. We evaluate SyzTrust on Trusted OSes from three major vendors: Samsung, Tsinglink Cloud, and Ali Cloud. These systems run on Cortex M23/33 MCUs, which provide the necessary abstraction for embedded TEEs. We discovered 70 previously unknown vulnerabilities in their Trusted OSes, receiving 10 new CVEs so far. Furthermore, compared to the baseline, SyzTrust has demonstrated significant improvements, including 66% higher code coverage, 651% higher state coverage, and 31% improved vulnerability-finding capability. We report all discovered new vulnerabilities to vendors and open source SyzTrust.Comment: To appear in the IEEE Symposium on Security and Privacy (IEEE S&P) 2024, San Francisco, CA, US

Acute cortical blindness caused by pre-eclampsia in the antepartum; posterior reversible encephalopathy syndrome (PRES

We present a case report of a patient presenting posterior reversible encephalopathy syndrome (PRES), a rare acute neurological condition associated with pre-eclampsia. A possible common aetiology and successful clinical management approach is reported

Design, synthesis, biological evaluation and docking study of 4-isochromanone hybrids bearing N-benzyl pyridinium moiety as dual binding site acetylcholinesterase inhibitors (part II)

A series of novel 4-isochromanone compounds bearing N-benzyl pyridinium moiety were designed and synthesized as acetylcholinesterase (AChE) inhibitors. The biological evaluation showed that most of the target compounds exhibited potent inhibitory activities against AChE. Among them, compound 1q possessed the strongest anti-AChE activity with an IC50 value of 0.15 nM and high AChE/BuChE selectivity (SI >5000). Moreover, compound 1q had low toxicity in normal nerve cells and was relatively stable in rat plasma. Together, the current finding may provide a new approach for the discovery of novel anti-Alzheimer’s disease agents

Design, synthesis, biological evaluation and docking study of 4-isochromanone hybrids bearing N-benzyl pyridinium moiety as dual binding site acetylcholinesterase inhibitors (part II)

A series of novel 4-isochromanone compounds bearing N-benzyl pyridinium moiety were designed and synthesized as acetylcholinesterase (AChE) inhibitors. The biological evaluation showed that most of the target compounds exhibited potent inhibitory activities against AChE. Among them, compound 1q possessed the strongest anti-AChE activity with an IC50 value of 0.15 nM and high AChE/BuChE selectivity (SI >5000). Moreover, compound 1q had low toxicity in normal nerve cells and was relatively stable in rat plasma. Together, the current finding may provide a new approach for the discovery of novel anti-Alzheimer’s disease agents

A 13-Gene Metabolic Prognostic Signature Is Associated With Clinical and Immune Features in Stomach Adenocarcinoma

Patients with advanced stomach adenocarcinoma (STAD) commonly show high mortality and poor prognosis. Increasing evidence has suggested that basic metabolic changes may promote the growth and aggressiveness of STAD; therefore, identification of metabolic prognostic signatures in STAD would be meaningful. An integrative analysis was performed with 407 samples from The Cancer Genome Atlas (TCGA) and 433 samples from Gene Expression Omnibus (GEO) to develop a metabolic prognostic signature associated with clinical and immune features in STAD using Cox regression analysis and least absolute shrinkage and selection operator (LASSO). The different proportions of immune cells and differentially expressed immune-related genes (DEIRGs) between high- and low-risk score groups based on the metabolic prognostic signature were evaluated to describe the association of cancer metabolism and immune response in STAD. A total of 883 metabolism-related genes in both TCGA and GEO databases were analyzed to obtain 184 differentially expressed metabolism-related genes (DEMRGs) between tumor and normal tissues. A 13-gene metabolic signature (GSTA2, POLD3, GLA, GGT5, DCK, CKMT2, ASAH1, OPLAH, ME1, ACYP1, NNMT, POLR1A, and RDH12) was constructed for prognostic prediction of STAD. Sixteen survival-related DEMRGs were significantly related to the overall survival of STAD and the immune landscape in the tumor microenvironment. Univariate and multiple Cox regression analyses and the nomogram proved that a metabolism-based prognostic risk score (MPRS) could be an independent risk factor. More importantly, the results were mutually verified using TCGA and GEO data. This study provided a metabolism-related gene signature for prognostic prediction of STAD and explored the association between metabolism and the immune microenvironment for future research, thereby furthering the understanding of the crosstalk between different molecular mechanisms in human STAD. Some prognosis-related metabolic pathways have been revealed, and the survival of STAD patients could be predicted by a risk model based on these pathways, which could serve as prognostic markers in clinical practice

Engineered Streptomyces lividans Strains for Optimal Identification and Expression of Cryptic Biosynthetic Gene Clusters

Streptomyces lividans is a suitable host for the heterologous expression of biosynthetic gene clusters (BGCs) from actinomycetes to discover “cryptic” secondary metabolites. To improve the heterologous expression of BGCs, herein we optimized S. lividans strain SBT5 via the stepwise integration of three global regulatory genes and two codon-optimized multi-drug efflux pump genes and deletion of a negative regulatory gene, yielding four engineered strains. All optimization steps were observed to promote the heterologous production of polyketides, non-ribosomal peptides, and hybrid antibiotics. The production increments of these optimization steps were additional, so that the antibiotic yields were several times or even dozens of times higher than the parent strain SBT5 when the final optimized strain, S. lividans LJ1018, was used as the heterologous expression host. The heterologous production of these antibiotics in S. lividans LJ1018 and GX28 was also much higher than in the strains from which the BGCs were isolated. S. lividans LJ1018 and GX28 markedly promoted the heterologous production of secondary metabolites, without requiring manipulation of gene expression components such as promoters on individual gene clusters. Therefore, these strains are well-suited as heterologous expression hosts for secondary metabolic BGCs. In addition, we successfully conducted high-throughput library expression and functional screening (LEXAS) of one bacterial artificial chromosome library and two cosmid libraries of three Streptomyces genomes using S. lividans GX28 as the library-expression host. The LEXAS experiments identified clones carrying intact BGCs sufficient for the heterologous production of piericidin A1, murayaquinone, actinomycin D, and dehydrorabelomycin. Notably, due to lower antibiotic production, the piericidin A1 BGC had been overlooked in a previous LEXAS screening using S. lividans SBT5 as the expression host. These results demonstrate the feasibility and superiority of S. lividans GX28 as a host for high-throughput screening of genomic libraries to mine cryptic BGCs and bioactive compounds