AND Logic-Gate-Based Dual-Locking Probe System for the Sensitive Detection of microRNA and APE1.

MicroRNA (miRNA) and apurinic/apyrimidinic endonuclease 1 (APE1) have been reported to be closely associated with cancers, making them potential crucial biomarkers and therapeutic targets. However, focusing on the detection of a single target is not conducive to the diagnosis and prognosis assessment of diseases. In this study, an AND logic-gate-based dual-locking hairpin-mediated catalytic hairpin assembly (DL-CHA) was developed for sensitive and specific detection of microRNA and APE1. By addition of a lock to each of the hairpins, with APE1 and microRNA serving as keys, fluorescence signals could only be detected in the presence of simultaneous stimulation by APE1 and miRNA-224. This indicated that the biosensor could operate as an AND logic gate. DL-CHA exhibited advantages such as a low background, rapid response, and high logic capability. Therefore, the biosensor serves as a novel approach to cancer diagnosis with significant potential applications.

DNA-based molecular classifiers for the profiling of gene expression signatures.

Although gene expression signatures offer tremendous potential in diseases diagnostic and prognostic, but massive gene expression signatures caused challenges for experimental detection and computational analysis in clinical setting. Here, we introduce a universal DNA-based molecular classifier for profiling gene expression signatures and generating immediate diagnostic outcomes. The molecular classifier begins with feature transformation, a modular and programmable strategy was used to capture relative relationships of low-concentration RNAs and convert them to general coding inputs. Then, competitive inhibition of the DNA catalytic reaction enables strict weight assignment for different inputs according to their importance, followed by summation, annihilation and reporting to accurately implement the mathematical model of the classifier. We validated the entire workflow by utilizing miRNA expression levels for the diagnosis of hepatocellular carcinoma (HCC) in clinical samples with an accuracy 85.7%. The results demonstrate the molecular classifier provides a universal solution to explore the correlation between gene expression patterns and disease diagnostics, monitoring, and prognosis, and supports personalized healthcare in primary care.

Indole alkaloids from endophytic fungus Robillarda sessilis and their antibacterial activity.

Three undescribed indole alkaloids, fusarindoles F and G (1 and 2), and chlamydosporin B (3), together with five known compounds (4-8) were isolated from Robillarda sessilis. Their structures were elucidated based on NMR, UV, HRESIMS, and ECD calculation. Fusarindole F (1) own unusual asymmetric bis-indole structure. Compounds 5, 6, 7 exhibited moderate antibacterial activity against methicillin-resistant Staphylococcus aureus with a MIC value of 12.5 µg/mL. According to molecular docking experiment, the target proteins of compound 7 against methicillin-resistant S. aureus may be ELANE, MAOB and STAT3.

Building a stable and robust anti-interference DNA dissipation system by eliminating the accumulation of systemic specified errors.

BACKGROUND: The emergence of DNA nanotechnology has enabled the systematic design of diverse bionic dissipative behaviors under the precise control of nucleic acid nanodevices. Nevertheless, when compared to the dissipation observed in robust living systems, it is highly desirable to enhance the anti-interference for artificial DNA dissipation to withstand perturbations and facilitate repairs within the complex biological environments. RESULTS: In this study, we introduce strategically designed "trash cans" to facilitate kinetic control over interferences, transforming the stochastic binding of individual components within a homogeneous solution into a competitive binding process. This approach effectively eliminates incorrect binding and the accumulation of systemic interferences while ensuring a consistent pattern of energy fluctuation from response to silence. Remarkably, even in the presence of numerous interferences differing by only one base, we successfully achieve complete system reset through multiple cycles, effectively restoring the energy level to a minimum. SIGNIFICANCE: The system was able to operate stably without any adverse effect under conditions of irregular interference, high-abundance interference, and even multiplex interferences including DNA and RNA crosstalk. This work not only provides an effective paradigm for constructing robust DNA dissipation systems but also greatly broadens the potential of DNA dissipation for applications in high-precision molecular recognition and complex biological reaction networks.

Homocysteine levels in first-episode patients with psychiatric disorders.

A high homocysteine (Hcy) level is a risk factor for schizophrenia, depression, and bipolar disorder. However, the role of hyperhomocysteinemia as either an independent factor or an auxiliary contributor to specific psychiatric symptoms or disorders remains unclear. This study aimed to examine Hcy levels in first-episode inpatients with psychotic symptoms and various psychiatric diseases to elucidate the association between Hcy levels and psychiatric disorders. This study enrolled 191 patients (aged 18-40 years) with psychiatric disorders. Seventy-five patients were diagnosed with schizophrenia, 48 with acute and transient psychotic disorders, 36 with manic episodes with psychosis, 32 with major depressive episodes with psychosis, and 56 healthy controls. Serum Hcy levels were measured using the enzyme cycle method. A Hcy concentration level of > 15 µmol/L was defined as hyperhomocysteinemia. Hcy levels were significantly higher in first-episode patients with psychiatric disorders compared to healthy controls (5.99 ± 3.60 vs. 19.78 ± 16.61 vs. 15.50 ± 9.08 vs. 20.00 ± 11.33 vs. 16.22 ± 12.06, F = 12.778, P < 0.001). Hcy levels were significantly higher in males with schizophrenia, acute and transient psychotic disorder, and major depressive disorder but not in mania [schizophrenia, (t = -4.727, P < 0.001); acute and transient psychotic disorders, (t = -3.389, P = 0.001); major depressive episode with psychosis, (t = -3.796, P < 0.001); manic episodes with psychosis, (t = -1.684, P = 0.101)]. However, serum Hcy levels were not significantly different among the psychiatric disorder groups (F = 0.139, P = 0.968). Multivariate linear regression showed that males had an increased risk for homocysteinemia. (95% CI = 8.192-15.370, P < 0.001). These results suggest that first-episode patients with psychiatric disorders have higher Hcy levels than in the general population, and men are at greater risk for psychiatric disorders. In conclusion, elevated Hcy levels may contribute to the pathogenesis of first-episode patients with psychotic symptoms.

Multi modality fusion transformer with spatio-temporal feature aggregation module for psychiatric disorder diagnosis.

Bipolar disorder (BD) is characterized by recurrent episodes of depression and mild mania. In this paper, to address the common issue of insufficient accuracy in existing methods and meet the requirements of clinical diagnosis, we propose a framework called Spatio-temporal Feature Fusion Transformer (STF2Former). It improves on our previous work - MFFormer by introducing a Spatio-temporal Feature Aggregation Module (STFAM) to learn the temporal and spatial features of rs-fMRI data. It promotes intra-modality attention and information fusion across different modalities. Specifically, this method decouples the temporal and spatial dimensions and designs two feature extraction modules for extracting temporal and spatial information separately. Extensive experiments demonstrate the effectiveness of our proposed STFAM in extracting features from rs-fMRI, and prove that our STF2Former can significantly outperform MFFormer and achieve much better results among other state-of-the-art methods.

Neural network establishes co-occurrence links between transformation products of the contaminant and the soil microbiome.

It remains challenging to establish reliable links between transformation products (TPs) of contaminants and corresponding microbes. This challenge arises due to the sophisticated experimental regime required for TP discovery and the compositional nature of 16S rRNA gene amplicon sequencing and mass spectrometry datasets, which can potentially confound statistical inference. In this study, we present a new strategy by combining the use of 2H-labeled Stable Isotope-Assisted Metabolomics (2H-SIAM) with a neural network-based algorithm (i.e., MMvec) to explore links between TPs of pyrene and the soil microbiome. The links established by this novel strategy were further validated using different approaches. Briefly, a metagenomic study provided indirect evidence for the established links, while the identification of pyrene degraders from soils, and a DNA-based stable isotope probing (DNA-SIP) study offered direct evidence. The comparison among different approaches, including Pearson's and Spearman's correlations, further confirmed the superior performance of our strategy. In conclusion, we summarize the unique features of the combined use of 2H-SIAM and MMvec. This study not only addresses the challenges in linking TPs to microbes but also introduces an innovative and effective approach for such investigations. Environmental Implication: Taxonomically diverse bacteria performing successive metabolic steps of the contaminant were firstly depicted in the environmental matrix.

Modified Unit-Mediated Strand Displacement Reactions for Direct Detection of Single Nucleotide Variants in Active Double-Stranded DNA.

Accurate identification of single nucleotide variants (SNVs) in key driver genes holds a significant value for disease diagnosis and treatment. Fluorescent probes exhibit tremendous potential in specific, high-resolution, and rapid detection of SNVs. However, additional steps are required in most post-PCR assays to convert double-stranded DNA (dsDNA) products into single-stranded DNA (ssDNA), enabling them to possess hybridization activity to trigger subsequent reactions. This process not only prolongs the complexity of the experiment but also introduces the risk of losing target information. In this study, we proposed two strategies for enriching active double-stranded DNA, involving PCR based on obstructive groups and cleavable units. Building upon this, we explored the impact of modified units on the strand displacement reaction (SDR) and assessed their discriminatory efficacy for mutations. The results showed that detection of low variant allele frequencies (VAF) as low as 0.1% can be achieved. The proposed strategy allowed orthogonal identification of 45 clinical colorectal cancer tissue samples with 100% specificity, and the results were generally consistent with sequencing results. Compared to existing methods for enriching active targets, our approach offers a more diverse set of enrichment strategies, characterized by the advantage of being simple and fast and preserving original information to the maximum extent. The objective of this study is to offer an effective solution for the swift and facile acquisition of active double-stranded DNA. We anticipate that our work will facilitate the practical applications of SDR based on dsDNA.

Novel fungal diphenyl ether biosynthetic gene clusters encode a promiscuous oxidase for elevated antibacterial activities.

Diphenyl ethers (DPEs) are produced by filamentous fungi using polyketide synthases (PKSs) directly, or via Cu oxidase-catalyzed oxidative rearrangements of benzophenone intermediates. Here, we use heterologous expression to reveal a third route towards DPEs in Preussia isomera that relies on an oxidative multienzyme cascade to convert a PKS-generated, ester-linked didepside to depsidones and further to DPEs, and apply comparative genomics to identify conserved biosynthetic gene clusters for this pathway in multiple fungi. The distribution of DPE products is modulated by the expression chassis upon pathway reconstitution. Among the post-PKS enzymes, the DpeH tyrosinase shows considerable substrate promiscuity towards synthetic DPE analogues. By creating hybrid enzymes with a DpeH orthologue from Aspergillus nidulans, we identify the C-terminal region of DpeH to alter substrate recognition. Our work highlights an evolutionarily conserved way to produce DPEs, and provides enzymatic tools to generate DPE analogues with broad spectrum antibiotic activity against multidrug-resistant human pathogens.