Search Results (35)

The triplex reciprocating drilling pump is a critical piece of equipment in drilling platforms, and the operational condition of its core component—the valve body—directly affects the pump’s performance and the stability of the entire system. Therefore, accurate prediction of the valve body’s Remaining Useful Life (RUL) is of great significance for ensuring the safe operation of drilling pumps and enabling predictive maintenance. However, achieving this goal involves two major challenges: (1) The complex degradation process of the valve body, which involves strong impact loads, nonlinear wear, and coupling effects between fluid and mechanical systems, makes it difficult to establish a stable degradation model and achieve accurate RUL prediction. (2) There is a lack of publicly available real-world datasets for research purposes. To address these challenges, we propose CEEMDAN-BWO-optimized Bidirectional LSTM for Remaining Useful Life prediction (CB²-RUL). The method first applies Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) to the raw vibration signals for decomposition and denoising, thereby improving signal stationarity and enhancing feature representation. Next, the Black Widow Optimization (BWO) algorithm is employed to automatically tune key hyperparameters of a Bidirectional Long Short-Term Memory (BiLSTM) network. Finally, the optimized BiLSTM captures the temporal evolution patterns of valve-body degradation and produces high-accuracy RUL estimates. Finally, to verify the effectiveness of the proposed approach, we constructed a real-world dataset named VB-Lifecycle, which comprises ten valve bodies from different positions within the equipment and spans the complete lifecycle from pristine condition to failure. Extensive experiments conducted on the VB-Lifecycle dataset demonstrate that the proposed method provides accurate RUL prediction for valve bodies. Full article

The role of alternative nucleic acid structures (ANS) in biology is an area of increasing interest. These non-canonical structures include the Z-DNA and Z-RNA duplexes (ZNA), the three-stranded triplex, the four-stranded G-quadruplex (GQ), and i-motifs. Previously, the biological relevance of ANS was dismissed. Their formation in vitro often required non-physiological conditions, and there was no genetic evidence for their function. Further, structural studies confirmed that sequence-specific transcription factors (TFs) bound B-DNA. In contrast, ANS are formed dynamically by a subset of repeat sequences, called flipons. The flip requires energy, but not strand cleavage. Flipons are enriched in promoters where they modulate transcription. Here, computational modeling based on AlphaFold V3 (AF3), under optimized conditions, reveals that known B-DNA-binding TFs also dock to ANS, such as ZNA and GQ. The binding of HLH and bZIP homodimers to Z-DNA is promoted by methylarginine modifications. Heterodimers only bind preformed Z-DNA. The interactions of TFs with ANS likely enhance genome scanning to identify cognate B-DNA-binding sites in active genes. Docking of TF homodimers to Z-DNA potentially facilitates the assembly of heterodimers that dissociate and are stabilized by binding to a cognate B-DNA motif. The process enables rapid discovery of the optimal heterodimer combinations required to regulate a nearby promoter. Full article

Computational and machine learning approaches play a pivotal role in identifying, characterizing, and targeting noncanonical DNA structures, including G-quadruplexes, Z-DNA, hairpins, and triplexes. These configurations play critical roles in maintaining genomic stability, facilitating DNA repair, and regulating chromatin organization. Although the human genome predominantly adopts the B DNA conformation, evidence indicates that non-B DNA forms exert significant influence on gene expression and disease development. This highlights the need for dedicated computational frameworks to systematically investigate these alternative structures. Machine learning model, encompassing supervised and unsupervised algorithms such as K Nearest Neighbors, Support Vector Machines, and deep learning architectures including Convolutional Neural Networks, have shown considerable potential in predicting sequence motifs predisposed to forming non-B DNA conformations. These predictive tools contribute to identifying genomic regions associated with disease susceptibility. Complementary bioinformatics platforms and molecular docking tools, notably Auto Dock, along with chemical libraries like ZINC, facilitate the virtual screening of small molecules targeting specific DNA structures. Stabilizers of G quadruplexes, exemplified by CX 5461, have demonstrated therapeutic promise in BRCA-deficient cancers, highlighting the translational impact of computational methods on drug discovery. Anticipating DNA structural shifts opens new avenues in personalized medicine for complex diseases, with computational chemistry and machine learning deepening our understanding of DNA topology and guiding smarter ligand design. The integrated approach proposed in this review addresses the previous studies performed in this field and highlights the current limitations in structural genomics and advances the development of precision therapeutics aligned with individual genomic profiles. Full article

This study offers a comprehensive overview of the scientific landscape surrounding computer-aided drug design (CADD) for triplex-forming oligonucleotides (TFOs) within antisense and antigene therapeutic strategies. A dual-method approach was used, combining bibliometric mapping of 6154 Scopus-indexed articles (1980–2023) to identify publication trends and intellectual networks, with a PRISMA 2020-guided systematic review of 62 experimental studies (2015–2024) from Scopus and Web of Science, after removing duplicates using AteneaSIRES. Results show the strong dominance and clinical maturity of antisense strategies, supported by 18 FDA/EMA/MHLW-approved drugs, whereas antigene approaches remain technically limited and underdeveloped. Antigene research has focused on triplex stability modeling and biophysical feasibility but faces challenges with poor biochemical stability, limited in vivo validation, and outdated methods. Meanwhile, antisense design benefits advanced CADD pipelines, including molecular dynamics and docking modeling. Based on these insights, we propose a practical, narrative roadmap as a methodological guide: integrating proven antisense design practices and providing actionable strategies to enhance antigene research, ultimately increasing the translational potential of therapeutic TFOs with solid mechanistic and translational support. Full article

RNA triple helices are relatively understudied, including their interactions with small molecules. In this study, we evaluated eight previously reported triplex-binding molecules (TBMs) for their functional effects on the premature and mature MALAT1 triple helix. Based on UV thermal denaturation experiments, the TBMs berberine, coralyne, sanguinarine, berenil, and neomycin selectively stabilize the Hoogsteen interface of the MALAT1 triple helix. Moreover, fisetin, luteolin, and quercetin were more sensitive to nucleotide composition, whereas berberine, coralyne, sanguinarine, and berenil were more sensitive to changes in the length of the major-groove triple helix. Most TBMs could not outcompete MALAT1 triple helix-binding proteins, except for neomycin. Surface plasmon resonance experiments demonstrated that berberine and sanguinarine display relatively quick association and dissociation binding profiles. Treating human colorectal carcinoma cells with each of the TBMs reduced MALAT1 levels by ~20–60%. This study demonstrates that TBMs broadly recognize the premature and mature MALAT1 triple helix but exhibit subtle sensitivities, suggesting that TBMs can be designed to selectively bind triple helices based on nucleotide composition, length, and structural context. Full article

The current study presents a multi-class, image-based classification of eight morphologically similar macroscopic Earthstar fungal species (Astraeus hygrometricus, Geastrum coronatum, G. elegans, G. fimbriatum, G. quadrifidum, G. rufescens, G. triplex, and Myriostoma coliforme) using deep learning and explainable artificial intelligence (XAI) techniques. For the first time in the literature, these species are evaluated together, providing a highly challenging dataset due to significant visual overlap. Eight different convolutional neural network (CNN) and transformer-based architectures were employed, including EfficientNetV2-M, DenseNet121, MaxViT-S, DeiT, RegNetY-8GF, MobileNetV3, EfficientNet-B3, and MnasNet. The accuracy scores of these models ranged from 86.16% to 96.23%, with EfficientNet-B3 achieving the best individual performance. To enhance interpretability, Grad-CAM and Score-CAM methods were utilised to visualise the rationale behind each classification decision. A key novelty of this study is the design of two hybrid ensemble models: EfficientNet-B3 + DeiT and DenseNet121 + MaxViT-S. These ensembles further improved classification stability, reaching 93.71% and 93.08% accuracy, respectively. Based on metric-based evaluation, the EfficientNet-B3 + DeiT model delivered the most balanced performance, with 93.83% precision, 93.72% recall, 93.73% F1-score, 99.10% specificity, a log loss of 0.2292, and an MCC of 0.9282. Moreover, this modeling approach holds potential for monitoring symbiotic fungal species in agricultural ecosystems and supporting sustainable production strategies. This research contributes to the literature by introducing a novel framework that simultaneously emphasises classification accuracy and model interpretability in fungal taxonomy. The proposed method successfully classified morphologically similar puffball species with high accuracy, while explainable AI techniques revealed biologically meaningful insights. All evaluation metrics were computed exclusively on a 10% independent test set that was entirely separate from the training and validation phases. Future work will focus on expanding the dataset with samples from diverse ecological regions and testing the method under field conditions. Full article

Background/Objectives: Temozolomide is an important drug used for the treatment of glioblastoma multiforme. Covalent conjugation of temozolomide to triplex-forming oligonucleotides could facilitate better sequence discrimination when targeted to DNA to lessen off-target effects and potentially reduce side-effects associated with conventional chemotherapy. The base sensitivity of temozolomide precludes use of basic deprotection conditions that typify the solid-supported synthesis of oligonucleotides. Methods: A novel di-iso-propylsilylene-linked solid support was developed and used in solid-supported synthesis of oligonucleotide conjugates. Results: Conditions were established whereby fully deprotected, solid-supported oligonucleotides could be prepared for derivatisation. Cleavage of the di-iso-propylsilylene linker was possible using mild, acidic conditions. Conclusions: The di-iso-propylsilylene-linked solid support was developed and shown to be compatible with base-sensitive oligonucleotide conjugate formation. The DNA triplex formation exhibited by a temozolomide oligonucleotide conjugate was equal in stability to the unconjugated control, opening new possibilities for sequence selective delivery of temozolomide to targeted DNA. Full article

Genomic sequences that form three-stranded triplexes (TPXs) under physiological conditions (called T-flipons) play an important role in defining DNA nucleosome-free regions (NFRs). Within these NFRs, other flipon types can cycle conformations to actuate gene expression. The transcripts read from the NFR form condensates that engage proteins and small RNAs. The helicases bound then trigger RNA polymerase release by dissociating the 7SK ribonucleoprotein. The TPXs formed usually incorporate RNA as the third strand. TPXs made only from DNA arise mostly during DNA replication. Many small RNA types (sRNAs) and long noncoding (lncRNA) can direct TPX formation. TPXs made with circular RNAs have greater stability and specificity than those formed with linear RNAs. LncRNAs can affect local gene expression through TPX formation and transcriptional interference. The condensates seeded by lncRNAs are updated by feedback loops involving proteins and noncoding RNAs from the genes they regulate. Some lncRNAs also target distant loci in a sequence-specific manner. Overall, lncRNAs can rapidly evolve by adding or subtracting sequence motifs that modify the condensates they nucleate. LncRNAs show less sequence conservation than protein-coding sequences. TPXs formed by lncRNAs and sRNAs help place nucleosomes to restrict endogenous retroelement (ERE) expression. The silencing of EREs starts early in embryogenesis and is essential for bootstrapping development. Once the system is set, EREs play a different role, with a notable enrichment of Short Interspersed Nuclear Repeats (SINEs) in Enhancer–Promoter condensates. The highly programmable TPX-dependent processes create a chromaverse capable of many complexities. Full article

This review explores the complex interactions between long noncoding RNAs (lncRNAs) and other biomolecules, highlighting their pivotal roles in gene regulation and cellular function. LncRNAs, defined as RNA transcripts exceeding 200 nucleotides without encoding proteins, are involved in diverse biological processes, from embryogenesis to pathogenesis. They interact with DNA through mechanisms like triplex structure formation, influencing chromatin organization and gene expression. LncRNAs also modulate RNA-mediated processes, including mRNA stability, translational control, and splicing regulation. Their versatility stems from their forming of complex structures that enable interactions with various biomolecules. This review synthesizes current knowledge on lncRNA functions, discusses emerging roles in development and disease, and evaluates potential applications in diagnostics and therapeutics. By examining lncRNA interactions, it provides insights into the intricate regulatory networks governing cellular processes, underscoring the importance of lncRNAs in molecular biology. Unlike the majority of previous reviews that primarily focused on individual aspects of lncRNA biology, this comprehensive review uniquely integrates structural, functional, and mechanistic perspectives on lncRNA interactions across diverse biomolecules. Additionally, this review critically evaluates cutting-edge methodologies for studying lncRNA interactions, bridges fundamental molecular mechanisms with potential clinical applications, and highlights their potential. Full article

In the field of drug development, the quest for novel compounds that bind to DNA with high affinity and specificity never ends. In the present work, we report the newest development in this field, namely, triplex DNA-specific binding ligands based on the 5-substituted flavone scaffold in our lab. Biophysical studies showed that the newly synthesized flavone derivatives (depending on the side chains) bind to triplex DNA with binding affinities better than or similar to 5-substituted 3,3′,4′,7-tetramethoxyflavonoids. These compounds selectively stabilize triplex DNA while having little effect on duplex DNA, as verified by various biophysical methods. A detailed structural analysis suggested that the binding of these compounds to triplex DNA depends on the type of amino groups in the side chains and the length of the side chains. Viscosity studies suggested that these ligands bind to triplex DNA via intercalation. A representative ligand, compound 4b, showed a positive inhibitory effect on the activity of a restriction endonuclease (DraI) via ligand-mediated triplex formation. Several of these compounds exhibited excellent cytotoxicity toward various cancer cell lines (HT-29, HCT116, and HL-60), as indicated by the MTT assay. The work presented here is part of a continued effort from our laboratory to explore the novel structural motifs of natural product flavonoids for the development of triplex-specific ligands as antigene enhancers. Full article

In the modern aviation field, flight control systems’ reliability and safety are paramount. This paper presents a triplex redundant flight control system based on the M1394B bus and designs several key algorithms to enhance system performance. Firstly, a triplex redundant flight control system with a redundant bus structure is constructed based on the characteristics of the M1394B bus. Secondly, a periodic synchronization algorithm with automatic adjustment capabilities is designed to achieve periodic synchronization among the Vehicle Management Computers. An improved voting algorithm based on a sliding window is proposed to enhance the decision-making accuracy and reliability of the control commands output by the flight control system. Additionally, a system reconstruction algorithm is designed to promptly identify and isolate faults, enabling the recovery and reallocation of system resources. Finally, experiments validate the effectiveness of the synchronization algorithm, voting algorithm, and system reconstruction algorithm. The results indicate that the system can effectively address practical engineering challenges and significantly improve reliability and stability. This research provides an essential theoretical foundation and practical reference for the design of future flight control systems for unmanned aerial vehicles and aircraft, holding significant relevance to application. Full article

Dynamic mutations in some human genes containing trinucleotide repeats are associated with severe neurodegenerative and neuromuscular disorders—known as Trinucleotide (or Triplet) Repeat Expansion Diseases (TREDs)—which arise when the repeat number of triplets expands beyond a critical threshold. While the mechanisms causing the DNA triplet expansion are complex and remain largely unknown, it is now recognized that the expandable repeats lead to the formation of nucleotide configurations with atypical structural characteristics that play a crucial role in TREDs. These nonstandard nucleic acid forms include single-stranded hairpins, Z-DNA, triplex structures, G-quartets and slipped-stranded duplexes. Of these, hairpin structures are the most prolific and are associated with the largest number of TREDs and have therefore been the focus of recent single-molecule FRET experiments and molecular dynamics investigations. Here, we review the structural and dynamical properties of nucleic acid hairpins that have emerged from these studies and the implications for repeat expansion mechanisms. The focus will be on CAG, GAC, CTG and GTC hairpins and their stems, their atomistic structures, their stability, and the important role played by structural interrupts. Full article

The dynamic landscape of non-canonical DNA G-quadruplex (G4) folding into G-triplex intermediates has led to the study of G-triplex structures and their ability to serve as peroxidase-mimetic DNAzymes. Here we report the formation, stability, and catalytic activity of a 5′-truncated c-MYC promoter region G-triplex, c-MYC-G3. Through circular dichroism, we demonstrated that c-MYC-G3 adopts a stable, parallel-stranded G-triplex conformation. The chemiluminescent oxidation of luminol by the peroxidase mimicking DNAzyme activity of c-MYC-G3 was increased in the presence of Ca²⁺ ions. We utilized surface plasmon resonance to characterize both c-MYC-G3 G-triplex formation and its interaction with hemin. The detailed study of c-MYC-G3 and its ability to form a G-triplex structure and its DNAzyme activity identifies issues that can be addressed in future G-triplex DNAzyme designs. Full article

Higher operating temperatures for gas turbine engines require highly durable thermal barrier coatings (TBCs) with improved insulation properties. A suspension plasma spray process (SPS) had been developed for the deposition of columnar-structured TBCs. SPS columnar TBCs are normally achieved at a short standoff distance (50.0 mm–75.0 mm), which is not practical when coating complex-shaped engine hardware since the plasma torch may collide with the components being sprayed. Therefore, it is critical to develop SPS columnar TBCs at longer standoff distances. In this work, a commercially available pressure-based suspension delivery system was used to deliver the suspension to the plasma jet, and a high-enthalpy TriplexPro-210 plasma torch was used for the SPS coating deposition. Suspension injection pressure was optimized to maximize the number of droplets injected into the hot plasma core and achieving the best particle-melting states and deposition efficiency. The highest deposition efficiency of 51% was achieved at 0.34 MPa injection pressure with a suspension flow rate of 31.0 g/min. With the optimized process parameters, 1000 μm thick columnar-structured SPS 8 wt% Y₂O₃-stabilized ZrO₂ (8YSZ) TBCs were successfully developed at a standoff distance of 100.0 mm. The SPS TBCs have a columnar width between 100 μm and 300 μm with a porosity of ~22%. Furnace cycling tests at 1125 °C showed the SPS columnar TBCs had an average life of 1012 cycles, which is ~2.5 times that of reference air-plasma-sprayed dense vertically cracked TBCs with the same coating thickness. The superior durability of the SPS columnar TBCs can be attributed to the high-strain-tolerant microstructure. SEM cross-section characterization indicated the failure of the SPS TBCs occurred at the ceramic top coat and thermally grown oxide (TGO) interface. Full article

Cyanobacteria produce a wealth of secondary metabolites. Since these organisms attach fatty acids into molecules in unprecedented ways, cyanobacteria can serve as a novel source for bioactive compounds acting as ligands for Peroxisome Proliferator-Activated Receptors (PPAR). PPARs (PPARα, PPARβ/δ and PPARγ) are ligand-activated nuclear receptors, involved in the regulation of various metabolic and cellular processes, thus serving as potential drug targets for a variety of pathologies. Yet, given that PPARs’ agonists can have pan-, dual- or isoform-specific action, some controversy has been raised over currently approved drugs and their side effects, highlighting the need for novel molecules. Here, we expand and validate a cell-based PPAR transactivation activity biosensor, and test it in a screening campaign to guide drug discovery. Biosensor upgrades included the use of different reporter genes to increase signal intensity and stability, a different promoter to modulate reporter gene expression, and multiplexing to improve efficiency. Sensor’s limit of detection (LOD) ranged from 0.36–0.89 nM in uniplex and 0.89–1.35 nM in multiplex mode. In triplex mode, the sensor’s feature screening, a total of 848 fractions of 96 cyanobacteria extracts were screened. Hits were confirmed in multiplex mode and in uniplex mode, yielding one strain detected to have action on PPARα and three strains to have dual action on PPARα and -β. Full article