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Human C-reactive protein (CRP) and lactate dehydrogenase are important markers in clinical laboratory testing—the former is used to detect in vivo inflammation, and the latter is used to detect cell necrosis and tissue destruction. We developed aptamers that bind to human CRP and human lactate dehydrogenase-5 (LDH-5) with high affinities (dissociation constants of 6.2 pM and 235 pM, respectively), applying the systematic evolution of ligands by exponential enrichment (SELEX) method, and by using a modified DNA library containing the following base-appended base modifications: analog adenine derivative at the fifth position of uracil (Uad), analog guanine derivative at the fifth position of uracil (Ugu), and analog adenine derivative at the seventh position of adenine (Aad). A potential application of these aptamers as sensor elements includes high-sensitivity target detection in point-of-care testing.

Background Nanopore long-read sequencing technology greatly expands the capacity of long-range, single-molecule DNA-modification detection. A growing number of analytical tools have been developed to detect DNA methylation from nanopore sequencing reads. Here, we assess the performance of different methylation-calling tools to provide a systematic evaluation to guide researchers performing human epigenome-wide studies. Results We compare seven analytic tools for detecting DNA methylation from nanopore long-read sequencing data generated from human natural DNA at a whole-genome scale. We evaluate the per-read and per-site performance of CpG methylation prediction across different genomic contexts, CpG site coverage, and computational resources consumed by each tool. The seven tools exhibit different performances across the evaluation criteria. We show that the methylation prediction at regions with discordant DNA methylation patterns, intergenic regions, low CG density regions, and repetitive regions show room for improvement across all tools. Furthermore, we demonstrate that 5hmC levels at least partly contribute to the discrepancy between bisulfite and nanopore sequencing. Lastly, we provide an online DNA methylation database ( https://nanome.jax.org ) to display the DNA methylation levels detected by nanopore sequencing and bisulfite sequencing data across different genomic contexts. Conclusions Our study is the first systematic benchmark of computational methods for detection of mammalian whole-genome DNA modifications in nanopore sequencing. We provide a broad foundation for cross-platform standardization and an evaluation of analytical tools designed for genome-scale modified base detection using nanopore sequencing.

5-Methylcytosine (5mC) is an important type of epigenetic modification. Bisulfite sequencing (BS-seq) has limitations, such as severe DNA degradation. Using single molecule real-time sequencing, we developed a methodology to directly examine 5mC. This approach holistically examined kinetic signals of a DNA polymerase (including interpulse duration and pulse width) and sequence context for every nucleotide within a measurement window, termed the holistic kinetic (HK) model. The measurement window of each analyzed double-stranded DNA molecule comprised 21 nucleotides with a cytosine in a CpG site in the center. We used amplified DNA (unmethylated) and M.SssI-treated DNA (methylated) (M.SssI being a CpG methyltransferase) to train a convolutional neural network. The area under the curve for differentiating methylation states using such samples was up to 0.97. The sensitivity and specificity for genome-wide 5mC detection at single-base resolution reached 90% and 94%, respectively. The HK model was then tested on human–mouse hybrid fragments in which each member of the hybrid had a different methylation status. The model was also tested on human genomic DNA molecules extracted from various biological samples, such as buffy coat, placental, and tumoral tissues. The overall methylation levels deduced by the HK model were well correlated with those by BS-seq (r = 0.99; P < 0.0001) and allowed the measurement of allele-specific methylation patterns in imprinted genes. Taken together, this methodology has provided a system for simultaneous genome-wide genetic and epigenetic analyses.

Biodiesel can be a significant alternative for diesel. Usually, it is produced through transesterification with a base catalyst. Using heterogeneous catalysts for transesterification, the process can be more efficient. Among the possible catalysts that can be used, biochars combine high performance for transesterification and valorization of waste biomass. Biochars are cheap materials, and are easy to activate through chemical treatment with acid or base solutions. In this short review, the application of biochar as solid heterogeneous catalysts for transesterification of lipids to produce biodiesel is discussed.

Biochar （BC） is a potential material for removal of polycyclic aromatic hydrocarbons t~om soil and water, and base modification is a promising method for improving its sorption ability. In this study, we synthesized a series of base-modified biochars, and evaluated their sorption of phenanthrene. Original biochars were produced by pyrolysis of three feedstocks （rice straw, wood and bamboo） at five temperatures （300~C, 350~C, 400~C, 500~C and 700~C）. Base-modified biochars were further obtained by washing ofbiochars with base solution. The base soluble carbon （SC） was extracted from the supernatant, which were only obtained from biochars pyrolyzed at low temperatures （ 〈 500~C） and the content was decreased with the increase of pyrolysis temperature. The SC content between different feedstocks followed the trend office straw〉wood〉bamboo when same pyrolysis conditions were applied, It was tbund that base modification improved the sorption of phenanthrene on biochars that SC could be extracted from （extractable-BCs）. However, base treatment but had limited effects for biochars that no SC could be extracted from. It suggested that base modification improved the sorption of phenanthrene to extractable-BCs by removing the SC and thus increasing the surface area and hydrophobicity. Therefore, base modification was suggested to be used in modifying extractable-BCs.

In this paper, magnetic coagulants (Fe-AFA, Fe-BFA) were prepared, by mixing acid-modified fly ash (AFA) and base-modified fly ash (BFA) with magnetic components, as adsorbents for chemical oxygen demand (COD) in desulfurization wastewater and their adsorption kinetics and mechanism are reported. BET, SEM, EDS, FTIR, XPS, magnetization intensity, and batch experiments on coagulation kinetic and adsorption isothermal characteristics of magnetic coagulants were carried out. The results show that Fe-AFA has the best COD adsorption performance and superparamagnetism, and the COD removal amounts can reach 5.69 mg/g, which is 112.43% higher than the raw fly ash. It was also found that the quasi-second-order kinetic and Langmuir equation could well describe the COD coagulation process. Thermodynamic tests results showed that the COD removal was a spontaneous, endothermic, and irreversible process. Reusability of magnetic coagulants was investigated. After five cycles, the COD removal amount of Fe-AFA was 2.74 mg/g. These findings provide a feasible method for environmental-benign utilization of fly ash as low-cost adsorbents in wastewater treatment.

Background: Nanopore sequencing produces ionic current signals that are sensitive to chemical modifications in DNA and RNA molecules. However, accurate modification detection remains challenging due to limited labeled data and variability across experimental conditions. Methods: We present a scalable unsupervised framework for modification discovery that learns reference signal distributions from unmodified sequences using a CNN–Transformer variational autoencoder (VAE). The model is trained on large-scale data via streaming sampling and k-mer-aware soft balancing to ensure robust signal representation. At inference, candidate nucleotides are scored using the VAE reconstruction error, and read-level signals are aggregated to produce site-level modification evidence. Results: On controlled DNA oligonucleotide datasets, models trained on unmodified sequences achieve strong discrimination when evaluated on modified oligos. In contrast, performance decreases in cell line samples when models trained on unmodified whole-genome-amplified (WGA) DNA and in vitro-transcribed (IVT) RNA are evaluated on natively modified (5mC/m6A) data, reflecting the impacts of biological noise and heterogeneity. Despite reduced classification accuracy, site-level anomaly score profiles exhibit peak-like patterns that correspond to known modification-enriched regions. Conclusions: These findings demonstrate the feasibility of large-scale unsupervised reference modeling for de novo modification detection, while underscoring the challenges in translating models built from synthetic oligo datasets into robust genome-wide modification detection.

Chemically modified nucleic acid bases are sources of genomic instability and mutations but may also regulate gene expression as epigenetic or epitranscriptomic modifications. Depending on the cellular context, they can have vastly diverse impacts on cells, from mutagenesis or cytotoxicity to changing cell fate by regulating chromatin organisation and gene expression. Identical chemical modifications exerting different functions pose a challenge for the cell’s DNA repair machinery, as it needs to accurately distinguish between epigenetic marks and DNA damage to ensure proper repair and maintenance of (epi)genomic integrity. The specificity and selectivity of the recognition of these modified bases relies on DNA glycosylases, which acts as DNA damage, or more correctly, as modified bases sensors for the base excision repair (BER) pathway. Here, we will illustrate this duality by summarizing the role of uracil-DNA glycosylases, with particular attention to SMUG1, in the regulation of the epigenetic landscape as active regulators of gene expression and chromatin remodelling. We will also describe how epigenetic marks, with a special focus on 5-hydroxymethyluracil, can affect the damage susceptibility of nucleic acids and conversely how DNA damage can induce changes in the epigenetic landscape by altering the pattern of DNA methylation and chromatin structure.

Cyclodextrins (CDs) are cyclic oligosaccharides which can trap hydrophobic molecules and improve their chemical, physical, and biological properties. γ-CD showed the highest aqueous solubility with the largest cavity diameter among other CD types. The current study describes a direct and easy method for nucleophilic mono-aminos to be substituted with γ-CD and tested for their ability to host the guest curcumin (CUR) as a hydrophobic drug model. The mass spectrometry and NMR analyses showed the successful synthesis of three amino-modified γ-CDs: mono-6-amino-6-deoxy-cyclodextrine (γ-CD-NH2), mono-6-deoxy-6-ethanolamine-γ-cyclodextrine (γ-CD-NHCH2CH2OH), and mono-6-deoxy-6-aminoethylamino)-γ-cyclodextrin (γ-CD-NHCH2CH2NH2). These three amino-modified γ-CDs were proven to be able to host CUR as native γ-CDs with formation constants equal to 6.70 ± 1.02, 5.85 ± 0.80, and 8.98 ± 0.90 mM−1, respectively. Moreover, these amino-modified γ-CDs showed no significant toxicity against human dermal fibroblast cells. In conclusion, the current work describes a mono-substitution of amino-modified γ-CDs that can still host guests and showed low toxicity in human dermal fibroblasts cells. Therefore, the amino-modified γ-CDs can be used as a carrier host and be conjugated with a wide range of molecules for different biomedical applications, especially for active loading methods.

Several different semantics have been proposed for conditional knowledge bases R containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by R . For the notion of c-representations which are a subclass of all ranking functions accepting R , a skeptical inference relation, called c-inference and taking all c-representations of R into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of R is reused for incrementally compiling extensions, contractions, and updates of R . For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of R . These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme.