Search

Real-time and accurate biomarker detection is highly desired in point-of-care diagnosis, food freshness monitoring, and hazardous leakage warning. However, achieving such an objective with existing technologies is still challenging. Herein, we demonstrate a wireless inductor-capacitor (LC) chemical sensor based on platinum-doped partially deprotonated-polypyrrole (Pt-PPy+ and PPy0) for real-time and accurate ammonia (NH3) detection. With the chemically wide-range tunability of PPy in conductivity to modulate the impedance, the LC sensor exhibits an up-to-180% improvement in return loss (S11). The Pt-PPy+ and PPy0 shows the p-type semiconductor nature with greatly-manifested adsorption-charge transfer dynamics toward NH3, leading to an unprecedented NH3 sensing range. The S11 and frequency of the Pt-PPy+ and PPy0-based sensor exhibit discriminative response behaviors to humidity and NH3, enabling the without-external-calibration compensation and accurate NH3 detection. A portable system combining the proposed wireless chemical sensor and a handheld instrument is validated, which aids in rationalizing strategies for individuals toward various scenarios. This work proposes a wireless inductor-capacitor chemical sensor with self-humidity compensation for real-time and accurate ammonia detection, providing a significant tool for individually rationalizing strategies toward various applications. [ABSTRACT FROM AUTHOR]

Motivation Transcription factors are pivotal in the regulation of gene expression, and accurate identification of transcription factor binding sites (TFBSs) at high resolution is crucial for understanding the mechanisms underlying gene regulation. The task of identifying TFBSs from DNA sequences is a significant challenge in the field of computational biology today. To address this challenge, a variety of computational approaches have been developed. However, these methods face limitations in their ability to achieve high-resolution identification and often lack interpretability. Results We propose BertSNR, an interpretable deep learning framework for identifying TFBSs at single-nucleotide resolution. BertSNR integrates sequence-level and token-level information by multi-task learning based on pre-trained DNA language models. Benchmarking comparisons show that our BertSNR outperforms the existing state-of-the-art methods in TFBS predictions. Importantly, we enhanced the interpretability of the model through attentional weight visualization and motif analysis, and discovered the subtle relationship between attention weight and motif. Moreover, BertSNR effectively identifies TFBSs in promoter regions, facilitating the study of intricate gene regulation. Availability and implementation The BertSNR source code can be found at https://github.com/lhy0322/BertSNR. [ABSTRACT FROM AUTHOR]

The static recrystallization and strain-induced precipitation behavior of Ti and Ti-Zr low carbon microalloyed steels were studied through isothermal stress relaxation experiments at different deformation temperatures (875–1025 °C). The precipitation kinetic curves of microalloyed carbides were obtained, and the effect of Zr on the precipitation kinetics of microalloyed carbides was analyzed. Two static recrystallization kinetic models were established, and the activation energies for static recrystallization of Ti steel and Ti-Zr steel were calculated to be 312.44 and 246.59 kJ/mol, respectively. The results indicate that the addition of Zr lowers the nose point temperature of the precipitation–time–temperature curve, shortens the incubation period for the nucleation of precipitates, promotes the nucleation of strain-induced precipitates in Ti microalloyed steel, and reduces the coarsening rate of precipitates particles by an order of magnitude. In addition, the addition of Zr also advances the end time of static recrystallization of deformed austenite, inhibits the growth of static recrystallization austenite grains in Ti steel during the isothermal process, and makes the austenite grains finer and more uniform. [ABSTRACT FROM AUTHOR]

Investigation on the effects of Zr and quenching and tempering processes on the microstructure and properties of high-strength Ti-Mo microalloyed steel using SEM, TEM, mechanical property testing, and First-principles calculations. The results show that within the tempering temperature range of 550–650 °C, the microstructures of Ti-Mo microalloyed steel and Ti-Zr-Mo microalloyed steel consist of ultra-low carbon martensite and carbides. Specifically, the strength of Ti-Mo microalloyed steel initially increases and then decreases with the increase in tempering temperature, while the strength of Ti-Zr-Mo microalloyed steel increases with the increase in tempering temperature. During tempering, the addition of Zr element affects the diffusion of C element, delaying the martensitic tempering transformation process, and slowing down the nucleation, growth, and coarsening processes of alloy carbides. First-principles calculation results indicate that ZrC preferentially forms during tempering, resulting in a certain sequential gradient of precipitated microalloy carbides, thereby enhancing the tempering stability of microalloyed steel. Compared to Ti-Mo steel, Ti-Zr-Mo steel exhibits narrower lath martensite width and finer dispersed precipitation phases after tempering at 600 °C and 650 °C. [ABSTRACT FROM AUTHOR]

Aim: To identify the spectrum of autoimmune encephalitis antibody biomarkers (AE‐Abs) in children with suspected autoimmune encephalitis and explore the clinical features indicating AE‐Abs presence. Method: We included children with suspected autoimmune encephalitis who underwent AE‐Abs tests at the Children's Hospital of Chongqing Medical University between June 2020 and June 2022. Clinical features suggestive of AE‐Abs were analysed based on AE‐Abs test results. Results: A total of 392 children were tested for AE‐Abs with suspected autoimmune encephalitis. Of these, 49.5% were male, with a median age of 7 years 11 months (6 months–17 years 11 months); 93.6% (367/392) of all patients had both serum and cerebrospinal fluid (CSF) tests performed. The antibody‐positive rate in the cohort was 23.7% (93/392), the serum antibody‐positive rate was 21.9% (84/384), and the CSF antibody‐positive rate was 20.8% (78/375). Eleven different AE‐Abs were detected. Serum analysis revealed that N‐methyl‐D‐aspartate receptor immunoglobulin‐G (NMDAR‐IgG) (15.1%) was greater than myelin oligodendrocyte glycoprotein (MOG)‐IgG (14.6%) and glial fibrillary acidic protein (GFAP)‐IgG (3.3%). CSF analysis revealed that NMDAR‐IgG (16.3%) was greater than MOG‐IgG (13.8%) and GFAP‐IgG (3.3%). Compared with antibody‐negative patients, antibody‐positive patients were more often female (odds ratio [OR] 1.86, p = 0.03), with memory impairment (OR 2.91, p = 0.01) and sleep disorders (OR 2.08, p = 0.02). Interpretation: In children, the most frequent AE‐Abs detected were NMDAR‐IgG and MOG‐IgG. Female sex, memory impairment, and sleep disorders predict a higher likelihood of AE‐Abs. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate whether minocycline could influence alterations of microglial subtypes, the morphology of dendrites and dendritic spines, the microstructures of synapses and synaptic proteins, or even cognition outcomes in immature male mice following status epilepticus (SE) induced by kainic acid. Methods: Golgi staining was performed to visualize the dendrites and dendritic spines of neurons of the hippocampus. The microstructures of synapses and synaptic proteins were observed using transmission electron microscopy and western blotting analysis, respectively. Microglial reactivation and their markers were evaluated using flow cytometry. The Morris water maze (MWM) test was used to analyze spatial learning and memory ability. Results: Significant partial spines increase (predominate in thin spines) was observed in the dendrites of neurons after acute SE and partial loss (mainly in thin spines) was presented by days 14 and 28 post‐SE. The postsynaptic ultrastructure was impaired on the 7th and 14th days after SE. The proportion of M1 microglia increased significantly only after acute SE Similarly, the proportion of M2 microglia increased in the acute stage with high expression levels of all surface markers. In contrast, a decrease in M2 microglia and their markers was noted by day 14 post‐SE. Minocycline could reverse the changes in dendrites and synaptic proteins caused by SE, and increase the levels of synaptic proteins. Meanwhile, minocycline could inhibit the reactivation of M1 microglia and the expression of their markers, except for promoting CD200R. In addition, treatment with minocycline could regulate the expression of M2 microglia and their surface markers, as well as ameliorating the impaired spatial learning and memory on the 28th day after SE. Conclusions: Dendritic spines and microglia are dynamically changed after SE. Minocycline could ameliorate the impaired cognition in the kainic acid‐induced mouse model by decreasing the damage to dendrites and altering microglial reactivation. [ABSTRACT FROM AUTHOR]

Interspecific variations in phenotypic plasticity of trees that are affected by climate change may alter the ecosystem function of forests. Seedlings of four common tree species (Castanopsis fissa , Michelia macclurei , Dalbergia odorifera and Ormosia pinnata) in subtropical plantations of southern China were grown in the field under rainout shelters and subjected to changing precipitation (48 L of water every 4 days in the dry season, 83 L of water every 1 day in the wet season; 4 g m−2 year−1 of nitrogen (N)), low N deposition (48 L of water every 2 days in the dry season, 71 L of water every 1 day in the wet season; 8 g m−2 year−1 N), high N deposition (48 L of water every 2 days in the dry season, 71 L of water every 1 day in the wet season; 10 g m−2 year−1 N) and their interactive effects. We found that the changes in seasonal precipitation reduced the light-saturated photosynthetic rate (A sat) for C. fissa due to declining area-based foliar N concentrations (Na). However, we also found that the interactive effects of changing precipitation and N deposition enhanced A sat for C. fissa by increasing foliar Na concentrations, suggesting that N deposition could alleviate N limitations associated with changing precipitation. Altered precipitation and high N deposition reduced A sat for D. odorifera by decreasing the maximum electron transport rate for RuBP regeneration (J max) and maximum rate of carboxylation of Rubisco (V cmax). Ormosia pinnata under high N deposition exhibited increasing A sat due to higher stomatal conductance and V cmax. The growth of D. odorifera might be inhibited by changes in seasonal precipitation and N deposition, while O. pinnata may benefit from increasing N deposition in future climates. Our study provides an important insight into the selection of tree species with high capacity to tolerate changing precipitation and N deposition in subtropical plantations. [ABSTRACT FROM AUTHOR]

DNA methylation at the N6 position of adenine (N6-methyladenine, 6 mA), which refers to the attachment of a methyl group to the N6 site of the adenine (A) of DNA, is an important epigenetic modification in prokaryotic and eukaryotic genomes. Accurately predicting the 6 mA binding sites can provide crucial insights into gene regulation, DNA repair, disease development and so on. Wet experiments are commonly used for analyzing 6 mA binding sites. However, they suffer from high cost and expensive time. Therefore, various deep learning methods have been widely used to predict 6 mA binding sites recently. In this study, we develop a framework based on multi-scale DNA language model named "iDNA6mA-MDL". "iDNA6mA-MDL" integrates multiple kmers and the nucleotide property and frequency method for feature embedding, which can capture a full range of DNA sequence context information. At the prediction stage, it also leverages DNABERT to compensate for the incomplete capture of global DNA information. Experiments show that our framework obtains average AUC of 0.981 on a classic 6 mA rice gene dataset, going beyond all existing advanced models under fivefold cross-validations. Moreover, "iDNA6mA-MDL" outperforms most of the popular state-of-the-art methods on another 11 6 mA datasets, demonstrating its effectiveness in 6 mA binding sites prediction., Competing Interests: Declaration of Competing Interest All authors disclosed no relevant relationships., (Copyright © 2024 Elsevier Ltd. All rights reserved.)