Chemical manipulation of m1A mediates its detection in human tRNA.

N 1-methyl adenosine (m1A) is a widespread RNA modification present in tRNA, rRNA, and mRNA. m1A modification sites in tRNAs are evolutionarily conserved and its formation on tRNA is catalyzed by methyltransferase TRMT61A and TRMT6 complex. m1A promotes translation initiation and elongation. Due to its positive charge under physiological conditions, m1A can notably modulate RNA structure. It also blocks Watson-Crick-Franklin base-pairing and causes mutation and truncation during reverse transcription. Several misincorporation-based high-throughput sequencing methods have been developed to sequence m1A. In this study, we introduce a reduction-based m1A sequencing (red-m1A-seq). We report that NaBH4 reduction of m1A can improve the mutation and readthrough rates using commercially available RT enzymes to give a better positive signature, while alkaline-catalyzed Dimroth rearrangement can efficiently convert m1A to m6A to provide good controls, allowing the detection of m1A with higher sensitivity and accuracy. We applied red-m1A-seq to sequence human small RNA, and we not only detected all the previously reported tRNA m1A sites, but also new m1A sites in mt-tRNAAsn-GTT and 5.8S rRNA.

Quantification of tRNA m1A modification by templated-ligation qPCR.

N1-methyladenosine (m1A) is a widespread modification in all eukaryotic, many archaeal, and some bacterial tRNAs. m1A is generally located in the T loop of cytosolic tRNA and between the acceptor and D stems of mitochondrial tRNAs; it is involved in the tertiary interaction that stabilizes tRNA. Human tRNA m1A levels are dynamically regulated that fine-tune translation and can also serve as biomarkers for infectious disease. Although many methods have been used to measure m1A, a PCR method to assess m1A levels quantitatively in specific tRNAs has been lacking. Here we develop a templated-ligation followed by a qPCR method (TL-qPCR) that measures m1A levels in target tRNAs. Our method uses the SplintR ligase that efficiently ligates two tRNA complementary DNA oligonucleotides using tRNA as the template, followed by qPCR using the ligation product as the template. m1A interferes with the ligation in specific ways, allowing for the quantitative assessment of m1A levels using subnanogram amounts of total RNA. We identify the features of specificity and quantitation for m1A-modified model RNAs and apply these to total RNA samples from human cells. Our method enables easy access to study the dynamics and function of this pervasive tRNA modification.

Historic dog Furs Unravel the Origin and Artificial Selection of Modern Nordic Lapphund and Elkhound dog Breeds.

The origins and extreme morphological evolution of the modern dog breeds are poorly studied because the founder populations are extinct. Here, we analyse eight 100 to 200 years old dog fur samples obtained from traditional North Swedish clothing, to explore the origin and artificial selection of the modern Nordic Lapphund and Elkhound dog breeds. Population genomic analysis confirmed the Lapphund and Elkhound breeds to originate from the local dog population, and showed a distinct decrease in genetic diversity in agreement with intense breeding. We identified eleven genes under positive selection during the breed development. In particular, the MSRB3 gene, associated with breed-related ear morphology, was selected in all Lapphund and Elkhound breeds, and functional assays showed that a SNP mutation in the 3'UTR region suppresses its expression through miRNA regulation. Our findings demonstrate analysis of near-modern dog artifacts as an effective tool for interpreting the origin and artificial selection of the modern dog breeds.

Compensating losses in polariton propagation with synthesized complex frequency excitation.

Surface plasmon polaritons and phonon polaritons offer a means of surpassing the diffraction limit of conventional optics and facilitate efficient energy storage, local field enhancement and highsensitivity sensing, benefiting from their subwavelength confinement of light. Unfortunately, losses severely limit the propagation decay length, thus restricting the practical use of polaritons. While optimizing the fabrication technique can help circumvent the scattering loss of imperfect structures, the intrinsic absorption channel leading to heat production cannot be eliminated. Here, we utilize synthetic optical excitation of complex frequency with virtual gain, synthesized by combining the measurements made at multiple real frequencies, to compensate losses in the propagations of phonon polaritons with dramatically enhanced propagation distance. The concept of synthetic complex frequency excitation represents a viable solution to the loss problem for various applications including photonic circuits, waveguiding and plasmonic/phononic structured illumination microscopy.

Accelerated free-breathing liver fat and R 2 * quantification using multi-echo stack-of-radial MRI with motion-resolved multidimensional regularized reconstruction: Initial retrospective evaluation.

PURPOSE: To improve image quality, mitigate quantification biases and variations for free-breathing liver proton density fat fraction (PDFF) and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ quantification accelerated by radial k-space undersampling. METHODS: A free-breathing multi-echo stack-of-radial MRI method was developed with compressed sensing with multidimensional regularization. It was validated in motion phantoms with reference acquisitions without motion and in 11 subjects (6 patients with nonalcoholic fatty liver disease) with reference breath-hold Cartesian acquisitions. Images, PDFF, and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps were reconstructed using different radial view k-space sampling factors and reconstruction settings. Results were compared with reference-standard results using Bland-Altman analysis. Using linear mixed-effects model fitting (p < 0.05 considered significant), mean and SD were evaluated for biases and variations of PDFF and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , respectively, and coefficient of variation on the first echo image was evaluated as a surrogate for image quality. RESULTS: Using the empirically determined optimal sampling factor of 0.25 in the accelerated in vivo protocols, mean differences and limits of agreement for the proposed method were [-0.5; -33.6, 32.7] s-1 for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and [-1.0%; -5.8%, 3.8%] for PDFF, close to those of a previous self-gating method using fully sampled radial views: [-0.1; -27.1, 27.0] s-1 for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and [-0.4%; -4.5%, 3.7%] for PDFF. The proposed method had significantly lower coefficient of variation than other methods (p < 0.001). Effective acquisition time of 64 s or 59 s was achieved, compared with 171 s or 153 s for two baseline protocols with different radial views corresponding to sampling factor of 1.0. CONCLUSION: This proposed method may allow accelerated free-breathing liver PDFF and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ mapping with reduced biases and variations.

Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.

PURPOSE: Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of static images. However, for carotid plaque recognition, there are high requirements for self-developed algorithms in real-time ultrasound detection. This study aims to establish an automatic recognition system, Be Easy to Use (BETU), for the real-time and synchronous diagnosis of carotid plaque from ultrasound videos based on an artificial neural network. MATERIALS AND METHODS: 445 participants (mean age, 54.6±7.8 years; 227 men) were evaluated. Radiologists labeled a total of 3259 segmented ultrasound images from 445 videos with the diagnosis of carotid plaque, 2725 images were collected as a training dataset, and 554 images as a testing dataset. The automatic plaque recognition system BETU was established based on an artificial neural network, and remote application on a 5G environment was performed to test its diagnostic performance. RESULTS: The diagnostic accuracy of BETU (98.5%) was consistent with the radiologist's (Kappa = 0.967, P < 0.001). Remote diagnostic feedback based on BETU-processed ultrasound videos could be obtained in 150ms across a distance of 1023 km between the ultrasound/BETU station and the consultation workstation. CONCLUSION: Based on the good performance of BETU in real-time plaque recognition from ultrasound videos, 5G plus Artificial intelligence (AI)-assisted ultrasound real-time carotid plaque screening was achieved, and the diagnosis was made.

Therapeutic drug monitoring of imipenem/cilastatin and meropenem in critically ill adult patients.

OBJECTIVES: To investigate the factors influencing imipenem/cilastatin (IMI) and meropenem (MEM) concentrations in critically ill adult patients and the role of these concentrations in the clinical outcome. METHODS: Plasma trough concentrations of IMI and MEM were detected by high-performance liquid chromatography. A target value of 100%-time above MIC was used for the drugs. RESULTS: A total of 186 patients were included, with 87 receiving IMI and 99 receiving MEM. The percentages of patients reaching the target IMI and MEM concentrations were 44.8% and 38.4%, respectively. The proportions of patients infected with drug-resistant bacteria were 57.5% and 69.7% in the IMI group and MEM group, respectively. In the multivariate analysis, the risk factors for an IMI concentration that did not reach the target were infection with drug-resistant bacteria, and those for MEM were infection with drug-resistant bacteria, estimated glomerular filtration rate, and diabetes mellitus. A total of 47.1% of patients had good outcomes in the IMI cohort, and 38.1% of patients had good outcomes in the MEM cohort. The duration of mechanical ventilation and IMI concentration were associated with ICU stay in patients in the IMI cohort, while MEM concentration and severe pneumonia affected the clinical outcome of patients in the MEM cohort. CONCLUSION: Infection with drug-resistant bacteria is an important factor influencing whether IMI and MEM concentrations reach the target. Furthermore, IMI and MEM concentrations are associated with the clinical outcome, and elevated doses of IMI and MEM should be given to patients who are infected with drug-resistant bacteria.

Large rectangular cross-section tunnel undercrossing urban road by micro pipe jacking and joint assembly structure (MPJ & JAS) method in soft soils.

With the continuous construction of urban traffic roads, more and more new roads are cut off by existing roads to form "dead end roads". There is an urgent need for a trenchless method suitable for urban ultra-shallow overburden to build the undercrossing tunnel. To solve this problem, this paper proposed the micro pipe jacking and joint assembly structure (MPJ & JAS) method, which has the characteristics of shallow burial depth, low cost, short construction time, flexible cross-section setting and high space utilization. The MPJ & JAS method construct a large cross-section tunnel through assembling small cross-section elements, quite different from traditional methods. Therefore, this paper designed a CT-shaped integrated joint, the mechanical performance of which was verified and clarified by tensile test. The bending test and finite element (FE) analysis proved the reliability of MPJ & JAS tunnel structure, and confirmed the structure performances such as the failure models, crack behaviors, load-deflection response and stress-strain distribution. Moreover, the influences of the steel plate thickness, concrete strength and shear connector spacing were determined by the FE analysis. On the basis of test results and reasonable assumptions, a theoretical design method considering the influence of the CT-shaped integrated joint was proposed, which can effectively predict the bending strength of the MPJ & JAS tunnel structure with an error of less than 10%. Finally, in view of the characteristics of the MPJ & JAS method, the suitable micro pipe jacking machine, soil reinforcement measure, hydraulic traction construction technology, high-precision guidance system and concrete construction quality detection method based on the phased array ultrasonic imaging technology were developed, supporting the accurate and efficient construction of the MPJ & JAS tunnel.

Protocol for nanoscale thermal mapping of electronic devices using atomic force microscopy with phase change material.

In this protocol, we present a facile nanoscale thermal mapping technique for electronic devices by use of atomic force microscopy and a phase change material Ge2Sb2Te5. We describe steps for Ge2Sb2Te5 thin film coating, Ge2Sb2Te5 temperature calibration, thermal mapping by varying heater power, and thermal mapping by varying heating time. The protocol can be applied for resolving surface temperatures of various operational microelectronic devices with a nanoscale precision. For complete details on the use and execution of this protocol, please refer to Cheng et al.1.

Steering and cloaking of hyperbolic polaritons at deep-subwavelength scales.

Polaritons are well-established carriers of light, electrical signals, and even heat at the nanoscale in the setting of on-chip devices. However, the goal of achieving practical polaritonic manipulation over small distances deeply below the light diffraction limit remains elusive. Here, we implement nanoscale polaritonic in-plane steering and cloaking in a low-loss atomically layered van der Waals (vdW) insulator, α-MoO3, comprising building blocks of customizable stacked and assembled structures. Each block contributes specific characteristics that allow us to steer polaritons along the desired trajectories. Our results introduce a natural materials-based approach for the comprehensive manipulation of nanoscale optical fields, advancing research in the vdW polaritonics domain and on-chip nanophotonic circuits.

Pseudouridine Detection and Quantification Using Bisulfite Incorporation Hindered Ligation.

Pseudouridine (Ψ) is a widespread RNA modification found in various RNA species, including rRNA, tRNA, snRNA, mRNA, and long noncoding RNA (lncRNA). Understanding the function of Ψ in these RNA types requires a robust method for the detection and quantification of the Ψ level at single-nucleotide resolution. A previously used method utilizes Ψ labeling by N-cyclohexyl-N'-ß-(4-methylmorpholinium)ethylcarbodiimide (CMC). The quantification of Ψ is based on the stop ratio after reverse transcription. However, the use of CMC followed by strong alkaline treatment causes severe RNA degradation, often requiring a large amount of RNA. The removal of CMC and recovery of RNA by ethanol precipitation are also time-consuming. Here, we introduce a Bisulfite Incorporation Hindered ligation-based method (BIHIND), which can detect and quantify Ψ sites on rRNA, mRNA, and noncoding RNA. BIHIND can be coupled with quantitative PCR (BIHIND-qPCR) for quantitative detection of Ψ fraction at individual modification sites, as well as with next-generation sequencing (BIHIND-seq) for high-throughput sequencing of Ψ without requiring reverse transcription. We validated the robustness of BIHIND with the elucidation of Ψ dynamics following pseudouridine synthase depletion.

Identification of Optic Nerve-Related Biomarkers in Primary Open-Angle Glaucoma Based on Comprehensive Bioinformatics and Mendelian Randomization.

Purpose: Glaucoma is the primary cause of permanent vision loss worldwide. However, the pathogenesis of primary open-angle glaucoma (POAG), the main type of glaucoma, has not yet been completely understood. Methods: In our study, the POAG cohorts were obtained from the Gene Expression Omnibus (GEO) database (GSE45570). Biomarkers with diagnostic utility for POAG were identified through combining differentially expressed analysis, enrichment analysis, machine learning algorithms, and receiver operating characteristic (ROC) analysis. The regulatory networks (including a competing endogenous RNA (ceRNA) regulatory network and a small molecule compounds-mRNA network) were created. In addition, the Mendelian randomization (MR) analysis was used to identify exposures causally associated with POAG. Finally, the expression of the biomarkers was validated via real-time quantitative polymerase chain reaction (RT-qPCR). Results: The Gene Ontology (GO) items that the differentially expressed genes (DEGs) between POAG and control groups enriched were relevant to light stimulation and DNA methylation. A total of three light stimulation-related biomarkers (RAB8A, PRG3, and SMAD3) were identified, which had diagnostic value for POAG patients. Besides, the ceRNA regulatory network contained 88 nodes and 93 edges, and a small molecule compounds-mRNA network included 66 nodes and 76 edges. The MR results indicated a causal association between DNA methylation GrimAge acceleration and POAG. Additionally, the results of RT-qPCR revealed that the expression trend of RAB8A was consistent with that of GSE45570. Conclusions: Taken together, this study provides three light stimulation-related biomarkers (RAB8A, PRG3, and SMAD3) for the diagnosis of POAG, providing scientifically valuable insights for further studies of POAG. Translational Relevance: Discovering biomarkers that possess diagnostic significance for POAG has the potential to offer new insights into the pathogenesis of POAG and present novel objectives for clinical intervention.

A novel Gaussian sum quaternion constrained cubature Kalman filter algorithm for GNSS/SINS integrated attitude determination and positioning system.

The quaternion cubature Kalman filter (QCKF) algorithm has emerged as a prominent nonlinear filter algorithm and has found extensive applications in the field of GNSS/SINS integrated attitude determination and positioning system (GNSS/SINS-IADPS) data processing for unmanned aerial vehicles (UAV). However, on one hand, the QCKF algorithm is predicated on the assumption that the random model of filter algorithm, which follows a white Gaussian noise distribution. The noise in actual GNSS/SINS-IADPS is not the white Gaussian noise but rather a ubiquitous non-Gaussian noise. On the other hand, the use of quaternions as state variables is bound by normalization constraints. When applied directly in nonlinear non-Gaussian system without considering normalization constraints, the QCKF algorithm may result in a mismatch phenomenon in the filtering random model, potentially resulting in a decline in estimation accuracy. To address this issue, we propose a novel Gaussian sum quaternion constrained cubature Kalman filter (GSQCCKF) algorithm. This algorithm refines the random model of the QCKF by approximating non-Gaussian noise with a Gaussian mixture model. Meanwhile, to account for quaternion normalization in attitude determination, a two-step projection method is employed to constrain the quaternion, which consequently enhances the filtering estimation accuracy. Simulation and experimental analyses demonstrate that the proposed GSQCCKF algorithm significantly improves accuracy and adaptability in GNSS/SINS-IADPS data processing under non-Gaussian noise conditions for Unmanned Aerial Vehicles (UAVs).

Drug-coated balloon angioplasty for the treatment of intracranial arterial stenosis in a young stroke patient: A case report.

BACKGROUND: Intracranial arterial narrowing is a significant factor leading to brief episodes of reduced blood flow to the brain, known as transient ischemic attacks, or full-blown strokes. While atherosclerosis is commonly associated with intracranial arterial narrowing, it is frequently of a non-atherosclerotic nature in younger patients. CASE SUMMARY: Here, we present the case of a young stroke patient with narrowing of the middle cerebral artery (MCA), characterized as non-atherosclerotic lesions, who experienced an ischemic stroke despite receiving standard drug therapy. The patient underwent digital subtraction angiography (DSA) to assess the entire network of blood vessels in the brain, revealing significant narrowing (approximately 80%) in the M1 segment of the right MCA. Subsequently, the patient underwent Drug-Coated Balloon Angioplasty to treat the stenosis in the right MCA's M1 segment. Follow-up DSA confirmed the resolution of stenosis in this segment. Although the remaining branches showed satisfactory blood flow, the vessel wall exhibited irregularities. A review of DSA conducted six months later showed no evident stenosis in the right MCA, with a smooth vessel wall. CONCLUSION: The use of drug-coated balloon angioplasty demonstrated favorable outcomes in repairing and reshaping the blood vessel wall in young patients. Therefore, it may be considered a promising treatment option for similar cases.

Growth differentiation factor-15 as a negative predictor for microvascular obstruction in ST-segment elevation myocardial infarction after primary percutaneous coronary intervention.

Growth differentiation factor-15 (GDF-15) is an anti-inflammatory cytokine with cardioprotective effects, but circulating GDF-15 concentration predicts adverse cardiovascular outcomes in clinical settings. Microvascular obstruction (MVO) formation contributed to poor prognosis in patients with ST-segment elevation myocardial infarction (STEMI) after primary percutaneous coronary intervention (pPCI). We aimed to investigate GDF-15 concentration in relation to cardiac magnetic resonance (CMR)-derived MVO in STEMI patients after pPCI, which might help better understand the role of GDF-15 in STEMI. GDF-15 levels at 6 h after pPCI and MVO extent at day 5 ± 2 after pPCI were measured in 74 STEMI patients (mean age 60.3 ± 12.8 years, 86.5% men). The adjusted association of GDF-15 with MVO was analyzed with MVO treated as a categorized variable (extensive MVO, defined as MVO extent ≥ 2.6% of left ventricular (LV)) and a continuous variable (MVO mass, % of LV), respectively, in multivariate logistic and linear regression models. 41.9% of the patients developed extensive MVO after pPCI. In multivariate analysis, the odds ratio (95% confidential interval (CI)) of each standard deviation (SD) increase in GDF-15 for developing extensive MVO was 0.46 (0.21, 0.82), p = 0.02). Consistently, when MVO was used a continuous variable, each SD increase in GDF-15 was associated with a substantially lower MVO mass (ß - 0.42, standard error 0.19, p = 0.03). GDF-15 was a negative predictor for MVO in STEMI patients after pPCI. The observation was consistent with results from experiment studies, suggesting a potential protective effect of GDF-15 against cardiac injury.

Ultrafast bisulfite sequencing detection of 5-methylcytosine in DNA and RNA.

Bisulfite sequencing (BS-seq) to detect 5-methylcytosine (5mC) is limited by lengthy reaction times, severe DNA damage, overestimation of 5mC level and incomplete C-to-U conversion of certain DNA sequences. We present ultrafast BS-seq (UBS-seq), which uses highly concentrated bisulfite reagents and high reaction temperatures to accelerate the bisulfite reaction by ~13-fold, resulting in reduced DNA damage and lower background noise. UBS-seq allows library construction from small amounts of purified genomic DNA, such as from cell-free DNA or directly from 1 to 100 mouse embryonic stem cells, with less overestimation of 5mC level and higher genome coverage than conventional BS-seq. Additionally, UBS-seq quantitatively maps RNA 5-methylcytosine (m5C) from low inputs of mRNA and allows the detection of m5C stoichiometry in highly structured RNA sequences. Our UBS-seq results identify NSUN2 as the major 'writer' protein responsible for the deposition of ~90% of m5C sites in HeLa mRNA and reveal enriched m5C sites in 5'-regions of mammalian mRNA, which may have functional roles in mRNA translation regulation.

MIGP: Metapath Integrated Graph Prompt Neural Network.

Graph neural networks (GNNs) leveraging metapaths have garnered extensive utilization. Nevertheless, the escalating parameters and data corpus within graph pre-training models incur mounting training costs. Consequently, GNN models encounter hurdles including diminished generalization capacity and compromised performance amidst small sample datasets. Drawing inspiration from the efficacy demonstrated by self-supervised learning methodologies in natural language processing, we embark on an exploration. We endeavor to imbue graph data with augmentable, learnable prompt vectors targeting node representation enhancement to foster superior adaptability to downstream tasks. This paper proposes a novel approach, the Metapath Integrated Graph Prompt Neural Network (MIGP), which leverages learnable prompt vectors to enhance node representations within a pretrained model framework. By leveraging learnable prompt vectors, MIGP aims to address the limitations posed by mall sample datasets and improve GNNs' model generalization. In the pretraining stage, we split symmetric metapaths in heterogeneous graphs into short metapaths and explicitly propagate information along the metapaths to update node representations. In the prompt-tuning stage, the parameters of the pretrained model are fixed, a set of independent basis vectors is introduced, and an attention mechanism is employed to generate task-specific learnable prompt vectors for each node. Another notable contribution of our work is the introduction of three patent datasets, which is a pioneering application in related fields. We will make these three patent datasets publicly available to facilitate further research on large-scale patent data analysis. Through comprehensive experiments conducted on three patent datasets and three other public datasets, i.e., ACM, IMDB, and DBLP, we demonstrate the superior performance of the MIGP model in enhancing model applicability and performance across a variety of downstream datasets. The source code and datasets are available in the website.1.

Multifunctional two-dimensional perovskite based solar cells for photodetectors and resistive switching.

The escalating interest in low-dimensional perovskites stems from their tunable optoelectronic traits and robust stability. The pursuit of multifaceted optoelectronic devices holds substantial importance for energy-efficient and space-constrained systems. This investigation showcases the realization of multifunctional two-dimensional perovskite solar cells, incorporating transient light detection and resistive switching functions within a single device, achievable by facile external bias adjustments. Serving as a photodetector, the device exhibits commendable self-powered photodetection attributes, including an exceptionally low dark current density of 1 nA mm-2, a remarkable specific detectivity of 7.67 × 1012 Jones, a swift response time of 0.60 µs, and an expansive linear dynamic range of 72 dB. As a memristor, it showcases enduring performance across 4 × 102 cycles, a substantial on/off ratio of 106, and a rapid operation time of less than 1 µs. This endeavor unveils a pioneering avenue for advancing high-performance, air-stable multifunctional two-dimensional perovskite electronics.

Manipulating hyperbolic transient plasmons in a layered semiconductor.

Anisotropic materials with oppositely signed dielectric tensors support hyperbolic polaritons, displaying enhanced electromagnetic localization and directional energy flow. However, the most reported hyperbolic phonon polaritons are difficult to apply for active electro-optical modulations and optoelectronic devices. Here, we report a dynamic topological plasmonic dispersion transition in black phosphorus via photo-induced carrier injection, i.e., transforming the iso-frequency contour from a pristine ellipsoid to a non-equilibrium hyperboloid. Our work also demonstrates the peculiar transient plasmonic properties of the studied layered semiconductor, such as the ultrafast transition, low propagation losses, efficient optical emission from the black phosphorus's edges, and the characterization of different transient plasmon modes. Our results may be relevant for the development of future optoelectronic applications.