Pulmonary Calcifying Fibrous Tumor in a Pediatric Patient: A Case Report.

A calcifying fibrous tumor (CFT), also known as calcifying fibrous pseudotumor, is an uncommon non-cancerous neoplasm usually located in the gastrointestinal tract. Its location in the lung is extremely rare, and only a few case reports have been published. This case report describes our diagnostic approach in a 9-year-old male patient with an incidental pulmonary mass. The mass was initially misdiagnosed, requiring multiple imaging tests and interventions to obtain the definitive diagnosis of pulmonary CFT. This paper aims to contribute to the limited information available on pulmonary CFT by presenting detailed findings from computed tomography and magnetic resonance imaging.

15-epi-lipoxin A5 promotes neutrophil exit from exudates for clearance by splenic macrophages.

Specialized proresolving mediators (SPMs) promote local macrophage efferocytosis but excess leukocytes early in inflammation require additional leukocyte clearance mechanism for resolution. Here, neutrophil clearance mechanisms from localized acute inflammation were investigated in mouse dorsal air pouches. 15-HEPE (15-hydroxy-5Z,8Z,11Z,13E,17Z-eicosapentaenoic acid) levels were increased in the exudates. Activated human neutrophils converted 15-HEPE to lipoxin A5 (5S,6R,15S-trihydroxy-7E,9E,11Z,13E,17Z-eicosapentaenoic acid), 15-epi-lipoxin A5 (5S,6R,15R-trihydroxy-7E,9E,11Z,13E,17Z-eicosapentaenoic acid), and resolvin E4 (RvE4; 5S,15S-dihydroxy-6E,8Z,11Z,13E,17Z-eicosapentaenoic acid). Exogenous 15-epi-lipoxin A5, 15-epi-lipoxin A4 and a structural lipoxin mimetic significantly decreased exudate neutrophils and increased local tissue macrophage efferocytosis, with comparison to naproxen. 15-epi-lipoxin A5 also cleared exudate neutrophils faster than the apparent local capacity for stimulated macrophage efferocytosis, so the fate of exudate neutrophils was tracked with CD45.1 variant neutrophils. 15-epi-lipoxin A5 augmented the exit of adoptively transferred neutrophils from the pouch exudate to the spleen, and significantly increased splenic SIRPa+ and MARCO+ macrophage efferocytosis. Together, these findings demonstrate new systemic resolution mechanisms for 15-epi-lipoxin A5 and RvE4 in localized tissue inflammation, which distally engage the spleen to activate macrophage efferocytosis for the clearance of tissue exudate neutrophils.

Multimodal Imaging-Assisted Intravascular Theranostic Photoactivation on Atherosclerotic Plaque.

BACKGROUND: Atherosclerosis is a chronic inflammatory disease causing a fatal plaque rupture, and its key aspect is a failure to resolve inflammation. We hypothesize that macrophage-targeted near-infrared fluorescence emitting photoactivation could simultaneously assess macrophage/lipid-rich plaques in vivo and facilitate inflammation resolution. METHODS AND RESULTS: We fabricated a dectin-1-targeted photoactivatable theranostic agent through the chemical conjugation of the near-infrared fluorescence-emitting photosensitizer chlorin e6 and the dectin-1 ligand laminarin-chlorin e6. Intravascular photoactivation by a customized fiber-based diffuser after administration of laminarin-chlorin e6 effectively reduced inflammation in the targeted plaques of atherosclerotic rabbits in vivo as serially assessed by dual-modal optical coherence tomography-near-infrared fluorescence structural-molecular catheter imaging after 4 weeks. The number of apoptotic macrophages peaked at 1 day after laser irradiation and then resolved until 4 weeks. Autophagy was strongly augmented 1 hour after the light therapy, with the formation of autophagolysosomes. Laminarin-chlorin e6 photoactivation increased the terminal deoxynucleotidyl transferase dUTP nick end labeling/RAM11- and MerTK (c-Mer tyrosine kinase)-positive cells in the plaques, suggesting enhanced efferocytosis. In line with inflammation resolution, photoactivation reduced the plaque burden through fibrotic replacement via the TGF (transforming growth factor)-ß/CTGF (connective tissue growth factor) pathway. CONCLUSIONS: Optical coherence tomography-near-infrared fluorescence imaging-guided macrophage dectin-1-targetable photoactivation could induce the transition of macrophage/lipid-rich plaques into collagen-rich lesions through autophagy-mediated inflammation resolution and TGF-ß-dependent fibrotic replacement. This novel strategy offers a new opportunity for the catheter-based theranostic strategy.

Structure-based investigation of a DNA aptamer targeting PTK7 reveals an intricate 3D fold guiding functional optimization.

DNA aptamers have emerged as novel molecular tools in disease theranostics owing to their high binding affinity and specificity for protein targets, which rely on their ability to fold into distinctive three-dimensional (3D) structures. However, delicate atomic interactions that shape the 3D structures are often ignored when designing and modeling aptamers, leading to inefficient functional optimization. Challenges persist in determining high-resolution aptamer-protein complex structures. Moreover, the experimentally determined 3D structures of DNA molecules with exquisite functions remain scarce. These factors impede our comprehension and optimization of some important DNA aptamers. Here, we performed a streamlined solution NMR-based structural investigation on the 41-nt sgc8c, a prominent DNA aptamer used to target membrane protein tyrosine kinase 7, for cancer theranostics. We show that sgc8c prefolds into an intricate three-way junction (3WJ) structure stabilized by long-range tertiary interactions and extensive base-base stackings. Delineated by NMR chemical shift perturbations, site-directed mutagenesis, and 3D structural information, we identified essential nucleotides constituting the key functional elements of sgc8c that are centralized at the core of 3WJ. Leveraging the well-established structure-function relationship, we efficiently engineered two sgc8c variants by modifying the apical loop and introducing L-DNA base pairs to simultaneously enhance thermostability, biostability, and binding affinity for both protein and cell targets, a feat not previously attained despite extensive efforts. This work showcases a simplified NMR-based approach to comprehend and optimize sgc8c without acquiring the complex structure, and offers principles for the sophisticated structure-function organization of DNA molecules.

Highly sensitive antibiotic sensing based on optical weak value amplification: A case study of chloramphenicol.

The public health concern of antibiotic residues in animal-origin food has been a long-standing issue. In this work, we present a novel method for antibiotic detection, leveraging optical weak value amplification and harnessing an indirect competitive inhibition assay, which significantly boosts the system's sensitivity in identifying small molecule antibiotics. We chose chloramphenicol as a model compound and mixed it with chloramphenicol-bovine serum albumin conjugates to bind to the chloramphenicol antibody competitively. We achieved a broad linear detection range of up to 3.24 ng/mL and a high concentration resolution of 33.20 pg/mL. To further validate the universality of our proposed detection methodology, we successfully applied it to testing gibberellin and tetracycline. Moreover, we conducted regeneration experiments and real-sample correlation studies. This study introduces a novel strategy for the label-free optical sensing of small molecule antibiotics, greatly expanding the range of applications for sensors utilizing optical weak value amplification.

Omnidirectional image super-resolution via position attention network.

For convenient transmission, omnidirectional images (ODIs) usually follow the equirectangular projection (ERP) format and are low-resolution. To provide better immersive experience, omnidirectional image super resolution (ODISR) is essential. However, ERP ODIs suffer from serious geometric distortion and pixel stretching across latitudes, generating massive redundant information at high latitudes. This characteristic poses a huge challenge for the traditional SR methods, which can only obtain the suboptimal ODISR performance. To address this issue, we propose a novel position attention network (PAN) for ODISR in this paper. Specifically, a two-branch structure is introduced, in which the basic enhancement branch (BE) serves to achieve coarse deep feature enhancement for extracted shallow features. Meanwhile, the position attention enhancement branch (PAE) builds a positional attention mechanism to dynamically adjust the contribution of features at different latitudes in the ERP representation according to their positions and stretching degrees, which achieves the enhancement for the differentiated information, suppresses the redundant information, and modulate the deep features with spatial distortion. Subsequently, the features of two branches are fused effectively to achieve the further refinement and adapt the distortion characteristic of ODIs. After that, we exploit a long-term memory module (LM), promoting information interactions and fusions between the branches to enhance the perception of the distortion, aggregating the prior hierarchical features to keep the long-term memory and boosting the ODISR performance. Extensive results demonstrate the state-of-the-art performance and the high efficiency of our PAN in ODISR.

Predicting the Prognosis of HIFU Ablation of Uterine Fibroids Using a Deep Learning-Based 3D Super-Resolution DWI Radiomics Model: A Multicenter Study.

RATIONALE AND OBJECTIVES: To assess the feasibility and efficacy of a deep learning-based three-dimensional (3D) super-resolution diffusion-weighted imaging (DWI) radiomics model in predicting the prognosis of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids. METHODS: This retrospective study included 360 patients with uterine fibroids who received HIFU treatment, including Center A (training set: N = 240; internal testing set: N = 60) and Center B (external testing set: N = 60) and were classified as having a favorable or unfavorable prognosis based on the postoperative non-perfusion volume ratio. A deep transfer learning approach was used to construct super-resolution DWI (SR-DWI) based on conventional high-resolution DWI (HR-DWI), and 1198 radiomics features were extracted from manually segmented regions of interest in both image types. Following data preprocessing and feature selection, radiomics models were constructed for HR-DWI and SR-DWI using Support Vector Machine (SVM), Random Forest (RF), and Light Gradient Boosting Machine (LightGBM) algorithms, with performance evaluated using area under the curve (AUC) and decision curves. RESULT: All DWI radiomics models demonstrated superior AUC in predicting HIFU ablated uterine fibroids prognosis compared to expert radiologists (AUC: 0.706, 95% CI: 0.647-0.748). When utilizing different machine learning algorithms, the HR-DWI model achieved AUC values of 0.805 (95% CI: 0.679-0.931) with SVM, 0.797 (95% CI: 0.672-0.921) with RF, and 0.770 (95% CI: 0.631-0.908) with LightGBM. Meanwhile, the SR-DWI model outperformed the HR-DWI model (P < 0.05) across all algorithms, with AUC values of 0.868 (95% CI: 0.775-0.960) with SVM, 0.824 (95% CI: 0.715-0.934) with RF, and 0.821 (95% CI: 0.709-0.933) with LightGBM. And decision curve analysis further confirmed the good clinical value of the models. CONCLUSION: Deep learning-based 3D SR-DWI radiomics model demonstrated favorable feasibility and effectiveness in predicting the prognosis of HIFU ablated uterine fibroids, which was superior to HR-DWI model and assessment by expert radiologists.

High-resolution dataset of manual claustrum segmentation.

The claustrum has a unique thin sheet-like structure that makes it hard to identify in typical anatomical MRI scans. Attempts have been made to identify the claustrum in anatomical images with either automatic segmentation techniques or using atlas-based approaches. However, the resulting labels fail to include the ventral claustrum portion, which consists of fragmented grey matter referred to as "puddles". The current dataset is a high-resolution label of the whole claustrum manually defined using an ultra-high resolution postmortem MRI image of one individual. Manual labelling was performed by four independent research trainees. Two trainees labelled the left claustrum and another two trainees labelled the right claustrum. For every hemisphere we created a union of the two labels and assessed the label correspondence using dice coefficients. We provide size measurements of the labels in MNI space by calculating the oriented bounding box size. These data are the first manual claustrum segmentation labels that include both the dorsal and ventral claustrum regions at such a high resolution in standard space. The label can be used to approximate the claustrum location in typical in vivo MRI scans of healthy individuals.

Development of a robust non-targeted analysis approach for fast identification of endocrine disruptors and their metabolites in human urine for exposure assessment.

Endocrine disrupting chemicals are of concern because of possible human health effects, thus they are frequently included in biomonitoring studies. Current analytical methods are focused on known chemicals and are incapable of identifying or quantifying other unknown chemicals and their metabolites. Non-targeted analysis (NTA) methods are advantageous since they allow for broad chemical screening, which provides a more comprehensive characterization of human chemical exposure, and can allow elucidation of metabolic pathways for unknown chemicals. There are still many challenges associated with NTA, which can impact the results obtained. The chemical space, i.e., the group of known and possible compounds within the scope of the method, must clearly be defined based on the sample preparation, as this is critical in identifying chemicals with confidence. Data acquisition modes and mobile phase additives used with liquid chromatography coupled to high-resolution mass-spectrometry can affect the chemicals ionized and structural identification based on the spectral quality. In this study, a sample preparation method was developed using a novel clean-up approach with CarbonS cartridges, for endocrine-disrupting chemicals in urine, including new bisphenol A analogues and benzophenone-based UV filters, like methyl bis (4-hydroxyphenyl acetate). The study showed that data dependent acquisition (DDA) had a lower identification rate (40%) at low spiking levels, i.e., 1 ng/mL, compared to data independent acquisition (DIA) (57%), when Compound Discoverer was used. In DDA, more compounds were identified using Compound Discoverer, with an identification rate of 95% when ammonium acetate was compared to acetic acid (82%) as a mobile phase additive. TraceFinder software had an identification rate of 53% at 1 ng/mL spiking level using the DDA data, compared to 40% using the DIA data. Using the developed method, 2,4 bisphenol F was identified for the first time in urine samples. The results show how NTA can provide human exposure information for risk assessment and regulatory action but standardized reporting of procedures is needed to ensure study results are reproducible and accurate.

Super-resolution Multispectral Imaging Nanoimmunosensor for Simultaneous Detection of Diverse Early Cancer Biomarkers.

In medical diagnosis, relying on only one type of biomarker is insufficient to accurately identify cancer. Blood-based multicancer early detection can help identify more than one type of cancer from a single blood sample. In this study, a super-resolution multispectral imaging nanoimmunosensor (srMINI) based on three quantum dots (QDs) of different color conjugated with streptavidin was developed for the simultaneous screening of various cancer biomarkers in blood at the single-molecule level. In the experiment, the srMINI chip was used to simultaneously detect three key cancer biomarkers: carcinoembryonic antigen (CEA), C-reactive protein (CRP), and alpha-fetoprotein (AFP). The srMINI chip exhibited 108 times higher detection sensitivity of 0.18-0.5 ag/mL (1.1-2.6 zM) for these cancer biomarkers than commercial enzyme-linked immunosorbent assay kits because of the absence of interfering signals from the substrate, establishing considerable potential for multiplex detection of cancer biomarkers in blood. Therefore, the simultaneous detection of various cancer biomarkers using the developed srMINI chip with high diagnostic precision and accuracy is expected to play a decisive role in early diagnosis or community screening as a single-molecule biosensor.

Diagnostic Value of High-Resolution Vessel Wall Imaging Technique in Intracranial Arterial Stenosis and Occlusion: A Comparative Analysis with Digital Subtraction Angiography.

Objective: To analyze the diagnostic value of HR-VWI in intracranial arterial stenosis and occlusion and compare it with DSA. Methods: A retrospective analysis of clinical data of 59 patients with intracranial arterial stenosis in our hospital was conducted to compare the diagnostic results of the two methods for different degrees of intracranial stenosis and various morphological plaques. Results: The diagnosis of stenosis and occlusion by both methods showed no significant difference (P > 0.05). Comparison of plaque morphology detected by HR-VWI with pathological examination results showed no significant difference (P > 0.05); however, there was a significant difference between plaque morphology detected by DSA and pathological examination results (P < 0.05). Additionally, there was a significant difference between plaque morphology detected by HR-VWI and DSA (P < 0.05). Conclusion: HR-VWI technique is comparable to DSA technique in diagnosing intracranial arterial stenosis and occlusion, but it is superior to DSA in plaque morphology diagnosis.

Mutual learning with memory for semi-supervised pest detection.

Effectively monitoring pest-infested areas by computer vision is essential in precision agriculture in order to minimize yield losses and create early scientific preventative solutions. However, the scale variation, complex background, and dense distribution of pests bring challenges to accurate detection when utilizing vision technology. Simultaneously, supervised learning-based object detection heavily depends on abundant labeled data, which poses practical difficulties. To overcome these obstacles, in this paper, we put forward innovative semi-supervised pest detection, PestTeacher. The framework effectively mitigates the issues of confirmation bias and instability among detection results across different iterations. To address the issue of leakage caused by the weak features of pests, we propose the Spatial-aware Multi-Resolution Feature Extraction (SMFE) module. Furthermore, we introduce a Region Proposal Network (RPN) module with a cascading architecture. This module is specifically designed to generate higher-quality anchors, which are crucial for accurate object detection. We evaluated the performance of our method on two datasets: the corn borer dataset and the Pest24 dataset. The corn borer dataset encompasses data from various corn growth cycles, while the Pest24 dataset is a large-scale, multi-pest image dataset consisting of 24 classes and 25k images. Experimental results demonstrate that the enhanced model achieves approximately 80% effectiveness with only 20% of the training set supervised in both the corn borer dataset and Pest24 dataset. Compared to the baseline model SoftTeacher, our model improves mAP @0.5 (mean Average Precision) at 7.3 compared to that of SoftTeacher at 4.6. This method offers theoretical research and technical references for automated pest identification and management.

Nerve enlargement in patients with Noonan syndrome: A retrospective cohort study.

Noonan syndrome (NS) is an autosomal dominant condition characterized by facial dysmorphism, congenital heart disease, development delay, growth retardation and lymphatic disease. It is caused by germline pathogenic variants in genes encoding proteins in the Ras/mitogen-activated protein kinase signaling pathway. Nerve enlargement is not generally considered as a feature of NS, although some cases have been reported. High-resolution nerve ultrasound enables detailed anatomical assessment of peripheral nerves and can show enlarged nerves. This retrospective cohort study aims to describe the sonographic findings of patients with NS performed during a 1-year time period. Data on the degree of enlargement, the relation to increasing age, pain in extremities, genotype on the gene level and clinical features were collected. Twenty-nine of 93 patients visiting the NS Center of Expertise of the Radboud University Medical Center Nijmegen underwent high-resolution ultrasound. In 24 patients (83%) nerve enlargement was found. Most of them experienced pain. We observed a weak correlation with increasing age and the degree of nerve enlargement but no association with pain, genotype at the gene level or clinical features. This study shows that patients with NS have a high predisposition for sonographic nerve enlargement and that the majority experience pain.

Development and validation of a nomogram to predict diabetes ketoacidosis resolution time in a tertiary care hospital in the United Arab Emirates.

AIM: This study aimed to develop and validate a nomogram to predict prolonged diabetes ketoacidosis (DKA) resolution time (DRT). METHODS: We retrospectively extracted sociodemographic, clinical, and laboratory data from the electronic medical records of 394 adult patients with DKA admitted to Tawam Hospital between January 2017 and October 2022. Logistic regression stepwise model was developed to predict DRT ≥ 24 h. Model discrimination was evaluated using C-index and calibration was determined using calibration plot and Brier score. RESULTS: The patients' average age was 34 years; 54 % were female. Using the stepwise model, the final variables including sex, diabetes mellitus type, loss of consciousness at presentation, presence of infection at presentation, body mass index, heart rate, and venous blood gas pH at presentation were used to generate a nomogram to predict DRT ≥ 24 h. The C-index was 0.76 in the stepwise model, indicating good discrimination. Despite the calibration curve of the stepwise model showing a slight overestimation of risk at higher predicted risk levels, the Brier score for the model was 0.17, indicating both good calibration and predictive accuracy. CONCLUSION: An effective nomogram was established for estimating the likelihood of DRT ≥ 24 h, facilitating better resource allocation and personalized treatment strategy.

Dexamethasone treatment influences tendon healing through altered resolution and a direct effect on tendon cells.

Inflammation, corticosteroids, and loading all affect tendon healing, with an interaction between them. However, underlying mechanisms behind the effect of corticosteroids and the interaction with loading remain unclear. The aim of this study was to investigate the role of dexamethasone during tendon healing, including specific effects on tendon cells. Rats (n = 36) were randomized to heavy loading or mild loading, the Achilles tendon was transected, and animals were treated with dexamethasone or saline. Gene and protein analyses of the healing tendon were performed for extracellular matrix-, inflammation-, and tendon cell markers. We further tested specific effects of dexamethasone on tendon cells in vitro. Dexamethasone increased mRNA levels of S100A4 and decreased levels of ACTA2/α-SMA, irrespective of load level. Heavy loading + dexamethasone reduced mRNA levels of FN1 and TenC (p < 0.05), while resolution-related genes were unaltered (p > 0.05). In contrast, mild loading + dexamethasone increased mRNA levels of resolution-related genes ANXA1, MRC1, PDPN, and PTGES (p < 0.03). Altered protein levels were confirmed in tendons with mild loading. Dexamethasone treatment in vitro prevented tendon construct formation, increased mRNA levels of S100A4 and decreased levels of SCX and collagens. Dexamethasone during tendon healing appears to act through immunomodulation by promoting resolution, but also through an effect on tendon cells.

Identification of z-axis filopodia in growth cones using super-resolution microscopy.

A growth cone is a highly motile tip of an extending axon that is crucial for neural network formation. Three-dimensional-structured illumination microscopy, a type of super-resolution light microscopy with a resolution that overcomes the optical diffraction limitation (ca. 200 nm) of conventional light microscopy, is well suited for studying the molecular dynamics of intracellular events. Using this technique, we discovered a novel type of filopodia distributed along the z-axis ("z-filopodia") within the growth cone. Z-filopodia were typically oriented in the direction of axon growth, not attached to the substratum, protruded spontaneously without microtubule invasion, and had a lifetime that was considerably shorter than that of conventional filopodia. Z-filopodia formation and dynamics were regulated by actin-regulatory proteins, such as vasodilator-stimulated phosphoprotein, fascin, and cofilin. Chromophore-assisted laser inactivation of cofilin induced the rapid turnover of z-filopodia. An axon guidance receptor, neuropilin-1, was concentrated in z-filopodia and was transported together with them, whereas its ligand, semaphorin-3A, was selectively bound to them. Membrane domains associated with z-filopodia were also specialized and resembled those of lipid rafts, and their behaviors were closely related to those of neuropilin-1. The results suggest that z-filopodia have unique turnover properties, and unlike xy-filopodia, do not function as force-generating structures for axon extension.

Functional organization of 3D plant thylakoid membranes as seen by high resolution microscopy.

In the field of photosynthesis, only a limited number of approaches of super-resolution fluorescence microscopy can be used, as the functional architecture of the thylakoid membrane in chloroplasts is probed through the natural fluorescence of chlorophyll molecules. In this work, we have used a custom-built fluorescence microscopy method called Single Pixel Reconstruction Imaging (SPiRI) that yields a 1.4 gain in lateral and axial resolution relative to confocal fluorescence microscopy, to obtain 2D images and 3D-reconstucted volumes of isolated chloroplasts, obtained from pea (Pisum sativum), spinach (Spinacia oleracea) and Arabidopsis thaliana. In agreement with previous studies, SPiRI images exhibit larger thylakoid grana diameters when extracted from plants under low-light regimes. The three-dimensional thylakoid architecture, revealing the complete network of the thylakoid membrane in intact, non-chemically-fixed chloroplasts can be visualized from the volume reconstructions obtained at high resolution. From such reconstructions, the stromal connections between each granum can be determined and the fluorescence intensity in the stromal lamellae compared to those of neighboring grana.

Treatment with lipoxin A 4 improves influenza A infection outcome through macrophage reprogramming, anti-inflammatory and pro-resolutive responses.

Objective and design: Here, we evaluated whether a synthetic lipoxin mimetic, designated AT-01-KG, would improve the course of influenza A infection in a murine model. Treatment: Mice were infected with influenza A/H1N1 and treated with AT-01-KG (1.7 mg/kg/day, i.p.) at day 3 post-infection. Methods: Mortality rate was assessed up to day 21 and inflammatory parameters were assessed at days 5 and 7. Results: AT-01-KG attenuated mortality, reducing leukocyte infiltration and lung damage at day 5 and day 7 post-infection. AT-01-KG is a Formyl Peptide Receptor 2 (designated FPR2/3 in mice) agonist, and the protective responses were not observed in FPR2/3 -/- animals. In mice treated with LXA4 (50mg/kg/day, i.p., days 3-6 post-infection), at day 7, macrophage reprogramming was observed, as seen by a decrease in classically activated macrophages and an increase in alternatively activated macrophages in the lungs. Furthermore, the number of apoptotic cells and cells undergoing efferocytosis was increased in the lavage of treated mice. Treatment also modulated the adaptive immune response, increasing the number of anti-inflammatory T cells (Th2) and regulatory T (Tregs) cells in the lungs of the treated mice. Conclusions: Therefore, treatment with a lipoxin A4 analog was beneficial in a model of influenza A infection in mice. The drug decreased inflammation and promoted resolution and beneficial immune responses, suggesting it may be useful in patients with severe influenza.

[Advances in mapping analysis of ribonucleic acid modifications through sequencing].

Over 170 chemical modifications have been discovered in various types of ribonucleic acids (RNAs), including messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and small nuclear RNA (snRNA). These RNA modifications play crucial roles in a wide range of biological processes such as gene expression regulation, RNA stability maintenance, and protein translation. RNA modifications represent a new dimension of gene expression regulation known as the "epitranscriptome". The discovery of RNA modifications and the relevant writers, erasers, and readers provides an important basis for studies on the dynamic regulation and physiological functions of RNA modifications. Owing to the development of detection technologies for RNA modifications, studies on RNA epitranscriptomes have progressed to the single-base resolution, multilayer, and full-coverage stage. Transcriptome-wide methods help discover new RNA modification sites and are of great importance for elucidating the molecular regulatory mechanisms of epitranscriptomics, exploring the disease associations of RNA modifications, and understanding their clinical applications. The existing RNA modification sequencing technologies can be categorized according to the pretreatment approach and sequencing principle as direct high-throughput sequencing, antibody-enrichment sequencing, enzyme-assisted sequencing, chemical labeling-assisted sequencing, metabolic labeling sequencing, and nanopore sequencing technologies. These methods, as well as studies on the functions of RNA modifications, have greatly expanded our understanding of epitranscriptomics. In this review, we summarize the recent progress in RNA modification detection technologies, focusing on the basic principles, advantages, and limitations of different methods. Direct high-throughput sequencing methods do not require complex RNA pretreatment and allow for the mapping of RNA modifications using conventional RNA sequencing methods. However, only a few RNA modifications can be analyzed by high-throughput sequencing. Antibody enrichment followed by high-throughput sequencing has emerged as a crucial approach for mapping RNA modifications, significantly advancing the understanding of RNA modifications and their regulatory functions in different species. However, the resolution of antibody-enrichment sequencing is limited to approximately 100-200 bp. Although chemical crosslinking techniques can achieve single-base resolution, these methods are often complex, and the specificity of the antibodies used in these methods has raised concerns. In particular, the issue of off-target binding by the antibodies requires urgent attention. Enzyme-assisted sequencing has improved the accuracy of the localization analysis of RNA modifications and enables stoichiometric detection with single-base resolution. However, the enzymes used in this technique show poor reactivity, specificity, and sequence preference. Chemical labeling sequencing has become a widely used approach for profiling RNA modifications, particularly by altering reverse transcription (RT) signatures such as RT stops, misincorporations, and deletions. Chemical-assisted sequencing provides a sequence-independent RNA modification detection strategy that enables the localization of multiple RNA modifications. Additionally, when combined with the biotin-streptavidin affinity method, low-abundance RNA modifications can be enriched and detected. Nevertheless, the specificity of many chemical reactions remains problematic, and the development of specific reaction probes for particular modifications should continue in the future to achieve the precise localization of RNA modifications. As an indirect localization method, metabolic labeling sequencing specifically localizes the sites at which modifying enzymes act, which is of great significance in the study of RNA modification functions. However, this method is limited by the intracellular labeling of RNA and cannot be applied to biological samples such as clinical tissues and blood samples. Nanopore sequencing is a direct RNA-sequencing method that does not require RT or the polymerase chain reaction (PCR). However, challenges in analyzing the data obtained from nanopore sequencing, such as the high rate of false positives, must be resolved. Discussing sequencing analysis methods for various types of RNA modifications is instructive for the future development of novel RNA modification mapping technologies, and will aid studies on the functions of RNA modifications across the entire transcriptome.