Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective:To investigate the value of nomogram model based on CT features in differentiating ectopic pancreas (EP) from gastrointestinal stromal tumors (GIST) with a long diameter less than 3 cm.Methods:This study was a case-control study. The clinical and imaging data of 43 patients with EP and 90 patients with GIST confirmed by pathology in the Affiliated Hospital of Guizhou Medical University from August 2013 to March 2024 were retrospectively analyzed. Preoperative CT images were analyzed to obtain qualitative features (number of lesions, location, morphology, growth pattern, borders, cystic degeneration, calcification, ulceration, catheter sign, central umbilication) and quantitative features (lesion long diameter, short diameter, long/short diameter, lesion and normal pancreas arterial-phase and venous-phase CT values, and enhancement ratio). Statistical analyses, including independent sample t-tests, Mann-Whitney U tests, χ2 tests, and Fisher exact tests, were performed to compare CT characteristics between the two groups. Binary logistic regression analysis was used to obtain independent predictors to identify the two groups, to establish a joint model, and to draw a nomogram. The discriminative performance of the independent predictors and the combined model was assessed using receiver operating characteristic (ROC) curves, while calibration curves were used to evaluate model fit. Results:The differences in age, location, morphology, border, catheter sign, central umbilication, short diameter, long/short diameter, arteriovenous phase enhancement CT value and arteriovenous phase enhancement ratio were statistically significant between the EP group and the GIST group (all P<0.05). The logistic analysis showed that the differences in age ( OR=0.920, 95% CI 0.885-0.956, P<0.001), border ( OR=5.994, 95% CI 2.111-17.022, P=0.001), long/short diameter ( OR=7.820, 95% CI 1.841-33.224, P=0.005), and venous phase enhancement ratio ( OR=8.847, 95% CI 1.103-70.972, P=0.040) were the independent predictors for distinguishing EP from GIST, and the area under the ROC curve (AUC) were 0.782 (95% CI 0.698-0.866), 0.684 (95% CI 0.600-0.767), 0.705 (95% CI 0.607-0.803), and 0.693 (95% CI 0.605-0.781), respectively. Combined age, border, long diameter/short diameter and venous phase enhancement ratio were plotted in a nomogram with an AUC of 0.881 (95% CI 0.817-0.945), sensitivity and specificity of 74.4% and 93.3%, respectively. The calibration curve demonstrated a strong agreement between predicted and actual probabilities (Hosmer-Lemeschow test, P=0.267). Conclusions:CT imaging reveals significant differences between EP and small GISTs (<3 cm). EP is more likely when patients are younger and lesions exhibit indistinct borders, a higher long-to-short diameter ratio, and greater venous-phase enhancement. The nomogram derived from CT features provides a valuable tool for differentiating EP from GIST.

The scaphoid bone is one of the important bone of hand,which is frequently injured and difficult to treat in clinical practice.Therefore,it is very important to deeply study the microstructure and biomechanical characteristics of the scaphoid bone for understanding its injury mechanism and optimizing treatment scheme.Microcomputed tomography(micro-CT)provides high-resolution imaging of bone tissue,while finite element analysis can help to simulate the stress distribution and behavioral patterns of the scaphoid bone under various physiological and pathological states.The high-resolution three-dimensional image of the scaphoid bone obtained by micro-CT technology can be used to construct finite element models of real anatomical structure of the scaphoid bone,thus achieving accurate simulation of the mechanical properties of the scaphoid bone.The fusion of these two advanced technologies provides a new perspective for revealing the structural and functional relationships and injury mechanism of the scaphoid bone.Therefore,this paper reviews the anatomical characteristics of the scaphoid bone and its biomechanical behavior in different states,emphasizing the specific applications and advantages of micro-CT and finite element analysis techniques in the study of the scaphoid bone.By summarizing the research findings in recent years,this paper provides novel scientific basis and methods for the diagnosis,treatment,and prevention of scaphoid bone-related disorders.

Aim To investigate the mechanism of Guanxinning injection regulating cardiac immune mi-croenvironment to improve myocardial infarction in mice.Methods In this study,MI model was estab-lished by permanent ligation of left anterior descending coronary artery in mice.The mice were divided into five groups:sham operation group,model group,Guanxinning injection low dose group,Guanxinning in-jection high dose group and positive drug captopril group.Hearts were weighed,heart tissues were collect-ed,and Masson staining was used for pathological anal-ysis of heart tissues;immunofluorescence staining was used to detect apoptosis and CCL21 expression in the infarct border zone;flow cytometry was used to detect the proportion of immune cells in myocardial ischemia tissues and lymph nodes;PCR was used to detect CCL21 expression in heart and in vitro human lymphat-ic endothelial cells(HLEC).Results Compared with the model group,the low and high dose groups of Guanxinning injection significantly improved cardiac hypertrophy.Apoptosis in the border zone of myocardi-al infarction was reduced in the low and high dose groups of Guanxinning injection and captopril group.Compared with the model group,the proportion of leu-kocytes in the infarct border zone was dreduced and the proportion of CD4+T cells,Treg cells,and CD8+T cells in the mediastinal lymph nodes and infarct border zone of the heart was regulated in the low and high dose groups of Guanxinning injection;CCL21 secretion by the heart and lymphatic vessels increased.Conclu-sions Guanxinning injection can significantly improve cardiac hypertrophy and fibrosis in MI mice,reduce ap-optosis in the infarct border zone,and play a role in an-ti-myocardial ischemia injury by promoting CCL21 ex-pression in lymphatic vessels to regulate the proportion of mediastinal lymph nodes and cardiac T cells after myocardial infarction.

Aim To investigate the mechanism of Guanxinning injection regulating cardiac immune mi-croenvironment to improve myocardial infarction in mice.Methods In this study,MI model was estab-lished by permanent ligation of left anterior descending coronary artery in mice.The mice were divided into five groups:sham operation group,model group,Guanxinning injection low dose group,Guanxinning in-jection high dose group and positive drug captopril group.Hearts were weighed,heart tissues were collect-ed,and Masson staining was used for pathological anal-ysis of heart tissues;immunofluorescence staining was used to detect apoptosis and CCL21 expression in the infarct border zone;flow cytometry was used to detect the proportion of immune cells in myocardial ischemia tissues and lymph nodes;PCR was used to detect CCL21 expression in heart and in vitro human lymphat-ic endothelial cells(HLEC).Results Compared with the model group,the low and high dose groups of Guanxinning injection significantly improved cardiac hypertrophy.Apoptosis in the border zone of myocardi-al infarction was reduced in the low and high dose groups of Guanxinning injection and captopril group.Compared with the model group,the proportion of leu-kocytes in the infarct border zone was dreduced and the proportion of CD4+T cells,Treg cells,and CD8+T cells in the mediastinal lymph nodes and infarct border zone of the heart was regulated in the low and high dose groups of Guanxinning injection;CCL21 secretion by the heart and lymphatic vessels increased.Conclu-sions Guanxinning injection can significantly improve cardiac hypertrophy and fibrosis in MI mice,reduce ap-optosis in the infarct border zone,and play a role in an-ti-myocardial ischemia injury by promoting CCL21 ex-pression in lymphatic vessels to regulate the proportion of mediastinal lymph nodes and cardiac T cells after myocardial infarction.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective:To investigate the value of nomogram model based on CT features in differentiating ectopic pancreas (EP) from gastrointestinal stromal tumors (GIST) with a long diameter less than 3 cm.Methods:This study was a case-control study. The clinical and imaging data of 43 patients with EP and 90 patients with GIST confirmed by pathology in the Affiliated Hospital of Guizhou Medical University from August 2013 to March 2024 were retrospectively analyzed. Preoperative CT images were analyzed to obtain qualitative features (number of lesions, location, morphology, growth pattern, borders, cystic degeneration, calcification, ulceration, catheter sign, central umbilication) and quantitative features (lesion long diameter, short diameter, long/short diameter, lesion and normal pancreas arterial-phase and venous-phase CT values, and enhancement ratio). Statistical analyses, including independent sample t-tests, Mann-Whitney U tests, χ2 tests, and Fisher exact tests, were performed to compare CT characteristics between the two groups. Binary logistic regression analysis was used to obtain independent predictors to identify the two groups, to establish a joint model, and to draw a nomogram. The discriminative performance of the independent predictors and the combined model was assessed using receiver operating characteristic (ROC) curves, while calibration curves were used to evaluate model fit. Results:The differences in age, location, morphology, border, catheter sign, central umbilication, short diameter, long/short diameter, arteriovenous phase enhancement CT value and arteriovenous phase enhancement ratio were statistically significant between the EP group and the GIST group (all P<0.05). The logistic analysis showed that the differences in age ( OR=0.920, 95% CI 0.885-0.956, P<0.001), border ( OR=5.994, 95% CI 2.111-17.022, P=0.001), long/short diameter ( OR=7.820, 95% CI 1.841-33.224, P=0.005), and venous phase enhancement ratio ( OR=8.847, 95% CI 1.103-70.972, P=0.040) were the independent predictors for distinguishing EP from GIST, and the area under the ROC curve (AUC) were 0.782 (95% CI 0.698-0.866), 0.684 (95% CI 0.600-0.767), 0.705 (95% CI 0.607-0.803), and 0.693 (95% CI 0.605-0.781), respectively. Combined age, border, long diameter/short diameter and venous phase enhancement ratio were plotted in a nomogram with an AUC of 0.881 (95% CI 0.817-0.945), sensitivity and specificity of 74.4% and 93.3%, respectively. The calibration curve demonstrated a strong agreement between predicted and actual probabilities (Hosmer-Lemeschow test, P=0.267). Conclusions:CT imaging reveals significant differences between EP and small GISTs (<3 cm). EP is more likely when patients are younger and lesions exhibit indistinct borders, a higher long-to-short diameter ratio, and greater venous-phase enhancement. The nomogram derived from CT features provides a valuable tool for differentiating EP from GIST.

The scaphoid bone is one of the important bone of hand,which is frequently injured and difficult to treat in clinical practice.Therefore,it is very important to deeply study the microstructure and biomechanical characteristics of the scaphoid bone for understanding its injury mechanism and optimizing treatment scheme.Microcomputed tomography(micro-CT)provides high-resolution imaging of bone tissue,while finite element analysis can help to simulate the stress distribution and behavioral patterns of the scaphoid bone under various physiological and pathological states.The high-resolution three-dimensional image of the scaphoid bone obtained by micro-CT technology can be used to construct finite element models of real anatomical structure of the scaphoid bone,thus achieving accurate simulation of the mechanical properties of the scaphoid bone.The fusion of these two advanced technologies provides a new perspective for revealing the structural and functional relationships and injury mechanism of the scaphoid bone.Therefore,this paper reviews the anatomical characteristics of the scaphoid bone and its biomechanical behavior in different states,emphasizing the specific applications and advantages of micro-CT and finite element analysis techniques in the study of the scaphoid bone.By summarizing the research findings in recent years,this paper provides novel scientific basis and methods for the diagnosis,treatment,and prevention of scaphoid bone-related disorders.

This study used kidney metabolomics to investigate the underlying mechanisms of Guilingji (GLJ) on mild cognitive impairment (MCI) rats. The rats were randomly divided into 6 groups (n = 8), i.e., control group, model group, positive drug (Ginkgo biloba tablet, donepezil) group, GLJ group (low and high dose group). The MCI rat model was replicated using subcutaneous injection of D-galactose into the back of the neck along with a semi-high-fat diet for a total of 8 weeks, and drug was administered from the 5th week for 4 weeks. The kidney function and renal pathological changes of each group of rats were tested. And LC-MS based kidney metabolomics coupled with multivariate data analysis were conducted to explore the potential biomarkers, and corresponding metabolic pathways were then determined. After administration of GLJ, the level of urea nitrogen was decreased compared with those of the model group, and the abnormalities of morphology in kidney tissues were improved. The positive drugs (ginkgo biloba tablet and donepezil) had no significant modulating effect on renal function indexes. Ginkgo biloba tablet can lessen the pathological injury of kidney tissue, and donepezil had no improvement on renal histopathology. A total of 23 MCI related differential metabolites were identified in kidney, and 17 metabolites were signifcantly restored by GLJ compared with those of the model group. Additionally, we found that the cysteine and methionine metabolism, nicotinate and nicotinamide metabolism, taurine and hypotaurine metabolism, glycerophospholipid metabolism were significantly involved in the regulatory effect of GLJ. The results illuminate the "cong shen zhi nao" mechanism of GLJ, and also provide a research basis for the clinical use of GLJ for the treatment of MCI. The animal experiment of this study was approved by the Ethics Committee of Shanxi University (approval number: 2020DW121).