Cardiac fibrosis is characterized by an elevated amount of extracellular matrix (ECM) within the heart. However, the persistence of cardiac fibrosis ultimately diminishes contractility and precipitates cardiac dysfunction. Circular RNAs (circRNAs) are emerging as important regulators of cardiac fibrosis. Here, we elucidate the functional role of a specific circular RNA CELF1 in cardiac fibrosis and delineate a novel feedback loop mechanism. Functionally, circ-CELF1 was involved in enhancing fibrosis-related markers' expression and promoting the proliferation of cardiac fibroblasts (CFs), thereby exacerbating cardiac fibrosis. Mechanistically, circ-CELF1 reduced the ubiquitination-degradation rate of BRPF3, leading to an elevation of BRPF3 protein levels. Additionally, BRPF3 acted as a modular scaffold for the recruitment of histone acetyltransferase KAT7 to facilitate the induction of H3K14 acetylation within the promoters of the Celf1 gene. Thus, the transcription of Celf1 was dramatically activated, thereby inhibiting the subsequent response of their downstream target gene Smad7 expression to promote cardiac fibrosis. Moreover, Celf1 further promoted Celf1 pre-mRNA transcription and back-splicing, thereby establishing a feedback loop for circ-CELF1 production. Consequently, a novel feedback loop involving CELF1/circ-CELF1/BRPF3/KAT7 was established, suggesting that circ-CELF1 may serve as a potential novel therapeutic target for cardiac fibrosis.

Objective To observe the value of multi-slice spiral CT(MSCT)post-processing technologies for diagnosing otosclerosis.Methods Clinical data and original axial plain MSCT of 47 patients with otosclerosis(92 ears)and 65 patients with non-otosclerosis hearing impairment(79 ears)were retrospectively enrolled.MSCT post-processing images,including multi-planar reformation(MPR)of stapes and cochleas and curved planar reformation(CPR)of ossicular chains were obtained.The diagnostic value of original MSCT images alone and raw data of MSCT combing with post-processing images for diagnosing otosclerosis were compared.Results Otosclerosis was correctly diagnosed in 66 ears according to original MSCT images alone,but in 89 ears combined with MSCT post-processing images.The sensitivity of original MSCT images alone and combined with MSCT post-processing images was 71.74％and 96.74％,respectively,and the diagnostic accuracy was 81.29％and 96.49％,respectively,those of the latter were both higher than of the former(both P＜0.05),which had specificities being not significantly different(92.41％vs.96.20％,P＞0.05).Conclusion Combining with post-processing technologies could increase the sensitivity and accuracy of MSCT for diagnosing otosclerosis.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

Traumatic supraorbital fissure syndrome (TSOFS) is a symptom complex caused by nerve entrapment in the supraorbital fissure after skull base trauma. If the compressed cranial nerve in the supraorbital fissure is not decompressed surgically, ptosis, diplopia and eye movement disorder may exist for a long time and seriously affect the patients′ quality of life. Since its overall incidence is not high, it is not familiarized with the majority of neurosurgeons and some TSOFS may be complicated with skull base vascular injury. If the supraorbital fissure surgery is performed without treatment of vascular injury, it may cause massive hemorrhage, and disability and even life-threatening in severe cases. At present, there is no consensus or guideline on the diagnosis and treatment of TSOFS that can be referred to both domestically and internationally. To improve the understanding of TSOFS among clinical physicians and establish standardized diagnosis and treatment plans, the Skull Base Trauma Group of the Neurorepair Professional Committee of the Chinese Medical Doctor Association, Neurotrauma Group of the Neurosurgery Branch of the Chinese Medical Association, Neurotrauma Group of the Traumatology Branch of the Chinese Medical Association, and Editorial Committee of Chinese Journal of Trauma organized relevant experts to formulate Chinese expert consensus on the diagnosis and treatment of traumatic supraorbital fissure syndrome ( version 2024) based on evidence of evidence-based medicine and clinical experience of diagnosis and treatment. This consensus puts forward 12 recommendations on the diagnosis, classification, treatment, efficacy evaluation and follow-up of TSOFS, aiming to provide references for neurosurgeons from hospitals of all levels to standardize the diagnosis and treatment of TSOFS.

Objective:To compare the effects of different reference brain regions on the semi-quantitative SUV ratio (SUVR) of 18F-Florzolotau PET images of Alzheimer′s disease (AD). Methods:The 18F-Florzolotau PET images of 28 (13 males, 15 females, age (57.3±9.5) years) normal controls (NC), 19 patients (4 males, 15 females, age (73.3±7.3) years) with β-amyloid (Aβ)-positive mild cognitive impairment (MCI) and 40 patients (19 males, 21 females, age (61.9±9.1) years) with AD were collected from Huashan Hospital, Fudan University between November 2018 and July 2020. Six semi-quantitative reference brain regions were defined, including whole cerebellum (WC), cerebellar gray matter (GM), cerebellar white matter (WM), parametric estimation of reference signal intensity (PERSI), WC after partial volume correction (WC_pvc), cerebellar GM after partial volume correction (GM_pvc). SUVR was calculated for 14 ROIs, which included the whole brain defined by the automated anatomical labeling (AAL) template, fusiform, inferior temporal, lingual, middle temporal, occipital, parahippocampal, parietal, posterior cingulate, precuneus defined by the AAL template, and Meta ROI composed of the above brain regions, and braak_Ⅰ-Ⅱ, braak_Ⅲ-Ⅳ, braak_Ⅴ-Ⅵ defined by the Desikan Killiany template. AUC was used to evaluate the classification ability of SUVR, and the correlation between SUVR and clinical scale scores were assessed by Spearman rank correlation analysis. Results:The SUVRs of most brain regions showed a steady upward trend in the AD disease spectrum. In the classification task of NC and MCI, the overall performance of SUVR based on WC_pvc was relatively optimal (AUCs: 0.975-1.000). In the classification task of NC and AD, SUVRs of 10 ROIs based on the WC_pvc method showed the relatively best performance (AUCs: 0.976-1.000). The correlation between SUVR of fusiform based on cerebellar WM and mini-mental state examination (MMSE) score was the strongest ( rs=-0.72, P<0.001), and the SUVR of precuneus based on WC_pvc showed the strongest correlation with clinical dementia rating (CDR) score ( rs=0.78, P<0.001). Conclusion:The SUVR based on WC_pvc method performs well in classification and correlation tasks, and is recommended to be used in semi-quantification of 18F-Florzolotau PET images of AD.

Objective:A voxel-level quantification method based on the tau IQ algorithm and Braak staging, excluding β-amyloid (Aβ) imaging, was developed to achieve specific tau quantification. Methods:This cross-sectional study included 92 subjects (35 males, 57 females; age (62.9±10.4) years) from the Nuclear Medicine/PET Center of Huashan Hospital, Fudan University between November 2018 and July 2020. The cohort comprised 28 cognitively normal (CN) individuals, 20 patients with mild cognitive impairment (MCI), and 44 patients with Alzheimer′s disease (AD). All participants underwent 18F-florzolotau PET imaging, Mini-Mental State Examination (MMSE), and Clinical Dementia Rating (CDR) scoring. A longitudinal tau dataset was constructed based on Braak staging. Voxel-level logistic regression fitting provided a baseline matrix, decomposed via least squares to yield the Tau load coefficient. One-way analysis of variance (with post hoc Tukey) was used to compare Tau load and SUV ratio (SUVR) among groups. ROC curve analysis was used to evaluate classification between CN, MCI and AD. Spearman rank correlation was used to assess the relationships between Tau load, SUVR, and MMSE scores or CDR scores. Results:The Tau load in the CN group was close to 0 and significantly lower than that in the MCI and AD groups ( F=55.03, P<0.001; post hoc tests all P<0.001). Significant differences were also observed in the SUVR across all ROIs ( F values: 36.46-55.38, all P<0.001). Compared to SUVR, Tau load demonstrated greater intergroup differences. In ROC curve analyses between each pair of CN, MCI, and AD groups, Tau load consistently achieved the highest AUC (0.754-1.000). Both Tau load and SUVR for each ROI were negatively correlated with MMSE scores ( rs values: from -0.698 to -0.583, all P<0.05) and positively correlated with CDR scores ( rs values: 0.648-0.783, all P<0.05), with Tau load showing the highest absolute correlation coefficients. Conclusion:Compared to the traditional semi-quantitative SUVR method, the Braak-tau IQ algorithm does not require a specific reference brain region to achieve specific tau quantification.

Objective:To investigate the changing trends in cardiac function following xenogeneic heterotopic heart transplantation of multi-gene edited pig hearts and assess the impact of recipient immune responses on donor heart, laying experimental groundwork for the clinical application of gene editing technology.Methods:On December 16, 2023, xenogeneic heterotopic heart transplantation was performed between pigs and rhesus monkeys. Functional status of the graft under post-transplantation load conditions and recipient immune indicators were observed.Results:The recipient monkeys survived for 40 days with satisfactory functionality of both donor and recipient hearts, and no hyperacute or acute immune rejection reactions were observed.Conclusion:Multi-gene editing technology provides potential for xenotransplantation, yet further exploration is needed for its clinical application.

Jumonji domain-containing protein D3(JMJD3)is a 2-oxoglutarate-dependent dioxygenase that specif-ically removes transcriptional repression marks di-and tri-methylated groups from lysine 27 on histone 3(H3K27me2/3).The erasure of these marks leads to the activation of some associated genes,thereby influencing various biological processes,such as development,differentiation,and immune response.However,comprehensive descriptions regarding the relationship between JMJD3 and inflammation are lacking.Here,we provide a comprehensive overview of JMJD3,including its structure,functions,and involvement in inflammatory pathways.In addition,we summarize the evidence supporting JMJD3's role in several inflammatory diseases,as well as the potential therapeutic applications of JMJD3 inhibitors.Additionally,we also discuss the challenges and opportunities associated with investigating the functions of JMJD3 and developing targeted inhibitors and propose feasible solutions to provide valuable insights into the functional exploration and discovery of potential drugs targeting JMJD3 for inflammatory diseases.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Objective:To explore the effect of fully automatic image segmentation of adenoid and nasopharyngeal airway by deep learning model based on U-Net network. Methods:From March 2021 to March 2022, 240 children underwent cone beam computed tomography（CBCT） in the Department of Otolaryngology, Head and Neck Surgery, General Hospital of Shenzhen University. 52 of them were selected for manual labeling of nasopharynx airway and adenoid, and then were trained and verified by the deep learning model. After applying the model to the remaining data, compare the differences between conventional two-dimensional indicators and deep learning three-dimensional indicators in 240 datasets. Results:For the 52 cases of modeling and training data sets, there was no significant difference between the prediction results of deep learning and the manual labeling results of doctors（P>0.05）. The model evaluation index of nasopharyngeal airway volume: Mean Intersection over Union（MIOU） s （86.32±0.54）%; Dice Similarity Coefficient（DSC）: （92.91±0.23）%; Accuracy: （95.92±0.25）%; Precision: （91.93±0.14）%; and the model evaluation index of Adenoid volume: MIOU: （86.28±0.61）%; DSC: （92.88±0.17）%; Accuracy: （95.90±0.29）%; Precision: （92.30±0.23）%. There was a positive correlation between the two-dimensional index A/N and the three-dimensional index AV/（AV+NAV） in 240 children of different age groups（P<0.05）, and the correlation coefficient of 9-13 years old was 0.74. Conclusion:The deep learning model based on U-Net network has a good effect on the automatic image segmentation of adenoid and nasopharynx airway, and has high application value. The model has a certain generalization ability.
Child ; Humans ; Adolescent ; Adenoids/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Pharynx ; Cone-Beam Computed Tomography ; Nose