Objective To explore the feasibility and image quality of respiratory-gated total-body ¹⁸F-FDG PET/CT imaging with a 4-minute acquisition in patients with malignant tumors. Methods Sixty-two patients with pathologically confirmed malignant tumors (118 lesions measured) who underwent total-body ¹⁸F-FDG PET/CT examination were consecutively enrolled at the Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, from September 23, 2021 to November 23, 2021, and their clinical and imaging data were retrospectively collected. PET data was acquired over 12 minutes with simultaneous respiratory waveform recorded. The data were reconstructed into four image sets: gated-12 group and gated-4 group (using all counts and the first 4-minute counts, respectively) and ungated-12 group and ungated-6 group (using all counts and the first 6-minute counts, respectively) reconstructed with respiratory gating that retained counts corresponding to the half respiratory window near end-expiration. Image quality assessment and quantitative analysis of lesions were performed and compared among the four image sets, and subgroup analyses were performed according to lesion location, size, and metabolic activity. Results The effective counts of 4 sets of PET images were highest in ungated-12 group, followed by ungated-6 group and gated-12 group, and lowest in gated-4 group (P＜0.001). Regardless of the metabolic level and size of the lesions, compared with the ungated-12 group and the ungated-6 group, the lesions in the gated-12 group showed higher maximum, average, and peak standardized uptake values (SUV_max, SUV_mean, and SUV_peak), tumor liver uptake ratio, tumor blood pool uptake ratio, and smaller metabolic volume (P＜0.05); There was no statistically significant difference in the above indicators between the gate-12 group and the gate-4 group. The background noise of gate-4 group images is slightly higher than that of gate-12 group images (Liver SUV_SD: [0.17＋0.05] vs [0.14＋0.04]); Blood pool SUV_SD: (0.08 ± 0.03) vs (0.06 ± 0.03). There was a statistically significant difference in subjective scores of PET image quality among the four groups (P＜0.001). The subjective scores of image quality in the gated-12 group (4.79 ± 0.41) were not significantly different from those in the non gated-12 group (4.97 ± 0.17) and non gated-6 group (4.79 ± 0.45), but were higher than those in the gated-4 group ([4.17 ± 0.45], P＜0.001)， And the scores have good consistency (Kappa＞0.75). Conclusion In total-body PET/CT imaging for malignant tumors, 4-minute respiratory-gated acquisition can achieve comparable quantitative performance to longer respiratory gating imaging while significantly shortening acquisition time. This approach demonstrates promising potential for clinical application.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P＜0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P＜0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.

OBJECTIVE To explore the application value of a diagnostic model based on machine learning and SHAP in the diagnosis of severe pneumonia caused by adenovirus infection in children.METHODS A total of 562 children with adenovirus infection who were admitted to Wuhan Third Hospital from Mar.2023 to Apr.2024 were selected and divided into a non-pneumonia group(n=236)and a pneumonia group(n=326).The pneumonia group was further divided into a training set(n=245)and a validation set(n=81)at a ratio of 3∶1.The training set was further categorized into a severe group(n=90)and a non-severe group(n=155)based on the severity of pneumonia.M ultivariate logistic regression analysis was used to identify the risk factors for severe pneumonia in children with adenovirus infection,and collinearity diagnosis was performed.Receiver operating characteristic(ROC)curves were used to validate the predictive performance of the model in both the training and validation sets,and the optimal model was selected.The optimal predictive model was interpreted using SHAP.RESULTS Compared with the non-pneumonia group,the pneumonia group had a high proportion of children aged＜2 years,with cough,wheezing,pulmonary consolidation,pleural effusion,mixed infections and allergic history,as well as long hospital stays and fever duration(P＜0.05).After univariate analysis and collinearity diagnosis to exclude confounding factors,the length of hospital stay(OR=1.112),fever duration(OR=1.964),wheezing(OR=2.430),pulmonary consolidation(OR=2.546),mixed infections(OR=2.617)and LDH level(OR=1.613)were identified as risk factors for severe pneumonia in children with adenovirus infection(P＜0.05).Among the eight machine learning models constructed based on these risk factors,the gradient boosting machine(GBM)model demonstrated the best performance in predicting severe pneumonia in children with adenovirus in-fection,with area under the curve(AUC)of 0.796 and 0.785 in the training and validation sets,respectively.SHAP analysis revealed that the top four contributing characteristics were LDH level,wheezing,fever duration and pulmonary consolidation.CONCLUSIONS The GBM model exhibits optimal performance in predicting the risk of severe pneumonia in children with adenovirus infection.Among the predictive characteristics,LDH level,wheezing,fever duration and pulmonary consolidation are significant,providing valuable reference for clinical di-agnosis and treatment.

A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P＜0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P＜0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.

Cilia,as cellular sensory organelles,actively partici-pate in and regulate cellular processes such as autophagy and metabolic breakdown during their generation and transportation.Autophagy,on the other hand,is a cell self-protection mecha-nism that maintains cellular homeostasis by clearing aggregates and damaged organelles.Combining recent research findings,this review comprehensively elucidates the bidirectional crosstalk between primary cilia and autophagy.Specifically,it highlights the crucial role of cilia-dependent signaling pathways in activa-ting cellular autophagy and how autophagy regulates cilia genera-tion and length by degrading specific ciliary proteins.Moreover,the dysregulation of primary cilia and autophagy is closely asso-ciated with the clinical manifestations and pathogenesis of vari-ous ciliopathy-related diseases such as polycystic kidney disease and tuberous sclerosis.In terms of pharmacotherapy,this review provides a comprehensive and in-depth overview of small mole-cule inhibitors targeting ciliogenesis,including cytoskeletal drugs and Hedgehog signaling pathway inhibitors.Despite the current limitations in clinical use,these drugs lay the groundw-ork for developing highly specific targeted small molecule inhibi-tors of ciliogenesis and for the treatment of ciliopathies and canc-ers.By systematically discussing ciliogenesis,autophagy,disea-ses and drugs,this review offers new insights for further elucida-ting the crosstalk between ciliogenesis and autophagy,exploring their pathological mechanisms in disease development,and de-veloping therapeutic strategies in the future.

Objective To compare the macular retinal thickness characteristics of diabetic kidney disease(DKD)patients with different blood pressure levels and explore the relationship between blood pressure and macular retinal damage in DKD patients.Methods A total of 435 DKD patients were selected and divided into four groups based on medical history and blood pressure:the non-hypertensive group(NH group,n=100),the well-controlled blood pressure group(G0 group,n=176),the grade 1 hypertension group(G1 group,n=118)and the grade 2 hypertension group(G2 group,n=41).General information,routine laboratory test results as well as the average thickness of the macular retinal nerve fiber layer(RNFL),ganglion cell layer(GCL),ganglion cell complex(GCC),choroidal layer(CL)and central macular retinal thickness(CMT)were compared between the four groups.The correlation between macular retinal thickness in both eyes and clinical data was analyzed.Results Compared with the G1 group and the G2 group,the G0 group had a longer duration of hypertension.Compared to the NH group,the G2 group had higher fasting plasma glucose(FPG).Compared to the G0 group,the G1 group and the G2 group had higher FPG,and the G2 group had higher glycated hemoglobin(HbA1c)and lower estimated glomerular filtration rate(eGFR).Compared to the NH group,the G0 group had decreased thickness in the GCL and GCC(P<0.05).The macular retinal thickness of the GCL and GCC in both eyes was negatively correlated with diastolic blood pressure(r=-0.158 and-0.195,respectively,P<0.05).Conclusion Macular retinal thickness is helpful in assessing the long-term effects of hypertension on optic nerve and microvascular damage in DKD patients.

Blonanserin,a second-generation atypical antipsychotic agent,acts as an antagonist for dopamine D2,D3,and serotonin 5-HT2A receptors.Clinical studies have demonstrated that blonanserin is non-inferior to other antipsychotics,such as haloperidol and risperidone,in alleviating the symptoms of schizophrenia.Moreover,it exhib-its beneficial effects on cognitive symptoms and social functioning,with a favorable safety profile,making it one of the key treatment options for schizophrenia.With extensive clinical experience accumulated in China,this expert consensus aims to provide psychiatrists with updated and localized guidance on the optimal use of blonan-serin.Based on a systematic review of the latest evidence-particularly studies in Chinese population,this paper pres-ents the updated Chinese expert recommendations for the clinical use of blonanserin in 2024.

Objective To explore the risk factors for noncontiguous spinal fractures(NSFs)in the elderly.Methods The clinical data of 614 elderly patients with spinal fracture from January 2013 to December 2019 were analyzed retrospectively.Patients were divided into the NSFs group and the Non-NSFs group according to whether NSFs occurred or not.Univariate analysis and multivariate Logistic regression analysis were used to screen the risk factors of NSFs.Results Univariate analysis showed that female(P=0.003),high-energy violent injury(P=0.032),osteoporosis(P=0.004),fracture in spring(P=0.020),and previous spinal fracture history(P<0.001)were associated with the occurrence of NSFs.Multivariate Logistic regression analysis showed that fracture in spring(P=0.024),previous spinal fracture history(P<0.001)and high-energy violent injury(P=0.038)were the independent risk factors for the occurrence of NSFs in the elderly.Conclusion High-energy violent injury,fracture in spring and previous spinal fracture history are the independent risk factors for the occurrence of NSFs in the elderly.Therefore,elderly patients with the above risk factors should be examined more carefully and comprehensively to avoid missed diagnosis and delayed diagnosis.In order to reduce the incidence of this disease,corresponding measures should be taken according to the preventable risk factors.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.