Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Radiopharmaceuticals play an important role in the diagnosis and treatment of cardiovascular and cerebrovascular diseases， malignant tumors， central nervous system diseases， and other diseases. Under the urgent need for clinical diagnosis and treatment as well as medical development， the clinical research of radiopharmaceuticals has become a hotspot in international research. By analyzing the current situation of clinical research on radiopharmaceuticals in Europe， America， and China， the ethical issues of clinical research on radiopharmaceuticals were elaborated from four aspects， including lack of relevant laws and regulations， a higher risk of radiopharmaceuticals， dilemmas in ethical review， and insufficient radiation protection. Response principles and measures were proposed from four aspects， including improving regulations and policies， enhancing radiological protection for all parties involved in the research， strengthening ethical review， and reinforcing the training of relevant personnel， to enhance the quality and level of clinical research on radiopharmaceuticals.

A 36-year-old male patient presented with repeated myocardial infarction. Despite regular dual-antiplatelet therapy and intensive lipid-lowering therapy, he still experienced restenosis after coronary stent implantation. He then transferred to the Zhongshan Hospital, Fudan University. According to the disease history, combined with coronary artery inflammation observed by PET/CT and effective anti-inflammatory treatment, he was finally diagnosed with Behçet’s disease (BD) combined with isolated coronary arteritis. BD has been included in the Chinese Second Catalog of Rare Diseases, and the disease that only involves the coronary arteries is even rarer, which makes it very easy to misdiagnose and underdiagnosis in clinical practice. Strengthening the understanding of the complex clinical phenotypes of various vasculitis, attaching importance to multidisciplinary consultation, and dynamically following up are of great value for the early diagnosis of this disease.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Background and Objectives: The Fractional Flow Reserve and Intravascular UltrasoundGuided Intervention Strategy for Clinical Outcomes in Patients with Intermediate Stenosis (FLAVOUR) trial demonstrated non-inferiority of fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) compared with intravascular ultrasound (IVUS)-guided PCI. We sought to investigate the cost-effectiveness of FFR-guided PCI compared to IVUS-guided PCI in Korea. Methods: A 2-part cost-effectiveness model, composed of a short-term decision tree model and a long-term Markov model, was developed for patients who underwent PCI to treat intermediate stenosis (40% to 70% stenosis by visual estimation on coronary angiography).The lifetime healthcare costs and quality-adjusted life-years (QALYs) were estimated from the healthcare system perspective. Transition probabilities were mainly referred from the FLAVOUR trial, and healthcare costs were mainly obtained through analysis of Korean National Health Insurance claims data. Health utilities were mainly obtained from the Seattle Angina Questionnaire responses of FLAVOUR trial participants mapped to EQ-5D. Results: From the Korean healthcare system perspective, the base-case analysis showed that FFR-guided PCI was 2,451 U.S. dollar lower in lifetime healthcare costs and 0.178 higher in QALYs compared to IVUS-guided PCI. FFR-guided PCI remained more likely to be cost-effective over a wide range of willingness-to-pay thresholds in the probabilistic sensitivity analysis. Conclusions Based on the results from the FLAVOUR trial, FFR-guided PCI is projected to decrease lifetime healthcare costs and increase QALYs compared with IVUS-guided PCI in intermediate coronary lesion, and it is a dominant strategy in Korea.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.