Impaired glucose regulation （IGR） is an intermediate state between normal blood glucose and diabetes， falling under the category of splenic pure heat in traditional Chinese medicine （TCM）. The core pathogenesis is believed to be the dysfunction of the zang-fu （脏腑） organs， leading to metabolic abnormalities of subtle essence and the generation of "turbid pathogen". Its accumulation can block qi movement， damage the vessel collaterals， and promote the disease progression toward diabetes. The concept of "turbid pulse" is proposed as an early sign of IGR， characterized by full and heavy sensation with stagnated and astringent circulation， which can serve as an effective supplement to clinical screening. The differentiation and treatment approach in clinical practice is summarized as follows. If the ascending and descending mechanisms of qi movement in the middle jiao （焦） are disrupted， with mutual interference between the clear and the turbid， treatment should focus on harmonizing the ascending and the descending， and transforming dampness with aromatic medicinals. For spleen-stomach qi deficiency due to long-term restriction of the spleen and stomach's function of transportation and transformation， it is suggested to fortify spleen and harmonize stomach， and transport turbid with sweet-warm medicinals. For spleen deficiency and liver constraint induced by internal generation of damp-heat in the middle jiao， the treatment should focus on soothing the liver and opening constraint， and directing the turbid downward with sour-sweat medicinals. For solid accumulation and stagnation caused by liver qi constraint， it is recommended to unblock intestine and remove stagnation， and discharge turbid with bitter-cold medicinals. When the disease is transmitted to the lower jiao， and the kidneys are affected， the treatment should be regulating spleen and kidney， and rectifying turbid with salty-sour medicinals. In conclusion， it is emphasized to promote the transformation of turbid pathogen to restore metabolic homeostasis， providing methods for the clinical diagnosis and treatment of IGR.

In recent years,artificial intelligence(AI)has been widely used in the medical field.Research shows that medical AI can not only improve diagnosis and treatment efficiency,but also enable personalized health management and optimize the allocation of medical resources,demonstrating enormous potential.However,while"technology empowers",medical AI is also accompanied by a series of ethical paradoxes,mainly manifested as the conflict between technological innovation and the protection of humanistic value.Based on the AI ethical framework proposed by Italian philosophy and ethicist Floridi,this paper systematically analyzes paradoxical manifestations of medical AI and the possible causes in 5 core ethical principles:respecting autonomy,not harming,doing good,fairness,and interpretability.It also explains the causes of these paradoxes from technical,social,and philosophical levels,and puts forward the following coping strategies:first,to improve explainability,algorithm audit technology,differentiated data collection technology,privacy protection technology,and human supervision and control technology,strengthening technical governance;second,to improve ethical regulations and establish a dynamic ethical governance mechanism that adapts to the pace of technological development,a hierarchical management model,and a responsible innovation mechanism,further improving the legal and regulatory frameworks in terms of data security,algorithm ethical responsibility recognition,etc;and third,to establish a global collaborative system,build a global governance framework for medical AI,establish unified development and application standards,and promote cross-border policy coordination and technical standard docking.

Reporting guidelines are structured checklists for researchers to follow when reporting spe-cific types of studies.As researches conducted in real-world settings to address practical issues,implementa-tion research has stringent requirements for the replicability of result and the transparency of reporting,making its reporting guidelines particularly important.This paper systematically introduces the reporting guidelines in the field of implementation science,outlines their classification systems and scopes of applica-tion,and focuses on explaining the core characteristics and functions of five key reporting guidelines,inclu-ding the Standards for Reporting Implementation Studies(StaRI),Reporting guidelines for implementation and operational research,the Template for Intervention Description and Replication(TIDieR),the Frame-work for Reporting Adaptations and Modifications-Enhanced(FRAME),and recommendations for specifying and reporting implementation strategies.Furthermore,combined with the PEDALs research paradigm in im-plementation science,this paper further clarifies the specific application pathways for reporting guidelines and discusses directions for refinement,aiming to provide references for researchers to select appropriate reporting guidelines.

Objective To investigate the preoperative prediction of the expression level of programmed cell death ligand 1(PD-L1)in non-small cell lung cancer(NSCLC)by a nomogram model constructed with clinical data,conventional CT signs and spectral CT parameters.Methods A retrospective analysis was conducted on 52 patients with pathologically confirmed NSCLC and undergoing preoperative spectral CT examination.The patients were categorized into positive and negative groups according to PD-L1 expression level,and their clinical data,conventional CT signs and spectral CT parameters were collected.Specifically,clinical data included gender,age,Ki-67 and tumor markers;conventional CT signs included tumor density,margins,calcification,spiculation,lobulation,pleural indentation and cavitation;and spectral CT parameters measured in the arterial and venous phases included effective atomic number(Eff-Z),iodine concentration(IC),water concentration(WC)and normalized iodine concentration(NIC).Intergroup differences were analyzed,and multivariate Logistic regression was used to identify independent predictors and establish the prediction model which was evaluated for prediction performance and accuracy using receiver operating characteristic(ROC)curves,calibration curve and decision curve analyses.Results For clinical data,only the difference in gender between two groups had statistical significance(P<0.05).The spectral CT parameters(IC,NIC and Eff-Z)in the arterial and venous phases of PD-L1 positive group were all greater than those of PD-L1 negative group,with statistically significant differences(P<0.05).Multivariate Logistic regression analysis identified gender(P=0.024),venous-phase Eff-Z(P=0.002),and venous-phase IC(P=0.003)as independent predictive factors for PD-L1 expression.The nomogram prediction model constructed with these independent predictors had an area under curve of 0.80,a sensitivity of 88.00%,and a specificity of 59.00%.The calibration curve showed that the predicted values had a high consistency with the actual values.The decision curve revealed that when the high-risk threshold was between 0.10 and 0.83,the model could achieve the maximum net benefit.Conclusion The nomogram model constructed with spectral CT parameters and clinical data has certain value in predicting the expression level of PD-L1 in NSCLC.

Glioma is the most common primary malignant tumor of the central nervous system in adults. Despite the standard treatment of surgery combined with radiotherapy and chemotherapy, the prognosis for high-grade glioma patients remains poor, highlighting the urgent need to further explore its pathogenesis and develop new therapeutic strategies. This article reviews the research progress in the field of glioma in China in 2024, covering tumorigenesis mechanisms, tumor immune microenvironment composition, advances in imaging techniques and novel imaging agents, improvements in surgical approaches, mechanisms of radio- and chemoresistance, and explorations of new therapeutic modalities. These studies provide a solid theoretical foundation for advancing clinical diagnosis and treatment of gliomas and may offer new opportunities to improve patient outcomes.

Objective:This study aimed to investigate the association between genetic factors and the risk of developing treatment-resistant depression (TRD), as well as the efficacy of modified electroconvulsive therapy (MECT), with a specific focus on identifying gene polymorphisms that can differentiate TRD from non-TRD.Methods:This case-control study included inpatients with depression in Adult Psychiatry Department, Affective Disorders Department and Geriatrics Department of Guangzhou Medical University Affiliated Brain Hospital from January 2023 to June 2024, as well as healthy individuals undergoing physical examinations in the outpatient department. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was utilized to genotype 16 loci across 10 candidate genes in 107 non-TRD patients, 101 TRD patients and 281 healthy controls. Hardy-Weinberg equilibrium testing, genotype frequency distribution analysis, and genetic association studies were conducted using PLINK software. Univariate binary logistic regression under a dominant model was performed using R software to analyze gene loci associated with non-TRD and TRD.Results:All 16 gene loci in the control group, the TRD group, and the non-TRD group were found to be in Hardy-Weinberg equilibrium ( P>0.05). No significant differences were observed in the genotype distribution of these gene loci across the groups ( P>0.05). Univariate binary logistic regression analysis revealed that individuals with depression carrying the HTR2A-rs7997012 G allele had a significantly lower risk of developing TRD ( OR=0.26, P=0.047). Among the patients receiving MECT, the proportion of G allele carriers who showed improvement at 2, 4, and 6 weeks of treatment was significantly higher compared to those who did not show improvement (96.61% vs. 80.95%, 96.55% vs. 50.00%, 96.59% vs. 46.15%, respectively), with χ2 values of 6.743, 29.295, and 32.300, respectively, and all P values <0.05. Conclusion:The HTR2A-rs7997012 polymorphism may represent a genetic distinction between TRD and non-TRD. Depressed patients with the rs7997012 G allele have a reduced likelihood of developing TRD, moreover, MECT demonstrates superior efficacy in this patient population.

Objective To investigate the influence of the and mechanism of liver failing to convey and disperse on age-related changes in attentional search based on ERPs.Methods oddball attention search task was administrated to record and analyze behavioral and EEG data(N2pc、SPCN、N2pc-Ptc components)of 120 subjects.Results Compared with liver controlling conveyance and dispersion group,the accuracy in subjects with liver failing to convey and disperse decreased significantly(P<0.05).The elderly group had a lower accuracy(P<0.001)and a longer reaction time(P<0.001)compared to the young group.The N2pc amplitude in subjects with liver failing to convey and disperse was significantly greater than that in subjects with liver controlling conveyance and dispersion(P<0.05).The interaction effect of SPCN amplitude between age and liver failing to convey and disperse status was significant(P=0.024).And in the elderly group,SPCN amplitude in subjects with liver dysregulation was significantly smaller than that of liver controlling conveyance and dispersion(P=0.042).The N2pc-Ptc peak to peak amplitude interaction effect between age and liver regulation status was marginal significant(P=0.087),and in liver failing to convey and disperse group,N2pc-Ptc peak to peak amplitude of the elderly was significantly smaller than that of the young(P=0.008).Conclusion Attention search ability is impaired in the elderly with liver failing to convey and disperse,and the electrophysiological abnormalities,such as directed attention allocation,spatiotemporal dynamic cohesion and short-term memory maintenance,may be part of the mechanism.

Objective:To explore the feasibility of applying deep learning image reconstruction (DLIR) in low-radiation dose liver dual-energy CT to further improve image quality, diagnostic confidence of lesion, and accuracy of iodine concentration (IC) measurement.Methods:This prospective cohort study enrolled 60 patients scheduled for enhanced liver CT at the First Affiliated Hospital of Anhui Medical University from June 2023 to January 2024. The participants were randomly assigned into the standard dose group and low radiation dose group with 30 cases in each using randomized block method. The standard radiation dose group underwent standard-radiation dose 120 kVp scans during the venous phase, while the low radiation dose group underwent low radiation dose scans with a rapid kVp-switching spectral scanning mode at 80 kVp and 140 kVp. The effective radiation dose (ED) was calculated for both groups. The standard radiation dose group was reconstructed using adaptive statistical iterative reconstruction-V (ASIR-V) algorithm 40% (AR40 120 kVp). The low radiation dose group using high-intensity DLIR (DLIR-H) to reconstructed 40 keV and 50 keV virtual monoenergetic images (VMI) (DH-VMI 40 keV, DH-VMI 50 keV). The image quality of the above three groups was objectively evaluated through the measurement of image noise and calculation of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the liver and portal vein; and the image quality was subjectively scored for image noise, contrast, lesion conspicuity, and diagnostic confidence. In the low radiation dose group, DLIR-H and ASIR-V40% reconstructed iodine maps were used to measure the liver and portal vein of IC values, standard deviations (SD), and coefficients of variation (CV). One-way analysis of variance or Kruskal-Wallis H test was used to compare the differences of subjective and objective image quality among the three groups, and paired t-test was used to compare the differences in measurement indexes between DLIR-H and ASIR-V40% reconstructed iodine maps. Results:The ED in the low radiation dose group [(2.2±0.5) mSv] was reduced by 56.8% compared to the conventional radiation dose group [(5.4±1.4) mSv]. Objective evaluations demonstrated that DH-VMI 40 keV had higher image noise, CNR, and SNR for liver and portal veins compared to AR40 120 kVp ( P<0.001). DH-VMI 50 keV had lower image noise ( P=0.200), with higher CNR and SNR for the liver and portal vein compared to AR40 120 kVp( P<0.001). In subjective evaluation, there was no statistically significant difference in image noise scores between DH-VMI 40 keV and AR40 120 kVp ( P>0.05), while the image noise score for DH-VMI 50 keV was lower than that of AR40 120 kVp ( P<0.05). Both DH-VMI 40 keV and DH-VMI 50 keV had higher scores for contrast, lesion conspicuity, and diagnostic confidence compared to those of AR40 120 kVp ( P<0.05). In the low radiation dose group, there was no statistically significant difference in IC values for the liver and portal vein between the ASIR-V40% and DLIR-H algorithm reconstructed iodine maps ( P>0.05). The SD and CV of liver and portal vein in the DLIR-H reconstructed iodine maps were lower than those in the ASIR-V40% reconstructed iodine maps ( P<0.001). Conclusions:DLIR can effectively reduce the image noise of low-energy (40, 50 keV) VMI, enhance lesion conspicuity and diagnostic confidence, and improve measurement accuracy without affecting IC values.

Objective:To investigate the additional prognostic value of coronary CT angiography (CCTA)-based flow reserve fraction (CT-FFR) over semi-quantitative CCTA risk scores in predicting the occurrence of major adverse cardiovascular events (MACE) in type 2 diabetic patients.Methods:A total of 231 patients with type 2 diabetes mellitus who underwent CCTA at Lanzhou University from May 2020 to April 2021 were retrospectively enrolled. Clinical baseline data were collected, and patients were divided into a MACE-positive group (20 cases) and a MACE-negative group (211 cases) based on follow-up results. The CCTA images of all patients were analyzed by semi-quantitative CCTA risk score, which included coronary artery disease reporting and data system classification, segment involvement score, segmental stenosis score, Leaman score, and Leiden score. CT-FFR measurements of CCTA data of all patients were performed using Coronary Analysis software. t-test, U-test, and χ2 test were used to compare baseline parameters between MACE-positive and MACE-negative groups. The Cox proportional hazards regression model was used to analyze the relationship between semi-quantitative CCTA risk score and CT-FFR with the occurrence of MACE, and the area under the curve (AUC) of the receiver operating characteristic (ROC) was used to calculate the efficacy of the prediction model established by the semi-quantitative CCTA risk score combined with CT-FFR. Results:There was no statistically significant difference in baseline data between patients in the MACE-positive and MACE-negative groups ( P>0.05), and there were significant differences in semi-quantitative CCTA risk scores and CT-FFR ( P<0.05). Multivariate Cox proportional risk regression analysis of CT-FFR≤0.80 ( HR=3.860, 95% CI 1.477-10.087, P=0.006) and Leaman score≥5 ( HR=5.210, 95% CI 1.136-23.908, P=0.029) were the best and independent predictors for the occurrence of MACE events. The combined CT-FFR and Leaman score prediction model (AUC=0.791, 95% CI 0.733-0.842, P<0.001) was a better predictor of MACE than CT-FFR alone (AUC=0.718, 95% CI 0.656-0.775, P<0.001) and Leaman score alone (AUC=0.711, 95% CI 0.648-0.768, P<0.001) both had better predictive efficacy ( Z=2.62, 1.98, P=0.009, 0.047). Conclusion:CT-FFR independently predict the occurrence of MACE in patients with type 2 diabetes mellitus and significantly improve the predictive capacity of semi-quantitative CCTA risk score for MACE.

Objective:To investigate the prevalence and severity of symptom burden among long-term survivors of oropharyngeal cancer after radiotherapy, to identify core symptom clusters, and to explore their correlation with quality of life.Methods:A previous retrospective study was conducted by the Cancer Hospital, Chinese Academy of Medical Sciences on patients with oropharyngeal cancer who underwent radiotherapy between January 2010 and December 2020. Patients who were still alive as of December 2023 were further followed and analyzed. From December 2023 to August 2024, symptom burden and quality of life were assessed using the Chinese version of the MD Anderson Symptom Inventory–Head and Neck Module (MDASI-HN) and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ). Exploratory factor analysis (principal component analysis with Promax rotation) were used to identify symptom clusters. Spearman correlation analysis was performed to explore the relationship between total symptom cluster scores and standardized domain scores of quality of life. Multivariate linear regression analysis was further employed to determine the relationship between identified symptom clusters and overall quality of life.Results:A total of 273 patients were included, with a median follow-up duration of 6.2 years (range: 3.5-14.5 years) and a median age of 61 years (range: 27-88 years) at follow-up. The top 5 incidence rates of symptom reported by patients were mucus problems in the mouth or throat (147 cases, 53.8%), dental or gum issues (143 cases, 52.4%), xerostomia (140 cases, 51.3%), difficulty swallowing or chewing (95 cases, 34.8%), and taste disturbance (79 cases, 28.9%). Among them, xerostomia was the most serious symptom. The most frequently reported interference was impact on work (including household chores) (55 cases, 20.1%). Exploratory factor analysis identified 3 symptom clusters: fatigue-nausea cluster, eating-voice cluster, and xerostomia-sleep cluster, all of which were significantly correlated with lower overall quality of life of patients (all P<0.001). Conclusion:Long-term survivors of oropharyngeal cancer after radiotherapy experience substantial symptom burden. The fatigue-nausea, eating-voice, and xerostomia-sleep clusters are the core symptom clusters impacting quality of life.