Immunotherapy has become a pivotal modality in clinical cancer treatment. However, its effectiveness is limited to a small subset of patients due to the low antigenicity, impaired innate response, and various adaptive immune resistance mechanisms of the tumor microenvironment (TME). Accumulating evidence reveals the critical roles of metal elements in shaping immunity against tumor progression and metastasis. The marriage of metalloimmunotherapy and nanotechnology further presents new opportunities to optimize the physicochemical and pharmacokinetic properties of metal ions in a precise spatiotemporal control manner. Several metallodrugs have demonstrated encouraging immunotherapeutic potential in preliminary studies and are currently undergoing clinical trials at different stages, yet challenges persist in scaling up production and addressing long-term biosafety concerns. This review delineates how metal materials modulate biological activities across diverse cell types to orchestrate antitumor immunity. Moreover, it summarizes recent progress in smart drug delivery-release systems integrating metal elements, either as cargo or vehicles, to enhance antitumor immune responses. Finally, the review introduces current clinical applications of nanomedicines in metalloimmunotherapy and discusses potential challenges that impede its widespread translation into clinical practice.

Based on commonly used acupoints in the clinical acupuncture treatment of functional dyspepsia （FD）， this study systematically analyzes the therapeutic differences and synergistic effects between local and distal point selection. It also examines the suitability of primary acupoint selection for different FD subtypes， postprandial distress syndrome （PDS） and epigastric pain syndrome （EPS）. The findings suggest that a combination of local and distal acupoints may be more appropriate as primary points for PDS， whereas local acupoints alone may be more suitable for EPS. Additionally， the study explores the impact of various factors， such as stimulation techniques， needling order， intensity or stimulation parameters， and depth， on the efficacy of acupuncture. It concludes that the intrinsic properties of acupoints are the primary determinants of therapeutic direction. Other factors mainly influence the magnitude rather than the direction of the effect. Future research may further investigate how different acupoint combinations， local versus distal， affect the treatment outcomes of FD subtypes， providing new insights for clinical acupuncture prescriptions.

Objective:In carbon ion treatment planning of water phantom, establish a conversion factor calculation system and conversion factor curves for organs at risk (OAR) for microdosimetric kinetic models (MKM) and local effect models (LEM), and validate them in clinical patient planning.Methods:Using a uniform spherical water phantom as the research object, relative biological effectiveness-weighted doses (RWD) for the LEM were re-calculated based on the physical dose of RayStation-MKM. The median dose within the planning target volume (PTV) of LEM and MKM was regarded as the conversion factor. The impacts of single-fraction target prescription dose, spread-out Bragg peak (SOBP) width and depth, shape, and irradiation mode on the conversion factor were assessed, and a conversion factor calculation system was established. Additionally, the accuracy of the conversion factor calculation system was validated using both water phantoms and clinical patient cases. The conversion factor curves for OAR were computed based on clinical patient treatment plans.Results:The primary influencing factors for the conversion factors were the single-fraction prescription dose, target SOBP width and depth. The conversion factors were increased with the increase of SOBP width and target depth, whereas decreased with the increase of the single-fraction prescription dose. Under single-field irradiation, a conversion factor calculation system was established based on above 3 parameters. For the plans of 9 patients, the average difference between the calculated results and the conversion factor calculation system was 0.340% ± 0.203%, and the average difference in the conversion curves for OAR was 2.650% ± 2.399%.Conclusion:A dose conversion factor calculation system and conversion factor curves for OAR for carbon ion radiotherapy are established for MKM and LEM, and their accuracy meets the requirements for use in clinical patient treatment plans.

Objective:To explore the mediating effect of sleep quality on the relationship between serum vitamin D3 level and depressive symptoms in community-dwelling elderly people with mild cognitive impairment(MCI).Methods:A total of 480 elderly people with MCI meeting inclusion criteria in a community health service center from Jan 2023 to Dec 2023 were selected as the research objects.The general information questionnaire,mini-mental state examination(MMSE),activity of daily living scale(ADL),Center for Epidemiological Studies Depression Scale(CES-D)and Pittsburgh sleep quality index(PSQI)were used to investigate the subjects.Serum vitamin D3 level was detected within 1 week.Spearson correlation analysis was used to explore the correlation between sleep quality,serum vitamin D3 level and depressive symptoms.The mediating effect model was tested by Model 4 in the Process plug-in.Results:Among the 480 MCI elderly,the average score of depression was(12.28±4.75),the average serum vitamin D3 level was(25.81±7.09)ng/ml,and the average score of sleep quality was(7.17±2.71).Depression severity was positively correlated with sleep quality score(r=0.294,P＜0.01),and negatively correlated with serum vitamin D3 level(r=-0.237,P＜0.01).Serum vitamin D3 level was negatively correlated with sleep quality score(r=-0.225,P＜0.01).Bootstrap analysis showed that the mediating effect of sleep quality between serum vitamin D3 level and depression level was-0.064(95%CI:-0.115--0.023),accounting for 26.57%of the total effect.Conclusion:Sleep quality partially mediates the relationship between serum vitamin D3 level and depressive symptoms in the elderly with MCI in the community.

Objective:To explore the mediating effect of sleep quality on the relationship between serum vitamin D3 level and depressive symptoms in community-dwelling elderly people with mild cognitive impairment(MCI).Methods:A total of 480 elderly people with MCI meeting inclusion criteria in a community health service center from Jan 2023 to Dec 2023 were selected as the research objects.The general information questionnaire,mini-mental state examination(MMSE),activity of daily living scale(ADL),Center for Epidemiological Studies Depression Scale(CES-D)and Pittsburgh sleep quality index(PSQI)were used to investigate the subjects.Serum vitamin D3 level was detected within 1 week.Spearson correlation analysis was used to explore the correlation between sleep quality,serum vitamin D3 level and depressive symptoms.The mediating effect model was tested by Model 4 in the Process plug-in.Results:Among the 480 MCI elderly,the average score of depression was(12.28±4.75),the average serum vitamin D3 level was(25.81±7.09)ng/ml,and the average score of sleep quality was(7.17±2.71).Depression severity was positively correlated with sleep quality score(r=0.294,P＜0.01),and negatively correlated with serum vitamin D3 level(r=-0.237,P＜0.01).Serum vitamin D3 level was negatively correlated with sleep quality score(r=-0.225,P＜0.01).Bootstrap analysis showed that the mediating effect of sleep quality between serum vitamin D3 level and depression level was-0.064(95%CI:-0.115--0.023),accounting for 26.57%of the total effect.Conclusion:Sleep quality partially mediates the relationship between serum vitamin D3 level and depressive symptoms in the elderly with MCI in the community.

Objective:In carbon ion treatment planning of water phantom, establish a conversion factor calculation system and conversion factor curves for organs at risk (OAR) for microdosimetric kinetic models (MKM) and local effect models (LEM), and validate them in clinical patient planning.Methods:Using a uniform spherical water phantom as the research object, relative biological effectiveness-weighted doses (RWD) for the LEM were re-calculated based on the physical dose of RayStation-MKM. The median dose within the planning target volume (PTV) of LEM and MKM was regarded as the conversion factor. The impacts of single-fraction target prescription dose, spread-out Bragg peak (SOBP) width and depth, shape, and irradiation mode on the conversion factor were assessed, and a conversion factor calculation system was established. Additionally, the accuracy of the conversion factor calculation system was validated using both water phantoms and clinical patient cases. The conversion factor curves for OAR were computed based on clinical patient treatment plans.Results:The primary influencing factors for the conversion factors were the single-fraction prescription dose, target SOBP width and depth. The conversion factors were increased with the increase of SOBP width and target depth, whereas decreased with the increase of the single-fraction prescription dose. Under single-field irradiation, a conversion factor calculation system was established based on above 3 parameters. For the plans of 9 patients, the average difference between the calculated results and the conversion factor calculation system was 0.340% ± 0.203%, and the average difference in the conversion curves for OAR was 2.650% ± 2.399%.Conclusion:A dose conversion factor calculation system and conversion factor curves for OAR for carbon ion radiotherapy are established for MKM and LEM, and their accuracy meets the requirements for use in clinical patient treatment plans.

Objective To observe the value of artificial intelligence(AI)knowledge graph and image classification for quality control(QC)of chest posterior-anterior position X-ray radiograph(abbreviated as chest film).Methods Totally 9 236 chest films from 595 medical institutions in Anhui province imaging cloud platform were retrospectively enrolled.QC knowledge graph containing 21 classification labels were constructed.Firstly,QC of chest films based on the above knowledge graph were performed by 10 technicians for 2 rounds of single person and 1 round of multi person,and the results were recorded as A,B and C,respectively.Then AI algorithms were used to classify and evaluate based on knowledge graph,and the result was recorded as D.Finally,a QC expert reviewed results C and D to determine the final QC results and taken those as references to analyze the efficiency of the above 4 QC.Results The area under the curve(AUC)of AI algorithm for QC of chest films were all ≥0.780,with an average value of 0.939.The average precision of QC for chest films of A,B,C and D was 81.15％,85.47％,91.65％and 92.21％,respectively.Conclusion AI knowledge graph and image classification technology could be effectively used for QC of chest posterior-anterior position X-ray radiograph.

Purpose Develop deep learning models to assess the clarity of chest X-ray images and validate the model's effectiveness by comparing it with the subjective evaluations of radiologists.Materials and Methods A retrospective collection of 9 135 chest X-ray images from 590 hospitals in Anhui Province,spanning from June 2015 to August 2022,was organized involving multiple radiologists who repeatedly evaluated the clarity of the images using a five-level scoring system.Individual assessments were designated as A and B,whereas the collective result of multiple assessments was designated as C.By constructing a deep learning model based on ResNet-50,image clarity evaluations of chest X-ray images were performed,we used the result C as the training and testing data for the model.The model's evaluation results were denoted as D.A radiology quality control expert conducted an audit assessment of the model's evaluation results and the multi-person assessments of physicians,serving as the reference standard for image clarity.Their assessment results were labeled as E.Statistical analysis,including Spearman's rank correlation coefficient,root mean square error(RMSE)and accuracy was employed to evaluate the effectiveness of the model.Results Compared with the reference standard E,D achieved an average accuracy of 0.85,exceeding the accuracy of C,which stood at 0.84.The ρ values for A,B,C,D and E were 0.58(0.54,0.62),0.59(0.55,0.63),0.74(0.71,0.77)and 0.80(0.78,0.82),respectively.The model exhibited the highest correlation with E.The ρ between A and B was 0.45(0.41,0.49),indicating a lower correlation between two individual subjective assessments of image clarity.The RMSE values for A,B,C,D and E were 0.99,0.94,0.72,and 0.71,respectively.The model's RMSE was lower than that of manual assessments.Conclusion This research model is capable of accurately assessing the clarity of chest X-ray images,and reducing the subjective interference of manual evaluation through deep learning methods,thereby providing an effective and objective evaluation tool for the assessment of clarity in clinical radiographic images.

Purpose To explore the influence of different spin-locking frequencies on T1ρ values based on a 3.0T MR system.Materials and Methods Thirty-eight healthy adult volunteers underwent cardiac magnetic resonance imaging at the First Affiliated Hospital of Anhui Medical University from July to September 2023.T1ρ mapping and short-axis cine imaging with steady-state free precession sequences were performed with 3.0T MR system.T1ρ mapping sequence in three short-axis slices with three spin-lock frequencies at the amplitude of 5 Hz,300 Hz,400 Hz,and 500 Hz was scanned,respectively.T1ρ relaxation times and myocardial fibrosis index were quantified for each slice and each myocardial segment,the difference in T1ρ of different spin-locking frequencies and myocardial fibrosis index was analyzed using one-way repeated-measures analysis of variance method.Results T1ρ of 5 Hz,300 Hz,400 Hz,and 500 Hz were(33.9±2.8)ms,(43.4±2.1)ms,(45.4±2.6)ms and(46.5±2.4)ms,respectively;and T1ρ values showed a significant progressive increase from the low spin-lock frequency to the high spin-lock frequency of the heart(300 Hz vs.400 Hz:P<0.001;300 Hz vs.500 Hz:P<0.001;400 Hz vs.500 Hz:P=0.043).In addition,the measured myocardial fibrosis index at 300 Hz,400 Hz and 500 Hz were(9.4±2.2)ms,(11.3±2.9)ms and(12.6±2.7)ms,respectively.Statistical analysis underscored significant variations among these measurements(300 Hz vs.400 Hz:P<0.001;300 Hz vs.500 Hz:P<0.001;400 Hz vs.500 Hz:P=0.033).Conclusion In this prospective study,myocardial T1ρ values for the specific cardiac magnetic resonance setting are provided,and we found that spin-lock frequency can affect the T1ρ values.

Purpose To explore the changes in biventricular volume and mass in chronic kidney disease(CKD)patients with preserved ejection fraction using cardiac magnetic resonance(CMR),and evaluate cardiac function using tissue-tracking strain analysis.Materials and Methods The retrospective analysis of 40 CKD patients without symptoms of cardiovascular disease,diabetes and the estimated glomerular filtration rate<60 ml/(min·1.73 m2)who were treated at the First Affiliated Hospital of Anhui Medical University from October 2020 to June 2023 and 25 age-and gender-matched healthy volunteers.All participants underwent 1.5T CMR scans to calculate left and right ventricular function,myocardial strain and native T1 and T2 values,and differences in various imaging parameters between the two groups were compared.Results The native T1 value[(1 109.6±35.9)ms]and T2 value[(58.1±2.9)ms]of CKD patients were significantly higher than those in control group[(1 046.3±15.9)ms,(53.3±2.3)ms](t=8.296,6.916,both P<0.001).The left ventricular end-diastolic volume index,left ventricular end-systolic volume index,left ventricular mass index,right ventricular end-diastolic volume index,right ventricular end-systolic volume index and right ventricular mass index of CKD patients were significantly increased compared with the control group(t=3.233,3.350,5.751,7.746,5.937,2.363,all P<0.05),while the left and right ventricular strain parameters,left ventricular global longitudinal strain,left ventricular global circumferential strain,left ventricular global radial strain,right ventricular global longitudinal strain,right ventricular global circumferential strain and right ventricular global radial strain were significantly decreased(t=9.506,9.072,-10.603,10.496,11.574,-4.018,all P<0.001),and the estimated glomerular filtration rate exhibited significant correlations with left ventricular global longitudinal strain(r=-0.636),left ventricular global radial strain(r=0.688),right ventricular global longitudinal strain(r=-0.513),right ventricular global circumferential strain(r=-0.827)and right ventricular global radial strain(r=0.514)(all P<0.001).Conclusion CMR can quantitatively assess myocardial fibrosis and edema in patients with CKD,and tissue tracking strain analysis can detect myocardial motion abnormalities before changes in ventricular ejection fraction,offering value in the early detection of cardiac involvement in CKD patients..