Objective To systematically evaluate the advance care planning readiness assessment tools applicable to the elderly and to provide a reliable assessment tool for the development of advance care planning.Methods PubMed,Web of Science,Cochrane Library,Embase,CINAHL,Yimaitong,Wanfang Database,China National Know-ledge Network,VIP Database,and China Biomedical Literature Database were systematically searched.The search time limit is from database establishment to April 30,2024.Pre-established medical care plan readiness assessment tools that meet the inclusion criteria were screened,and the"consensus based standards for the selection of health measurement instruments"was used to evaluate the methodological quality and measurement attributes of the inclusion assessment tools.The improved version of the evidence quality evaluation and recommendation strength grading method is used to grade the evidence of the assessment tool and form the final recommendation opinion.Results A total of 14 articles were included,including 10 advance care planning readiness assessment tools suitable for the elderly.None of the articles reported cross-cultural validity,measurement error,and responsiveness.The content validity and internal consistency of the Chinese Advance Care Planning Readiness Scale and the Advance Care Planning Readiness Scale for Chronic Disease Patients were both"adequate",with A-level recommendations,and the remaining assessment tools were all B-level recommendations.Conclusion There are various types of advance care planning readiness assessment tools for the elderly,but the methodological quality needs to be improved and the measurement properties need to be further evaluated.It is temporarily recommended to use the Chinese Advance Care Planning Readiness Scale and the Advance Care Planning Readiness Scale for Chronic Disease Patients.

Objective To design a visual command and management platform for hospitals to provide technical support for the unified management and command of people,events and materials in hospitals.Methods A hospital visual command and management platform based on 3D visualization technology was designed with the B/S architecture and developed with the front-end and back-end separation mode.The front end was realized with Vue+three.js framework,and the back end based on the SpringCloud microservice architecture was implemented with Java language.The platform developed was composed of three systems for visual display,integrated situation monitoring and command management.Results The platform developed realized intuitive display,real-time dynamic monitoring and efficient arrangement and command for kinds of data resources and different businesses in hospitals,and enhanced hospital emergency command and management efficiency and patient experience.Conclusion The platform developed meets the requirements of hospitals in command and management,and comprehensively improves the operation and management efficiency of hospitals.[Chinese Medical Equipment Journal,2025,46(6):42-46]

In the context of an aging society,the number of elderly cancer patients is constantly increasing,and geriatric oncology has garnered significant attention in recent years.Given the heterogeneity in the health status of older patients,it has become increasingly important to provide individualized diagnosis,treatment,follow-up,and care.Thus,it must be emphasized the Comprehensive Geriatric Assessment(CGA)for elderly patients,which encompasses their physical function,nutritional status,cognitive function,emotional state,comorbidities,polypharmacy,social situation,and treatment preferences.This article provides consensus recommendations on CGA tools for elderly patients prior to anticancer treatment,offering valuable references and insights for clinical practice in China.

Antibody-drug conjugates(ADCs)are emerging anti-cancer drugs that have been widely applied in the treatment of hematological and solid tumors.ADCs deliver cytotoxic drugs to tumor cells with precision through anti-body targeting,enhancing efficacy while reducing side effects.Elderly cancer patients face treatment challenges due to factors such as drug metabolism,multiple comorbidities and decreased physical function.However,ADCs have therapeutic advantages in elderly patients.The article discusses the efficacy,safety,dosing strategies,and adverse reaction management of ADCs in elderly patients,in order to provide effective and safe treatment options for elderly cancer patients.

Objective To evaluate the clinical value of a modified Cancer and Aging Research Group(CARG)model in guiding anticancer drug dose adjustments for elderly cancer patients in China.Methods This prospective study enrolled patients aged≥65 years with solid tumors at the Department of Oncology,Peking Union Medical College Hospital from September 1,2022 to October 29,2023.All patients underwent comprehensive geriatric assessment(CGA)and CARG risk scoring,and were stratified into low-,intermediate-,and high-risk groups.Anti-cancer drug doses(including chemotherapy,targeted therapy or immunotherapy)were reduced proportionally based on CARG risk stratification and treatment intent(curative vs.palliative).Treatment outcomes and adverse events(AEs)were recorded regularly.Fisher's Exact Test compared AE incidence between the CARG-guided dose adjust-ment group(experimental)and the physician-experience-guided dose adjustment group(control).Receiver operating characteristic(ROC)curve analysis was used to assess the predictive value of the CARG model for severe toxicity.Results Among 166 enrolled patients(median age:71 years[range:65-90];78.3%were male;68.7%had gastro-intestinal cancers;69.3%had stageⅣ),95 were assigned to the experimental group(CARG low-risk:24[25.3%],intermediate-risk:51[53.7%],high-risk:20[21.0%])and 71 were included into the control group.By December 31,2024,81 patients experienced disease progression and 10 patients died.Overall AE rates was 92.6%in the ex-perimental group and 94.4%in the control group,while grade≥3 AEs were recorded in 45.3%vs.43.7%,respec-tively(both P＞0.05).Conclusions The modified CARG model-guided dose adjustment strategy achieved comparable safety to empirical dose adjustment,which is in line with the individualized treatment paradigm for elderly cancer pa-tients,representing a structured framework for optimizing therapeutic decision-making in geriatric oncology.

Objective To investigate the effect of sal-like gene 2(Sall2)gene overexpression on the progression of disease in human superoxide dismutase 1(hSOD1)-G93A mutant amyotrophic lateral sclerosis(ALS)transgenic mice,with the aim of identifying potential therapeutic targets for ALS gene therapy.Methods Differential Sall2 gene were screened through bioinformatics analysis.Forty-eight ALS transgenic mice were selected for this study.AAV-PHP.eB-Sall2 adeno-associated virus with a neuron-specific promoter,human synapsin I(hSyn),was constructed and administered via tail vein injection to six-week-old mice.In parallel,the same litter of ALS mice received an injection of AAV-PHP.eB-GFP.The staining of Sall2 and neuron-specific nuclear protein(NeuN)/GFAP in the spinal cord and cerebral cortex of mice were detected through immunofluorescent double-label staining technology.The survival period,weight changes,exercise ability,and electromyographic changes of the gastrocnemius muscle were detected.The morphological changes in the spinal cord anterior horn neurons were detected through Nissl staining.The effect of Sall2 gene overexpression on the expression of the cell cycle protein E1(cyclin E1)was investigated through Western blotting.Results Bioinformatics analysis showed out that Sall2 was differentially expressed in ALS mice.Compared with ALS mice in the control group,the Sall2 protein expression of ALS mice in the overexpressing Sall2 gene group increased in both the spinal cord and cerebral cortex,and the Sall2 integral absorbance values of Sall2+/NeuN+double-positive cells were higher.The survival time of ALS mice in the Sall2 gene overexpressing group was prolonged,the rate of weight loss was slowed down,the performance in the rotarod and inverted grid tests was improved with longer times,and the positive sharp waves and fibrillation potentials in the gastrocnemius electromyography were reduced.The number of Nissl bodies labeled neurons increased in the spinal cord anterior horn of the Sall2 gene overexpressing mice,and the condition of neuronal damage was improved.Overexpression of the Sall2 gene also reduced the expression of cyclin E1 in both the spinal cord and cerebral cortex of ALS transgenic mice.Conclusion Overexpression of the Sall2 gene can delay disease progression and improve motor performance in ALS transgenic mice,affecting the expression of cyclin E1,thus exerting a therapeutic effect on these mice.

Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]

Objective To investigate the effect of ClearInfinity deep learning reconstruction algorithm on image quality and radiation dose of abdominal computed tomography angiography(CTA)at low kV and low contrast medium.Methods One hundred patients who underwent abdominal CTA were selected and randomly divided into group A and group B.Group A:tube voltage 70 kV,con-trast medium 30-35 mL,divided into A1 and A2 subgroups according to reconstruction algorithm,group A1 50%ClearInfinity,group A2 50%ClearView iterative algorithm;group B:tube voltage 100 kV,contrast medium 60-70 mL,50%ClearView.CT values and standard deviation(SD)values of region of interest(ROI)of abdominal aorta,proper hepatic artery,superior mesenteric artery,renal artery and common iliac artery were evaluated objectively,while signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated;subjective scores were evaluated by two physicians;radiation doses of groups A and B were analyzed.Results Volume CT dose index(CTDIvol),dose length product(DLP)and effective dose(ED)in group A were significantly lower than those in group B(P<0.05),subjective scores in group A1 and group B were higher than those in group A2(P<0.05),and there was no difference between group A1 and group B(P>0.05).Compared with group A1,SNR and CNR of all vessels in group A2 were significantly decreased.CT values of abdominal aorta and common iliac artery,CNR of common iliac artery and supe-rior mesenteric artery in group B were significantly increased,SNR of renal artery was significantly decreased(P<0.05).Conclusion ClearInfinity deep learning reconstruction algorithm combined with 70 kV scanning technology can obtain better abdom-inal CTA image quality,and effectively reduce the radiation dose and contrast medium of patients,which has high clinical application value.

Retinal vein occlusion(RVO)is the second most common blinding retinal vascular disease, and its secondary macular edema(ME)is an important cause of visual function impairment in patients. Intravitreal injection of anti-vascular endothelial growth factor(VEGF)drugs serves as the first-line treatment, yet it is confronted with such issues as the need for repeated injections and non-response in some patients. Imaging and laboratory biomarkers play a crucial role in the early accurate diagnosis, prediction of disease progression, and evaluation of visual prognosis of RVO-ME. This study systematically reviews the research progress of imaging and laboratory biomarkers related to the prognosis of RVO-ME after anti-VEGF treatment in recent years, covering imaging biomarkers like central retinal thickness and ellipsoid zone integrity, as well as laboratory biomarkers such as serum APLN and aqueous humor IL-6. It summarizes the associations between different biomarkers and the prognosis of anti-VEGF therapy, aiming to provide a basis for the early accurate assessment and optimization of individualized treatment for RVO-ME patients, which holds significant clinical reference value.

Objective To investigate the effect of ClearInfinity deep learning reconstruction algorithm on image quality and radiation dose of abdominal computed tomography angiography(CTA)at low kV and low contrast medium.Methods One hundred patients who underwent abdominal CTA were selected and randomly divided into group A and group B.Group A:tube voltage 70 kV,con-trast medium 30-35 mL,divided into A1 and A2 subgroups according to reconstruction algorithm,group A1 50%ClearInfinity,group A2 50%ClearView iterative algorithm;group B:tube voltage 100 kV,contrast medium 60-70 mL,50%ClearView.CT values and standard deviation(SD)values of region of interest(ROI)of abdominal aorta,proper hepatic artery,superior mesenteric artery,renal artery and common iliac artery were evaluated objectively,while signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated;subjective scores were evaluated by two physicians;radiation doses of groups A and B were analyzed.Results Volume CT dose index(CTDIvol),dose length product(DLP)and effective dose(ED)in group A were significantly lower than those in group B(P<0.05),subjective scores in group A1 and group B were higher than those in group A2(P<0.05),and there was no difference between group A1 and group B(P>0.05).Compared with group A1,SNR and CNR of all vessels in group A2 were significantly decreased.CT values of abdominal aorta and common iliac artery,CNR of common iliac artery and supe-rior mesenteric artery in group B were significantly increased,SNR of renal artery was significantly decreased(P<0.05).Conclusion ClearInfinity deep learning reconstruction algorithm combined with 70 kV scanning technology can obtain better abdom-inal CTA image quality,and effectively reduce the radiation dose and contrast medium of patients,which has high clinical application value.