Objective:To investigate the molecular characteristics of low-risk acute myeloid leukemia(AML)at recurrence,and analyze the factors affecting retreatment efficacy and prognosis.Methods:A retrospective analysis was conducted on the clinical and laboratory data of 31 patients with newly diagnosed low-risk AML who relapsed during consolidation treatment or follow-up after treatment in our hospital from April 2017 to January 2023.Gene mutations before and after relapse were compared,retreatment efficacy following relapse was evaluated,and univariate and multivariate analyses were performed to identify factors influencing treatment efficacy and prognosis.Results:Gene sequencing results after relapse showed that the most common newly acquired mutation was FLT3-ITD,while RAS mutation detected at initial diagnosis were predisposed to loss of expression during relapse.The median overall survival(OS)after relapse for the entire cohort was 349(170-528)days,with non-hematopoietic stem cell transplantation(HSCT)group and HSCT group demonstrating median survival times of 210(106-314)days and not reached,respectively(P=0.001).Multivariate analysis revealed that age ≥60 years was a significant risk factor for achieving remission after retreatment in initially diagnosed low-risk AML patients who experienced relapse(OR=18.222,95％CI:1.188-279.597,P=0.037).Additionally,DNMT3A mutation was identified as an independent risk factor for OS(HR=13.165,95％CI:2.018-85.877,P=0.007),while HSCT post-relapse demonstrated significant survival benefits(HR=0.133,95％CI:0.025-0.698,P=0.017)and served as an independent protective factor for OS.Conclusion:Relapsed low-risk AML is often associated with loss of RAS and novel mutations in FLT3-ITD.Age ≥ 60 years and DNMT3A mutations were identified as independent adverse factors for achieving subsequent remission and post-relapse survival,respectively,while HSCT significantly improved patient outcomes.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Purpose To explore the role of translesion synthesis-related gene NmrA like redox sensor 1(NMRAL1)in the development of papillary thyroid carcinoma(PTC).Methods Bioinformatics analysis was em-ployed to investigate the expression of the NMRAL1 gene across various cancer types and its correlation with prognosis.Immunohistochemistry was utilized to analyze the expression pattern of NMRAL1 in PTC and conduct clinicopathological correlation analysis.Additionally,stable cell lines overexpressing NMRAL1 were established in TPC-1 cells.The effects of NMRAL1 overexpression on cell proliferation,migration,and invasion of TPC-1 and Nthy-ori 3-1 cells were assessed using CCK-8 assay,clonogenic assay,Transwell assay,and scratch assay,respectively.Furthermore,RT-qPCR experiments were conducted to investigate the regulatory effect of NMRAL1 on the expression of genes associated with translesion DNA synthesis.Results Bioinformatics analysis revealed that NMRAL1 was highly expressed in all 26 types of tumors compared to normal tissues in the TCGA x GTEx dataset.Patients with high expression of NMRAL1 in thyroid cancer had significantly lower survival rates than those with low expression(P＜0.05).In the immunohisto-chemical validation of 30 PTC samples,NMRAL1 had a positive rate of 73.33％,in PTC tissues,while it was not ex-pressed in adjacent normal thyroid tissues.The staining intensity scores of NMRAL1 in PTC and adjacent tissues exhib-it significant differences(P＜0.000 1).High expression of NMRAL1 was associated with the size of the tumor(P=0.027 4)and lymph node metastasis(P=0.044 1).In vitro functional experiments revealed a significant enhance-ment in both cell proliferation and migration/invasion capacities upon overexpression of NMRAL1(P＜0.05).Moreo-ver,mRNA and protein expression levels of translesion synthesis-related genes were upregulated(P＜0.001).Con-clusion NMRAL1 promotes proliferation and migration of thyroid carcinoma cells,suggesting that this function may be achieved by enhancing DNA damage repair capacity,thereby improving the survival of damaged cells.

Objective:To investigate the molecular characteristics of low-risk acute myeloid leukemia(AML)at recurrence,and analyze the factors affecting retreatment efficacy and prognosis.Methods:A retrospective analysis was conducted on the clinical and laboratory data of 31 patients with newly diagnosed low-risk AML who relapsed during consolidation treatment or follow-up after treatment in our hospital from April 2017 to January 2023.Gene mutations before and after relapse were compared,retreatment efficacy following relapse was evaluated,and univariate and multivariate analyses were performed to identify factors influencing treatment efficacy and prognosis.Results:Gene sequencing results after relapse showed that the most common newly acquired mutation was FLT3-ITD,while RAS mutation detected at initial diagnosis were predisposed to loss of expression during relapse.The median overall survival(OS)after relapse for the entire cohort was 349(170-528)days,with non-hematopoietic stem cell transplantation(HSCT)group and HSCT group demonstrating median survival times of 210(106-314)days and not reached,respectively(P=0.001).Multivariate analysis revealed that age ≥60 years was a significant risk factor for achieving remission after retreatment in initially diagnosed low-risk AML patients who experienced relapse(OR=18.222,95％CI:1.188-279.597,P=0.037).Additionally,DNMT3A mutation was identified as an independent risk factor for OS(HR=13.165,95％CI:2.018-85.877,P=0.007),while HSCT post-relapse demonstrated significant survival benefits(HR=0.133,95％CI:0.025-0.698,P=0.017)and served as an independent protective factor for OS.Conclusion:Relapsed low-risk AML is often associated with loss of RAS and novel mutations in FLT3-ITD.Age ≥ 60 years and DNMT3A mutations were identified as independent adverse factors for achieving subsequent remission and post-relapse survival,respectively,while HSCT significantly improved patient outcomes.

Objective:To analyze the prevalence and risk factors of blindness and moderate to severe visual impairment among Han and Kazakh residents aged 50 years and older in Tacheng City, Xinjiang Uygur Autonomous Region.Methods:This study is a cross-sectional survey conducted using cluster random sampling from October 2015 to June 2018 in Emin County, Tacheng City, Xinjiang Uygur Autonomous Region. The study included individuals aged 50 years and older to survey blindness and moderate to severe visual impairment. Ophthalmological examinations combined with questionnaires were conducted to gather basic information. The data collected from the questionnaires included general demographic information and health conditions. The results of the eye examinations were used to diagnose a total of 12 risk factors including cataracts, glaucoma, pterygium, suspected glaucoma, glaucoma, and refractive errors. These risk factors were analyzed in relation to blindness and moderate to severe visual impairment. Univariate analysis was conducted first, followed by logistic regression to identify the significant factors.Results:A total of 2 114 patients were included in the final analysis, among which the prevalence of moderate to severe visual impairment was 18.54% (392/2 114), and the prevalence of blindness was 2.74% (58/2 114). Univariate analysis showed that blindness and moderate to severe visual impairment were associated with age ( χ2 = 32.97, P < 0.05), hypertension ( χ2 = 3.48, P < 0.05), age-related cataract ( χ2 = 17.43, P < 0.05), glaucoma ( χ2 = 3.90, P < 0.05), macular degeneration ( χ2 = 16.04, P < 0.05), diabetes ( χ2 = 3.09, P < 0.05), pterygium ( χ2 = 2.57, P < 0.05), and fundus arteriosclerosis ( χ2 = 2.31, P < 0.05). Multivariate logistic regression analysis indicated that moderate to severe visual impairment was correlated with age (50 to < 60 years: OR = 2.91, 95% CI: 0.44-13.45; 60 to < 70 years: OR = 3.52, 95% CI: 0.73-8.77; 70 to < 80 years: OR = 4.31, 95% CI: 0.85-8.96), ethnicity ( OR = 4.45, 95% CI: 0.56-5.95), sex ( OR = 0.47, 95% CI: 0.34-0.64), age-related cataract ( OR = 1.67, 95% CI: 1.05-2.65), glaucoma ( OR = 2.97, 95% CI: 1.67-5.30), and coronary heart disease ( OR = 2.56, P < 0.05). Blindness was correlated with age (70-79 years: OR = 1.54, 95% CI: 1.12-2.11), sex ( OR = 0.67, 95% CI: 0.34-0.64), glaucoma ( OR = 1.65, 95% CI: 0.42-6.49), diabetes ( OR = 2.05, 95% CI: 1.35-3.09), and coronary heart disease ( OR = 1.92, 95% CI: 1.07-3.43). Among these, age (70-79 years), glaucoma, diabetes, and coronary heart disease were identified as risk factors for blindness, while sex was observed as a protective factor against blindness in this region. Based on univariate and multivariate analyses as well as clinical practice, it was concluded that age (50 to < 60 years: OR = 4.42, 95% CI: 1.31-14.92; 60 to < 70 years: OR = 4.49, 95% CI: 1.70-11.84; 70 to < 80 years: OR = 3.19, 95% CI: 1.29-7.87), age-related cataract ( OR = 1.67, 95% CI: 1.05-2.65), and glaucoma ( OR = 2.97, 95% CI: 1.67-5.30) were identified as significant risk factors for moderate to severe visual impairment. Glaucoma ( OR = 1.65, 95% CI: 0.42-6.49) and diabetes ( OR = 2.05, 95% CI: 1.35-3.09) were identified as the main risk factors for blindness in this region (both P < 0.05). Conclusions:In Tacheng City, Xinjiang Uygur Autonomous Region, the prevalence rates of moderate to severe visual impairment and blindness among Han and Kazakh residents are relatively high. Age-related cataracts and glaucoma are the primary causes, while age and diabetes are the main risk factors.

Objective To explore the predictive value of dose surface histogram(DSH)in image guided radiotherapy(IGRT)for radiotherapy-induced acute radiation proctitis(ARP)in cervical cancer(CCA).Methods Totally 380 patients with CCA IGRT admitted to some hospital from May 2019 to May 2023 were selected prospectively and randomly divided into a control group(n=1 80)and an experimental group(n=200).The patients in the 2 groups were followed up and the incidence rates of ARP were counted,and rectal dose distribution was evaluated using dose volume histogram(DVH)in the control group and DSH in the experimental group.The predictive values of DVH and DSH for ARP were evaluated and compared using ROC curves.Statistical analysis was performed using SPSS 21.0 software.Results The two groups did not have statistically significant difference in the incidence rate of ARP(P＞0.05),while there were significant differences in the evaluation indicators of the rectal dose distribution(P＜0.05).V40,V50,S40 and S50 proved to have low predictive values for grade Ⅰ-Ⅳ ARP with AUC 0.700(P＜0.05);V60 and S60 had moderate predictive values for grade Ⅰ-Ⅳ ARP with AUC greater than 0.700 and less than or equal to 0.900(P＜0.05);V70,V78,S70 and S7s showed high predictive values for grade Ⅰ-Ⅳ ARP with AUC higher than 0.900(P＜0.05).Delong's test results indicated that DVH and DSH had no significant differences in AUC when used to predict gradeⅠ-Ⅳ ARP(allP＞0.05).Conclusion DSH is essentially the same as DVH when used for the prediction of grade Ⅰ-Ⅳ ARP due to CCA IGRT,and thus can be used for the supplementation and optimization of radiotherapy planning systems.[Chinese Medical Equipment Journal,2025,46(3):48-53]

Purpose To explore the role of translesion synthesis-related gene NmrA like redox sensor 1(NMRAL1)in the development of papillary thyroid carcinoma(PTC).Methods Bioinformatics analysis was em-ployed to investigate the expression of the NMRAL1 gene across various cancer types and its correlation with prognosis.Immunohistochemistry was utilized to analyze the expression pattern of NMRAL1 in PTC and conduct clinicopathological correlation analysis.Additionally,stable cell lines overexpressing NMRAL1 were established in TPC-1 cells.The effects of NMRAL1 overexpression on cell proliferation,migration,and invasion of TPC-1 and Nthy-ori 3-1 cells were assessed using CCK-8 assay,clonogenic assay,Transwell assay,and scratch assay,respectively.Furthermore,RT-qPCR experiments were conducted to investigate the regulatory effect of NMRAL1 on the expression of genes associated with translesion DNA synthesis.Results Bioinformatics analysis revealed that NMRAL1 was highly expressed in all 26 types of tumors compared to normal tissues in the TCGA x GTEx dataset.Patients with high expression of NMRAL1 in thyroid cancer had significantly lower survival rates than those with low expression(P＜0.05).In the immunohisto-chemical validation of 30 PTC samples,NMRAL1 had a positive rate of 73.33％,in PTC tissues,while it was not ex-pressed in adjacent normal thyroid tissues.The staining intensity scores of NMRAL1 in PTC and adjacent tissues exhib-it significant differences(P＜0.000 1).High expression of NMRAL1 was associated with the size of the tumor(P=0.027 4)and lymph node metastasis(P=0.044 1).In vitro functional experiments revealed a significant enhance-ment in both cell proliferation and migration/invasion capacities upon overexpression of NMRAL1(P＜0.05).Moreo-ver,mRNA and protein expression levels of translesion synthesis-related genes were upregulated(P＜0.001).Con-clusion NMRAL1 promotes proliferation and migration of thyroid carcinoma cells,suggesting that this function may be achieved by enhancing DNA damage repair capacity,thereby improving the survival of damaged cells.

Objective To investigate the density,species composition,and seasonal prevalence of domestic rodents in different habitats within Lanzhou garrisons,providing basic information for rodent prevention and control.Methods A total of 12 monitoring sites were sampled across urban,suburban,and rural residential areas from 2014 to 2022.Rodent density was monitored using the night-trapping method in the middle of odd-numbered months.Results From 2014 to 2022,346 domestic rodents were captured using 122 035 effective traps,with an average domestic rodent density of 0.28％.The highest domestic rodent density was 0.63％in 2016,and the lowest was 0.07％in 2020,showing significant differences across years,with an overall trend of initially decreasing and then increasing(χ2=136.555,P<0.001).The dominant species was Rattus norvegicus,accounting for 83.24％of the total rodents captured.Rattus norvegicus accounted for a relatively high proportion across different years,with a statistically significant difference in species composition(χ2=20.931,P<0.05).Rodent densities and species composition also varied significantly among the monitored habitats(P<0.001),with the highest densities observed in rural residential areas and the lowest in urban areas.Seasonal variation in rodent densities showed a bimodal pattern,with smaller peaks in January or March and a larger peak in July.Conclusions Domestic rodent density in Lanzhou garrisons has shown an upward trend in the past few years.Rodent control measures should focus on barracks in rural residential areas,with targeted interventions to reduce the risk of rodent-borne diseases.