Objective:To investigate the clinical characteristics and genetic etiology of Duchenne muscular dystrophy (DMD) with myogenic tumors.Methods:The clinical data of 2 children with DMD combined with myogenic tumors diagnosed in Children′s Hospital Affiliated to Zhengzhou University in July 2021 and February 2022 were collected. The relevant literature was reviewed to summarize the clinical characteristics and explore the mechanism of the dystrophin ( DMD) gene in myogenic tumors. Results:A 6-year and 10-month-old boy with DMD (deletion of exon 45) and a 12-year-old boy with DMD (deletion of exon 51) were diagnosed with tumors. They were diagnosed with DMD for delayed motor development in the Department of Neurology of Children′s Hospital Affiliated to Zhengzhou University. They presented with painless masses in the waist. Postoperative pathological diagnosis: the pathology and immunohistochemistry of case 1 showed an alveolar rhabdomyosarcoma (ARMS) and both myogenin and myogenic differentiation 1 positive; the pathology and immunohistochemistry of case 2 showed an alveolar soft part sarcoma(ASPS) and transcription factor enhancer 3 positive; both cases were myogenic tumors. Literature review (including this paper) showed that there were in total 14 cases with DMD combined with myogenic tumors including 13 cases of rhabdomyosarcoma (RMS) and 1 case of ASPS. All of them are male, and the age of onset of the tumors was 4-17 years. Pathological subtypes were described in 6 cases of ARMS and 5 cases of embryonal RMS, and were not described in 2 cases. The 9 cases described all had large deletions in the DMD gene which can change the reading frame of the DMD gene, and all gene mutations did not exceed exon 62. Conclusions:DMD gene with deletion may increase the risk of having myogenic tumors, and RMS is more common, which is manifested as painless mass in early stage. All DMD gene deletions do not exceed exon 62 and lead to change of the gene reading frame with severe clinical phenotype and degenerative changes in muscle function.

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 and validate a fast Monte Carlo(MC)-based patient-specific quality assurance(PSQA)tool using the treatment log files that is suitable to be used in the online adaptive radiotherapy for pencil beam scanning proton therapy(PBSPT-ART).Methods The proposed tool first used the delivery log file of a PBSPT plan to reversely reconstruct the PBSPT(rPBSPT)plan,and then used an in-house developed graphic processing unit(GPU)-accelerated virtual particle MC(VPMC)dose engine to calculate the dose distribution of the rPBSPT plan.The rPBSPT dose calculated by VPMC was then compared to the rPBSPT dose calculated by another independent MC dose engine(MCsquare),using 3D gamma analysis to verify the accuracy of VPMC calculation.As a demonstration of the feasibility of developed log file-based PSQA,the VPMC calculated dose of the rPBSPT plan was compared to the pre-delivery second check dose of the corresponding PBSPT plan calculated by MCsquare,using 3D gamma analysis.3D gamma analysis employes a criterion of 2 mm/2%/10%.Twenty patients with different disease sites were representatively selected to validate the efficiency and accuracy of the tool.Results The average calculation time of a rPBSPT plan by VPMC was(5.88±4.00)s in the accuracy verification.Compared to MCsquare,the passing rate of the 3D gamma analysis was 99.47%±0.72%.In the proposed PSQA tool demonstration,the passing rate of comparing the VPMC calculated rPBSPT dose to MCsquare calculated second check dose of the corresponding PBSPT plan was 98.91%±0.92%.Conclusion The accuracy and efficiency of the tool can meet the requirements of PSQA in the online PBSPT-ART workflow.

Objective:To analyze clinical characteristics and prognosis of B-cell acute lymphoblastic leukemia(B-ALL)patients with IKZF1 deletion.Methods:72 patients with B-ALL admitted to our hospital from April 2020 to January 2023 were selected,IKZF1 deletion were detected,and clinical characteristics and prognosis were analyzed.Results:Among the 72 patients,a total of 32 patients(44.4％)were identified with IKZF1 deletions(IKZF1+).There was no statistically significant difference in basic clinical data between patients with normal IKZF1(IKZF1-)and those with IKZF1+(P＞0.05).The proportion of patients with IKZF1+in Ph+group was significantly higher than that in Ph-group(P＜0.05).The main types of IKZF1+were exon 1-8 deletion(34.4％)and exon 4-7 deletion(31.2％).The median OS and PFS of IKZF1-patients were significantly longer than those of IKZF1+patients(OS:26.0 months vs 16.0 months,x2=23.094,P＜0.05;PFS:26.0 months vs 16.0 months,x2=11.150,P＜0.05).Among IKZF1+patients,the median OS of patients who received allogeneic hematopoietic stem cell transplantation(allo-HSCT)was significantly longer than that of patients who did not receive allo-HSCT(no reached vs 15.0 months,x2=5.685,P＜0.05).Conclusion:IKZF1 deletion is a risk factor affecting the prognosis of B-ALL patients.

Objective To investigate the changes of serum microRNA (miR)-138-5p and microRNA(miR)-574-5p expression levels and their clinical significance in newborns acute respiratory distress syndrome (nARDS). Methods A total of 112 infants with nARDS from September 2018 to August 2023 in the Neonatal Department of Xiaogan Hospital Affiliated to Wuhan University of Science and Technology were collected as the observation group. They were divided into good prognosis group (n=98) and the poor prognosis group (n=14). A total of 104 healthy full-term newborns born at the same time were selected as the control group. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of miR-138-5p and miR-574-5p in serum. ROC curve was used to analyze the diagnostic value of serum miR-574-5p and miR-138-5p levels for poor prognosis of infants with nARDS. Multivariate Logistic regression analysis of factors affecting the poor prognosis of infants with nARDS. Results Compared with the control group,the expression level of serum miR-574-5p in the observation group increased (1.72±0.23 vs 1.04±0.17),with the expression level of miR-138-5p decreased (0.55±0.08 vs 1.02±0.16),with statistically significant differences (t=24.557,25.597,all P<0.05). Compared with the good prognosis group,the serum miR-138-5p expression level in the poor prognosis group decreased (0.41±0.06 vs 0.57±0.08),with the miR-574-5p expression level increased (2.07±0.25 vs 1.67±0.19),with statistically significant differences (t=7.188,7.069,all P<0.05). The age,intrauterine distress,and proportion of abnormal amniotic fluid in the poor prognosis group were higher than those in the good prognosis group (t=5.359,4.257,6.577,all P<0.05). MiR-574-5p was an independent risk factor for poor prognosis with nARDS,and miR-138-5p was a protective factor (all P<0.05).The AUC (95％ CI) of serum miR-138-5p and miR-574-5p alone and combined diagnosis of nADRS were 0.793 (0.706～0.864),0.898 (0.826～0.947) and 0.931 (0.867～0.970),respectively. The combined prediction of miR-138-5p and miR-574-5p were better than that of miR-138-5p alone and miR-574-5p alone (Z=2.151,1.982,all P<0.05). Conclusion The expression levels of miR-138-5p in serum of infant with nARDS were lower and the expression levels of miR-574-5p were higher,both of which have certain diagnostic value for poor prognosis of infant with nARDS .

Objective To develop and validate a fast Monte Carlo(MC)-based patient-specific quality assurance(PSQA)tool using the treatment log files that is suitable to be used in the online adaptive radiotherapy for pencil beam scanning proton therapy(PBSPT-ART).Methods The proposed tool first used the delivery log file of a PBSPT plan to reversely reconstruct the PBSPT(rPBSPT)plan,and then used an in-house developed graphic processing unit(GPU)-accelerated virtual particle MC(VPMC)dose engine to calculate the dose distribution of the rPBSPT plan.The rPBSPT dose calculated by VPMC was then compared to the rPBSPT dose calculated by another independent MC dose engine(MCsquare),using 3D gamma analysis to verify the accuracy of VPMC calculation.As a demonstration of the feasibility of developed log file-based PSQA,the VPMC calculated dose of the rPBSPT plan was compared to the pre-delivery second check dose of the corresponding PBSPT plan calculated by MCsquare,using 3D gamma analysis.3D gamma analysis employes a criterion of 2 mm/2%/10%.Twenty patients with different disease sites were representatively selected to validate the efficiency and accuracy of the tool.Results The average calculation time of a rPBSPT plan by VPMC was(5.88±4.00)s in the accuracy verification.Compared to MCsquare,the passing rate of the 3D gamma analysis was 99.47%±0.72%.In the proposed PSQA tool demonstration,the passing rate of comparing the VPMC calculated rPBSPT dose to MCsquare calculated second check dose of the corresponding PBSPT plan was 98.91%±0.92%.Conclusion The accuracy and efficiency of the tool can meet the requirements of PSQA in the online PBSPT-ART workflow.

Objective:To investigate the clinical characteristics and genetic etiology of Duchenne muscular dystrophy (DMD) with myogenic tumors.Methods:The clinical data of 2 children with DMD combined with myogenic tumors diagnosed in Children′s Hospital Affiliated to Zhengzhou University in July 2021 and February 2022 were collected. The relevant literature was reviewed to summarize the clinical characteristics and explore the mechanism of the dystrophin ( DMD) gene in myogenic tumors. Results:A 6-year and 10-month-old boy with DMD (deletion of exon 45) and a 12-year-old boy with DMD (deletion of exon 51) were diagnosed with tumors. They were diagnosed with DMD for delayed motor development in the Department of Neurology of Children′s Hospital Affiliated to Zhengzhou University. They presented with painless masses in the waist. Postoperative pathological diagnosis: the pathology and immunohistochemistry of case 1 showed an alveolar rhabdomyosarcoma (ARMS) and both myogenin and myogenic differentiation 1 positive; the pathology and immunohistochemistry of case 2 showed an alveolar soft part sarcoma(ASPS) and transcription factor enhancer 3 positive; both cases were myogenic tumors. Literature review (including this paper) showed that there were in total 14 cases with DMD combined with myogenic tumors including 13 cases of rhabdomyosarcoma (RMS) and 1 case of ASPS. All of them are male, and the age of onset of the tumors was 4-17 years. Pathological subtypes were described in 6 cases of ARMS and 5 cases of embryonal RMS, and were not described in 2 cases. The 9 cases described all had large deletions in the DMD gene which can change the reading frame of the DMD gene, and all gene mutations did not exceed exon 62. Conclusions:DMD gene with deletion may increase the risk of having myogenic tumors, and RMS is more common, which is manifested as painless mass in early stage. All DMD gene deletions do not exceed exon 62 and lead to change of the gene reading frame with severe clinical phenotype and degenerative changes in muscle function.

Objective To investigate the changes of serum microRNA (miR)-138-5p and microRNA(miR)-574-5p expression levels and their clinical significance in newborns acute respiratory distress syndrome (nARDS). Methods A total of 112 infants with nARDS from September 2018 to August 2023 in the Neonatal Department of Xiaogan Hospital Affiliated to Wuhan University of Science and Technology were collected as the observation group. They were divided into good prognosis group (n=98) and the poor prognosis group (n=14). A total of 104 healthy full-term newborns born at the same time were selected as the control group. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of miR-138-5p and miR-574-5p in serum. ROC curve was used to analyze the diagnostic value of serum miR-574-5p and miR-138-5p levels for poor prognosis of infants with nARDS. Multivariate Logistic regression analysis of factors affecting the poor prognosis of infants with nARDS. Results Compared with the control group,the expression level of serum miR-574-5p in the observation group increased (1.72±0.23 vs 1.04±0.17),with the expression level of miR-138-5p decreased (0.55±0.08 vs 1.02±0.16),with statistically significant differences (t=24.557,25.597,all P<0.05). Compared with the good prognosis group,the serum miR-138-5p expression level in the poor prognosis group decreased (0.41±0.06 vs 0.57±0.08),with the miR-574-5p expression level increased (2.07±0.25 vs 1.67±0.19),with statistically significant differences (t=7.188,7.069,all P<0.05). The age,intrauterine distress,and proportion of abnormal amniotic fluid in the poor prognosis group were higher than those in the good prognosis group (t=5.359,4.257,6.577,all P<0.05). MiR-574-5p was an independent risk factor for poor prognosis with nARDS,and miR-138-5p was a protective factor (all P<0.05).The AUC (95％ CI) of serum miR-138-5p and miR-574-5p alone and combined diagnosis of nADRS were 0.793 (0.706～0.864),0.898 (0.826～0.947) and 0.931 (0.867～0.970),respectively. The combined prediction of miR-138-5p and miR-574-5p were better than that of miR-138-5p alone and miR-574-5p alone (Z=2.151,1.982,all P<0.05). Conclusion The expression levels of miR-138-5p in serum of infant with nARDS were lower and the expression levels of miR-574-5p were higher,both of which have certain diagnostic value for poor prognosis of infant with nARDS .

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 evaluate the management and indicators of pathogen detection before antimicrobial treat-ment for inpatients in second level and above medical institutions(MIs)in Guangdong Province,and provide direc-tion and decision-making basis for the improvement of pathogen detection quality in the region.Methods The ma-nagement status,information system functions,and pathogen detection rate indicators of secondary and above MIs in 21 cities in Guangdong Province was surveyed through online questionnaire surveys and system submission.A baseline survey on sentinel monitoring MIs was conducted from July 15th to August 8th,2023.From November 7th to 30th,a baseline survey on non-sentinel monitoring MIs was launched.Surveys on indicator information of all MIs were completed from January 15th to 30th,2024.Results A total of 265 MIs were surveyed,and the proportions of establishing special working groups(83.98％),developing special action improvement plans(79.01％),estab-lishing pathogen detection rate management systems(91.71％),and developing management assessment plans(76.80％)of tertiary MIs were all higher than that of secondary MIs,differences were all statistically significant(all P＜0.05).The proportion of tertiary MIs with various information system functions was higher than that of secondary MIs(all P＜0.05).The pathogen detection rate(61.07％)before antimicrobial treatment and health-care-associated infection(HAI)diagnosis-related pathogen detection rate(88.00％)of inpatients in tertiary MIs were both higher than those in secondary MIs(both P＜0.05).Among different types of MIs,pathogen detection rate before antimicrobial treatment of inpatients in maternal and child health MIs was higher than that in other types of MIs.HAI diagnosis-related pathogen detection rate in other specialized hospitals was the highest,and pathogen detection rate before combined use of key antimicrobial treatment in traditional Chinese medicine hospitals was the lowest,differences were all statistically significant(all P＜0.05).Conclusion Tertiary MIs have more advantages in management strategies and information technology construction than secondary MIs,secondary MIs need more guidance and support.Monitoring and analysis of pathogen detection rate indicators in MIs of different levels and types should be strengthened through special actions.