OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

[Purpose]To analyze the incidence and mortality of pancreatic cancer in 2020 and the change trend from 2010 to 2020 in cancer registration areas of Gansu Province.[Methods]The data of pancreatic cancer from 2010 to 2020 were collected from cancer registries in Gansu Province.The crude incidence/mortality rate,age-standardized incidence/mortality rate by Chinese standard population(ASIRC/ASMRC)and world standard population(ASIRW/ASMRW),0～74 years old cumulative rate and proportion of pancreatic cancer were calculated.Joinpoint 4.7.0 software was used to calculate the average annual percentage change(AAPC)of ASIRC/ASMRC of pancreatic cancer in cancer registration areas of Gansu Province from 2010 to 2020.[Results]In 2020,a total of 838 new cases of pancreatic cancer were reported in the cancer registration areas of Gansu Province,with a crude incidence rate of 6.52/105,ASIRC and ASIRW of 4.03/105 and 4.49/105 respectively,accounting for 2.50％of all malignant tumor incidence.In 2020,702 cases of pan-creatic cancer deaths were reported in the cancer registration areas of Gansu Province,with a crude mortality rate of 5.46/105,ASMRC and ASMRW of 3.25/105 and 3.73/105,respectively,ac-counting for 3.98％of all malignant tumor deaths.From 2010 to 2020,a total of 2 413 cases of pancreatic cancer were reported in cancer registration areas in Gansu Province,accounting for 1.90％of all malignant tumors in the province.The crude incidence rate of pancreatic cancer was 5.28/105,the ASIRC was 4.18/105,the ASIRW was 4.63/105,and the cumulative rate of 0～74 years old was 0.49％.From 2010 to 2020,a total of 1 871 pancreatic cancer deaths were reported in cancer registration areas of Gansu Province,accounting for 2.38％of all malignant tumor deaths in the province.The crude mortality rate was 3.92/105,the ASMRC was 3.09/105,the ASMRW was 3.50/105,and the cumulative rate of 0～74 years old was 0.36％.In terms of sex and region,the incidence and mortality of pancreatic cancer from 2010 to 2020 in men were higher than those in women,and higher in rural areas than those in urban areas.From 2010 to 2020,the incidence and mortality were at a low level under the age of 44 years old,and increased significantly after 45 years old,reaching a peak in the age group of 80～84 years old.ASIRC showed no significant change from 2010 to 2020 with an AAPC of 0.41 1％(P＞0.05).From 2010 to 2020,the ASMRC showed an significantly increasing trend with an AAPC of 6.515％(P=0.014).[Conclusion]From 2010 to 2020,the ASRIC of pancreatic cancer in Gansu Province showed no significant change,while the ASMRC showed a significantly in-creasing trend.The incidence and mortality rates were higher in men than those in women and higher in rural areas than those in urban areas.Middle-aged and elderly men in rural areas are the key groups of prevention and treatment of pancreatic cancer,so targeted prevention and control measures should be carried out.

Loss of protein homeostasis is a hallmark of cellular senescence, and ribosome pausing plays a crucial role in the collapse of proteostasis. However, our understanding of ribosome pausing in senescent cells remains limited. In this study, we utilized ribosome profiling and G-quadruplex RNA immunoprecipitation sequencing techniques to explore the impact of RNA G-quadruplex (rG4) on the translation efficiency in senescent cells. Our results revealed a reduction in the translation efficiency of rG4-rich genes in senescent cells and demonstrated that rG4 structures within coding sequence can impede translation both in vivo and in vitro. Moreover, we observed a significant increase in the abundance of rG4 structures in senescent cells, and the stabilization of the rG4 structures further exacerbated cellular senescence. Mechanistically, the RNA helicase DHX9 functions as a key regulator of rG4 abundance, and its reduced expression in senescent cells contributing to increased ribosome pausing. Additionally, we also observed an increased abundance of rG4, an imbalance in protein homeostasis, and reduced DHX9 expression in aged mice. In summary, our findings reveal a novel biological role for rG4 and DHX9 in the regulation of translation and proteostasis, which may have implications for delaying cellular senescence and the aging process.
G-Quadruplexes ; Cellular Senescence ; Ribosomes/genetics* ; Humans ; Animals ; Mice ; DEAD-box RNA Helicases/genetics* ; Protein Biosynthesis ; RNA/chemistry* ; Neoplasm Proteins

Pre-admission is a critical initiative to optimize medical service processes and alleviate the challenge of "difficult access to healthcare. "However, there is currently a lack of standardized protocols for pre-admission procedures. This study aims to systematically analyze key nodes and risk factors in pre-admission process design and propose optimization strategies, providing a foundation for policy formulation and hospital practices. By constructing a "forward-reverse" dual-process model of pre-admission and identifying risk points based on stakeholder theory (patients, hospitals, healthcare administration, and insurance), the study reveals that while pre-admission can reduce the average length of stay, improve bed turnover rates, and enhance patient satisfaction, it also presents risks such as cross-period financial settlement, challenges in insurance policy adaptability, demands for information system integration, and the need for defining medical safety boundaries. To optimize the pre-admission process and mitigate these risks, this study explores framework improvements in areas including eligibility criteria, mode selection, cost settlement, transition between pre-admission and inpatient status, and cancellation of pre-admission, offering practical guidance for public hospitals. The authors argue that pre-admission requires tripartite collaboration among hospitals, insurers, and healthcare administrations: hospitals should establish top-level design, continuously refine processes, and implement dynamic risk assessment mechanisms; insurance providers should support cross-period settlement policies; and healthcare administrations should issue guiding policies or standardized protocols. Through multi-department coordination and collaborative efforts, the optimization and innovation of pre-admission processes can be advanced, ultimately delivering more efficient and convenient healthcare experiences for patients.

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 structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

[Purpose]To analyze the incidence and mortality of pancreatic cancer in 2020 and the change trend from 2010 to 2020 in cancer registration areas of Gansu Province.[Methods]The data of pancreatic cancer from 2010 to 2020 were collected from cancer registries in Gansu Province.The crude incidence/mortality rate,age-standardized incidence/mortality rate by Chinese standard population(ASIRC/ASMRC)and world standard population(ASIRW/ASMRW),0～74 years old cumulative rate and proportion of pancreatic cancer were calculated.Joinpoint 4.7.0 software was used to calculate the average annual percentage change(AAPC)of ASIRC/ASMRC of pancreatic cancer in cancer registration areas of Gansu Province from 2010 to 2020.[Results]In 2020,a total of 838 new cases of pancreatic cancer were reported in the cancer registration areas of Gansu Province,with a crude incidence rate of 6.52/105,ASIRC and ASIRW of 4.03/105 and 4.49/105 respectively,accounting for 2.50％of all malignant tumor incidence.In 2020,702 cases of pan-creatic cancer deaths were reported in the cancer registration areas of Gansu Province,with a crude mortality rate of 5.46/105,ASMRC and ASMRW of 3.25/105 and 3.73/105,respectively,ac-counting for 3.98％of all malignant tumor deaths.From 2010 to 2020,a total of 2 413 cases of pancreatic cancer were reported in cancer registration areas in Gansu Province,accounting for 1.90％of all malignant tumors in the province.The crude incidence rate of pancreatic cancer was 5.28/105,the ASIRC was 4.18/105,the ASIRW was 4.63/105,and the cumulative rate of 0～74 years old was 0.49％.From 2010 to 2020,a total of 1 871 pancreatic cancer deaths were reported in cancer registration areas of Gansu Province,accounting for 2.38％of all malignant tumor deaths in the province.The crude mortality rate was 3.92/105,the ASMRC was 3.09/105,the ASMRW was 3.50/105,and the cumulative rate of 0～74 years old was 0.36％.In terms of sex and region,the incidence and mortality of pancreatic cancer from 2010 to 2020 in men were higher than those in women,and higher in rural areas than those in urban areas.From 2010 to 2020,the incidence and mortality were at a low level under the age of 44 years old,and increased significantly after 45 years old,reaching a peak in the age group of 80～84 years old.ASIRC showed no significant change from 2010 to 2020 with an AAPC of 0.41 1％(P＞0.05).From 2010 to 2020,the ASMRC showed an significantly increasing trend with an AAPC of 6.515％(P=0.014).[Conclusion]From 2010 to 2020,the ASRIC of pancreatic cancer in Gansu Province showed no significant change,while the ASMRC showed a significantly in-creasing trend.The incidence and mortality rates were higher in men than those in women and higher in rural areas than those in urban areas.Middle-aged and elderly men in rural areas are the key groups of prevention and treatment of pancreatic cancer,so targeted prevention and control measures should be carried out.

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 structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

Objective To obtain the monitoring measurement range of quality indicators of red blood cells,plasma and derivatives and leukocyte-reduced apheresis platelets provided by blood stations in Hebei province,explore the distribution of monitoring values and the change of monitoring level,so as to further strengthen the homogenization construction of quality control laboratories in blood stations in Hebei.Methods In 2023,the sampling data of 12 blood stations in Hebei from 2015 to 2022 were collected,scatter plots were made and the range markers were set,and the"mean±SD"line was taken as the upper limit and lower limit of the measurement range.In 2024,the monitoring values in 2023 were added,and the changes of two measurement ranges were compared to analyze the stability and overall level.Results Comparison of the measurement range from 2015 to 2022 and the measurement range from 2015 to 2023 showed that the standard deviation of the content of deleukocyte suspension of red blood cells-hemoglobin,washed erythrocyte-hemoglobin,washed erythrocyte-su-pernatant protein,cryoprecipitate coagulation factor-FⅧ,fresh frozen plasma-FⅧ,leukocyte-reduced apheresis platelets-leukocyte residue and leukocyte-reduced apheresis platelet-red blood cell concentration decreased from 8.132 to 7.993,6.252 to 6.104,0.273 to 0.267,57.506 to 56.276,0.920 to 0.892,0.653 to 0.644 and 2.653 to 2.603,respectively.The narrowing of the standard deviation range of the above items led to more concentrated monitoring values and reduced disper-sion.Comparison of the measurement range from 2015 to 2022 and the measurement range from 2015 to 2023 showed that the mean value of leukocyte residue of the deleukocyte suspension of red blood cells,hemoglobin content of the wash eryth-rocyte,protein content of supernatant of the wash erythrocyte,hemolysis rate of the wash erythrocyte,FⅧ content of the cryoprecipitate coagulation factor,plasma protein content of the fresh frozen plasma,FⅧ content of the fresh frozen plasma,platelet content of the leukocyte-reduced apheresis platelets changed from 0.362 to 0.476,44.915 to 44.861,0.280 to 0.283,0.137 to 0.142,133.989 to 133.271,60.262 to 60.208,1.301 to 1.277 and 3.036 to 3.033,respectively,and was closer to the national standard line,which reflects an increase in the number of unqualified monitoring values or values close to the national standard line in 2023.The long-term qualified rate of coagulation items was low,and no improvement has been ob-served.The stability of biochemical items has been enhanced but overall deviation has occurred,with the average value close to the national standard line.The possibility of subsequent testing failure has increased.The counting items showed no obvi-ous common characteristics.Conclusion The use of"mean±SD"in the analysis can visually display the distribution of mo-nitoring values of different items in Hebei,forming an indicator measurement range covering the past nine years.It shows the characteristics of each item,and provides reference for subsequent quality control laboratory data analysis of each blood sta-tions to takes active measures to improve the monitoring level.