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

Dysregulated RNA splicing is a well-recognized characteristic of colorectal cancer (CRC); however, its intricacies remain obscure, partly due to challenges in profiling full-length transcript variants at the single-cell level. Here, we employ high-depth long-read scRNA-seq to define the full-length transcriptome of colorectal epithelial cells in 12 CRC patients, revealing extensive isoform diversities and splicing alterations. Cancer cells exhibited increased transcript complexity, with widespread 3'-UTR shortening and reduced intron retention. Distinct splicing regulation patterns were observed between intrinsic-consensus molecular subtypes (iCMS), with iCMS3 displaying even higher splicing factor activities and more pronounced 3'-UTR shortening. Furthermore, we revealed substantial shifts in isoform usage that result in alterations of protein sequences from the same gene with distinct carcinogenic effects during tumorigenesis of CRC. Allele-specific expression analysis revealed dominant mutant allele expression in key oncogenes and tumor suppressors. Moreover, mutated PPIG was linked to widespread splicing dysregulation, and functional validation experiments confirmed its critical role in modulating RNA splicing and tumor-associated processes. Our findings highlight the transcriptomic plasticity in CRC and suggest novel candidate targets for splicing-based therapeutic strategies.
Humans ; Colorectal Neoplasms/metabolism* ; RNA Isoforms/metabolism* ; Single-Cell Analysis ; RNA Splicing ; Gene Expression Regulation, Neoplastic ; RNA, Neoplasm/metabolism* ; Transcriptome

Objective:To explore the application effect of nursing coordination process based on healthcare failure mode and effect analysis (HFMEA) management in the treatment of patients with acute ST-segment elevation myocardial infarction (STEMI), so as to improve clinical treatment efficiency.Methods:In this prospective cohort study, STEMI patients requiring emergency percutaneous coronary intervention (PCI) admitted to the Department of Emergency, Subei People′s Hospital of Jiangsu Province from January to May 2024 were selected by random sampling method. According to the admission time, patients were divided into control group (from January to February 2024, received routine emergency process) and experimental group (from April to May 2024, received nursing coordination process based on HFMEA management). The triage evaluation time, reception time, reporting time of the first electrocardiogram, coming out time of troponin T results, improvement time of preoperative preparation, treatment effect (length of hospital stay, success rate of treatment, nosocomial mortality) and emergency physicians′ satisfaction with nursing work in the two groups were compared.Results:In the 100 STEMI patients, there were 48 cases in the control group, with 23 males and 25 females, aged (61.64 ± 4.37) years old. There were 52 cases in the experimental group, with 26 males and 26 females, aged (62.11 ± 4.61) years old. The triage evaluation time, reception time, reporting time of the first electrocardiogram, coming out time of troponin T results and improvement time of preoperative preparation in the experimental group were (1.65 ± 0.57), (2.46 ± 0.57), (7.58 ± 1.32), (16.43 ± 2.16), (46.18 ± 3.94) min, shorter than (2.48 ± 0.69), (3.41 ± 0.63), (10.69 ± 1.24), (18.66 ± 2.37), (54.37 ± 4.11) min in the control group, the differences were statistically significant ( t values were 4.92-12.12, all P<0.05). The length of hospital stay and nosocomial mortality in the experimental group were (10.16 ± 2.34) d, 3.85% (2/52), lower than (12.38 ± 2.09) d, 16.67% (8/48) in the control group, and success rate of treatment was 90.38% (47/52), higher than 75.00% (36/48) in the control group, the differences were statistically significant ( t=4.99, χ2=4.56, 4.19, all P<0.05). The emergency physicians′ satisfaction with nursing work in the experimental group was (79.43 ± 6.00) points, higher than (64.44 ± 6.54) points in the control group, the difference was statistically significant ( t=11.95, P<0.05). Conclusions:Nursing coordination process based on HFMEA management can effectively improve emergency efficiency in STEMI patients, shorten emergency time and reduce nosocomial mortality.

Objective:To explore the application effect of nursing coordination process based on healthcare failure mode and effect analysis (HFMEA) management in the treatment of patients with acute ST-segment elevation myocardial infarction (STEMI), so as to improve clinical treatment efficiency.Methods:In this prospective cohort study, STEMI patients requiring emergency percutaneous coronary intervention (PCI) admitted to the Department of Emergency, Subei People′s Hospital of Jiangsu Province from January to May 2024 were selected by random sampling method. According to the admission time, patients were divided into control group (from January to February 2024, received routine emergency process) and experimental group (from April to May 2024, received nursing coordination process based on HFMEA management). The triage evaluation time, reception time, reporting time of the first electrocardiogram, coming out time of troponin T results, improvement time of preoperative preparation, treatment effect (length of hospital stay, success rate of treatment, nosocomial mortality) and emergency physicians′ satisfaction with nursing work in the two groups were compared.Results:In the 100 STEMI patients, there were 48 cases in the control group, with 23 males and 25 females, aged (61.64 ± 4.37) years old. There were 52 cases in the experimental group, with 26 males and 26 females, aged (62.11 ± 4.61) years old. The triage evaluation time, reception time, reporting time of the first electrocardiogram, coming out time of troponin T results and improvement time of preoperative preparation in the experimental group were (1.65 ± 0.57), (2.46 ± 0.57), (7.58 ± 1.32), (16.43 ± 2.16), (46.18 ± 3.94) min, shorter than (2.48 ± 0.69), (3.41 ± 0.63), (10.69 ± 1.24), (18.66 ± 2.37), (54.37 ± 4.11) min in the control group, the differences were statistically significant ( t values were 4.92-12.12, all P<0.05). The length of hospital stay and nosocomial mortality in the experimental group were (10.16 ± 2.34) d, 3.85% (2/52), lower than (12.38 ± 2.09) d, 16.67% (8/48) in the control group, and success rate of treatment was 90.38% (47/52), higher than 75.00% (36/48) in the control group, the differences were statistically significant ( t=4.99, χ2=4.56, 4.19, all P<0.05). The emergency physicians′ satisfaction with nursing work in the experimental group was (79.43 ± 6.00) points, higher than (64.44 ± 6.54) points in the control group, the difference was statistically significant ( t=11.95, P<0.05). Conclusions:Nursing coordination process based on HFMEA management can effectively improve emergency efficiency in STEMI patients, shorten emergency time and reduce nosocomial mortality.

Objective:To investigate the predictive values of 18F-FDG PET/CT image feature and metabolic parameters for the malignant potential of gastrointestinal stromal tumor (GIST). Methods:From March 2014 to June 2020, the 18F-FDG PET/CT imaging and surgical pathological data of 35 patients with GIST (27 males, 8 females; age 44-84 years) from Union Hospital, Tongji Medical College, Huazhong University of Science and Technology and Zhongnan Hospital of Wuhan University were analyzed retrospectively. Patients were divided into ring-shaped uptake group and other uptake patterns group according to 18F-FDG PET/CT image feature. Fisher′s exact test was used to analyze the differences of tumor necrosis and National Institutes of Health (NIH) risk classification (short for NIH classification) between different image feature groups. Mann-Whitney U test was used to analyze the differences of SUV max , metabolic parameters at different thresholds (2.5, 40%, 50%) of SUV max (metabolic tumor volume (MTV; MTV 2.5, MTV 40%, MTV 50%) and total lesion glycolysis (TLG; TLG 2.5, TLG 40%, TLG 50%)) between different clinicopathological features (lesion location, tumor diameter, mitotic count, Ki-67, necrosis, image feature, NIH classification) groups. Spearman rank correlation analysis was used to explore the correlation between clinicopathological features and metabolic parameters. ROC curve analysis was used to distinguish NIH classification of different metabolic parameters. Delong test was used to compared differences between different AUCs. Results:Of 35 GIST patients, 11(31.4%) were ring-shaped uptake and 24(68.6%) were other uptake patterns, and the differences of necrosis (7/11 vs 12.5%(3/24); P=0.004) and NIH classification (11/11 vs 25.0%(6/24); P<0.001) between the two groups were significant. There were significant differences of metabolic parameters between different groups of tumor diameter, mitotic count, necrosis, image feature, NIH classification ( z values: from -4.70 to -2.09, all P<0.05), while there were no significant differences of Ki-67 ( z values: from -0.83 to -0.71, all P>0.05). Metabolic parameters were correlated with mitotic count, tumor diameter, necrosis, image feature and NIH classification ( rs values: 0.36-0.81, all P<0.05), while was not correlated with Ki-67 ( rs values: 0.12-0.14, all P>0.05). The differences of AUCs between SUV max and MTV 2.5, TLG 2.5, TLG 40%, TLG 50%were significant (0.752, 0.856, 0.856, 0.882, 0.886; z values: 1.96-2.12, all P<0.05). Conclusions:The NIH classification of GIST with ring-shaped uptake on 18F-FDG PET/CT is higher and more prone to necrosis. The 18F-FDG PET/CT metabolic parameters based on different thresholds of SUV max have certain significance for the prediction of NIH classification of GIST, and may be superior to SUV max.

We report a case of type A insulin resistance syndrome. A 16-year-old girl with BMI of 19.1 kg/m 2 presented with primary amenorrhea and hyperglycemia for two years. Baseline HbA 1C was 10.8%, along with severe hyperinsulinemia, increased total testosterone and free androgen index(FAI). Ultrasonography showed polycystic ovaries. Next generation sequencing identified a novel and de novo heterozygous missense mutation of Trp1220Gly in the insulin receptor gene. Short-term intensive insulin pump treatment was initiated, followed by insulin glargine, pioglitazone and acarbose combination regiment. Fasting blood glucose and insulin levels decreased significantly, but post-load hyperglycemia and hyperinsulinemia remained unsatisfactory. HbA 1C dropped to 7.6% at 1-year follow up. Patients with polycystic ovarian syndrome who are adolescent-onset and with lean body type should be taken into account of type A insulin resistance syndrome. Currently, there is no standardized treatment protocol, and therapy should be individualized based on the specific gene mutation of each patient.

The rapid changes in the research and development environment of new anti-tumor drugs in China have brought various challenges to drug innovation. How to explore the clinical advantages of new drugs in the early phase, and design scientific, reasonable and efficient pivotal clinical trials for drug registration accordingly, is one of the key challenges. This article takes innovative new drugs for hematological malignancies as an example, comprehensively elaborates the considerations on the timing for entering the pivotal clinical trial and the key elements of the trial design from the perspective of clinical reviewers.

Hemophilia is the only rare hereditary hemorrhagic disorder included in the First Rare Diseases catalogue. However, rare bleeding diseases identified in the clinic are far more common than hemophilia. Most other rare hemorrhagic disorders have less effective treatment than hemophilia. Hemophilia has a history of successful drug development in rare hemorrhagic diseases, and the cycle between clinical research and drug development has been gradually realized. Drug research and pharmaceutical companies can refer to the drug research and development process in the field of hemophilia, learn from the experience of hemophilia drug research and develop treatments. The industry can increase drug development by strengthening basic research, focusing on the value of natural history research, the application of quantitative pharmacological tools and improving the efficiency of drug development to meet the urgent unmet medical needs of patients with rare hemorrhagic diseases.

Objective:To explore the clinical application value of MRI-PDFF on different liver segments for the evaluation of non-alcoholic fatty liver disease (NAFLD).Methods:178 volunteers from March 2019 to February 2020 were included. PDFF values ??of all nine segments of the liver were measured using CSE3.0T MRI scan. The obtained average value was used to represent the average liver fat content. PDFF values of each or combined liver segment were equally compared with the average value to observe the representativeness of fat content. Receiver operating characteristic curve was used to analyze the diagnostic performance of each liver segment, and the Youden index was used to calculate the cutoff value. Paired-sample t-test or non-parametric Kruskal-Wallis test were used to compare measurement data among groups.Results:178 volunteers average liver fat content ranged from 0.89% to 42.61% with MRI-PDFF, and 71.35% (127/178) of the volunteers had PDFF > 5%. There was no significant difference between SIII, SIVb, SV, and SVIII liver segments when compared with the average value ( P > 0.05). PDFF values ??of SI, SII, and SIV a liver segments were all lower than the average value, while the PDFF values ??of SVI and SVII liver segments were all higher than the average value ( P ??< 0.05). MRI-PDFF sensitivity value for diagnosing liver steatosis of nine liver segments was 85.8% ~ 94.5%, and the specificity was higher than 96.0%. Among them, the SV liver segment had the highest sensitivity (94.5%), and the corresponding optimal diagnostic threshold value was 5.13%. Compared with single and combined liver segment, the PDFF value of SII, SV, SVI combined liver segment had the highest diagnostic performance for fatty liver, with the sensitivity and specificity of 96.9%, and 100%, respectively, and the corresponding optimal diagnostic threshold value was 5.17%. Conclusion:Compared with single and other combined liver segments, MRI-PDFF values of SII, SV, and SVI combined liver segments have higher sensitivity and specificity for the diagnosis of NAFLD, and it can be used as the first choice for the determination of liver fat content with MRI.

In recent years,the relatinship is hot spot between glycemic indexes and prognosis of critical patients in critical medicine area.To control the fluctuation of blood glucose is more important than to control high blood glucose,so to control the fluctuation is a significant strategy to control the value of blood sugar in critical patients.The indexes reflected blood glucose fluctuation have a lot,such as the mean value of blood glucose,variation coefficient of blood glucose,instability index of blood glucose,etc.This paper will summarize the type and computational method of glycemic indexes and the relationship between glycemic indexes and critical patients prognosis,and prospect how to improve the glycimic indexes in clinic in the future.