Objective To explore the application value of iterative model reconstruction(IMR)technique in low-dose lumbar CT scanning.Methods A total of 48 patients who underwent lumbar CT plain scan were selected and divided into regular-dose group(group A)and ultra-low dose group(group B).The group A underwent imaging with 120 kV tube voltage,automatic tube current modulation technology,and iDose 4 reconstruction.The group B was scanned with a tube voltage of 100 kV and a tube current of 80 mAs,and the images of B1 and B2 groups were reconstructed by iDose 4 and IMR,respectively.The standard deviation(SD)value(the SD value represents the noise of the measured tissue),signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR)of cancellous bone,intervertebral disc,dural sac,and psoas muscle were measured and calculated at the L3-L4 vertebral body level.Two diagnosticians rated the image quality.Sample t-test and ANOVA were used to compare the measurement results and subjective scores.Results The comparison of SD for intervertebral disc,dural sac,and psoas muscle showed group B2＜group A＜group B1,while the subjective score comparison indicated group A＞group B2＞group B1.The SNR for intervertebral disc and psoas muscle demonstrated group B2＞group A＞group B1.There was no significant difference in bone quality score between group A and group B1(P＞0.05),but there was a significantly different between the bone quality scores of group B2 and those obtained with iDose 4 reconstruction(group A and group B1)(P＜0.05).The effective dose(ED)of group B was reduced by approximately 70.28％compared with group A.Conclusion IMR can significantly reduce SD,improves SNR and CNR,resulting in high-quality images.Compared to iDose 4 technique,IMR has more advantages in soft tissue display,while iDose 4 technique is superior in observing fine bone structures.The combined application of iDose 4 and IMR technique ensures high-quality images for diagnosis,while significantly reducing the radiation dose to patients.

Background::An evidence gap still exists regarding the efficacy and safety of tegoprazan in patients with erosive esophagitis (EE) in China. This study aimed to verify the efficacy and safety of tegoprazan vs. esomeprazole in patients with EE in China. Methods::This study was a multicenter, randomized, double-blind, parallel, active-controlled, non-inferiority phase III trial of patients with EE randomized 1:1 to tegoprazan 50 mg/day vs. esomeprazole 40 mg/day. This study was conducted in 32 sites between October 24, 2018 and October 18, 2019. The primary endpoint was the cumulative endoscopic healing rate at week 8. The secondary endpoint included endoscopic healing rate at week 4, changes in the reflux disease questionnaire (RDQ) and gastroesophageal reflux disease health-related quality of life (GERD-HRQL) scores, and symptom improvement. Results::A total of 261 patients were randomized: 132 to the tegoprazan group and 129 to the esomeprazole group. The cumulative endoscopic healing rate at 8 weeks in the tegoprazan group was non-inferior to that of the esomeprazole group (91.1% vs. 92.8%, difference: -1.7%, 95% confidence interval [CI]: -8.5%, 5.0%, P = 0.008). There were no statistically significant differences in the changes in RDQ (total, severity, and frequency) and GERD-HRQL scores between the two groups (all P >0.05). The percentages of days without symptoms, including daytime and nighttime symptoms based on patients' diaries, were similar between the two groups (all P >0.05). In the tegoprazan and esomeprazole groups, 71.5% (93/130) and 61.7% (79/128) of the participants reported adverse events (AEs), 2.3% and 0 experienced serious AEs, while 70.0% and 60.2% had treatment-emergent AEs, respectively. Conclusion::Tegoprazan 50 mg/day demonstrated non-inferior efficacy in healing EE, symptom improvement, and quality of life, and it has similar tolerability compared with esomeprazole 40 mg/day.

Objective:To investigate the expression of long noncoding RNA (lncRNA) BMPR1B-AS1 in ovarian cancer and its impact on prognosis, so as to evaluate its value as a potential biomarker.Methods:The TCGA, GEPIA, and UALCAN databases were used to retrospectively analyze the expression differences of BMPR1B-AS1 in gynecological tumors, and prognostic analysis was performed in combination with clinical data. The expression level of BMPR1B-AS1 in ovarian cancer tissues and cell lines was verified by real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR), and univariate and multivariate Cox regression models were used to analyze its relationship with the prognosis of ovarian cancer.Results:Database analysis showed that the expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer was higher than that in the non-tumor group (all P<0.05), and high expression of BMPR1B-AS1 in ovarian cancer was associated with better prognosis ( P<0.05). Experimental verification showed that the expression of BMPR1B-AS1 in ovarian cancer tissues was significantly higher than that in benign ovarian tissues, and the expression of BMPR1B-AS1 in ovarian cancer cell lines was higher than that in normal human ovarian epithelial cells ( P<0.05). Cox regression analysis indicated that high expression of BMPR1B-AS1 was an independent protective factor for the prognosis of ovarian cancer ( P<0.05). Conclusions:The expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer is higher than that in non-tumor groups, and it is an independent protective factor for good prognosis in ovarian cancer patients. It may serve as a new biomarker, providing new ideas for the diagnosis and treatment of ovarian cancer.

Objective:To investigate the causal relationships between multiple obesity indices, including body mass index (BMI), body fat percentage, whole-body fat mass, trunk fat mass, leg fat percentage, arm fat percentage, waist circumference, and hip circumference, and preeclampsia (PE) using Mendelian randomization (MR), and to evaluate the mediating effect of triglycerides.Methods:Genome-wide association studies (GWAS) summary statistics from European populations were utilized. Independent genetic loci associated with obesity indices and PE served as instrumental variables of exposure and outcomes. Obesity data (approximately 191 000 female samples) came from UK Biobank; PE data ( n=242 852) from FinnGen Biobank. Causal effects were assessed primarily via inverse variance weighted (IVW), supplemented by MR-Egger, weighted median, MR-pleiotropy residual sum and outlier (MR-PRESSO), and Bayesian weighted MR. Bonferroni correction was applied. Cochran's Q test evaluated heterogeneity; MR-Egger intercept test assessed horizontal pleiotropy; leave-one-out, funnel, and scatter plots conducted sensitivity analyses. Odds ratio ( OR) measured effect sizes. Two-step MR explored triglyceride mediation. Results:Eighty-two to 112 single nucleotide polymorphisms were included as instrumental variables. After Bonferroni correction, significant positive causal associations with PE were observed for: BMI (IVW: OR=1.703, 95% CI: 1.469-1.974, P<0.001), body fat percentage (IVW: OR=1.595, 95% CI: 1.321-1.925, P<0.001), whole-body fat mass (IVW: OR=1.639, 95% CI: 1.389-1.934, P<0.001), right leg fat percentage (IVW: OR=1.610, 95% CI: 1.360-1.905, P<0.001), left leg fat percentage (IVW: OR=1.622, 95% CI: 1.363-1.930, P<0.001), right arm fat percentage (IVW: OR=1.591, 95% CI: 1.351-1.872, P<0.001), left arm fat percentage (IVW: OR=1.710, 95% CI: 1.444-2.024, P<0.001), and waist circumference (IVW: OR=1.815, 95% CI: 1.534-2.148, P<0.001). Sensitivity analyses confirmed robustness. Triglycerides mediated 4.6%-8.2% of these effects. Trunk fat mass and hip circumference showed potential positive associations (IVW: OR>1, 0.005≤ P<0.05). Conclusions:Higher BMI, body fat percentage, whole-body fat mass, leg/arm fat percentages, and waist circumference may increase PE risk, with waist circumference showing the strongest association. These effects may be partially mediated by triglycerides.

Objective To explore the application value of iterative model reconstruction(IMR)technique in low-dose lumbar CT scanning.Methods A total of 48 patients who underwent lumbar CT plain scan were selected and divided into regular-dose group(group A)and ultra-low dose group(group B).The group A underwent imaging with 120 kV tube voltage,automatic tube current modulation technology,and iDose 4 reconstruction.The group B was scanned with a tube voltage of 100 kV and a tube current of 80 mAs,and the images of B1 and B2 groups were reconstructed by iDose 4 and IMR,respectively.The standard deviation(SD)value(the SD value represents the noise of the measured tissue),signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR)of cancellous bone,intervertebral disc,dural sac,and psoas muscle were measured and calculated at the L3-L4 vertebral body level.Two diagnosticians rated the image quality.Sample t-test and ANOVA were used to compare the measurement results and subjective scores.Results The comparison of SD for intervertebral disc,dural sac,and psoas muscle showed group B2＜group A＜group B1,while the subjective score comparison indicated group A＞group B2＞group B1.The SNR for intervertebral disc and psoas muscle demonstrated group B2＞group A＞group B1.There was no significant difference in bone quality score between group A and group B1(P＞0.05),but there was a significantly different between the bone quality scores of group B2 and those obtained with iDose 4 reconstruction(group A and group B1)(P＜0.05).The effective dose(ED)of group B was reduced by approximately 70.28％compared with group A.Conclusion IMR can significantly reduce SD,improves SNR and CNR,resulting in high-quality images.Compared to iDose 4 technique,IMR has more advantages in soft tissue display,while iDose 4 technique is superior in observing fine bone structures.The combined application of iDose 4 and IMR technique ensures high-quality images for diagnosis,while significantly reducing the radiation dose to patients.

Objective:To investigate the expression of long noncoding RNA (lncRNA) BMPR1B-AS1 in ovarian cancer and its impact on prognosis, so as to evaluate its value as a potential biomarker.Methods:The TCGA, GEPIA, and UALCAN databases were used to retrospectively analyze the expression differences of BMPR1B-AS1 in gynecological tumors, and prognostic analysis was performed in combination with clinical data. The expression level of BMPR1B-AS1 in ovarian cancer tissues and cell lines was verified by real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR), and univariate and multivariate Cox regression models were used to analyze its relationship with the prognosis of ovarian cancer.Results:Database analysis showed that the expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer was higher than that in the non-tumor group (all P<0.05), and high expression of BMPR1B-AS1 in ovarian cancer was associated with better prognosis ( P<0.05). Experimental verification showed that the expression of BMPR1B-AS1 in ovarian cancer tissues was significantly higher than that in benign ovarian tissues, and the expression of BMPR1B-AS1 in ovarian cancer cell lines was higher than that in normal human ovarian epithelial cells ( P<0.05). Cox regression analysis indicated that high expression of BMPR1B-AS1 was an independent protective factor for the prognosis of ovarian cancer ( P<0.05). Conclusions:The expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer is higher than that in non-tumor groups, and it is an independent protective factor for good prognosis in ovarian cancer patients. It may serve as a new biomarker, providing new ideas for the diagnosis and treatment of ovarian cancer.

Objective:To investigate the causal relationships between multiple obesity indices, including body mass index (BMI), body fat percentage, whole-body fat mass, trunk fat mass, leg fat percentage, arm fat percentage, waist circumference, and hip circumference, and preeclampsia (PE) using Mendelian randomization (MR), and to evaluate the mediating effect of triglycerides.Methods:Genome-wide association studies (GWAS) summary statistics from European populations were utilized. Independent genetic loci associated with obesity indices and PE served as instrumental variables of exposure and outcomes. Obesity data (approximately 191 000 female samples) came from UK Biobank; PE data ( n=242 852) from FinnGen Biobank. Causal effects were assessed primarily via inverse variance weighted (IVW), supplemented by MR-Egger, weighted median, MR-pleiotropy residual sum and outlier (MR-PRESSO), and Bayesian weighted MR. Bonferroni correction was applied. Cochran's Q test evaluated heterogeneity; MR-Egger intercept test assessed horizontal pleiotropy; leave-one-out, funnel, and scatter plots conducted sensitivity analyses. Odds ratio ( OR) measured effect sizes. Two-step MR explored triglyceride mediation. Results:Eighty-two to 112 single nucleotide polymorphisms were included as instrumental variables. After Bonferroni correction, significant positive causal associations with PE were observed for: BMI (IVW: OR=1.703, 95% CI: 1.469-1.974, P<0.001), body fat percentage (IVW: OR=1.595, 95% CI: 1.321-1.925, P<0.001), whole-body fat mass (IVW: OR=1.639, 95% CI: 1.389-1.934, P<0.001), right leg fat percentage (IVW: OR=1.610, 95% CI: 1.360-1.905, P<0.001), left leg fat percentage (IVW: OR=1.622, 95% CI: 1.363-1.930, P<0.001), right arm fat percentage (IVW: OR=1.591, 95% CI: 1.351-1.872, P<0.001), left arm fat percentage (IVW: OR=1.710, 95% CI: 1.444-2.024, P<0.001), and waist circumference (IVW: OR=1.815, 95% CI: 1.534-2.148, P<0.001). Sensitivity analyses confirmed robustness. Triglycerides mediated 4.6%-8.2% of these effects. Trunk fat mass and hip circumference showed potential positive associations (IVW: OR>1, 0.005≤ P<0.05). Conclusions:Higher BMI, body fat percentage, whole-body fat mass, leg/arm fat percentages, and waist circumference may increase PE risk, with waist circumference showing the strongest association. These effects may be partially mediated by triglycerides.

Background::An evidence gap still exists regarding the efficacy and safety of tegoprazan in patients with erosive esophagitis (EE) in China. This study aimed to verify the efficacy and safety of tegoprazan vs. esomeprazole in patients with EE in China. Methods::This study was a multicenter, randomized, double-blind, parallel, active-controlled, non-inferiority phase III trial of patients with EE randomized 1:1 to tegoprazan 50 mg/day vs. esomeprazole 40 mg/day. This study was conducted in 32 sites between October 24, 2018 and October 18, 2019. The primary endpoint was the cumulative endoscopic healing rate at week 8. The secondary endpoint included endoscopic healing rate at week 4, changes in the reflux disease questionnaire (RDQ) and gastroesophageal reflux disease health-related quality of life (GERD-HRQL) scores, and symptom improvement. Results::A total of 261 patients were randomized: 132 to the tegoprazan group and 129 to the esomeprazole group. The cumulative endoscopic healing rate at 8 weeks in the tegoprazan group was non-inferior to that of the esomeprazole group (91.1% vs. 92.8%, difference: -1.7%, 95% confidence interval [CI]: -8.5%, 5.0%, P = 0.008). There were no statistically significant differences in the changes in RDQ (total, severity, and frequency) and GERD-HRQL scores between the two groups (all P >0.05). The percentages of days without symptoms, including daytime and nighttime symptoms based on patients' diaries, were similar between the two groups (all P >0.05). In the tegoprazan and esomeprazole groups, 71.5% (93/130) and 61.7% (79/128) of the participants reported adverse events (AEs), 2.3% and 0 experienced serious AEs, while 70.0% and 60.2% had treatment-emergent AEs, respectively. Conclusion::Tegoprazan 50 mg/day demonstrated non-inferior efficacy in healing EE, symptom improvement, and quality of life, and it has similar tolerability compared with esomeprazole 40 mg/day.

Objective:To establish a menstrual prediction model after the first course of hormone replacement therapy(HRT)in premature ovarian insufficiency(POI)patients after allogeneic hematopoietic stem cell transplan-tation(allo-HSCT),and to provide certain reference value for formulating HRT plans.Methods:The retrospective analysis recruited 154 POI patients after allo-HSCT in the First Affiliated Hospital of Soochow University from Jan-uary 2017 to October 2022.They were divided into ideal menstruation group(n=116)and unideal menstruation group(n=38)according to menstruation after the first course of HRT.Basic characteristics and clinical data were compared in single-factor analysis to select predictive factors.Patients were randomly divided into training set and test set.The menstrual prediction model was developed based on random forest algorithm on the training set and the prediction efficiency was verified by the test set.Finally,we made a user interaction interface and deployed to the server for sharing.Results:The single-factor analysis suggested statistic difference of age of visit,body mass index(BMI),gravidity,parity,hematologic diseases,transplantation age,donor gender,follicle-stimulating hormone(FSH),Luteinizing Hormone(LH),lumbar bone mineral density(BMD)and HRT plan(P<0.05).According to mean decrease accuracy,the predictive factors included visit age,transplantation age,BMI,FSH,HRT plans,gravidity and parity.After the initial establishment of the random forest model,we improved it by adjusting ntree to 500,mtry to 6 and training/test set division to 80%/20% .We also used tenfold cross validation to reduce over-fitting.The area under curve(AUC)of the final constructed menstrual prediction model was 0.768,a sensitiv-ity of 0.695 and a specificity of 0.735.Conclusions:This study successfully established a menstrual prediction model for amenorrhea patients after allo-HSCT when finished the first course of HRT.The false positive rate was low,suggesting that if the prediction result of the model is non-ideal menstruation,we may consider adjusting HRT plans to promote menstruation in time.

Objective:To establish a menstrual prediction model after the first course of hormone replacement therapy(HRT)in premature ovarian insufficiency(POI)patients after allogeneic hematopoietic stem cell transplan-tation(allo-HSCT),and to provide certain reference value for formulating HRT plans.Methods:The retrospective analysis recruited 154 POI patients after allo-HSCT in the First Affiliated Hospital of Soochow University from Jan-uary 2017 to October 2022.They were divided into ideal menstruation group(n=116)and unideal menstruation group(n=38)according to menstruation after the first course of HRT.Basic characteristics and clinical data were compared in single-factor analysis to select predictive factors.Patients were randomly divided into training set and test set.The menstrual prediction model was developed based on random forest algorithm on the training set and the prediction efficiency was verified by the test set.Finally,we made a user interaction interface and deployed to the server for sharing.Results:The single-factor analysis suggested statistic difference of age of visit,body mass index(BMI),gravidity,parity,hematologic diseases,transplantation age,donor gender,follicle-stimulating hormone(FSH),Luteinizing Hormone(LH),lumbar bone mineral density(BMD)and HRT plan(P<0.05).According to mean decrease accuracy,the predictive factors included visit age,transplantation age,BMI,FSH,HRT plans,gravidity and parity.After the initial establishment of the random forest model,we improved it by adjusting ntree to 500,mtry to 6 and training/test set division to 80%/20% .We also used tenfold cross validation to reduce over-fitting.The area under curve(AUC)of the final constructed menstrual prediction model was 0.768,a sensitiv-ity of 0.695 and a specificity of 0.735.Conclusions:This study successfully established a menstrual prediction model for amenorrhea patients after allo-HSCT when finished the first course of HRT.The false positive rate was low,suggesting that if the prediction result of the model is non-ideal menstruation,we may consider adjusting HRT plans to promote menstruation in time.