AIM: To explore the factors associated with significant corneal astigmatism during the perioperative period in patients with pterygium. METHODS: Patients with primary pterygium presenting at Shanxi Eye Hospital between February and June 2025 were enrolled. All patients underwent medical history collection. Pre- and postoperative data were obtained using Pentacam, anterior segment photography, Image J software, and anterior segment optical coherence tomography(AS-OCT). All patients underwent pterygium excision combined with autologous bulbar conjunctival flap transplantation under local infiltration anesthesia. RESULTS: A total of 76 patients(76 eyes)with pterygium were finally enrolled(30 males, 46 females)with a mean age of 62.2±8.2 y. The mean length of corneal invasion by pterygium was 3.61±0.89 mm, the mean depth of invasion into the anterior corneal surface was 0.15±0.09 mm, and the median area of corneal invasion was 10.25(6.90, 18.75)mm2. The median preoperative corneal astigmatism was 1.50(0.70, 5.45)D. Median astigmatism was 0.8(0.40, 1.28)D at 2 wk postoperatively and 0.60(0.30, 1.15)D at 1 mo postoperatively. Patient age showed a positive correlation with preoperative astigmatism, and with residual astigmatism at 2 wk and 1 mo postoperatively(all P<0.05). The length of corneal invasion was positively correlated with preoperative astigmatism and residual astigmatism at both postoperative timepoints(P<0.01). The depth of invasion showed no significant linear correlation with astigmatism at any stage(P=0.250, 0.761, 0.686). The area of corneal invasion was positively correlated with astigmatism at all stages(P<0.01). Patients were grouped based on significant astigmatism(≥1.0 D)and non-significant astigmatism(<1.0 D), after adjusting for other variables, age(P=0.031)and the area of corneal invasion(P=0.004)were identified as risk factors for significant astigmatism. Pterygium invasion length was not significant factors(P>0.05). Receiver operating characteristic(ROC)analysis showed the highest area under the curve(AUC)for the invasion area(AUC=0.915). CONCLUSION: Significant preoperative corneal astigmatism in pterygium patients is correlated with patient age, the length of corneal invasion, and the area of invasion. The area of pterygium invasion into the cornea is the strongest predictor of significant preoperative corneal astigmatism.

Objective:To investigate the risk factors for hemorrhagic transformation (HT) after intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS), and the predictive value of Neutrophil to lymphocyte ratio (NLR).Methods:Consecutive patients with AIS received IVT in Zhengzhou People’s Hospital from January 2021 to December 2022 were retrospectively enrolled. HT was defined as no intracranial hemorrhage was found on the first imaging examination after admission, and new intracranial hemorrhage was found on the imaging examination 24 h after IVT or when symptoms worsened. sHT was defined as HT and the National Institutes of Health Stroke Scale (NIHSS) score increased by ≥4 compared to admission or required surgical treatment such as intubation and decompressive craniectomy. The baseline clinical and laboratory data of the patients were collected, and NLR, lymphocyte to monocyte ratio (LMR), and platelet to neutrophil ratio (PNR) were calculated. Multivariate logistic regression analysis was used to identify the independent predictors of HT and sHT, and receiver operating characteristic (ROC) curve was used to analyze the predictive value of NLR for HT and sHT after IVT. Results:A total of 196 patients were included (age 65.37±13.10 years, 124 males [63.3%]). The median baseline NIHSS score was 4 (interquartile range: 2-10). Twenty patients (10.2%) developed HT, and 12 (6.1%) developed sHT. Univariate analysis showed that there were statistically significant differences in age, baseline NIHSS score, creatinine, NLR, and stroke etiology type between the HT group and the non-HT group (all P<0.05); there were statistically significant differences in age, NLR, PNR, creatinine, baseline NIHSS score, and stroke etiological type between the sHT group and the non-sHT group (all P<0.05). Multivariate logistic regression analysis showed that NLR was an independent predictor of HT (odds ratio [ OR] 1.375, 95% confidence interval [ CI] 1.132-1.670; P=0.001) and sHT ( OR 1.647, 95% CI 1.177-2.304; P=0.004) after IVT. The ROC curve analysis showed that the area under the curve for predicting HT by NLR was 0.683 (95% CI 0.533-0.833; P=0.007), the optimal cutoff value was 5.78, the sensitivity and specificity were 55.0% and 84.1%, respectively. The area under the curve for predicting sHT by NLR was 0.784 (95% CI 0.720-0.839; P=0.001), the optimal cutoff value was 5.94, the sensitivity and specificity were 66.67% and 84.24%, respectively. Conclusions:A higher baseline NLR is associated with an increased risk of HT and sHT after IVT in patients with AIS, and can serve as a biomarker for predicting HT and sHT after IVT.

Objective:To investigate the effect of cesarean scar defect and endometrial cavity fluid on the pregnancy outcomes of infertility patients with previous cesarean scar uterus undergoing in vitro fertilization-embryo transfer (IVF-ET). Methods:This was a retrospective cohort study. Totally 732 cases of patients with previous cesarean scar uterus were selected from frozen-thawed embryo transfer (FET) cycles in the Fertility Center, Shenzhen Zhongshan Urology Hospital from January 2019 to March 2020. They were divided into four groups: group A ( n=39) including patients with previous cesarean scar defect and without endometrial cavity fluid; group B ( n=82) including patients with previous cesarean scar defect and with endometrial cavity fluid; group C ( n=495) including patients without previous cesarean scar defect and without endometrial cavity fluid; group D ( n=116) including patients without previous cesarean scar defect and with endometrial cavity fluid. The general data and pregnancy outcomes were compared among these groups. Multivariate logistics regression analysis of pregnancy outcome indexes was performed. Results:The transplantation age of group A was higher than that of group B [(38.33±3.55) years vs. (36.93±3.59) years, P=0.045], the endometrial thickness of luteal transformation day and the rate of good-quality embryo transplantation of group C were higher than those of group D [(9.40±1.56) mm vs. (9.03±1.59) mm, P=0.025; 75.76% (375/495) vs. 65.52% (76/116), P=0.024]. The egg retrieval age of group A was higher than that of group C [(37.72±3.55) years vs. (36.25±4.52) years, P=0.049], but the endometrial thickness of luteal transformation day was thinner [(8.74±1.58) mm vs. (9.40±1.56) mm, P=0.012], and the differences were statistically significant. The implantation rate, the biochemical pregnancy rate and the clinical pregnancy rate of group C were higher than those of group D [34.23% (230/672) vs. 22.58% (35/155), P=0.007; 48.28% (239/495) vs. 37.93% (44/116), P=0.044; 42.83% (212/495) vs. 30.17% (35/116), P=0.012]. The early abortion rate in group D was higher than that in group B [40.00% (14/35) vs. 17.24 % (5/29), P=0.047], the difference was statistically significant. Multivariate logistics regression analyses were used with adjustment for possible confounders: the maternal age at embryo transfer, the maternal age at egg retrieval, anti-Müllerian hormone (AMH),antral follicle count (AFC), basic follicle-stimulating hormone (FSH), endometrial CD138 results, FET protocol, and embryo attributes, the number of embryos transferred, embryo quality, the endometrial thickness and the progesterone value on the day of luteal transformation, the result showed that the implantation rate, the biochemical pregnancy rate and the clinical pregnancy rate of group D were lower than those of group C [22.58% (35/155) vs. 34.23% (230/672), P=0.006; 37.93% (44/116) vs. 48.28% (239/495), P=0.047; 30.17% (35/116) vs. 42.83% (212/495), P=0.022] and the differences were statistically significant. The implantation rate, the biochemical pregnancy rate and the clinical pregnancy rate of group B were higher than those of group D [29.52% (31/105) vs. 22.58% (35/155), P=0.049; 48.78% (40/82) vs. 37.93% (44/116), P=0.012; 35.37% (29/82) vs. 30.17% (35/116), P=0.030] and the differences were statistically significant. Conclusion:Endometrial cavity fluid is the main factor that obviously affects the pregnancy outcome of infertility patients with previous cesarean scar uterus undergoing FET cycles.

Objective:To investigate the effect of cesarean scar defect and endometrial cavity fluid on the pregnancy outcomes of infertility patients with previous cesarean scar uterus undergoing in vitro fertilization-embryo transfer (IVF-ET). Methods:This was a retrospective cohort study. Totally 732 cases of patients with previous cesarean scar uterus were selected from frozen-thawed embryo transfer (FET) cycles in the Fertility Center, Shenzhen Zhongshan Urology Hospital from January 2019 to March 2020. They were divided into four groups: group A ( n=39) including patients with previous cesarean scar defect and without endometrial cavity fluid; group B ( n=82) including patients with previous cesarean scar defect and with endometrial cavity fluid; group C ( n=495) including patients without previous cesarean scar defect and without endometrial cavity fluid; group D ( n=116) including patients without previous cesarean scar defect and with endometrial cavity fluid. The general data and pregnancy outcomes were compared among these groups. Multivariate logistics regression analysis of pregnancy outcome indexes was performed. Results:The transplantation age of group A was higher than that of group B [(38.33±3.55) years vs. (36.93±3.59) years, P=0.045], the endometrial thickness of luteal transformation day and the rate of good-quality embryo transplantation of group C were higher than those of group D [(9.40±1.56) mm vs. (9.03±1.59) mm, P=0.025; 75.76% (375/495) vs. 65.52% (76/116), P=0.024]. The egg retrieval age of group A was higher than that of group C [(37.72±3.55) years vs. (36.25±4.52) years, P=0.049], but the endometrial thickness of luteal transformation day was thinner [(8.74±1.58) mm vs. (9.40±1.56) mm, P=0.012], and the differences were statistically significant. The implantation rate, the biochemical pregnancy rate and the clinical pregnancy rate of group C were higher than those of group D [34.23% (230/672) vs. 22.58% (35/155), P=0.007; 48.28% (239/495) vs. 37.93% (44/116), P=0.044; 42.83% (212/495) vs. 30.17% (35/116), P=0.012]. The early abortion rate in group D was higher than that in group B [40.00% (14/35) vs. 17.24 % (5/29), P=0.047], the difference was statistically significant. Multivariate logistics regression analyses were used with adjustment for possible confounders: the maternal age at embryo transfer, the maternal age at egg retrieval, anti-Müllerian hormone (AMH),antral follicle count (AFC), basic follicle-stimulating hormone (FSH), endometrial CD138 results, FET protocol, and embryo attributes, the number of embryos transferred, embryo quality, the endometrial thickness and the progesterone value on the day of luteal transformation, the result showed that the implantation rate, the biochemical pregnancy rate and the clinical pregnancy rate of group D were lower than those of group C [22.58% (35/155) vs. 34.23% (230/672), P=0.006; 37.93% (44/116) vs. 48.28% (239/495), P=0.047; 30.17% (35/116) vs. 42.83% (212/495), P=0.022] and the differences were statistically significant. The implantation rate, the biochemical pregnancy rate and the clinical pregnancy rate of group B were higher than those of group D [29.52% (31/105) vs. 22.58% (35/155), P=0.049; 48.78% (40/82) vs. 37.93% (44/116), P=0.012; 35.37% (29/82) vs. 30.17% (35/116), P=0.030] and the differences were statistically significant. Conclusion:Endometrial cavity fluid is the main factor that obviously affects the pregnancy outcome of infertility patients with previous cesarean scar uterus undergoing FET cycles.

Corynebacterium glutamicum is one of the most important traditional industrial microorganisms and receiving more and more attention towards a novel cellular factory due to the recently rapid development in genomics and genetic operation toolboxes for Corynebacterium. However, compared to other model organisms such as Escherichia coli, there were few studies on its metabolic regulation, especially a genome-scale integrated cellular network model currently missing for Corynebacterium, which hindered the systematic study of Corynebacterium glutamicum and large-scale rational design and optimization for strains. Here, by gathering relevant information from a number of public databases, we successfully constructed an integrated cellular network, which was composed of 1384 reactions, 1276 metabolites, 88 transcriptional factors and 999 pairs of transcriptional regulatory relationships. The transcriptional regulatory sub-network could be arranged into five layers and the metabolic sub-network presented a clear bow-tie structure. We proposed a new method to extract complex metabolic and regulatory sub-network for product-orientated study taking lysine biosynthesis as an example. The metabolic and regulatory sub-network extracted by our method was more close to the real functional network than the simplex biochemical pathways. The results would be greatly helpful for understanding the high-yielding biomechanism for amino acids and the re-design of the industrial strains.
Corynebacterium glutamicum ; genetics ; metabolism ; Gene Expression Regulation, Bacterial ; Gene Regulatory Networks ; genetics ; Lysine ; biosynthesis ; Metabolic Networks and Pathways ; genetics ; Transcription Factors ; genetics ; Transcription, Genetic