AIM:To compare the effect of AT TORBI 709M and Tecnis ZMT intraocular lenses on astigmatism correction in patients with corneal astigmatism at 3 mo after operation based on the standard astigmatism vector analysis.METHODS: This was a retrospective case-control study. The clinical data of 69 patients(69 eyes)with corneal astigmatism who underwent phacoemulsification and implantation of toric intraocular lens(IOL)from June 2021 to December 2021 in Day Surgery Center of Xi'an No.1 Hospital was analyzed. The patients were divided into two groups. In group one, 38 cases(38 eyes)were implanted with AT TORBI 709M, and 31 patients(31 eyes)with Tecnis ZMT in group two. The axial length, preoperative astigmatism and axis, and the degree of intraocular lens were recorded. The uncorrected distance visual acuity(UCDVA), best corrected distance visual acuity(BCDVA), diopter, residual astigmatism and axis were recorded preoperatively and at 1 wk, 1 and 3 mo postoperatively. The postoperative surgical indicators, including spherical equivalent(SE), target induced astigmatism vector(TIA), surgically induced astigmatism vector(SIA), magnitude of error(ME), absolute value of angle of error(|AE|), absolute value of difference vector(|DV|), correction index(CI), and index of success(IOS)were evaluated by the standard astigmatism vector analysis.RESULTS:Postoperative UCDVA and BCDVA were significantly improved(all P<0.001), and there were statistically significant differences compared to preoperative UCDVA and BCDVA(all P<0.001). While, there was no significant difference in UCDVA and BCDVA between the two groups(P=0.275, 0.124). The standard astigmatism vector analysis showed that a good astigmatism correction was achieved in both AT TORBI 709M group and Tecnis ZMT group, and both |DV| and IOS were close to 0(P=0.329, 0.288). The CI of the AT TORBI 709M group was closer to 1, indicating a better astigmatism correction, while the CI of the Tecnis ZMT group was higher than 1, suggesting an overcorrection of astigmatism. However, the difference between the two groups was not statistically significant(P=0.193). The mean residual astigmatism at 3 mo postoperatively was -0.11±0.91 D in the AT TORBI 709M group and -0.46±0.76 D in the Tecnis ZMT group, respectively, showing no statistically significance difference(t=1.732, P=0.088).CONCLUSION:Both the flat loop AT TORBI 709M and the double C-loop Tecnis ZMT intraocular lenses can effectively improve postoperative visual acuity in patients with regular corneal astigmatism, showing good rotational stability and comparable correction abilities for both astigmatism with the rule and against-the-rule astigmatism.

BACKGROUND:Osteoporotic fracture is the most serious complication of osteoporosis.Previous studies have demonstrated that gut microbiota has a regulatory effect on skeletal tissue and that gut microbiota has an important relationship with osteoporotic fracture,but the causal relationship between the two is unclear. OBJECTIVE:To explore the causal relationship between gut microbiota and osteoporotic fractures using Mendelian randomization method. METHODS:The genome-wide association study(GWAS)datasets of gut microbiota and osteoporotic fracture were obtained from the IEU Open GWAS database and the Finnish database R9,respectively.Using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,Mendelian randomization analyses with random-effects inverse variance weighted,MR-Egger regression,weighted median,simple model,and weighted model methods were performed to assess whether there is a causal relationship between gut microbiota and osteoporotic fracture.Sensitivity analyses were performed to test the reliability and robustness of the results.Reverse Mendelian randomization analyses were performed to further validate the causal relationship identified in the forward Mendelian randomization analyses. RESULTS AND CONCLUSION:The results of this Mendelian randomization analysis indicated a causal relationship between gut microbiota and osteoporotic fracture.Elevated abundance of Actinomycetales[odds ratio(OR)=1.562,95%confidence interval(CI):1.027-2.375,P=0.037),Actinomycetaceae(OR=1.561,95%CI:1.027-2.374,P=0.037),Actinomyces(OR=1.544,95%CI:1.130-2.110,P=0.006),Butyricicoccus(OR=1.781,95%CI:1.194-2.657,P=0.005),Coprococcus 2(OR=1.550,95%CI:1.068-2.251,P=0.021),Family ⅩⅢ UCG-001(OR=1.473,95%CI:1.001-2.168,P=0.049),Methanobrevibacter(OR=1.274,95%CI:1.001-1.621,P=0.049),and Roseburia(OR=1.429,95%CI:1.015-2.013,P=0.041)would increase the risk of osteoporotic fractures in patients.Elevated abundance of Bacteroidia(OR=0.660,95%CI:0.455-0.959,P=0.029),Bacteroidales(OR=0.660,95%CI:0.455-0.959,P=0.029),Christensenellacea(OR=0.725,95%CI:0.529-0.995,P=0.047),Ruminococcaceae(OR=0.643,95%CI:0.443-0.933,P=0.020),Enterorhabdus(OR=0.558,95%CI:0.395-0.788,P=0.001),Eubacterium rectale group(OR=0.631,95%CI:0.435-0.916,P=0.016),Lachnospiraceae UCG008(OR=0.738,95%CI:0.546-0.998,P=0.048),and Ruminiclostridium 9(OR=0.492,95%CI:0.324-0.746,P=0.001)would reduce the risk of osteoporotic fractures in patients.We identified 16 gut microbiota associated with osteoporotic fracture by the Mendelian randomization method.That is,using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,eight gut microbiota showed positive causal associations with osteoporotic fracture and another eight gut microbiota showed negative causal associations with osteoporotic fracture.The results of this study not only identify new biomarkers for the early prediction of osteoporotic fracture and potential therapeutic targets in clinical practice,but also provide an experimental basis and theoretical basis for the study of improving the occurrence and prognosis of osteoporotic fracture through gut microbiota in bone tissue engineering.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Small-for-size syndrome (SFSS) remains a critical challenge in living donor liver transplantation (LDLT), characterized by graft insufficiency due to inadequate liver volume, leading to significant postoperative morbidity and mortality. As the global adoption of LDLT increases, the ability to predict and manage SFSS has become paramount in optimizing recipient outcomes. This review provides a comprehensive examination of the pathophysiology, risk factors, and strategies for managing SFSS across the pre-, intra-, and postoperative phases. The pathophysiology of SFSS has evolved from being solely volume-based to incorporating portal hemodynamics, now recognized as small-for-flow syndrome. Key risk factors include donor-related parameters like age and graft volume, recipient-related factors such as MELD score and portal hypertension, and intraoperative factors related to venous outflow and portal inflow modulation. Current strategies to mitigate SFSS include careful graft selection based on graft-to-recipient weight ratio and liver volumetry, surgical techniques to optimize portal hemodynamics, and novel interventions such as splenic artery ligation and hemiportocaval shunts. Pharmacological agents like somatostatin and terlipressin have also shown promise in modulating portal pressure. Advances in 3D imaging and artificial intelligence-based volumetry further aid in preoperative planning. This review emphasizes the importance of a multifaceted approach to prevent and manage SFSS, advocating for standardized definitions and grading systems. Through an integrated approach to surgical techniques, hemodynamic monitoring, and perioperative management, significant strides can be made in improving the outcomes of LDLT recipients. Further research is necessary to refine these strategies and expand the application of LDLT, especially in challenging cases involving small-for-size grafts.

Many triterpenoid compounds have been successfully heterologously synthesized in Saccharomyces cerevisiae. To increase the yield of triterpenoids, various metabolic engineering strategies have been developed. One commonly applied strategy is to enhance the supply of precursors, which has been widely used by researchers. Squalene, as a precursor to triterpenoid biosynthesis, plays a crucial role in the synthesis of these compounds. This study primarily investigates the effect of different squalene levels in chassis strains on the synthesis of triterpenoids(oleanolic acid and ursolic acid), and the underlying mechanisms are further explored using real-time quantitative PCR(qPCR) analysis. The results demonstrate that the chassis strain CB-9-5, which produces high levels of squalene, inhibits the synthesis of oleanolic acid and ursolic acid. In contrast, chassis strains with moderate to low squalene production, such as Y8-1 and CNPK, are more conducive to the synthesis of oleanolic acid and ursolic acid. The qPCR analysis reveals that the expression levels of ERG1, βAS, and CrCYP716A154 in the oleanolic acid-producing strain CB-OA are significantly lower than those in the control strains C-OA and Y-OA, suggesting that high squalene production in the chassis strains suppresses the transcription of certain genes, leading to a reduced yield of triterpenoids. Our findings indicate that when constructing S. cerevisiae strains for triterpenoid production, chassis strains with high squalene content may suppress the expression of certain genes, ultimately lowering their production, whereas chassis strains with moderate squalene levels are more favorable for triterpenoid biosynthesis.
Squalene/analysis* ; Saccharomyces cerevisiae/genetics* ; Triterpenes/metabolism* ; Metabolic Engineering ; Oleanolic Acid/biosynthesis* ; Ursolic Acid

This study explored the potential therapeutic targets and mechanisms of Danggui Shaoyao San(DSS) in the prevention and treatment of Alzheimer's disease(AD) through transcriptomics and metabolomics, combined with animal experiments. Fifty male C57BL/6J mice, aged seven weeks, were randomly divided into the following five groups: control, model, positive drug, low-dose DSS, and high-dose DSS groups. After the intervention, the Morris water maze was used to assess learning and memory abilities of mice, and Nissl staining and hematoxylin-eosin(HE) staining were performed to observe pathological changes in the hippocampal tissue. Transcriptomics and metabolomics were employed to sequence brain tissue and identify differential metabolites, analyzing key genes and metabolites related to disease progression. Reverse transcription-quantitative polymerase chain reaction(RT-qPCR) was employed to validate the expression of key genes. The Morris water maze results indicated that DSS significantly improved learning and cognitive function in scopolamine(SCOP)-induced model mice, with the high-dose DSS group showing the best results. Pathological staining showed that DSS effectively reduced hippocampal neuronal damage, increased Nissl body numbers, and reduced nuclear pyknosis and neuronal loss. Transcriptomics identified seven key genes, including neurexin 1(Nrxn1) and sodium voltage-gated channel α subunit 1(Scn1a), and metabolomics revealed 113 differential metabolites, all of which were closely associated with synaptic function, oxidative stress, and metabolic regulation. RT-qPCR experiments confirmed that the expression of these seven key genes was consistent with the transcriptomics results. This study suggests that DSS significantly improves learning and memory in SCOP model mice and alleviates hippocampal neuronal pathological damage. The mechanisms likely involve the modulation of synaptic function, reduction of oxidative stress, and metabolic balance, with these seven key genes serving as important targets for DSS in the treatment of AD.
Animals ; Alzheimer Disease/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Mice, Inbred C57BL ; Metabolomics ; Transcriptome/drug effects* ; Maze Learning/drug effects* ; Hippocampus/metabolism* ; Humans ; Disease Models, Animal ; Memory/drug effects*

This study aims to investigate the pharmacological effects and mechanisms of Yougui Yin in treating glucocorticoid-induced osteonecrosis. A rat model of glucocorticoid-associated osteonecrosis of the femoral head(GA-ONFH) was established by intramuscular injection of dexamethasone at 20 mg·kg~(-1) every other day for 8 weeks. Rats were randomly allocated into control, model, and low-and high-dose(1.5 and 3.0 g·kg~(-1), respectively) Yougui Yin groups. After modeling, rats in Yougui Yin groups were administrated with Yougui Yin via gavage, which was followed by femoral specimen collection. Hematoxylin-eosin staining was employed to observe femoral head repair, and immunofluorescence was employed to assess adipogenic differentiation of bone marrow mesenchymal stem cells(BMSCs) within the femoral head. Cell experiments were carried out with dexamethasone(1 μmol·L~(-1))-treated BMSCs to evaluate the effects of Yougui Yin-medicated serum on adipogenic differentiation. Animal experiments demonstrated that compared with the model group, Yougui Yin at both high and low doses significantly improved bone mineral density(BMD), bone volume/total volume(BV/TV) ratio, and trabecular thickness(Tb.Th) in the femoral head. Additionally, Yougui Yin alleviated necrosis-like changes and adipocyte infiltration and significantly reduced the expression level of peroxisome proliferator-activated receptor γ(PPARγ) in the femoral head, thereby suppressing the adipogenic differentiation of BMSCs in GA-ONFH rats. The cell experiments revealed that Yougui Yin-medicated serum markedly inhibited dexamethasone-induced adipogenic differentiation of BMSCs and down-regulated the level of PPARγ. The overexpression of PPARγ attenuated the inhibitory effect of Yougui Yin-medicated serum on the adipogenic differentiation of BMSCs, indicating the critical role of PPARγ in Yougui Yin-mediated suppression of adipogenic differentiation of BMSCs. In conclusion, Yougui Yin exerts therapeutic effects on glucocorticoid-induced osteonecrosis by down-regulating PPARγ expression and inhibiting adipogenic differentiation of BMSCs.
Animals ; Mesenchymal Stem Cells/metabolism* ; PPAR gamma/genetics* ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Glucocorticoids/adverse effects* ; Rats, Sprague-Dawley ; Adipogenesis/drug effects* ; Osteonecrosis/genetics* ; Cell Differentiation/drug effects* ; Bone Marrow Cells/metabolism* ; Femur Head Necrosis/chemically induced* ; Humans