Identification of potential therapeutic targets for breast cancer using Mendelian randomization analysis and drug target prediction.

Breast cancer stands as the foremost cause of cancer-related mortality among women, presenting a substantial economic impact on society. The limitations in current therapeutic options, coupled with poor patient tolerance, underscore the urgent need for novel treatments. Our study embarked on a genomic association exploration of breast cancer, leveraging whole-genome sequencing data from the Finngen database, complemented by expression quantitative trait loci (eQTL) insights from the eQTLGen and GTEx Consortiums. An initial investigation was conducted through summary-based Mendelian randomization (MR) to pinpoint primary eQTLs. Analysis of blood specimens revealed 103 eQTLs significantly correlated with breast cancer. Focusing our efforts, we identified 19 candidates with potential therapeutic significance. Further scrutiny via two-sample MR pinpointed UROD, LMO4, HORMAD1, and ZSWIM5 as promising targets for breast cancer therapy. Our research sheds light on new avenues for the treatment of breast cancer, highlighting the potential of genomic association studies in uncovering viable therapeutic targets.

Application of O-RADS Ultrasound Lexicon-Based Logistic Regression Analysis Model in the Diagnosis of Solid Component-Containing Ovarian Malignancies.

Objective: To use the logistic regression model to evaluate the value of ultrasound characteristics in the Ovarian-Adnexal Reporting and Data System ultrasound lexicon in determining ovarian solid component-containing mass benignancy/malignancy. Methods: We retrospectively analyzed the data of 172 patients with adnexal masses discovered by ultrasound, and diagnosis was confirmed by postoperative pathological tests from January 2019 to December 2021. Thirteen ovarian tumor-related parameters in the benign and malignant ovarian tumor groups were selected for univariate analyses. Statistically significant parameters were included in multivariate logistic regression analyses to construct a logistic regression diagnosis model, and the diagnostic performance of the model in predicting ovarian malignancies was calculated. Results: Of the 172 adnexal tumors, 104 were benign, and 68 were malignant. There were differences in cancer antigen 125, maximum mass diameter, maximum solid component diameter, multilocular cyst with solid component, external contour, whether acoustic shadows were present in the solid component, number of papillae, vascularity, presence/absence of ascites, and presence/absence of peritoneal thickening or nodules between the benign ovarian tumor and malignancy groups (p < 0.05). Logistic regression analyses showed that maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites were included in the logistic regression model, and the area under the receiver operating characteristic curve for this regression model in predicting ovarian malignancy was 0.962 (95% confidence interval: 0.933~0.990; p < 0.001). Logit (p) ≥ -0.02 was used as the cutoff value, and the prediction accuracy, sensitivity, specificity, positive predictive value, and negative predictive values were 93.6%, 86.8%, 98.1%, 96.7%, and 91.9%, respectively. Conclusion: The logistic regression model containing the maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites can help in determining the benignancy/malignancy of solid component-containing masses.

Accidental infusion leakage at subgalea in infants: report of 6 cases.

Infiltration remains the commonest iatrogenic injury within infants care. We report a series of 6 infants affected by accidental infusion leakage occurring in subgalea. They were applied wet-hot compresses by sterile gauze, and topically administrated mucopolysaccharide polysulfate (MPS) cream following hot compress. There was no skin impairment in all cases. Early recognition and appropriate care for topical skin are essential to minimize the extent of accidental infusion leakage.