LCP1 correlates with immune infiltration: a prognostic marker for triple-negative breast cancer.

OBJECTIVE: Triple-Negative Breast Cancer (TNBC) is known for its aggressiveness and treatment challenges due to the absence of ER, PR, and HER2 receptors. Our work emphasizes the prognostic value of LCP1 (Lymphocyte cytosolic protein 1), which plays a crucial role in cell processes and immune cell activity, to predict outcomes and guide treatments in TNBC. METHODS: We explored LCP1 as a potential biomarker in TNBC and investigated the mRNA and protein expression levels of LCP1. We investigated different databases, including GTEX, TCGA, GEO, cBioPortal and Kaplan-Meier Plotter. Immunohistochemistry on TNBC and benign tumor samples was performed to examine LCP1's relationship with patient clinical characteristics and macrophage markers. We also assessed survival rates, immune cell infiltration, and drug sensitivity related to LCP1 using various bioinformatics tools. RESULTS: The results indicated that LCP1 expression was higher in TNBC tissues compared to adjacent normal tissues. However, high expression of LCP1 was significantly associated with favorable survival outcomes in patients with TNBC. Enrichment analysis revealed that genes co-expressed with LCP1 were significantly enriched in various immune processes. LCP1 showed a positive correlation with the infiltration of resting dendritic cells, M1 macrophages, and memory CD4 T cells, and a negative correlation with M2 macrophages. Further analysis suggested a link between high levels of LCP1 and increased survival outcomes in cancer patients receiving immunotherapy. CONCLUSION: LCP1 may serve as a potential diagnostic and prognostic biomarker for TNBC, which was closely associated with immune cell infiltration, particularly M1 and M2 macrophages. Our findings may provide valuable insights into immunotherapeutic strategies for TNBC patients.

Effects of sleep duration and sleep quality in early pregnancy and their interaction on gestational diabetes mellitus.

PURPOSE: To examine the association of sleep duration and quality in early pregnancy with gestational diabetes mellitus (GDM), and explore their interaction effect on GDM. METHODS: Participants from 2 hospitals were enrolled in this case-control study between April 2018 and November 2020. Sleep duration and quality were measured using the Pittsburg Sleep Quality Index (PSQI). RESULTS: A total of 1300 participants (396 GDM and 904 controls) were included. After adjusting for potential confounders, higher global PSQI scores or poor sleep quality were associated with GDM with odds ratios of 1.13 (95% CI 1.07, 1.19, p < 0.001) and 1.75 (95% CI 1.29, 2.38, p < 0.001), respectively; sleep duration < 7 h, 9-9.9 h and ≥ 10 h were all associated with increased GDM with odds ratios of 4.28 (95% CI 2.51, 7.31, p < 0.001), 1.69 (95% CI 1.20, 2.39, p = 0.003), and 4.42 (95% CI 3.01, 6.50, p < 0.001), respectively. In the stratified analysis based on sleep duration, the effect of poor sleep quality on GDM in the < 7 h group (OR 5.47, 95% CI 2.57, 11.64, p < 0.001) was much stronger than that in the 7-8.9 h group (OR 1.24, 95% CI 0.81, 1.91, p = 0.327), and the p value of the interaction was 0.011. CONCLUSIONS: Poor sleep quality and short or long sleep duration in early pregnancy were all associated with GDM, and an interaction effect between short sleep duration and poor sleep quality on GDM was noted.

Tuberous sclerosis complex-lymphangioleiomyomatosis involving several visceral organs: A case report.

BACKGROUND: Lymphangioleiomyomatosis (LAM) is a rare cystic lung disease characterized by the proliferation, metastasis, and infiltration of smooth muscle cells in the lung and other tissues, which can be associated with tuberous sclerosis complex (TSC). The disorder of TSC has a variable expression, and there is great phenotypic variability. CASE SUMMARY: A 32-year-old Chinese woman with a history of multiple renal angioleiomyolipoma presented with a productive cough persisting for over 2 wk. High-resolution chest computed tomography revealed interstitial changes, multiple pulmonary bullae, bilateral pulmonary nodules, and multiple fat density areas of the inferior mediastinum. Conventional and contrast ultrasonography revealed multiple high echogenic masses of the liver, kidneys, retroperitoneum, and inferior mediastinum. These masses were diagnosed as angiomyolipomas. Pathology through thoracoscopic lung biopsy confirmed LAM. Furthermore, high-throughput genome sequencing of peripheral blood DNA confirmed the presence of a heterozygous mutation, c.1831C>T (p.Arg611Trp), of the TSC2 gene. The patient was diagnosed with TSC-LAM. CONCLUSION: We highlight a rare case of TSC-LAM and the first report of a mediastinum lymphangioleiomyoma associated with TSC-LAM.

Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network.

A number of real-world networks are heterogeneous information networks, which are composed of different types of nodes and links. Numerical prediction in heterogeneous information networks is a challenging but significant area because network based information for unlabeled objects is usually limited to make precise estimations. In this paper, we consider a graph regularized meta-path based transductive regression model (Grempt), which combines the principal philosophies of typical graph-based transductive classification methods and transductive regression models designed for homogeneous networks. The computation of our method is time and space efficient and the precision of our model can be verified by numerical experiments.