Publications

Background: Pericytes, a type of mural cells, exert important functions in the CNS. One major challenge in pericyte research is the lack of pericyte-specific and subpopulation-specific markers.

Methods: To address this knowledge gap, we first generated a novel transgenic mouse line in which vascular smooth muscle cells (vSMCs) are permanently labeled with tdTomato. Next, we isolated PDGFRβ⁺tdTomato^- pericytes and PDGFRβ⁺tdTomato⁺ vSMCs from the brains of these mice and subsequently performed RNAseq analysis to identify pericyte-enriched genes.

Results: Using this approach, we successfully identified 40 pericyte-enriched genes and 158 vSMC-enriched genes, which are involved in different biological processes and molecular functions. Using ISH/IHC analysis, we found that Pla1a and Cox4i2 were predominantly enriched in subpopulations of brain pericytes, although they also marked some non-vascular parenchymal cells.

Conclusions: These findings suggest that Pla1a and Cox4i2 preferably label subpopulations of pericytes in the brain compared to vSMCs, and thus, they may be useful in distinguishing these populations.

BACKGROUND: Current breast cancer prediction models typically rely on personal information and medical history, with limited inclusion of blood-based biomarkers. This study aimed to identify novel breast cancer risk factors using machine learning algorithms. By integrating both personal clinical factors and peripheral blood biochemical biomarkers, it sought to enhance the understanding of breast cancer risk.

METHODS: Data were screened and normalized according to predefined inclusion and exclusion criteria. Logistic regression with forward selection and six other machine learning algorithms were employed to identify variables associated with breast cancer incidence. The performance of the models was evaluated using the area under the curve (AUC) through 5-fold cross-validation.

RESULTS: The data were divided into a training cohort of 17,360 cases and a testing cohort of 8,551 cases. Logistic regression analysis revealed that breast cancer incidence was increased with age (odds ratio [OR]:1.136, 95% confidence interval [CI]: [1.130, 1.142], P < 0.001), gamma-glutamyl transferase (GGT) (OR: 1.002, 95% CI: [1.000, 1.004], P = 0.014), and alanine transaminase (ALT) (OR: 1.005, 95% CI: [1.001, 1.008], P = 0.008). Furthermore, the six machine learning algorithms consistently identified GGT and ALT as the most significant predictive features. The AUC values obtained from the six models after 5-fold cross-validation ranged from 0.779 to 0.862, with accuracy ranging from 0.780 to 0.841.

CONCLUSIONS: Our study identified two biochemical biomarkers (GGT and ALT) as promising indicators for breast cancer prediction. Incorporating these findings into a tailored breast cancer risk prediction model is needed in our future research.

OBJECTIVE: To evaluate the presence of Fusobacterium spp. and Fusobacterium nucleatum in eutopic endometrial samples from women with endometriosis compared to controls, and assess their association with the disease.

DESIGN: Retrospective case-control study.

SUBJECTS: Ninety-two women (55 endometriosis cases and 37 controls) aged 18-44 undergoing gynecologic endoscopy for endometriosis and/or benign conditions at University of Pennsylvania, Endomarker Study (PMID: 29524590).

EXPOSURE: DNA extraction from eutopic endometrial samples using QIAamp DNA Microbiome and IndiSpin® Pathogen Kits. Quantification of Fusobacterium spp. and F. nucleatum by quantitative PCR using genus- and species-specific primers.

MAIN OUTCOME MEASURE(S): Relative abundance of Fusobacterium spp. and F. nucleatum in cases versus controls, analyzed using the ΔCt method.

RESULTS: No significant difference in Fusobacterium spp. or F. nucleatum abundance was observed between cases and controls (P = 0.258 for genus-specific primers, P = 0.738 for species-specific primers). Subgroup analysis by disease severity (minimal-mild: n=42; moderate-severe: n=13) also showed no significant differences (Fusobacterium spp.: P = 0.1465; F. nucleatum: P = 0.2936).

CONCLUSION: Fusobacterium spp. is not differentially present in eutopic endometrium of women with endometriosis, regardless of disease severity according to rASRM classification. This contrasts with prior findings in eutopic endometrium in patients with ovarian endometriosis, suggesting that Fusobacterium has limited diagnostic or prognostic value in endometriosis.

[This corrects the article on p. 99 in vol. 14, PMID: 40271276.].

[This corrects the article on p. 300 in vol. 17, PMID: 21253388.].

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer, with tumor cells readily disseminating to other organs through the bloodstream, lymphatic system, and nervous system, thereby impacting patients' survival rates. PDAC is often associated with perineural invasion (PNI), which not only facilitates tumor spread but may also lead to symptoms such as pain, further affecting the patient's quality of life. PNI is frequently observed in PDAC and has become an important histopathological marker associated with poor clinical outcomes. Many studies suggest that a high density of Schwann cells (SCs) is typically found in areas of PNI in PDAC. What's more, as the primary glial cells in the PNS, SCs actively contribute to pancreatic tumour progression by releasing substances capable of interacting with cancer cells and promoting cancer cells proliferation and migration in tumor microenvironment (TME). Therefore, SCs are crucial in the interactions between nerves and tumors as the primary glial cells within PNS. In this review, our objective is to present novel insights and perspectives for PDAC therapy that targets SCs and related signal pathways to decrease PNI, thereby reduce pain and prolong survival in cancer patients. We detail and summarize the multiple mechanisms by which SCs promote PNI in tumors and thus lead to malignancy.

This corrects the article on p. e63 in vol. 40, PMID: 40329789.

This commentary article discusses a recent study article published in Journal of International Cardiology, entitled "Abusnina, W., Chaturvedi, A., Chitturi, K.R., Lupu, L., Haberman, D., Cellamare, M., Sawant, V., Zhang, C., Ben-Dor, I., Satler, L.F., Hashim, H.D., Case, B.C., Waksman, R. Gender disparities incangrelorusage for the treatment of patients with acute coronary syndrome undergoing percutaneous coronary intervention. Int J Cardiol., 432 (2025), pp. 133280. doi: 10.1016/j.ijcard.2025.133280.". PMID: 40228585. Online ahead of print.