Identification of Ovarian High-Grade Serous Carcinoma with Mitochondrial Gene Variation.

Gonzalez Bosquet J, Wagner V, Polio A, Linder KE, Bender DP, Goodheart MJ, Schickling BM.

Int J Mol Sci. 2025 Feb 5;26(3):1347. doi: 10.3390/ijms26031347. PMID: 39941116; PMCID: PMC11818617.

Women diagnosed with advanced-stage ovarian cancer have a much worse survival rate than women diagnosed with early-stage ovarian cancer, but the early detection of this disease remains a clinical challenge. Some recent reports indicate that genetic variations could be useful for the early detection of several malignancies. In this pilot observational retrospective study, we aimed to assess whether mitochondrial DNA (mtDNA) variations could discriminate the most frequent type of ovarian cancer, high-grade serous carcinoma (HGSC), from normal tissue. We identified mtDNA variations from 20 whole-exome sequenced (WES) HGSC samples and 14 controls (normal tubes) using the best practices of genome sequencing. We built prediction models of cancer with these variants, with good performance measured by the area under the curve (AUC) of 0.88 (CI: 0.74-1.00). The variants included in the best model were correlated with gene expression to assess the potentially affected processes. These analyses were validated with the Cancer Genome Atlas (TCGA) dataset, (including over 420 samples), with a fair performance in AUC terms (0.63-0.71). In summary, we identified a set of mtDNA variations that can discriminate HGSC with good performance. Specifically, variations in the MT-CYB gene increased the risk for HGSC by over 30%, and MT-CYB expression was significantly decreased in HGSC patients. Robust models of ovarian cancer detection with mtDNA variations could be applied to liquid biopsy technology, like those which have been applied to other cancers, with a special focus on the early detection of this lethal disease.

For a full text of the article, click here: https://www.mdpi.com/1422-0067/26/3/1347

Vaccines in Pregnancy: An Update on Recommendations From CDC's Advisory Committee on Immunization Practices.

Rasmussen SA, Kim J, Jamieson DJ.

Birth Defects Res. 2025 Feb;117(2):e2459. doi: 10.1002/bdr2.2459. PMID: 39996387.

Vaccinations in pregnancy are an essential part of prenatal care and play a critical role in protecting both pregnant persons and their infants from certain infectious diseases. In the United States, recommendations for vaccines are made through a comprehensive review of currently available scientific literature, including clinical trials and post-marketing surveillance data, by the Advisory Committee on Immunization Practices (ACIP). The ACIP is an advisory committee to the US Centers for Disease Control and Prevention (CDC), comprised of medical and public health experts who develop evidence-based recommendations and guidelines for vaccinations, including for pregnant persons. The ACIP has several work groups that review scientific evidence on an ongoing basis, and full-committee public meetings are held at least three times a year. As more data regarding the safety and efficacy of vaccines in pregnancy become available, these recommendations continue to evolve. To develop these recommendations, the ACIP carefully considers the risks of exposure to infectious agents against the potential risks of vaccination. We review here current ACIP recommendations for vaccinations and their use in pregnant persons. Recommendations are divided into four categories: vaccines recommended during pregnancy, vaccines recommended during pregnancy under certain circumstances, vaccines not recommended or contraindicated during pregnancy, and vaccines without specific ACIP recommendations. To ensure optimal care during pregnancy, healthcare providers who care for pregnant persons need to be familiar with these recommendations.

For a full text of the article, click here: https://onlinelibrary.wiley.com/doi/full/10.1002/bdr2.2459

Validation of the Patient-Reported Outcomes Measurement Information System Pain Intensity and Brief Pain Inventory During Pregnancy.

Vignato J, Perkhounkova Y, Marilim H, Lee J, Hein M, Santillan D, Santillan M.

West J Nurs Res. 2025 Feb 8:1939459251317270. doi: 10.1177/01939459251317270. Epub ahead of print. PMID: 39921452.

• We sought to (1) validate the Patient-Reported Outcomes Measurement Information System (PROMIS) Pain Intensity Short Form 3a measure and Brief Pain Inventory (BPI) for assessing pain during pregnancy and (2) evaluate pain in a sample of pregnant individuals.

• Pregnant individuals (N = 196) were prospectively surveyed: n = 171 up to 22 weeks gestational age, n = 123 during their third trimester of pregnancy, and n = 98 both times. Additional measures included SPRINT Post-Traumatic Stress Disorder Tool, Neurological Quality of Life, Edinburgh Postnatal Depression Scale and anxiety subscale, and Adverse Childhood Experiences Questionnaire. Validity evidence examined included content validity, reliability, convergent and discriminant validity, and relevant criterion relationships.

• Content validity analysis suggests that the PROMIS pain measure was easy to use and interpret while the BPI provided more detail. However, BPI questions regarding medication usage and relief were unclear to some pregnant individuals. In addition, the relationships among pain ratings were stronger than relationships between pain ratings and measures intended to assess other constructs suggesting convergent and discriminant validity. Relationships with relevant criterions were presented for both the PROMIS and BPI by comparing ratings of pain intensity and severity for pregnant individuals with and without areas of pain reported on BPI.

Conclusion: Results indicate that PROMIS and BPI provided valid information on pain intensity or severity for our perinatal sample. Depending on the research question, the PROMIS pain or BPI may be more appropriate to an individual study. Either measure could also be included in an electronic health record for accurate pain assessment in clinical settings.

For a full text of the article, click here: https://journals.sagepub.com/doi/epub/10.1177/01939459251317270