The microbiota is the complex community of microorganisms that populate a particular environment in the human body, whereas the microbiome is defined by the entire habitat—microorganisms and their environment. The most abundant and, therefore, the most studied microbiome is that of the gastrointestinal tract. However, the microbiome of the female reproductive tract is an interesting research avenue, and this article explores its role in disease development. The vagina is the reproductive organ that hosts the largest number of bacteria, with a healthy profile represented mainly by Lactobacillus spp. On the other hand, the female upper reproductive tract (uterus, Fallopian tubes, ovaries) contains only a very small number of bacteria. Previously considered sterile, recent studies have shown the presence of a small microbiota here, but there are still debates on whether this is a physiologic or pathologic occurrence. Of particular note is that estrogen levels significantly influence the composition of the microbiota of the female reproductive tract. More and more studies show a link between the microbiome of the female reproductive tract and the development of gynecological cancers. This article reviews some of these findings.

Background/Objectives: Integrating Artificial Intelligence Clinical Decision Support Systems (AI-CDSSs) into healthcare can improve diagnostic accuracy, optimize clinical workflows, and support evidence-based medical decision-making. However, the adoption of AI-CDSSs remains uneven, influenced by technological, organizational, and perceptual factors. This study, conducted between November 2024 and February 2025, analyzes the determinants of AI-CDSS adoption among healthcare professionals through investigating the impacts of perceived benefits, technological costs, and social and institutional influence, as well as the transparency and control of algorithms, using an adapted Path Dependence-Augmented–Unified Theory of Acceptance and Use of Technology model. Methods: This research was conducted through a cross-sectional study, employing a structured questionnaire administered to a sample of 440 healthcare professionals selected using a stratified sampling methodology. Data were collected via specialized platforms and analyzed using structural equation modeling (PLS-SEM) to examine the relationships between variables and the impacts of key factors on the intention to adopt AI-CDSSs. Results: The findings highlight that the perceived benefits of AI-CDSSs are the strongest predictor of intention to adopt AI-CDSSs, while technology effort cost negatively impacts attitudes toward AI-CDSSs. Additionally, social and institutional influence fosters acceptance, whereas perceived control and transparency over AI enhance trust, reinforcing the necessity for explainable and clinician-supervised AI systems. Conclusions: This study confirms that the intention to adopt AI-CDSSs in healthcare depends on the perception of utility, technological accessibility, and system transparency. The creation of interpretable and adaptive AI architectures, along with training programs dedicated to healthcare professionals, represents measures enhancing the degree of acceptance.

Background: Vascular endothelial growth factor (VEGF) plays an important role in tumor progression in ovarian cancer, but the complex mechanism and interaction with oxidative stress are not fully understood. Methods: A prospective study included 52 patients with ovarian adenocarcinoma stage IIIA-IV. Serum VEGF and reactive oxygen species (ROS) such as malondialdehyde and ceruloplasmin were measured. Results: VEGF levels were elevated (mean 1014.7 ± 165 pg/mL), especially in patients with macroscopic residual disease (1058 vs. 810 pg/mL, p = 0.0001). Median progression-free survival (PFS) and overall survival (OS) were 6 and 40 months in patients with a very high VEGF (over 1200 pg/mL), 11 and 48 months in patients with VEGF between 1000–1200 pg/mL, 18 and 84 months in patients with VEGF between 800–1000 pg/mL, and not reached in patients with normal VEGF. Increased VEGF values were associated with a 2.6-fold increased risk of disease progression (HR = 2.60, 95% CI 1.69–3.99), and a 1.4-fold increased risk of death (HR = 1.4, 95% CI 1.15–1.91, p = 0.002). Receiver operator characteristic (ROC) curves were used to validate VEGF as a prognostic factor and the area under the curve (AUC) was 0.814, p = 0.036 for PFS and 0.729, p = 0.043, for OS. There was a positive correlation between VEGF and malondialdehyde, Pearson coefficient of 0.35, p = 0.0001. Conclusions: VEGF and malondialdehyde are important prognostic markers in ovarian cancer, especially in macroscopic residual disease, and there is a positive correlation between angiogenesis and oxidative stress.

Background/Objectives: Malnutrition is a key determinant of quality of life (QoL) in patients with head and neck cancers (HNCs), influencing treatment outcomes and the occurrence of adverse events (AEs). Despite there being numerous studies on nutritional status and QoL, there is no standardized risk or prognostic model integrating clinical and demographic factors. Methods: A literature search was conducted in September 2024 in Scopus, PubMed, and Web of Science, covering studies published between 2013 and 2024. Articles were selected based on their relevance to AEs, nutritional interventions, and QoL assessments in HNC patients. Results: The key factors influencing QoL in HNC patients include age, sex, weight, BMI, educational level, and tumor features. Mucositis was identified as the most significant food intake-impairing AE, contributing to malnutrition and reduced QoL. Current QoL assessments rely on descriptive questionnaires, which lack personalization and predictive capabilities. Digital tools, including machine learning models and digital twins, offer potential solutions for risk prediction and personalized nutritional interventions. Conclusions: Despite significant research efforts, QoL assessment in HNC patients remains non-uniform, and risk models integrating nutritional status are lacking. A comprehensive, personalized approach is needed, leveraging digital tools to improve nutritional intervention strategies.

Background: Cervical cancer ranks third in frequency among female cancers globally and causes high mortality worldwide. Concurrent chemoradiotherapy improves the overall survival in cervical cancer patients by 6% but it can cause significant acute and late toxicities affecting patient quality of life. Whole pelvis radiotherapy doses of 10–20 Gy can lead to myelosuppression and to subsequent hematological toxicities since pelvic bones contain half of bone marrow tissue. Methods: A total of 69 patients with IB-IVB-staged cervical cancer have been included in this retrospective cohort study. We analyzed clinical adverse events and changes in blood cell counts (hemoglobin, neutrophils, leukocytes, and platelets) during radiation or chemoradiotherapy received at the Oncological Institute of Bucharest from 2018 to 2021. Results: Decreases in hemoglobin levels of over 2.30 g/dL during treatment were associated with BMI > 23.2 kg/m² (OR = 8.68, 95%CI = [1.01, 75.01]), age over 53 years (OR = 4.60 95%CI = [1.10, 19.22]), with conformational 3D irradiation (OR = 4.78, 95%CI = [1.31, 17.40]) and with total EQD2 of over 66.1 Gy (OR = 3.67, 95%CI = [1.02, 13.14]). The hemoglobin decrease rate of 0.07 g/dL/day was related to 95% isodose volume (OR = 18.00). Neutropenia is associated frequently with gastrointestinal side effects and with the bowel and rectal V45 isodoses (OR = 16.5 and OR = 18.0, respectively). Associations of total external and internal radiation dose with the time durations calculated from the initiation of treatment to the onset of hematological adverse reactions were also obtained. The maximum drop in leukocytes was observed before day 35 from the RT initiation in patients who underwent treatment with 3D conformal radiotherapy (OR = 4.44, 95%CI = [1.25, 15.82]). Neutrophil levels under 2.2 × 10³/μL and thrombocyte levels under 131 × 10³/μL during the follow-up period were associated with a total planned dose of 54 Gy to the pelvic region volume (OR = 6.82 and OR = 6.67, respectively). Conclusions: This study shows the existence of clinical and blood predictors of hematological adverse reactions in cervical cancer patients. Thus, patients who are in a precarious clinical situation, with low hematological values (but not yet abnormal), should be monitored during days 29–35 after the initiation of RT, especially if they are obese or over 53 years of age.