Oncolytic viruses (OVs) are emerging as potential treatment options for cancer. Natural and genetically engineered viruses exhibit various antitumor mechanisms. OVs act by direct cytolysis, the potentiation of the immune system through antigen release, and the activation of inflammatory responses or indirectly by interference with different types of elements in the tumor microenvironment, modification of energy metabolism in tumor cells, and antiangiogenic action. The action of OVs is pleiotropic, and they show varied interactions with the host and tumor cells. An important impediment in oncolytic virotherapy is the journey of the virus into the tumor cells and the possibility of its binding to different biological and nonbiological vectors. OVs have been demonstrated to eliminate cancer cells that are resistant to standard treatments in many clinical trials for various cancers (melanoma, lung, and hepatic); however, there are several elements of resistance to the action of viruses per se. Therefore, it is necessary to evaluate the combination of OVs with other standard treatment modalities, such as chemotherapy, immunotherapy, targeted therapies, and cellular therapies, to increase the response rate. This review provides a comprehensive update on OVs, their use in oncolytic virotherapy, and the future prospects of this therapy alongside the standard therapies currently used in cancer treatment.

(1) Background: Perilla frutescens (L.) Britt. is an important pharmaceutical crop that remains a focus point for researchers worldwide due to its complex phytochemical constituents, medicinal effects, and nutraceutical properties. The literature data are based on animal and cell culture studies, so the clinical evidence for the therapeutic effects is poorly outlined. The aim of this review was to provide an updated and thorough understanding of Perilla frutescens applications in clinical practice using data derived from human studies, and to outline the potential directions and perspectives for further studies on this crop. (2) Methods: Medline, Embase, and Cochrane databases were used to find relevant studies. All interventional studies that evaluated the effect of Perilla frutescens in human subjects were assessed. (3) Results: The main perspectives that can be contoured from the presented literature evaluation are an important clinical effect of Perilla frutescens extracts on allergic rhinoconjuctivitis, especially in young populations, a potent hypolipemiant effect that, in conjunction with increased serum biological antioxidant potential, determines significant improvements in cognitive function and a wide variety of miscellaneous clinical effects that need further exploration. (4) Conclusions: Supplementary research is needed in order to demonstrate the therapeutic effects of Perilla frutescens in controlled clinical settings.

(1) Background: This study aimed to outline the antioxidant, antitumoral, and cytotoxic proprieties of various types of Perilla frutescens extracts obtained from the leaves of the species. (2) Methods: We determined total polyphenols, flavonoids and anthocyanins contents, as well as the in vitro antioxidant, antitumoral, and cytotoxic actions in three types of ethanolic extracts (E1, E2, E3) and in three types of acetone: ethanol extracts (A1, A2, A3) of Perilla frutescens according to standardized procedures. (3) Results: We found that Perilla frutescens ethanolic extracts had the highest total phenol and anthocyanins concentrations. The flavonoids concentration was not statistically different between the extracts. The iron chelating capacity, hydroxyl radical scavenging capacity, superoxide anion radical scavenging capacity, and lipoxygenase inhibition capacity showed a significant increase with higher concentrations of Perilla frutescens extracts, particularly the ethanolic extracts. Perillyl alcohol had greater cytotoxic capacity in the MG-63 cell line and E1 extract showed similar significant cytotoxic effects in the A431 cell line. (4) Conclusions: Both ethanolic and acetone–ethanol extracts from Perilla frutescens exhibited important antioxidant and antitumoral actions in vitro, which proportionally increased with concentration. The cytotoxic threshold determined in this study for various types of extracts could help determine the best dosage with the maximum antioxidant and antitumoral potential. Our results could serve as a basis for further studies that will investigate the cytotoxic effects of Perilla frutescens variants on various types of cancer cell lines.

Background and Objectives: Intra/postpartum hemorrhage stands as a significant obstetric emergency, ranking among the top five leading causes of maternal mortality. The aim of this study was to assess the predictive performance of four machine learning algorithms for the prediction of postpartum and intrapartum hemorrhage. Materials and Methods: A prospective multicenter study was conducted, involving 203 patients with or without intra/postpartum hemorrhage within the initial 24 h postpartum. The participants were categorized into two groups: those with intra/postpartum hemorrhage (PPH) and those without PPH (control group). The PPH group was further stratified into four classes following the Advanced Trauma Life Support guidelines. Clinical data collected from these patients was included in four machine learning-based algorithms whose predictive performance was assessed. Results: The Naïve Bayes (NB) algorithm exhibited the highest accuracy in predicting PPH, boasting a sensitivity of 96.3% and an accuracy of 98.6%, with a false negative rate of 3.7%. Following closely were the Decision Tree (DT) and Random Forest (RF) algorithms, each achieving sensitivities exceeding 94% with a false negative rate of 5.9%. Regarding severity classification I, the NB and Support Vector Machine (SVM) algorithms demonstrated superior predictive capabilities, achieving a sensitivity of 96.4%, an accuracy of 92.1%, and a false negative rate of 3.6%. The most severe manifestations of HPP were most accurately predicted by the NB algorithm, with a sensitivity of 89.3%, an accuracy of 82.4%, and a false negative rate of 10.7%. Conclusions: The NB algorithm demonstrated the highest accuracy in predicting PPH. A notable discrepancy in algorithm performance was observed between mild and severe forms, with the NB and SVM algorithms displaying superior sensitivity and lower rates of false negatives, particularly for mild forms.

(1) Background: Cervical elastography is a new concept that could allow clinicians to assess cervical consistency in various clinical scenarios. We aimed to evaluate the predictive performance of the strain ratio (SR) at the level of the internal os, either individually or in combination with other parameters, in the prediction of spontaneous preterm birth (PTB) at various gestational ages. (2) Methods: This prospective study included 114 pregnant patients with a high-risk profile for PTB who underwent cervical elastography during the second trimester. Clinical and paraclinical data were assessed using univariate analysis, logistic regression, and sensitivity analysis. (3) Results: The SR achieved an area under the receiver operating curve (AUROC) value of 0.850, a sensitivity of 85.71%, and a specificity of 84.31% in the prediction of PTB before 37 weeks of gestation. The combined model showed superior results in terms of accuracy (AUROC = 0.938), sensitivity (92.31%), and specificity (95.16%). When considering PTB subtypes, the highest AUROC value (0.80) and accuracy (95.61%) of this marker were achieved in the prediction of extremely preterm birth, before 28 weeks of gestation. (4) Conclusions: The SR achieved an overall good predictive performance in the prediction of PTB and could be further evaluated in various cohorts of patients.

Background: Pyelonephritis during pregnancy represents a significant maternal–fetal risk, particularly in the context of increasing multidrug-resistant (MDR) bacterial infections. This study aimed to characterize the microbiological profiles and antimicrobial resistance patterns of MDR pathogens causing pyelonephritis in pregnancy. Secondary objectives included the evaluation of patient characteristics, associated risk factors, and pregnancy outcomes. Methods: A retrospective comparative study was conducted including 171 pregnant patients hospitalized with acute pyelonephritis between 1 January 2017 and 30 April 2025. Thirty-four patients with MDR bacterial infections were compared with 137 patients with infections caused by pathogens with conserved antibiotic susceptibility (Non-MDR). Results: Patients with MDR pyelonephritis were significantly older than those with Non-MDR infections (mean age 27.76 vs. 25.30 years, p = 0.03). MDR infections were more frequently diagnosed in the third trimester of pregnancy (58.8% vs. 29.9%, p = 0.003) and affected multiparous women more often (44.1% vs. 19.7%, p = 0.006). No statistically significant differences were observed between groups regarding clinical presentation or laboratory parameters (p > 0.05). Prior antibiotic exposure was significantly more common in the MDR group (85.29% vs. 26.61%, p < 0.001), as was a history of urological procedures, including urinary catheterization (29.41% vs. 15.10%, p = 0.009). For multivariate analysis, two factors were predictive for pyelonephritis with MDR pathogens: previous antibiotic treatment—OR 20.37 (95% CI 2.19–189.88) and urological procedures—OR 13.23 (95% CI 2.24-78-22). Escherichia coli was the predominant pathogen in both groups but was isolated more frequently in the Non-MDR cohort (81.75% vs. 58.82%, p = 0.015), followed by Klebsiella pneumoniae, which appeared more frequently in the study group (23.53% vs. 10.22%, p = 0.011). MDR isolates demonstrated significantly higher resistance rates to all tested antibiotics (p < 0.05). Complete resistance to ampicillin was observed in the MDR group (100%), compared with 58.01% in the Non-MDR group, indicating markedly reduced efficacy of this agent. Adverse neonatal outcomes were more frequent in the MDR group, with higher rates of Apgar scores < 7 at admission (23.5% vs. 8.8%, p = 0.01) and increased neonatal intensive care unit admission (20.6% vs. 7.3%, p = 0.02). For multivariate analysis, pyelonephritis with MDR pathogens was predictive for Neonatal Intensive Care Unit (NICU) admission (OR 8.17, 95% CI 2.41–27.67). Conclusions: These findings highlight the need for the periodic revision of empirical antibiotic protocols and risk-adapted therapeutic strategies in pregnant patients in order to reduce maternal and fetal morbidity.