Drones have evolved significantly in recent years, acquiring greater autonomy and carrier capacity. Therefore, drones can play a substantial role in civil medicine, especially in emergency situations or for the detection and monitoring of disease spread, such as during the COVID-19 pandemic. The aim of this paper is to present the real possibilities of using drones in field rescue operations, as well as in nonsegregated airspace, in order to obtain solutions for monitoring activities and aerial work in support of the public health system in crisis situations. The particularity of our conceptual system is the use of a “swarm” of fast drones for aerial reconnaissance that operate in conjunction, thus optimizing both the search and identification time while also increasing the information area and the operability of the system. We also included a drone with an RF relay, which was connected to a hub drone. If needed, a carrier drone with medical supplies or portable devices can be integrated, which can also offer two-way audio and video communication capabilities. All of these are controlled from a mobile command center, in real time, connected also to the national dispatch center to shorten the travel time to the patient, provide support with basic but life-saving equipment, and offer the opportunity to access remote or difficult-to-reach places. In conclusion, the use of drones for medical purposes brings many advantages, such as quick help, shortened travel time to the patient, support with basic but life-saving equipment, and the opportunity to access remote or difficult-to-reach places.

(1) Background: Poisonings in children are common reasons for addressing ED and can potentially have serious complications. Our research aims to review risk factors leading to poisoning in children. (2) Methods: A retrospective review of all pediatric poisoning cases addressing the Children’s emergency department of St Mary Hospital over a two-year period was performed. (3) Results: We collected data on 797 children admitted for acute poisoning. The highest incidence identified was in the 12–18 and 1–3-year-old age groups. The distribution of voluntary versus unintentional poisonings was relatively balanced: 50.19% versus 47.43% (for some cases the type of intoxication remained unknown). Exposure to the toxic substance by ingestion was significant compared to the other routes, with an incidence of 87.1%. Acute poisoning happened at home in 70.4% of cases. A known risk factor before reaching the ED was present in 13.04%. (4) Conclusions: Our study showed a greater risk for acute poisoning in children between 1–3 years of age, and adolescents over 12 years. Identifying and documenting epidemiological aspects and other variables is important for establishing preventive measures and for therapeutic conduct. Adequate risk stratification and preventive measures involving closer supervision of minors or cognitive-behavioral programs can prevent voluntary intoxication.

Cardiopulmonary resuscitation (CPR) in special circumstances includes the emergency intervention for special causes, special environments, and special patients. Special causes cover the potential reversible causes of cardiac arrest that must be identified or excluded during any resuscitation act. The special environments section includes recommendations for the treatment of cardiac arrest occurring in specific locations: cardiac surgery, catheterization laboratory, dialysis unit, dental surgery, commercial airplanes or air ambulances, playing field, difficult environment (eg, drowning, high altitude, avalanche, and electrical injuries) or mass casualty incident. CPR for special patients gives guidance for the patients with severe comorbidities (asthma, heart failure with ventricular assist devices, neurological disease, and obesity) and pregnant women or older people. There are no generally worldwide accepted resuscitation guidelines for special circumstance, and there are still few studies investigating the safety and outcome of cardiac arrest in special circumstances. Applying standard advanced life support (ALS) guidelines in this situation is not enough to obtain better results from CPR, for example, cardiac arrest caused by electrolyte abnormalities require also the treatment of that electrolyte disturbance, not only standard CPR, or in the case of severe hypothermia, when standard ALS approach is not recommended until a temperature threshold is reached after warming measures. Data sources for this article are scientific articles describing retrospective studies conducted in CPR performed in special circumstances, experts' consensus, and related published opinion of experts in CPR. The newest advance in therapeutics applied to resuscitation field for these particular situations is the use of extracorporeal life support/extracorporeal membrane oxygenation devices during CPR. In special circumstances, ALS guidelines require modification and special attention for causes, environment, and patient particularities, with specific therapeutic intervention concomitant with standard ALS.

Background/Objective: This study explores the use of AI-powered radiomics to classify and monitor brain metastasis progression and regression following Gamma Knife radiosurgery (GKRS) based on MRI imaging. A clinical decision support application was developed using Streamlit to provide real-time, AI-driven predictions for treatment monitoring. Methods: MRI scans from 60 patients (3194 images) were analyzed using a transfer learning-enhanced AlexNet deep learning model. Class imbalance was mitigated through dynamic class weighting and data augmentation to ensure equitable performance across all classes. Optimized preprocessing pipelines ensured dataset standardization. Model performance was evaluated using accuracy, precision, recall, F1-scores, and AUC, with 95% confidence intervals. Additionally, a comparative analysis of Gamma Knife radiosurgery (GKRS) outcomes and predictive modeling demonstrated strong correlations between tumor volume evolution and treatment response. The AI predictions and visualizations were integrated into a Streamlit-based application to ensure clinical usability and ease of access. The AI-driven approach effectively classified progression and regression patterns, reinforcing its potential for clinical integration. Results: The transfer learning model achieved flawless classification accuracy (100%; 95% CI: 100–100%) along with perfect precision, recall, and F1-scores. The AUC score of 1.0000 (95% CI: 1.0000–1.0000) indicated excellent discrimination between progression and regression cases. Compared to the baseline AlexNet model (99.53% accuracy; 95% CI: 98.90–100.00%), the TL-enhanced model resolved all misclassifications. Tumor volume analysis identified the baseline size as a key predictor of progression (Pearson r = 0.795, r = 0.795, r = 0.795, p < 0.0001, p < 0.0001, and p < 0.0001). The training time (420.12 s) was faster than ResNet-50 (443.38 s) and EfficientNet-B0 (439.87 s), while achieving equivalent metrics. Despite 100% accuracy, the model requires multi-center validation for generalizability. Conclusions: This study demonstrates that transfer learning with dynamic class weighting provides a highly accurate and reliable framework for monitoring brain metastases post-GKRS. The Streamlit-based AI application enhances clinical decision-making by improving diagnostic precision and reducing variability. Explainable AI techniques, such as Grad-CAM visualizations, improve interpretability and support clinical adoption. These findings emphasize the transformative potential of AI in personalized treatment strategies, extending applications to genomic profiling, survival modeling, and longitudinal follow-ups for brain metastasis management.

Drug delivery to the anterior or posterior segments of the eye is a major challenge due to the protection barriers and removal mechanisms associated with the unique anatomical and physiological nature of the ocular system. The paper presents the preparation and characterization of drug-loaded polymeric particulated systems based on pre-emulsion coated with biodegradable polymers. Low molecular weight biopolymers (chitosan, sodium hyaluronate and heparin sodium) were selected due to their ability to attach polymer chains to the surface of the growing system. The particulated systems with dimensions of 190–270 nm and a zeta potential varying from −37 mV to +24 mV depending on the biopolymer charges have been obtained. Current studies show that particles release drugs (dexamethasone/pilocarpine/bevacizumab) in a safe and effective manner, maintaining therapeutic concentration for a longer period of time. An extensive modeling study was performed in order to evaluate the drug release profile from the prepared systems. In a multifractal paradigm of motion, nonlinear behaviors of a drug delivery system are analyzed in the fractal theory of motion, in order to correlate the drug structure with polymer. Then, the functionality of a SL(2R) type “hidden symmetry” implies, through a Riccati type gauge, different “synchronization modes” (period doubling, damped oscillations, quasi-periodicity and intermittency) during the drug release process. Among these, a special mode of Kink type, better reflects the empirical data. The fractal study indicated more complex interactions between the angiogenesis inhibitor Bevacizumab and polymeric structure.

Endometriosis is considered a serious public health issue because of the large number of females affected by this illness. Chronic pain management in patients with endometriosis demands new strategies to increase the life quality of these patients. The development of drug delivery systems represents a new approach in pain treatment among endometriosis patients. Diclofenac sodium, one of the most utilized nonsteroidal anti-inflammatory drugs (NSAID), has its own limitations when being used in formulas such as oral, parental, or local applications. In this paper, a series of four drug release formulations based on chitosan, 2-hydroxy-5-nitrobenzaldehyde, and diclofenac sodium salt were prepared in view of the investigation of the drug release ability. The formulations were analyzed from a morphological and supramolecular point of view by scanning electron microscopy and polarized light microscopy. The in vitro drug release ability was investigated by mimicking a physiologic environment. A mathematical model, using the fractal paradigm of motion, is utilized to explain the behaviors of the drug delivery system presented in this paper. These results suggest a great potential of the proposed drug delivery system, based on chitosan and 2-hydroxy-5-nitrobenzaldehyde to improve the diclofenac sodium salt bioavailability, and it may represent a future treatment formula for endometriosis pain.