Purpose: To evaluate the effect of switching from preserved prostaglandin analog-timolol fixed combinations (PG-timolol FCs) to preservative-free latanoprost-timolol FC (PF-LT) on intraocular pressure (IOP), ocular surface health, and tolerability in glaucoma and ocular hypertension (OH) patients with the concurrent ocular surface disease (OSD). Methods: This was a longitudinal, prospective, interventional, real-life study among 42 patients. Up to 3 visits were planned, at baseline, 30, and 90 days to assess efficacy on IOP decrease and local tolerance. The severity of OSD symptoms [Ocular Surface Disease Index (OSDI) questionnaire], subjective drug tolerability [visual analog scale (VAS)], conjunctival hyperemia (McMonnies scale), and tear break-up time (TBUT) were the main parameters assessed. Results: Data from 36 patients were available for statistical analysis. IOP was significantly reduced at day 30 and day 90 compared to baseline (16 vs 14 vs 14 mmHg, p < 0.001). Significant improvement was demonstrated in OSD symptoms, signs, and VAS scores from the baseline to the second and third visits. Median OSDI (27.1 vs 9.6 vs 4.2, p < 0.001), conjunctival hyperemia (2 vs 1 vs 1, p < 0.001), corneal surface staining (p < 0.001), and conjunctival staining scores (p < 0.001), and the percentage of patients with eyelid and periocular hyperemia (61.1 vs 12.5 vs 2.8%, p < 0.001), significantly decreased. TBUT (4 vs 5 vs 6 s, p < 0.001) and VAS score regarding tolerability (5 vs 2 vs 1, p < 0.001) significantly increased. Conclusion: A switch from preserved PG-timolol FCs to PF-LT improved tolerability and optimized IOP control, providing better adherence with greater chances of treatment success.

Fast development of digital and computer systems has profoundly shaped the evolution of artificial intelligence (AI) and expanded its use across almost every aspect of society. Medicine stands among the fields most deeply transformed by this revolution where AI can accelerate diagnostic processes, personalize treatments, support clinical decision-making and enhance education. Yet the same technological progress that enables these benefits also introduces new vulnerabilities and exposure to growing cyber threats. As in other areas of use of digital and computer technologies (especially advanced ones), the possibility of their misuse for various purposes and with different motives is increasing: from personal revenge, through organized crime (national and international) and influencing operations to espionage and terrorism. This paper explores the dual nature of AI in medicine: as both an enabler of progress and a potential vector of systemic risk, through the lenses of information and cybersecurity, intelligence, and resilience. It examines the technological and organizational dimensions of these challenges by jointly analyzing documented AI-enabled clinical infrastructures, data flows, and security controls alongside governance structures, institutional responsibilities, and human factors shaping system resilience. As researchers, clinicians, technologists, intelligence analysts, and security professionals, we believe that this human dimension must guide all our efforts to ensure that AI (today and in the future) serves its true purpose: strengthening medicine’s capacity to heal, protect, learn, prevent, and uphold the dignity of human life.