Grigore T. Popa University of Medicine and Pharmacy

Heart rate variability (HRV) reflects autonomic regulation and has emerged as a dual-use digital biomarker across clinical care and operational performance. We sought to integrate evidence on HRV’s physiological basis, clinical utility, defense applications, and AI-enabled analytics, and to propose a cross-sector framework for predictive, ethical deployment. We conducted a structured literature review in MEDLINE (PubMed), Embase, and Scopus between July 1st and August 31st, 2025, without language restriction. Eligible studies reported human HRV parameters measured in clinical, operational/defense, or AI contexts. Owing to heterogeneity, findings were summarized narratively across five domains: physiology, clinical applications, operational use, AI/predictive analytics, and ethics/standardization. Evidence from military and operational studies supports HRV as a physiological indicator of stress accumulation, fatigue, and recovery during sustained workload and mission exposure. Across training environments, continuous HRV monitoring captured early autonomic changes preceding measurable performance decline or clinical symptoms. During prolonged field exercises, nocturnal HRV reductions consistently reflected accumulated allostatic load, while daily fluctuations in SDNN, RMSSD, and LF/HF ratios revealed real-time adaptations to physical exertion, sleep deprivation, and psychological strain. These dynamic shifts offered a quantifiable index of resilience, distinguishing between individuals able to sustain operational effectiveness and those approaching physiological or cognitive exhaustion. AI further enhances this capability by identifying non-linear and context-dependent HRV patterns that precede fatigue or decompensation. Machine-learning models trained on multimodal data streams enable early detection of autonomic instability and predictive risk stratification in both training and operational theaters. HRV is not just a number—it is a real-time window into how our bodies respond to life’s challenges, from the doctor’s office to the most demanding missions. What makes HRV so unique is its “dual-use” quality: it matters just as much for medical professionals caring for patients as it does for those monitoring the wellbeing and performance of people working under stress, such as soldiers or first responders. By treating HRV as a dual-use tool, one can bridge the worlds of healthcare and operational performance. This means the same heartbeat data that helps predict heart problems for a patient can also warn a team leader when their crew might be on the edge of exhaustion. But making the most of HRV in both settings requires to collect data consistently, analyze it with trustworthy AI, protect privacy, and put clear guidelines in place. In doing so, HRV becomes more than a monitor—a practical, ethical way to support better decisions, whether saving lives in a hospital or keeping people safe and effective under pressure.

Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) are high-burden healthcare-associated pathogens that increase mortality, prolong hospitalisation, and drive substantial healthcare costs worldwide. These infections are associated with high morbidity, increased mortality, prolonged hospital stays, and significant costs, particularly among immunocompromised patients or those with extended hospitalizations. This systematic review was conducted and reported in accordance with PRISMA 2020, aiming to synthesise existing data on the epidemiology, resistance mechanisms, clinical manifestations, and strategies for the diagnosis, treatment, and prevention of MRSA and VRE infections. Data were qualitatively synthesised. A total of 113 records published between 2020 and 2025 met the inclusion criteria and were identified through searches in multiple bibliographic databases and publisher platforms (e.g., PubMed, Scopus, Web of Science). MRSA and VRE are implicated in numerous severe infections, including ventilator-associated pneumonia, catheter-associated urinary tract infections, endocarditis, and bacteraemia. Antimicrobial resistance is driven by the mecA, vanA, and vanB genes, while biofilm formation further complicates therapeutic efforts. Biofilm formation can promote antibiotic tolerance (slower killing without an increase in MIC) and persistence (survival of ‘persister’ cells), distinct from genetic resistance, and may complicate therapy in selected infections. Effective strategies include appropriate anti-MRSA/anti-VRE agents (e.g., ceftaroline for MRSA; linezolid or daptomycin for VRE), active screening, stringent infection prevention and control measures, and antimicrobial stewardship programmes. Implementation is often hindered by institutional barriers, limited resources, and insufficient staff training. A multidisciplinary, evidence-based approach is essential for the effective management of these infections. Reducing this burden requires coordinated implementation of rapid diagnostics, stringent infection prevention and control, and antimicrobial stewardship, supported by sustained institutional and public health investment.

Background/Objectives: This study evaluated the diagnostic accuracy of cervical cytology, CINtec® (p16/Ki-67 dual staining), and PD-L1 immunohistochemistry, individually and in combination with high-risk HPV (HR-HPV) testing, for identifying histologically confirmed cervical lesions ranging from CIN1 to invasive carcinoma. Methods: We conducted a prospective cross-sectional study including 114 patients who underwent cervical cytology, CINtec®, PD-L1 staining, HPV genotyping, and histopathologic confirmation at a tertiary clinical center between September 2024 and September 2025. Sensitivity, specificity, PPV, NPV, and ROC performance were calculated for each test across lesion categories. Multivariable logistic regression models incorporating HR-HPV status were used to assess added predictive value. Results: All tests showed poor performance for CIN1 (cytology AUC 0.488; CINtec® 0.374; PD-L1 0.366). Diagnostic accuracy improved markedly with lesion severity. For CIN3, CINtec® demonstrated the highest discriminative ability (AUC 0.826), with cytology and PD-L1 also performing well (AUC 0.820 and 0.753). Cytology achieved the strongest ROC performance for CIN2+ (AUC 0.937), CIN3+ (0.913), and invasive carcinoma (0.887). PD-L1 consistently showed lower accuracy across categories. Cytology + HR-HPV demonstrated the highest AUC across all lesion categories. Conclusions: Cytology and CINtec® exhibited strong diagnostic accuracy for high-grade lesions, while PD-L1 showed limited utility as an independent screening marker. Combining cytology with HR-HPV testing enhanced predictive performance across all lesion categories. These findings support the continued use of cytology-based triage and highlight CINtec® as a valuable adjunct for high-grade disease detection. Because this study used a high-prevalence referral cohort, specificity may be overestimated and not representative of population-based screening.

Obesity and type 2 diabetes mellitus are increasingly recognized as important risk factors for cancer development and progression, including cancers of the digestive system. Indeed, epidemiologic evidence demonstrated that both conditions increase the risk of digestive system cancer incidence and mortality, although with sex-specific and ethnic variations for certain associations with specific types of cancers. While these associations were quite consistent, study design and quality differences, lack of uniform adjustment for confounding factors, heterogeneity and various biases require caution when interpreting the results. The intricate processes by which these two closely related metabolic diseases contribute to carcinogenesis involve increased substrate availability and metabolic dysregulation that create a cellular microenvironment permissive to the activation of multiple signaling pathways that contribute to tumor growth and proliferation. This review thoroughly explores the complex interplay of metabolic and inflammatory mechanisms underlying these processes, including hyperglycemia, insulin resistance, altered insulin‑like growth factor-1 signaling, dysregulated adipokines, hormonal imbalance, gut dysbiosis, chronic inflammation and altered immune response, altered mitochondrial function and oxidative stress, circadian rhythm disruption, altered autophagy. Nevertheless, most mechanistic evidence derives from in vitro systems or non-human animal models which may not fully replicate human pathophysiology and disease, and thus extrapolation to human cancer risk should be made cautiously. Given this complex mechanistic interplay, it is evident that obesity and T2DM-associated metabolic alterations play an important role in carcinogenesis, highlighting the need for targeted prevention strategies in high-risk populations, such as weight management and glycemic control, to mitigate cancer burden.

Background/Objectives: Multilayer zirconia restorations can feature a shade gradient or a strength gradient, with layers differing in color or phase composition within the same material. The aim of this in vitro study was to evaluate the color stability in all layers of multilayer zirconia after exposure to staining solutions and artificial aging. Methods: Square-shaped specimens (N = 120) of color A2 were fabricated from 4Y-PSZ and 3Y/4Y-PSZ multilayer zirconia—Katana STML, DD Cube One ML, and Katana YML—and their baseline color values (T0) were measured with a clinical spectrophotometer (VITA Easyshade V). The specimens were randomly divided into four groups (n = 10/gp) and immersed in physiologic solution, 0.2% chlorhexidine gluconate (CHX) mouth rinse, and staining coffee solution. Then, they were measured continuously for 7 (T1), 14 (T2), and 21 days (T3). The last group of specimens underwent accelerated aging in a steam autoclave at 134 °C and 2 bar pressure and measured after 1 (T1), 3 (T2), and 5 h (T3). After the immersion process and artificial aging, discoloration values (ΔE) were calculated using the formula ΔE = [(ΔL*)2 + (Δa*)2 + (Δb*)2]1/2 and analyzed with the SPSS v 23.0 software with a p value < 0.05. Results: All specimens showed significant color differences in the T3 measurements after exposure to coffee and CHX, with the highest ΔE values in the enamel layers. Katana YML showed the most significant differences in ΔE in the cervical layers after exposure to artificial aging. Conclusions: Multilayer zirconia exhibited dependent optical changes, with the enamel layers being the most affected after exposure to staining solutions. Gradient pigmentation and differences in phase composition caused differences in color to the multilayer zirconia layers after exposure to staining solutions and artificial aging.