Background/Objectives: To assess the knowledge, attitudes, and practices of ophthalmologists in Saudi Arabia towards genomic medicine and genetic testing, in light of the growing significance of genomics in ophthalmology and the national transition towards precision medicine. Methods: A cross-sectional, questionnaire-based survey was conducted among ophthalmologists, including consultants, specialists, fellows, and residents, across Saudi Arabia. The questionnaire included four domains: demographics, knowledge of genomic principles and gene therapy, self-rated confidence in genetic tasks (scored 1–10), and attitudes toward genetic testing. Data were analyzed using descriptive and inferential statistics, with subgroup comparisons performed using chi-square tests and t-tests/ANOVA. Results: A total of 115 ophthalmologists participated (46% male, 54% female; mean age 34 years; mean post-board experience 4 years). Most were consultants (40%) and practiced in Riyadh (52%). Knowledge was variable: 92% correctly identified human chromosome count, and 99% recognized autosomal recessive inheritance, but only 9% answered DNA base-pairing correctly, and 54% recognized mitochondrial inheritance. Confidence was highest for referral to specialists (mean 7.3/10) and lowest for test selection and counseling (4.7/10). The internet was the primary knowledge source among our sample (65%). The majority of individuals had positive attitudes towards genomic medicine: 90% believed testing was beneficial, 89% considered it enhanced health outcomes, and 89% indicated they would undergo testing themselves. On the other hand, 77% indicated difficulty in access, 91% strongly concurred on the significance of privacy and confidentiality, and more than half expressed concerns regarding misuse and bias. Conclusions: Ophthalmologists in Saudi Arabia acknowledge the importance of genetics. Yet, there are substantial gaps in knowledge and familiarity with genomic medicine and genetic testing. To overcome these challenges, it is essential to integrate genetics into ophthalmology curricula.

Background: Central sensitization (CS) has been held responsible for both persistent pain and high disease activity scores in Spondyloarthritis (SpA). The Central Sensitization Inventory (CSI) is a questionnaire used to determine CS frequency: a score of at least 40 is associated with a high likelihood of CS. Objectives: To investigate the prevalence of CS in our cohort and its association with clinical characteristics of patients and their quality of life. Methods: Adult patients with a diagnosis of Psoriatic Arthritis (PsA) or Axial Spondyloarthritis (AxSpA) who were also classifiable according to ClASsification criteria for Psoriatic Arthritis (CASPAR) and Assessment of SpondyloArthritis international Society (ASAS) criteria respectively, and regularly followed at the SpA outpatient clinic of our Unit were consecutively enrolled from April to November 2023. Their epidemiologic, clinical and clinimetric data were collected, as well as patient-reported outcome measures (PROMs) [CSI, Health Assessment Questionnaire (HAQ), FACIT-Fatigue (FACIT-F), SHORT-FORM 36 (SF-36), and Hospital Anxiety and Depression Scale (HADS)]. Considering the definition of “difficult-to-treat” rheumatoid arthritis, we defined as “multi-failure” those patients who were treated with more than two biologic disease-modifying anti-rheumatic drugs (bDMARDs) with different mechanisms of action. Intergroup comparisons were assessed by using Chi-square, t-test and ANOVA. p-values < 0.05 were considered significant. Results: A total of 100 patients were enrolled, 46 male (46.0%) and 54 female (54.0%), with a mean age of 59.4 ± 9.8 years and a mean disease duration of 14.8 ± 10.1 years; 79 patients (79%) had a diagnosis of PsA and 21 (21%) of AS. Forty-two patients (42.0%) had a CSI score ≥ 40. Significant correlations were found between a CSI score ≥ 40 and female sex (p = 0.004), the occurrence of enthesitis (p = 0.05), DAPSA-CRP (p = 0.02) and ASDAS scores (p = 0.03), a multi-failure condition (p = 0.01), fibromyalgia (FM) (p = 0.004), thyroid disease (p = 0.016) and obesity (p = 0.047). Regarding PROMs, significant correlations were found between CSI and values of HADS (both anxiety and depression), FACIT-F, HAQ and all the domains of SF-36 (p-value < 0.0001). Conclusions: Our data confirmed that more than 40% of SpA patients had CSI values ≥ 40 and underlined how CS could widely impair their disease burden. A routinary evaluation of CS and a multifactorial biopsychosocial perspective in the diagnosis and management of chronic pain in patients with SpA could help rheumatologists in improving their quality of care.

Personalized spine care is increasingly understood as more than the use of custom implants, robotics, navigation, or advanced imaging alone [...]

Background/Objectives: Stroke generates 157 million disability-adjusted life-years (DALYs) annually, making it the leading neurological cause of global disease burden. Artificial intelligence (AI) and machine learning (ML) have emerged as transformative technologies across the stroke care continuum. This narrative review maps the trajectory of AI in stroke medicine over the decade from 2015 to 2025. Methods: We conducted a narrative review with a structured, pre-specified search strategy across eight pre-specified thematic clusters using PubMed/MEDLINE (January 2015-December 2025), identifying 8549 records and including 1335 studies after screening. Inclusion criteria encompassed primary research articles, systematic reviews, meta-analyses, and RCTs reporting quantitative performance metrics or clinical outcome data for AI/ML in stroke. Results: Stroke imaging AI is the most commercially mature domain, with over 30 FDA-cleared tools. Automated ASPECTS scoring reduced radiologist reading time by 74.8% (AUC 84.97%; 95% CI: 83.1-86.8%). The only triage AI RCT demonstrated an 11.2 min reduction in door-to-groin time without significant improvement in 90-day functional independence (OR 1.3, 95% CI 0.42-4.0). Brain-computer interface rehabilitation showed significant upper limb recovery in a 17-center RCT (FMA-UE mean difference +3.35 points, 95% CI 1.05-5.65; p = 0.0045). AF detection AI is FDA-cleared and RCT-validated. LLMs and federated learning are pre-regulatory but growing exponentially. Conclusions: AI in stroke has achieved diagnostic maturity but therapeutic immaturity. Bridging algorithmic performance to patient outcomes, addressing equity gaps, and building the economic evidence base for scalable deployment are the defining challenges of the next decade.

Background: Parathyroid lipoadenoma, oncocytic parathyroid adenoma, and water-clear cell parathyroid adenoma (WCCA) are exceptionally rare subtypes of parathyroid adenoma, whose real clinical impact remains unclear. Methods: We performed a literature review and comparison of these uncommon subtypes of parathyroid adenoma, as these lesions may be associated with distinct clinical, pathological and radiological phenotypes. Results: The three groups were comparable in terms of age and gender, mainly affecting middle-aged women. As for the biochemical findings, although PTH level did not show statistically significant differences among the three adenomas, in the two-tail comparison between WCCAs and lipoadenomas, there was a trend towards higher PTH values (p = 0.058). However, serum calcium levels differed significantly, with higher levels in WCCAs than in lipoadenomas (12.1 vs. 11.3 mg/dL; p = 0.002). From a preoperative point of view, ultrasound positivity was significantly higher in WCCAs than in lipoadenomas and oncocytic adenomas (97% vs. 50% vs. 55.3%, p < 0.001), compared to scintigraphy positivity, which was comparable between subtypes and relatively suboptimal (66.7% vs. 64.3% vs. 61.3%; p = 0.825); WCCAs also had an overall more voluminous morphological phenotype. Conclusions: This review, although limited by its reliance primarily on case reports and small case series, confirms that lipoadenoma, oxyphilic adenoma, and WCCAs are rare but clinically relevant subtypes of parathyroid adenoma. These entities may be associated with atypical presentations of primary hyperparathyroidism (including difficult preoperative localization and clinicopathological features raising suspicion of malignancy) and should be recognized as a potential source of diagnostic difficulty. A better understanding of these rare subtypes may improve clinicopathological interpretation, increase awareness of potential diagnostic pitfalls and support a more personalized diagnostic and surgical approach in the future.

Transoral endoscopic therapies in gastro-esophageal reflux disease (GERD) are increasingly performed in patients who do not respond to medical therapy or are not suitable for or willing to undergo long-term PPI therapy or surgery. Currently available effective techniques include reconstruction of the gastro-esophageal valve by transoral incisionless fundoplication (TIF) and tightening of the gastro-esophageal junction through scarring, obtained by mucosal resection or ablation. TIF may be accomplished by an EsophyX 2.0/Z, MUSE, or GERD-X device. An iatrogenic stricture of the cardia may be obtained using a procedure called anti-reflux mucosectomy (ARMS), which includes several technical variants, or through mucosal ablation (ARMA). TIF using EsophyX 2.0 has strong evidence of efficacy in patients with small hiatal hernias, irrespective of hernia reducibility, who experience high-volume reflux episodes and troublesome regurgitation despite PPI therapy. MUSE can be performed only in the presence of a spontaneously reducing hiatal hernia and is probably more effective than EsophyX in maintaining the reduced hernia over time. However, MUSE is no longer available in Western countries. GERD-X shows promising results but needs further confirmation of its efficacy over the long term. ARMS and ARMA are not indicated in the presence of hiatal hernias but have shown promising results in the short term and are less expensive than TIF. Appropriate patient selection and the possibility of proposing a tailored approach to different types of patients and clinical/anatomical conditions result in favorable outcomes in most GERD patients, especially considering their quality of life and independence from PPIs. In the last several years, transoral endoscopic therapies have been proposed, along with concomitant laparoscopic repair for large hiatal hernias (cTIF), for GERD occurring after esophageal peroral endoscopic myotomy (E-POEM), in obese patients before or after bariatric surgery, and in patients with Barrett's esophagus.

Acute postoperative pain remains a major clinical challenge, affecting both recovery and resource utilisation. Beyond nociceptive input, pain is shaped by cognitive and emotional factors, including patient expectations. This narrative review examines the role of expectations in perioperative pain modulation, framed within predictive coding and Bayesian inference models. These models conceptualise pain as a probabilistic process that integrates sensory input with prior expectations, weighted by precision. In theory, positive expectations may enhance analgesic efficacy, whereas negative expectations may amplify pain via nocebo mechanisms. Control modifies expectations and may reduce perceived pain, while uncertainty diminishes these benefits. Evidence from observational studies links preoperative pain self-efficacy and anticipated pain scores to postoperative outcomes, yet interventional trials remain scarce. In this narrative review, we propose that expectation-sensitive strategies, including structured communication and computational modelling, may inform individualised anaesthesia and analgesia. Future research should validate these frameworks in clinical trials, optimise preoperative expectation management, and explore synergistic approaches that combine pharmacology with cognitive modulation. Understanding and leveraging expectations may offer a promising conceptual direction for more individualised perioperative care, although this approach remains hypothesis-generating at present.

Traditional one size fits all pharmacotherapy often yields suboptimal clinical outcomes, preventable adverse drug reactions (ADRs), and significant drug waste, imposing substantial economic and ecological burdens on healthcare systems. This review evaluates the transformative potential of pharmacogenomics (PGx) testing, particularly cytochrome P450 (CYP) gene variants, as a foundation for an ecosystem-centric accountability framework for green pharmacy and links human metabolic variability to specific environmental outcomes. Personalized CYP profiling is shown to minimize the environmental release of unused drugs and potentially ecotoxic metabolites into aquatic ecosystems, in contrast to standard uniform drug use approaches. The limitations of ethnicity-based dosing models, which rely on population genetic variation, are examined in the context of increasing global genetic admixture. It is argued that individual genetic profiling, conceptualized as a PGx-Green Passport, provides a reliable safety standard that accounts for individual differences, thereby enhancing efficiency and well-being in a globalized society. By integrating clinical data, including real-world evidence on hospital utilization, with sustainability frameworks, this review demonstrates that PGx-guided therapy is not only a tool for clinical efficiency but also a fundamental requirement for systematically achieving environmentally sustainable healthcare.

To better understand the complexity of biological systems, research has shifted from a reductionist to a holistic approach, expanding the focus from single genes to a genome-scale view of gene activity and regulation. This is known as transcriptomics, a continuously growing field generating gene expression signatures from different technologies. A comparable paradigm shift has occurred in computational systems biology with the implementation of Artificial Intelligence (AI) learning models for gene expression analysis and integration. These models enable transcriptome-based profiling to address challenges of data heterogeneity, integration, and updating, assisting human intelligence and enhancing their ability to retrieve, analyze, integrate, and generate data recursively, thanks to their intrinsic predictive, inferential, reinforcement, and generative capabilities. Additionally, while scientists worldwide are still learning how to leverage AI methods that can maintain the human-in-the-loop, a new fundamental change is emerging: agentic AI, which can autonomously act and employ other AI methods to pursue its objectives. As a futuristic perspective, the proposed data analysis pipeline imagines agentic AI systems allowing the automated retrieval and pre-processing of heterogeneous transcriptomics data, analysis and integration with other omics datasets, performed with an incremental updating and recurrent analysis (IURA) model that could allow the detection of guideline updates (e.g., disease reclassification) and the generation of new hypotheses, such as candidate biomarkers or transcriptome-phenotype correlations. Since personalized medicine could derive profound benefits from its use, this scenario also raises important considerations regarding the advantages and concerns associated with the use of scientific AI agents in research and clinical practice.

Background/Objectives: Clonal evolution is mainly defined based on the appearance or expansion of clones harboring specific somatic mutations and/or cytogenetic abnormalities, whereas few studies have investigated immunophenotypic heterogeneity assessed by flow cytometry and its relationship with disease progression. In this study, flow cytometry immunophenotyping of acute myeloid leukemia (AML) was carried out to identify phenotypic subclones based on antigen expression and to investigate clonal sweep. Methods: A total of 24 patients diagnosed with AML followed at the Hematology and Transplant Center of Salerno were included. Bone marrow or peripheral blood specimens were subjected to flow cytometry immunophenotyping and leukemic cell characterization. Phenotypic profiles were also compared to molecular alterations detected by next-generation sequencing. Results: We found that flow cytometry-defined clonal heterogeneity was more complex than molecular heterogeneity at diagnosis and disease relapse. Flow cytometry enabled the identification of small phenotypic subclones that were not detected by molecular profiling and that, in several cases, expanded over time, consistent with a phenotypic clonal sweep. The presence of small clones was associated with shorter progression-free survival and overall survival. Conclusions: Flow cytometric clonal heterogeneity, especially the presence of small clones (defined by antigen expression from 2 to 30%), may serve as an additional prognostic factor in AML. Immunophenotyping integrated with molecular data may improve risk stratification, enhance measurable residual disease assessment, and contribute to a more personalized disease monitoring strategy.