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Autophagy activation in granulosa cells as a mechanism of astaxanthin action: evidence from a pilot randomised trial in PMOS-associated infertility.

Astaxanthin (AST) has been reported to influence oxidative stress, endoplasmic reticulum stress, and apoptosis in women with polyendocrine metabolic ovarian syndrome (PMOS), formerly referred to as polycystic ovary syndrome (PCOS), but its effects on granulosa-cell (GC) autophagy remain unclear. Given the central role of autophagy in follicular development, this triple-blind, placebo-controlled pilot randomised trial evaluated whether AST modulates autophagy-related signalling in GCs and how these molecular effects relate to ovarian response. Fifty women with PMOS-related anovulatory infertility were enrolled between November 2023 and September 2024 and received AST (12 mg/day) or placebo for six weeks prior to oocyte retrieval; forty-four completed the study (21 AST, 23 placebo). Primary exploratory endpoints were molecular markers of adenosine monophosphate-activated protein kinase (AMPK)-autophagy signalling, and primary clinical outcomes included ovarian response indicators and cleavage stage embryo quality. AST supplementation increased autophagy-related gene 7 (ATG7) expression, enhanced autophagy flux, reduced apoptosis, and showed a trend toward increased AMPK activation. Before adjustment, AST improved oocyte maturity rate (OMR) and increased mature (metaphase II; MII) oocyte yield. After adjusting for age, body mass index, and anti-mullerian hormone level, total oocyte and MII oocyte yields remained significantly higher with AST, while OMR became non-significant. Among embryology outcomes, both the top-ranking embryo rate and the number of embryos suitable for cryopreservation were significantly higher with AST after adjustment. Pregnancy outcomes were numerically higher but not statistically significant. This pilot trial suggests that AST activates autophagy- and apoptosis-related pathways in GCs and may enhance oocyte competence and embryo quality in PMOS. Larger studies are needed to confirm these mechanistic and clinical effects.

Female

Expression profiles of miRNAs in ruminant intermediate hosts with cystic echinococcosis.

Cystic echinococcosis (CE), caused by the larval stage of Echinococcus granulosus sensu lato (s.l.), is a parasitic zoonotic disease recognized by the World Health Organization as a neglected tropical disease of significant public health concern. Despite ongoing control programs, CE remains endemic, underlining the need for integrated control strategies that involve new diagnostic and therapeutic tools. Recent investigations have spotlighted microRNAs (miRNAs) as key regulators in parasite development, immunomodulation, and as potential diagnostic and therapeutic targets. In the present research, a molecular study was conducted to investigate hydatid cyst samples (protoscoleces and germinal membranes) collected in southern Italy from different ruminant species (sheep, cattle, and water buffaloes), naturally infected with CE, with the ultimate goal of establishing a more comprehensive picture of miRNA expression patterns in these intermediate hosts. The bioinformatic analysis of hydatid cyst samples revealed 168 mature miRNAs. Among these, egr-miR-10-5p, egr-let-7-5p, and egr-miR-71-5p were the most abundant, with egr-miR-10-5p showing particularly high expression levels. No significant differences in miRNA abundance between host species were found. In contrast, when focusing on the comparison between protoscoleces and sterile germinal membranes, 24 miRNAs were found to be differentially expressed. Targeted qPCR of four selected miRNAs (egr-miR-71-5p, egr-let-7-5p, egr-miR-125-5p, and egr-miR-10-5p) showed clear overexpression in protoscoleces and in fertile germinal membranes compared with sterile ones. The differential miRNA expression patterns provide insight into the molecular mechanisms controlling the parasite's lifecycle and may guide the development of novel intervention methods to enhance CE control in endemic areas.

Animals

Digital healthcare solutions in preoperative care: A systematic review.

OBJECTIVE: Active participation in preoperative anesthesia preparation is crucial to ensure safe and efficient care. Compliance with preoperative instructions improves clinical outcomes, enhances patient satisfaction and optimizes use of healthcare resources. As digital communication becomes increasingly integrated into healthcare, interactive digital tools such as smartphone applications and Short Message Service (SMS) reminders may offer a valuable means of engaging patients in their own care. In this review, we evaluated the role of digital tools in guiding patients during their preoperative care pathway for anesthesia. METHODS: Following registration (CRD420250655119), we conducted a systematic review of studies evaluating the use of smartphone applications or SMS reminders designed to support preoperative preparation for anesthesia or procedural sedation in adult patients undergoing elective procedures. The primary outcome was compliance with preoperative instructions. Secondary outcomes included rate of late cancellations, patient satisfaction and cost-effectiveness. Studies were eligible if they reported at least one of these outcomes. RESULTS: Ten studies (1 RCT and 9 observational studies), including 11501 participants, were identified. Compliance with preoperative instructions was assessed in 8 studies, most of which reported higher compliance in patients receiving digital interventions across multiple instruction domains, although statistical significance was not consistently observed. Evidence suggested a beneficial effect on reducing late cancellations and improving patient satisfaction. However, results varied across study designs, and data on cost-effectiveness were limited. CONCLUSIONS: Digital tools for preoperative anesthesia guidance were associated with higher compliance and showed potential reduction of late cancellations and increase of patient satisfaction. However, the current evidence is predominantly observational and heterogeneous, limiting the strength of conclusions. PRACTICAL IMPLICATIONS: With healthcare systems under pressure, digital technologies may offer a scalable and patient-centered care solution to support preoperative anesthesia preparation. Nonetheless, further high-quality research is needed to evaluate their long-term clinical, economic and equity implications.

Humans

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan® for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans

Exploratory proteomic and metabolomic profiling of pleural effusions identifies histone H4 and alanine as promising complementary markers for pleural tuberculosis.

The diagnosis of pleural tuberculosis (Pl-TB) remains challenging. Histopathological analysis and pathogen detection in pleural biopsies are informative but limited. We investigated differentially expressed proteins and metabolites in pleural effusions from patients with Pl-TB, malignancies, and other pathologies. A proteomic analysis of pooled pleural effusions identified 45 proteins exclusively detected or upregulated in Pl-TB samples, many linked to infectious processes. Conversely, 18 proteins were uniquely found or upregulated in malignant pleural effusions, mainly associated with detoxification and hemostasis. To validate these findings, we employed targeted proteomics in individual samples. Eight proteins were validated: S100-A9, histone H4, insulin-like growth factor-binding protein 2, fibrinogen beta chain, ficolin-3, immunoglobulin heavy constant alpha 1, sulfhydryl oxidase 1, and histidine-rich glycoprotein. Additionally, NMR-based metabolomics identified 13 metabolites with differential abundance between Pl-TB and non-TB samples. Notably, N-acetyl-glycoprotein and the branched-chain amino acids, alanine and lysine differed between groups. Proteomic and metabolomic analyses revealed distinct molecular profiles between Pl-TB and non-TB patients, despite intra-group variability. To address this, we applied classification models. Histone H4 and alanine consistently emerged as discriminative features. Overall, this study provides novel insights into the molecular landscape of Pl-TB. The combined quantification of proteins and metabolites may improve differential diagnosis, although should be further validated in larger, independent cohorts before clinical application.

Humans

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products

Copper-Containing Surface Engineering for Soft-Tissue Biomedical Devices: Structure-Function Relationships and Ion Release-Driven Biological Performance, A Systematic Review.

Copper and copper-based materials have gained increasing attention for the functional modification of implantable medical devices intended for prolonged soft-tissue contact, including vascular stents, catheters, and intrauterine devices. Owing to their broad-spectrum antimicrobial activity, redox reactivity, and involvement in angiogenesis and cellular signaling, copper-based systems offer significant potential for multifunctional surface engineering. However, achieving a balance between antibacterial efficacy, corrosion behavior, controlled ion release, and cytocompatibility remains a critical challenge. This PRISMA-compliant systematic review analyzes copper-containing materials and surface modification strategies for soft-tissue biomedical applications. A structured search of Scopus, Web of Science, and PubMed (2015-2025) identified 65 eligible studies. The review encompasses bulk copper-containing alloys, electrochemical and chemical surface modification techniques, physical vapor deposition approaches, and advanced hybrid systems integrating copper with polymers, hydrogels, or metal-phenolic networks. Across the reviewed literature, antibacterial performance was strongly dependent on copper concentration, microstructural distribution, and spatiotemporal ion release profiles. Moderate, well-controlled copper incorporation frequently improved antibacterial efficacy while maintaining acceptable hemocompatibility and cytocompatibility, particularly in vascular and blood-contacting devices. In contrast, excessive copper loading often accelerated corrosion and induced adverse cellular responses. Emerging multifunctional architectures demonstrated improved regulation of biological interactions, enabling simultaneous antibacterial, antithrombotic, and proendothelial effects. Overall, copper-based surface technologies represent a versatile platform for soft-tissue implant modification. Future translational progress will require precise control of copper release kinetics and comprehensive long-term in vivo validation to ensure safety and sustained therapeutic performance. From the authors' perspective, the most promising future direction involves multifunctional copper-based hybrid coatings capable of dynamically regulating ion release, host tissue integration, and antibacterial performance simultaneously. Strategies integrating hierarchical architectures, stimulus-responsive release systems, and clinically scalable fabrication methods are expected to play a key role in translating copper-containing surfaces from experimental concepts toward commercially viable soft-tissue biomedical devices.

Copper

METTL14-mediated m6A modification of CCNE1 accelerates progression of myelodysplastic syndromes via MAPK-ERK and PI3K-AKT signaling pathways.

BACKGROUND: N6-methyladenosine (m6A) is the most common RNA modification and plays a key role in the initiation, progression, and relapse of multiple cancers, including hematologic malignancies. However, the role of m6A and m6A regulatory genes in myelodysplastic syndromes (MDS) remains unclear. This study aims to elucidate the function and molecular mechanism of methyltransferase METTL14 in MDS. METHODS: RT-qPCR was used to assess the expression of multiple m6A regulators, focusing on METTL14 in MDS patients and cell lines. METTL14 overexpressing and knockdown cell lines were established, and CCK-8, EdU, and flow cytometry assays were performed to explore the biological functions of METTL14.Dot blot, MeRIP-Seq, MeRIP-qPCR, RT-qPCR, and Western blot were employed to investigate the underlying molecular mechanism. RESULTS: Dysregulation of multiple m6A regulators was observed in MDS, among which METTL14 was upregulated. Elevated METTL14 expression increases MDS risk and adverse prognosis, emerging as a biomarker for poor prognosis. METTL14 promoted proliferation and cell-cycle progression of MDS cells while inhibiting apoptosis; corresponding changes were observed in cell cycle and apoptosis markers. METTL14 regulated cellular m6A levels. Downstream targets of METTL14 were enriched in cell cycle-related pathways, with CCNE1 identified as a critical target. Knockdown of METTL14, actinomycin D, or S-adenosylhomocysteine treatment reduced CCNE1 mRNA and protein levels. Furthermore, METTL14 activated MAPK-ERK and PI3K-AKT signaling via CCNE1 in an m6A-dependent manner, thereby promoting proliferative MDS cells' capacity. CONCLUSIONS: This study delineates a METTL14/m6A/CCNE1 signaling axis in MDS progression and suggests that METTL14-mediated m6A modification may be a potential therapeutic target for MDS.

Humans

Opposing kinase signaling may underlie the inverse relationship between cancer and Alzheimer's disease.

Cancer and Alzheimer's disease (AD) are leading causes of mortality and exhibit an inverse relationship, where AD patients have reduced cancer risk and vice versa. However, the molecular basis of this relationship remains poorly understood. We reanalyzed published proteomic and phosphoproteomic datasets to investigate this relationship. Differentially abundant proteins were identified in lung adenocarcinoma and glioblastoma samples relative to controls and compared with proteins altered in AD brains, revealing 37 proteins with opposing abundance patterns. Protein-protein interaction and pathway analyses revealed enrichment in kinase signaling and phosphorylation pathways. Phosphoproteomic analysis identified 52 differentially phosphorylated sites with opposing patterns, while kinase-substrate enrichment analysis identified 44 kinases with opposing inferred activity profiles. Integration of kinase activity and phosphosite data identified 29 kinase-phosphosite pairs, including 4 prioritized pairs with opposing patterns relevant to both diseases. Across seven independent cancer cohorts, 17 of 20 statistically significant phosphosite-cohort comparisons (85%) were concordant with the discovery findings, supporting reproducibility of the prioritized phosphosites. Together, these findings highlight opposing kinase signaling as a prominent feature of the inverse relationship and suggest potential biomarkers and therapeutic targets. This study provides a novel systems-level framework for investigating inverse relationships, supported by an R Shiny application for data exploration (https://advscancer.shinyapps.io/advscancer/). SIGNIFICANCE: This study presents an integrated proteomic and phosphoproteomic framework for investigating the inverse relationship between cancer and Alzheimer's disease (AD). By integrating differential protein abundance, phosphosite phosphorylation, inferred kinase activity, and curated kinase-substrate relationships, we identified opposing signaling patterns and prioritized four kinase-phosphosite pairs. Independent evaluation across seven CPTAC cancer cohorts supported the reproducibility of the prioritized phosphosite patterns. These findings provide insight into molecular processes potentially associated with the inverse relationship between cancer and AD, identify candidate biomarkers and therapeutic targets, and demonstrate the value of systems-level, data-driven approaches for investigating shared and opposing disease processes.

Humans

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n = 24) and direct mediator (n = 22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD = 1.49, 95% CI [0.55,2.43], p = 0.002) and skills (SMD = 0.66, 95% CI [0.02,1.31], p = 0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

Humans

Searching for New Genes That Cause Usher Syndrome.

PURPOSE: The purpose of this project was to identify novel Usher syndrome (USH) candidate genes from phenotyping data of 9139 knockout (KO) mouse lines. METHODS: We evaluated phenotype data for concurrent retinopathy and hearing abnormalities in single-gene KO mice generated by the International Mouse Phenotyping Consortium (IMPC). A search was performed to determine whether each gene had been previously associated with retinopathy and/or deafness in humans. Bioinformatic tools were used to predict protein interactions, molecular functions, signaling pathways, and the expression of human orthologues of candidate genes in the retina and inner ear. RESULTS: We identified 18 single-gene KO lines exhibiting hearing abnormality and retinopathy after ear and eye examinations, respectively, and/or by histopathology. The molecular functions and signaling pathways of the human orthologues of the 18 candidate genes partially overlapped with those of USH genes. Particularly, FER and DYRK1B proteins were predicted to interact with proteins encoded by known ciliopathy genes. ADIPOR1, ATP8B1, and MPDZ were associated with retinal degeneration in humans. CHSY1 and IDUA may be pathogenic causes of hearing impairment in people. Furthermore, CHSY1, CSTB, and SPRED1 were located adjacent to unsolved genetic loci related to USH. CONCLUSIONS: A screen of 9139 KO mouse lines revealed 18 candidate genes exhibiting both retinal and inner ear abnormalities consistent with the principal clinical features associated with USH. As the observed phenotypes are attributed to gene deletion in mice, these genes warrant further study to determine the causation of retinal degeneration and hearing loss in patients.

Animals

Origins and timing of somatic variants in the brain.

Somatic variants accumulate in human brain cells throughout the lifespan. Variant allele fraction has traditionally been used as a proxy for both the developmental timing of somatic variants and their functional effect, based on the assumption that earlier mutations are shared by larger cell populations and therefore have greater potential for severe phenotypes. However, recent discoveries challenge this simplified model. Variables such as developmental bottlenecks, lineage restriction, and cellular and molecular context play critical roles in shaping the distribution and functional impact of somatic variants in the brain. These insights support a shift toward a context-dependent framework for interpreting somatic mosaicism.

Humans

Nutrikinetics and bioavailability of Promunel®, a standardized poplar-type propolis phenolic extract: a double-blinded, placebo-controlled, cross-over, randomized trial.

Brown poplar-type propolis has been recognized and used for centuries to help prevent upper respiratory tract infections (URTIs). However, the scarce, incomplete information in humans on the nutrikinetics and bioavailability of its phenolic constituents, combined with a lack of standardization in its phenolic content and profile pose major challenges to develop bioactive ingredients. Thus, the aim of this study was to establish the nutrikinetics and total bioavailability (NKBA) parameters of brown poplar-type propolis phenolics in humans using the Standardized Propolis Extract (SPE) Promunel®. To achieve this, a 48 h NBKA study was conducted following a double blinded, randomized, placebo-controlled, cross-over design in healthy humans (n = 10) with two doses of SPE (1X = 400 mg or 4X = 1600 mg). Phenolic compounds were detected, identified and quantified in the extract, plasma and urine through different LC-MS/UV technologies. The SPE used is a rich (304.44 ± 15.61 µmol mg-1) and diverse source of phenolic compounds (5 sub-families). A total of 63 and 85 phenolic metabolites were identified and quantified in plasma and urine, mostly in the form of glucuronides and sulfates. In plasma, phenolic metabolites reached Cmax (1.22 ± 0.20 for 1X and 4.80 ± 0.48 µM for 4X) after 1 h of SPE intake, while urinary excretion occurred mostly during the first 3 h after. The total net bioavailability of SPE phenolic compounds at 48 h was 57.16 ± 5.71% for 1X and 43.82 ± 6.77% for 4X. Generally, the data between SPE 1X and 4X were proportional, indicating that a higher dose does not substantially modulate total net bioavailability. Overall, our data shows that brown poplar-type SPE phenolic compounds are highly bioavailable in the form of cinnamic acid and flavonoid conjugates, and that these compounds are rapidly absorbed and eliminated through the urine. Our results suggest that, for a sustained presence in circulation, brown poplar-type propolis supplements should be consumed more than once a day.

Humans

One Year After a Cyberattack: Lessons Learned and Dosimetric Analysis of Contingency Radiotherapy Plans.

PURPOSE: Cyberattacks on health care institutions pose significant risks to patient care, particularly in radiotherapy departments, which are heavily reliant on digital systems. This study examines the impact of a ransomware attack on our hospital and evaluates the effectiveness of the contingency measures implemented to resume radiotherapy treatments. METHODS AND MATERIALS: Following the cyberattack, our radiotherapy department faced a complete shutdown. After an initial estimate considering a shutdown of several weeks, a contingency plan was executed, including manual patient data retrieval and collaboration with a backup hospital. Contingency plans were prepared and delivered within hours, despite a partial lack of information. These plans allowed some patients to restart treatment 3 days after the attack. A dosimetric analysis was performed for the contingency plans, including various pathologies, mainly glioblastoma, head and neck cancers, and lung cancer. We compared the original and contingency plans in terms of dose coverage to the clinical target volume, biological effective dose, and their clinical impact as assessed at the 1‑year follow‑up after the cyberattack. RESULTS: Treatments resumed within 12 days at our hospital. Patients with glioblastoma showed good target coverage because of generous margins, resulting in favorable outcomes. In head and neck cases, the lack of detailed imaging led to significant target volume misses, suggesting that more conservative initial treatments could have been beneficial. Lung cases demonstrated accurate peripheral lesion targeting but faced challenges in central lesions because of the absence of positron emission tomography information. In most cases, the approach of using a contingency plan, even with limited information, led to a higher biological effective dose than would have been achieved if treatment had been stopped until full recovery at our hospital. CONCLUSIONS: The study highlights the critical importance of robust contingency planning in radiotherapy departments, emphasizing the need for backup systems and tailored approaches based on tumor location and available diagnostic information. These lessons emphasize that preparedness for digital disruptions should not focus exclusively on information and technology infrastructure.

Humans

Delphi study robot consenso: Strategies for the implementation of robotic surgery in general surgery in the Spanish hospital network.

INTRODUCTION: The implementation of robotic surgery in public hospitals presents multiple logistical, educational, and organizational challenges. In the absence of unified guidelines, a national consensus is required to optimize its safe and efficient adoption. This study aimed to establish a set of consensus-based and measurable recommendations for the implementation of robotic surgery programs in hospitals within the Spanish National Health System, based on the experience of centres with established robotic programs and intended to serve as guidance for hospitals that are initiating or planning their implementation. METHODS: A national Delphi study was conducted with the participation of robotic surgery experts from 26 public hospitals. The expert panel was composed exclusively of digestive surgeons with experience in robotic surgery. Three iterative rounds of expert panel evaluation were conducted between March 2024 and March 2025. The questions were grouped into five thematic blocks. Consensus was defined as an agreement level of ≥66.7%. Kendall's W coefficient was used to assess concordance. RESULTS: High levels of consensus were achieved on key aspects related to infrastructure, structured training, cost evaluation, and quality assurance mechanisms. Areas of disagreement were also identified, such as the need for a dedicated anaesthesiologist, purchase of accessory instruments during the initial phase, and official accreditation pathways. CONCLUSIONS: This study provides a guideline for developing a national robotic surgery strategy focused on patient safety, program sustainability, and standardized training of surgical teams. These recommendations can guide hospitals at different stages of robotic technology adoption. Given that the consensus was reached from an exclusively surgical perspective, the recommendations focus on patient safety, program sustainability, and standardized training of the surgical team, and should be interpreted in an adaptable manner according to each centre's context, case volume, and available resources.

Cirugía Asistida por Robot

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS]&#x2009;&#x2265;&#x2009;0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (&#x2265;&#x2009;0.3 to <&#x2009;0.84) and only 3.2% remained completely unclassifiable (CS&#x2009;<&#x2009;0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors

Retrograde intrarenal surgery with flexible and navigable suction access sheaths vs mini-percutaneous nephrolithotomy for large upper urinary tract stones: a&#xa0;systematic review and meta-analysis.

OBJECTIVE: To conduct a meta-analysis comparing the efficacy and perioperative outcomes of contemporary flexible and navigable suction access sheath-assisted retrograde intrarenal surgery (FANS-RIRS) against percutaneous nephrolithotomy (PCNL) for the management of large upper urinary tract stones, as despite technological advances in RIRS such as high-powered lasers and FANS that have substantially enhanced its performance, current guidelines continue to recommend&#x2009;PCNL as first-line treatment for renal stones >2cm. METHODS: MEDLINE, Embase, and the Cochrane Library were searched for studies performing direct comparisons of FANS-RIRS against PCNL in adult patients until September 2025. Primary outcomes included stone-free rates (SFRs) and need for ancillary procedures. Secondary outcomes included operative time, length of postoperative hospitalisation, and postoperative complications. RESULTS: A total of 10 studies (three randomised control trials, seven retrospective cohort studies) comprising 2347 patients were included; preoperative stone sizes were predominantly 2-3&#x2009;cm. All PCNL procedures in the studies included were performed as mini-PCNL. The SFRs for FANS-RIRS were comparable with mini-PCNL across all stone sizes (odds ratio [OR] 0.90, 95% confidence interval [CI] 0.70-1.17) and stones &#x2265;2&#x2009;cm (OR 0.80, 95% CI 0.60-1.08), with low heterogeneity. Ancillary procedures rates were similar (OR 1.22, 95% CI 0.61-2.44). FANS-RIRS was associated with significantly fewer overall complications, specifically smaller haemoglobin decline, need for transfusion, and shorter hospital stay. However, mini-PCNL demonstrated shorter operative times for stones &#x2265;2&#x2009;cm. Urosepsis rates were low and similar between both groups. Limitations include predominance of Asian studies, variability of practice, and inclusion of non-randomised studies. CONCLUSIONS: Contemporary FANS-RIRS achieves SFRs comparable to mini-PCNL even for 2-3&#x2009;cm stones, while offering superior safety profiles and shorter hospitalisation; this supports FANS-RIRS as a viable primary treatment in selected patients.

Humans