We investigate the asymptotic behavior of a proposed ordinary differential equation (ODE) model for Genetic Toggle switches from Gardner et. al. and I. Rajapakse and S. Smale: dxdt=a1+ym−x and dydt=b1+xn−y where a,b,m,n>0 and x(t),y(t)≥0. We also investigate the asymptotic behavior of the Euler discretization of this system: xn+1=a1xn+b11+ynm=f(xn,yn) and yn+1=a2yn+b21+xnn=g(xn,yn), where 1−h=a1, 1−k=a2, ah=b1 and bk=b2, a1,a2∈(0,1) and h,k>0 are steps of discretizations. Here, x and y represent protein concentrations at a particular time in both genes and a,b,m,n>0, respectively, above. We will apply the theory of competitive maps to find the basins of attractions of different equilibrium points and period-two solutions of systems of difference equations.

Background/Objectives: Totally endoscopic mitral valve repair reduces surgical trauma and accelerates recovery but can be technically challenging, particularly for precise annuloplasty suturing. The VirtuoSEW® (LSI Solutions, Victor, NY 14564m, USA) automated annular suturing system was developed to standardize and simplify suture placement. This study was an early evaluation of this technology’s safety, efficacy, and feasibility in totally endoscopic microInvasive mitral valve repair (µMVr). Methods: We conducted a retrospective observational study of 20 patients with severe mitral valve disease of various etiologies. All patients underwent mitral valve repair using the VirtuoSEW® system for automated placement of annuloplasty sutures, combined with leaflet resection or chordal management as appropriate. Postoperative outcomes were assessed at one month using echocardiography and clinical evaluation. Perioperative and postoperative complications and early mortality were systematically recorded. Results: VirtuoSEW®-assisted mitral valve repair was safe and effective, achieving complete elimination of severe mitral regurgitation in all patients (N = 20, 100%). Annuloplasty rings included Physio-ring (N = 12, 60%), Memo 3D (N = 4, 20%), and Memo 4D (N = 4, 20%), combined with leaflet repair techniques: leaflet plication (N = 5, 25%), neochordae implantation (N = 7, 35%), sliding plasty (N = 2, 10%), commissural repair (N = 1, 5%), and hemibutterfly repair (N = 1, 5%). Concomitant procedures included: tricuspid valve repair (N = 1, 5%) and atrial septal defect closure (N = 1, 5%). Mitral annulus diameter decreased from 42.0 ± 5.3 mm to 34.2 ± 2.2 mm (p = 0.001). Mean total surgery, cardiopulmonary bypass, and aortic cross-clamp times were 170.3 ± 21.3, 143.4 ± 21.5, and 80.4 ± 7.9 min, respectively. ICU stay was 1.0 ± 0.2 days, with a hospital stay of 8.0 ± 1.9 days. No perioperative complications—including bleeding (N = 0, 0%), stroke (N = 0, 0%), infections (N = 0, 0%), or 30-day mortality (N = 0, 0%)—occurred. Conclusions: µMVR invasive mitral valve repair using the VirtuoSEW® system is safe, effective, and reproducible, as well as compatible with almost all repair techniques, providing complete restoration of valve competence with no early device-related complications. To our knowledge, this is the first clinical study reporting outcomes with this device, supporting its potential to streamline mitral repair and improve procedural efficiency.

The Tortonese’s stingray (Dasyatis tortonesei Capapé, 1975) is a poorly understood species, likely endemic to the Mediterranean Sea, where its distribution remains inadequately delineated due to historical taxonomic uncertainty and misidentification with its closely related congeners. The present study reports the first well-documented records of D. tortonesei in the Adriatic Sea, based on six specimens collected during systematic field surveys off Vlorë, Albania. All specimens were identified through a comprehensive assessment of diagnostic morphological features, and detailed biometric data are provided. Notably, one individual exhibited a fully healed traumatic loss of both the tail and stinging apparatus, suggesting a degree of resilience to sub-lethal injury. The present findings extend the range of D. tortonesei and establish a valuable baseline for future biodiversity assessments. In addition, this paper underscores the urgent need for integrative taxonomic approaches and regional capacity-building to improve species-level identification and inform effective conservation of Mediterranean elasmobranchs (sharks and rays).

Precision surgical interventions rely on accurate integration of preoperative and intraoperative imaging to guide clinical decision-making and improve patient outcomes. Traditionally, most 3D imaging modalities capture the entirety of the target object, allowing for the segmentation of its entire volume. However, some medical imaging devices trade full field-of-view for other considerations, such as size and ability to access the target organ in unique ways. This is particularly true of ultrasound, where imaging deeper organs from outside the body is not viable due to attenuation, thus motivating the need for alternative imaging strategies. In scenarios such as image-guided intervention, it is often necessary to put this partial view of the object in its full anatomical context, such as alignment to a pre-operative MRI. We propose a method for jointly segmenting the portion of the object visible in the acquired image and estimating its full shape. We do this by combining a pre-trained shape prior with a patient-specific expectation of organ shape acquired via pre-operative imaging. In a simulated dataset for prostate MRI/US fusion, we show the ability to accurately estimate the prostate shape from ultrasound images capturing only a fraction of its total volume.

This study aimed to describe and compare background factors and symptoms at diagnosis of patients with non-advanced or advanced stage lung cancer and patients without cancer, and to develop predictive models identifying key variables that contribute to the detection of early and late-stage lung cancer. Univariate logistic regression and three machine learning algorithms were used. Compared to patients without cancer, six background factors and two symptoms differed in non-advanced lung cancer, while 11 background factors and 19 symptoms differed in advanced cases. The machine learning models showed moderate performance in classifying patients with lung cancer from those without cancer. Notably, top predictors extended beyond classic respiratory symptoms. Demographic and lifestyle factors, particularly age, smoking status, and living situation, remained essential alongside symptoms such as pain, appetite loss, weight reduction, and respiratory problems. These findings support integrating clinical, demographic, and patient-reported symptoms to improve lung cancer risk models and refine referral decisions in screening pathways. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-026-46710-8.

Noise-induced hearing loss (NIHL) occurs as a result of long term exposure to workplace noise. The aim of the study was to identify job positions with an increased risk of hearing impairment due to occupational noise exposure, by analyzing changes in audiometric findings over a six-month period of work under conditions with elevated noise levels. The study included participants exposed to workplace noise and participants working in a quiet environment, employed in the same companies but in different job positions. Audiometric examinations were conducted at baseline and after six months of follow-up. Paired and independent-samples t-tests were applied. A statistically significant difference in hearing loss was found among participants exposed to occupational noise during the six-month period (t = 4.84, df = 35, p < 0.001), while no significant difference was observed among participants working in a quiet environment (t = 1.64, df = 35, p = 0.109). A significant difference was also identified between the noise-exposed group and the control group in mean hearing threshold values at baseline and at the final assessment after six months (t = 4.13, df = 71, p < 0.001). Occupations with an increased risk of the development and progression of hearing impairment were identified. The results confirmed the need for continuous monitoring and implementation of preventive hearing protection measures in high-risk workplaces, including oil refineries, textile and metal industries, the wood-processing sector, and selected service industries.

The fruit of Rosa canina (rosehip) has long been used in traditional medicine, and recent studies confirm its health benefits due to its content of flavonoids, carotenoids, fatty acids, and high vitamin C levels. This study examined three preparations: infusion, ultrasound-assisted extract, and traditional jam. Total phenols were measured using the Folin-Ciocalteu method, and antioxidant activity by the DPPH method. The highest total phenolic content was observed in the infusion of dried fruit (163.477 mg GAE/l), followed by the fruit extract (44.932 mg GAE/l), with the jam extract showing the lowest content (23.477 mg GAE/l). Antioxidant activity was assessed via DPPH inhibition percentage and IC50 values to identify the most effective form of compounds. The findings suggest that infusion of dried rosehip fruit provides the highest antioxidative capacity, highlighting its potential as a functional food ingredient.

Strict minimum message length (SMML) is an information-theoretic coding principle that represents a continuous statistical model by a finite set of assertions and a partition of the sample space. We show that the SMML objective decomposes into assertion entropy and conditional cross-entropy, balancing the cost of identifying an assertion against the cost of encoding data under the assigned model. For any fixed partition, the optimal codepoint for each cell is the model distribution that minimises Kullback–Leibler (KL) divergence from the data distribution restricted to that cell. Using the local Fisher–Rao geometry of regular parametric models, we show that, under a high-resolution LAN-scale regime, SMML partitions are asymptotically the pullback, through the maximum-likelihood estimator, of weighted Fisher–Rao Voronoi tessellations in parameter space, with assertion probabilities appearing as additive weights. For regular canonical exponential families, SMML codepoints satisfy a moment-matching condition and admit an interpretation as KL/Bregman centroids, while exact SMML cells are pullbacks of convex polyhedra in sufficient-statistic space. Together, these results show that SMML induces a natural information-geometric quantisation linking entropy-based coding, KL projection, and divergence-based Voronoi geometry.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, driven by profound molecular heterogeneity and resistance to current therapy. To support systematic target identification, we established a proteomics-anchored knowledge discovery framework integrating cross-model proteomics harmonization, network topology, high-confidence structural modeling, and large-scale in silico docking. From 1,975 proteins consistently detected across murine and human PDAC models, 32 immunohistochemically confirmed candidates were prioritized for structure-based screening against 7,509 clinically characterized compounds. Blind docking, refined pose sampling, ligand-efficiency scoring, and ADME filtering identified EIF2A, STAM, ANXA2, and AHNAK2 as robustly druggable targets. These proteins exhibited high-affinity interactions with zavegepant (a clinically approved CGRP receptor antagonist), omilancor, bemcentinib, conivaptan, and APTO-253. Docking validation (RMSD 1.98 to 2.56 Å) confirmed methodological reliability, and network analyses placed the 4 proteins within modules linked to endosomal/membrane trafficking and invasive phenotypes. Survival analyses in 176 PDAC patients further supported their clinical relevance. Thus, we suggest a systems-level platform for nominating ligandable PDAC targets and clinically actionable compounds. The framework highlights opportunities for rational drug repurposing and motivates future mechanistic studies at the intersection of proteomics and structure-based screening for targets to PDAC.

Urbanization of cities demands efficient spatial management. The construction of utility lines significantly alters the spatial landscape. The subsurface space is often neglected, resulting in outdated or absent records of underground utility infrastructure. This clearly underscores the need and importance of maintaining accurate utility records. Modern non-destructive techniques for underground utility detection, such as ground penetrating radar (GPR), can enhance the documentation and mapping of subsurface infrastructure. The subject of this paper is the optimization of GPR survey and processing workflows to improve the accuracy of underground utility detection when using the Leica DS2000. The research comprises both theoretical and experimental analyses, including the application of various GPR data collection methods on test sites. The experimental component of the research was conducted using the Leica DS2000 GPR system. The geospatial data were processed using several software applications, including uNext Advanced, IQMaps, and Geolitix. Based on the multicriteria analysis of these results and an assessment of detection accuracy, an optimal workflow (decision diagram) was defined for the detection of underground utility infrastructure using Leica DS2000 under favorable soil conditions. This study explored the feasibility of efficiently updating the cadastral database of public utility infrastructure through non-invasive technologies, thereby contributing to the improvement of subsurface utility infrastructure management.

In this study, we analyze a discrete two-dimensional host–parasitoid model in which the host population follows logistic growth and is additionally subject to a strong Allee effect on the proportion of hosts that avoid parasitism. The parasitoid population dynamics are driven by host availability, attack success rate, and the number of parasitoids produced per successful attack. We classify the equilibrium points and explore the system’s local and global dynamics. Our analysis shows that, in certain parameter regions, an extinction equilibrium can be globally stable. For the boundary equilibrium, we prove the existence of transcritical and period-doubling bifurcations. Regarding interior equilibria, when multiple equilibria exist, their stabilities alternate. We prove the occurrence of codimension-1 period-doubling and Neimark–Sacker bifurcations, indicating the emergence of complex dynamics, including quasi-periodic and even chaotic behavior. Despite the possibility of complex dynamics, we prove that the system can exhibit uniform persistence and permanence under specific conditions, thereby ensuring the long-term coexistence of the host and parasitoid populations.

The phenomenon of digital obituaries and posthumous identities is increasingly shaping the way contemporary society perceives death, remembrance, and the grieving process. Death no longer signifies the complete end of social presence, as digital profiles of the deceased remain active on social media platforms even after physical death, enabling a continuity of symbolic connection with them. This paper explores the emotional, psychological, social, ethical, and legal dimensions of digital memorialization, focusing on the impact of virtual spaces and algorithmic reminders on the grieving process and emotional resolution. A qualitative approach was employed in analyzing secondary sources, grounded in contemporary theories of identity, grief, and digital legacy. The paradoxes of digital mourning are analyzed, wherein memorial profiles and digital obituaries may offer a sense of presence and support, yet simultaneously prolong emotional attachment and hinder acceptance of loss. The paper also examines how the algorithmic functioning of digital platforms generates memories and reminders without sensitivity to the emotional state of users, potentially burdening the grieving process further. It raises critical ethical and legal questions surrounding the management of digital identities after death, including unclear ownership, control, and rights to content removal. The complexity of survivors’ emotional responses and the growing significance of digital legacy further reinforce the need for clear regulations aligned with the psychological dimensions of grief and ethical principles of dignity. In this context, digital memorialization emerges not only as a form of remembrance, but also as a challenge requiring thoughtful consideration within the frameworks of mental health, social practice, and legal accountability.

This text is a review of the book: Nidžara Ahmetašević, Media as a Tool of International Intervention: House of Cards, Routledge, London and New York, 2024

Multi-sample bulk DNA sequencing enables reconstruction of a tumor’s clonal history, but scalable methods often rely on heuristic search and provide no optimality guarantees. We present CITUP2, an integrative combinatorial optimization framework that reconstructs clonal trees from descendant cell fractions (DCFs) of mutational clusters. CITUP2 formulates tree inference as a mixed-integer quadratic program (MIQP) that jointly determines the tree topology and clone prevalences across samples. It minimizes a weighted discrepancy between observed and inferred DCFs, with options to prioritize trees exhibiting consistency in the presence-absence patterns of parent-child clones. Under this formulation, CITUP2 returns provably optimal solutions (with respect to the model) and avoids the combinatorial explosion of exhaustive topology enumeration used by existing methods with optimality guarantees. In addition, CITUP2 can report a user-specified number of best trees. In simulations and analyses of a large, recently published multi-sample TRACERx cohort, CITUP2 scales to trees with tens of clones (approximately 30) and matches or improves on the fit attained by state-of-the-art approaches, while providing clear optimality certificates. Salem Malikic, Hamza Iseric, Chih Hao Wu, Erin Molloy, S. Cenk Sahinalp. Reconstruction of Tumor Clonal Trees with Multi-Sample Bulk Sequencing Data by Integrative Combinatorial Optimization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6905.

Tumor evolution is driven by various mutational processes, ranging from single nucleotide variants (SNVs) to large structural variants (SVs) to dynamic shifts in DNA methylation. Current short-read sequencing methods struggle to accurately capture the full spectrum of these genomic and epigenomic alterations, as well as their relations, due to inherent technical limitations. Here we used Nanopore long-read sequencing to profile 23 subclones, each derived from a single cell of a mouse melanoma cell line, for precise detection and evolutionary ordering of SNVs, SVs, copy number alterations (CNAs), and DNA methylation changes at subclonal level. Through phylogenetic analysis of these subclones, we reconstruct the timing of mutational processes and their contributions to diverse clonal phenotypes. The analysis reveals recurrent amplifications of putative driver genes, generated by independent SVs across different lineages, suggesting parallel evolution. Additionally, we described lineage-specific methylation changes associated with aggressive tumor subclones, highlighting epigenetic trajectories linked to tumor progression. Overall, we demonstrate that our long-read approach enables a uniquely comprehensive view of melanoma progression, highlighting that SVs and methylation played an important role in initiation, clonal diversification, and development of therapeutic resistance in this tumor, in consistence with recent clinical findings. We will release the sequencing data and curated variant calls to encourage developments of new computational methods. Chi-Ping Day, Yuelin Liu, Anton Goretsky, Ayse Keskus, Salem Malikic, Eva Perez-Guijarro, Glenn Merlino, Eytan Ruppin, Suleyman Cenk Sahinalp, Mikhail Kolmogorov. Full-range genomic analysis at single-cell resolution reveals genetic, epigenetic, and parallel evolution of melanoma subclones [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 704.