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.

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.

Cell-Free Massive Multiple-Input Multiple-Output (CF-MaMIMO) in Open Radio Access Network (O-RAN) promises high spectral efficiency but is limited by frequent Channel State Information (CSI) exchanges, which strain fronthaul/midhaul/backhaul (X-haul) bandwidth and exceed the capabilities of existing approaches relying on uncompressed CSI or heavy predictors. To overcome these constraints, we propose LITE, a lightweight pipeline combining a 1-D convolutional Autoencoder (AE) at the O-RAN Distributed Unit (O-DU) with a Squeeze-and-Excitation (SE)-enhanced Bidirectional Long Short-Term Memory (BiLSTM) predictor at the Near-Real-Time RAN Intelligent Controller (Near-RT-RIC), enabling short-horizon trajectory-unaware forecasting under strict transport and processing budgets. LITE applies 50% CSI compression and an asymmetric SE-BiLSTM, reducing model complexity by 83.39% while improving accuracy by 5% relative to a baseline BiLSTM. With compression-aware training, the Lightweight Intelligent Trajectory Estimator (LITE) incurs only 6% accuracy loss versus the BiLSTM baseline, outperforming independent and end-to-end strategies. A TensorRT-optimized implementation achieves 147k Queries per Second (QPS), a 4.6x throughput gain. These results demonstrate that LITE delivers X-haul-efficient, low-latency, and deployment-ready channel-gain prediction compatible with O-RAN splits.

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).

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.

We develop an asymptotic theory for strict minimum message length (SMML) estimators in regular parametric models with countable data spaces. We show that, asymptotically, the optimal SMML partition is induced by a weighted Fisher--Voronoi tessellation in parameter space, pulled back through the maximum likelihood estimator. We further show that each SMML codepoint is asymptotically a weighted average of the maximum likelihood estimates associated with observations in its cell. These results imply that the SMML estimator is consistent and converges at the usual parametric $n^{-1/2}$ rate under standard regularity conditions. We also give a Kullback--Leibler projection interpretation of SMML codepoints and a decomposition of the expected SMML codelength into an assertion entropy and an expected conditional cross-entropy. In exponential families, the theory simplifies further: SMML codepoints satisfy a moment-matching condition, and optimal SMML cells are induced by a polyhedral partition of the sufficient-statistic space.

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.

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

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.

To support the high data rates for latency-critical applications, future wireless systems will employ fully digital beamforming multiple-input multiple-output (MIMO) architectures at millimeter wave (mmWave) frequencies. Moreover, mmWave MIMO deployments will coexist with conventional sub-6 GHz MIMO systems, creating opportunities to exploit out-of-band sub-6 GHz information to enhance channel estimation at mmWave frequencies. In this work, we analyze the pilot-aided channel estimation performance of mmWave MIMO systems under various pilot configurations in both static and dynamic environments. We evaluate the system performance in terms of spectral efficiency (SE) for line-of-sight and non-line-of-sight propagation conditions. Simulation results show that incorporating out-of-band sub-6 GHz information yields notable SE gains in both static and dynamic scenarios.

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.

Clonal evolution of cancer results in intratumor heterogeneity, making treatment and cure challenging. Single-cell sequencing has advanced our understanding of intratumor heterogeneity, but tracing subclonal evolution using mutational profiles of cells is limited by scale and noise. Moreover, available tumor progression tree inference methods usually offer a single tree to explain the progression of a tumor, and do not inform about alternative evolutionary scenarios. We introduce the bi-partition function for a tumor progression tree, to assess the reliability of any proposed subclonal structure in a single-cell sequenced tumor. By using the bi-partition function, we calculate the probability that any given subset R of mutation-profiled single cells from a tumor forms a clade rooted by a specified mutation ρ across all possible tumor progression trees. This provides the means to evaluate whether R forms a subclone with ρ as a possible subclonal driver, which is especially useful if the cells of R are biologically or clinically significant, e.g., have aggressive growth, therapy resistance, or metastatic potential. We also introduce an algorithm to estimate the bi-partition function, which treats the ground truth as a probability distribution derived from mutational profiles of single cells and samples a tumor progression tree from this distribution independently in each iteration. We prove that our algorithm’s estimate of the bi-partition function asymptotically approaches the ground truth and demonstrate its accuracy on simulated data. Applying our algorithm to the tumor progression tree inferred from single-cell-derived melanoma sublines revealed that, while major clades and their root mutations are robust, (i) the placement of one clade in the tree is unreliable, which we later observed to be a result of Loss of Heterozygosity, and (ii) some of the mutations identified as false positives in the tree are unreliable, which later turned out to be the result of a doublet - a subline which has contamination from another subline. Interestingly, bootstrapping, a technique commonly employed for species trees, failed to point out any of these issues. After correcting the input data for these issues, the reliability of the progression tree improved substantially, demonstrating how our bi-partition function algorithm can aid studies on tumor evolution and intratumor heterogeneity. Farid Rashidi Mehrabadi, Erfan Sadeqi Azer, John D. Bridgers, Teresa M. Przytycka, Salem Malikic, Funda Ergun, Cenk Sahinalp. A bi-partition function algorithm to evaluate inferred subclonal structures in single-cell sequencing data [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 6897.