Understanding and comparing tumor evolutionary histories is fundamental to cancer genomics, with direct implications for tracking subclonal population dynamics, treatment resistance, and tumor heterogeneity. Clonal trees, widely used to model tumor progression, are rooted, unordered trees in which each node represents a subclone labeled by a set of distinct mutations. Various principled and efficient methods have been developed for inferring clonal trees from either bulk or single-cell sequencing data. However, no existing computational approach offers a method that is both efficient and principled to fully align clonal trees and to compare their subclonal architectures, which limits the robustness of any downstream analysis based on inferred clonal trees. We introduce omlta, the optimal multi-label tree alignment of two clonal trees, which removes the minimum number of mutation labels, so that the remaining trees are isomorphic. Computing omlta is NP-hard. Here, we present a fixed-parameter tractable algorithm to compute the omlta, with a running time of O(L^3 log L 2^k) where L is the number of mutation labels shared between the input trees and k is the minimum possible number of mutation labels that need to be removed for the alignment - which we call omltd, the optimal multi-label tree edit distance. Our approach provides an exponentially better (in k) asymptotic runtime than the state-of-the-art algorithm by Akutsu et al. for computing the classic tree alignment and edit distance, concepts similar to what omlta/omltd optimizes on clonal trees. We applied omlta to 126 multi-sample bulk-sequencing data from the TRACERx study on non-small cell lung cancers by comparing clonal trees inferred by CONIPHER and PairTree. Despite the theoretically exponential runtime, we could compute the tree alignment for each tumor quickly, often within seconds. The omltd between CONIPHER and PairTree clonal trees on the same tumor varies substantially across tumors and the distances are negatively associated with the mean cancer cell fraction among mutations. For the tumors characterized by mutations with low cancer cell fractions, it is thus advisable not to use a single tree, but rather the alignment of multiple alternative trees, so that downstream inferences are informed only by robustly placed mutations. We further evaluated our algorithm on an in-house melanoma sample with clonal trees inferred by PhISCS and ScisTree, highlighting the utility of omlta on trees inferred from single-cell sequencing data. On these datasets, our algorithm completed all analyses in practical wall-clock times and showed that it can identify common evolutionary trajectories among clonal trees representing (i) distinct tumors, (ii) distinct samples from the same tumor, (iii) distinct sequencing data from the same sample. Additional supplementary results demonstrate the robustness of our approach in comparison to alternatives on simulated data. Jacob Gilbert, Chih Hao Wu, Marina Knittel, Alejandro Schaffer, Salem Malikić, S. Cenk Sahinalp. Identifying robust subclonal structures through tumor progression tree alignment [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 6898.

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.

Copy number alterations (CNA) is a phenomenon during cancer evolution where some regions of the genome may be amplified or deleted. This results in heterogeneous collections of cancer cells. Profiling and classification of CNA profiles play a vital role in understanding the cancer heterogeneity and evolution to better inform diagnosis and treatment. There are several short-reads haplotype-specific CNA profiling tools but short reads provide a limited phasing range. Long-reads facilitate the direct phasing of genomic variants into megabase-scale haplotypes, which supports the reconstruction of longer, up to chromosome-scale, CNA profiles. Here we present Wakhan, a tool to analyze haplotype-specific chromosome-scale somatic copy number aberrations using long reads. Leveraging high-quality genome assembly coverage profiles, we show that Wakhan significantly outperforms other common short- and long-read CNA callers in achieving chromosome-level CNA consistency. Wakhan uses tumor-normal long-read BAMs and phased germline SNP calls as input. It first extends the input phasing to be chromosome-scale by exploiting haplotype coverage imbalance. Wakhan detects those phase switch regions and corrects them by taking into consideration the changes in haplotype-specific coverage. Next, Severus utilizes this enhanced phasing to generate phased structural variant (SV) calls. Finally, Wakhan's integrated CNA algorithm uses the SV calls as boundaries and employs a haplotype coverage model to assign integer copy-number states to the resultant CNA regions. https://github.com/KolmogorovLab/Wakhan We sought to compare Wakhan's performance against several state-of-the-art haplotype-specific CNA calling tools. The tools selected for short-read analysis included: Purple, Hatchet, Battenberg and for long-read analysis Purple and Savana are included. As benchmarks for small variants and SV calling are available but no similar benchmarks for somatic CNA calls are available. We designed a CASTLE panel based CNA calling benchmark, consisting of 6 pairs of tumor/normal cell lines sequenced with multiple short- and long-read sequencing technologies. We define segment error (SE) as for each CNA segment, we calculate the haplotype-specific mean squared distance between expected and reference coverage at heterozygous SNPs. This is then used to compute a weighted chromosomal average, normalized by the tumor haplotype's mean coverage. Similarly, for chromosome error (CE), compare the phase of the whole chromosome against the reference coverage. In the five CASTLE datasets, Wakhan and PURPLE had the lowest SE50 and SE75, indicating high accuracy in reconstructing individual CNA segments. We also evaluated Wakhan on a tumor-only dataset. Both Wakhan and PURPLE handled the absence of normal samples well and accurately reflected the expected tumor/normal profiles. Tanveer Ahmad, Ayse Keskus, Mikhail Kolmogorov, Sergey Aganezov, Michael C. Dean, Midhat S. Farooqi, S. Cenk Sahinalp, Benedict Paten, Karen H. Miga, Salem Malikić, Yuelin Liu, Byunggil Yoo, Ataberk Ataberk Donmez, Anton Goretsky. Wakhan: Reconstruction of chromosome-scale copy number profiles of tumor genomes with long-read sequencing [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 6900.

Dynamic changes in lipid membrane composition are a common response to stress, often involving shifts in key lipid molecules. Phosphatidic acid (PA), a central precursor in lipid biosynthesis, accumulates when anionic phospholipid synthesis is blocked—lipids that are typically primary targets of membrane-active antimicrobial peptides (AMPs). This raises the question of how cationic AMPs adapt to such lipid remodeling, which is especially relevant given their promise as novel therapeutics against escalating antimicrobial resistance. Their killing mechanism is often unclear. To identify ongoing processes clearly linked to bacterial cell death, six assays targeting membrane integrity and cell viability were performed alongside bactericidal measurements. These assays were conducted on Escherichia coli and a mutant depleted of anionic phospholipids, treated with the cationic peptides melittin and LL-37. Correlation of assays generated characteristic antimicrobial profiles, providing insight into the peptides’ mechanisms. LL-37 acted independently of membrane composition, while melittin showed increased activity in the absence of anionic phospholipids. This study confirmed specific interactions with PA, but their action suggests targets beyond the membrane, as bacteria remained viable during membrane disruption but failed to form colonies. Overall, these findings indicate that both peptides can effectively handle lipid remodeling and uncover processes driving bacterial cell death.

Global birth rates have been in steady decline and are projected to continue this trajectory in the coming decades. While existing literature provides important insights into the demographic and socioeconomic dimensions of this trend, there remains a critical gap in theoretical frameworks that engage with the broader implications of declining fertility. Current family planning programs often concentrate on pregnancy and postnatal care but tend to overlook the preconception period, particularly the need to equip women with the resources and autonomy required to make informed decisions about reproduction. Such omissions may have unintended consequences for women’s reproductive choices and broader fertility patterns. Meanwhile, rather than centering policy efforts solely on increasing birth rates, it is imperative to shift the focus toward improving the quality of births which emphasizes the long-term comprehensive benefits to individuals, families and society. This approach necessitates the provision of comprehensive support covering the entire reproductive cycle for women, supported by robust engagement from the global health community. This study seeks to explore the multifaceted factors that shape women’s capacity and inclination to bear children under conditions conducive to positive maternal and infant outcomes. It introduces a holistic framework designed to inform the policies and practices of health and governmental institutions, with the aim of promoting women’s overall well-being and effective and sustainable fertility outcomes.

The Wallace--Freeman estimator is a classical invariant point estimator whose large-sample properties have not been fully developed in a modern asymptotic framework. We show that the estimator can be formulated as a penalised M-estimator with a specific penalty weight, yielding a unified route to its asymptotic analysis. This representation allows us to establish existence, consistency, an asymptotic linear expansion, and asymptotic normality under standard regularity conditions. We further derive the first-order difference between the Wallace--Freeman estimator and the maximum likelihood estimator, and show that this induces an explicit $O(n^{-1})$ bias correction determined by the gradient of the penalty. As a consequence, the Cox--Snell bias formula for the maximum likelihood estimator extends naturally to the Wallace--Freeman estimator by the addition of a penalty-driven correction term. As an illustration, we derive the first-order bias of the Wallace--Freeman estimator for the Weibull model and show how the penalty modifies the corresponding maximum likelihood bias. These results place the Wallace--Freeman estimator within the general theory of penalised likelihood and provide a rigorous asymptotic basis for its use in parametric inference.

The search for new anticancer agents with improved efficacy and reduced toxicity has intensified interest in metal-based compounds. In this study, two novel palladium(II) complexes, synthesized from Schiff base ligands derived from 5-chloro-salicylaldehyde and p-hydroxybenzylamine or tyramine, were chemically characterized and biologically evaluated. Both complexes exhibited significant cytotoxic activity against the MCF-7 breast cancer cell line in a dose- and time-dependent manner, with Pd2 showing slightly higher potency. Morphological analysis of treated cells indicated that apoptosis is the predominant mechanism of cell death. To gain deeper insight into the potential mechanisms underlying the observed anticancer activity, several biologically relevant targets were investigated. Enzyme kinetics revealed that the complexes act as uncompetitive inhibitors of liver catalase, suggesting a possible role in the induction of oxidative stress. Fluorescence studies demonstrated that Pd2 interacts with CT-DNA through combined intercalative and minor groove binding modes and exhibits significant binding affinity toward human serum albumin, predominantly at Sudlow’s site I. Molecular docking analysis further supported favorable interactions with catalase, estrogen receptor α, and B-form DNA, providing structural insight into the experimentally observed biological effects. Overall, the study explores multiple potential mechanisms of anticancer action, underscoring the promising therapeutic potential of these palladium(II) complexes, while antitumor activity has been initially assessed using a MCF-7 cell line as a preliminary model.

Autori u radu pišu o političkoj situaciji u Banja Luci od 1990. do kraja 1992. godine. To je period od održavanja prvih višestranačkih izbora do perioda intenzivne kampanje protjerivanja i masovnih zločina u Banja Luci. Osim osvrta na rezultate izbora 1990., demografska slika opštine prema popisu stanovništva u Bosni i Hercegovini 1991. godine imala je veoma važnu ulogu u odnosu prema brojčano manjinskim narodima. U Banja Luci i cijeloj Bosanskoj krajini već su 1991. godine bile vidljive refleksije agresije Jugoslovenske narodne armije (JNA) na Hrvatsku, što je dovelo do zaoštravanja međunacionalnih odnosa. Izbijanjem agresije na Republiku Bosnu i Hercegovinu 1992. godine počinjeni su masovni zločini nad banjalučkim civilima bošnjačke i hrvatske nacionalnosti od strane Vojske Srpske Republike BiH (VSrRBiH) / Vojske Republike Srpske (VRS) i pripadnika policijskih struktura pri Ministarstvu unutrašnjih poslova (MUP) SrRBiH/RS. Terorisanje, zločini, prisilno odvođenje u logore i druga mjesta zatočenja te progon nad pripadnicima ova dva naroda nastavljeni su i nakon 1992. godine o čemu govore relevantni dokumenti i svjedočenja očevidaca.

Introduction: Cognitive impairment is the most common neurological disorder associated with brain tumors, which leads to linguistic communication damage. Anxiety and depression are among the most prevalent psychiatric comorbidities in this population. Objectives: To determine the level of cognitive functioning, anxiety, and depression in patients with intracranial tumors with and without aphasia. Subjects and methods: A prospective study was conducted on 91 patients with verified brain tumors which were hospitalized at the Clinic for Neurosurgery for one year period. The patients were assessed with Mini Mental State Examination, Beck’s depression inventory, and Beck’s anxiety inventory. The type and severity of aphasia were determined by the Boston Aphasia Test. Results: The highest number of patients, a total of 31 (37.3%), had moderate anxiety disorder. 30 patients (36.1%) had shown symptoms of moderate depression, and 33 (39.7%) had shown mild and moderate cognitive dysfunction. Conclusion: Anxiety, depression, and cognitive dysfunction were significantly more pronounced in subjects with aphasia.

To evaluate clinical characteristics and outcomes of urgent bronchoscopies due to foreign body aspiration (FBA), we analyzed cases from January 1954 to December 2021. The study included children up to 14 years of age who underwent emergency bronchoscopy on suspicion of a foreign body in the lower respiratory tract. Each patient was assessed for age, sex, nature and location of the foreign body, bronchoscopy findings, complications, and airway involvement. A total of 889 children underwent urgent bronchoscopy over 67 years. Most cases (66.7%) occurred within the first three years of life, and 10.6% involved children under one year of age. Recently, a marked decrease in positive findings in infants has been observed. Boys represented 62.5% of cases. Organic foreign bodies, predominantly pumpkin seeds, were most common. The right bronchus was the predominant location (51%). In the most recent period, multiple-location foreign bodies became more frequent. Both the annual number of bronchoscopies and the proportion of positive findings have declined. During the COVID-19 pandemic, suspicion of FBA and the number of bronchoscopies significantly decreased.

Generative artificial intelligence (AI) occupies a dominant transformational position in a wide range of fields, including education, business, law, medicine, rehabilitation – among others. Despite the controversies regarding the use and abuse of this technology, it is possible for professionals, especially those in education, to reap its benefits for instruction, research, and administrative endeavors. Keeping in mind the ethical concerns and the current limitations of the system, AI can provide substantial assistance to, for example, teachers, students, and scholars. Setting aside fears of this technology, teachers can save time and become more efficient and productive with their administrative and instructional tasks. Teachers can also use AI to improve the academic, communication, and social skills of students, including—and especially--students in special education programs. Students can learn to use AI independently; in fact, AI can help students to become autonomous and critical seekers of knowledge. After highlighting some challenges of using AI, the present manuscript discusses a few benefits of AI for children and adolescence who are d/Deaf and hard of hearing (d/Dhh). The manuscript also contains recommendations for teacher education and future research endeavors.

This paper aims to systematically present existing research on cognitive and executive functions, speech and auditory perception, language, literacy, and academic development, and cross-modal reorganization in children with CIs. The methodology included a systematic search of databases (PubMed, Scopus, Web of Science) using keywords related to cognition and CIs. After eliminating duplicates and applying inclusion criteria, an analysis was conducted of relevant references published from 2015 to the present, which were analyzed both in tables and narratively. Research confirms that the cognitive development of children with CIs depends on auditory input and the brain’s ability to integrate information from different sensory modalities. Multisensory and interactive approaches to rehabilitation have the potential to enhance cognitive development and should be further researched and applied in practice.