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.

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.

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.

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.

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.

Objective To compare cognitive profiles and dementia severity among older patients with atrial fibrillation (AF), with and without ischemic stroke (IS), and to evaluate the contribution of vascular burden to global cognitive status. Methods This cross-sectional clinical study included 124 patients aged ≥55 years who were stratified into three groups: AF without IS (n = 50), AF with IS (n = 25), and IS without AF (n = 49). Global cognitive status was assessed using ordinal categories derived from the Mini-Mental State Examination (MMSE). Attention and working memory were additionally evaluated using the Information-Memory-Concentration (IMC) test derived from the Blessed Dementia Scale. Vascular burden was assessed using the Hachinski Ischemic Score (HIS). Group differences were analyzed using appropriate statistical tests, and predictors of worse cognitive status were examined using ordinal logistic regression. Results Patients with combined AF and IS demonstrated a trend toward a less favorable cognitive profile and higher vascular burden compared with patients with AF alone or IS alone. The proportion of female participants differed significantly across groups (p = 0.022), whereas age category and educational level were comparable. In multivariable ordinal logistic regression analysis, higher Hachinski Ischemic Score independently predicted worse global cognitive status (OR 1.79, 95% CI 1.42–2.25; p < 0.001) after adjustment for age, sex, education, and major vascular risk factors. Conclusions Vascular burden plays an important role in cognitive impairment among older patients with atrial fibrillation, particularly when accompanied by ischemic stroke. Incorporating vascular burden assessment into routine clinical evaluation may facilitate earlier recognition and characterization of cognitive impairment in aging populations.

Background This study explored whether tumor regression following neoadjuvant therapy can be used as a reliable indicator of surgical operability in patients with stage IIIA non-small cell lung cancer (NSCLC). Methods A retrospective cohort analysis was performed, including patients with stage IIIA NSCLC treated at a tertiary thoracic surgery center. Patients were categorized according to treatment approach: induction therapy followed by surgery or primary surgical management. Treatment response was assessed using imaging findings, pathological staging changes, residual tumor burden, and lymph node status. Surgical feasibility and perioperative outcomes were evaluated. Statistical significance was defined at p<0.05. Results Patients receiving induction therapy demonstrated greater tumor reduction, higher rates of mediastinal nodal regression, and more frequent complete pathological response. Complete (R0) resection was achieved more often in this group. Tumor regression and nodal response were identified as independent predictors of surgical feasibility. Postoperative complication rates and mortality did not differ significantly between groups. Conclusion Tumor response after neoadjuvant therapy is closely associated with surgical operability in stage IIIA NSCLC. Response-based selection may improve resectability without increasing perioperative risk.

Rapid global changes in climate and habitats lead to shifts in species' geographic ranges. Range contractions experienced by numerous species may result in local extinctions and connectivity disruptions. In some species, range expansions have been observed instead, suggesting the enlargement of suitable habitats and/or adaptations to changing environments. Despite its importance for wildlife management, our understanding of the factors influencing species' spatial responses to rapidly changing environments remains limited. The golden jackal serves as an excellent model to address this knowledge gap, given its ongoing rapid range expansion. In this study, we investigated environmental factors contributing to genetic connectivity and local adaptation across the expanding range of the golden jackal, based on a comprehensive sampling scheme across Eurasia (n = 363), a high‐quality set of genomic markers (19,746 SNPs), and a landscape genomics framework. At the continental scale, geographic distance emerged as the predominant factor. At finer spatial scales, genetic connectivity was best explained by climatic predictors, specifically high annual and seasonal variations in precipitation and temperature, which can shape the species' spatial genetic structure by constraining gene flow. Our connectivity models for current and future climatic conditions show that the species' northward expansion is facilitated by changes in these variables in central and northern Europe promoting high connectivity. Precipitation and temperature were also responsible for most local adaptation signals. Given the potential role of hybridization with domestic dogs in shaping range expansion patterns, we investigated the association between environmental conditions and dog admixture proportions. We found no significant trends, indicating a limited effect of dog admixture on habitat choice. Collectively, our findings suggest that the golden jackal has the potential to continue its expansion across Eurasia in response to ongoing global climate change, providing an example of a species that rapidly tracks the expansion of its suitable habitats.

Sitagliptin is a dipeptidyl peptidase-4 (DPP-4) inhibitor used to treat type 2 diabetes. However, several studies have demonstrated its anti-inflammatory and immunomodulatory properties. The aim of this study was to investigate the effect of sitagliptin on the functional and phenotypic properties of human neutrophils under normal (NG, 5.5 mM)- and high (HG, 22 mM)-glucose conditions in vitro. Neutrophils were pretreated with varying concentrations of sitagliptin and stimulated with phorbol-12-myristate-13-acetate (PMA), N-formyl-L-methionyl-L-leucyl-L-phenylalanine (fMLP), calcium ionophore (CaI), or opsonized zymosan (OpZym). Survival, phenotypic, and functional characteristics were then assessed. Our results showed that sitagliptin was non-cytotoxic to neutrophils even at very high concentrations. It decreased the production of reactive oxygen species (ROS) and neutrophil extracellular traps (NETs), generally following a stimulus- and concentration-dependent pattern. The effect was more pronounced under HG conditions. Furthermore, sitagliptin showed a significant ROS-scavenging effect in a cell-free system. It also rapidly altered the expression of surface markers in both resting and fMLP-stimulated neutrophils, typically upregulating CD10, CD16, CD62L, CD63, CD88, CD89, and PD-L1, and downregulating CD11b/CD18, CD66b, and CD182, a phenotype consistent with a dampened, less-primed activation state of these cells. In conclusion, sitagliptin exhibited marked antioxidative/ROS-scavenging activity in neutrophil cultures and induced a coordinated shift in neutrophil phenotype, accompanied by suppression of NETosis under both NG and HG conditions. Collectively, these data support the view that neutrophils may constitute an additional cellular target contributing to sitagliptin’s anti-inflammatory and immunomodulatory profile.

Abstract Introduction Sepsis is a global health priority with nearly 50 million cases annually. Cardiovascular dysfunction is common, frequently manifesting as hypotension that persists despite fluid resuscitation. Most affected patients require the use of intravenous (IV) vasoactive agents, typically necessitating intensive care unit (ICU)-level monitoring, invasive interventions and contributing substantially to healthcare costs. Midodrine, an oral alpha-1 agonist approved for orthostatic hypotension, has increasingly been used off-label as a vasopressor-sparing (reducing IV vasopressor use) strategy in sepsis, despite limited and inconsistent evidence. This pragmatic, randomised, open-label trial evaluates the efficacy and safety of midodrine in patients with sepsis-associated hypotension. We hypothesise that, compared with standard care, midodrine administration will reduce the duration of IV vasopressor use. Methods and analysis A total of 308 adult patients with sepsis-associated hypotension will be enrolled (154 per arm). The intervention group will, in addition to standard of care, receive enteral midodrine 10 mg three times daily. Outcomes will be ascertained pragmatically via electronic health record-based data retrieval and adjudicated by research coordinators blinded to treatment assignment. The primary outcome is time alive and off IV vasopressors in the first 28 days (in hours) after randomisation. Secondary outcomes include cumulative vasopressor exposure; use and duration of central venous access; cumulative fluid balance over the first 48 hours and up to 7 days of ICU stay; ICU and hospital length of stay; and ICU-, hospital-, and organ support-free days through day 28. Safety outcomes include adverse events potentially attributable to midodrine during hospitalisation including acute kidney injury. Primary analyses will follow an intention-to-treat framework, including all randomised participants according to their assigned treatment groups. Primary and secondary outcomes will be compared using a van Elteren test stratified by randomisation factors. A predefined secondary Bayesian analysis of the primary outcome will provide complementary estimates of treatment effect. Safety outcomes will be summarised descriptively without formal between-arm hypothesis testing. Ethics and dissemination The Mayo Clinic Institutional Review Board approved this protocol and required written informed consent from all participants (IRB# 24–0 00 121). Findings will be disseminated through peer-reviewed publications and international conference presentations. Trial registration number NCT06319248.