Functional Signatures Research Articles

TransCAE: Enhancing cell type annotation in single-cell RNA-seq data with transfer learning and convolutional autoencoder.

Single-cell RNA sequencing (scRNA-seq) analysis offers tremendous potential for addressing various biological questions, with one key application being the annotation of query datasets with unknown cell types using well-annotated external reference datasets. However, the performance of existing supervised or semi-supervised methods largely depends on the quality of source data. Furthermore, these methods often struggle with the batch effects arising from different platforms when handling multiple reference or query datasets, making precise annotation challenging. We developed transCAE, a robust transfer learning-based algorithm for single-cell annotation that integrates unsupervised dimensionality reduction with supervised cell type classification. This approach fully leverages information from both reference and query datasets to achieve precise cell classification within the query data. Extensive evaluations show that transCAE significantly enhances classification accuracy and efficiently mitigates batch effects. Compared to other state-of-the-art methods, transCAE demonstrates superior performance in experiments involving multiple reference or query datasets. These strengths position transCAE as an optimal annotation method for scRNA-seq datasets.

Affect: An Affine Type and Effect System

Effect handlers form a powerful construct that can express complex programming abstractions. They are a generalization of exception handlers, but allow resumption of the continuation from where the effect was raised. Allowing continuations to be resumed at most once ( one-shot ) or an arbitrary number of times ( multi-shot ) has far-reaching consequences. In addition to performance considerations, multi-shot effects break key rules of reasoning and thus render certain standard transformation/optimizations unsound, especially in languages with mutable references (such as OCaml 5). It is therefore desirable to statically track whether continuations are used in a one-shot or multi-shot discipline, so that a compiler could use this information to efficiently implement effect handlers and to determine what optimizations it may perform. We address this problem by developing a type and effect system–called Affect –which uses affine types to track the usage of continuations. A challenge is to soundly deal with advanced programming features—such as references that store continuations and nested continuations—which are crucial to support challenging examples from the effects literature (such as control inversion and cooperative concurrency ). Another challenge is to support generic type signatures of polymorphic effectful functions. We address these challenges by using and extending Rust’s Cell type and Wadler’s use types . To prove soundness of Affect we model types and judgements semantically via a logical relation in the Iris separation logic framework in Coq.

Editorial Expression of Concern: Functional connectivity signatures of political ideology.

Editorial Expression of Concern: Functional connectivity signatures of political ideology.

Covariation Between Microbiome Composition and Host Transcriptome in the Gut of Wild Drosophila melanogaster: A Re-Analysis.

Gut microbiota are fundamental for healthy animal function, but the evidence that host function can be predicted from microbiota taxonomy remains equivocal, and natural populations remain understudied compared to laboratory animals. Paired analyses of covariation in microbiota and host parameters are powerful approaches to characterise host-microbiome relationships mechanistically, especially in wild populations of animals that are also lab models, enabling insight into the ecological basis of host function at molecular and cellular levels. The fruitfly Drosophila melanogaster is a preeminent model organism, amenable to field investigation by 'omic analyses. Previous work in wild male D. melanogaster guts analysed paired measurements of (A) bacterial diversity and abundance, measured by 16S amplicon sequencing; and (B) the host gut transcriptome, but no signature of covariation was detected. Here, we re-analyse those data comprehensively. We find orthogonal axes of microbial genera, which correspond to differential expression of host genes. The differentially expressed gene sets were enriched in functions including protein translation, mitochondrial respiration, immunity and reproduction. Each gene set had a distinct functional signature, suggesting that wild flies exhibit a range of distinct axes of functional variation, which correspond to orthogonal axes of microbiome variation. These findings lay a foundation to better connect ecology and functional genetics of a leading host-microbiome model.

Bacteriophage derived dsRNA induces polarized activation of alveolar macrophages from Balb/c and C57Bl/6 mice in vitro in sex- and age-dependent manner.

Bacteriophage-derived dsRNA (bp-dsRNA), also known as Larifan, is a poly-functional and wide-spectrum antiviral medication with potent interferonogenic activity. In the lungs of golden Syrian hamsters infected with SARS-CoV-2, Larifan substantially reduces viral load and decreases infection-induced pathological lesion severity. Alveolar macrophages (AM) are key sentinel cells in the lung, which play an important role in antiviral innate immune responses and, at the same time, can trigger infection-associated hyper-inflammatory response. This study revealed that treatment with bp-dsRNA (Larifan) in vitro modulates the functional profile of AM from intact Balb/c and C57Bl/6 mice. The pattern of the drug response depends on the animal strain, age and sex. AM from Balb/c mice generated a weaker response to the preparation as compared to cells from C57Bl/6 mice. Most emphatic responses to the treatment with bf-dsRNA (Larifan) were registered in AM from old males of both BALB/c and C57BL/6 strains with the strongest in the latter. AM from old C57BL/6 females were less likely to be influenced by the preparation. In most cases, exposure to bf-dsRNA (Larifan) increased AM phagocytic activity and was more often accompanied by the stimulation of intracellular reactive oxygen species generation, than by its decrease. In most animal groups, treatment with bf-dsRNA (Larifan) did not affect significantly CD206 expression and down-regulated CD80 expression in AM. Taken together, our findings suggest that bf-dsRNA (Larifan) not so much stimulates the bivalent phenotype of AM, as restrains their hyper-inflammatory responses through the control of antigen-presentation while preserving functional signatures typical of patrolling tissue-resident macrophages.

Evaluating sex-specific responses to western diet across the lifespan: impact on cardiac function and transcriptomic signatures in C57BL/6J mice at 530 and 640/750 days of age

BackgroundLong-term consumption of Western Diet (WD) is a well-established risk factor for the development of cardiovascular disease (CVD); however, there is a paucity of studies on the long-term effects of WD on the pathophysiology of CVD and sex-specific responses.MethodsOur study aimed to investigate the sex-specific pathophysiological changes in left ventricular (LV) function using transthoracic echocardiography (ECHO) and LV tissue transcriptomics in WD-fed C57BL/6 J mice for 125 days, starting at the age of 300 through 425 days.ResultsIn female mice, consumption of the WD diet showed long-term effects on LV structure and possible development of HFpEF-like phenotype with compensatory cardiac structural changes later in life. In male mice, ECHO revealed the development of an HFrEF-like phenotype later in life without detectable structural alterations. The transcriptomic profile revealed a sex-associated dichotomy in LV structure and function. Specifically, at 530-day, WD-fed male mice exhibited differentially expressed genes (DEGs), which were overrepresented in pathways associated with endocrine function, signal transduction, and cardiomyopathies. At 750 days, WD-fed male mice exhibited dysregulation of several genes involved in various lipid, glucagon, and glutathione metabolic pathways. At 530 days, WD-fed female mice exhibited the most distinctive set of DEGs with an abundance of genes related to circadian rhythms. At 640 days, altered DEGs in WD-fed female mice were associated with cardiac energy metabolism and remodeling.ConclusionsOur study demonstrated distinct sex-specific and age-associated differences in cardiac structure, function, and transcriptome signature between WD-fed male and female mice.Graphical

Mitochondrial respiration atlas reveals differential changes in mitochondrial function across sex and age

Organ function declines with age, and large-scale transcriptomic analyses have highlighted differential aging trajectories across tissues. The mechanism underlying shared and organ-selective functional changes across the lifespan, however, still remains poorly understood. Given the central role of mitochondria in powering cellular processes needed to maintain tissue health, we therefore undertook a systematic assessment of respiratory activity across 33 different tissues in young (2.5 months) and old (20 months) mice of both sexes. Our high-resolution mitochondrial respiration atlas reveals: (1) within any group of mice, mitochondrial activity varies widely across tissues, with the highest values consistently seen in heart, brown fat, and kidney; (2) biological sex is a significant but minor contributor to mitochondrial respiration, and its contributions are tissue-specific, with major differences seen in the pancreas, stomach, and white adipose tissue; (3) age is a dominant factor affecting mitochondrial activity, especially across most brain regions, different fat depots, skeletal muscle groups, eyes, and different regions of the gastrointestinal tract; (4) age effects can be sex- and tissue-specific, with some of the largest effects seen in pancreas, heart, adipose tissue, and skeletal muscle; and (5) while aging alters the functional trajectories of mitochondria in a majority of tissues, some are remarkably resilient to age-induced changes. Altogether, our data provide the most comprehensive compendium of mitochondrial respiration and illuminate functional signatures of aging across diverse tissues and organ systems.

Mitochondrial respiration atlas reveals differential changes in mitochondrial function across sex and age.

Organ function declines with age, and large-scale transcriptomic analyses have highlighted differential aging trajectories across tissues. The mechanism underlying shared and organ-selective functional changes across the lifespan, however, still remains poorly understood. Given the central role of mitochondria in powering cellular processes needed to maintain tissue health, we therefore undertook a systematic assessment of respiratory activity across 33 different tissues in young (2.5 months) and old (20 months) mice of both sexes. Our high-resolution mitochondrial respiration atlas reveals: (1) within any group of mice, mitochondrial activity varies widely across tissues, with the highest values consistently seen in heart, brown fat, and kidney; (2) biological sex is a significant but minor contributor to mitochondrial respiration, and its contributions are tissue-specific, with major differences seen in the pancreas, stomach, and white adipose tissue; (3) age is a dominant factor affecting mitochondrial activity, especially across most brain regions, different fat depots, skeletal muscle groups, eyes, and different regions of the gastrointestinal tract; (4) age effects can be sex- and tissue-specific, with some of the largest effects seen in pancreas, heart, adipose tissue, and skeletal muscle; and (5) while aging alters the functional trajectories of mitochondria in a majority of tissues, some are remarkably resilient to age-induced changes. Altogether, our data provide the most comprehensive compendium of mitochondrial respiration and illuminate functional signatures of aging across diverse tissues and organ systems.

MultiKano: an automatic cell type annotation tool for single-cell multi-omics data based on Kolmogorov-Arnold network and data augmentation.

MultiKano: an automatic cell type annotation tool for single-cell multi-omics data based on Kolmogorov-Arnold network and data augmentation.

Cell Type Differentiation Using Network Clustering Algorithms.

Single cell RNA-seq (scRNA-seq) technologies provide unprecedented resolution representing transcriptomics at the level of single cell. One of the biggest challenges in scRNA-seq data analysis is the cell type annotation, which is usually inferred by cell separation approaches. In-silico algorithms that accurately identify individual cell types in ongoing single-cell sequencing studies are crucial for unlocking cellular heterogeneity and understanding the biological basis of diseases. In this study, we focus on robustly identifying cell types in single-cell RNA sequencing data; we conduct a comparative analysis using methods established in biology, like Seurat, Leiden, and WGCNA, as well as Infomap, statistical inference via Stochastic Block Models (SBM), and single-cell Graph Neural Networks (scGNN). We also analyze preprocessing pipelines to identify and optimize key components in the process. Leveraging two independent datasets, PBMC and ROSMAP, we employ clustering algorithms on cell-cell networks derived from gene expression data. Our findings reveal that while clusters detected by WGCNA exhibit limited correspondence with cell types, those identified by multiresolution Infomap and Leiden, and SBM show a closer alignment, with Infomap standing out as a particularly effective approach. Infomap notably offers valuable insights for the precise characterization of cellular landscapes related to neurodegenration and immunology in scRNA-seq.

Sex-Dependent Gut Microbiota Features and Functional Signatures in Metabolic Disfunction-Associated Steatotic Liver Disease.

Background/Objectives: This study investigates the gut microbiota's role in metabolic dysfunction-associated steatotic liver disease (MASLD), focusing on microbial and functional signatures and sex-based differences. Methods: Using baseline data from 98 MASLD patients and 45 controls from the Fatty Liver in Obesity (FLiO) study, the gut microbiota was profiled with 16S gene sequencing, followed by statistical and machine learning analyses to identify disease-associated microbial signatures. Results: Notable alpha and beta diversity differences were observed between MASLD patients and the controls, varying by sex. Machine learning models highlighted specific microbial signatures for each sex, achieving high accuracy (area under the receiver operating characteristic curves of 0.91 for women and 0.72 for men). The key microbial taxa linked to MASLD included Christensenella and Limosilactobacillus in women and Beduinibacterium and Anaerotruncus in men. Functional profiling showed that MASLD patients had increased pathways for amine biosynthesis and amino acid degradation, while the controls exhibited enhanced fermentation pathways. These microbial features were associated with systemic inflammation, insulin resistance, and metabolite production linked to gut dysbiosis. Conclusions: The findings support the potential of gut microbiota signatures to be used as non-invasive indicators of MASLD and highlight sex-specific variations that could inform personalized diagnostic and therapeutic approaches.

Macrophages excite muscle spindles with glutamate to bolster locomotion

The stretch reflex is a fundamental component of the motor system that orchestrates the coordinated muscle contractions underlying movement. At the heart of this process lie the muscle spindles (MS), specialized receptors finely attuned to fluctuations in tension within intrafusal muscle fibres. The tension variation in the MS triggers a series of neuronal events including an initial depolarization of sensory type Ia afferents that subsequently causes the activation of motoneurons within the spinal cord1,2. This neuronal cascade culminates in the execution of muscle contraction, underscoring a presumed closed-loop mechanism between the musculoskeletal and nervous systems. By contrast, here we report the discovery of a new population of macrophages with exclusive molecular and functional signatures within the MS that express the machinery for synthesizing and releasing glutamate. Using mouse intersectional genetics with optogenetics and electrophysiology, we show that activation of MS macrophages (MSMP) drives proprioceptive sensory neuron firing on a millisecond timescale. MSMP activate spinal circuits, motor neurons and muscles by means of a glutamate-dependent mechanism that excites the MS. Furthermore, MSMP respond to neural and muscle activation by increasing the expression of glutaminase, enabling them to convert the uptaken glutamine released by myocytes during muscle contraction into glutamate. Selective silencing or depletion of MSMP in hindlimb muscles disrupted the modulation of the stretch reflex for force generation and sensory feedback correction, impairing locomotor strategies in mice. Our results have identified a new cellular component, the MSMP, that directly regulates neural activity and muscle contraction. The glutamate-mediated signalling of MSMP and their dynamic response to sensory cues introduce a new dimension to our understanding of sensation and motor action, potentially offering innovative therapeutic approaches in conditions that affect sensorimotor function.

Multimodal neural correlates of childhood psychopathology.

Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples and robust to variations in analytical parameters. Although model parameters yielded statistically significant brain-behavior associations in unseen data, generalizability of the model was rather limited for all three latent components (r change from within- to out-of-sample statistics: LC1within=0.36, LC1out=0.03; LC2within=0.34, LC2out=0.05; LC3within=0.35, LC3out=0.07). Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.

Spatially Aware Domain Adaptation Enables Cell Type Deconvolution from Multi-Modal Spatially Resolved Transcriptomics.

Spatially Resolved Transcriptomics (SRT) offers unprecedented opportunities to elucidate the cellular arrangements within tissues. Nevertheless, the absence of deconvolution methods that simultaneously model multi-modal features has impeded progress in understanding cellular heterogeneity in spatial contexts. To address this issue, SpaDA is developed, a novel spatially aware domain adaptation method that integrates multi-modal data (i.e., transcriptomics, histological images, and spatial locations) from SRT to accurately estimate the spatial distribution of cell types. SpaDA utilizes a self-expressive variational autoencoder, coupled with deep spatial distribution alignment, to learn and align spatial and graph representations from spatial multi-modal SRT data and single-cell RNA sequencing (scRNA-seq) data. This strategy facilitates the transfer of cell type annotation information across these two similarity graphs, thereby enhancing the prediction accuracy of cell type composition. The results demonstrate that SpaDA surpasses existing methods in cell type deconvolution and the identification of cell types and spatial domains across diverse platforms. Moreover, SpaDA excels in identifying spatially colocalized cell types and key marker genes in regions of low-quality measurements, exemplified by high-resolution mouse cerebellum SRT data. In conclusion, SpaDA offers a powerful and flexible framework for the analysis of multi-modal SRT datasets, advancing the understanding of complex biological systems.

D-Mannose-Mediated metabolic pathways sustain the molecular signatures of sperm function and fertilization.

Mammalian sperm within a single ejaculate exhibit significant heterogeneity, with only a subset possessing the molecular characteristics required for successful fertilization. Identifying the defining traits of these high-fertility sperm remains an open question. To elucidate the molecular markers and mechanisms underlying the fertilization potential of sperm in both mice and humans, with a focus on the role of D-mannose. Sperm morphology and functionality were analyzed using flow cytometry, biochemical assays, and immunofluorescence. Multi-omics analyses, including proteomics, metabolomics, and lipidomics, were conducted to identify distinct molecular signatures. Pharmacological interventions were employed to validate the role of key pathways, particularly Akt/mTOR signaling. Sperm with longer flagella demonstrated enhanced motility, mitochondrial activity, and fertilization potential in both mice and humans. Multi-omics analyses revealed distinct molecular profiles in high-fertility sperm, characterized by specific proteins, lipids, and metabolites. Notably, D-mannose supplementation enhanced sperm motility and fertilization capacity, even in asthenozoospermic sperm, by activating the Akt/mTOR pathway. This effect was not replicated by D-glucose or ATP supplementation. Mechanistically, D-mannose bypassed glycolytic rate-limiting steps, increasing ATP production and promoting mitochondrial and acrosomal integrity. This study identifies key molecular signatures of fertilization-competent sperm and highlights D-mannose as a novel modulator of sperm quality and function. These findings provide valuable insights into sperm biology and propose innovative therapeutic strategies for treating male infertility and optimizing assisted reproduction technologies.

Serotonin 5-HT1A receptor biased agonists: The challenge of translating an innovative neuropharmacological concept into therapeutics.

Serotonin 5-HT1A receptor agonists are prime candidates for CNS drug discovery due to their involvement physiological and pathological processes relevant to neurology and psychiatry. However, the lack of target specificity of many previously characterized agonists has long been a barrier to pharmacological and therapeutic progress. Some of the obstacles may be overcome through the recent concept of biased agonism, which has attracted considerable attention to the development of novel chemical entities at 5-HT, and particularly 5-HT1A receptors, by specifically targeting intracellular signalling pathways that may themselves be linked to specific brain regions and therapeutic indications. There is now abundant translational data demonstrating distinct molecular and functional pharmacological signatures between different 5-HT1A receptor agonists, opening new opportunities for research in neurology and psychiatry. Nevertheless, important limitations need to be overcome, including understanding the precise molecular basis for biased agonism, the need for improved translatable models, and the currently limited clinical data on biased agonists. Here, we review the current limits of our knowledge of 5-HT1A receptor biased agonists and the limitations of available pharmacological tools, counterbalanced by the translational possibilities and therapeutic perspectives opened by novel, highly selective 5-HT1A receptor drug-candidates.

IDclust: Iterative clustering for unsupervised identification of cell types with single cell transcriptomics and epigenomics.

The increasing diversity of single-cell datasets require systematic cell type characterization. Clustering is a critical step in single-cell analysis, heavily influencing downstream analyses. However, current unsupervised clustering algorithms rely on biologically irrelevant parameters that require manual optimization and fail to capture hierarchical relationships between clusters. We developed IDclust, a framework that identifies clusters with significant biological features at multiple resolutions using biologically meaningful thresholds like fold change, adjusted P-value and fraction of expressing cells. By iteratively processing and clustering subsets of the dataset, IDclust guarantees that all clusters found have significantly different features and stops only when no more interpretable cluster is found. It also creates a hierarchy of clusters, enabling visualization of the hierarchical relationships between different clusters. Analyzing multiple single-cell transcriptomic reference datasets, IDclust achieves superior clustering accuracy compared to state of the art algorithms. We showcase its utility by identifying previously unannotated clusters and identifying branching patterns in scATAC datasets. Using it's unsupervised nature and ability to analyze different -omics, we compare the resolution of different histone marks in multi-omic paired-tag dataset. Overall, IDclust automates single-cell exploration, facilitates cell type annotation and provides a biologically interpretable basis for clustering.

HSP mRNA sequences and its expression under different thermal oscillation patterns and heat-stress in two populations of Nodipecten subnodosus.

Understanding the molecular mechanisms underlying thermal acclimation and heat shock responses (HSR) in marine ectotherms is critical for assessing their adaptive capacity in the context of climate change and climate extremes. This study examines the expression dynamics of heat shock proteins (HSPs) in the scallop Nodipecten subnodosus, shedding light on their role in thermal adaptation. Our analysis revealed the presence of several conserved functional signatures in N. subnodosus HSPs deduced amino acid sequences. Comparative gene expression profiling between two populations of N. subnodosus, maintained for 15 days under constant and oscillatory thermal regimes and then exposed to acute heat stress, revealed conserved adaptive traits. The heat-inducible nature of N. subnodosus HSP70 (HSPA8) gene expression highlights its potential as a stress marker, in contrast to its human homolog, which is constitutively expressed. Furthermore, the identification of HSP90 (HSPC3) and its overexpression during acute heat stress underscores its critical role in initiating a protective stress response. Population-specific responses in the magnitude of gene expression were observed; however, both populations exhibited similar overall patterns of HSP induction, suggesting a shared adaptive response mechanism. This study also elucidated the diversity and expansion of members of the HSP70 family members, specifically the HSPA12 subfamily, in N. subnodosus. This characteristic, previously observed in other bivalves, underscores the role of HSPA12 in environmental adaptation, providing molecular plasticity to withstand varying environmental pressures. These findings offer valuable insights into the molecular basis of thermal adaptation in N. subnodosus, highlighting the importance of HSPs in coping with environmental stochasticity under climate change scenarios.

Single-cell multiomics reveals simvastatin inhibits pan-cancer epithelial-mesenchymal transition via the MEK/ERK pathway in XBP1+ mast cells

Distant metastasis is the leading cause of cancer-related mortality, and achieving survival benefits through advancements in systemic therapy remains challenging. Mast cells play a dual role in shaping the tumor microenvironment (TME) and influencing distant metastasis, underscoring the significant research value of targeting mast cells for systemic therapy in advanced cancer. We investigated variations in mast cell infiltration levels in primary and metastatic malignancies using immunocyte infiltration analysis. Mast cell subsets were identified from pan-cancer distant metastasis single-cell sequencing data through dimensionality reduction clustering and cell type annotation, combined with cell trajectory and communication network analyses. A prognostic model was established using WGCNA and 12 machine learning algorithms to identify potential mast cell targets. Drug sensitivity and Mendelian randomization analyses were conducted to select potential drugs targeting mast cells, and their effects on epithelial-mesenchymal transition (EMT) were validated through in vitro experiments, including wound healing, transwell, and western blot assays. Results revealed that activated mast cells show increased infiltration in metastatic tumors, correlating with poor survival duration. XBP1+ mast cells were identified as key components of the inhibitory TME, potentially involved in EMT activation. Simvastatin was identified as a potential drug, reversing EMT induced by XBP1+ mast cells in pan-cancer. Aberrant activation of MEK/ERK signaling in XBP1+ mast cells can stimulate cancer cell EMT by modulating degranulation, while Simvastatin can inhibit EMT by suppressing degranulation.

Inflammatory Mesenchymal Stromal Cells and IFN-responsive T cells are key mediators of human bone marrow niche remodeling in CHIP and MDS.

Somatic mutations in hematopoietic stem/progenitor cells (HSPCs) can lead to clonal hematopoiesis of indeterminate potential (CHIP), potentially progressing to myelodysplastic syndromes (MDS). Here, we investigated how CHIP and MDS remodel the human bone marrow (BM) niche relative to healthy elderly donors, using single cell and anatomical analyses in a large BM cohort. We found distinct inflammatory remodeling of the BM in CHIP and MDS. Furthermore, the stromal compartment progressively lost its HSPC-supportive adipogenic CXCL12-abundant reticular cells while an inflammatory mesenchymal stroma cell (iMSCs) population emerged in CHIP, which expanded in MDS. iMSCs exhibited distinct functional signatures in CHIP and MDS, retaining residual HSPC-support and angiogenic activity in MDS, corresponding with an increase in microvasculature in the MDS niche. Additionally, an IFN-responsive T cell population was linked to fueling inflammation in the stroma. Overall, these findings open new avenues for early intervention in hematological malignancies.