Biology subjects

Saberi, M.

Publications and source records attributed to Saberi, M..

6 recordsLinked to original sources

bioRxiv2025

Sialylated CD43 is a glyco-immune checkpoint for macrophage phagocytosis

Macrophages in the tumor microenvironment exert potent anti-tumorigenic activity through phagocytosis. Yet therapeutics that enhance macrophage phagocytosis have not improved outcomes in clinical trials for patients with acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS). To systematically identify regulators of phagocytosis, we performed genome-scale CRISPR knockout screens in human leukemia cells co-cultured with human monocyte-derived macrophages. Surprisingly, we found that whereas the classic "dont eat me" signal CD47 inhibited mouse macrophages, it did not inhibit phagocytosis by human macrophages. In contrast, the O-linked glycosylation and sialylation pathways were strong negative regulators of phagocytosis. In AML, the cell surface O-linked glycoprotein CD43 was the major effector of the O-linked glycosylation and sialylation pathways. Genetic deletion or antibody blockade of CD43 enhanced macrophage phagocytosis. This work highlights the importance of using human platforms to identify immune checkpoints, and nominates CD43 as a glyco-immune regulator of human macrophage phagocytosis.

cancer biology↗

bioRxiv2024

The brain selectively allocates energy to functional brain networks under cognitive control

Network energy has been conceptualized based on structural balance theory in the physics of complex networks. We utilized this framework to assess the energy of functional brain networks under cognitive control and to understand how energy is allocated across canonical functional networks during various cognitive control tasks. We extracted network energy from functional connectivity patterns of subjects who underwent fMRI scans during cognitive tasks involving working memory, inhibitory control, and cognitive flexibility, in addition to task-free scans. We found that the energy of the whole-brain network increases when exposed to cognitive control tasks compared to the task-free resting state, which serves as a reference point. The brain selectively allocates this elevated energy to canonical functional networks; sensory networks receive more energy to support flexibility for processing sensory stimuli, while cognitive networks relevant to the task, functioning efficiently, require less energy. Furthermore, employing network energy, as a global network measure, improves the performance of predictive modeling, particularly in classifying cognitive control tasks and predicting chronological age. Our results highlight the robustness of this framework and the utility of network energy in understanding brain and cognitive mechanisms, including its promising potential as a biomarker for mental conditions and neurological disorders.

neuroscience↗

bioRxiv2024

Single-Cell Data Integration and Cell Type Annotation through Contrastive Adversarial Open-set Domain Adaptation

Single-cell sequencing technologies have enabled in-depth analysis of cellular heterogeneity across tissues and disease contexts. However, as datasets increase in size and complexity, characterizing diverse cellular populations, integrating data across multiple modalities, and correcting batch effects remain challenges. We present SAFAARI (Single-cell Annotation and Fusion with Adversarial Open-Set Domain Adaptation Reliable for Data Integration), a unified deep learning framework designed for cell annotation, batch correction, and multi-omics integration. SAFAARI leverages supervised contrastive learning and adversarial domain adaptation to achieve domain-invariant embeddings and enables label transfer across datasets, addressing challenges posed by batch effects, biological domain shifts, and multi-omics modalities. SAFAARI identifies novel cell types and mitigates class imbalance to enhance the detection of rare cell types. Through comprehensive benchmarking, we evaluated SAFAARI against existing annotation and integration methods across real-world datasets exhibiting batch effects and domain shifts, as well as simulated and multi-omics data. SAFAARI demonstrated scalability and robust performance in cell annotation via label transfer across heterogeneous datasets, detection of unknown cell types, correction of batch effects, and cross-omics data integration while leveraging available annotations for improved integration. SAFAARIs innovative approach outperformed competing methods in both qualitative and quantitative metrics, offering a flexible, accurate, and scalable solution for single-cell analysis with broad applicability to diverse biological and clinical research questions.

bioinformatics↗

bioRxiv2024

Elevated body mass index in youth is associated with dysregulated surrogate markers of neural inhibition & excitation, and internetwork functional dysconnectivity

The developing child and adolescent brain is thought to have an increased vulnerability to the negative impact of obesity and excessive consumption of hyperpalatable and energy-rich foods. In this study, we investigated the neurophysiological effects of overweight and obesity in 30 participants spanning childhood and adolescence (8-19 years), using a naturalistic viewing paradigm with Inscapes, in a pseudo-resting-state protocol scan with magnetoencephalography (MEG). Subjects were median split on body mass indices (BMI), categorised into two groups comprising: lower <25 kg/m2 (n=15) and higher [≥]25 kg/m2 (n=15). We assessed spontaneous, regional neural function indexed by oscillatory activity, and functional connectivity within and between intrinsic resting brain networks, including the default mode network, dorsal and ventral attention, somatomotor, visual, language, central executive and salience networks. Elevated BMI was associated with significant reductions in activity of the posterior dominant rhythm, and gamma hyperactivity across widespread cortical areas, suggesting intrinsic neuronal hyperexcitability and disinhibition in children and adolescents. Additionally, we observed low-frequency theta hypoconnectivity between resting state networks including the salience, visual, and default mode networks, and overall reduced global efficiency in brain network structure, suggesting reduced effectiveness in neural communication. These findings underscore the neural impact of body composition on the developing brain, suggesting deleterious alterations in excitation and inhibition from surrogate neural markers associated with neurochemistry and brain networks linked with cognitive and behavioural functioning. These alterations may contribute to the persistent behavioural rigidity and difficulties in adopting healthier eating behaviours into adulthood.

neuroscience↗

bioRxiv2022

Pattern of frustration formation in the functional brain network

The brain is a frustrated system that contains conflictual link arrangements named frustration. The frustration as a source of disorder prevents the system from settling into low energy states and provides flexibility for brain network organization. In this research, we tried to identify the pattern of frustration formation in the brain at the levels of region, connection, canonical network, and hemisphere. We found that frustration formation has not a uniform pattern. Some subcortical elements have an active role in frustration formation, despite many low contributed cortical elements. Frustrating connections are mostly between-network types and triadic frustrations are mainly formed between three regions from three distinct canonical networks. Although there were no significant differences between brain hemispheres. We also did not find any robust differences between the frustration formation patterns of various lifespan stages. Our results may be interesting for those who study the organization of brain links and promising for those who want to manipulate brain networks.

neuroscience↗

bioRxiv2021

Topological impact of negative links on the stability of resting-state brain network

Stability is a physical attribute that stands opposite the change. However, it is still unclear how the arrangement of links called topology affects network stability. In this study, we tackled this issue in the resting-state brain network using structural balance. Structural balance theory employs the quality of triadic associations between signed links to determine the network stability. In this study, we showed that negative links of the resting-state network make hubs to reduce balance-energy and push the network into a more stable state compared to null-networks with trivial topologies. In this regard, we created a global measure entitled tendency to make hub to assess the hubness of the network. Besides, we revealed nodal degrees of negative links have an exponential distribution that confirms the existence of negative hubs. Our findings indicate that the arrangement of negative links plays an important role in the balance (stability) of the resting-state brain network.

neuroscience↗