Biology subjects

Basak, A.

Publications and source records attributed to Basak, A..

8 recordsLinked to original sources

bioRxiv2026

Behavioral and ERP Markers of Emotion Recognition: Comparing Embodied, Facial, and Emoji Stimuli

While extensive research has been conducted on emotion recognition from facial stimuli, it remains unclear how embodied emotional cues conveyed through body postures, gestures and actions (e.g., stick figures) compare with facial (human faces) and face-like symbolic representations (emoji faces) in shaping behavioral and neural responses. We employed a multimodal approach, combining behavioral measures (accuracy and reaction time) with electroencephalography (EEG) to examine the electrophysiological correlates of emotion recognition. Overall, sixty-six (equal number of males and females; 18-30 year old) participants identified positive, negative, and neutral emotions depicted in the three formats. Behavioral results showed significant effects of both emotion and format on accuracy and reaction time. Emoji faces were recognized with the highest accuracy and fastest reaction times, followed by stick figures and then human faces (p < .001, some comparisons p < .05). Thirty-four participants (17 males and 17 females) underwent EEG, which revealed distinct patterns of event-related potentials (ERPs). The Early Posterior Negativity (EPN) amplitude showed a significant overall effect of format. Post-hoc comparisons indicated that stick figures elicited greater (more negative) EPN amplitudes than human faces during positive emotion recognition (p = .003), and greater amplitudes than both emoji faces (p = .027) and human faces (p = .007) during negative emotion recognition. No significant differences were observed between emoji and human faces. N170 and Late Positive Potential (LPP) amplitudes did not reveal significant differences (all p > .05). Correlation analyses revealed no significant associations between ERP and behavioral measures. Thus, abstract, minimalistic representations like stick figures elicit enhanced early emotion-related processing despite similar early and later processing across formats. HighlightsO_LIEmotion recognition across realistic (human faces), symbolic (emoji faces) and embodied (stick figures) modalities were compared. C_LIO_LIEmotions were recognized fastest and most accurately in emoji faces format. C_LIO_LIStick figures format elicited significantly higher EPN compared to other two formats across positive and negative emotions. C_LIO_LINo significant differences were observed in terms of N170 and LPP. C_LIO_LIEmbodied, abstract emotional cues modulate automatic emotional appraisal, rather than initial sensory encoding and sustained cognitive evaluation. C_LI

neuroscience↗

bioRxiv2026

Network reciprocity reshaped by environmental knowledge and feedback

Cooperative interactions often unfold in environments that are shaped by collective behavior, yet how knowledge about such changing environments feeds back into evolutionary dynamics remains poorly understood. While network reciprocity explains how spatial structure enables clusters of cooperators to emerge and grow under certain conditions, it typically ignores how individuals respond to environmental change. Here, we integrate stochastic environmental feedback with network reciprocity to examine how knowledge about environmental state shapes the evolution of cooperation in structured populations. We compare regimes in which individuals either condition their behavior on the current state or remain unaware of it. Under weak selection, we derive a simple condition showing that cooperation is favored when the benefit-to-cost ratio exceeds a modified classic reciprocity threshold accounting for the effect of environmental transitions and state knowledge. Environmental shifts can either promote or hinder cooperation depending on accessibility and fidelity of state knowledge. Counterintuitively, greater knowledge does not universally enhance cooperation: for certain transition rules, state awareness raises the critical threshold for cooperation, a phenomenon we term a "knowledge curse". Our results reveal that, in an ever-changing environment, cooperation in structured populations emerges from a subtle interplay between environmental feedback and information availability.

animal behavior and cognition↗

bioRxiv2026

Toward Computationally Complete Spatial Omics

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

genomics↗

bioRxiv2026

Single-Cell and Spatial Methods for Multimodal Functional Glycan Profiling in Tissues

Glycans regulate multiple physiological processes, including immune recognition and cancer progression. In disease, altered glycan landscapes are interpreted by human lectins. Functional glycan-lectin interactions are difficult to profile because glycans are not genome-encoded and their changes are poorly captured by existing multimodal methods. We present two platforms, single-cell outlining and transcriptome sequencing (scGOAT-seq) and GlycoScope, which use human lectins to enable functional glycan accessibility into single-cell and spatial multiomic measurements. ScGOAT-seq quantifies lectin-accessible glycan states with gene expression, while GlycoScope enables multiplexed in situ co-detection of glycans and proteins in tissues. Applying these approaches to immune cells, we identify stimulus-specific glycan remodeling and show that distinct Siglec-ligand-defined programs stratify immune activation states not captured by traditional methods; in follicular lymphoma, GlycoScope, resolves spatial glycan programs associated with malignant B cells and localized immune microenvironments. The presented methods provide a general framework for integrating functional glycan accessibility into single-cell and spatial multiomics.

molecular biology↗

bioRxiv2024

Same-Slide Spatial Multi-Omics Integration Reveals Tumor Virus-Linked Spatial Reorganization of the Tumor Microenvironment

The advent of spatial transcriptomics and spatial proteomics have enabled profound insights into tissue organization to provide systems-level understanding of diseases. Both technologies currently remain largely independent, and emerging same slide spatial multi-omics approaches are generally limited in plex, spatial resolution, and analytical approaches. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined and resource-effective approach compatible with various spatial platforms. This iterative approach first entails single-cell spatial proteomics and rapid analysis to guide subsequent spatial transcriptomics capture on the same slide without loss in RNA signal. To enable multi-modal insights not possible with current approaches, we introduce k-bandlimited Spectral Graph Cross-Correlation (SGCC) for integrative spatial multi-omics analysis. Application of IN-DEPTH and SGCC on lymphoid tissues demonstrated precise single-cell phenotyping and cell-type specific transcriptome capture, and accurately resolved the local and global transcriptome changes associated with the cellular organization of germinal centers. We then implemented IN-DEPTH and SGCC to dissect the tumor microenvironment (TME) of Epstein-Barr Virus (EBV)-positive and EBV-negative diffuse large B-cell lymphoma (DLBCL). Our results identified a key tumor-macrophage-CD4 T-cell immunomodulatory axis differently regulated between EBV-positive and EBV-negative DLBCL, and its central role in coordinating immune dysfunction and suppression. IN-DEPTH enables scalable, resource-efficient, and comprehensive spatial multi-omics dissection of tissues to advance clinically relevant discoveries.

systems biology↗

bioRxiv2024

Evolution of cooperation in multichannel games on multiplex networks

Humans navigate diverse social relationships and concurrently interact across multiple social contexts. An individuals behavior in one context can influence behavior in other contexts. Different payoffs associated with interactions in the different domains have motivated recent studies of the evolution of cooperation through the analysis of multichannel games where each individual is simultaneously engaged in multiple repeated games. However, previous investigations have ignored the potential role of network structure in each domain and the effect of playing against distinct interacting partners in different domains. Multiplex networks provide a useful framework to represent social interactions between the same set of agents across different social contexts. We investigate the role of multiplex network structure and strategy linking in multichannel games on the spread of cooperative behavior in all layers of the multiplex. We find that multiplex structure along with strategy linking enhances the cooperation rate in all layers of the multiplex compared to a well-mixed population, provided the network structure is identical across layers. The effectiveness of strategy linking in enhancing cooperation depends on the degree of similarity of the network structure across the layers and perception errors due to imperfect memory. Higher cooperation rates are achieved when the degree of structural overlap of the different layers is sufficiently large, and the probability of perception error is relatively low. Our work reveals how the social network structure in different layers of a multiplex can affect the spread of cooperation by limiting the ability of individuals to link strategies across different social domains.

animal behavior and cognition↗

bioRxiv2024

Glycan-costumed virus-like particles promote type 1 anti-tumor immunity

Cancer vaccine development is inhibited by a lack of strategies for directing dendritic cell (DC) induction of effective tumor-specific cellular immunity. Pathogen engagement of DC lectins and toll-like receptors (TLRs) shapes immunity by directing T cell function. Strategies to activate specific DC signaling pathways via targeted receptor engagement are crucial to unlocking type 1 cellular immunity. Here, we engineered a glycan-costumed virus-like particle (VLP) vaccine that delivers programmable peptide antigens to induce tumor-specific cellular immunity in vivo. VLPs encapsulating TLR7 agonists and decorated with a selective mannose-derived ligand for the lectin DC-SIGN induced robust DC activation and type 1 cellular immunity, whereas VLPs lacking this key DC-SIGN ligand failed to promote DC-mediated immunity. Vaccination with glycan-costumed VLPs generated tumor antigen-specific Th1 CD4+ and CD8+ T cells that infiltrated solid tumors, inhibiting tumor growth in a murine melanoma model. Thus, VLPs employing lectin-driven immune reprogramming provide a framework for advancing cancer immunotherapies.

biochemistry↗

bioRxiv2022

Targeting an evolutionarily conserved "E-L-L" motif in the spike protein to develop a small molecule fusion inhibitor against SARS-CoV-2

As newer variants of SARS-CoV-2 continue to pose major threats to global human health and economy, identifying novel druggable antiviral targets is the key towards sustenance. Here, we identify an evolutionary conserved "E-L-L" motif present within the HR2 domain of all human and non-human coronavirus spike (S) proteins that play a crucial role in stabilizing the post-fusion six-helix bundle (6-HB) structure and thus, fusion-mediated viral entry. Mutations within this motif reduce the fusogenicity of the S protein without affecting its stability or membrane localization. We found that posaconazole, an FDA-approved drug, binds to this "E-L-L" motif resulting in effective inhibition of SARS-CoV-2 infection in cells. While posaconazole exhibits high efficacy towards blocking S protein-mediated viral entry, mutations within the "E-L-L" motif rendered the protein completely resistant to the drug, establishing its specificity towards this motif. Our data demonstrate that posaconazole restricts early stages of infection through specific inhibition of membrane fusion and viral genome release into the host cell and is equally effective towards all major variants of concerns of SARS-CoV-2 including beta, kappa, delta, and omicron. Together, we show that this conserved essential "E-L-L" motif is an ideal target for the development of prophylactic and therapeutic interventions against SARS-CoV-2.

biochemistry↗