Biology subjects

Baliyan, A.

Publications and source records attributed to Baliyan, A..

3 recordsLinked to original sources

bioRxiv2026

Structural insights into the inhibition of sickle hemoglobin polymerization by asymmetric hemoglobin tetramer HbFS (α2γβS)

Sickle cell disease (SCD) is caused by a single amino acid substitution in the {beta}S globin chain at 6th position (6E[->]V). This results in polymerization of deoxy state of sickle hemoglobin (HbS), followed by its precipitation and subsequent sickling of erythrocytes. These deformed cells can block small capillaries (vaso-occlusion), causing cardiovascular complications, ultimately leading to ischemia-reperfusion injury, severe oxygen deficiency, and progressive systemic damage. Occasionally, patients with SCD have been observed to produce exorbitantly high levels of fetal hemoglobin (HbF), which has been linked with the inhibition of HbS polymerization. One of the effects of hydroxyurea, the most commonly used therapeutic for SCD, is to elevate HbF levels. However, the mechanism of inhibitory role of HbF on HbS polymerization is largely unknown. This study attempts to gain insights into the mechanisms involved in this process by means of native mass spectrometry, ion mobility mass spectrometry, and hydrogen deuterium exchange-based mass spectrometry (H/DX-MS). The conformational flexibility of asymmetric hemoglobin, HbFS (2{gamma}{beta}S), for the observed regions in the tetrameric molecule appears to be more in the deoxy state as compared to the oxy state, eventually leading to reduced polymerization of sickle hemoglobin in patients with SCD that express elevated HbF levels.

biochemistry↗

bioRxiv2025

MitoXRNet: Deep Learning-enabled 3D Segmentation of Mitochondria and Nucleus in Soft X-ray Tomograms

Mitochondrial morphology is crucial for cellular function, but large-scale analysis is limited by challenges in high-resolution imaging and segmentation. MitoXRNet, a compact 3D deep-learning model, efficiently segments mitochondria and nuclei from Soft X-ray Tomography data using multi-axis slicing, Sobel-based boundary enhancement, and combined BCE-Robust Dice loss. With 1.4M parameters, it achieves a Dice score of 73.8% on INS-1E cells, outperforming existing models. Automated analysis indicated that glucose induced larger mitochondria and higher matrix density, and that GIP and GKA induced smaller and denser mitochondria, highlighting previously unreported {beta}-cell mitochondrial remodeling. MitoXRNet allows for scalable profiling of organelle-level morpho-biophysical data. HighlightsO_LIA data-efficient method for 3D segmentation of mitochondria and nucleus from Soft X-ray tomograms. C_LIO_LIIncorporates domain-specific Sobel filter-based preprocessing to improve segmentation accuracy and quality under imperfect or noisy labels. C_LIO_LIEnables rapid and automated analysis of mitochondrial morphology, facilitating quantitative assessment of pharmacological effects on cellular ultrastructure. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/682919v2_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@8600f6org.highwire.dtl.DTLVardef@1a9230eorg.highwire.dtl.DTLVardef@13c6f09org.highwire.dtl.DTLVardef@9dc9f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Spatial differentiation of proteome in cervical cancer tissues using Imaging Mass Spectrometry

Cervical cancer, which is the fourth most common gynaecological cancer across the globe, has a poorly understood molecular pathogenesis and etiology. Current methods of diagnosis are based on cytology, histology and presence of Human Papillomavirus (HPV). Shortcomings of these methods lie with poor quality of smears which is very common in Papanicolaou (pap) smears, limited sensitivity in terms of early detection, dependence on presence of HPV, etc. Due to its high sensitivity and non-targeted approach, Matrix Assisted Laser Desorption Ionization based Imaging Mass Spectrometry (MALDI-IMS) might be advantageous to understand the pathogenesis, molecular mechanism, precise identification of surgical margins and identification of novel biomarkers. Since it can also identify proteins in the extracellular matrix, it is especially beneficial for the tissue types with sparse cells and excessive extracellular matrix. Although tissue proteome profiling for cervical cancer were reported, the heterogeneous distribution of proteins across cervical cancer tissues havent been explored. In this study, we employed a non-targeted MALDI-IMS based approach to profile the spatial distribution of proteins within cervical cancer tissues. We observed overexpression of Keratin 5 and Prelamin A/C in the region of cervical cancer tissues which were categorically labelled with cancerous morphology using histopathological examination. Both these proteins have been earlier associated with progression and aggressiveness of other cancers like breast and prostate cancers. However, no such reports are available for cervical cancer. Further studies are required on a large dataset to validate and quantitate these proteins as biomarkers for early diagnosis and prognosis of cervical cancer.

cancer biology↗