Biology subjects

Shakya, B. R.

Publications and source records attributed to Shakya, B. R..

3 recordsLinked to original sources

bioRxiv2025

Characterization of calcifications in posterior horn of human meniscus using micro-computed tomography

ObjectiveMeniscal calcifications are associated with meniscal degeneration and osteoarthritis (OA). We investigated micro-computed tomography ({micro}CT) imaging for identification of calcification patterns caused by basic calcium phosphate (BCP) and calcium pyrophosphate (CPP). DesignPosterior horns of human medial and lateral menisci from 19 individuals with medial compartment knee OA and 21 deceased donors were imaged with high-resolution {micro}CT. Raman spectroscopy characterized the calcification types from histological sections, adjacent to {micro}CT piece. Qualitative and quantitative analysis, visualization, and grading were performed using 3D {micro}CT images of meniscal calcifications. ResultsDifferent calcification patterns were observed with BCP and CPP. BCP was found at the borders of meniscal tissue and inside complex tears or fibrillation. In contrast, CPP accumulated as circumferential rod-like structures between collagen bundles, mainly inside the meniscal tissue, and lacked the porous 3D structure observed in BCP calcifications. Quantitatively, CPP samples had a higher calcification volume compared to BCP with a geometric mean ratio of 14 (95%CI; 3,73), and larger particle sizes with a ratio of 7 (95%CI; 2,8). Additionally, BCP calcifications had an organized porous structure with a closed porosity range of 6-19, while a similar structure was not seen in CPPs (range 1-3.5). ConclusionsWe qualitatively and quantitatively identified volumetric and morphological differences in the calcification deposition patterns between BCP and CPP calcifications in human meniscus. The calculated differences may help distinguish the calcification types with in vivo imaging modalities in the future, as well as provide a better understanding of their role in OA.

bioengineering↗

bioRxiv2025

Characterizing meniscal calcifications with photon counting-based dual-energy computed tomography

Meniscal calcifications are associated with meniscal degeneration and osteoarthritis (OA). However, differentiating between calcification types, such as basic calcium phosphate (BCP) and calcium pyrophosphate (CPP), remains challenging in vivo. Therefore, assessing new imaging possibilities is crucial in understanding the calcification pathologies and their relationship with OA. This study investigated dual-energy computed tomography combined with a photon counting detector (PCD-DECT) to identify calcifications in human meniscal samples ex vivo, using Raman spectroscopy as reference. 82 meniscus samples from 41 donors were imaged using PCD-DECT at 120kVp. Data were collected in two energy bins (20-50keV and 50-120keV) with an isotropic resolution of 37{micro}m. Raman spectroscopy was used to classify the calcifications as BCP or CPP. Among 82 samples, Raman spectroscopy identified 36 samples with only either BCP or CPP calcifications, that were included in the subsequent analysis. Regression models were used to compare the dual-energy index (DEI) and to assess the low energy values for corresponding high energy values between calcification types. The highest difference observed between BCP and CPP in comparison of low energy values for corresponding high energy values was 166HU (95%CI: 73, 259) at high energy value of 500HU and the difference between DEI values was 0.035 (95%CI: 0.011, 0.059), suggesting a potential difference in the measured parameters of calcification types. To conclude, PCD-DECT allowed the measurement of BCP and CPP calcifications ex vivo, offering new potential in vivo applications in the future, which could help understand calcification processes and evaluate the efficacy of disease-modifying drugs targeting calcification inhibition.

bioengineering↗

bioRxiv2020

Discrimination of melanoma cell lines with Fourier Transform Infrared (FTIR) spectroscopy

Among skin cancers, melanoma is the lethal form and the leading cause of death in humans. Melanoma begins in melanocytes and is curable at early stages. Thus, early detection and evaluation of its metastatic potential are crucial for effective clinical intervention. Fourier transform infrared (FTIR) spectroscopy has gained considerable attention due to its versatility in detecting biochemical and biological features present in the samples. Changes in these features are used to differentiate between samples at different stages of the disease. Previously, FTIR spectroscopy has been mostly used to distinguish between healthy and diseased conditions. With this study, we aim to discriminate between different melanoma cell lines based on their FTIR spectra. Formalin-fixed paraffin embedded samples from three melanoma cell lines (IPC-298, SK-MEL-30 and COLO-800) were used. Statistically significant differences were observed in the prominent spectral bands of three cell lines along with shifts in peak positions. A partial least square discriminant analysis (PLS-DA) model built for the classification of three cell lines showed an overall accuracy of 92.6% with a sensitivity of 85%, 95.75%, 96.54%, and specificity of 97.80%, 92.14%, 98.64% for the differentiation of IPC-298, SK-MEL-30, and COLO-800, respectively. The results suggest that FTIR spectroscopy can differentiate between different melanoma cell lines and thus potentially characterize the metastatic potential of melanoma. Sources of FundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

bioinformatics↗