Biomedical subjects

Archana Singh

Publications and source records attributed to Archana Singh.

4 recordsLinked to original sources

PubMed2026

Glycaemic burden disrupts innate immunity in TB by modulating CD206 expression and macrophage antimicrobial responses.

Tuberculosis (TB) and diabetes mellitus (DM) represent a growing dual global health burden, with chronic hyperglycaemia recognized as a major modifier of host immunity against Mycobacterium tuberculosis (Mtb). Macrophages, central to pathogen recognition, phagocytosis, antigen presentation, and intracellular killing, may be particularly vulnerable to diabetic metabolic dysregulation. This study evaluated phenotypic and functional macrophage alterations in individuals with pulmonary TB, type 2 DM, TB-DM comorbidity, and healthy controls. Surface receptor expression was analysed by multicolour flow cytometry, while phagocytosis and intracellular bacterial clearance were assessed using FITC-labelled Mtb assays and colony-forming unit enumeration. Hyperglycaemia was associated with reduced CD11b, MARCO, and TLR2 expression alongside upregulation of the mannose receptor CD206, which correlated positively with HbA1c levels, indicating a shift toward a permissive M2-like phenotype. Phagocytic uptake of Mtb was significantly impaired and inversely correlated with HbA1c. Antigen-presenting capacity was selectively compromised, with reduced CD80 and CD86 expression in DM and TB-DM groups, while HLA-DR remained unchanged. Intracellular Mtb killing was markedly diminished in diabetic macrophages. These findings demonstrate that chronic hyperglycaemia profoundly disrupts macrophage innate immunity, contributing to increased TB susceptibility and poor infection control in diabetic populations.

Humans↗

PubMed2006

Single-copy genes define a conserved order between rice and wheat for understanding differences caused by duplication, deletion, and transposition of genes.

The high-quality rice genome sequence is serving as a reference for comparative genome analysis in crop plants, especially cereals. However, early comparisons with bread wheat showed complex patterns of conserved synteny (gene content) and colinearity (gene order). Here, we show the presence of ancient duplicated segments in the progenitor of wheat, which were first identified in the rice genome. We also show that single-copy (SC) rice genes, those representing unique matches with wheat expressed sequence tag (EST) unigene contigs in the whole rice genome, show more than twice the proportion of genes mapping to syntenic wheat chromosome as compared to the multicopy (MC) or duplicated rice genes. While 58.7% of the 1,244 mapped SC rice genes were located in single syntenic wheat chromosome groups, the remaining 41.3% were distributed randomly to the other six non-syntenic wheat groups. This could only be explained by a background dispersal of genes in the genome through transposition or other unknown mechanism. The breakdown of rice-wheat synteny due to such transpositions was much greater near the wheat centromeres. Furthermore, the SC rice genes revealed a conserved primordial gene order that gives clues to the origin of rice and wheat chromosomes from a common ancestor through polyploidy, aneuploidy, centromeric fusions, and translocations. Apart from the bin-mapped wheat EST contigs, we also compared 56,298 predicted rice genes with 39,813 wheat EST contigs assembled from 409,765 EST sequences and identified 7,241 SC rice gene homologs of wheat. Based on the conserved colinearity of 1,063 mapped SC rice genes across the bins of individual wheat chromosomes, we predicted the wheat bin location of 6,178 unmapped SC rice gene homologs and validated the location of 213 of these in the telomeric bins of 21 wheat chromosomes with 35.4% initial success. This opens up the possibility of directed mapping of a large number of conserved SC rice gene homologs in wheat. Overall, only 46.4% of these SC genes code for proteins with known functional domains; the remaining 53.6% have unknown function, and hence, represent an important, but yet, under explored category of genes.

Gene Deletion↗

PubMed2005

Virtual 10-20 measurement on MR images for inter-modal linking of transcranial and tomographic neuroimaging methods.

It is important to create a link between stereotaxic coordinates and head-surface-based positioning systems in order to share data between tomographic and transcranial brain mapping studies. In our previous studies, we established the probabilistic correspondence of the international 10-20 positions to the standard stereotaxic coordinate systems and made a reference database. However, its expansion required the physical marking of the 10-20 positions and the subsequent acquisition of MR images. To avoid such tedious procedures, we developed a virtual 10-20 measurement algorithm that can be applied to re-analyze any structural MR image that covers the whole head. As in the physical 10-20 measurements, with the reference points given, the algorithm automatically determines each 10-20 position step by step. Using the virtual 10-20 measurement method, we re-analyzed the MR images of 17 healthy subjects for whom we had determined 10-20 positions by physical marking in our previous study. The acquired 10-20 positions were normalized to the Montreal Neurological Institute (MNI) stereotactic coordinates and compared with the positions previously determined by physical measurements. 10-20 positions determined using the virtual and physical methods were roughly consistent. Average standard deviations for virtual and physical methods were 7.7 mm and 9.0 mm, respectively. There was a systematic shift in the virtual method, likely due to the absence of hair interference. We corrected the shift with affine transformation. The virtual 10-20 measurement method proved to be an effective alternative to physical marking. This method will serve as an essential tool for expanding the reference database and will further strengthen the link between tomographic and transcranial brain mapping methods.

Adult↗

PubMed2004

Sequence analysis of the long arm of rice chromosome 11 for rice-wheat synteny.

The DNA sequence of 106 BAC/PAC clones in the minimum tiling path (MTP) of the long arm of rice chromosome 11, between map positions 57.3 and 116.2 cM, has been assembled to phase 2 or PLN level. This region has been sequenced to 10x redundancy by the Indian Initiative for Rice Genome Sequencing (IIRGS) and is now publicly available in GenBank. The region, excluding overlaps, has been predicted to contain 2,932 genes using different software. A gene-by-gene BLASTN search of the NCBI wheat EST database of over 420,000 cDNA sequences revealed that 1,143 of the predicted rice genes (38.9%) have significant homology to wheat ESTs (bit score >/= 100). Further BLASTN search of these 1,143 rice genes with the GrainGenes database of sequence contigs containing bin-mapped wheat ESTs allowed 113 of the genes to be placed in bins located on wheat chromosomes of different homoeologous groups. The largest number of genes, about one-third, mapped to the homoeologous group 4 chromosomes of wheat, suggesting a common evolutionary origin. The remaining genes were located on wheat chromosomes of different groups with significantly higher numbers for groups 3 and 5. Location of bin-mapped wheat contigs to chromosomes of all the seven homoeologous groups can be ascribed to movement of genes (transpositions) or chromosome segments (translocations) within rice or the hexaploid wheat genomes. Alternatively, it could be due to ancient duplications in the common ancestral genome of wheat and rice followed by selective elimination of genes in the wheat and rice genomes. While there exists definite conservation of gene sequences and the ancestral chromosomal identity between rice and wheat, there is no obvious conservation of the gene order at this level of resolution. Lack of extensive colinearity between rice and wheat genomes suggests that there have been many insertions, deletions, duplications and translocations that make the synteny comparisons much more complicated than earlier thought. However, enhanced resolution of comparative sequence analysis may reveal smaller conserved regions of colinearity, which will facilitate selection of markers for saturation mapping and sequencing of the gene-rich regions of the wheat genome.

Base Sequence↗