Oral Findings in Postmenopausal Women Attending Dental Hospital in Western Part of India

Objectives: To know the nature, incidence and severity of oral manifestations occurring in postmenopausal women. Study design: Oral changes were observed in 365 postmenopausal women and 365 age matched male individuals attending the department of Oral Medicine and Radiology. The patients were asked about complaints of dry mouth, taste and breath changes, mucosal and facial pain and were examined for oral changes such as ulceration, white and red lesions. The results obtained from the study were then correlated with various other similar studies. Results: The important oral findings in postmenopausal women were mucosal burning/pain (25.8%), dry mouth (27.1%), altered taste (3.6%), altered breath (6.3%) and facial pain (3.6%). Oral submucous fibrosis (OSMF) was significantly more common in males (5.5%) as compared to postmenopausal females (1.9%). Conclusion: Results from the present study reveal that oral symptoms are common problems in postmenopausal women. Postmenopausal patients showed significantly more oral changes than the control. These changes could be related to the hormone alterations. Therefore, dentists need to refer postmenopausal women with oral symptoms to a gynaecologist for more careful examinations and medical interventions if necessary

Livestock disease risk forewarning bulletin October 2022

Not AvailableThis bulletin forecasts the livestock diseases two months in advance for the benefit of the livestock farmers and state animal husbandry departments.Not Availabl

Not Available

Not AvailableThe livestock diseases forewarning bulletin will forecast the occurrence of the livestock diseases at district level in advance of two months to take necessary preventive measures by the State Animal Husbandry Departments in India.Not Availabl

Research Article A New Informatics Framework for Evaluating the Codon Usage Metrics, Evolutionary Models and Phylogeographic Reconstruction of Tomato Yellow Leaf Curl Virus (TYLCV) in Different Regions of Asian Countries

Not AvailableTomato yellow leaf curl virus (TYLCV) is a major devastating viral disease, majorly affecting the tomato production globally. The disease is majorly transmitted by the Whitefly. The Begomovirus (TYLCV) having a six major protein coding genes, among them the C1/AC1 is evidently associated with viral replication. Owing to immense role of C1/AC1 gene, the present study is an initial effort to elucidate the factors shaping the codon usage bias and evolutionary pattern of TYLCV-C1/AC1 gene in five major Asian countries. Based on publicly available nucleotide sequence data the Codon usage pattern, Evolutionary and Phylogeographic reconstruction was carried out. The study revealed the presence of significant variation between the codon bias indices in all the selected regions. Implying that the codon usage pattern indices (eNC, CAI, RCDI, GRAVY, Aromo) are seriously affected by selection and mutational pressure, taking a supremacy in shaping the codon usage bias of viral gene. Further, the tMRCA age was 1853, 1939, 1855, 1944, 1828 for China, India, Iran, Oman and South Korea, respectively for TYLCV-C1/AC1 gene. The integrated analysis of Codon usage bias, Evolutionary rate and Phylogeography analysis in viruses signifies the positive role of selection and mutational pressure among the selected regions for TYLCV (C1/AC1) gene.Not Availabl

A statistical framework for genetic association studies of power curves in bird flight

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution

3D extracellular matrix microenvironment in bioengineered tissue models of primary pediatric and adult brain tumors.

Dynamic alterations in the unique brain extracellular matrix (ECM) are involved in malignant brain tumors. Yet studies of brain ECM roles in tumor cell behavior have been difficult due to lack of access to the human brain. We present a tunable 3D bioengineered brain tissue platform by integrating microenvironmental cues of native brain-derived ECMs and live imaging to systematically evaluate patient-derived brain tumor responses. Using pediatric ependymoma and adult glioblastoma as examples, the 3D brain ECM-containing microenvironment with a balance of cell-cell and cell-matrix interactions supports distinctive phenotypes associated with tumor type-specific and ECM-dependent patterns in the tumor cells\u27 transcriptomic and release profiles. Label-free metabolic imaging of the composite model structure identifies metabolically distinct sub-populations within a tumor type and captures extracellular lipid-containing droplets with potential implications in drug response. The versatile bioengineered 3D tumor tissue system sets the stage for mechanistic studies deciphering microenvironmental role in brain tumor progression

Microstructural and Mössbauer properties of low temperature synthesized Ni-Cd-Al ferrite nanoparticles

We report the influence of Al3+ doping on the microstructural and Mössbauer properties of ferrite nanoparticles of basic composition Ni0.2Cd0.3Fe2.5 - xAlxO4 (0.0 ≤ x ≤ 0.5) prepared through simple sol-gel method. X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray, transmission electron microscopy (TEM), Fourier transformation infrared (FTIR), and Mössbauer spectroscopy techniques were used to investigate the structural, chemical, and Mössbauer properties of the grown nanoparticles. XRD results confirm that all the samples are single-phase cubic spinel in structure excluding the presence of any secondary phase corresponding to any structure. SEM micrographs show the synthesized nanoparticles are agglomerated but spherical in shape. The average crystallite size of the grown nanoparticles was calculated through Scherrer formula and confirmed by TEM and was found between 2 and 8 nm (± 1). FTIR results show the presence of two vibrational bands corresponding to tetrahedral and octahedral sites. Mössbauer spectroscopy shows that all the samples exhibit superparamagnetism, and the quadrupole interaction increases with the substitution of Al3+ ions

Differential Producibility Analysis (DPA) of Transcriptomic Data with Metabolic Networks: Deconstructing the Metabolic Response of M. tuberculosis

A general paucity of knowledge about the metabolic state of Mycobacterium tuberculosis within the host environment is a major factor impeding development of novel drugs against tuberculosis. Current experimental methods do not allow direct determination of the global metabolic state of a bacterial pathogen in vivo, but the transcriptional activity of all encoded genes has been investigated in numerous microarray studies. We describe a novel algorithm, Differential Producibility Analysis (DPA) that uses a metabolic network to extract metabolic signals from transcriptome data. The method utilizes Flux Balance Analysis (FBA) to identify the set of genes that affect the ability to produce each metabolite in the network. Subsequently, Rank Product Analysis is used to identify those metabolites predicted to be most affected by a transcriptional signal. We first apply DPA to investigate the metabolic response of E. coli to both anaerobic growth and inactivation of the FNR global regulator. DPA successfully extracts metabolic signals that correspond to experimental data and provides novel metabolic insights. We next apply DPA to investigate the metabolic response of M. tuberculosis to the macrophage environment, human sputum and a range of in vitro environmental perturbations. The analysis revealed a previously unrecognized feature of the response of M. tuberculosis to the macrophage environment: a down-regulation of genes influencing metabolites in central metabolism and concomitant up-regulation of genes that influence synthesis of cell wall components and virulence factors. DPA suggests that a significant feature of the response of the tubercle bacillus to the intracellular environment is a channeling of resources towards remodeling of its cell envelope, possibly in preparation for attack by host defenses. DPA may be used to unravel the mechanisms of virulence and persistence of M. tuberculosis and other pathogens and may have general application for extracting metabolic signals from other “-omics” data

A Role for the Unfolded Protein Response (UPR) in Virulence and Antifungal Susceptibility in Aspergillus fumigatus

Filamentous fungi rely heavily on the secretory pathway, both for the delivery of cell wall components to the hyphal tip and the production and secretion of extracellular hydrolytic enzymes needed to support growth on polymeric substrates. Increased demand on the secretory system exerts stress on the endoplasmic reticulum (ER), which is countered by the activation of a coordinated stress response pathway termed the unfolded protein response (UPR). To determine the contribution of the UPR to the growth and virulence of the filamentous fungal pathogen Aspergillus fumigatus, we disrupted the hacA gene, encoding the major transcriptional regulator of the UPR. The ΔhacA mutant was unable to activate the UPR in response to ER stress and was hypersensitive to agents that disrupt ER homeostasis or the cell wall. Failure to induce the UPR did not affect radial growth on rich medium at 37°C, but cell wall integrity was disrupted at 45°C, resulting in a dramatic loss in viability. The ΔhacA mutant displayed a reduced capacity for protease secretion and was growth-impaired when challenged to assimilate nutrients from complex substrates. In addition, the ΔhacA mutant exhibited increased susceptibility to current antifungal agents that disrupt the membrane or cell wall and had attenuated virulence in multiple mouse models of invasive aspergillosis. These results demonstrate the importance of ER homeostasis to the growth and virulence of A. fumigatus and suggest that targeting the UPR, either alone or in combination with other antifungal drugs, would be an effective antifungal strategy