Endocrine disorders have been shown to be a consequence of blast traumatic brain injury in soldiers returning from military conflicts. Hormone deficiency and adrenocorticotropic hormone (ACTH) dysfunction can lead to symptoms such as fatigue, anxiety, irritability, insomnia, sexual dysfunction, and decreased quality of life. Given these changes following blast exposure, the current study focused on investigating chronic pathology within the hypothalamus following blast, in addition to systemic effects. An established rodent model of blast neurotrauma was used to induce mild blast-induced neurotrauma. Adipose tissue, blood, and brain samples were collected at one and three months following a single blast exposure. Adipose tissue and blood were evaluated for changes in ACTH, adiponectin, C-reactive protein, glial fibrillary acidic protein, interleukin (IL)-1b, and leptin. The hypothalamus was evaluated for injury using immunohistochemical techniques. The results demonstrated that the weight of the blast animals was significantly less, compared with the sham group. The slower rate of increase in their weight was associated with changes in ACTH, IL-1b, and leptin levels. Further, histological analysis indicated elevated levels of cleaved caspase-3 positive cells within the hypothalamus. The data suggest that long-term outcomes of brain injury occurring from blast exposure include dysfunction of the hypothalamus, which leads to compromised hormonal function, elevated biological stress-related hormones, and subsequent adipose tissue remodeling.
The analytical investigation of the pharmaceutical process monitors the critical process parameters of the drug, beginning from its development until marketing and postmarketing, and appropriate corrective action can be taken to change the pharmaceutical design at any stage of the process. Advanced analytical methods, such as Raman spectroscopy, are particularly suitable for use in the field of drug analysis, especially for qualitative and quantitative work, due to the advantages of simple sample preparation, fast, nondestructive analysis speed, and effective avoidance of moisture interference. Advanced Raman imaging techniques have gradually become a powerful alternative method for monitoring changes in polymorph distribution and active pharmaceutical ingredient distribution in drug processing and pharmacokinetics. Surface-enhanced Raman spectroscopy (SERS) has also solved the inherent insensitivity and fluorescence problems of Raman, which has made good progress in the field of illegal drug analysis. This review summarizes the application of Raman spectroscopy and imaging technology, which are used in the qualitative and quantitative analysis of solid tablets, quality control of the production process, drug crystal analysis, illegal drug analysis, and monitoring of drug dissolution and release in the field of drug analysis in recent years.
Identifying cell phenotypes is essential for understanding the function of biological macromolecules and molecular biology. We developed a noninvasive, label-free, single-cell Raman imaging analysis platform to distinguish between the cell phenotypes of the HeLa cell wild type (WT) and cyclin-dependent kinase 6 (CDK6) gene knockout (KO) type. Via large-scale Raman spectral and imaging analysis, two phenotypes of the HeLa cells were distinguished by their intrinsic biochemical profiles. A significant difference was found between the two cell lines: large lipid droplets formed in the knockout HeLa cells but were not observed in the WT cells, which was confirmed by Oil Red O staining. The band ratio of the Raman spectrum of saturated/unsaturated fatty acids was identified as the Raman spectral marker for HeLa cell WT or gene knockout type differentiation. The interaction between organelles involved in lipid metabolism was revealed by Raman imaging and Lorentz fitting, where the distribution intensity of the mitochondria and the endoplasmic reticulum membrane decreased. At the same time, lysosomes increased after the CDK6 gene knockout. The parameters obtained from Raman spectroscopy are based on hierarchical cluster analysis and one-way ANOVA, enabling highly accurate cell classification.
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