MATERIALS/METHODS: The study was conducted on ten histologically proven cases of oral cancer undergoing radiotherapy. Stimulated whole saliva was collected at three stages of radiotherapy-0, 3, and 6 weeks. Salivary amylase was estimated using Henry-Chiamori method and comparison was made with appropriate age- and gender-matched controls.
RESULTS: Salivary amylase levels showed significant decrease in healthy subjects when compared to oral cancer patients (P < 0.001). The latter group also showed changing trend with initial decrease from 0 to 3 weeks followed by increase from 3 to 6 weeks following radiotherapy (P < 0.0528).
CONCLUSIONS: The trend in changes in the levels of salivary amylase could be used as a surrogate marker of salivary gland function in patients with oral cancer undergoing radiotherapy as primary treatment.
METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.
RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.
CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.
METHODS: A total of three databases were searched on September 15, 2020: PubMed, Web of Science, and Science Direct. The searches were conducted using a pre-specified search strategy to record studies reported the reproductive number of coronavirus from its inception in December 2019. It includes keywords of coronavirus and its reproductive number, which were combined using the Boolean operators (AND, OR). Based on the included studies, we estimated a summary reproductive number by using the meta-analysis. We used narrative synthesis to explain the results of the studies where the reproductive number was reported, however, were not possible to include in the meta-analysis because of the lack of data (mostly due to confidence interval was not reported).
RESULTS: Total of 42 studies included in this review whereas 29 of them were included in the meta-analysis. The estimated summary reproductive number was 2.87 (95% CI, 2.39-3.44). We found evidence of very high heterogeneity (99.5%) of the reproductive number reported in the included studies. Our sub-group analysis was found the significant variations of reproductive number across the country for which it was estimated, method and model that were used to estimate the reproductive number, number of case that was considered to estimate the reproductive number, and the type of reproductive number that was estimated. The highest reproductive number was reported for the Diamond Princess Cruise Ship in Japan (14.8). In the country-level, the higher reproductive number was reported for France (R, 6.32, 95% CI, 5.72-6.99) following Germany (R, 6.07, 95% CI, 5.51-6.69) and Spain (R, 3.56, 95% CI, 1.62-7.82). The higher reproductive number was reported if it was estimated by using the Markov Chain Monte Carlo method (MCMC) method and the Epidemic curve model. We also reported significant heterogeneity of the type of reproductive number- a high-value reported if it was the time-dependent reproductive number.
CONCLUSION: The estimated summary reproductive number indicates an exponential increase of coronavirus infection in the coming days. Comprehensive policies and programs are important to reduce new infections as well as the associated adverse consequences including death.
RESULTS: We show that Rasd1 is expressed in vasopressin neurons of the PVN and SON, within which mRNA levels are induced by hyperosmotic cues. Dexamethasone treatment of AtT20 cells decreased forskolin stimulation of c-Fos, Nr4a1 and phosphorylated CREB expression, effects that were mimicked by overexpression of Rasd1, and inhibited by knockdown of Rasd1. These effects were dependent upon isoprenylation, as both farnesyltransferase inhibitor FTI-277 and CAAX box deletion prevented Rasd1 inhibition of cAMP-induced gene expression. Injection of lentiviral vector into rat SON expressing Rasd1 diminished, whereas CAAX mutant increased, cAMP inducible genes in response to osmotic stress.
CONCLUSIONS: We have identified two mechanisms of Rasd1 induction in the hypothalamus, one by elevated glucocorticoids in response to stress, and one in response to increased plasma osmolality resulting from osmotic stress. We propose that the abundance of RASD1 in vasopressin expressing neurons, based on its inhibitory actions on CREB phosphorylation, is an important mechanism for controlling the transcriptional responses to stressors in both the PVN and SON. These effects likely occur through modulation of cAMP-PKA-CREB signaling pathway in the brain.