The Role of Ca2+/Calmodulin Dependent Protein Kinase II, CaMK-II, in Kidney Morphogenesis

Autosomal dominant polycystic kidney disease (ADPKD) is one of the most common heritable diseases in the world, characterized by the development of large fluid filled cyst. Treatments for this disease are limited due to a lack of understanding of disease pathogenesis. Ca2+/calmodulin dependent protein kinase II (CaMK-II) is necessary for kidney morphogenesis in zebrafish as well as being a downstream effector of pkd2, one of the genes most commonly mutated in ADPKD patients. The roles of CaMK-II during zebrafish kidney development include regulation of kidney cell migration as well as cloacal cilia stability. The influence of CaMK-II on these pathways is partially dependent on its regulation of HDAC4 localization. Inhibition of CaMK-II caused the translocation of HDAC4 from the cytosol to the nucleus, leading to the model that CaMK-II activation via PKD2 retains HDAC4 in the cytosol allowing for transcription of its target genes. Further studies attempted with a zebrafish camk2g1 mutant proved inconclusive as mutants displayed none of the phenotypic defects seen in morphant embryos. Analysis of CaMK-II gene expression in camk2g1 mutants identified the capability of genetic compensation between CaMK-II family members. In camk2g1 mutants, the paralog gene camk2g2 is upregulated over 3 fold, compensating for the loss of its paralog gene. In conclusion, this study has furthered the understanding of the roles of CaMK-II during kidney development and demonstrated the ability of CaMK-II family members to compensate for one other. In addition, this study also further validates the uses of knockdown methods in developmental studies

Testing general relativity with accretion onto compact objects

The X-ray emission of neutron stars and black holes presents a rich phenomenology that can lead us to a better understanding of their nature and to address more general physics questions: Does general relativity apply in the strong gravity regime? Is spacetime around black holes described by the Kerr metric? This white paper considers how we can investigate these questions by studying reverberation mapping and quasi-periodic oscillations in accreting systems with a combination of high-spectral and high-timing resolution. In the near future, we will be able to study compact objects in the X-rays in a new way: advancements in transition-edge sensors (TES) technology will allow for electron-volt-resolution spectroscopy combined with nanoseconds-precision timing.Comment: White paper submitted for Astro2020 Decadal Survey. 8 pages, 2 figure

Do western Atlantic bluefin tuna spawn outside of the Gulf of Mexico? Results from a larval survey in the Atlantic Ocean in 2013

In 2013, a larval survey was conducted north and east of the Bahamas aboard the NOAA Ship NANCY FOSTER. Sampling areas were selected based on larval habitat model predictions, and daily satellite analysis of surface temperature and ocean color. Samples were collected at 97 stations, and 18 larval BFT (Thunnus thynnus) were found at 9 stations. Six of these stations came from oceanographically complex regions characterized by cyclonic and anticyclonic gyres. Larvae ranged in size from 3.22mm to 7.58 mm, corresponding to approximately 5-12 days in age. Analysis of satellite derived surface currents and CTD data suggest that these larvae were spawned and retained in this area. Larval habitat models show areas of high predicted abundance extending east to 650 W, but the actual extent of spawning in this area remains unknown.En prens

Metformin improves healthspan and lifespan in mice

Metformin is a drug commonly prescribed to treat patients with type 2 diabetes. Here we show that long-term treatment with metformin (0.1% w/w in diet) starting at middle age extends healthspan and lifespan in male mice, while a higher dose (1% w/w) was toxic. Treatment with metformin mimics some of the benefits of calorie restriction, such as improved physical performance, increased insulin sensitivity, and reduced LDL and cholesterol levels without a decrease in caloric intake. At a molecular level, metformin increases AMP-activated protein kinase activity and increases antioxidant protection, resulting in reductions in both oxidative damage accumulation and chronic inflammation. Our results indicate that these actions may contribute to the beneficial effects of metformin on healthspan and lifespan. These findings are in agreement with current epidemiological data and raise the possibility of metformin-based interventions to promote healthy aging

AGEMAP: A Gene Expression Database for Aging in Mice

We present the AGEMAP (Atlas of Gene Expression in Mouse Aging Project) gene expression database, which is a resource that catalogs changes in gene expression as a function of age in mice. The AGEMAP database includes expression changes for 8,932 genes in 16 tissues as a function of age. We found great heterogeneity in the amount of transcriptional changes with age in different tissues. Some tissues displayed large transcriptional differences in old mice, suggesting that these tissues may contribute strongly to organismal decline. Other tissues showed few or no changes in expression with age, indicating strong levels of homeostasis throughout life. Based on the pattern of age-related transcriptional changes, we found that tissues could be classified into one of three aging processes: (1) a pattern common to neural tissues, (2) a pattern for vascular tissues, and (3) a pattern for steroid-responsive tissues. We observed that different tissues age in a coordinated fashion in individual mice, such that certain mice exhibit rapid aging, whereas others exhibit slow aging for multiple tissues. Finally, we compared the transcriptional profiles for aging in mice to those from humans, flies, and worms. We found that genes involved in the electron transport chain show common age regulation in all four species, indicating that these genes may be exceptionally good markers of aging. However, we saw no overall correlation of age regulation between mice and humans, suggesting that aging processes in mice and humans may be fundamentally different

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan. [Abstract copyright: © 2022 The Authors.