Adding our leaves: A communityâ wide perspective on research directions in ecohydrology

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154539/1/hyp13693.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154539/2/hyp13693_am.pd

Resolving phytoplankton pigments from spectral images using convolutional neural networks

Motivated by the need for rapid and robust monitoring of phytoplankton in inland waters, this article introduces a protocol based on a mobile spectral imager for assessing phytoplankton pigments from water samples. The protocol includes (1) sample concentrating; (2) spectral imaging; and (3) convolutional neural networks (CNNs) to resolve concentrations of chlorophyll a (Chl a), carotenoids, and phycocyanin. The protocol was demonstrated with samples from 20 lakes across Scotland, with special emphasis on Loch Leven where blooms of cyanobacteria are frequent. In parallel, samples were prepared for reference observations of Chl a and carotenoids by high-performance liquid chromatography and of phycocyanin by spectrophotometry. Robustness of the CNNs were investigated by excluding each lake from model trainings one at a time and using the excluded data as independent test data. For Loch Leven, median absolute percentage difference (MAPD) was 15% for Chl a and 36% for carotenoids. MAPD in estimated phycocyanin concentration was high (102%); however, the system was able to indicate the possibility of a cyanobacteria bloom. In the leave-one-out tests with the other lakes, MAPD was 26% for Chl a, 27% for carotenoids, and 75% for phycocyanin. The higher error for phycocyanin was likely due to variation in the data distribution and reference observations. It was concluded that this protocol could support phytoplankton monitoring by using Chl a and carotenoids as proxies for biomass. Greater focus on the distribution and volume of the training data would improve the phycocyanin estimates

Cross-trait analyses with migraine reveal widespread pleiotropy and suggest a vascular component to migraine headache

Background: Nearly a fifth of the world's population suffer from migraine headache, yet risk factors for this disease are poorly characterized. Methods: To further elucidate these factors, we conducted a genetic correlation analysis using cross-trait linkage disequilibrium (LD) score regression between migraine headache and 47 traits from the UK Biobank. We then tested for possible causality between these phenotypes and migraine, using Mendelian randomization. In addition, we attempted replication of our findings in an independent genome-wide association study (GWAS) when available. Results: We report multiple phenotypes with genetic correlation (P < 1.06 × 10-3) with migraine, including heart disease, type 2 diabetes, lipid levels, blood pressure, autoimmune and psychiatric phenotypes. In particular, we find evidence that blood pressure directly contributes to migraine and explains a previously suggested causal relationship between calcium and migraine. Conclusions: This is the largest genetic correlation analysis of migraine headache to date, both in terms of migraine GWAS sample size and the number of phenotypes tested. We find that migraine has a shared genetic basis with a large number of traits, indicating pervasive pleiotropy at migraine-associated loci.Peer reviewe

Embigin is a fibronectin receptor that affects sebaceous gland differentiation and metabolism

Stem cell renewal and differentiation are regulated by interactions with the niche. Although multiple cell populations have been identified in distinct anatomical compartments, little is known about niche-specific molecular factors. Using skin as a model system and combining single-cell RNA-seq data analysis, immunofluorescence, and transgenic mouse models, we show that the transmembrane protein embigin is specifically expressed in the sebaceous gland and that the number of embigin-expressing cells is negatively regulated by Wnt. The loss of embigin promotes exit from the progenitor compartment and progression toward differentiation, and also compromises lipid metabolism. Embigin modulates sebaceous niche architecture by affecting extracellular matrix organization and basolateral targeting of monocarboxylate transport. We discover through ligand screening that embigin is a direct fibronectin receptor, binding to the N-terminal fibronectin domain without impairing integrin function. Our results solve the long-standing question of how embigin regulates cell adhesion and demonstrate a mechanism that couples adhesion and metabolism.</p

A functional alternative splicing mutation in human tryptophan hydroxylase-2

The brain serotonergic system has an essential role in the physiological functions of the central nervous system and dysregulation of serotonin (5-HT) homeostasis has been implicated in many neuropsychiatric disorders. The tryptophan hydroxylase-2 (TPH2) gene is the rate-limiting enzyme in brain 5-HT synthesis, and thus is an ideal candidate gene for understanding the role of dysregulation of brain serotonergic homeostasis. Here, we characterized a common, but functional single-nucleotide polymorphism (SNP rs1386493) in the TPH2 gene, which decreases efficiency of normal RNA splicing, resulting in a truncated TPH2 protein (TPH2-TR) by alternative splicing. TPH2-TR, which lacks TPH2 enzyme activity, dominant-negatively affects full-length TPH2 function, causing reduced 5-HT production. The predicted mRNA for TPH2-TR is present in postmortem brain of rs1386493 carriers. The rs13864923 variant does not appear to be overrepresented in either global or multiplex depression cohorts. However, in combination with other gene variants linked to 5-HT homeostasis, this variant may exhibit important epistatic influences

Cerebral small vessel disease genomics and its implications across the lifespan

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

A rare case of peri-implant distal radius fracture

A peri-implant fracture near the volar plate of distal radius represent a very rare injury. The main factor of this lesion is high energy trauma on the wrist. We report a case of a 61-year-old woman with a peri-implant fracture located just proximally to the plate and a fracture of the ulnar head that occurred after a simple fall. The patient was surgically treated by plate and screws removal. The fracture was fixed using a longer volar plate for the radial fracture and a plate for the head ulnar fracture. Different factors such as osteoporosis, BMI and screw position could influence the fracture pattern. However, considering growing use of plates for distal radius fracture fixation, the frequency of these kind of fracture will probably increase