DACC Resting State Functional Connectivity as a Predictor of Pain Symptoms Following Motor Vehicle Crash: A Preliminary Investigation

There is significant heterogeneity in pain outcomes following motor vehicle crashes (MVCs), such that a sizeable portion of individuals develop symptoms of chronic pain months after injury while others recover. Despite variable outcomes, the pathogenesis of chronic pain is currently unclear. Previous neuroimaging work implicates the dorsal anterior cingulate cortex (dACC) in adaptive control of pain, while prior resting state functional magnetic resonance imaging studies find increased functional connectivity (FC) between the dACC and regions involved in pain processing in those with chronic pain. Hyper-connectivity of the dACC to regions that mediate pain response may therefore relate to pain severity. The present study completed rsfMRI scans on N=22 survivors of MVCs collected within two weeks of the incident to test whole-brain dACC-FC as a predictor of pain severity six months later. At two weeks, pain symptoms were predicted by positive connectivity between the dACC and the premotor cortex. Controlling for pain symptoms at two weeks, pain symptoms at six months were predicted by negative connectivity between the dACC and the precuneus. Previous research implicates the precuneus in the individual subjective awareness of pain. Given a relatively small sample size, approximately half of which did not experience chronic pain at six months, findings warrant replication. Nevertheless, this study provides preliminary evidence of enhanced dACC connectivity with motor regions and decreased connectivity with pain processing regions as immediate and prospective predictors of pain following MVC. Perspective: This article presents evidence of distinct neural vulnerabilities that predict chronic pain in motor vehicle crash survivors based on whole-brain connectivity with the dorsal anterior cingulate cortex

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Helios is a key transcriptional regulator of outer hair cell maturation

The sensory cells that are responsible for hearing include the cochlear inner hair cells (IHCs) and outer hair cells (OHCs), with the OHCs being necessary for sound sensitivity and tuning1. Both cell types are thought to arise from common progenitors; however, our understanding of the factors that control the fate of IHCs and OHCs remains limited. Here we identify Ikzf2 (which encodes Helios) as an essential transcription factor in mice that is required for OHC functional maturation and hearing. Helios is expressed in postnatal mouse OHCs, and in the cello mouse model a point mutation in Ikzf2 causes early-onset sensorineural hearing loss. Ikzf2cello/cello OHCs have greatly reduced prestin-dependent electromotile activity, a hallmark of OHC functional maturation, and show reduced levels of crucial OHC-expressed genes such as Slc26a5 (which encodes prestin) and Ocm. Moreover, we show that ectopic expression of Ikzf2 in IHCs: induces the expression of OHC-specific genes; reduces the expression of canonical IHC genes; and confers electromotility to IHCs, demonstrating that Ikzf2 can partially shift the IHC transcriptome towards an OHC-like identity

\u3ci\u3eDrosophila\u3c/i\u3e Muller F Elements Maintain a Distinct Set of Genomic Properties Over 40 Million Years of Evolution

The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25–50%) than euchromatic reference regions (3–11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11–27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4–3.6 vs. 8.4–8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu

Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma.

Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function