Mapping Brain Response to Pain in Fibromyalgia Patients Using Temporal Analysis of fMRI

Background: Nociceptive stimuli may evoke brain responses longer than the stimulus duration often partially detected by conventional neuroimaging. Fibromyalgia patients typically complain of severe pain from gentle stimuli. We aimed to characterize brain response to painful pressure in fibromyalgia patients by generating activation maps adjusted for the duration of brain responses. Methodology/Principal Findings: Twenty-seven women (mean age: 47.8 years) were assessed with fMRI. The sample included nine fibromyalgia patients and nine healthy subjects who received 4 kg/cm2 of pressure on the thumb. Nine additional control subjects received 6.8 kg/cm2 to match the patients for the severity of perceived pain. Independent Component Analysis characterized the temporal dynamics of the actual brain response to pressure. Statistical parametric maps were estimated using the obtained time courses. Brain response to pressure (18 seconds) consistently exceeded the stimulus application (9 seconds) in somatosensory regions in all groups. fMRI maps following such temporal dynamics showed a complete pain network response (sensory-motor cortices, operculo-insula, cingulate cortex, and basal ganglia) to 4 kg/cm2 of pressure in fibromyalgia patients. In healthy subjects, response to this low intensity pressure involved mainly somatosensory cortices. When matched for perceived pain (6.8 kg/cm2), control subjects showed also comprehensive activation of pain-related regions, but fibromyalgia patients showed significantly larger activation in the anterior insula-basal ganglia complex and the cingulate cortex. Conclusions/Significance: The results suggest that data-driven fMRI assessments may complement conventional neuroimaging for characterizing pain responses and that enhancement of brain activation in fibromyalgia patients may be particularly relevant in emotion-related regions

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

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

Expression and signaling of group I metabotropic glutamate receptors in astrocytes and microglia

Stimulation of astrocytes with the excitatory neurotransmitter glutamate leads to the formation of inositol 1,4,5-trisphosphate and the subsequent increase of intracellular calcium content. Astrocytes express both ionotropic receptors and metabotropic glutamate (mGlu) receptors, of which mGlu(5) receptors are probably involved in glutamate-induced calcium signaling. The mGlu(5) receptor occurs as two splice variants, mGlu,, and mGlu(5a), but it was hitherto unknown which splice Variant is responsible for the glutamate-induced effects in astrocytes, We report here that both mRNAs encoding mGlu(5) receptor splice variants are expressed by cultured astrocytes. The expression of mGlu(5a) receptor mRNA is much stronger than that of mGlu(5b) receptor mRNA in these cells. In situ hybridization experiments reveal neuronal expression of mGlu(5a) receptor mRNA in adult rat forebrain but a strong neuronal expression of mGlu(5a) mRNA only in olfactory bulb. Signals for mGlu(5a) receptor mRNA in the rest of the brain were diffuse and weak but consistently above background. Activation of mGlu(5) receptors in astrocytes yields increases in inositol phosphate production and transient calcium responses. It is surprising that the rank order of agonist potency [quisqualate > (2S,1'S,2'S)-2-(carboxycyclopropyl)glycine = trans-(1S,3R)-1-amino-1,3-cyclopentanedicarboxylic acid (1S,3R-ACPD) > glutamate] differs from that reported for recombinantly expressed mGlu(5a) receptors, The expression of mGlu(5a) receptor mRNA and the occurrence of 1S,3R-ACPD-induced calcium signaling were found also in cultured microglia, indicating for the first time expression of mGlu(5a) receptors in these macrophage-like cells