Diabetic gastroparesis: Therapeutic options

Gastroparesis is a condition characterized by delayed gastric emptying and the most common known underlying cause is diabetes mellitus. Symptoms include nausea, vomiting, abdominal fullness, and early satiety, which impact to varying degrees on the patient’s quality of life. Symptoms and deficits do not necessarily relate to each other, hence despite significant abnormalities in gastric emptying, some individuals have only minimal symptoms and, conversely, severe symptoms do not always relate to measures of gastric emptying. Prokinetic agents such as metoclopramide, domperidone, and erythromycin enhance gastric motility and have remained the mainstay of treatment for several decades, despite unwanted side effects and numerous drug interactions. Mechanical therapies such as endoscopic pyloric botulinum toxin injection, gastric electrical stimulation, and gastrostomy or jejunostomy are used in intractable diabetic gastroparesis (DG), refractory to prokinetic therapies. Mitemcinal and TZP-101 are novel investigational motilin receptor and ghrelin agonists, respectively, and show promise in the treatment of DG. The aim of this review is to provide an update on prokinetic and mechanical therapies in the treatment of DG

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

Modeling psychiatric disorders: from genomic findings to cellular phenotypes

Major programs in psychiatric genetics have identified 4150 risk loci for psychiatric disorders. These loci converge on a small number of functional pathways, which span conventional diagnostic criteria, suggesting a partly common biology underlying schizophrenia, autism and other psychiatric disorders. Nevertheless, the cellular phenotypes that capture the fundamental features of psychiatric disorders have not yet been determined. Recent advances in genetics and stem cell biology offer new prospects for cell-based modeling of psychiatric disorders. The advent of cell reprogramming and induced pluripotent stem cells (iPSC) provides an opportunity to translate genetic findings into patient-specific in vitro models. iPSC technology is less than a decade old but holds great promise for bridging the gaps between patients, genetics and biology. Despite many obvious advantages, iPSC studies still present multiple challenges. In this expert review, we critically review the challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes

Histone methyltransferase DOT1L coordinates AR and MYC stability in prostate cancer

Histone methyltransferase, DOTL1 is implicated in the pathogenesis of MLL-rearranged leukemia, however, not much is known of its role in prostate cancer (PCa). Here, the authors report that DOTL1 inhibition suppresses both androgen receptor and MYC pathways in a negative feed forward manner to reduce growth of AR-positive PCa