Hermansky-Pudlak syndrome type 2 manifests with fibrosing lung disease early in childhood

Background: Hermansky-Pudlak syndrome (HPS), a hereditary multisystem disorder with oculocutaneous albinism, may be caused by mutations in one of at least 10 separate genes. The HPS-2 subtype is distinguished by the presence of neutropenia and knowledge of its pulmonary phenotype in children is scarce. Methods: Six children with genetically proven HPS-2 presented to the chILD-EU register between 2009 and 2017; the data were collected systematically and imaging studies were scored blinded. Results: Pulmonary symptoms including dyspnea, coughing, need for oxygen, and clubbing started 3.3 years before the diagnosis was made at the mean age of 8.83 years (range 2-15). All children had recurrent pulmonary infections, 3 had a spontaneous pneumothorax, and 4 developed scoliosis. The frequency of pulmonary complaints increased over time. The leading radiographic pattern was ground-glass opacities with a rapid increase in reticular pattern and traction bronchiectasis between initial and follow-up Computer tomography (CT) in all subjects. Honeycombing and cysts were newly detectable in 3 patients. Half of the patients received a lung biopsy for diagnosis; histological patterns were cellular non-specific interstitial pneumonia, usual interstitial pneumonia-like, and desquamative interstitial pneumonia. Conclusions: HPS-2 is characterized by a rapidly fibrosing lung disease during early childhood. Effective treatments are required

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

Hypoxia-inducible factor 2α plays a critical role in the formation of alveoli and surfactant

Alveolarization of the developing lung is an important step toward the switch from intrauterine life to breathing oxygen-rich air after birth. The distal airways structurally change to minimize the gas exchange path, and Type II pneumocytes increase the production of surfactants, which are required to reduce surface tension at the air-liquid interface in the alveolus. Hypoxia-inducible factor 2α(Hif2α) is an oxygen-regulated transcription factor expressed in endothelial and Type II cells, and

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 science. © The Author(s) 2019. Published by Oxford University Press

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field