Ubiquitin ligase MARCH5 localizes to peroxisomes to regulate pexophagy

Mitochondria and peroxisomes are independent but functionally closely related organelles. A few proteins have been characterized as dual-organelle locating proteins with distinct or similar roles on mitochondria and peroxisomes. MARCH5 is a mitochondria-associated ubiquitin ligase best known for its regulatory role in mitochondria quality control, fission, and fusion. Here, we used a proximity tagging system, PUP-IT, and identified new interacting proteins of MARCH5. Our data uncover that MARCH5 is a dual-organelle locating protein that interacts with several peroxisomal proteins. PEX19 binds the transmembrane region on MARCH5 and targets it to peroxisomes. On peroxisomes, MARCH5 binds and mediates the ubiquitination of PMP70. Furthermore, we find PMP70 ubiquitination and pexophagy induced by mTOR inhibition are blocked in the absence of MARCH5. Our study suggests novel roles of MARCH5 on peroxisomes.

Validation of an Automatic Tagging System for Identifying Respiratory and Hemodynamic Deterioration Events in the Intensive Care Unit

Objectives: Predictive models for critical events in the intensive care unit (ICU) might help providers anticipate patient deterioration. At the heart of predictive model development lies the ability to accurately label significant events, thereby facilitating the use of machine learning and similar strategies. We conducted this study to establish the validity of an automated system for tagging respiratory and hemodynamic deterioration by comparing automatic tags to tagging by expert reviewers.Methods: This retrospective cohort study included 72,650 unique patient stays collected from Electronic Medical Records of the University of Massachusetts’ eICU. An enriched subgroup of stays was manually tagged by expert reviewers. The tags generated by the reviewers were compared to those generated by an automated system.Results: The automated system was able to rapidly and efficiently tag the complete database utilizing available clinical data. The overall agreement rate between the automated system and the clinicians for respiratory and hemodynamic deterioration tags was 89.4% and 87.1%, respectively. The automatic system did not add substantial variability beyond that seen among the reviewers.Conclusions: We demonstrated that a simple rule-based tagging system could provide a rapid and accurate tool for mass tagging of a compound database. These types of tagging systems may replace human reviewers and save considerable resources when trying to create a validated, labeled database used to train artificial intelligence algorithms. The ability to harness the power of artificial intelligence depends on efficient clinical validation of targeted conditions; hence, these systems and the methodology used to validate them are crucial.

Targeted Protein Acetylation in Cells Using Heterobifunctional Molecules

Protein acetylation is a central event in orchestrating diverse cellular processes. However, current strategies to investigate protein acetylation in cells are often non-specific or lack temporal and magnitude control. Here, we developed an acetylation tagging system, AceTAG, to induce acetylation of targeted proteins. The AceTAG system utilizes bifunctional molecules to direct the lysine acetyltransferase p300/CBP to proteins fused with the small protein tag FKBP12F36V, resulting in their induced acetylation. Using AceTAG, we induced targeted acetylation of a diverse array of proteins in cells, specifically histone H3.3, the NF-kB subunit p65/RelA, and the tumor suppressor p53. We demonstrate that targeted acetylation with the AceTAG system is rapid, selective, reversible, and can be controlled in a dose-dependent fashion. AceTAG represents a useful strategy to modulate protein acetylation and will enable the exploration of targeted acetylation in basic biological and therapeutic contexts.

An Arduino Real-Time Jump Tagging System for Exploring Stereotyped Jumping Behavior in Mice

The jump is one of the common stereotyped behavior in rodents. It is the natural state in some types of mice and also can be found in certain types of disease models, such as addiction. It is straightforward and easy to identify by the human eye in offline analysis. However, jumping is a short-lived act that happens immediately. It is difficult to be tagged in real-time by manual operation, which limits the detailed exploration of its neural mechanisms with the new techniques, such as fiber photometry recording or optogenetics. Here we introduced an arduino real-time jump tagging system (Art-JT system) to record the jump based on online monitoring the pressure changes of the floor in which the mouse is free exploring. Meanwhile, the Art-JT system can send the digital signal of the jump timing to the external device for tagging the events in the fiber photometry system or triggering the optogenetics laser. We tested it with the mice induced by Naloxone precipitated withdrawal jumping. The results showed that it could accurately record the jump events and provide several detailed parameters of the jump. Furthermore, it was easy and fast to get the GCaMP6 signal correlated with the jump in the medial prefrontal cortex and primary motor cortex by combining the Art-JT system and multichannel fiber photometry system. Our results suggested that the Art-JT system may be a powerful tool for recording and analyzing jumping efficiently and helping us to understand stereotyped behavior.

A method of query expansion based on topic models and user profile for search in folksonomy

With the development of the web 2.0 communities, information retrieval has been widely applied based on the collaborative tagging system. However, a user issues a query that is often a brief query with only one or two keywords, which leads to a series of problems like inaccurate query words, information overload and information disorientation. The query expansion addresses this issue by reformulating each search query with additional words. By analyzing the limitation of existing query expansion methods in folksonomy, this paper proposes a novel query expansion method, based on user profile and topic model, for search in folksonomy. In detail, topic model is constructed by variational antoencoder with Word2Vec firstly. Then, query expansion is conducted by user profile and topic model. Finally, the proposed method is evaluated by a real dataset. Evaluation results show that the proposed method outperforms the baseline methods.

Design of a 3D Printed Tagging System to Improve Accessibility in Medical Education

Anatomy, one of the cornerstones of medical education is often subject to testing in a practical manner utilizing tagged specimen-based exams. The design and production of 3D printed tags described here offers a unique ability to design in factors that support students with visual and learning disabilities. The lack of commercially available tags that can withstand the rigors and chemical exposure within this specific environment make the creation of this novel intervention vital to a great number of facilities. This report outlines the iterative process in creating a successful tag and the specifications needed to repeat the project. The success of these tags will impact students for years to come.