AlignOT: An Optimal Transport Based Algorithm for Fast 3D Alignment With Applications to Cryogenic Electron Microscopy Density Maps

Aligning electron density maps from Cryogenic electron microscopy (cryo-EM) is a first key step for studying multiple conformations of a biomolecule. As this step remains costly and challenging, with standard alignment tools being potentially stuck in local minima, we propose here a new procedure, called AlignOT, which relies on the use of computational optimal transport (OT) to align EM maps in 3D space. By embedding a fast estimation of OT maps within a stochastic gradient descent algorithm, our method searches for a rotation that minimizes the Wasserstein distance between two maps, represented as point clouds. We quantify the impact of various parameters on the precision and accuracy of the alignment, and show that AlignOT can outperform the standard local alignment methods, with an increased range of rotation angles leading to proper alignment. We further benchmark AlignOT on various pairs of experimental maps, which account for different types of conformational heterogeneities and geometric properties. As our experiments show good performance, we anticipate that our method can be broadly applied to align 3D EM maps.

Application of transport-based metric for continuous interpolation between cryo-EM density maps

Cryogenic electron microscopy (cryo-EM) has become widely used for the past few years in structural biology, to collect single images of macromolecules "frozen in time". As this technique facilitates the identification of multiple conformational states adopted by the same molecule, a direct product of it is a set of 3D volumes, also called EM maps. To gain more insights on the possible mechanisms that govern transitions between different states, and hence the mode of action of a molecule, we recently introduced a bioinformatic tool that interpolates and generates morphing trajectories joining two given EM maps. This tool is based on recent advances made in optimal transport, that allow efficient evaluation of Wasserstein barycenters of 3D shapes. As the overall performance of the method depends on various key parameters, including the sensitivity of the regularization parameter, we performed various numerical experiments to demonstrate how MorphOT can be applied in different contexts and settings. Finally, we discuss current limitations and further potential connections between other optimal transport theories and the conformational heterogeneity problem inherent with cryo-EM data.

Structural Characterization of Endogenous Tuberous Sclerosis Protein Complex Revealed Potential Polymeric Assembly

Tuberous sclerosis protein complex (pTSC) nucleates a proteinaceous signaling hub that integrates information about the internal and external energy status of the cell in the regulation of growth and energy consumption. Biochemical and cryo-electron microscopy studies of recombinant pTSC have revealed its structure and stoichiometry and hinted at the possibility that the complex may form large oligomers. Here, we have partially purified endogenous pTSC from fasted mammalian brains of rat and pig by leveraging a recombinant antigen binding fragment (F_ab) specific for the TSC2 subunit of pTSC. We demonstrate F_ab-dependent purification of pTSC from membrane-solubilized fractions of the brain homogenates. Negative stain electron microscopy of the samples purified from pig brain demonstrates rod-shaped protein particles with a width of 10 nm, a variable length as small as 40 nm, and a high degree of conformational flexibility. Larger filaments are evident with a similar 10 nm width and a ≤1 μm length in linear and weblike organizations prepared from pig brain. Immunogold labeling experiments demonstrate linear aggregates of pTSC purified from mammalian brains. These observations suggest polymerization of endogenous pTSC into filamentous superstructures.

Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study

Background

Mental illness affects a significant portion of the worldwide population. Online mental health forums can provide a supportive environment for those afflicted and also generate a large amount of data that can be mined to predict mental health states using machine learning methods.

Objective

This study aimed to benchmark multiple methods of text feature representation for social media posts and compare their downstream use with automated machine learning (AutoML) tools. We tested on datasets that contain posts labeled for perceived suicide risk or moderator attention in the context of self-harm. Specifically, we assessed the ability of the methods to prioritize posts that a moderator would identify for immediate response.

Methods

We used 1588 labeled posts from the Computational Linguistics and Clinical Psychology (CLPsych) 2017 shared task collected from the Reachout.com forum. Posts were represented using lexicon-based tools, including Valence Aware Dictionary and sEntiment Reasoner, Empath, and Linguistic Inquiry and Word Count, and also using pretrained artificial neural network models, including DeepMoji, Universal Sentence Encoder, and Generative Pretrained Transformer-1 (GPT-1). We used Tree-based Optimization Tool and Auto-Sklearn as AutoML tools to generate classifiers to triage the posts.

Results

The top-performing system used features derived from the GPT-1 model, which was fine-tuned on over 150,000 unlabeled posts from Reachout.com. Our top system had a macroaveraged F1 score of 0.572, providing a new state-of-the-art result on the CLPsych 2017 task. This was achieved without additional information from metadata or preceding posts. Error analyses revealed that this top system often misses expressions of hopelessness. In addition, we have presented visualizations that aid in the understanding of the learned classifiers.

Conclusions

In this study, we found that transfer learning is an effective strategy for predicting risk with relatively little labeled data and noted that fine-tuning of pretrained language models provides further gains when large amounts of unlabeled text are available.

Computational proteome-wide screening predicts neurotoxic drug-protein interactome for the investigational analgesic BIA 10-2474

The investigational compound BIA 10-2474, designed as a long-acting and reversible inhibitor of fatty acid amide hydrolase for the treatment of neuropathic pain, led to the death of one participant and hospitalization of five others due to intracranial hemorrhage in a Phase I clinical trial. Putative off-target activities of BIA 10-2474 have been suggested to be major contributing factors to the observed neurotoxicity in humans, motivating our study's proteome-wide screening approach to investigate its polypharmacology. Accordingly, we performed an in silico screen against 80,923 protein structures reported in the Protein Data Bank. The resulting list of 284 unique human interactors was further refined using target-disease association analyses to a subset of proteins previously linked to neurological, intracranial, inflammatory, hemorrhagic or clotting processes and/or diseases. Eleven proteins were identified as potential targets of BIA 10-2474, and the two highest-scoring proteins, Factor VII and thrombin, both essential blood-clotting factors, were predicted to be inhibited by BIA 10-2474 and suggest a plausible mechanism of toxicity. Once this small molecule becomes commercially available, future studies will be conducted to evaluate the predicted inhibitory effect of BIA 10-2474 on blood clot formation specifically in the brain.

Nonsurgical repair of furcal perforations: a literature review

The important steps in the management of a furcal perforation are immediate action, adequate isolation, debridement, and sealing of the defect. Studies have shown that repair materials or underlying matrix material such as amalgam, Cavit, calcium hydroxide, glass ionomers, hydroxylapatite, tricalcium phosphate, and demineralized freeze-dried bone have not been able to produce consistent results. However, current research on new materials such as mineral trioxide aggregate may advance treatment modalities significantly for furcation repair.

Analgesic efficacy of paracetamol in children using tonsillectomy as a pain model

The analgesic efficacy of paracetamol was assessed in a prospective, randomized, double-blinded study of 100 children undergoing tonsillectomy with or without adenoidectomy. Fifty children were given paracetamol elixir 40 mg/kg 40 minutes preoperatively (Group A); the remaining 50 children were given an oral placebo 40 minutes preoperatively and paracetamol suppositories 40 mg/kg after induction of anaesthesia (Group B). Paracetamol was the only analgesic given and was given either orally or rectally in order to produce high variations in plasma paracetamol concentrations postoperatively. At 30 minutes after the end of surgery a pain score (0-10) was obtained and a venous blood sample was taken for serum paracetamol concentration analysis. Children given paracetamol elixir had a higher mean paracetamol concentration (0.15 [SD 0.06] mmol/l vs 0.05 [SD 0.03] mmol/l, P < 0.001) and a lower median pain score (5 vs 7, P < 0.02) than those who were given suppositories. The use of rescue morphine was higher (10 vs 23, P < 0.001) in the latter group. The incidence of nausea and vomiting was the same in both groups (20%) during the 24 hour postoperative period. Plasma paracetamol concentrations of 0.066-0.132 mmol/l are known to reduce temperature; plasma paracetamol concentrations which provide analgesia are unknown. Children with plasma paracetamol concentrations above 0.07 mmol/l had superior analgesia to those with concentrations below this level (P < 0.05).

Urinary catecholamines and plasma hormones predict mood state in rapid cycling bipolar affective disorder

Over the course of 1 year, a patient with a rapid cycling bipolar affective disorder was followed at weekly intervals to examine whether plasma hormones and urinary catecholamines could predict current or future mood. Higher cortisol levels were found to predict depressed mood 3 days after blood sampling, higher urinary dopamine predicted a manic mood 3 days after blood sampling, urinary norepinephrine was associated with severity of current mood and prolactin was lower with concurrent depressed mood. In multivariate analyses of mood against cortisol, prolactin and three urinary catecholamines, > 50% of the variance in mood state in 3 days was explained by combinations of these biologic measures, especially cortisol and urinary dopamine, while all five biologic variables contributed to explaining 50% of the variance in current mood state. Based on the interrelationships between urinary dopamine, norepinephrine and mood, we postulate the existence of an overcompensating mechanism which is reflected in opposing correlations between urinary dopamine and norepinephrine with mood, despite the two urinary catecholamines being positively correlated.

Changes in plasma vitamin levels in the first 48 hours after onset of acute myocardial infarction

To establish whether plasma vitamin measurements made after acute myocardial infarction (AMI) can be used in case-control studies of coronary artery disease, the short-term effect of AMI on plasma concentrations of 25-hydroxyvitamin D3, beta-carotene, vitamin E and retinol was investigated. Sequential measures of these vitamins were made during the first 48 hours after AMI in 13 patients admitted to the hospital within 4 hours after the onset of symptoms. Plasma levels of 25-hydroxyvitamin D did not change significantly during the first 12 hours after onset of symptoms. Beta-carotene levels increased significantly (p less than 0.05) during the first 12 hours and then decreased, whereas levels of vitamin E and retinol progressively decreased during the first 48 hours by 26 and 25%, respectively. These results suggest that, of these vitamins, only plasma measurements of 25-hydroxyvitamin D3 collected within 12 hours of onset of symptoms may provide reliable information for case-control studies of AMI.