Large-Scale, Wavelet-Based Analysis of Lysosomal Trajectories and Co-Movements of Lysosomes with Nanoparticle Cargos

Lysosomes—that is, acidic organelles known for degradation/recycling—move through the cytoplasm alternating between bursts of active transport and short, diffusive motions or even pauses. While their mobility is essential for lysosomes’ fusogenic and non-fusogenic interactions with target organelles, their movements have not been characterized in adequate detail. Here, large-scale statistical analysis of lysosomal movement trajectories reveals that lysosome trajectories in all examined cell types—both cancer and noncancerous ones—are superdiffusive and characterized by heavy-tailed distributions of run and flight lengths. Consideration of Akaike weights for various potential models (lognormal, power law, truncated power law, stretched exponential, and exponential) indicates that the experimental data are best described by the lognormal distribution, which, in turn, can be related to one of the space-search strategies particularly effective when “thorough” search needs to balance search for rare target(s) (organelles). In addition, automated, wavelet-based analysis allows for co-tracking the motions of lysosomes and the cargos they carry—particularly the nanoparticle aggregates known to cause selective lysosome disruption in cancerous cells. The methods we describe here could help study nanoparticle assemblies, viruses, and other objects transported inside various vesicle types, as well as coordinated movements of organelles/particles in the cytoplasm. Custom-written code that includes integrated workflow for our analyses is made available for academic use.

A conversation on accelerating innovation in biopharma and life sciences through global collaboration and alliances

We note and reflect on the power of international partnering and collaborations that led to many of the innovations that were brought to market extremely quickly and successfully during the Covid-19 pandemic. These collaborative global approaches suggest the potential for developing broader, open innovation models in more extensive regional and global collaborations for other biopharma and life science market segments. In this article, we adopt a ‘virtual panel discussion format” to frame and discuss potential issues and models that would need to be designed, developed and tested, with the purpose of engaging emerging global regions as equal partners. We also consider similar challenges for regions within countries – even in the US - that lack significant sources for capital across the company life cycle. Several recent open innovation alliance approaches or models are discussed as potential models. They are: the Eli Lilly FIP Net (fully integrated pharmaceutical network); the Enlight Bioscience alliance developed by Pure Tech Ventures; the Harrington Project linking academia to industry; and, the Corporate Accelerator model notably recently expanded globally by Illumina. We outline a proposal to create a guiding coalition, or “think tank” to further test and develop the proposals discussed herein.

MPolSys Modeler, a tool for computational modeling of linear polymer systems

The computational study of intermolecular relationships of a given material can be used as a route for predicting quantities impossible or difficult to be determined experimentally. Furthermore properties of new materials can also be predicted by techniques of this type, when they are still in the modeling phase. This technique reproduces the classical dynamic relationships between the constituent elements of the material, atoms or unicorpuscular approximations of molecules, from interaction potential models called force fields. This work aims to develop a tool that performs the composition of linear polymeric chain systems through a self-avoided walk. For this, the concept of self-experimentation of long walks (SAWLC) was used, together with the Python language to develop MpolSys Modeler. This tool is a non-overlapping polymer chain generator, which in turn generates outputs that can be used as input to Moltemplate. To validate the tool's results, experiments were carried out in which the numbers and polymerization chains of the simulated polymer were varied, observing the overlap or not of the molecules that make up the simulation. At the end of the simulations, there were positive results that indicate a promising usage of the tool for the creation of polymers with a high number of chains and degrees of polymerization.

Methodological foundations of innovative solutions in renewable energy engineering

Рассмотрен подход, позволяющий методами системного анализа исследовать энергетическую систему с возобновляемыми источниками энергии. Предлагается использовать возможности методов многокритериальной оптимизации, анализа и принятия решений при разработке системы моделей поступления и потенциала возобновляемых источников энергии, позволяющей учитывать особенности технологии преобразования энергии. We deal with the approach that makes it possible to investigate the energy system with renewable energy sources (RES) by methods of system analysis. We propose to use multi-criterion optimization, analysis and decision-making techniques in the development of a system of input and potential models for renewable energy sources that took into account the characteristics of energy conversion technology.

“The Blind Dread of Physical Pain”

This chapter puts Edith Wharton’s insistence on pain’s refining power and her disdain for her pain-averse contemporaries in dialogue with the eclectic New Thought movement, which persuaded many Americans that a positive mental outlook could minimize or even vanquish pain. Wharton openly disdained the national faith in self-improvement, attainable happiness, and avoidable pain espoused in the optimistic bestseller, Pollyanna, and by New Thinkers like Ella Wheeler Wilcox. Although she carefully distinguishes between “sterile” and potentially fruitful pain, Wharton depicts an instinctive aversion to pain of all kinds as an all-too-common American flaw, whose only upside was allowing the select few capable of an unusually sensitive appreciation of pain to stand out from the crowd. Rather than positioning these rare sensitive souls as potential models, her writings increasingly rely on them to bring the extent of US cultural and political debasement into sharper relief.

An archive of whose own? White feminism and racial justice in fan fiction’s digital infrastructure

In summer 2020, when the language of racial reckoning entered US and transnational public spheres following the murder of George Floyd, the contradictions of fandom's long-standing claims to progressive politics became sharply visible. An open letter with specific demands asking the fan fiction platform Archive of Our Own (AO3) to address the issue of racist content in the archive circulated widely. After offering a brief history of critiques of fannish racism, we turn to the specifics of AO3, the political commitments embedded in its systems, and how attention to racial justice could transform them. Drawing on fan fiction genres, we offer three potential models for thinking through these possibilities: a fix-it that would extend AO3's existing metadata structures; a canon divergence that would alter the makeup of the content on AO3; and an alternative universe that draws from abolitionist organizing to imagine the broadest structural changes of all.

Fashion Recommendation Systems, Models and Methods: A Review

In recent years, the textile and fashion industries have witnessed an enormous amount of growth in fast fashion. On e-commerce platforms, where numerous choices are available, an efficient recommendation system is required to sort, order, and efficiently convey relevant product content or information to users. Image-based fashion recommendation systems (FRSs) have attracted a huge amount of attention from fast fashion retailers as they provide a personalized shopping experience to consumers. With the technological advancements, this branch of artificial intelligence exhibits a tremendous amount of potential in image processing, parsing, classification, and segmentation. Despite its huge potential, the number of academic articles on this topic is limited. The available studies do not provide a rigorous review of fashion recommendation systems and the corresponding filtering techniques. To the best of the authors’ knowledge, this is the first scholarly article to review the state-of-the-art fashion recommendation systems and the corresponding filtering techniques. In addition, this review also explores various potential models that could be implemented to develop fashion recommendation systems in the future. This paper will help researchers, academics, and practitioners who are interested in machine learning, computer vision, and fashion retailing to understand the characteristics of the different fashion recommendation systems.

Characterization of the Electrophysiologic Remodeling of Patients With Ischemic Cardiomyopathy by Clinical Measurements and Computer Simulations Coupled With Machine Learning

RationalePatients with ischemic cardiomyopathy (ICMP) are at high risk for malignant arrhythmias, largely due to electrophysiological remodeling of the non-infarcted myocardium. The electrophysiological properties of the non-infarcted myocardium of patients with ICMP remain largely unknown.ObjectivesTo assess the pro-arrhythmic behavior of non-infarcted myocardium in ICMP patients and couple computational simulations with machine learning to establish a methodology for the development of disease-specific action potential models based on clinically measured action potential duration restitution (APDR) data.Methods and ResultsWe enrolled 22 patients undergoing left-sided ablation (10 ICMP) and compared APDRs between ICMP and structurally normal left ventricles (SNLVs). APDRs were clinically assessed with a decremental pacing protocol. Using genetic algorithms (GAs), we constructed populations of action potential models that incorporate the cohort-specific APDRs. The variability in the populations of ICMP and SNLV models was captured by clustering models based on their similarity using unsupervised machine learning. The pro-arrhythmic potential of ICMP and SNLV models was assessed in cell- and tissue-level simulations. Clinical measurements established that ICMP patients have a steeper APDR slope compared to SNLV (by 38%, p < 0.01). In cell-level simulations, APD alternans were induced in ICMP models at a longer cycle length compared to SNLV models (385–400 vs 355 ms). In tissue-level simulations, ICMP models were more susceptible for sustained functional re-entry compared to SNLV models.ConclusionMyocardial remodeling in ICMP patients is manifested as a steeper APDR compared to SNLV, which underlies the greater arrhythmogenic propensity in these patients, as demonstrated by cell- and tissue-level simulations using action potential models developed by GAs from clinical measurements. The methodology presented here captures the uncertainty inherent to GAs model development and provides a blueprint for use in future studies aimed at evaluating electrophysiological remodeling resulting from other cardiac diseases.