We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of dailylife activity video spanning hundreds of scenarios (household, outdoor, workplace, leisure, etc.) captured by 931 unique camera wearers from 74 worldwide locations and 9 different countries. The approach to collection is designed to uphold rigorous privacy and ethics standards, with consenting participants and robust de-identification procedures where relevant. Ego4D dramatically expands the volume of diverse egocentric video footage publicly available to the research community. Portions of the video are accompanied by audio, 3D meshes of the environment, eye gaze, stereo, and/or synchronized videos from multiple egocentric cameras at the same event. Furthermore, we present a host of new benchmark challenges centered around understanding the first-person visual experience in the past (querying an episodic memory), present (analyzing hand-object manipulation, audio-visual conversation, and social interactions), and future (forecasting activities). By publicly sharing this massive annotated dataset and benchmark suite, we aim to push the frontier of first-person perception.

Iron oxide nanoparticles (IONs) have been widely explored for biomedical applications due to their high biocompatibility, surface-coating versatility, and superparamagnetic properties. Upon exposure to an external magnetic field, IONs can be precisely directed to a region of interest and serve as exceptional delivery vehicles and cellular markers. However, the design of nanocarriers that achieve an efficient endocytic uptake, escape lysosomal degradation, and perform precise intracellular functions is still a challenge for their application in translational medicine. This review highlights several aspects that mediate the activation of the endosomal pathways, as well as the different properties that govern endosomal escape and nuclear transfection of magnetic IONs. In particular, we review a variety of ION surface modification alternatives that have emerged for facilitating their endocytic uptake and their timely escape from endosomes, with special emphasis on how these can be manipulated for the rational design of cell-penetrating vehicles. Moreover, additional modifications for enhancing nuclear transfection are also included in the design of therapeutic vehicles that must overcome this barrier. Understanding these mechanisms opens new perspectives in the strategic development of vehicles for cell tracking, cell imaging and the targeted intracellular delivery of drugs and gene therapy sequences and vectors.

Emerging water pollutants such as pharmaceutical contaminants are suspected to induce adverse effects to human health. These molecules became worrisome due to their increasingly high concentrations in surface waters. Despite this alarming situation, available data about actual concentrations in the environment is rather scarce, as it is not commonly monitored or regulated. This is aggravated even further by the absence of portable and reliable methods for their determination in the field. A promising way to tackle these issues is the use of enzyme-based and miniaturized biosensors for their electrochemical detection. Here, we present an overview of the latest developments in amperometric microfluidic biosensors that include, modeling and multiphysics simulation, design, manufacture, testing, and operation methods. Different types of biosensors are described, highlighting those based on oxidases/peroxidases and the integration with microfluidic platforms. Finally, issues regarding the stability of the biosensors and the enzyme molecules are discussed, as well as the most relevant approaches to address these obstacles.

We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,025 hours of dailylife activity video spanning hundreds of scenarios (household, outdoor, workplace, leisure, etc.) captured by 855 unique camera wearers from 74 worldwide locations and 9 different countries. The approach to collection is designed to uphold rigorous privacy and ethics standards with consenting participants and robust de-identification procedures where relevant. Ego4D dramatically expands the volume of diverse egocentric video footage publicly available to the research community. Portions of the video are accompanied by audio, 3D meshes of the environment, eye gaze, stereo, and/or synchronized videos from multiple egocentric cameras at the same event. Furthermore, we present a host of new benchmark challenges centered around understanding the first-person visual experience in the past (querying an episodic memory), present (analyzing hand-object manipulation, audio-visual conversation, and social interactions), and future (forecasting activities). By publicly sharing this massive annotated dataset and benchmark suite, we aim to push the frontier of first-person perception.

One of the challenges of modern biotechnology is to find new routes to mitigate the resistance to conventional antibiotics. Antimicrobial peptides (AMPs) are an alternative type of biomolecules, naturally present in a wide variety of organisms, with the capacity to overcome the current microorganism resistance threat. Here, we reviewed our recent efforts to develop a new library of non-rationally produced AMPs that relies on bacterial genome inherent diversity and compared it with rationally designed libraries. Our approach is based on a four-stage workflow process that incorporates the interplay of recent developments in four major emerging technologies: artificial intelligence, molecular dynamics, surface-display in microorganisms, and microfluidics. Implementing this framework is challenging because to obtain reliable results, the in silico algorithms to search for candidate AMPs need to overcome issues of the state-of-the-art approaches that limit the possibilities for multi-space data distribution analyses in extremely large databases. We expect to tackle this challenge by using a recently developed classification algorithm based on deep learning models that rely on convolutional layers and gated recurrent units. This will be complemented by carefully tailored molecular dynamics simulations to elucidate specific interactions with lipid bilayers. Candidate AMPs will be recombinantly-expressed on the surface of microorganisms for further screening via different droplet-based microfluidic-based strategies to identify AMPs with the desired lytic abilities. We believe that the proposed approach opens opportunities for searching and screening bioactive peptides for other applications.