Abstract Small proteins (SPs) are typically characterized as eukaryotic proteins shorter than 100 amino acids and prokaryotic proteins shorter than 50 amino acids. Historically, they were disregarded because of the arbitrary size thresholds to define proteins. However, recent research has revealed the existence of many SPs and their crucial roles. Despite this, the identification of SPs and the elucidation of their functions are still in their infancy. To pave the way for future SP studies, we briefly introduce the limitations and advancements in experimental techniques for SP identification. We then provide an overview of available computational tools for SP identification, their constraints, and their evaluation. Additionally, we highlight existing resources for SP research. This survey aims to initiate further exploration into SPs and encourage the development of more sophisticated computational tools for SP identification in prokaryotes and microbiomes.
more »
« less
Geometric Phase Control of Surface Plasmons by Dipole Sources
Abstract Geometric phase metasurfaces, as one of the main branches of meta‐optics, have attracted enormous interest in the last two decades. Recently, through rotating a set of subwavelength dipole sources, geometric phase concept has been extended to near‐field regime for the control of surface plasmons (SPs). Despite this progress, puzzles and shortcomings still exist: it is curious that geometric phases equal to once and twice the rotation angle of dipole source are both reported for SP controls, and the control strategies examined thus far only work for a single wavelength. Hereby, a rigorous derivation of the SP excitation of dipole sources upon circularly polarized illumination is performed, and the rotation dependence and in‐plane coordinate correlation of geometric phase control of SPs is clarified. Moreover, a holographic approach is proposed to implement multiplexed geometric phase control, experimentally demonstrating several metalenses that can couple and steer the incident circular polarizations of four wavelengths and two spin directions to different SP focusing beams. This work will pave an avenue toward the development of integrated and multiplexed SP devices.
more »
« less
- Award ID(s):
- 2114103
- PAR ID:
- 10419166
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Laser & Photonics Reviews
- Volume:
- 17
- Issue:
- 6
- ISSN:
- 1863-8880
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Adding new unlicensed wireless spectrum is a promising approach to accommodate increasing traffic demand. However, unlicensed spectrum may have a high risk of becoming congested, and service providers (SPs) may have difficulty to differentiate their wireless services when offering them on the same unlicensed spectrum. When SPs offer identical services, the resulting competition can lead to zero profits. In this work, we consider the case where an SP bundles its wireless service with a content service. We show that this can differentiate the SPs’ services and lead to positive SP profits. In particular, we study the characteristics of the content services that an SP should bundle with its wireless service, and analyze the impact of bundling on consumer surplus.more » « less
-
Small Proteins (SPs) are pivotal in various cellular functions such as immunity, defense, and communication. Despite their significance, identifying them is still in its infancy. Existing computational tools are tailored to specific eukaryotic species, leaving only a few options for SP identification in prokaryotes. In addition, these existing tools still have suboptimal performance in SP identification. To fill this gap, we introduce PSPI, a deep learning-based approach designed specifically for predicting prokaryotic SPs. We showed that PSPI had a high accuracy in predicting generalized sets of prokaryotic SPs and sets specific to the human metagenome. Compared with three existing tools, PSPI was faster and showed greater precision, sensitivity, and specificity not only for prokaryotic SPs but also for eukaryotic ones. We also observed that the incorporation of (n,k)-mers greatly enhances the performance of PSPI, suggesting that many SPs may contain short linear motifs. The PSPI tool, which is freely available athttps://www.cs.ucf.edu/∼xiaoman/tools/PSPI/, will be useful for studying SPs as a tool for identifying prokaryotic SPs and it can be trained to identify other types of SPs as well.more » « less
-
Signal peptides (SPs) play a crucial role in protein translocation in cells. The development of large protein language models (PLMs) and prompt-based learning provide a new opportunity for SP prediction, especially for the categories with limited annotated data. We present a parameter-efficient fine-tuning (PEFT) framework for SP prediction, PEFT-SP, to effectively utilize pretrained PLMs. We integrated low-rank adaptation (LoRA) into ESM-2 models to better leverage the protein sequence evolutionary knowledge of PLMs. Experiments show that PEFT-SP using LoRA enhances state-of-the-art results, leading to a maximum Matthews correlation coefficient (MCC) gain of 87.3% for SPs with small training samples and an overall MCC gain of 6.1%. Furthermore, we also employed two other PEFT methods, prompt tuning and adapter tuning, in ESM-2 for SP prediction. More elaborate experiments show that PEFT-SP using adapter tuning can also improve the state-of-the-art results by up to 28.1% MCC gain for SPs with small training samples and an overall MCC gain of 3.8%. LoRA requires fewer computing resources and less memory than the adapter tuning during the training stage, making it possible to adapt larger and more powerful protein models for SP prediction.more » « less
-
Understanding bond rupture in polymer networks remains a fundamental challenge due to the interplay of network topology and condensed phase effects. In this work, we introduce a predictive approach for determining bond rupture in thermosets based on shortest paths (SPs) analysis of the network topology. This method enumerates SP sets in networks with periodic boundary conditions, with applications to both all-atom and coarse-grained simulations. We find that bond rupture is most likely to initiate on the first (shortest) SP in the thermoset network and the strain at which the first bond ruptures is linearly correlated with the topological path length. As a result, one can predict the first bond rupture by computing the first SP directly from the initial thermoset topology without resorting to MD simulations. Furthermore, the specific bond rupture location along the first SP follows a probability distribution associated with the SP-based betweenness centrality. Subsequent bond rupture events are dictated by the instantaneous SP of partially broken networks. Moreover, we quantify the length scale dependence of SP distributions, introducing a means of partially bridging the observed ductile rupture in molecular simulations and brittle rupture in experiments.more » « less
An official website of the United States government
