9 research outputs found
Sub-token ViT Embedding via Stochastic Resonance Transformers
We discover the presence of quantization artifacts in Vision Transformers
(ViTs), which arise due to the image tokenization step inherent in these
architectures. These artifacts result in coarsely quantized features, which
negatively impact performance, especially on downstream dense prediction tasks.
We present a zero-shot method to improve how pre-trained ViTs handle spatial
quantization. In particular, we propose to ensemble the features obtained from
perturbing input images via sub-token spatial translations, inspired by
Stochastic Resonance, a method traditionally applied to climate dynamics and
signal processing. We term our method ``Stochastic Resonance Transformer"
(SRT), which we show can effectively super-resolve features of pre-trained
ViTs, capturing more of the local fine-grained structures that might otherwise
be neglected as a result of tokenization. SRT can be applied at any layer, on
any task, and does not require any fine-tuning. The advantage of the former is
evident when applied to monocular depth prediction, where we show that
ensembling model outputs are detrimental while applying SRT on intermediate ViT
features outperforms the baseline models by an average of 4.7% and 14.9% on the
RMSE and RMSE-log metrics across three different architectures. When applied to
semi-supervised video object segmentation, SRT also improves over the baseline
models uniformly across all metrics, and by an average of 2.4% in F&J score. We
further show that these quantization artifacts can be attenuated to some extent
via self-distillation. On the unsupervised salient region segmentation, SRT
improves upon the base model by an average of 2.1% on the maxF metric. Finally,
despite operating purely on pixel-level features, SRT generalizes to non-dense
prediction tasks such as image retrieval and object discovery, yielding
consistent improvements of up to 2.6% and 1.0% respectively
Effect of Berberine on promoting the excretion of cholesterol in high-fat diet-induced hyperlipidemic hamsters
Isolation of Endogenously Assembled RNA-Protein Complexes Using Affinity Purification Based on Streptavidin Aptamer S1
Efficient isolation of endogenously assembled viral RNA-protein complexes is essential for understanding virus replication mechanisms. We have developed an affinity purification strategy based on an RNA affinity tag that allows large-scale preparation of native viral RNA-binding proteins (RBPs). The streptavidin-binding aptamer S1 sequence was inserted into the 3′ end of dengue virus (DENV) 5′–3′ UTR RNA, and the DENV RNA UTR fused to the S1 RNA aptamer was expressed in living mammalian cells. This allowed endogenous viral ribonucleoprotein (RNP) assembly and isolation of RNPs from whole cell extract, through binding the S1 aptamer to streptavidin magnetic beads. Several novel host DENV RBPs were subsequently identified by liquid chromatography with tandem mass spectrometry (LC-MS/MS), including RPS8, which we further implicate in DENV replication. We proposed efficient S1 aptamer-based isolation of viral assembled RNPs from living mammalian cells will be generally applicable to the purification of high- and low-affinity RBPs and RNPs under endogenous conditions
Protein Microspheres with Unique Green and Red Autofluorescence for Noninvasively Tracking and Modeling Their in Vivo Biodegradation
Bovine
serum albumin (BSA) microspheres were prepared through a
facile and low-cost route including a high-speed dispersion of BSA
in cross-linking solution followed by spray drying. Interestingly
the as-prepared BSA microspheres possess unique blue-green, green,
green-yellow, and red fluorescence when excited by specific wavelengths
of laser or LED light. The studies of UV–visible reflectance
spectra and fluorescence emission spectra indicated that four classes
of fluorescent compounds are presumably formed during the fabrication
processes. The formation and the potential contributors for the unique
green and red autofluorescence were also discussed and proposed though
the exact structures of the fluorophores formed remain elusive due
to the complexity of the protein system. The effect of spray-drying
conditions on the morphology of spray-dried samples was investigated
and optimized. FTIR was further employed to characterize the formation
of the functional groups in the as-prepared autofluorescent microspheres.
Good in vitro and in vivo biocompatibility was demonstrated by the
cytotoxicity test on the A549 cancer cells and tissue histological
analysis, respectively. The autofluorescent BSA microspheres themselves
were then applied as a novel tracer for convenient tracking/modeling
of the biodegradation of autofluorescent BSA microspheres injected
into mouse model based on noninvasive, time-dependent fluorescence
images of the mice, in which experimental data are in good agreement
with the proposed mathematical model. All these studies indicate that
the as-developed protein microspheres exhibiting good biocompatibility,
biodegradability, and unique autofluorescence, can significantly broaden
biomedical applications of fluorescent protein particles