Modality-Independent Teachers Meet Weakly-Supervised Audio-Visual Event Parser

Audio-visual learning has been a major pillar of multi-modal machine learning, where the community mostly focused on its modality-aligned setting, i.e., the audio and visual modality are both assumed to signal the prediction target. With the Look, Listen, and Parse dataset (LLP), we investigate the under-explored unaligned setting, where the goal is to recognize audio and visual events in a video with only weak labels observed. Such weak video-level labels only tell what events happen without knowing the modality they are perceived (audio, visual, or both). To enhance learning in this challenging setting, we incorporate large-scale contrastively pre-trained models as the modality teachers. A simple, effective, and generic method, termed Visual-Audio Label Elaboration (VALOR), is innovated to harvest modality labels for the training events. Empirical studies show that the harvested labels significantly improve an attentional baseline by 8.0 in average F-score (Type@AV). Surprisingly, we found that modality-independent teachers outperform their modality-fused counterparts since they are noise-proof from the other potentially unaligned modality. Moreover, our best model achieves the new state-of-the-art on all metrics of LLP by a substantial margin (+5.4 F-score for Type@AV). VALOR is further generalized to Audio-Visual Event Localization and achieves the new state-of-the-art as well. Code is available at: https://github.com/Franklin905/VALOR

On character table of Clifford groups

Based on a presentation of $\mathcal{C}_n$ and the help of [GAP], we construct the character table of the Clifford group $\mathcal{C}_n$ for $n=1,2,3$. As an application, we can efficiently decompose the (higher power of) tensor product of the matrix representation in those cases. Our results recover some known results in [HWW, WF] and reveal some new phenomena. We prove that the trivial character is the only linear character for $\mathcal{C}_n$ and hence $\mathcal{C}_n$ equals to its commutator subgroup when $n\geq 3$. A few conjectures about $\mathcal{C}_n$ for general $n$ are proposed.Comment: 13 pages; comments and suggestions are welcom

Motor neuron-derived Thsd7a is essential for zebrafish vascular development via the Notch-dll4 signaling pathway.

BackgroundDevelopment of neural and vascular systems displays astonishing similarities among vertebrates. This parallelism is under a precise control of complex guidance signals and neurovascular interactions. Previously, our group identified a highly conserved neural protein called thrombospondin type I domain containing 7A (THSD7A). Soluble THSD7A promoted and guided endothelial cell migration, tube formation and sprouting. In addition, we showed that thsd7a could be detected in the nervous system and was required for intersegmental vessels (ISV) patterning during zebrafish development. However, the exact origin of THSD7A and its effect on neurovascular interaction remains unclear.ResultsIn this study, we discovered that zebrafish thsd7a was expressed in the primary motor neurons. Knockdown of Thsd7a disrupted normal primary motor neuron formation and ISV sprouting in the Tg(kdr:EGFP/mnx1:TagRFP) double transgenic zebrafish. Interestingly, we found that Thsd7a morphants displayed distinct phenotypes that are very similar to the loss of Notch-delta like 4 (dll4) signaling. Transcript profiling further revealed that expression levels of notch1b and its downstream targets, vegfr2/3 and nrarpb, were down-regulated in the Thsd7a morphants. These data supported that zebrafish Thsd7a could regulate angiogenic sprouting via Notch-dll4 signaling during development.ConclusionsOur results suggested that motor neuron-derived Thsd7a plays a significant role in neurovascular interactions. Thsd7a could regulate ISV angiogenesis via Notch-dll4 signaling. Thus, Thsd7a is a potent angioneurin involved in the development of both neural and vascular systems

Deltex1 Is a Target of the Transcription Factor NFAT that Promotes T Cell Anergy

SummaryThe molecular process underlying T cell anergy is incompletely understood. Deltex1 (DTX1) is a Notch target with unknown physiological function. Here we show that Dtx1 was a transcription target of nuclear factor of activated T cells (NFAT) and participated in T cell anergy. DTX1 protein was upregulated during T cell anergy, and transgenic expression of Dtx1 attenuated T cell activation. DTX1 inhibited T cell activation by both E3-dependent and E3-independent mechanisms. In addition, DTX1 suppressed T cell activation in the absence of its Notch-binding domain. Importantly, DTX1 regulated the expression of two anergy-associated molecules, growth arrest and DNA-damage-inducible 45 β (Gadd45β) and Cbl-b. DTX1 interacted with early growth response 2 (Egr-2) for optimum expression of Cbl-b. Furthermore, deficiency of DTX1 augmented T cell activation, conferred resistance to anergy induction, enhanced autoantibody generation, and increased inflammation. DTX1 therefore represents a component downstream of calcium-NFAT signaling that regulates T cell anergy

Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline

Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by quantization and saturation of camera sensors. In contrast to existing learning-based methods, our core idea is to incorporate the domain knowledge of the LDR image formation pipeline into our model. We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization. We then propose to learn three specialized CNNs to reverse these steps. By decomposing the problem into specific sub-tasks, we impose effective physical constraints to facilitate the training of individual sub-networks. Finally, we jointly fine-tune the entire model end-to-end to reduce error accumulation. With extensive quantitative and qualitative experiments on diverse image datasets, we demonstrate that the proposed method performs favorably against state-of-the-art single-image HDR reconstruction algorithms.Comment: CVPR 2020. Project page: https://www.cmlab.csie.ntu.edu.tw/~yulunliu/SingleHDR Code: https://github.com/alex04072000/SingleHD

Caspase-8 inactivation drives autophagy-dependent inflammasome activation in myeloid cells.

Caspase-8 activity controls the switch from cell death to pyroptosis when apoptosis and necroptosis are blocked, yet how caspase-8 inactivation induces inflammasome assembly remains unclear. We show that caspase-8 inhibition via IETD treatment in Toll-like receptor (TLR)-primed Fadd-/-Ripk3-/- myeloid cells promoted interleukin-1β (IL-1β) and IL-18 production through inflammasome activation. Caspase-8, caspase-1/11, and functional GSDMD, but not NLRP3 or RIPK1 activity, proved essential for IETD-triggered inflammasome activation. Autophagy became prominent in IETD-treated Fadd-/-Ripk3-/- macrophages, and inhibiting it attenuated IETD-induced cell death and IL-1β/IL-18 production. In contrast, inhibiting GSDMD or autophagy did not prevent IETD-induced septic shock in Fadd-/-Ripk3-/- mice, implying distinct death processes in other cell types. Cathepsin-B contributes to IETD-mediated inflammasome activation, as its inhibition or down-regulation limited IETD-elicited IL-1β production. Therefore, the autophagy and cathepsin-B axis represents one of the pathways leading to atypical inflammasome activation when apoptosis and necroptosis are suppressed and capase-8 is inhibited in myeloid cells

Highly reliable GIGA-sized synthetic human therapeutic antibody library construction

BackgroundMonoclonal antibodies (mAbs) and their derivatives are the fastest expanding category of pharmaceuticals. Efficient screening and generation of appropriate therapeutic human antibodies are important and urgent issues in the field of medicine. The successful in vitro biopanning method for antibody screening largely depends on the highly diverse, reliable and humanized CDR library. To rapidly obtain potent human antibodies, we designed and constructed a highly diverse synthetic human single-chain variable fragment (scFv) antibody library greater than a giga in size by phage display. Herein, the novel TIM-3-neutralizing antibodies with immunomodulatory functions derived from this library serve as an example to demonstrate the library’s potential for biomedical applications.MethodsThe library was designed with high stability scaffolds and six complementarity determining regions (CDRs) tailored to mimic human composition. The engineered antibody sequences were optimized for codon usage and subjected to synthesis. The six CDRs with variable length CDR-H3s were individually subjected to β-lactamase selection and then recombined for library construction. Five therapeutic target antigens were used for human antibody generation via phage library biopanning. TIM-3 antibody activity was verified by immunoactivity assays.ResultsWe have designed and constructed a highly diverse synthetic human scFv library named DSyn-1 (DCB Synthetic-1) containing 2.5 × 1010 phage clones. Three selected TIM-3-recognizing antibodies DCBT3-4, DCBT3-19, and DCBT3-22 showed significant inhibition activity by TIM-3 reporter assays at nanomolar ranges and binding affinities in sub-nanomolar ranges. Furthermore, clone DCBT3-22 was exceptionally superior with good physicochemical property and a purity of more than 98% without aggregation.ConclusionThe promising results illustrate not only the potential of the DSyn-1 library for biomedical research applications, but also the therapeutic potential of the three novel fully human TIM-3-neutralizing antibodies

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data