212 research outputs found
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The autophagic degradation of cytosolic pools of peroxisomal proteins by a new selective pathway.
Damaged or redundant peroxisomes and their luminal cargoes are removed by pexophagy, a selective autophagy pathway. In yeasts, pexophagy depends mostly on the pexophagy receptors, such as Atg30 for Pichia pastoris and Atg36 for Saccharomyces cerevisiae, the autophagy scaffold proteins, Atg11 and Atg17, and the core autophagy machinery. In P. pastoris, the receptors for peroxisomal matrix proteins containing peroxisomal targeting signals (PTSs) include the PTS1 receptor, Pex5, and the PTS2 receptor and co-receptor, Pex7 and Pex20, respectively. These shuttling receptors are predominantly cytosolic and only partially peroxisomal. It remains unresolved as to whether, when and how the cytosolic pools of peroxisomal receptors, as well as the peroxisomal matrix proteins, are degraded under pexophagy conditions. These cytosolic pools exist both in normal and mutant cells impaired in peroxisome biogenesis. We report here that Pex5 and Pex7, but not Pex20, are degraded by an Atg30-independent, selective autophagy pathway. To enter this selective autophagy pathway, Pex7 required its major PTS2 cargo, Pot1. Similarly, the degradation of Pex5 was inhibited in cells missing abundant PTS1 cargoes, such as alcohol oxidases and Fox2 (hydratase-dehydrogenase-epimerase). Furthermore, in cells deficient in PTS receptors, the cytosolic pools of peroxisomal matrix proteins, such as Pot1 and Fox2, were also removed by Atg30-independent, selective autophagy, under pexophagy conditions. In summary, the cytosolic pools of PTS receptors and their cargoes are degraded via a pexophagy-independent, selective autophagy pathway under pexophagy conditions. These autophagy pathways likely protect cells from futile enzymatic reactions that could potentially cause the accumulation of toxic cytosolic products.Abbreviations: ATG: autophagy related; Cvt: cytoplasm to vacuole targeting; Fox2: hydratase-dehydrogenase-epimerase; PAGE: polyacrylamide gel electrophoresis; Pot1: thiolase; PMP: peroxisomal membrane protein; Pgk1: 3-phosphoglycerate kinase; PTS: peroxisomal targeting signal; RADAR: receptor accumulation and degradation in the absence of recycling; RING: really interesting new gene; SDS: sodium dodecyl sulphate; TCA, trichloroacetic acid; Ub: ubiquitin; UPS: ubiquitin-proteasome system Vid: vacuole import and degradation
Automated cropping intensity extraction from isolines of wavelet spectra
Timely and accurate monitoring of cropping intensity (CI) is essential to help us understand changes in food production. This paper aims to develop an automatic Cropping Intensity extraction method based on the Isolines of Wavelet Spectra (CIIWS) with consideration of intra- class variability. The CIIWS method involves the following procedures: (1) characterizing vegetation dynamics from time–frequency dimensions through a continuous wavelet transform performed on vegetation index temporal profiles; (2) deriving three main features, the skeleton width, maximum number of strong brightness centers and the intersection of their scale intervals, through computing a series of wavelet isolines from the wavelet spectra; and (3) developing an automatic cropping intensity classifier based on these three features. The proposed CIIWS method improves the understanding in the spectral–temporal properties of vegetation dynamic processes. To test its efficiency, the CIIWS method is applied to China’s Henan province using 250 m 8 days composite Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series datasets. An overall accuracy of 88.9% is achieved when compared with in-situ observation data. The mapping result is also evaluated with 30 m Chinese Environmental Disaster Reduction Satellite (HJ-1)-derived data and an overall accuracy of 86.7% is obtained. At county level, the MODIS-derived sown areas and agricultural statistical data are well correlated (r2 = 0.85). The merit and uniqueness of the CIIWS method is the ability to cope with the complex intra-class variability through continuous wavelet transform and efficient feature extraction based on wavelet isolines. As an objective and meaningful algorithm, it guarantees easy applications and greatly contributes to satellite observations of vegetation dynamics and food security efforts
Grasp Stability Assessment Through Attention-Guided Cross-Modality Fusion and Transfer Learning
Extensive research has been conducted on assessing grasp stability, a crucial
prerequisite for achieving optimal grasping strategies, including the minimum
force grasping policy. However, existing works employ basic feature-level
fusion techniques to combine visual and tactile modalities, resulting in the
inadequate utilization of complementary information and the inability to model
interactions between unimodal features. This work proposes an attention-guided
cross-modality fusion architecture to comprehensively integrate visual and
tactile features. This model mainly comprises convolutional neural networks
(CNNs), self-attention, and cross-attention mechanisms. In addition, most
existing methods collect datasets from real-world systems, which is
time-consuming and high-cost, and the datasets collected are comparatively
limited in size. This work establishes a robotic grasping system through
physics simulation to collect a multimodal dataset. To address the sim-to-real
transfer gap, we propose a migration strategy encompassing domain randomization
and domain adaptation techniques. The experimental results demonstrate that the
proposed fusion framework achieves markedly enhanced prediction performance
(approximately 10%) compared to other baselines. Moreover, our findings suggest
that the trained model can be reliably transferred to real robotic systems,
indicating its potential to address real-world challenges.Comment: Accepted by IROS 202
Multimodal Fish Feeding Intensity Assessment in Aquaculture
Fish feeding intensity assessment (FFIA) aims to evaluate the intensity
change of fish appetite during the feeding process, which is vital in
industrial aquaculture applications. The main challenges surrounding FFIA are
two-fold. 1) robustness: existing work has mainly leveraged single-modality
(e.g., vision, audio) methods, which have a high sensitivity to input noise. 2)
efficiency: FFIA models are generally expected to be employed on devices. This
presents a challenge in terms of computational efficiency. In this work, we
first introduce an audio-visual dataset, called AV-FFIA. AV-FFIA consists of
27,000 labeled audio and video clips that capture different levels of fish
feeding intensity. To our knowledge, AV-FFIA is the first large-scale
multimodal dataset for FFIA research. Then, we introduce a multi-modal approach
for FFIA by leveraging single-modality pre-trained models and modality-fusion
methods, with benchmark studies on AV-FFIA. Our experimental results indicate
that the multi-modal approach substantially outperforms the single-modality
based approach, especially in noisy environments. While multimodal approaches
provide a performance gain for FFIA, it inherently increase the computational
cost. To overcome this issue, we further present a novel unified model, termed
as U-FFIA. U-FFIA is a single model capable of processing audio, visual, or
audio-visual modalities, by leveraging modality dropout during training and
knowledge distillation from single-modality pre-trained models. We demonstrate
that U-FFIA can achieve performance better than or on par with the
state-of-the-art modality-specific FFIA models, with significantly lower
computational overhead. Our proposed U-FFIA approach enables a more robust and
efficient method for FFIA, with the potential to contribute to improved
management practices and sustainability in aquaculture
Locally advanced head and neck squamous cell carcinoma treatment efficacy and safety: a systematic review and network meta-analysis
Head and neck squamous cell carcinoma (HNSCC) accounts for approximately 3% of new cancer cases and 3% of all deaths worldwide. Most HNSCC patients are locally advanced (LA) at diagnosis. The combination of radiotherapy (RT), chemotherapy, targeted therapy, and immunotherapy are the primary LA-HNSCC treatment options. Nevertheless, the choice of optimal LA-HNSCC treatment remains controversial. We systematically searched public databases for LA-HNSCC-related studies and assess treatment effectiveness and safety by assessing the objective response rate (ORR), ≥3 adverse events (AEs), overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), local-region control (LRC), and disease-specific survival (DSS). 126 randomized controlled clinical trials (RCTs) were included in this study. We show that concurrent RT with nimotuzumab or conventional concurrent chemo-radiotherapy (CCRT) had significantly better efficacy and long-term survival without increasing AEs than RT alone. Accelerated fractionated radiotherapy (AFRT) showed better efficiency than conventional fractionated RT, although it had higher AEs. In addition, concurrent cetuximab combined with RT failed to show a significant advantage over RT alone.Trial registration: PROSPERO CRD42022352127
LRRC8 family proteins within lysosomes regulate cellular osmoregulation and enhance cell survival to multiple physiological stresses
LRRC8 family proteins on the plasma membrane play a critical role in cellular osmoregulation by forming volume-regulated anion channels (VRACs) necessary to prevent necrotic cell death.We demonstrate that intracellular LRRC8 proteins acting within lysosomes also play an essential role in cellular osmoregulation. LRRC8 proteins on lysosome membranes generate large lysosomal volume-regulated anion channel (Lyso-VRAC) currents in response to low cytoplasmic ionic strength conditions. When a double-leucine L706L707 motif at the C terminus of LRRC8A was mutated to alanines, normal plasma membrane VRAC currents were still observed, but Lyso-VRAC currents were absent. We used this targeting mutant, as well as pharmacological tools, to demonstrate that Lyso-VRAC currents are necessary for the formation of large lysosome-derived vacuoles, which store and then expel excess water to maintain cytosolic water homeostasis. Thus, Lyso-VRACs allow lysosomes of mammalian cells to act as the cell`s “bladder.” When Lyso-VRAC current was selectively eliminated, the extent of necrotic cell death to sustained stress was greatly increased, not only in response to hypoosmotic stress, but also to hypoxic and hypothermic stresses. Thus Lyso-VRACs play an essential role in enabling cells to mount successful homeostatic responses to multiple stressors
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