87 research outputs found
SpOctA: A 3D Sparse Convolution Accelerator with Octree-Encoding-Based Map Search and Inherent Sparsity-Aware Processing
Point-cloud-based 3D perception has attracted great attention in various
applications including robotics, autonomous driving and AR/VR. In particular,
the 3D sparse convolution (SpConv) network has emerged as one of the most
popular backbones due to its excellent performance. However, it poses severe
challenges to real-time perception on general-purpose platforms, such as
lengthy map search latency, high computation cost, and enormous memory
footprint. In this paper, we propose SpOctA, a SpConv accelerator that enables
high-speed and energy-efficient point cloud processing. SpOctA parallelizes the
map search by utilizing algorithm-architecture co-optimization based on octree
encoding, thereby achieving 8.8-21.2x search speedup. It also attenuates the
heavy computational workload by exploiting inherent sparsity of each voxel,
which eliminates computation redundancy and saves 44.4-79.1% processing
latency. To optimize on-chip memory management, a SpConv-oriented non-uniform
caching strategy is introduced to reduce external memory access energy by 57.6%
on average. Implemented on a 40nm technology and extensively evaluated on
representative benchmarks, SpOctA rivals the state-of-the-art SpConv
accelerators by 1.1-6.9x speedup with 1.5-3.1x energy efficiency improvement.Comment: Accepted to ICCAD 202
BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation
The upscaling of Large Language Models (LLMs) has yielded impressive advances
in natural language processing, yet it also poses significant deployment
challenges. Weight quantization has emerged as a widely embraced solution to
reduce memory and computational demands. This paper introduces BitDistiller, a
framework that synergizes Quantization-Aware Training (QAT) with Knowledge
Distillation (KD) to boost the performance of LLMs at ultra-low precisions
(sub-4-bit). Specifically, BitDistiller first incorporates a tailored
asymmetric quantization and clipping technique to maximally preserve the
fidelity of quantized weights, and then proposes a novel Confidence-Aware
Kullback-Leibler Divergence (CAKLD) objective, which is employed in a
self-distillation manner to enable faster convergence and superior model
performance. Empirical evaluations demonstrate that BitDistiller significantly
surpasses existing methods in both 3-bit and 2-bit configurations on general
language understanding and complex reasoning benchmarks. Notably, BitDistiller
is shown to be more cost-effective, demanding fewer data and training
resources. The code is available at https://github.com/DD-DuDa/BitDistiller
Large Trajectory Models are Scalable Motion Predictors and Planners
Motion prediction and planning are vital tasks in autonomous driving, and
recent efforts have shifted to machine learning-based approaches. The
challenges include understanding diverse road topologies, reasoning traffic
dynamics over a long time horizon, interpreting heterogeneous behaviors, and
generating policies in a large continuous state space. Inspired by the success
of large language models in addressing similar complexities through model
scaling, we introduce a scalable trajectory model called State Transformer
(STR). STR reformulates the motion prediction and motion planning problems by
arranging observations, states, and actions into one unified sequence modeling
task. With a simple model design, STR consistently outperforms baseline
approaches in both problems. Remarkably, experimental results reveal that large
trajectory models (LTMs), such as STR, adhere to the scaling laws by presenting
outstanding adaptability and learning efficiency. Qualitative results further
demonstrate that LTMs are capable of making plausible predictions in scenarios
that diverge significantly from the training data distribution. LTMs also learn
to make complex reasonings for long-term planning, without explicit loss
designs or costly high-level annotations
Effects of fertilizer application schemes and soil environmental factors on nitrous oxide emission fluxes in a rice-wheat cropping system, east China
Nitrous oxide (N2O) is a potent greenhouse gas (GHG) with agricultural soils representing its largest anthropogenic source. However, the mechanisms involved in the N2O emission and factors affecting N2O emission fluxes in response to various nitrogenous fertilizer applications remain uncertain. We conducted a four-year (2012–2015) field experiment to assess how fertilization scheme impacts N2O emissions from a rice-wheat cropping system in eastern China. The fertilizer treatments included Control (CK), Conventional fertilizer (CF), CF with shallow-irrigation (CF+SI), CF with deep-irrigation system (CF+DI), Optimized fertilizer (OF), OF with Urease inhibitor (OF+UI), OF with conservation tillage (OF+CT) and Slow-release fertilizer (SRF). N2O emissions were measured by a closed static chamber method. N2O emission fluxes ranged from 0.61 μg m-2 h-1 to 1707 μg m-2 h-1, indicating a significant impact of nitrogen fertilizer and cropping type on N2O emissions. The highest crop yields for wheat (3515–3667 kg ha-1) and rice (8633–8990 kg ha-1) were observed under the SRF and OF+UI treatments with significant reduction in N2O emissions by 16.94–21.20% and 5.55–7.93%, respectively. Our findings suggest that the SRF and OF+UI treatments can be effective in achieving maximum crop yield and lowering N2O emissions for the rice-wheat cropping system in eastern China
A novel host restriction factor MRPS6 mediates the inhibition of PDCoV infection in HIEC-6 cells
IntroductionPorcine deltacoronavirus (PDCoV) is a zoonotic pathogen with a global distribution, capable of infecting both pigs and humans. To mitigate the risk of cross-species transmission and potential outbreaks, it is crucial to characterize novel antiviral genes, particularly those from human hosts.MethodsThis research used HIEC-6 to investigate PDCoV infection. HIEC-6 cells were infected with PDCoV. Samples were collected 48 h postinfection for proteomic analysis.ResultsWe discovered differential expression of MRPS6 gene at 48 h postinfection with PDCoV in HIEC-6 cells. The gene expression initially increased but then decreased. To further explore the role of MRPS6 in PDCoV infection, we conducted experiments involving the overexpression and knockdown of this gene in HIEC-6 and Caco2 cells, respectively. Our findings revealed that overexpression of MRPS6 significantly inhibited PDCoV infection in HIEC-6 cells, while knockdown of MRPS6 in Caco2 cells led to a significant increase of virus titer. Furthermore, we investigated the correlation between PDCoV infection and the expression of MRPS6. Subsequent investigations demonstrated that MRPS6 exerted an augmentative effect on the production of IFN-β through interferon pathway activation, consequently impeding the progression of PDCoV infection in cellular systems. In conclusion, this study utilized proteomic analysis to investigate the differential protein expression in PDCoV-infected HIEC-6 cells, providing evidence for the first time that the MRPS6 gene plays a restrictive role in PDCoV virus infection.DiscussionOur findings initially provide the validation of MRPS6 as an upstream component of IFN-β pathway, in the promotion of IRF3, IRF7, STAT1, STAT2 and IFN-β production of HIEC-6 via dual-activation from interferon pathway
Potent anti-tumor effects of a dual specific oncolytic adenovirus expressing apoptin in vitro and in vivo
<p>Abstract</p> <p>Background</p> <p>Oncolytic virotherapy is an attractive drug platform of cancer gene therapy, but efficacy and specificity are important prerequisites for success of such strategies. Previous studies determined that Apoptin is a p53 independent, bcl-2 insensitive apoptotic protein with the ability to specifically induce apoptosis in tumor cells. Here, we generated a conditional replication-competent adenovirus (CRCA), designated Ad-hTERT-E1a-Apoptin, and investigated the effectiveness of the CRCA a gene therapy agent for further clinical trials.</p> <p>Results</p> <p>The observation that infection with Ad-hTERT-E1a-Apoptin significantly inhibited growth of the melanoma cells, protecting normal human epidermal melanocytes from growth inhibition confirmed cancer cell selective adenoviral replication, growth inhibition, and apoptosis induction of this therapeutic approach. The <it>in vivo </it>assays performed by using C57BL/6 mice containing established primary or metastatic tumors expanded the <it>in vitro </it>studies. When treated with Ad-hTERT-E1a-Apoptin, the subcutaneous primary tumor volume reduction was not only observed in intratumoral injection group but in systemic delivery mice. In the lung metastasis model, Ad-hTERT-E1a-Apoptin effectively suppressed pulmonary metastatic lesions. Furthermore, treatment of primary and metastatic models with Ad-hTERT-E1a-Apoptin increased mice survival.</p> <p>Conclusions</p> <p>These data further reinforce the previously research showing that an adenovirus expressing Apoptin is more effective and advocate the potential applications of Ad-hTERT-E1a-Apoptin in the treatment of neoplastic diseases in future clinical trials.</p
Identification of lipid droplet structure-like/resident proteins in Caenorhabditis elegans.
The lipid droplet (LD) is a cellular organelle that stores neutral lipids in cells and has been linked with metabolic disorders. Caenorhabditis elegans has many characteristics which make it an excellent animal model for studying LDs. However, unlike in mammalian cells, no LD structure-like/resident proteins have been identified in C. elegans, which has limited the utility of this model for the study of lipid storage and metabolism. Herein based on three lines of evidence, we identified that MDT-28 and DHS-3 previously identified in C. elegans LD proteome were two LD structure-like/resident proteins. First, MDT-28 and DHS-3 were found to be the two most abundant LD proteins in the worm. Second, the proteins were specifically localized to LDs and we identified the domains responsible for this targeting in both proteins. Third and most importantly, the depletion of MDT-28 induced LD clustering while DHS-3 deletion reduced triacylglycerol content (TAG). We further characterized the proteins finding that MDT-28 was ubiquitously expressed in the intestine, muscle, hypodermis, and embryos, whereas DHS-3 was expressed mainly in intestinal cells. Together, these two LD structure-like/resident proteins provide a basis for future mechanistic studies into the dynamics and functions of LDs in C. elegans
Immunogenicity and protective potential of chimeric virus-like particles containing SARS-CoV-2 spike and H5N1 matrix 1 proteins
Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has posed a constant threat to human beings and the world economy for more than two years. Vaccination is the first choice to control and prevent the pandemic. However, an effective SARS-CoV-2 vaccine against the virus infection is still needed. This study designed and prepared four kinds of virus-like particles (VLPs) using an insect expression system. Two constructs encoded wild-type SARS-CoV-2 spike (S) fused with or without H5N1 matrix 1 (M1) (S and SM). The other two constructs contained a codon-optimized spike gene and/or M1 gene (mS and mSM) based on protein expression, stability, and ADE avoidance. The results showed that the VLP-based vaccine could induce high SARS-CoV-2 specific antibodies in mice, including specific IgG, IgG1, and IgG2a. Moreover, the mSM group has the most robust ability to stimulate humoral immunity and cellular immunity than the other VLPs, suggesting the mSM is the best immunogen. Further studies showed that the mSM combined with Al/CpG adjuvant could stimulate animals to produce sustained high-level antibodies and establish an effective protective barrier to protect mice from challenges with mouse-adapted strain. The vaccine based on mSM and Al/CpG adjuvant is a promising candidate vaccine to prevent the COVID-19 pandemic
Exploring the mechanism of JiGuCao capsule formula on treating hepatitis B virus infection via network pharmacology analysis and in vivo/vitro experiment verification
The JiGuCao capsule formula (JCF) has demonstrated promising curative effects in treating chronic hepatitis B (CHB) in clinical trials. Here, we aimed to investigate JCF’s function and mechanism in diseases related to the hepatitis B virus (HBV). We used mass spectrometry (MS) to identify the active metabolites of JCF and established the HBV replication mouse model by hydrodynamically injecting HBV replication plasmids into the mice’s tail vein. Liposomes were used to transfect the plasmids into the cells. The CCK-8 kit identified cell viability. We detected the levels of HBV s antigen (HBsAg) and HBV e antigen (HBeAg) by the quantitative determination kits. qRT-PCR and Western blot were used to detect the genes’ expression. The key pathways and key genes related to JCF on CHB treatment were obtained by network pharmacological analysis. Our results showed that JCF accelerated the elimination of HBsAg in mice. JCF and its medicated serum inhibited HBV replication and proliferation of HBV-replicating hepatoma cells in vitro. And the key targets of JCF in treating CHB were CASP3, CXCL8, EGFR, HSPA8, IL6, MDM2, MMP9, NR3C1, PTGS2, and VEGFA. Furthermore, these key targets were related to pathways in cancer, hepatitis B, microRNAs in cancer, PI3K-Akt signaling, and proteoglycans in cancer pathways. Finally, Cholic Acid, Deoxycholic Acid, and 3′, 4′, 7-Trihydroxyflavone were the main active metabolites of JCF that we obtained. JCF employed its active metabolites to perform an anti-HBV effect and prevent the development of HBV-related diseases
Nuclear cGMP-Dependent Kinase Regulates Gene Expression via Activity-Dependent Recruitment of a Conserved Histone Deacetylase Complex
Elevation of the second messenger cGMP by nitric oxide (NO) activates the cGMP-dependent protein kinase PKG, which is key in regulating cardiovascular, intestinal, and neuronal functions in mammals. The NO-cGMP-PKG signaling pathway is also a major therapeutic target for cardiovascular and male reproductive diseases. Despite widespread effects of PKG activation, few molecular targets of PKG are known. We study how EGL-4, the Caenorhabditis elegans PKG ortholog, modulates foraging behavior and egg-laying and seeks the downstream effectors of EGL-4 activity. Using a combination of unbiased forward genetic screen and proteomic analysis, we have identified a conserved SAEG-1/SAEG-2/HDA-2 histone deacetylase complex that is specifically recruited by activated nuclear EGL-4. Gene expression profiling by microarrays revealed >40 genes that are sensitive to EGL-4 activity in a SAEG-1–dependent manner. We present evidence that EGL-4 controls egg laying via one of these genes, Y45F10C.2, which encodes a novel protein that is expressed exclusively in the uterine epithelium. Our results indicate that, in addition to cytoplasmic functions, active EGL-4/PKG acts in the nucleus via a conserved Class I histone deacetylase complex to regulate gene expression pertinent to behavioral and physiological responses to cGMP. We also identify transcriptional targets of EGL-4 that carry out discrete components of the physiological response
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