567 research outputs found
Attenuating Ischemic Disruption of K+ Homeostasis in the Cortex of Hypoxic-Ischemic Neonatal Rats: DOR Activation vs. Acupuncture Treatment
No full textPerinatal hypoxic-ischemic (HI) brain injury results in death or profound long-term neurologic disability in both children and adults. However, there is no effective pharmacological therapy due to a poor understanding of HI events, especially the initial triggers for hypoxic-ischemic injury such as disrupted ionic homeostasis and the lack of effective intervention strategy. In the present study, we showed that neonatal brains undergo a developmental increase in the disruption of K+ homeostasis during simulated ischemia, oxygen-glucose deprivation (OGD) and neonatal HI cortex has a triple phasic response (earlier attenuation, later enhancement, and then recovery) of disrupted K+ homeostasis to OGD. This response partially involves the activity of the δ-opioid receptor (DOR) since the earlier attenuation of ischemic disruption of K+ homeostasis could be blocked by DOR antagonism, while the later enhancement was reversed by DOR activation. Similar to DOR activation, acupuncture, a strategy to promote DOR activity, could partially reverse the later enhanced ischemic disruption of K+ homeostasis in the neonatal cortex. Since maintaining cellular K+ homeostasis and inhibiting excessive K+ fluxes in the early phase of hypoxic-ischemic insults may be of therapeutic benefit in the treatment of ischemic brain injury and related neurodegenerative conditions, and since many neurons and other cells can be rescued during the “window of opportunity” after HI insults, our first findings regarding the role of acupuncture and DOR in attenuating ischemic disruption of K+ homeostasis in the neonatal HI brain suggest a potential intervention therapy in the treatment of neonatal brain injury, especially hypoxic-ischemic encephalopathy
Using cyclostratigraphic evidence to define the unconformity caused by the Mesoproterozoic Qinyu Uplift in the North China Craton
No full textIn the Yanliao Basin of the North China Craton, the Mesoproterozoic Xiamaling Formation contacted unconformably with the underlying Tieling Formation. This unconformity was caused by the Qinyu Uplift. Underneath this unconformity, the Tieling Formation experienced variably weathering with more extensive erosion of carbonates in the west than in the northeast of the basin. To constrain the timing of the Qinyu Uplift and the duration of subsequent unconformity, cyclostratigraphic analysis was conducted on the Tieling carbonate rocks. Referencing the periodicities of the eccentricity, obliquity and precession obtained from the Mesoproterozoic Xiamaling and Hongshuizhuang Formations, Milankovitch cycles during the Tieling Formation were recognized. A bentonite located at the middle of the Tieling Formation was recognized from the core at the Beizhangzi section, and was considered to be contemporaneous with those found at the Jixian and Liujiagou sections, which had a consistent age of 1441 Ma. Then a deposition rate from the bentonite layer to the top interface of the Tieling Formation was calculated to be 1.65 ± 0.22 cm kyr−1, and the duration time were ca. 9 million years. So the minimum age of the Tieling Formation was ca. 1432 Ma. Combined with our new 207Pb/206Pb weighted average age of 1418 ± 14 Ma obtained from the bottom of the Xiamaling Formation, the Qinyu Uplift was constrained to occur between 1432 Ma and 1418 Ma, older than the previously suggested age of 1400 Ma. The duration of this unconformity was suggested to be no less 14 million years, and might be longer in the western part.</p
To Spike or Not To Spike: A Digital Hardware Perspective on Deep Learning Acceleration
Get PDFAs deep learning models scale, they become increasingly competitive from domains spanning from computer vision to natural language processing; however, this happens at the expense of efficiency since they require increasingly more memory and computing power. The power efficiency of the biological brain outperforms any large-scale deep learning (DL) model; thus, neuromorphic computing tries to mimic the brain operations, such as spike-based information processing, to improve the efficiency of DL models. Despite the benefits of the brain, such as efficient information transmission, dense neuronal interconnects, and the co-location of computation and memory, the available biological substrate has severely constrained the evolution of biological brains. Electronic hardware does not have the same constraints; therefore, while modeling spiking neural networks (SNNs) might uncover one piece of the puzzle, the design of efficient hardware backends for SNNs needs further investigation, potentially taking inspiration from the available work done on the artificial neural networks (ANNs) side. As such, when is it wise to look at the brain while designing new hardware, and when should it be ignored? To answer this question, we quantitatively compare the digital hardware acceleration techniques and platforms of ANNs and SNNs. As a result, we provide the following insights: (i) ANNs currently process static data more efficiently, (ii) applications targeting data produced by neuromorphic sensors, such as event-based cameras and silicon cochleas, need more investigation since the behavior of these sensors might naturally fit the SNN paradigm, and (iii) hybrid approaches combining SNNs and ANNs might lead to the best solutions and should be investigated further at the hardware level, accounting for both efficiency and loss optimization
Characterization of a novel family of nucleolus localized RNAs
Get PDFEukaryotic cell nucleus is compartmentalized into various non-membranous sub-nuclear domains with nucleolus being the most prominent one. The nucleolus is the largest sub-nuclear domain where ribosomal gene transcription, pre-rRNA processing, and the initial steps of ribosome sub-unit assembly take place. In human cells, nucleoli are formed around nucleolar organizer regions (NORs) located on the short arms of the five acrocentric chromosomes. NORs are composed of tandem copies of hundreds of rDNA repeats. However, the sequence beyond the rDNA array within the p-arms of NOR containing acrocentric chromosomes is largely unknown. In human cells, ~400 copies of rDNA repeats code for rRNAs. Interestingly, at any time point only ~50% of rRNA genes remain transcriptionally active. While the dynamic changes in histone or DNA modifications on rDNA regulatory elements, and noncoding RNAs have been implicated in regulating the transcription of individual rRNA genes, the precise mechanism of how ~50% of rRNA genes remains silenced at any time point is yet to understand.
In Chapter II, I focus on the characterization of a novel abundant family of ncRNAs, Single NUcleolus Localized RNA (SNUL-RNA). SNUL-RNAs decorate individual nucleolus in the form of a ‘cloud’ in primary and transformed human cells. Super-resolution microscopy imaging revealed that SNUL-RNA showed similar nuclear distribution to pre-rRNA. Further studies suggested that SNUL-RNA is transcribed by RNA Pol I and behaves similarly to pre-rRNA during biological processes when the nucleolar structure is disrupted. Long-read RNA-sequencing analyses indicate that full-length SNULs show significant similarities to pre-rRNAs, implying that SNULs could be evolved from duplications of rDNA genes during evolution. Intriguingly, SNUL-RNAs are found to ‘coat’ the p-arm of NOR-containing chromosomes in a monoallelic fashion, and this monoallelic expression of SNUL-RNAs is epigenetically inheritable and potentially regulated by histone and DNA modifications. Loss-of-function studies reveal that SNUL-RNAs might play a negative regulatory role on rRNA biogenesis. My studies emphasized that not all nucleoli within a cell are functionally identical and NORs on different acrocentric chromosomes are distinct from each other. It also revealed a novel RNA-mediated mechanism for regulating rDNA gene expression and nucleolar function.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-05-01The student, Qinyu Hao, accepted the attached license on 2021-04-19 at 10:41.The student, Qinyu Hao, submitted this Dissertation for approval on 2021-04-19 at 11:03.This Dissertation was approved for publication on 2021-04-20 at 08:46.DSpace SAF Submission Ingestion Package generated from Vireo submission #16403 on 2021-09-16 at 20:10:45Made available in DSpace on 2021-09-17T04:04:32Z (GMT). No. of bitstreams: 2
HAO-DISSERTATION-2021.pdf: 14979917 bytes, checksum: 72f20dd5a347b74bd3fc28d0bf951e6d (MD5)
LICENSE.txt: 4206 bytes, checksum: 276cd0962efb90d42a391136faa95d34 (MD5)
Previous issue date: 2021-04-20Embargo set by: Seth Robbins for item 118677
Lift date: 2023-09-17T04:04:53Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 118677
Lift date: 2023-09-17T04:07:01Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemAuthor requested closed access (OA after 2yrs) in Vireo ETD systemLimite
Role of microRNA-host-lncRNAs in cell cycle
Get PDFMade available in DSpace on 2020-08-27T00:46:52Z (GMT). No. of bitstreams: 2
SUN-DISSERTATION-2020.pdf: 9175277 bytes, checksum: e2efccee2ecdb753df410d65867ed198 (MD5)
LICENSE.txt: 4206 bytes, checksum: d9400be8634f345516a8365c493c941a (MD5)
Previous issue date: 2020-03-17Embargo set by: Seth Robbins for item 115844
Lift date: 2022-08-27T00:46:59Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 115844
Lift date: 2022-08-27T00:50:22Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 115844
Lift date: 2022-08-27T00:51:40Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLong non-coding RNAs (lncRNAs) regulate vital biological processes, including cell proliferation, differentiation and development. A subclass of lncRNAs is synthesized from microRNA (miRNA) host genes (MIRHGs) due to pre-miRNA processing and are categorized as microRNA-host gene lncRNAs (lnc-MIRHGs). Presently, the cellular function of most lnc-MIRHGs is not well understood. In this thesis, I describe studies showing the potential role of two lnc-MIRHGs in cell cycle progression.
In chapter 2, I focus on investigating the role of lnc-MIRHGs in regulating the cell cycle re-entry post quiescence. Cellular quiescence is coupled with cellular development, tissue homeostasis, and cancer progression. Both quiescence and cell cycle re-entry are controlled by active and precise regulation of gene expression. However, the roles of long noncoding RNAs (lncRNAs) during these processes remain to be elucidated. By performing a genome-wide transcriptome analysis, I identify thousands of differentially expressed lncRNAs, including ~30 lnc-MIRHGs, during cellular quiescence and during serum-stimulation in human diploid fibroblast cells. I observe that the mature MIR222HG display serum-stimulated induction due to enhanced pre-RNA splicing. Serum-stimulated binding of the pre-mRNA splicing factor SRSF1 to a micro-exon, which partially overlaps with the primary miR-222 precursor, facilitates enhanced MIR222HG splicing. In serum-stimulated cells, SRSF1 negatively regulates the Drosha/DGCR8-catalyzed cleavage of pri-miR-222, thereby increasing the cellular pool of the mature MIR222HG. Further, loss-of-function studies indicate that the mature MIR222HG facilitates the serum-stimulated cell cycle re-entry in a microRNA-independent manner. Mechanistically, MIR222HG, along with ILF3/2 complex, forms a RNA:RNA duplex with DNM3OS lncRNA, thereby promoting DNM3OS stability. This study identifies a mechanism in which the interplay between splicing versus microprocessor complex dictates the serum-induced expression of MIR222HG for efficient cell cycle re-entry.
In Chapter 3, I demonstrate a microRNA-independent role for a nuclear-enriched and G1-elevated lnc-MIRHG in cell cycle progression of human osteosarcoma. Our knowledge of protein-coding genes in cell cycle regulation is rather complete, but the roles of lncRNAs in this important biological process remain to be elucidated. By performing the genome-wide transcriptome profiling analysis, I discovered 38 phase-specific lnc-MIRHGs that showed elevated expression in one particular cell cycle stage (G1, G1S, S, G2, or M). I further show that MIR100HG produces spliced and stable lncRNAs that display elevated levels during the G1 phase of the cell cycle. Depletion of MIR100HG-encoded lncRNAs in human cells results in aberrant cell cycle progression without altering the levels of miRNA encoded within MIR100HG. Notably, MIR100HG interacts with HuR/ELAVL1 as well as with several HuR-target mRNAs. Further, MIR100HG-depleted cells show reduced interaction between HuR and three of its target mRNAs, indicating that MIR100HG facilitates interaction between HuR and target mRNAs. This study unearths novel roles played by a MIRHG-encoded lncRNA in regulating RNA binding protein activity.
In Chapter 4, I summarize my findings during the discovery of lnc-MIRHGs and discuss my opinions about the future directions of lnc-MIRHGs research.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01The student, Qinyu Sun, accepted the attached license on 2020-03-12 at 20:35.The student, Qinyu Sun, submitted this Dissertation for approval on 2020-03-12 at 20:36.This Dissertation was approved for publication on 2020-03-17 at 08:31.DSpace SAF Submission Ingestion Package generated from Vireo submission #14895 on 2020-08-25 at 17:39:01Author requested closed access (OA after 2yrs) in Vireo ETD systemLimite
Clutch control during starting of AMT
No full textAbstractThe author analyzed the basic ideas and realization methods of current starting strategy and put forward the start throttle control strategy based on the characteristic of the clutch studied in this paper. The result of the simulation and experiment show that the starting strategy is better to be applied in the clutch using the pneumatic control method
Adaptive joints with variable stiffness: Strategically arranged materials with transduction properties
No full textThe environment around buildings keeps changing, while the static design solutions of buildings cannot perform well during the whole service life. In order to improve structural performances including strength (i.e. avoid collapse) and serviceability, adaptive structures are likely to establish as one of future trends in both research and application for the built environment. This project aims to synthesize a type of structural joints with variable stiffness capabilities. Stiffness variation is achieved by strategically arranged materials with transduction properties. Shape memory polymers (SMPs) feature large variation of stiffness between a glassy and a rubbery state, which makes them good candidates for application in shape control of adaptive structures. The structures will change themselves into optimal shapes corresponding to different load conditions. However, large shape changes require significant flexibility of the joints because their fixity can affect load-path and shape control. To address this problem, a variable stiffness joint is proposed. During shape/load-path control, the joint reduces its stiffness so that required deformation patterns can be achieved with low actuation energy. After shape control the joint recovers rigidity. Experimental studies showed the potential for application of joints with variable stiffness in adaptive structures.Energy Innovation #5: 4TU.BOUW Lighthouse projects + PDEng ISBN 978-94-6366-246-8Architectural Engineerin
Design and characterization of variable stiffness structural joints
Get PDFThis paper presents design and characterization of a new type of structural joint which can vary its stiffness through actuation. Stiffness variation is employed to control the dynamic response of frame structures equipped with such joints. The joint is made of a shape memory polymer (SMP) core which is reinforced by an SMP-aramid composite skin. A controlled stiffness reduction of the joint core material, induced by resistive heating, results in a shift of the structure natural frequencies. This work comprises two main parts: 1) characterization of material thermomechanical properties and viscoelastic behavior; 2) numerical simulations of the dynamic response of a 1-story planar frame equipped with two such variable stiffness joints. The experimental material model obtained through Dynamic Mechanical Analysis has been used to carry out modal and non-linear transient analysis. However, control time delays due to heating and cooling as well as fatigue are not considered in the numerical simulations. Results have shown that through joint stiffness control, the fundamental frequency shifts up to 8.72% causing a drastic reduction of the dynamic response under resonance loading. The SMP-aramid skin is effective to restrain the joint deformation in the activated state while maintaining viscoelastic damping properties.IMA
Cerebron: A Reconfigurable Architecture for Spatio-Temporal Sparse Spiking Neural Networks
No full textSpiking neural networks (SNNs) are promising alternatives to artificial neural networks (ANNs) since they are more realistic brain-inspired computing models. SNNs have sparse neuron firing over time, i.e., spatiotemporal sparsity; thus, they are helpful in enabling energy-efficient hardware inference. However, exploiting the spatiotemporal sparsity of SNNs in hardware leads to unpredictable and unbalanced workloads, degrading the energy efficiency. Compared to SNNs with simple fully connected structures, those extensive structures (e.g., standard convolutions, depthwise convolutions, and pointwise convolutions) can deal with more complicated tasks but lead to difficulties in hardware mapping. In this work, we propose a novel reconfigurable architecture, Cerebron, which can fully exploit the spatiotemporal sparsity in SNNs with maximized data reuse and propose optimization techniques to improve the efficiency and flexibility of the hardware. To achieve flexibility, the reconfigurable compute engine is compatible with a variety of spiking layers and supports inter-computing-unit (CU) and intra-CU reconfiguration. The compute engine can exploit data reuse and guarantee parallel data access when processing different convolutions to achieve memory efficiency. A two-step data sparsity exploitation method is introduced to leverage the sparsity of discrete spikes and reduce the computation time. Besides, an online channelwise workload scheduling strategy is designed to reduce the latency further. Cerebron is verified on image segmentation and classification tasks using a variety of state-of-the-art spiking network structures. Experimental results show that Cerebron has achieved at least 17.5<inline-formula> <tex-math notation="LaTeX"></tex-math> </inline-formula> prediction energy reduction and 20<inline-formula> <tex-math notation="LaTeX"></tex-math> </inline-formula> speedup compared with state-of-the-art field-programmable gate array (FPGA)-based accelerators.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Electronic
- …
