35 research outputs found
Performance characteristics and design of voltage references
Integrated circuits comprise the core of essentially all electronic systems. In the design of many integrated circuits, one task of the design engineer is to provide accurate voltages to sub blocks in the circuit structure. The circuits that provide these voltages are often referred to as voltage references. A widely used class of voltage references that typically have low supply, process, and temperature sensitivities are bandgap references whose output voltage is dominated by the bandgap voltage of silicon. Though several structurally different bandgap reference circuits are widely used in industry, there is little in the literature that focuses on how the performance of these circuits can be optimized or how the performance of different bandgap circuits compare. The task of optimization and comparison is complicated by the realization that each of the bandgap circuits themselves have several degrees of freedom in the design. In this work, a metric for fairly comparing the basic performance of different bandgap references based upon the normalized second-order temperature derivative is introduced. This metric is used to compare the performance of several of the most popular bandgap reference circuits that are used in the production. The comparisons show that even though the structure of these reference circuits are fundamentally different and even though each circuit has several degrees of design freedom, the normalized temperature coefficients of all circuits in the comparison group at a fixed operating temperature are the same. The comparisons also show that the designer cannot optimize the basic performance of any of these circuits through judicious utilization of the degrees of design freedom.
In this work, a new very low power voltage reference obtained by replacing the diode-connected bipolar transistors in a basic bandgap circuit with diode-connected MOS transistors operating in deep weak inversion is also discussed. An analytical formulation of the weak-inversion MOS voltage reference shows that the MOSFET-based structure has even lower temperature sensitivity than the basic bandgap circuits. The issue of practicality of the MOS-based reference is, however, of concern since the extremely low currents appear to create the need for very large resistors which are not realistically available in most standard CMOS processes
Word Definitions from Large Language Models
Dictionary definitions are historically the arbitrator of what words mean,
but this primacy has come under threat by recent progress in NLP, including
word embeddings and generative models like ChatGPT. We present an exploratory
study of the degree of alignment between word definitions from classical
dictionaries and these newer computational artifacts. Specifically, we compare
definitions from three published dictionaries to those generated from variants
of ChatGPT. We show that (i) definitions from different traditional
dictionaries exhibit more surface form similarity than do model-generated
definitions, (ii) that the ChatGPT definitions are highly accurate, comparable
to traditional dictionaries, and (iii) ChatGPT-based embedding definitions
retain their accuracy even on low frequency words, much better than GloVE and
FastText word embeddings
Ligand Selectivity in the Recognition of Protoberberine Alkaloids by Hybrid-2 Human Telomeric G-Quadruplex: Binding Free Energy Calculation, Fluorescence Binding, and NMR Experiments
The human telomeric G-quadruplex (G4) is an attractive target for developing anticancer drugs. Natural products protoberberine alkaloids are known to bind human telomeric G4 and inhibit telomerase. Among several structurally similar protoberberine alkaloids, epiberberine (EPI) shows the greatest specificity in recognizing the human telomeric G4 over duplex DNA and other G4s. Recently, NMR study revealed that EPI recognizes specifically the hybrid-2 form human telomeric G4 by inducing large rearrangements in the 50-flanking segment and loop regions to form a highly extensive four-layered binding pocket. Using the NMR structure of the EPI-human telomeric G4 complex, here we perform molecular dynamics free energy calculations to elucidate the ligand selectivity in the recognition of protoberberines by the human telomeric G4. The MM-PB(GB)SA (molecular mechanics-Poisson Boltzmann/Generalized Born) Surface Area) binding free energies calculated using the Amber force fields bsc0 and OL15 correlate well with the NMR titration and binding affinity measurements, with both calculations correctly identifying the EPI as the strongest binder to the hybrid-2 telomeric G4 wtTel26. The results demonstrated that accounting for the conformational flexibility of the DNA-ligand complexes is crucially important for explaining the ligand selectivity of the human telomeric G4. While the MD-simulated (molecular dynamics) structures of the G-quadruplex-alkaloid complexes help rationalize why the EPI-G4 interactions are optimal compared with the other protoberberines, structural deviations from the NMR structure near the binding site are observed in the MD simulations. We have also performed binding free energy calculation using the more rigorous double decoupling method (DDM); however, the results correlate less well with the experimental trend, likely due to the difficulty of adequately sampling the very large conformational reorganization in the G4 induced by the protoberberine binding
Performance characteristics and design of voltage references
Integrated circuits comprise the core of essentially all electronic systems. In the design of many integrated circuits, one task of the design engineer is to provide accurate voltages to sub blocks in the circuit structure. The circuits that provide these voltages are often referred to as voltage references. A widely used class of voltage references that typically have low supply, process, and temperature sensitivities are bandgap references whose output voltage is dominated by the bandgap voltage of silicon. Though several structurally different bandgap reference circuits are widely used in industry, there is little in the literature that focuses on how the performance of these circuits can be optimized or how the performance of different bandgap circuits compare. The task of optimization and comparison is complicated by the realization that each of the bandgap circuits themselves have several degrees of freedom in the design. In this work, a metric for fairly comparing the basic performance of different bandgap references based upon the normalized second-order temperature derivative is introduced. This metric is used to compare the performance of several of the most popular bandgap reference circuits that are used in the production. The comparisons show that even though the structure of these reference circuits are fundamentally different and even though each circuit has several degrees of design freedom, the normalized temperature coefficients of all circuits in the comparison group at a fixed operating temperature are the same. The comparisons also show that the designer cannot optimize the basic performance of any of these circuits through judicious utilization of the degrees of design freedom.
In this work, a new very low power voltage reference obtained by replacing the diode-connected bipolar transistors in a basic bandgap circuit with diode-connected MOS transistors operating in deep weak inversion is also discussed. An analytical formulation of the weak-inversion MOS voltage reference shows that the MOSFET-based structure has even lower temperature sensitivity than the basic bandgap circuits. The issue of practicality of the MOS-based reference is, however, of concern since the extremely low currents appear to create the need for very large resistors which are not realistically available in most standard CMOS processes.</p
Ligand Selectivity in the Recognition of Protoberberine Alkaloids by Hybrid-2 Human Telomeric G-Quadruplex: Binding Free Energy Calculation, Fluorescence Binding, and NMR Experiments
The human telomeric G-quadruplex (G4) is an attractive target for developing anticancer drugs. Natural products protoberberine alkaloids are known to bind human telomeric G4 and inhibit telomerase. Among several structurally similar protoberberine alkaloids, epiberberine (EPI) shows the greatest specificity in recognizing the human telomeric G4 over duplex DNA and other G4s. Recently, NMR study revealed that EPI recognizes specifically the hybrid-2 form human telomeric G4 by inducing large rearrangements in the 5′-flanking segment and loop regions to form a highly extensive four-layered binding pocket. Using the NMR structure of the EPI-human telomeric G4 complex, here we perform molecular dynamics free energy calculations to elucidate the ligand selectivity in the recognition of protoberberines by the human telomeric G4. The MM-PB(GB)SA (molecular mechanics-Poisson Boltzmann/Generalized Born) Surface Area) binding free energies calculated using the Amber force fields bsc0 and OL15 correlate well with the NMR titration and binding affinity measurements, with both calculations correctly identifying the EPI as the strongest binder to the hybrid-2 telomeric G4 wtTel26. The results demonstrated that accounting for the conformational flexibility of the DNA-ligand complexes is crucially important for explaining the ligand selectivity of the human telomeric G4. While the MD-simulated (molecular dynamics) structures of the G-quadruplex-alkaloid complexes help rationalize why the EPI-G4 interactions are optimal compared with the other protoberberines, structural deviations from the NMR structure near the binding site are observed in the MD simulations. We have also performed binding free energy calculation using the more rigorous double decoupling method (DDM); however, the results correlate less well with the experimental trend, likely due to the difficulty of adequately sampling the very large conformational reorganization in the G4 induced by the protoberberine binding
TRPM2 Promotes Atherosclerotic Progression in a Mouse Model of Atherosclerosis
Atherosclerosis is a chronic inflammatory arterial disease characterized by build-up of atheromatous plaque, which narrows the lumen of arteries. Hypercholesterolemia and excessive oxidative stress in arterial walls are among the main causative factors of atherosclerosis. Transient receptor potential channel M2 (TRPM2) is a Ca2+-permeable cation channel activated by oxidative stress. However, the role of TRPM2 in atherosclerosis in animal models is not well studied. In the present study, with the use of adeno-associated virus (AAV)-PCSK9 and TRPM2 knockout (TRPM2−/−) mice, we determined the role of TRPM2 in hypercholesterolemia-induced atherosclerosis. Our results demonstrated that TRPM2 knockout reduced atherosclerotic plaque area in analysis of En face Oil Red O staining of both whole aortas and aortic-root thin sections. Furthermore, TRPM2 knockout reduced the expression of CD68, α-SMA, and PCNA in the plaque region, suggesting a role of TRPM2 in promoting macrophage infiltration and smooth-muscle cell migration into the lesion area. Moreover, TRPM2 knockout reduced the expression of ICAM-1, MCP-1, and TNFα and decreased the ROS level in the plaque region, suggesting a role of TRPM2 in enhancing monocyte adhesion and promoting vascular inflammation. In bone-marrow-derived macrophages and primary cultured arterial endothelial cells, TRPM2 knockout reduced the production of inflammatory cytokines/factors and decreased ROS production. In addition, a TRPM2 antagonist N-(p-amylcinnamoyl) anthranilic acid (ACA) was able to inhibit atherosclerotic development in an ApoE−/− mouse model of atherosclerosis. Taken together, the findings of our study demonstrated that TRPM2 contributes to the progression of hypercholesterolemia-induced atherosclerosis. Mechanistically, TRPM2 channels may provide an essential link that can connect ROS to Ca2+ and inflammation, consequently promoting atherosclerotic progression
Assessment and quantification of NOx sources at a regional background site in North China: Comparative results from a Bayesian isotopic mixing model and a positive matrix factorization model
Regional sources of nitrogen oxides (NOx) in North China during summer were explored using both a Bayesian isotopic mixing model and a positive matrix factorization (PMF) model. Results showed that the nitrogen isotope (delta N-15) composition of particulate nitrate (NO3-) varied between -8.9%0 and +14.1%0, while the oxygen isotope (delta O-18) composition ranged from +57.4%0 to +93.8%0. Based on results from the Bayesian isotopic mixing model, the contribution of the hydroxyl radical (center dot OH) NOx conversion pathway showed clear diurnal fluctuation; values were higher during the day (0.53 +/- 0.16) and lower overnight (0.42 +/- 0.17). Values peaked at 06:00-12:00 and then decreased gradually until 00:00-06:00 the next day. Coal combustion (3134 +/- 9.04%) was the most significant source of NOx followed by biomass burning (25.74 +/- 2.58%), mobile sources (23.83 +/- 3.66%), and microbial processes (19.09 +/- 5.21%). PMF results indicated that the contribution from mobile sources was 19.83%, slightly lower as compared to the Bayesian model (23.83%). The PMF model also reported a lower contribution from coal combustion (28.65%) as compared to the Bayesian model (31.34%); however, the sum of biomass burning and microbial processes in the Bayesian model (44.83%) was lower than the aggregate of secondary inorganic aerosol, sea salt, and soil dust in PMF model (51.52%). Overall, differences between the two models were minor, suggesting that this study provided a reasonable source quantification for NOx in North China during summer. (C) 2018 Elsevier Ltd. All rights reserved
A Transcriptional Sequencing Analysis of Islet Stellate Cell and Pancreatic Stellate Cell
Background. Our previous studies have shown that islet stellate cell (ISC), similar to pancreatic stellate cell (PSC) in phenotype and biological characters, may be responsible for the islet fibrosis in type 2 diabetes. To further identify the differences between PSC and ISC and for better understanding of the physiological function of ISC, we employed genome-wide transcriptional analysis on the PSCs and ISCs of Wistar rats. Method. PSCs and ISCs from each rat were primarily cultured at the same condition. Genome-wide transcriptional sequence of stellate cells was generated. The identified differentially expressed genes were validated using RT-PCR. Results. 32 significant differentially expressed genes between PSCs and ISCs were identified. Moreover, collagen type 11a1 (COL11A1), was found to be expressed 2.91-fold higher in ISCs compared with PSCs, indicating that COL11A1 might be a potential key gene modulating the differences between PSC and ISC. Conclusions. Our study identified and validated the differences between PSC and ISC in genome-wide transcriptional scale, confirming the assumption that ISC and PSC are similar other than identical. Moreover, our data might be instrumental for further investigation of ISC and islet fibrosis, and some differential expressed genes may provide an insight into new therapeutic targets for type 2 diabetes
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Aridity threshold in controlling ecosystem nitrogen cycling in arid and semi-arid grasslands.
Higher aridity and more extreme rainfall events in drylands are predicted due to climate change. Yet, it is unclear how changing precipitation regimes may affect nitrogen (N) cycling, especially in areas with extremely high aridity. Here we investigate soil N isotopic values (δ(15)N) along a 3,200 km aridity gradient and reveal a hump-shaped relationship between soil δ(15)N and aridity index (AI) with a threshold at AI=0.32. Variations of foliar δ(15)N, the abundance of nitrification and denitrification genes, and metabolic quotient along the gradient provide further evidence for the existence of this threshold. Data support the hypothesis that the increase of gaseous N loss is higher than the increase of net plant N accumulation with increasing AI below AI=0.32, while the opposite is favoured above this threshold. Our results highlight the importance of N-cycling microbes in extremely dry areas and suggest different controlling factors of N-cycling on either side of the threshold