Robust Digital Molecular Design of Binarized Neural Networks

Molecular programming - a paradigm wherein molecules are engineered to perform computation - shows great potential for applications in nanotechnology, disease diagnostics and smart therapeutics. A key challenge is to identify systematic approaches for compiling abstract models of computation to molecules. Due to their wide applicability, one of the most useful abstractions to realize is neural networks. In prior work, real-valued weights were achieved by individually controlling the concentrations of the corresponding "weight" molecules. However, large-scale preparation of reactants with precise concentrations quickly becomes intractable. Here, we propose to bypass this fundamental problem using Binarized Neural Networks (BNNs), a model that is highly scalable in a molecular setting due to the small number of distinct weight values. We devise a noise-tolerant digital molecular circuit that compactly implements a majority voting operation on binary-valued inputs to compute the neuron output. The network is also rate-independent, meaning the speed at which individual reactions occur does not affect the computation, further increasing robustness to noise. We first demonstrate our design on the MNIST classification task by simulating the system as idealized chemical reactions. Next, we map the reactions to DNA strand displacement cascades, providing simulation results that demonstrate the practical feasibility of our approach. We perform extensive noise tolerance simulations, showing that digital molecular neurons are notably more robust to noise in the concentrations of chemical reactants compared to their analog counterparts. Finally, we provide initial experimental results of a single binarized neuron. Our work suggests a solid framework for building even more complex neural network computation

Programmable chemical controllers made from DNA

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language' and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents

Down-regulation of PKCζ in renal cell carcinoma and its clinicopathological implications

<p>Abstract</p> <p>Background</p> <p>Metastatic renal cell carcinoma (RCC) is highly resistant to systemic chemotherapy. Unfortunately, nearly all patients die of the metastatic and chemoresistant RCC. Recent studies have shown the atypical PKCζ is an important regulator of tumorigenesis. However, the correlation between PKC<b>ζ </b>expression and the clinical outcome in RCC patients is unclear. We examined the level of PKCζ expression in human RCC.</p> <p>Methods</p> <p>PKCζ mRNA and protein expressions were examined by real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC) respectively in RCC tissues of 144 patients. Cellular cytotoxicity and proliferation were assessed by MTT.</p> <p>Results</p> <p>PKCζ expression was significantly higher in normal than in cancerous tissues (<it>P </it>< 0.0001) by real-time PCR and IHC. Similarly, PKCζ expression was down-regulated in four renal cancer cell lines compared to immortalized benign renal tubular cells. Interestingly, an increase of PKCζ expression was associated with the elevated tumor grade (<it>P </it>= 0.04), but no such association was found in TNM stage (<it>P </it>= 0.13). Tumors with higher PKCζ expression were associated with tumor size (<it>P </it>= 0.048). Expression of higher PKCζ found a poor survival in patients with high tumor grade. Down-regulation of PKCζ showed the significant chemoresistance in RCC cell lines. Inactivation of PKCζ expression enhanced cellular resistance to cisplatin and paclitaxel, and proliferation in HK-2 cells by specific PKC<b>ζ </b>siRNA and inhibitor.</p> <p>Conclusions</p> <p>PKCζ expression was associated with tumorigenesis and chemoresistance in RCC.</p

DNA storage in thermoresponsive microcapsules for repeated random multiplexed data access

In support of the publication "DNA storage in thermoresponsive microcapsules for repeated random multiplexed data access" we share the following datasets and code: AutoCAD drawing of the microfluidic trapping device. Sequences of the DNA used to encode the 25 files used in the current study. FASTQ-files of the sequencing experiments of Figures 5b and d. Python scripts that allow for the reproduction of our sequencing data analysis. The code has been tested on MacOS 13.0.1, Python 3.7.13, samtools 1.16.1 and BWA 0.7.17

CXCR4 identifies transitional bone marrow premonocytes that replenish the mature monocyte pool for peripheral responses

It is well established that Ly6C(hi) monocytes develop from common monocyte progenitors (cMoPs) and reside in the bone marrow (BM) until they are mobilized into the circulation. In our study, we found that BM Ly6C(hi) monocytes are not a homogenous population, as current data would suggest. Using computational analysis approaches to interpret multidimensional datasets, we demonstrate that BM Ly6C(hi) monocytes consist of two distinct subpopulations (CXCR4(hi) and CXCR4(lo) subpopulations) in both mice and humans. Transcriptome studies and in vivo assays revealed functional differences between the two subpopulations. Notably, the CXCR4(hi) subset proliferates and is immobilized in the BM for the replenishment of functionally mature CXCR4(lo) monocytes. We propose that the CXCR4(hi) subset represents a transitional premonocyte population, and that this sequential step of maturation from cMoPs serves to maintain a stable pool of BM monocytes. Additionally, reduced CXCR4 expression on monocytes, upon their exit into the circulation, does not reflect its diminished role in monocyte biology. Specifically, CXCR4 regulates monocyte peripheral cellular activities by governing their circadian oscillations and pulmonary margination, which contributes toward lung injury and sepsis mortality. Together, our study demonstrates the multifaceted role of CXCR4 in defining BM monocyte heterogeneity and in regulating their function in peripheral tissues

Biochemical Controller Made From DNA

Thesis (Ph.D.)--University of Washington, 2015The potential of robots operating at a molecular or cellular scale is only limited by the imagination — for instance, nanorobots could navigate the bloodstream, identify a tumor and eliminate it cell by cell resulting in cancer treatment with minimal side effects. To perform such complex tasks, nanorobots need sensors for detecting their environment, actuators that allow them to move through their environment and embedded control circuits that convert sensor information to motor activity. In this thesis we focus on developing systematic design strategies for the de novo construction of embedded molecular controllers with DNA nanotechnology (introduced in Chapter 1). To systematically engineer DNA computing systems, we developed a new class of programmable DNA circuitry that, in principle, can implement any behavior captured by chemical reaction networks (CRNs) (Chapter 2). Although CRNs have been widely used as a framework for describing and modeling the time evolution of chemical systems, we were the first to show that CRNs can also serve as a prescriptive language for specifying many complex computations, including oscillations, memory, and distributed algorithms. We thus treated CRNs as a programming language, allowing us to design our DNA circuitry while abstracting away from the molecular details. To demonstrate our approach experimentally, we constructed DNA circuits to implement a CRN that embodies, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents. Having made significant progress in the engineering of DNA computing systems in vitro, we next began to explore the design principles for adapting DNA circuitry to a much more complex environment, the mammalian cell (Chapter 3). Applying DNA circuitry in vivo, however, requires special considerations to minimize unwanted interference from host cellular activity. We showed that the use of modified RNA bases and backbones greatly enhances circuit performance in cells. Building on this breakthrough, we constructed nucleic acid-based AND and OR logic circuits and demonstrated that they function predictably and reliably within cells. Our work is a first step toward porting the rich toolbox of DNA nanotechnology into live cells

Multilevel LINC System Designs for Power Efficiency Enhancement

在現今的無線通訊系統中，功率放大器是最消耗功率的元件。而功率放大器又具有非線性特性，因此要設計高效率又高線性度的無線發射機便成了一個相當困難的挑戰。於是多種不同功率放大器的線性化技術被採用來改善無線發射機的線性度及效率。 在這些線性化的技術中，LINC技術可以使用高效率的非線性功率放大器而且可達成線性放大。除此之外，數位信號處理在CMOS製程下具有相對的低成本及其不易受製程變易影響的特性，因此數位化的LINC架構特別適用於當今的製程。 當LINC提高功率放大器效率的同時，LINC需要一個額外的功率合成器來達成線性放大。然而這個低效率的功率合成器會導致整個無線發射機的效率大幅降低。為了改善功率合成器的效率，且同時達到高效率的功率放大器，我們提出了一個多階級系統。基於這個多階級系統，我們提出兩種不同的線性化架構: 增益調整多階級LINC(Gain-adjusting multilevel LINC, GA-MLINC)及包絡調整多階級LINC(Envelope-adjusting multilevel LINC, EA-MLINC)。在WCDMA系統線性度的要求下，三階的增益調整多階級LINC及三階的包絡調整多階級LINC分別可改善LINC系統的輔助功率從16.5%到23.6%及33.4%。Power amplifiers (PAs) are the most power-hungry devices in modern wireless communication systems. Designing a high linearity and high power efficiency wireless transmitter is a big challenge due to the nonlinear characteristic of the power amplifier. Various PA linearization techniques have been adopted to improve linearity and power efficiency of wireless transmitters. Among them, the linear amplification with nonlinear components (LINC) technique can use high-efficiency nonlinear PAs and achieve a linear amplification. In addition, digital signal processing is widely available at a relatively low cost in nowadays CMOS technology and insensitivity to process variation. Thus, the digital LINC architecture is more suitable for modern process technologies. While LINC increases the efficiency of power amplifiers, LINC requires an extra power combiner to obtain the linearly amplified signal. This low-efficiency power combiner results in low system power efficiency of wireless transmitters. To not only increase power combiner efficiency but also achieve high PA efficiency, we propose a multilevel out-phasing (MOP) scheme and two architectures: gain-adjusting multilevel LINC (GA-MLINC) and envelope-adjusting multilevel LINC (EA-MLINC). Under WCDMA linearity requirements, 3-level GA-MLINC and 3-level EA-MLINC enhance the LINC system power-added efficiency from 16.5% to 23.6% and 33.4%, respectively.Chapter 1 Introduction 1 1.1 Motivation and Goal 1 1.2 Approach 2 1.3 Organization 3 Chapter 2 PA Linearization Techniques Overview 5 2.1 Characteristic of Power amplifier 5 2.1.1 Behavior of an Ideal Linear PA 5 2.1.2 Square Law and Third Order Characteristic of PA 5 2.1.3 Saleh Model 8 2.1.4 Varying Envelope and Constant Envelope Input Signals 9 2.2 Methods of Power Amplifier Linearization 11 2.2.1 Feedback Architecture 11 2.2.2 Feedfordward Architecture 12 2.2.3 Predistortion Architecture 13 2.2.4 Envelope Elimination Restoration 14 2.2.5 Linear Amplification with Nonlinear Components 16 Chapter 3 LINC Transmitter System Overview 19 3.1 LINC Overview 19 3.1.1 Phase Modulation Method 21 3.1.2 I/Q Modulation Method 22 3.2 Review of the system architecture of LINC 22 3.2.1 Conventional Analog LINC Architecture 22 3.2.2 In Phase / Quardrature Method Architecture 24 3.2.3 Digital IF with Image Rejection 25 3.3 System Efficiency of LINC Transmitter 26 2.3.1 LINC System Efficiency 26 3.3.2 LINC System Power Added Efficiency 27 3.4 Power Combiners for LINC Transmitter 27 3.4.1 Lossy Combiners 28 3.4.2 Lossless Combiners 28 Chapter 4 Multilevel Out-Phasing Scheme 29 4.1 Out-phasing Technique 29 4.2 Multilevel Scaling Technique 31 4.2.1 Optimal Scale Factor Determination 32 4.3 Multilevel Linearization Technique 34 Chapter 5 Multilevel LINC Architectures 39 5.1 Multilevel Signal Component Separator 39 5.2 Gain-Adjusting MLINC 39 5.2.1 Gain-Adjusting Technique 39 5.2.2 GA-MLINC Architecture 40 5.3 Envelope-Adjusting MLINC 43 5.3.1 Envelope-Adjusting Technique 43 5.3.2 EA-MLINC Architecture 44 Chapter 6 LINC System Simulations and Comparisons 47 6.1 System Specification of WCDMA Transmitter System 47 6.1.1 Error Vector magnitude 47 6.1.2 Spectrum Emission Mask 48 6.1.3 Adjacent Channel Leakage Power Ratio 49 6.2 Combiner Efficiency 51 6.3 System Simulation Results of LINC 53 6.3.1 System Output Power Comparison 53 6.3.2 System PAE Comparison 53 6.3.3 Linearity Comparison 55 6.3.4 Linear Region Comparison 56 6.3.5 Performance Comparison 58 Chapter 7 Conclusions and Future Work 59 7.1 Conclusions 59 7.2 Future Work 60 References 61 Appendix 6

Synthetic DNA applications in information technology

Synthetic DNA is a growing alternative to electronic-based technologies in fields such as data storage, product tagging, or signal processing. Its value lies in its characteristic attributes, namely Watson-Crick base pairing, array synthesis, sequencing, toehold displacement and polymerase chain reaction (PCR) capabilities. In this review, we provide an overview of the most prevalent applications of synthetic DNA that could shape the future of information technology. We emphasize the reasons why the biomolecule can be a valuable alternative for conventional electronic-based media, and give insights on where the DNA-analog technology stands with respect to its electronic counterparts.ISSN:2041-172