To overcome some of the deficiencies with current molecular typing schema for Campylobacter spp., we developed a prototype PCR binary typing (P-BIT) approach. We investigated the distribution of 68 gene targets in 58 Campylobacter jejuni strains, one Campylobacter lari strain, and two Campylobacter coli strains for this purpose. Gene targets were selected on the basis of distribution in multiple genomes or plasmids, and known or putative status as an epidemicity factor. Strains were examined with Penner serotyping, pulsed-field gel electrophoresis (PFGE; using SmaI and KpnI enzymes), and multilocus sequence typing (MLST) approaches for comparison. P-BIT provided 100% typeability for strains and gave a diversity index of 98.5%, compared with 97.0% for SmaI PFGE, 99.4% for KpnI PFGE, 96.1% for MLST, and 92.8% for serotyping. Numerical analysis of the P-BIT data clearly distinguished strains of the three Campylobacter species examined and correlated somewhat with MLST clonal complex assignations and with previous classifications of "high" and "low" risk. We identified 18 gene targets that conferred the same level of discrimination as the 68 initially examined. We conclude that P-BIT is a useful approach for subtyping, offering advantages of speed, cost, and potential for strain risk ranking unavailable from current molecular typing schema for Campylobacter spp.
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http://dx.doi.org/10.1128/AEM.02215-09 | DOI Listing |
Nat Commun
May 2024
Birck Nanotechnology Center, Purdue University, West Lafayette, IN, 47907, USA.
Probabilistic computing is a computing scheme that offers a more efficient approach than conventional complementary metal-oxide-semiconductor (CMOS)-based logic in a variety of applications ranging from optimization to Bayesian inference, and invertible Boolean logic. The probabilistic bit (or p-bit, the base unit of probabilistic computing) is a naturally fluctuating entity that requires tunable stochasticity; by coupling low-barrier stochastic magnetic tunnel junctions (MTJs) with a transistor circuit, a compact implementation is achieved. In this work, by combining stochastic MTJs with 2D-MoS field-effect transistors (FETs), we demonstrate an on-chip realization of a p-bit building block displaying voltage-controllable stochasticity.
View Article and Find Full Text PDFNanotechnology
September 2023
Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL 60208, United States of America.
Probabilistic (p-) computing is a physics-based approach to addressing computational problems which are difficult to solve by conventional von Neumann computers. A key requirement for p-computing is the realization of fast, compact, and energy-efficient probabilistic bits. Stochastic magnetic tunnel junctions (MTJs) with low energy barriers, where the relative dwell time in each state is controlled by current, have been proposed as a candidate to implement p-bits.
View Article and Find Full Text PDFNano Lett
November 2022
School of Materials Engineering, Purdue University, West Lafayette, Indiana47907, United States.
Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. Here, we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen.
View Article and Find Full Text PDFMicromachines (Basel)
June 2022
Zhejiang Lab, Hangzhou 311121, China.
Probabilistic computing is an emerging computational paradigm that uses probabilistic circuits to efficiently solve optimization problems such as invertible logic, where traditional digital computations are difficult to solve. This paper proposes a true random number generator (TRNG) based on resistive random-access memory (RRAM), which is combined with an activation function implemented by a piecewise linear function to form a standard p-bit cell, one of the most important parts of a p-circuit. A p-bit multiplexing strategy is also applied to reduce the number of p-bits and improve resource utilization.
View Article and Find Full Text PDFNature
September 2019
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA.
Conventional computers operate deterministically using strings of zeros and ones called bits to represent information in binary code. Despite the evolution of conventional computers into sophisticated machines, there are many classes of problems that they cannot efficiently address, including inference, invertible logic, sampling and optimization, leading to considerable interest in alternative computing schemes. Quantum computing, which uses qubits to represent a superposition of 0 and 1, is expected to perform these tasks efficiently.
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