Efficient Conversion of Acetate to 3-Hydroxypropionic Acid by Engineered Escherichia coli

Acetate, which is an abundant carbon source, is a potential feedstock for microbial processes that produce diverse value-added chemicals. In this study, we produced 3-hydroxypropionic acid (3-HP) from acetate with engineered Escherichia coli. For the efficient conversion of acetate to 3-HP, we initially introduced heterologous mcr (encoding malonyl-CoA reductase) from Chloroflexus aurantiacus. Then, the acetate assimilating pathway and glyoxylate shunt pathway were activated by overexpressing acs (encoding acetyl-CoA synthetase) and deleting iclR (encoding the glyoxylate shunt pathway repressor). Because a key precursor malonyl-CoA is also consumed for fatty acid synthesis, we decreased carbon flux to fatty acid synthesis by adding cerulenin. Subsequently, we found that inhibiting fatty acid synthesis dramatically improved 3-HP production (3.00 g/L of 3-HP from 8.98 g/L of acetate). The results indicated that acetate can be used as a promising carbon source for microbial processes and that 3-HP can be produced from acetate with a high yield (44.6% of the theoretical maximum yield).11Ysciescopu

A Reinforcement Learning Approach to Access Management in Wireless Cellular Networks

In smart city applications, huge numbers of devices need to be connected in an autonomous manner. 3rd Generation Partnership Project (3GPP) specifies that Machine Type Communication (MTC) should be used to handle data transmission among a large number of devices. However, the data transmission rates are highly variable, and this brings about a congestion problem. To tackle this problem, the use of Access Class Barring (ACB) is recommended to restrict the number of access attempts allowed in data transmission by utilizing strategic parameters. In this paper, we model the problem of determining the strategic parameters with a reinforcement learning algorithm. In our model, the system evolves to minimize both the collision rate and the access delay. The experimental results show that our scheme improves system performance in terms of the access success rate, the failure rate, the collision rate, and the access delay

Enhanced volcanic activity and long-term warmth in the middle Eocene revealed by mercury and osmium isotopes from IODP Expedition 369 Site U1514

Rapid plate reorganization may have influenced global climate during the Eocene; however, its linkage remains poorly constrained, particularly during the middle Eocene. To elucidate this tectonic–climatic relationship, here, we conducted a comprehensive analysis based on high-resolution mercury (Hg) and osmium (Os) abundance and isotope data obtained from the complete Eocene sedimentary sequence of Site U1514, drilled in the Mentelle Basin off southwest Australia. The Hg signals in this sedimentary sequence, which are characterized by significantly high enrichment and insignificant mass-independent fractionation (Δ199Hg) signal, confirm that the middle Eocene (∼45–38 Ma) was a period of persistent, increased volcanism, accompanied by intense tectonic activity. In particular, a remarkable seafloor volcanic eruption persisted for approximately 1.5 million years (∼42.0–40.5 Ma), immediately preceding the Middle Eocene Climate Optimum (MECO). Contemporaneously, the trends toward a slightly more radiogenic seawater 187Os/188Os (Osi) composition denote the prevalence of intensified continental weathering under a warm, humid climate during the middle Eocene, a phenomenon particularly evident during the MECO. Importantly, the Hg and Os records from Site U1514 reveal the occurrence of a multi-million-year warming reversal amid the long-term Eocene cooling trend, which likely contributed to significant CO2 reduction during the late Eocene. These findings significantly enhance our understanding of Eocene climate dynamics, which are fundamentally linked to intensive tectonic-driven volcanic activity and associated continental chemical weathering

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

A Stepwise and Hybrid Trust Evaluation Scheme for Tactical Wireless Sensor Networks

In tactical wireless sensor networks, tactical sensors are increasingly expected to be exploited for information collection in battlefields or dangerous areas on behalf of soldiers. The main function of these networks is to use sensors to measure radiation, nuclear, and biochemical values for the safety of allies and also to monitor and carry out reconnaissance of enemies. These tactical sensors require a network traffic flow that sends various types of measured information to the gateway, which needs high reliability. To ensure reliability, it must be able to detect malicious nodes that perform packet-dropping attacks to disrupt the network traffic flow, and energy-constrained sensors require energy-efficient methods to detect them. Therefore, in this paper, we propose a stepwise and hybrid trust evaluation scheme for locating malicious nodes that perform packet-dropping attacks in a tree-based network. Sensors send a query to the gateway by observing the traffic patterns of their child nodes. Moreover, depending on the situation, the gateway detects malicious nodes by choosing between gateway-assisted trust evaluation and gateway-independent trust evaluation. We implemented and evaluated the proposed scheme with the OPNET simulator, and the results showed that a higher packet delivery ratio can be achieved with significantly lower energy consumption

Extending the Leverage of Air-Bridge Thermophotovoltaic Architecture: Design, Modeling, and Experimental Demonstration

Diversifying renewable energy sources is important for reducing greenhouse gas emissions, promoting energy security, and economic development. Thermophotovoltaics (TPV) are promising for energy harvesting using electromagnetic radiation to generate electricity via the photovoltaic effect. Photon recycling enabled by spectrally selective TPV cells, in particular, has sparked intense research interest in the pursuit of high-efficiency TPV systems. An air-bridge (AB) TPV architecture can optimize out-of-band (OOB) photon recycling by suppressing Fresnel reflections at the interface between air and semiconductors. However, a thin-film TPV membrane spanning Au gridlines that forms the air bridge is vulnerable to being buckled and cracked due to the small tolerances to strain (less than 1–2 %) before fracture. Such structural failures limit the application of the AB-TPV architectures for energy conversion applications. This thesis focuses on overcoming the challenges and exploring the use of thin-film TPV architectures in many applications. These studies present comprehensive strategies for the diverse applications of AB-TPV architectures. Understanding the mechanism of thin-film membrane buckling suggests a solution for extending AB-TPV architecture for renewable and sustainable energy harvesting. The demonstrations of InGaAs thin-film AB-TPV devices overcome persistent challenges such as low yield and difficulty of fabrication. The multi-air-bridge tandem structure provides an innovative solution to realize unlimited bandgap partners and optimize photon recycling with air bridges. Identifying the factors limiting the TPV performance helps to forecast the possible PCE limit for AB-TPV cells. Finally, this work opens up the possibility for realizing high-efficiency thin-film AB-TPV architectures.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/176595/1/jihunlim_1.pd

A Reinforcement Learning Approach to Access Management in Wireless Cellular Networks

In smart city applications, huge numbers of devices need to be connected in an autonomous manner. 3rd Generation Partnership Project (3GPP) specifies that Machine Type Communication (MTC) should be used to handle data transmission among a large number of devices. However, the data transmission rates are highly variable, and this brings about a congestion problem. To tackle this problem, the use of Access Class Barring (ACB) is recommended to restrict the number of access attempts allowed in data transmission by utilizing strategic parameters. In this paper, we model the problem of determining the strategic parameters with a reinforcement learning algorithm. In our model, the system evolves to minimize both the collision rate and the access delay. The experimental results show that our scheme improves system performance in terms of the access success rate, the failure rate, the collision rate, and the access delay

Metabolic Engineering of 3-Hydroxypropionic Acid producing Escherichia coli via Malonyl-CoA Dependent Pathway

2