Clinical trials may often be encountered with truncation-by-death problem, where subjects enrolled in the experiment dies before their outcomes are collected. It is worth noting that truncation by death is a totally different concept from censoring. Censoring refers to the cases that subjects do have an outcome (such as time to recovery), but this outcome is masked by loss of follow-up, while truncation by death leaves the outcome undefined. In this article, we address the truncation-by death issue by reviewing two clinical trials on remdesivir for COVID-19, and provide some instructions to deal with the truncation-by-death problem.
Metal-organic frameworks (MOFs) are innovative porous structures consisting of metal ions and organic ligands, which have been verified for extraordinary applications in nanomedicine and pharmaceuticals. PCN-224 is a type of Zr-based MOFs, which has recently emerged as one of the most attractive nanomaterials for various applications, such as drug delivery, bioimaging and cancer therapy due to its favorable and fascinating physical-chemical properties. However, the safety evaluation and the potential toxicological properties remain unclear. In this study, the general cytotoxicity of PCN-224 were examined in both human hepatocytes L-02 cells and mouse macrophages RAW264.7. Furthermore, the effect of inflammation and autophagy were measured in L-02 cells. The results indicated that PCN-224 was engulfed in L-02 cells and subsequently resulted in morphological changes, cell membrane destruction, and oxidative stress in L-02 cells. PCN-224 might trigger inflammation by promoting the secretion of inflammatory factors such as Tumor necrosis factors (TNF-alpha) and Interleukin (IL-6). PCN-224 might induce autophagosome accumulation and subsequently autophagic dysfunction. Additionally, PCN-224 induced cytotoxicity in RAW264.7 cells and increased the protein levels of the inflammasome component NLR Family Pyrin Domain Containing 3 (NLRP3) molecular, which indicated its cellular effects in different cell types. All of these results will support the reasonable use of PCN-224.
With deep peak-load regulations, utility boilers are frequently operated under variable/low load conditions. However, their hydrodynamics, combustion and NOx emission characteristics are uncertain and relevant theoretical guidance are lacking. For this purpose, a comprehensive CFD model including flow, coal combustion and NOx formation is established for a 630 MW tangentially fired pulverized-coal boiler, aiming at solving the problem of decreasing combustion stability and increasing NOx emission in low-load operation. Based on the grid independence and model validation, the flow field, temperature profile, species concentration profile and NOx emission are predicted, and the influences of angle/arrangement of burners are further evaluated. Simulation results indicate that under low-load conditions, residual airflow rotation still persists at the top of boiler regardless of how to adjust the angle/arrangement of burners. With tilting the burner angle upward, flame is more concentrated, combustion becomes more stable, and heat flux rises in the upper zone; the burner arrangement of ABDE gives more uniform temperature distribution in the combustion zone. CO species shows higher content in the combustion zone; the 0° tilt angle gives maximum CO content, followed by the 15° angle, and finally the −15° angle; compared to the ACDE and ABCE arrangement, the ABDE arrangement mode gives much lower CO contents. Burner tilt angle of −15° benefits for lower NOx emission (183 mg/m3) but goes against stable combustion; the burner arrangement mode of ABDE is optimal for the present boiler, which ensures both stable combustion and lower NOx emission (209 mg/m3).
The Internet of Things (IoT) is an interface with the physical world that usually operates in random-sparse-event (RSE) scenarios. This article discusses main challenges of IoT chips: power consumption, power supply, artificial intelligence (AI), small-signal acquisition, and evaluation criteria. To overcome these challenges, many works recently aimed at IoT system design have emerged. This work reviews the architecture and circuit innovations that have contributed to IoT developments. This paper does not cover security of IoT. Event-driven architectures and nonuniform sampling ADCs significantly reduce the long-term average power. Besides, embedding AI engines in IoT nodes (AIoT) is one critical trend. The computing-in-memory technique improves the energy efficiency of the AI engine. Asynchronous spike neural networks (ASNNs) AI engines show low power potential. In addition to data processing, small-signal acquisition is also critical. The charge-domain analog-front-end (AFE) techniques such as floating inverter-based amplifiers improve energy efficiency. In addition to the above low power and high energy efficiency technologies, energy harvesting can also enhance the lifetime of AIoT devices. This article discusses recent ambient RF and natural energy harvesting approaches and high-efficiency DC-DC with a wide load range. Finally, novel evaluation criteria are introduced to establish benchmark standards for AIoT chips.
Widespread antibiotic resistance across Earth's habitats has become a critical health concern. However, large-scale investigation on the distribution of antibiotic resistance genes (ARGs) in the microbiomes from most types of ecosystem is still lacking. In this study, we provide a comprehensive characterization of ARGs for 52,515 microbial genomes covering various Earth's ecosystems, and conduct the risk assessment for ARG-carrying species based on further identification of mobile genetic elements (MGEs) and virulence factor genes (VFGs). We identify a total of 6159 ARG-carrying metagenome-assembled genomes (ACMs), and most of them are recovered from human gut and city subway. Our results show that efflux pump is the most common mechanism for bacteria to acquire multidrug resistance genes in Earth's microbiomes. Enterobacteriaceae species are the largest hosts of ARGs, accounting for 14% of total ACMs with 64% of the total ARG hits. Most of ARG-carrying species are unique in the different ecosystem categories, while 33 potential background ARGs are commonly shared by all ecosystem categories. We then detect 36 high-risk ARGs that likely threat public health in all ACMs. Based on ranking the importance of ARG-carrying species in the different ecosystem categories, several bacterial taxa such as Escherichia coli, Enterococcus faecalis, and Pseudomonas_A stutzeri are recognized as priority species for surveillance and control. Overall, our study gives a broad view of ARG-host associations in the environments.