Self-assembling subnanometer pores with unusual mass-transport properties

A long-standing aim in molecular self-assembly is the development of synthetic nanopores capable of mimicking the mass-transport characteristics of biological channels and pores. Here we report a strategy for enforcing the nanotubular assembly of rigid macrocycles in both the solid state and solution based on the interplay of multiple hydrogen-bonding and aromatic π − π stacking interactions. The resultant nanotubes have modifiable surfaces and inner pores of a uniform diameter defined by the constituent macrocycles. The self-assembling hydrophobic nanopores can mediate not only highly selective transmembrane ion transport, unprecedented for a synthetic nanopore, but also highly efficient transmembrane water permeability. These results establish a solid foundation for developing synthetically accessible, robust nanostructured systems with broad applications such as reconstituted mimicry of defined functions solely achieved by biological nanostructures, molecular sensing, and the fabrication of porous materials required for water purification and molecular separations

Etiologic Diagnosis of Lower Respiratory Tract Bacterial Infections Using Sputum Samples and Quantitative Loop-Mediated Isothermal Amplification

Etiologic diagnoses of lower respiratory tract infections (LRTI) have been relying primarily on bacterial cultures that often fail to return useful results in time. Although DNA-based assays are more sensitive than bacterial cultures in detecting pathogens, the molecular results are often inconsistent and challenged by doubts on false positives, such as those due to system- and environment-derived contaminations. Here we report a nationwide cohort study on 2986 suspected LRTI patients across P. R. China. We compared the performance of a DNA-based assay qLAMP (quantitative Loop-mediated isothermal AMPlification) with that of standard bacterial cultures in detecting a panel of eight common respiratory bacterial pathogens from sputum samples. Our qLAMP assay detects the panel of pathogens in 1047(69.28%) patients from 1533 qualified patients at the end. We found that the bacterial titer quantified based on qLAMP is a predictor of probability that the bacterium in the sample can be detected in culture assay. The relatedness of the two assays fits a logistic regression curve. We used a piecewise linear function to define breakpoints where latent pathogen abruptly change its competitive relationship with others in the panel. These breakpoints, where pathogens start to propagate abnormally, are used as cutoffs to eliminate the influence of contaminations from normal flora. With help of the cutoffs derived from statistical analysis, we are able to identify causative pathogens in 750 (48.92%) patients from qualified patients. In conclusion, qLAMP is a reliable method in quantifying bacterial titer. Despite the fact that there are always latent bacteria contaminated in sputum samples, we can identify causative pathogens based on cutoffs derived from statistical analysis of competitive relationship

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

Regulatory Roles of MicroRNAs in Diabetes

MicroRNAs (miRNAs), a class of endogenous small noncoding RNAs in eukaryotes, have been recognized as significant regulators of gene expression through post-transcriptional mechanisms. To date, >2000 miRNAs have been identified in the human genome, and they orchestrate a variety of biological and pathological processes. Disruption of miRNA levels correlates with many diseases, including diabetes mellitus, a complex multifactorial metabolic disorder affecting >400 million people worldwide. miRNAs are involved in the pathogenesis of diabetes mellitus by affecting pancreatic β-cell functions, insulin resistance, or both. In this review, we summarize the investigations of the regulatory roles of important miRNAs in diabetes, as well as the potential of circulating miRNAs as diagnostic markers for diabetes mellitus

Kryptein: a compressive-sensing-based encryption scheme for the Internet of Things

Internet of Things (IoT) is flourishing and has penetrated deeply into people's daily life. With the seamless connection to the physical world, IoT provides tremendous opportunities to a wide range of applications. However, potential risks exist when the IoT system collects sensor data and uploads it to the cloud. The leakage of private data can be severe with curious database administrator or malicious hackers who compromise the cloud. In this work, we propose Kryptein, a compressive-sensing-based encryption scheme for cloud-enabled IoT systems to secure the interaction between the IoT devices and the cloud. Kryptein supports random compressed encryption, statistical decryption, and accurate raw data decryption. According to our evaluation based on two real datasets, Kryptein provides strong protection to the data. It is 250 times faster than other state-of-the-art systems and incurs 120 times less energy consumption. The performance of Kryptein is also measured on off-the-shelf IoT devices, and the result shows Kryptein can run efficiently on IoT devices

Physicochemical properties and feasibility of coconut oil-based diacylglycerol as an alternative fat for healthy non-dairy creamer

Non-dairy creamers have been widely used for coffee whitening and texture improvement. To avoid the intake of trans fatty acids from partially hydrogenated oil, coconut oil-based diacylglycerol (CO-DAG) was applied in non-dairy creamer as core material. In this study, effects of DAG content (30, 50, 70, 90%) on the characteristics of CO-DAG were evaluated, including rheological and thermodynamic properties. The CO-DAG with a content of 50% exhibited a wide plastic range and contained mixture of β and β' polymorphic forms. Using CO-DAG (50%) as core material, the physicochemical properties of non-dairy creamer were characterized and compared with commercial products. The results indicated that CO-DAG-based non-dairy creamers showed similar encapsulation efficiency (92.74%) and thermal stability to commercial products. Furthermore, CO-DAG-based non-dairy creamer showed higher whiteness index (54.20) than commercial non-dairy creamers (50.22) when applied to black coffee. Overall, it is anticipated that CO-DAG-based non-dairy creamers have great potentials in coffee whitening

Rapid fabrication of a microdevice with concave microwells and its application in embryoid body formation

Here, we report a novel method for the fabrication of polydimethylsiloxane microdevices with complicated 3-D structures, such as concave and crater shapes, using an easily machined polymethyl methacrylate mold combined with a one-step molding process. The procedure presented here enables rapid preparation of complex 3-D microstructures varying in shape and dimensions. To regulate embryoid body (EB) formation, we fabricated a microfluidic device with an array of concave microwells and found that EBs growing in microwells maintained their shape, viability, and a high degree of homogeneity. We believe that this novel method provides an alternative for rapid prototyping, especially in fabricating devices with curved 3-D microstructures

Towards a Compressive-Sensing-Based Lightweight Encryption Scheme for the Internet of Things

Internet of Things (IoT) is flourishing and has penetrated deeply into people’s daily life. With the seamless connection to the physical world, IoT provides tremendous opportunities to a wide range of applications. However, potential risks exist when the IoT system collects sensor data and uploads it to the Cloud. The leakage of private data can be severe with curious database administrator or malicious hackers who compromise the Cloud. In this work, we propose Kryptein, a compressive-sensing-based lightweight encryption scheme for Cloud-enabled IoT systems to secure the interaction between the IoT devices and the Cloud. Kryptein supports random compressed encryption, statistical computation over cipher, and accurate raw data decryption. According to our evaluation based on two real datasets, Kryptein provides strong protection to the data. It is 250 times faster than other state-of-the-art systems and incurs 120 times less energy consumption. The performance of Kryptein is also measured on off-the-shelf IoT devices, and the result shows Kryptein can run efficiently on IoT devices. After comparing with other state-of-the-art lightweight ciphers on IoT (Simon and Speck), IoT system with Kryptein is expected to have a much more longevity with about 35 percent extended lifetime. Further, experiments illustrated IoT data variance will not affect Kryptein’s accuracy in a long term usage, and Krpytein is also able to support basic analytics tasks like machine learning (e.g., classification)