Matrix Manipulation of Directly-Synthesized PbS Quantum Dot Inks Enabled by Coordination Engineering

The direct-synthesis of conductive PbS quantum dot (QD) ink is facile, scalable, and low-cost, boosting the future commercialization of optoelectronics based on colloidal QDs. However, manipulating the QD matrix structures still is a challenge, which limits the corresponding QD solar cell performance. Here, for the first time a coordination-engineering strategy to finely adjust the matrix thickness around the QDs is presented, in which halogen salts are introduced into the reaction to convert the excessive insulating lead iodide into soluble iodoplumbate species. As a result, the obtained QD film exhibits shrunk insulating shells, leading to higher charge carrier transport and superior surface passivation compared to the control devices. A significantly improved power-conversion efficiency from 10.52% to 12.12% can be achieved after the matrix engineering. Therefore, the work shows high significance in promoting the practical application of directly synthesized PbS QD inks in large-area low-cost optoelectronic devices.     

Genetic and Epigenomic Modifiers of Diabetic Neuropathy

Diabetic neuropathy (DN), the most common chronic and progressive complication of diabetes mellitus (DM), strongly affects patients’ quality of life. DN could be present as peripheral, autonomous or, clinically also relevant, uremic neuropathy. The etiopathogenesis of DN is multifactorial, and genetic components play a role both in its occurrence and clinical course. A number of gene polymorphisms in candidate genes have been assessed as susceptibility factors for DN, and most of them are linked to mechanisms such as reactive oxygen species production, neurovascular impairments and modified protein glycosylation, as well as immunomodulation and inflammation. Different epigenomic mechanisms such as DNA methylation, histone modifications and non-coding RNA action have been studied in DN, which also underline the importance of “metabolic memory” in DN appearance and progression. In this review, we summarize most of the relevant data in the field of genetics and epigenomics of DN, hoping they will become significant for diagnosis, therapy and prevention of DN.     

In Silico Analysis of the Molecular-Level Impact of SMPD1 Variants on Niemann-Pick Disease Severity

Sphingomyelin phosphodiesterase (SMPD1) is a key enzyme in the sphingolipid metabolism. Genetic SMPD1 variants have been related to the Niemann-Pick lysosomal storage disorder, which has different degrees of phenotypic severity ranging from severe symptomatology involving the central nervous system (type A) to milder ones (type B). They have also been linked to neurodegenerative disorders such as Parkinson and Alzheimer. In this paper, we leveraged structural, evolutionary and stability information on SMPD1 to predict and analyze the impact of variants at the molecular level. We developed the SMPD1-ZooM algorithm, which is able to predict with good accuracy whether variants cause Niemann-Pick disease and its phenotypic severity; the predictor is freely available for download. We performed a large-scale analysis of all possible SMPD1 variants, which led us to identify protein regions that are either robust or fragile with respect to amino acid variations, and show the importance of aromatic-involving interactions in SMPD1 function and stability. Our study also revealed a good correlation between SMPD1-ZooM scores and in vitro loss of SMPD1 activity. The understanding of the molecular effects of SMPD1 variants is of crucial importance to improve genetic screening of SMPD1-related disorders and to develop personalized treatments that restore SMPD1 functionality.     

Acquisition and Spread of Antimicrobial Resistance: A tet(X) Case Study

Understanding the mechanisms leading to the rise and dissemination of antimicrobial resistance (AMR) is crucially important for the preservation of power of antimicrobials and controlling infectious diseases. Measures to monitor and detect AMR, however, have been significantly delayed and introduced much later after the beginning of industrial production and consumption of antimicrobials. However, monitoring and detection of AMR is largely focused on bacterial pathogens, thus missing multiple key events which take place before the emergence and spread of AMR among the pathogens. In this regard, careful analysis of AMR development towards recently introduced antimicrobials may serve as a valuable example for the better understanding of mechanisms driving AMR evolution. Here, the example of evolution of tet(X), which confers resistance to the next-generation tetracyclines, is summarised and discussed. Initial mechanisms of resistance to these antimicrobials among pathogens were mostly via chromosomal mutations leading to the overexpression of efflux pumps. High-level resistance was achieved only after the acquisition of flavin-dependent monooxygenase-encoding genes from the environmental microbiota. These genes confer resistance to all tetracyclines, including the next-generation tetracyclines, and thus were termed tet(X). ISCR2 and IS26, as well as a variety of conjugative and mobilizable plasmids of different incompatibility groups, played an essential role in the acquisition of tet(X) genes from natural reservoirs and in further dissemination among bacterial commensals and pathogens. This process, which took place within the last decade, demonstrates how rapidly AMR evolution may progress, taking away some drugs of last resort from our arsenal.     

Optimized structure and electrochemical properties of sulfonated carbon nanotubes/Co–Ni bimetallic layered hydroxide composites for high-performance supercapacitors

Technical development in electronic devices is frequently stifled by their insufficient capacity and cyclic stability of energy-storage devices. The nano-structured materials have sensational importance for providing novel and optimized combination to overcome exiting boundaries and provide efficient energy storage systems. Metal hydroxide materials with high capacity for pseudo-capacitance properties have grabbed special attention. Lately, the blend of nickel and cobalt hydroxides has been considered as a favorable class of metallic hydroxide materials owing to their comparatively high capacitance and exceptional redox reversibility. The sulfonated carbon nanotube fluid (SCNTF) was prepared by the ion exchange method to be utilized as the exceptional templates due to astonishing specific surface area, ensuring the maximum utilization of the active material. The CoNi-layered double hydroxides (LDHs)/SCNTF core-shell nanocomposite was prepared by the simple solvothermal method. Structural analysis showed that the composite material had the high conductance of carbon materials, the pseudo-capacitance characteristics of metal hydroxides, and porous structure, which facilitates the ion shuttle when the electrolyte reacts with the active material. Electrochemical analysis results showed that CoNi-LDHs/SCNTF had excellent rate performance, reversible charge-discharge properties and cycle stability. It exhibited an extreme specific capacity of 1190.5 F g^?1 at a current density of 1 A g^?1; whereas specific capacity remained 953.7 F g^?1 at the current density was 10 A g^?1. In addition, the capacity retention rate after 5000 charge-discharge cycles at a current density of 20 A g^?1 was 81.0%. The results indicated that the CoNi-LDHs/SCNTF core-shell nanocomposite material is cost efficient and an effective substitute in energy storage applications.     

基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level，SPL）作为单一评价指标，既不能全面反映噪声的物理属性，也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声，引入声品质，运用大涡模拟（Large eddy simulation，LES）对风振噪声进行数值仿真，根据实车道路试验判断仿真的准确性；对仿真结果进行声品质客观评价与主观评价，综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型；利用遗传算法（Genetic algorithm，GA），进一步对BP神经网络的结构参数进行优化，建立GA-BP声品质预测模型。研究结果表明，GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果，其预测值可以代替传统的声压级评价指标，为风振噪声提供更为准确合理的评价。