Modulation of engineered nanomaterial interactions with organ barriers for enhanced drug transport

The biomedical use of nanoparticles (NPs) has been the focus of intense research for over a decade. As most NPs are explored as carriers to alter the biodistribution, pharmacokinetics and bioavailability of associated drugs, the delivery of these NPs to the tissues of interest remains an important topic. To date, the majority of NP delivery studies have used tumor models as their tool of interest, and the limitations concerning tumor targeting of systemically administered NPs have been well studied. In recent years, the focus has also shifted to other organs, each presenting their own unique delivery challenges to overcome. In this review, we discuss the recent advances in leveraging NPs to overcome four major biological barriers including the lung mucus, the gastrointestinal mucus, the placental barrier, and the blood-brain barrier. We define the specific properties of these biological barriers, discuss the challenges related to NP transport across them, and provide an overview of recent advances in the field. We discuss the strengths and shortcomings of different strategies to facilitate NP transport across the barriers and highlight some key findings that can stimulate further advances in this field.</p

Efficient Q-Value Zero-Leakage Protection Scheme in SRS Regularly Publishing Private Data

Spontaneous Reporting System (SRS) has been widely established to collect adverse drug events. Thus, SRS promotes the detection and analysis of ADR (adverse drug reactions), such as the FDA Adverse Event Reporting System (FAERS). The SRS data needs to be provided to researchers. Meanwhile, the SRS data is publicly available to facilitate the study of ADR detection and analysis. In general, SRS data contains private information of some individual characteristics. Before the information is published, it is necessary to anonymize private information in the SRS data to prevent disclosure of individual privacy. There are many privacy protection methods. The most classic method for protecting SRS data is called as PPMS. However, in the real world, SRS data is growing dynamically and needs to be published regularly. In this case, PPMS has some shortcomings in the memory consumption, anonymity efficiency, data update and data security. To remove these shortcomings, we propose an Efficient Q-value Zero-leakage protection Scheme in SRS regularly publishing private data, called EQZS. EQZS can deal with almost all of potential attacks. Meanwhile, EQZS removes the shortcomings of PPMS. The experimental results show that our scheme EQZS solves the problem of privacy leakage in SRS regularly publishing private data. Meanwhile, EQZS significantly outperforms PPMS on the efficiency of memory consumption, privacy anonymity and data update

Modulation of engineered nanomaterial interactions with organ barriers for enhanced drug transport

The biomedical use of nanoparticles (NPs) has been the focus of intense research for over a decade. As most NPs are explored as carriers to alter the biodistribution, pharmacokinetics and bioavailability of associated drugs, the delivery of these NPs to the tissues of interest remains an important topic. To date, the majority of NP delivery studies have used tumor models as their tool of interest, and the limitations concerning tumor targeting of systemically administered NPs have been well studied. In recent years, the focus has also shifted to other organs, each presenting their own unique delivery challenges to overcome. In this review, we discuss the recent advances in leveraging NPs to overcome four major biological barriers including the lung mucus, the gastrointestinal mucus, the placental barrier, and the blood-brain barrier. We define the specific properties of these biological barriers, discuss the challenges related to NP transport across them, and provide an overview of recent advances in the field. We discuss the strengths and shortcomings of different strategies to facilitate NP transport across the barriers and highlight some key findings that can stimulate further advances in this field.</p

Partial cystectomy for bladder squamous cell carcinoma with a 10-year follow-up: a case report

Squamous cell carcinoma (SCC) of the bladder is a rare malignancy of the urinary system. It is prone to invasion and metastasis in the early stage and has a poor prognosis. This case reports a 65-year-old female patient with SCC of the bladder who was free of disease recurrence and metastasis 10 years after partial cystectomy (PC) combined with left ureteral reimplantation. The treatment plan and admission of this patient were retrospectively analyzed in order to provide some reference significance for the treatment plan for the SCC of the bladder

Characterization of an aspartate aminotransferase encoded by YPO0623 with frequent nonsense mutations in Yersinia pestis

Yersinia pestis, the causative agent of plague, is a genetically monomorphic bacterial pathogen that evolved from Yersinia pseudotuberculosis approximately 7,400 years ago. We observed unusually frequent mutations in Y. pestis YPO0623, mostly resulting in protein translation termination, which implies a strong natural selection. These mutations were found in all phylogenetic lineages of Y. pestis, and there was no apparent pattern in the spatial distribution of the mutant strains. Based on these findings, we aimed to investigate the biological function of YPO0623 and the reasons for its frequent mutation in Y. pestis. Our in vitro and in vivo assays revealed that the deletion of YPO0623 enhanced the growth of Y. pestis in nutrient-rich environments and led to increased tolerance to heat and cold shocks. With RNA-seq analysis, we also discovered that the deletion of YPO0623 resulted in the upregulation of genes associated with the type VI secretion system (T6SS) at 26°C, which probably plays a crucial role in the response of Y. pestis to environment fluctuations. Furthermore, bioinformatic analysis showed that YPO0623 has high homology with a PLP-dependent aspartate aminotransferase in Salmonella enterica, and the enzyme activity assays confirmed its aspartate aminotransferase activity. However, the enzyme activity of YPO0623 was significantly lower than that in other bacteria. These observations provide some insights into the underlying reasons for the high-frequency nonsense mutations in YPO0623, and further investigations are needed to determine the exact mechanism

RNA therapeutics in the clinic

Abstract Ribonucleic acid (RNA) therapeutics are being actively researched as a therapeutic modality in preclinical and clinical studies. They have become one of the most ubiquitously known and discussed therapeutics in recent years in part due to the ongoing coronavirus pandemic. Since the first approval in 1998, research on RNA therapeutics has progressed to discovering new therapeutic targets and delivery strategies to enhance their safety and efficacy. Here, we provide an overview of the current clinically relevant RNA therapeutics, mechanistic basis of their function, and strategies to improve their clinical use. We discuss the 17 approved RNA therapeutics and perform an in‐depth analysis of the 222 ongoing clinical trials, with an emphasis on their respective mechanisms and disease areas. We also provide perspectives on the challenges for clinical translation of RNA therapeutics and suggest potential strategies to address these challenges

Grouping Neural Network-Based Smith PID Temperature Controller for Multi-Channel Interaction System

The thermal vacuum test (TVT) is an important verification process in the development of spacecraft and load. There are often multiple temperature points on the device under test (DUT) that require control. The interaction among multiple channels poses a challenge for temperature control in the TVT. To solve this problem, a multi-channel Smith proportional–integral–derivative (PID) controller based on a grouping neural network (Grouping-NN) is proposed. Firstly, the mathematical derivation for a typical multi-channel temperature control model of the TVT is carried out. Then, the multi-channel interaction system is identified using a Grouping-NN to predict the output temperature of each channel by grouping the hidden layer neurons according to the number of channels. Finally, two Grouping-NNs are utilized to update the Smith predictor, and the time-delay error is fed back to the PID controller, which is used to optimize the control effect of the multi-channel interaction system under high time delay. The proposal is compared with the traditional PID controller and Smith predictor-based PID controller through simulation. The simulation results show that the proposed method has better suppression of overshooting. In addition, the algorithm is verified by controlling the temperature of six channels in a practical thermal vacuum test