Evaluation of Interactions between SARS-CoV-2 RBD and Full-Length ACE2 with Coarse-Grained Molecular Dynamics Simulations.

Compared to all-atom models, coarse-grained models enable the investigation of the dynamics of simulation systems on a much larger length scale and a longer time scale, which makes them suitable for studying macromolecular systems. Hence, in this work, we performed multiple µs-scale Martini coarse-grained molecular dynamics simulations to reveal the interaction details between SARS-CoV-2 RBD and full-length human ACE2. Besides, the key coarse-grained systems were backmapped into the corresponding all-atom system for the display of structural details. Our results indicated that the plier structure in two ends of the binding interface plays a key role in the binding process of SARS-CoV-2 RBD with ACE2. Furthermore, we also found that when there is no B0AT1 in the simulation system, the N-terminus of ACE2 is more likely to approach the cell membrane, which has a strong correlation with the subsequent fusion of the virus with the cell membrane. These binding details of SARS-CoV-2 RBD and the ACE2 protease domain (PD) as well as the membrane orientation thermodynamics can promote the development of therapeutic drugs and preventive vaccines against SARS-CoV-2.

Revealing the crystal phases of primary particles formed during the coprecipitation of iron oxides.

The mechanistic investigation of the coprecipitation formation of iron oxides has been a long-standing challenge due to the rapid reaction kinetics and high complexity of iron hydrolysis reactions. Although a few studies have suggested that the coprecipitation of iron oxide nanoparticles follows a non-classic route through inter-particle attachment, the compositions of the primary particles remain undetermined. Herein, by using a specially designed gas/liquid mixed phase fluidic reactor we controlled the reaction time from 3 s to over 5 min, and successfully identified the concentration of different intermediate phases as a function of time. We suggest that the initial Fe3+ ions are hydrolyzed under the alkaline condition to give Fe(OH)3, which then rapidly dehydrates to yield α-FeOOH. In the presence of Fe2+ ions, which could also act as the catalyst, α-FeOOH finally transforms to Fe3O4.

Moderate cooling coprecipitation for extremely small iron oxide as a pH dependent T1-MRI contrast agent.

Iron based nanomedicine (IBNM) has been one powerful diagnostic tool as a magnetic resonance imaging (MRI) contrast agent (CA) in the clinic for years. Conventional IBNMs are generally employed as T2-MRI CAs, but most of them are constrained in clinical indication expansion by magnetic susceptibility artifacts. In comparison, extremely small iron oxide (ESIO) with a core size less than 5 nm has demonstrated the T1-MRI effect, which provides prospects for a Gd-based agent alternative. Nevertheless, currently developed ESIOs for T1-MRI CAs always require harsh conditions such as a high temperature and high boiling point reagent. Moreover, very few of the currently developed ESIOs meet the stringent pharmaceutical standard. Herein, on the basis of a crystal nuclear precipitation-dissolution equilibrium mechanism and outer/inner sphere T1-MRI theory, monodisperse ESIOs with an average size of 3.43 nm (polydispersity index of 0.104) are fabricated using a moderate cooling procedure with mild coprecipitation reaction conditions. The as-synthesized ESIOs display around 3-fold higher T1 MRI signal intensity than that of commercial Ferumoxytol (FMT), comparable to that of Gd-based CAs in vitro. Additionally, the T1-MRI performance of the ESIOs is pH dependent and delivers bright signal augmentation. Eventually, the internalization into mesenchymal stem cells of the ESIO is realized in the absence of a transferring agent. Considering the identical structure and composition of the ESIOs as compared to that of FMT, they could meet the pharmaceutical criteria, thus providing great potential as T1-MRI Cas, for instance as stem cell tracers.

A Deep Learning-Based Radiomics Model for Differentiating Benign and Malignant Renal Tumors.

OBJECTIVES: To investigate the effect of transfer learning on computed tomography (CT) images for the benign and malignant classification on renal tumors and to attempt to improve the classification accuracy by building patient-level models. METHODS: One hundred ninety-two cases of renal tumors were collected and identified by pathologic diagnosis within 15 days after enhanced CT examination (66% male, 70% malignant renal tumors, average age of 62.27 ±â€¯12.26 years). The InceptionV3 model pretrained by the ImageNet dataset was cross-trained to perform this classification. Five image-level models were established for each of the Slice, region of interest (ROI), and rectangular box region (RBR) datasets. Then, two patient-level models were built based on the optimal image-level models. The network's performance was evaluated through analysis of the receiver operating characteristic (ROC) and five-fold cross-validation. RESULTS: In the image-level models, the test results of model trained on the Slice dataset [accuracy (ACC) = 0.69 and Matthews correlation coefficient (MCC) = 0.45] were the worst. The corresponding results on the ROI dataset (ACC = 0.97 and MCC = 0.93) were slightly better than those on the RBR dataset (ACC = 0.93 and MCC = 0.85) when freezing the weights before the mixed6 layer. Compared with the image-level models, both patient-level models could discriminate better (ACC increased by 2%-5%) on the RBR and Slice datasets. CONCLUSIONS: Deep learning can be used to classify benign and malignant renal tumors from CT images. Our patient-level models could benefit from 3D data to improve the accuracy.

Roles of PIP2 in the membrane binding of MIM I-BAR: insights from molecular dynamics simulations.

In order to probe the roles of PIP2 in the interactions between MIM I-BAR and model membranes, we performed a series of 10 µs-scale coarse-grained molecular dynamics simulations. Our results indicate that PIP2 plays predominant roles in the membrane binding of MIM I-BAR in a concentration-dependent manner and via electrostatic interactions. Besides, we find that the occurrence of the membrane curvature may induce the re-distribution of lipids in the membrane and result in the local enrichment of PIP2 at negatively curved membrane areas. Combining these roles of PIP2 in the membrane binding of MIM I-BAR helps explain how MIM I-BAR senses negative curvature and, thus, contributes to maintaining membrane protrusions.

Sinapultide-loaded lipid microbubbles and the stabilization effect of sinapultide on the shells of lipid microbubbles.

Microbubbles (MBs) hold promise in various biomedical applications due to their ultrasound-responsive properties. However, the stability and contrast enhancement duration of gas encapsulated MBs are still challenging. The aim of this study is to fabricate novel sinapultide (a synthetic pulmonary surfactant) stabilized MBs as ultrasound contrast agents. The optimized MBs generated from a mixture of phospholipid components and sinapultide have an average diameter of 1.82 ± 0.15 µm and a zeta potential of -55.2 ± 3.9 mV. Over 95% of the MBs have a mean diameter of less than 8 µm, indicating that the appropriately sized MBs can be applied as ultrasound contrast agents used in clinic. Furthermore, the interaction between sinapultide and lipid molecules and the stabilization mechanism of sinapultide on the shells of MBs were investigated by molecular dynamics simulation. The results demonstrate that the stability of MBs was increased effectively when the appropriate amount of sinapultide was added due to the decrease of surface tension. Accordingly, acoustic accumulation imaging analysis in vitro indicates that stable gas encapsulated sinapultide loaded MBs can provide a high scattering intensity resulting in better echogenicity. And the optimized concentration of sinapultide-loaded MBs can improve the contrast enhancement effect obviously compared with non-sinapultide MBs. Therefore, sinapultide-loaded lipid MBs may be designed as novel ultrasound contrast agents and used for clinical application in the future.

Effects of temperature and PEG grafting density on the translocation of PEGylated nanoparticles across asymmetric lipid membrane.

Plasma membrane internalization of nanoparticles (NPs) is important for their biomedical applications such as drug-delivery carriers. On one hand, in order to improve their half-life in circulation, PEGylation has been widely used. However, it may hinder the NPs' membrane internalization ability. On the other hand, higher temperature could enhance the membrane permeability and may affect the NPs' ability to enter into or exit from cells. To make full use of their advantages, we systematically investigated the effects of temperature and PEG density on the translocation of PEGylated nanoparticles across the plasma asymmetric membrane of eukaryotic cells, using near-atom level coarse-grained molecular dynamics simulations. Our results showed that higher temperature could accelerate the translocation of NPs across membranes by making lipids more disorder and faster diffusion. On the contrary, steric hindrance effects of PEG would inhibit NPs' translocation process and promote lipids flip-flops. The PEG chains could rearrange themselves to minimize the contacts between PEG and lipid tails during the translocation, which was similar to 'snorkeling effect'. Moreover, lipid flip-flops were affected by PEGylated density as well as NPs' translocation direction. Higher PEG grafting density could promote lipid flip-flops, but inhibit lipid extraction from bilayers. The consequence of lipid flip-flop and extraction was that the membranes got more symmetric.

[Development of a software standardizing optical density with operation settings related to several limitations].

OBJECTIVE: To develop a software that can be used to standardize optical density to normalize the procedures and results of standardization in order to effectively solve several problems generated during standardization of in-direct ELISA results. METHODS: The software was designed based on the I-STOD method with operation settings to solve the problems that one might encounter during the standardization. Matlab GUI was used as a tool for the development. The software was tested with the results of the detection of sera of persons from schistosomiasis japonica endemic areas. RESULTS: I-STOD V1.0 (WINDOWS XP/WIN 7, 0.5 GB) was successfully developed to standardize optical density. A serial of serum samples from schistosomiasis japonica endemic areas were used to examine the operational effects of I-STOD V1.0 software. The results indicated that the software successfully overcame several problems including reliability of standard curve, applicable scope of samples and determination of dilution for samples outside the scope, so that I-STOD was performed more conveniently and the results of standardization were more consistent. CONCLUSION: I-STOD V1.0 is a professional software based on I-STOD. It can be easily operated and can effectively standardize the testing results of in-direct ELISA.