Application and progress of CRISPR/Cas9 gene editing in B-cell lymphoma: a narrative review.

Background and Objective: Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) gene editing and CRISPR/Cas9 screening libraries are hot topics, and have high application values in the diagnosis and treatment of genetic diseases, and the improvement of prognosis. The major treatment of B-cell lymphoma is chemotherapy combined with biological therapy. Due to the individual specificity and the emergence of drug resistance, the therapeutic efficacy varies. The objective of this article is to explore potential targets to enhance therapeutic effects, optimize treatment plans, and improve the prognosis of patients with B-cell lymphoma. Methods: We undertook a comprehensive, narrative review of the latest literature to define the current application and progress of CRISPR/Cas9 in B-cell lymphoma. Key Content and Findings: The concepts of CRISPR/Cas9, the mechanism of gene editing, and the procedures of CRISPR/Cas9 screening libraries are investigated for candidate genes. We mainly focus on application and progress of CRISPR/Cas9 in B-cell lymphoma and screen out some genes, signaling pathways, and cytokines, which may become potential targets for clinical treatment. Conclusions: CRISPR/Cas9 gene editing has great promise in the treatment of B-cell lymphoma. This article reviews some genes, signaling pathways, and cytokines related to the progression and prognosis of B-cell lymphoma to provide a strong theoretical basis.

Comparison of splinting immobilization and K-wire fixation in children with type II phalange neck fracture.

To compare outcomes of type II phalangeal neck fractures in children who received closed reduction followed by splinting immobilization or by K-wire fixation. Furthermore, we analyzed the remodeling potential of residual deformities and the relationship between age and outcomes. Patients in Children's Hospital of Fudan University, Xiamen Hospital were included in the study from October 2015 to October 2018. We compared outcomes between the conservation group and operation group. Remodeling of residual deformities was calculated on a series of anteroposterior and lateral radiography. The correlation between age and outcomes was analyzed using Spearman's rank correlation coefficient. Forty patients (25 males) were enrolled. Nineteen patients had subtype IIa, 19 subtype IIb, and two subtype IIc fractures. Left hands were affected more than right hands, and small finger and proximal phalanx were more frequently involved. There were no significant differences between conservation group and operation group among excellent, good, and fair outcomes. And the outcomes were not significantly different between the IIa and IIb subtypes. An average sagittal remodeling rate was 88.5%, and coronal remodeling rate was 56.71%, respectively, in 13 patients with residual deformities. There was a significant correlation between age and final outcomes. Closed reduction and stable splint fixation may be an effective and economical initial treatment option. Fracture subtype does not seem to be a key factor for choosing treatment options. The fractured phalangeal neck had remodeling potential whether on sagittal or coronal plane. Younger age might be a predictor of better outcomes in children with type II phalanx neck fractures.

From ab initio to continuum: Linking multiple scales using deep-learned forces.

We develop a deep learning-based algorithm, called DeepForce, to link ab initio physics with the continuum theory to predict concentration profiles of confined water. We show that the deep-learned forces can be used to predict the structural properties of water confined in a nanochannel with quantum scale accuracy by solving the continuum theory given by Nernst-Planck equation. The DeepForce model has an excellent predictive performance with a relative error less than 7.6% not only for confined water in small channel systems (L < 6 nm) but also for confined water in large channel systems (L = 20 nm) which are computationally inaccessible through the high accuracy ab initio molecular dynamics simulations. Finally, we note that classical Molecular dynamics simulations can be inaccurate in capturing the interfacial physics of water in confinement (L < 4.0 nm) when quantum scale physics are neglected.

Data-Driven Approach to Coarse-Graining Simple Liquids in Confinement.

We propose a data-driven framework for identifying coarse-grained (CG) Lennard-Jones (LJ) potential parameters in confined systems for simple liquids. Our approach involves the use of a Deep Neural Network (DNN) that is trained to approximate the solution of the Inverse Liquid State (ILST) problem for confined systems. The DNN model inherently incorporates essential physical characteristics specific to confined fluids, enabling an accurate prediction of inhomogeneity effects. By utilizing transfer learning, we predict single-site LJ potentials of simple multiatomic liquids confined in a slit-like channel, which effectively replicate both the fluid structure and molecular force of the target All-Atom (AA) system when the electrostatic interactions are not dominant. In addition, we showcase the synergy between the data-driven approach and the well-known Bottom-Up coarse-graining method utilizing Relative-Entropy (RE) Minimization. Through the sequential utilization of these two methods, the robustness of the iterative RE method is significantly augmented, leading to a remarkable enhancement in convergence.

Exposure to manganese (II) chloride induces developmental toxicity, oxidative stress and inflammatory response in Marine medaka (Oryzias melastigma) embryos.

Manganese (Mn) is an essential metal for organisms, but high levels can induce serious toxicity. To date, the toxic mechanism of Mn to marine fish is still poorly understood. In the present study, Oryzias melastigma embryos were exposed to different concentrations of MnCl2 (0-152.00 mg/L) to investigate its effect on early development. The results showed that exposure to MnCl2 caused developmental toxicity to embryos, including increased heart rate, delayed hatching time, decreased hatching rate and increased malformation rate. MnCl2 exposure could induce oxidative stress in O. melastigma embryos, as indicated by increased the contents of malondialdehyde (MDA) and the activities of the antioxidant enzymes (superoxide dismutase (SOD), glutathione peroxidase (GPx) and catalase (CAT)). The heart might be an important target organ for MnCl2 because of cardiac malformations and disruption in the expression of cardiac development-related genes (ATPase, epo, fg8g, cox1, cox2, bmp4 and gata4). In addition, the expression levels of stress- (omTERT and p53) and inflammation-related genes (TNFα and il1ß) were significantly up-regulated, suggesting that MnCl2 can trigger stress and inflammatory response in O. melastigma embryos. In conclusion, this study demonstrated that MnCl2 exposure can induce developmental toxicity, oxidative stress and inflammatory response in O. melastigma embryos, providing insights into the toxic mechanism of Mn to the early development of marine fish.

Spatio-temporal patterns of zooplankton community in the Yellow River estuary: Effects of seasonal variability and water-sediment regulation.

Zooplankton community is ecological important because of its high sensitivity to environmental changes especially in estuarine areas. The Yellow River estuary (YRE) in China is the fifth biggest estuary in the world with significant seasonal characteristics and anthropogenic influence of Water-Sediment Regulation (WSR). This study investigated the spatio-temporal patterns of zooplankton in the YRE to explore the response of zooplankton to seasonal variation and WSR. Results suggested that the temporal patterns of zooplankton were mainly characterized by seasonal shift of dominant species. Hierarchical cluster analysis and non-metric multidimensional scaling determined summer, summer-autumn and winter-spring three zooplankton assemblages. Zooplankton spatial distributions represented seasonal consistency, in which the abundance generally showed a decreasing gradient from the river mouth to sea. WSR caused a high species replacement rate in July-August (80.36%) and a dramatic abundance decline from 4224.60 ind./m3 to 1541.10 ind./m3 with persistency and hysteresis effect. The high zooplankton abundance moved seaward in spatial distribution after WSR. Summer spatial pattern was determined with two and three zooplankton station assemblages, which was more clear after WSR. Redundancy analysis identified SSS, SST and transparency as important factors structuring zooplankton spatio-temporal patterns, in which SSS was the key one. The results provide a necessary reference for understanding the response of zooplankton community in estuarine areas to spontaneous changes and anthropogenic factors, and can help the protection of estuarine ecosystems and the formulation of hydrological regulatory policies.

Real-Space Charge Density Profiling of Electrode-Electrolyte Interfaces with Angstrom Depth Resolution.

The accumulation and depletion of charges at electrode-electrolyte interfaces is crucial for all types of electrochemical processes. However, the spatial profile of such interfacial charges remains largely elusive. Here we develop charge profiling three-dimensional (3D) atomic force microscopy (CP-3D-AFM) to experimentally quantify the real-space charge distribution of the electrode surface and electric double layers (EDLs) with angstrom depth resolution. We first measure the 3D force maps at different electrode potentials using our recently developed electrochemical 3D-AFM. Through statistical analysis, peak deconvolution, and electrostatic calculations, we derive the depth profile of the local charge density. We perform such charge profiling for two types of emergent electrolytes, ionic liquids, and highly concentrated aqueous solutions, observe pronounced sub-nanometer charge variations, and find the integrated charge densities to agree with those derived from macroscopic electrochemical measurements.

Innermost Ion Association Configuration Is a Key Structural Descriptor of Ionic Liquids at Electrified Interfaces.

The structure of electric double layers (EDLs) is crucial for all types of electrochemical processes. While in dilute solutions EDL structure can be approximately treated within the Gouy-Chapman-Stern regime, in highly ionic electrolytes the description of EDL has been largely elusive. Here we study the EDL structure of an ionic liquid on a series of crystalline electrodes. Through molecular dynamics (MD) simulations, we observe strong intermolecular interaction among cations and anions and propose that the cation-anion association structure at the innermost layer is a key descriptor of the EDL. Using our recently developed electrochemical 3D atomic force microscopy (EC-3D-AFM) technique, we confirm the theoretical prediction and further find that the width of the first EDL is an experimental gauge of the ion association structure in that layer. We expect such ion association descriptors to be broadly applicable to a large range of highly ionic electrolytes on various electrode surfaces.

Deep learning-based quasi-continuum theory for structure of confined fluids.

Predicting the structural properties of water and simple fluids confined in nanometer scale pores and channels is essential in, for example, energy storage and biomolecular systems. Classical continuum theories fail to accurately capture the interfacial structure of fluids. In this work, we develop a deep learning-based quasi-continuum theory (DL-QT) to predict the concentration and potential profiles of a Lennard-Jones (LJ) fluid and water confined in a nanochannel. The deep learning model is built based on a convolutional encoder-decoder network (CED) and is applied for high-dimensional surrogate modeling to relate the fluid properties to the fluid-fluid potential. The CED model is then combined with the interatomic potential-based continuum theory to determine the concentration profiles of a confined LJ fluid and confined water. We show that the DL-QT model exhibits robust predictive performance for a confined LJ fluid under various thermodynamic states and for water confined in a nanochannel of different widths. The DL-QT model seamlessly connects molecular physics at the nanoscale with continuum theory by using a deep learning model.

Habitat hierarchies distribution of Sargassum muticum in Lidao bay, Shandong, China based on habitat suitability index model.

We used the habitat suitability index (HSI) model to determine the habitat suitability of Sargassum muticum in Lidao bay, Shandong Province. Eight environmental factors, including temperature, salinity, depth, turbidity, sediment, inorganic nitrogen concentration, phosphate concentration, distance from seaweed bed, were used as input variables for HSI model. The weight of each factor was defined by the analytic hierarchy process (AHP). We implemented the distribution of S. muticum suitable habitat along the coast of Lidao bay with the HSI model, based on the investigation of the environmental factors in spring and autumn 2018. The results showed that most of the S. muticum natural habitats were identified as excellent habitat and suitable habitat, accounting for 14.2% in spring and 18.6% in autumn. The distribution of habitat hierarchies varied across seasons, while habitat hierarchies showed spatial intersections in different seasons. There were significant seasonal differences in the factor suitability indices of temperature and phosphate concentration, which accounted for the seasonal HSI variations of S. muticum in Lidao bay. The S. muticum HSI model could be used to detect the habitat hierarchies distribution of S. muticum, and also to find its potential suitable habitat, which could provide a reference for future resource conservation and artificial proliferation of S. muticum.

Predicting Effective Diffusivity of Porous Media from Images by Deep Learning.

We report the application of machine learning methods for predicting the effective diffusivity (De) of two-dimensional porous media from images of their structures. Pore structures are built using reconstruction methods and represented as images, and their effective diffusivity is computed by lattice Boltzmann (LBM) simulations. The datasets thus generated are used to train convolutional neural network (CNN) models and evaluate their performance. The trained model predicts the effective diffusivity of porous structures with computational cost orders of magnitude lower than LBM simulations. The optimized model performs well on porous media with realistic topology, large variation of porosity (0.28-0.98), and effective diffusivity spanning more than one order of magnitude (0.1 ≲ De < 1), e.g., >95% of predicted De have truncated relative error of <10% when the true De is larger than 0.2. The CNN model provides better prediction than the empirical Bruggeman equation, especially for porous structure with small diffusivity. The relative error of CNN predictions, however, is rather high for structures with De < 0.1. To address this issue, the porosity of porous structures is encoded directly into the neural network but the performance is enhanced marginally. Further improvement, i.e., 70% of the CNN predictions for structures with true De < 0.1 have relative error <30%, is achieved by removing trapped regions and dead-end pathways using a simple algorithm. These results suggest that deep learning augmented by field knowledge can be a powerful technique for predicting the transport properties of porous media. Directions for future research of machine learning in porous media are discussed based on detailed analysis of the performance of CNN models in the present work.

Note: A top-view optical approach for observing the coalescence of liquid drops.

We developed a new device that is capable of top-view optical examination of the coalescence of liquid drops. The device exhibits great potential for visualization, particularly for the early stage of liquid bridge expansion, owing to the use of a high-speed shadowgraph technique. The fluid densities of the two approaching drops and that of the ambient fluid are carefully selected to be negligibly different, which allows the size of the generated drops to be unlimitedly large in principle. The unique system design allows the point of coalescence between two drops to serve as an undisturbed optical pathway through which to image the coalescence process. The proposed technique extended the dimensionless initial finite radius of the liquid bridge to 0.001, in contrast to 0.01 obtained for conventional optical measurements. An examination of the growth of the bridge radius for a water and oil-tetrachloroethylene system provided results similar to Paulsen's power laws of the inertially limited viscous and inertial regimes. Furthermore, a miniscule shift in the center of the liquid bridge was detected at the point of crossover between the two regimes, which can be scarcely distinguished with conventional side-view techniques.

[ANTIBIOTIC-IMPREGNATED ARTICULAR CEMENT SPACER FOR TREATMENT OF PERIPROSTHETIC JOINT INFECTION].

OBJECTIVE: To investigate the current problems and corresponding solutions regarding the use of antibiotic-impregnated cement spacer for the treatment of periprosthetic joint infection (PJI). METHODS: A retrospective analysis was made on the clinical data of 27 patients with PJI who underwent two-stage revision with antibiotic-impregnated cement spacer between January 2001 and January 2013. There were 12 males and 15 females, with an average age of 62.7 years (range, 25-81 years). All arthroplasties were unilateral, including 19 hip PJI and 8 knee PJI. The mean duration from primary arthroplasty to PJI was 25 months (range, 3-252 months). After infection was controlled with the antibiotic-impregnated cement spacer combined with systematic antibiotics treatment, two-stage revision was performed. The effectiveness was evaluated. Results One patient died of myocardial infarction at 2 days after surgery. Infection was controlled, and two-stage revision was successfully performed in 19 patients; deep venous thrombosis occurred in 1 of 3 patients who experienced hip spacer fractures, which was cured after conservative management. The spacers were removed and bacteria-sensitive antibiotics was used because of recurrent infections after the first-stage surgery in 7 patients; 3 patients gave up treatment because infection was not controlled, 4 patients received revision after infection was controlled. Twenty-three patients were followed up 1-5 years (mean, 2.3 years). The average Harris hip score and KSS score at 1 years after revision were significantly improved when compared with preoperative ones (P<0.05). In the 8 patients with gram-negative or fungus infection, 7 were found to have recurrent infection after the first-stage surgery; in the 12 patients with gram-positive infection, no recurrent infection was found. Failed treatment was observed in 1 patient with gram-positive and gram-negative infections and 2 with fungus infection, respectively. CONCLUSION: Antibiotic- impregnated cement spacer has a satisfactory effectiveness for PJI. However, complication of spacer fracture should be noted, especially hip spacers. If the pathogen is gram-negative bacteria or fungus, the implanted spacer may increase the possibility of recurrent infection.

The mitochondrial genomes of two nemerteans, Cephalothrix sp. (Nemertea: Palaeonemertea) and Paranemertes cf. peregrina (Nemertea: Hoplonemertea).

The mitochondrial genome sequences were determined for two species of nemerteans, Cephalothrix sp. (15,800 bp sequenced, near-complete) and Paranemertes cf. peregrina (14,558 bp, complete). As seen in most metazoans, the genomes encode 13 protein, 2 ribosomal RNA and 22 transfer RNA genes. The nucleotide composition is strongly biased toward A and T, as is typical for metazoan mtDNAs. There is also a significant strand skew in the distribution of these nucleotides, with the coding strand being richer in T than A and in G than C. All genes are transcribed in the same direction except for trnP and trnT, which is consistent with that reported for Cephalothrix hongkongiensis and Lineus viridis. Gene arrangement of Cephalothrix sp. is identical to that of C. hongkongiensis, while in P. cf. peregrina it is similar to L. viridis, but differs significantly from the three Cephalothrix species in the position of four protein-coding genes and seven tRNAs. Some protein-coding genes have 3' end stem-loop structures, which may allow mRNA processing without flanking tRNAs. The major non-coding regions observed in the two genomes with potential to form stem-loop structures may be involved in the initiation of replication or transcription. The average Ka/Ks values, varying from 0.12 to 0.89, are markedly different among the 13 mitochondrial protein-coding genes, suggesting that there may exist different selective pressure among mitochondrial genes of nemerteans.