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The Berendsen barostat from molecular dynamics simulation is applied in both standard dissipative particle dynamics (DPD) and many-body dissipative particle dynamics (MDPD) simulations. The original Berendsen barostat works well in (M)DPD simulation of a single-component system under constant pressure condition and in nonequilibrium dynamic processes. The partial Berendsen barostat is proposed for multi-component system simulation with (M)DPD. The displacement rescaling process of the Berendsen barostat is only applied on the particles outside the center region, acting as a pressure "boundary condition." The center part forms the free zone, in which the interface shape and nonequilibrium dynamic behavior between different phases can be captured properly. An immiscible bubble in the second fluid under constant pressure condition is studied, and the oscillation of the bubble radius and fluctuation of systempressure can be obtained by the current barostat. Preliminary models for bubble growing and collapsing under square pressure wave and bubble oscillation under harmonic pressure wave are also reported in the current simulation. It shows that the partial Berendsen barostat is suitable for the modeling of nonequilibrium process of single or few droplets/bubbles in multi-component systems.

Triggering receptor expressed on myeloid cell 2 (TREM2) is a surface receptor that, in the central nervous system, is exclusively expressed on microglia. TREM2 variants have been linked to increased risk for neurodegenerative diseases, but the functional effects of microglial TREM2 remain largely unknown. To this end, we investigated TAR-DNA binding protein 43 kDa (TDP-43)-related neurodegenerative disease via viral-mediated expression of human TDP-43 protein (hTDP-43) in neonatal and adult mice or inducible expression of hTDP43 with defective nuclear localization signals in transgenic mice. We found that TREM2 deficiency impaired microglia phagocytic clearance of pathological TDP-43, and enhanced neuronal damage and motor function impairments. Mass cytometry analysis revealed that hTDP-43 induced a TREM2-dependent subpopulation of microglia with high CD11c expression and higher phagocytic ability. Using mass spectrometry, we further demonstrated an interaction between TDP-43 and TREM2, in vitro and in vivo, in hTDP-43-expressing transgenic mouse brains. We computationally identified the region within hTDP-43 that interacts with TREM2 and observed the potential interaction in ALS patient tissues. Our data reveal the novel interaction between TREM2 and TDP-43, highlighting that TDP-43 is a potential ligand for microglial TREM2 and the interaction mediates neuroprotection of microglial TREM2 in TDP-43-related neurodegeneration.

Crack is an important indicator for evaluating the damage level of concrete structures. However, traditional crack detection algorithms have complex implementation and weak generalization. The existing crack detection algorithms based on deep learning are mostly window-level algorithms with low pixel precision. In this article, the CrackUnet model based on deep learning is proposed to solve the above problems. First, crack images collected from the lab, earthquake sites, and the Internet are resized, labeled manually, and augmented to make a dataset (1200 subimages with 256 × 256 × 3 resolutions in total). Then, an improved Unet-based method called CrackUnet is proposed for automated pixel-level crack detection. A new loss function named generalized dice loss is adopted to detect cracks more accurately. How the size of the dataset and the depth of the model affect the training time, detecting accuracy, and speed is researched. The proposed methods are evaluated on the test dataset and a previously published dataset. The highest results can reach 91.45%, 88.67%, and 90.04% on test dataset and 98.72%, 92.84%, and 95.44% on CrackForest Dataset for precision, recall, and F1 score, respectively. By comparing the detecting accuracy, the training time, and the information of datasets, CrackUnet model outperform than other methods. Furthermore, six images with complicated noise are used to investigate the robustness and generalization of CrackUnet models.

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The histopathological examination of the periprosthetic soft tissue and bone has contributed to the identification and description of the morphological features of adverse local tissue reactions (ALTR)/adverse reactions to metallic debris (ARMD). The need of a uniform vocabulary for all disciplines involved in the diagnosis and management of ALTR/ARMD and of clarification of the parameters used in the semi-quantitative scoring systems for their classification has been considered a pre-requisite for a meaningful interdisciplinary evaluation. This review of key terms used for ALTR/ARMD has resulted in the following outcomes: (a) pseudotumor is a descriptive term for ALTR/ARMD, classifiable in two main types according to its cellular composition defining its clinical course; (b) the substitution of the term metallosis with presence of metallic wear debris, since it cannot be used as a category of implant failure or histological diagnosis; (c) the term aseptic lymphocytic-dominated vasculitis- associated lesion (ALVAL) should be replaced due to the absence of a vasculitis with ALLTR/ALRMD for lymphocytic-predominant and AMLTR/AMRMD for macrophage-predominant reaction. This review of the histopathological classifications of ALTR/ARMD has resulted in the following outcomes: (a) distinction between cell death and tissue necrosis; (b) the association of corrosion metallic debris with adverse local lymphocytic reaction and tissue necrosis; (c) the importance of cell and particle debris for the viscosity and density of the lubricating synovial fluid; (d) a consensus classification of lymphocytic infiltrate in soft tissue and bone marrow; (e) evaluation of the macrophage infiltrate in soft tissues and bone marrow; (f) classification of macrophage induced osteolysis/aseptic loosening as a delayed type of ALTR/ARMD; (g) macrophage motility and migration as possible driving factor for osteolysis; (h) usefulness of the histopathological examination for the natural history of the adverse reactions, radiological correlation, post-marketing surveillance, and implant registries. The review of key terms used for the description and histopathological classification of ALTR/ARMD has resulted in a comprehensive, new standard for all disciplines involved in their diagnosis, clinical management, and long-term clinical follow-up. Cite this article: EFORT Open Rev 2021;6:399-419. DOI: 10.1302/2058-5241.6.210013

Single nucleotide variants in the open reading frames (ORFs) of pharmacogenes are important causes of interindividual variability in drug response. The functional characterization of variants of unknown significance within ORFs remains a major challenge for pharmacogenomics. Deep mutational scanning (DMS) is a high-throughput technique that makes it possible to analyze the functional effect of hundreds of variants in a parallel and scalable fashion. We adapted a "landing pad" DMS system to study the function of missense variants in the ORFs of cytochrome P450 family 2 subfamily C member 9 (CYP2C9) and cytochrome P450 family 2 subfamily C member 19 (CYP2C19). We studied 230 observed missense variants in the CYP2C9 and CYP2C19 ORFs and found that 19 of 109 CYP2C9 and 36 of 121 CYP2C19 variants displayed less than ~ 25% of the wild-type protein expression, a level that may have clinical relevance. Our results support DMS as an efficient method for the identification of damaging ORF variants that might have potential clinical pharmacogenomic application. Genetic polymorphisms in or near pharmacogenes are a major cause of individual variation in drug response phenotypes. 1 Cytochrome P450 family 2 subfamily C member 9 (CYP2C9) and cytochrome P450 family 2 subfamily C member 19 (CYP2C19) are genes that encode important cytochrome P450 enzymes that catalyze the phase I biotransformation of a variety of therapeutic drugs, including antiplatelet agents, selective serotonin reuptake inhibitors, and proton pump inhibitors. 2-5 Several years ago, the Mayo Clinic launched the RIGHT 1K study, in which next generation DNA sequencing (NGS) was performed with DNA from 1013 Mayo Biobank participants to identify variants in 84 pharmacogenes, including CYP2C9 and CYP2C19. 1,6 However, many of the polymorphisms observed in those patients were variants of unknown significance (VUS). 1,7,8 In a recent publication, we functionally characterized six novel nonsynonymous open reading frame (ORF) variants in the CYP2C9 gene and seven nonsynonymous ORF variants in the CYP2C19 gene observed in DNA from participants in the Right 1K study. 9 Conventional methods for the characterization of individual sequence variants "one-at-a-time" are reliable, but they are also time-consuming, labor-intense, and not easily scalable. As a result, only a limited number of variants can practically be investigated in that fashion. To help address this challenge, predictive algorithms, such as Polyphen-2, SIFT, and PROVEAN, among others, represent efforts to help identify deleterious variants, but their reliability is variable and inadequate for clinical application. 10-12

We previously reported that SNPs near TSPAN5 were associated with plasma serotonin (5-HT) concentrations which were themselves associated with selective serotonin reuptake inhibitor treatment outcomes in patients with major depressive disorder (MDD). TSPAN5 SNPs were also associated with alcohol consumption and alcohol use disorder (AUD) risk. The present study was designed to explore the biological function of TSPAN5 with a focus on 5-HT and kynurenine concentrations in the tryptophan pathway. Ethanol treatment resulted in decreased 5-HT concentrations in human induced pluripotent stem cell (iPSC)-derived neuron culture media, and the downregulation of gene expression of TSPAN5, DDC, MAOA, MAOB, TPH1, and TPH2 in those cells. Strikingly, similar observations were made when the cells were treated with acamprosate—an FDA approved drug for AUD therapy. These results were replicated in iPSC-derived astrocytes. Furthermore, TSPAN5 interacted physically with proteins related to clathrin and other vesicle-related proteins, raising the possibility that TSPAN5 might play a role in vesicular function in addition to regulating expression of genes associated with 5-HT biosynthesis and metabolism. Downregulation of TSPAN5 expression by ethanol or acamprosate treatment was also associated with decreased concentrations of kynurenine, a major metabolite of tryptophan that plays a role in neuroinflammation. Knockdown of TSPAN5 also influenced the expression of genes associated with interferon signaling pathways. Finally, we determined that TSPAN5 SNPs were associated with acamprosate treatment outcomes in AUD patients. In conclusion, TSPAN5 can modulate the concentrations of 5-HT and kynurenine. Our data also highlight a potentially novel pharmacogenomic mechanism related to response to acamprosate.