Dynamic Implicit-Solvent Coarse-Grained Models of Lipid Bilayer Membranes : Fluctuating Hydrodynamics Thermostat

Many coarse-grained models have been developed for equilibrium studies of lipid bilayer membranes. To achieve in simulations access to length-scales and time-scales difficult to attain in fully atomistic molecular dynamics, these coarse-grained models provide a reduced description of the molecular degrees of freedom and often remove entirely representation of the solvent degrees of freedom. In such implicit-solvent models the solvent contributions are treated through effective interaction terms within an effective potential for the free energy. For investigations of kinetics, Langevin dynamics is often used. However, for many dynamical processes within bilayers this approach is insufficient since it neglects important correlations and dynamical contributions that are missing as a result of the momentum transfer that would have occurred through the solvent. To address this issue, we introduce a new thermostat based on fluctuating hydrodynamics for dynamic simulations of implicit-solvent coarse-grained models. Our approach couples the coarse-grained degrees of freedom to a stochastic continuum field that accounts for both the solvent hydrodynamics and thermal fluctuations. We show our approach captures important correlations in the dynamics of lipid bilayers that are missing in simulations performed using conventional Langevin dynamics. For both planar bilayer sheets and bilayer vesicles, we investigate the diffusivity of lipids, spatial correlations, and lipid flow within the bilayer. The presented fluctuating hydrodynamics approaches provide a promising way to extend implicit-solvent coarse-grained lipid models for use in studies of dynamical processes within bilayers

Alchemical and structural distribution based representation for improved QML

We introduce a representation of any atom in any chemical environment for the generation of efficient quantum machine learning (QML) models of common electronic ground-state properties. The representation is based on scaled distribution functions explicitly accounting for elemental and structural degrees of freedom. Resulting QML models afford very favorable learning curves for properties of out-of-sample systems including organic molecules, non-covalently bonded protein side-chains, (H$_2$O)$_{40}$-clusters, as well as diverse crystals. The elemental components help to lower the learning curves, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training, as evinced for single, double, and triple bonds among main-group elements

EXPERIMENTAL STUDY ON THE SEISMIC DAMAGE OF AEOLIAN SAND CONCRETE COLUMNS WITH DIFFERENT REINFORCEMENTS

Aeolian sand is a kind of natural material with abundant reserves and a low price. Many scholars have conducted extensive studies on the engineering applications of aeolian sand. This paper addresses the seismic damage behaviour of aeolian sand concrete columns to promote the application of aeolian sand in frame structures. A total of 5 aeolian sand concrete column specimens with different reinforcements were studied using cyclic loading tests. The failure modes, stiffness degradation, bearing capacity, hysteresis peculiarity, ductility, and energy consumption of the specimens were analysed and compared. Then, applicable damage models of the specimens were proposed. The study results prove that the seismic damage behaviour of the specimens increases with the increase of longitudinal reinforcement percentage and with the transverse steel ratio when the replacement percentage of aeolian sand is constant. Additionally, the damage model which is revised in this paper agrees well with the test results. It can be used to assess the degree of damage to the aeolian sand concrete columns

Conjunctival Flap Covering Combined with Antiviral and Steroid Therapy for Severe Herpes Simplex Virus Necrotizing Stromal Keratitis

Herpes simplex virus (HSV) necrotizing stromal keratitis is a common type of herpetic stromal keratitis (HSK). Antiviral medication alone cannot control the disease, and corticosteroid eye drops may aggravate the ulcer and result in corneal perforation. Amniotic membrane transplantation effectively treats superficial corneal ulcer resulting from necrotizing stromal HSK. However, the efficacy of this approach seems to be limited for more serious cases. This study presented the clinical treatment of severe HSV necrotizing stromal keratitis (ulcer depth greater than half of the corneal stroma) by conjunctival flap covering surgery in 25 patients (25 eyes) combined with antivirus and corticosteroid treatment at Shandong Eye Hospital from January 2007 to December 2013. Clinical results showed that the mean best spectacle-corrected visual acuity improved from preoperative 20/333 to postoperative 20/40 (P<0.05). All patients recovered ocular surface stabilization. There was recurrence in two eyes, which was cured with antiviral medication. Conjunctival flap covering combined with antivirus and corticosteroid treatment is effective in treating severe HSV necrotizing stromal keratitis

Tumor microenvironment in pancreatic ductal adenocarcinoma: Implications in immunotherapy

Pancreatic ductal adenocarcinoma is one of the most aggressive and lethal cancers. Surgical resection is the only curable treatment option, but it is available for only a small fraction of patients at the time of diagnosis. With current therapeutic regimens, the average 5-year survival rate is less than 10% in pancreatic cancer patients. Immunotherapy has emerged as one of the most promising treatment options for multiple solid tumors of advanced stage. However, its clinical efficacy is suboptimal in most clinical trials on pancreatic cancer. Current studies have suggested that the tumor microenvironment is likely the underlying barrier affecting immunotherapy drug efficacy in pancreatic cancer. In this review, we discuss the role of the tumor microenvironment in pancreatic cancer and the latest advances in immunotherapy on pancreatic cancer

Eosinophils Instance Object Segmentation on Whole Slide Imaging Using Multi-label Circle Representation

Eosinophilic esophagitis (EoE) is a chronic and relapsing disease characterized by esophageal inflammation. Symptoms of EoE include difficulty swallowing, food impaction, and chest pain which significantly impact the quality of life, resulting in nutritional impairments, social limitations, and psychological distress. The diagnosis of EoE is typically performed with a threshold (15 to 20) of eosinophils (Eos) per high-power field (HPF). Since the current counting process of Eos is a resource-intensive process for human pathologists, automatic methods are desired. Circle representation has been shown as a more precise, yet less complicated, representation for automatic instance cell segmentation such as CircleSnake approach. However, the CircleSnake was designed as a single-label model, which is not able to deal with multi-label scenarios. In this paper, we propose the multi-label CircleSnake model for instance segmentation on Eos. It extends the original CircleSnake model from a single-label design to a multi-label model, allowing segmentation of multiple object types. Experimental results illustrate the CircleSnake model's superiority over the traditional Mask R-CNN model and DeepSnake model in terms of average precision (AP) in identifying and segmenting eosinophils, thereby enabling enhanced characterization of EoE. This automated approach holds promise for streamlining the assessment process and improving diagnostic accuracy in EoE analysis. The source code has been made publicly available at https://github.com/yilinliu610730/EoE

Deep Learning-Based Open Source Toolkit for Eosinophil Detection in Pediatric Eosinophilic Esophagitis

Eosinophilic Esophagitis (EoE) is a chronic, immune/antigen-mediated esophageal disease, characterized by symptoms related to esophageal dysfunction and histological evidence of eosinophil-dominant inflammation. Owing to the intricate microscopic representation of EoE in imaging, current methodologies which depend on manual identification are not only labor-intensive but also prone to inaccuracies. In this study, we develop an open-source toolkit, named Open-EoE, to perform end-to-end whole slide image (WSI) level eosinophil (Eos) detection using one line of command via Docker. Specifically, the toolkit supports three state-of-the-art deep learning-based object detection models. Furthermore, Open-EoE further optimizes the performance by implementing an ensemble learning strategy, and enhancing the precision and reliability of our results. The experimental results demonstrated that the Open-EoE toolkit can efficiently detect Eos on a testing set with 289 WSIs. At the widely accepted threshold of >= 15 Eos per high power field (HPF) for diagnosing EoE, the Open-EoE achieved an accuracy of 91%, showing decent consistency with pathologist evaluations. This suggests a promising avenue for integrating machine learning methodologies into the diagnostic process for EoE. The docker and source code has been made publicly available at https://github.com/hrlblab/Open-EoE

Genome-Wide Characterization of Endogenous Retroviruses in Bombyx mori Reveals the Relatives and Activity of env Genes

Endogenous retroviruses (ERVs) are retroviral sequences that remain fixed in the host genome, where they could play an important role. Some ERVs have been identified in insects and proven to have infectious properties. However, no information is available regarding Bombyx mori ERVs (BmERVs) to date. Here, we systematically identified 256 potential BmERVs in the silkworm genome via a whole-genome approach. BmERVs were relatively evenly distributed across each of the chromosomes and accounted for about 25% of the silkworm genome. All BmERVs were classified as young ERVs, with insertion times estimated to be less than 10 million years. Seven BmERVs possessing the env genes were identified. With the exception of the Orf133 Helicoverpa armigera nuclear polyhedrosis virus, the env sequences of BmERVs were distantly related to genes encoding F (Fa and Fb) and GP64 proteins from Group I and Group II NPVs. In addition, only the amino acid sequence of the BmERV-21 envelope protein shared a similar putative furin-like cleavage site and fusion peptide with Group II baculoviruses. All of the env genes in the seven BmERVs were verified to exist in the genome and be expressed in the midgut and fat bodies, which suggest that BmERVs might play an important role in the host biology

Probiotic Lactobacillus rhamnosus GG Induces Alterations in Ileal Microbiota With Associated CD3-CD19-T-bet+IFNγ+/- Cell Subset Homeostasis in Pigs Challenged With Salmonella enterica Serovar 4,[5],12:i:-

Salmonella enterica serovar 4,[5],12:i:- (S. 4,[5],12:i:-) is an emerging foodborne pathogen causing salmonellosis in humans and animals. Probiotic Lactobacillus rhamnosus GG (LGG) is an effective strategy for controlling enteric infections through maintaining gut microbiota homeostasis and regulating the intestinal innate immune response. Here, LGG was orally administrated to newly weaned piglets for 1 week before S. 4,[5],12:i:- challenge. S. 4,[5],12:i:- challenge led to disturbed gut microbiota, characterized by increased levels of Psychrobacter, Chryseobacterium indoltheticum, and uncultured Corynebacteriaceae populations, as well as an aberrant correlation network in Prevotellaceae NK3B31 group-centric species. The beneficial effect of LGG correlated with attenuating the expansion of Prevotellaceae NK3B31 group. Fusobacterium only found in the pigs treated with LGG was positively correlated with Lactobacillus animalis and Propionibacterium. Administration of LGG induced the expansion of CD3-CD19-T-bet+IFNγ+ and CD3-CD19-T-bet+IFNγ- cell subsets in the peripheral blood at 24 h after a challenge of S. 4,[5],12:i:-. S. 4,[5],12:i:- infection increased the population of intraepithelial CD3-CD19-T-bet+IFNγ+ and CD3-CD19-T-bet+IFNγ- cells in the ileum; however, this increase was attenuated via LGG administration. Correlation analysis revealed that LGG enriched Flavobacterium frigidarium and Facklamia populations, which were negatively correlated with intraepithelial CD3-CD19-T-bet+IFNγ+ and CD3-CD19-T-bet+IFNγ- cells in the ileum. The present data suggest that probiotic LGG alters gut microbiota with associated CD3-CD19-T-bet+IFNγ+/- cell subset homeostasis in pigs challenged with S. enterica 4,[5],12:i:-. LGG may be used in potential gut microbiota-targeted therapy regimens to regulate the specific immune cell function and, consequently, control enteric infections