Alkali-Activation of Synthetic Aluminosilicate Glass With Basaltic Composition

Alkali-activated materials (AAMs) are a potential alternative to Portland cement because they can have high strength, good durability and low environmental impact. This paper reports on the structural and mechanical characteristics of aluminosilicate glass with basalt-like compositions, as a feedstock for AAMs. The alkali-activation kinetics, microstructure, and mechanical performance of the alkali activated glass were investigated. The results show that AAMs prepared from basalt glass have high compressive strength (reaching up to 90 MPa after 7 days of hydration) compared to those made using granulated blast furnace slag (GBFS). In addition, calorimetry data show that the hydrolysis of the developed glass and subsequent polymerization of the reaction product occur at a faster rate compared to GBFS. Furthermore, the obtained results show that the alkali activation of the developed glass formed sodium aluminosilicate hydrate (N-A-S-H) intermixed with Ca aluminosilicate hydrate gel (C-A-S-H), while the alkali activation of GBFS resulted in predominantly C-A-S-H gel. The developed glass can be formed from carbonate-free and abundant natural resources such as basalt rocks or mixtures of silicate minerals. Therefore, the glass reported herein has high potential as a new feedstock of AAMs.

Efficient Inhibition of HIV Using CRISPR/Cas13d Nuclease System

Recently discovered Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas13 proteins are programmable RNA-guided ribonucleases that target single-stranded RNA (ssRNA). CRISPR/Cas13-mediated RNA targeting has emerged as a powerful tool for detecting and eliminating RNA viruses. Here, we demonstrate the effectiveness of CRISPR/Cas13d to inhibit HIV-1 replication. We designed guide RNAs (gRNAs) targeting highly conserved regions of HIV-1. RfxCas13d (CasRx) in combination with HIV-specific gRNAs efficiently inhibited HIV-1 replication in cell line models. Furthermore, simultaneous targeting of four distinct, non-overlapping sites in the HIV-1 transcript resulted in robust inhibition of HIV-1 replication. We also show the effective HIV-1 inhibition in primary CD4+ T-cells and suppression of HIV-1 reactivated from latently infected cells using the CRISPR/Cas13d system. Our study demonstrates the utility of the CRISPR/Cas13d nuclease system to target acute and latent HIV infection and provides an alternative treatment modality against HIV.

Rescue of a lysosomal storage disorder caused by Grn loss of function with a brain penetrant progranulin biologic

GRN mutations cause frontotemporal dementia (GRN-FTD) due to deficiency in progranulin (PGRN), a lysosomal and secreted protein with unclear function. Here, we found that Grn-/- mice exhibit a global deficiency in bis(monoacylglycero)phosphate (BMP), an endolysosomal phospholipid we identified as a pH-dependent PGRN interactor as well as a redox-sensitive enhancer of lysosomal proteolysis and lipolysis. Grn-/- brains also showed an age-dependent, secondary storage of glucocerebrosidase substrate glucosylsphingosine. We investigated a protein replacement strategy by engineering protein transport vehicle (PTV):PGRN-a recombinant protein linking PGRN to a modified Fc domain that binds human transferrin receptor for enhanced CNS biodistribution. PTV:PGRN rescued various Grn-/- phenotypes in primary murine macrophages and human iPSC-derived microglia, including oxidative stress, lysosomal dysfunction, and endomembrane damage. Peripherally delivered PTV:PGRN corrected levels of BMP, glucosylsphingosine, and disease pathology in Grn-/- CNS, including microgliosis, lipofuscinosis, and neuronal damage. PTV:PGRN thus represents a potential biotherapeutic for GRN-FTD.

Prediction of the sorption efficiency of heavy metal onto biochar using a robust combination of fuzzy C-means clustering and back-propagation neural network

Heavy metal adsorption onto biochar is an effective method for the treatment of the heavy metal contamination of water and wastewater. This study aims to evaluate the heavy metals sorption efficiency of different biochar characteristics and propose a novel intelligence method for predicting the sorption efficiency of heavy metal onto biochar with high accuracy based on the back-propagation neural network (BPNN) and fuzzy C-means clustering algorithm (FCM), named as FCM-BPNN. Accordingly, the FCM algorithm was used to simulate the properties of metal adsorption data and divide them into clusters with similar features. The clustering results showed that the FCM algorithm simulated metal adsorption data's properties very well and classified them based on biochar characteristics and adsorption conditions. Afterward, BPNN models were well-developed based on these clusters, and their outcomes were then combined (i.e., FCM-BPNN). The results indicated that the FCM-BPNN model could predict heavy metal's sorption efficiency onto biochar with a promising result (i.e., RMSE of 0.036, R² of 0.987, RSE of 0.006, MAPE of 0.706, and VAF of 98.724). Whereas the BPNN model, without optimizing the FCM algorithm, was proved with lower performance (RMSE = 0.050, R² = 0.977, RSE = 0.011, MAPE = 0.802, and VAF = 97.662). These findings revealed that the FCM algorithm's presence impressively improved the BPNN model's accomplishment in predicting heavy metal's sorption efficiency onto biochar, and the proposed FCM-BPNN model can improve water/wastewater treatment plants' quality and provide a more efficient process for heavy metals with performance superiority.

Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3-2.8, one-sided p = 6.0 × 10-4), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ.

Vascular and Blood Compatibility of Engineered Cationic Cellulose Nanocrystals in Cell-Based Assays

An emerging interest regarding nanoparticles (NPs) concerns their potential immunomodulatory and pro-inflammatory activities, as well as their impact in the circulatory system. These biological activities of NPs can be related to the intensity and type of the responses, which can raise concerns about adverse side effects and limit the biomedical applicability of these nanomaterials. Therefore, the purpose of this study was to investigate the impact of a library of cationic cellulose nanocrystals (CNCs) in the human blood and endothelial cells using cell-based assays. First, we evaluated whether the cationic CNCs would cause hemolysis and aggregation or alteration on the morphology of red blood cells (RBC). We observed that although these nanomaterials did not alter RBC morphology or cause aggregation, at 24 h exposure, a mild hemolysis was detected mainly with unmodified CNCs. Then, we analyzed the effect of various concentrations of CNCs on the cell viability of human umbilical vein endothelial cells (HUVECs) in a time-dependent manner. None of the cationic CNCs caused a dose-response decrease in the cell viability of HUVEC at 24 h or 48 h of exposure. The findings of this study, together with the immunomodulatory properties of these cationic CNCs previously published, support the development of engineered cationic CNCs for biomedical applications, in particular as vaccine nanoadjuvants.

The Effect of Fibrous Reinforcement on the Polycondensation Degree of Slag-Based Alkali Activated Composites

Alternative cementitious binders, based on industrial side streams, characterized by a low carbon footprint, are profitably proposed to partially replace Portland cement. Among these alternatives, alkali-activated materials have attracted attention as a promising cementitious binder. In this paper, the chemical stability of the matrix, in fiber-reinforced slag-based alkali-activated composites, was studied, in order to assess any possible effect of the presence of the reinforcement on the chemistry of polycondensation. For this purpose, organic fiber, cellulose, and an inorganic fiber, basalt, were chosen, showing a different behavior in the alkaline media that was used to activate the slag fine powders. The novelty of the paper is the study of consolidation by means of chemical measurements, more than from the mechanical point of view. The evaluation of the chemical behavior of the starting slag in NaOH, indeed, was preparatory to the understanding of the consolidation degree in the alkali-activated composites. The reactivity of alkali-activated composites was studied in water (integrity test, normed leaching test, pH and ionic conductivity), and acids (leaching in acetic acid and HCl attack). The presence of fibers does not favor nor hinder the geopolymerization process, even if an increase in the ionic conductivity in samples containing fibers leads to the hypothesis that samples with fibers are less consolidated, or that fiber dissolution contributes to the conductivity values. The amorphous fraction was enriched in silicon after HCl attack, but the structure was not completely dissolved, and the presence of an amorphous phase is confirmed (C-S-H gel). Basalt fibers partly dissolved in the alkaline environment, leading to the formation of a C-N-A-S-H gel surrounding the fibers. In contrast, cellulose fiber remained stable in both acidic and alkaline conditions.

Predicting the sorption efficiency of heavy metal based on the biochar characteristics, metal sources, and environmental conditions using various novel hybrid machine learning models

Heavy metals in water and wastewater are taken into account as one of the most hazardous environmental issues that significantly impact human health. The use of biochar systems with different materials helped significantly remove heavy metals in the water, especially wastewater treatment systems. Nevertheless, heavy metal's sorption efficiency on the biochar systems is highly dependent on the biochar characteristics, metal sources, and environmental conditions. Therefore, this study implicates the feasibility of biochar systems in the heavy metal sorption in water/wastewater and the use of artificial intelligence (AI) models in investigating efficiency sorption of heavy metal on biochar. Accordingly, this work investigated and proposed 20 artificial intelligent models for forecasting the sorption efficiency of heavy metal onto biochar based on five machine learning algorithms and bagging technique (BA). Accordingly, support vector machine (SVM), random forest (RF), artificial neural network (ANN), M5Tree, and Gaussian process (GP) algorithms were used as the key algorithms for the aim of this study. Subsequently, the individual models were bagged with each other to generate new ensemble models. Finally, 20 intelligent models were developed and evaluated, including SVM, RF, M5Tree, GP, ANN, BA-SVM, BA-RF, BA-M5Tree, BA-GP, BA-ANN, SVM-RF, SVM-M5Tree, SVM-GP, SVM-ANN, RF-M5Tree, RF-GP, RF-ANN, M5Tree-GP, M5Tree-ANN, GP-ANN. Of those, the hybrid models (i.e., BA-SVM, BA-RF, BA-M5Tree, BA-GP, BA-ANN, SVM-RF, SVM-M5Tree, SVM-GP, SVM-ANN, RF-M5Tree, RF-GP, RF-ANN, M5Tree-GP, M5Tree-ANN, GP-ANN) are introduced as the novelty of this study for estimating the heavy metal's sorption efficiency on the biochar systems. Also, the biochar characteristics, metal sources, and environmental conditions were comprehensively assessed and used, and they are considered as a novelty of the study as well. For this aim, a dataset of sorption efficiency of heavy metal was collected and processed with 353 experimental tests. Various performance indexes were applied to evaluate the models, such as RMSE, R², MAE, color intensity, Taylor diagram, box and whiskers plots. This study's findings revealed that AI models could predict heavy metal's sorption efficiency onto biochar with high reliability, and the efficiency of the ensemble models is higher than those of individual models. The results also reported that the SVM-ANN ensemble model is the most superior model among 20 developed models. The predictive model proposed that heavy metal's efficiency sorption on biochar can be accurately forecasted and early warning for the water pollution by heavy metal.

Brain delivery and activity of a lysosomal enzyme using a blood-brain barrier transport vehicle in mice

Most lysosomal storage diseases (LSDs) involve progressive central nervous system (CNS) impairment, resulting from deficiency of a lysosomal enzyme. Treatment of neuronopathic LSDs remains a considerable challenge, as approved intravenously administered enzyme therapies are ineffective in modifying CNS disease because they do not effectively cross the blood-brain barrier (BBB). We describe a therapeutic platform for increasing the brain exposure of enzyme replacement therapies. The enzyme transport vehicle (ETV) is a lysosomal enzyme fused to an Fc domain that has been engineered to bind to the transferrin receptor, which facilitates receptor-mediated transcytosis across the BBB. We demonstrate that ETV fusions containing iduronate 2-sulfatase (ETV:IDS), the lysosomal enzyme deficient in mucopolysaccharidosis type II, exhibited high intrinsic activity and degraded accumulated substrates in both IDS-deficient cell and in vivo models. ETV substantially improved brain delivery of IDS in a preclinical model of disease, enabling enhanced cellular distribution to neurons, astrocytes, and microglia throughout the brain. Improved brain exposure for ETV:IDS translated to a reduction in accumulated substrates in these CNS cell types and peripheral tissues and resulted in a complete correction of downstream disease-relevant pathologies in the brain, including secondary accumulation of lysosomal lipids, perturbed gene expression, neuroinflammation, and neuroaxonal damage. These data highlight the therapeutic potential of the ETV platform for LSDs and provide preclinical proof of concept for TV-enabled therapeutics to treat CNS diseases more broadly.

Understanding LRRK2 kinase activity in preclinical models and human subjects through quantitative analysis of LRRK2 and pT73 Rab10

Variants in the leucine-rich repeat kinase 2 (LRRK2) gene are associated with increased risk for familial and sporadic Parkinson's disease (PD). Pathogenic variants in LRRK2, including the common variant G2019S, result in increased LRRK2 kinase activity, supporting the therapeutic potential of LRRK2 kinase inhibitors for PD. To better understand the role of LRRK2 in disease and to support the clinical development of LRRK2 inhibitors, quantitative and high-throughput assays to measure LRRK2 levels and activity are needed. We developed and applied such assays to measure the levels of LRRK2 as well as the phosphorylation of LRRK2 itself or one of its substrates, Rab10 (pT73 Rab10). We observed increased LRRK2 activity in various cellular models of disease, including iPSC-derived microglia, as well as in human subjects carrying the disease-linked variant LRRK2 G2019S. Capitalizing on the high-throughput and sensitive nature of these assays, we detected a significant reduction in LRRK2 activity in subjects carrying missense variants in LRRK2 associated with reduced disease risk. Finally, we optimized these assays to enable analysis of LRRK2 activity following inhibition in human peripheral blood mononuclear cells (PBMCs) and whole blood, demonstrating their potential utility as biomarkers to assess changes in LRRK2 expression and activity in the clinic.

Early-Onset Cardiomyopathy After Pacemaker Implanted in a Preterm Infant With Congenital Complete Heart Block and Anti-Ro/SSA Antibodies

Congenital complete heart block is a potentially fatal complication that can occur in neonates whose mothers have autoimmune disorders; it has rarely been reported in the presence of Sjögren syndrome. Pacemaker implantation is recommended to treat rhythm abnormalities in these neonates. We report the case of a late-preterm infant with Sjögren-syndrome-antibody-induced complete heart block who underwent temporary bipolar epicardial pacing as a bridge to permanent pacemaker implantation. Soon after the pacemaker was implanted, takotsubo cardiomyopathy developed. To our knowledge, this is the first report of reversible cardiomyopathy after pacemaker implantation in an infant.

Low-Dose vs. Standard-Dose Intravenous Alteplase in Bridging Therapy Among Patients With Acute Ischemic Stroke: Experience From a Stroke Center in Vietnam

Background: To date, the role of bridging intravenous thrombolysis before mechanical thrombectomy (MTE) is controversial but still recommended in eligible patients. Different doses of intravenous alteplase have been used for treating patients with acute ischemic stroke from large-vessel occlusion (LVO-AIS) in Asia, largely due to variations in the risks for intracerebral hemorrhage (ICH) and treatment affordability. Uncertainty exists over the potential benefits of treating low-dose alteplase, as opposed to standard-dose alteplase, prior to MTE among patients with LVO-AIS. Aim: The aim of the study was to compare outcomes of low- vs. standard-dose of bridging intravenous alteplase before MTE among LVO-AIS patients. Methods: We performed a retrospective analysis of LVO-AIS patients who were treated with either 0.6 mg/kg or 0.9 mg/kg alteplase prior to MTE at a stroke center in Northern Vietnam. Multivariable logistic regression models, accounting for potential confounding factors including comorbidities and clinical factors (e.g., stroke severity), were used to compare the outcomes between the two groups. Our primary outcome was functional independence at 90 days following stroke (modified Rankin score; mRS ≤ 2). Secondary outcomes included any ICH incidence, early neurological improvement, recanalization rate, and 90-day mortality. Results: We analyzed data of 107 patients receiving bridging therapy, including 73 with low-dose and 34 with standard-dose alteplase before MTE. There were no statistically significant differences between the two groups in functional independence at 90 days (adjusted OR 1.02, 95% CI 0.29-3.52) after accounting for potential confounding factors. Compared to the standard-dose group, patients with low-dose alteplase before MTE had similar rates of successful recanalization, early neurological improvement, 90-day mortality, and ICH complications. Conclusion: In the present study, patients with low-dose alteplase before MTE were found to achieve comparable clinical outcomes compared to those receiving standard-dose alteplase bridging with MTE. The findings suggest potential benefits of low-dose alteplase in bridging therapy for Asian populations, but this needs to be confirmed by further clinical trials.

Identifying metal binding amino acids based on backbone geometries as a tool for metalloprotein engineering

Metal cofactors within proteins perform a versatile set of essential cellular functions. In order to take advantage of the diverse functionality of metalloproteins, researchers have been working to design or modify metal binding sites in proteins to rationally tune the function or activity of the metal cofactor. This study has performed an analysis on the backbone atom geometries of metal-binding amino acids among 10 different metal binding sites within the entire protein data bank. A set of 13 geometric parameters (features) was identified that is capable of predicting the presence of a metal cofactor in the protein structure with overall accuracies of up to 97% given only the relative positions of their backbone atoms. The decision tree machine-learning algorithm used can quickly analyze an entire protein structure for the presence of sets of primary metal coordination spheres upon mutagenesis, independent of their original amino acid identities. The methodology was designed for application in the field of metalloprotein engineering. A cluster analysis using the data set was also performed and demonstrated that the features chosen are useful for identifying clusters of structurally similar metal-binding sites.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.46 ppm

We present the first results of the Fermilab National Accelerator Laboratory (FNAL) Muon g-2 Experiment for the positive muon magnetic anomaly a_{μ}≡(g_{μ}-2)/2. The anomaly is determined from the precision measurements of two angular frequencies. Intensity variation of high-energy positrons from muon decays directly encodes the difference frequency ω_{a} between the spin-precession and cyclotron frequencies for polarized muons in a magnetic storage ring. The storage ring magnetic field is measured using nuclear magnetic resonance probes calibrated in terms of the equivalent proton spin precession frequency ω[over ˜]_{p}^{'} in a spherical water sample at 34.7 °C. The ratio ω_{a}/ω[over ˜]_{p}^{'}, together with known fundamental constants, determines a_{μ}(FNAL)=116 592 040(54)×10^{-11} (0.46 ppm). The result is 3.3 standard deviations greater than the standard model prediction and is in excellent agreement with the previous Brookhaven National Laboratory (BNL) E821 measurement. After combination with previous measurements of both μ^{+} and μ^{-}, the new experimental average of a_{μ}(Exp)=116 592 061(41)×10^{-11} (0.35 ppm) increases the tension between experiment and theory to 4.2 standard deviations.

Candida parapsilosis endocarditis in an immunocompetent host

This case describes an 83-year-old immunocompetent woman who presented to the emergency department with complaints of nausea, vomiting, and dizziness. She was found to have evidence of embolic stroke secondary to Candida parapsilosis endocarditis. This case emphasizes the challenge of diagnosing fungal endocarditis, as it can be difficult to culture, and the importance of broad differentials even in patients with no obvious risk factors.

Presentation and Treatment of cholinergic Crisis in the setting of Carbamate poisoning

The case details the acute onset of muscarinic poisoning with associated symptoms and long-term complications, as a new readily available suicide tool that clinicians should be keen to, combined with the appropriate treatment so lifesaving therapy may be urgently administered along with future mental health therapy.