Correction: Thrombotic and bleeding events,mortality, and anticoagulant use among 546,656 hospitalized patients with COVID‑19 in the United States: a retrospective cohort study

Journal of Thrombosis and Thrombolysis -     

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.     

Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m^?2,1.04 kg m^?2, and 1.13 kg m^?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R² (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m^?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.     

In vivo epigenetic effects induced by engineered nanomaterials: A case study of copper oxide and laser printer-emitted engineered nanoparticles

Evidence continues to grow on potential environmental health hazards associated with engineered nanomaterials (ENMs). While the geno- and cytotoxic effects of ENMs have been investigated, their potential to target the epigenome remains largely unknown. The aim of this study is two-fold: 1) determining whether or not industry relevant ENMs can affect the epigenome in vivo and 2) validating a recently developed in vitro epigenetic screening platform for inhaled ENMs. Laser printer-emitted engineered nanoparticles (PEPs) released from nano-enabled toners during consumer use and copper oxide (CuO) were chosen since these particles induced significant epigenetic changes in a recent in vitro companion study. In this study, the epigenetic alterations in lung tissue, alveolar macrophages and peripheral blood from intratracheally instilled mice were evaluated. The methylation of global DNA and transposable elements (TEs), the expression of the DNA methylation machinery and TEs, in addition to general toxicological effects in the lung were assessed. CuO exhibited higher cell-damaging potential to the lung, while PEPs showed a greater ability to target the epigenome. Alterations in the methylation status of global DNA and TEs, and expression of TEs and DNA machinery in mouse lung were observed after exposure to CuO and PEPs. Additionally, epigenetic changes were detected in the peripheral blood after PEPs exposure. Altogether, CuO and PEPs can induce epigenetic alterations in a mouse experimental model, which in turn confirms that the recently developed in vitro epigenetic platform using macrophage and epithelial cell lines can be successfully utilized in the epigenetic screening of ENMs.     

Exact confidence intervals for the average causal effect on a binary outcome

Based on the physical randomization of completely randomized experiments, in a recent article in Statistics in Medicine, Rigdon and Hudgens propose two approaches to obtaining exact confidence intervals for the average causal effect on a binary outcome. They construct the first confidence interval by combining, with the Bonferroni adjustment, the prediction sets for treatment effects among treatment and control groups, and the second one by inverting a series of randomization tests. With sample size n, their second approach requires performing O(n⁴)randomization tests. We demonstrate that the physical randomization also justifies other ways to constructing exact confidence intervals that are more computationally efficient. By exploiting recent advances in hypergeometric confidence intervals and the stochastic order information of randomization tests, we propose approaches that either do not need to invoke Monte Carlo or require performing at most O(n²)randomization tests. We provide technical details and R code in the Supporting Information . Copyright © 2016 John Wiley & Sons, Ltd.     

A randomized study on the effect of modified behavioral activation treatment for depressive symptoms in rural left-behind elderly

Objective: To evaluate the effectiveness of a modified behavioral activation treatment (MBAT) intervention on reducing depressive symptoms in rural left-behind elderly.

Method: This is a randomized study registered in Chinese Clinical Trial Registry (ChiCTR-IOR-17011289). Eighty rural left-behind elderly people who had a Geriatric Depression Scale (GDS) score between 11 and 25 were randomly assigned to the intervention (n?=?40) and control group (n?=?40). The intervention group received both MBAT and regular treatment for 8 weeks while the control group received regular treatment. Both groups were assessed with the GDS, Beck Anxiety Inventory (BAI), and Oxford Happiness Questionnaire (OHQ) at baseline, immediately post-intervention, and at 3 months post-intervention.

Results: There were a total of 73 participants that completed the intervention. The scores of GDS and BAI decreased significantly, but the scores of OHQ increased significantly in the intervention group after 8 sessions of MBAT (P?<?.01). The reduction in depression symptoms after the intervention was maintained at the 3-month follow-up. Significant differences in GDS, BAI, and OHQ scores were observed between the intervention group and the control group (P?<?.01).

Conclusion: MBAT produced a significantly greater reduction in depressive symptoms than regular care in rural left-behind elderly.

Clinical or methodological significance of this article: A modified behavioral activation (BA) psychotherapy can significantly reduce the recurrence and seriousness of depression symptoms in the left-behind elderly with mild to moderate depression. This study also suggests that further study of the MBAT as an intervention will provide a direction for the management of mental health in rural left-behind elders.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.