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Upgrading of polyethylene terephthalate (PET) waste into valuable oxygenated molecules is a fascinating process, yet it remains challenging. Herein, we developed a two‐step strategy involving methanolysis of PET to dimethyl terephthalate (DMT), followed by hydrogenation of DMT to produce the high‐valued chemical methyl p‐methyl benzoate (MMB) using a fixed‐bed reactor and a Cu/ZrO2 catalyst. Interestingly, we discovered the phase structure of ZrO2 significantly regulates the selectivity of products. Cu supported on monoclinic ZrO2 (5 %Cu/m‐ZrO2) exhibits an exceptional selectivity of 86 % for conversion of DMT to MMB, while Cu supported on tetragonal ZrO2 (5 %Cu/t‐ZrO2) predominantly produces p‐xylene (PX) with selectivity of 75 %. The superior selectivity of MMB over Cu/m‐ZrO2 can be attributed to the weaker acid sites present on m‐ZrO2 compared to t‐ZrO2. This weak acidity of m‐ZrO2 leads to a moderate adsorption capability of MMB, and facilitating its desorption. Furthermore, DFT calculations reveal Cu/m‐ZrO2 catalyst shows a higher effective energy barrier for cleavage of second C−O bond compared to Cu/t‐ZrO2 catalyst; this distinction ensures the high selectivity of MMB. This catalyst not only presents an approach for upgrading of PET waste into fine chemicals but also offers a strategy for controlling the primary product in a multistep hydrogenation reaction. [ABSTRACT FROM AUTHOR]

PurposeThe purpose of this study was to evaluate the relationship between apolipoprotein A-IV (apoA-IV) plasma concentrations and acute coronary syndrome (ACS).MethodsPlasma apoA-IV concentrations were measured in 115 patients with different types of ACS and in 68 gender- and age-matched control subjects using Enzyme-Linked Immunosorbent Assay (ELISA) kits. The clinical data were collected by an internist, who was blinded to plasma apoA-IV concentrations.ResultsPlasma apoA-IV levels in ACS patients were significantly decreased compared to the levels in control subjects (437.0±157.5 μg/mL vs. 590.2±183.7 μg/mL, P

During cortical development, Cajal-Retzius (CR) cells are among the earliest-born subclasses of neurons. These enigmatic neurons play an important role in cortical development through their expression of the extracellular protein, reelin. CR cells arise from discrete sources within the telencephalon, including the pallial-subpallial border and the medial (cortical hem) regions of the pallium. Combined evidence suggests that CR cells derived from distinct origins may have different distributions and functions. By tracing CR cells derived from the cortical hem using the inducible Cre transgenic mouse tool, Frizzled 10-CreER™, we examined the specific properties of hem-derived CR cells during cortical development. Our results show that the progenitor zone for later production of CR cells from the hem can be specifically marked as early as embryonic day 6.5 (E6.5), a pre-neural period. Moreover, using our Cre line, we found that some hem-derived CR cells migrated out along the fimbrial radial glial scaffold, which was also derived from the cortical hem, and preferentially settled in the hippocampal marginal zone, which indicated specific roles for hem-derived CR cells in hippocampal development.

In December 2019, a series of cases of pneumonia of unknown cause was reported in Wuhan, Hubei Province, China. On January 7, 2020, the causative pathogen was identified as a [...]

For the textile industry, fabric defect detection is an important part of production. In order to make the automatic fabric defect detection system used in production sites, this article proposes a lightweight algorithm Lightweight Single Shot Multi-Box Detector (LW-SSD) to address the issues of low detection accuracy, high computational complexity, and difficulty in deploying on hardware devices with limited computing power in fabric defect detection. Firstly, MobileNetv3 is introduced as the backbone network to reduce the number of model parameters. Secondly, in the feature fusion module, down-sampling stacking is used to fuse the feature maps processed by maximum pooling and regular 3 × 3 convolution, respectively, to enhance the generalization and small target feature extraction capability of the network. Then, the dilated convolution is incorporated into the Inceptionv3 to form a multi-branch parallel dilated convolution module, which can expand the receptive field of the feature layer and enhance the extraction of the target information. Finally, a dual-channel attention module is added, which adds the maximum pooling operation based on the efficient channel attention for deep convolutional neural networks (ECA) channel attention mechanism to highlight defect features and suppress background noise features. The experiments show that the accuracy of the system is improved while maintaining the faster detection speed. Among them, the LW-SSD algorithm has an accuracy improvement of 10.03% on the self-made dataset, a reduction of 58% in the number of model parameters compared to the Single Shot Multi-Box Detector (SSD) algorithm, and the detection speed reaches 48 frames per second. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop clinical scores to predict the risk of intensive care unit (ICU) admission in patients with COVID-19 and end stage kidney disease (ESKD). This was a prospective study in which 100 patients with ESKD were enrolled and divided into two groups: the ICU group and the non-ICU group. We utilized univariate logistic regression and nonparametric statistics to analyze the clinical characteristics and liver function changes of both groups. By plotting receiver operating characteristic curves, we identified clinical scores that could predict the risk of ICU admission. Out of the 100 patients with Omicron infection, 12 patients were transferred to the ICU due to disease aggravation, with an average of 9.08 days from hospitalization to ICU transfer. Patients transferred to the ICU more commonly experienced shortness of breath, orthopnea, and gastrointestinal bleeding. The peak liver function and changes from baseline in the ICU group were significantly higher, with p values <.05. We found that the baseline platelet-albumin-bilirubin score (PALBI) and neutrophil-to-lymphocyte ratio (NLR) were good predictors of ICU admission risk, with area under curve values of 0.713 and 0.770, respectively. These scores were comparable to the classic Acute Physiology and Chronic Health Evaluation II (APACHE-II) score (p >.05). Patients with ESKD and Omicron infection who are transferred to the ICU are more likely to have abnormal liver function. The baseline PALBI and NLR scores can better predict the risk of clinical deterioration and early transfer to the ICU for treatment. [ABSTRACT FROM AUTHOR]