Role of Tim-3 in COVID-19: a potential biomarker and therapeutic target.

T cell immunoglobulin and mucin domain containing protein 3 (Tim-3), an immune checkpoint, is important for maintaining immune tolerance. There is increasing evidence that Tim-3 is aberrantly expressed in patients with COVID-19, indicating that it may play an important role in COVID-19. In this review, we discuss the altered expression and potential role of Tim-3 in COVID-19. The expression of Tim-3 and its soluble form (sTim-3) has been found to be upregulated in COVID-19 patients. The levels of Tim-3 on T cells and circulating sTim-3 have been shown to be associated with the severity of COVID-19, suggesting that this protein could be a potential biomarker of COVID-19. Moreover, this review also highlights the potential of Tim-3 as a therapeutic target of COVID-19.

Infrared Image Super Resolution by Combining Compressive Sensing and Deep Learning.

Super resolution methods alleviate the high cost and high difficulty in applying high resolution infrared image sensors. In this paper we present a novel single image super resolution method for infrared images by combining compressive sensing theory and deep learning. Low resolution images can be regarded as the compressed sampling results of the high resolution ones in compressive sensing. With sparsity in this theory, higher resolution images can be reconstructed. However, because of diverse level of sparsity for different images, the output contains noise and loss of high frequency information. Deep convolutional neural network provides a solution to relieve the noise and supplement some missing high frequency information. By concatenating two methods, we manage to produce better results in super resolution tasks for infrared images than SRCNN and ScSR. PSNR and SSIM values are used to quantify the performance. Applying our method to open datasets and actual infrared imaging experiments, we also find better visual results are preserved.

Zeolite A synthesized from alkaline assisted pre-activated halloysite for efficient heavy metal removal in polluted river water and industrial wastewater.

High quality zeolite A was synthesized through a hydrothermal process using alkaline-assisted pre-activated halloysite mineral as the alumina and silica source. The synthesis conditions employed in this study were finely tuned by varying the activating temperature, sodium hydroxide content, water content and Si/Al ratio. The obtained zeolite A showed excellent adsorption properties for both single metal cation solutions and mixed cation solutions when the concentrations of the mixed cations were comparable with those in polluted natural river water and industrial wastewater. High adsorptive capacities for Ag+ (123.05mg/g) and Pb2+ (227.70mg/g) were achieved using the synthesized zeolite A. This observation indicates that the zeolite A synthesized from alkaline-assisted pre-activated halloysite can be used as a low-cost and relatively effective adsorbent to purify heavy metal cation polluted natural river water and industrial wastewater.

PKU-3: An HCl-Inclusive Aluminoborate for Strecker Reaction Solved by Combining RED and PXRD.

A novel microporous aluminoborate, denoted as PKU-3, was prepared by the boric acid flux method. The structure of PKU-3 was determined by combining the rotation electron diffraction and synchrotron powder X-ray diffraction data with well resolved ordered Cl(-) ions in the channel. Composition and crystal structure analysis showed that there are both proton and chlorine ions in the channels. Part of these protons and chlorine ions can be washed away by basic solutions to activate the open pores. The washed PKU-3 can be used as an efficient catalyst in the Strecker reaction with yields higher than 90%.

Key toxic components and sources affecting oxidative potential of atmospheric particulate matter using interpretable machine learning: Insights from fog episodes.

Fog significantly affects the air quality and human health. To investigate the health effects and mechanisms of atmospheric fine particulate matter (PM2.5) during fog episodes, PM2.5 samples were collected from the coastal suburb of Qingdao during different seasons from 2021 to 2022, with the major chemical composition in PM2.5 analyzed. The oxidative potential (OP) of PM2.5 was determined using the dithiothreitol (DTT) method. A positive matrix factorization model was adopted for PM2.5. Interpretable machine learning (IML) was used to reveal and quantify the key components and sources affecting OP. PM2.5 exhibited higher oxidative toxicity during fog episodes. Water-soluble organic carbon (WSOC), NH4+, K+, and water-soluble Fe positively affected the enhancement of DTTV (volume-based DTT activity) during fog episodes. The IML analysis demonstrated that WSOC and K+ contributed significantly to DTTV, with values of 0.31 ± 0.34 and 0.27 ± 0.22 nmol min-1 m-3, respectively. Regarding the sources, coal combustion and biomass burning contributed significantly to DTTV (0.40 ± 0.38 and 0.39 ± 0.36 nmol min-1 m-3, respectively), indicating the significant influence of combustion-related sources on OP. This study provides new insights into the effects of PM2.5 compositions and sources on OP by applying IML models.

Quantifying the pollution changes and meteorological dependence of airborne trace elements coupling source apportionment and machine learning.

Airborne trace elements (TEs) present in atmospheric fine particulate matter (PM2.5) exert notable threats to human health and ecosystems. To explore the impact of meteorological conditions on shaping the pollution characteristics of TEs and the associated health risks, we quantified the variations in pollution characteristics and health risks of TEs due to meteorological impacts using weather normalization and health risk assessment models, and analyzed the source-specific contributions and potential sources of primary TEs affecting health risks using source apportionment approaches at four sites in Shandong Province from September to December 2021. Our results indicated that TEs experience dual effects from meteorological conditions, with a tendency towards higher TE concentrations and related health risks during polluted period, while the opposite occurred during clean period. The total non-carcinogenic and carcinogenic risks of TEs during polluted period increased approximately by factors of 0.53-1.74 and 0.44-1.92, respectively. Selenium (Se), manganese (Mn), and lead (Pb) were found to be the most meteorologically influenced TEs, while chromium (Cr) and manganese (Mn) were identified as the dominant TEs posing health risks. Enhanced emissions of multiple sources for Cr and Mn were found during polluted period. Depending on specific wind speeds, industrialized and urbanized centers, as well as nearby road dusts, could be key sources for TEs. This study suggested that attentions should be paid to not only the TEs from primary emissions but also the meteorology impact on TEs especially during pollution episodes to reduce health risks in the future.

Impacts of dust events on chemical characterization and associated source contributions of atmospheric particulate matter in northern China.

Sand and dust have significant impacts on air quality, climate, and human health. To investigate the influences of dust storms on chemical characterization and source contributions of fine particulate matter (PM2.5) in areas with different distances from dust source regions, PM2.5 and associated chemical composition were measured in two industrial cities with one near sand sources (i.e., Wuhai) and the other far from sand sources (i.e., Jinan) in northern China in March 2021. Results showed that PM mass concentrations significantly increased and exceeded the Chinese National Ambient Air Quality standard during the dust events, with absolute concentrations and fractional contributions of PM2.5-bound crustal and trace elements increased while secondary inorganic ions decreased at both sites. Crustal materials dominated the increased PM2.5 mass from non-dust period to dust period in both cities. These were further evidenced by PM2.5 source apportionment results from positive matrix factorization model. During the dust events, dust sources contributed up to 88% of PM2.5 mass in Wuhai and ∼38% of PM2.5 mass in Jinan, a city about thousands of kilometers away from the sand source. Besides, the measurement data indicated that dust from northwest China may also bring along with high abundance of organic matter and vanadium. Secondary and traffic sources were two of the most important source contributors to PM2.5 in both cities during the non-dust periods. However, the near sand source city was more susceptible to the aggravating effects of dust and minerals, with much higher contributions by crustal materials (∼47%, from the aspect of chemical components) and dust-related sources (∼26%, from the aspect of sources) to PM2.5 mass even during non-dust periods. This study highlighted the urgent need for more action and effective control of sand sources to reduce the impact on air quality in downstream regions.

Variations of PM2.5-bound elements and their associated effects during long-distance transport of dust storms: Insights from multi-sites observations.

Dust storms are a significant concern because of their adverse effects on ambient air quality and human health. To investigate the evolution of dust storms during long-distance transport and its impacts on air quality and human health risks in cities along the transport pathway, we monitored the major fraction of dust (i.e., particle-bound elements) online in four cities in northern China during March 2021. Three dust events originating from the Gobi Desert of North China and Mongolia and the Taklimakan Desert of Northwest China were captured. We investigated the source regions of dust storms using daily multi-sensor absorbing aerosol index products, backward trajectories, and specific element ratios, identified and quantified sources of particle-bound elements using Positive Matrix Factorization model, and calculated the carcinogenic and non-carcinogenic risks of elements using a health risk assessment model. Our results indicated that under the influence of dust storms, mass concentrations of crustal elements increased up to dozens of times in cities near the dust source and up to ten times in cities farther from the source. In contrast, anthropogenic elements increased less or even decreased, depending on the relative contributions of the increase caused by accumulation of dust itself and entrainment along the transport path and the decrease caused by dilution of high wind speeds. Si/Fe ratio was found to be a valuable indicator for characterizing the attenuation of the amount of dust along its transport pathways, especially for the case originated from northern source regions. This study highlights the significant role of source regions, intensity and attenuation rates of dust storms, and wind speeds in determining the increased levels of element concentrations during dust storms and its associated impacts on downwind areas. Furthermore, non-carcinogenic risks of particle-bound elements increased at all sites during dust events, emphasizing the importance of personal exposure protection during dust storms.

Resveratrol activates the SIRT1/PGC-1 pathway in mice to improve synaptic-related cognitive impairment after TBI.

Traumatic brain injury (TBI) is the most common form of craniocerebral injury. Post-TBI neurological impairment is often accompanied by cognitive dysfunction. The potential molecular mechanisms of post-TBI cognitive impairment are not well characterized. Resveratrol, a natural polyphenolic agent, has been shown to improve cognitive function in neurological disorders and aging models through its anti-inflammatory activity. However, whether it can affect synapses to improve cognitive function and the potential mechanisms are not clear. Synapse plays an important role in cognitive function, and synaptophysin(SYN) is one of the important factors involved in synapse formation. Sirtuin 1 (SIRT1) has a neuroprotective effect via its effect on various biological processes, such as inflammation, metabolism, apoptosis, and autophagy. The results of this research suggest that resveratrol increases synaptophysin by activating the SIRT1/PGC-1 pathway and improves post-TBI cognitive function. Use of SIRT1 inhibitor (EX-527) and agonist (SRT1720) in the mice experiments verified the effect and mechanism of action of resveratrol in improving cognitive function. Our study identifies potential therapeutic targets for post-TBI cognitive dysfunction.

Geochemistry of dissolved trace elements and heavy metals in the Dan River Drainage (China): distribution, sources, and water quality assessment.

Dissolved trace elements and heavy metals in the Dan River drainage basin, which is the drinking water source area of South-to-North Water Transfer Project (China), affect large numbers of people and should therefore be carefully monitored. To investigate the distribution, sources, and quality of river water, this study integrating catchment geology and multivariate statistical techniques was carried out in the Dan River drainage from 99 river water samples collected in 2013. The distribution of trace metal concentrations in the Dan River drainage was similar to that in the Danjiangkou Reservoir, indicating that the reservoir was significantly affected by the Dan River drainage. Moreover, our results suggested that As, Sb, Cd, Mn, and Ni were the major pollutants. We revealed extremely high concentrations of As and Sb in the Laoguan River, Cd in the Qingyou River, Mn, Ni, and Cd in the Yinhua River, As and Sb in the Laojun River, and Sb in the Dan River. According to the water quality index, water in the Dan River drainage was suitable for drinking; however, an exposure risk assessment model suggests that As and Sb in the Laojun and Laoguan rivers could pose a high risk to humans in terms of adverse health and potential non-carcinogenic effects.