Preparation and characterization of high-ash coal slime-based soil amendment as well as investigations of its adsorption performance and mechanisms towards heavy metals in soil.

In this study, high-ash coal slime-based mineral soil amendment (MSA) was prepared via the hydrothermal method using high-ash coal slime as raw material, supplemented with activator calcium oxide and additive KOH solution. After hydrothermal treatment at 230 °C for 5 h, the original crystalline phase (quartz and kaolinite) of the high-ash slime was completely transformed into hydrotalcite zeolite, tobermorite, and silicate of potassium aluminosilicate, which has the largest specific surface area. The adsorption of Pb2+ and Cd2+ was adherent to the kinetic equation of secondary adsorption and Freundlich models, and the removal of Pb2+ and Cd2+ reached up to 362.58 mg g-1 and 64.67 mg g-1. The successive releases of SiO2 and CaO from MSA conformed to the Elovich equation, whereas the releases of SiO2 in Cd-containing environments and CaO in Pb- and Cd-containing environments more closely conformed to the power function; the releases of K2O all conformed to the first-order kinetic equation. The presence of Pb2+ and Cd2+ in the environment promotes the release of potassium and calcium elements with MSA's ion-exchange ability, and attenuates the release of silicon elements. Combining Pb2+ and Cd2+ with silicon resulted in the intolerant precipitation of 3PbO·2SiO2 and Cd2SiO4. The mineral precipitation mechanism is the most important mechanism of MSA in immobilizing heavy metals, accounting for 72.7%-80.5% of the total adsorption. Further contaminated soil immobilization experiments also showed that the application of MSA significantly reduced the bioavailability of soil heavy metals. When the MSA addition amount was 1.6%, the residual state increased by 63.58%. In conclusion, preparing MSA may effectively utilize coal-based solid waste with high added value.

Hydrothermal alkaline synthesis and release properties of silicon compound fertiliser using high-ash coal slime.

High-ash coal slime is difficult to utilise as a boiler fuel, and its accumulation results in environmental pollution. In this study, we describe a new method for the preparation of high-ash coal slime silica compound fertiliser (HASF) using CaO-KOH mixed hydrothermal method to optimize the utilization of this industrial waste and relieve the pressure on the fertiliser industry. The coal slime (D0) used in this study and its dry basis ash content by 1 mol/L and 4 mol/L sulfuric acid pre-activation (D1, D4) were greater than 85%. The effective silicon content of D0, D1, and D4 silica compound fertilisers reached 30.24%, 31.24%, and 17.35%, respectively, and the sums of effective silica-calcium-potassium oxides were 57.28%, 58.87%, and 48.16%, respectively, under the optimal reaction conditions of 230 °C, 15 h, and 1 mol/L KOH, which met the market requirements, as determined using single-factor experiments. We used XRD, FTIR, and SEM-EDS analysis techniques to demonstrate that tobermorite and leucite were the main mineral phases of the compound fertiliser, and activated coal slime D4, which contains only quartz single crystals, required more demanding reaction conditions in the synthesis reaction. Subsequently, the cumulative release pattern of HASF silica was well described by the power function equation via repeated extraction and dissolution experiments, with the dissolution rate following D4 > D1 ≈ D0. Furthermore, 4 mol/L sulfuric acid pre-activation resulted in the enrichment of HASF combined with organic matter and increased the slow-release rate of HASF silica. Thus, the synthesized HASF could have potential application prospects in soil improvement and fertilisation.

Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study.

Background: Tongue images (the colour, size and shape of the tongue and the colour, thickness and moisture content of the tongue coating), reflecting the health state of the whole body according to the theory of traditional Chinese medicine (TCM), have been widely used in China for thousands of years. Herein, we investigated the value of tongue images and the tongue coating microbiome in the diagnosis of gastric cancer (GC). Methods: From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiome of the tongue coating samples. Then, artificial intelligence (AI) deep learning models were established to evaluate the value of tongue images and the tongue coating microbiome in the diagnosis of GC. Considering that tongue imaging is more convenient and economical as a diagnostic tool, we further conducted a prospective multicentre clinical study from May 2020 to March 2022 in China and recruited 937 patients with GC and 1911 participants with NGC from 10 centres across China to further evaluate the role of tongue images in the diagnosis of GC. Moreover, we verified this approach in another independent external validation cohort that included 294 patients with GC and 521 participants with NGC from 7 centres. This study is registered at ClinicalTrials.gov, NCT01090362. Findings: For the first time, we found that both tongue images and the tongue coating microbiome can be used as tools for the diagnosis of GC, and the area under the curve (AUC) value of the tongue image-based diagnostic model was 0.89. The AUC values of the tongue coating microbiome-based model reached 0.94 using genus data and 0.95 using species data. The results of the prospective multicentre clinical study showed that the AUC values of the three tongue image-based models for GCs reached 0.88-0.92 in the internal verification and 0.83-0.88 in the independent external verification, which were significantly superior to the combination of eight blood biomarkers. Interpretation: Our results suggest that tongue images can be used as a stable method for GC diagnosis and are significantly superior to conventional blood biomarkers. The three kinds of tongue image-based AI deep learning diagnostic models that we developed can be used to adequately distinguish patients with GC from participants with NGC, even early GC and precancerous lesions, such as atrophic gastritis (AG). Funding: The National Key R&D Program of China (2021YFA0910100), Program of Zhejiang Provincial TCM Sci-tech Plan (2018ZY006), Medical Science and Technology Project of Zhejiang Province (2022KY114, WKJ-ZJ-2104), Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer (JBZX-202006), Natural Science Foundation of Zhejiang Province (HDMY22H160008), Science and Technology Projects of Zhejiang Province (2019C03049), National Natural Science Foundation of China (82074245, 81973634, 82204828), and Chinese Postdoctoral Science Foundation (2022M713203).

Modulation effect of low-intensity transcranial ultrasound stimulation on REM and NREM sleep.

Previous studies have shown that modulating neural activity can affect rapid eye movement (REM) and non-rapid eye movement (NREM) sleep. Low-intensity transcranial ultrasound stimulation (TUS) can effectively modulate neural activity. However, the modulation effect of TUS on REM and NREM sleep is still unclear. In this study, we used ultrasound to stimulate motor cortex and hippocampus, respectively, and found the following: (i) In healthy mice, TUS increased the NREM sleep ratio and decreased the REM sleep ratio, and altered the relative power and sample entropy of the delta band and spindle in NREM sleep and that of the theta and gamma bands in REM sleep. (ii) In sleep-deprived mice, TUS decreased the ratio of REM sleep or the relative power of the theta band during REM sleep. (iii) In sleep-disordered Alzheimer's disease (AD) mice, TUS increased the total sleep time and the ratio of NREM sleep and modulated the relative power and the sample entropy of the delta and spindle bands during NREM and that of the theta band during REM sleep. These results demonstrated that TUS can effectively modulate REM and NREM sleep and that modulation effect depends on the sleep state of the samples, and can improve sleep in sleep-disordered AD mice.

Role of a cotton endoreduplication-related gene, GaTOP6B, in response to drought stress.

MAIN CONCLUSION: Cotton GaTOP6B is involved in cellular endoreduplication and a positive response to drought stress via promoting plant leaf and root growth. Drought is deemed as one of adverse conditions that could cause substantial reductions in crop yields worldwide. Since cotton exhibits a moderate-tolerant phenotype under water-deficit conditions, the plant could therefore be used to characterize potential new genes regulating drought tolerance in crop plants. In this work, GaTOP6B, encoding DNA topoisomerase VI subunit B, was identified in Asian cotton (Gossypium arboreum). Virus-induced gene silencing (VIGS) and overexpression (OE) were used to investigate the biological function of GaTOP6B in G. arboreum and Arabidopsis thaliana under drought stress. The GaTOP6B-silencing plants showed a reduced ploidy level, and displayed a compromised tolerance phenotype including lowered relative water content (RWC), decreased proline content and antioxidative enzyme activity, and an increased malondialdehyde (MDA) content under drought stress. GaTOP6B-overexpressing Arabidopsis lines, however, had increased ploidy levels, and were more tolerant to drought treatment, associated with improved RWC maintenance, higher proline accumulation, and reduced stomatal aperture under drought stress. Transcriptome analysis showed that genes involved in the processes like cell cycle, transcription and signal transduction, were substantially up-regulated in GaTOP6B-overexpressing Arabidopsis, promoting plant growth and development. More specifically, under drought stress, the genes involved in the biosynthesis of secondary metabolites such as phenylpropanoid, starch and sucrose were selectively enhanced to improve tolerance in plants. Taken together, the results demonstrated that GaTOP6B could coordinately regulate plant leaf and root growth via cellular endoreduplication, and positively respond to drought stress. Thus, GaTOP6B could be a competent candidate gene for improvement of drought tolerance in crop species.