Small extracellular vesicle-based delivery of interleukin-10 improves treatment of experimental autoimmune uveitis.

Non-infectious uveitis is an intraocular autoimmune disease mainly characterized by immune dysregulation of the eye, which may cause blindness if not well treated. Interleukin 10 (IL-10) is a potent cytokine with multiple immunoregulatory functions. However, it's in vivo activity is unstable owing to its inherent protein instability and short plasma half-life. Therefore, our previous research tried to establish IL-10-overexpressing MSC-sEVs (sEVs-IL10) using lentiviral transfection. While this approach indeed improved drug delivery, it also suffered from tedious procedures and limited loading efficiency. Accordingly, we constructed a novel MSC-sEVs-based delivery system for IL-10 (IL-10@sEVs) by sonication. The obtained formulation (IL-10@sEVs) had relatively higher loading efficiency and exerted a more profound immunomodulatory effect than sEVs-IL10 in vitro. Furthermore, IL-10@sEVs had significant therapeutic effects in a mouse model of experimental autoimmune uveitis (EAU) by decreasing the percentage of Th17 cells, increasing regulatory T cells in the eye, and draining lymph nodes. In summary, sonication outperforms conventional transfection methods for loading IL-10 into MSC-sEVs.

Decision tree-based identification of important molecular fragments for protein-ligand binding.

Fragment-based drug design is an emerging technology in pharmaceutical research and development. One of the key aspects of this technology is the identification and quantitative characterization of molecular fragments. This study presents a strategy for identifying important molecular fragments based on molecular fingerprints and decision tree algorithms and verifies its feasibility in predicting protein-ligand binding affinity. Specifically, the three-dimensional (3D) structures of protein-ligand complexes are encoded using extended-connectivity fingerprints (ECFP), and three decision tree models, namely Random Forest, XGBoost, and LightGBM, are used to quantitatively characterize the feature importance, thereby extracting important molecular fragments with high reliability. Few-shot learning reveals that the extracted molecular fragments contribute significantly and consistently to the binding affinity even with a small sample size. Despite the absence of location and distance information for molecular fragments in ECFP, 3D visualization, in combination with the reverse ECFP process, shows that the majority of the extracted fragments are located at the binding interface of the protein and the ligand. This alignment with the distance constraints critical for binding affinity further supports the reliability of the strategy for identifying important molecular fragments.

Neural networks prediction of the protein-ligand binding affinity with circular fingerprints.

BACKGROUND: Protein-ligand binding affinity is of significant importance in structure-based drug design. Recently, the development of machine learning techniques has provided an efficient and accurate way to predict binding affinity. However, the prediction performance largely depends on how molecules are represented. OBJECTIVE: Different molecular descriptors are designed to capture different features. The study aims to identify the optimal circular fingerprints for predicting protein-ligand binding affinity with matched neural network architectures. METHODS: Extended-connectivity fingerprints (ECFP) and protein-ligand extended connectivity fingerprints (PLEC) encode circular atomic and bonding connectivity environments with the preference for intra- and inter-molecular features, respectively. Densely-connected neural networks are employed to map the circular fingerprints of protein-ligand complexes to binding affinitiesRESULTS:The performance of neural networks is sensitive to the parameters used for ECFP and PLEC fingerprints. The R2_score of the evaluated ECFP and PLEC fingerprints reaches 0.52 and 0.49, higher than that of the improperly set ECFP and PLEC fingerprints with R2_score of 0.45 and 0.38, respectively. Additionally, compared to the predictions from the standalone fingerprints, the ECFP+PLEC conjoint ones slightly improve the prediction accuracy with R2_score of approximately 0.55. CONCLUSION: Both intra- and inter-molecular structural features encoded in the circular fingerprints contribute to the protein-ligand binding affinity. Optimizing the parameters of ECFP and PLEC can enhance performance. The conjoint fingerprint scheme can be generally extended to other molecular descriptors for enhanced feature engineering and improved predictive performance.

cRNAsp12 Web Server for the Prediction of Circular RNA Secondary Structures and Stabilities.

Circular RNAs (circRNAs) are a novel class of non-coding RNA that, unlike linear RNAs, form a covalently closed loop without the 5' and 3' ends. Growing evidence shows that circular RNAs play important roles in life processes and have great potential implications in clinical and research fields. The accurate modeling of circRNAs structure and stability has far-reaching impact on our understanding of their functions and our ability to develop RNA-based therapeutics. The cRNAsp12 server offers a user-friendly web interface to predict circular RNA secondary structures and folding stabilities from the sequence. Through the helix-based landscape partitioning strategy, the server generates distinct ensembles of structures and predicts the minimal free energy structures for each ensemble with the recursive partition function calculation and backtracking algorithms. For structure predictions in the limited structural ensemble, the server also provides users with the option to set the structural constraints of forcing the base pairs and/or forcing the unpaired bases, such that only structures that meet the criteria are enumerated recursively.

Pollution Characteristics, Spatial Distribution, and Evaluation of Heavy Metal(loid)s in Farmland Soils in a Typical Mountainous Hilly Area in China.

Heavy metal(loid)s pollution in farmland soil is not only a serious environmental but also a human health-related issue. Accurate understanding and evaluation of heavy metal pollution levels in the soil are very important for sustainable agricultural development and food safety. Mountainous and hilly areas have the dual functions of industrial development and agricultural production, and the farmland soil in these areas is more susceptible to heavy metal pollution. In this study, the single factor index, Nemerow index, geo-accumulation index, enrichment factor index, and potential ecological risk indices, which are mainly used to assess the contamination and risk of heavy metals in farmland soils. The sources of heavy metals in agricultural soils of the study area were analyzed using correlation analysis and principal component analysis. Finally, geostatistical methods were used to map the heavy metal contamination of farmland soils. An average concentration of all heavy metals (except As) in farmland soils of the study area exceeded the corresponding background values, as indicated by the obtained results. The results of the principal component analysis showed that the heavy metal sources in the soils of the study area can be classified into two groups. The five pollutant index methods all showed the most serious Hg pollution in the study area. The integrated pollutant mapping results showed that the risk of heavy metal pollution in the study area was mostly moderate, except for the western and central parts of the region. This study enhances understanding of the pollution levers of heavy metals in Yiyuan farmland soils, and also can facilitate the monitoring of heavy metal contaminants at the primary stage of the food chain and assess the risk of the presence of heavy metal contaminants in food, thus improving the health of the residents.

Different MicroRNA profiles in Peripheral Blood mononuclear cells from patients with initial-onset and recurrent vogt-Koyanagi-Harada Disease.

BACKGROUND: Vogt-Koyanagi-Harada (VKH) disease is a common type of uveitis that leads to blindness. The clinical manifestations and treatment solutions are different between initial-onset and recurrent VKH. Therefore, identifying the microRNA (miRNA) profiles from initial-onset and recurrent VKH patients may shed light on the molecular mechanisms underlying the pathogenesis of VKH disease. METHODS AND RESULTS: RNAs isolated from peripheral blood mononuclear cells (PBMCs) from patients with initial-onset VKH, recurrent VKH, and healthy individuals were subjected to high-throughput miRNA sequencing. Pairwise analysis of miRNA sequencing data between groups was conducted to identify differentially expressed miRNAs (DEMs), which were verified using real-time quantitative polymerase chain reaction. After receiver operating characteristic analyses, we found that hsa-miR-4664-3p, hsa-miR-7704, hsa-miR-4504, and hsa-miR-206 may serve as biomarkers of different VKH stages. DEMs were classified into three groups based on their differential expression: DEMs in initial-onset stage, DEMs in recurrent stage, and DEMs common between both VKH stages (shared DEMs). Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes identified the mitogen-activated protein kinase, tumor necrosis factor, and mechanistic target of rapamycin kinase pathways as significantly enriched among the target genes of recurrent stage and shared DEMs. Furthermore, we mapped a network of competing endogenous RNAs for hsa-miR-206, which we used to identify putative targets for VKH treatment. CONCLUSION: Hsa-miR-4664-3p, hsa-miR-7704, hsa-miR-4504, and hsa-miR-206 may serve as biomarkers for different stages of VKH. Additionally, our competing endogenous RNA network of hsa-miR-206 provides a new direction for VKH treatment.

Thermal enhancement of gangue-cemented paste backfill with graphite and silica sand: an experimental investigation.

Thermal conductivity of mine backfill is vital for understanding the geothermal energy extraction potential in deep underground mines. Geothermal energy extraction efficiency could be improved with higher thermal conductivity of backfill. Thermal conductivities of gangue-cemented paste backfill enhanced with graphite and silica sand were investigated through laboratory tests in this article. The thermal conductivity measurement was conducted using the Hot Disk Thermal Constants Analyzer. Effects of graphite and silica sand on the thermal conductivity, slump, and compressive strength of gangue-cemented paste backfill were analyzed. The results highlighted the favorable influence of graphite on the thermal performance of backfilling materials, with adverse effect on the mechanical behavior and negative impact on the flowability. Thermal conductivity of gangue-cemented paste backfill markedly increased with graphite ratio, while more water is consumed for the workable slurry with the increased graphite ratio, which also leads to the degradation of compressive strength. The reasonable graphite content should be determined with the expected thermal enhancement and acceptable compressive strength. The addition of silica sand can effectively enhance the thermal conductivity of GCPB without degrading the compressive performance and flow performance. This study would provide a new insight into the design of backfill considering the thermal conductivity and lay a foundation for the efficient geothermal energy in deep mines.

Long term leaching behavior of arsenic from cemented paste backfill made of construction and demolition waste: Experimental and numerical simulation studies.

The arsenic long-term leaching behavior of the cemented paste backfill obtained from the construction and demolition waste (CPB-CDW) is captured, which can be utilized in the potential engineering application. Laboratory studies were conducted on samples obtained from a mining site and the test results were imported into a numerical simulation model. It was found that the Elovich equation can describe well the As leaching behavior. Initially, the As concentrations decreased in the roadway in the mine and then increased along the roadway and attained a maximum concentration (8.149 × 10-3 mg/L) at the lower segment. When the groundwater was in the static mode, the As concentration increased dramatically followed by a gradual increase. Eventually, the concentration decreased gradually. For the dynamic condition, the As tended to move in a cluster form and the associated leaching and mass transfer process of As in the CPB-CDW were similar to those observed when the groundwater was in a static condition. However, the difference in the distribution of the amount of As in the leachate fluctuated continuously and the overall trend was to approach a steady state. As such, the time frame of such a mass transfer in the mobilized water is reduced significantly.

The effect of folic acid deficiency on Mest/Peg1 in neural tube defects.

OBJECTIVE: Neural tube defects (NTDs) are one of the most common and serious birth defects in human beings caused by genetic and environmental factors. Folate insufficiency is involved in the occurrence of NTDs and folic acid supplementation can prevent NTDs occurrence, however, the underlying mechanism remains poorly understood. METHODS: We established cell and animal models of folic acid deficiency to detect the methylation modification and expression levels of genes by MassARRAY and real-time PCR, respectively. Results and conclusion: In the present study, we found firstly that in human folic acid-insufficient NTDs, the methylation level of imprinted gene Mest/Peg1 was decreased. By using a folic acid-deficient cell model, we demonstrated that Mest/Peg1 methylation was descended. Meanwhile, the mRNA level of Mest/Peg1 was up-regulated via hypomethylation modification under low folic acid conditions. Consistent with the results in cell models, Mest/Peg1 expression was elevated through hypomethylation regulation in folate-deficient animal models. Furthermore, the up-regulation of Mest/Peg1 inhibited the expression of Lrp6 gene, a crucial component of Wnt pathway. Similar results with Lrp6 down-regulation of fetal brain were verified in animal models under folic acid-deficient condition. Taken together, our findings indicated folic acid increased the expression of Mest/Peg1 via hypomethylation modification, and then inhibited Lrp6 expression, which may ultimately impact on the development of nervous system through the inactivation of Wnt pathway.

Environmental behavior of construction and demolition waste as recycled aggregates for backfilling in mines: Leaching toxicity and surface subsidence studies.

Environmental behavior of construction and demolition waste in cemented backfilling mining technology (CW-CBMT) is studied, with the aim of expanding the scope of construction and demolition waste (CDW) utilization, as well as developing strategies to release coal resources. Toxicity leaching, scanning electron microscopy (SEM), and mechanical properties testing about on-site sampling are carried out, and surface subsidence is surveyed. The results reveal that the maximum leaching concentration (0.00113 mg/L) of arsenic from cemented backfilling body with construction and demolition waste (CBCW) is small, the leaching solution is alkaline, and the leaching of heavy metals is influenced by aggregate particle size and by acidity and alkalinity. The results also show that the average compressive strength of CBCW is 2.4 MPa. The distribution of aggregates and elemental content influence the spatial distribution of compressive strength. The variation of internal distribution of elemental content of the CBCW can be interpreted by multifractal parameters. The maximum surface subsidence value is 245 mm, with the fastest sinking speed occurring in the mining stage and a return of surface subsidence stability after halting of mining. A comprehensive analysis of the test results shows that, from an environmental viewpoint, the application of CW-CBMT is successful.

Low Maternal Dietary Folate Alters Retrotranspose by Methylation Regulation in Intrauterine Growth Retardation (IUGR) Fetuses in a Mouse Model.

BACKGROUND Maternal folate deficiency-mediated metabolic disruption is considered to be associated with the risk of intrauterine growth retardation (IUGR), but the exact mechanism remains unclear. The retrotransposon long interspersed nucleotide element-1 (LINE-1), which can induce birth defects via RNA intermediates, plays crucial roles during embryonic development. We investigated potential relationships between maternal folate and DNA methylation, and possible roles of LINE-1 in IUGR. MATERIAL AND METHODS The IUGR model was established by feeding female mice 1 of 3 diets - control diet (CD), folate-deficient diet for 2 weeks (FD2w), and folate-deficient diet for 4 weeks (FD4w) - prior to mating. Maternal serum folate, 5-methyltetrahydrofolate (5-MeTHF), S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH) concentrations and global DNA methylation were assessed by LC/MS/MS method. LINE-1 methylation levels in fetuses were examined by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. LINE-1 expression levels were validated by real-time PCR. RESULTS Maternal folate deficiency caused plasma folate and 5-MeTHF levels to decrease and SAH level to increase in the FD4w group. Compared with the CD group, methylation levels of genomic DNA and LINE-1 decreased significantly in placenta and fetal tissues from the FD4w group. Expression of LINE-1 open reading frame 1 (ORF1) protein was elevated in fetal liver tissues. Furthermore, a strong correlation was found between methylation and disrupted one-carbon metabolism, implying that dietary folate plays important roles during embryogenesis. CONCLUSIONS Maternal dietary folate deficiency impaired one-carbon metabolism, leading to global DNA and LINE-1 hypomethylation, and then increased retrotransposition in fetuses, which can lead to IUGR.