Research progress in water quality prediction based on deep learning technology: a review

Water, an invaluable and non-renewable resource, plays an indispensable role in human survival and societal development. Accurate forecasting of water quality involves early identification of future pollutant concentrations and water quality indices, enabling evidence-based decision-making and targeted environmental interventions. The emergence of advanced computational technologies, particularly deep learning, has garnered considerable interest among researchers for applications in water quality prediction because of its robust data analytics capabilities. This article comprehensively reviews the deployment of deep learning methodologies in water quality forecasting, encompassing single-model and mixed-model approaches. Additionally, we delineate optimization strategies, data fusion techniques, and other factors influencing the efficacy of deep learning-based water quality prediction models, because understanding and mastering these factors are crucial for accurate water quality prediction. Although challenges such as data scarcity, long-term prediction accuracy, and limited deployments of large-scale models persist, future research aims to address these limitations by refining prediction algorithms, leveraging high-dimensional datasets, evaluating model performance, and broadening large-scale model application. These efforts contribute to precise water resource management and environmental conservation.

An Efficient Probe-Based Quantitative PCR Assay Targeting Human-Specific DNA in ST6GALNAC3 for the Quantification of Human Cells in Preclinical Animal Models

Precise quantification of human cells in preclinical animal models by a sensitive and specific approach is warranted. The probe-based quantitative PCR (qPCR) assay as a sensitive and swift approach is suitable for the quantification of human cells by targeting human-specific DNA sequences. In this study, we developed an efficient qPCR assay targeting human-specific DNA in ST6GALNAC3 (termed ST6GAL-qPCR) for the quantification of human cells in preclinical animal models. ST6GAL-qPCR probe was synthesized with FAM and non-fluorescent quencher-minor groove binder conjugated to the 5' and 3' end of the probe, respectively. Genomic DNA from human, rhesus monkeys, cynomolgus monkeys, New Zealand White rabbits, SD rats, C57BL/6, and BALB/c mice were utilized for analyzing the specificity and sensitivity of the ST6GAL-qPCR assay. The ST6GAL-qPCR assay targeted human-specific DNA was cloned to pUCM-T vector and released by EcoR I/Hind III digestion for generating a calibration curve. Cell mixing experiment was performed to validate the ST6GAL-qPCR assay by analysis of 0.1%, 0.01%, and 0.001% of human leukocytes mixed with murine thymocytes. The ST6GAL-qPCR assay detected human DNA rather than DNA from the tested animal species. The amplification efficiency of the ST6GAL-qPCR assay was 93% and the linearity of calibration curve was R2 = 0.999. The ST6GAL-qPCR assay detected as low as 5 copies of human-specific DNA and is efficient to specially amplify as low as 30-pg human DNA in the presence of 1 μg of DNA from the tested species, respectively. The ST6GAL-qPCR assay was able to quantify as low as 0.01% of human leukocytes within murine thymocytes. This ST6GAL-qPCR assay can be used as an efficient approach for the quantification of human cells in preclinical animal models.

Efficient genome editing in grapevine using CRISPR/LbCas12a system

Clustered regularly interspaced short palindromic repeats (CRISPR) /Cas12a system, also known as CRISPR/Cpf1, has been successfully harnessed for genome engineering in many plants, but not in grapevine yet. Here we developed and demonstrated the efficacy of CRISPR/Cas12a from Lachnospiraceae bacterium ND2006 (LbCas12a) in inducing targeted mutagenesis by targeting the tonoplastic monosaccharide transporter1 (TMT1) and dihydroflavonol-4-reductase 1 (DFR1) genes in 41B cells. Knockout of DFR1 gene altered flavonoid accumulation in dfr1 mutant cells. Heat treatment (34℃) improved the editing efficiencies of CRISPR/LbCas12a system, and the editing efficiencies of TMT1-crRNA1 and TMT1-crRNA2 increased from 35.3% to 44.6% and 29.9% to 37.3% after heat treatment, respectively. Moreover, the sequences of crRNAs were found to be predominant factor affecting editing efficiencies irrespective of the positions within the crRNA array designed for multiplex genome editing. In addition, genome editing with truncated crRNAs (trucrRNAs) showed that trucrRNAs with 20 nt guide sequences were as effective as original crRNAs with 24 nt guides in generating targeted mutagenesis, whereas trucrRNAs with shorter regions of target complementarity ≤ 18 nt in length may not induce detectable mutations in 41B cells. All these results provide evidence for further applications of CRISPR/LbCas12a system in grapevine as a powerful tool for genome engineering.