Unveiling unique alternative splicing responses to low temperature in Zoysia japonica through ZjRTD1.0, a high-quality reference transcript dataset.

Inadequate reference databases in RNA-seq analysis can hinder data utilization and interpretation. In this study, we have successfully constructed a high-quality reference transcript dataset, ZjRTD1.0, for Zoysia japonica, a widely-used turfgrass with exceptional tolerance to various abiotic stress, including low temperatures and salinity. This dataset comprises 113,089 transcripts from 57,143 genes. BUSCO analysis demonstrates exceptional completeness (92.4%) in ZjRTD1.0, with reduced proportions of fragmented (3.3%) and missing (4.3%) orthologs compared to prior datasets. ZjRTD1.0 enables more precise analyses, including transcript quantification and alternative splicing assessments using public datasets, which identified a substantial number of differentially expressed transcripts (DETs) and differential alternative splicing (DAS) events, leading to several novel findings on Z. japonica's responses to abiotic stresses. First, spliceosome gene expression influenced alternative splicing significantly under abiotic stress, with a greater impact observed during low-temperature stress. Then, a significant positive correlation was found between the number of differentially expressed genes (DEGs) encoding protein kinases and the frequency of DAS events, suggesting the role of protein phosphorylation in regulating alternative splicing. Additionally, our results suggest possible involvement of serine/arginine-rich (SR) proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs) in generating inclusion/exclusion isoforms under low-temperature stress. Furthermore, our investigation revealed a significantly enhanced overlap between DEGs and differentially alternatively spliced genes (DASGs) in response to low-temperature stress, suggesting a unique co-regulatory mechanism governing transcription and splicing in the context of low-temperature response. In conclusion, we have proven that ZjRTD1.0 will serve as a reliable and useful resource for future transcriptomic analyses in Z. japonica.

Pan-cancer integrated analysis of ANKRD1 expression, prognostic value, and potential implications in cancer.

There is substantial evidence demonstrating the crucial role of inflammation in oncogenesis. ANKRD1 has been identified as an anti-inflammatory factor and is related to tumor drug resistance. However, there have been no studies investigating the prognostic value and molecular function of ANKRD1 in pan-cancer. In this study, we utilized the TCGA, GTEx, GSCALite, ENCORI, CTRP, DAVID, AmiGO 2, and KEGG databases as well as R language, to explore and visualize the role of ANKRD1 in tumors. We employed the ROC curve to explore its diagnostic significance, while the Kaplan-Meier survival curve and Cox regression analysis were used to investigate its prognostic value. Additionally, we performed Pearson correlation analysis to evaluate the association between ANKRD1 expression and DNA methylation, immune cell infiltration, immune checkpoints, TMB, MSI, MMR, and GSVA. Our findings indicate that ANKRD1 expression is dysregulated in pan-cancer. The ROC curve revealed that ANKRD1 expression is highly sensitive and specific in diagnosing CHOL, LUAD, LUSC, PAAD, SKCM, and UCS (AUC > 85.0%, P < 0.001). Higher ANKRD1 expression was related to higher overall survival (OS) in LGG, but with lower OS in COAD and STAD (P < 0.001). Moreover, Cox regression and nomogram analyzes suggested that ANKRD1 is an independent factor for COAD, GBM, HNSC, and LUSC. Dysregulation of ANKRD1 expression in pan-cancer involves DNA methylation and microRNA regulation. Using the CTRP database, we discovered that ANKRD1 may influence the half-maximal inhibitory concentration (IC50) of several anti-tumor drugs. ANKRD1 expression showed significant correlations with immune cell infiltration (including cancer-associated fibroblast and M2 macrophages), immune checkpoints, TMB, MSI, and MMR. Furthermore, ANKRD1 is involved in various inflammatory and immune pathways in COAD, GBM, and LUSC, as well as cardiac functions in HNSC. In vitro experiments demonstrated that ANKRD1 promotes migration, and invasion activity, while inhibiting apoptosis in colorectal cancer cell lines (Caco2, SW480). In summary, ANKRD1 represents a potential prognostic biomarker and therapeutic target in human cancers, particularly in COAD.

Locally enhanced mixed-order model for chloramine decay in drinking water disinfection.

Chloramine is the second most popular disinfectant and is widely used in the disinfection of drinking water. For chloramine disinfection, some standards require the total chlorine concentration to be maintained in an appropriate range in the water distribution system. Therefore, exploring the mechanism of chloramine decay and deriving an accurate chloramine decay model helps to optimize the disinfection process and ensure water quality safety. This paper proposed a locally enhanced mixed-order(LEM) model consisting of the first order model and the mixed order model to describe chloramine auto-decomposition and decays caused by other reactions respectively. Via proving the parameter a and k2 related to temperatures instead of initial chloramine concentration, the model had been further simplified. Nine chloramine decay experiments with different initial chloramine concentrations and temperatures were designed and carried out to evaluate the new model performance for chloramine decay simulation. The research results showed that the simplified LEM model could simulate the whole process of chloramine decay well. Its accuracy evaluation indexes (R2 and SSE) were better than that obtained from the first order model and the mixed order model. This paper proposed a simple and accurate method to simulate the process of chloramine decay and had a guiding significance for water quality safety assurance.

Dendronized Polymer-Derived Nanomedicines for Mitochondrial Dynamics Regulation and Immune Modulation.

The effects of dendron side chains in polymeric conjugates on tumor penetration and antigen presentation are systematically examined. Three polymer-gemcitabine (Gem) conjugates (pG0-Gem, pG1-Gem, pG2-Gem) are designed and prepared. The pG2-Gem conjugate uniquely binds to the mitochondria of tumor cells, thus regulating mitochondrial dynamics. The interaction between the pG2-Gem conjugate and the mitochondria promotes great penetration and accumulation of the conjugate at the tumor site, resulting in pronounced antitumor effects in an animal model. Such encouraging therapeutic effects can be ascribed to immune modulation since MHC-1 antigen presentation is significantly enhanced due to mitochondrial fusion and mitochondrial metabolism alteration after pG2-Gem treatment. Crucially, the drug-free dendronized polymer, pG2, is identified to regulate mitochondrial dynamics, and the regulation is independent of the conjugated Gem. Furthermore, the combination of pG2-Gem with anti-PD-1 antibody results in a remarkable tumor clearance rate of 87.5% and a prolonged survival rate of over 150 days, demonstrating the potential of dendronized polymers as an innovative nanoplatform for metabolic modulation and synergistic tumor immunotherapy.

Bioorthogonal In Situ Polymerization of Dendritic Agents for Hijacking Lysosomes and Enhancing Antigen Presentation in Cancer Cells.

A low-generation lysine dendrimer, SPr-G2, responds to intracellular glutathione to initiate bioorthogonal in situ polymerization, resulting in the formation of large assemblies in mouse breast cancer cells. The intracellular large assemblies of SPr-G2 can interact with lysosomes to induce lysosome expansion and enhance lysosomal membrane permeabilization, leading to major histocompatibility complex class I upregulation on tumor cell surfaces and ultimately tumor cell death. Moreover, the use of the SPr-G2 dendrimer to conjugate the chemotherapeutic drug, camptothecin (CPT), can boost the therapeutic potency of CPT. Excellent antitumor effects in vitro and in vivo are obtained from the combinational treatment of the SPr-G2 dendrimer and CPT. This combinational effect also enhances antitumor immunity through promoting activation of cytotoxic T cells in tumor tissues and maturation of dendritic cells. This study can shed new light on the development of peptide dendritic agents for cancer therapy.

Congenital disorder of glycosylation type Ia in a Chinese family: Function analysis of a novel PMM2 complex heterozygosis mutation.

Congenital disorder of glycosylation type Ia (CDG-Ia) is an autosomal recessive genetic disease caused by a mutation in the phosphomannomutase 2 (PMM2) gene. We have identified a 13-month-old boy who has been diagnosed with CDG-Ia. He displays several characteristic symptoms, including cerebellar hypoplasia, severe developmental retardation, hypothyroidism, impaired liver function, and abnormal serum ferritin levels. Through whole-exome sequencing, we discovered novel complex heterozygous mutations in the PMM2 gene, specifically the c.663C > G (p.F221L) mutation and loss of exon 2. Further analysis revealed that the enzymatic activity of the mutant PMM2 protein was significantly reduced by 44.97% (p < 0.05) compared to the wild-type protein.

Efficient nitrogen removal by multi-stage A/O mud membrane composite process with segmented influent: Performance and microbial community structure.

In this paper, a multi-stage A/O mud membrane composite process with segmented influent was constructed for the first time and compared with the traditional activated sludge process and the multi-stage A/O pure membrane process with segmented influent. The nitrogen removal efficiency of the process under different influencing factors was studied. Under the optimum conditions, the highest removal rate of ammonia nitrogen can reach 99%, and the average removal rate of total nitrogen was 80%. The removal rate of COD in effluent reached 93%. The relative abundance of Proteobacteria was the highest in the multi-stage A/O mud membrane composite reactor with segmented influent. The community diversity and richness of activated sludge and biofilm in aerobic pool were the highest. Dechloromonas, Flavobacterium and Rhodobacter were dominant bacteria, and they were aerobic denitrifying bacteria that significantly contributed to the removal rate of ammonia nitrogen.

Multi-omic profiling reveals associations between the gut microbiome, host genome and transcriptome in patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the leading cancer worldwide. Microbial agents have been considered to contribute to the pathogenesis of different disease. But the underlying relevance between CRC and microbiota remain unclear. METHODS: We dissected the fecal microbiome structure and genomic and transcriptomic profiles of matched tumor and normal mucosa tissues from 41 CRC patients. Of which, the relationship between CRC-associated bacterial taxa and their significantly correlated somatic mutated gene was investigated by exome sequencing technology. Differentially expressed functional genes in CRC were clustered according to their correlation with differentially abundant species, following by annotation with DAVID. The composition of immune and stromal cell types was identified by XCELL. RESULTS: We identified a set of 22 microbial gut species associated with CRC and estimate the relative abundance of KEGG ontology categories. Next, the interactions between CRC-related gut microbes and clinical phenotypes were evaluated. 4 significantly mutated gene: TP53, APC, KRAS, SMAD4 were pointed out and the associations with cancer related microbes were identified. Among them, Fusobacterium nucleatum positively corelated with different host metabolic pathways. Finally, we revealed that Fusobacterium nucleatum modified the tumor immune environment by TNFSF9 gene expression. CONCLUSION: Collectively, our multi-omics data could help identify novel biomarkers to inform clinical decision-making in the detection and diagnosis of CRC.

Euphzycopins A - D, macrocyclic diterpenoids with potential anti-inflammatory activity from Euphorbia Helioscopia.

Four new diterpenoids (1-4) and four known diterpenoids (5-8) were purified from the whole plant of Euphorbia helioscopia L. Compounds 1 and 2 were jathophanes diterpenoids with a 5/12 polycyclic systems, compound 3 was rhamofolane diterpenoid with a 5/10 bicyclic skeleton and compound 4 was a rare class of euphorbia diterpenes featuring an unusual 5/10 fused ring system. Anti-inflammatory activity tests were conducted on the separated compounds, indicating that compound 4 had significant inhibitory effect on NLRP3 inflammasome with an IC50 value of 7.75 µM. Further, the inhibitory effect of 4 was determined using immunofluorescence assays.

Unraveling Ros Conversion Through Enhanced Enzyme-Like Activity with Copper-Doped Cerium Oxide for Tumor Nanocatalytic Therapy.

Nanozyme catalytic therapy for cancer treatments has become one of the heated topics, and the therapeutic efficacy is highly correlated with their catalytic efficiency. In this work, three copper-doped CeO2 supports with various structures as well as crystal facets are developed to realize dual enzyme-mimic catalytic activities, that is superoxide dismutase (SOD) to reduce superoxide radicals to H2 O2 and peroxidase (POD) to transform H2 O2 to ∙OH. The wire-shaped CeO2 /Cu-W has the richest surface oxygen vacancies, and a low level of oxygen vacancy (Vo) formation energy, which allows for the elimination of intracellular reactive oxygen spieces (ROS) and continuous transformation to ∙OH with cascade reaction. Moreover, the wire-shaped CeO2 /Cu-W displays the highest toxic ∙OH production capacity in an acidic intracellular environment, inducing breast cancer cell death and pro-apoptotic autophagy. Therefore, wire-shaped CeO2 /Cu nanoparticles as an artificial enzyme system can have great potential in the intervention of intracellular ROS in cancer cells, achieving efficacious nanocatalytic therapy.

Detection of citrus diseases in complex backgrounds based on image-text multimodal fusion and knowledge assistance.

Diseases pose a significant threat to the citrus industry, and the accurate detection of these diseases represent key factors for their early diagnosis and precise control. Existing diagnostic methods primarily rely on image models trained on vast datasets and limited their applicability due to singular backgrounds. To devise a more accurate, robust, and versatile model for citrus disease classification, this study focused on data diversity, knowledge assistance, and modal fusion. Leaves from healthy plants and plants infected with 10 prevalent diseases (citrus greening, citrus canker, anthracnose, scab, greasy spot, melanose, sooty mold, nitrogen deficiency, magnesium deficiency, and iron deficiency) were used as materials. Initially, three datasets with white, natural, and mixed backgrounds were constructed to analyze their effects on the training accuracy, test generalization ability, and classification balance. This diversification of data significantly improved the model's adaptability to natural settings. Subsequently, by leveraging agricultural domain knowledge, a structured citrus disease features glossary was developed to enhance the efficiency of data preparation and the credibility of identification results. To address the underutilization of multimodal data in existing models, this study explored semantic embedding methods for disease images and structured descriptive texts. Convolutional networks with different depths (VGG16, ResNet50, MobileNetV2, and ShuffleNetV2) were used to extract the visual features of leaves. Concurrently, TextCNN and fastText were used to extract textual features and semantic relationships. By integrating the complementary nature of the image and text information, a joint learning model for citrus disease features was achieved. ShuffleNetV2 + TextCNN, the optimal multimodal model, achieved a classification accuracy of 98.33% on the mixed dataset, which represented improvements of 9.78% and 21.11% over the single-image and single-text models, respectively. This model also exhibited faster convergence, superior classification balance, and enhanced generalization capability, compared with the other methods. The image-text multimodal feature fusion network proposed in this study, which integrates text and image features with domain knowledge, can identify and classify citrus diseases in scenarios with limited samples and multiple background noise. The proposed model provides a more reliable decision-making basis for the precise application of biological and chemical control strategies for citrus production.

Comparison and Evaluation of Two Combination Modes of Angiotensin for Establishing Murine Aortic Dissection Models.

Aortic dissection (AD) is a potentially fatal cardiovascular emergency caused by separation of different layers of aortic wall. However, because of limited time window available for clinical research, there is an urgent need for an ideal animal research model. In recent years, the incidence of AD complicated by atherosclerosis has increased with improvements of living standards and changes of eating habits. Accordingly, considering multiple risk factors, we successfully and efficiently established a novel AD model through a high-fat diet combined with chronic angiotensin II (AngII) infusion. Compared with traditional chemical induction model using AngII and ß-aminopropionitrile, our model is more clinically relevant for atherosclerosis-related AD. Moreover, infiltration of neutrophils and apoptosis of vascular smooth muscle cells in AD tissues were more significant. In addition to enriching the existing models, the novel model may be a long-term useful tool for more in-depth investigation of AD mechanisms and preclinical therapeutic developments.

Mutual interference between 3,6-dichlorinated carbazole and p,p'-dichlorodiphenyltrichloroethane in gas chromatography mass spectrometry analysis.

The widespread contamination of the environment by polyhalogenated carbazoles (PHCZs) has been increasingly observed during the past decade. Among numerous PHCZ congeners, 3,6-dichlorocarbazole (36-CCZ) is often among the most frequently detected at higher concentrations. Although the environmental level of the legacy pesticide p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT) has been declining, it continues to be ubiquitously detected. These two compounds were found to interfere with each other during analyses using gas chromatography (GC) coupled with single- or triple-quadrupole low-resolution mass spectrometry (MS or MS/MS). The base peak in the mass spectra was that of m/z 235 for both compounds. In MS/MS with multiple reaction monitoring (MRM), the same transitions (235 → 200 and 235 → 165) were often used. Under the same GC operating conditions, the SH-I-5MS capillary column used in this work did not resolve the two compounds at baseline. Pre-treatment using cleanup column chromatography can fractionate the sample extract, with the two compounds separated in different fractions before instrumental analyses. Reversed-phase HPLC columns also work for resolving 36-CCZ and p,p'-DDT. Possible overlaps in GC retention and similarity in MS spectra might have caused data inaccuracy for 36-CCZ as well as p,p'-DDT in some studies published to date, and steps to avoid the interference should be taken into quality control protocols in future research and environmental monitoring.

[Characterization of the cellular immune response induced by Mycobacterium tuberculosis Rv2626c].

Nearly a quarter of the world's population is infected with Mycobacterium tuberculosis and remains long-term asymptomatic infection. Rv2626c is a latent infection-related protein regulated by DosR of M. tuberculosis. In this study, the Rv2626c protein was prokaryotically expressed and purified, and its immunobiological characteristics were analyzed using RAW264.7 cells and mice as infection models. SDS-PAGE and Western blotting analysis showed that the Rv2626c-His fusion protein was mainly expressed in soluble form and specifically reacted with the rabbit anti-H37RV polyclonal serum. In addition, we found that the Rv2626c protein bound to the surface of RAW264.7 macrophages and up-regulated the production of NO. Moreover, the Rv2626c protein significantly induced the production of pro-inflammatory cytokines IFN-γ, TNF-α, IL-6 and MCP-1, and induced strong Th1-tendency immune response. These results may help to reveal the pathogenic mechanism of M. tuberculosis and facilitate the development of new tuberculosis vaccine.

Biofilm on the pipeline wall is an important transmission route of resistome in drinking water distribution system.

Due to the intensive use of antibiotics, the drinking water distribution system (DWDS) has become one of the hotspots of antibiotic resistance. However, little is known about the role of biofilm in the aspect of spreading resistance in DWDS. In present study, four lab-scale biological annular reactors (BAR) were constructed to investigate the transmission of ARGs exposed to a certain amount of antibiotic (sulfamethoxazole) synergistic disinfectants. It was emphasized that pipe wall biofilm was an important way for ARGs to propagate in the pipeline, and the results were quantified by constructing an operational taxonomic unit (OTU) network map. The network analysis results showed the biofilm contribution to waterborne bacteria was finally estimated to be 51.45% and 34.27% in polyethylen (PE) pipe and ductile iron (DI) pipe, respectively. The proportion of vertical gene transfer (VGT) in biofilm was higher than that in water, and the occurrence of this situation had little relationship with the selection of pipe type. Overall, this study revealed how biofilm promoted the transmission of resistome in bulk water, which can provide insights into assessing biofilm-associated risks and optimizing pipe material selection for biofilm control in DWDS.

A systemic evaluation of aerobic granular sludge among granulation, operation, storage, and reactivation processes in an SBR.

As a biological promising wastewater treatment technology, aerobic granular sludge (AGS) technology had been widely studied in sequencing batch reactors (SBRs) for the decades. Presently, the whole processes of its granulation, long-term operation, storage, and reactivation have not been thoroughly evaluated, and also the relationships among microbial diversity, granular size, and characteristics were still not that clear. Hence, they were systematically evaluated in an AGS-SBR in this work. The results demonstrated that Proteobacteria and Bacteroidetes were the dominant phyla, Flavobacterium, Acinetobacter, Azoarcus, and Chryseobacterium were the core genera with discrepant abundances in diverse stages or granular size. Microbial immigration was significant in various stages due to microbial diversity had a line relationship with COD/MLVSS ratio (R2 = 0.367). However, microbial diversity had no line relationship with granular size (R2 = 0.001), indicating the microbial diversity in different-sized AGS was similar, although granular size had a line relationship with settleability (R2 = 0.978). Overall, compared to sludge traits (e.g., sludge size, settleability), COD/MLVSS played a key role on microbial evolution. This study revealed the relationships between granule characteristics and microbial community, and contributed to the future AGS-related studies.

Cost-Effectiveness Analysis of Combined Chemotherapy Regimen Containing Bedaquiline in the Treatment of Multidrug-Resistant Tuberculosis in China.

Objective: This study aims to estimate the cost-effectiveness of the combined chemotherapy regimen containing Bedaquiline (BR) and the conventional treatment regimen (CR, not containing Bedaquiline) for the treatment of adults with multidrug-resistant tuberculosis (MDR-TB) in China. Methods: A combination of a decision tree and a Markov model was developed to estimate the cost and effects of MDR patients in BR and CR within ten years. The model parameter data were synthesized from the literature, the national TB surveillance information system, and consultation with experts. The incremental cost-effectiveness ratio (ICER) of BR vs. CR was determined. Results: BR ( vs. CR) had a higher sputum culture conversion rate and cure rate and prevented many premature deaths (decreased by 12.8%), thereby obtaining more quality-adjusted life years (QALYs) (increased by 2.31 years). The per capita cost in BR was as high as 138,000 yuan, roughly double that of CR. The ICER for BR was 33,700 yuan/QALY, which was lower than China's 1× per capita Gross Domestic Product (GDP) in 2020 (72,400 yuan). Conclusion: BR is shown to be cost effective. When the unit price of Bedaquiline reaches or falls below 57.21 yuan per unit, BR is expected to be the dominant strategy in China over CR.

Change and challenge: An online course in Medical Biochemistry and Molecular Biology.

The development of information technology and portable devices has sparked a revolution in the field of education, facilitating access to diverse educational resources and lifelong learning. In particular, the COVID-19 pandemic has accelerated the transition from face-to-face to distance teaching, which requires online education to be provided worldwide. Biochemistry and Molecular Biology are key basic medical courses in laboratory-based science that cover complicated theories and applications. The balance between traditional and online courses, and the effectiveness of online courses, are fundamental to the teaching quality of Biochemistry and Molecular Biology. In this study, we explored the concepts, designs, and practices of a new blended online course and identified potential challenges. We hope that our experiences will provide new ideas for online teaching and promote teaching reform and the development of Medical Biochemistry and Molecular Biology education.

Analysis of polyhalogenated carbazoles and two related compounds in earthworms using a modified QuEChERS method with GC/MS and GC/MS/MS.

A precise analytical method based on QuEChERS has been proposed for the concurrent determination of 11 polyhalogenated carbazoles (PHCZs), benzocarbazole (BZCZ), and 9H-carbazoles (CZ). The quantification was confirmed by gas chromatography using triple quadrupole tandem mass spectrometry (Shimadzu GC-MS/MS-TQ8040) and gas chromatography coupled mass spectrometry (Agilent 7890A-5973 GC-MS). The developed method was validated by testing the following parameters: linearity, instrument limit of detection (LOD), instrument limit of quantification (LOQ), method limit of detection (MLD), method limit of quantification (MLQ), matrix effect (ME), accuracy, and precision. All compounds showed good linearity in the range of 0.005-0.2 µg/mL with correlation coefficients higher than 0.992. The method demonstrated satisfactory recoveries (ranging from 71.21 to 105.04%) for most of the compounds with relative standard deviation precision (RSD) < 10.46%, except 3-BCZ (Recovery = 67.53%, RSD = 2.83%). The values of LOD and LOQ varied from 0.05 to 0.24 ng and 0.14 to 0.92 ng, respectively, while those of MLD and MLQ ranged from 0.02 to 0.12 ng/g wet weight (ww) and 0.07 to 0.45 ng/g ww, respectively. The developed method represents a reliable tool for the routine analysis of PHCZ congeners in invertebrate animals.

The mixed-order chlorine decay model with an analytical solution and corresponding trihalomethane generation model in drinking water.

Ensuring effective drinking water disinfection, remaining a certain amount of residual chlorine, and controlling disinfection by-product formation were very important for guarantying water quality safety and protecting public health; thus, the chlorine decay model and corresponding disinfection by-product formation model were necessary. This paper proposed a mixed-order chlorine bulk decay model (two parameters) based on Taylor's formula and derived its analytical solution. The accuracy of the mixed-order model was evaluated by comparing it with the nth-order model. To optimize the model and reduce the number of parameters required to be calibrated, the relationship of parameters with temperature, initial chlorine concentration, TOC and inorganic substance (ammonia nitrogen and iodide ion) was explored. The result proved that one of the parameters could be regarded as temperature dependent only. Meanwhile, the temperature equation of the model parameters was established by the Arrhenius formula. Subsequently, this paper selected trihalomethane as the target and study the linear relationship between chlorine consumption and trihalomethane formation. The results indicated that the liner slope had little correlation with initial chlorine concentration and temperature. On this basis, the corresponding trihalomethane model was built and its performance was proven to be good. The modeling developed in this work could be applied to drinking water distribution systems for residual chlorine and trihalomethane prediction, and provided a reference for the decision involving water quality.