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Water quality modeling in sewer networks: Review and future research directions

Jia Y, Zheng F, Maier HR, Ostfeld A, Creaco E, Savic D, et al.

Water Res, 2021 Sep 01;202:117419.
PMID: 34274902 DOI: 10.1016/j.watres.2021.117419

Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs. Given the proliferation of different water quality models and the promise they have shown, it is timely to assess the state-of-the-art in this field, to identify potential challenges and suggest future research directions. In this review, model types, modeled quality parameters, modeling purpose, data availability, type of case studies and model performance evaluation are critically analyzed and discussed based on a review of 110 papers published between 2010 and 2019. The review identified that applications of empirical and kinetic models dominate those of data-driven models for addressing water quality issues. The majority of models are developed for prediction and process understanding using experimental or field sampled data. While many models have been applied to real problems, the corresponding prediction accuracies are overall moderate or, in some cases, low, especially when dealing with larger SNs. The review also identified the most common issues associated with water quality modeling of SNs and based on these proposed several future research directions. These include the identification of appropriate data resolutions for the development of different SN models, the need and opportunity to develop hybrid SN models and the improvement of SN model transferability.
Foul sewer model development using geotagged information and smart water meter data

Jia Y, Zheng F, Zhang Q, Duan HF, Savic D, Kapelan Z

Water Res, 2021 Oct 01;204:117594.
PMID: 34474249 DOI: 10.1016/j.watres.2021.117594

Hydraulic modeling of a foul sewer system (FSS) enables a better understanding of the behavior of the system and its effective management. However, there is generally a lack of sufficient field measurement data for FSS model development due to the low number of in-situ sensors for data collection. To this end, this study proposes a new method to develop FSS models based on geotagged information and water consumption data from smart water meters that are readily available. Within the proposed method, each sewer manhole is firstly associated with a particular population whose size is estimated from geotagged data. Subsequently, a two-stage optimization framework is developed to identify daily time-series inflows for each manhole based on physical connections between manholes and population as well as sewer sensor observations. Finally, a new uncertainty analysis method is developed by mapping the probability distributions of water consumption captured by smart meters to the stochastic variations of wastewater discharges. Two real-world FSSs are used to demonstrate the effectiveness of the proposed method. Results show that the proposed method can significantly outperform the traditional FSS model development approach in accurately simulating the values and uncertainty ranges of FSS hydraulic variables (manhole water depths and sewer flows). The proposed method is promising due to the easy availability of geotagged information as well as water consumption data from smart water meters in near future.
MiR-26b-3p Promotes Intestinal Motility Disorder by Targeting FZD10 to Inhibit GSK3β/β-Catenin Signaling and Induce Enteric Glial Cell Apoptosis

Zhan Y, Wen Y, Zheng F, Du LJ, Chen TY, Shen XL, et al.

Mol Neurobiol, 2024 Mar;61(3):1543-1561.
PMID: 37728849 DOI: 10.1007/s12035-023-03600-8

Enteric glial cells (EGCs) are the major component of the enteric nervous system and affect the pathophysiological process of intestinal motility dysfunction. MicroRNAs (miRNAs) play an important role in regulating gastrointestinal homeostasis. However, the mechanism of miRNA-mediated regulation of EGCs in intestinal dysmotility remains unclear. In this study, we investigated the effect of EGC apoptosis on intestinal dysmotility, and the effect of miR-26b-3p on EGC proliferation and apoptosis in vivo and in vitro. A loperamide hydrochloride (Lop)-induced constipated mouse model and an in vitro culture system of rat EGCs were established. The transcriptome was used to predict the differentially expressed gene miR-26b-3p and the target gene Frizzled 10 (FZD10), and their targeting binding relationship was verified by luciferase. EGCs were transfected with miR-26b-3p mimic or antagomir, and the FZD10 expression was down-regulated by siRNA. Immunofluorescence and flow cytometry were used to detect EGC apoptosis. MiR-26b-3p and FZD10 expressions were examined using quantitative real-time PCR (qRT-PCR). The CCK-8 assay was used to detect EGC proliferation. The protein levels were detected by Western blotting and enzyme-linked immunosorbent assay (ELISA). The results showed that miR-26b-3p was up-regulated in the Lop group, whereas FZD10 was down-regulated, and EGC apoptosis was increased in the colon of intestinal dysmotility mice. FZD10 down-regulation and miR-26b-3p mimic significantly increased glycogen synthase kinase-3β phosphorylation (p-GSK3β) levels, decreased β-catenin expression, and promoted EGC apoptosis. MiR-26b-3p antagomir alleviated intestinal dysmotility, promoted EGC increased activity of EGCs, and reduced EGC apoptosis in vivo. In conclusion, this study indicated that miR-26b-3p promotes intestinal motility disorders by targeting FZD10 to block GSK3β/β-catenin signaling and induces apoptosis in EGCs. Our results provide a new research target for the treatment and intervention of intestinal dysmotility.
A new medical device applied in a case of acute fecal impaction with overflow diarrhea: a case report

Huang Q, Zheng F, Wang H, Yang Y, Ma C, Zhu L

J Med Case Rep, 2024 Mar 06;18(1):89.
PMID: 38444013 DOI: 10.1186/s13256-024-04407-4

BACKGROUND: Fecal impaction is a digestive system disease, that is most common in the elderly population and becomes more prevalent with increasing age. Manual removal can successfully remove the impaction in 80% of fecal impaction cases. In severe cases, endoscopy and surgery may be necessary.
CASE PRESENTATION: A 78-year-old Han Chinese man living in a nursing home was diagnosed with fecal impaction; his initial symptom was overflow diarrhea, which is a rare occurrence with regard to fecal impaction. Nevertheless, we were able to effectively treat this situation by employing a new medical device that presents a novel method for addressing fecal impaction.
CONCLUSION: Early identification of fecal impaction with atypical symptoms is crucial to provide proper emergency management. A safe and noninvasive treatment method, especially for elderly patients with fecal impaction, should be chosen.
Total Flavonoids of Aurantii Fructus Immaturus Regulate miR-5100 to Improve Constipation by Targeting Fzd2 to Alleviate Calcium Balance and Autophagy in Interstitial Cells of Cajal

Wen Y, Zhan Y, Chen T, Li J, Long Q, Zheng F, et al.

Mol Neurobiol, 2024 Aug;61(8):5882-5900.
PMID: 38244148 DOI: 10.1007/s12035-024-03958-3

Aurantii Fructus Immaturus total flavonoids (AFIF) is the main effective fraction extracted from AFI, which has a good effect on promoting gastrointestinal motility. This study aimed to investigate AFIF which regulates miR-5100 to improve constipation symptoms in mice by targeting Frizzled-2 (Fzd2) to alleviate interstitial cells of Cajal (ICCs) calcium ion balance and autophagy apoptosis. The constipated mouse model was induced by an antibiotic suspension, and then treated with AFIF. RNA-seq sequencing, luciferase assay, immunofluorescence staining, transmission electron microscopy, ELISA, flow cytometry, quantitative polymerase chain reaction (PCR), and Western blot were applied in this study. The results showed that AFIF improved constipation symptoms in antibiotic-induced constipated mice, and decreased the autophagy-related protein Beclin1 levels and the LC3-II/I ratio in ICCs. miR-5100 and its target gene Fzd2 were screened as key miRNAs and regulator associated with autophagy. Downregulation of miR-5100 caused increased expression of Fzd2, decreased proliferation activity of ICCs, increased apoptotic cells, and enhanced calcium ion release and autophagy signals. After AFIF treatment, miR-5100 expression was upregulated and Fzd2 was downregulated, while autophagy-related protein levels and calcium ion concentration decreased. Furthermore, AFIF increased the levels of SP, 5-HT, and VIP, and increased the expression of PGP9.5, Sy, and Cx43, which alleviated constipation by improving the integrity of the enteric nervous system network. In conclusion, AFIF could attenuate constipation symptoms by upregulating the expression of miR-5100 and targeting inhibition of Fzd2, alleviating calcium overload and autophagic death of ICCs, regulating the content of neurotransmitters, and enhancing the integrity of the enteric nervous system network.
Fulltext The Role of 1-Methylcyclopropene in the regulation of ethylene biosynthesis and ethylene receptor gene expression in Mangifera indica L. (Mango Fruit)

Li L, Shuai L, Sun J, Li C, Yi P, Zhou Z, et al.

Food Sci Nutr, 2020 Feb;8(2):1284-1294.
PMID: 32148834 DOI: 10.1002/fsn3.1417

Mango (Mangifera indica L.) is respiratory climacteric fruit that ripens and decomposes quickly following their harvest. 1-methylcyclopropene (1-MCP) is known to affect the ripening of fruit, delaying the decay of mango stored under ambient conditions. The objective of this study was to clarify the role of 1-MCP in the regulation of ethylene biosynthesis and ethylene receptor gene expression in mango. 1-MCP significantly inhibited the 1-aminocyclopropane-1-carboxylic acid (ACC) content. The activity of ACC oxidase (ACO) increased on days 6, 8, and 10 of storage, whereas delayed ACC synthase (ACS) activity increased after day 4. The two homologous ethylene receptor genes, ETR1 and ERS1 (i.e., MiETR1 and MiERS1), were obtained and deposited in GenBank® (National Center for Biotechnology Information-National Institutes of Health [NCBI-NIH]) (KY002681 and KY002682). The MiETR1 coding sequence was 2,220 bp and encoded 739 amino acids (aa). The MiERS1 coding sequence was 1,890 bp and encoded 629 aa, similar to ERS1 in other fruit. The tertiary structures of MiETR1 and MiERS1 were also predicted. MiERS1 lacks a receiver domain and shares a low homology with MiETR1 (44%). The expression of MiETR1 and MiERS1 mRNA was upregulated as the storage duration extended and reached the peak expression on day 6. Treatment with 1-MCP significantly reduced the expression of MiETR1 on days 4, 6, and 10 and inhibited the expression of MiETR1 on days 2, 4, 6, and 10. These results indicated that MiETR1 and MiERS1 had important functions in ethylene signal transduction. Treatment with 1-MCP might effectively prevent the biosynthesis of ethylene, as well as ethylene-induced ripening and senescence. This study presents an innovative method for prolonging the storage life of mango after their harvest through the regulation of MiETR1 and MiERS1 expression.
Fulltext Analysis of hyperforin (St. John's wort) action at TRPC6 channel leads to the development of a new class of antidepressant drugs

El Hamdaoui Y, Zheng F, Fritz N, Ye L, Tran MA, Schwickert K, et al.

Mol Psychiatry, 2022 Dec;27(12):5070-5085.
PMID: 36224261 DOI: 10.1038/s41380-022-01804-3

St. John's wort is an herb, long used in folk medicine for the treatment of mild depression. Its antidepressant constituent, hyperforin, has properties such as chemical instability and induction of drug-drug interactions that preclude its use for individual pharmacotherapies. Here we identify the transient receptor potential canonical 6 channel (TRPC6) as a druggable target to control anxious and depressive behavior and as a requirement for hyperforin antidepressant action. We demonstrate that TRPC6 deficiency in mice not only results in anxious and depressive behavior, but also reduces excitability of hippocampal CA1 pyramidal neurons and dentate gyrus granule cells. Using electrophysiology and targeted mutagenesis, we show that hyperforin activates the channel via a specific binding motif at TRPC6. We performed an analysis of hyperforin action to develop a new antidepressant drug that uses the same TRPC6 target mechanism for its antidepressant action. We synthesized the hyperforin analog Hyp13, which shows similar binding to TRPC6 and recapitulates TRPC6-dependent anxiolytic and antidepressant effects in mice. Hyp13 does not activate pregnan-X-receptor (PXR) and thereby loses the potential to induce drug-drug interactions. This may provide a new approach to develop better treatments for depression, since depression remains one of the most treatment-resistant mental disorders, warranting the development of effective drugs based on naturally occurring compounds.
Fulltext Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective

Gunasekeran DV, Zheng F, Lim GYS, Chong CCY, Zhang S, Ng WY, et al.

Front Med (Lausanne), 2022;9:875242.
PMID: 36314006 DOI: 10.3389/fmed.2022.875242

BACKGROUND: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract.
METHODS: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning.
RESULTS: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83.
CONCLUSION: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.