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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.Insights into microbiota adaptation to increased ammonia stress, and identification of indicator microorganisms can help to optimize the operation of anaerobic digesters. To identify microbial indicators and investigate their metabolic contribution to acetoclastic methanogenesis (AM), syntrophic acetate oxidation (SAO) or hydrogenotrophic methanogenesis (HM), 40 anaerobic batch reactors fed with acetate of 110 mmol/L were set up at NH4+-N concentrations of 0.14 g/L, 5.00 g/L or 7.00 g/L, inoculated with thermophilic or mesophilic microbiota with or without pre-exposure to ammonia stress. Four stable carbon isotope probing approaches were applied in parallel, with [1,2-13C]-CH3COOH, [2-13C]-CH3COOH, [13C]NaHCO3 or non-labeled CH3COOH used individually. The last three approaches were used to quantify the methanogenic pathways by tracking labeled 13C or natural 13C signatures in the resulting CH4 and CO2, and consistently detected the dynamic transition of dominant pathways from AM to SAO-HM under ammonia stress. Results of quantitative PCR and fluorescence in-situ hybridization illustrated the procedure, acetotrophic methanogens being outcompeted by acetate-oxidizing syntrophs. The first and last isotope-labeling approaches were designed to probe the active acetate-mineralizing microbes with DNA-SIP. Known acetate-oxidizing bacteria like Syntrophaceticus and Tepidanaerobacter, as well as novel members of Pseudomonas, Bacillus and Symbiobacteraceae were detected, with Methanoculleus as the predominant H2/CO2-utilizing partner. Using NanoSIMS, some bacterial cells were observed to be fixing CO2 from [13C]NaHCO3. In this study, Methanosaeta was only active with ammonia 500 mg-N/L. Under ammonia stress, diverse known and novel microbial taxa were involved in acetate mineralization, comparable with those identified in previous studies.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused many deaths and complications worldwide. However, limited data are available about COVID-19 during pregnancy. This study aimed to assess the epidemiological and clinical features of COVID-19, and the adverse maternal and fetal outcomes.

This retrospective analytical cohort study was conducted on all pregnant women with confirmed COVID-19 at Nekouei-Hedayati-Forghani Hospital in Qom, Iran from 15 March 2020 to 15 November 2020. For the same period, 165 pregnant women who did not have COVID-19 were selected at random and included in this study. All epidemiological and clinical features were collected from the medical records of the participants. A logistic regression model was used to determine associations between COVID-19 in pregnancy and maternal and fetal outcomes.

The most common symptoms reported by pregnant women with COVID-19 were shortness of breath (60.9%), dry cough (59%) and fever (42.9%). After adjustment for potential confounding factors, COVID-19 in pregnancy was associated with a significantly higher risk of admission to the intensive care unit (ICU) [odds ratio (OR) 6.16, 95% confidence interval (CI) 1.23-31], caesarean section (OR 0.45, 95 CI 0.25-1.03), preterm birth (OR 3.01, 95% CI 1.4-6.54), fetal distress (OR 5.7, 95% CI 2.13-15.59) and admission to the neonatal intensive care unit (NICU) (OR 3.04, 95% CI 1.21-7.70).

COVID-19 is associated with adverse maternal and fetal outcomes, including ICU admission, caesarean section, fetal distress, preterm birth and NICU admission.

COVID-19 is associated with adverse maternal and fetal outcomes, including ICU admission, caesarean section, fetal distress, preterm birth and NICU admission.In Asia, prostate cancer is becoming a growing concern, impacting both socially and economically, compared with what is seen in western countries. Hence, it is essential to know the mechanisms associated with the development and tumorigenesis of PCa for primary diagnosis, risk management, and development of therapy strategies against PCa. Kinesin family member 15 (KIF15), a kinesin family member, is a plus-end-directed kinesin that functions to form bipolar spindles. There is emerging evidence indicating that KIF15 plays a significant role in several malignancies, such as pancreatic cancer, hepatocellular carcinoma, lung adenocarcinoma, and breast cancer. Still, the function of KIF15 remains unclear in prostate cancer. Here, we study the functional importance of KIF15 in the tumorigenesis of PCa. The bioinformatic analysis from PCa patients revealed high KIF15 expression compared to normal prostate tissues. High expression hinting at a possible functional role of KIF15 in regulating cell proliferation of PCa, which was demonstrated by both in vitro and in vivo assays. Downregulation of KIF15 silenced the expression of CDK2, p-RB, and Cyclin D1 and likewise blocked the cells at the G1 stage of the cell cycle. Androgen Receptor Antagonist molecular weight In addition, KIF15 downregulation inhibited MEK-ERK signaling by significantly silencing p-ERK and p-MEK levels. In conclusion, this study confirmed the functional significance of KIF15 in the growth and development of prostate cancer and could be a novel therapeutic target for the treatment of PCa.Thyroid hormones (THs) play a critical role in the metabolic phenotype of the heart; and most of the effects involve transcriptional regulation via thyroid hormone receptors (TRs). TRs ability to form combinatorial complexes with an array of partners accounts for TRs physiological flexibility in modulating gene expression. To identify proteins that associate with TRβ1 in the heart we performed a pull-down assay on cardiac tissue using GST-TRβ1 as bait and identified the bound proteins by LC MS/MS. ACAA2, a mitochondrial thiolase enzyme, was identified as a novel interacting protein. We confirmed ACAA2 localized to the nucleus and using a luciferase reporter assay showed ACAA2 acted as a TH-dependent coactivator for TRβ1. ACAA2 showed an ability to bind to TR recognition sequences but did not alter TRβ1 DNA binding ability. Thus, ACAA2 as a novel TRβ1 associating protein opens a new paradigm to understanding how TH/TRs may be manipulated by energetic pathway molecules.Wnt signaling is one of the major signaling pathways that regulate cell differentiation, tissue patterning and stem cell homeostasis and its dysfunction causes many human diseases, such as cancer. It is of tremendous interests to understand how Wnt signaling is regulated in a precise manner both temporally and spatially. Naked cuticle (Nkd) acts as a negative-feedback inhibitor for Wingless (Wg, a fly Wnt) signaling in Drosophila embryonic development. However, the role of Nkd remains controversial in later fly development, particularly on the canonical Wg pathway. In the present study, we show that nkd is essential for wing pattern formation, such that both gain and loss of nkd result in the disruption of Wg target expression in larvae stage and abnormal adult wing morphologies. Furthermore, we demonstrate that a thirty amino acid fragment in Nkd, identified previously in Wharton lab, is critical for the canonical Wg signaling, but is dispensable for Wg/planar cell polarity pathway. Putting aside the pleiotropic nature of nkd function, i.e. its role in the Decapentaplegic signaling, we conclude that Nkd universally inhibits the canonical Wg pathway across a life span of Drosophila development.In this research, more than 302,000 images of five different types of extra virgin olive oils (EVOOs) have been collected to train and validate a system based on convolutional neural networks (CNNs) to carry out their classification. Furthermore, comparable deep learning models have also been trained to detect and quantify the adulteration of these EVOOs with other vegetable oils. In this work, three groups of CNN models have been tested for (i) the classification of all EVOOs, (ii) the detection and quantification of adulterated samples for each individual EVOO, and (iii) a global version of the previous models combining all EVOOs into a single quantifying CNN. This last model was successfully validated using 30,195 images that were initially isolated from the initial database. The result was an algorithm capable of detecting and accurately classifying the five types of EVOO and their respective adulteration concentrations with an overall hit rate of >96%. Therefore, EVOO droplet analyses via CNNs have proven to be a convincing quality control tool for the evaluation of EVOO, which can be carried by producers, distributors, or even final consumers, to help locate adulterations.Piper nigrum L. is commonly used worldwide and its pericarp, stalks, leaves will be major wastes materials. 42 amide alkaloids were identified in black, white pepper and pericarp by UHPLC-LTQ-Orbitrap HRMS method, followed by 40 constituents in stalks and 36 constituents in leaves. 8 amide alkaloids were reported for the first time in P. nigrum. An ultra-high-performance supercritical fluid chromatography (UHPSFC)-MS method was firstly applied to simultaneously determine 9 characteristic constituents (piperine, piperlonguminine, piperanine, pipercallosine, dehydropipernonaline, pipernonatine, retrofractamide B, pellitorine and guineensine). The most abundant compound in each extract was piperine with a concentration from 0.10 to 12.37 mg/g of dry weight. The fruits, pericarp and leaves extracts could improve cell viability in 6-OHDA-induced SK-N-SH and SH-SY5Y cells. The results showed the characteristics of amide alkaloids of different parts of P. nigrum and evaluated their neuroprotective activities.

Unverricht-Lundborg disease (ULD) is a common type of progressive myoclonic epilepsy (PME). It is caused mostly by biallelic dodecamer repeat expansions in the promoter region of CSTB gene. Despite highly prevalent in the Mediterranean countries, no studies have been reported from Egypt. This article study the presence of CSTB gene mutations among Egyptian patients clinically suspected with ULD, and describes the clinical and genetic characteristics of those with confirmed gene mutation.

Medical records of patients following up in two specialized epilepsy clinics in Cairo, Egypt were retrospectively reviewed. Twenty patients who belonged to 13 unrelated families were provisionally diagnosed with ULD based on the clinical presentation. Genetic testing was done. Clinical characteristics, demographic data and EEG findings were documented.

Genetic studies confirmed the presence of the CSTB dodecamer repeat expansion in 14 patients from 8 families (frequency 70 %). The mean duration of the follow-up was 5 years.