Development an electronic nose to recognize pesticides in groundwater.

Timely detection of Groundwater pollution is essential to protect human health, especially for pesticide pollution. To solve this issue, we proposed a novel solution to realize the prediction of pesticide in groundwater by using the electronic nose (e-nose). The main work of this paper was divided into three steps: 1) checking whether sample was polluted by pesticides, 2) further predicting the pesticide type, brand and pollution degree when the sample was polluted by pesticides, and 3) optimizing the sensor array. Random forest was used to complete the first step, which had the best accuracy and sensitivity of 100 %. Support vector machine was applied to complete the second step, and the accuracy reaching 98.08 %. As for the third step, recursive feature elimination was used to optimize the sensor array. After optimization, the number of sensors was reduced from 26 to 8. In addition, the e-nose developed in this paper was compared with a commercial e-nose. The results showed that the cost of the developed e-nose was much lower than that of the commercial e-nose despite its slightly weaker prediction performance. Thus, this e-nose can be employed to recognize the pesticides in groundwater, and even can be integrated into the while drilling technology to realize the in-situ detection of groundwater.

Ceramides and ceramide synthases in cancer: Focus on apoptosis and autophagy.

Different studies corroborate a role for ceramide synthases and their downstream products, ceramides, in modulation of apoptosis and autophagy in the context of cancer. These mechanisms of regulation, however, appear to be context dependent in terms of ceramides' fatty acid chain length, subcellular localization, and the presence or absence of their downstream targets. Our current understanding of the role of ceramide synthases and ceramides in regulation of apoptosis and autophagy could be harnessed to pioneer the development of new treatments to activate or inhibit a single type of ceramide synthase, thereby regulating the apoptosis induction or cross talk of apoptosis and autophagy in cancer cells. Moreover, the apoptotic function of ceramide suggests that ceramide analogues can pave the way for the development of novel cancer treatments. Therefore, in the current review paper we discuss the impact of ceramide synthases and ceramides in regulation of apoptosis and autophagy in context of different types of cancers. We also briefly introduce the latest information on ceramide synthase inhibitors, their application in diseases including cancer therapy, and discuss approaches for drug discovery in the field of ceramide synthase inhibitors. We finally discussed strategies for developing strategies to use lipids and ceramides analysis in biological fluids for developing early biomarkers for cancer.

Chinese Few-Shot Named Entity Recognition and Knowledge Graph Construction in Managed Pressure Drilling Domain.

Managed pressure drilling (MPD) is the most effective means to ensure drilling safety, and MPD is able to avoid further deterioration of complex working conditions through precise control of the wellhead back pressure. The key to the success of MPD is the well control strategy, which currently relies heavily on manual experience, hindering the automation and intelligence process of well control. In response to this issue, an MPD knowledge graph is constructed in this paper that extracts knowledge from published papers and drilling reports to guide well control. In order to improve the performance of entity extraction in the knowledge graph, a few-shot Chinese entity recognition model CEntLM-KL is extended from the EntLM model, in which the KL entropy is built to improve the accuracy of entity recognition. Through experiments on benchmark datasets, it has been shown that the proposed model has a significant improvement compared to the state-of-the-art methods. On the few-shot drilling datasets, the F-1 score of entity recognition reaches 33%. Finally, the knowledge graph is stored in Neo4J and applied for knowledge inference.

Improving Recognition Accuracy of Pesticides in Groundwater by Applying TrAdaBoost Transfer Learning Method.

Accurate and rapid prediction of pesticides in groundwater is important to protect human health. Thus, an electronic nose was used to recognize pesticides in groundwater. However, the e-nose response signals for pesticides are different in groundwater samples from various regions, so a prediction model built on one region's samples might be ineffective when tested in another. Moreover, the establishment of a new prediction model requires a large number of sample data, which will cost too much resources and time. To resolve this issue, this study introduced the TrAdaBoost transfer learning method to recognize the pesticide in groundwater using the e-nose. The main work was divided into two steps: (1) qualitatively checking the pesticide type and (2) semi-quantitatively predicting the pesticide concentration. The support vector machine integrated with the TrAdaBoost was adopted to complete these two steps, and the recognition rate can be 19.3% and 22.2% higher than that of methods without transfer learning. These results demonstrated the potential of the TrAdaBoost based on support vector machine approaches in recognizing the pesticide in groundwater when there were few samples in the target domain.

Development of an electronic nose to characterize water quality parameters and odor concentration of wastewater emitted from different phases in a wastewater treatment plant.

For public health consideration, it is important to ensure the wastewater discharged from wastewater treatment plant is within the regulatory limits. This problem can be effectively solved by improving the accuracy and rapid characterization of water quality parameters and odor concentration of wastewater. In this paper, we proposed a novel solution to realize the precisive analysis of water quality parameters and odor concentration of wastewater by the electronic nose device. The main work of this paper was divided into three steps: 1) recognizing wastewater samples qualitatively from different sampling points, 2) analyzing the correlation between electronic nose response signals and water quality parameters and odor concentration, and 3) predicting the odor concentration and water quality parameters quantitatively. Combined with different feature extraction methods, support vector machine and linear discriminant analysis were applied as classifiers to recognize samples at different sampling points, which reported the best recognition rate of 98.83%. Partial least squares regression was applied to complete the second step, and R2 was reaching 0.992. As for the third step, ridge regression was used to predict water quality parameters and odor concentration with the RMSE less than 0.9476. Thus, electronic noses can be applied to determine water quality parameters and odor concentrations in the effluent discharged from wastewater plants.

A preliminary screening system for diabetes based on in-car electronic nose.

Studies have found differences in the concentration of volatile organic compounds in the breath of diabetics and healthy people, prompting attention to the use of devices such as electronic noses to detect diabetes. In this study, we explored the design of a non-invasive diabetes preliminary screening system that uses a homemade electronic nose sensor array to detect respiratory gas markers. In the algorithm part, two feature extraction methods were adopted, gradient boosting method was used to select promising feature subset, and then particle swarm optimization algorithm was introduced to extract 24 most effective features, which reduces the number of sensors by 56% and saves the system cost. Respiratory samples were collected from 120 healthy subjects and 120 diabetic subjects to assess the system performance. Random forest algorithm was used to classify and predict electronic nose data, and the accuracy can reach 93.33%. Experimental results show that on the premise of ensuring accuracy, the system has low cost and small size after the number of sensors is optimized, and it is easy to install on in-car. It provides a more feasible method for the preliminary screening of diabetes on in-car and can be used as an assistant to the existing detection methods.

Structure-activity relationship studies of benzothiazole-phenyl analogs as multi-target ligands to alleviate pain without affecting normal behavior.

Soluble epoxide hydrolase (sEH) and fatty acid amide hydrolase (FAAH) are potential targets for several diseases. Previous studies have reported that concomitant selective inhibition of sEH and FAAH produced antinociception effects in an animal model of pain. However, the co-administration of a selective sEH inhibitor and a selective FAAH inhibitor might produce serious side effects due to drug-drug interactions that could complicate drug development in the long term. Thus, discovering dual sEH/FAAH inhibitors, single small molecules that can simultaneously inhibit both sEH and FAAH, would be a significant accomplishment in the medicinal chemistry field. Herein, we report the synthesis and biological evaluation of benzothiazole-phenyl-based analogs as potential dual sEH/FAAH inhibitors. This work represents a follow-up structure-activity relationship (SAR) and metabolic-stability studies of our best dual sEH/FAAH inhibitor identified previously, as well as in vivo evaluation of its effects on voluntary locomotor behavior in rats. Our SAR study indicates that trifluoromethyl groups on the aromatic rings are well tolerated by the targeted enzymes when placed at the ortho and para positions; however, they, surprisingly, did not improve metabolic stability in liver microsomes. Our behavioral studies indicate that doses of dual sEH/FAAH inhibitors that alleviate pain do not depress voluntary behavior in naïve rats, which is a common side effect of currently available analgesic drugs (e.g., opioids). Thus, dual sEH/FAAH inhibitors may be a safe and effective approach to treat pain.

Effect of swelling agent treatment on grape fruit quality and the application of electronic nose identification detection.

The swelling agent is a plant growth regulator that alters the composition and content of nutrients and volatile gases in the fruit. To identify whether grape fruit had been treated with swelling agent, the odor information and quality indexes of grape berries treated with different concentrations of swelling agent were examined by using electronic nose technology and traditional methods. The contents of soluble sugars, soluble solids, soluble proteins and vitamin C were significantly increased in N-(2-chloro-4-pyridyl)-N'-phenylurea (CPPU) treated fruit. The contents of hexanal, (E)-2-hexenal, and nonanal aldehydes decreased significantly. Similarly, the levels of phenyl ethanol, 1-octanol, ethanol, and ethyl acetate alcohols and esters also decreased noticeably. Additionally, the levels of damascenone, linalool, and geraniol ketones and terpenoids decreased. However, the contents of benzaldehyde, D-limonene, acetic acid and hexanoic acid increased. In addition, the electrical signals generated by the electronic nose (e-nose) were analyzed by linear discriminant analysis (LDA), support vector machine (SVM) and random forest (RF). The average recognition rate of SVM was 94.4%. The results showed that electronic nose technology can be used to detect whether grapes have been treated with swelling agent, and it is an economical and efficient detection method.

Laparoscopic resection of benign schwannoma in the hepatoduodenal ligament: A case report and review of the literature.

Schwannomas are mesenchymal neoplasms with a low malignant potential, which arise from Schwann cells. The tumors can occur in most parts of the body; however, the head, neck and flexor surfaces of the extremities are the most common locations. Schwannomas occurring in the hepatoduodenal ligament are extremely rare. To the best of our knowledge, only two cases of schwannoma in the hepatoduodenal ligament have been reported in the literature, and treatment of such cases by laparoscopic surgery has not yet been reported. The present study reports a case of schwannoma in the hepatoduodenal ligament in a 50-year-old male patient. Physical and laboratory examinations showed no abnormal results. Ultrasound and computed tomography failed to definitively diagnose the mass and identify its location. During laparoscopic surgery, a mass was identified in the hepatoduodenal ligament and was completely removed. The gross specimen was a 4.5×2.5×2.5-cm localized mass, yellowish-white in color. Microscopic examination revealed that the tumor was mainly composed of spindle-shaped cells and no atypical cells were identified. Immunohistochemical staining showed a strong positive S-100 protein reaction, whereas cluster of differentiation 34 and epithelial membrane antigen were negative. The final diagnosis of the lesion was benign schwannoma of the hepatoduodenal ligament. The patient was followed-up for 7 months and, at the time of writing, was healthy and without any complications. The aim of the present study was to describe a rare case of hepatoduodenal ligament schwannoma in a 50-year-old male patient, and present a review of the literature. To the best of our knowledge, this is the first case of hepatoduodenal ligament schwannoma treated by laparoscopic surgery.