2-Chloro-N′-(2-chloro­benzyl­idene)benzohydrazide

The mol­ecule of the title compound, C14H10Cl2N2O, adopts an E configuration about the C=N bond. The dihedral angle between the two benzene rings is 79.7 (2)°. In the crystal structure, mol­ecules are linked by inter­molecular N—H⋯O, C—H⋯Cl and C—H⋯O hydrogen bonds, forming chains running along the b axis

Semi-supervised Time Series Anomaly Detection Model Based on LSTM Autoencoder

Nowadays, time series data is more and more likely to appear in various real-world systems, such as power plants, medical care, etc. In these systems, time series anomaly detection is necessary, which involves predictive maintenance, intrusion detection, anti-fraud, cloud platform monitoring and management, etc. Generally, the anomaly detection of time series is regarded as an unsupervised learning problem. However, in a real scenario, in addition to a large set of unlabeled data, there is usually a small set of available labeled data, such as normal or abnormal data sets labeled by experts. Only a few methods use labeled data, and the existing semi-supervised algorithms are not yet suitable for the field of time series anomaly detection. In this work, we propose a semi-supervised time series anomaly detection model based on LSTM autoencoder. We improve the loss function of the LSTM autoencoder so that it can be affected by unlabeled data and labeled data at the same time, and learn the distribution of unlabeled data and labeled data at the same time by minimizing the loss function. In a large number of experiments on the Yahoo! Webscope S5 and NAB data sets, we compared the performance of the unsupervised model and the semi-supervised model of the same network framework to prove that the performance of the semi-supervised model is improved compared to the unsupervised model

Effects of domestic cooking process on the chemical and biological properties of dietary phytochemicals

peer-reviewedFoods are good sources of vitamins, minerals and dietary fibers as well as phytochemicals, which are beneficial for the human body as nutritional supplements. The nutritional value (crude fibers, crude proteins, crude fats, flavonols, carotenoids, polyphenols, glucosinolate, chlorophyll, and ascorbic acid) and biological or functional properties (antioxidant activity, anticancer activity, or anti-mutagenic activity) of foods can be well retained and protected with the appropriate cooking methods. The chemical, physical and enzyme modifications that occur during cooking will alter the dietary phytochemical antioxidant capacity and digestibility. This paper reviewed the recent advances on the effects of domestic cooking process on the chemical and biological properties of dietary phytochemicals. Furthermore, the possible mechanisms underlying these changes were discussed, and additional implications and future research goals were suggested. The domestic cooking process for improving the palatability of foods and increasing the bioavailability of nutrients and bioactive phytochemicals has been well supported

Hard Disk Failure Prediction via Transfer Learning

Due to the large-scale growth of data, the storage scale of data centers is getting larger and larger. Hard disk is the main storage medium, once a failure occurs, it will bring huge losses to users and enterprises. In order to improve the reliability of storage systems, many machine learning methods have been widely employed to predict hard disk failure in the past few decades. However, due to the large number of different models of hard disks in the heterogeneous disk system, traditional machine learning methods cannot build a general model. Inspired by a DANN based unsupervised domain adaptation approach for image classification, in this paper, we propose the DFPTL (Disk Failure Prediction via Transfer Learning) approach, which introduce the DANN approach to predict failure in heterogeneous disk systems by reducing the distribution differences between different models of disk datasets. This approach only needs unlabeled data (the target domain) of a specific disk model and the labeled data (the source domain) collected from a different disk model from the same manufacturer. Experimental results on real-world datasets demonstrate that DFPTL can achieve adaptation effect in the presence of domain shifts and outperform traditional machine learning algorithms

The clinical efficacy of ozone combined with steroid in the treatment of discogenic low back pain: a randomized, double-blinded clinical study

ObjectiveThis randomized double-blinded clinical study is to investigate the clinical efficacy of per-paravertebral disk ozone injection combined with steroids in the treatment of patients with chronic discogenic low back pain (CDLBP).MethodsGroup A (N = 60) received a per-paravertebral injection of a steroid mixture of 10 mL with pure oxygen 20 mL, while group B (N = 60) received a per-paravertebral injection of a steroid mixture of 10 mL combined with ozone 20 mL (30 μg/mL). Injections were administered once a week for 3 weeks, with a follow-up of 6 months. Clinical outcomes were assessed at week 1, month 3, and month 6 with the help of Visual Analog Scale (VAS) scores and Macnab efficacy evaluation.ResultsThe VAS score of both group A (1.65 vs. 6.87, p = 0.000) and group B (1.25 vs. 6.85, p = 0.000) at week 1 was significantly reduced compared to baseline. The effect was sustained at the 3- and 6-month follow-up periods (p < 0.05). Group B had significantly lower VAS scores at month 3 (1.53 vs. 3.82, p = 0.000) and month 6 (2.80 vs. 5.05, p = 0.000) compared to group A, respectively. Based on Macnab criteria, 95 and 96.7% of patients in groups A and B had good rates “excellent plus good” at week 1, respectively. Good rates were significantly higher in group B at month 3 (91.7 vs. 78.3%, p = 0.041) and month 6 (85.0 vs. 68.3%, p = 0.031) compared to group A, respectively. No serious adverse events were noted in both groups.ConclusionPer-paravertebral injection of steroid and ozone combination resulted in better relief of CDLBP compared to pure oxygen plus steroid.Clinical Trial RegistrationChiCTR2100044434 https://www.chictr.org.cn/showproj.html?proj=121571

Recent advances on the synthesis, structure, and properties of polyoxotantalates

Polyoxotantalates (POTas) are an important branch of polyoxometalates (POMs) that remain largely undeveloped compared with other members of the POM family including polyoxovanadates, polyoxotungstates, polyoxomolybdates, and polyoxoniobates. Owing to their promising applications in diverse fields such as photo/electrocatalysis, ion conduction, environmental protection, and magnetism, the development of synthetic strategies for new POTas has attracted continuous interest over the past decades. This review summarizes the current status in the development of POTas, including their synthetic methods, crystal structures, physicochemical properties, and potential applications. Additionally, synthetic challenges and prospects are also discussed. It is hoped that this review will be of reference value for the further development of POTas

Characteristic gene expression profiles in the progression from liver cirrhosis to carcinoma induced by diethylnitrosamine in a rat model

<p>Abstract</p> <p>Background</p> <p>Liver cancr is a heterogeneous disease in terms of etiology, biologic and clinical behavior. Very little is known about how many genes concur at the molecular level of tumor development, progression and aggressiveness. To explore the key genes involved in the development of liver cancer, we established a rat model induced by diethylnitrosamine to investigate the gene expression profiles of liver tissues during the transition to cirrhosis and carcinoma.</p> <p>Methods</p> <p>A rat model of liver cancer induced by diethylnitrosamine was established. The cirrhotic tissue, the dysplasia nodules, the early cancerous nodules and the cancerous nodules from the rats with lung metastasis were chosen to compare with liver tissue of normal rats to investigate the differential expression genes between them. Affymetrix GeneChip Rat 230 2.0 arrays were used throughout. The real-time quantity PCR was used to verify the expression of some differential expression genes in tissues.</p> <p>Results</p> <p>The pathological changes that occurred in the livers of diethylnitrosamine-treated rats included non-specific injury, fibrosis and cirrhosis, dysplastic nodules, early cancerous nodules and metastasis. There are 349 upregulated and 345 downregulated genes sharing among the above chosen tissues when compared with liver tissue of normal rats. The deregulated genes play various roles in diverse processes such as metabolism, transport, cell proliferation, apoptosis, cell adhesion, angiogenesis and so on. Among which, 41 upregulated and 27 downregulated genes are associated with inflammatory response, immune response and oxidative stress. Twenty-four genes associated with glutathione metabolism majorly participating oxidative stress were deregulated in the development of liver cancer. There were 19 members belong to CYP450 family downregulated, except CYP2C40 upregulated.</p> <p>Conclusion</p> <p>In this study, we provide the global gene expression profiles during the development and progression of liver cancer in rats. The data obtained from the gene expression profiles will allow us to acquire insights into the molecular mechanisms of hepatocarcinogenesis and identify specific genes (or gene products) that can be used for early molecular diagnosis, risk analysis, prognosis prediction, and development of new therapies.</p

In-silico investigations into natural products as nonnucleoside DNA methyltransferase 1 inhibitors for treating epi-mutation in gastric cancer

Purpose: To explore in silico methods to search for the best reported non-nucleoside DNA methyltransferase 1 (DNMT1) inhibitor of epimutation in gastric cancer.Methods: A dataset of reported non-nucleoside DNMT1 inhibitors was used to target the active site of crystallized DNMT1 protein. Molecular docking simulations were carried out using AutoDock 4.2.6 l. The results were analyzed using Discovery studio visualizer.Results: In silico analysis of known natural non-nucleoside DNMT1 inhibitors gave genistein as the top ranked compound with ΔG of -6.39 Kcal/mol. Further, the results indicated that epigallocatechin gallate and curcumin are poor non-nucleoside DNMT1 inhibitors, as the in silico data suggest that they failed to bind to the catalytic site of DNMT1.Conclusion: The results indicate that genistein is the top rated compound for DNMT1 inhibition. Previous in vitro and in vivo work by other researchers seem to validate the findings of the study.Keywords: Epi-mutation, DNA methyltransferase, Non-nucleoside, DNMT1 inhibitor, Dockin