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Motor imagery (MI)-electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with external world via manipulating smart equipment. Currently, deep learning (DL)-based methods are popular for EEG decoding. Whereas the utilization efficiency of EEG features in frequency and temporal domain is not sufficient, which results in poor MI classification performance. To address this issue, an EEG-based MI classification model based on a frequency enhancement module, a deformable convolutional network, and a crop module (FDCN-C) is proposed. Firstly, the frequency enhancement module is innovatively designed to address the issue of extracting frequency information. It utilizes convolution kernels at continuous time scales to extract features across different frequency bands. These features are screened by calculating attention and integrated into the original EEG data. Secondly, for temporal feature extraction, a deformable convolution network is employed to enhance feature extraction capabilities, utilizing offset parameters to modulate the convolution kernel size. In spatial domain, a one-dimensional convolution layer is designed to integrate all channel information. Finally, a dilated convolution is used to form a crop classification module, wherein the diverse receptive fields of the EEG data are computed multiple times. Two public datasets are employed to verify the proposed FDCN-C model, the classification accuracy obtained from the proposed model is greater than that of state-of-the-art methods. The model's accuracy has improved by 14.01% compared to the baseline model, and the ablation study has confirmed the effectiveness of each module in the model. [ABSTRACT FROM AUTHOR]

Half maximal (50%) effective concentration ( EC50) values are widely used to express fungicide potency and sensitivity of plant pathogens. This study explored the necessity of logarithmic transformation for statistical analysis of EC50 values. The results demonstrated that without logarithmic transformation, none of the five sets of epoxiconazole EC50 data ( n = 26-33) against Sclerotinia sclerotiorum fitted a normal distribution. But after logarithmic transformation, four of the five datasets became normally distributed. Of the five sets of pyraclostrobin EC50 data ( n = 29-32), only one dataset fitted a normal distribution. After logarithmic transformation, four datasets became normally distributed. Logarithmic transformation transformed the heterogeneity of variance across the five sets of epoxiconazole EC50 data to homogeneity but failed to improve the heterogeneity of variance across the five sets of pyraclostrobin EC50 data. For 150 isolates' EC50 values to epoxiconazole and 153 isolates' EC50 values to pyraclostrobin, the intervals of arithmetic means ± standard deviations ( SD) covered 85.3% and 90.2% of data points, respectively, whereas the intervals of geometric means ( [ABSTRACT FROM AUTHOR]

Naturally derived compounds show promise as treatments for microbial infections. Polyphenols, abundantly found in various plants, fruits, and vegetables, are noted for their physiological benefits including antimicrobial effects. This study introduced a new set of acylated phloroglucinol derivatives, synthesized and tested for their antifungal activity in vitro against seven different pathogenic fungi. The standout compound, 3-methyl-1-(2,4,6-trihydroxyphenyl) butan-1-one ( 2b ), exhibited remarkable fungicidal strength, with EC 50 values of 1.39 μg/mL against Botrytis cinerea and 1.18 μg/mL against Monilinia fructicola , outperforming previously screened phenolic compounds. When tested in vivo, 2b demonstrated effective antifungal properties, with cure rates of 76.26% for brown rot and 83.35% for gray mold at a concentration of 200 μg/mL, rivaling the commercial fungicide Pyrimethanil in its efficacy against B. cinerea . Preliminary research suggests that 2b' s antifungal mechanism may involve the disruption of spore germination, damage to the fungal cell membrane, and leakage of cellular contents. These results indicate that compound 2b has excellent fungicidal properties against B. cinerea and holds potential as a treatment for gray mold.

Objective: To explore the biological function and possible underlying mechanism of aldo-keto reductase family 1 member B10 (AKR1B10) gene during hepatocarcinogenesis., Methods: A pair of chemically synthesized small interfering RNA (siRNA) targeting on AKR1B10 was transfected into liver cancer cell line MHCC97H by LipofectamineTM 2000. After confirming the interfering effects of AKR1B10-siRNAs through Quant SYBR Green polymerase chain reaction (Real-time PCR), Western blot and enzymatic activity assay, the capabilities of proliferation and apoptosis of the transfected cells were observed by CCK-8 assay and flow cytometry analysis, and the expressions of a group of tumor-related gene such as c-myc, c-fos, N-ras were observed through Real-time PCR., Results: The expressions of AKR1B10 and the enzymatic activity were down-regulated significantly in AKR1B10-siRNA-transfected cells. Compared with mock and blank control groups, cell growth in AKR1B10-siRNA-transfected group was inhibited by 26.6%+/-3.1% at 72h after transfection. The ratio of apoptotic cells was 37.3%+/-1.0% in AKR1B10-siRNA-transfected group, which was significantly higher than that in mock and blank control groups (P < 0.01). Real-time PCR showed that the expressions of oncogene c-myc, c-fos and N-ras, and the proliferation-associated gene ki-67 were down-regulated in AKR1B10-siRNA-transfected cells, while the expressions of apoptosis-promoting gene caspas-3 and bax were up-regulated., Conclusions: AKR1B10 might promote proliferation, inhibit apoptosis and then induce malignant transformation of hepatocytes by regulating the expression level of some tumor-related genes.

Objective: To screen the differentially expressed proteins especially at the precancerous stage of diethylnitrosamine (DEN) induced hepatocarcinogenesis by comparative proteome research., Methods: Rats were divided into normal and DEN groups and sacrificed periodically. The liver samples were stained with gamma-glutamyl transpeptidase (GGT) and HE to distinguish the preneoplastic lesion (pre-HCC) from the normal and HCC tissues. The two-dimensional electrophoresis (2-DE) and mass spectrometry (MALDI-TOF-MS/MS) were then applied to analyze the differentially expressed protein between pre-HCC and normal tissues, pre-HCC and HCC, as well as HCC and normal tissues. A few of the candidate proteins such as laminin receptor 1 (67LR) and agmatinase were validated by Western blot and RT-PCR., Results: Totally, there were 82 proteins that differentially expressed two fold or more in one kind of tissues sample than the other, 47 of which occurred in the pre-HCC tissues. Eight proteins including 67LR were consistently up-regulated from normal tissue to pre-HCC and then to HCC tissues, while 22 proteins including agmatinase showed progressively down-regulated in these tissues samples., Conclusion: The protein expression profiles are different during the process of hepatocarcinogenesis. Further study on the differentially expressed protein, especially these upregulated in the precancerous stage such as 67LR and agmatinase, might contribute to prevention and early diagnosis of human HCC.