1.Prediction of Pharmacoresistance in Drug-Naïve Temporal Lobe Epilepsy Using Ictal EEGs Based on Convolutional Neural Network.
Yiwei GONG ; Zheng ZHANG ; Yuanzhi YANG ; Shuo ZHANG ; Ruifeng ZHENG ; Xin LI ; Xiaoyun QIU ; Yang ZHENG ; Shuang WANG ; Wenyu LIU ; Fan FEI ; Heming CHENG ; Yi WANG ; Dong ZHOU ; Kejie HUANG ; Zhong CHEN ; Cenglin XU
Neuroscience Bulletin 2025;41(5):790-804
Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis. However, it still lacks effective predictors and approaches. Here, a classical model of pharmacoresistant temporal lobe epilepsy (TLE) was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats. Ictal electroencephalograms (EEGs) recorded before phenytoin treatment were analyzed. Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats, a convolutional neural network predictive model was constructed to predict pharmacoresistance, and achieved 78% prediction accuracy. We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power, which was verified in seizure EEGs from pharmacoresistant TLE patients. Prospectively, therapies targeting the subiculum in those predicted as "pharmacoresistant" individual rats significantly reduced the subsequent occurrence of pharmacoresistance. These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model. This may be of translational importance for the precise management of pharmacoresistant TLE.
Epilepsy, Temporal Lobe/diagnosis*
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Animals
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Drug Resistant Epilepsy/drug therapy*
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Electroencephalography/methods*
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Rats
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Anticonvulsants/pharmacology*
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Neural Networks, Computer
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Male
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Humans
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Phenytoin/pharmacology*
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Adult
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Disease Models, Animal
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Female
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Rats, Sprague-Dawley
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Young Adult
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Convolutional Neural Networks
2.Optimization of the preparation process for Qinggan Liangxue Granules based on active components
Yan CHEN ; Wenli YAN ; Deyong ZHOU ; Tuoxin LI ; Heming FAN ; Dongping LIU
International Journal of Traditional Chinese Medicine 2024;46(11):1475-1479
Objective:To optimize the preparation process of Qinggan Liangxue Granules.Methods:The L 9 (3 4) orthogonal experimental design was used to investigate the effects of water addition, extraction time and extraction times on the extraction process of Qinggan Liangxue Granules by taking the transfer rate of astilbin and paeoniflorin as the indexes, so as to screen the optimal extraction process. The evaluation indexes of granule molding rate, water content, solubility and fluidity were used to compare the effect of finished products under different ratios of excipients and granulation conditions. Results:The optimal extraction process was to add 10 times the amount of water reflux extraction twice, each time 1.5 h; using wet granulation, the ratio of dry paste powder to base material was 4:1 ( m/ m), and the wetting agent was 95% ethanol. Conclusion:The preparation process of Qinggan Liangxue Granules is stable and feasible, which lays a foundation for further research and development and quality control.
3.High performance liquid chromatography combined with microwave-assisted extraction and solid phase extraction in determination of mefenacet residues in rice
Tao WANG ; Heming MI ; Yifeng CHAI ; Guorong FAN
Academic Journal of Second Military Medical University 2000;0(07):-
Objective:To establish a method by combining microwave-assisted extraction(MAE),solid phase extraction(SPE)and high performance liquid chromatography(HPLC)for determination of the mefenacet residues in rice.Methods:Acetone and acetontrile(37)were used as extraction solvent.Microwave-assisted extraction was used to extract mefenacet residues in the rice.The extracts were then cleaned up with a Florisil cartridge and then subjected to Hypersil C18 column(5 ?m,4.6 mm?200 mm),with acetonitrilewater(5050,V/V)solution as mobile phase and with a flow rate of 1.0 ml/min;the ultraviolet detection wavelength was at 217 nm.Results:Good linear correlation for mefenacet was found within a concentration range of 0.198-9.900 ?g/ml.The detection limit was 0.039 6 ?g/mL for mefenacet(S/N=2).The average recovery rate of rice hull and brown rice were 90.8%(RSD 1.8%)and 85.6%(RSD 2.5%),respectively.Conclusion:The present method is simple and rapid;it can be used for the determination of mefenacet residues in rice.
4.Separation of soybean isoflavone glucosides from Semen Sojae Praeparatum by preparative reversed-phase high performance liquid chromatography
Liping QU ; Guorong FAN ; Heming MI ; Liang SUN
Academic Journal of Second Military Medical University 1981;0(03):-
Objective:To search for a rapid and efficient method for the isolation of 3 kinds of isoflavone glucosides from the ethanol extract of Semen Sojae Praeparatum.Methods: The crude isoflavones were extracted by 75% aqueous ethanol after removing the oil by Soxhlet extraction.Then 1300 macroporous resin,water and different concentrations of aqueous ethanol(10%,20%,30%,40%,50%,70%,and 95%) were used to separate and elute the crude isoflavones.The fraction eluted by 40% aqueous ethanol was subjected to preparative HPLC analysis.The chromatographic conditions: A YWG C18(10.0 mm?200 mm,i.d.10 ?m) column was used;the mobile phase consisted of acetonitrile-water-acetic acid at volume ratio of 25751(V/V/V) and a flow rate of 3.0 ml/min;the injection volume was 750 ?l;and the detection wave length was set at 260 nm.Results: Daidzin,glycitin and genistin were rapidly separated with the purities over 99% as determined by external standard HPLC.Conclusion: This technique is simple and suitable for the isolation of daidzin,glycitin and genistin from Semen Sojae Praeparatum.

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