Objective To study the protective effect of Irisin in doxorubicin(Dox)induced-Cardiomyopathy and its possible mechanism.Methods AC 16 cells were used to construct Dox injury model and divided into control group(AC 16 cells were cultured with complete medium),Irisin group(AC16 cells were treated with 10 ng·L-1 Irisin for 24 h),Dox group(AC 16 cells were treated with 4 μmol·L-1 Dox for 24 h),Dox+Irisin group(AC 16 cells were pretreated with 10 ng·L-1 Irisin for 2 h,and then treated with 4 pmol·L-1 Dox for 24 h).Cell counting kit-8(CCK-8),terminal deoxynucleotidyl transferase-mediated nick end labeling(TUNEL)and lactate dehydrogenase(LDH)were used to detect the proliferation,apoptosis and mortality of AC 16 cells.Western blot was used to detect the expression levels of nuclear factor-κB(NF-κB)signaling pathway and apoptotic factors B-cell lymphoma-2(Bcl-2),Bcl-2-associated X protein(Bax)and caspase-9 protein.Mito-Tracker Red CMXRos probe was used to detect mitochondrial membrane potential.Results In the contrl group,Irisin group,Dox group,Dox+Irisin group,the rate of apoptosis were(0.97±0.09)％,0,(42.80±6.70)％,(11.74±1.79)％;the expression of Bax protein were 0.85±0.01,0.36±0.02,1.15±0.07,0.37±0.11;the expression of caspase-9 protein were 0.52±0.02,0.59±0.03,1.11±0.02,0.67±0.08;the expression of Bcl-2 protein were 1.01±0.04,1.05±0.25,0.43±0.02 and 0.99±0.30;the probability of mitochondrial damage were(0.02±0.01)％,(0.5±0.15)％,(38.6±2.39)％,(1.58±0.54)％.The difference of the above indexes between the contrl group and the Dox group were statistically significant(all P＜0.05);the difference between Dox group and Dox+Irisin group were statisically significant(all P＜0.05).Conclusion Irisin could reduce the expression level of Bax,caspase-9,p-NF-κB,and p-mTOR caused by Dox,increase the expression level of Bcl-2,ameliorate the myocardial damage caused by Dox,and reduce cardiotoxicity.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective The characteristics of supramolecular"imprinting template"of volatile oil of Curcuma kwangsiensis and Curcuma phaeocaulis were analyzed and studied based on the supramolecular"qixi"theory of Chinese materia medica combined with chemometrics.Methods The volatile oil of C.kwangsiensis and C.phaeocaulis were extracted by steam distillation,and the fingerprint and composition information of each batch were obtained by GC-MS.Total statistical moment method was used to compare the imprinting characteristics of the"imprinting template"of C.kwangsiensis and C.phaeocaulis.The core index(CI)of each batch of essential oil of C.kwangsiensis and C.phaeocaulis was calculated,and the topological characteristics of types of"imprinting template"of C.kwangsiensis and C.phaeocaulis were compared by chemometrics.Results There was no significant difference in the extraction rate of volatile oil between C.kwangsiensis and C.phaeocaulis.The average values of total zero order moment(AUCT)were(1.907±0.177)×108,(1.979±0.413)×108 μV·s,respectively,showing that there was no significant difference in the total content of volatile oil between the two groups.The mean values of the total first order moment(MCRTT)were(30.969±0.962)and(33.198±0.409)min.The average value of total second order moment(VCRTT)was(56.176±11.368)and(43.891±4.113)min2,respectively,indicating that there were significant differences in the content ratio and species of volatile oils between the two groups.The similarity of total statistical moments of C.kwangsiensis and C.phaeocaulis was mostly lower than the defined value,indicating that the chemical composition and composition ratio of the volatile oil were different.Principal component analysis and orthogonal partial least squares discriminant analysis could obviously divide C.kwangsiensis and C.phaeocaulis into two categories.Through the analysis of P value and VIP value,the CI values of Xvp 4th order,Xvpc 5th order,Xvpc 6th order,Xvpc 7th order,Xvc 3rd order,Xvpc 4th order were the main difference values of C.kwangsiensis and C.phaeocaulis.Conclusion Through the characterization of"imprinting property"and"topological characteristics"of the supramolecular"imprinting template"and combining with chemometric analysis,it is possible to successfully distinguish C.kwangsiensis and C.phaeocaulis,and find the different CI values between two"imprinting templates".

Objective To investigate the clinical efficacy and safety of Zishen Jianpi Quyu Formula in treating patients with migraine without aura in the postmenstrual period of kidney deficiency and blood stasis type.Methods A total of 104 patients with migraine without aura of kidney deficiency and blood stasis type were randomly divided into the control group and the trial group,with 52 cases in each group.The control group was treated with Flunarizine Hydrochloride Capsules,and the trial group was treated with Zishen Jianpi Quyu Formula on the basis of treatment for the control group.One menstrual cycle constituted a course of treatment,and the treatment covered a total of two courses(eight weeks).The changes of traditional Chinese medicine(TCM)syndrome score,migraine attack frequency,duration of migraine headaches,visual analogue scale(VAS)score of migraine headache intensity,Headache Impact Test-6(HIT-6)score and hemorheology indexes in the two groups before and after treatment were observed.Moreover,the efficacy for TCM syndrome and clinical safety in the two groups were evaluated.Results(1)After two courses of treatment,the total effective rate of the trial group was 90.38%(47/52),and that of the control group was 69.23%(36/52),the intergroup comparison(by chi-square test)showed that the efficacy for TCM syndrome in the trial group was significantly superior to that of the control group(P＜0.05).(2)After treatment,the TCM syndrome scores of the patients in both groups were significantly lower than those before treatment(P＜0.05),and the reduction of TCM syndrome score in the trial group was significantly superior to that in the control group(P＜0.05).(3)After treatment,the migraine attack frequency,duration of migraine headaches,VAS scores of migraine headache intensity in the two groups of patients were significantly improved compared with those before treatment(P＜0.05),and the improvement of migraine headache parameters in the trial group was significantly superior to that in the control group(P＜0.05).(4)After treatment,the HIT-6 score in the two groups was decreased significantly compared with those before treatment(P＜0.05),and the decrease of HIT-6 score in the trial group was significantly superior to that in the control group(P＜0.05).(5)After treatment,hemorheology indexes(including plasma viscosity,whole blood high-shear viscosity,whole blood low-shear viscosity,fibrinogen,and hematocrit)in the two groups were improved compared with those before treatment(P＜0.05),and the improvement of each of hemorheology indexes in the trial group was significantly superior to that in the control group(P＜0.05).(6)During treatment,no serious adverse events occurred in the two groups,which was of high safety.Conclusion Zishen Jianpi Quyu Formula exerts remarkable clinical efficacy in treating patients of migraine without aura in the postmenstrual period of kidney deficiency and blood stasis type.The formula is effective on improving the TCM syndromes and migraine attacks of the patients,achieving the efficacy of milder headache,lower attack frequency and shorter duration,more stability hemorheology indexes and higher safety.

Human brain banks use a standardized protocol to collect,process and store post-mortem human brains and related tissues,along with relevant clinical information,and to provide the tissue samples and data as a resource to foster neuroscience research according to a standardized operating protocols(SOP).Human brain bank serves as the foundation for neuroscience research and the diagnosis of neurological disorders,highlighting the crucial rule of ensuring the consistency of standardized quality for brain tissue samples.The first version of SOP in 2017 was published by the China Human Brain Bank Consortium.As members increases from different regions in China,a revised SOP was drafted by experts from the China Human Brain Bank Consortium to meet the growing demands for neuroscience research.The revised SOP places a strong emphasis on ethical standards,incorporates neuropathological evaluation of brain regions,and provides clarity on spinal cord sampling and pathological assessment.Notable enhancements in this updated version of the SOP include reinforced ethical guidelines,inclusion of matching controls in recruitment,and expansion of brain regions to be sampled for neuropathological evaluation.

Objective:To detect the pharmacokinetic(PK)parameters of coagulation factor Ⅷ(FⅧ)in adult patients with severe hemophilia A,identify the potential factors influencing FⅧ PK,and optimize the use of FⅧ in individual prophylaxis regimens.Methods:PK characteristics of FⅧ were studied in a total of 23 severe hemophilia A adults.The correlation of patients'characteristics including age,von Willebrand factor antigen(vWF:Ag),blood group,weight,body mass index(BMI)and FⅧ genotype,with FⅧ PK were evaluated.Individual prophylaxis regimens were given based on FⅧ PK parameters.Results:The mean terminal half-life(t1/2)of FⅧ was 20.6±9.3 h,ranged from 11.47 h to 30.12 h.The age(r=0.580)and vWF:Ag(r=0.814)were significantly positively correlated with t1/2 of FⅧ.The mean area under the plasma concentration curve(AUC)of FⅧ was 913±399(328-1 878)IU h/dl,and the AUC of FⅧ was positively correlated with age(r=0.557)and vWF:Ag(r=0.784).The mean residence time(MRT)of FⅧ was 24.7±12.4(13.2-62.2)h,and the MRT of FⅧ was positively correlated with age(r=0.664)and vWF:Ag(r=0.868).The mean in vivo recovery(IVR)of FⅧ was 2.59±0.888(1.5-4.29)IU/dl per IU/kg,the mean clearance(CL)of FⅧ was 3±1.58(0.97-7.18)ml/(kg·h),and there was no significant correlation of IVR and CL with age and vWF:Ag.According to the individual PK parameters,ultra low-dose,low-dose and moderate-dose FⅧ were applied to 15,6,2 adults patients with severe hemophilia A for prophylaxis,respectively.Conclusion:There are significant individual differences in the FⅧ half-life of adult patients with severe hemophilia A.The older the patient,the higher the vWF:Ag level,and the longer the FⅧ half-life.Individual administration is required based on the FⅧ PK parameters to optimize prophylaxis treatment.

Aim To explore the effect and mechanism of the artesunate(ART)on hepatocellular carcinoma(HCC).Methods The cell lines MHCC-97H and HCC-LM3 were used to be detected.MTT and clone formation were used to determine the cell proliferation;Wound healing was used to detect the cell migration;Transwell was used to test the cell invasion.Flow-cy-tometry was used to detect cell apoptosis and cell cy-cle.RNA-seq and qRT-PCR was used to detect the genes expression.Results The proliferation,migra-tion and invasion of treated cells were obviously inhibi-ted(P＜0.01).Moreover,the apoptosis rate in-creased significantly,so did the proportion of G2/M cells.Transcriptomic analysis identified GADD45A as a potential target of ART through RNA-sequencing da-ta,and suggested that ART might induce apoptosis and cell cycle arrest through regulating the expression of GADD45A.In addition,the results of mechanism studies and signaling analysis suggested that GADD45A had interaction with its upstream gene NACC1(nucle-us accumbens associated 1).Moreover,after ART treatment,the expressions of GADD45A and NACC1 were changed significantly.Conclusion ART may be a potential drug to resist HCC by affecting the expres-sion of GADD45A and its upstream gene NACC1,which provides a new drug,a new direction and a new method for the clinical treatment of HCC.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.