Moringa oleifera, widely utilized in Ayurvedic medicine, is recognized for its leaves, seeds, and velamen possessing traditional effects such as vātahara(wind alleviation), sirovirecaka(brain clearing), and hridya(mental nourishment). This study aims to identify the medicinal part of ■ in the Sārasvata ghee formulation as described in the Bower Manuscript, while investigating the ameliorative effects of different medicinal parts of M. oleifera on learning and memory deficits in mice and elucidating the underlying molecular mechanisms. A total of 144 male ICR mice were randomly assigned to the following groups: control, model(scopolamine hydrobromide, Sco, 2 mg·kg~(-1)), donepezil(donepezil hydrochloride, Don, 3 mg·kg~(-1)), M. oleifera leaf low-, medium-, and high-dose groups(0.5, 1, 2 g·kg~(-1)), M. oleifera seeds low-, medium-, and high-dose groups(0.25, 0.5, 1 g·kg~(-1)), and M. oleifera velamen low-, medium-, and high-dose groups(0.31, 0.62, 1.24 g·kg~(-1)). Learning and memory abilities were assessed using the passive avoidance test and Morris water maze. Nissl and HE staining were employed to examine histopathological changes in the hippocampus. Transcriptomics and targeted metabolomics were used to screen differential genes and metabolites, with MetaboAnalyst 6.0 and O2PLS methods applied to identify key disease-related targets and pathways. RESULTS:: demonstrated that M. oleifera leaf(1 g·kg~(-1)) significantly ameliorated Sco-induced learning and memory deficits, outperforming M. oleifera seeds(0.25 g·kg~(-1)) and M. oleifera velamen(1.24 g·kg~(-1)). This was evidenced by improved behavioral performance, reversal of neuronal damage, and reduced acetylcholinesterase(AChE) activity. Multi-omics analysis revealed that M. oleifera leaf upregulated Tuba1c gene expression through the synaptic vesicle cycle, enhancing glutamate(Glu), dopamine(DA), and acetylcholine(ACh) release via Tuba1c-Glu associations for neuroprotection. M. oleifera seeds targeted the dopaminergic synapse pathway, promoting memory consolidation through Drd2-ACh associations. M. oleifera velamen was associated with the cocaine addiction pathway, modulating dopamine metabolism via Adora2a-DOPAC, with limited relevance to learning and memory. In conclusion, M. oleifera leaf exhibits superior efficacy and mechanistic advantages over M. oleifera seeds and velamen, suggesting that the ■ in the Sārasvata ghee formulation is likely M. oleifera leaf, providing scientific evidence for its identification in ancient texts.
Animals ; Moringa oleifera/chemistry* ; Male ; Mice ; Seeds/chemistry* ; Plant Leaves/chemistry* ; Mice, Inbred ICR ; Memory Disorders/psychology* ; Transcriptome/drug effects* ; Memory/drug effects* ; Learning/drug effects* ; Metabolomics ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Maze Learning/drug effects*

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

Objective To explore the effects of different acupoints,different target organs,and different interventions on acupoint efficacy based on ACU&MOX-DATA platform;To illustrate and visualize whether the above factors have the characteristics of"specific effect"or"common effect"of acupoint efficacy.Methods The multi-source heterogeneous data were integrated from the original omics data and public omics data.After standardization,differential gene analysis,disease pathology network analysis,and enrichment analysis were performed using Batch Search and Stimulation Mode modules in ACU&MOX-DATA platform under the conditions of different acupoints,different target organs,and different interventions.Results Under the same disease state and the same intervention,there were differences in effects among different acupoints;under the same disease state,the same acupoint and intervention,the responses produced by different target organs were not completely consistent;under the same disease state and acupoint,there were differences in effects among different intervention measures.Conclusion Based on the analysis of ACU&MOX-DATA platform,it is preliminary clear that acupoints,target organs,and interventions are the key factors affecting acupoint efficacy.Meanwhile,the above results have indicated that there are specific or common regulatory characteristics of acupoint efficacy.Applying ACU&MOX-DATA platform to analyze and visualize the critical scientific problems in the field of acupuncture and moxibustion can provide references for deepening acupoint cognition,guiding clinical acupoint selection,and improving clinical efficacy.

Objective To reveal the characteristics of Tibetan human body composition in Gannan.Methods The body composition of 410 Tibetan adults(221 males and 189 females)in Gannan was measured by bioelectrical impedance method.The data were processed by SPSS 20.0 statistical software.Results Related analysis results showed that the total body muscle mass,estimated fat level and trunk muscle mass of the male decreased with age,while the percent body water,visceral fat level and percent trunk fat increased with age.The stature and left lower limb muscle mass of the female decreased with age,while body weight,percent body fat,body mass index,visceral fat level,percent right upper limb fat,right upper limb muscle mass,percent left upper limb,left upper limb muscle mass,percent right lower limb fat,percent left lower limb fat,left lower limb muscle mass and percent trunk fat increased with age.Analysis of single factor variance showed that there were statistically significant differences in the four indexes of male percent body water,visceral fat level,percent trunk fat and trunk muscle mass,while there were no statistically significant differences in the other 14 indexes among age groups.Females weight,stature,percent body fat,total body muscle mass,estimated fat level,body mass index,visceral fat level,percent right upper limb fat,right upper limb muscle mass,percent left upper limb fat,left upper limb muscle mass,percent right lower limb fat,percent left lower limb fat,left lower limb muscle mass,percent trunk fat,trunk muscle mass 16 index values were statistically significant differences between age groups,the remaining two index values were not statistically significant differences between age groups.The results of u test showed that the body weight,total body muscle mass,estimated fat level,percent body water,limb muscle mass and trunk muscle mass of males were higher than those of females,and percent body fat,limb fat rate,visceral fat rate and trunk fat rate of females were higher than those of males.According to the body mass index,Gannan Tibetan male and female were overweight;according to the percent body fat,Gannan Tibetan males were non-obesity and females were obesity.Conclusion The body mass index and overall fat content of Tibetan males and females in Gannan are relatively high among the 13 ethnic groups.

Objective To analyze the characteristics of adult body composition and obesity status of three ethnic groups:Ewenki,Daur and Mongolian Buryat.Methods The bioelectrical impedance analysis(BIA)was used to measure 18 body composition components in three adults ethnic groups:245(male 124,female 121)Ewenki,207(male 90,female 117)Daur,and 181(male 74,female 107)Mongolian Buryat.The data were processed using Excel 2016 and SPSS 24.0 statistical software.Results The result of correlation analysis showed that visceral fat level was significantly and positively correlated with age(P＜0.01).Stature,total body muscle mass,estimated bone mass and trunk muscle mass were all significantly and negatively correlated with age(P＜0.01)in males and females of the three ethnic groups.The percent body fat,percent left upper limb fat and percent trunk fat were positively correlated with age in Ewenki males(P＜0.05 or P＜0.01)and the percent body fat,body mass index(BMI),percent limb fat and percent trunk fat were positively correlated with age in Ewenki females(P＜0.05 or P＜0.01).Body weight,BMI,percent left upper limb fat,left upper limb muscle mass,bilateral lower limb fat and muscle mass were all negatively correlated with age in Daur males(P＜0.05 or P＜0.01).Body weight,upper limb muscle mass and left lower limb muscle mass were negatively correlated with age(P＜0.05 or P＜0.01)in Mongolian Buryat males and percent trunk fat was positively correlated with age(P＜0.05)in Mongolian Buryat females.Comparison between ethnic groups showed that most of the body composition index values of the Ewenki and Mongolian Buryat divisions were closest to each other,and the body fat content was higher than that of the Daur.BMI,percent body fat and visceral fat level were all manifested in the Mongolian Buryat Department＞Ewenki＞Daur.Cluster analysis showed that Ewenki,Daur and Mongolian Buryat were closer to the northern groups and further from the southern groups.Conclusion The Ewenki is most similar to the Mongolian Buryat in body composition characteristics all three ethnic groups has a more serious obesity problem.

Objective To explore the common features of Chinese ethnic groups.Methods Eight body indexes of 62 ethnic groups in China were analyzed.Results The cluster analysis showed that 52 males and 59 females ethnic groups were grouped into the mixed group dominated by the northern ethnic group and the mixed group dominated by the southern ethnic group.Eight Han ethnic groups were grouped into each group,but no Han group was aggregated.The result of body index classification showed that the main body types of Chinese male population were long trunk,middle chest,wide shoulder,wide pelvis and middle leg.Middle body,wide chest,wide shoulder,wide pelvis and middle leg were the main body types of Chinese female population.This showed that the characteristics of Chinese ethnic groups had obvious consistency.The consistency of Chinese group features was related to its close origin.It should be said that Han nationality played an important role in the process of communication and integration of various ethnic groups in China.In the history of the Han nationality,there had been many large-scale population migration.The southern movement of the northern ethnic minorities into the northern Han and the southward movement of the northern Han into the south promoted the formation of the Southern Han,which made the southern Han and the northern Han had similar body features,and also promoted the southern ethnic minorities into the southern Han.In addition,the Han nationality who moved into minority areas also gradually integrated into minority areas.Conclusion There are obvious commonalities in Chinese ethnic groups.

Objective To study the correlation of anti-C1q antibodies with active systemic lupus erythematosus(SLE)and lupus nephritis(LN)in children,as well as their diagnostic value for active SLE and LN.Methods A retrospective selection of 90 hospitalized children with SLE at the Children's Medical Center of Second Xiangya Hospital,Central South University from January 2016 to March 2019 as the SLE group,all of whom were tested for anti-C1q antibodies.A control group was formed by collecting 70 hospitalized children with other autoimmune diseases(OAD)during the same period.The differences in anti-C1q antibody levels were compared between two groups.The correlation of anti-C1q antibodies with various indicators of SLE and LN was analyzed,and the diagnostic value of anti-C1q in SLE and LN was evaluated.Results The serum levels of anti-C1q antibodies in the SLE group were higher than those in the OAD group(P<0.05).The SLE disease activity index score was positively correlated with anti-C1q antibodies(rs=0.371,P<0.001)and positively correlated with anti-double-stranded DNA antibodies(rs=0.370,P<0.001).The sensitivity and specificity of anti-C1q antibodies for diagnosing active SLE were 89.90%and 53.90%,respectively,with an area under the curve of 0.720(P<0.05)and a critical value of 5.45 U/mL.The sensitivity and specificity of anti-C1q antibody levels for diagnosing active LN were 58.50%and 85.00%,respectively,with an area under the curve of 0.675(P<0.05)and a critical value of 22.05 U/mL.Conclusions Anti-C1q antibodies can serve as non-invasive biomarkers for evaluating the activity of SLE or predicting the activity of LN in children.

Near infrared spectroscopy(NIRS)technology combined with chemometrics algorithms has been widely used in quantitative and qualitative analysis of food and medicine.However,traditional chemometrics methods,especially linear classification methods,often yield unsatisfactory results when addressing multi-class classification problems.Convolutional neural network(CNN)is adept at extracting deep-level features from data and suitable for handling non-linear relationships.The modeling performance of CNN depends on the size and diversity of sample,while the collection and preprocessing of NIRS sample data is often time-consuming and labor-intensive.This study proposed a NIRS qualitative analysis method based on data augmentation strategies and CNN.The data augmentation strategy included two steps.Firstly,applying Bootstrap resampling and generative adversarial network(GAN)methods to augment three NIRS datasets(Medicine,coffee and grape).Secondly,combining the original samples(Y)with the Bootstrap augmented samples(B)and GAN augmented samples(G)to obtain three augmented datasets(Y-B,Y-G and Y-B-G).Based on this,a CNN model structure suitable for these datasets was designed,consisting of 2 one-dimensional convolutional layers,1 max-pooling layer,and 1 fully connected layer.The results showed that compared to the optimal models of partial least squares discriminant analysis(PLS-DA),support vector machine(SVM),and back propagation neural network(BP),the CNN model based on Y-B dataset achieved average accuracy improvements of 3.998%,9.364%,and 4.689%for medicine(Binary classification);the CNN model based on the Y-B-G dataset achieved average accuracy improvements of 6.001%,2.004%,and 7.523%for coffee(7-class classification);and the CNN model based on the Y-B dataset achieved average accuracy improvements of 33.408%,51.994%,and 34.378%for grapes(20-class classification).It was evident that the models established based on data augmentation strategies and CNN demonstrated better classification accuracy and generalization performance with different datasets and classification categories.