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*

This study selected 6 529 plant-based Chinese materia medica(PCMM) from Chinese Materia Medica as research subjects and applied a random permutation test to explore the overall correlation characteristics between nature and flavor, as well as the correlation characteristics after distinguishing different medicinal parts and harvest seasons. The results showed that the overall correlation characteristics between nature and flavor in PCMM were significantly associated in the following pairs: cold and bitter, cool and bitter, cool and astringent, cool and light, neutral and sweet, neutral and astringent, neutral and light, neutral and sour, hot and pungent, and warm and pungent. When analyzing the data by distinguishing medicinal parts and/or harvest seasons, new correlation patterns emerged, characterized by the disappearance of some significant correlations and the emergence of new ones. When analyzing by medicinal parts alone, significant correlations were found in the following cases: cold and light in leaves, cold and salty in barks, cool and sweet in fruits and seeds, neutral and pungent in whole herbs, neutral and salty in stems, and warm and salty in flowers. However, no significant correlations were found between cool and bitter in stems and other types of herbs, cool and astringent in fruits, seeds, flowers, and other types of herbs, cool and light in leaves, fruits, seeds, barks, flowers and other types of herbs, neutral and sweet in barks, neutral and astringent in whole herbs and stems, neutral and light in leaves, fruits, seeds, and flowers, neutral and sour in whole herbs, stems, barks, flowers, and other types of herbs, and hot and pungent in whole herbs, stems, flowers, and other types of herbs. When analyzing by harvest season alone, significant correlations were found in the following cases: cold and salty, and cool and sour in herbs harvested in winter, and neutral and salty in herbs harvested year-round. However, no significant correlation was found between cool and light in herbs harvested in winter. When considering both medicinal parts and harvest seasons, compared to the independent influence of medicinal parts, 14 new significant correlations emerged(e.g., the correlation between cool and bitter in stems harvested in spring), while 53 previously significant correlations disappeared(e.g., the correlation between cool and bitter in barks harvested in summer). Compared to the independent influence of harvest seasons, 11 new significant correlations appeared(e.g., the correlation between cold and light in barks harvested in autumn), while 50 previously significant correlations disappeared(e.g., the correlation between hot and pungent in leaves harvested in winter). This study is the first to reveal the influence of medicinal parts and harvest seasons on the correlation between nature and flavor in PCMM, which highlights that these two factors can interact and jointly affect nature-flavor correlations. Further research is needed to explore the underlying mechanisms. This study provides a deeper understanding of the inherent scientific connotations of herbal properties and offers a theoretical foundation for the cultivation and harvesting of PCMM.
Seasons ; Plants, Medicinal/growth & development* ; Drugs, Chinese Herbal/chemistry* ; Taste

OBJECTIVE: To investigate the clinical characteristics and prognosis of primary pulmonary lymphoma (PPL). METHODS: The clinical data of 17 patients with PPL admitted to Gansu Provincial Hospital from January 2013 to June 2023 were collected, and their clinical characteristics and prognosis were retrospectively analyzed and summarized. RESULTS: The median age of the 17 patients was 56 (29-73) years old. There were 8 males and 9 females. According to Ann Arbor staging system, there were 9 patients with stage I-II and 8 patients with stage III-IV. There were 14 patients with IPI score of 0-2 and 3 patients with IPI score of 3-4. All 17 patients had symptoms at the initial diagnosis, most of the first symptoms were cough, and 6 patients had B symptoms.Among the 17 patients, there were 8 cases of diffuse large B-cell lymphoma (DLBCL), 5 cases of mucosa-associated lymphoid tissue (MALT) lymphoma, 1 case of gray zone lymphoma (GZL), and 3 cases of Hodgkin's lymphoma (HL). 15 patients received chemotherapy, of which 3 cases received autologous hematopoietic stem cell transplantation(ASCT) and 3 cases received radiotherapy; 2 patients did not receive treatment. The median number of chemotherapy courses was 6(2-8). The short-term efficacy was evaluated, 12 patients achieved complete remission (CR) and 3 patients achieved partial remission (PR). The age, pathological subtype, sex, Ann Arbor stage, β₂-microglobulin(β₂-MG) level, lactate dehydrogenase(LDH) level were not correlated with CR rate (P >0.05), while IPI score was correlated with recent CR rate (P < 0.05 ). The median follow-up time was 31(2-102) months. One of the 12 CR patients died of COVID-19, and the rest survived. Among the 3 patients who did not reach CR, 1 died after disease progression, while the other 2 survived. One of the 2 untreated patients died one year after diagnosis. Both the median progression-free survival (PFS) time and overall survival (OS) time of the 17 patients were both 31 (2-102) months. CONCLUSION The incidence of PPL is low, and the disease has no specific clinical manifestations, which is easily missed and misdiagnosed. The pathological subtypes are mainly MALT lymphoma and DLBCL, and the treatment is mainly combined chemotherapy. The IPI score is related to the treatment efficacy.
Humans ; Middle Aged ; Male ; Female ; Adult ; Prognosis ; Aged ; Lung Neoplasms/therapy* ; Retrospective Studies ; Neoplasm Staging ; Lymphoma/therapy* ; Lymphoma, Large B-Cell, Diffuse

Objective:To study genotype analysis and influence factors analysis of hepatitis B virus(HBV)deoxyribonucleic acid(DNA)positive samples of negative hepatitis B surface antigen(HBsAg)donors in blood donors without compensation in Nan'an area.Methods:A total of 62,000 HBsAg fast-screened blood donor samples from January 2021 to June 2024 were selected as the study objects.HBV infection,viral load and genotype of HBV DNA positive samples,single factor and influencing factor of HBV DNA positive samples were detected and analyzed.Results:Among the 62000 HBsAg fast-screened blood donor samples,the results were negative by HBsAg screening,moreover,285 cases(0.46％)were HBsAg positive and 61715 cases(99.54％)were negative.NAT positive 180 cases and 118 cases were positive for HBV DNA.The HBV DNA positive rate of HBsAg negative donors was 0.19％(118/62000).HBV DNA of the viral load of positive specimens with＜20 IU/mL was higher than those with 20 to 99 IU/mL and ≥ 100 IU/mL(P＜0.05).HBV DNA of C style of the genotype of positive specimens was higher than B style and unsamples(P＜0.05).Univariate analysis found that HBV DNA positivity was mainly related to the history of intravenous drug use and risky sexual behavior,as well as the history of hepatitis B vaccination and blood transfusion(P＜0.05).According to the Logistic regression analysis,history of intravenous drug use and risky sexual behavior,and blood transfusion were risk factors for positive HBV DNA(OR＞1,P＜0.05),vaccination of hepatitis B vaccine was a protective factor for HBV DNA positivity(OR＜1,P＜0.05).Conclusion:The proportion of HBsAg in Nan'an area is relatively high,but there are still a small number of positive samples,the main genotype was type C,and history of intravenous drug use and risky risk behaviors,as well as history of blood transfusion were all risk factors for positive HBV DNA,vaccination of hepatitis B vaccine is protective factor for HBV DNA positivity.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To investigate influencing factors of textbook outcome(TO)in patients with pancreatic ductal adenocarcinoma undergoing minimally invasive pancreaticoduodenectomy(MIPD).Methods A retrospective analysis was conducted on the clinical data of 101 cases of pancreatic ductal adenocarcinoma treated with MIPD in our hospital from January 2020 to December 2022.According to the inclusion and exclusion criteria,89 cases were ultimately included in this study,of which 61 cases reached TO(TO group)and 28 cases did not reach TO(non-TO group).Variables with P<0.05 in univariate analysis were included in multivariate logistic regression analysis to identify independent prognostic factors of TO.Results Univariate analysis showed that there were significant differences in pancreatic duct dilation>3 mm,preoperative neutrophil lymphocyte ratio(NLR),extended hospital stay,postoperative hospitalstay,and drain fluid amylase(DFA)>1100 U/L at1-3 d aftersurgery(P<0.05).Multivariate logistic regression analysis showed that the independent prognostic factors affecting TO were:pancreatic duct dilation>3 mm(OR=7.290,95%CI:1.485-35.786,P=0.014),postoperative hospital stay(OR=0.862,95%CI:0.751-0.989,P=0.034),and the DFA on the first postoperative day>1100 U/L(OR=0.052,95%CI:0.005-0.545,P=0.014).Conclusions The outcome of TO in patients after MIPD is not related to the surgical approach(robot assisted minimally invasive pancreaticoduodenectomy or laparoscopic pancreaticoduodenectomy).Pancreatic duct dilation>3 mm,postoperative hospital stay,and DFA on the first postoperative day>1100 U/L are independent prognostic factors of TO after MIPD in patients with pancreatic ductal adenocarcinoma.

Objective:To predict very early recurrence after radical resection in patients with pancreatic head cancer by combining preoperative enhanced CT imaging findings and clinicopathological features.Methods:The clinicopathological and preoperative enhanced CT imaging features of 241 patients who underwent radical pancreaticoduodenectomy at Peking University Third Hospital from Jan 2010 to Dec 2022 were retrospectively collected and analyzed.Results:Using recurrence within 3 months after surgery as the definition for very early recurrence, 49 out of 241 patients experienced very early recurrence. Multivariate analysis showed that preoperative BMI<18.5 kg/m2( P=0.040), rim enhancement( P=0.028), lymphovascular invasion( P<0.001), and poor tumor differentiation ( P=0.013) were independent risk factors for very early recurrence. Conclusion:Enhanced CT imaging features combined with clinicopathological characteristics can predict very early recurrence after resection of pancreatic head cancer.