This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

Elemental imaging analysis based on laser induced-breakdown spectroscopy(LIBS)can provide significant reference value for oil and gas exploration activities.Improving the scanning speed and spatial resolution of LIBS elemental imaging analysis instruments contributes to enhancing the efficiency of mineral surface elemental analysis,which is crucial for achieving in-situ,real-time,and rapid LIBS analysis.In this study,a high-speed scanning LIBS elemental imaging analysis instrument was developed based on a scanning mirror device,achieving a scanning speed of 100 Hz and a spatial resolution of 50 μm.The stability of spectral data collected by this instrument was validated using aluminum alloy standard samples with uniform elemental distribution.The experimental results showed that the relative standard deviations(RSD)of the spectral data collected at different locations were 2.76％,2.79％,2.35％and 2.55％,respectively,demonstrating that the instrument's performance met analysis requirements.Analysis of spectral acquisition channels led to the selection of the 337-595 nm spectral range.Imaging analysis of major elements on the surface of meteorite mineral samples with complex matrices was conducted using this instrument,coupled with a multi-element imaging algorithm enabling visualization analysis of four major elements on the same image.The results revealed a higher level of detail and complexity in element distribution.The study demonstrated that this instrument,combined with multi-element imaging analysis algorithms,could provide crucial technical support for rapid imaging of element distribution in minerals at a microscopic scale during geological research.

Objective The volume and cortical thickness of gray matter in patients with multiple sclerosis (MS) and neuromyelitis optica (NMO) were compared and analyzed by voxel⁃based morphometry (VBM) and surface⁃based morphometry (SBM), and the differences in the structural changes of gray matter in the two diseases were discussed. Methods A total of 21 MS patients, 16 NMO patients and 19 healthy controls were scanned by routine MRI sequence. The data were processed and analyzed by VBM and SBM method based on the statistical parameter tool SPM12 of Matlab2014a platform and the small tool CAT12 under SPM12. Results Compared with the normal control group (NC), after Gaussian random field (GRF) correction, the gray matter volume in MS group was significantly reduced in left superior occipital, left cuneus, left calcarine, left precuneus, left postcentral, left central paracentral lobule, right cuneus, left middle frontal, left superior frontal and left superior medial frontal (P<0. 05). After family wise error (FWE) correction, the thickness of left paracentral, left superiorfrontal and left precuneus cortex in MS group was significantly reduced (P<0. 05). Compared with the NC group, after GRF correction, the gray matter volume in the left postcentral, left precentral, left inferior parietal, right precentral and right middle frontal in NMO group was significantly increased (P<0. 05). In NMO group, the volume of gray matter in left middle occipital, left superior occipital, left inferior temporal, right middle occipital, left superior frontal orbital, right middle cingulum, left anterior cingulum, right angular and left precuneus were significantly decreased (P<0. 05). Brain regions showed no significant differences in cortical thickness between NMO groups after FWE correction. Compared with the NMO group, after GRF correction, the gray matter volume in the right fusiform and right middle frontal in MS group was increased significantly(P<0. 05). In MS group, the gray matter volume of left thalamus, left pallidum, left precentral, left middle frontal, left middle temporal, right pallidum, left inferior parietal and right superior parietal were significantly decreased (P<0. 05). After FWE correction, the thickness of left inferiorparietal, left superiorparietal, left supramarginal, left paracentral, left superiorfrontal and left precuneus cortex in MS group decreased significantly (P<0. 05). Conclusion The atrophy of brain gray matter structure in MS patients mainly involves the left parietal region, while NMO patients are not sensitive to the change of brain gray matter structure. The significant difference in brain gray matter volume between MS patients and NMO patients is mainly located in the deep cerebral nucleus mass.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
Humans ; Angioedemas, Hereditary/drug therapy*

As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
Humans ; Angioedemas, Hereditary/drug therapy*

OBJECTIVE To explore the efficacy of Sour Jujube Seed Decoction combined with Huanglian Wendan Decoction on adult chronic insomnia and its effect on hypnotic withdrawal.METHODS 187 patients with chronic insomnia were included for anal-ysis,including 102 in the traditional Chinese medicine(TCM)group and 85 in the western medicine group.The TCM group was trea-ted with Sour Jujube Seed Decoction combined with Huanglian Wendan Decoction,while the western medicine group was treated with benzodiazepine under the consideration of doctor.The intervention period was 1 month,with assessments using the Pittsburgh Sleep Quality Index(PSQI)conducted before and after the intervention.Follow-up evaluations were performed at 3 months and 6 months re-spectively after the intervention.RESULTS There was no significant difference between the two groups at baseline.After the inter-vention,the PSQI scores of patients in both groups were significantly improved(P<0.01).Among them,the TCM group was better than the western medicine group in the improvement of sleep quality and sleeping pills,total PSQI score reduction(P<0.01).The re-sults of linear regression analysis showed that after controlling for confounding factors,the regression coefficients of the TCM group in two different models were1.821 and 1.922 respectively,and the former was statistically significant(P<0.05).By screening patients who took hypnotics at baseline in the TCM group and comparing them with those in the western medicine group,the influencing factors of hypnotic withdrawal were analyzed.During the 3-month follow-up,25 out of 39 patients in the TCM group and 17 out of 80 patients in the western medicine group had hypnotic withdrawal(χ2= 19.25,P<0.001);during the 6-month follow-up,23 of the 39 patients in the TCM group and 18 of the 79 patients in the western medicine group had hypnotic withdrawal(χ2= 13.53,P<0.001),the with-drawal rate of patients in the TCM group was significantly higher than that in the western medicine group.Further regression analysis showed that after adjusting for confounding factors,the results showed that the western medicine group had a significantly higher rate of not withdrawal than the TCM group at 3 months(OR=5.50,95%CI:2.30～13.72)and 6 months(OR=6.43,95%CI:2.54～17.77),and the results were statistically different(P<0.05).CONCLUSION Sour Jujube Seed Decoction combined with Huangli-an Wendan Decoction is effective in treating adult chronic insomnia and assisting in hypnotic withdrawal.

Aim To determine the effect of histamine H

Valencene, a kind of sesquiterpenoid with a citrus flavor, is mainly found in Valencia orange and is commonly used in cosmetics and food additives, as well as industrial synthetic nootkatone. In this study, synthetic biology was used to create a Saccharomyces cerevisiae cell factory to produce valencene. Fistly, valencene synthase gene (CnVS) from Callitropsis nootkatensis was inserted into the chromosome of the chassis strain YTT-T5. The resulting strain VAL-01 could produce 1.1 mg·L^-1 valencene. Protein fusion technique was used, different valencene synthases were compared and the copy number of key genes was adjusted, yielding valencene to 436.4 mg·L^-1. Then, knocking-out the transcription factor ROX1 resulted in valencene improvement by 17.4%. Moreover, the induction system of galactose was regulated, transcription factor PDR3 and INO2 were overexpressed. The engineered strain VAL-10 could produce 2 798.6 mg·L^-1 valencene by high cell density fermentation method (nearly 2 500 times higher than VAL-01). This study provides a basis for green production of valencene.

Patchoulol is an important sesquiterpenoid in the volatile oil of Pogostemon cablin, and is also considered to be the main contributing component to the pharmacological efficacy and fragrance of P. cablin oil, which has antibacterial, antitumor, antioxidant, and other biological activities. Currently, patchoulol and its essential oil blends are in high demand worldwide, but the traditional plant extraction method has many problems such as wasting land and polluting the environment. Therefore, there is an urgent need for a new method to produce patchoulol efficiently and at low cost. To broaden the production method of patchouli and achieve the heterologous production of patchoulol in Saccharomyces cerevisiae, the patchoulol synthase(PS) gene from P. cablin was codon optimized and placed under the inducible strong promoter GAL1 to transfer into the yeast platform strain YTT-T5, thereby obtaining strain PS00 with the production of(4.0±0.3) mg·L~(-1) patchoulol. To improve the conversion rate, this study used protein fusion method to fuse SmFPS gene from Salvia miltiorrhiza with PS gene, leading to increase the yield of patchoulol to(100.9±7.4) mg·L~(-1) by 25-folds. By further optimizing the copy number of the fusion gene, the yield of patchoulol was increased by 90% to(191.1±32.7) mg·L~(-1). By optimizing the fermentation process, the strain was able to achieve a patchouli yield of 2.1 g·L~(-1) in a high-density fermentation system, which was the highest yield so far. This study provides an important basis for the green production of patchoulol.
Saccharomyces cerevisiae/metabolism* ; Sesquiterpenes/metabolism* ; Pogostemon ; Oils, Volatile/metabolism*