Processing for deodorization is widely used in the production of animal-derived Chinese medicinal materials. In this study, Heracles Neo ultra-fast gas-phase electronic nose combined with chemometrics was employed to analyze the overall odor difference of Cervi Cornu Pantotrichum(focusing on that derived from Cervus nippon Temminck in this study) before and after processing. The results showed that the electronic nose effectively distinguished between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. HS-GC-MS was used to identify and quantify the volatile components in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum, and 35 and 37 volatile components were detected in the medicinal materials and decoction pieces, respectively. The medicinal materials and decoction pieces contained 28 common volatile components contributing to the odor of Cervi Cornu Pantotrichum. The odor activity value(OAV) of each volatile component was calculated based on the olfactory threshold and relative content. The results showed that there were 17 key odor substances such as isovaleraldehyde, 2-methylbutanal, isobutyraldehyde, hexanal, and methanethiol in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. All of them had bad odor and were the main source of the odor of Cervi Cornu Pantotrichum. The results of principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) showed that there were significant differences in volatile components between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. Based on the thresholds of P<0.05 and Variable Importance in Projection(VIP)>1, 21 differential volatile odor components were screened out. Among them, isopentanol, isovaleraldehyde, 2-methylbutanal, n-nonanal, and dimethylamine were the key differential odor compounds between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. The odor compounds and their relative content reduced, and some flavor substances such as esters were produced after processing with wine, which was the main reason for the reduction of the odor after processing of Cervi Cornu Pantotrichum.
Odorants/analysis* ; Electronic Nose ; Gas Chromatography-Mass Spectrometry/methods* ; Animals ; Volatile Organic Compounds/analysis* ; Deer ; Drugs, Chinese Herbal/chemistry*

Objective Based on 25 indicators including immune factors, cell count classification, and smear results of the knee joint fluid, machine learning models were established to distinguish between osteoarthritis (OA) and rheumatoid arthritis (RA). Methods 100 OA and 40 RA patients scheduled for total knee arthroplasty were enrolled respectively. Each patient's knee joint fluid was collected preoperatively. Nucleated cells were counted and classified. The expression levels of immune factors, including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), IL-6, IL-8, IL-15, matrix metalloproteinase 3 (MMP3), MMP9, MMP13, rheumatoid factor (RF), serum amyloid A (SAA), C-reactive protein (CRP), and others were measured. Smears and microscopic classification of all the immune factors were performed. Independent influencing factors for OA or RA were identified using univariate binary logistic regression, Lasso regression, and multivariate binary logistic regression. Based on the independent influencing factors, three machine learning models were constructed which are logistic regression, random forest, and support vector machine. Receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to evaluate and compare the models. Results A total of 5 indicators in the knee joint fluid were screened out to distinguish OA and RA, which were IL-1β(odds ratio(OR)=10.512, 95× confidence interval (95×CI) was 1.048-105.42, P=0.045), IL-6 (OR=1.007, 95×CI was 1.001-1.014, P=0.022), MMP9 (OR=3.202, 95×CI was 1.235-8.305, P=0.017), MMP13 (OR=1.002, 95× CI was 1-1.004, P=0.049), and RF (OR=1.091, 95×CI was 1.01-1.179, P=0.026). According to the results of ROC, calibration curve and DCA, the accuracy (0.979), sensitivity (0.98) and area under the curve (AUC, 0.996, 95×CI was 0.991-1) of the random forest model were the highest. It has good validity and feasibility, and its distinguishing ability is better than the other two models. Conclusion The machine learning model based on immune factors in the knee joint fluid holds significant value in distinguishing OA and RA. It provides an important reference for the clinical early differential diagnosis, prevention and treatment of OA and RA.
Humans ; Arthritis, Rheumatoid/metabolism* ; Machine Learning ; Male ; Female ; Middle Aged ; Aged ; Synovial Fluid/immunology* ; Osteoarthritis, Knee/metabolism* ; Knee Joint/metabolism* ; ROC Curve ; Diagnosis, Differential

AIM To study the chemical constituents from the sticks and leaves of Croton cascarilloides Raeusch.and their biological activities.METHODS The 95％ethanol extract from the sticks and leaves of C.cascarilloides was isolated and purified by MCI,silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.LPS-induced NO RAW264.7 cell model induced by LPS was used to evaluate its anti-inflammatory activity in vitro.GES-1 injury model induced by taurocholic acid was used to screen the gastric mucosal protection activity.RESULTS Fourteen compounds were isolated and identified as bullatantriol(1),(-)-boscialin(2),(+)-dehydrovomifoliol(3),3-(hydroxylacetyl)-indole(4),pinoresinol(5),3,7-dimethyl-octa-1,7-diene-3,6-ol(6),(+)-syringaresinol(7),curcasinlignan B(8),cleomiscosin C(9),cleomiscosinD(10),2,6-dimethyl-octa-1,7-dien-3,6-diol(11),vanillin(12),vanillic acid(13),methyl vanillate(14).Compound 4 had certain anti-inflammatory activity,with IC50 values of 73.62 μmol/L.The protective rates of 25 μmol/L compounds 1-4,6,9-12 and 14 on gastric mucosal epithelial cells were 30.07％,34.18％,23.91％,30.92％,17.51％,19.69％,31.76％,22.46％,30.56％and 14.49％,respectively.CONCLUSION Compounds 1-14 are isolated from this plant for the first time.Compound 4 shows anti-inflammatory activity,1-4,6,9-12 and 14 show different degrees of gastric mucosal epithelial cell protective activity.

AIM To study the chemical constituents from the stems and leaves of Dendrobium formosum Roxb.ex Lindl.and their biological activities.METHODS The 95％ethanol extract from the stems and leaves of D.formosum was isolated and purified by silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their inhibitory activities onα-glucosidase were determined by PNPG method,and their in vitro anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Fifteen compounds were isolated and identified as coniferyl p-coumarate(1),(-)-pinoresinol(2),2,5,7-trihydroxy-4-methoxy-9,10-dihydrophenanthrene(3),naringenin(4),spiropreussomerin A(5),7-hydroxy-14-de-O-methyl-lasiodiplodin(6),(4S,5S,6Z,8E)-5-hydroxydeca-6,8-dien-4-olide(7),(6S,9R)-blumenol C(8),p-hydroxybenzoic acid(9),m-hydroxybenzoic acid(10),p-hydroxy benzenepropanoic acid(11),5,7-dihydroxy-isobenzofuran(12),2-(4-hydroxyphenyl)-ethanol(13),β-sitostenone(14),β-sitosterol(15).The IC50 values of compounds 1 and 4 on α-glucosidase inhibition were(65.60±3.31)and(98.95±2.53)μmol/L,respectively.Compound 3 presented inhibitory activity on NO production in RAW 264.7 cells,with IC50 value of(3.97±0.12)μmol/L.CONCLUSION Compounds 5-6,8 and 12 are isolated from Orchidacae family for the first time,and 2-15 are first isolated from this plant.Compounds 1 and 4 have α-glucosidase inhibitory activities,and 3 has anti-inflammatory activity.

AIM To study the chemical constituents from the stems and leaves of Dendrobium formosum Roxb.ex Lindl.and their biological activities.METHODS The 95％ethanol extract from the stems and leaves of D.formosum was isolated and purified by silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their inhibitory activities onα-glucosidase were determined by PNPG method,and their in vitro anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Fifteen compounds were isolated and identified as coniferyl p-coumarate(1),(-)-pinoresinol(2),2,5,7-trihydroxy-4-methoxy-9,10-dihydrophenanthrene(3),naringenin(4),spiropreussomerin A(5),7-hydroxy-14-de-O-methyl-lasiodiplodin(6),(4S,5S,6Z,8E)-5-hydroxydeca-6,8-dien-4-olide(7),(6S,9R)-blumenol C(8),p-hydroxybenzoic acid(9),m-hydroxybenzoic acid(10),p-hydroxy benzenepropanoic acid(11),5,7-dihydroxy-isobenzofuran(12),2-(4-hydroxyphenyl)-ethanol(13),β-sitostenone(14),β-sitosterol(15).The IC50 values of compounds 1 and 4 on α-glucosidase inhibition were(65.60±3.31)and(98.95±2.53)μmol/L,respectively.Compound 3 presented inhibitory activity on NO production in RAW 264.7 cells,with IC50 value of(3.97±0.12)μmol/L.CONCLUSION Compounds 5-6,8 and 12 are isolated from Orchidacae family for the first time,and 2-15 are first isolated from this plant.Compounds 1 and 4 have α-glucosidase inhibitory activities,and 3 has anti-inflammatory activity.

AIM To study the chemical constituents from the sticks and leaves of Croton cascarilloides Raeusch.and their biological activities.METHODS The 95％ethanol extract from the sticks and leaves of C.cascarilloides was isolated and purified by MCI,silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.LPS-induced NO RAW264.7 cell model induced by LPS was used to evaluate its anti-inflammatory activity in vitro.GES-1 injury model induced by taurocholic acid was used to screen the gastric mucosal protection activity.RESULTS Fourteen compounds were isolated and identified as bullatantriol(1),(-)-boscialin(2),(+)-dehydrovomifoliol(3),3-(hydroxylacetyl)-indole(4),pinoresinol(5),3,7-dimethyl-octa-1,7-diene-3,6-ol(6),(+)-syringaresinol(7),curcasinlignan B(8),cleomiscosin C(9),cleomiscosinD(10),2,6-dimethyl-octa-1,7-dien-3,6-diol(11),vanillin(12),vanillic acid(13),methyl vanillate(14).Compound 4 had certain anti-inflammatory activity,with IC50 values of 73.62 μmol/L.The protective rates of 25 μmol/L compounds 1-4,6,9-12 and 14 on gastric mucosal epithelial cells were 30.07％,34.18％,23.91％,30.92％,17.51％,19.69％,31.76％,22.46％,30.56％and 14.49％,respectively.CONCLUSION Compounds 1-14 are isolated from this plant for the first time.Compound 4 shows anti-inflammatory activity,1-4,6,9-12 and 14 show different degrees of gastric mucosal epithelial cell protective activity.

Objective To analyze the combined effect of body mass index(BMI)and age with cancer occurrence among a hypertensive population in Minhang District,Shanghai.Methods Participants of this study were 212 394 hypertensive patients without cancer in Minhang District,Shanghai,registered in the electronic health information system from 2007 to 2015.Age and BMI were included as smoothing functions in the generalized additive Cox proportional risk model.The bivariate response model was constructed to visualize results using surface plots and to comprehensively analyze the association of BMI and age with the risk of cancer occurrence.Results A total of 22 141 participants developed cancer by Dec 31,2018.The association between age and the risk of cancer incidence showed an overall linear trend while the association between BMI and the risk of cancer incidence showed an overall"U"shape.BMI at about 26 kg/m2 showed the lowest risk of cancer incidence.The risk of cancer occurrence increased with increasing age in people with different BMIs.The associations between BMI and the risk of cancer incidence were different at different age groups:there was no significant association between BMI and the risk of cancer incidence in the young people(20-44 years).While in the middle-aged and older people aged over 45 years,BMI was associated with the risk of cancer incidence in a"U"shape.The lowest risk of cancer incidence was around the BMI of 26 kg/m2.Conclusion BMI among the population with hypertension should be controlled in a reasonable range,especially in the middle-aged and older population,to prevent cancer occurrence.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective:To explore the effects of the core symptoms of attention deficit hyperactivity disorder (ADHD) and behavior problems on the sleep of children with ADHD and their correlation.Methods:In this cross-sectional study, a total of 289 children aged 6-12 years with ADHD who visited the Outpatient Department of the Center for Cognition and Sleep at the People′s Hospital of Guangxi Zhuang Autonomous Region from June 2021 to December 2022 were selected.The Swanson, Nolan and Pelham Rating Scale Ⅳ was used to assess ADHD core symptoms (attention deficit and hyperactivity-impulsivity), the Conners Parent Symptom Questionnaire was used to assess behavior problems (conduct, learning, psychosomatic symptoms, and anxiety), and the Sleep Disturbance Scale for Children (SDSC) was used to assess sleep.Multivariate Logistic regression, multivariate linear regression, and path analysis were performed for statistical analysis of the data.Results:Multivariate Logistic regression analysis showed that after controlling age, gender, verbal intelligence quotient and performance intelligence quotient, attention deficit ( P=0.008, OR=2.60, 95% CI: 1.28-5.28), psychosomatic symptoms ( P=0.027, OR=6.77, 95% CI: 1.24-36.93) and anxiety ( P=0.013, OR=3.96, 95% CI: 1.43-11.67) increased the risk of sleep disturbances in children with ADHD (SDSC score >39 points).Path analysis showed that attention deficit ( β=0.244, P=0.001), psychosomatic symptoms ( β=0.114, P=0.046) and anxiety ( β=0.216, P<0.001) directly affected the SDSC score.Hyperactivity-impulsivity indirectly affected the SDSC score through psychosomatic symptoms ( β=0.142, P=0.039), and attention deficit indirectly affected the SDSC score through anxiety ( β=0.321, P<0.001). Conclusions:The severer the core symptoms of ADHD and behavior problems are, the higher the degree of sleep disturbances in children with ADHD is.Psychosomatic symptoms and anxiety are directly associated with the sleep disturbances of ADHD children.Attention deficit has direct or anxiety-mediated indirect impact on the sleep of ADHD children.Hyperactivity-impulsivity indirectly affects the sleep of children with ADHD through psychosomatic symptoms.