In Vitro and In Silico Pharmacological and Cosmeceutical Potential of Ten Essential Oils from Aromatic Medicinal Plants from the Mascarene Islands.

In this study, 10 essential oils (EOs), from nine plants (Cinnamomum camphora, Curcuma longa, Citrus aurantium, Morinda citrifolia, Petroselinum crispum, Plectranthus amboinicus, Pittosporum senacia, Syzygium coriaceum, and Syzygium samarangense) were assessed for their antimicrobial, antiaging and antiproliferative properties. While only S. coriaceum, P. amboinicus (MIC: 0.50 mg/mL) and M. citrifolia (MIC: 2 mg/mL) EOs showed activity against Cutibacterium acnes, all EOs except S. samarangense EO demonstrated activity against Mycobacterium smegmatis (MIC: 0.125-0.50 mg/mL). The EOs were either fungistatic or fungicidal against one or both tested Candida species with minimum inhibitory/fungicidal concentrations of 0.016-32 mg/mL. The EOs also inhibited one or both key enzymes involved in skin aging, elastase and collagenase (IC50: 89.22-459.2 µg/mL; 0.17-0.18 mg/mL, respectively). Turmerone, previously identified in the C. longa EO, showed the highest binding affinity with the enzymes (binding energy: -5.11 and -6.64 kcal/mol). Only C. aurantium leaf, C. longa, P. amboinicus, P. senacia, S. coriaceum, and S. samarangense EOs were cytotoxic to the human malignant melanoma cells, UCT-MEL1 (IC50: 88.91-277.25 µg/mL). All the EOs, except M. citrifolia EO, were also cytotoxic to the human keratinocytes non-tumorigenic cells, HaCat (IC50: 33.73-250.90 µg/mL). Altogether, some interesting therapeutic properties of the EOs of pharmacological/cosmeceutical interests were observed, which warrants further investigations.

[Identification of critical process parameters of Jinqing alcohol precipitation of Reduning Injection by big data].

Lonicerae Japonicae Flos and Artemisiae Annuae Herba(LA or Jinqing) alcohol precipitation has various process parameters and complex process mechanism, and is one of the key units for manufacturing Reduning Injection. In order to identify the critical process parameters(CPPs) affecting the weight of the extract produced from the alcohol precipitation process, 259 batches of historical production data from 2017 to 2018 were collected, with a total of 829 318 data points. These data showed characteristics of large data, such as a large data volume, a low value density, and diverse sources. The data cleaning and feature extraction were first performed, and 48 feature variables were selected. The original data points were reduced to 9 936. Then, a combination of Pearson correlation analysis and grey correlation analysis were used to screen out 15 potential critical process parameters(pCPPs). After that, the partial least squares(PLS) was used in prediction of the weight of the extract, proving that the performance of predictive model based on 15 pCMAs is equivalent to that of predictive model based on 48 feature variables. The variable importance in projection(VIP) index was used to identify 9 CPPs, including 2 alcohol precipitation supernatant volume parameters, 4 initial extract weight parameters and 3 added alcohol volume parameters. As a result, the number of data points was 1 863, accounting for 0.28% of the original data. The big data analysis approach from a holistic point of view can effectively increase the value density of the original data. The critical process parameters obtained can help to accurately describe the quality transfer mechanism of the Jinqing alcohol precipitation process.

[Predictive model for hygroscopicity of contents in Guizhi Fuling Capsules].

To control the risks of powder caking and capsule shell embrittlement of Guizhi Fuling Capsules, a predictive model for hygroscopicity of contents in Guizhi Fuling Capsules was built. A total of 90 batches of samples, including raw materials, intermediate powders and capsules, were collected during the manufacturing of Guizhi Fuling Capsules. According to the production sequence, 47 batches were used as the calibration set, and the properties of raw materials and the four intermediate powders were comprehensively characterized by the physical fingerprint. Then, the partial least squares(PLS) model was developed with the content hygroscopicity as the response variable. The variable importance in projection(VIP), variance inflation factor(VIF) and regression coefficients were used to screen out potential critical material attributes(pCMAs). As a result, five pCMAs from 54 physical parameters were screened out. Furthermore, different models were built by different combinations of pCMAs, and their predictive robustness of 43 batches was evaluated on the basis of the validation set. Finally, the tap density(D_c) of wet granules obtained from wet granulation and the angle of repose(α) of raw materials were identified as the critical material attributes(CMAs) affecting the hygroscopicity of the contents of Guizhi Fuling Capsules. The prediction model established with the two CMAs as independent variables had an average relative prediction error of 2.68% for samples in the validation set, indicating a good accuracy of prediction. This paper proved the feasibility of predictive modeling toward the control of critical quality attributes of Chinese medicine oral solid dosage(OSD). The combination of the continuous quality improvement, the industrial big data and the process modeling technique paved the way for the intelligent manufacturing of Chinese medicine oral solid preparations.

[Real time release testing of disintegration time of uncoated Tianshu Tablets].

In this paper, a real time release testing(RTRT) model for predicting the disintegration time of Tianshu tablets was established on the basis of the concept of quality by design(QbD), in order to improve the quality controllability of the production process. First, 49 batches of raw materials and intermediates were collected. Afterwards, the physical quality attributes of all materials were comprehensively characterized. The partial least square(PLS) regression model was established with the 72 physical quality attributes of raw materials and intermediates as input and the disintegration time(DT) of uncoated tablets as output. Then, the variable screening was carried out based on the variable importance in the projection(VIP) indexes. Moisture content of raw materials(%HR), tapped density of wet masses(D_c), hygroscopicity of dry granules(%H), moisture content of milling granules(%HR) and Carr's index of mixed granules(IC) were determined as the potential critical material attributes(pCMAs). According to the effects of interactions of pCMAs on the performance of the prediction model, it was finally determined that the wet masses' D_c and the dry granules'%H were critical material attributes(CMAs). A RTRT model of the disintegration time prediction was established as DT=34.09+2×D_c+3.59×%H-5.29×%H×D_c,with R~2 equaling to 0.901 7 and the adjusted R~2 equaling to 0.893 3. The average relative prediction error of validation set for the RTRT model was 3.69%. The control limits of the CMAs were determined as 0.55 g·cm~(-3)<D_c<0.63 g·cm~(-3) and 4.77<%H<7.59 according to the design space. The RTRT model of the disintegration time reflects the understanding of the process system, and lays a foundation for the implementation of intelligent control strategy of the key process of Tianshu Tablets.

Primary understanding of syndrome differentiation treatment of COVID-19 with traditional Chinese medicine based on 3-5 edition of Diagnosis and Treatment of Novel Coronavirus Pneumonia and ancient literatures / 中草药

There are an increasing number of patients suffering from coronavirus disease 2019 (COVID-19) in our country and overseas. After the outbreak, the state health administrative sections have updated steadily several editions of Diagnosis and Treatment of Novel Coronavirus Pneumonia. According to the change of exposition of traditional Chinese medicine (TCM) treatment in these editions and the characteristics of cases in clinic, COVID-19 corresponds to pestilence category of TCM, which also based on the ancient literatures from the seasonal-febrile-disease subject of TCM. The disease contributes to pestilential pathogen caused by specifically regional climate characteristics of Wuhan city. It is important for COVID-19 patients to eliminate pathogens as soon as possible, which should apply defense-qi-nutrient-blood diagnosis to different courses of disease. The TCM therapy should be established according to the different organs where the virus lives and characters. In order to control the epidemic at an early date, it is necessary to consider the local conditions and use the combination of traditional Chinese and western medicine to treat COVID -19 patients.

Tea Consumption and Longitudinal Change in High-Density Lipoprotein Cholesterol Concentration in Chinese Adults.

BACKGROUND: The relation between tea consumption and age-related changes in high-density lipoprotein cholesterol (HDL-C) concentrations remains unclear, and longitudinal human data are limited. The aim of current study was to examine the relation between tea intake and longitudinal change in HDL-C concentrations. METHODS AND RESULTS: Baseline (2006) tea consumption was assessed via a questionnaire, and plasma HDL-C concentrations were measured in 2006, 2008, 2010, and 2012 among 80 182 individuals (49±12 years of age) who did not have cardiovascular diseases or cancer, or did not use cholesterol-lowering agents both at baseline (2006) and during the follow-up period (2006-2012). The associations between baseline tea consumption and rate of change in HDL-C concentrations were examined using generalized estimating equation models. Tea consumption was inversely associated with a decreased rate of HDL-C concentrations (P-trend <0.0001) in the fully adjusted model. The adjusted mean difference in the HDL-C decreased rate was 0.010 (95% confidence interval, 0.008, 0.012) mmol/L per year for tea consumers versus nonconsumers (never or less than once/month group). Interactions between tea consumption and age, sex, lifestyle scores, and metabolic syndrome (all P-interaction <0.0001) were identified. The associations between greater tea consumption and slower decrease in HDL-C concentrations were more pronounced in men, individuals aged 60 or older, individuals with a lower lifestyle score, and individuals with metabolic syndrome (all P-trend <0.0001). CONCLUSIONS: Tea consumption was associated with slower age-related decreases in HDL-C concentrations during 6 years of follow-up. CLINICAL TRIAL REGISTRATION: URL: www.chictr.org. Unique identifier: ChiCTR-TNRC-11001489.

Folic acid-conjugated silica-modified gold nanorods for X-ray/CT imaging-guided dual-mode radiation and photo-thermal therapy.

Multifunctional nanoprobes are designed to own various functions such as tumor targeting, imaging and selective therapy, which offer great promise for the future of cancer prevention, diagnosis, imaging and treatment. Herein, silica was applied to replace cetyltrimethylammonium bromide (CTAB) molecules on the surface of gold nanorods (GNRs) by the classic Stöber method, thus eliminating their cytotoxicity and improving their biocompatibility. Folic acid molecule was covalently anchored on the surface of GNRs with silane coupling agent. The resultant folic acid-conjugated silica-modified GNRs show highly selective targeting, enhanced radiation therapy (RT) and photo-thermal therapy (PTT) effects on MGC803 gastric cancer cells, and also exhibited strong X-ray attenuation for in vivo X-ray and computed tomography (CT) imaging. In conclusion, the as-prepared nanoprobe is a good candidate with excellent imaging and targeting ability for X-ray/CT imaging-guided targeting dual-mode enhanced RT and PTT.

Protein-directed solution-phase green synthesis of BSA-conjugated M(x)Se(y) (M = Ag, Cd, Pb, Cu) nanomaterials.

Bovine serum albumin (BSA)-conjugated M(x)Se(y) (M = Ag, Cd, Pb, Cu) nanomaterials with different shapes and sizes were synthesized in water at room temperature by a protein-directed, solution-phase, green synthetic method. The method features very low energy consumption and nontoxic reagents with high yields of concentrated nanoparticles. The obtained bioconjugated nanoparticles have good dispersibility, bioactivity, and biocompatibility. In addition, various functional groups of protein on the surface of the nanocrystals are suitable for further biological interactions or couplings, which is very important for further biological applications.