Objective To examine the association between the polymorphisms of brain-derived neurotrophic factor (BDNF)gene with heroin dependence.Methods Genomic DNA was isolated from the venous blood leukocytes of 308 unrelated patients with heroin dependence and 31 7 healthy individuals.Seven single nucleotide polymorphisms (SNPs)were genotyped using MassARRAY system.Data were analyzed using HaploView 4.0 and SPSS 20.0 software.Results There was a significant difference in the genotype frequency of rs6265 between heroin dependence group and healthy control group (χ2 =1 5.1 5 1,P =0.001).The rs6265 G allele was significantly higher than in controls (χ2 =9.864,P =0.002,OR =1.429,95% CI =1.143 -1.786).Furthermore,there was also a significant difference in the genotype frequency of rs13306221 between heroin dependence group and control group (χ2 =7.699,P =0.006).The rs13306221 G allele was significantly higher than in controls (χ2 =7.137,P =0.008,OR =0.539,95% CI =0.340-0.853).Strong linkage disequilibrium (LD)was observed in one block (D’> 0.9;r 2 >0.8),and significantly less G-G haplotype frequency of block 1 (χ2 =4.546;P =0.033)was found in heroin dependence group. Conclusion Our findings support the role of BDNF rs6265 and rs13306221 polymorphisms in heroin dependence and may guide future studies to identify other genetic risk factors for heroin dependence.

Objective To study the effects of Weibimei and its Chinese medicine portions(cortex frangulae, fennel powder, acorus tatarinowii, glycyrrhizae and asparagus) on cell cycle regulation in gastric cancer cells and growth inhibition in gastric cancer Xenografts.Methods Gastric cancer SGC-7901 cells were normally cultured and treated with Weibimei, extractum glycyrrhizae, cortex frangulae, fennel powder, acorus tatarinowii and asparagus.Then, the proliferation of SGC-7901 cells were detected by MTT assay, their effect on SGC-7901 cell cycle were measured by flow cytometry, and the expression of cell cycle related proteins were examined by Western blot.Animal models of SGC-7901 cells xenografts in nude mice were constructed to evaluate the growth inhibition effects of Weibimei and its Chinese medicine portions, and the expression of STAT3,p-STAT3, Cyclin D1, Bcl-2 and Survivin in gastric tumors were detected by immunohistochemical assays.Results Weibimei and its three kinds of Chinese medicine portions, cortex frangulae, fennel and acorus tatarinowii could obviously inhibit the proliferation of SGC-7901 cells, compared to control group, with a statistical significant difference (P<0.05).The cell cycle of SGC-7901 was arrested at G1 phase with cortex frangulae, fennel and acorus tatarinowii treatment, the expression of Cyclin A, B, D, E were decreased significantly (P<0.05).However, no significant effects was found in glycyrrhizae or asparagus group.Xenografts tumor sizes in Weibimei, cortex frangulae, fennel or acorus tatarinowi groups were much smaller than that in saline group or Triple Therapy group (three-kinds-drugs-combination for the treatment of gastric ulcer) (P<0.05).Xenografts experiments showed that the tumor growth in nude mice in Weibimei, cortex frangulae, fennel or acorus tatarinowi groups were significantly smaller than that in control group or in Triple Therapy Group (P<0.05), and phosphorylated STAT3, and STAT3 signaling targeted genes, including Bcl-2, Cyclin D1 and Survivin were all significantly down-regulated by immunostaining.Conclusion Weibimei and its Chinese medicine portions including cortex frangulae, fennel and acorus tatarinowii can could significantly inhibit the growth of SGC-7901 cells proliferation and arrested the cell cycle of G1 phase in vitro, and inhibit gastric cancer xenografts in nude mice in vivo.

Objective To evaluate the effect of Eucommia on hyperlipidemia and related indexes in rats, and provide animal data useful for the clinical experimental studies on hyperlipidemia.Methods Seventy-two healthy male SD rats were used in this study.One group of 12 rats fed with normal diet was chosen as normal control group, and other 60 rats were fed with high fat diet for two weeks to generate rat models of hyperlipidemia.48 of the hyperlipidemic model rats were taken and divided randomly into 4 groups, including model group, high dose Eucommia, moderate dose Eucommia, and low dose Eucommia groups.The last three groups were gavaged different dose of Eucommia, respectively.Druing this period, the other groups except the normal control group were fed with high fat diet continuously.The levels of serum TC, TG, LDL-C, and HDL-C of rats were measured on day 30 and 45.Results The serum levels of TC and LDL-C of the rats in the model group were obviously higher than those in the normal control group.The rat models of hyperlipidemia were established successfully.The three dose groups had a tendency of lowing blood lipid after 30 days.At 45 days, the levels of serum TC and LDL-C in the low and high dose groups were lower than those in the model group (P<0.01, P<0.05), (P<0.01, P<0.01).TG in the high, moderate and low dose groups were lower than that in the model group (P<0.01, P<0.01, P<0.01), but the level of the serum HDL-C was not significantly lower than that in the model group (P>0.05, P>0.05, P>0.05).Conclusions Eucommia in a dose of 0.43 g/kg, 0.86 g/kg and 1.71 g/kg administered for 30 days have a tendency to reduce the level of serum TC, TG, and LDL-C.When Eucommia is administered in a dose of 0.43 g/kg, 1.71g/kg and 3.42 g/kg for 45 days, it shows an adjuvant hypolipidemic effect.

Objective: To investigate the risk factors for central lymph node metastasis (CLNM) and lateral cervical lymph node metasta-sis in papillary thyroid carcinoma (PTC) patients. Methods: We retrospectively reviewed 1,835 PTC patients who underwent central lymph node dissection or thyroidectomy with lateral cervical lymph node dissection between January and November 2016 at Tianjin Medical University Cancer Institute and Hospital. Univariate and multivariate logistic regression models were used to analyze related factors that may affect lymph node metastasis in PTC patients. Results: Of the 1,835 patients included in this study, 1,007 (54.88%) pa-tients had CLNM and 371 (20.22%) patients had lateral cervical lymph node metastasis. In the univariate analysis, the following were identified as risk factors for CLNM and lateral cervical lymph node metastasis (P<0.05): male sex, age<45 years, primary tumor size>10 mm, multifocality,anti-thyroglobulin (anti-Tg) levels >100.00 IU/mL and ,Tg>130.70 μg/L. Anti-thyroid peroxidase antibody (anti-TPO) level>100.00 IU/mL is a protective factor that reduces the risk of CLNM. However, CLNM is a risk factor for lateral cervical lymph node metastasis in PTC patients. Multivariate analysis revealed that male sex, age<45 years, primary tumor size>10 mm, multifocality, and anti-TG levels>100.00 IU/mL were associated with an increased risk of CLNM in PTC patients. Anti-TPO levels>100.00 IU/mL are protective factors for CLNM. The male sex, age<45 years, tumor size>10 mm, multifocality, Tg levels>130.70 ug/L, anti-TG levels>100.00 IU/mL, and CLNM are risk factors for lateral lymph node metastasis. Conclusions: Thus, men aged<45 years with a multifocal primary tumor>10 mm in size and with anti-Tg levels>100.00 IU/mL are more likely to develop CLNM and lateral cervical lymph node metastasis; patients with CLNM are more likely to develop lateral cervical lymph node metastasis. However, patients with anti-TPO lev-el>100 IU/mL are less likely to develop CLNM.

Objective:To construct a clinical-radiomics model based on MRI, and to explore its predictive value for biochemical recurrence (BCR) after radical prostatectomy in prostate cancer patients.Methods:A total of 212 patients with prostate cancer who underwent radical prostatectomy in the First Affiliated Hospital of Soochow University from January 2015 to December 2018 and had complete follow-up data were retrospectively analyzed. The random toolkit of Python language was used to randomly sample the patients at a ratio of 7∶3 without replacement, and they were divided into a training set (149 cases) and a test set (63 cases). The endpoint of follow-up was BCR or at least 3 years. BCR occurred in 50 patients in the training group and 21 patients in the test group. The imaging features of the main lesion area in the preoperative T 2WI, diffusion-weighted imaging and apparent diffusion coefficient map of patients in the training set were extracted, and the unsupervised K means clustering algorithm was used to screen the features. The selected features were fitted by a multivariate Cox regression model, and the radiomics model was constructed. Univariate Cox regression analyses were used to screen the main clinical risk factors associated with BCR, and the clinical-radiomics model was constructed combined with RadScore. In the test set, the time-dependent receiver operating characteristic (ROC) curve was constructed, and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of the radiomics model, clinical-radiomics model and prostate cancer risk assessment after radical resection (CAPRA-S) score for the occurrence of BCR. Harrell consistency index (C-index) was used to evaluate the model to predict BCR consistency. The calibration curve was used to evaluate the degree of variation of the model. The decision curve was used to evaluate the clinical application value of the prediction model. Results:A total of 26 radiomics features were screened to establish the radiomics model. The univariate Cox showed that the preoperative clinical features included preoperative prostate-specific antigen level (HR=1.006, 95%CI 1.002-1.009, P=0.001), Gleason score of biopsy (HR=1.422, 95%CI 1.153-1.753, P=0.001), clinical T stage (HR=1.501, 95%CI 1.238-1.822, P<0.001). The multivariate Cox showed that the RadScore was an independent predictor of BCR after radical prostatectomy (HR=51.214, 95%CI 18.226-143.908, P<0.001). The selected preoperative clinical features were combined with RadScore to construct a clinical-radiomics model. In the test set, the AUCs of the time (3 years)-dependent ROC curves of the radiomics model, the clinical-radiomics model, and the CAPRA-S score were 0.824 (95%CI 0.701-0.948), 0.841 (95%CI 0.714-0.968), and 0.662 (95%CI 0.518-0.806), respectively. The C-index of the radiomics model, clinical-radiomics model and CAPRA-S score were 0.784 (95%CI 0.660-0.891), 0.802 (95%CI 0.637-0.912) and 0.650 (95%CI 0.601-0.821), respectively. The calibration curve showed that the predicted probability and actual probability of BCR by radiomics model, clinical-radiomics model and CAPRA-S score were in good agreement (χ 2=7.64, 10.61, 6.37, P=0.465, 0.225, 0.498). The decision curve showed that the clinical net benefit of the clinical-radiomics model and the radiomics model was significantly higher than the CAPRA-S score. When the threshold probability was 0.20-0.30, 0.40-0.50, and >0.55, the clinical net benefit of the clinical radiomics model was higher than that of the radiomics model. Conclusions:The clinical-radiomics model can effectively predict the occurrence of BCR in patients with prostate cancer after radical prostate ctomy, and the prediction efficacy is better than the radiomics model and CAPRA-S score.

Objective:To evaluate the diagnostic efficacy of prostate imaging recurrence reporting (PI-RR) system for detecting local recurrence after radical prostatectomy (RP) in prostate cancer (PCa) and to assess the consistency of the PI-RR scores assigned by different seniority radiologists.Methods:This study was a cross-sectional study. A total of 176 PCa patients who underwent multi-parametric MRI (mpMRI) for biochemical recurrence (BCR) after RP from July 2015 to October 2021 at the First Affiliated Hospital of Soochow University were retrospectively collected. The mpMRI images were reviewed and the PI-RR scores of the main lesions were assigned independently by six different seniority radiologists (2 junior, 2 senior and 2 expert radiologists). Following the reference standard determined by biopsy pathologic results, follow-up imaging, or prostate specific antigen levels, the patients were divided into two groups: 54 patients with local recurrence and 122 patients without local recurrence. The intraclass correlation coefficient ( ICC) and Kappa test were used to evaluate the consistency of the PI-RR scores by different seniority radiologists. The receiver operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic efficacy of the PI-RR scores assessed by different seniority radiologists for detecting local recurrence of PCa after RP. The DeLong test was utilized to compare the areas under the ROC curve (AUC) of different seniority radiologist PI-RR scores and a false discovery rate (FDR) was applied to correct results using the Benjamini and Hochberg method. Sensitivity and specificity were calculated according to the cutoff value of PI-RR score≥3 or 4. Results:The ICC (95% CI) of all different seniority radiologists was 0.70 (0.64-0.76). The Kappa value was 0.528, 0.325 and 0.370 respectively between expert and senior radiologists, expert and junior radiologists, senior and junior radiologists. The AUC (95% CI) of junior, senior, and expert radiologists were separately 0.73 (0.65-0.81), 0.81 (0.74-0.88), and 0.86 (0.80-0.93). The AUC of the expert radiologist PI-RR score was higher than those of senior and junior radiologist PI-RR scores ( Z=2.22, 3.21, FDR P=0.039, 0.003). The PI-RR score of senior radiologist had higher AUC than that of junior radiologist ( Z=2.22, FDR P=0.026). With the PI-RR score of 3 or greater as a cutoff value, the sensitivity of junior, senior and expert radiologists were respectively 0.59, 0.65, and 0.78 and the specificity were 0.82, 0.93, and 0.95. With the PI-RR score of 4 or greater as a cutoff value, the sensitivity of junior, senior and expert radiologists were respectively 0.50, 0.54, and 0.69 and the specificity were 0.88, 0.96 and 0.97. Conclusion:PI-RR score can accurately diagnose local recurrence of PCa after RP. PI-RR score has a moderate inter-reader consistency across different seniority radiologists. And the diagnostic performance is influenced by the experience of radiologists.

Currently,human health due to corona virus disease 2019(COVID-19)pandemic has been seriously threatened.The coronavirus severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)spike(S)protein plays a crucial role in virus transmission and several S-based therapeutic approaches have been approved for the treatment of COVID-19.However,the efficacy is compromised by the SARS-CoV-2 evolvement and mutation.Here we report the SARS-CoV-2 S protein receptor-binding domain(RBD)inhibitor licorice-saponin A3(A3)could widely inhibit RBD of SARS-CoV-2 variants,including Beta,Delta,and Omicron BA.1,XBB and BQ1.1.Furthermore,A3 could potently inhibit SARS-CoV-2 Omicron virus in Vero E6 cells,with EC50 of 1.016 pM.The mechanism was related to binding with Y453 of RBD deter-mined by hydrogen-deuterium exchange mass spectrometry(HDX-MS)analysis combined with quan-tum mechanics/molecular mechanics(QM/MM)simulations.Interestingly,phosphoproteomics analysis and multi fluorescent immunohistochemistry(mIHC)respectively indicated that A3 also inhibits host inflammation by directly modulating the JNK and p38 mitogen-activated protein kinase(MAPK)path-ways and rebalancing the corresponding immune dysregulation.This work supports A3 as a promising broad-spectrum small molecule drug candidate for COVID-19.

Smart manufacturing still remains critical challenges for pharmaceutical manufacturing. Here, an original data-driven engineering framework was proposed to tackle the challenges. Firstly, from sporadic indicators to five kinds of systematic quality characteristics, nearly 2,000,000 real-world data points were successively characterized from Ginkgo Folium tablet manufacturing. Then, from simplex to the multivariate system, the digital process capability diagnosis strategy was proposed by multivariate C_pk integrated Bootstrap-t. The C_pk of Ginkgo Folium extracts, granules, and tablets were discovered, which was 0.59, 0.42, and 0.78, respectively, indicating a relatively weak process capability, especially in granulating. Furthermore, the quality traceability was discovered from unit to end-to-end analysis, which decreased from 2.17 to 1.73. This further proved that attention should be paid to granulating to improve the quality characteristic. In conclusion, this paper provided a data-driven engineering strategy empowering industrial innovation to face the challenge of smart pharmaceutical manufacturing.

It is an urgent demand worldwide to control the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The 3-chymotrypsin-like protease (3CL^pro) and papain-like protease (PL^pro) are key targets to discover SARS-CoV-2 inhibitors. After screening 12 Chinese herbal medicines and 125 compounds from licorice, we found that a popular natural product schaftoside inhibited 3CL^pro and PL^pro with IC₅₀ values of 1.73 ± 0.22 and 3.91 ± 0.19 μmol/L, respectively, and inhibited SARS-CoV-2 virus in Vero E6 cells with EC₅₀ of 11.83 ± 3.23 μmol/L. Hydrogen-deuterium exchange mass spectrometry analysis, quantum mechanics/molecular mechanics calculations, together with site-directed mutagenesis indicated the antiviral activities of schaftoside were related with non-covalent interactions with H41, G143 and R188 of 3CL^pro, and K157, E167 and A246 of PL^pro. Moreover, proteomics analysis and cytokine assay revealed that schaftoside also regulated immune response and inflammation of the host cells. The anti-inflammatory activities of schaftoside were confirmed on lipopolysaccharide-induced acute lung injury mice. Schaftoside showed good safety and pharmacokinetic property, and could be a promising drug candidate for the prevention and treatment of COVID-19.