Due to patient compliance and convenience, oral medication is likely the most common and acceptable method of drug administration. However, traditional dosage forms such as tablets or capsules may lead to low drug bioavailability and poor therapeutic efficiency. Therefore, with advancements in material science and micro/nano manufacturing technology, various carriers have been developed to enhance drug absorption in the gastrointestinal tract. In this context, we initially discuss the key biological factors that hinder drug transport and absorption (including anatomical, physical, and biological factors). Building on this foundation, recent progress in both conventional and innovative oral drug delivery routes aimed at improving drug bioavailability and targeting is reviewed. Finally, we explore future prospects for oral drug delivery systems as well as potential challenges in clinical translation.

Natural products are important sources for the discovery of anti-tumor drugs. Evodiamine is the main alkaloid component of the traditional Chinese herb Wu-Chu-Yu, and it has weak antitumor activity. In recent years, a number of highly active antitumor candidates have been discovered with a significant progress. This article reviews the research progress of evodiamine-based antitumor drug design strategies, in order to provide reference for the development of new drugs with natural products as leads.

Parkinson's disease (PD) is a chronic neurodegenerative disease. At present, levodopa and other drugs are mainly used for dopamine supplementation therapy. However, the absorption of levodopa in the gastrointestinal tract is unstable and its half-life is short, and long-term use of levodopa will lead to the end-of-dose deterioration, dyskinesia, the "ON-OFF" phenomenon and other symptoms. Therefore, new preparations need to be developed to improve drug efficacy, reduce side effects or improve compliance of patients. Based on the above clinical needs, this review briefly introduced the preparation modification strategies for the treatment of PD through case analysis, in order to provide references for the research and development of related preparations.

AIM To optimize the extraction process for uracil,hypoxanthine,xanthine,uridine,thymine,inosine,guanosine and 2'-deoxyguanosine from Pheretima guillelmi(Michaelsen),and to determine their contents.METHODS With solid-liquid ratio,ultrasonic time and ultrasonic temperature as influencing factors,contents of hypoxanthine and total nucleosides as evaluation indices,the extraction process was optimized by orthogonal test.HPLC was adopted in the content determination of varioud nucleosides,the analysis was performed on a 30℃thermostatic Agilent C18 column(4.6 mm×250 mm,5 μm),with the mobile phase comprising of methanol-water flowing at 1 mL/min in a gradient elution manner,and the detection wavelength was set at 260 nm.RESULTS The optimal conditions were determined to be 1∶250 for solid-liquid ratio,60 min for ultrasonic time,and 60℃for ultrasonic temperature.Eight nucleosides showed good linear relationships within their own ranges(R2＞0.999 0),whose average recoveries were 99.11%-103.27%with the RSDs of 0.85%-2.89%.CONCLUSION This stable and reliable method can be used for the extraction and content determination of nucleosides from P.guillelmi.

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.

Objective:To analyze and compare the differences of expression profiles between RPL and normal adipose tissue by transcriptome sequencing(RNA-Seq),then identify the key genes related to prognosis and explore their potential mechanisms.Methods:Tumor tissues and normal adipose tissues of patients with RPL were collected for RNA-Seq,and then the differentially ex-pressed genes were analyzed by GO and KEGG enrichment analysis.Based on TCGA,the high-risk genes related to prognosis were screened and verified by Kaplan-Meier curve and receiver operat-ing characteristic(ROC)curve.Results:Compared with normal adipose tissue,279 differentially expressed genes were simultaneously up-regulated in RPL tissues,which were mainly enriched in immune response and PPAR signaling pathway.Combined with TCGA,7 stable prognostic high risk genes were identified and the overall survival rate of the high risk group was significantly lower than that of the low risk group(P＜0.05).Conclusion:KCNQ5,RBPJ and some other genes may be re-lated to the poor prognosis of RPL patients.The analysis of the mechanism of these genes in RPL is expected to provide new evidence for the formulation of diagnosis and treatment strategies for RPL patients.

There is growing evidence that the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with increased risks of psychiatric sequelae. Depression, anxiety, cognitive impairments, sleep disturbance, and fatigue during and after the acute phase of COVID-19 are prevalent, long-lasting, and exerting negative consequences on well-being and imposing a huge burden on healthcare systems and society. This current review presented timely updates of clinical research findings, particularly focusing on the pathogenetic mechanisms underlying the neuropsychiatric sequelae, and identified potential key targets for developing effective treatment strategies for long COVID. In addition, we introduced the Formosa Long COVID Multicenter Study (FOCuS), which aims to apply the inflammation theory to the pathogenesis and the psychosocial and nutrition treatments of post-COVID depression and anxiety.

Objective: To explore the application and efficacy of paclitaxel liposome in the treatment of advanced breast cancer among Chinese population in the real world. Methods: The clinical characteristics of patients with advanced breast cancer who received paclitaxel liposome as salvage treatment from January 1, 2016 to August 31, 2019 in 11 hospitals were collected and retrospectively analyzed. The primary outcome was progression free survival (PFS), and the secondary outcome included objective response rate (ORR) and safety. The survival curve was drawn by Kaplan-Meier analysis and the Cox regression model were used for the multivariate analysis. Results: Among 647 patients with advanced breast cancer who received paclitaxel liposome, the first-line treatment accounted for 43.3% (280/647), the second-line treatment accounted for 27.7% (179/647), and the third-line and above treatment accounted for 29.1% (188/647). The median dose of first-line and second-line treatment was 260 mg per cycle, and 240 mg in third line and above treatment. The median period of paclitaxel liposome alone and combined chemotherapy or targeted therapy is 4 cycles and 6 cycles, respectively. In the whole group, 167 patients (25.8%) were treated with paclitaxel liposome combined with capecitabine±trastuzumab (TX±H), 123 patients (19.0%) were treated with paclitaxel liposome alone (T), and 119 patients (18.4%) were treated with paclitaxel liposome combined with platinum ± trastuzumab (TP±H), 108 patients (16.7%) were treated with paclitaxel liposome combined with trastuzumab ± pertuzumab (TH±P). The median PFS of first-line and second-line patients (5.5 and 5.5 months, respectively) were longer than that of patients treated with third line and above (4.9 months, P<0.05); The ORR of the first line, second line, third line and above patients were 46.7%, 36.8% and 28.2%, respectively. Multivariate analysis showed that event-free survival (EFS) and the number of treatment lines were independent prognostic factors for PFS. The common adverse events were myelosuppression, gastrointestinal reactions, hand foot syndrome and abnormal liver function. Conclusion: Paclitaxel liposomes is widely used and has promising efficacy in multi-subtype advanced breast cancer.
Humans ; Female ; Breast Neoplasms/chemically induced* ; Paclitaxel/adverse effects* ; Liposomes/therapeutic use* ; Retrospective Studies ; Treatment Outcome ; Trastuzumab/therapeutic use* ; Capecitabine/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/adverse effects*

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
Humans ; Nomograms ; Retrospective Studies ; Carcinoma, Renal Cell/pathology* ; Prognosis ; Risk Factors ; Nephrectomy ; Kidney Neoplasms/pathology* ; Necrosis

Objective: To report the long-term survival of renal cell carcinoma (RCC) patients treated with radical nephrectomy in Sun Yat-sen University Cancer Center. Methods: We retrospectively analyzed the clinical, pathological and follow-up records of 1 367 non-metastatic RCC patients treated with radical nephrectomy from 1999 to 2020 in this center. The primary endpoint of this study was overall survival rate. Survival curves were estimated using the Kaplan-Meier method, and group differences were compared through Log-rank test. Univariate and multivariate Cox analysis were fit to determine the clinical and pathological features associated with overall survival rate. Results: A total of 1 367 patients treated with radical nephrectomy with complete follow-up data were included in the study. The median follow-up time was 52.6 months, and 1 100 patients survived and 267 died, with the median time to overall survival not yet reached. The 5-year and 10-year overall survival rates were 82.8% and 74.9%, respectively. The 5-year and 10-year overall survival rates of Leibovich low-risk patients were 93.3% and 88.2%, respectively; of Leibovich intermediate-risk patients were 82.2% and 72.3%, respectively; and of Leibovich high-risk patients were 50.5% and 30.2%, respectively. There were significant differences in the long-term survival among the three groups (P<0.001). The 10-year overall survival rates for patients with pT1, pT2, pT3 and pT4 RCC were 83.2%, 73.6%, 55.0% and 31.4%, respectively. There were significant differences among pT1, pT2, pT3 and pT4 patients(P<0.001). The 5-year and 10-year overall survival rates of patients with lymph node metastasis were 48.5% and 35.6%, respectively, and those of patients without lymph node metastasis were 85.1% and 77.5%, respectively. There was significant difference in the long-term survival between patients with lymph node metastasis and without lymph node metastasis. The 10-year overall survival rate was 96.2% for nuclear Grade 1, 81.6% for nuclear Grade 2, 60.5% for nuclear Grade 3, and 43.4% for nuclear Grade 4 patients. The difference was statistically significant. There was no significant difference in the long-term survival between patients with localized renal cancer (pT1-2N0M0) who underwent open surgery and minimally invasive surgery (10-year overall survival rate 80.5% vs 85.6%, P=0.160). Multivariate Cox analysis showed that age≥55 years (HR=2.11, 95% CI: 1.50-2.96, P<0.001), T stage(T3+ T4 vs T1a: HR=2.37, 95% CI: 1.26-4.46, P=0.008), local lymph node metastasis (HR=3.04, 95%CI: 1.81-5.09, P<0.001), nuclear grade (G3-G4 vs G1: HR=4.21, 95%CI: 1.51-11.75, P=0.006), tumor necrosis (HR=1.66, 95% CI: 1.17-2.37, P=0.005), sarcomatoid differentiation (HR=2.39, 95% CI: 1.31-4.35, P=0.005) and BMI≥24kg/m(2) (HR=0.56, 95%CI: 0.39-0.80, P=0.001) were independent factors affecting long-term survival after radical nephrectomy. Conclusions: The long-term survival of radical nephrectomy in patients with renal cell carcinoma is satisfactory. Advanced age, higher pathological stage and grade, tumor necrosis and sarcomatoid differentiation were the main adverse factors affecting the prognosis of patients. Higher body mass index was a protective factor for the prognosis of patients.
Humans ; Middle Aged ; Carcinoma, Renal Cell/secondary* ; Lymphatic Metastasis ; Retrospective Studies ; Neoplasm Staging ; Kidney Neoplasms/pathology* ; Prognosis ; Nephrectomy ; Survival Analysis ; Necrosis/surgery* ; Survival Rate