Enhancing metformin-induced tumor metabolism destruction by glucose oxidase for triple-combination therapy.

Despite decades of laboratory and clinical trials, breast cancer remains the main cause of cancer-related disease burden in women. Considering the metabolism destruction effect of metformin (Met) and cancer cell starvation induced by glucose oxidase (GOx), after their efficient delivery to tumor sites, GOx and Met may consume a large amount of glucose and produce sufficient hydrogen peroxide in situ. Herein, a pH-responsive epigallocatechin gallate (EGCG)-conjugated low-molecular-weight chitosan (LC-EGCG, LE) nanoparticle (Met-GOx/Fe@LE NPs) was constructed. The coordination between iron ions (Fe3+) and EGCG in this nanoplatform can enhance the efficacy of chemodynamic therapy via the Fenton reaction. Met-GOx/Fe@LE NPs allow GOx to retain its enzymatic activity while simultaneously improving its stability. Moreover, this pH-responsive nanoplatform presents controllable drug release behavior. An in vivo biodistribution study showed that the intracranial accumulation of GOx delivered by this nanoplatform was 3.6-fold higher than that of the free drug. The in vivo anticancer results indicated that this metabolism destruction/starvation/chemodynamic triple-combination therapy could induce increased apoptosis/death of tumor cells and reduce their proliferation. This triple-combination therapy approach is promising for efficient and targeted cancer treatment.

Safety, Pharmacokinetics, and Pharmacodynamics of SHR7280, a Non-peptide GnRH Antagonist in Premenopausal Women with Endometriosis: A Randomized, Double-Blind, Placebo-Controlled Phase 1 Study.

BACKGROUND: Oral gonadotropin-releasing hormone (GnRH) antagonists are promising agents in the treatment of endometriosis-related pain. Here we assessed the safety, pharmacokinetics (PK), and pharmacodynamics (PD) of SHR7280, an oral non-peptide GnRH antagonist in premenopausal women with endometriosis. METHODS: In the Phase 1 part of the randomized, double-blinded, placebo-controlled, dose-ascending, Phase 1/2 trial, premenopausal women with endometriosis were randomized (4:1) to receive SHR7280 or placebo treatment for 21 consecutive days. The treatment dose started from 200 mg QD, and then increased to 300 mg QD and 200 mg BID. Safety, PK, and PD parameters were assessed. RESULTS: In total, 30 patients received assigned treatment, 24 with SHR7280 and 6 with placebo. SHR7280 was well tolerated. Adverse events (AEs) were reported in 19 (79.2%, 19/24) patients in the SHR7280 group and 5 (83.3%, 5/6) patients in the placebo group. Most AEs were mild and no severe AEs occurred. SHR7280 showed a rapid absorption, with a time to maximum plasma concentration (Tmax) of 1.0 h, 1.0 h, and 0.8 h for the 200 mg QD, 300 mg QD, and 200 mg BID regimens, respectively. Plasma concentration of SHR7280 was dose dependent. The mean half-life (t1/2) at steady state was 6.9 h, 7.4 h, and 2.8 h, respectively, and little or no accumulation was observed. Pharmacodynamic analysis showed that SHR7280 could effectively suppress estradiol and luteinizing hormone concentrations and prevent progesterone increase in a dose-dependent manner. SHR7280 at doses of 300 mg QD and 200 mg BID could suppress estradiol levels within the desired therapeutic window of 20-50 pg/mL throughout the treatment period. CONCLUSIONS: SHR7280 showed favorable safety, PK, and PD profiles in the doses of 200 mg QD, 300 mg QD, and 200 mg BID. The results of this study provide evidence to support the further development of SHR7280 as a GnRH antagonist for the treatment of endometriosis-related pain in the subsequent Phase 2 trial. TRIAL REGISTRY: Trial registration number: Clinicaltrials.gov, identifier: NCT04417972. Trial registration date: 5 June 2020.

Neutrophil-to-lymphocyte ratio is associated with stroke progression and functional outcome in patients with ischemic stroke.

OBJECTIVE: The objective of the present research was to examine the correlation between the neutrophil-to-lymphocyte ratio (NLR) and stroke progression (SP) as well as the functional outcome following an ischemic stroke (IS). METHODS: The current study was conducted as prospective observational research. A cohort of 341 participants diagnosed with IS was included in the study from March 2019 to August 2021. This study's primary measure of interest was the occurrence of SP within the initial week following hospital admission. The secondary outcome was functional status 3 months after IS as measured by a modified Rankin scale score. The association between NLR with SP, and poor functional outcomes was examined using multivariate logistic regression. The predictive value of NLR for SP and poor functional outcomes was evaluated using the receiver operating characteristic (ROC) curve. RESULTS: Among the 341 enrolled patients, 56 (16.4%) had SP, and 285 (83.6%) had no SP. The results of the multivariate logistic regression analysis demonstrated that the existence of diabetes mellitus and the NLR were independently associated with SP and poor functional outcomes. The area under the ROC curve of NLR in predicting poor functional outcome was 0.6117 (95% confidence interval, .5341-.6893, p = .0032), and the optimal cut-off point was 4.2139. The sensitivity and specificity of NLR in predicting poor functional outcomes were 52.7% and 72.0%, respectively. CONCLUSION: Patients with acute IS exhibited a very high incidence of SP. NLR may be a valuable prognostic indicator in clinical practice because it was independently associated with SP and a poor functional outcome.

Machine learning algorithms for prediction of ventilator associated pneumonia in traumatic brain injury patients from the MIMIC-III database.

BACKGROUND: Ventilator associated pneumonia (VAP) is a common complication and associated with poor prognosis of traumatic brain injury (TBI) patients. OBJECTIVES: This study was conducted to explore the predictive performance of different machine-learning algorithms for VAP in TBI patients. METHODS: TBI patients receiving mechanical ventilation more than 48 hours from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were eligible for the study. The VAP was confirmed based on the ICD-9 code. Included patients were separated to the training cohort and the validation cohort with a ratio of 7:3. Predictive models based on different machine learning algorithms were developed using 5-fold cross validation in the training cohort and then verified in the validation cohort by evaluating the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy and F score. RESULTS: 786 TBI patients from the MIMIC-III were finally included with the VAP incidence of 44.0%. The random forest performed the best on predicting VAP in the training cohort with a AUC of 1.000. The XGBoost and AdaBoost were ranked the second and the third with a AUC of 0.915 and 0.789 in the training cohort. While the AdaBoost performed the best on predicting VAP in the validation cohort with a AUC of 0.706. The XGBoost and random forest were ranked the second and the third with the AUC of 0.685 and 0.683 in the validation cohort. Generally, the random forest and XGBoost were likely to be over-fitting while the AdaBoost was relatively stable in predicting the VAP. CONCLUSIONS: The AdaBoost performed well and stably on predicting the VAP in TBI patients. Developing programs using AdaBoost in portable electronic devices may effectively assist physicians in assessing the risk of VAP in TBI.

Liver fibrosis score is associated with the mortality of traumatic brain injury patients.

The fibrosis-4 score is a marker of liver fibrosis and has been confirmed to be associated with the prognosis of various diseases. There is no study exploring the prognostic value of the fibrosis-4 score in traumatic brain injury (TBI) patients. We design this study to explore the association between the fibrosis-4 score and mortality from TBI. TBI patients from the Medical Information Mart for Intensive Care-III database were extracted for the study. Univariate and multivariate logistic regressions were sequentially performed to analyze the association between fibrosis-4 and mortality in TBI. The area under the receiver operating characteristic curve (AUC) was drawn to evaluate the prognostic value of fibrosis-4 and other scores. A total of 1018 TBI patients were included, with a 30-day mortality of 24.2%. Non-survivors had older age, lower Glasgow Coma Scale (GCS), and higher injury severity score (ISS) than survivors. The aspartate aminotransferase platelet ratio index (APRI) and fibrosis-4 score were significantly higher in non-survivors. Univariate logistic regression showed that age, GCS, ISS, white blood cell, hemoglobin, fibrosis-4 score, subarachnoid hemorrhage, and anticoagulants were associated with the mortality of TBI patients. Multivariate logistic regression presented that age, GCS, ISS, fibrosis-4 score, subarachnoid hemorrhage, and anticoagulants were independent risk factors of mortality in TBI patients after adjusting for confounding effects. The AUC of the GCS, ISS, APRI, and fibrosis-4 score for predicting mortality was 0.711, 0.625, 0.592, and 0.627, respectively. Composed of age, GCS, ISS, fibrosis-4 score, subarachnoid hemorrhage, and anticoagulants, the predictive model had the highest AUC value of 0.790. The fibrosis-4 score is an independent risk factor for mortality in TBI. The model incorporating fibrosis-4 performs well in predicting the prognosis of TBI patients.

A Single-dose, Two-Period Crossover Bioequivalence Study Comparing Two Liraglutide Formulations in Healthy Chinese Subjects.

Liraglutide, a glucagon-like peptide 1 receptor agonist, is indicated as an adjunct to diet and exercise to improve glycemic control in patients with type 2 diabetes. The original liraglutide products are costly, which limits patient access to this therapeutic treatment. Herein, a biosimilar was developed that is highly similar to the reference drug in molecular structure and bioactivity, and is expected to have similar pharmacokinetic (PK) and safety profiles in clinical studies. This study aimed to primarily evaluate the bioequivalence of 2 liraglutide formulations and secondarily assess their safety in healthy Chinese subjects following a single-dose subcutaneous injection. Thirty-two healthy volunteers were recruited in this randomized, open-label, single-dose, 2-period crossover bioequivalence study (ChiCTR2100043348). The geometric mean ratios (GMRs) of the test drug to the reference drug (T/R) and corresponding 90% confidence intervals (CIs) for maximum concentration (Cmax ) and the area under the concentration-time curve from time 0 to the time of the last quantifiable concentration (AUC0-t ) were estimated using a mixed-effects model, and bioequivalence was determined to have been achieved if the 2-sided 90%CI fell within the predefined range of 80%-125%. PK parameters were comparable between T and R, with GMRs of T/R for Cmax and AUC0-t being 105.7% and 107.7%, respectively, the 90%CI of which met the acceptance criteria for bioequivalence. We also observed a similar and favorable safety profile in the T and R arms, with adverse events being predominantly mild in severity and of gastrointestinal origin. Our findings indicate that the test drug is safe and well tolerated, bioequivalent to the reference drug, and warrants further testing in a phase III clinical trial.

Prediction of Acute Respiratory Distress Syndrome in Traumatic Brain Injury Patients Based on Machine Learning Algorithms.

Background: Acute respiratory distress syndrome (ARDS) commonly develops in traumatic brain injury (TBI) patients and is a risk factor for poor prognosis. We designed this study to evaluate the performance of several machine learning algorithms for predicting ARDS in TBI patients. Methods: TBI patients from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were eligible for this study. ARDS was identified according to the Berlin definition. Included TBI patients were divided into the training cohort and the validation cohort with a ratio of 7:3. Several machine learning algorithms were utilized to develop predictive models with five-fold cross validation for ARDS including extreme gradient boosting, light gradient boosting machine, Random Forest, adaptive boosting, complement naïve Bayes, and support vector machine. The performance of machine learning algorithms were evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy and F score. Results: 649 TBI patients from the MIMIC-III database were included with an ARDS incidence of 49.5%. The random forest performed the best in predicting ARDS in the training cohort with an AUC of 1.000. The XGBoost and AdaBoost ranked the second and the third with an AUC of 0.989 and 0.815 in the training cohort. The random forest still performed the best in predicting ARDS in the validation cohort with an AUC of 0.652. AdaBoost and XGBoost ranked the second and the third with an AUC of 0.631 and 0.620 in the validation cohort. Several mutual top features in the random forest and AdaBoost were discovered including age, initial systolic blood pressure and heart rate, Abbreviated Injury Score chest, white blood cells, platelets, and international normalized ratio. Conclusions: The random forest and AdaBoost based models have stable and good performance for predicting ARDS in TBI patients. These models could help clinicians to evaluate the risk of ARDS in early stages after TBI and consequently adjust treatment decisions.

A phase I, single-sequence, open-label study to evaluate the drug-drug interaction between hetrombopag and cyclosporine in healthy Chinese subjects.

AIMS: This study aims to evaluate the drug-drug interaction (DDI) between hetrombopag and cyclosporine in healthy Chinese subjects. METHODS: Twenty-six eligible subjects enrolled in this single-centre, single-sequence, open-label, DDI study with 3 treatment periods, receiving 5 mg hetrombopag once on Day 1, 100 mg cyclosporine twice daily from Day 11 to Day 15 and 5 mg hetrombopag + 100 mg cyclosporine on Day 16. Serial blood samples were collected for pharmacokinetic evaluation. Adverse events were monitored throughout the study. RESULTS: The plasma hetrombopag geometric mean ratios (90% confidence interval) of maximum plasma concentration, area under the plasma concentration-time curve (AUC) from predose to time of last quantifiable sample and AUC to infinity of coadministration of hetrombopag with cyclosporine vs. hetrombopag alone were 95.97% (70.08-131.43%), 105.75% (75.04-149.04%) and 104.19% (74.71-145.32%), respectively, indicating multiple doses of cyclosporine had minimal effects on hetrombopag exposure. The geometric mean ratios (90% confidence interval) of maximum blood concentration and AUC at steady state during a dosing interval for blood cyclosporine of coadministration vs. cyclosporine alone were 100.49% (91.89-109.89%) and 100.81% (107.88-103.82%), respectively, suggesting a single dose of hetrombopag had no impact on the exposure of cyclosporine. Coadministration of hetrombopag with cyclosporine was generally well tolerated. CONCLUSION: No clinically significant DDI was observed when coadministration of hetrombopag with cyclosporine. The results of this study will inform the appropriate use of this combination therapy both in clinical trials and clinical settings.

The safety and immunogenicity of an inactivated SARS-CoV-2 vaccine in Chinese adults aged 18-59 years: A phase I randomized, double-blinded, controlled trial.

BACKGROUND: This study examined the safety and immunogenicity of an inactivated SARS-CoV-2 vaccine. METHOD: In a phase I randomized, double-blinded, placebo-controlled trial involving 192 healthy adults 18-59 years old, two injections of three doses (50 EU, 100 EU, 150 EU) of an inactivated SARS-CoV-2 vaccine or placebo were administered intramuscularly at a 2- or 4-week interval. The safety and immunogenicity of the vaccine were evaluated. RESULTS: Vaccination was completed in 191 subjects. Forty-four adverse reactions occurred within 28 days, most commonly mild pain and redness at the injection site or slight fatigue. At days 14 and 28, the seroconversion rates were 87.5% and 79.2% (50 EU), 100% and 95.8% (100 EU), and 95.8% and 87.5% (150 EU), respectively, with geometric mean titers (GMTs) of 18.1 and 10.6, 54.5 and 15.4, and 37.1 and 18.5, respectively, for the schedules with 2-week and 4-week intervals. Seroconversion was associated with synchronous upregulation of antibodies against the S protein, N protein and virion and a cytotoxic T lymphocyte (CTL) response. No cytokines and immune cells related to immunopathology were observed. Transcriptome analysis revealed the genetic diversity of immune responses induced by the vaccine. INTERPRETATION: In a population aged 18-59 years in this trial, this inactivated SARS-CoV-2 vaccine was safe and immunogenic. TRIAL REGISTRATION: CTR20200943 and NCT04412538.

Prognostic significance of lymphocyte monocyte ratio in patients with ovarian cancer.

BACKGROUND: This study aimed to systematically assess the prognostic value of lymphocyte monocyte ratio (LMR) in patients with ovarian cancer through performing a meta-analysis. METHODS: Web of Science, PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure databases were searched for potentially eligible studies. The baseline characteristics and relevant data were extracted. Hazard ratios with 95% confidence intervals (CIs) were combined to assess the prognostic value of LMR in patients with ovarian cancer. RESULTS: Nine studies enrolling 2809 patients were included. The pooled hazard ratios of lower LMR for overall survival and progression free survival in patients with ovarian cancer were 1.71 (95% CI, 1.40-2.09) and 1.68 (95% CI, 1.49-1.88), respectively. Subgroup analysis and sensitivity analysis were also performed. No significant publication bias was found. CONCLUSION: Our results suggested that lower LMR was associated with poorer overall survival and progression free survival in patients with ovarian cancer. The findings may assist prognosis evaluation and future research on therapies based on modulating host immune response in ovarian cancer.

Association of serum leptin with breast cancer: A meta-analysis.

BACKGROUND: Accumulating evidence has demonstrated that leptin is associated to the tumorigenesis and progression of breast cancer (BC). However, these studies remain inconsistent. Thus, a meta-analysis was conducted to investigate the role of leptin in the patients with BC. METHOD: A systematic search in PubMed, Embase, ISI Web of Science, and Chinese National Knowledge Infrastructure (CNKI) databases was conducted up to September 1, 2017. The standardized mean difference (SMD) with 95% confidence interval (CI) was applied to pool the effect size. A funnel plot and Egger test were used to evaluate publication bias. RESULTS: Finally, 43 eligible studies were included in the current meta-analysis. Overall, serum leptin levels in BC cases were significantly higher compared with the controls (SMD = 0.61, P <.0001). When subgroup analyses were restricted to ethnicity and menstrual status, higher serum leptin concentration was also detected in patients with BC. Moreover, BC cases with body mass index (BMI) >25 indicated significantly higher serum leptin levels (SMD = 1.48, P = .034). Furthermore, the BC cases with lymph node metastases showed significantly higher serum leptin concentration (SMD = 0.53, P = .015). CONCLUSION: The present meta-analysis suggests that the serum leptin may profiles as a pivotal role in the pathogenesis and metastasis of BC. In addition, leptin will provide useful information for a therapeutic target to treat BC.

Prognostic role of neutrophil lymphocyte ratio in patients with spontaneous intracerebral hemorrhage.

The aim of this study was to evaluate the prognostic role of neutrophil lymphocyte ratio (NLR) in patients with spontaneous intracerebral hemorrhage (ICH). PubMed, EMBASE, Web of Knowledge, Cochrane Library and China National Knowledge Infrastructure were searched for potentially relevant literature. The study and patient characteristics were extracted. Odds ratios (ORs) with 95% confidence intervals (CIs) were pooled to estimate the prognostic role of NLR in patients with ICH. Poor functional outcome was defined as modified Rankin Scale≥3. Four studies with 1,720 patients were included. The pooled OR of higher NLR for poor functional outcome at 3 months was 2.74 (95% CI, 1.33-5.65). The pooled OR of higher NLR for death at 3 months was 1.58 (95% CI, 0.44-5.68). Subgroup analysis and sensitivity analysis were also performed. Publication bias was not present. In conclusion, for patients with ICH, higher NLR was associated with poorer functional outcome at 3 months, while higher NLR was not associated with higher risk of death at 3 months.

[The expression of Caspase-3 in granulosa cells of endometriosis treated with mifepristone].

OBJECTIVE: To investigate the effect of mifepristone on the expression of Caspase-3 in the granulosa cells. METHODS: Forty Sprague-Dawley (SD) female rats with (230 +/- 20) g weight were divided into four groups, low-dose group with 1.04 mg/(kg x d) of mifepristone, middle-dose group with 2.604 mg/(kg x d) of mifepristone, high dose group with 10.4 mg/(kg x d) of mifepristone, as well as blank group. Mifepristone tablets were given through gastromy in diestrus of rat for four weeks. Rats were sacrificed after the treatment, and the the expression of Caspase-3 in the granulosa cells of developing follicles was detected by immunohistochemical staining. RESULTS: The Caspase-3 protein expression was observed in granulosa cells of developing follicles, while the positive expression level and integrated optical density (IOD) value were increased along with the dosage of mifepristone increasing. The difference among the three dosage groups were significant (P < 0.05). CONCLUSION: Regulating Caspase-3 protein expression may be one of the ways for mifepristone inducing granulosa cell apoptosis.