Protective Effects of Epigallocatechin Gallate for Male Sexual Dysfunction in Streptozotocin-Induced Diabetic Rats.

Sexual dysfunction is a common problem for men with diabetes. Epigallocatechin gallate (EGCG) is known to ameliorate erectile function in aging rats. However, there has not yet been a report to evaluate its effects on diabetic male rat sexual behavior in the literature. In this study, we investigated the effects of EGCG on male sexual behavior in diabetic rats. Diabetic rats were induced by a single intraperitoneal injection of 65 mg/kg of streptozotocin. After streptozotocin injection for one week, animals were then orally treated with 40 mg/kg of EGCG or vehicle. Copulatory behavior and fasting blood glucose levels were recorded before treatment, as well as 7 and 14 days after treatment. Serum LH, testosterone, and PDE5a levels were measured by EIA assay after the last behavioral test. Data showed that diabetic rats who had diminished sexual functions demonstrated significantly increased latencies in mount, intromission, and ejaculation, as well as significant decreases in frequencies of intromission and ejaculation, compared to non-diabetic controls, indicating sexual function recovery. Lower blood glucose levels were also found in diabetic rats after EGCG treatment. Additionally, the lower LH and higher PDE5a levels in diabetic rats than controls were also noted. The findings declared that EGCG had a protective effect on male sexual behavior in diabetic rats.

Developmental Prediction of Poststroke Patients in Activities of Daily Living by Using Tree-Structured Parzen Estimator-Optimized Stacking Ensemble Approaches.

Poststroke injuries limit the daily activities of patients and cause considerable inconvenience. Therefore, predicting the activities of daily living (ADL) results of patients with stroke before hospital discharge can assist clinical workers in formulating more personalized and effective strategies for therapeutic intervention, and prepare hospital discharge plans that suit the patients needs. This study used the leave-one-out cross-validation procedure to evaluate the performance of the machine learning models. In addition, testing methods were used to identify the optimal weak learners, which were then combined to form a stacking model. Subsequently, a hyperparameter optimization algorithm was used to optimize the model hyperparameters. Finally, optimization algorithms were used to analyze each feature, and features of high importance were identified by limiting the number of features to be included in the machine learning models. After various features were fed into the learning models to predict the Barthel index (BI) at discharge, the results indicated that random forest (RF), adaptive boosting (AdaBoost), and multilayer perceptron (MLP) produced suitable results. The most critical prediction factor of this study was the BI at admission. Machine learning models can be used to assist clinical workers in predicting the ADL of patients with stroke at hospital discharge.

Ensemble learning based functional independence ability estimator for pediatric brain tumor survivors.

A history of brain tumor strongly affects children's cognitive abilities, performance of daily activities, quality of life, and functional outcomes. In light of the difficulties in cognition, communication, physical skills, and behavior that these patients may encounter, occupational therapists should perform a comprehensive needs-led assessment of their global functioning after recovery. Such an assessment would ensure that the patients receive adequate support and services at school, at home, and in the community. By predicting the functional activity performance of children with a history of brain tumor, clinical workers can determine the progress of their ability recovery and the optimal treatment plan. We selected several features for testing and employed common machine learning models to predict Functional Independence Measure (WeeFIM) scores. The ensemble learning models exhibited stronger predictive performance than did the individual machine learning models. The ensemble learning models effectively predicted WeeFIM scores. Machine learning models can help clinical workers predict the functional assessment scores of patients with childhood brain tumors. This study used machine learning models to predict the WeeFIM scores of patients with childhood brain tumors and to demonstrate that ensemble machine learning models are more suitable for this task than are individual machine learning models.

Distinguishing features of a novel humanized anti-EGFR monoclonal antibody based on cetuximab with superior antitumor efficacy.

BACKGROUND: Cetuximab, the first approved EGFR targeting therapeutic antibody, is currently used to treat colorectal cancer and head and neck cancer. While effective, cetuximab is associated with a higher rate of skin rash, infusion reactions, and gastrointestinal toxicity, which was suggested to be linked to the presence of heterogeneous glycan contents on the Fab of the SP2/0-produced cetuximab. OBJECTIVE AND METHODS: To improve efficacy and minimize toxicity of EGFR inhibition treatment, we re-engineered cetuximab by humanizing its Fab regions and minimizing its glycan contents to generate HLX07. RESULTS: HLX07 binds to EGFR with similar affinity as cetuximab and shows better bioactivity compared to cetuximab in vitro. In vivo studies demonstrated that HLX07 significantly inhibited the growth of A431, FaDu, NCI-H292, and WiDr tumor cells and synergized them with chemotherapeutics and immune simulator agents such as anti-PD-1. In cynomolgus monkeys, 13-week repeat-dose GLP toxicokinetic studies showed minimal-to-mild toxicities in the dose range of up to 60 mg/kg/wk. In the preliminary phase 1 dose-escalation study, HLX07 had showed lower incidence of skin rashes with grade >2 severities. CONCLUSION: HLX07 is currently under phase 1/2 clinical development. We believe HLX07 would potentially be an alternative for patients who have been suffering from cetuximab-mediated toxicity.

Biomechanical characterization of the periodontal ligament: Orthodontic tooth movement.

OBJECTIVE: To quantify the biomechanical properties of the bovine periodontal ligament (PDL) in postmortem sections and to apply these properties to study orthodontic tooth intrusion using finite element analysis (FEA). We hypothesized that PDL's property inherited heterogeneous (anatomical dependency) and nonlinear stress-strain behavior that could aid FEA to delineate force vectors with various rectangular archwires. MATERIALS AND METHODS: A dynamic mechanical analyzer was used to quantify the stress-strain behavior of bovine PDL. Uniaxial tension tests using three force levels (0.5, 1, and 3 N) and samples from two anatomical locations (circumferential and longitudinal) were performed to calculate modulus. The Mooney-Rivlin hyperelastic (MRH) model was applied to the experimental data and used in an FEA of orthodontic intrusion rebounded via a 0.45-mm step bend with three archwire configurations of two materials (stainless steel and TMA). RESULTS: Force levels and anatomical location were statistically significant in their effects on modulus (P < .05). The apical part had a greater stiffness than did the middle part. The MRH model was found to approximate the experimental data well (r = 0.99), and it demonstrated a reasonable stress-strain outcome within the PDL and bone for FEA intrusion simulation. The force acting on the tooth increased five times from the 0.016 × 0.022-inch TMA to the 0.019 × 0.025-inch stainless steel. CONCLUSIONS: The PDL is a nonhomogeneous tissue in which the modulus changed in relation to location. PDL nonlinear constitutive model estimated quantitative force vectors for the first time to compare intrusive tooth movement in 3-D space in response to various rectangular archwires.

Anticoagulants (thrombin inhibitors) and aspirin synergize with P2Y12 receptor antagonism in thrombosis.

BACKGROUND: This study was designed to determine whether (1) P2Y12 antagonism synergizes with other antithrombotics and (2) anticoagulants (thrombin inhibitors) affect the antithrombotic activity elicited by P2Y12 antagonism. METHODS AND RESULTS: Thrombosis was achieved by perfusion of human and murine blood through type III collagen-coated capillaries at arterial shear rate. CT50547, a direct-acting P2Y12 antagonist, inhibited thrombosis in PPACK- but not heparin-anticoagulated human blood. In contrast, CT50547 inhibited thrombosis in aspirin-treated individuals independently of the anticoagulant. Thrombin and TXA2 also synergized with P2Y12 in the absence of anticoagulation, because combined treatment of aspirin or C921-78 (a factor Xa inhibitor) with CT50547 or 2-MeSAMP (a P2Y12 antagonist) inhibited the thrombotic process, whereas all treatments failed to inhibit thrombosis when used individually. Synergism was also observed ex vivo when P2Y12-deficient (P2Y12-/-) mice were administered aspirin or coagulation inhibitors (C921-78 and bivalirudin). Finally, using intravital microscopy, we found that both C921-78 and bivalirudin abrogated the thrombotic process in P2Y12+/- mice, whereas each showed only partial efficacy in P2Y12+/+ animals. CONCLUSIONS: Our study indicates that (1) thrombin inhibitors and aspirin have a demonstrable synergy of antithrombotic activity with P2Y12 antagonism and (2) the in vitro analysis of the antithrombotic activity of P2Y12 antagonists is affected by the anticoagulant used for blood collection. This suggests that the antithrombotic potential of P2Y12 antagonists in vitro may be overestimated in anticoagulated samples of blood and best achieved in vivo by the inclusion of aspirin and/or a thrombin inhibitor.

Inhibition of purified factor Xa amidolytic activity may not be predictive of inhibition of in vivo thrombosis: implications for identification of therapeutically active inhibitors.

OBJECTIVE: In this study we test the hypothesis that blood/plasma-based prothrombinase assays, rather than inhibition of purified factor Xa (fXa), are predictive of in vivo antithrombotic activity. METHODS AND RESULTS: Six fXa inhibitors with equivalent nanomolar Ki were studied in thrombin generation assays using human plasma/blood and endogenous macromolecular substrate. In all assays, benzamidine inhibitors were more potent (100 to 800 nmol/L) than the aminoisoquinolines (5 to 58 micromol/L) or neutral inhibitors (3 to 10 micromol/L). A similar rank order of compound inhibition was also seen in purified prothrombinase assays as well as in a rabbit model of deep vein thrombosis. CONCLUSIONS: Assays using prothrombinase with protein substrates are better predictors of in vivo efficacy than fXa Ki using amidolytic substrates.

Induction of c-Cbl contributes to anti-cancer effects of HDAC inhibitor in lung cancer.

Here we found loss of c-Cbl, an E3 ligase, expression in non-small cell lung cancer (NSCLC) compared with its adjacent normal tissue in patient specimens. HDAC inhibition by WJ or knockdown of HDAC 1, HDAC2, HDAC3 or HDAC6 all induced c-Cbl. Ectopic expression of c-Cbl induced decreased EGFR, inhibited growth in NSCLC cells. Knockdown of EGFR inhibited NSCLC growth. Mutation of EGFR at Y1045 decreased WJ-induced growth inhibition as well as in vivo anti-cancer effect and EGFR degradation mediated by WJ. Time-lapse confocal analysis showed co-localization of c-Cbl and EGFR after WJ treatment. Furthermore, WJ inhibited lung tumor growth through c-Cbl induction in orthotopic and tail vein injected models. C-Cbl up-regulation induced by HDACi is a potential strategy for NSCLC treatment.