AIF Downregulation and Its Interaction with STK3 in Renal Cell Carcinoma

Apoptosis-inducing factor (AIF) plays a crucial role in caspase-independent programmed cell death by triggering chromatin condensation and DNA fragmentation. Therefore, it might be involved in cell homeostasis and tumor development. In this study, we report significant AIF downregulation in the majority of renal cell carcinomas (RCC). In a group of RCC specimens, 84% (43 out of 51) had AIF downregulation by immunohistochemistry stain. Additional 10 kidney tumors, including an oxyphilic adenoma, also had significant AIF downregulation by Northern blot analysis. The mechanisms of the AIF downregulation included both AIF deletion and its promoter methylation. Forced expression of AIF in RCC cell lines induced massive apoptosis. Further analysis revealed that AIF interacted with STK3, a known regulator of apoptosis, and enhanced its phosphorylation at Thr180. These results suggest that AIF downregulation is a common event in kidney tumor development. AIF loss may lead to decreased STK3 activity, defective apoptosis and malignant transformation

Targeting cancer-related inflammation with non-steroidal anti-inflammatory drugs: Perspectives in pharmacogenomics

Inflammatory processes are essential for innate immunity and contribute to carcinogenesis in various malignancies, such as colorectal cancer, esophageal cancer and lung cancer. Pharmacotherapies targeting inflammation have the potential to reduce the risk of carcinogenesis and improve therapeutic efficacy of existing anti-cancer treatment. Non-steroidal anti-inflammatory drugs (NSAIDs), comprising a variety of structurally different chemicals that can inhibit cyclooxygenase (COX) enzymes and other COX-independent pathways, are originally used to treat inflammatory diseases, but their preventive and therapeutic potential for cancers have also attracted researchers’ attention. Pharmacogenomic variability, including distinct genetic characteristics among different patients, can significantly affect pharmacokinetics and effectiveness of NSAIDs, which might determine the preventive or therapeutic success for cancer patients. Hence, a more comprehensive understanding in pharmacogenomic characteristics of NSAIDs and cancer-related inflammation would provide new insights into this appealing strategy. In this review, the up-to-date advances in clinical and experimental researches targeting cancer-related inflammation with NSAIDs are presented, and the potential of pharmacogenomics are discussed as well

Enhanced Anti-tumor of Pep-1 Modified Superparamagnetic Iron Oxide/PTX Loaded Polymer Nanoparticles

Superparamagnetic iron-oxide nanoparticle (SPION) has gained tremendous attention for drug delivery applications due to their unique properties. In this study, we developed a dual targeted delivery system with paclitaxel (PTX) and SPION co-loaded PLGA nanoparticles, modified with Pep-1 peptide (Pep-NP-SPION/PTX), to achieve magnetic targeting and active targeting for tumor treatment. SPION was synthesized by a co-precipitation method and was then encapsulated with PTX simultaneously into PLGA nanoparticles. After that, the non-complex was conjugated with Pep-1 through chemical modification. The resulting Pep-NP-SPION/PTX showed a spherical morphology and an average size of 100 nm. The enhancement cellular uptake of Pep-NP-SPION was demonstrated in in vitro through cell experiments. The IC50 value of Pep-NP-SPION/PTX and NP-SPION/PTX was determined to be 10.2 and 19.4 μg/mL, respectively. A biodistribution study showed that obvious higher accumulations of Pep-NP-SPION was observed in tumors, compared with that of non-targeting nanocomposites. Moreover, under the condition of a magnetic field, both NP-SPION and Pep-NP-SPION exhibited much higher tumor distribution. Furthermore, Pep-NP-SPION/PTX presented desirable in vivo anti-tumor effects based on active targeting and magnetic targeting characteristics. Altogether, Pep-NP-SPION/PTX can offer magnetic targeting and receptor mediated targeting to enhance the anti-tumor outcome

Altered gut microbiota profile in patients with perimenopausal panic disorder

IntroductionFemales in the perimenopausal period are susceptible to mood disorders. Perimenopausal panic disorder (PPD) is characterized by repeated and unpredictable panic attacks during perimenopause, and it impacts the patient's physical and mental health and social function. Pharmacotherapy is limited in the clinic, and its pathological mechanism is unclear. Recent studies have demonstrated that gut microbiota is strongly linked to emotion; however, the relation between PPD and microbiota is limitedly known.MethodsThis study aimed to discover specific microbiota in PPD patients and the intrinsic connection between them. Gut microbiota was analyzed in PPD patients (n = 40) and healthy controls (n = 40) by 16S rRNA sequencing.ResultsThe results showed reduced α-diversity (richness) in the gut microbiota of PPD patients. β-diversity indicated that PPD and healthy controls had different intestinal microbiota compositions. At the genus level, 30 species of microbiota abundance had significantly different between the PPD and healthy controls. In addition, HAMA, PDSS, and PASS scales were collected in two groups. It was found that Bacteroides and Alistipes were positively correlated with PASS, PDSS, and HAMA.DiscussionBacteroides and Alistipes dysbiosis dominate imbalanced microbiota in PPD patients. This microbial alteration may be a potential pathogenesis and physio-pathological feature of PPD. The distinct gut microbiota can be a potential diagnostic marker and a new therapeutic target for PPD

Dynamic modelling, simulation, and control of a vertical turret tunnelling machine

Tunnelling machines are utilized for many types of excavations in mining and civil engineering applications. To date, the control of tunnelling machines has not been automated to any significant extent. This thesis investigates the dynamic control of a vertical turret, boom-type tunnelling machine. Models of the actuators, kinematics, rigid body dynamics, and cutter-rock interaction are formulated. These models are validated through computer simulation. Controllers are then designed for the actuators using the pole-placement technique, in both continuous and discrete time. The controllers are tested in a variety of operational modes, using the computer simulation of the machine model. Results show that good tracking and disturbance rejection is achieved

Modelling and simulation of electric mining shovels

The electric mining shovel is the main rock loading machine at the majority of surface mining operations. The performance and utilization of these multi-million dollar machines can govern an entire mining operation. Despite their significance, they remain largely unexplored in terms of their potential. The thesis discusses the development of the forward and inverse kinematic models, the Newton-Euler dynamics, and the actuator dynamics for an electric mining shovel. The thesis relates to work undertaken towards the development of a mining shovel simulator, the purpose of which is to explore productivity and machine performance issues as a function of the interaction of the shovel with the ground. Both the parametric and nonparametric system identification results are presented, based on field test data collected from an operating mining shovel. Simulator results describing analytical and empirical models, as well as continuous-time controller and disturbance rejection are also presented. The thesis concludes with a discussion of planned continuing work