Molecular Mechanism of Puerarin Against Diabetes and its Complications

Puerarin is a predominant component of Radix Puerarin. Despite its anti-tumor and anti-virus effects and efficacy in improving cardiovascular or cerebrovascular diseases and preventing osteoporosis, it has been shown to protect against diabetes and its complications. This review summarizes the current knowledge on Puerarin in diabetes and related complications, aiming to provide an overview of antidiabetic mechanisms of Puerarin and new targets for treatment.

Understanding and managing pain in the arthritic synovial joint: an update

Osteoarthritis is a very common cause of chronic pain in dogs and cats. Great progress has been made in the last 2–3 decades in unravelling the molecular mediators of joint pain. Now we are starting to see the benefits of this research in terms of new targets to block joint pain and new medicines reaching our pharmacy shelves. This review summarises the progress that has been made in understanding why and how arthritic joints cause pain. This will help readers understand novel medicines and provide insight into the others that might follow in the future.

Strategies employed to evade the host immune response and the mechanism of drug resistance in Mycobacterium tuberculosis: In search of finding new targets

: The partial effectiveness of the host immune response to M. tuberculosis drives bacteria into a latent state, but it is difficult to eliminate the bacteria completely. Usually, this latent condition of M. tuberculosis is reversible, and reactivation of tuberculosis is the leading cause of the majority of transmission. A number of studies performed on animal models and in humans have not yet provided a detailed understanding of the mechanisms or correlates of immunity of M. tuberculosis infection or why there is a significant immunity failure to remove the pathogen. Moreover, the mechanism of resistance involved in drug-resistant M. tuberculosis leading to the emergence of strains of bacteria that show significant resistance to the majority of anti-tuberculosis drugs. We have also provided the recent findings and trends regarding the development of new drug molecules to treat drug and multidrug-resistant tuberculosis and the advancements in immunotherapy in the treatment of drug-resistant tuberculosis. This article provides an in-depth and critical analysis of various strategies employed by the drug-resistant M. tuberculosis to escape the host immune response, as a result of which this bacterium persists in the host for a longer period of time and leads to the development of tuberculosis infection. Furthermore, we also discussed the new targets for the effective treatment of drug resistant tuberculosis.

The Discovery of New Drug-Target Interactions for Breast Cancer Treatment

Drug–target interaction (DTIs) prediction plays a vital role in probing new targets for breast cancer research. Considering the multifaceted challenges associated with experimental methods identifying DTIs, the in silico prediction of such interactions merits exploration. In this study, we develop a feature-based method to infer unknown DTIs, called PsePDC-DTIs, which fuses information regarding protein sequences extracted by pseudo-position specific scoring matrix (PsePSSM), detrended cross-correlation analysis coefficient (DCCA coefficient), and an FP2 format molecular fingerprint descriptor of drug compounds. In addition, the synthetic minority oversampling technique (SMOTE) is employed for dealing with the imbalanced data after Lasso dimensionality reduction. Then, the processed feature vectors are put into a random forest classifier to perform DTIs predictions on four gold standard datasets, including nuclear receptors (NR), G-protein-coupled receptors (GPCR), ion channels (IC), and enzymes (E). Furthermore, we explore new targets for breast cancer treatment using its risk genes identified from large-scale genome-wide genetic studies using PsePDC-DTIs. Through five-fold cross-validation, the average values of accuracy in NR, GPCR, IC, and E datasets are 95.28%, 96.19%, 96.74%, and 98.22%, respectively. The PsePDC-DTIs model provides us with 10 potential DTIs for breast cancer treatment, among which erlotinib (DB00530) and FGFR2 (hsa2263), caffeine (DB00201) and KCNN4 (hsa3783), as well as afatinib (DB08916) and FGFR2 (hsa2263) are found with direct or inferred evidence. The PsePDC-DTIs model has achieved good prediction results, establishing the validity and superiority of the proposed method.

New Targets for PET Imaging of Myeloma

Recent advances in the treatment of multiple myeloma (MM) have increased the need for accurate diagnosis and detection of minimal residual disease (MRD), disease characterization and localization, and response evaluation and prognostication. Positron emission tomography (PET)/computed tomography (CT) imaging combines molecular and morphological information and has been shown to be especially valuable in this disease. The most frequently used PET tracer in MM is the glucose analog 18F-fluorodeoxyglucose ([18F]FDG). [18F]FDG PET/CT has a sensitivity for detection of MM between 80% to 100% and is currently the main imaging modality for assessing treatment response and for determining MRD. However, 18F-FDG PET/CT has some limitations, and imaging with alternative tracers that may overcome these constraints should be further explored. This article discusses new targets for PET/CT imaging in the assessment of MM.