The use of isotretinoin for acne – an update on optimal dosing,surveillance, and adverse effects

ABSTRACT

Introduction

Acne is a chronic, inflammatory, and immune mediated disease of pilosebaceous unit, highly prevalent in adolescents. It involves face, trunk, and back; may leave scars and affect quality of life. Early, effective, and safe treatment is the key for disease resolution. Oral isotretinoin is the unique treatment for cure or prolonged remission for moderate and severe acne, preventing psychosocial impact and scars. It inhibits sebaceous glands activity and has anti-inflammatory and immunoregulatory properties.     

BCL2 G quadruplex-binding small molecules: Current status and prospects for the development of next-generation anticancer therapeutics

B cell lymphoma 2 (BCL2) overexpression in a range of human tumors is often related to chemotherapy resistance and poor prognosis. GC-rich regions upstream of the P1 promoter in human BCL2 can form G-quadruplex (G4) structures through the stacking of four Hoogsteen-paired guanine bases. Stabilizing the G4 fold implies the inhibition of BCL2 expression and, thus, small molecules that selectively bind to the G4 are promising anticancer candidates. In this review, we discuss the structural aspects, binding affinity, selectivity, and biological activity of well-characterized BCL2 G4 binding ligands in vitro and in vivo. We also explore future directions in the research and development of G4-based anticancer therapeutics.     

Matters of size: Roles of hyaluronan in CNS aging and disease

Involvement of extracellular matrix (ECM) components in aging and age-related neurodegeneration is not well understood. The role of hyaluronan (HA), a major extracellular matrix glycosaminoglycan, in malignancy and inflammation is gaining new understanding. In particular, the differential biological effects of high molecular weight (HMW-HA) and low molecular weight hyaluronan (LMW-HA), and the mechanism behind such differences are being uncovered. Tightly regulated in the brain, HA can have diverse effects on cellular development, growth and degeneration. In this review, we summarize the homeostasis and signaling of HA in healthy tissue, discuss its distribution and ontogeny in the central nervous system (CNS), summarize evidence for its involvement in age-related neurodegeneration and Alzheimer Disease (AD), and assess the potential of HA as a therapeutic target in the CNS.     

Metabolic and Nutritional Issues Associated with Spinal Muscular Atrophy

Spinal muscular atrophy (SMA), the main genetic cause of infant death, is a neurodegenerative disease characterized by the selective loss of motor neurons in the anterior horn of the spinal cord, accompanied by muscle wasting. Pathomechanically, SMA is caused by low levels of the survival motor neuron protein (SMN) resulting from the loss of the SMN1 gene. However, emerging research extends the pathogenic effect of SMN deficiency beyond motor neurons. A variety of metabolic abnormalities, especially altered fatty acid metabolism and impaired glucose tolerance, has been described in isolated cases of SMA; therefore, the impact of SMN deficiency in metabolic abnormalities has been speculated. Although the life expectancy of these patients has increased due to novel disease-modifying therapies and standardization of care, understanding of the involvement of metabolism and nutrition in SMA is still limited. Optimal nutrition support and metabolic monitoring are essential for patients with SMA, and a comprehensive nutritional assessment can guide personalized nutritional therapy for this vulnerable population. It has recently been suggested that metabolomics studies before and after the onset of SMA in patients can provide valuable information about the direct or indirect effects of SMN deficiency on metabolic abnormalities. Furthermore, identifying and quantifying the specific metabolites in SMA patients may serve as an authentic biomarker or therapeutic target for SMA. Here, we review the main epidemiological and mechanistic findings that link metabolic changes to SMA and further discuss the principles of metabolomics as a novel approach to seek biomarkers and therapeutic insights in SMA.     

Machine intelligence in peptide therapeutics: A next-generation tool for rapid disease screening

Discovery and development of biopeptides are time-consuming, laborious, and dependent on various factors. Data-driven computational methods, especially machine learning (ML) approach, can rapidly and efficiently predict the utility of therapeutic peptides. ML methods offer an array of tools that can accelerate and enhance decision making and discovery for well-defined queries with ample and sophisticated data quality. Various ML approaches, such as support vector machines, random forest, extremely randomized tree, and more recently deep learning methods, are useful in peptide-based drug discovery. These approaches leverage the peptide data sets, created via high-throughput sequencing and computational methods, and enable the prediction of functional peptides with increased levels of accuracy. The use of ML approaches in the development of peptide-based therapeutics is relatively recent; however, these techniques are already revolutionizing protein research by unraveling their novel therapeutic peptide functions. In this review, we discuss several ML-based state-of-the-art peptide-prediction tools and compare these methods in terms of their algorithms, feature encodings, prediction scores, evaluation methodologies, and software utilities. We also assessed the prediction performance of these methods using well-constructed independent data sets. In addition, we discuss the common pitfalls and challenges of using ML approaches for peptide therapeutics. Overall, we show that using ML models in peptide research can streamline the development of targeted peptide therapies.     

The tyrosine kinase inhibitor nilotinib has antineoplastic activity in prostate cancer cells but up-regulates the ERK survival signal—Implications for targeted therapies

BackgroundNovel therapeutic options beyond hormone ablation and chemotherapy are urgently needed for patients with advanced prostate cancer. Tyrosine kinase inhibitors (TKIs) are an attractive option as advanced prostate cancers show a highly altered phosphotyrosine proteome. However, despite favorable initial clinical results, the combination of the TKI dasatinib with docetaxel did not result in improved patient survival for reasons that are not known in detail.MethodsThe National Cancer Institute–Approved Oncology Drug Set II was used in a phenotypic drug screen to identify novel compounds with antineoplastic activity in prostate cancer cells. Validation experiments were carried out in vitro and in vivo.ResultsWe identified the TKI nilotinib as a novel compound with antineoplastic activity in hormone-refractory prostate cancer cells. However, further analyses revealed that treatment with nilotinib was associated with a significant up-regulation of the phospho-extracellular-signal-regulated kinases (ERK) survival signal. ERK blockade alone led to a significant antitumoral effect and enhanced the cytotoxicity of nilotinib when used in combination.ConclusionsOur findings underscore that TKIs, such as nilotinib, have antitumoral activity in prostate cancer cells but that survival signals, such as ERK up-regulation, may mitigate their effectiveness. ERK blockade alone or in combination with TKIs may represent a promising therapeutic strategy in advanced prostate cancer.