Cysteine Cathepsin Protease Inhibition: An update on its Diagnostic, Prognostic and Therapeutic Potential in Cancer

In keeping with recent developments in basic research; the importance of the Cathepsins as targets in cancer therapy have taken on increasing importance and given rise to a number of key areas of interest in the clinical setting. In keeping with driving basic research in this area in a translational direction; recent findings have given rise to a number of exciting developments in the areas of cancer diagnosis; prognosis and therapeutic development. As a fast-moving area of research; the focus of this review brings together the latest findings and highlights the translational significance of these developments

Integrative p53, micro-RNA and Cathepsin Protease Co-Regulatory Expression Networks in Cancer

As the direct regulatory role of p53 and some of its isoform proteins are becoming established in modulating gene expression in cancer research, another aspect of this mode of gene regulation that has captured significant interest over the years is the mechanistic interplay between p53 and micro-RNA transcriptional regulation. The input of this into modulating gene expression for some of the cathepsin family members has been viewed as carrying noticeable importance based on their biological effects during normal cellular homeostasis and cancer progression. While this area is still in its infancy in relation to general cathepsin gene regulation, we review the current p53-regulated micro-RNAs that are generating significant interest through their regulation of cathepsin proteases, thereby strengthening the link between activated p53 forms and cathepsin gene regulation. Additionally, we extend our understanding of this developing relationship to how such micro-RNAs are being utilized as diagnostic or prognostic tools and highlight their future uses in conjunction with cathepsin gene expression as potential biomarkers within a clinical setting

Quality of life and adherence to therapy in patients with chronic heart failure who were remotely monitored by chatbot compared to the standard follow-up group for 3 months

BACKGROUND: Chronic heart failure (CHF) is one of the leading causes of death. Telemedicine and remote monitoring (RM) are a way to increase life expectancy and quality of life in patients with CHF. Methods based on messengers familiar to patients promote adherence and do not require additional training. AIM: To compare quality of life and adherence to therapy in patients with CHF who were on RM using a chatbot compared to the standard follow-up (SFU) group for 3 months. METHODS: Patients with CHF on optimal drug therapy discharged from the hospital were included in the study. Comparison groups were formed according to the method of observation, particularly, RM and SFU. A chatbot was set up for patients in the RM group. Monitoring was done using a seven-question survey sent daily. The signs of decompensation (red flags [RF]) were increased edema, dyspnea, body weight 2 kg per week, and changes in individual parameters of heart rate and blood pressure. If a RF was detected, telephone contact was made, and the therapy was corrected if necessary. Quality of life was assessed according to the Minnesota Quality of Life Questionnaire for patients with CHF (highest, 0 points; lowest, 105 points), and adherence was assessed using the Adherence Scale of the National Society for Evidence-based Pharmacotherapy. RESULTS: A total of 60 patients were included in the study; 37 patients completed a 3-month follow-up. The RM group (n=17, 13 men, 76.5%; median age 61 [51; 62]) and comparison group (n=20, 14 men, 70%; mean age 64.98.9) were comparable according to the functional class (New York Heart Association), but differed in ejection fraction (42.813% versus 53.210.4% [p 0.05]). Adherence to the chat-bot was 67.2%. Adherence to therapy was not significantly different between the RM and SFU groups accounting for (17 [100%]) and (18 [90%], respectively, (p=0.62). In the RM group, RF was detected in 7 (41%) patients. Only one patient required correction of therapy. Patients in the RM group required no referral to a medical facility, whereas 2 patients in the SFU group required medical care. Quality of life was statistically significantly higher in the RM group, reaching 28.713.9 points compared to 37.717.9 points in the SFU group (p=0.04). CONCLUSIONS: After 3 months, patients in the RM group were committed to the chatbot, with adherence to therapy comparable to the SFU group. Quality of life was statistically significantly higher in the RM group. Patients in the RM group did not go to medical facilities, in contrast to the SFU group. The limitations of the study were the small sample size and short follow-up period. The results require further research to obtain additional data

BH3-mimetics:recent developments in cancer therapy

Abstract The hopeful outcomes from 30 years of research in BH3-mimetics have indeed served a number of solid paradigms for targeting intermediates from the apoptosis pathway in a variety of diseased states. Not only have such rational approaches in drug design yielded several key therapeutics, such outputs have also offered insights into the integrated mechanistic aspects of basic and clinical research at the genetics level for the future. In no other area of medical research have the effects of such work been felt, than in cancer research, through targeting the BAX-Bcl-2 protein-protein interactions. With these promising outputs in mind, several mimetics, and their potential therapeutic applications, have also been developed for several other pathological conditions, such as cardiovascular disease and tissue fibrosis, thus highlighting the universal importance of the intrinsic arm of the apoptosis pathway and its input to general tissue homeostasis. Considering such recent developments, and in a field that has generated so much scientific interest, we take stock of how the broadening area of BH3-mimetics has developed and diversified, with a focus on their uses in single and combined cancer treatment regimens and recently explored therapeutic delivery methods that may aid the development of future therapeutics of this nature

Theoretical Study of Dissociative Hydrogen Chemisorption on MgB2 Nanotubes

Теоретическое исследование процесса диссоциативной хемосорбции водорода на внешней и внутренней поверхностях нанотруб состава MgB2 показало возможность применения данного материала в качестве эффективного сорбента водорода.The dissociative chemisorption of hydrogen on the external and internal surfaces of MgB2 nanotubes is investigated by the ab-initio DFT method. It was shown that this material may be effective sorbent of hydrogen for the hydrogen energy industry

Theoretical Study of Dissociative Hydrogen Chemisorption on MgB2 Nanotubes

Теоретическое исследование процесса диссоциативной хемосорбции водорода на внешней и внутренней поверхностях нанотруб состава MgB2 показало возможность применения данного материала в качестве эффективного сорбента водорода.The dissociative chemisorption of hydrogen on the external and internal surfaces of MgB2 nanotubes is investigated by the ab-initio DFT method. It was shown that this material may be effective sorbent of hydrogen for the hydrogen energy industry

Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults

Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p< 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling