Identifying Prognostic Groups Using Machine Learning Tools in Patients Undergoing Chemoradiation for Inoperable Locally Advanced Nonsmall Cell Lung Carcinoma

Introduction Unresectable stage III nonsmall cell lung cancer (NSCLC) continues to have dismal 5-year overall survival (OS) rate. However, a subset of the patients treated with chemoradiation show significantly better outcome. Prediction of treatment outcome can be improved by utilizing machine learning tools, such as cluster analysis (CA), and is capable of identifying complex interactions among many variables. We have utilized CA to identify a cluster with good prognosis within stage III NSCLC. Materials and Methods Retrospective analysis of treatment outcomes was done for 92 patients who underwent chemoradiation for inoperable locally advanced NSCLC from 2012 to 2018. Using various patient- and treatment-related variables, an exploratory factor analysis was performed to extract factors with eigenvalue > 1. An appropriate number of homogeneous groups were identified using agglomerative hierarchical cluster analysis. Further K-mean cluster analysis was applied to classify each patient into their homogeneous clusters. The newly formed cluster variable was used as an independent variable to estimate survival over time using Kaplan–Meier method. Results With a median follow-up of 18 months, median OS was 14 months. Using CA, three prognostic clusters were obtained. Cluster 2 with 36 patients had a median OS of 36 months, whereas Cluster 1 with 34 patients had a median OS of 20 months (p = 0.004). Conclusion A cluster could thus be identified with a relatively good prognosis within stage III NSCLC. Using CA, we have attempted to create a model which may provide more specific prognostic information in addition to that provided by tumor node metastasis-based models

Plan quality assessment of modern radiotherapy delivery techniques in left-sided breast cancer: an analysis stratified by target delineation guidelines

Objective: This study compares planning techniques stratified by consensus delineation guidelines in patients undergoing whole-breast radiotherapy based on an objective plan quality assessment scale. Methods: 10 patients with left-sided breast cancer were randomly selected, and target delineation for intact breast was performed using Tangent (RTOG 0413), ESTRO, and RTOG guidelines. Consensus Plan Quality Metric (PQM) scoring was defined and communicated to the physicist before commencing treatment planning. Field-in-field IMRT (FiF), inverse IMRT (IMRT) and volumetric modulated arc therapy (VMAT) plans were created for each delineation. Statistical analyses utilised a two-way repeated measures analysis of variance, after applying a Bonferroni correction. Results: Total PQM score of plans for Tangent and ESTRO were comparable for FiF and IMRT techniques (FiF vs IMRT for Tangent, p = 0.637; FiF vs IMRT for ESTRO, p = 0.304), and were also significantly higher compared to VMAT. Total PQM score of plans for RTOG revealed that IMRT planning achieved a significantly higher score compared to both FiF and VMAT (IMRT vs FiF, p &lt; 0.001; IMRT vs VMAT, p &lt; 0.001). Conclusions: Total PQM scores were equivalent for FiF and IMRT for both Tangent and ESTRO delineations, whereas IMRT was best suited for RTOG delineation. Advances in knowledge: FiF and IMRT planning techniques are best suited for ESTRO or Tangent delineations. IMRT also yields better results with RTOG delineation. </jats:sec

Studies on two polyherbal formulations (ZPTO and ZTO) for comparison of their antidyslipidemic, antihypertensive and endothelial modulating activities

Background Cardiovascular disorders (CVDs) are the leading cause of disease burden worldwide. Apart from available synthetic drugs used in CVDs, there are many herbal formulations including POL-10 (containing 10 herbs), which have been shown to be effective in animal studies but POL-10 was found to cause tachycardia in rodents as its side effect. This study was designed to modify the composition of POL-10 for better efficacy and/or safety profile in CVDs. Methods To assess the antidyslipidemic, antihypertensive and endothelial modulatory properties of two herbal formulations, (ZPTO and ZTO) containing Z: Zingiber officinalis, P: Piper nigrum, T: Terminalia belerica and O: Orchis mascula, different animal models including, tyloxapol and high fat diet-induced dyslipidemia and spontaneously hypertensive rats (SHR) were used. Effect on endothelial function was studied using isolated tissue bath set up coupled with PowerLab data acquisition system. The antioxidant activity was carried out using DPPH radical-scavenging assay. Results Based on preliminary screening of the ingredients of POL-10 in tyloxapol-induced hyperlipidemic rats, ZPTO and ZTO containing four active ingredients namely; Z, P, T and O were identified for further studies and comparison. In tyloxapol-induced hyperlipidemic rats, both ZPTO and ZTO caused significant reduction in serum triglyceride (TG) and total cholesterol (TC). In high fat diet-fed rats, ZPTO decreased TC, low-density lipoproteins cholesterol (LDL-C) and atherogenic index (AI). ZTO also showed similar effects to those of ZPTO with additional merits being more effective in reducing AI, body weight and more importantly raising high-density lipoproteins. In SHR, both formulations markedly reduced systolic blood pressure, AI and TG levels, ZTO being more potent in reversing endothelial dysfunction while was devoid of cardiac stimulatory effect. In addition, ZTO also reduced LDL-C and improved glucose levels in SHR. In DPPH radical-scavenging activity test, ZTO was also more potent than ZPTO. Conclusion The modified formulation, ZTO was not only found more effective in correcting cardiovascular abnormalities than ZPTO or POL-10 but also it was free from tachycardiac side-effect, which might be observed because of the presence of Piper nigrum in ZPTO

Addition of magnesium chloride to enhance mono-dispersity of a coiled-coil recombinant mouse macrophage protein

X-ray crystallography for the determination of three-dimensional structures of protein macromolecules represents an important tool in function assignment of uncharacterized proteins. However, crystallisation is often difficult to achieve. A protein sample fully characterized in terms of dispersity may increase the likelihood of successful crystallisation by improving the predictability of the crystallisation process. To maximize the probability of crystallisation of a novel mouse macrophage protein (rMMP), target molecule was characterized and refined to improve monodispersity. Addition of MgCl2 at low concentrations resolves the rMMP into a monodisperse solution, and finally successful crystallization of rMMP was achieved. The effect of MgCl2 was studied using gel filtration chromatography and dynamic light scattering