Factors associated with increased survival after surgical resection of glioblastoma in octogenarians.

Elderly patients with glioblastoma represent a clinical challenge for neurosurgeons and oncologists. The data available on outcomes of patients greater than 80 undergoing resection is limited. In this study, factors linked to increased survival in patients over the age of 80 were analyzed. A retrospective chart review of all patients over the age of 80 with a new diagnosis of glioblastoma and who underwent surgical resection with intent for maximal resection were examined. Patients who had only stereotactic biopsies were excluded. Immunohistochemical expression of oncogenic drivers (p53, EGFR, IDH-1) and a marker of cell proliferation (Ki-67 index) performed upon routine neuropathological examination were recorded. Stepwise logistic regression and Kaplan Meier survival curves were plotted to determine correlations to overall survival. Fifty-eight patients fit inclusion criteria with a mean age of 83 (range 80-93 years). The overall median survival was 4.2 months. There was a statistically significant correlation between Karnofsky Performance Status (KPS) and overall survival (P < 0.05). There was a significantly longer survival among patients undergoing either radiation alone or radiation and chemotherapy compared to those who underwent no postoperative adjuvant therapy (p < 0.05). There was also an association between overall survival and lack of p53 expression (p < 0.001) and lack of EGFR expression (p <0.05). In this very elderly population, overall survival advantage was conferred to those with higher preoperative KPS, postoperative adjuvant therapy, and lack of protein expression of EGFR and p53. These findings may be useful in clinical decision analysis for management of patients with glioblastoma who are octogenarians, and also validate the critical role of EGFR and p53 expression in oncogenesis, particularly with advancing age

Predicting Noise From Aircraft Turbine-Engine Combustors

COMBUSTOR and CNOISE are computer codes that predict far-field noise that originates in the combustors of modern aircraft turbine engines -- especially modern, low-gaseous-emission engines, the combustors of which sometimes generate several decibels more noise than do the combustors of older turbine engines. COMBUSTOR implements an empirical model of combustor noise derived from correlations between engine-noise data and operational and geometric parameters, and was developed from databases of measurements of acoustic emissions of engines. CNOISE implements an analytical and computational model of the propagation of combustor temperature fluctuations (hot spots) through downstream turbine stages. Such hot spots are known to give rise to far-field noise. CNOISE is expected to be helpful in determining why low-emission combustors are sometimes noisier than older ones, to provide guidance for refining the empirical correlation model embodied in the COMBUSTOR code, and to provide insight on how to vary downstream turbinestage geometry to reduce the contribution of hot spots to far-field noise

Characteristic distributions of finite-time Lyapunov exponents

We study the probability densities of finite-time or \local Lyapunov exponents (LLEs) in low-dimensional chaotic systems. While the multifractal formalism describes how these densities behave in the asymptotic or long-time limit, there are significant finite-size corrections which are coordinate dependent. Depending on the nature of the dynamical state, the distribution of local Lyapunov exponents has a characteristic shape. For intermittent dynamics, and at crises, dynamical correlations lead to distributions with stretched exponential tails, while for fully-developed chaos the probability density has a cusp. Exact results are presented for the logistic map, $x \to 4x(1-x)$. At intermittency the density is markedly asymmetric, while for `typical' chaos, it is known that the central limit theorem obtains and a Gaussian density results. Local analysis provides information on the variation of predictability on dynamical attractors. These densities, which are used to characterize the {\sl nonuniform} spatial organization on chaotic attractors are robust to noise and can therefore be measured from experimental data.Comment: To be appear in Phys. Rev

Growth and nutrition in children with Ataxia telangiectasia

Background: Ataxia telangiectasia (A-T) is a rare multisystem disease with high early mortality from lung disease and cancer. Nutritional failure adversely impacts outcomes in many respiratory diseases. Several factors influence nutrition in children with A-T. We hypothesised that children with A-T have progressive growth failure and that early gastrostomy tube feeding (percutaneous endoscopic gastrostomy, or PEG) is a favourable management option with good nutritional outcomes. Methods: Data were collected prospectively on weight, height and body mass index (BMI) at the national paediatric A-T clinic. Adequacy and safety of oral intake was assessed. Nutritional advice was given at each multidisciplinary review. Results: 101 children (51 girls) had 222 measurements (32 once, 32 twice, 24 thrice) between 2009 and 2016. Median (range) age was 9.3 (1.5 to 18.4) years. Mean (sd) weight, height and BMI Z-scores were respectively -1.03(1.57), -1.17 (1.18) and -0.36 (1.43). 35/101 children had weight Z-scores below -2 on at least one occasion. Weight, height and BMI Z-scores declined over time. Decline was most obvious after 8 years of age. 14/101 (13.9%) children had a PEG, with longitudinal data available for 12. In a nested case control study, there was a trend for improvement in weight in those with a PEG (p = 0.06). Conclusions: A-T patients decline in growth over time. There is an urgent need for new strategies, including an understanding of why growth falters. We suggest early proactive consideration of PEG from age 8 years onwards in order to prevent progressive growth failure

Comparison of Classification Algorithm for Crop Decision based on Environmental Factors using Machine Learning

Crop decision is a very complex process. In Agriculture it plays a vital role. Various biotic and abiotic factors affect this decision. Some crucial Environmental factors are Nitrogen Phosphorus, Potassium, pH, Temperature, Humidity, Rainfall. Machine Learning Algorithm can perfectly predict the crop necessary for this environmental condition. Various algorithms and model are used for this process such as feature selection, data cleaning, Training, and testing split etc. Algorithms such as Logistic regression, Decision Tree, Support vector machine, K- Nearest Neighbour, Navies Bayes, Random Forest. A comparison based on the accuracy parameter is presented in this paper along with various training and testing split for optimal choice of best algorithm. This comparison is done on two tools i.e., on Google collab using python and its libraries for implementation of Machine Learning Algorithm and WEKA which is a pre-processing tool to compare various algorithm of machine learning

Material Management: A Sustainable Way to Reduce the Wastage

In today’s world construction work are going at unexpected speed in all area like building, bridge, high-rise and so on. As we know there are two side of coin same way there are some disadvantage of this speedy construction which leads towards a wastage, like Material, Money, Time, and so on. One of the most important part of wastage is due to Improper Material Management. If we not prepare good management technic of material management than it convert in to wastage. It shall be very hard to manage wastage rather than managing the material. So if we want to manage the waste we need to manage the material in Proper Way. For that first of all we need to find out the importance of Phases of Material Management and Crucial Factors which affects the material management

Using atomistic solution scattering modelling to elucidate the role of the Fc glycans in human IgG4

Human immunoglobulin G (IgG) exists as four subclasses IgG1-4, each of which has two Fab subunits joined by two hinges to a Fc subunit. IgG4 has the shortest hinge with 12 residues. The Fc subunit has two glycan chains, but the importance of glycosylation is not fully understood in IgG4. Here, to evaluate the stability and structure of non-glycosylated IgG4, we performed a multidisciplinary structural study of glycosylated and deglycosylated human IgG4 A33 for comparison with our similar study of human IgG1 A33. After deglycosylation, IgG4 was found to be monomeric by analytical ultracentrifugation; its sedimentation coefficient of 6.52 S was reduced by 0.27 S in reflection of its lower mass. X-ray and neutron solution scattering showed that the overall Guinier radius of gyration RG and its cross-sectional values after deglycosylation were almost unchanged. In the P(r) distance distribution curves, the two M1 and M2 peaks that monitor the two most common distances within IgG4 were unchanged following deglycosylation. Further insight from Monte Carlo simulations for glycosylated and deglycosylated IgG4 came from 111,382 and 117,135 possible structures respectively. Their comparison to the X-ray and neutron scattering curves identified several hundred best-fit models for both forms of IgG4. Principal component analyses showed that glycosylated and deglycosylated IgG4 exhibited different conformations from each other. Within the constraint of unchanged RG and M1-M2 values, the glycosylated IgG4 models showed more restricted Fc conformations compared to deglycosylated IgG4, but no other changes. Kratky plots supported this interpretation of greater disorder upon deglycosylation, also observed in IgG1. Overall, these more variable Fc conformations may demonstrate a generalisable impact of deglycosylation on Fc structures, but with no large conformational changes in IgG4 unlike those seen in IgG1

Does Doxycycline work in synergy with cisplatin and oxaliplatin in colorectal cancer?

Background: In recent years, apart from antibacterial properties, doxycycline is reported to have cytotoxic and anti-proliferative actions in various cancers including colorectal cancer. Colorectal cancer constitutes one of the most common cancers in the western population. Apart from surgery, chemotherapy plays crucial role in the treatment of colorectal cancer. Cisplatin and oxaliplatin are most commonly used platinum compounds for the cancer chemotherapy. This study has looked for any impact of doxycycline on the cytotoxic effects of platinum compounds in colorectal cancer including its mechanisms of actions.Methods: HT 29 colorectal cancer cells were used for this study. These cells were treated with cisplatin and oxaliplatin with or without doxycycline treatment. The caspase 3 gene expression was quantitated by gel electrophoresis and qualitated by real time polymerase chain reactions. The caspase 3 activity was assessed in HT 29 cells with fluorescence kit.Results: The results revealed increased caspase 3 gene expressions and activities in HT 29 cells treated with cisplatin, oxaliplatin and doxycycline; however the combination of doxycycline with cisplatin and oxaliplatin did not report increased caspase 3 gene expressions and activity compared to cisplatin and oxaliplatin alone.Conclusion: We concluded that doxycycline has role in apoptosis induction in the colorectal cancer. However, it did not show any synergy with platinum compounds in the colorectal cancer cells. This study also pointed towards possible caspase-independent actions of doxycycline with cisplatin and oxaliplatin. However, further work is required to underpin the mechanisms of actions of doxycycline