Peripheral blood-derived inflammation-based scores such as the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) have recently been proposed as prognostic markers in solid ...tumours. Although evidence to support these markers as unfavourable prognostic factors is more compelling in gastrointestinal cancers, very little is known of their impact on breast cancer. We investigated the association between the NLR and PLR, and overall survival after breast cancer.
Data from the University of Malaya Medical Centre Breast Cancer Registry was used. Of 2059 consecutive patients diagnosed from 2000 to 2008, we included 1435 patients with an available pre-treatment differential blood count (∼70%). Patients were stratified into quintiles of the NLR/PLR. Multivariable Cox regression was used to determine the independent prognostic significances of the NLR/PLR.
Compared with the first quintile of the NLR, women in quintile 5 were younger, had bigger tumours, nodal involvement, distant metastases and higher tumour grades. Higher NLR quintiles were significantly associated with poorer survival with a 5-year relative survival ratio (RSR) of 76.4% (95% CI: 69.6-82.1%) in quintile 1, 79.4% (95% CI: 74.4-83.7%) in quintile 2, 72.1% (95% CI: 66.3-77.3%) in quintile 3, 65.6% (95% CI: 59.8-70.8%) in quintile 4 and 51.1% (95% CI: 43.3-58.5%) in quintile 5. Following adjustment for demography, tumour characteristics, treatment and the PLR, the adjusted hazard ratio (HR) for quintile 5 vs quintile 1 was 1.50 (95% CI: 1.08-1.63); Ptrend=0.004. Results were unchanged when the NLR was analysed as a dichotomous variable using different cutoff points. Although patients in PLR quintile 5 had lower survival than in quintile 1 (5-year RSR: 53.2% (95% CI: 46.9-59.2%) vs 77.0% (95% CI: 70.9-82.2%)), this association was not significant after multivariable adjustment. However, a PLR >185 was significantly associated with poorer survival; adjusted HR: 1.25 (95% CI: 1.04-1.52).
Both the NLR and PLR are independently associated with an increased risk of mortality in breast cancer. Their added value in the prognostication of breast cancer in clinical practice warrants investigation.
Prussian blue (PB) is a good candidate as cathode material in potassium ion batteries (KIB) due to its high electrochemical performance. Thus, to verify the performance, the structural and electronic ...properties of PB were performed using first-principles studies based on the density functional theory (DFT) method. The properties of PB, KPB and K
2
PB were calculated using the Cambridge Serial Total Energy Package (CASTEP) computer code. From the geometrical optimization of pure PB, the generalized gradient approximation for Perdew-Burke-Ernzerhof (GGA-PBE) functional shows the most comparable structural properties compared to local density approximation by Ceperley and Adler as parameterized by Perdew and Zunger (LDA-CAPZ) and the generalized gradient approximation for Perdew-Burke-Ernzerhof for solids (GGA-PBEsol) functional. In addition, the electronic properties of the pure PB band gap is 0.72 eV which is slightly underestimated from the experimental value. Thus, the Hubbard U was used to broaden the bands crossing the Fermi level. The band gap using GGA-PBE + U is 1.77 eV, whereU for Fe
3+
is 6 eV and Fe
2+
is 4 eV. The calculations of the total and partial density of states (pDOS) present the Fe, C and N orbitals at the valence band and conduction band. Other electronic properties such as electron density were also calculated. The intercalation voltage with different numbers of K
+
in PB is calculated to be 4.33 and 1.40 V for KPB and K
2
PB, respectively. It was found that the calculated voltage has been improved near the experimental value. Therefore, the first-principles calculation in this work can give more understanding of the behavior of pure PB, KPB and K
2
PB for its uses as cathode material in KIB.
Construction on problematic soil that has low bearing capacity, low shear strength, high compressibility, and high water-content will interfere with the smooth construction process and will affect ...time and cost due to repetitive maintenance. Pavement built on problematic soil as its subgrade is exposed to pavement failures, such as fatigue cracking, longitudinal cracking, and pumping, owing to swelling or shrinkage due to moisture variation and differential settlement. Therefore, improvement of the ground needs to commence so as to improve its load bearing capacity, in order to sustain the load on top of it. Consequently, the main aim of this study is to determine the effectiveness of crumb tyre rubber mixed with soil samples as one of the soil stabilisation techniques and to establish the optimum usage percentage of crumb tyre rubber as a stabiliser. Clayey sand soil was mixed with 5%, 10% and 15% of crumb tyre rubber by weight of the soil sample and was tested for physical properties, such as particle size distribution and plasticity index. In obtaining the changes in strength, mixed clayey sand-crumb tyre rubber samples were subjected to compaction and California Bearing Ratio (CBR) tests. The results showed that the increment of crumb tyre rubber percentage as an additive, increased the CBR value and therefore enhanced the strength of the modified soil. However, the crumb tyre rubber stabiliser affected the optimum moisture content and maximum dry density of the modified samples by decreasing their values. The optimum percentage of crumb tyre rubber mixture was found to be 10% by weight at the end of this study. These findings indicate that the measured crumb tyre rubber is suitable for supporting the clayey sand soil for the subgrade of pavement construction.
ABSTRAK: Pembinaan di atas tanah bermasalah yang mengandungi kapasiti galas rendah, kekuatan ricih rendah, kebolehmampatan tinggi dan kandungan air tinggi akan mengganggu kelancaran proses pembinaan dan akan menjejaskan kekangan masa dan wang akibat penyelenggaraan berulang. Jalan raya yang dibina di atas tanah yang bermasalah akan mengalami kegagalan turapan seperti keretakan, rekahan membujur dan pengepaman, disebabkan oleh subgrednya terdedah kepada pembengkakan atau pengecutan akibat perubahan kelembapan dan pemendapan berbeza. Oleh itu, penambah baikan tanah perlu dilakukan bagi mencapai kapasiti galas beban lebih baik untuk menampung beban di atasnya. Oleh itu, tujuan utama kajian ini adalah bagi menentukan keberkesanan serpihan tayar getah yang dicampur dengan sampel tanah sebagai salah satu teknik penstabilan tanah dan menentukan peratusan optimum penggunaan tayar getah sebagai penstabil. Tanah pasir liat sebagai bahan utama dalam kajian ini dicampur dengan 5%, 10% dan 15% serbuk tayar getah mengikut berat sampel tanah dan telah diuji sifat fizikalnya, seperti taburan saiz zarah dan indeks keplastikan. Perubahan dalam kekuatan ditentukan dengan cara menggaul sebatian sampel tayar getah bersama pasir tanah liat dan diuji dengan eksperimen pemadatan dan ujian Nisbah Bearing California (CBR). Dapatan kajian menunjukkan bahawa penambahan peratusan serbuk tayar getah sebagai bahan penstabil telah meningkatkan nilai CBR dan sekaligus meningkatkan kekuatan tanah yang diubah suai. Walau bagaimanapun, penstabil tayar getah mempengaruhi kandungan lembapan optimum dan ketumpatan kering maksimum sampel yang diubah suai dengan nilai berkurang. Pada akhir kajian ini, peratusan optimum bancuhan serbuk tayar getah yang diperolehi adalah sebanyak 10% berat sampel. Dapatan ini menunjukkan bahawa tayar getah remah adalah sesuai dalam menyokong tanah pasir liat bagi subgred pembinaan turapan.
A simple and contactless intensity modulated displacement sensor is proposed and demonstrated for sensing uric acid concentration. For a concentration change of uric acid from 0 ppm to 500 ppm, two ...peak voltages are obtained from the displacement curve correspond to the highest reflectivity of each concentration. Those peak light intensities increase linearly with the concentration due to the increase of the refractive index of the uric acid solution. This implies that the higher concentration of uric acid tends to detect a stronger signal. The measured sensitivities are obtained at 0.0015 V/ppm and 0.0016 V/ppm for the first peak voltage and second peak voltage respectively. The result showed the percentage of similarity for the first peak to the second peak is almost 94% and the linearity more than 97% for both peak voltages is obtained suggested the consistency of the sensor system. The stability and simplicity of the contactless sensor offer a good and valuable opportunity for many applications especially in the hazardous chemical, pharmaceutical, process control and diagnostic sectors.
Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be ...improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question.
Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes.
Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors.
Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.
Previous phytochemical studies from the Aglaia genus reported the presence of terpenoid compound. This research describes the isolation and structure elucidation of sesquiterpend compound from the ...stembark of Aglaia simplicifolia. Dried stembark of A. simplicifolia extracted with methanol and then partitioned with n-hexane, ethyl acetate, and n-butanol, respectively. The n-hexane extract then was separated and purified with chromatography techniques to obtain isolated compound. The chemical structure of isolated compound was elucidated by IR, NMR 1D, NMR 2D as well as mass spectra and by comparison with those previously reported spectra data. The compound identified as senecrassidiol. This compound showed cytotoxicity activity against HeLa cervical cancer cells with IC50 values of 2.18 µM.
Breast cancer survival prediction can have an extreme effect on selection of best treatment protocols. Many approaches such as statistical or machine learning models have been employed to predict the ...survival prospects of patients, but newer algorithms such as deep learning can be tested with the aim of improving the models and prediction accuracy. In this study, we used machine learning and deep learning approaches to predict breast cancer survival in 4,902 patient records from the University of Malaya Medical Centre Breast Cancer Registry. The results indicated that the multilayer perceptron (MLP), random forest (RF) and decision tree (DT) classifiers could predict survivorship, respectively, with 88.2 %, 83.3 % and 82.5 % accuracy in the tested samples. Support vector machine (SVM) came out to be lower with 80.5 %. In this study, tumour size turned out to be the most important feature for breast cancer survivability prediction. Both deep learning and machine learning methods produce desirable prediction accuracy, but other factors such as parameter configurations and data transformations affect the accuracy of the predictive model.
Although an association between protein‐truncating variants and breast cancer risk has been established for 11 genes, only alterations in BRCA1, BRCA2, TP53 and PALB2 have been reported in Asian ...populations. Given that the age of onset of breast cancer is lower in Asians, it is estimated that inherited predisposition to breast cancer may be more significant. To determine the potential utility of panel testing, we investigated the prevalence of germline alterations in 11 established and 4 likely breast cancer genes in a cross‐sectional hospital‐based cohort of 108 moderate to high‐risk breast cancer patients using targeted next generation sequencing. Twenty patients (19%) were identified to carry deleterious mutations, of whom 13 (12%) were in the BRCA1 or BRCA2, 6 (6%) were in five other known breast cancer predisposition genes and 1 patient had a mutation in both BRCA2 and BARD1. Our study shows that BRCA1 and BRCA2 account for the majority of genetic predisposition to breast cancer in our cohort of Asian women. Although mutations in other known breast cancer genes are found, the functional significance and breast cancer risk have not yet been determined, thus limiting the clinical utility of panel testing in Asian populations.
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