The value of carcinoembryonic antigen stage in staging, prognosis, and management of colorectal cancer: results from two cohort studies

BackgroundCombining the carcinoembryonic antigen (CEA) level (C stage) with TNM staging can provide a more comprehensive prognostic assessment of colorectal cancer (CRC). However, the clinical value of incorporating CEA status into the TNM staging system needs to be evaluated.MethodsWe used the SEER database (N = 49,350) and a retrospective cohort from China (N = 1,440). A normal CEA level was staged as C0 and an elevated CEA level was staged as C1. Restricted cubic spline analysis was used to examine the dose-response relationship between the CEA level and survival. The Kaplan-Meier method with the log-rank test was used to plot survival curves. Multivariable Cox proportional hazards regression models with forward stepwise variable selection were used to estimate the hazard ratios and 95% confidence intervals.ResultsPatients with C1 were more likely to have advanced disease than those with C0. CEA on a continuous scale was positively associated with mortality risk. Compared with patients with C0 stage, those with C1 stage had significantly lower survival rates. In the SEER dataset, C1 was independently associated with poor prognosis in patients with CRC, with an approximately 70% increased risk of mortality. Patients with C1 stage had significantly lower survival than those with C0 stage at all clinical stages. Incorporating the C stage into the TNM staging refined the prediction of prognosis of patients with CRC, with a gradual decline in prognosis from stage I C0 to stage IV C1. A similar pattern was observed in the present retrospective cohort study. At each lymph node stage, patients with C1 had significantly lower 5-year survival rates than patients with C0. Compared with lymph node positivity, CEA positivity may have a stronger correlation with a worse prognosis.ConclusionOur findings not only validated the independent prognostic significance of CEA in CRC but also demonstrated its enhanced prognostic value when combined with TNM staging. Our study provides evidence supporting the inclusion of C stage in the TNM staging system

The fast light of CsI(Na) crystals

The responds of different common alkali halide crystals to alpha-rays and gamma-rays are tested in our research. It is found that only CsI(Na) crystals have significantly different waveforms between alpha and gamma scintillations, while others have not this phenomena. It is suggested that the fast light of CsI(Na) crystals arises from the recombination of free electrons with self-trapped holes of the host crystal CsI. Self-absorption limits the emission of fast light of CsI(Tl) and NaI(Tl) crystals.Comment: 5 pages, 11 figures Submit to Chinese Physics

Serum creatinine/cystatin C ratio as a prognostic indicator for patients with colorectal cancer

BackgroundThis study aimed to explore the relationship between creatinine/cystatin C ratio and progression-free survival (PFS) and overall survival (OS) in colorectal cancer (CRC) patients undergoing surgical treatment.MethodsA retrospective analysis was conducted on 975 CRC patients who underwent surgical resection from January 2012 to 2015. Restricted three-sample curve to display the non-linear relationship between PFS/OS and creatinine-cystatin C ratio. Cox regression model and Kaplan-Meier method were used to evaluate the effect of the creatinine-cystatin C ratio on the survival of CRC patients. Prognostic variables with p-value ≤0.05 in multivariate analysis were used to construct prognostic nomograms. The receiver operator characteristic curve was used to compare the efficacy of prognostic nomograms and the traditional pathological stage.ResultsThere was a negative linear relationship between creatinine/cystatin C ratio and adverse PFS in CRC patients. Patients with low creatinine/cystatin C ratio had significantly lower PFS/OS than those with high creatinine/cystatin C ratio (PFS, 50.8% vs. 63.9%, p = 0.002; OS, 52.5% vs. 68.9%, p < 0.001). Multivariate analysis showed that low creatinine/cystatin C ratio was an independent risk factor for PFS (HR=1.286, 95%CI = 1.007–1.642, p=0.044) and OS (HR=1.410, 95%CI=1.087–1.829, p=0.010) of CRC patients. The creatinine/cystatin C ratio-based prognostic nomograms have good predictive performance, with a concordance index above 0.7, which can predict the 1–5-year prognosis.ConclusionCreatinine/cystatin C ratio may be an effective prognostic marker for predicting PFS and OS in CRC patients, aid in pathological staging, and along with tumour markers help in-depth prognostic stratification in CRC patients

Antidepressant Effects of Repetitive Transcranial Magnetic Stimulation Over Prefrontal Cortex of Parkinson's Disease Patients With Depression: A Meta-Analysis

Objective: The purpose of this meta-analysis was to investigate the antidepressant effects of repetitive transcranial magnetic stimulation (rTMS) over the prefrontal cortex (PFC) of patients with Parkinson's disease (PD) and to determine the optimal rTMS parameters, such as the intensity, frequency and the delivered pattern of rTMS stimulation.Methods: EMBASE, PubMed, Web of Science, MEDLINE, and Cochrane data bases were researched for papers published before March 12, 2018. Studies investigating the anti-depression effects of rTMS over PFC in patients with PD were considered. The main outcomes of pre- and post-rTMS treatment as well as score changes were all extracted. The mean effect size was estimated by calculating the standardized mean difference (SMD) with 95% confidence interval (CI) by using fixed or random effect models as appropriate.Results: Nine studies containing 137 PD patients with depression were included. The pooled results showed significant pre-post anti-depressive effects of rTMS over PFC in PD patients with depression (SMD = −0.80, P < 0.00001). The subgroup analyses of stimulation intensity, frequencies, and models also revealed significant effects (Intensities: 90% RMT: SMD = −1.16, P = 0.0006; >100% RMT: SMD = −0.82, P < 0.0001. Frequencies: < 1.0 Hz: SMD = −0.83, P = 0.03; 5.0 Hz: SMD = −1.10, P < 0.0001; ≥10.0 Hz: SMD = −0.55, P = 0.02. Models: Continuous: SMD = −0.79, P < 0.0001; Discontinuous: SMD = −0.84, P = 0.02). But the results of the studies with place-controlled designs were not significant (Overall: SMD = −0.27, P = 0.54. Intensities: 90% RMT: SMD = 0.27, P = 0.68; 100% RMT: SMD = −0.32, P = 0.33. Frequencies: 5.0 Hz: SMD = −0.87, P = 0.10; ≥10.0 Hz: SMD = 0.27, P = 0.66. Models: Continuous: SMD = −0.28, P = 0.68; Discontinuous: SMD = −0.32, P = 0.33). The greater effect sizes of rTMS with 90% RMT, 5.0 Hz in discontinuous days can be observed rather than the other parameters in both kinds of analyses across study design.Conclusions: rTMS may have a significant positive pre-post anti-depressive effect over PFC on patients with depression, especially by using 5.0 Hz frequency with 90% RMT intensity in discontinuous days, which may produce better effects than other parameters. The real effect, though, was not different from that of the placebo. Future studies with larger sample sizes and high-quality studies are needed to further corroborate our results and to identify the optimal rTMS protocols

Childhood Sexual Abuse and the Development of Recurrent Major Depression in Chinese Women

Background Our prior study in Han Chinese women has shown that women with a history of childhood sexual abuse (CSA) are at increased risk for developing major depression (MD). Would this relationship be found in our whole data set? Method Three levels of CSA (non-genital, genital, and intercourse) were assessed by self-report in two groups of Han Chinese women: 6017 clinically ascertained with recurrent MD and 5983 matched controls. Diagnostic and other risk factor information was assessed at personal interview. Odds ratios (ORs) were calculated by logistic regression. Results We confirmed earlier results by replicating prior analyses in 3,950 new recurrent MD cases. There were no significant differences between the two data sets. Any form of CSA was significantly associated with recurrent MD (OR 4.06, 95% confidence interval (CI) [3.19–5.24]). This association strengthened with increasing CSA severity: non-genital (OR 2.21, 95% CI 1.58–3.15), genital (OR 5.24, 95% CI 3.52–8.15) and intercourse (OR 10.65, 95% CI 5.56–23.71). Among the depressed women, those with CSA had an earlier age of onset, longer depressive episodes. Recurrent MD patients those with CSA had an increased risk for dysthymia (OR 1.60, 95%CI 1.11–2.27) and phobia (OR 1.41, 95%CI 1.09–1.80). Any form of CSA was significantly associated with suicidal ideation or attempt (OR 1.50, 95% CI 1.20–1.89) and feelings of worthlessness or guilt (OR 1.41, 95% CI 1.02–2.02). Intercourse (OR 3.47, 95%CI 1.66–8.22), use of force and threats (OR 1.95, 95%CI 1.05–3.82) and how strongly the victims were affected at the time (OR 1.39, 95%CI 1.20–1.64) were significantly associated with recurrent MD

Roadmap on spatiotemporal light fields

Spatiotemporal sculpturing of light pulse with ultimately sophisticated structures represents the holy grail of the human everlasting pursue of ultrafast information transmission and processing as well as ultra-intense energy concentration and extraction. It also holds the key to unlock new extraordinary fundamental physical effects. Traditionally, spatiotemporal light pulses are always treated as spatiotemporally separable wave packet as solution of the Maxwell's equations. In the past decade, however, more generalized forms of spatiotemporally nonseparable solution started to emerge with growing importance for their striking physical effects. This roadmap intends to highlight the recent advances in the creation and control of increasingly complex spatiotemporally sculptured pulses, from spatiotemporally separable to complex nonseparable states, with diverse geometric and topological structures, presenting a bird's eye viewpoint on the zoology of spatiotemporal light fields and the outlook of future trends and open challenges.Comment: This is the version of the article before peer review or editing, as submitted by an author to Journal of Optics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from i

Associations of Educational Attainment, Occupation, Social Class and Major Depressive Disorder among Han Chinese Women

Background The prevalence of major depressive disorder (MDD) is higher in those with low levels of educational attainment, the unemployed and those with low social status. However the extent to which these factors cause MDD is unclear. Most of the available data comes from studies in developed countries, and these findings may not extrapolate to developing countries. Examining the relationship between MDD and socio economic status in China is likely to add to the debate because of the radical economic and social changes occurring in China over the last 30 years. Principal findings We report results from 3,639 Chinese women with recurrent MDD and 3,800 controls. Highly significant odds ratios (ORs) were observed between MDD and full time employment (OR = 0.36, 95% CI = 0.25–0.46, logP = 78), social status (OR = 0.83, 95% CI = 0.77–0.87, logP = 13.3) and education attainment (OR = 0.90, 95% CI = 0.86–0.90, logP = 6.8). We found a monotonic relationship between increasing age and increasing levels of educational attainment. Those with only primary school education have significantly more episodes of MDD (mean 6.5, P-value = 0.009) and have a clinically more severe disorder, while those with higher educational attainment are likely to manifest more comorbid anxiety disorders. Conclusions In China lower socioeconomic position is associated with increased rates of MDD, as it is elsewhere in the world. Significantly more episodes of MDD occur among those with lower educational attainment (rather than longer episodes of disease), consistent with the hypothesis that the lower socioeconomic position increases the likelihood of developing MDD. The phenomenology of MDD varies according to the degree of educational attainment: higher educational attainment not only appears to protect against MDD but alters its presentation, to a more anxious phenotype

Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins

<p>Abstract</p> <p>Background</p> <p>Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residue preferences have been widely used in many studies but the results are often not satisfactory. Although different amino acid compositions among the interaction sites of different complexes have been observed, such differences have not been integrated into the prediction process. Furthermore, the evolution information has not been exploited to achieve a more powerful propensity.</p> <p>Result</p> <p>In this study, the residue interface propensities of four kinds of complexes (homo-permanent complexes, homo-transient complexes, hetero-permanent complexes and hetero-transient complexes) are investigated. These propensities, combined with sequence profiles and accessible surface areas, are inputted to the support vector machine for the prediction of protein binding sites. Such propensities are further improved by taking evolutional information into consideration, which results in a class of novel propensities at the profile level, i.e. the binary profiles interface propensities. Experiment is performed on the 1139 non-redundant protein chains. Although different residue interface propensities among different complexes are observed, the improvement of the classifier with residue interface propensities can be negligible in comparison with that without propensities. The binary profile interface propensities can significantly improve the performance of binding sites prediction by about ten percent in term of both precision and recall.</p> <p>Conclusion</p> <p>Although there are minor differences among the four kinds of complexes, the residue interface propensities cannot provide efficient discrimination for the complicated interfaces of proteins. The binary profile interface propensities can significantly improve the performance of binding sites prediction of protein, which indicates that the propensities at the profile level are more accurate than those at the residue level.</p

Prediction of protein binding sites in protein structures using hidden Markov support vector machine

<p>Abstract</p> <p>Background</p> <p>Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance.</p> <p>Results</p> <p>In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Common features derived from protein sequences and structures, including protein sequence profile and residue accessible surface area, are used to train hidden Markov support vector machine. When tested on six data sets, the method based on hidden Markov support vector machine shows better performance than some state-of-the-art methods, including artificial neural networks, support vector machines and conditional random field. Furthermore, its running time is several orders of magnitude shorter than that of the compared methods.</p> <p>Conclusion</p> <p>The improved prediction performance and computational efficiency of the method based on hidden Markov support vector machine can be attributed to the following three factors. Firstly, the relation between labels of neighbouring residues is useful for protein binding site prediction. Secondly, the kernel trick is very advantageous to this field. Thirdly, the complexity of the training step for hidden Markov support vector machine is linear with the number of training samples by using the cutting-plane algorithm.</p