25 research outputs found
Uncovering Symptom Progression History from Disease Registry Data with Application to Young Cystic Fibrosis Patients
The growing availability of various disease registry data has brought precious opportunities to epidemiologists to understand the natural history of the registered diseases. It also presents challenges to the traditional data analysis techniques due to complicated censoring/truncation schemes and temporal dynamics of covariate influences. In a case study of the Cystic Fibrosis Foundation Patient Registry data, we propose analyses of progressive symptoms using temporal process regressions, as an alternative to the commonly employed proportional hazards models. Two end points are considered, the prevalence of ever positive and currently positive for Pseudomonas aeruginosa (PA) infection in the lungs, which capture different aspect of the disease process. The analysis of ever PA positive via a time-varying coefficient model demonstrates the lack of fit, as well as the potential loss of information, in the standard proportional hazards analysis. The analysis of currently PA positive yields results which are clinically meaningful and have not previously been reported in the cystic fibrosis literature. Our analyses demonstrate that prenatal/neonatal screening results in lower prevalence of PA infection compared to traditional diagnosis via signs and symptoms, but this benefit attenuates with age. Calendar years of diagnosis also affect the risk of PA infection; patients diagnosed in more recent cohort show higher prevalence of ever PA positive but lower prevalence of currently PA positive
Accelerated biological aging in COVID-19 patients
Chronological age is a risk factor for SARS-CoV-2 infection and severe COVID-19. Previous findings indicate that epigenetic age could be altered in viral infection. However, the epigenetic aging in COVID-19 has not been well studied. In this study, DNA methylation of the blood samples from 232 healthy individuals and 413 COVID-19 patients is profiled using EPIC methylation array. Epigenetic ages of each individual are determined by applying epigenetic clocks and telomere length estimator to the methylation profile of the individual. Epigenetic age acceleration is calculated and compared between groups. We observe strong correlations between the epigenetic clocks and individual's chronological age (r > 0.8, p < 0.0001). We also find the increasing acceleration of epigenetic aging and telomere attrition in the sequential blood samples from healthy individuals and infected patients developing non-severe and severe COVID-19. In addition, the longitudinal DNA methylation profiling analysis find that the accumulation of epigenetic aging from COVID-19 syndrome could be partly reversed at late clinic phases in some patients. In conclusion, accelerated epigenetic aging is associated with the risk of SARS-CoV-2 infection and developing severe COVID-19. In addition, the accumulation of epigenetic aging from COVID-19 may contribute to the post-COVID-19 syndrome among survivors. Age is a risk factor for SARS-CoV-2 infection and severe disease. Here the authors perform DNA methylation analyses in whole blood from COVID-19 patients using established epigenetic clocks and telomere length estimators, and describing correlations between epigenetic aging and the risk of SARS-CoV-2 infection and severe disease
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Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer
Background
We aimed to develop a radiomic model based on pre-treatment computed tomography (CT) to predict the pathological complete response (pCR) in patients with rectal cancer after neoadjuvant treatment and tried to integrate our model with magnetic resonance imaging (MRI)-based radiomic signature.
Methods
This was a secondary analysis of the FOWARC randomized controlled trial. Radiomic features were extracted from pre-treatment portal venous-phase contrast-enhanced CT images of 177 patients with rectal cancer. Patients were randomly allocated to the primary and validation cohort. The least absolute shrinkage and selection operator regression was applied to select predictive features to build a radiomic signature for pCR prediction (rad-score). This CT-based rad-score was integrated with clinicopathological variables using gradient boosting machine (GBM) or MRI-based rad-score to construct comprehensive models for pCR prediction. The performance of CT-based model was evaluated and compared by receiver operator characteristic (ROC) curve analysis. The LR (likelihood ratio) test and AIC (Akaike information criterion) were applied to compare CT-based rad-score, MRI-based rad-score and the combined rad-score.
Results
We developed a CT-based rad-score for pCR prediction and a gradient boosting machine (GBM) model was built after clinicopathological variables were incorporated, with improved AUCs of 0.997 [95% CI 0.990–1.000] and 0.822 [95% CI 0.649–0.995] in the primary and validation cohort, respectively. Moreover, we constructed a combined model of CT- and MRI-based radiomic signatures that achieve better AIC (75.49 vs. 81.34 vs.82.39) than CT-based rad-score (P = 0.005) and MRI-based rad-score (P = 0.003) alone did.
Conclusions
The CT-based radiomic models we constructed may provide a useful and reliable tool to predict pCR after neoadjuvant treatment, identify patients that are appropriate for a 'watch and wait' approach, and thus avoid overtreatment. Moreover, the CT-based radiomic signature may add predictive value to the MRI-based models for clinical decision making
Blood‐derived product therapies for SARS‐CoV‐2 infection and long COVID
Abstract Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is capable of large‐scale transmission and has caused the coronavirus disease 2019 (COVID‐19) pandemic. Patients with COVID‐19 may experience persistent long‐term health issues, known as long COVID. Both acute SARS‐CoV‐2 infection and long COVID have resulted in persistent negative impacts on global public health. The effective application and development of blood‐derived products are important strategies to combat the serious damage caused by COVID‐19. Since the emergence of COVID‐19, various blood‐derived products that target or do not target SARS‐CoV‐2 have been investigated for therapeutic applications. SARS‐CoV‐2‐targeting blood‐derived products, including COVID‐19 convalescent plasma, COVID‐19 hyperimmune globulin, and recombinant anti‐SARS‐CoV‐2 neutralizing immunoglobulin G, are virus‐targeting and can provide immediate control of viral infection in the short term. Non‐SARS‐CoV‐2‐targeting blood‐derived products, including intravenous immunoglobulin and human serum albumin exhibit anti‐inflammatory, immunomodulatory, antioxidant, and anticoagulatory properties. Rational use of these products can be beneficial to patients with SARS‐CoV‐2 infection or long COVID. With evidence accumulated since the pandemic began, we here summarize the progress of blood‐derived product therapies for COVID‐19, discuss the effective methods and scenarios regarding these therapies, and provide guidance and suggestions for clinical treatment
The Effects of Sleeve Gastrectomy on Glucose Metabolism and Glucagon-Like Peptide 1 in Goto-Kakizaki Rats
Purpose. To investigate the effects of sleeve gastrectomy (SG) on glucose metabolism and changes in glucagon-like peptide 1 (GLP-1) in Goto-Kakizaki (GK) rats. Methods. GK rats were randomly assigned to one of three groups: SG, SG pair-fed plus sham surgery (PF-sham), and ad libitum-fed no surgery (control). Food intake, body weight, blood glucose, GLP-1 and insulin levels, and GLP-1 expression in the jejunum and ileum were compared. Results. The SG rats exhibited lower postoperative food intake, body weight, and fasting glucose than did the control rats (P<0.05). SG significantly improved glucose and insulin tolerance (P<0.05). Plasma GLP-1 levels were higher in SG rats than in control or PF-sham rats in the oral glucose tolerance test (OGTT) (P<0.05). Blood glucose levels expressed as a percentage of baseline were higher in SG rats than in control rats after exendin (9-39) administration (P<0.05). The levels of GLP-1 expression in the jejunum and ileum were higher in SG rats than in PF-sham and control rats (P<0.05). Conclusions. Improvement of glucose metabolism by SG was associated with increased GLP-1 secretion. SG contributes to an increase in plasma GLP-1 levels via increased GLP-1 expression in the mucosa of the jejunum and/or ileum
Improved Survival Outcome and Access to Cancer Screening from Hemorrhoid in Patients with Rectal Cancer
Background. The interventions for hemorrhoid increase access to rectal cancer screening and thus might reduce cancer death. We aimed to examine the impact of hemorrhoid on survival outcomes in rectal cancer. Methods. We identified 510 patients with stage I to III rectal cancer from a prospectively collected database. Patients were divided into hemorrhoid and non-hemorrhoid group. The primary endpoints were disease-free survival (DFS) and overall survival (OS). Results. Hemorrhoid group had significantly more stage I-II diseases in comparison to nonhemorrhoid group (71.1% vs. 55.9%, P=0.049). The hemorrhoid group had significantly better DFS and OS compared to nonhemorrhoid group, the hazard ratios (HRs) of which were 0.39 (95% CI 0.17-0.88, P=0.018) and 0.33 (95% CI 0.12-0.92, P=0.034), respectively. Multivariate analysis revealed that hemorrhoid was independently associated with DFS [adjusted HR 0.43 (95% CI 0.17-0.95, P=0.045)]. A nomogram for predicting DFS outcome was generated based on hemorrhoid history, with a concordance index of 0.71 (95% CI 0.66-0.75, P<0.001). Conclusions. There may exist a screening effect and survival benefit from hemorrhoid in rectal cancer, which supports the significance of rectal cancer screening in lowering its mortality
Tight Focusing Properties of Ring Pearcey Beams with a Cross Phase
We theoretically investigated the properties of tightly focused ring Pearcey beams with a cross phase (CPRPB). The expressions of the distributions of both electric field and magnetic field in the focal region of an objective were first derived from the vectorial Debye theory, and then numerical calculations were carried out to obtain the focused intensity distribution and the Poynting vector of CPRPB near the focus. Numerical calculations indicate that as CPRPB is focused on an objective of high numerical aperture (NA), two nonuniform self-focusing spots occur at both sides of the geometrical focus of the objective symmetrically, and the angle between their directions is 90 degrees. The stronger is the strength of cross-phase modulation, the flatter are the ellipses of the self-focusing spots, and the smaller is the intensity at the geometrical focus of the objective. Numerical calculations also demonstrate that the optical gradient force produced by tightly focused CPRPB in the focal region can be manipulated in magnitude and in direction by tuning the strength of cross-phase modulation. Due to these properties of tightly focused CPRPB, they might find applications in the manipulation of micro- and nanoparticles and so on
Optical trapping forces of focused circular partially coherent beams on Rayleigh particles
The optical trapping forces of tightly-focused radially polarized circular partially coherent beams on Rayleigh particles are theoretically investigated. Numerical calculations are performed to study the optical trapping forces on Rayleigh particles for different initial coherent length of the incident circular partially coherent beams. The results show that the magnitude of the gradient force decreases with the reduction of the initial coherent length of the focused radially polarized circular partially coherent beams, while the balanced position (i.e., the position where the optical trapping forces becomes zero) stays constant. Moreover, the focused spot gradually elongates along the optical axis with the reduction of the initial coherent length, and the axial gradient force on Rayleigh particles also decreases gradually with the reduction of the intensity gradient in axial direction. As there exists an spherical aberrant in the focusing optical system, the focal spot in the direction of the optical axis becomes trumpet-shaped, and the optical trapping forces on Rayleigh particles change as well
Radiological lymph‐node size improves the prognostic value of systemic inflammation index in rectal cancer with pathologically negative nodes
Abstract Background The relationship between the radiological lymph node (rLN) size and survival outcome in node‐negative rectal cancer is still uncertain. In this study, we aimed to explore the role of enlarged rLN in predicting the survival of node‐negative rectal cancers. Methods We retrospectively reviewed the records of 722 node‐negative rectal cancer who underwent curative resection. Factors associated with DFS (disease‐free survival) and CSS (cancer‐specific survival) were assessed with univariate and multivariate analysis. Survival analysis was performed according to presence with or without enlarged rLN. Combining rLN with NLR as a new index‐inflammation immune score (IIS) for predicting survival. Comparing different models to assess the predictive powers. Results A total of 119 patients had tumor recurrence and 73 patients died due to cancer. Patients with enlarged rLN (≥5 mm) was significantly associated with better DFS (HR:0.517, 95%CI:0.339–0.787, p = 0.002) and CSS (HR:0.43, 95%CI:0.242–0.763, p = 0.004). The risk factors of recurrence were rLN, neutrophil‐lymphocyte ratio (NLR), CEA level, and distance from the anal verge. The risk of recurrence increased by 1.88‐ and 2.83‐fold for the high score in IIS compared with the low and intermediate score group (All p < 0.001). Similarly, the high score in IIS also increased the risk of cancer‐specific death. In the model comparison, the AIC and LR were improved by including the rLN into the NLR model for DFS and CSS prediction (All p < 0.05). Conclusions Node‐negative rectal cancer patients with enlarged rLN had a better survival outcome. IIS might be a more comprehensive and complete inflammation immune index for survival prediction
Aberrant methylation in neurofunctional gene serves as a hallmark of tumorigenesis and progression in colorectal cancer
Abstract Background DNA methylation is one of the most promising biomarkers in predicting the prognosis of colorectal cancer (CRC). We aimed to develop a DNA methylation biomarker that could evaluate the prognosis of CRC. Methods A promising DNA methylation biomarker was developed by hypermethylated genes in cancer tissue that were identified from Illumina EPIC methylation arrays. A cohort comprising 30 pairs of snap-frozen tumor tissue and adjacent normal tissue was used for correlation analysis between the methylation and expression status of the marker. The other cohort comprising 254 formalin-fixed paraffin-embedded (FFPE) tumor tissue from 254 CRC patients was used for prognosis analysis. Results Regulating synaptic membrane exocytosis 2 (RIMS2) was hypermethylated and lowly expressed in CRC comparing to adjacent normal tissue. Hypermethylation of RIMS2 in CRC was correlated with less frequent KRAS mutant and high differentiation. RIMS2 promoter methylation showed independent predictive value for survival outcome (P = 0.015, HR 1.992, 95% CI [(1.140–3.48)]), and a combination of RIMS2 methylation with KRAS status could predict prognosis better. Conclusions RIMS2 is frequently hypermethylated in CRC, which can silence the expression of RIMS2. RIMS2 methylation is a novel biomarker for predicting the prognosis of CRC