High-throughput digital quantification of Alzheimer disease pathology and associated infrastructure in large autopsy studies

High-throughput digital pathology offers considerable advantages over traditional semiquantitative and manual methods of counting pathology. We used brain tissue from 5 clinical-pathologic cohort studies of aging; the Religious Orders Study, the Rush Memory and Aging Project, the Minority Aging Research Study, the African American Clinical Core, and the Latino Core to (1) develop a workflow management system for digital pathology processes, (2) optimize digital algorithms to quantify Alzheimer disease (AD) pathology, and (3) harmonize data statistically. Data from digital algorithms for the quantification of β-amyloid (Aβ, n = 413) whole slide images and tau-tangles (n = 639) were highly correlated with manual pathology data (r = 0.83 to 0.94). Measures were robust and reproducible across different magnifications and repeated scans. Digital measures for Aβ and tau-tangles across multiple brain regions reproduced established patterns of correlations, even when samples were stratified by clinical diagnosis. Finally, we harmonized newly generated digital measures with historical measures across multiple large autopsy-based studies. We describe a multidisciplinary approach to develop a digital pathology pipeline that reproducibly identifies AD neuropathologies, Aβ load, and tau-tangles. Digital pathology is a powerful tool that can overcome critical challenges associated with traditional microscopy methods.

Developing a futuristic multi-objective optimization of the fuel management problems for the nuclear research reactors

In this paper, at the same time, two separate objectives and two safety and operational constraints are chosen to optimize fuel reloading pattern of a Material Testing Reactor (MTR), independently and coherently. This is one of the most difficult type of engineering problems as a constrained, non-continuous, combinatorial, and fully multi-objective optimization problem. Decision space is a non-continuous multimodal space restricted by both of the combinatorial and safety constraints. A smart software application and a robust hybrid algorithm have been developed to get Pareto optimal set with respect to both of the economy of irradiating utilizations and nuclear safety based on the heuristic soft computing. The hybrid algorithm is composed of a fast and elitist Multi-Objective Genetic Algorithm (MOGA) and a fast fitness function evaluating system based on the semi-deep learning cascade feed forward Artificial Neural Networks (ANNs). The smart software is used to produce database automatically required for the ANN training and test data. It can be also used to revise data accurately, impose further irradiating benefits or Operating Limits and Conditions (OLCs), and to advise the reactor supervisor on the most desire pattern based on the smart searches and filtering. The results are highly promising. For more details, optimization results dominate conventional operating core parameters, significantly. Also chosen OLCs are protected. Furthermore, this is very good practice to reach a fully developed practical application of the complex soft computing for the nuclear fuel management problems.

Developing a futuristic multi-objective optimization of the fuel management problems for the nuclear research reactors

In this paper, at the same time, two separate objectives and two safety and operational constraints are chosen to optimize fuel reloading pattern of a Material Testing Reactor (MTR), independently and coherently. This is one of the most difficult type of engineering problems as a constrained, non-continuous, combinatorial, and fully multi-objective optimization problem. Decision space is a non-continuous multimodal space restricted by both of the combinatorial and safety constraints. A smart software application and a robust hybrid algorithm have been developed to get Pareto optimal set with respect to both of the economy of irradiating utilizations and nuclear safety based on the heuristic soft computing. The hybrid algorithm is composed of a fast and elitist Multi-Objective Genetic Algorithm (MOGA) and a fast fitness function evaluating system based on the semi-deep learning cascade feed forward Artificial Neural Networks (ANNs). The smart software is used to produce database automatically required for the ANN training and test data. It can be also used to revise data accurately, impose further irradiating benefits or Operating Limits and Conditions (OLCs), and to advise the reactor supervisor on the most desire pattern based on the smart searches and filtering. The results are highly promising. For more details, optimization results dominate conventional operating core parameters, significantly. Also chosen OLCs are protected. Furthermore, this is very good practice to reach a fully developed practical application of the complex soft computing for the nuclear fuel management problems.

Endothelial cell-glucocorticoid receptor interactions and regulation of Wnt signaling

Vascular inflammation is present in many cardiovascular diseases, and exogenous glucocorticoids have traditionally been used as a therapy to suppress inflammation. However, recent data have shown that endogenous glucocorticoids, acting through the endothelial glucocorticoid receptor, act as negative regulators of inflammation. Here, we performed ChIP for the glucocorticoid receptor, followed by next-generation sequencing in mouse endothelial cells to investigate how the endothelial glucocorticoid receptor regulates vascular inflammation. We identified a role of the Wnt signaling pathway in this setting and show that loss of the endothelial glucocorticoid receptor results in upregulation of Wnt signaling both in vitro and in vivo using our validated mouse model. Furthermore, we demonstrate glucocorticoid receptor regulation of a key gene in the Wnt pathway, Frzb, via a glucocorticoid response element gleaned from our genomic data. These results suggest a role for endothelial Wnt signaling modulation in states of vascular inflammation.

Simulation and analysis of the Loss of Flow Accident (LOFA) scenarios for an open pool type research reactor by using the RELAP5/MOD3.2 code

In this paper, a 5 MW open pool type research reactor is simulated and analyzed to check and pass a complete and practical safety assessment against various LOFA scenarios. Generally, LOFA may occur in a research reactor when the reactor primary pump or the safety flapper valve fail. The simulation includes the study of a downward core cooling system circulated by the gravity driven force, the performance and failure effects of the safety flapper valve, the flow reversal mode and transition, the natural convection mode, different possible types of LOFA, and impacts of the surrounding empty boxes. First of all, the code nodalization is successfully benchmarked against available experimental data of the reactor operating parameters. Then, all possible DBAs in this field of study are simulated and discussed in detail. Results are completely satisfactory to simulate and analyze a pool-type research reactor in response to LOFA using the RELAP5 code. Furthermore, transients including the natural convection mode and even flow reversal mode are following naturally without any oscillation or source of errors. Finally, TRR is completely safe against the DBA type of LOFA scenarios.

Prognostic factors in survival of colorectal cancer patients after surgery

OBJECTIVE

To determine the factors affecting survival, following resection of large bowel for colorectal carcinoma.

METHOD

From the cancer database of a single referral institution, a total of 1090 patients who had undergone colorectal resection between 1999 and 2002 were identified. Cases with recurrent colorectal cancer or previous history of neoadjuvant chemotherapy were excluded. Survival curves were plotted using the Kaplan-Meier method. Univariate analysis of factors thought to influence survival was then made using Logrank test. Criteria studied consisted of age, sex, TNM stage, T-status, nodal status, distant metastasis, histological grade, lymphatic and vascular invasion, tumour location, preoperative carcinoembryonic antigen (CEA) level and liver function tests. Multivariate analysis was conducted using Cox regression analysis.

RESULTS

The mean survival time for all patients was 42.8 (SEM = 2.8) months. The overall 1-, 3- and 5-year survival rates were 72%, 54% and 47%, respectively. In univariate analysis, patients' age (P < 0.0001), TNM stage (P < 0.0001), T-status (P = 0.015), nodal status (P = 0.016), distant metastasis (P < 0.0001), grade (P = 0.005), lymphatic and vascular invasion (P < 0.0001) and presurgery CEA level > 5 ng/ml (P = 0.021) were found to be predictors that could affect survival. In Cox regression analysis, age (P < 0.0001), TNM stage (P = 0.001) and grade (P = 0.008) were determined as independent prognostic factors of survival.

CONCLUSION

Age, TNM stage, T-status, nodal status, distant metastasis, grade, lymphatic and vascular invasion and presurgery CEA level can predict the postsurgical survival rate in patients with colorectal cancer.

[Dysphagia and cervical osteophytosis: case report and review of the literature]

Dysphagia with anterior osteophytosis of the cervical bone is a more and more reported affection, especially after the age of 60. However it remains a rare event. The cause to effect relationship between these two entities should be documented by a complete assessment. Surgical treatment is reserved for patients whose medical treatment has failed. We describe an original case of cervical bone osteophytosis which was diagnosed during an acute and febrile aphagia and review the literature about its assessment and treatment.

Medialization framework surgery for voice improvement after endoscopic cordectomy

Seven dysphonic patients who had previously undergone total or extended cordectomy underwent laryngeal framework medialization. A minimum 6-month period between cordectomy and framework surgery was enforced to allow the vocal cord to scar and form a fibrous "neocord", to evaluate the voice recovery achieved by speech therapy alone and avoid the risk of operating on a patient with undiagnosed early recurrence. The operation is performed with fiberscopic control under general anesthesia. These operating conditions are required because undermining the fibrous tissue at the inner side of the thyroid ala is a lengthy and laborious procedure. This step is necessary to ensure easy placement of the implant. Caution must be taken to avoid tearing the fibrous tissue, with consequent risk of prosthesis extrusion. The cartilage window is left intact. Whereas cartilage implants remain indicated for minor gaps, we advocate Friedrich's implant for wider gaps. The vocal outcome revealed an increased median maximum phonation time from 5 s (range 2-12 s) to 7.5 s (range 3-23 s); a reduced phonation quotient from 516.5 ml/s (range 235-1000 ml/s) to 222 ml/s (range 146-595 ml/s); a slightly increased modal intensity from 61.5 dB (range 57-75 dB) to 67 dB (range 46-68 dB); an improved intensity range from 24.5 dB (range 16-36 dB) to 30 dB (range 16-62 dB); a steady fundamental frequency from 150 Hz (range 132-290) to 152 Hz (range 125-200); and an increased median spectral analysis class from 2 (range 1-3) to 3 (range 2-4). Subjectively, the patients noted that, throughout the day, phonation required less effort and induced less vocal fatigue.