scholarly journals Systematically understanding the key roles of microglia in AD development

2019 ◽  
Author(s):  
Zhiwei Ji ◽  
Changan Liu ◽  
Weiling Zhao ◽  
Claudio Soto ◽  
Xiaobo Zhou
Keyword(s):  
Late Stage ◽  
Early Stage ◽  
The United States ◽  
Scale Model ◽  
Drug Candidates ◽  
Multi Scale ◽  
Age Related ◽  
Activation Profile ◽  
Current Therapies ◽  
Optimal Therapeutic Strategy

AbstractAlzheimer’s disease (AD) is the leading cause of age-related dementia, affecting over 5 million people in the United States. Unfortunately, current therapies are largely palliative and several potential drug candidates have failed in late-stage clinical trials. Studies suggest that microglia-mediated neuroinflammation might be responsible for the failures of various therapies. Microglia contribute to Aβ clearance in the early stage of neurodegeneration and may contribute to AD development at the late stage by releasing pro-inflammatory cytokines. However, the activation profile and phenotypic changes of microglia during the development of AD are poorly understood. To systematically understand the key role of microglia in AD progression and predict the optimal therapeutic strategyin silico, we developed a 3D multi-scale model of AD (MSMAD) by integrating multi-level experimental data, to manipulate the neurodegeneration in a simulated system. Based on our analysis, we revealed how TREM2-related signal transduction leads to an imbalance in the activation of different microglia phenotypes, thereby promoting AD development. Our MSMAD model also provides an optimal treatment strategy for improving the outcome of AD treatment.

Effect of Screening Mammography on Breast Cancer Detection and Mortality

2021 ◽  
pp. 164-169
Author(s):  
Myrlene Jeudy ◽  
Monique Swain ◽  
Mark Pearlman
Keyword(s):  
Breast Cancer ◽  
New England ◽  
Late Stage ◽  
Mammography Screening ◽  
Early Stage ◽  
Breast Cancer Incidence ◽  
The United States ◽  
Population Based ◽  
Screening Mammography ◽  
Trend Data

This widely discussed study by Bleyer and Welch published in The New England Journal of Medicine (NEJM) “The Effects of Three Decades of Screening Mammography on Breast Cancer Incidence” concluded that screening mammography leads to a substantial overdiagnosis of early breast cancer (estimated 69% increase) while only having a small effect on late-stage breast cancer (estimated 8% decrease). In a population-based observational study, the authors utilized trend data from the Surveillance, Epidemiology and End Results (SEER) database to examine trends on the incidence and stage of early- versus late-stage breast cancer at the time of diagnosis. They compared 2 time frames: prior to widespread mammography screening (1976–1978) and after mammography screening was introduced in the United States (2006––2008). This article reviews this NEJM article and describes several methodological assumptions by the authors that have been soundly criticized and the associated limitations. As a result of these limitations, there was an exaggeration of the overdiagnosis of early-stage disease with mammography and, more importantly, a substantial underestimate of the impact of mammography on decreasing late-stage breast cancer.

Multi-Scale Numerical Model for Groundwater flow Simulation of a Karst Tunnel in Kunming,China

2020 ◽  
Author(s):  
Mo Xu ◽  
Jihong Qi ◽  
Yige Tang ◽  
Xiao Li ◽  
JIan Guo
Keyword(s):  
Groundwater Flow ◽  
Water Level ◽  
Large Scale ◽  
Early Stage ◽  
Water Discharge ◽  
Scale Model ◽  
Small Scale ◽  
Tunnel Construction ◽  
Multi Scale ◽  
Pipe Model

<p>Due to the inhomogeneity of the carbonate rocks and discreteness of the karst water, delineation of the groundwater flow within karst area remains a challenging task as yet. Based on KunCheng tunnel of a water diversion project in KunMing, multi-scale groundwater flow models were set upto simulate the groundwater flow. Large scale model was used to obtain the boundary conditions and hydrogeological parameters, which were then assigned to the small scale model.The small scale model was generalized as an equivalent continuous medium, and two karst pipelines are established  by module River. After then,  the multi-scale numerical modelswere used to simulate the  groundwater seepage field and predict the recovery of groundwater after tunnel construction. The main results and conclusions are as follows.</p><p>(1)Black karst pipeline and white karst pipeline systems share one recharge source but have two independent discharge systems. The recharge source is the exposed karst rock in the northeast part of study area. Obstructed by aluminum clay rock of P<sub>1</sub>d, groundwater discharge is divided into two parts during the runoff process.</p><p>(2)During the tunnel construction process, the water level at the exit of White karst pipeline reduced 9m in pipe model B<sub>1</sub> while reduced 10m in the solution fissure model B<sub>2</sub>, both two models suggest that the tunnel construction will cause the drainage of White karst pipeline exit. The water level at the exit of black karst pipeline reduced 1m in pipe model B<sub>1</sub> while reduced 4m in the solution fissure model B<sub>2</sub>.</p><p>(3)In model B<sub>1</sub>, total water discharge during tunnel construction is 69876m<sup>3</sup>/d, in model B<sub>2</sub> , the total water discharge is 95817 m<sup>3</sup>/d  and  is much larger than model B<sub>1</sub> due to the quick groundwater transporting and exchange in karst pipeline..</p><p>(4)After the tunnel construction, exits of two pipelines and observation well see the water level recovery because of the formation sealing . The recovery trend is relatively rapid in the early stage, and slow in the later stage. It takes 8.5 years and 10 years for the exits of black and white pipelines and observation wells to reach the original water level, respectively. During the recovery process, groundwater exchange form was changing from pipe supplying aquifer to aquifer supplying pipe, which made model B<sub>2</sub> recovered faster than model B<sub>1</sub> in early stage, and vice versa.</p><p>Using large scale model combining with secondary scale model, and the module River to generalize karst pipeline can reflect the flow dynamic characteristics of karst pipeline effectively.</p>

scholarly journals Automatic Drusen Segmentation for Age-Related Macular Degeneration in Fundus Images Using Deep Learning

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1617
Author(s):  
Quang T. M. Pham ◽  
Sangil Ahn ◽  
Su Jeong Song ◽  
Jitae Shin
Keyword(s):  
Deep Learning ◽  
Macular Degeneration ◽  
Early Stage ◽  
Age Related Macular Degeneration ◽  
Fundus Images ◽  
Main Aspect ◽  
Multi Scale ◽  
Age Related ◽  
Segmentation Task ◽  
Deep Learning Model

Drusen are the main aspect of detecting age-related macular degeneration (AMD). Ophthalmologists can evaluate the condition of AMD based on drusen in fundus images. However, in the early stage of AMD, the drusen areas are usually small and vague. This leads to challenges in the drusen segmentation task. Moreover, due to the high-resolution fundus images, it is hard to accurately predict the drusen areas with deep learning models. In this paper, we propose a multi-scale deep learning model for drusen segmentation. By exploiting both local and global information, we can improve the performance, especially in the early stages of AMD cases.

Changes in early- and late-stage colorectal cancer incidence during the era of screening: 1976-2009.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 1522-1522
Author(s):  
Daniel X Yang ◽  
Cary Philip Gross ◽  
James B. Yu
Keyword(s):  
Colorectal Cancer ◽  
United States ◽  
Cancer Screening ◽  
Cancer Incidence ◽  
Late Stage ◽  
Early Stage ◽  
The United States ◽  
Screening Colonoscopy ◽  
The Past ◽  
Colorectal Cancer Incidence

1522 Background: Ideally, screening detects cancer at a more curable stage, and as a result decreases the incidence of subsequent diagnosis at a late stage. Whereas breast cancer screening is suggested to have led to a substantial increase in the number of early-stage cancers diagnosed in the United States with only marginal reductions in the number of late stage cancers, the impact of colorectal cancer screening on cancer incidence is unknown. Methods: Colorectal cancer incidence data spanning over three decades, 1976—2009, were collected from the Surveillance, Epidemiology, and End Result (SEER) database. Screening utilization data spanning 1986—2010 were collected from the National Health Survey (NHS) progress reports. We examined trends in the incidence of early-stage (in situ, local) and late-stage (regional, distant) colorectal cancer among adults 50 years or older. Results: Over the past three decades, the incidence of late-stage colorectal cancer decreased significantly, from 118 to 74 cases per 100,000 people—a 37% decrease. The incidence of early-stage colorectal cancer also decreased, from 77 to 67 cases per 100,000 people. There was also an associated increase in the utilization rates of screening colonoscopy. From 1987 to 2010—the years for which NHS data were available—the percentage of adults 50 and older who received screening colonoscopy rose from 27% to 63%. After adjusting for trends in cancer incidence in non-screened populations, we estimated that colorectal screening was associated with a reduction of approximately 550,000 cases of colorectal cancer over the past three decades in the United States. Using the most conservative assumption of constant cancer incidence during the past three decades, 235,000 cases of colorectal cancer were prevented. Conclusions: There has been a significant decline in both early and late stage colorectal cancer diagnoses, during a time of increasing rates of increased screening.

Three-dimensional Reconstruction of Microscopic Image Based on Multi-ST Algorithm

2020 ◽  
Vol 64 (2) ◽  
pp. 20506-1-20506-7
Author(s):  
Min Zhu ◽  
Rongfu Zhang ◽  
Pei Ma ◽  
Xuedian Zhang ◽  
Qi Guo
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Scale Model ◽  
Microscopic Image ◽  
Multi Scale ◽  
Gaussian Pyramid ◽  
Cost Aggregation ◽  
Dimensional Reconstruction ◽  
Image Pairs ◽  
Accurate Matching

Abstract Three-dimensional (3D) reconstruction is extensively used in microscopic applications. Reducing excessive error points and achieving accurate matching of weak texture regions have been the classical challenges for 3D microscopic vision. A Multi-ST algorithm was proposed to improve matching accuracy. The process is performed in two main stages: scaled microscopic images and regularized cost aggregation. First, microscopic image pairs with different scales were extracted according to the Gaussian pyramid criterion. Second, a novel cost aggregation approach based on the regularized multi-scale model was implemented into all scales to obtain the final cost. To evaluate the performances of the proposed Multi-ST algorithm and compare different algorithms, seven groups of images from the Middlebury dataset and four groups of experimental images obtained by a binocular microscopic system were analyzed. Disparity maps and reconstruction maps generated by the proposed approach contained more information and fewer outliers or artifacts. Furthermore, 3D reconstruction of the plug gauges using the Multi-ST algorithm showed that the error was less than 0.025 mm.

Bringing Biocatalysis into the Deuteration Toolbox

2019 ◽  
Author(s):  
Jack Rowbotham ◽  
Oliver Lenz ◽  
Holly Reeve ◽  
Kylie Vincent
Keyword(s):  
Late Stage ◽  
Hydrogen Isotope ◽  
Reductive Amination ◽  
Mechanistic Studies ◽  
Ambient Conditions ◽  
Synthetic Pathway ◽  
Drug Candidates ◽  
Isotopic Selectivity ◽  
Reducing Equivalents

<p></p><p>Chemicals labelled with the heavy hydrogen isotope deuterium (<sup>2</sup>H) have long been used in chemical and biochemical mechanistic studies, spectroscopy, and as analytical tracers. More recently, demonstration of selectively deuterated drug candidates that exhibit advantageous pharmacological traits has spurred innovations in metal-catalysed <sup>2</sup>H insertion at targeted sites, but asymmetric deuteration remains a key challenge. Here we demonstrate an easy-to-implement biocatalytic deuteration strategy, achieving high chemo-, enantio- and isotopic selectivity, requiring only <sup>2</sup>H<sub>2</sub>O (D<sub>2</sub>O) and unlabelled dihydrogen under ambient conditions. The vast library of enzymes established for NADH-dependent C=O, C=C, and C=N bond reductions have yet to appear in the toolbox of commonly employed <sup>2</sup>H-labelling techniques due to requirements for suitable deuterated reducing equivalents. By facilitating transfer of deuterium atoms from <sup>2</sup>H<sub>2</sub>O solvent to NAD<sup>+</sup>, with H<sub>2</sub> gas as a clean reductant, we open up biocatalysis for asymmetric reductive deuteration as part of a synthetic pathway or in late stage functionalisation. We demonstrate enantioselective deuteration via ketone and alkene reductions and reductive amination, as well as exquisite chemo-control for deuteration of compounds with multiple unsaturated sites.</p><p></p>

Privileged Structures in the Design of Potential Drug Candidates for Neglected Diseases

2019 ◽  
Vol 26 (23) ◽  
pp. 4323-4354 ◽  
Author(s):  
Ana Cristina Lima Leite ◽  
José Wanderlan Pontes Espíndola ◽  
Marcos Veríssimo de Oliveira Cardoso ◽  
Gevanio Bezerra de Oliveira Filho
Keyword(s):  
Biologically Active ◽  
Neglected Diseases ◽  
Financial Return ◽  
Drug Candidates ◽  
Lead Compounds ◽  
Wide Range ◽  
Methods Of Synthesis ◽  
Current Therapies ◽  
Resistant Strains ◽  
Privileged Structures

Background: Privileged motifs are recurring in a wide range of biologically active compounds that reach different pharmaceutical targets and pathways and could represent a suitable start point to access potential candidates in the neglected diseases field. The current therapies to treat these diseases are based in drugs that lack of the desired effectiveness, affordable methods of synthesis and allow a way to emergence of resistant strains. Due the lack of financial return, only few pharmaceutical companies have been investing in research for new therapeutics for neglected diseases (ND). Methods: Based on the literature search from 2002 to 2016, we discuss how six privileged motifs, focusing phthalimide, isatin, indole, thiosemicarbazone, thiazole, and thiazolidinone are particularly recurrent in compounds active against some of neglected diseases. Results: It was observed that attention was paid particularly for Chagas disease, malaria, tuberculosis, schistosomiasis, leishmaniasis, dengue, African sleeping sickness (Human African Trypanosomiasis - HAT) and toxoplasmosis. It was possible to verify that, among the ND, antitrypanosomal and antiplasmodial activities were between the most searched. Besides, thiosemicarbazone moiety seems to be the most versatile and frequently explored scaffold. As well, phthalimide, isatin, thiazole, and thiazolidone nucleus have been also explored in the ND field. Conclusion: Some described compounds, appear to be promising drug candidates, while others could represent a valuable inspiration in the research for new lead compounds.

Application of Advanced Technologies in Natural Product Research: A Review with Special Emphasis on ADMET Profiling

2020 ◽  
Vol 21 (10) ◽  
pp. 751-767
Author(s):  
Pobitra Borah ◽  
Sangeeta Hazarika ◽  
Satyendra Deka ◽  
Katharigatta N. Venugopala ◽  
Anroop B. Nair ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Natural Product ◽  
Dynamic Range ◽  
Early Stage ◽  
Attrition Rate ◽  
Drug Candidates ◽  
Advanced Technologies ◽  
Natural Product Research ◽  
The Status ◽  
Safety Parameters

The successful conversion of natural products (NPs) into lead compounds and novel pharmacophores has emboldened the researchers to harness the drug discovery process with a lot more enthusiasm. However, forfeit of bioactive NPs resulting from an overabundance of metabolites and their wide dynamic range have created the bottleneck in NP researches. Similarly, the existence of multidimensional challenges, including the evaluation of pharmacokinetics, pharmacodynamics, and safety parameters, has been a concerning issue. Advancement of technology has brought the evolution of traditional natural product researches into the computer-based assessment exhibiting pretentious remarks about their efficiency in drug discovery. The early attention to the quality of the NPs may reduce the attrition rate of drug candidates by parallel assessment of ADMET profiling. This article reviews the status, challenges, opportunities, and integration of advanced technologies in natural product research. Indeed, emphasis will be laid on the current and futuristic direction towards the application of newer technologies in early-stage ADMET profiling of bioactive moieties from the natural sources. It can be expected that combinatorial approaches in ADMET profiling will fortify the natural product-based drug discovery in the near future.

Effects of parametric uncertainty on multi-scale model predictions of shock response of a pressed energetic material

2019 ◽  
Vol 125 (23) ◽  
pp. 235104 ◽  
Author(s):  
Sangyup Lee ◽  
Oishik Sen ◽  
Nirmal Kumar Rai ◽  
Nicholas J. Gaul ◽  
K. K. Choi ◽  
...  
Keyword(s):  
Energetic Material ◽  
Parametric Uncertainty ◽  
Scale Model ◽  
Multi Scale ◽  
Model Predictions ◽  
Shock Response
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