Background And Aims: Colorectal cancer (CRC) rates are increasing in young people, and new guidelines recommend screening should begin at age 45 years. We aimed to evaluate CRC detection rates in a large integrated healthcare system to assess treatment outcomes in younger CRC patients and to determine factors that could aid in identifying these individuals.
Methods: We analyzed confirmed cases of CRC using a cancer database spanning from 1985 to 2017 from a large integrated healthcare system composed of 15 hospitals, 150 outpatient clinics, and 20 outpatient oncology clinics. Three cohorts were evaluated (18-44 years, 45-49 years, and ≥50 years).
Results: Significant increases in CRC detection were seen in the cohort aged 18 to 44 (annual percentage change, 2.70%) and the cohort aged 45 to 49 (annual percentage change, 4.15%). A higher proportion of African American, Hispanic, and obese subjects were seen in the younger cohorts. A family history of CRC was found in 49% of patients aged 18 to 44 and 38% of patients aged 45 to 50. Patients younger than age 50 were more likely to have metastases at diagnosis (6.8%) versus the cohort over 50 (4.15%; P < .05). Survival was better in younger cohorts, and they were more likely to receive multimodality treatment (surgery with chemotherapy or radiation). Survival probability was similar in different ethnic groups.
Conclusions: CRC is increasing at similar rates in young people aged 18 to 44 and 45 to 49, and they are more likely to present with advanced disease needing multimodality treatment. A family history identifies some patients <50 years. Young patients presenting with changes in bowel habit, rectal bleeding, anemia, and weight loss should undergo colonoscopy. Rectal and anal symptoms should prompt careful physical and endoscopic evaluation.
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http://dx.doi.org/10.1016/j.gie.2021.03.024 | DOI Listing |
Vaccines (Basel)
November 2024
Laboratory of Biology of Cellular Interactions, Department of Morphology, Federal University of Minas Gerais, Belo Horizonte 31270-901, MG, Brazil.
Background/objectives: Considering the large number of candidates in vaccine-testing studies against different pathogens and the amount of time spent in the preclinical and clinical trials, there is a pressing need to develop an improved in vivo system to quickly screen vaccine candidates. The model of a polyester-polyurethane sponge implant provides a rapid analysis of the specific stimulus-response, allowing the study of a compartmentalized microenvironment. The sponge implant's defined measurements were standardized as a compartment to assess the immune response triggered by the vaccinal antigen.
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December 2024
Ministry-of-Education Key Laboratory for the Green Preparation and Application of Functional Materials, School of Materials Science & Engineering, Hubei University, Wuhan 430062, China.
The MEMS gas sensor is one of the most promising gas sensors nowadays due to its advantage of small size, low power consumption, and easy integration. It has been widely applied in energy components, portable devices, smart living, etc. The performance of the gas sensor is largely determined by the sensing materials, as well as the fabrication methods.
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December 2024
School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK.
Camera traps offer enormous new opportunities in ecological studies, but current automated image analysis methods often lack the contextual richness needed to support impactful conservation outcomes. Integrating vision-language models into these workflows could address this gap by providing enhanced contextual understanding and enabling advanced queries across temporal and spatial dimensions. Here, we present an integrated approach that combines deep learning-based vision and language models to improve ecological reporting using data from camera traps.
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December 2024
School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China.
Deep unfolding networks (DUNs) have attracted growing attention in compressed sensing (CS) due to their good interpretability and high performance. However, many DUNs often improve the reconstruction effect at the price of a large number of parameters and have the problem of feature information loss during iteration. This paper proposes a novel adaptive memory-augmented unfolding network for compressed sensing (AMAUN-CS).
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December 2024
Faculty of Mechatronics, Warsaw University of Technology, ul. św. Boboli 8, 02-525 Warsaw, Poland.
This paper considers the problem of flying a UAV along a given trajectory at speeds close to the speed of sound and above. A novel pitch channel control system is presented using the example of a trajectory with rapid and large changes in flight height. The control system uses a proportional-integral-differential (PID) controller, whose gains were first determined using the Ziegler-Nichols II method.
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