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Cardiology Cardiology

Construction of Exosome SORL1 Detection Platform Based on 3D Porous Microfluidic Chip and its Application in Early Diagnosis of Colorectal Cancer.

In Small (Weinheim an der Bergstrasse, Germany)

Exosomes are promising new biomarkers for colorectal cancer (CRC) diagnosis, due to their rich biological fingerprints and high level of stability. However, the accurate detection of exosomes with specific surface receptors is limited to clinical application. Herein, an exosome enrichment platform on a 3D porous sponge microfluidic chip is constructed and the exosome capture efficiency of this chip is ≈90%. Also, deep mass spectrometry analysis followed by multi-level expression screenings revealed a CRC-specific exosome membrane protein (SORL1). A method of SORL1 detection by specific quantum dot labeling is further designed and the ensemble classification system is established by extracting features from 64-patched fluorescence images. Importantly, the area under the curve (AUC) using this system is 0.99, which is significantly higher (p < 0.001) than that using a conventional biomarker (carcinoembryonic antigen (CEA), AUC of 0.71). The above system showed similar diagnostic performance, dealing with early-stage CRC, young CRC, and CEA-negative CRC patients.

Li Peilong, Chen Jiaci, Chen Yuqing, Song Shangling, Huang Xiaowen, Yang Yang, Li Yanru, Tong Yao, Xie Yan, Li Juan, Li Shunxiang, Wang Jiayi, Qian Kun, Wang Chuanxin, Du Lutao

2023-Feb-17

artificial intelligence, biomarkers, cancer, exosomes, microfluidic chips

General General

Selecting relevant moderators with Bayesian regularized meta-regression.

In Research synthesis methods

When meta-analyzing heterogeneous bodies of literature, meta-regression can be used to account for potentially relevant between-studies differences. A key challenge is that the number of candidate moderators is often high relative to the number of studies. This introduces risks of overfitting, spurious results, and model non-convergence. To overcome these challenges, we introduce Bayesian Regularized Meta-Analysis (BRMA), which selects relevant moderators from a larger set of candidates by shrinking small regression coefficients towards zero with regularizing (LASSO or horseshoe) priors. This method is suitable when there are many potential moderators, but it is not known beforehand which of them are relevant. A simulation study compared BRMA against state-of-the-art random effects meta-regression using restricted maximum likelihood (RMA). Results indicated that BRMA outperformed RMA on three metrics: BRMA had superior predictive performance, which means that the results generalized better; BRMA was better at rejecting irrelevant moderators, and worse at detecting true effects of relevant moderators, while the overall proportion of Type I and Type II errors was equivalent to RMA. BRMA regression coefficients were slightly biased towards zero (by design), but its residual heterogeneity estimates were less biased than those of RMA. BRMA performed well with as few as 20 studies, suggesting its suitability as a small sample solution. We present free open source software implementations in the R-package pema (for penalized meta-analysis) and in the stand-alone statistical program JASP. An applied example demonstrates the use of the R-package. This article is protected by copyright. All rights reserved.

Van Lissa Caspar J, van Erp Sara, Clapper Eli-Boaz

2023-Feb-16

bayesian, horseshoe, lasso, machine learning, meta-analysis, regularization

General General

Artificial Intelligence in Long-Term Care: Technological Promise, Aging Anxieties, and Sociotechnical Ageism.

In Journal of applied gerontology : the official journal of the Southern Gerontological Society

This article explores views about older people and aging underpinning practices and perceptions of development and implementation of Artificial Intelligence (AI) in long-term care homes (LTC). Drawing on semi-structured interviews with seven AI developers, seven LTC staff, and four LTC advocates, we analyzed how AI technologies for later life are imagined, designed, deployed, and resisted. Using the concepts of "promissory discourse" and "aging anxieties", we investigated manifestations of ageism in accounts of AI applications in LTC. Despite positive intentions, both AI developers and LTC staff/advocates engaged in simplistic scripts about aging, care, and the technological capacity of older people. We further uncovered what we termed sociotechnical ageism-a form that is not merely digital but rests on interacting pre-conceptions about the inability or lack of interest of older people to use emerging technologies coupled with social assumptions about aging, LTC, and technological innovation.

Neves Barbara Barbosa, Petersen Alan, Vered Mor, Carter Adrian, Omori Maho

2023-Feb-17

ageism, algorithmic bias, digital ageism, nursing homes, older people, techno-solutionism, technology

General General

Being ostensive (reply to commentaries on "Expression unleashed").

In The Behavioral and brain sciences

One of our main goals with "Expression unleashed" was to highlight the distinctive, ostensive nature of human communication, and the many roles that ostension can play in human behavior and society. The commentaries we received forced us to be more precise about several aspects of this thesis. At the same time, no commentary challenged the central idea that the manifest diversity of human expression is underpinned by a common cognitive unity. Our reply is organized around six issues: (1) languages and their cultural evolution; (2) the pervasiveness of expression in human behavior; (3) artificial intelligence and ostensive communication; (4) communication in other animals; (5) the ecology and evolution of ostensive communication; and (6) biolinguistics and pragmatics.

Heintz Christophe, Scott-Phillips Thom

2023-Feb-17

General General

Expression unleashed in artificial intelligence.

In The Behavioral and brain sciences

The problem of generating generally capable agents is an important frontier in artificial intelligence (AI) research. Such agents may demonstrate open-ended, versatile, and diverse modes of expression, similar to humans. We interpret the work of Heintz & Scott-Phillips as a minimal sufficient set of socio-cognitive biases for the emergence of generally expressive AI, separate yet complementary to existing algorithms.

Tolstaya Ekaterina I, Gupta Abhinav, Hughes Edward

2023-Feb-17

General General

Can ChatGPT draft a research article? An example of population-level vaccine effectiveness analysis.

In Journal of global health

We reflect on our experiences of using Generative Pre-trained Transformer ChatGPT, a chatbot launched by OpenAI in November 2022, to draft a research article. We aim to demonstrate how ChatGPT could help researchers to accelerate drafting their papers. We created a simulated data set of 100 000 health care workers with varying ages, Body Mass Index (BMI), and risk profiles. Simulation data allow analysts to test statistical analysis techniques, such as machine-learning based approaches, without compromising patient privacy. Infections were simulated with a randomized probability of hospitalisation. A subset of these fictitious people was vaccinated with a fictional vaccine that reduced this probability of hospitalisation after infection. We then used ChatGPT to help us decide how to handle the simulated data in order to determine vaccine effectiveness and draft a related research paper. AI-based language models in data analysis and scientific writing are an area of growing interest, and this exemplar analysis aims to contribute to the understanding of how ChatGPT can be used to facilitate these tasks.

Macdonald Calum, Adeloye Davies, Sheikh Aziz, Rudan Igor

2023-Feb-17