38 research outputs found
Source attribution of poly- and perfluoroalkyl substances (PFASs) in surface waters from Rhode Island and the New York Metropolitan Area
Exposure to poly- and perfluoroalkyl substances (PFASs) has been associated with adverse health effects in humans and wildlife. Understanding pollution sources is essential for environmental regulation, but source attribution for PFASs has been confounded by limited information about industrial releases and rapid changes in chemical production. Here we use principal component analysis (PCA), hierarchical clustering, and geospatial analysis to understand source contributions to 14 PFASs measured across 37 sites in the northeastern United States in 2014. PFASs are significantly elevated in urban areas compared to rural sites except for perfluorobutanesulfonate, N-methyl perfluorooctanesulfonamidoacetic acid, perfluoroundecanate, and perfluorododecanate. The highest PFAS concentrations across sites were those of perfluorooctanate (PFOA, 56 ng L−1) and perfluorohexanesulfonate (PFHxS, 43 ng L−1), and perfluorooctanesulfonate (PFOS) levels are lower than earlier measurements of U.S. surface waters. PCA and cluster analysis indicate three main statistical groupings of PFASs. Geospatial analysis of watersheds reveals the first component/cluster originates from a mixture of contemporary point sources such as airports and textile mills. Atmospheric sources from the waste sector are consistent with the second component, and the metal smelting industry plausibly explains the third component. We find this source-attribution technique is effective for better understanding PFAS sources in urban areas
FetusMapV2: Enhanced Fetal Pose Estimation in 3D Ultrasound
Fetal pose estimation in 3D ultrasound (US) involves identifying a set of
associated fetal anatomical landmarks. Its primary objective is to provide
comprehensive information about the fetus through landmark connections, thus
benefiting various critical applications, such as biometric measurements, plane
localization, and fetal movement monitoring. However, accurately estimating the
3D fetal pose in US volume has several challenges, including poor image
quality, limited GPU memory for tackling high dimensional data, symmetrical or
ambiguous anatomical structures, and considerable variations in fetal poses. In
this study, we propose a novel 3D fetal pose estimation framework (called
FetusMapV2) to overcome the above challenges. Our contribution is three-fold.
First, we propose a heuristic scheme that explores the complementary network
structure-unconstrained and activation-unreserved GPU memory management
approaches, which can enlarge the input image resolution for better results
under limited GPU memory. Second, we design a novel Pair Loss to mitigate
confusion caused by symmetrical and similar anatomical structures. It separates
the hidden classification task from the landmark localization task and thus
progressively eases model learning. Last, we propose a shape priors-based
self-supervised learning by selecting the relatively stable landmarks to refine
the pose online. Extensive experiments and diverse applications on a
large-scale fetal US dataset including 1000 volumes with 22 landmarks per
volume demonstrate that our method outperforms other strong competitors.Comment: 16 pages, 11 figures, accepted by Medical Image Analysis(2023
A voice recognition-based digital cognitive screener for dementia detection in the community: Development and validation study
IntroductionTo facilitate community-based dementia screening, we developed a voice recognition-based digital cognitive screener (digital cognitive screener, DCS). This proof-of-concept study aimed to investigate the reliability, validity as well as the feasibility of the DCS among community-dwelling older adults in China.MethodsEligible participants completed demographic, clinical, and the DCS. Diagnosis of mild cognitive impairment (MCI) and dementia was made based on the Montreal Cognitive Assessment (MoCA) (MCI: MoCA < 23, dementia: MoCA < 14). Time and venue for test administration were recorded and reported. Internal consistency, test-retest reliability and inter-rater reliability were examined. Receiver operating characteristic (ROC) analyses were conducted to examine the discriminate validity of the DCS in detecting MCI and dementia.ResultsA total of 103 participants completed all investigations and were included in the analysis. Administration time of the DCS was between 5.1–7.3 min. No significant difference (p > 0.05) in test scores or administration time was found between 2 assessment settings (polyclinic or community center). The DCS showed good internal consistency (Cronbach’s alpha = 0.73), test-retest reliability (Pearson r = 0.69, p < 0.001) and inter-rater reliability (ICC = 0.84). Area under the curves (AUCs) of the DCS were 0.95 (0.90, 0.99) and 0.77 (0.67, 086) for dementia and MCI detection, respectively. At the optimal cut-off (7/8), the DCS showed excellent sensitivity (100%) and good specificity (80%) for dementia detection.ConclusionThe DCS is a feasible, reliable and valid digital dementia screening tool for older adults. The applicability of the DCS in a larger-scale community-based screening stratified by age and education levels warrants further investigation
Segment Anything Model for Medical Images?
The Segment Anything Model (SAM) is the first foundation model for general
image segmentation. It designed a novel promotable segmentation task, ensuring
zero-shot image segmentation using the pre-trained model via two main modes
including automatic everything and manual prompt. SAM has achieved impressive
results on various natural image segmentation tasks. However, medical image
segmentation (MIS) is more challenging due to the complex modalities, fine
anatomical structures, uncertain and complex object boundaries, and wide-range
object scales. SAM has achieved impressive results on various natural image
segmentation tasks. Meanwhile, zero-shot and efficient MIS can well reduce the
annotation time and boost the development of medical image analysis. Hence, SAM
seems to be a potential tool and its performance on large medical datasets
should be further validated. We collected and sorted 52 open-source datasets,
and build a large medical segmentation dataset with 16 modalities, 68 objects,
and 553K slices. We conducted a comprehensive analysis of different SAM testing
strategies on the so-called COSMOS 553K dataset. Extensive experiments validate
that SAM performs better with manual hints like points and boxes for object
perception in medical images, leading to better performance in prompt mode
compared to everything mode. Additionally, SAM shows remarkable performance in
some specific objects and modalities, but is imperfect or even totally fails in
other situations. Finally, we analyze the influence of different factors (e.g.,
the Fourier-based boundary complexity and size of the segmented objects) on
SAM's segmentation performance. Extensive experiments validate that SAM's
zero-shot segmentation capability is not sufficient to ensure its direct
application to the MIS.Comment: 23 pages, 14 figures, 12 table
The Chinese Open Science Network (COSN): Building an Open Science Community From Scratch
Open Science is becoming a mainstream scientific ideology in psychology and related fields. However, researchers, especially early-career researchers (ECRs) in developing countries, are facing significant hurdles in engaging in Open Science and moving it forward. In China, various societal and cultural factors discourage ECRs from participating in Open Science, such as the lack of dedicated communication channels and the norm of modesty. To make the voice of Open Science heard by Chinese-speaking ECRs and scholars at large, the Chinese Open Science Network (COSN) was initiated in 2016. With its core values being grassroots-oriented, diversity, and inclusivity, COSN has grown from a small Open Science interest group to a recognized network both in the Chinese-speaking research community and the international Open Science community. So far, COSN has organized three in-person workshops, 12 tutorials, 48 talks, and 55 journal club sessions and translated 15 Open Science-related articles and blogs from English to Chinese. Currently, the main social media account of COSN (i.e., the WeChat Official Account) has more than 23,000 subscribers, and more than 1,000 researchers/students actively participate in the discussions on Open Science. In this article, we share our experience in building such a network to encourage ECRs in developing countries to start their own Open Science initiatives and engage in the global Open Science movement. We foresee great collaborative efforts of COSN together with all other local and international networks to further accelerate the Open Science movement
Detection of Poly- and Perfluoroalkyl Substances (PFASs) in U.S. Drinking Water
Spatial analysis of relationship between point sources in watershed and the national occurence data of PFASs in drinking wate
Sodium butyrate reduces ammonia production in the cecum of laying hens by regulating ammonia-producing bacteria
ABSTRACT: Sodium butyrate is a commonly used feed additive and can reduce ammonia (NH3) emissions from laying hens, but the mechanism of this effect is unknown. In this study, the sodium butyrate and cecal content of Lohmann pink laying hens were measured, and in vitro fermentation experiments and NH3-producing bacteria coculture experiments were carried out to explore the relationship between NH3 emissions and its associated microbiota metabolism. Sodium butyrate was found to significantly reduce NH3 emission from the cecal microbial fermentation of Lohmann pink laying hens (P < 0.05). The concentration of NO3−-N in the fermentation broth of the sodium butyrate-supplemented group increased significantly, and the concentration of NH4+-N decreased significantly (P < 0.05). Moreover, sodium butyrate significantly reduced the abundance of harmful bacteria and increased the abundance of beneficial bacteria in the cecum. The culturable NH3-producing bacteria consisted mainly of Escherichia and Shigella, such as Escherichia fergusonii, Escherichia marmotae and Shigella flexnerii. Among them, E. fergusonii had the highest potential for NH3 production. The coculture experiment showed that sodium butyrate can significantly downregulate the expression of the lpdA, sdaA, gcvP, gcvH and gcvT genes of E. fergusonii (P < 0.05), thus reducing the NH3 emission produced by the bacteria during metabolism. In general, sodium butyrate regulated NH3-producing bacteria to reduce NH3 production in the cecum of laying hens. These results are of great significance for NH3 emission reduction in the layer breeding industry and for future research
Hydrolysis-Induced Morphology Evolution of Linear and Bottlebrush Block Copolymers in Thin Films with Acid Vapor or Photoacid Generators
The
self-assembly of high-χ low-N block
copolymers (BCPs) can give patterns with sub-10 nm full pitch, serving
as a promising alternative to photolithographic methods. In this work,
we synthesized poly(solketal methacrylate)-block-polystyrene
copolymers, PSM-b-PS, with various volume ratios
of the two blocks. After hydrolysis of the PSM block into poly(glycerol
monomethacrylate), PGM, the BCPs had both lamellar and cylindrical
microdomain morphologies in the bulk phase and in thin films. In addition
to our previously developed solid-state hydrolysis strategy involving
trifluoroacetic acid vapor, we developed a new photoinduced solid-state
hydrolysis using photoacid generators, PAGs, embedded within the polymer
films. After exposure to UV followed by a postexposure baking or solvent
vapor annealing, the BCPs transitioned from the disordered, phase-mixed
state into laterally ordered cylindrical patterns. In comparison to
linear BCPs that rely on a random copolymer layer to modify interfacial
interactions with the substrate to promote an orientation of the microdomains
normal to the interface, we found that the microdomains in bottlebrush
multiblock copolymers oriented normal to the interface absent substrate
modification due to the chain architecture