23 research outputs found
A Longitudinal Analysis about the Effect of Air Pollution on Astigmatism for Children and Young Adults
Purpose: This study aimed to investigate the correlation between air
pollution and astigmatism, considering the detrimental effects of air pollution
on respiratory, cardiovascular, and eye health. Methods: A longitudinal study
was conducted with 127,709 individuals aged 4-27 years from 9 cities in
Guangdong Province, China, spanning from 2019 to 2021. Astigmatism was measured
using cylinder values. Multiple measurements were taken at intervals of at
least 1 year. Various exposure windows were used to assess the lagged impacts
of air pollution on astigmatism. A panel data model with random effects was
constructed to analyze the relationship between pollutant exposure and
astigmatism. Results: The study revealed significant associations between
astigmatism and exposure to carbon monoxide (CO), nitrogen dioxide (NO2), and
particulate matter (PM2.5) over time. A 10 {\mu}g/m3 increase in a 3-year
exposure window of NO2 and PM2.5 was associated with a decrease in cylinder
value of -0.045 diopters and -0.017 diopters, respectively. A 0.1 mg/m3
increase in CO concentration within a 2-year exposure window correlated with a
decrease in cylinder value of -0.009 diopters. No significant relationships
were found between PM10 exposure and astigmatism. Conclusion: This study
concluded that greater exposure to NO2 and PM2.5 over longer periods aggravates
astigmatism. The negative effect of CO on astigmatism peaks in the exposure
window of 2 years prior to examination and diminishes afterward. No significant
association was found between PM10 exposure and astigmatism, suggesting that
gaseous and smaller particulate pollutants have easier access to human eyes,
causing heterogeneous morphological changes to the eyeball
Object Detection for Caries or Pit and Fissure Sealing Requirement in Children's First Permanent Molars
Dental caries is one of the most common oral diseases that, if left
untreated, can lead to a variety of oral problems. It mainly occurs inside the
pits and fissures on the occlusal/buccal/palatal surfaces of molars and
children are a high-risk group for pit and fissure caries in permanent molars.
Pit and fissure sealing is one of the most effective methods that is widely
used in prevention of pit and fissure caries. However, current detection of
pits and fissures or caries depends primarily on the experienced dentists,
which ordinary parents do not have, and children may miss the remedial
treatment without timely detection. To address this issue, we present a method
to autodetect caries and pit and fissure sealing requirements using oral photos
taken by smartphones. We use the YOLOv5 and YOLOX models and adopt a tiling
strategy to reduce information loss during image pre-processing. The best
result for YOLOXs model with tiling strategy is 72.3 mAP.5, while the best
result without tiling strategy is 71.2. YOLOv5s6 model with/without tiling
attains 70.9/67.9 mAP.5, respectively. We deploy the pre-trained network to
mobile devices as a WeChat applet, allowing in-home detection by parents or
children guardian
Prompt-enhanced Hierarchical Transformer Elevating Cardiopulmonary Resuscitation Instruction via Temporal Action Segmentation
The vast majority of people who suffer unexpected cardiac arrest are
performed cardiopulmonary resuscitation (CPR) by passersby in a desperate
attempt to restore life, but endeavors turn out to be fruitless on account of
disqualification. Fortunately, many pieces of research manifest that
disciplined training will help to elevate the success rate of resuscitation,
which constantly desires a seamless combination of novel techniques to yield
further advancement. To this end, we collect a custom CPR video dataset in
which trainees make efforts to behave resuscitation on mannequins independently
in adherence to approved guidelines, thereby devising an auxiliary toolbox to
assist supervision and rectification of intermediate potential issues via
modern deep learning methodologies. Our research empirically views this problem
as a temporal action segmentation (TAS) task in computer vision, which aims to
segment an untrimmed video at a frame-wise level. Here, we propose a
Prompt-enhanced hierarchical Transformer (PhiTrans) that integrates three
indispensable modules, including a textual prompt-based Video Features
Extractor (VFE), a transformer-based Action Segmentation Executor (ASE), and a
regression-based Prediction Refinement Calibrator (PRC). The backbone of the
model preferentially derives from applications in three approved public
datasets (GTEA, 50Salads, and Breakfast) collected for TAS tasks, which
accounts for the excavation of the segmentation pipeline on the CPR dataset. In
general, we unprecedentedly probe into a feasible pipeline that genuinely
elevates the CPR instruction qualification via action segmentation in
conjunction with cutting-edge deep learning techniques. Associated experiments
advocate our implementation with multiple metrics surpassing 91.0%.Comment: Transformer for Cardiopulmonary Resuscitatio
Smartphone-Based Quantitative Detection of Ochratoxin A in Wheat via a Lateral Flow Assay
Ochratoxin A (OTA) poses a severe health risk to livestock along the food chain. Moreover, according to the International Agency for Research on Cancer, it is also categorized as being possibly carcinogenic to humans. The lack of intelligent point-of-care test (POCT) methods restricts its early detection and prevention. This work establishes a smartphone-enabled point-of-care test for OTA detection via a fluorescent lateral flow assay within 6 min. By using a smartphone and portable reader, the assay allows for the recording and sharing of the detection results in a cloud database. This intelligent POCT provided (iPOCT) a linearity range of 0.1–3.0 ng/mL and a limit of detection (LOD) of 0.02 ng/mL (0.32 µg/kg in wheat). By spiking OTA in blank wheat samples, the recoveries were 89.1–120.4%, with a relative standard deviation (RSD) between 3.9–9.1%. The repeatability and reproducibility were 94.2–101.7% and 94.6–103.4%, respectively. This work provides a promising intelligent POCT method for food safety
Evaluation and comparison of in vitro antioxidant activities of unsaponifiable fraction of 11 kinds of edible vegetable oils
The radical scavenging capabilities of the extracts from eleven edible vegetable oils were investigated by using 2,2âdiphenylâ1âpicrylhydrazyl (DPPH ), 2,2âČâazinoâbisâ3â ethylbenzothiazolineâ6âsulfonic acid (ABTS ), and ferric reducing ability of plasma (FRAP ) assays. The results indicated that rapeseed oil and sesame oil showed higher radical scavenging abilities than other vegetable oils. When the radical scavenging capabilities of the extracts from virgin camellia oils and commercially available refined camellia oils were evaluated by FRAP assay, the results showed that the antioxidant capabilities of the former were higher than the latter. Therefore, it is recommended that moderate refining processes should be taken to minimize the loss of antioxidant components and people consume virgin oils or less processed edible vegetable oils for higher antioxidant activities
A Rapid and Nondestructive Detection Method for Rapeseed Quality Using NIR Hyperspectral Imaging Spectroscopy and Chemometrics
In this study, a fast and non-destructive method was proposed to analyze rapeseed quality parameters with the help of NIR hyperspectral imaging spectroscopy and chemometrics. Hyperspectral images were acquired in the reflectance mode. Meanwhile, the region of interest was extracted from each image by the regional growth algorithm. The kernel partial least square regression was used to build prediction models for crude protein content, oil content, erucic acid content, and glucosinolate content of rapeseed. The results showed that the correlation coefficients were 0.9461, 0.9503, 0.9572, and 0.9335, whereas the root mean square errors of prediction were 0.5514%, 0.5680%, 2.8113%, and 10.3209 ”mol/g for crude protein content, oil content, erucic acid content, and glucosinolate content, respectively. It demonstrated that NIR hyperspectral imaging is a promising tool to determine rapeseed quality parameters in a rapid and non-invasive manner
Risk Assessment on Dietary Exposure to Aflatoxin B1 in Post-Harvest Peanuts in the Yangtze River Ecological Region
Based on the 2983 peanut samples from 122 counties in six provinces of Chinaâs Yangtze River ecological region collected between 2009â2014, along with the dietary consumption data in Chinese resident nutrition and health survey reports from 2002 and 2004, dietary aflatoxin exposure and percentiles in the corresponding statistics were calculated by non-parametric probability assessment, Monte Carlo simulation and bootstrap sampling methods. Average climatic conditions in the Yangtze River ecological region were calculated based on the data from 118 weather stations via the Thiessen polygon method. The survey results found that the aflatoxin contamination of peanuts was significantly high in 2013. The determination coefficient (R2) of multiple regression reflected by the aflatoxin B1 content with average precipitation and mean temperature in different periods showed that climatic conditions one month before harvest had the strongest impact on aflatoxin B1 contamination, and that Hunan and Jiangxi provinces were greatly influenced. The simulated mean aflatoxin B1 intake from peanuts at the mean peanut consumption level was 0.777â0.790 and 0.343â0.349 ng/(kg·d) for children aged 2â6 and standard adults respectively. Moreover, the evaluated cancer risks were 0.024 and 0.011/(100,000 persons·year) respectively, generally less than Chinaâs current liver cancer incidence of 24.6 cases/(100,000 persons·year). In general, the dietary risk caused by peanut production and harvest was low. Further studies would focus on the impacts of peanut circulation and storage on aflatoxin B1 contamination risk assessment in order to protect peanut consumersâ safety and boost international trade
Development of an Ultrasensitive and Rapid Fluorescence Polarization Immunoassay for Ochratoxin A in Rice
Ochratoxin A (OTA) is a known food contaminant that affects a wide range of food and agricultural products. The presence of this fungal metabolite in foods poses a threat to human health. Therefore, various detection and quantification methods have been developed to determine its presence in foods. Herein, we describe a rapid and ultrasensitive tracer-based fluorescence polarization immunoassay (FPIA) for the detection of OTA in rice samples. Four fluorescent tracers OTA-fluorescein thiocarbamoyl ethylenediamine (EDF), OTA-fluorescein thiocarbamoyl butane diamine (BDF), OTA-amino-methyl fluorescein (AMF), and OTA-fluorescein thiocarbamoyl hexame (HDF) with fluorescence polarization values (δFP = FPbind-FPfree) of 5, 100, 207, and 80 mP, respectively, were synthesized. The tracer with the highest δFP value (OTA-AMF) was selected and further optimized for the development of an ultrasensitive FPIA with a detection range of 0.03–0.78 ng/mL. A mean recovery of 70.0% to 110.0% was obtained from spiked rice samples with a relative standard deviation of equal to or less than 20%. Good correlations (r2 = 0.9966) were observed between OTA levels in contaminated rice samples obtained by the FPIA method and high-performance liquid chromatography (HPLC) as a reference method. The rapidity of the method was confirmed by analyzing ten rice samples that were analyzed within 25 min, on average. The sensitivity, accuracy, and rapidity of the method show that it is suitable for screening and quantification of OTA in food samples without the cumbersome pre-analytical steps required in other mycotoxin detection methods
Time-Resolved Fluorescence Immunochromatographic Assay Developed Using Two Idiotypic Nanobodies for Rapid, Quantitative, and Simultaneous Detection of Aflatoxin and Zearalenone in Maize and Its Products
Aflatoxins
and zearalenone (ZEN) are highly common mycotoxins in
maize and maize-based products. This study aimed to report a time-resolved
fluorescence immunochromatographic assay (TRFICA) developed using
two idiotypic nanobodies for rapid, quantitative, and simultaneous
detection of aflatoxin B<sub>1</sub> (AFB<sub>1</sub>) and ZEN in
maize and its products. A novel Eu/TbÂ(III) nanosphere with enhanced
fluorescence was prepared as a label and conjugated to anti-idiotypic
nanobody (AIdnb) and monoclonal antibody (mAb). On the basis of nanosphereâantibody
conjugation, two patterns of competitive time-resolved strip methods
(AIdnbâTRFICA and mAbâTRFICA) were established and compared.
The half inhibition concentration of AIdnbâTRFICA was 0.46
and 0.86 ng·mL<sup>â1</sup> for AFB<sub>1</sub> and ZEN,
which was 18.3- and 20.3-fold more sensitive than that of mAbâTRFICA
for AFB<sub>1</sub> and ZEN, respectively. Under optimal conditions,
AIdnbâTRFICA for dual mycotoxin was established and provided
a quantitative relationship ranging from 0.13 to 4.54 ng·mL<sup>â1</sup> for AFB<sub>1</sub> and 0.20 to 2.77 ng·mL<sup>â1</sup> for ZEN, with a detection limit of 0.05 and 0.07
ng·mL<sup>â1</sup> in the buffer solution, respectively.
AIdnbâTRFICA showed good recoveries (72.6%â106.6%) in
samples and was applied to detect dual mycotoxin in maize samples
with satisfying results. To the best of our knowledge, it is the first
report about a time-resolved strip method based on AIdnbs for dual
mycotoxin