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Colorectal cancer is the most common malignant tumor of digestive tract, and the incidence of colorectal cancer in China is especially characterized by middle and low rectal cancer. In recent years, with the progress of computer science, artificial intelligence technology has developed rapidly, and has achieved a lot of application results in the medical field. At present, artificial intelligence technology has covered various stages of colorectal cancer, including screening, individualized assessment, auxiliary diagnosis and treatment decision-making, refined surgery and prognosis judgment, providing help for the accurate and individualized treatment of rectal cancer. However, the lack of standardized, systematic, and scalable AI models remains a major pain point for the field. Therefore, it is necessary to carry out large-scale prospective clinical studies on artificial intelligence model to further confirm its application value in the clinical diagnosis and treatment of rectal cancer.

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Objective: To establish reference values for carotid intima-media thickness (CIMT) of adult dwellers in Shenzhen City. Methods: The study was conducted based on the Shenzhen heart failure epidemiological survey from 2021 to 2022. In this survey, residents aged 18 years and above in Shenzhen were selected by using a multi-stage stratified random sampling method. General information, cardiovascular disease (CVD) related behavior and carotid ultrasound examination and etc. were collected from the participants. People with CVD factors, a history of atherosclerotic cardiovascular disease, carotid plaque or having no carotid ultrasound examination results were excluded. The parameter regression model based on fractional polynomial was used to establish the reference values of CIMT by age and sex. Results: A total of 2 163 healthy individuals were enrolled in the final analysis, including 576 males (26.6%) and 1 587 females (73.4%). The fractional polynomial regression of the CIMT mean and standard deviation was obtained. For men, the regression was meanCIMT=0.324 7+0.006 9×age and SDCIMT=0.076 9+0.001 2×age. For women, the regression was meanCIMT=0.354 9+0.005 4×age and SDCIMT=0.041 6+0.002 0×age. Conclusion: The age and sex reference values for CIMT of adult people in Shenzhen established in this study could provide the latest reference standards for early screening of subclinical CVD.

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OBJECTIVE: To establish a deep learning algorithm that can accurately determine three-dimensional facial anatomical landmarks, multi-view stacked hourglass convolutional neural networks (MSH-CNN) and to construct three-dimensional facial midsagittal plane automatically based on MSH-CNN and weighted Procrustes analysis algorithm. METHODS: One hundred subjects with no obvious facial deformity were collected in our oral clinic. Three-dimensional facial data were scanned by three-dimensional facial scanner. Experts annotated twenty-one facial landmarks and midsagittal plane of each data. Eighty three-dimensional facial data were used as training set, to train the MSH-CNN in this study. The overview of MSH-CNN network architecture contained multi-view rendering and training the MSH-CNN network. The three-dimensional facial data were rendered from ninety-six views that were fed to MSH-CNN and the output was one heatmap per landmark. The result of the twenty-one landmarks was accurately placed on the three-dimensional facial data after a three-dimensional view ray voting process. The remaining twenty three-dimensional facial data were used as test set. The trained MSH-CNN automatically determined twenty-one three-dimensional facial anatomical landmarks of each case of data, and calculated the distance between each MSH-CNN landmark and the expert landmark, which was defined as position error. The midsagittal plane of the twenty subjects' could be automatically constructed, using the MSH-CNN and Procrustes analysis algorithm. To evaluate the effect of midsagittal plane by automatic method, the angle between the midsagittal plane constructed by the automatic method and the expert annotated plane was calculated, which was defined as angle error. RESULTS: For twenty subjects with no obvious facial deformity, the average angle error of the midsagittal plane constructed by MSH-CNN and weighted Procrustes analysis algorithm was 0.73°±0.50°, in which the average position error of the twenty-one facial landmarks automatically determined by MSH-CNN was (1.13±0.24) mm, the maximum position error of the orbital area was (1.31±0.54) mm, and the minimum position error of the nasal area was (0.79±0.36) mm. CONCLUSION: This research combines deep learning algorithms and Procrustes analysis algorithms to realize the fully automated construction of the three-dimensional midsagittal plane, which initially achieves the construction effect of clinical experts. The obtained results constituted the basis for the independent intellectual property software development.

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Objective: To analyze the trend of suicide mortality in residents of Hainan province, and explore the application of time sequence model in the prediction of the mortality of suicide. Methods: The mortality data of suicide in residents of Hainan province between January, 2014 and December, 2016 were collected and analyzed with time sequence model and the mortality rate of suicide during January-June, 2017 in Hainan was predicted with the model. Results: During January, 2014 to June 2017, a total of 576 suicide cases were reported in Hainan, the mortality rate was 1.5/100 000. The established ARIMA model had good fitting for the suicide mortality in previous times and the prediction result was quite similar to the actual mortality, the predicted mortality rate was within the 95% confidence interval of the actual rate. Conclusion: The time sequence model for the prediction of suicide mortality in Hainan was "ARIMA (0, 1, 0) (0, 0, 0) (12)" , and the prediction effect of the model was better, which can be used to predict the suicide mortality in Hainan.

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The Daya Bay Reactor Neutrino Experiment has measured a nonzero value for the neutrino mixing angle θ(13) with a significance of 5.2 standard deviations. Antineutrinos from six 2.9 GWth reactors were detected in six antineutrino detectors deployed in two near (flux-weighted baseline 470 m and 576 m) and one far (1648 m) underground experimental halls. With a 43,000 ton-GWth-day live-time exposure in 55 days, 10,416 (80,376) electron-antineutrino candidates were detected at the far hall (near halls). The ratio of the observed to expected number of antineutrinos at the far hall is R=0.940±0.011(stat.)±0.004(syst.). A rate-only analysis finds sin(2)2θ(13)=0.092±0.016(stat.)±0.005(syst.) in a three-neutrino framework.

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BACKGROUND: There are ethnic differences in the prevalence and types of androgenetic alopecia (AGA). Although there have been several reports on the prevalence and types of AGA in caucasian and Asian populations, there are very few data on a Chinese population that have been derived from a sufficient number of samples. OBJECTIVES: To estimate the prevalence and types of AGA in a Chinese population, and to compare the results with those in caucasians and Koreans reported previously in the literature. METHODS: A population-based cross-sectional study was carried out in 7056 subjects (3519 men and 3537 women) from May 2006 to December 2006 in a community of Shanghai. Questionnaires were completed during face-to-face interviews at the subjects' homes. The degree of AGA was classified according to the Norwood and Ludwig classifications. RESULTS: The prevalence of AGA in Chinese men was 19.9%, and the prevalence of female pattern AGA in men was 0.1%. The most common type in men was type III vertex (3.5%). The prevalence of AGA in women was 3.1%, while male pattern AGA was found in those aged over 50 years (0.4%), and the most common type was type I (Ludwig classification) (1.4%). A family history of AGA was present in 55.8% of men and 32.4% of women with AGA. CONCLUSIONS: The prevalence of AGA in Chinese men was lower than in caucasian men but was similar to that in Korean men; however, over the age of 60 years it was approaching that in caucasian men but was higher than that in Korean men. The most common type in Chinese men with AGA was type III vertex. Interestingly, the prevalence of AGA in Chinese women was lower than that in Korean women and caucasian women, and type I was the most common type (Ludwig classification).

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BACKGROUND: Glucocorticoids are widely used for the treatment of various diseases, despite known side-effects such as skin atrophy. Many studies have shown that the status of collagen fibres in the skin is affected by glucocorticoid treatment. However, the molecular mechanism underlying the alteration of collagen metabolism in the skin by glucocorticoid treatment remains unknown. OBJECTIVES: To characterize the molecular mechanisms related to the deterioration of the dermis in response to glucocorticoids, the status of two major types of collagen, collagenase, and tissue inhibitors of metalloproteinases (TIMPs) in the dorsal skin of rats was studied at the protein and mRNA levels. METHODS: Samples of rat dorsal skin were obtained after daily (1 mg kg-1) subcutaneous injections of dexamethasone (DEX) for 8 days. mRNA levels of two types of collagen and of TIMPs were measured by a lysate RNase protection assay. mRNA levels of collagenase were measured by a quantitative polymerase chain reaction. Protein levels of collagen and collagenase were measured by an immunoblot analysis. RESULTS: Levels of type I tropocollagen and type III tropocollagen were drastically reduced in response to DEX. The effects of DEX treatment were more severe on type III than type I collagen: it also produced a significant decrease in fibril collagen of type III collagen. DEX treatment was found to decrease both active and latent forms of collagenase as well as its mRNA levels. Among TIMPs, mRNA levels of TIMP-1 and TIMP-2 were decreased in response to DEX treatment, whereas those of TIMP-3 were not affected. CONCLUSIONS: These results suggest that DEX treatment strongly interferes with both the synthesis and degradation of type I collagen and, more drastically, type III collagen, the molecule that is known to play a major role in the initiation of wound healing. The present study may provide a molecular basis for the deterioration of skin function, impaired wound healing, and skin atrophy caused by glucocorticoid treatment.

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We investigated the effects of vitamin A (VA) nutritional status on the levels of expression of retinoic acid (RA) receptor-beta (RARbeta) gene in the various tissues of Japanese quail. VA deficiency caused a significant decrease in the mRNA levels of brain, liver, heart, lung and kidney RARbeta2/beta4, whereas no change was observed in the level of testis RARbeta2 transcript. In contrast, reduction in the RARbeta1 transcript caused by VA depletion was observed only in the lung, remaining unchanged in the other tissues. The administration of RA to the VA-deficient quail rapidly induced the expression of RARbeta2/beta4 mRNAs in all the tissues examined, but RA increased the expression of RARbeta1 transcript in the liver, heart, lung and kidney at a lower magnitude. RA could not change the expression of the brain RARbeta1 transcript, while it induced the expression of the testis RARbeta1 mRNA in a temporal way. These results clearly indicate that VA nutritional status differently regulates the expression of RARbeta1 and RARbeta2/beta4 transcripts in a tissue-specific manner.

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A single "orbital" navigator echo, that has a circular k-space trajectory, is used to simultaneously measure in-plane rotational and multi-axis translational global motion. Rotation is determined from the shift in the magnitude profile of the echo with respect to a reference echo. Displacements are calculated from the phase difference between the current echo and a reference echo. Phantom studies show that this technique can accurately measure rotation and translations. Preliminary results from adaptive motion correction studies on phantom and human subjects indicate that the orbital navigator echo is an effective method for motion measurement in MRI.

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