新近,欧洲糖尿病预防指南与培训标准工作组(Development and Implementation of a European Guideline and Training Standards for Diabetes Prevention,IMAGE)颁布了2型糖尿病(T2DM)预防指南,其要点摘译如下:
Assimilating Sentinel-2 images with the CERES-Wheat model can improve the precision of winter wheat yield estimates at a regional scale. To verify this method, we applied the ensemble Kalman filter(EnKF) to assimilate...Assimilating Sentinel-2 images with the CERES-Wheat model can improve the precision of winter wheat yield estimates at a regional scale. To verify this method, we applied the ensemble Kalman filter(EnKF) to assimilate the leaf area index(LAI) derived from Sentinel-2 data and simulated by the CERES-Wheat model. From this, we obtained the assimilated daily LAI during the growth stage of winter wheat across three counties located in the southeast of the Loess Plateau in China: Xiangfen, Xinjiang, and Wenxi. We assigned LAI weights at different growth stages by comparing the improved analytic hierarchy method, the entropy method, and the normalized combination weighting method, and constructed a yield estimation model with the measurements to accurately estimate the yield of winter wheat. We found that the changes of assimilated LAI during the growth stage of winter wheat strongly agreed with the simulated LAI. With the correction of the derived LAI from the Sentinel-2 images, the LAI from the green-up stage to the heading–filling stage was enhanced, while the LAI decrease from the milking stage was slowed down, which was more in line with the actual changes of LAI for winter wheat. We also compared the simulated and derived LAI and found the assimilated LAI had reduced the root mean square error(RMSE) by 0.43 and 0.29 m^(2) m^(–2), respectively, based on the measured LAI. The assimilation improved the estimation accuracy of the LAI time series. The highest determination coefficient(R2) was 0.8627 and the lowest RMSE was 472.92 kg ha^(–1) in the regression of the yields estimated by the normalized weighted assimilated LAI method and measurements. The relative error of the estimated yield of winter wheat in the study counties was less than 1%, suggesting that Sentinel-2 data with high spatial-temporal resolution can be assimilated with the CERES-Wheat model to obtain more accurate regional yield estimates.展开更多
Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT w...Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content inversion.However,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered.Therefore,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation levels.Quantitative inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were derived.The scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were calculated.The results showed that LAI,CCC,and CEWT were inversely related with PPC-induced stress.When applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),respectively.Compared to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for CCC.The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.展开更多
Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer...Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer.Methods We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging(MRI).The morphological characteristics of breast lesions were evaluated using DCE,DWI,and T2WI based on BI-RADS lexicon descriptors by trained radiologists.Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions,and the differences between benign and malignant lesions in each group were compared.Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis.Diagnostic efficacies were compared using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results For mass-like lesions,all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE,DWI,and T2WI(P<0.05).The combined method(DCE+DWI+T2WI)had a higher AUC(0.865)than any of the individual modality(DCE:0.786;DWI:0.793;T2WI:0.809)(P<0.05).For non-mass-like lesions,DWI signal intensity was a significant predictor of malignancy(P=0.036),but the model using DWI alone had a low AUC(0.669).Conclusion Morphological assessment using the combination of DCE,DWI,and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.展开更多
BACKGROUND Colorectal cancer is a malignancy with a high risk of lymph node metastasis and poor prognosis,and thus requires an accurate diagnosis.AIM To assess the diagnostic value of combined magnetic resonance T2-we...BACKGROUND Colorectal cancer is a malignancy with a high risk of lymph node metastasis and poor prognosis,and thus requires an accurate diagnosis.AIM To assess the diagnostic value of combined magnetic resonance T2-weighted imaging(T2WI)and diffusion-weighted imaging(DWI)in colorectal cancer.METHODS We included 120 patients with suspected colorectal cancer who underwent magnetic resonance imaging.Surgical pathology was used as the gold standard for comparison.Combined T2WI and DWI showed higher diagnostic efficacy than either of the two methods used individually.RESULTS The combined method achieved 94.74%sensitivity,95.45%specificity,95.00%accuracy,94.74%positive predictive value,and 95.45%negative predictive value in qualitative diagnosis.It showed 94.44%sensitivity,95.00%specificity,94.74%accuracy,94.44%positive predictive value,and 95.00%negative predictive value in clinical staging.Finally,it showed 94.74%sensitivity,94.59%specificity,94.74%accuracy,94.74%positive predictive value,and 94.59%negative predictive value in diagnosing lymph node metastasis.These results were highly consistent with that of the gold standard.CONCLUSION This study combined T2WI and DWI for accurate diagnosis of colorectal cancer,aiding clinical staging and lymph node metastasis assessment.This approach is promising for clinical application.展开更多
This paper describes a 2D/3D vision chip with integrated sensing and processing capabilities.The 2D/3D vision chip architecture includes a 2D/3D image sensor and a programmable visual processor.In this architecture,we...This paper describes a 2D/3D vision chip with integrated sensing and processing capabilities.The 2D/3D vision chip architecture includes a 2D/3D image sensor and a programmable visual processor.In this architecture,we design a novel on-chip processing flow with die-to-die image transmission and low-latency fixed-point image processing.The vision chip achieves real-time end-to-end processing of convolutional neural networks(CNNs)and conventional image processing algo-rithms.Furthermore,an end-to-end 2D/3D vision system is built to exhibit the capacity of the vision chip.The vision system achieves real-timing applications under 2D and 3D scenes,such as human face detection(processing delay 10.2 ms)and depth map reconstruction(processing delay 4.1 ms).The frame rate of image acquisition,image process,and result display is larger than 30 fps.展开更多
Background:Successful liver resection in oncologic surgery depends on safety,precision,and efficacy,all of which require a thorough understanding of liver anatomy.Contrast-enhanced computed tomography(CT)-generated th...Background:Successful liver resection in oncologic surgery depends on safety,precision,and efficacy,all of which require a thorough understanding of liver anatomy.Contrast-enhanced computed tomography(CT)-generated three-dimensional(3D)models have been proposed as a valuable tool to enhance this understanding.However,a systematic comparison of different display modalities across professional groups has not yet been performed.Methods:In this prospective,monocentric randomized trial,we compared high-resolution twodimensional(2D)CT images of liver malignancies with their corresponding standardized,non-colored 3D virtual and printed models in facilitating anatomical and spatial understanding as well as surgical decision-making.A total of 91 participants,including 40 surgeons,10 radiologists,and 41 students,evaluated six clinical cases(three centrally and three peripherally located liver malignancies).Each participant assessed one central and one peripheral case per display modality,presented in a random order.Results:Compared to 2D CT images,both 3D virtual and printed models significantly improved the identification of tumor location(P<0.001),enhanced the comprehension of spatial relationships with adjacent liver and portal veins(P<0.001 and P=0.019,respectively),and facilitated clinical decisionmaking(P<0.001).No significant difference was observed between virtual and printed models in terms of effectiveness.Within the different groups,surgeons and students,but not radiologists,more accurately identified tumor location and spatial relationships with adjacent liver and portal veins using 3D models.Subjectively,most surgeons and students preferred 3D printed models over virtual models and 2D CT images.Conclusions:This study demonstrated that standardized,non-colored 3D virtual and printed models equally help preoperative anatomical understanding and decision-making,particularly for surgeons and students.By isolating the influence of display modality,our findings clarify prior inconsistent results and support the integration of cost-effective 3D visualization by applying virtual models into surgical planning and education.Preference for printed models despite comparable efficacy highlights the importance of user-centered implementation strategies.展开更多
Prostate cancer （PCa） is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） to classify men with P...Prostate cancer （PCa） is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） to classify men with PCa, clinically significant PCa （CSPCa）, or no PCa, especially among those with serum total prostate-specific antigen （tPSA） levels in the ＂gray zone＂ （4-10 ng ml-1）. A total of 308 patients （355 lesions） were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density （PSAD） were independent predictors of PCa and CSPCa. A PI-RADS v2 score L≥4 provided high negative predictive values （91.39% for PCa and 95.69% for CSPCa）. A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group （PI-RADS score = 5 and PSAD L≥0 15 ng ml-1 cm-3, with tPSA in the gray zone, or PI-RADS score L≥4 with high tPSA level） with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.展开更多
BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and H...BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.展开更多
Objective:To achieve precision medicine,the use of imaging methods to help the clinical detection of cerebral infarction is conducive to the clinical development of a treatment plan and increase of the cure rate and i...Objective:To achieve precision medicine,the use of imaging methods to help the clinical detection of cerebral infarction is conducive to the clinical development of a treatment plan and increase of the cure rate and improvement of the prognosis of patients.Methods:In this work,T2-weighted imaging(T2WI),diffusion-weighted imaging(DWI),susceptibility-weighted imaging(SWI),and diffusion tensor imaging(DTI)examinations were performed on 34 patients with clinically diagnosed cerebral infarction to measure the difference in signal intensity between the lesion and its mirror area and make a comparative analysis by means of the Student-Newman-Keuls method.Results:The detection rate of T2WI was 79%(27/34),the detection rate of DWI was 97%(33/34),the detection rate of SWI was 88%(30/34),and the detection rate of DTI was 94%(32/34).Conclusion:The imaging performance was in the order DWI>DTI>SWI>T2WI for the diagnosis of cerebral infarction,and combined imaging is better than single imaging.展开更多
AIM: To investigate the accuracy of T2*-weighted magnetic resonance imaging (MRI T2*) in the evaluation of iron overload in beta-thalassemia major patients. METHODS: In this cross-sectional study, 210 patients with be...AIM: To investigate the accuracy of T2*-weighted magnetic resonance imaging (MRI T2*) in the evaluation of iron overload in beta-thalassemia major patients. METHODS: In this cross-sectional study, 210 patients with beta-thalassemia major having regular blood transfusions were consecutively enrolled. Serum ferritin levels were measured, and all patients underwent MRI T2* of the liver. Liver biopsy was performed in 53 patients at an interval of no longer than 3 mo after the MRIT2* in each patient. The amount of iron was assessed in both MRI T2* and liver biopsy specimens of each patient. RESULTS: Patients’ ages ranged from 8 to 54 years with a mean of 24.59 ± 8.5 years. Mean serum ferritin level was 1906 ± 1644 ng/mL. Liver biopsy showed a moderate negative correlation with liver MRI T2* (r = -0.573, P = 0.000) and a low positive correlation with ferritin level (r = 0.350, P = 0.001). Serum ferritin levels showed a moderate negative correlation with liver MRI T2* values (r = -0.586, P = 0.000). CONCLUSION: Our study suggests that MRI T2* is a non-invasive, safe and reliable method for detecting iron load in patients with iron overload.展开更多
BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation gr...BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation grade of CRC is of great value.AIM To develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on T2-weighted images(T2WI).METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023.Patients were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 ratio.Lesions were delineated layer by layer on high-resolution T2WI.Least absolute shrinkage and selection operator regression was applied to screen for radiomic features.Radiomics and clinical models were constructed using the multilayer perceptron(MLP)algorithm.These radiomic features and clinically relevant variables(selected based on a significance level of P<0.05 in the training set)were used to construct radiomics-clinical models.The performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULTS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic model.Eight different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic performance.The AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation cohort.The AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation cohort.The clinical model achieved an AUC of 0.751(95%CI:0.661-0.842)in the training cohort and 0.676(95%CI:0.525-0.827)in the validation cohort.All three models demonstrated good accuracy.In the training cohort,the AUC of the radiomic-clinical model was significantly greater than that of the clinical model(P=0.005)and the radiomic model(P=0.016).DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process.CONCLUSION In this study,we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC.This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.展开更多
The diagnosis of the recurrent optic neuritis is commonly established clinically,and sometimes it could be challenging because the involved optic nerve does not always show significant enhancement on conventional cont...The diagnosis of the recurrent optic neuritis is commonly established clinically,and sometimes it could be challenging because the involved optic nerve does not always show significant enhancement on conventional contrast enhanced-T1 weighted imaging（CE-T1W1）.In this paper,we reported a middle-aged female with early diagnosis of recurrent optic neuritis using contrast-enhanced T2 fluid-attenuated inversion recovery imaging（CET2FLAIR）.The involved optic nerve presented evident enhancement on CE-T2FLAIR and no enhancement on CE-T1W1.This case suggested that the CE-T2FLAIR may be a useful diagnostic tool specifically for the recurrent optic neuritis in clinical practice.展开更多
We use laser-scanning nonlinear imaging microscopy in atomically thin transition metal dichalcogenides(TMDs)to reveal information on the crystalline orientation distribution,within the 2D lattice.In particular,we perf...We use laser-scanning nonlinear imaging microscopy in atomically thin transition metal dichalcogenides(TMDs)to reveal information on the crystalline orientation distribution,within the 2D lattice.In particular,we perform polarization-resolved second-harmonic generation(PSHG)imaging in a stationary,raster-scanned chemical vapor deposition(CVD)-grown WS2 flake,in order to obtain with high precision a spatially resolved map of the orientation of its main crystallographic axis(armchair orientation).By fitting the experimental PSHG images of sub-micron resolution into a generalized nonlinear model,we are able to determine the armchair orientation for every pixel of the image of the 2D material,with further improved resolution.This pixel-wise mapping of the armchair orientation of 2D WS2 allows us to distinguish between different domains,reveal fine structure,and estimate the crystal orientation variability,which can be used as a unique crystal quality marker over large areas.The necessity and superiority of a polarization-resolved analysis over intensity-only measurements is experimentally demonstrated,while the advantages of PSHG over other techniques are analysed and discussed.展开更多
Patients with type 2 diabetes mellitus(T2 DM) often have cognitive impairment and structural brain abnormalities.The magnetic resonance imaging(MRI)-based brain atrophy and lesion index can be used to evaluate common ...Patients with type 2 diabetes mellitus(T2 DM) often have cognitive impairment and structural brain abnormalities.The magnetic resonance imaging(MRI)-based brain atrophy and lesion index can be used to evaluate common brain changes and their correlation with cognitive function,and can therefore also be used to reflect whole-brain structural changes related to T2 DM.A total of 136 participants(64 men and 72 women,aged 55–86 years) were recruited for our study between January 2014 and December 2016.All participants underwent MRI and Mini-Mental State Examination assessment(including 42 healthy control,38 T2 DM without cognitive impairment,26 with cognitive impairment but without T2 DM,and 30 T2 DM with cognitive impairment participants).The total and sub-category brain atrophy and lesion index scores in patients with T2 DM with cognitive impairment were higher than those in healthy controls.Differences in the brain atrophy and lesion index of gray matter lesions and subcortical dilated perivascular spaces were found between non-T2 DM patients with cognitive impairment and patients with T2 DM and cognitive impairment.After adjusting for age,the brain atrophy and lesion index retained its capacity to identify patients with T2 DM with cognitive impairment.These findings suggest that the brain atrophy and lesion index,based on T1-weighted and T2-weighted imaging,is of clinical value for identifying patients with T2 DM and cognitive impairment.Gray matter lesions and subcortical dilated perivascular spaces may be potential diagnostic markers of T2 DM that is complicated by cognitive impairment.This study was approved by the Medical Ethics Committee of University of South China(approval No.USC20131109003) on November 9,2013,and was retrospectively registered with the Chinese Clinical Trial Registry(registration No.Chi CTR1900024150) on June 27,2019.展开更多
Many existing intelligent recognition technologies require huge datasets for model learning.However,it is not easy to collect rectal cancer images,so the performance is usually low with limited training samples.In add...Many existing intelligent recognition technologies require huge datasets for model learning.However,it is not easy to collect rectal cancer images,so the performance is usually low with limited training samples.In addition,traditional rectal cancer staging is time-consuming,error-prone,and susceptible to physicians’subjective awareness as well as professional expertise.To settle these deficiencies,we propose a novel deep-learning model to classify the rectal cancer stages of T2 and T3.First,a novel deep learning model(RectalNet)is constructed based on residual learning,which combines the squeeze-excitation with the asymptotic output layer and new cross-convolution layer links in the residual block group.Furthermore,a two-stage data augmentation is designed to increase the number of images and reduce deep learning’s dependence on the volume of data.The experiment results demonstrate that the proposed method is superior to many existing ones,with an overall accuracy of 0.8583.Oppositely,other traditional techniques,such as VGG16,DenseNet121,EL,and DERNet,have an average accuracy of 0.6981,0.7032,0.7500,and 0.7685,respectively.展开更多
Variational models provide reliable formulation for segmentation of features and their boundaries in an image, following the seminal work of Mumford-Shah （1989, Commun. Pure Appl. Math.） on dividing a general surfac...Variational models provide reliable formulation for segmentation of features and their boundaries in an image, following the seminal work of Mumford-Shah （1989, Commun. Pure Appl. Math.） on dividing a general surface into piecewise smooth sub-surfaces. A cen- tral idea of models based on this work is to minimize the length of feature＇s boundaries （i.e., 7-I1 Hausdorff measure）. However there exist problems with irregular and oscillatory object boundaries, where minimizing such a length is not appropriate, as noted by Barchiesi et al. （2010, SIAM J. Multiscale Model. Simu.） who proposed to miminize ~：2 Lebesgue measure of the ~,-neighborhood of the boundaries. This paper presents a dual level set selective segmen- tation model based on Barchiesi et al. （2010） to automatically select a local feature instead of all global features. Our model uses two level set functions： a global level set which segments all boundaries, and the local level set which evolves and finds the boundary of the object closest to the geometric constraints. Using real life images with oscillatory boundaries, we show qualitative results demonstrating the effectiveness of the proposed method.展开更多
WS2 nanosheets were prepared by the solvent-thermal method in the presence of n-butyl lithium, then the exfoliation under the condition of ultrasound. The formed WS2 nanosheets were conjugated with thiol-modified poly...WS2 nanosheets were prepared by the solvent-thermal method in the presence of n-butyl lithium, then the exfoliation under the condition of ultrasound. The formed WS2 nanosheets were conjugated with thiol-modified polyethylene glycol （PEG-SH） to improve the biocompatibility. The nanosheets （WS2- PEG） were able to inhibit the growth of a model HeLa cancer cell line in vitro due to the high photothermal conversion efficiency of ~35% irradiated by an 808 nm laser （1 W/cm^2）. As a proof of concept, WS2-PEG nanosheets with the better X-ray attenuation property than the clinical computed tomography （CT） contrast agent （lohexol） could be performed for CT imaging of the lymph vessel.展开更多
Atmospheric CO2 can signal the presence of food, predators or environmental stress and trigger stereotypical behaviors in both vertebrates and invertebrates. Recent studies have shown that the necklace olfactory syste...Atmospheric CO2 can signal the presence of food, predators or environmental stress and trigger stereotypical behaviors in both vertebrates and invertebrates. Recent studies have shown that the necklace olfactory system in mice sensitively detects CO2 in the air. Olfactory CO2 neurons are believed to rely on cyclic gnanosine monophosphate （cGMP） as the key second messenger; however, the specific ion channel underlying CO2 responses remains unclear. Here we show that CO2-evoked neuronal and behavioral responses require cyclic nucleotide-gated （CNG） channels consisting of the CNGA3 subunit. Through Ca2＋-imaging, we found that CO2-triggered Ca2＋ influx was abolished in necklace olfactory sensory neurons （OSNs） of CNGA3-knockout mice. Olfactory detection tests using a Go/No-go paradigm showed that these knockout mice failed to detect 0.5% CO2. Thus, sensitive detection of atmospheric CO2 depends on the function of CNG channels consisting of the CNGA3 subunit in necklace OSNs. These data support the important role of the necklace olfactory system in CO2 sensing and extend our understanding of the signal transduction pathway mediating CO2 detection in mammals [Current Zoology 56 （6）： 793-799, 2010].展开更多
文摘新近,欧洲糖尿病预防指南与培训标准工作组(Development and Implementation of a European Guideline and Training Standards for Diabetes Prevention,IMAGE)颁布了2型糖尿病(T2DM)预防指南,其要点摘译如下:
基金supported by the National Key Research and Development Program of China (2018YFD020040103)the National Key Research and Development Program of Shanxi Province, China (201803D221005-2)。
文摘Assimilating Sentinel-2 images with the CERES-Wheat model can improve the precision of winter wheat yield estimates at a regional scale. To verify this method, we applied the ensemble Kalman filter(EnKF) to assimilate the leaf area index(LAI) derived from Sentinel-2 data and simulated by the CERES-Wheat model. From this, we obtained the assimilated daily LAI during the growth stage of winter wheat across three counties located in the southeast of the Loess Plateau in China: Xiangfen, Xinjiang, and Wenxi. We assigned LAI weights at different growth stages by comparing the improved analytic hierarchy method, the entropy method, and the normalized combination weighting method, and constructed a yield estimation model with the measurements to accurately estimate the yield of winter wheat. We found that the changes of assimilated LAI during the growth stage of winter wheat strongly agreed with the simulated LAI. With the correction of the derived LAI from the Sentinel-2 images, the LAI from the green-up stage to the heading–filling stage was enhanced, while the LAI decrease from the milking stage was slowed down, which was more in line with the actual changes of LAI for winter wheat. We also compared the simulated and derived LAI and found the assimilated LAI had reduced the root mean square error(RMSE) by 0.43 and 0.29 m^(2) m^(–2), respectively, based on the measured LAI. The assimilation improved the estimation accuracy of the LAI time series. The highest determination coefficient(R2) was 0.8627 and the lowest RMSE was 472.92 kg ha^(–1) in the regression of the yields estimated by the normalized weighted assimilated LAI method and measurements. The relative error of the estimated yield of winter wheat in the study counties was less than 1%, suggesting that Sentinel-2 data with high spatial-temporal resolution can be assimilated with the CERES-Wheat model to obtain more accurate regional yield estimates.
基金funded by the National Natural Science Foundation of China(42071300)the Fujian Province Natural Science(2020J01504)+4 种基金the China Postdoctoral Science Foundation(2018M630728)the Open Fund of Fujian Provincial Key Laboratory of Resources and Environment Monitoring&Sustainable Management and Utilization(ZD202102)the Program for Innovative Research Team in Science and Technology in Fujian Province University(KC190002)the Open Fund of University Key Lab of Geomatics Technology and Optimize Resources Utilization in Fujian Province(fafugeo201901)supported by the Research Project of Jinjiang Fuda Science and Education Park Development Center(2019-JJFDKY-17)。
文摘Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content inversion.However,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered.Therefore,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation levels.Quantitative inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were derived.The scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were calculated.The results showed that LAI,CCC,and CEWT were inversely related with PPC-induced stress.When applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),respectively.Compared to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for CCC.The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.
文摘Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer.Methods We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging(MRI).The morphological characteristics of breast lesions were evaluated using DCE,DWI,and T2WI based on BI-RADS lexicon descriptors by trained radiologists.Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions,and the differences between benign and malignant lesions in each group were compared.Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis.Diagnostic efficacies were compared using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results For mass-like lesions,all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE,DWI,and T2WI(P<0.05).The combined method(DCE+DWI+T2WI)had a higher AUC(0.865)than any of the individual modality(DCE:0.786;DWI:0.793;T2WI:0.809)(P<0.05).For non-mass-like lesions,DWI signal intensity was a significant predictor of malignancy(P=0.036),but the model using DWI alone had a low AUC(0.669).Conclusion Morphological assessment using the combination of DCE,DWI,and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.
文摘BACKGROUND Colorectal cancer is a malignancy with a high risk of lymph node metastasis and poor prognosis,and thus requires an accurate diagnosis.AIM To assess the diagnostic value of combined magnetic resonance T2-weighted imaging(T2WI)and diffusion-weighted imaging(DWI)in colorectal cancer.METHODS We included 120 patients with suspected colorectal cancer who underwent magnetic resonance imaging.Surgical pathology was used as the gold standard for comparison.Combined T2WI and DWI showed higher diagnostic efficacy than either of the two methods used individually.RESULTS The combined method achieved 94.74%sensitivity,95.45%specificity,95.00%accuracy,94.74%positive predictive value,and 95.45%negative predictive value in qualitative diagnosis.It showed 94.44%sensitivity,95.00%specificity,94.74%accuracy,94.44%positive predictive value,and 95.00%negative predictive value in clinical staging.Finally,it showed 94.74%sensitivity,94.59%specificity,94.74%accuracy,94.74%positive predictive value,and 94.59%negative predictive value in diagnosing lymph node metastasis.These results were highly consistent with that of the gold standard.CONCLUSION This study combined T2WI and DWI for accurate diagnosis of colorectal cancer,aiding clinical staging and lymph node metastasis assessment.This approach is promising for clinical application.
基金supported in part by the National Key Research and Development Program of China(Grant No.2019YFB2204300)in part by the National Natural Science Foundation of China(Grant Nos.62334008 and 62274154)in part by the Key Program of National Natural Science Foundation of China(Grant No.62134004).
文摘This paper describes a 2D/3D vision chip with integrated sensing and processing capabilities.The 2D/3D vision chip architecture includes a 2D/3D image sensor and a programmable visual processor.In this architecture,we design a novel on-chip processing flow with die-to-die image transmission and low-latency fixed-point image processing.The vision chip achieves real-time end-to-end processing of convolutional neural networks(CNNs)and conventional image processing algo-rithms.Furthermore,an end-to-end 2D/3D vision system is built to exhibit the capacity of the vision chip.The vision system achieves real-timing applications under 2D and 3D scenes,such as human face detection(processing delay 10.2 ms)and depth map reconstruction(processing delay 4.1 ms).The frame rate of image acquisition,image process,and result display is larger than 30 fps.
文摘Background:Successful liver resection in oncologic surgery depends on safety,precision,and efficacy,all of which require a thorough understanding of liver anatomy.Contrast-enhanced computed tomography(CT)-generated three-dimensional(3D)models have been proposed as a valuable tool to enhance this understanding.However,a systematic comparison of different display modalities across professional groups has not yet been performed.Methods:In this prospective,monocentric randomized trial,we compared high-resolution twodimensional(2D)CT images of liver malignancies with their corresponding standardized,non-colored 3D virtual and printed models in facilitating anatomical and spatial understanding as well as surgical decision-making.A total of 91 participants,including 40 surgeons,10 radiologists,and 41 students,evaluated six clinical cases(three centrally and three peripherally located liver malignancies).Each participant assessed one central and one peripheral case per display modality,presented in a random order.Results:Compared to 2D CT images,both 3D virtual and printed models significantly improved the identification of tumor location(P<0.001),enhanced the comprehension of spatial relationships with adjacent liver and portal veins(P<0.001 and P=0.019,respectively),and facilitated clinical decisionmaking(P<0.001).No significant difference was observed between virtual and printed models in terms of effectiveness.Within the different groups,surgeons and students,but not radiologists,more accurately identified tumor location and spatial relationships with adjacent liver and portal veins using 3D models.Subjectively,most surgeons and students preferred 3D printed models over virtual models and 2D CT images.Conclusions:This study demonstrated that standardized,non-colored 3D virtual and printed models equally help preoperative anatomical understanding and decision-making,particularly for surgeons and students.By isolating the influence of display modality,our findings clarify prior inconsistent results and support the integration of cost-effective 3D visualization by applying virtual models into surgical planning and education.Preference for printed models despite comparable efficacy highlights the importance of user-centered implementation strategies.
文摘Prostate cancer （PCa） is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） to classify men with PCa, clinically significant PCa （CSPCa）, or no PCa, especially among those with serum total prostate-specific antigen （tPSA） levels in the ＂gray zone＂ （4-10 ng ml-1）. A total of 308 patients （355 lesions） were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density （PSAD） were independent predictors of PCa and CSPCa. A PI-RADS v2 score L≥4 provided high negative predictive values （91.39% for PCa and 95.69% for CSPCa）. A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group （PI-RADS score = 5 and PSAD L≥0 15 ng ml-1 cm-3, with tPSA in the gray zone, or PI-RADS score L≥4 with high tPSA level） with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.
基金Supported by the Key Research and Development Plan of Shaanxi Province,No.2021SF-298.
文摘BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.
文摘Objective:To achieve precision medicine,the use of imaging methods to help the clinical detection of cerebral infarction is conducive to the clinical development of a treatment plan and increase of the cure rate and improvement of the prognosis of patients.Methods:In this work,T2-weighted imaging(T2WI),diffusion-weighted imaging(DWI),susceptibility-weighted imaging(SWI),and diffusion tensor imaging(DTI)examinations were performed on 34 patients with clinically diagnosed cerebral infarction to measure the difference in signal intensity between the lesion and its mirror area and make a comparative analysis by means of the Student-Newman-Keuls method.Results:The detection rate of T2WI was 79%(27/34),the detection rate of DWI was 97%(33/34),the detection rate of SWI was 88%(30/34),and the detection rate of DTI was 94%(32/34).Conclusion:The imaging performance was in the order DWI>DTI>SWI>T2WI for the diagnosis of cerebral infarction,and combined imaging is better than single imaging.
基金Supported by The Gastrointestinal and Liver Disease Research Center of Tehran University of Medical Sciences
文摘AIM: To investigate the accuracy of T2*-weighted magnetic resonance imaging (MRI T2*) in the evaluation of iron overload in beta-thalassemia major patients. METHODS: In this cross-sectional study, 210 patients with beta-thalassemia major having regular blood transfusions were consecutively enrolled. Serum ferritin levels were measured, and all patients underwent MRI T2* of the liver. Liver biopsy was performed in 53 patients at an interval of no longer than 3 mo after the MRIT2* in each patient. The amount of iron was assessed in both MRI T2* and liver biopsy specimens of each patient. RESULTS: Patients’ ages ranged from 8 to 54 years with a mean of 24.59 ± 8.5 years. Mean serum ferritin level was 1906 ± 1644 ng/mL. Liver biopsy showed a moderate negative correlation with liver MRI T2* (r = -0.573, P = 0.000) and a low positive correlation with ferritin level (r = 0.350, P = 0.001). Serum ferritin levels showed a moderate negative correlation with liver MRI T2* values (r = -0.586, P = 0.000). CONCLUSION: Our study suggests that MRI T2* is a non-invasive, safe and reliable method for detecting iron load in patients with iron overload.
基金the Fujian Province Clinical Key Specialty Construction Project,No.2022884Quanzhou Science and Technology Plan Project,No.2021N034S+1 种基金The Youth Research Project of Fujian Provincial Health Commission,No.2022QNA067Malignant Tumor Clinical Medicine Research Center,No.2020N090s.
文摘BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation grade of CRC is of great value.AIM To develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on T2-weighted images(T2WI).METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023.Patients were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 ratio.Lesions were delineated layer by layer on high-resolution T2WI.Least absolute shrinkage and selection operator regression was applied to screen for radiomic features.Radiomics and clinical models were constructed using the multilayer perceptron(MLP)algorithm.These radiomic features and clinically relevant variables(selected based on a significance level of P<0.05 in the training set)were used to construct radiomics-clinical models.The performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULTS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic model.Eight different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic performance.The AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation cohort.The AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation cohort.The clinical model achieved an AUC of 0.751(95%CI:0.661-0.842)in the training cohort and 0.676(95%CI:0.525-0.827)in the validation cohort.All three models demonstrated good accuracy.In the training cohort,the AUC of the radiomic-clinical model was significantly greater than that of the clinical model(P=0.005)and the radiomic model(P=0.016).DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process.CONCLUSION In this study,we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC.This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.
文摘The diagnosis of the recurrent optic neuritis is commonly established clinically,and sometimes it could be challenging because the involved optic nerve does not always show significant enhancement on conventional contrast enhanced-T1 weighted imaging（CE-T1W1）.In this paper,we reported a middle-aged female with early diagnosis of recurrent optic neuritis using contrast-enhanced T2 fluid-attenuated inversion recovery imaging（CET2FLAIR）.The involved optic nerve presented evident enhancement on CE-T2FLAIR and no enhancement on CE-T1W1.This case suggested that the CE-T2FLAIR may be a useful diagnostic tool specifically for the recurrent optic neuritis in clinical practice.
文摘We use laser-scanning nonlinear imaging microscopy in atomically thin transition metal dichalcogenides(TMDs)to reveal information on the crystalline orientation distribution,within the 2D lattice.In particular,we perform polarization-resolved second-harmonic generation(PSHG)imaging in a stationary,raster-scanned chemical vapor deposition(CVD)-grown WS2 flake,in order to obtain with high precision a spatially resolved map of the orientation of its main crystallographic axis(armchair orientation).By fitting the experimental PSHG images of sub-micron resolution into a generalized nonlinear model,we are able to determine the armchair orientation for every pixel of the image of the 2D material,with further improved resolution.This pixel-wise mapping of the armchair orientation of 2D WS2 allows us to distinguish between different domains,reveal fine structure,and estimate the crystal orientation variability,which can be used as a unique crystal quality marker over large areas.The necessity and superiority of a polarization-resolved analysis over intensity-only measurements is experimentally demonstrated,while the advantages of PSHG over other techniques are analysed and discussed.
基金supported by the National Natural Science Foundation of China,No.81271538 (to SNP)345 Talent Project and the Natural Science Foundation of Liaoning Province of China,No.2019-ZD-0794 (to SNP)+1 种基金the Natural Science Foundation of Hunan Province of China,Nos.2017JJ2225 (to JCL),2018JJ2357 (to GHL)Hunan Provincial Science and Technology Innovation Program of China,No.2017SK50203 (to HZ)。
文摘Patients with type 2 diabetes mellitus(T2 DM) often have cognitive impairment and structural brain abnormalities.The magnetic resonance imaging(MRI)-based brain atrophy and lesion index can be used to evaluate common brain changes and their correlation with cognitive function,and can therefore also be used to reflect whole-brain structural changes related to T2 DM.A total of 136 participants(64 men and 72 women,aged 55–86 years) were recruited for our study between January 2014 and December 2016.All participants underwent MRI and Mini-Mental State Examination assessment(including 42 healthy control,38 T2 DM without cognitive impairment,26 with cognitive impairment but without T2 DM,and 30 T2 DM with cognitive impairment participants).The total and sub-category brain atrophy and lesion index scores in patients with T2 DM with cognitive impairment were higher than those in healthy controls.Differences in the brain atrophy and lesion index of gray matter lesions and subcortical dilated perivascular spaces were found between non-T2 DM patients with cognitive impairment and patients with T2 DM and cognitive impairment.After adjusting for age,the brain atrophy and lesion index retained its capacity to identify patients with T2 DM with cognitive impairment.These findings suggest that the brain atrophy and lesion index,based on T1-weighted and T2-weighted imaging,is of clinical value for identifying patients with T2 DM and cognitive impairment.Gray matter lesions and subcortical dilated perivascular spaces may be potential diagnostic markers of T2 DM that is complicated by cognitive impairment.This study was approved by the Medical Ethics Committee of University of South China(approval No.USC20131109003) on November 9,2013,and was retrospectively registered with the Chinese Clinical Trial Registry(registration No.Chi CTR1900024150) on June 27,2019.
基金supported in part by the National Natural Science Foundation of China under Grants 62172192,U20A20228,and 62171203in part by the 2018 Six Talent Peaks Project of Jiangsu Province under Grant XYDXX-127in part by the Science and Technology Demonstration Project of Social Development of Jiangsu Province under Grant BE2019631.
文摘Many existing intelligent recognition technologies require huge datasets for model learning.However,it is not easy to collect rectal cancer images,so the performance is usually low with limited training samples.In addition,traditional rectal cancer staging is time-consuming,error-prone,and susceptible to physicians’subjective awareness as well as professional expertise.To settle these deficiencies,we propose a novel deep-learning model to classify the rectal cancer stages of T2 and T3.First,a novel deep learning model(RectalNet)is constructed based on residual learning,which combines the squeeze-excitation with the asymptotic output layer and new cross-convolution layer links in the residual block group.Furthermore,a two-stage data augmentation is designed to increase the number of images and reduce deep learning’s dependence on the volume of data.The experiment results demonstrate that the proposed method is superior to many existing ones,with an overall accuracy of 0.8583.Oppositely,other traditional techniques,such as VGG16,DenseNet121,EL,and DERNet,have an average accuracy of 0.6981,0.7032,0.7500,and 0.7685,respectively.
文摘Variational models provide reliable formulation for segmentation of features and their boundaries in an image, following the seminal work of Mumford-Shah （1989, Commun. Pure Appl. Math.） on dividing a general surface into piecewise smooth sub-surfaces. A cen- tral idea of models based on this work is to minimize the length of feature＇s boundaries （i.e., 7-I1 Hausdorff measure）. However there exist problems with irregular and oscillatory object boundaries, where minimizing such a length is not appropriate, as noted by Barchiesi et al. （2010, SIAM J. Multiscale Model. Simu.） who proposed to miminize ~：2 Lebesgue measure of the ~,-neighborhood of the boundaries. This paper presents a dual level set selective segmen- tation model based on Barchiesi et al. （2010） to automatically select a local feature instead of all global features. Our model uses two level set functions： a global level set which segments all boundaries, and the local level set which evolves and finds the boundary of the object closest to the geometric constraints. Using real life images with oscillatory boundaries, we show qualitative results demonstrating the effectiveness of the proposed method.
基金partially supported by National Natural Science Foundation of China (Nos.21271130,21371122,and 11275050)Program for Changjiang Scholars and Innovative Research Team in University (No.IRT1269)+4 种基金Shanghai Science and Technology Development Fund (Nos.12ZR1421800 and 13520502800)Shanghai Pujiang Program (No.13PJ1406600)Shanghai Municipal Education Commission (No.13ZZ110)Shanghai Normal University (Nos.DXL122 and SK201339)International Joint Laboratory on Resource Chemistry (IJLRC)
文摘WS2 nanosheets were prepared by the solvent-thermal method in the presence of n-butyl lithium, then the exfoliation under the condition of ultrasound. The formed WS2 nanosheets were conjugated with thiol-modified polyethylene glycol （PEG-SH） to improve the biocompatibility. The nanosheets （WS2- PEG） were able to inhibit the growth of a model HeLa cancer cell line in vitro due to the high photothermal conversion efficiency of ~35% irradiated by an 808 nm laser （1 W/cm^2）. As a proof of concept, WS2-PEG nanosheets with the better X-ray attenuation property than the clinical computed tomography （CT） contrast agent （lohexol） could be performed for CT imaging of the lymph vessel.
基金supported by the China Ministry of Science and Technology 973 (2010CB833902)863 grants (2008AA022902)
文摘Atmospheric CO2 can signal the presence of food, predators or environmental stress and trigger stereotypical behaviors in both vertebrates and invertebrates. Recent studies have shown that the necklace olfactory system in mice sensitively detects CO2 in the air. Olfactory CO2 neurons are believed to rely on cyclic gnanosine monophosphate （cGMP） as the key second messenger; however, the specific ion channel underlying CO2 responses remains unclear. Here we show that CO2-evoked neuronal and behavioral responses require cyclic nucleotide-gated （CNG） channels consisting of the CNGA3 subunit. Through Ca2＋-imaging, we found that CO2-triggered Ca2＋ influx was abolished in necklace olfactory sensory neurons （OSNs） of CNGA3-knockout mice. Olfactory detection tests using a Go/No-go paradigm showed that these knockout mice failed to detect 0.5% CO2. Thus, sensitive detection of atmospheric CO2 depends on the function of CNG channels consisting of the CNGA3 subunit in necklace OSNs. These data support the important role of the necklace olfactory system in CO2 sensing and extend our understanding of the signal transduction pathway mediating CO2 detection in mammals [Current Zoology 56 （6）： 793-799, 2010].
