Recent advancements in artificial intelligence have transformed three-dimensional(3D)optical imaging and metrology,enabling high-resolution and high-precision 3D surface geometry measurements from one single fringe pa...Recent advancements in artificial intelligence have transformed three-dimensional(3D)optical imaging and metrology,enabling high-resolution and high-precision 3D surface geometry measurements from one single fringe pattern projection.However,the imaging speed of conventional fringe projection profilometry(FPP)remains limited by the native sensor refresh rates due to the inherent"one-to-one"synchronization mechanism between pattern projection and image acquisition in standard structured light techniques.Here,we present dual-frequency angular-multiplexed fringe projection profilometry(DFAMFPP),a deep learning-enabled 3D imaging technique that achieves high-speed,high-precision,and large-depth-range absolute 3D surface measurements at speeds 16 times faster than the sensor's native frame rate.By encoding multi-timeframe 3D information into a single multiplexed image using multiple pairs of dual-frequency fringes,high-accuracy absolute phase maps are reconstructed using specially trained two-stage number-theoretical-based deep neural networks.We validate the effectiveness of DFAMFPP through dynamic scene measurements,achieving 10,000 Hz 3D imaging of a running turbofan engine prototype with only a 625 Hz camera.By overcoming the sensor hardware bottleneck,DFAMFPP significantly advances high-speed and ultra-high-speed 3D imaging,opening new avenues for exploring dynamic processes across diverse scientific disciplines.展开更多
Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL...Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL models,however,do not necessarily obey the fundamental governing laws of PAM physical systems,nor do they generalize well to scenarios on which they have not been trained.In this work,a physics-embedded degeneration learning(PEDL)approach is proposed to enhance the image quality of PAM with a self-attention enhanced U-Net network,which obtains greater physical consistency,improves data efficiency,and higher adaptability.The proposed method is demonstrated on both synthetic and real datasets,including animal experiments in vivo(blood vessels of mouse's ear and brain).And the results show that compared with previous DL methods,the PEDL algorithm exhibits good performance in recovering PAM images qualitatively and quantitatively.It overcomes the challenges related to training data,accuracy,and robustness which a typical data-driven approach encounters,whose exemplary application envisions to provide a new perspective for existing DL tools of enhanced PAM.展开更多
Colitis-associated colorectal cancer(CAC),a serious complication of ulcerative colitis(UC),is associated with a poor prognosis.The vitamin D receptor(VDR)is recognized for its protective role in UC and CAC through the...Colitis-associated colorectal cancer(CAC),a serious complication of ulcerative colitis(UC),is associated with a poor prognosis.The vitamin D receptor(VDR)is recognized for its protective role in UC and CAC through the maintenance of intestinal barrier integrity and the regulation of inflammation.This study demonstrates a significant reduction in m^(6)A-related genes,particularly methyltransferase like 14(METTL14),in UC and CAC patients and identifies an association between METTL14 and VDR.In the azoxymethane(AOM)/dextran sodium sulfate(DSS)-induced mousemodel,vitamin D treatment increases METTL14 expression and reduces tumorburden,while Vdr-knockout mice exhibit lower METTL14 levels and increased tumorigenesis.In vitro,the VDR agonist calcipotriol upregulates METTL14 in NCM460 cells,with this effect attenuated by VDR knockdown.VDRknockdown inDLD-1colon cancer cellsdecreases METTL14 expressionand promotes proliferation,which is reversed by METTL14 overexpression.Mechanistic studies reveal that VDR regulates METTL14 expression via promoter binding,modulating key target genes such as SOX4,DROSH,and PHLPP2.This study highlights the role of the VDR-METTL14 axis as a protective mechanism in CAC and suggests its potential as a therapeutic target for preventing and treating CAC.展开更多
恶性肿瘤的免疫治疗是当前肿瘤研究和治疗领域的热点,免疫检查点分子程序性死亡受体-1(programmed cell death receptor-1,PD-1)和细胞毒性T淋巴细胞相关抗原4(cytotoxic T lymphocyte-associated antigen 4,CTLA-4)相关信号通路的激活...恶性肿瘤的免疫治疗是当前肿瘤研究和治疗领域的热点,免疫检查点分子程序性死亡受体-1(programmed cell death receptor-1,PD-1)和细胞毒性T淋巴细胞相关抗原4(cytotoxic T lymphocyte-associated antigen 4,CTLA-4)相关信号通路的激活可以抑制T淋巴细胞活化,肿瘤细胞通过激活该信号通路实现免疫逃逸。免疫检查点抑制剂(immuno-checkpoint inhibitors,ICIs)通过抑制该信号通路,活化T淋巴细胞发挥机体对肿瘤细胞的清除。因此,ICIs的相关毒性包括免疫相关的不良事件(immune-related adverse effects,irAEs)。消化系统如胃肠道、肝脏作为人体重要的消化吸收器官、代谢解毒器官,同时也是重要的免疫相关器官,是irAEs的常见受累系统。本文将分别对ICIs的肝脏、胃肠道不良反应的发生率、临床表现、诊断和处理分别进行阐述。展开更多
Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a sing...Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a single fringe image.In this paper,we demonstrate that the deep neural networks can be trained to directly recover the absolute phase from a unique fringe image that involves spatially multiplexed fringe patterns of different frequencies.The extracted phase is free from spectrum-aliasing problem which is hard to avoid for traditional spatial-multiplexing methods.Experiments on both static and dynamic scenes show that the proposed approach is robust to object motion and can obtain high-quality 3D reconstructions of isolated objects within a single fringe image.展开更多
To reveal the fundamental aspects hidden behind a variety of transient events in mechanics,physics,and biology,the highly desired ability to acquire three-dimensional(3D)images with ultrafast temporal resolution has b...To reveal the fundamental aspects hidden behind a variety of transient events in mechanics,physics,and biology,the highly desired ability to acquire three-dimensional(3D)images with ultrafast temporal resolution has been long sought.As one of the most commonly employed 3D sensing techniques,fringe projection profilometry(FPP)reconstructs the depth of a scene from stereo images taken with sequentially structured illuminations.However,the imaging speed of current FPP methods is generally capped at several kHz,which is limited by the projector-camera hardware and the number of fringe patterns required for phase retrieval and unwrapping.Here we report a novel learning-based ultrafast 3D imaging technique,termed single-shot super-resolved FPP(SSSR-FPP),which enables ultrafast 3D imaging at 100,000 Hz.SSSR-FPP uses only one pair of low signal-to-noise ratio(SNR),low-resolution,and pixelated fringe patterns as input,while the high-resolution unwrapped phase and fringe orders can be deciphered with a specific trained deep neural network.Our approach exploits the significant speed gain achieved by reducing the imaging window of conventional high-speed cameras,while"regenerating"the lost spatial resolution through deep learning.To demonstrate the high spatio-temporal resolution of SSSR-FPP,we present 3D videography of several transient scenes,including rotating turbofan blades,exploding building blocks,and the reciprocating motion of a steam engine,etc.,which were previously challenging or even impossible to capture with conventional methods.Experimental results establish SSSR-FPP as a significant step forward in the field of 3D optical sensing,offering new insights into a broad spectrum of dynamic processes across various scientific disciplines.展开更多
The current state of traditional optoelectronic imaging technology is constrained by the inherent limitations of its hardware.These limitations pose significant challenges in acquiring higher-dimensional information a...The current state of traditional optoelectronic imaging technology is constrained by the inherent limitations of its hardware.These limitations pose significant challenges in acquiring higher-dimensional information and reconstructing accurate images,particularly in applications such as scattering imaging,superresolution,and complex scene reconstruction.However,the rapid development and widespread adoption of deep learning are reshaping the field of optical imaging through computational imaging technology.Datadriven computational imaging has ushered in a paradigm shift by leveraging the nonlinear expression and feature learning capabilities of neural networks.This approach transcends the limitations of conventional physical models,enabling the adaptive extraction of critical features directly from data.As a result,computational imaging overcomes the traditional“what you see is what you get”paradigm,paving the way for more compact optical system designs,broader information acquisition,and improved image reconstruction accuracy.These advancements have significantly enhanced the interpretation of highdimensional light-field information and the processing of complex images.This review presents a comprehensive analysis of the integration of deep learning and computational imaging,emphasizing its transformative potential in three core areas:computational optical system design,high-dimensional information interpretation,and image enhancement and processing.Additionally,this review addresses the challenges and future directions of this cutting-edge technology,providing novel insights into interdisciplinary imaging research.展开更多
Inammatory bowel disease(IBD),which includes Crohn’s disease(CD)and ulcerative colitis(UC),is a chronic,progressive illness thatuctuates in severity and involves recurring periods of relapse and remission.It has emer...Inammatory bowel disease(IBD),which includes Crohn’s disease(CD)and ulcerative colitis(UC),is a chronic,progressive illness thatuctuates in severity and involves recurring periods of relapse and remission.It has emerged as a global public health challenge.Traditionally,IBD has been predominantly found in Western countries,with North America and Europe exhibiting the highest rates of prevalence and incidence.Specically,the prevalence and incidence rates for UC were 505/100,000 and 249/100,000,respectively,while for CD they were 322/100,000 and 319/100,000,respectively.[1]However,there has been a recent stabilization of IBD incidence in countries with high prevalence rates.展开更多
The role of Chinese expert consensus in standardization and improvement of the clinical diagnosis and treatment of inflammatory bowel disease(IBD)is self-evident.As clinical and basic research in China becomes standar...The role of Chinese expert consensus in standardization and improvement of the clinical diagnosis and treatment of inflammatory bowel disease(IBD)is self-evident.As clinical and basic research in China becomes standardized under a better understanding of IBD,more data on Chinese patients have become available to develop a consensus and guideline.This guideline,collaboratively developed by the IBD Group,Chinese Society of Gastroenterology,incorporates the latest international consensus statements,[1-7]domestic research findings,and practical considerations,as an update based on the 2018 Chinese consensus on IBD management.[8]The IBD guideline consists of two parts:ulcerative colitis(UC)and Crohn’s disease,and this manuscript presented the UC part.The evidence used in this guideline was collected and analyzed by the standard of guideline,and the contents were organized as problem statements,for clarity.The formulation of this guideline aimed to reflect the latest progress in IBD,providing comprehensive and valuable guidance for the clinical management of IBD.展开更多
Background:Inflammatory bowel disease(IBD)imposes a significant economic and social burden in China.We aim to assess the epidemiological trends of IBD in China,and to predict the burden in the near future.Methods:The ...Background:Inflammatory bowel disease(IBD)imposes a significant economic and social burden in China.We aim to assess the epidemiological trends of IBD in China,and to predict the burden in the near future.Methods:The incidence,mortality,prevalence,and disability-adjusted life year(DALYs)of IBD from 1990 to 2021 were obtained from Global Burden of Disease Study 2021.Estimated annual percentage change(EAPC),average annual percent change,total percent change,and age-period-cohort model were used to access trends.Bayesian age–period–cohort model was utilized to predict the risk of incidence and mortality.Results:In 2021,IBD affected 168,077 people in China,with 24,941 new cases and 5640 deaths.The age-standardized rate(ASR)of incidence and death was 1.4 and 0.3,respectively.The incidence and prevalence in China were lower than the global and high socio-demographic index(SDI)regions,but the ASR of incidence and prevalence(EAPC:2.93 and 2.54,respectively)had rapidly increased from 1990 to 2021.The ASR of death and DALYs had significantly decreased(EAPC:−3.05 and−2.93,respectively).Middle-aged and elderly populations faced a severe burden of incidence and prevalence,while the elderly population faced a severe mortality burden.It is projected that by 2035,the ASR of incidence will continue to rise,whereas the death rate will continue to decline.Conclusions:The burden of IBD in China is serious and increasingly severe.Establishing a comprehensive disease management system in China will help better control the medical burden of IBD.展开更多
To investigate the prevalence of gastroesophageal reflux disease(GERD),reflux esophagitis(RE),digestive ulcer gastric ulcer(GU),duodenal ulcer(DU),and Helicobacter pylori infection in Chinese adults aged 18-64 years a...To investigate the prevalence of gastroesophageal reflux disease(GERD),reflux esophagitis(RE),digestive ulcer gastric ulcer(GU),duodenal ulcer(DU),and Helicobacter pylori infection in Chinese adults aged 18-64 years and their associated factors,a community-based cross-sectional study using a stratified multi-stage sampling method was conducted.A standardized questionnaire survey,the^(13)C-urea breath test,and gastroscopy were performed.Weighted methods were used to estimate the prevalence of diseases or infection mentioned above and their risk factors.Finally,27,637 participants aged 18-64 years were enrolled from 2017 to 2018.The prevalence(95%confidence interval)of GERD,RE,GU,DU,and H.pylori infection was estimated to be 10.5%(7.8%-14.2%),5.4%(3.9%-7.3%),2.5%(1.7%-3.7%),4.5%(3.6%-5.4%),and 41.5%(36.7%-46.4%),respectively.The fraction of H.pylori infection reached 58.6%and 61.1%among the GU and DU patients,respectively.Weighted multivariable logistic regression models showed that GERD,RE,and GU shared the common risk factors of age and obesity.Dose-response relationships were observed between smoking and all four diseases,as well as alcohol consumption and GERD and H.pylori infection.Northwest China had the highest prevalence of GERD(23.9%),RE(8.7%),GU(7.8%),DU(7.3%),and H.pylori infection(63.6%);however,the southwest region had the highest prevalence of GU but the lowest of DU,RE,and H.pylori infection.Non-steroidal anti-inflammatory drugs were positively associ-ated with GERD risk.On the contrary,a reduced risk of GU was observed among H.pylori-infected patients taking this drug.In summary,the prevalence of GERD,RE,and H.pylori infection still appears high in China.H.pylori infection eradication remains the priority to reduce the burden of peptic ulcer dis-ease.The aging population,high prevalence of overweight or obesity,smoking,and drinking in China could explain the high burden of these diseases,thus suggesting the targeted preventive measures for upper gastrointestinal diseases in the future.展开更多
Background:Erosive esophagitis(EE)is a gastroesophageal reflux disease characterized by mucosal breaks in the esophagus.Proton pump inhibitors are widely used as maintenance therapy for EE,but many patients still rela...Background:Erosive esophagitis(EE)is a gastroesophageal reflux disease characterized by mucosal breaks in the esophagus.Proton pump inhibitors are widely used as maintenance therapy for EE,but many patients still relapse.In this trial,we evaluated the noninferiority of vonoprazan vs.lansoprazole as maintenance therapy in patients with healed EE.Methods:We performed a double-blind,double-dummy,multicenter,phase 3 clinical trial among non-Japanese Asian adults with endoscopically confirmed healed EE from April 2015 to February 2019.Patients from China,South Korea,and Malaysia were randomized to vonoprazan 10 mg or 20 mg once daily or lansoprazole 15 mg once daily for 24 weeks.The primary endpoint was endoscopically confirmed EE recurrence rate over 24 weeks with a noninferiority margin of 10%using a two-sided 95%confidence interval(CI).Treatment-emergent adverse events(TEAEs)were recorded.Results:Among 703 patients,EE recurrence was observed in 24/181(13.3%)and 21/171(12.3%)patients receiving vonoprazan 10 mg or 20 mg,respectively,and 47/184(25.5%)patients receiving lansoprazole(differences:-12.3%[95%CI,-20.3%to-4.3%]and-13.3%[95%CI,-21.3%to-5.3%],respectively),meeting the primary endpoint of noninferiority to lansoprazole in preventing EE recurrence at 24 weeks.Evidence of superiority(upper bound of 95%CI<0%)was also observed.At 12 weeks,endoscopically confirmed EE recurrence was observed in 5/18,2/20,and 7/20 of patients receiving vonoprazan 10 mg,vonoprazan 20 mg,and lansoprazole,respectively.TEAEs were experienced by 66.8%(157/235),69.0%(156/226),and 65.3%(158/242)of patients receiving vonoprazan 10 mg,vonoprazan 20 mg,and lansoprazole,respectively.The most common TEAE was upper respiratory tract infection in 12.8%(30/235)and 12.8%(29/226)patients in vonoprazan 10 mg and 20 mg groups,respectively and 8.7%(21/242)patients in lansoprazole group.Conclusion:Vonoprazan maintenance therapy was well-tolerated and noninferior to lansoprazole for preventing EE recurrence in Asian patients with healed EE.Trial Registration:https://clinicaltrials.gov;NCT02388737.展开更多
Recent advances in imaging sensors and digital light projection technology have facilitated rapid progress in 3D optical sensing,enabling 3D surfaces of complexshaped objects to be captured with high resolution and ac...Recent advances in imaging sensors and digital light projection technology have facilitated rapid progress in 3D optical sensing,enabling 3D surfaces of complexshaped objects to be captured with high resolution and accuracy.Nevertheless,due to the inherent synchronous pattern projection and image acquisition mechanism,the temporal resolution of conventional structured light or fringe projection profilometry(FPP)based 3D imaging methods is still limited to the native detector frame rates.In this work,we demonstrate a new 3D imaging method,termed deep-learning-enabled multiplexed FPP(DLMFPP),that allows to achieve high-resolution and high-speed 3D imaging at near-one-order of magnitude-higher 3D frame rate with conventional low-speed cameras.By encoding temporal information in one multiplexed fringe pattern,DLMFPP harnesses deep neural networks embedded with Fourier transform,phase-shifting and ensemble learning to decompose the pattern and analyze separate fringes,furnishing a high signal-to-noise ratio and a ready-to-implement solution over conventional computational imaging techniques.We demonstrate this method by measuring different types of transient scenes,including rotating fan blades and bullet fired from a toy gun,at kHz using cameras of around 100 Hz.Experiential results establish that DLMFPP allows slow-scan cameras with their known advantages in terms of cost and spatial resolution to be used for high-speed 3D imaging tasks.展开更多
With the advances in scientific foundations and technological implementations,optical metrology has become versatile problem-solving backbones in manufacturing,fundamental research,and engineering applications,such as...With the advances in scientific foundations and technological implementations,optical metrology has become versatile problem-solving backbones in manufacturing,fundamental research,and engineering applications,such as quality control,nondestructive testing,experimental mechanics,and biomedicine.In recent years,deep learning,a subfield of machine learning,is emerging as a powerful tool to address problems by learning from data,largely driven by the availability of massive datasets,enhanced computational power,fast data storage,and novel training algorithms for the deep neural network.It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology.Unlike the traditional,,physics-basedH approach,deep-learning-enabled optical metrology is a kind of,/data-drivenw approach,which has already provided numerous alternative solutions to many challenging problems in this field with better performances.In this review,we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology.We first briefly introduce both traditional image-processing algorithms in optical metrology and the basic concepts of deep learning,followed by a comprehensive review of its applications in various optical metrology tasks,such as fringe denoising,phase retrieval,phase unwrapping,subset correlation,and error compensation.The open challenges faced by the current deep-learning approach in optical metrology are then discussed.Finally,the directions for future research are outlined.展开更多
Structured illumination microscopy(SIM)is one of the powerful super-resolution modalities in bioscience with the advantages of full-field imaging and high photon efficiency.However,artifact-free super-resolution image...Structured illumination microscopy(SIM)is one of the powerful super-resolution modalities in bioscience with the advantages of full-field imaging and high photon efficiency.However,artifact-free super-resolution image reconstruction requires precise knowledge about the illumination parameters.The sample-and environment-dependent on-the-fly experimental parameters need to be retrieved a posteriori from the acquired data,posing a major challenge for real-time,long-term live-cell imaging,where low photobleaching,phototoxicity,and light dose are a must.In this work,we present an efficient and robust SIM algorithm based on principal component analysis(PCA-SIM).PCA-SIM is based on the observation that the ideal phasor matrix of a SIM pattern is of rank one,leading to the low complexity,precise identification of noninteger pixel wave vector and pattern phase while rejecting components that are unrelated to the parameter estimation.We demonstrate that PCA-SIM achieves non-iteratively fast,accurate(below 0.01-pixel wave vector and 0.1%of 2relative phase under typical noise level),and robust parameter estimation at low SNRs,which allows real-time super-resolution imaging of live cells in complicated experimental scenarios where other state-of-the-art methods inevitably fail.In particular,we provide the open-source MATLAB toolbox of our PCA-SIM algorithm and associated datasets.The combination of iteration-free reconstruction,robustness to noise,and limited computational complexity makes PCA-SIM a promising method for high-speed,long-term,artifact-free super-resolution imaging of live cells.展开更多
To the Editor:Increasing attention is being paid to preventing ulcerative colitis(UC)-associated carcinogenesis.The intestinal microbiota plays an important role in maintaining the intestinal barrier and immune functi...To the Editor:Increasing attention is being paid to preventing ulcerative colitis(UC)-associated carcinogenesis.The intestinal microbiota plays an important role in maintaining the intestinal barrier and immune function.Probiotic mixture VSL#3,that was bought from Sigma-Tau pharmaceuticals(De Simone Formulation)in May 2015,is a mixture of Lactobacillus casei,L.plantarum,L.acidophilus,L.delbrueckii subsp.bulgaricus,Bifidobacterium longum,B.breve,B.infantis and Streptococcus salivarius andcontains 4.5 billion live bacterialcolonies.i Previous studies have shown that VSL#3 can help induce and maintain UC remission.The effects of probiotics on UC-associated carcinogenesis are difficult to observe clinically;therefore,mouse models are often used to study this disease.Previous studies have shown that azoxymethane(AOM)combined with dextran sulfate sodium(DSS)can quickly induce a UC-associated carcinogenesis model.展开更多
A consensus statement on the diagnosis and treatment of pancreatic exocrine insufficiency(PEI)after pancreatic surgery was developed based on the latest references,combined with China’s actual situation.More than 20 ...A consensus statement on the diagnosis and treatment of pancreatic exocrine insufficiency(PEI)after pancreatic surgery was developed based on the latest references,combined with China’s actual situation.More than 20 Chinese excellent experts participated in this work and contributed many thorough discussions.This consensus discusses the definition,epidemiology,diagnosis,treatment,and follow-up of PEI after pancreatic surgery.The authors hope this consensus will promote the standard procedure of diagnosis and treatment of PEI in China.展开更多
Fecal microbiota transplantation(FMT)describes a therapeutic approach in which feces from healthy donors are delivered into the guts of recipient patients through either the upper or lower gastrointestinal tract.FMT i...Fecal microbiota transplantation(FMT)describes a therapeutic approach in which feces from healthy donors are delivered into the guts of recipient patients through either the upper or lower gastrointestinal tract.FMT is now a standard therapeutic option for patients with recurrent Clostridium difficile infection(rCDI),but FMT has also been applied to several other gut diseases,not least inflammatory bowel disease(IBD),especially ulcerative colitis(UC).Several clinical trials have now shown that FMT is an efficacious and safe treatment not only for patients with mild-to-moderate active UC but also those in clinical remission.展开更多
Objectives:The aim of this multicenter,prospective,registry study was to summarize the epidemiology of Chinese patients with locally advanced and end-stage gastroenteropancreatic neuroendocrine tumors(GEP-NETs)as well...Objectives:The aim of this multicenter,prospective,registry study was to summarize the epidemiology of Chinese patients with locally advanced and end-stage gastroenteropancreatic neuroendocrine tumors(GEP-NETs)as well as the diagnostic methods and treatment strategies used for these patients.Methods:GEP-NET patients from 11 departments of 8 hospitals in China were prospectively enrolled for a pre-defined period(June 30,2011 to May 29,2012).The patients’demographic,pathological,and treatment data were recorded,analyzed,and released on June 29,2015.Results:Seventy-nine eligible patients were enrolled,and most of these patients were classified according to the World Health Organization 2010 classifications.The most common primary tumor site was the pancreas.The liver was the most common site of metastases,followed by the lymph nodes.The majority of the patients underwent surgical interventions.Patients also received local treatment,medication,or chemotherapy.Conclusion:The pancreas was the most common primary tumor site of locally advanced and end-stage GEP-NETs.Surgical interventions are currently the most common treatment strategy.展开更多
基金supported by National Key Research and Development Program of China(2022YFB2804603,2022YFB2804605)National Natural Science Foundation of China(U21B2033)+4 种基金Fundamental Research Funds forthe Central Universities(2023102001,2024202002)National Key Laborato-ry of Shock Wave and Detonation Physics(JCKYS2024212111)China Post-doctoral Science Fund(2023T160318)Open Research Fund of JiangsuKey Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105,JSGP202201)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX25_0695,SJCX25_0188)。
文摘Recent advancements in artificial intelligence have transformed three-dimensional(3D)optical imaging and metrology,enabling high-resolution and high-precision 3D surface geometry measurements from one single fringe pattern projection.However,the imaging speed of conventional fringe projection profilometry(FPP)remains limited by the native sensor refresh rates due to the inherent"one-to-one"synchronization mechanism between pattern projection and image acquisition in standard structured light techniques.Here,we present dual-frequency angular-multiplexed fringe projection profilometry(DFAMFPP),a deep learning-enabled 3D imaging technique that achieves high-speed,high-precision,and large-depth-range absolute 3D surface measurements at speeds 16 times faster than the sensor's native frame rate.By encoding multi-timeframe 3D information into a single multiplexed image using multiple pairs of dual-frequency fringes,high-accuracy absolute phase maps are reconstructed using specially trained two-stage number-theoretical-based deep neural networks.We validate the effectiveness of DFAMFPP through dynamic scene measurements,achieving 10,000 Hz 3D imaging of a running turbofan engine prototype with only a 625 Hz camera.By overcoming the sensor hardware bottleneck,DFAMFPP significantly advances high-speed and ultra-high-speed 3D imaging,opening new avenues for exploring dynamic processes across diverse scientific disciplines.
基金supported by National Natural Science Foundation of China(62227818,12204239,62275121)Youth Foundation of Jiangsu Province(BK20220946)+1 种基金Fundamental Research Funds for the Central Universities(30923011024)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202201).
文摘Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL models,however,do not necessarily obey the fundamental governing laws of PAM physical systems,nor do they generalize well to scenarios on which they have not been trained.In this work,a physics-embedded degeneration learning(PEDL)approach is proposed to enhance the image quality of PAM with a self-attention enhanced U-Net network,which obtains greater physical consistency,improves data efficiency,and higher adaptability.The proposed method is demonstrated on both synthetic and real datasets,including animal experiments in vivo(blood vessels of mouse's ear and brain).And the results show that compared with previous DL methods,the PEDL algorithm exhibits good performance in recovering PAM images qualitatively and quantitatively.It overcomes the challenges related to training data,accuracy,and robustness which a typical data-driven approach encounters,whose exemplary application envisions to provide a new perspective for existing DL tools of enhanced PAM.
基金funded by National High-Level Hospital Clinical Research Funding (2022-PUMCH-A-203)CAMS Innovation Fund for Medical Sciences (2021-I2M-1-001)+4 种基金Health Research & Special Projects Grant of China (201002020 and 201502005)The Integrated Entrusted Project of Research Funding at Peking Union Medical College Hospital (ZC201903347)the National Natural Science Foundation of China (81970495)Capital Health Development Scientific Research Fund (2022-2-4014)Peking Union Medical College Hospital Research Funding for Postdoc (kyfyjj202315)
文摘Colitis-associated colorectal cancer(CAC),a serious complication of ulcerative colitis(UC),is associated with a poor prognosis.The vitamin D receptor(VDR)is recognized for its protective role in UC and CAC through the maintenance of intestinal barrier integrity and the regulation of inflammation.This study demonstrates a significant reduction in m^(6)A-related genes,particularly methyltransferase like 14(METTL14),in UC and CAC patients and identifies an association between METTL14 and VDR.In the azoxymethane(AOM)/dextran sodium sulfate(DSS)-induced mousemodel,vitamin D treatment increases METTL14 expression and reduces tumorburden,while Vdr-knockout mice exhibit lower METTL14 levels and increased tumorigenesis.In vitro,the VDR agonist calcipotriol upregulates METTL14 in NCM460 cells,with this effect attenuated by VDR knockdown.VDRknockdown inDLD-1colon cancer cellsdecreases METTL14 expressionand promotes proliferation,which is reversed by METTL14 overexpression.Mechanistic studies reveal that VDR regulates METTL14 expression via promoter binding,modulating key target genes such as SOX4,DROSH,and PHLPP2.This study highlights the role of the VDR-METTL14 axis as a protective mechanism in CAC and suggests its potential as a therapeutic target for preventing and treating CAC.
基金This work was supported by National Natural Science Foundation of China(62075096,62005121,U21B2033)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+4 种基金“333 Engineering”Research Project of Jiangsu Province(BRA2016407)Jiangsu Provincial“One belt and one road”innovation cooperation project(BZ2020007)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX21_0273)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105).
文摘Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a single fringe image.In this paper,we demonstrate that the deep neural networks can be trained to directly recover the absolute phase from a unique fringe image that involves spatially multiplexed fringe patterns of different frequencies.The extracted phase is free from spectrum-aliasing problem which is hard to avoid for traditional spatial-multiplexing methods.Experiments on both static and dynamic scenes show that the proposed approach is robust to object motion and can obtain high-quality 3D reconstructions of isolated objects within a single fringe image.
基金supported by National Key Research and Development Program of China(2022YFB2804603,2022YFA1205002,2024YFE0101300)National Natural Science Foundation of China(U21B2033,62075096,62105151,62175109,62227818,62361136588)+4 种基金Leading Technology of Jiangsu Basic Research Plan(BK20192003)"333 Engineering"Research Project of Jiangsu Province(BRA2016407)Jiangsu Provincial"One belt and one road"innovation cooperation project(BZ2020007)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(USGP202105,JSGP202201).
文摘To reveal the fundamental aspects hidden behind a variety of transient events in mechanics,physics,and biology,the highly desired ability to acquire three-dimensional(3D)images with ultrafast temporal resolution has been long sought.As one of the most commonly employed 3D sensing techniques,fringe projection profilometry(FPP)reconstructs the depth of a scene from stereo images taken with sequentially structured illuminations.However,the imaging speed of current FPP methods is generally capped at several kHz,which is limited by the projector-camera hardware and the number of fringe patterns required for phase retrieval and unwrapping.Here we report a novel learning-based ultrafast 3D imaging technique,termed single-shot super-resolved FPP(SSSR-FPP),which enables ultrafast 3D imaging at 100,000 Hz.SSSR-FPP uses only one pair of low signal-to-noise ratio(SNR),low-resolution,and pixelated fringe patterns as input,while the high-resolution unwrapped phase and fringe orders can be deciphered with a specific trained deep neural network.Our approach exploits the significant speed gain achieved by reducing the imaging window of conventional high-speed cameras,while"regenerating"the lost spatial resolution through deep learning.To demonstrate the high spatio-temporal resolution of SSSR-FPP,we present 3D videography of several transient scenes,including rotating turbofan blades,exploding building blocks,and the reciprocating motion of a steam engine,etc.,which were previously challenging or even impossible to capture with conventional methods.Experimental results establish SSSR-FPP as a significant step forward in the field of 3D optical sensing,offering new insights into a broad spectrum of dynamic processes across various scientific disciplines.
基金supported by the National Natural Science Foundation of China(Nos.62405231,62205259,62075175,62105254,and 62375212)the National Key Laboratory of Infrared Detection Technologies(No.IRDT-23-06)+1 种基金the Fundamental Research Funds for the Central Universities(Nos.XJSJ24028 and XJS222202)the Open Research Fund of Beijing Key Laboratory of Advanced Optical Remote Sensing Technology(No.AORS202405).
文摘The current state of traditional optoelectronic imaging technology is constrained by the inherent limitations of its hardware.These limitations pose significant challenges in acquiring higher-dimensional information and reconstructing accurate images,particularly in applications such as scattering imaging,superresolution,and complex scene reconstruction.However,the rapid development and widespread adoption of deep learning are reshaping the field of optical imaging through computational imaging technology.Datadriven computational imaging has ushered in a paradigm shift by leveraging the nonlinear expression and feature learning capabilities of neural networks.This approach transcends the limitations of conventional physical models,enabling the adaptive extraction of critical features directly from data.As a result,computational imaging overcomes the traditional“what you see is what you get”paradigm,paving the way for more compact optical system designs,broader information acquisition,and improved image reconstruction accuracy.These advancements have significantly enhanced the interpretation of highdimensional light-field information and the processing of complex images.This review presents a comprehensive analysis of the integration of deep learning and computational imaging,emphasizing its transformative potential in three core areas:computational optical system design,high-dimensional information interpretation,and image enhancement and processing.Additionally,this review addresses the challenges and future directions of this cutting-edge technology,providing novel insights into interdisciplinary imaging research.
基金supported by the National High-Level Hospital Clinical Research Funding(Nos.2022-PUMCH-C-018,2022-PUMCH-B-022)CAMS Innovation Fund for Medical Sciences(No.2022-I2M-C&T-B-011)+2 种基金Capital Health Research and Development of Special Foundation(No.2022-2-4014)National Natural Science Foundation of China(No.81970495)National Key Clinical Specialty Construction Project(No.ZK108000)
文摘Inammatory bowel disease(IBD),which includes Crohn’s disease(CD)and ulcerative colitis(UC),is a chronic,progressive illness thatuctuates in severity and involves recurring periods of relapse and remission.It has emerged as a global public health challenge.Traditionally,IBD has been predominantly found in Western countries,with North America and Europe exhibiting the highest rates of prevalence and incidence.Specically,the prevalence and incidence rates for UC were 505/100,000 and 249/100,000,respectively,while for CD they were 322/100,000 and 319/100,000,respectively.[1]However,there has been a recent stabilization of IBD incidence in countries with high prevalence rates.
基金funded by the National Key R&D Program(No.2023YFC2507300)Guangdong R&D Program in Key Fields(No.2023B1111040003).
文摘The role of Chinese expert consensus in standardization and improvement of the clinical diagnosis and treatment of inflammatory bowel disease(IBD)is self-evident.As clinical and basic research in China becomes standardized under a better understanding of IBD,more data on Chinese patients have become available to develop a consensus and guideline.This guideline,collaboratively developed by the IBD Group,Chinese Society of Gastroenterology,incorporates the latest international consensus statements,[1-7]domestic research findings,and practical considerations,as an update based on the 2018 Chinese consensus on IBD management.[8]The IBD guideline consists of two parts:ulcerative colitis(UC)and Crohn’s disease,and this manuscript presented the UC part.The evidence used in this guideline was collected and analyzed by the standard of guideline,and the contents were organized as problem statements,for clarity.The formulation of this guideline aimed to reflect the latest progress in IBD,providing comprehensive and valuable guidance for the clinical management of IBD.
基金Capital Health Research and Development of Special Foundation(No.2022-2-4014)National Key Clinical Specialty Construction Project(No.ZK108000)+5 种基金National High-Level Hospital Clinical Research Funding(Nos.2022-PUMCH-B-022,2022-PUMCH-C-018,2022-PUMCH-A-074,and 2022-PUMCH-A-179)National Natural Science Foundation of China(No.81970495)CAMS Innovation Fund for Medical Sciences(No.2022-I2M-C&T-B-011)National Key R&D Program of China(No.2023YFC2507300,2023YFC2507302)State Key Laboratory Special Fund(No.2060204)Undergraduate Training Program on Innovation and Entrepreneurship(No.2024dcxm091)。
文摘Background:Inflammatory bowel disease(IBD)imposes a significant economic and social burden in China.We aim to assess the epidemiological trends of IBD in China,and to predict the burden in the near future.Methods:The incidence,mortality,prevalence,and disability-adjusted life year(DALYs)of IBD from 1990 to 2021 were obtained from Global Burden of Disease Study 2021.Estimated annual percentage change(EAPC),average annual percent change,total percent change,and age-period-cohort model were used to access trends.Bayesian age–period–cohort model was utilized to predict the risk of incidence and mortality.Results:In 2021,IBD affected 168,077 people in China,with 24,941 new cases and 5640 deaths.The age-standardized rate(ASR)of incidence and death was 1.4 and 0.3,respectively.The incidence and prevalence in China were lower than the global and high socio-demographic index(SDI)regions,but the ASR of incidence and prevalence(EAPC:2.93 and 2.54,respectively)had rapidly increased from 1990 to 2021.The ASR of death and DALYs had significantly decreased(EAPC:−3.05 and−2.93,respectively).Middle-aged and elderly populations faced a severe burden of incidence and prevalence,while the elderly population faced a severe mortality burden.It is projected that by 2035,the ASR of incidence will continue to rise,whereas the death rate will continue to decline.Conclusions:The burden of IBD in China is serious and increasingly severe.Establishing a comprehensive disease management system in China will help better control the medical burden of IBD.
基金supported by the Industry Special Fund of the Ministry of Health(201002020).
文摘To investigate the prevalence of gastroesophageal reflux disease(GERD),reflux esophagitis(RE),digestive ulcer gastric ulcer(GU),duodenal ulcer(DU),and Helicobacter pylori infection in Chinese adults aged 18-64 years and their associated factors,a community-based cross-sectional study using a stratified multi-stage sampling method was conducted.A standardized questionnaire survey,the^(13)C-urea breath test,and gastroscopy were performed.Weighted methods were used to estimate the prevalence of diseases or infection mentioned above and their risk factors.Finally,27,637 participants aged 18-64 years were enrolled from 2017 to 2018.The prevalence(95%confidence interval)of GERD,RE,GU,DU,and H.pylori infection was estimated to be 10.5%(7.8%-14.2%),5.4%(3.9%-7.3%),2.5%(1.7%-3.7%),4.5%(3.6%-5.4%),and 41.5%(36.7%-46.4%),respectively.The fraction of H.pylori infection reached 58.6%and 61.1%among the GU and DU patients,respectively.Weighted multivariable logistic regression models showed that GERD,RE,and GU shared the common risk factors of age and obesity.Dose-response relationships were observed between smoking and all four diseases,as well as alcohol consumption and GERD and H.pylori infection.Northwest China had the highest prevalence of GERD(23.9%),RE(8.7%),GU(7.8%),DU(7.3%),and H.pylori infection(63.6%);however,the southwest region had the highest prevalence of GU but the lowest of DU,RE,and H.pylori infection.Non-steroidal anti-inflammatory drugs were positively associ-ated with GERD risk.On the contrary,a reduced risk of GU was observed among H.pylori-infected patients taking this drug.In summary,the prevalence of GERD,RE,and H.pylori infection still appears high in China.H.pylori infection eradication remains the priority to reduce the burden of peptic ulcer dis-ease.The aging population,high prevalence of overweight or obesity,smoking,and drinking in China could explain the high burden of these diseases,thus suggesting the targeted preventive measures for upper gastrointestinal diseases in the future.
文摘Background:Erosive esophagitis(EE)is a gastroesophageal reflux disease characterized by mucosal breaks in the esophagus.Proton pump inhibitors are widely used as maintenance therapy for EE,but many patients still relapse.In this trial,we evaluated the noninferiority of vonoprazan vs.lansoprazole as maintenance therapy in patients with healed EE.Methods:We performed a double-blind,double-dummy,multicenter,phase 3 clinical trial among non-Japanese Asian adults with endoscopically confirmed healed EE from April 2015 to February 2019.Patients from China,South Korea,and Malaysia were randomized to vonoprazan 10 mg or 20 mg once daily or lansoprazole 15 mg once daily for 24 weeks.The primary endpoint was endoscopically confirmed EE recurrence rate over 24 weeks with a noninferiority margin of 10%using a two-sided 95%confidence interval(CI).Treatment-emergent adverse events(TEAEs)were recorded.Results:Among 703 patients,EE recurrence was observed in 24/181(13.3%)and 21/171(12.3%)patients receiving vonoprazan 10 mg or 20 mg,respectively,and 47/184(25.5%)patients receiving lansoprazole(differences:-12.3%[95%CI,-20.3%to-4.3%]and-13.3%[95%CI,-21.3%to-5.3%],respectively),meeting the primary endpoint of noninferiority to lansoprazole in preventing EE recurrence at 24 weeks.Evidence of superiority(upper bound of 95%CI<0%)was also observed.At 12 weeks,endoscopically confirmed EE recurrence was observed in 5/18,2/20,and 7/20 of patients receiving vonoprazan 10 mg,vonoprazan 20 mg,and lansoprazole,respectively.TEAEs were experienced by 66.8%(157/235),69.0%(156/226),and 65.3%(158/242)of patients receiving vonoprazan 10 mg,vonoprazan 20 mg,and lansoprazole,respectively.The most common TEAE was upper respiratory tract infection in 12.8%(30/235)and 12.8%(29/226)patients in vonoprazan 10 mg and 20 mg groups,respectively and 8.7%(21/242)patients in lansoprazole group.Conclusion:Vonoprazan maintenance therapy was well-tolerated and noninferior to lansoprazole for preventing EE recurrence in Asian patients with healed EE.Trial Registration:https://clinicaltrials.gov;NCT02388737.
基金supported by National Key Research and Development Program of China(2022YFB2804603)National Natural Science Foundation of China(62075096,62005121,U21B2033)+3 种基金Leading Technology of Jiangsu Basic Research Plan(BK20192003)“333 Engineering”Research Project of Jiangsu Province(BRA2016407)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Fundamental Research Funds for the Central Universities(2023102001,2024202002).
文摘Recent advances in imaging sensors and digital light projection technology have facilitated rapid progress in 3D optical sensing,enabling 3D surfaces of complexshaped objects to be captured with high resolution and accuracy.Nevertheless,due to the inherent synchronous pattern projection and image acquisition mechanism,the temporal resolution of conventional structured light or fringe projection profilometry(FPP)based 3D imaging methods is still limited to the native detector frame rates.In this work,we demonstrate a new 3D imaging method,termed deep-learning-enabled multiplexed FPP(DLMFPP),that allows to achieve high-resolution and high-speed 3D imaging at near-one-order of magnitude-higher 3D frame rate with conventional low-speed cameras.By encoding temporal information in one multiplexed fringe pattern,DLMFPP harnesses deep neural networks embedded with Fourier transform,phase-shifting and ensemble learning to decompose the pattern and analyze separate fringes,furnishing a high signal-to-noise ratio and a ready-to-implement solution over conventional computational imaging techniques.We demonstrate this method by measuring different types of transient scenes,including rotating fan blades and bullet fired from a toy gun,at kHz using cameras of around 100 Hz.Experiential results establish that DLMFPP allows slow-scan cameras with their known advantages in terms of cost and spatial resolution to be used for high-speed 3D imaging tasks.
基金National Natural Science Foundation of China(U21B2033,62075096,62005121)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+3 种基金"333 Engineering"Research Projea of Jiangsu Province(BRA2016407)Jiangsu Provincial"One belt and one road"innovation cooperation project(BZ2020007)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Open Research Fund of Jiangsu Key Laboratory of Spearal Imaging&Intelligent Sense(JSGP202105).
文摘With the advances in scientific foundations and technological implementations,optical metrology has become versatile problem-solving backbones in manufacturing,fundamental research,and engineering applications,such as quality control,nondestructive testing,experimental mechanics,and biomedicine.In recent years,deep learning,a subfield of machine learning,is emerging as a powerful tool to address problems by learning from data,largely driven by the availability of massive datasets,enhanced computational power,fast data storage,and novel training algorithms for the deep neural network.It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology.Unlike the traditional,,physics-basedH approach,deep-learning-enabled optical metrology is a kind of,/data-drivenw approach,which has already provided numerous alternative solutions to many challenging problems in this field with better performances.In this review,we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology.We first briefly introduce both traditional image-processing algorithms in optical metrology and the basic concepts of deep learning,followed by a comprehensive review of its applications in various optical metrology tasks,such as fringe denoising,phase retrieval,phase unwrapping,subset correlation,and error compensation.The open challenges faced by the current deep-learning approach in optical metrology are then discussed.Finally,the directions for future research are outlined.
基金supported by the National Natural Science Foundation of China(61905115,62105151,62175109,U21B2033)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+2 种基金Youth Foundation of Jiangsu Province(BK20190445,BK20210338)Fundamental Research Funds for the Central Universities(30920032101)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105).
文摘Structured illumination microscopy(SIM)is one of the powerful super-resolution modalities in bioscience with the advantages of full-field imaging and high photon efficiency.However,artifact-free super-resolution image reconstruction requires precise knowledge about the illumination parameters.The sample-and environment-dependent on-the-fly experimental parameters need to be retrieved a posteriori from the acquired data,posing a major challenge for real-time,long-term live-cell imaging,where low photobleaching,phototoxicity,and light dose are a must.In this work,we present an efficient and robust SIM algorithm based on principal component analysis(PCA-SIM).PCA-SIM is based on the observation that the ideal phasor matrix of a SIM pattern is of rank one,leading to the low complexity,precise identification of noninteger pixel wave vector and pattern phase while rejecting components that are unrelated to the parameter estimation.We demonstrate that PCA-SIM achieves non-iteratively fast,accurate(below 0.01-pixel wave vector and 0.1%of 2relative phase under typical noise level),and robust parameter estimation at low SNRs,which allows real-time super-resolution imaging of live cells in complicated experimental scenarios where other state-of-the-art methods inevitably fail.In particular,we provide the open-source MATLAB toolbox of our PCA-SIM algorithm and associated datasets.The combination of iteration-free reconstruction,robustness to noise,and limited computational complexity makes PCA-SIM a promising method for high-speed,long-term,artifact-free super-resolution imaging of live cells.
基金The study was funded by grants from National Natural Science Foundation of China(Nos.81370500 and 81770559)。
文摘To the Editor:Increasing attention is being paid to preventing ulcerative colitis(UC)-associated carcinogenesis.The intestinal microbiota plays an important role in maintaining the intestinal barrier and immune function.Probiotic mixture VSL#3,that was bought from Sigma-Tau pharmaceuticals(De Simone Formulation)in May 2015,is a mixture of Lactobacillus casei,L.plantarum,L.acidophilus,L.delbrueckii subsp.bulgaricus,Bifidobacterium longum,B.breve,B.infantis and Streptococcus salivarius andcontains 4.5 billion live bacterialcolonies.i Previous studies have shown that VSL#3 can help induce and maintain UC remission.The effects of probiotics on UC-associated carcinogenesis are difficult to observe clinically;therefore,mouse models are often used to study this disease.Previous studies have shown that azoxymethane(AOM)combined with dextran sulfate sodium(DSS)can quickly induce a UC-associated carcinogenesis model.
文摘A consensus statement on the diagnosis and treatment of pancreatic exocrine insufficiency(PEI)after pancreatic surgery was developed based on the latest references,combined with China’s actual situation.More than 20 Chinese excellent experts participated in this work and contributed many thorough discussions.This consensus discusses the definition,epidemiology,diagnosis,treatment,and follow-up of PEI after pancreatic surgery.The authors hope this consensus will promote the standard procedure of diagnosis and treatment of PEI in China.
基金Beijing Municipal Natural Science Foundation(No.7212078)National key clinical specialty construction project(No.ZK108000)National High Level Hospital Clinical Research Funding(No.2022-PUMCH-B-022)
文摘Fecal microbiota transplantation(FMT)describes a therapeutic approach in which feces from healthy donors are delivered into the guts of recipient patients through either the upper or lower gastrointestinal tract.FMT is now a standard therapeutic option for patients with recurrent Clostridium difficile infection(rCDI),but FMT has also been applied to several other gut diseases,not least inflammatory bowel disease(IBD),especially ulcerative colitis(UC).Several clinical trials have now shown that FMT is an efficacious and safe treatment not only for patients with mild-to-moderate active UC but also those in clinical remission.
文摘Objectives:The aim of this multicenter,prospective,registry study was to summarize the epidemiology of Chinese patients with locally advanced and end-stage gastroenteropancreatic neuroendocrine tumors(GEP-NETs)as well as the diagnostic methods and treatment strategies used for these patients.Methods:GEP-NET patients from 11 departments of 8 hospitals in China were prospectively enrolled for a pre-defined period(June 30,2011 to May 29,2012).The patients’demographic,pathological,and treatment data were recorded,analyzed,and released on June 29,2015.Results:Seventy-nine eligible patients were enrolled,and most of these patients were classified according to the World Health Organization 2010 classifications.The most common primary tumor site was the pancreas.The liver was the most common site of metastases,followed by the lymph nodes.The majority of the patients underwent surgical interventions.Patients also received local treatment,medication,or chemotherapy.Conclusion:The pancreas was the most common primary tumor site of locally advanced and end-stage GEP-NETs.Surgical interventions are currently the most common treatment strategy.
