BACKGROUND This case report demonstrates the simultaneous development of a gastrointestinal stromal tumour(GIST)with arteriovenous malformations(AVMs)within the jejunal mesentery.A 74-year-old male presented to the de...BACKGROUND This case report demonstrates the simultaneous development of a gastrointestinal stromal tumour(GIST)with arteriovenous malformations(AVMs)within the jejunal mesentery.A 74-year-old male presented to the department of surgery at our institution with a one-month history of abdominal pain.Contrast-enhanced computed tomography revealed an AVM.During exploratory laparotomy,hyperspectral imaging(HSI)and indocyanine green(ICG)fluorescence were used to evaluate the extent of the tumour and determine the resection margins.Intraoperative imaging confirmed AVM,while histopathological evaluation showed an epithelioid,partially spindle cell GIST.CASE SUMMARY This is the first case reporting the use of HSI and ICG to image GIST intermingled with an AVM.The resection margins were planned using intraoperative analysis of additional optical data.Image-guided surgery enhances the clinician’s knowledge of tissue composition and facilitates tissue differentiation.CONCLUSION Since image-guided surgery is safe,this procedure should increase in popularity among the next generation of surgeons as it is associated with better postoperative outcomes.展开更多
Fingerprints are unique and life-long to everyone, so they occupy very important statuses in forensic science. However, due to the limit of current imaging technologies and instruments, recognition and matching of fin...Fingerprints are unique and life-long to everyone, so they occupy very important statuses in forensic science. However, due to the limit of current imaging technologies and instruments, recognition and matching of fingerprints are mostly based on their level 2 structures（bifurcation, crossover, and etc.）.Moreover, in real-world cases, fingerprints collected in the field are often incomplete or damaged, which adds further difficulty in fingerprint analysis. Quantum dots（QDs） are superior fluorescent imaging agents for latent fingerprints, which can provide both level 2 and level 3（sweat pores） details. Here, we used red-emitting N-acetylcysteine-capped Cd Te QDs as imaging agent for staining of eccrine LFPs. The numbers of level 2 and level 3 features that can be mapped are significantly larger than those obtained by cyanoacrylate fuming, a standard technique being adopted at forensic scene. Therefore, the level 2 and level 3 characteristics from QD-staining were simultaneously extracted for improved fingerprint analysis.A preliminary fingerprint matching based modified Pore Matching algorithm was thus developed based on the integration of both level 2 and level 3 characteristics. Satisfactory results of fingerprint matching were obtained, demonstrating the advantage of the QD-staining for advanced fingerprint analysis.展开更多
High-repetition-rate(HRR) pulsed fiber lasers have attracted much attention in various fields. To effectively achieve HRR pulses in fiber lasers, dissipative four-wave-mixing mode-locking is a promising method. In thi...High-repetition-rate(HRR) pulsed fiber lasers have attracted much attention in various fields. To effectively achieve HRR pulses in fiber lasers, dissipative four-wave-mixing mode-locking is a promising method. In this work, we demonstrated an HRR pulsed fiber laser based on a virtually imaged phased array(VIPA), serving as a comb filter. Due to the high spectral resolution and low polarization sensitivity features of VIPA, the 30 GHz pulse with high quality and high stability could be obtained. In the experiments, both the single-waveband and dual-waveband HRR pulses were achieved. Such an HRR pulsed fiber laser could have potential applications in related fields, such as optical communications.展开更多
Organoids possess immense potential for unraveling the intricate functions of human tissues and facilitating preclinical disease treatment.Their applications span from high-throughput drug screening to the modeling of...Organoids possess immense potential for unraveling the intricate functions of human tissues and facilitating preclinical disease treatment.Their applications span from high-throughput drug screening to the modeling of complex diseases,with some even achieving clinical translation.Changes in the overall size,shape,boundary,and other morphological features of organoids provide a noninvasive method for assessing organoid drug sensitivity.However,the precise segmentation of organoids in bright-field microscopy images is made difficult by the complexity of the organoid morphology and interference,including overlapping organoids,bubbles,dust particles,and cell fragments.This paper introduces the precision organoid segmentation technique(POST),which is a deep-learning algorithm for segmenting challenging organoids under simple bright-field imaging conditions.Unlike existing methods,POST accurately segments each organoid and eliminates various artifacts encountered during organoid culturing and imaging.Furthermore,it is sensitive to and aligns with measurements of organoid activity in drug sensitivity experiments.POST is expected to be a valuable tool for drug screening using organoids owing to its capability of automatically and rapidly eliminating interfering substances and thereby streamlining the organoid analysis and drug screening process.展开更多
Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological me...Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological mechanisms,preventing and treating cerebral small vessel vasculopathy is challenging.Recent studies have shown that the glymphatic system plays a crucial role in interstitial solute clearance and the maintenance of brain homeostasis.Increasing evidence also suggests that dysfunction in glymphatic clearance is a key factor in the progression of cerebral small vessel disease.This review begins with a comprehensive introduction to the structure,function,and driving factors of the glymphatic system,highlighting its essential role in brain waste clearance.Afterwards,cerebral small vessel disease was reviewed from the perspective of the glymphatic system,after which the mechanisms underlying their correlation were summarized.Glymphatic dysfunction may lead to the accumulation of metabolic waste in the brain,thereby exacerbating the pathological processes associated with cerebral small vessel disease.The review also discussed the direct evidence of glymphatic dysfunction in patients and animal models exhibiting two subtypes of cerebral small vessel disease:arteriolosclerosis-related cerebral small vessel disease and amyloid-related cerebral small vessel disease.Diffusion tensor image analysis along the perivascular space is an important non-invasive tool for assessing the clearance function of the glymphatic system.However,the effectiveness of its parameters needs to be enhanced.Among various nervous system diseases,including cerebral small vessel disease,glymphatic failure may be a common final pathway toward dementia.Overall,this review summarizes prevention and treatment strategies that target glymphatic drainage and will offer valuable insight for developing novel treatments for cerebral small vessel disease.展开更多
Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accel...Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.展开更多
Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indice...Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.展开更多
Metasurfaces are artificial structures that can finely control the characteristics of electromagnetic waves at subwavelength scales,and they are widely used to manipulate the propagation,phase,amplitude,and polariza⁃t...Metasurfaces are artificial structures that can finely control the characteristics of electromagnetic waves at subwavelength scales,and they are widely used to manipulate the propagation,phase,amplitude,and polariza⁃tion of light.In this work,a bound state in the continuum(BIC)structure based on a metallic metasurface is pro⁃posed.By adjusting the metallic structure using CST and COMSOL software,a significant quasi-BIC peak can be achieved at a frequency of 0.8217 terahertz(THz).Through multi-level expansion analysis,it is found that the electric dipole(ED)is the main factor contributing to the resonant characteristics of the structure.By leveraging the characteristics of BIC,an imaging system was created and operated.According to the simulation results,the imaging system demonstrated excellent sensitivity and resolution,revealing the great potential of terahertz imag⁃ing.This research not only provides new ideas for the creation of BIC structures but also offers an effective refer⁃ence for the development of high-performance terahertz imaging technology.展开更多
Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its develop...Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its development still faces challenges such as weak signals,slow acquisition speed,and insufficient penetration depth.In recent years,the rapid development of aggregate science has provided new insights for addressing these limitations.Aggregation-induced emission(AIE)materials exhibit enhanced signals in the aggregated state,which may compensate for the inherent weak Raman signals.This article reviews the cutting-edge progress of Raman imaging technology and its current status in cross-disciplinary research with aggregate science,emphasizing the strategy of constructing AIE-Raman dual-responsive probes through molecular engineering to achieve functional complementarity between fluorescence localization and Raman quantification,thereby significantly improving detection sensitivity and specificity.These probes have demonstrated single-cell resolution and high spatiotemporal accuracy in applications such as tumor surgical navigation,diagnosis and treatment of drug-resistant bacteria,and dynamic monitoring of organelles.We also analyze the bottlenecks in this field,such as biological safety and the complexity of molecular design,and outline the future development directions,including intelligent responsive probes,artificial intelligence-assisted analysis,and multimodal fusion platforms.The integration of Raman imaging and AIE sheds new light in the field of medical imaging.展开更多
Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and...Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.展开更多
Two novel aggregation-induced emission(AIE)-active probes,TPA-H and TPA-2 F,were designed and synthesized based on a triphenylamine(TPA)core.Systematic characterization demonstrated that both probes exhibit excellent ...Two novel aggregation-induced emission(AIE)-active probes,TPA-H and TPA-2 F,were designed and synthesized based on a triphenylamine(TPA)core.Systematic characterization demonstrated that both probes exhibit excellent biocompatibility(cell viability>90%at concentrations up to 50μmol/L)and outstanding LD-targeting speci⁃ficity with minimal colocalization with other organelles such as mitochondria and lysosomes.During early differentia⁃tion of 3 T 3-L 1 adipocytes,both TPA-2 F and TPA-H clearly visualized small and nascent LDs that were difficult to be detected with BODIPY,indicating superior imaging sensitivity compared to the existing fluorescent probes for LDs.Moreover,TPA-2 F demonstrated exceptional photostability,retaining over 90%of its initial fluorescence intensity after 100 continuous laser scanning cycles,significantly outperforming TPA-H.This work not only provides two high-performance LD imaging tools but also highlights the potential of AIE luminogens(AIEgens)in organelle-specific bioimaging,offering promising avenues for early diagnosis and mechanistic research of lipid-related metabolic diseases.展开更多
Near-infrared image sensors are widely used in fields such as material identification,machine vision,and autonomous driving.Lead sulfide colloidal quantum dot-based infrared photodiodes can be integrated with sil⁃icon...Near-infrared image sensors are widely used in fields such as material identification,machine vision,and autonomous driving.Lead sulfide colloidal quantum dot-based infrared photodiodes can be integrated with sil⁃icon-based readout circuits in a single step.Based on this,we propose a photodiode based on an n-i-p structure,which removes the buffer layer and further simplifies the manufacturing process of quantum dot image sensors,thus reducing manufacturing costs.Additionally,for the noise complexity in quantum dot image sensors when capturing images,traditional denoising and non-uniformity methods often do not achieve optimal denoising re⁃sults.For the noise and stripe-type non-uniformity commonly encountered in infrared quantum dot detector imag⁃es,a network architecture has been developed that incorporates multiple key modules.This network combines channel attention and spatial attention mechanisms,dynamically adjusting the importance of feature maps to en⁃hance the ability to distinguish between noise and details.Meanwhile,the residual dense feature fusion module further improves the network's ability to process complex image structures through hierarchical feature extraction and fusion.Furthermore,the pyramid pooling module effectively captures information at different scales,improv⁃ing the network's multi-scale feature representation ability.Through the collaborative effect of these modules,the network can better handle various mixed noise and image non-uniformity issues.Experimental results show that it outperforms the traditional U-Net network in denoising and image correction tasks.展开更多
The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adver...The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adversarial network(GAN)algorithm was proposed.Taking GAN as the basic framework,it combined a depthwise separable convolution module,attention mechanism,and reconstructed convolution module to realize the enhancement of underwater degraded images.Multi-scale features were captured by the depthwise separable convolution module,and the attention mechanism was utilized to enhance attention to important features.The reconstructed convolution module further extracts and fuses local and global features.Experimental results showed that the algorithm performs well in improving the color bias and blurring of underwater images,with PSNR reaching 27.835,SSIM reaching 0.883,UIQM reaching 3.205,and UCIQE reaching 0.713.The enhanced image outperforms the comparison algorithm in both subjective and objective metrics.展开更多
Evaluating Adherence to Safety Standards for Physical Space Design, Equipment, and Patient and Staff Protection in Magnetic Resonance Imaging Centers:A Descriptive Cross-sectional Study Amirreza Sadeghinasab1, Jafar F...Evaluating Adherence to Safety Standards for Physical Space Design, Equipment, and Patient and Staff Protection in Magnetic Resonance Imaging Centers:A Descriptive Cross-sectional Study Amirreza Sadeghinasab1, Jafar Fatahiasl2, Mahmoud Mohammadi-Sadr1, Masoud Heydari Kahkesh3, and Marziyeh Tahmasbi2(1.Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran;2.Department of Radiologic Technology, School of Allied Medical Sciences, Ahvaz, Jundishapur University of Medical Sciences, Ahvaz, Iran;3.Department of Radiology and Radiotherapy, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran)Abstract:Magnetic resonance imaging(MRI) has revolutionized disease diagnosis and treatment.However, the technology poses safety risks, such as exposure to magnetic fields, RF pulses, and cryogens, necessitating strict adherence to safety protocols to protect patients and healthcare workers.展开更多
The heterogeneity and invasiveness of cancer cells pose serious challenges in cancer diagnosis and treatment.Advancements and innovations in metal-based nanomedicines provide novel avenues for addressing these challen...The heterogeneity and invasiveness of cancer cells pose serious challenges in cancer diagnosis and treatment.Advancements and innovations in metal-based nanomedicines provide novel avenues for addressing these challenges.Metal-based nanomedicines possess unique physicochemical properties that enable their interaction with living organisms,thereby inducing complex biological responses.These nanomaterials have been extensively used to enhance the contrast and sensitivity of cancer imaging and to amplify the distinction between cancerous and healthy tissues.Moreover,these nanomaterials can effectively combat a wide spectrum of cancers through various methods,including drug delivery,radiotherapy,photothermal therapy(PTT),photodynamic therapy(PDT),sonodynamic therapy(SDT),biocatalytic therapy,ion interference therapy(IIT),and immunotherapy.Currently,there is still a need for a comprehensive summary on the metal-based nanomaterials for cancer diagnosis and treatment.Herein,we present a systematic and complete overview of action mechanisms and the applications of metal-based nanomaterials in cancer theranostics.A summary of common strategies for synthesizing and modifying metal-based nanomedicines is presented,and their biosafety is analyzed.Then,the latest developments in their applications for cancer imaging and anticancer treatment are provided.Finally,the key technical challenges and reasonable perspectives of metal-based nanomedicines for cancer theranostics in clinical applications are discussed.展开更多
Although Transformer-based image restoration methods have demonstrated impressive performance,existing Transformers still insufficiently exploit multiscale information.Previous non-Transformer-based studies have shown...Although Transformer-based image restoration methods have demonstrated impressive performance,existing Transformers still insufficiently exploit multiscale information.Previous non-Transformer-based studies have shown that incorporating multiscale features is crucial for improving restoration results.In this paper,we propose a multiscale Transformer(MST)that captures cross-scale attention among tokens,thereby effectively leveraging the multiscale patch recurrence prior of natural images.Furthermore,we introduce a channel-gate feed-forward network(CGFN)to enhance inter-channel information aggregation and reduce channel redundancy.To simultaneously utilise global,local and multiscale features,we design a multitype feature integration block(MFIB).Extensive experiments on both image super-resolution and HEVC compressed video artefact reduction demonstrate that the proposed MST achieves state-of-the-art performance.Ablation studies further verify the effectiveness of each proposed module.展开更多
Neuromorphic cameras,or dynamic vision sensors,are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level.Recently,they garnered increasing interest...Neuromorphic cameras,or dynamic vision sensors,are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level.Recently,they garnered increasing interest due to their extremely high temporal resolution,wide dynamic range,low power consumption,and high pixel bandwidth.Despite their advantages,most existing three-dimensional (3D) event imaging solutions rely on multicamera configurations,which are costly,complex,and challenging to synchronize.In this study,we introduce a new framework for four-dimensional (4D) event imaging using a single static neuromorphic camera.We take advantage of the inherent sparsity of event data to combine optically encoded stereo channels into a single event camera.By utilizing optical channel multiplexing,we maintain sensor resolution while retaining the key advantages of event cameras.展开更多
文摘BACKGROUND This case report demonstrates the simultaneous development of a gastrointestinal stromal tumour(GIST)with arteriovenous malformations(AVMs)within the jejunal mesentery.A 74-year-old male presented to the department of surgery at our institution with a one-month history of abdominal pain.Contrast-enhanced computed tomography revealed an AVM.During exploratory laparotomy,hyperspectral imaging(HSI)and indocyanine green(ICG)fluorescence were used to evaluate the extent of the tumour and determine the resection margins.Intraoperative imaging confirmed AVM,while histopathological evaluation showed an epithelioid,partially spindle cell GIST.CASE SUMMARY This is the first case reporting the use of HSI and ICG to image GIST intermingled with an AVM.The resection margins were planned using intraoperative analysis of additional optical data.Image-guided surgery enhances the clinician’s knowledge of tissue composition and facilitates tissue differentiation.CONCLUSION Since image-guided surgery is safe,this procedure should increase in popularity among the next generation of surgeons as it is associated with better postoperative outcomes.
基金supported by the National Natural Science Foundation of China (Nos. 21475090 and 21522505)
文摘Fingerprints are unique and life-long to everyone, so they occupy very important statuses in forensic science. However, due to the limit of current imaging technologies and instruments, recognition and matching of fingerprints are mostly based on their level 2 structures（bifurcation, crossover, and etc.）.Moreover, in real-world cases, fingerprints collected in the field are often incomplete or damaged, which adds further difficulty in fingerprint analysis. Quantum dots（QDs） are superior fluorescent imaging agents for latent fingerprints, which can provide both level 2 and level 3（sweat pores） details. Here, we used red-emitting N-acetylcysteine-capped Cd Te QDs as imaging agent for staining of eccrine LFPs. The numbers of level 2 and level 3 features that can be mapped are significantly larger than those obtained by cyanoacrylate fuming, a standard technique being adopted at forensic scene. Therefore, the level 2 and level 3 characteristics from QD-staining were simultaneously extracted for improved fingerprint analysis.A preliminary fingerprint matching based modified Pore Matching algorithm was thus developed based on the integration of both level 2 and level 3 characteristics. Satisfactory results of fingerprint matching were obtained, demonstrating the advantage of the QD-staining for advanced fingerprint analysis.
基金supported in part by the National Natural Science Foundation of China(NSFC)(Nos.61805084,11974006,11874018 and 61875058)Science and Technology Program of Guangzhou(No.2019050001)+4 种基金Guangdong Key R&D Program(No.2018B090904003)Guangdong Basic and Applied Basic Research Foundation(No.2019A1515010879)Foundation for Young Talents in Higher Education of Guangdong(No.2017KQNCX051)Scientific Research Foundation of Young Teacher of South China Normal University(No.17KJ09)Open Fund of the Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques(South China University of Technology,2019-2)
文摘High-repetition-rate(HRR) pulsed fiber lasers have attracted much attention in various fields. To effectively achieve HRR pulses in fiber lasers, dissipative four-wave-mixing mode-locking is a promising method. In this work, we demonstrated an HRR pulsed fiber laser based on a virtually imaged phased array(VIPA), serving as a comb filter. Due to the high spectral resolution and low polarization sensitivity features of VIPA, the 30 GHz pulse with high quality and high stability could be obtained. In the experiments, both the single-waveband and dual-waveband HRR pulses were achieved. Such an HRR pulsed fiber laser could have potential applications in related fields, such as optical communications.
基金supported by the National Key R&D Program of China(No.2022YFC2504403)the National Natural Science Foundation of China(No.62172202)+1 种基金the Experiment Project of China Manned Space Program(No.HYZHXM01019)the Fundamental Research Funds for the Central Universities from Southeast University(No.3207032101C3)。
文摘Organoids possess immense potential for unraveling the intricate functions of human tissues and facilitating preclinical disease treatment.Their applications span from high-throughput drug screening to the modeling of complex diseases,with some even achieving clinical translation.Changes in the overall size,shape,boundary,and other morphological features of organoids provide a noninvasive method for assessing organoid drug sensitivity.However,the precise segmentation of organoids in bright-field microscopy images is made difficult by the complexity of the organoid morphology and interference,including overlapping organoids,bubbles,dust particles,and cell fragments.This paper introduces the precision organoid segmentation technique(POST),which is a deep-learning algorithm for segmenting challenging organoids under simple bright-field imaging conditions.Unlike existing methods,POST accurately segments each organoid and eliminates various artifacts encountered during organoid culturing and imaging.Furthermore,it is sensitive to and aligns with measurements of organoid activity in drug sensitivity experiments.POST is expected to be a valuable tool for drug screening using organoids owing to its capability of automatically and rapidly eliminating interfering substances and thereby streamlining the organoid analysis and drug screening process.
基金supported by the National Natural Science Foundation of China,No.82274304(to YH)the Major Clinical Study Projects of Shanghai Shenkang Hospital Development Center,No.SHDC2020CR2046B(to YH)Shanghai Municipal Health Commission Talent Plan,No.2022LJ010(to YH).
文摘Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological mechanisms,preventing and treating cerebral small vessel vasculopathy is challenging.Recent studies have shown that the glymphatic system plays a crucial role in interstitial solute clearance and the maintenance of brain homeostasis.Increasing evidence also suggests that dysfunction in glymphatic clearance is a key factor in the progression of cerebral small vessel disease.This review begins with a comprehensive introduction to the structure,function,and driving factors of the glymphatic system,highlighting its essential role in brain waste clearance.Afterwards,cerebral small vessel disease was reviewed from the perspective of the glymphatic system,after which the mechanisms underlying their correlation were summarized.Glymphatic dysfunction may lead to the accumulation of metabolic waste in the brain,thereby exacerbating the pathological processes associated with cerebral small vessel disease.The review also discussed the direct evidence of glymphatic dysfunction in patients and animal models exhibiting two subtypes of cerebral small vessel disease:arteriolosclerosis-related cerebral small vessel disease and amyloid-related cerebral small vessel disease.Diffusion tensor image analysis along the perivascular space is an important non-invasive tool for assessing the clearance function of the glymphatic system.However,the effectiveness of its parameters needs to be enhanced.Among various nervous system diseases,including cerebral small vessel disease,glymphatic failure may be a common final pathway toward dementia.Overall,this review summarizes prevention and treatment strategies that target glymphatic drainage and will offer valuable insight for developing novel treatments for cerebral small vessel disease.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0530000)the Discipline Construction Foundation of“Double World-class Project”.
文摘Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.
基金supported by the National Natural Science Foundation of China,No.82071909(to GF)the Natural Science Foundation of Liaoning Province,No.2023-MS-07(to HL)。
文摘Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.
基金supported by the National Natural Science Foundation of China(61927813,61865009,12104203)Jiangxi Provincial Natu-ral Science Foundation(20212ACB201007)。
文摘Metasurfaces are artificial structures that can finely control the characteristics of electromagnetic waves at subwavelength scales,and they are widely used to manipulate the propagation,phase,amplitude,and polariza⁃tion of light.In this work,a bound state in the continuum(BIC)structure based on a metallic metasurface is pro⁃posed.By adjusting the metallic structure using CST and COMSOL software,a significant quasi-BIC peak can be achieved at a frequency of 0.8217 terahertz(THz).Through multi-level expansion analysis,it is found that the electric dipole(ED)is the main factor contributing to the resonant characteristics of the structure.By leveraging the characteristics of BIC,an imaging system was created and operated.According to the simulation results,the imaging system demonstrated excellent sensitivity and resolution,revealing the great potential of terahertz imag⁃ing.This research not only provides new ideas for the creation of BIC structures but also offers an effective refer⁃ence for the development of high-performance terahertz imaging technology.
文摘Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its development still faces challenges such as weak signals,slow acquisition speed,and insufficient penetration depth.In recent years,the rapid development of aggregate science has provided new insights for addressing these limitations.Aggregation-induced emission(AIE)materials exhibit enhanced signals in the aggregated state,which may compensate for the inherent weak Raman signals.This article reviews the cutting-edge progress of Raman imaging technology and its current status in cross-disciplinary research with aggregate science,emphasizing the strategy of constructing AIE-Raman dual-responsive probes through molecular engineering to achieve functional complementarity between fluorescence localization and Raman quantification,thereby significantly improving detection sensitivity and specificity.These probes have demonstrated single-cell resolution and high spatiotemporal accuracy in applications such as tumor surgical navigation,diagnosis and treatment of drug-resistant bacteria,and dynamic monitoring of organelles.We also analyze the bottlenecks in this field,such as biological safety and the complexity of molecular design,and outline the future development directions,including intelligent responsive probes,artificial intelligence-assisted analysis,and multimodal fusion platforms.The integration of Raman imaging and AIE sheds new light in the field of medical imaging.
文摘Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.
文摘Two novel aggregation-induced emission(AIE)-active probes,TPA-H and TPA-2 F,were designed and synthesized based on a triphenylamine(TPA)core.Systematic characterization demonstrated that both probes exhibit excellent biocompatibility(cell viability>90%at concentrations up to 50μmol/L)and outstanding LD-targeting speci⁃ficity with minimal colocalization with other organelles such as mitochondria and lysosomes.During early differentia⁃tion of 3 T 3-L 1 adipocytes,both TPA-2 F and TPA-H clearly visualized small and nascent LDs that were difficult to be detected with BODIPY,indicating superior imaging sensitivity compared to the existing fluorescent probes for LDs.Moreover,TPA-2 F demonstrated exceptional photostability,retaining over 90%of its initial fluorescence intensity after 100 continuous laser scanning cycles,significantly outperforming TPA-H.This work not only provides two high-performance LD imaging tools but also highlights the potential of AIE luminogens(AIEgens)in organelle-specific bioimaging,offering promising avenues for early diagnosis and mechanistic research of lipid-related metabolic diseases.
基金Supported by the National key research and development program in the 14th five year plan 2021YFA1200700)the National Natural Science Foundation of China(62535018,62431025,62561160113)the Natural Science Foundation of Shanghai(23ZR1473400).
文摘Near-infrared image sensors are widely used in fields such as material identification,machine vision,and autonomous driving.Lead sulfide colloidal quantum dot-based infrared photodiodes can be integrated with sil⁃icon-based readout circuits in a single step.Based on this,we propose a photodiode based on an n-i-p structure,which removes the buffer layer and further simplifies the manufacturing process of quantum dot image sensors,thus reducing manufacturing costs.Additionally,for the noise complexity in quantum dot image sensors when capturing images,traditional denoising and non-uniformity methods often do not achieve optimal denoising re⁃sults.For the noise and stripe-type non-uniformity commonly encountered in infrared quantum dot detector imag⁃es,a network architecture has been developed that incorporates multiple key modules.This network combines channel attention and spatial attention mechanisms,dynamically adjusting the importance of feature maps to en⁃hance the ability to distinguish between noise and details.Meanwhile,the residual dense feature fusion module further improves the network's ability to process complex image structures through hierarchical feature extraction and fusion.Furthermore,the pyramid pooling module effectively captures information at different scales,improv⁃ing the network's multi-scale feature representation ability.Through the collaborative effect of these modules,the network can better handle various mixed noise and image non-uniformity issues.Experimental results show that it outperforms the traditional U-Net network in denoising and image correction tasks.
文摘The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adversarial network(GAN)algorithm was proposed.Taking GAN as the basic framework,it combined a depthwise separable convolution module,attention mechanism,and reconstructed convolution module to realize the enhancement of underwater degraded images.Multi-scale features were captured by the depthwise separable convolution module,and the attention mechanism was utilized to enhance attention to important features.The reconstructed convolution module further extracts and fuses local and global features.Experimental results showed that the algorithm performs well in improving the color bias and blurring of underwater images,with PSNR reaching 27.835,SSIM reaching 0.883,UIQM reaching 3.205,and UCIQE reaching 0.713.The enhanced image outperforms the comparison algorithm in both subjective and objective metrics.
文摘Evaluating Adherence to Safety Standards for Physical Space Design, Equipment, and Patient and Staff Protection in Magnetic Resonance Imaging Centers:A Descriptive Cross-sectional Study Amirreza Sadeghinasab1, Jafar Fatahiasl2, Mahmoud Mohammadi-Sadr1, Masoud Heydari Kahkesh3, and Marziyeh Tahmasbi2(1.Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran;2.Department of Radiologic Technology, School of Allied Medical Sciences, Ahvaz, Jundishapur University of Medical Sciences, Ahvaz, Iran;3.Department of Radiology and Radiotherapy, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran)Abstract:Magnetic resonance imaging(MRI) has revolutionized disease diagnosis and treatment.However, the technology poses safety risks, such as exposure to magnetic fields, RF pulses, and cryogens, necessitating strict adherence to safety protocols to protect patients and healthcare workers.
基金supported by the National Natural Science Foundation of China(82071981)the Program of Youth Science and Technology Innovation and Entrepreneurship Outstanding Talents(Team)of Jilin Province,China(20230508063RC)+3 种基金the Excellent Youth Training Foundation of Jilin University,China(419080520665)the Innovation and Entrepreneurship Talent Funding Program of Jilin Province,Chinathe Health Special Project of the Finance Department of Jilin Province,Chinathe Graduate Innovation Fund of Jilin University,China(2025CX297)。
文摘The heterogeneity and invasiveness of cancer cells pose serious challenges in cancer diagnosis and treatment.Advancements and innovations in metal-based nanomedicines provide novel avenues for addressing these challenges.Metal-based nanomedicines possess unique physicochemical properties that enable their interaction with living organisms,thereby inducing complex biological responses.These nanomaterials have been extensively used to enhance the contrast and sensitivity of cancer imaging and to amplify the distinction between cancerous and healthy tissues.Moreover,these nanomaterials can effectively combat a wide spectrum of cancers through various methods,including drug delivery,radiotherapy,photothermal therapy(PTT),photodynamic therapy(PDT),sonodynamic therapy(SDT),biocatalytic therapy,ion interference therapy(IIT),and immunotherapy.Currently,there is still a need for a comprehensive summary on the metal-based nanomaterials for cancer diagnosis and treatment.Herein,we present a systematic and complete overview of action mechanisms and the applications of metal-based nanomaterials in cancer theranostics.A summary of common strategies for synthesizing and modifying metal-based nanomedicines is presented,and their biosafety is analyzed.Then,the latest developments in their applications for cancer imaging and anticancer treatment are provided.Finally,the key technical challenges and reasonable perspectives of metal-based nanomedicines for cancer theranostics in clinical applications are discussed.
基金supported in part by the National Natural Science Foundation of China under Grants 62101346 and 62301330the Guangdong Basic and Applied Basic Research Foundation under Grants 2021A1515011702 and 2022A1515110101+1 种基金the Shenzhen Science and Technology Programme under Grants JCYJ20240813141358076 and 20231121103807001the Guangdong Provincial Key Laboratory under Grant 2023B1212060076.
文摘Although Transformer-based image restoration methods have demonstrated impressive performance,existing Transformers still insufficiently exploit multiscale information.Previous non-Transformer-based studies have shown that incorporating multiscale features is crucial for improving restoration results.In this paper,we propose a multiscale Transformer(MST)that captures cross-scale attention among tokens,thereby effectively leveraging the multiscale patch recurrence prior of natural images.Furthermore,we introduce a channel-gate feed-forward network(CGFN)to enhance inter-channel information aggregation and reduce channel redundancy.To simultaneously utilise global,local and multiscale features,we design a multitype feature integration block(MFIB).Extensive experiments on both image super-resolution and HEVC compressed video artefact reduction demonstrate that the proposed MST achieves state-of-the-art performance.Ablation studies further verify the effectiveness of each proposed module.
基金support from the Kreitman School of Advanced Graduate Studies, Ben-Gurion University of the Negev。
文摘Neuromorphic cameras,or dynamic vision sensors,are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level.Recently,they garnered increasing interest due to their extremely high temporal resolution,wide dynamic range,low power consumption,and high pixel bandwidth.Despite their advantages,most existing three-dimensional (3D) event imaging solutions rely on multicamera configurations,which are costly,complex,and challenging to synchronize.In this study,we introduce a new framework for four-dimensional (4D) event imaging using a single static neuromorphic camera.We take advantage of the inherent sparsity of event data to combine optically encoded stereo channels into a single event camera.By utilizing optical channel multiplexing,we maintain sensor resolution while retaining the key advantages of event cameras.
