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Artificial intelligence-based analysis of tumor-infiltrating lymphocyte spatial distribution for colorectal cancer prognosis

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Chinese Medical Journal 2024年第4期137卷 421-430页

作者： Ming Cai ke zhao Lin Wu Yanqi Huang Minning zhao Qingru Hu Qicong Chen Su Yao Zhenhui Li Xinjuan Fan Zaiyi Liu Department of Radiology Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong 510080China Guangdong Provincial key Laboratory of Artificial Intelligence in Medical Image Analysis and Application GuangzhouGuangdong 510080China Guangdong Cardiovascular Institute Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong 510080China Medical Research Institute Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong 510080China Department of Pathology The Third Affiliated Hospital of Kunming Medical UniversityYunnan Cancer HospitalYunnan Cancer CenterKunmingYunnan 650118China The Second School of Clinical Medicine Southern Medical UniversityGuangzhouGuangdong 510515China Institute of Computing Science and Technology Guangzhou UniversityGuangzhouGuangdong 510006China Department of Pathology Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong 510080China Department of Pathology The Sixth Affiliated Hospital of Sun Yat-sen UniversityGuangzhouGuangdong 510655China

Background:Artificial intelligence(AI)technology represented by deep learning has made remarkable achievements in digital pathology,enhancing the accuracy and reliability of diagnosis and prognosis evaluation.The spatial distribution of CD3^(+)and CD8^(+)T cells within the tumor microenvironment has been demonstrated to have a significant impact on the prognosis of colorectal cancer(CRC).This study aimed to investigate CD3_(CT)(CD3^(+)T cells density in the core of the tumor[CT])prognostic ability in patients with CRC by using AI technology.Methods:The study involved the enrollment of 492 patients from two distinct medical centers,with 358 patients assigned to the training cohort and an additional 134 patients allocated to the validation cohort.To facilitate tissue segmentation and T-cells quantification in whole-slide images(WSIs),a fully automated workflow based on deep learning was devised.Upon the completion of tissue segmentation and subsequent cell segmentation,a comprehensive analysis was conducted.Results:The evaluation of various positive T cell densities revealed comparable discriminatory ability between CD3_(CT) and CD3-CD8(the combination of CD3^(+)and CD8^(+)T cells density within the CT and invasive margin)in predicting mortality(C-index in training cohort:0.65 vs.0.64;validation cohort:0.69 vs.0.69).The CD3_(CT) was confirmed as an independent prognostic factor,with high CD3_(CT) density associated with increased overall survival(OS)in the training cohort(hazard ratio[HR]=0.22,95%confidence interval[CI]:0.12–0.38,P<0.001)and validation cohort(HR=0.21,95%CI:0.05–0.92,P=0.037).Conclusions:We quantify the spatial distribution of CD3^(+)and CD8^(+)T cells within tissue regions in WSIs using AI technology.The CD3_(CT) confirmed as a stage-independent predictor for OS in CRC patients.Moreover,CD3_(CT) shows promise in simplifying the CD3-CD8 system and facilitating its practical application in clinical settings.

关键词： Colorectal cancer Artificial intelligence Deep learning Digital pathology Prognosis Immune cells CD3 CD8 TME

Recent advances in core-shell organic framework-based photocatalysts for energy conversion and environmental remediation

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Journal of Energy Chemistry 2024年第8期95卷 168-199页

作者： Qibing Dong Ximing Li Yanyan Duan Qingyun Tian Xinxin Liang Yiyin Zhu Lin Tian Junjun Wang Atif Sial Yongqian Cui ke zhao Chuanyi Wang School of Environmental Science and Engineering Shaanxi University of Science and Technology Guangdong Engineering Technology Research Center for Environmental Purification and Functional Materials Guangzhou Institute of Industrial Intelligence Helmholtz-Zentrum Berlin für Materialien und Energie Jiangxi key Lab of Flexible Electronics Flexible Electronics Innovation Institute Jiangxi Science and Technology Normal University

Direct conversion of solar energy into chemical energy in an environmentally friendly manner is one of the most promising strategies to deal with the environmental pollution and energy crisis. Among a variety of materials developed as photocatalysts, the core-shell metal/covalent-organic framework（MOF or COF）photocatalysts have garnered significant attention due to their highly porous structure and the adjustability in both structure and functionality. The existing reviews on core-shell organic framework photocatalytic materials have mainly focused on core-shell MOF materials. However, there is still a lack of indepth reviews specifically addressing the photocatalytic performance of core-shell COFs and MOFs@COFs. Simultaneously, there is an urgent need for a comprehensive review encompassing these three types of core-shell structures. Based on this, this review aims to provide a comprehensive understanding and useful guidelines for the exploration of suitable core-shell organic framework photocatalysts towards appropriate photocatalytic energy conversion and environmental governance. Firstly, the classification, synthesis, formation mechanisms, and reasonable regulation of core-shell organic framework were summarized. Then, the photocatalytic applications of these three kinds of core-shell structures in different areas, such as H2evolution, CO2reduction, and pollutants degradation are emphasized. Finally, the main challenges and development prospects of core-shell organic framework photocatalysts were introduced. This review aims to provide insights into the development of a novel generation of efficient and stable core-shell organic framework materials for energy conversion and environmental remediation.

关键词： Core-shell structure Energy conversion Environmental remediation Organic framework Photocatalysis

A risk assessment method considering risk attributes and work safety informational needs and its application

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Chinese Journal of Chemical Engineering 2024年第4期68卷 253-262页

作者： Cong Luo Yunsheng zhao ke Xu School of Political Science and Public Administration Shandong UniversityQingdao 266200China Faculty of Engineering China University of GeosciencesWuhan 430074China Department of Emergency Management of Hubei Province Wuhan 430064China

The technological revolution has spawned a new generation of industrial systems,but it has also put forward higher requirements for safety management accuracy,timeliness,and systematicness.Risk assessment needs to evolve to address the existing and future challenges by considering the new demands and advancements in safety management.The study aims to propose a systematic and comprehensive risk assessment method to meet the needs of process system safety management.The methodology first incorporates possibility,severity,and dynamicity(PSD)to structure the“51X”evaluation indicator system,including the inherent,management,and disturbance risk factors.Subsequently,the four-tier(risk point-unit-enterprise-region)risk assessment(RA)mathematical model has been established to consider supervision needs.And in conclusion,the application of the PSD-RA method in ammonia refrigeration workshop cases and safety risk monitoring systems is presented to illustrate the feasibility and effectiveness of the proposed PSD-RA method in safety management.The findings show that the PSD-RA method can be well integrated with the needs of safety work informatization,which is also helpful for implementing the enterprise's safety work responsibility and the government's safety supervision responsibility.

关键词： Risk assessment Safey “51X”evaluation indicator system Four-tier risk assessment model Risk attributes Process system

Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1239-1249页

作者： ke Li Shunyi zhao Biao Huang Fei Liu key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan UniversityWuxi 214122China Department of Chemical and Materials Engineering University of AlbertaEdmonton AB T6G 2G6Canada

In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensionality,and directly exploiting holistic information for state inference is not always computationally affordable.This paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear systems.The high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense dimensions.After that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state segmentation.Moreover,the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing methods.Simulation results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

关键词： filtering estimation error

Smart Contract Vulnerability Detection Method Based on Feature Graph and Multiple Attention Mechanisms

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Computers, Materials & Continua 2024年第5期79卷 3023-3045页

作者： Zhenxiang He Zhenyu zhao ke Chen Yanlin Liu School of Cyber Security Gansu University of Political Science and LawLanzhou730070China

The fast-paced development of blockchain technology is evident.Yet,the security concerns of smart contracts represent a significant challenge to the stability and dependability of the entire blockchain ecosystem.Conventional smart contract vulnerability detection primarily relies on static analysis tools,which are less efficient and accurate.Although deep learning methods have improved detection efficiency,they are unable to fully utilize the static relationships within contracts.Therefore,we have adopted the advantages of the above two methods,combining feature extraction mode of tools with deep learning techniques.Firstly,we have constructed corresponding feature extraction mode for different vulnerabilities,which are used to extract feature graphs from the source code of smart contracts.Then,the node features in feature graphs are fed into a graph convolutional neural network for training,and the edge features are processed using a method that combines attentionmechanismwith gated units.Ultimately,the revised node features and edge features are concatenated through amulti-head attentionmechanism.The result of the splicing is a global representation of the entire feature graph.Our method was tested on three types of data:Timestamp vulnerabilities,reentrancy vulnerabilities,and access control vulnerabilities,where the F1 score of our method reaches 84.63%,92.55%,and 61.36%.The results indicate that our method surpasses most others in detecting smart contract vulnerabilities.

关键词： Blockchain smart contracts deep learning graph neural networks

Adaptable "bubble particles" prepared by green aqueous phase reshaping for completely removing odor

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Nano Research 2024年第3期17卷 2172-2180页

作者： Jiajia Ma Yichang Xia Tienan zhao Wenfeng Hu Weifeng Zhang Qinfei ke Yi zhao Shanghai Frontiers Science Center of Advanced Textiles Donghua UniversityShanghai 201620China Engineering Research Center of Technical Textiles Ministry of EducationDonghua UniversityShanghai 201620China School of Fashion Engineering Central Laboratory Shanghai University of Engineering ScienceShanghai 201620China Department of Materials Science and Engineering National University of SingaporeSingapore 117575Singapore School of Perfume and Aroma Technology Shanghai Institute of TechnologyShanghai 201418China

Facile and ecofriendly loading of micro/nano function-specific substances to create functional materials is a trend being pursued by researchers.However,current micro/nano particles loading approaches are often hindered by issues such as uneven distribution,unsatisfactory stability and complicate procedure.In this work,we present an aqueous phase reshaping method that only utilizes the moisture to fabricate the"bubble particles",which could perfectly cater to the topography of the substrate.The green preparation of bubble particles adopts an absolutely zero-pollution method,realizing the firm loading of particles on the substrate.Integrating the preparation and loading of particles overcomes the traditional complicate process,while the aqueous phase reshaping ensures uniform and firm loading of the"bubble particles"onto the substrate.Our mechanism demonstrates a significant enhancement in the interface relation after aqueous phase reshaping,with a 121-fold increase in contact surface area achieved by reducing the height by 1μm.Furthermore,we explore for the first time the influence of the nature of the receiving substrate on the interface morphology of particles during electrostatic spraying,which has important guiding significance for the interface relationship of electrostatic spraying and even electrostatic spinning materials.We also screen out the natural antibacterial essential oil linalool as the effective specialized antibacterial agent,which can specifically inhibit the odor-producing Proteus in urine,with an antibacterial rate of up to 100%.Taken together,this simple,ecofriendly method for fabricating functional materials with optimal interface stability appears highly promising for use in various products formed by electrostatic spraying/spinning.

关键词： bubble particle electrostatic spraying aqueous phase reshaping interface bonding remove odor nano spraying

Trophic niche and adaptation in highland lizards:sex has greater influences than species matching

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Integrative Zoology 2024年第3期19卷 564-576页

作者： Shengnan YANG Jiapeng QU ke TANG Xinquan zhao Huakun ZHOU Junhua HU Chengdu Institute of Biology Chinese Academy of SciencesChengduChina Qinghai Provincial key Laboratory of Restoration Ecology for Cold Region Northwest lnstitute of Plateau BiologyChinese Academy of SciencesXiningChina University of Chinese Academy of Sciences BeijingChina Qinghai University XiningChina

The plateau environments are typically arid,cool,and high altitude,posing formidable challenges to wildlife survival due to resource scarcity and harsh conditions.Unraveling ecological adaptability in severe conditions requires a deeper understanding of the niche characteristics of plateau species.Trophic niche,which is a comprehensive indicator describing the energy acquisition strategy of animals,remains relatively understudied in plateau species.Here,by combining stable isotopes and morphological data,we quantified the trophic niches of two allopatric lizard species(Phrynocephalus vlangalii and P.erythrurus)that live in the hinterland of the Qinghai–Tibetan Plateau,and explored how their trophic niches correlate with morphological and environmental factors.While both trophic niche and morphological traits were similar between species,noteworthy distinctions were observed between male and female Phrynocephalus lizards.The morphological traits associated with predation(i.***.limb length and head size)and reproduction(i.***.abdomen length),annual mean temperature,and sex played influential roles in shifting trophic niches.These results imply that sexual dimorphism may facilitate inter-sex divergence in resource utilization,leading to trophic niche variations in the highland lizards.Furthermore,extreme environmental stress can constrain interspecific divergence in morphological and trophic traits.Our findings illustrate the dynamic variations of trophic niches in highland lizards,contributing to a more comprehensive understanding of the adaptation strategies employed by lizard species in plateau environments.

关键词： environmental adaptation Phrynocephalus Qinghai-Tibetan Plateau sexual dimorphism stable isotope

Zinc glycine chelate ameliorates DSS‑induced intestinal barrier dysfunction via attenuating TLR4/NF‑κB pathway in meat ducks

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Journal of Animal Science and Biotechnology 2024年第2期15卷 765-778页

作者： Yaqi Chang ke Wang Guangmang Liu Hua zhao Xiaoling Chen Jingyi Cai Gang Jia Institute of Animal Nutrition Key Laboratory for Animal Disease‑Resistance Nutrition of ChinaMinistry of EducationSichuan Agricultural UniversityChengdu 611130SichuanChina

Background Zinc glycine chelate(Zn-Gly)has anti-inflammation and growth-promoting properties;however,the mechanism of Zn-Gly contribution to gut barrier function in Cherry Valley ducks during intestinal inflammation is unknown.Three-hundred 1-day-old ducks were divided into 5 groups(6 replicates and 10 ducks per replicate)in a completely randomized design:the control and dextran sulfate sodium(DSS)groups were fed a corn-soybean meal basal diet,and experimental groups received supplements of 70,120 or 170 mg/kg Zn in form of Zn-Gly.The DSS and treatment groups were given 2 mL of 0.45 g/mL DSS daily during d 15–21,and the control group received normal saline.The experiment lasted 21 d.Results Compared with DSS group,70,120 and 170 mg/kg Zn significantly increased body weight(BW),villus height and the ratio of villus to crypt,and significantly decreased the crypt depth of jejunum at 21 d.The number of goblet cells in jejunal villi in the Zn-Gly group was significantly increased by periodic acid-Schiff staining.Compared with control,the content of intestinal permeability marker D-lactic acid(D-LA)and fluxes of fluorescein isothiocyanate(FITC-D)in plasma of DSS group significantly increased,and 170 mg/kg Zn supplementation significantly decreased the D-LA content and FITC-D fluxes.Compared with control,contents of plasma,jejunum endotoxin and jejunum pro-inflammatory factors IL-1β,IL-6 and TNF-αwere significantly increased in DSS group,and were significantly decreased by 170 mg/kg Zn supplementation.Dietary Zn significantly increased the contents of anti-inflammatory factors IL-10,IL-22 and sIgA and IgG in jejunum.Real-time PCR and Western blot results showed that 170 mg/kg Zn supplementation significantly increased mRNA expression levels of CLDN-1 and expression of OCLN protein in jejunum,and decreased gene and protein expression of CLDN-2 compared with DSS group.The 120 mg/kg Zn significantly promoted the expressions of IL-22 and IgA.Dietary Zn-Gly supplementation significantly decreased pro-inflammatory genes IL-8

关键词： Cherry Valley ducks Growth performance Gut inflammation Intestinal barrier Zn-Gly

Asymmetric two-dimensional diffraction grating via a vortex field in an inverted-Ytype atomic system

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Communications in Theoretical Physics 2024年第5期76卷 77-85页

作者： Duo Zhang ke Wang Kunpeng zhao Mei Wang zhaoyu Sun School of Electrical and Electronic Engineering Wuhan Polytechnic UniversityWuhan 430023China

We propose a theoretical scheme to realize a two-dimensional(2D)diffraction grating in a four-level inverted-Y-type atomic system coupled by a standing-wave(SW)field and a Laguerre-Gaussian(LG)vortex field.Owing to asymmetric spatial modulation of the LG vortex field,the incident probe field can be lopsidedly diffracted into four domains and an asymmetric 2D electromagnetically induced grating is created.By adjusting the detunings of the probe field and the LG vortex field,the intensities of the LG vortex field and the coherent SW field,as well as the interaction length,the diffraction properties and efficiency,can be effectively manipulated.In addition,the effect of the azimuthal parameter on the Fraunhofer diffraction of the probe field is also discussed.This asymmetric 2D diffraction grating scheme may provide a versatile platform for designing quantum devices that require asymmetric light transmission.

关键词： asymmetric diffraction grating standing-wave field Laguerre-Gaussian vortex field diffraction property