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Article ; Online: Memory-Based Cross-Image Contexts for Weakly Supervised Semantic Segmentation.

Fan, Junsong / Zhang, Zhaoxiang

IEEE transactions on pattern analysis and machine intelligence

2023 Volume 45, Issue 5, Page(s) 6006–6020

Abstract: Weakly supervised semantic segmentation (WSSS) trains segmentation models by only weak labels, aiming to save the burden of expensive pixel-level annotations. This paper tackles the WSSS problem of utilizing image-level labels as the weak supervision. ... ...

Abstract	Weakly supervised semantic segmentation (WSSS) trains segmentation models by only weak labels, aiming to save the burden of expensive pixel-level annotations. This paper tackles the WSSS problem of utilizing image-level labels as the weak supervision. Previous approaches address this problem by focusing on generating better pseudo-masks from weak labels to train the segmentation model. However, they generally only consider every single image and overlook the potential cross-image contexts. We emphasize that the cross-image contexts among a group of images can provide complementary information for each other to obtain better pseudo-masks. To effectively employ cross-image contexts, we develop an end-to-end cross-image context module containing a memory bank mechanism and a transformer-based cross-image attention module. The former extracts cross-image contexts online from the feature encodings of input images and stores them as the memory. The latter mines useful information from the memorized contexts to provide the original queries with additional information for better pseudo-mask generation. We conduct detailed experiments on the Pascal VOC 2012 and the COCO dataset to demonstrate the advantage of utilizing cross-image contexts. Besides, state-of-the-art performance is also achieved. Codes are available at https://github.com/js-fan/MCIC.git.
Language	English
Publishing date	2023-04-03
Publishing country	United States
Document type	Journal Article
ISSN	1939-3539
ISSN (online)	1939-3539
DOI	10.1109/TPAMI.2022.3203402
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: NRTR: Neuron Reconstruction With Transformer From 3D Optical Microscopy Images.

Wang, Yijun / Lang, Rui / Li, Rui / Zhang, Junsong

IEEE transactions on medical imaging

2024 Volume 43, Issue 2, Page(s) 886–898

Abstract: The neuron reconstruction from raw Optical Microscopy (OM) image stacks is the basis of neuroscience. Manual annotation and semi-automatic neuron tracing algorithms are time-consuming and inefficient. Existing deep learning neuron reconstruction methods, ...

Abstract	The neuron reconstruction from raw Optical Microscopy (OM) image stacks is the basis of neuroscience. Manual annotation and semi-automatic neuron tracing algorithms are time-consuming and inefficient. Existing deep learning neuron reconstruction methods, although demonstrating exemplary performance, greatly demand complex rule-based components. Therefore, a crucial challenge is designing an end-to-end neuron reconstruction method that makes the overall framework simpler and model training easier. We propose a Neuron Reconstruction Transformer (NRTR) that, discarding the complex rule-based components, views neuron reconstruction as a direct set-prediction problem. To the best of our knowledge, NRTR is the first image-to-set deep learning model for end-to-end neuron reconstruction. The overall pipeline consists of the CNN backbone, Transformer encoder-decoder, and connectivity construction module. NRTR generates a point set representing neuron morphological characteristics for raw neuron images. The relationships among the points are established through connectivity construction. The point set is saved as a standard SWC file. In experiments using the BigNeuron and VISoR-40 datasets, NRTR achieves excellent neuron reconstruction results for comprehensive benchmarks and outperforms competitive baselines. Results of extensive experiments indicate that NRTR is effective at showing that neuron reconstruction is viewed as a set-prediction problem, which makes end-to-end model training available.
MeSH term(s)	Microscopy ; Brain ; Neurons ; Algorithms ; Imaging, Three-Dimensional/methods ; Image Processing, Computer-Assisted
Language	English
Publishing date	2024-02-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	622531-7
ISSN	1558-254X ; 0278-0062
ISSN (online)	1558-254X
ISSN	0278-0062
DOI	10.1109/TMI.2023.3323466
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Article ; Online: Rapid antibiotic screening based on E. coli apoptosis using a potentiometric sensor array.

Zhang, Han / Mou, Junsong / Ding, Jiawang / Qin, Wei

Analytica chimica acta

2024 Volume 1297, Page(s) 342378

Abstract: Phenotypic antimicrobial susceptibility testing enables reliable antibiotic screening but requires multiple strategies to identify each phenotypic change induced by different bactericidal mechanisms. Bacteria apoptosis with typical phenotypic features ... ...

Abstract	Phenotypic antimicrobial susceptibility testing enables reliable antibiotic screening but requires multiple strategies to identify each phenotypic change induced by different bactericidal mechanisms. Bacteria apoptosis with typical phenotypic features has never been explored for antibiotic screening. Herein, we developed an antibiotic screening method based on the measurement of antibiotic-induced phosphatidylserine (PS) exposure of apoptotic bacteria. Phosphatidylserine externalization of E. coli that can be widely used as an apoptosis marker for antibiotics with different antibacterial mechanisms was explored. A positively charged PS-binding peptide was immobilized on magnetic beads (MBs) to recognize and capture apoptotic E. coli with PS externalization. Apoptotic E. coli binding led to the charge or charge density change of MBs-peptide, resulting in a potential change on a magneto-controlled polymeric membrane potentiometric sensor. Based on the detection of apoptotic E. coli killed by antibiotics, antibiotic screening for different classes of antibiotics and silver nanoparticles was achieved within 1.5 h using a potentiometric sensor array. This approach enables sensitive, general, and time-saving antibiotic screening, and may open up a new path for antibiotic susceptibility testing.
MeSH term(s)	Escherichia coli ; Metal Nanoparticles ; Phosphatidylserines ; Silver ; Anti-Bacterial Agents/pharmacology ; Apoptosis ; Peptides
Chemical Substances	Phosphatidylserines ; Silver (3M4G523W1G) ; Anti-Bacterial Agents ; Peptides
Language	English
Publishing date	2024-02-14
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1483436-4
ISSN	1873-4324 ; 0003-2670
ISSN (online)	1873-4324
ISSN	0003-2670
DOI	10.1016/j.aca.2024.342378
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Article ; Online: Editorial: Unveiling the structure and function of brain microcircuits: Experiments, algorithms and simulations.

Qi, Guanxiao / Zhang, Junsong / Bird, Alexander D

Frontiers in neural circuits

2022 Volume 16, Page(s) 991137

MeSH term(s)	Algorithms ; Brain ; Models, Neurological
Language	English
Publishing date	2022-08-12
Publishing country	Switzerland
Document type	Editorial ; Research Support, Non-U.S. Gov't
ZDB-ID	2452968-0
ISSN	1662-5110 ; 1662-5110
ISSN (online)	1662-5110
ISSN	1662-5110
DOI	10.3389/fncir.2022.991137
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Article ; Online: A Modular Neural Motion Retargeting System Decoupling Skeleton and Shape Perception.

Zhang, Jiaxu / Tu, Zhigang / Weng, Junwu / Yuan, Junsong / Du, Bo

IEEE transactions on pattern analysis and machine intelligence

2024 Volume PP

Abstract: Motion mapping between characters with different structures but corresponding to homeomorphic graphs, meanwhile preserving motion semantics and perceiving shape geometries, poses significant challenges in skinned motion retargeting. We propose M-R2ET, a ... ...

Abstract	Motion mapping between characters with different structures but corresponding to homeomorphic graphs, meanwhile preserving motion semantics and perceiving shape geometries, poses significant challenges in skinned motion retargeting. We propose M-R2ET, a modular neural motion retargeting system to comprehensively address these challenges. The key insight driving M-R2ET is its capacity to learn residual motion modifications within a canonical skeleton space. Specifically, a cross-structure alignment module is designed to learn joint correspondences among diverse skeletons, enabling motion copy and forming a reliable initial motion for semantics and geometry perception. Besides, two residual modification modules, i.e., the skeleton-aware module and shape-aware module, preserving source motion semantics and perceiving target character geometries, effectively reduce interpenetration and contact-missing. Driven by our distance-based losses that explicitly model the semantics and geometry, these two modules learn residual motion modifications to the initial motion in a single inference without post-processing. To balance these two motion modifications, we further present a balancing gate to conduct linear interpolation between them. Extensive experiments on the public dataset Mixamo demonstrate that our M-R2ET achieves the state-of-the-art performance, enabling cross-structure motion retargeting, and providing a good balance among the preservation of motion semantics as well as the attenuation of interpenetration and contact-missing.
Language	English
Publishing date	2024-04-10
Publishing country	United States
Document type	Journal Article
ISSN	1939-3539
ISSN (online)	1939-3539
DOI	10.1109/TPAMI.2024.3386777
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Article ; Online: A review of visual sustained attention

Huimin Huang / Rui Li / Junsong Zhang

PeerJ, Vol 11, p e

neural mechanisms and computational models

2023 Volume 15351

Abstract: Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural ... ...

Abstract	Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural mechanisms of sustained attention with computational models to facilitate research and application. Although many studies have assessed attention, the evaluation of humans’ sustained attention is not sufficiently comprehensive. Hence, this study provides a current review on both neural mechanisms and computational models of visual sustained attention. We first review models, measurements, and neural mechanisms of sustained attention and propose plausible neural pathways for visual sustained attention. Next, we analyze and compare the different computational models of sustained attention that the previous reviews have not systematically summarized. We then provide computational models for automatically detecting vigilance states and evaluation of sustained attention. Finally, we outline possible future trends in the research field of sustained attention.
Keywords	Sustained attention ; Computational models ; Neural mechanisms ; Evaluation ; Neural pathways ; Medicine ; R ; Biology (General) ; QH301-705.5
Subject code	621
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	PeerJ Inc.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Application of artificial intelligence-based dual source CT scanning in the differentiation of lung adenocarcinoma in situ and minimally invasive adenocarcinoma.

Liu, Lihong / Ni, Zhihua / Zhang, Jian / Zhao, Junsong / Shen, Jieyun

Pakistan journal of medical sciences

2024 Volume 40, Issue 3Part-II, Page(s) 271–276

Abstract: Background and objective: Lung adenocarcinoma is the most common type of lung cancer with highly incidence and mortality. Due to the overlap of morphological features, it is difficult to distinguish clinically between preinvasive lesions (in situ ... ...

Abstract	Background and objective: Lung adenocarcinoma is the most common type of lung cancer with highly incidence and mortality. Due to the overlap of morphological features, it is difficult to distinguish clinically between preinvasive lesions (in situ adenocarcinoma, AIS) and invasive lesions (minimally invasive adenocarcinoma, MIA), which appear as ground glass cloudy nodules. This study was performed to probe the application value of artificial intelligence (AI)-based dual source CT scanning in the differentiation of AIS as well as MIA. Methods: The clinical data of 136 patients in Shanghai Baoshan Hospital of Integrated Traditional Chinese and Western Medicine from January 2019 to January 2022 were retrospectively analyzed. The accuracy of AI in distinguishing lung AIS (n=76) and MIA (n=60) were analyzed. The effectiveness of AI in detecting nodules and its diagnostic efficacy for AIS and MIA were explored. Results: The proportion of patients with clear and regular lesion boundaries in AIS was higher than that in MIA. The mean lesion diameter of AIS patients was shorter than MIA patients. There was no difference in the CT value between AIS and MIA in the ground glass nodule density area of pure ground glass nodule and mixed ground glass nodule, but the CT value of the solid nodule density area in AIS was lower. The occurrence of pulmonary vascular abnormality, air bronchogram sign, and pleural depression in AIS patients were lower than MIA patients. The detection rate of AI for lung adenocarcinoma with nodule diameter ≤ 5 mm, complete solid nodules and ground glass nodules was significantly higher than radiologists. The sensitivity, specificity, positive prediction rate, negative prediction rate and accuracy of AI detection were significantly higher than radiologists. Conclusion: AI-based dual source CT scanning can clearly show the morphological characteristics of lung adenocarcinoma, which is helpful for the differential diagnosis of lung AIS as well as MIA.
Language	English
Publishing date	2024-01-29
Publishing country	Pakistan
Document type	Journal Article
ZDB-ID	2032827-8
ISSN	1681-715X ; 1682-024X ; 1017-4699
ISSN (online)	1681-715X
ISSN	1682-024X ; 1017-4699
DOI	10.12669/pjms.40.3.8454
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Zs.A 3948: Show issues

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Article ; Online: Celastrus orbiculatus extract reverses precancerous lesions of gastric cancer by inhibiting autophagy via regulating the PDCD4-ATG5 signaling pathway.

Zhu, Fangyuan / Zhang, Xiaoze / Wen, Junsong / Liu, Yanqing / Zhu, Yaodong

The Journal of pharmacy and pharmacology

2024 Volume 76, Issue 3, Page(s) 257–268

Abstract: Objectives: Celastrus orbiculatus ethyl acetate extract (COE) is the main extract of the stem of the Chinese herbal C. orbiculatus, which has anti-tumor and anti-inflammatory biological effects. Our previous study showed that COE had a certain reversal ... ...

Abstract	Objectives: Celastrus orbiculatus ethyl acetate extract (COE) is the main extract of the stem of the Chinese herbal C. orbiculatus, which has anti-tumor and anti-inflammatory biological effects. Our previous study showed that COE had a certain reversal effect on the precancerous lesions of gastric cancer (PLGC) in rats, but the exact mechanism of action remains elusive. We aimed to explore the therapeutic effects of COE on PLGC and the potential mechanisms. Methods: The PLGC rat model was successfully constructed by N-methyl-N´-nitro-N-nitrosoguanidine (MNNG) multifactorial induction method. Then, COE was prepared to treat the PLGC rat model. Hematoxylin & eosin staining was used to observe gastric mucosal lesions in rats, AB-PAS and HID-AB staining were used to observe intestinal metaplasia. PDCD4-ATG5 signaling pathway was detected by immunohistochemistry (IHC) and reverse transcription polymerase chain reaction (RT-PCR) in vivo, and autophagy level was detected by IHC, transmission electron microscopy, and RT-PCR in vivo. Besides, the PLGC (MC) cell model was successfully constructed by treating GES-1 cells with MNNG. Then, the morphology, proliferation, and apoptosis of MC cells, and the role of the PDCD4-ATG5 signaling pathway and autophagy in MC cells were evaluated by COE and after the overexpression of PDCD4 treatment. Key findings: COE significantly improved gastric mucosal injury and cellular heteromorphism and retarded the progression of PLGC in rats. Further studies indicated COE not only inhibited the level of autophagy but also interfered with the PDCD4-ATG5 signaling pathway in vivo. On the other hand, COE treatment could effectively reverse MC cell damage, inhibit MC cell proliferation, and promote MC cell apoptosis. Furthermore, COE also promoted PDCD4 and inhibited ATG5 expression in vitro, and the inhibitory effect of COE on ATG5-mediated autophagy was further enhanced after the overexpression of PDCD4. Conclusions: The study revealed that COE could regulate the PDCD4-ATG5 signaling pathway to inhibit autophagy in gastric epithelial cells, which contributes to reversing the progression of PLGC.
MeSH term(s)	Animals ; Rats ; Apoptosis Regulatory Proteins ; Autophagy ; Celastrus/chemistry ; Cell Line, Tumor ; Methylnitronitrosoguanidine ; Precancerous Conditions/drug therapy ; Signal Transduction ; Stomach Neoplasms/drug therapy ; Stomach Neoplasms/pathology ; Plant Extracts/therapeutic use
Chemical Substances	Apoptosis Regulatory Proteins ; Methylnitronitrosoguanidine (12H3O2UGSF) ; Plant Extracts
Language	English
Publishing date	2024-02-09
Publishing country	England
Document type	Journal Article
ZDB-ID	3107-0
ISSN	2042-7158 ; 0022-3573 ; 0373-1022
ISSN (online)	2042-7158
ISSN	0022-3573 ; 0373-1022
DOI	10.1093/jpp/rgae006
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Article ; Online: A review of visual sustained attention: neural mechanisms and computational models.

Huang, Huimin / Li, Rui / Zhang, Junsong

PeerJ

2023 Volume 11, Page(s) e15351

Abstract	Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural mechanisms of sustained attention with computational models to facilitate research and application. Although many studies have assessed attention, the evaluation of humans' sustained attention is not sufficiently comprehensive. Hence, this study provides a current review on both neural mechanisms and computational models of visual sustained attention. We first review models, measurements, and neural mechanisms of sustained attention and propose plausible neural pathways for visual sustained attention. Next, we analyze and compare the different computational models of sustained attention that the previous reviews have not systematically summarized. We then provide computational models for automatically detecting vigilance states and evaluation of sustained attention. Finally, we outline possible future trends in the research field of sustained attention.
MeSH term(s)	Humans ; Attention ; Neural Pathways ; Wakefulness ; Models, Neurological ; Computer Simulation
Language	English
Publishing date	2023-06-13
Publishing country	United States
Document type	Review ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2703241-3
ISSN	2167-8359 ; 2167-8359
ISSN (online)	2167-8359
ISSN	2167-8359
DOI	10.7717/peerj.15351
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Article ; Online: Social Enterprises and Their Role in Revitalizing Shrinking Cities—A Case Study on Shimizusawa of Japan

Jian Liu / Yixin Zhang / Junsong Mao

Land, Vol 12, Iss 12, p

2023 Volume 2146

Abstract: Since their birth in the 1990s, social enterprises, as a kind of third-party organization with the attributes of both a not-for-profit entity and a profit-making enterprise, have played a significant role in the socio-economic development of cities, in ... ...

Abstract	Since their birth in the 1990s, social enterprises, as a kind of third-party organization with the attributes of both a not-for-profit entity and a profit-making enterprise, have played a significant role in the socio-economic development of cities, in particular those facing the challenge of shrinking. But why are social enterprises so deeply embedded in the regeneration process of shrinking cities, and how do they promote their multi-dimensional revitalization? In order to answer these questions, this paper presents a case study on Shimizusawa in Japan based on a literature review and field research. In line with the embeddedness and institution–function–instrument theories, it reviews the revitalization of Shimizusawa by involving a social enterprise in the adaptive reuse of industrial heritage sites and the development of industrial tourism, analyzes the establishment process and organizational characteristics of this social enterprise, and summarizes the four major experiences of its practice—that is, the governance structure of two types of institutions and two types of functions, the planning for both profitable and non-profitable activities, the operation of both for-profit and not-for-profit businesses, and the fund management of leveraging multiple parties to raise funds and reinvesting the profits locally. The extensive support provided by the Shimizusawa Social Enterprise that creates not only economic value but also social value justifies the significant role of social enterprises in the revitalization of shrinking industrial areas. This case study, together with its analytical framework, may serve as a meaningful reference for the revitalization of shrinking industrial areas in other parts of the world.
Keywords	social enterprise ; private–public partnership ; planning governance ; industrial tourism ; industrial heritage protection ; Agriculture ; S
Subject code	300
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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