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Article: Identifying Mild Alzheimer's Disease With First 30-Min

Shen, Chushu / Wang, Zhenguo / Chen, Hongzhao / Bai, Yan / Li, Xiaochen / Liang, Dong / Liu, Xin / Zheng, Hairong / Wang, Meiyun / Yang, Yongfeng / Wang, Haifeng / Sun, Tao

Frontiers in aging neuroscience

2022 Volume 14, Page(s) 785495

Abstract: ... can provide a better differentiating performance using the data from the first 30-min dynamic scan. Moreover ...

Abstract	Introduction: 11 Methods: 11 Results: The Kruskal-Wallis test suggested that AQI, SUVR, and DVR can all differentiate between the healthy and subjects with mild AD ( Conclusion: Amyloid quantification index combines early-phase kinetic information and a certain degree of β-amyloid deposition, and can provide a better differentiating performance using the data from the first 30-min dynamic scan. Moreover, it was shown that clinically indistinguishable AD cases regarding PiB retention potentially can be correctly identified.
Language	English
Publishing date	2022-04-05
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2558898-9
ISSN	1663-4365
ISSN	1663-4365
DOI	10.3389/fnagi.2022.785495
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Article ; Online: Worst-Case Discriminative Feature Learning via Max-Min Ratio Analysis.

Wang, Zheng / Nie, Feiping / Zhang, Canyu / Wang, Rong / Li, Xuelong

IEEE transactions on pattern analysis and machine intelligence

2023 Volume 46, Issue 1, Page(s) 641–658

Abstract: We propose a novel discriminative feature learning method via Max-Min Ratio Analysis (MMRA ... within same class is diverging. We propose a new criterion, i.e., Max-Min Ratio Analysis (MMRA) that focuses ... However, solving such a non-smooth non-convex max-min ratio problem is challenging. As an important theoretical ...

Abstract	We propose a novel discriminative feature learning method via Max-Min Ratio Analysis (MMRA) for exclusively dealing with the long-standing "worst-case class separation" problem. Existing technologies simply consider maximizing the minimal pairwise distance on all class pairs in the low-dimensional subspace, which is unable to separate overlapped classes entirely especially when the distribution of samples within same class is diverging. We propose a new criterion, i.e., Max-Min Ratio Analysis (MMRA) that focuses on maximizing the minimal ratio value of between-class and within-class scatter to extremely enlarge the separability on the overlapped pairwise classes. Furthermore, we develop two novel discriminative feature learning models for dimensionality reduction and metric learning based on our MMRA criterion. However, solving such a non-smooth non-convex max-min ratio problem is challenging. As an important theoretical contribution in this paper, we systematically derive an alternative iterative algorithm based on a general max-min ratio optimization framework to solve a general max-min ratio problem with rigorous proofs of convergence. More importantly, we also present another solver based on bisection search strategy to solve the SDP problem efficiently. To evaluate the effectiveness of proposed methods, we conduct extensive pattern classification and image retrieval experiments on several artificial datasets and real-world ScRNA-seq datasets, and experimental results demonstrate the effectiveness of proposed methods.
Language	English
Publishing date	2023-12-05
Publishing country	United States
Document type	Journal Article
ISSN	1939-3539
ISSN (online)	1939-3539
DOI	10.1109/TPAMI.2023.3323453
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Article ; Online: Wavelength selection method for near-infrared spectroscopy based on Max-Relevance Min-Redundancy.

Ma, Xiao-Hui / Chen, Zheng-Guang / Liu, Jin-Ming

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

2024 Volume 310, Page(s) 123933

Abstract: ... feature selection on the spectral data becomes critical. The Max-Relevance Min-Redundancy (mRMR) method ... in this paper, the Max-Relevance Min-Redundancy algorithm outperforms others regarding the corn germination rate ...

Abstract	Near-infrared spectroscopy (NIRS) is a rapid, nondestructive analytical technique utilized in various fields. However, the NIR data, which consists of hundreds of dimensions, may exhibit considerable duplication in the spectrum information. This redundancy might impair modeling effectiveness. As a result, feature selection on the spectral data becomes critical. The Max-Relevance Min-Redundancy (mRMR) method stands out among the different feature selection techniques for dimensional reduction. The approach depends on mutual information (MI) between random variables as the basis for feature selection and is unaffected by modeling methods. However, it is necessary to clarify the benefits of the maximum correlation minimal redundancy algorithm in the context of near-infrared spectral feature selection, as well as its adaptability to various modeling methods. This research focuses on the NIR spectral dataset of maize germination rate, and the mRMR method is utilized to select spectral features. Based on the preceding foundation, we create models for Support Vector Regression, Gaussian Process Regression, Random Forest, and Neural Networks. The experimental findings demonstrate that, among the feature selection methods employed in this paper, the Max-Relevance Min-Redundancy algorithm outperforms others regarding the corn germination rate dataset.
Language	English
Publishing date	2024-01-22
Publishing country	England
Document type	Journal Article
ZDB-ID	210413-1
ISSN	1873-3557 ; 0370-8322 ; 0584-8539 ; 1386-1425
ISSN (online)	1873-3557
ISSN	0370-8322 ; 0584-8539 ; 1386-1425
DOI	10.1016/j.saa.2024.123933
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Article ; Online: Active Transport of Membrane Components by Self-Organization of the Min Proteins.

Shih, Yu-Ling / Huang, Ling-Ting / Tu, Yu-Ming / Lee, Bo-Fan / Bau, Yu-Chiuan / Hong, Chia Yee / Lee, Hsiao-Lin / Shih, Yan-Ping / Hsu, Min-Feng / Lu, Zheng-Xin / Chen, Jui-Szu / Chao, Ling

Biophysical journal

2019 Volume 116, Issue 8, Page(s) 1469–1482

Abstract: ... Min proteins can impose steric pressure on the membrane, resulting in transport and directional ... of binding and dissociation of the Min proteins in the propagating waves on the membrane surface ... of the membrane component. Thus, transportation of the membrane component by the Min proteins follows a simple ...

Abstract	Heterogeneous distribution of components in the biological membrane is critical in the process of cell polarization. However, little is known about the mechanisms that can generate and maintain the heterogeneous distribution of the membrane components. Here, we report that the propagating wave patterns of the bacterial Min proteins can impose steric pressure on the membrane, resulting in transport and directional accumulation of the component in the membrane. Therefore, the membrane component waves represent transport of the component in the membrane that is caused by the steric pressure gradient induced by the differential levels of binding and dissociation of the Min proteins in the propagating waves on the membrane surface. The diffusivity, majorly influenced by the membrane anchor of the component, and the repulsed ability, majorly influenced by the steric property of the membrane component, determine the differential spatial distribution of the membrane component. Thus, transportation of the membrane component by the Min proteins follows a simple physical principle, which resembles a linear peristaltic pumping process, to selectively segregate and maintain heterogeneous distribution of materials in the membrane. VIDEO ABSTRACT.
MeSH term(s)	Bacterial Proteins/chemistry ; Bacterial Proteins/metabolism ; Biological Transport, Active ; Cell Membrane/metabolism ; Kinetics ; Models, Biological
Chemical Substances	Bacterial Proteins
Language	English
Publishing date	2019-03-23
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	218078-9
ISSN	1542-0086 ; 0006-3495
ISSN (online)	1542-0086
ISSN	0006-3495
DOI	10.1016/j.bpj.2019.03.011
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Book ; Online: Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization

Wu, Ting / Zheng, Rui / Gui, Tao / Zhang, Qi / Huang, Xuanjing

2023

Abstract: Models trained with empirical risk minimization (ERM) are revealed to easily rely on spurious correlations, resulting in poor generalization. Group distributionally robust optimization (group DRO) can alleviate this problem by minimizing the worst-case ... ...

Abstract	Models trained with empirical risk minimization (ERM) are revealed to easily rely on spurious correlations, resulting in poor generalization. Group distributionally robust optimization (group DRO) can alleviate this problem by minimizing the worst-case loss over pre-defined groups. While promising, in practice factors like expensive annotations and privacy preclude the availability of group labels. More crucially, when taking a closer look at the failure modes of out-of-distribution generalization, the typical procedure of reweighting in group DRO loses efficiency. Hinged on the limitations, in this work, we reformulate the group DRO framework by proposing Q-Diversity. Characterized by an interactive training mode, Q-Diversity relaxes the group identification from annotation into direct parameterization. Furthermore, a novel mixing strategy across groups is presented to diversify the under-represented groups. In a series of experiments on both synthetic and real-world text classification tasks, results demonstrate that Q-Diversity can consistently improve worst-case accuracy under different distributional shifts, outperforming state-of-the-art alternatives. Comment: Findings of ACL 2023
Keywords	Computer Science - Computation and Language
Subject code	006
Publishing date	2023-05-20
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Accelerated Single-Call Methods for Constrained Min-Max Optimization

Cai, Yang / Zheng, Weiqiang

2022

Abstract: We study first-order methods for constrained min-max optimization. Existing methods either require ... of non-convex non-concave min-max optimization problems. Finally, we show that the Reflected Gradient (RG ... convergence rate for constrained convex-concave min-max optimization, answering an open problem of [Heish et ...

Abstract	We study first-order methods for constrained min-max optimization. Existing methods either require two gradient calls or two projections in each iteration, which may be costly in some applications. In this paper, we first show that a variant of the Optimistic Gradient (OG) method, a single-call single-projection algorithm, has $O(\frac{1}{\sqrt{T}})$ best-iterate convergence rate for inclusion problems with operators that satisfy the weak Minty variation inequality (MVI). Our second result is the first single-call single-projection algorithm -- the Accelerated Reflected Gradient (ARG) method that achieves the optimal $O(\frac{1}{T})$ last-iterate convergence rate for inclusion problems that satisfy negative comonotonicity. Both the weak MVI and negative comonotonicity are well-studied assumptions and capture a rich set of non-convex non-concave min-max optimization problems. Finally, we show that the Reflected Gradient (RG) method, another single-call single-projection algorithm, has $O(\frac{1}{\sqrt{T}})$ last-iterate convergence rate for constrained convex-concave min-max optimization, answering an open problem of [Heish et al, 2019]. Our convergence rates hold for standard measures such as the tangent residual and the natural residual. Comment: Published as a conference paper at ICLR 2023
Keywords	Mathematics - Optimization and Control ; Computer Science - Computer Science and Game Theory ; Computer Science - Machine Learning
Subject code	510
Publishing date	2022-10-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A 1-min double embedding method for small tissue specimens preserves comedone histology and eliminates the need for punch biopsies.

Xu, De-Tian / Zheng, Yan / Shi, Yu / Jin, Hua / Liu, Wei / Wang, Xiu-Li

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)

2022 Volume 29, Issue 1, Page(s) e13235

Abstract: Background: It is difficult to preserve the structure and microbial distribution inside comedonal plugs during routine processing.: Objective: The objective of this study is to determine the optimal method to preserve the comedonal corneum plug ... ...

Abstract	Background: It is difficult to preserve the structure and microbial distribution inside comedonal plugs during routine processing. Objective: The objective of this study is to determine the optimal method to preserve the comedonal corneum plug structure and inherent microorganisms thereby eliminating the need to perform punch biopsies in relevant studies. Methods: Corneum plugs were extracted from comedones of acne vulgaris patients. Primary embedding using either a 2% agarose, 2% agar, 25% gelatin, or 2% agar + 2.5% gelatin solution was subsequently performed and the results compared. The specimens were then fixed, waxed, sectioned, and examined by light, fluorescence, and scanning electron microscopies to observe the structures and microorganisms within the plugs. Results: Both the 25% gelatin and 2% agarose solutions successfully preserved the structural integrity of corneum plugs and the inherent microorganisms. When considering other factors such as thermostability, reusability, and convenience, the 25% gelatin solution was the superior choice among the four materials. Conclusion: We report a simple and effective method for double embedding comedonal plugs and other small tissue specimens. The technique preserves the structure and microbial distribution in situ within comedonal corneum plugs, eliminates the need for punch biopsies. This method may also be applied to other tiny and fragile tissue specimens, thereby enabling a potentially wide array of future large-scale investigations and alleviated patients' pain.
MeSH term(s)	Humans ; Gelatin ; Agar ; Sepharose ; Acne Vulgaris/drug therapy ; Biopsy
Chemical Substances	Gelatin (9000-70-8) ; Agar (9002-18-0) ; Sepharose (9012-36-6)
Language	English
Publishing date	2022-12-08
Publishing country	England
Document type	Journal Article
ZDB-ID	1229160-2
ISSN	1600-0846 ; 0909-752X ; 1397-1344
ISSN (online)	1600-0846
ISSN	0909-752X ; 1397-1344
DOI	10.1111/srt.13235
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Article: A Clinical-Radiomic Model for Predicting Indocyanine Green Retention Rate at 15 Min in Patients With Hepatocellular Carcinoma.

Wu, Ji / Xie, Feng / Ji, Hao / Zhang, Yiyang / Luo, Yi / Xia, Lei / Lu, Tianfei / He, Kang / Sha, Meng / Zheng, Zhigang / Yong, Junekong / Li, Xinming / Zhao, Di / Yang, Yuting / Xia, Qiang / Xue, Feng

Frontiers in surgery

2022 Volume 9, Page(s) 857838

Abstract: Purpose: The indocyanine green retention rate at 15 min (ICG-R15) is of great importance ...

Abstract	Purpose: The indocyanine green retention rate at 15 min (ICG-R15) is of great importance in the accurate assessment of hepatic functional reserve for safe hepatic resection. To assist clinicians to evaluate hepatic functional reserve in medical institutions that lack expensive equipment, we aimed to explore a novel approach to predict ICG-R15 based on CT images and clinical data in patients with hepatocellular carcinoma (HCC). Methods: In this retrospective study, 350 eligible patients were enrolled and randomly assigned to the training cohort (245 patients) and test cohort (105 patients). Radiomics features and clinical factors were analyzed to pick out the key variables, and based on which, we developed the random forest regression, extreme gradient boosting regression (XGBR), and artificial neural network models for predicting ICG-R15, respectively. Pearson's correlation coefficient (R) was adopted to evaluate the performance of the models. Results: We extracted 660 CT image features in total from each patient. Fourteen variables significantly associated with ICG-R15 were picked out for model development. Compared to the other two models, the XGBR achieved the best performance in predicting ICG-R15, with a mean difference of 1.59% (median, 1.53%) and an Conclusion: The proposed approach that incorporates the optimal radiomics features and clinical factors can allow for individualized prediction of ICG-R15 value of patients with HCC, regardless of the specific equipment and detection reagent (NO. ChiCTR2100053042; URL, http://www.chictr.org.cn).
Language	English
Publishing date	2022-03-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2773823-1
ISSN	2296-875X
ISSN	2296-875X
DOI	10.3389/fsurg.2022.857838
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Article ; Online: The difference in soil organic carbon distribution between natural and planted forests: A case study on stony soils mountainous area in the Upper Min River Arid Valley, China

Yunwei, Han / Qing, Wang / Fucheng, Li / Yalin, Guo / Weipo, Yan / Yida, An / Yinping, Bai / Min, Yang / Yuting, Zheng / Qi, Hu

Soil Use and Management. 2023 Jan., v. 39, no. 1 p.147-160

2023

Abstract: ... accumulation and sequestration in the Upper Min River Arid Valley, China. The differences in SOC distribution ...

Abstract	Few studies have been conducted on the factors and distribution of soil organic carbon (SOC) in plantation forests in arid mountainous regions, especially in orchards. We aimed to unravel the SOC distribution among land‐use types and the effects of altitude gradients and rock fragment content (RFC) on SOC accumulation and sequestration in the Upper Min River Arid Valley, China. The differences in SOC distribution among land‐use types were quantified. The correlation analysis of SOC with various factors, such as altitude and RFC, was conducted. The variation percentage in SOC content and stocks was explained by the factors' contribution using mixed‐effects models. SOC distribution was characterized by high content and low stocks in native forests and shrubs, high content and high stocks in eco‐forest, and low content and high stocks in orchards. At the surface (0–30 cm), SOC content and stocks in orchards (cherry, plum, and apple) were significantly lower than those in eco‐forests. There was a significant positive correlation between altitude and SOC content at the surface but not at the subsoil (30–60 cm). With RFC increased, the surface SOC content decreased in native forests, shrubs, and eco‐forests, while it increased in orchards. Our results suggest that land management is the main factor controlling the variation in SOC distribution. Enhancing the surface SOC stability in orchards by land management is a priority for soil carbon pool management in the Arid Valleys.
Keywords	administrative management ; altitude ; apples ; carbon sinks ; case studies ; cherries ; land use ; mountains ; plums ; rivers ; soil organic carbon ; subsoil ; China
Language	English
Dates of publication	2023-01
Size	p. 147-160.
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	742151-5
ISSN	1475-2743 ; 0266-0032
ISSN (online)	1475-2743
ISSN	0266-0032
DOI	10.1111/sum.12860
Database	NAL-Catalogue (AGRICOLA)

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Article: Effect of 3 min whole-body and lower limb cold water immersion on subsequent performance of agility, sprint, and intermittent endurance exercise.

Zhang, Wei / Ren, Shoupeng / Zheng, Xinyan

Frontiers in physiology

2022 Volume 13, Page(s) 981773

Abstract: ... lower-limb cold-water immersion (LCWI) employed during a 15-min recovery period on the subsequent exercise ... exercise protocols (1 and 2) separated by a 15-min recovery period. The participants completed the same ...

Abstract	The aim of this study was to investigate the effects of whole-body cold-water immersion (WCWI) and lower-limb cold-water immersion (LCWI) employed during a 15-min recovery period on the subsequent exercise performance as well as to determine the physiological and perceptual parameters in the heat (39°C). Eleven males performed team-sports-specific tests outdoors. The exercise program consisted of two identical exercise protocols (1 and 2) separated by a 15-min recovery period. The participants completed the same tests in each exercise protocol, in the following order: agility
Language	English
Publishing date	2022-10-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2564217-0
ISSN	1664-042X
ISSN	1664-042X
DOI	10.3389/fphys.2022.981773
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