USAGE: A Unified Seed Area Generation Paradigm for Weakly Supervised Semantic Segmentation

Seed area generation is usually the starting point of weakly supervised semantic segmentation (WSSS). Computing the Class Activation Map (CAM) from a multi-label classification network is the de facto paradigm for seed area generation, but CAMs generated from Convolutional Neural Networks (CNNs) and Transformers are prone to be under- and over-activated, respectively, which makes the strategies to refine CAMs for CNNs usually inappropriate for Transformers, and vice versa. In this paper, we propose a Unified optimization paradigm for Seed Area GEneration (USAGE) for both types of networks, in which the objective function to be optimized consists of two terms: One is a generation loss, which controls the shape of seed areas by a temperature parameter following a deterministic principle for different types of networks; The other is a regularization loss, which ensures the consistency between the seed areas that are generated by self-adaptive network adjustment from different views, to overturn false activation in seed areas. Experimental results show that USAGE consistently improves seed area generation for both CNNs and Transformers by large margins, e.g., outperforming state-of-the-art methods by a mIoU of 4.1% on PASCAL VOC. Moreover, based on the USAGE-generated seed areas on Transformers, we achieve state-of-the-art WSSS results on both PASCAL VOC and MS COCO

A novel universal real-time PCR system using the attached universal duplex probes for quantitative analysis of nucleic acids

BACKGROUND: Real-time PCR techniques are being widely used for nucleic acids analysis, but one limitation of current frequently employed real-time PCR is the high cost of the labeled probe for each target molecule. RESULTS: We describe a real-time PCR technique employing attached universal duplex probes (AUDP), which has the advantage of generating fluorescence by probe hydrolysis and strand displacement over current real-time PCR methods. AUDP involves one set of universal duplex probes in which the 5' end of the fluorescent probe (FP) and a complementary quenching probe (QP) lie in close proximity so that fluorescence can be quenched. The PCR primer pair with attached universal template (UT) and the FP are identical to the UT sequence. We have shown that the AUDP technique can be used for detecting multiple target DNA sequences in both simplex and duplex real-time PCR assays for gene expression analysis, genotype identification, and genetically modified organism (GMO) quantification with comparable sensitivity, reproducibility, and repeatability with other real-time PCR methods. CONCLUSION: The results from GMO quantification, gene expression analysis, genotype identification, and GMO quantification using AUDP real-time PCR assays indicate that the AUDP real-time PCR technique has been successfully applied in nucleic acids analysis, and the developed AUDP real-time PCR technique will offer an alternative way for nucleic acid analysis with high efficiency, reliability, and flexibility at low cost.Litao Yang, Wanqi Liang, Lingxi Jiang, Wenquan Li, Wei Cao, Zoe A Wilson, and Dabing Zhan

A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction

The rapid development of deep learning has made a great progress in image segmentation, one of the fundamental tasks of computer vision. However, the current segmentation algorithms mostly rely on the availability of pixel-level annotations, which are often expensive, tedious, and laborious. To alleviate this burden, the past years have witnessed an increasing attention in building label-efficient, deep-learning-based image segmentation algorithms. This paper offers a comprehensive review on label-efficient image segmentation methods. To this end, we first develop a taxonomy to organize these methods according to the supervision provided by different types of weak labels (including no supervision, inexact supervision, incomplete supervision and inaccurate supervision) and supplemented by the types of segmentation problems (including semantic segmentation, instance segmentation and panoptic segmentation). Next, we summarize the existing label-efficient image segmentation methods from a unified perspective that discusses an important question: how to bridge the gap between weak supervision and dense prediction -- the current methods are mostly based on heuristic priors, such as cross-pixel similarity, cross-label constraint, cross-view consistency, and cross-image relation. Finally, we share our opinions about the future research directions for label-efficient deep image segmentation.Comment: Accepted to IEEE TPAM

The effect of delignification process with alkaline peroxide on lactic acid production from furfural residues

Furfural residues produced from the furfural industry were investigated as a substrate for lactic acid production by simultaneous saccharification and fermentation (SSF). Alkaline peroxide was used for delignification of furfural residues to improve the final lactic acid concentration. The residue was treated with 1.3% to 1.7% hydrogen peroxide at 80 °C for 1 h with a substrate concentration of 3.33%. SSF of furfural residues with different delignification degrees were carried out to evaluate the effect of delignification degree on lactic acid production. Using corn hydrolysates/ furfural residues as substrates, SSF with different media were carried out to investigate the effect of lignin on the interaction between enzymes and lactic acid bacteria. Lactic acid bacteria had a negative effect on cellulase, thus resulting in the reduction of enzyme activity. Lignin and nutrients slowed down the decreasing trend of enzyme activity. A higher delignification resulted in a slower fermentation rate and lower yield due to degradation products of lignin and the effect of lignin on the interaction between enzymes and lactic acid bacteria. For the purpose of lactic acid production, a moderate delignification (furfural residues with the lignin content of 14.8%) was optimum

A comprehensive estimate of recent carbon sinks in China using both top-down and bottom-up approaches

Atmospheric inversions use measurements of atmospheric CO2 gradients to constrain regional surface fluxes. Current inversions indicate a net terrestrial CO2 sink in China between 0.16 and 0.35 PgC/yr. The uncertainty of these estimates is as large as the mean because the atmospheric network historically contained only one high altitude station in China. Here, we revisit the calculation of the terrestrial CO2 flux in China, excluding emissions from fossil fuel burning and cement production, by using two inversions with three new CO2 monitoring stations in China as well as aircraft observations over Asia. We estimate a net terrestrial CO2 uptake of 0.39-0.51 PgC/yr with a mean of 0.45 PgC/yr in 2006-2009. After considering the lateral transport of carbon in air and water and international trade, the annual mean carbon sink is adjusted to 0.35 PgC/yr. To evaluate this top-down estimate, we constructed an independent bottom-up estimate based on ecosystem data, and giving a net land sink of 0.33 PgC/yr. This demonstrates closure between the top-down and bottom-up estimates. Both top-down and bottom-up estimates give a higher carbon sink than previous estimates made for the 1980s and 1990s, suggesting a trend towards increased uptake by land ecosystems in China.</p

Analysis of the behavior and influencing factors of pickled and smoked products consumption in residents in Southwest China

ObjectiveTo investigate the current situation and risk factors of high-frequency consumption of pickled and smoked products in Southwest China and put forward corresponding countermeasures and suggestions.MethodsA questionnaire survey was conducted from February to May in 2021 in Southwest China （Yunnan， Guizhou， Sichuan and Chongqing） by convenient sampling to obtain data. The geographical， demographic and sociological factors， health knowledge and behavior factors were collected. The risk factors of high-frequency pickled and smoked products consumption were analyzed by disordered multi classification logistic regression.ResultsGeographical factor analysis showed that the risk of high-frequency consumption of pickled and smoked products in Yunnan， Guizhou and rural areas was high. The risk of high-frequency consumption of pickled and smoked products in Yunnan province were 2.764 times and 2.126 times higher than that in Chongqing respectively. Among the demographic sociological factors， high-frequency consumption of pickled and smoked products was positively correlated with age and education to a certain extent， and intellectual labor was a protective factor. The most noteworthy factor was the age： the risk of the elderly over 60 years old was the highest， and only 46.70% of the youth aged from 18 had the behavior. In terms of health knowledge and behavior， there was a statistical difference between the knowledge of salt and the consumption of smoked products. The risk of the group with zero correct rate was 1.372 times higher than that of the group with all correct answers. The frequency of drinking alcohol and the risk of pickled and smoked products were basically positively correlated. In the two groups of dependent variables， people who drunk more than three times a week had the highest risk， and the risk of those who never drunk was only 32.10% compared to the drinkers.ConclusionPickled and smoked products are the characteristic food in Southwest China. Geographical factors， demographic and sociological factors， health knowledge and behavior factors are related to high-frequency consumption of pickled and smoked products. It is necessary to control the health risks brought by high-frequency eating behaviors， promote targeted health education in Yunnan， Guizhou and rural areas， and elderly and less educated groups， encourage healthy eating behaviors， and promote the “Healthy Southwest Action” of “Healthy China”

Dynamic cerebral blood flow assessment based on electromagnetic coupling sensing and image feature analysis

Dynamic assessment of cerebral blood flow (CBF) is crucial for guiding personalized management and treatment strategies, and improving the prognosis of stroke. However, a safe, reliable, and effective method for dynamic CBF evaluation is currently lacking in clinical practice. In this study, we developed a CBF monitoring system utilizing electromagnetic coupling sensing (ECS). This system detects variations in brain conductivity and dielectric constant by identifying the resonant frequency (RF) in an equivalent circuit containing both magnetic induction and electrical coupling. We evaluated the performance of the system using a self-made physical model of blood vessel pulsation to test pulsatile CBF. Additionally, we recruited 29 healthy volunteers to monitor cerebral oxygen (CO), cerebral blood flow velocity (CBFV) data and RF data before and after caffeine consumption. We analyzed RF and CBFV trends during immediate responses to abnormal intracranial blood supply, induced by changes in vascular stiffness, and compared them with CO data. Furthermore, we explored a method of dynamically assessing the overall level of CBF by leveraging image feature analysis. Experimental testing substantiates that this system provides a detection range and depth enhanced by three to four times compared to conventional electromagnetic detection techniques, thereby comprehensively covering the principal intracranial blood supply areas. And the system effectively captures CBF responses under different intravascular pressure stimulations. In healthy volunteers, as cerebral vascular stiffness increases and CO decreases due to caffeine intake, the RF pulsation amplitude diminishes progressively. Upon extraction and selection of image features, widely used machine learning algorithms exhibit commendable performance in classifying overall CBF levels. These results highlight that our proposed methodology, predicated on ECS and image feature analysis, enables the capture of immediate responses of abnormal intracranial blood supply triggered by alterations in vascular stiffness. Moreover, it provides an accurate diagnosis of the overall CBF level under varying physiological conditions

Novel Genetic Risk and Metabolic Signatures of Insulin Signaling and Androgenesis in the Anovulation of Polycystic Ovary Syndrome

Funding Information: The authors are grateful to all staff in the PCOSAct group for their effort in the collection of blood samples and clinical dataset which used in current study. Special thanks to Prof. Attila Toth from Institute of Physiological Chemistry, Dresden, Germany for the REC114 antibody. This study was supported by the National key Research and Development Program of China (2019YFC1709500); the National Collaboration Project of Critical Illness by Integrating Chinese Medicine and Western Medicine; the Project of Heilongjiang Province Innovation Team “TouYan;” the Yi-Xun Liu and Xiao-Ke Wu Academician Workstation; the Innovation Team of Reproductive Technique with Integrative Chinese Medicine and Western Medicine in Xuzhou City, China; Heilongjiang University of Chinese Medicine from the National Clinical Trial Base; Heilongjiang Provincial Clinical Research Center for Ovary Diseases; the Research Grant Council (T13-602/21-N, C5045-20EF, and 14122021); and Food and Health Bureau in Hong Kong, China (06171026). Ben Willem J. Mol is supported by a National Health and Medical Research Council (NHMRC) Investigator grant (GNT1176437). Ben Willem J. Mol reports consultancy for ObsEva and Merck and travel support from Merck. Xiaoke Wu, Yongyong Shi, and Chi Chiu Wang developed the research question and designed the study. Xiaoke Wu, Yongyong Shi, Yijuan Cao, and Chi Chiu Wang designed the analysis. Yongyong Shi and Zhiqiang Li contributed to the design of the experiment of whole-exome plus targeted SNP sequencing and the analysis, and interpreted the results. Jingshu Gao, Hui Chang, Duojia Zhang, Jing Cong, Yu Wang, Qi Wu, Xiaoxiao Han, Pui Wah Jacqueline Chung, Yiran Li, and Lin Zeng contributed to the experiment of metabolic profile and immunofluorescent staining and the analysis, and interpreted the results. Astrid Borchert and Hartmut Kuhn provided antibody support and advice. Xu Zheng and Lingxi Chen contributed to create the predictive model with deep machine learning. Jian Li, Qi Wu, Hongli Ma, Xu Zheng, and Lingxi Chen contributed to the analysis of the clinical characteristics and interpreted the results. Jian Li, Hongli Ma, Hui Chang, Jing Cong, and Chi Chiu Wang drafted the manuscript. All authors reviewed and revised the manuscript. Xiaoke Wu is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Xiaoke Wu, Chi Chiu Wang, Yijuan Cao, Jian Li, Zhiqiang Li, Hongli Ma, Jingshu Gao, Hui Chang, Duojia Zhang, Jing Cong, Yu Wang, Qi Wu, Xiaoxiao Han, Pui Wah Jacqueline Chung, Yiran Li, Xu Zheng, Lingxi Chen, Lin Zeng, Astrid Borchert, Hartmut Kuhn, Zijiang Chen, Ernest Hung Yu Ng, Elisabet Stener-Victorin, Heping Zhang, Richard S. Legro, Ben Willem J. Mol, and Yongyong Shi declare that they have no conflict of interest or financial conflicts to disclose. Funding Information: This study was supported by the National key Research and Development Program of China ( 2019YFC1709500 ); the National Collaboration Project of Critical Illness by Integrating Chinese Medicine and Western Medicine ; the Project of Heilongjiang Province Innovation Team “TouYan;” the Yi-Xun Liu and Xiao-Ke Wu Academician Workstation; the Innovation Team of Reproductive Technique with Integrative Chinese Medicine and Western Medicine in Xuzhou City , China; Heilongjiang University of Chinese Medicine from the National Clinical Trial Base ; Heilongjiang Provincial Clinical Research Center for Ovary Diseases ; the Research Grant Council ( T13-602/21-N , C5045-20EF , and 14122021 ); and Food and Health Bureau in Hong Kong, China ( 06171026 ). Publisher Copyright: © 2023Peer reviewedPublisher PD

A pH-Responsive Cluster Metal-Organic Framework Nanoparticle for Enhanced Tumor Accumulation and Antitumor Effect

As a result of the deficient tumor-specific antigens, potential off-target effect, and influence of protein corona, metal–organic framework nanoparticles have inadequate accumulation in tumor tissues, limiting their therapeutic effects. In this work, a pH-responsive linker (L) is prepared by covalently modifying oleylamine (OA) with 3-(bromomethyl)-4-methyl-2,5-furandione (MMfu) and poly(ethylene glycol) (PEG). Then, the L is embedded into a solid lipid nanoshell to coat apilimod (Ap)-loaded zeolitic imidazolate framework (Ap-ZIF) to form Ap-ZIF@SLN#L. Under the tumor microenvironment, the hydrophilic PEG and MMfu are removed, exposing the hydrophobic OA on Ap-ZIF@SLN#L, increasing their uptake in cancer cells and accumulation in the tumor. The ZIF@SLN#L nanoparticle induces reactive oxygen species (ROS). Ap released from Ap-ZIF@SLN#L significantly promotes intracellular ROS and lactate dehydrogenase generation. Ap-ZIF@SLN#L inhibits tumor growth, increases the survival rate in mice, activates the tumor microenvironment, and improves the infiltration of macrophages and T cells in the tumor, as demonstrated in two different tumor-bearing mice after injections with Ap-ZIF@SLN#TL. Furthermore, mice show normal tissue structure of the main organs and the normal serum level in alanine aminotransferase and aspartate aminotransferase after treatment with the nanoparticles. Overall, this pH-responsive targeting strategy improves nanoparticle accumulation in tumors with enhanced therapeutic effects.</p