Effect of gelatin edible coating with Aronia melanocarpa pomace polyphenols on the cold storage of chilled pork.

In this research, the Aronia melanocarpa pomace polyphenols (AMPPs) were extracted and purified. The purified AMPPs contained the most abundant chlorogenic acid (CGA) at 36.91 mg/100 mg, followed by chrysin at 8.61 mg/100 mg. At a concentration of 60 µg/mL, the purified AMPPs exhibited stronger scavenging activity against: DPPH radical, hydroxyl radical, ABTS∙+, and also showed greater Fe3+ reducing activity than the VC control group. To solve the problem of easy spoilage of chilled meat during storage, gelatin edible coatings containing Aronia melanocarpa pomace polyphenols, referred to as G/AMPPs, were investigated for their effect on the chilled storage of pork. At a 1:1 volume ratio of 1 % polyphenol solution to 3 % gelatin solution, the G/AMPPs coating effectively curbed pH, TVB-N, TVC, drip loss, and b* value increases in chilled pork, while delaying declines in hardness, adhesion, a* value and L* value; The TVB-N content and TVC values demonstrated that the G/AMPPs coating significantly extended the shelf life of chilled pork by up to 15 days. The results showed that G/AMPPs had good preservative, antibacterial and antioxidant effects on chilled pork and thus development of G/AMPPs based coating shows appeared to offer promise for meat preservation.

Hsa-miR-3928-3p targets the CCL3/CCR5 axis to induce amniotic epithelial cell senescence involved in labor initiation.

INTRODUCTION: Senescence in human amniotic epithelial cells (hAECs) and increased sterile inflammation in the amniotic cavity can lead to the initiation of term labor (TL). We investigated the possible roles of hsa-miR-3928-3p and chemokine ligand 3 (CCL3) in labor initiation and the underlying molecular mechanisms. METHODS: Microarray chip screening was used to analyse the differential expression of miRNAs in amniotic fluid exosomes from women in TL and term not-in-labor. The GEO and miRWalk databases were used to identify differential genes, and a dual luciferase assay was used to verify the relationship. Reverse transcription quantitative PCR (RT-qPCR) and immunofluorescence were used to determine the expression and localization of CCL3/CCR5 in fetal membranes. RT-qPCR and western blotting were used to detect the expression of CCL3/CCR5 in hAECs with hsa-miR-3928-3p knockdown/overexpression. Cell counting kit 8, flow cytometry, EdU proliferation, senescence-associated ß-galactosidase, and enzyme-linked immunosorbent assays were performed to detect the impact of hsa-miR-3928-3p on hAEC function. RESULTS: hsa-miR-3928-3p expression was downregulated in TL. CCL3 (macrophage inflammatory protein-1α) was identified as a differentially expressed target gene. hsa-miR-3928-3p targeted the 3' UTR of CCL3. Downregulation of hsa-miR-3928-3p expression increased CCL3 expression. CCL3, via its CCR5 receptor, decreased the proliferation, but increased the senescence, apoptosis rate, secretion of inflammatory factors (IL-8, TNF-α, and IL-6), and expression of senescence-associated protein p21 in hAECs. DISCUSSION: hsa-miR-3928-3p negatively regulates CCL3, promoting hAEC senescence through the CCL3-CCR5 axis and inducing signals for labor initiation. These findings provide novel insights for labor initiation in clinical settings.

Cone-beam CT landmark detection for measuring basal bone width: a retrospective validation study.

BACKGROUND: Accurate assessment of basal bone width is essential for distinguishing individuals with normal occlusion from patients with maxillary transverse deficiency who may require maxillary expansion. Herein, we evaluated the effectiveness of a deep learning (DL) model in measuring landmarks of basal bone width and assessed the consistency of automated measurements compared to manual measurements. METHODS: Based on the U-Net algorithm, a coarse-to-fine DL model was developed and trained using 80 cone-beam computed tomography (CBCT) images. The model's prediction capabilities were validated on 10 CBCT scans and tested on an additional 34. To evaluate the performance of the DL model, its measurements were compared with those taken manually by one junior orthodontist using the concordance correlation coefficient (CCC). RESULTS: It took approximately 1.5 s for the DL model to perform the measurement task in only CBCT images. This framework showed a mean radial error of 1.22 ± 1.93 mm and achieved successful detection rates of 71.34%, 81.37%, 86.77%, and 91.18% in the 2.0-, 2.5-, 3.0-, and 4.0-mm ranges, respectively. The CCCs (95% confidence interval) of the maxillary basal bone width and mandibular basal bone width distance between the DL model and manual measurement for the 34 cases were 0.96 (0.94-0.97) and 0.98 (0.97-0.99), respectively. CONCLUSION: The novel DL framework developed in this study improved the diagnostic accuracy of the individual assessment of maxillary width. These results emphasize the potential applicability of this framework as a computer-aided diagnostic tool in orthodontic practice.

Deterministic Assembly of Single-Emitter Plasmonic Antenna for Ultrahigh Photoluminescence Enhancement.

Single-emitter nanoantennas play a crucial role in the fabrication of nanosensors and integrated sources. Since the coupling of single emitter to nanoantennas is largely based on stochastic methods, low qualified rate still hinders a massive deployment. Here, we proposed a deterministic, optical-force-driven method to achieve gap-plasmonic photoluminescence enhancement. Two deterministic steps are carried out in sequence: a composite nanoemitter is first synthesized by linking quantum dots to a silica-rapped gold nanoparticle, followed by an optical delivery of the nanoparticle into a nanoaperture in a gold film. We reason that the nanoparticle-in-nanoaperture (NPiNA) structure efficiently couples out-of-plane excitation light into a gap-plasmon via a transverse electromagnetic mode (TEM)-like transmission mode. An in situ photoluminescence measurement demonstrates a 3× brightness as compared to the nanoparticle-on-mirror (NPoM). This approach paves the way toward deterministic positioning of individual nanoparticles for a wide range of applications on nanophotonics structures on-a-chip.

Graph Convolutional Network With Self-Augmented Weights for Semi-Supervised Multi-View Learning.

Recently, owing to the effectiveness in exploiting inherent connections between data in different views, graph-based deep learning approaches have gained widespread popularity in semi-supervised multi-view tasks. Generally, the existing approaches fuse the information from different views via the linear or nonlinear weight strategies, which distinguish the importance of different views by attributing their weights between [0, 1] , i.e., some less important views are discarded since assigned with 0 and the pivotal views are not enhanced. However, these view-weighting strategies ignore the complementary information from the less important views. To address this issue, a superior-performing graph convolutional network (GCN) with self-augmented weights is proposed. The proposed self-augmented weight strategy is based on exponential series integration, which preserves the less important views and simultaneously strengthens the key views for multi-view fusion. Specifically, the designed weight strategy can adaptively preserve the complementary information from the less important views by assigning nonzero weights and strengthen the pivotal views by assigning higher weights based on exponential series integration. Besides, to further improve the model performance, an orthogonal constraint layer with a forced orthogonal weight is introduced, which is capable of making the representation more discriminative. Extensive experiments demonstrate the superiority of the proposed method.

ChineseMPD: A Semantic Segmentation Dataset of Chinese Martial Arts Classic Movie Props.

Recent advances in computer vision and deep learning techniques have facilitated significant progress in video scene understanding, thus helping film and television practitioners achieve accurate video editing. However, so far, publicly available semantic segmentation datasets are mostly limited to indoor scenes, city streets, and natural images, often ignoring example objects in action movies, which is a research gap that needs to be urgently filled. In this paper, we introduce a large-scale, high-precision semantic segmentation dataset of props in Chinese martial arts movie clips, named ChineseMPD. Specifically, this dataset first establishes segmentation rules and general review criteria for audiovisual data, and then provides semantic segmentation annotations for six weapon props (Gun, Sword, Stick, Knife, Hook, and Arrow) with a summary of 32,992 objects.To the best of our knowledge, this dataset is the largest semantic segmentation dataset for movie props to date. ChineseMPD dataset not only significantly expands the application of traditional tasks of computer vision such as object detection and scene understanding, but also opens up new avenues for interdisciplinary research.

Modular Prodrug-Engineered Oxygen Nano-Tank With Outstanding Nanoassembly Performance, High Oxygen Loading, and Closed-Loop Tumor Hypoxia Relief.

The clinical translation of tumor hypoxia intervention modalities still falls short of expectation, restricted by poor biocompatibility of oxygen-carrying materials, unsatisfactory oxygen loading performance, and abnormally high cellular oxygen consumption-caused insufficient hypoxia relief. Herein, a carrier-free oxygen nano-tank based on modular fluorination prodrug design and co-assembly nanotechnology is elaborately exploited, which is facilely fabricated through the molecular nanoassembly of a fluorinated prodrug (FSSP) of pyropheophorbide a (PPa) and an oxygen consumption inhibitor (atovaquone, ATO). The nano-tank adeptly achieves sufficient oxygen enrichment while simultaneously suppressing oxygen consumption within tumors for complete tumor hypoxia alleviation. Significant, the fluorination module in FSSP not only confers favorable co-assemblage of FSSP and ATO, but also empowers the nanoassembly to readily carry oxygen. As expected, it displays excellent oxygen carrying capacity, favorable pharmacokinetics, on-demand laser-triggerable ATO release, closed-loop tumor hypoxia relief, and significant enhancement to PPa-mediated PDT in vitro and in vivo. This study provides a novel nanotherapeutic paradigm for tumor hypoxia intervention-enhanced cancer therapy.

Natural Occurrence and Co-Occurrence of Beauvericin and Enniatins in Wheat Kernels from China.

A total of 769 wheat kernels collected from six provinces in China were analyzed for beauvericin (BEA) and four enniatins (ENNs), namely, ENA, ENA1, ENB and ENB1, using a solid phase extraction (SPE) technique with ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The results show that the predominant toxin was BEA, which had a maximum of 387.67 µg/kg and an average of 37.69 µg/kg. With regard to ENNs, the prevalence and average concentrations of ENB and ENB1 were higher than those of ENA and ENA1. The geographical distribution of BEA and ENNs varied. Hubei and Shandong exhibited the highest and lowest positive rates of BEA and ENNs (13.46% and 87.5%, respectively). However, no significant difference was observed among these six provinces. There was a co-occurrence of BEA and ENNs, and 42.26% of samples were simultaneously detected with two or more toxins. Moreover, a significant linear correlation in concentrations was observed between the four ENN analogs (r range: 0.75~0.96, p < 0.05). This survey reveals that the contamination and co-contamination of BEA and ENNs in Chinese wheat kernels were very common.

Soil bacterial diversity and community structure of Suaeda glauca vegetation in the Hetao Irrigation District, Inner Mongolia, China.

Exploring the bacterial community in the S. glauca rhizosphere was of great value for understanding how this species adapted to the saline-alkali environment and for the rational development and use of saline-alkali soils. In this study, high-throughput sequencing technology was used to investigate the diversity characteristics and distribution patterns of soil bacterial communities in the rhizosphere of S.glauca-dominated communities in the Hetao Irrigation Distract, Inner Mongolia, China. The relationships among bacterial characteristics, soil physicochemical properties and vegetation in four sampling sites were analyzed. The soil bacterial communities in the rhizosphere of S. glauca-dominated communities were mainly composed of 16 phyla (i.e., Proteobacteria, Actinobacteria, Bacteroidetes, Gemmatimonadetes, Chloroflexi, Acidobacteria, Firmicutes, Planctomycetes, Deinococcus-Thermus, Verrucomicrobia, Saccharibacteria, Cyanobacteria, Nitrospirae, JL-ETNP-Z39, Parcubacteria and Chlorobi), and these populations accounted for more than 99% of the total bacterial community. At the genus level, the main bacterial communities comprised Halomonas, Nitriliruptor, Euzebya and Pelagibius, which accounted for 15.70% of the total bacterial community. An alpha diversity analysis indicated that the richness and diversity of rhizosphere soil bacteria differed significantly among the sampling sites, and the bacterial richness and diversity indices of severe saline-alkali land were higher than those of light and moderate saline-alkali land. The principal component analysis (PCA) and linear discriminant analysis effect size (LEfSe) showed significant differences in the species composition of the rhizosphere soil bacterial community among different sampling sites. A correlation analysis showed that the number of bacterial species exhibited the highest correlation with the soil water content (SWC). The richness and evenness indices were significantly correlated with the SWC and SO4 2-, K+ and Mg2+ concentrations. The electrical conductivity (EC), soluble ions (Na+, CO3 2- + HCO3 -, K+, Ca2+, Mg2+, and SO4 2+), SWC and vegetation coverage (VC) were the main drivers affecting the changes in its community structure. The bacterial community in the rhizosphere of S. glauca enhanced the adaptability of S. glauca to saline-alkali environment by participating in the cycling process of nutrient elements, the decomposition of organic matter and the production of plant growth regulating substances. These results provided a theoretical reference for further study on the relationship among rhizosphere soil microorganisms and salt tolerance in halophytes.

Single-cell transcriptomic analyses of mouse idh1 mutant growth plate chondrocytes reveal distinct cell populations responsible for longitudinal growth and enchondroma formation.

Enchondromas are a common tumor in bone that can occur as multiple lesions in enchondromatosis, which is associated with deformity of the effected bone. These lesions harbor mutations in IDH and driving expression of a mutant Idh1 in Col2 expressing cells in mice causes an enchondromatosis phenotype. In this study we compared growth plates from E18.5 mice expressing a mutant Idh1 with control littermates using single cell RNA sequencing. Data from Col2 expressing cells were analyzed using UMAP and RNA pseudo-time analyses. A unique cluster of cells was identified in the mutant growth plates that expressed genes known to be upregulated in enchondromas. There was also a cluster of cells that was underrepresented in the mutant growth plates that expressed genes known to be important in longitudinal bone growth. Immunofluorescence showed that the genes from the unique cluster identified in the mutant growth plates were expressed in multiple growth plate anatomic zones, and pseudo-time analysis also suggested these cells could arise from multiple growth plate chondrocyte subpopulations. This data identifies subpopulations of cells in control and mutant growth plates, and supports the notion that a mutant Idh1 alters the subpopulations of growth plate chondrocytes, resulting a subpopulation of cells that become enchondromas at the expense of other populations that contribute to longitudinal growth.

An antioxidant hydrogel dressing with wound pH indication function prepared based on silanized bacterial nanocellulose crosslinked with beet red pigment extract.

Maintaining wound moisture and monitoring of infection are crucial aspects of chronic wound treatment. The development of a pH-sensitive functional hydrogel dressing is an effective approach to monitor, protect, and facilitate wound healing. In this study, beet red pigment extract (BRPE) served as a native and efficient pH indicator by being grafted into silane-modified bacterial nanocellulose (BNC) to prepare a pH-sensitive wound hydrogel dressing (S-g-BNC/BRPE). FTIR confirmed the successful grafting of BRPE into the BNC matrix. The S-g-BNC/BRPE showed superior mechanical properties (0.25 MPa), swelling rate (1251 % on average), and hydrophilic properties (contact angle 21.83°). The composite exhibited a notable color change as the pH changed between 4.0 and 9.0. It appeared purple-red when the pH ranged from 4.0 to 6.0, and appeared light pink at pH 7.0 and 7.4, and appeared ginger-yellow at pH 8.0 and 9.0. Subsequently, the antioxidant activity and cytotoxicity of the composite was evaluated, its DPPH·, ABTS+, ·OH scavenging rates were 32.33 %, 19.31 %, and 30.06 %, respectively, and the cytotoxicity test clearly demonstrated the safety of the dressing. The antioxidant hydrogel dressing, fabricated with a cost-effective and easy method, not only showed excellent biocompatibility and dressing performance but could also indicated the wound state based on pH changes.

Simultaneous detection of dental caries and fissure sealant in intraoral photos by deep learning: a pilot study.

BACKGROUND: Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous detection of dental caries and fissure sealants in intraoral photos. METHODS: A total of 1020 intraoral photos were collected from 762 volunteers. Teeth, caries and sealants were annotated by two endodontists using the LabelMe tool. ToothNet was developed by modifying the YOLOX framework for simultaneous detection of caries and fissure sealants. The area under curve (AUC) in the receiver operating characteristic curve (ROC) and free-response ROC (FROC) curves were used to evaluate model performance in the following aspects: (i) classification accuracy of detecting dental caries and fissure sealants from a photograph (image-level); and (ii) localization accuracy of the locations of predicted dental caries and fissure sealants (tooth-level). The performance of ToothNet and dentist with 1year of experience (1-year dentist) were compared at tooth-level and image-level using Wilcoxon test and DeLong test. RESULTS: At the image level, ToothNet achieved an AUC of 0.925 (95% CI, 0.880-0.958) for caries detection and 0.902 (95% CI, 0.853-0.940) for sealant detection. At the tooth level, with a confidence threshold of 0.5, the sensitivity, precision, and F1-score for caries detection were 0.807, 0.814, and 0.810, respectively. For fissure sealant detection, the values were 0.714, 0.750, and 0.731. Compared with ToothNet, the 1-year dentist had a lower F1 value (0.599, p < 0.0001) and AUC (0.749, p < 0.0001) in caries detection, and a lower F1 value (0.727, p = 0.023) and similar AUC (0.829, p = 0.154) in sealant detection. CONCLUSIONS: The proposed deep learning model achieved multi-task simultaneous detection in intraoral photos and showed good performance in the detection of dental caries and fissure sealants. Compared with 1-year dentist, the model has advantages in caries detection and is equivalent in fissure sealants detection.

Bulk Segregant Analysis Sequencing and RNA-Seq Analyses Reveal Candidate Genes Associated with Sepal Color Phenotype of Eggplant (Solanum melongena L.).

Eggplant is a highly significant vegetable crop and extensively cultivated worldwide. Sepal color is considered one of the major commercial traits of eggplant. Eggplant sepals develop from petals, and sepals have the ability to change color by accumulating anthocyanins, but whether the eggplants in sepal and their biosynthetic pathways are the same as those in petals is not known. To date, little is known about the underlying mechanisms of sepal color formation. In this study, we performed bulked segregant analysis and transcriptome sequencing using eggplant sepals and obtained 1,452,898 SNPs and 182,543 InDel markers, respectively, as well as 123.65 Gb of clean data using transcriptome sequencing. Through marker screening, the genes regulating eggplant sepals were localized to an interval of 2.6 cM on chromosome 10 by bulked segregant analysis sequencing and transcriptome sequencing and co-analysis, combined with screening of molecular markers by capillary electrophoresis. Eight possible candidate genes were then screened to further interpret the regulatory incentives for the eggplant sepal color.

Modeling Nitrogen Fate and Water and Nitrogen Use Efficiencies under Different Greenhouse Vegetable Production Systems Using the WHCNS-Veg Model.

Quantitative evaluation of the effects of diverse greenhouse vegetable production systems (GVPS) on vegetable yield, soil water consumption, and nitrogen (N) fates could provide a scientific basis for identifying optimum water and fertilizer management practices for GVPS. This research was conducted from 2013 to 2015 in a greenhouse vegetable field in Quzhou County, North China. Three production systems were designed: conventional (CON), integrated (INT), and organic (ORG) systems. The WHCNS-Veg model was employed for simulating vegetable growth, water dynamics, and fates of N, as well as water and N use efficiencies (WUE and NUE) for four continuous growing seasons. The simulation results revealed that nitrate leaching and gaseous N emissions constituted the predominant N loss within GVPS, which separately accounted for 11.5-59.4% and 6.0-21.1% of the N outputs. The order of vegetable yield, N uptake, WUE, and NUE under different production systems was ORG > INT > CON, while the order of nitrate leaching and gaseous N loss was CON > INT > ORG. Compared to CON, ORG exhibited a significant increase in yield, N uptake, WUE, and NUE by 24.6%, 24.2%, 26.1%, and 89.7%, respectively, alongside notable reductions in nitrate leaching and gaseous N loss by 67.7% and 63.2%, respectively. The ORG system should be recommended to local farmers.

Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One.

Graph neural networks (GNN) suffer from severe inefficiency due to the exponential growth of node dependency with the increase of layers. It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming. To address this problem, we propose to decouple a multi-layer GNN as multiple simple modules for more efficient training, which is comprised of classical forward training (FT) and designed backward training (BT). Under the proposed framework, each module can be trained efficiently in FT by stochastic algorithms without distortion of graph information owing to its simplicity. To avoid the only unidirectional information delivery of FT and sufficiently train shallow modules with the deeper ones, we develop a backward training mechanism that makes the former modules perceive the latter modules, inspired by the classical backward propagation algorithm. The backward training introduces the reversed information delivery into the decoupled modules as well as the forward information delivery. To investigate how the decoupling and greedy training affect the representational capacity, we theoretically prove that the error produced by linear modules will not accumulate on unsupervised tasks in most cases. The theoretical and experimental results show that the proposed framework is highly efficient with reasonable performance, which may deserve more investigation.

Green manure removal with reduced nitrogen improves saline-alkali soil organic carbon storage in a wheat-green manure cropping system.

The incorporation of green manure into cropping systems is a potential strategy for sequestering soil carbon (C), especially in saline-alkali soil. Yet, there are still unknown about the substitution impacts of green manure on nitrogen (N) fertilizer in wheat-green manure multiple cropping system. Herein, a five-year field experiment was performed to determine the impact of three levels of N fertilizer inputs [i.e., N fertilizer reduced by 0 % (100N), 10 % (90 N), and 20 % (80 N)] with aboveground biomass of green manure removal (0GM) and return (100GM) on soil organic carbon (SOC) storage and its primary determinants. The results demonstrated that no significant interaction on SOC storage was detected between green manure and N fertilizer management. 80 N enhanced SOC storage in bulk soil by 7.4 and 13.2 % in 0-20 cm soil depth relative to 100 N and 90 N (p < 0.05). Regardless of N fertilizer levels, compared with 100GM, 0GM increased SOC storage in bulk soil by 14.2-34.6 % in 0-40 cm soil depth (p < 0.05). This was explained by an increase in soil macro-aggregates (>2 and 0.25-2 mm) proportion contributing to SOC physical protection. Meanwhile, the improvement of SOC storage under 0GM was due to the decrease of soil C- and N-acquisition enzyme activities, and microbial resource limitation. Alternatively, the variation partitioning analyses (VPA) results further suggested that C- and N-acquisition enzyme activities, as well as microbial resource limitation were the most important factors for SOC storage. The findings highlighted those biological factors played a dominant role in SOC accumulation compared to physical factors. The aboveground biomass of green manure removal with N fertilizer reduced by 20 % is a viable option to enhance SOC storage in a wheat-green manure multiple cropping system.

Excitation characteristics of circumferential SH guided waves in steel pipes generated by EMATs with few-cycle PPM.

Circumferential Shear Horizontal (CSH) guided waves provide an effective method for detecting defects like axial cracks and corrosion in pipes. Periodic Permanent Magnet Electromagnetic Acoustic Transducers (PPM EMATs) are typically used to generate CSH guided waves. However, there is an offset problem to which little attention has been paid. The offset problem refers to the offset of the center (position of maximum energy) of the operating region caused by the variation in the peak frequency of the spatial spectra of PPM with 2 or fewer cycles. Furthermore, the excitability of guided waves is one of the factors that needs to be considered when selecting the excitation parameters of EMATs, but there are still some studies that have not sufficiently addressed this issue. In this paper, the offset problem and the excitability of CSH guided waves were investigated. Firstly, by obtaining the operating regions corresponding to PPM with different cycles, the cause and influences of the offset problem were studied. The results show that the offset in the peak frequency of the spatial spectrum of PPM is the fundamental reason causing the offset problem, and it not only leads to incorrect prediction of the excitation efficiency of guided waves but also affects the selection of the excitation parameters of EMATs. Secondly, finite element simulations and experiments were performed to assess the influence of the excitability on the excitation efficiency of the CSH0 and CSH1 modes in pipes. By analyzing the simulation and experimental results of 2-cycle PPM, as well as the simulation results for PPM with 1 to 5 cycles, the impact of the excitability on the CSH1 mode was confirmed from two perspectives. The final conclusion indicates that an accurate prediction of the amplitudes of CSH guided waves with different modes is only possible through a comprehensively consideration of the operating region of EMAT and the excitability of guided waves.

A novel method for colposcopic shunting in HPV-positive women: Quantitative detection of HPV E7 oncoprotein.

The objective of the study was to evaluate the clinical application potential of quantitatively detecting human papillomavirus (HPV) E7 oncoprotein in HPV-positive women, with the goal of detecting potential high-grade cervical squamous intraepithelial lesions (HSIL) and cervical cancer improving the accuracy of colposcopic shunting in these patients.HPV-positive women (N = 611) were selected for quantitatively detecting HPV E7 protein levels by magnetic particle-based chemiluminescence immunoassay before colposcopy. Receiver operating characteristic (ROC) curve analysis was performed (n = 400) to determine diagnostic detection thresholds for HPV E7 oncoprotein. ThinPrep cytology test (TCT) and Aptima HPV E6/E7 mRNA analysis were also performed (n = 211). The diagnostic performance of these three diagnostic methods in detecting HSIL and cervical cancer was compared with the gold standard of pathological diagnosis. The area under the ROC curve was 0.724. The diagnostic detection threshold of HPV E7 oncoprotein was ≥10.88 ng/mL. The sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and Youden index of HPV E7 oncoprotein for the identification of HSIL and cervical cancer were 78.7 %, 77.9 %, 72.2 %, 83.3 %, and 56.6 %, respectively, which were higher than those of TCT and HPV E6/E7 mRNA.The results indicate that quantitative detection of HPV E7 oncoprotein can effectively shunt HPV-positive women and reduce unnecessary colposcopy and biopsy. It can detect potential HSIL and cervical cancer in a timely manner and prevent high-risk patients from missing diagnosis.

A spatially adaptive regularization based three-dimensional reconstruction network for quantitative susceptibility mapping.

Objective.Quantitative susceptibility mapping (QSM) is a new imaging technique for non-invasive characterization of the composition and microstructure ofin vivotissues, and it can be reconstructed from local field measurements by solving an ill-posed inverse problem. Even for deep learning networks, it is not an easy task to establish an accurate quantitative mapping between two physical quantities of different units, i.e. field shift in Hz and susceptibility value in ppm for QSM.Approach. In this paper, we propose a spatially adaptive regularization based three-dimensional reconstruction network SAQSM. A spatially adaptive module is specially designed and a set of them at different resolutions are inserted into the network decoder, playing a role of cross-modality based regularization constraint. Therefore, the exact information of both field and magnitude data is exploited to adjust the scale and shift of feature maps, and thus any information loss or deviation occurred in previous layers could be effectively corrected. The network encoding has a dynamic perceptual initialization, which enables the network to overcome receptive field intervals and also strengthens its ability to detect features of various sizes.Main results. Experimental results on the brain data of healthy volunteers, clinical hemorrhage and simulated phantom with calcification demonstrate that SAQSM can achieve more accurate reconstruction with less susceptibility artifacts, while perform well on the stability and generalization even for severe lesion areas.Significance. This proposed framework may provide a valuable paradigm to quantitative mapping or multimodal reconstruction.