HDTR-Net: A Real-Time High-Definition Teeth Restoration Network for Arbitrary Talking Face Generation Methods

Talking Face Generation (TFG) aims to reconstruct facial movements to achieve high natural lip movements from audio and facial features that are under potential connections. Existing TFG methods have made significant advancements to produce natural and realistic images. However, most work rarely takes visual quality into consideration. It is challenging to ensure lip synchronization while avoiding visual quality degradation in cross-modal generation methods. To address this issue, we propose a universal High-Definition Teeth Restoration Network, dubbed HDTR-Net, for arbitrary TFG methods. HDTR-Net can enhance teeth regions at an extremely fast speed while maintaining synchronization, and temporal consistency. In particular, we propose a Fine-Grained Feature Fusion (FGFF) module to effectively capture fine texture feature information around teeth and surrounding regions, and use these features to fine-grain the feature map to enhance the clarity of teeth. Extensive experiments show that our method can be adapted to arbitrary TFG methods without suffering from lip synchronization and frame coherence. Another advantage of HDTR-Net is its real-time generation ability. Also under the condition of high-definition restoration of talking face video synthesis, its inference speed is $300\%$ faster than the current state-of-the-art face restoration based on super-resolution.Comment: 15pages, 6 figures, PRCV202

Food resources for Spoon-billed Sandpipers (<i>Calidris pygmaea</i>) in the mudflats of Leizhou Bay, southern China

Leizhou Bay in Guangdong Province is the most important wintering site in China for the critically endangered Spoon-billed Sandpipers (Calidris pygmaea). As food is usually a strong predictor of presence, in the winters of 2019-2022 we studied arthropod food resources and diet on the intertidal mudflats at the Tujiao and Hebei mudflats in Leizhou Bay. In December 2020, using a sampling device that encloses mobile epibenthic prey before the human sampler would disturb them in shallow pools, we visited 34 stations in their core foraging area at Tujiao. A total of 15 mobile benthic species were identified, including 13 arthropod and 2 fish species, with a total density of 106 animals/m2 (range= 0.2-48 animals/m2), with the lengths of the animals ranging from 1-19 mm. Two amphipod and one cumacean species contributed 85%. On the basis of photographs of foraging during low tide in 2019-2022, the visibly ingested prey items appeared to mainly consist of small shrimp, but also included crabs and fish. At 27 mm (compared with the 22 mm long bill of Spoon-billed Sandpipers) the average visibly ingested prey showed a strong size bias. Among the measured environmental covarying factors (sediment pH, salinity, TOC content, median particle size and distance from the seawall etc.) potentiually affecting the mobile epibenthic prey in shallow pools, only distance from the seawall was significantly and negatively correlated. Densities were higher within 1 km of the seawall (126 animals/m2) than further offshore (69 animals/m2). This may relate to the mangrove forests growing in abundance near the seawall providing released minerals, nutrients, bacterial production and diatoms for the benthic community in the adjacent mudflats. However, the potential negative impact of artificial mangrove expansion in Leizhou mudflats need to be carefully monitored and assessed to balance both mangrove and Spoon-billed Sandpipers conservation

Identification of molecular pattern and prognostic risk model based on ligand-receptor pairs in liver cancer

IntroductionThe tumor microenvironment of hepatocellular carcinoma is composed of multiple cells, and the interactive communication between cells drives tumor progression and characterizes the tumor. Communication between cells is mainly achieved through signal transduction between receptor ligands, and the rise of single-cell technology has made it possible to analyze the communication network between cells.MethodsWe applied a train of bioinformatic techniques and in vitro experiments. We analyzed the composition of the microenvironment of liver cancer by combining single-cell sequencing data and transcriptome sequencing data from liver cancer to construct molecular typing and risk models for LRs. Then, we analyzed association of it with prognosis, mutation, KEGG, tumor microenvironment (TME), immune infiltration, tumor mutational burden (TMB) and drug sensitivity in liver cancer. qPCR and was used to identify SLC1A5 expression in LIHC cell lines and CCK8, transwell and cell colony formation were performed to validate the function of SLC1A5. Meanwhile, we also performed polarization of macrophages.ResultsIn this experiment, we found that liver cancer tissues are rich in immune and mesenchymal cells, and there is extensive signaling between individual cells, so we constructed molecular typing and risk models for LRs. Combining clinical data revealed significant differences in clinical characteristics, prognosis and mutated genes between the molecular typing of receptor-ligand pairs, as well as in sensitivity to drugs; similarly, there were significant prognostic differences between the risk models. There were also notable differences in activated signaling pathways, infiltrating immune cells and immune subtypes. Subsequently, we used siRNA to knock down SLC1A5 in hepatocellular carcinoma cells and found that cell proliferation, migration and invasion were diminished.ConclusionsIn conclusion, our LRs model may become a marker to guide clinical treatment and prognosis

Overexpression of CDC25C affects the cell cycle of ovarian granulosa cells from adult and young goats

Background: CDC25 is a dual-specificity phosphatase that was first identified in the yeast Schizosaccharomyces pombe as a cell cycle-defective mutant. Although CDC25 is involved in the cell cycle of ovarian granulosa cells, the CDC25 signaling pathway has not been clarified fully. To explore the role of CDC25C in the cell cycle of goat ovarian granulosa cells, a CDC25C-overexpressing vector, pCMV-HA-CDC25C, was constructed and transfected into granulosa cells from adult and young white goats from Jiangsu Nantong. RT-PCR was used to measure CDC25C, CDK1, and WEE1 gene expression levels, and flow cytometry was used to distinguish ovarian granulosa cells in different phases of the cell cycle. Progesterone and estradiol levels in transfected ovarian granulosa cells were also measured. Results: In adult goat follicular granulosa cells transfected with pCMV-HA-CDC25C, CDC25C expression increased significantly, which greatly increased the relative gene expression levels of both CDK1 and WEE1. Additionally, progesterone and estradiol levels were increased in goat follicular granulosa cells overexpressing CDC25C. And the cell cycle results showed that transfection of pCMV-HA-CDC25C leads to a higher proportion of cells in S phase compared to the no vector-transfected groups. Conclusions: The results of this study indicated that the overexpression of CDC25C may increase the gene expression levels of both WEE1 and CDK1 in S phase and accelerate the transition of cells from G1 phase to S phase

A nomogram combining thoracic CT and tumor markers to predict the malignant grade of pulmonary nodules ≤3 cm in diameter

BackgroundWith the popularity of computed tomography (CT) of the thorax, the rate of diagnosis for patients with early-stage lung cancer has increased. However, distinguishing high-risk pulmonary nodules (HRPNs) from low-risk pulmonary nodules (LRPNs) before surgery remains challenging.MethodsA retrospective analysis was performed on 1064 patients with pulmonary nodules (PNs) admitted to the Qilu Hospital of Shandong University from April to December 2021. Randomization of all eligible patients to either the training or validation cohort was performed in a 3:1 ratio. Eighty-three PNs patients who visited Qianfoshan Hospital in the Shandong Province from January through April of 2022 were included as an external validation. Univariable and multivariable logistic regression (forward stepwise regression) were used to identify independent risk factors, and a predictive model and dynamic web nomogram were constructed by integrating these risk factors.ResultsA total of 895 patients were included, with an incidence of HRPNs of 47.3% (423/895). Logistic regression analysis identified four independent risk factors: the size, consolidation tumor ratio, CT value of PNs, and carcinoembryonic antigen levels in blood. The area under the ROC curves was 0.895, 0.936, and 0.812 for the training, internal validation, and external validation cohorts, respectively. The Hosmer-Lemeshow test demonstrated excellent calibration capability, and the fit of the calibration curve was good. DCA has shown the nomogram to be clinically useful.ConclusionThe nomogram performed well in predicting the likelihood of HRPNs. In addition, it identified HRPNs in patients with PNs, achieved accurate treatment with HRPNs, and is expected to promote their rapid recovery