TalkingStyle: Personalized Speech-Driven 3D Facial Animation with Style Preservation.

It is a challenging task to create realistic 3D avatars that accurately replicate individuals' speech and unique talking styles for speech-driven facial animation. Existing techniques have made remarkable progress but still struggle to achieve lifelike mimicry. This paper proposes "TalkingStyle", a novel method to generate personalized talking avatars while retaining the talking style of the person. Our approach uses a set of audio and animation samples from an individual to create new facial animations that closely resemble their specific talking style, synchronized with speech. We disentangle the style codes from the motion patterns, allowing our method to associate a distinct identifier with each person. To manage each aspect effectively, we employ three separate encoders for style, speech, and motion, ensuring the preservation of the original style while maintaining consistent motion in our stylized talking avatars. Additionally, we propose a new style-conditioned transformer decoder, offering greater flexibility and control over the facial avatar styles. We comprehensively evaluate TalkingStyle through qualitative and quantitative assessments, as well as user studies demonstrating its superior realism and lip synchronization accuracy compared to current state-of-the-art methods. To promote transparency and further advancements in the field, we also make the source code publicly available at https://github.com/wangxuanx/TalkingStyle.

SERPINE2 promotes liver cancer metastasis by inhibiting c-Cbl-mediated EGFR ubiquitination and degradation.

BACKGROUND: Liver cancer is a malignancy with high morbidity and mortality rates. Serpin family E member 2 (SERPINE2) has been reported to play a key role in the metastasis of many tumors. In this study, we aimed to investigate the potential mechanism of SERPINE2 in liver cancer metastasis. METHODS: The Cancer Genome Atlas database (TCGA), including DNA methylation and transcriptome sequencing data, was utilized to identify the crucial oncogene associated with DNA methylation and cancer progression in liver cancer. Data from the TCGA and RNA sequencing for 94 pairs of liver cancer tissues were used to explore the correlation between SERPINE2 expression and clinical parameters of patients. DNA methylation sequencing was used to detect the DNA methylation levels in liver cancer tissues and cells. RNA sequencing, cytokine assays, immunoprecipitation (IP) and mass spectrometry (MS) assays, protein stability assays, and ubiquitination assays were performed to explore the regulatory mechanism of SERPINE2 in liver cancer metastasis. Patient-derived xenografts and tumor organoid models were established to determine the role of SERPINE2 in the treatment of liver cancer using sorafenib. RESULTS: Based on the public database screening, SERPINE2 was identified as a tumor promoter regulated by DNA methylation. SERPINE2 expression was significantly higher in liver cancer tissues and was associated with the dismal prognosis in patients with liver cancer. SERPINE2 promoted liver cancer metastasis by enhancing cell pseudopodia formation, cell adhesion, cancer-associated fibroblast activation, extracellular matrix remodeling, and angiogenesis. IP/MS assays confirmed that SERPINE2 activated epidermal growth factor receptor (EGFR) and its downstream signaling pathways by interacting with EGFR. Mechanistically, SERPINE2 inhibited EGFR ubiquitination and maintained its protein stability by competing with the E3 ubiquitin ligase, c-Cbl. Additionally, EGFR was activated in liver cancer cells after sorafenib treatment, and SERPINE2 knockdown-induced EGFR downregulation significantly enhanced the therapeutic efficacy of sorafenib against liver cancer. Furthermore, we found that SERPINE2 knockdown also had a sensitizing effect on lenvatinib treatment. CONCLUSIONS: SERPINE2 promoted liver cancer metastasis by preventing EGFR degradation via c-Cbl-mediated ubiquitination, suggesting that inhibition of the SERPINE2-EGFR axis may be a potential target for liver cancer treatment.

Rethinking Object Saliency Ranking: A Novel Whole-Flow Processing Paradigm.

Existing salient object detection methods are capable of predicting binary maps that highlight visually salient regions. However, these methods are limited in their ability to differentiate the relative importance of multiple objects and the relationships among them, which can lead to errors and reduced accuracy in downstream tasks that depend on the relative importance of multiple objects. To conquer, this paper proposes a new paradigm for saliency ranking, which aims to completely focus on ranking salient objects by their "importance order". While previous works have shown promising performance, they still face ill-posed problems. First, the saliency ranking ground truth (GT) orders generation methods are unreasonable since determining the correct ranking order is not well-defined, resulting in false alarms. Second, training a ranking model remains challenging because most saliency ranking methods follow the multi-task paradigm, leading to conflicts and trade-offs among different tasks. Third, existing regression-based saliency ranking methods are complex for saliency ranking models due to their reliance on instance mask-based saliency ranking orders. These methods require a significant amount of data to perform accurately and can be challenging to implement effectively. To solve these problems, this paper conducts an in-depth analysis of the causes and proposes a whole-flow processing paradigm of saliency ranking task from the perspective of "GT data generation", "network structure design" and "training protocol". The proposed approach outperforms existing state-of-the-art methods on the widely-used SALICON set, as demonstrated by extensive experiments with fair and reasonable comparisons. The saliency ranking task is still in its infancy, and our proposed unified framework can serve as a fundamental strategy to guide future work. The code and data will be available at https://github.com/MengkeSong/Saliency-Ranking-Paradigm.

FineStyle: Semantic-Aware Fine-Grained Motion Style Transfer with Dual Interactive-Flow Fusion.

We present FineStyle, a novel framework for motion style transfer that generates expressive human animations with specific styles for virtual reality and vision fields. It incorporates semantic awareness, which improves motion representation and allows for precise and stylish animation generation. Existing methods for motion style transfer have all failed to consider the semantic meaning behind the motion, resulting in limited controls over the generated human animations. To improve, FineStyle introduces a new cross-modality fusion module called Dual Interactive-Flow Fusion (DIFF). As the first attempt, DIFF integrates motion style features and semantic flows, producing semantic-aware style codes for fine-grained motion style transfer. FineStyle uses an innovative two-stage semantic guidance approach that leverages semantic clues to enhance the discriminative power of both semantic and style features. At an early stage, a semantic-guided encoder introduces distinct semantic clues into the style flow. Then, at a fine stage, both flows are further fused interactively, selecting the matched and critical clues from both flows. Extensive experiments demonstrate that FineStyle outperforms state-of-the-art methods in visual quality and controllability. By considering the semantic meaning behind motion style patterns, FineStyle allows for more precise control over motion styles. Source code and model are available on https://github.com/XingliangJin/Fine-Style.git.

FXR Maintains the Intestinal Barrier and Stemness by Regulating CYP11A1-Mediated Corticosterone Synthesis in Biliary Obstruction Diseases.

Biliary obstruction diseases are often complicated by an impaired intestinal barrier, which aggravates liver injury. Treatment of the intestinal barrier is often neglected. To investigate the mechanism by which intestinal bile acid deficiency mediates intestinal barrier dysfunction after biliary obstruction and identify a potential therapeutic modality, we mainly used a bile duct ligation (BDL) mouse model to simulate biliary obstruction and determine the important role of the bile acid receptor FXR in maintaining intestinal barrier function and stemness. Through RNA-seq analysis of BDL and sham mouse crypts and qRT-PCR performed on intestinal epithelial-specific Fxr knockout (FxrΔIEC) and wild-type mouse crypts, we found that FXR might maintain intestinal stemness by regulating CYP11A1 expression. Given the key role of CYP11A1 during glucocorticoid production, we also found that FXR activation could promote intestinal corticosterone (CORT) synthesis by ELISA. Intestinal organoid culture showed that an FXR agonist or corticosterone increased crypt formation and organoid growth. Further animal experiments showed that corticosterone gavage treatment could maintain intestinal barrier function and stemness, decrease LPS translocation, and attenuate liver injury in BDL mice. Our study hopefully provides a new theoretical basis for the prevention of intestinal complications and alleviation of liver injury after biliary obstruction.

Graph Diffusion Convolutional Network for Skeleton Based Semantic Recognition of Two-Person Actions.

Graph Convolutional Networks (GCNs) have successfully boosted skeleton-based human action recognition. However, existing GCN-based methods mostly cast the problem as separated person's action recognition while ignoring the interaction between the action initiator and the action responder, especially for the fundamental two-person interactive action recognition. It is still challenging to effectively take into account the intrinsic local-global clues of the two-person activity. Additionally, message passing in GCN depends on adjacency matrix, but skeleton-based human action recognition methods tend to calculate the adjacency matrix with the fixed natural skeleton connectivity. It means that messages can only travel along a fixed path at different layers of the network or in different actions, which greatly reduces the flexibility of the network. To this end, we propose a novel graph diffusion convolutional network for skeleton based semantic recognition of two-person actions by embedding the graph diffusion into GCNs. At technical fronts, we dynamically construct the adjacency matrix based on practical action information, so that we can guide the message propagation in a more meaningful way. Simultaneously, we introduce the frame importance calculation module to conduct dynamic convolution, so that we can avoid the negative effect caused by the traditional convolution, wherein the shared weights may fail to capture key frames or be affected by noisy frames. Besides, we comprehensively leverage the multidimensional features related to joints' local visual appearances, global spatial relationship and temporal coherency, and for different features, different metrics are designed to measure the similarity underlying the corresponding real physical law of the motions. Moreover, extensive experiments and comprehensive evaluations on four public large-scale datasets (NTU-RGB+D 60, NTU-RGB+D 120, Kinetics-Skeleton 400, and SBU-Interaction) demonstrate that our method outperforms the state-of-the-art methods.

Effects of Velocity-Based versus Percentage-Based Resistance Training on Explosive Neuromuscular Adaptations and Anaerobic Power in Sport-College Female Basketball Players.

The purpose of this study was to compare the impact of velocity-based resistance training (VBRT) and percentage-based resistance training (PBRT) on anaerobic ability, sprint performance, and jumping ability. Eighteen female basketball players from a Sport College were randomly divided into two groups: VBRT (n = 10) and PBRT (n = 8). The six-week intervention consisted of two sessions per week of free-weight back squats with linear periodization from 65% to 95%1RM. In PBRT, the weights lifted were fixed based on 1RM percentage, while in VBRT, the weights were adjusted based on individualized velocity profiles. The T-30m sprint time, relative power of countermovement jump (RP-CMJ), and Wingate test were evaluated. The Wingate test assessed peak power (PP), mean power (MP), fatigue index (FI), maximal velocity (Vmax), and total work (TW). Results showed that VBRT produced a very likely improvement in RP-CMJ, Vmax, PP, and FI (Hedges' g = 0.55, 0.93, 0.68, 0.53, respectively, p < 0.01). On the other hand, PBRT produced a very likely improvement in MP (Hedges' g = 0.38) and TW (Hedges' g = 0.45). Although VBRT showed likely favorable effects in RP-CMJ, PP, and Vmax compared to PBRT (p < 0.05 for interaction effect), PBRT produced greater improvements in MP and TW (p < 0.05 for interaction effect). In conclusion, PBRT may be more effective in maintaining high-power velocity endurance, while VBRT has a greater impact on explosive power adaptations.

Biochar combined with organic and inorganic fertilizers promoted the rapeseed nutrient uptake and improved the purple soil quality.

Biochar is a kind of organic matter that can be added into soil to improve soil quality. To study the effect of biochar combined with organic and inorganic fertilizers on rapeseed growth and purple soil fertility and microbial community, a completely randomized block design was designed with three levels of biochar (B0: no biochar, B1: low-rate biochar, B2: high-rate biochar); two levels of inorganic fertilizers (F1: low-rate inorganic fertilizer; F2: high-rate inorganic fertilizer); and two levels of organic fertilizers (M1: no organic fertilizer; M2: with organic fertilizer). All combinations were repeated three times. The combined application of biochar and organic and inorganic fertilizers could improve soil pH, soil fertility and soil microbial community richness: The pH of B1F2M1 increased 0.41 compared with the control, the nitrogen, phosphorus and potassium content increased by 103.95, 117.88, and 99.05%. Meanwhile, soil microbial community richness was also improved. Our research showed that biochar could promote the Nutrient Uptake of rapeseed, and the combined application of biochar with organic and inorganic fertilizers could improve soil fertility and increase microbial diversity. Low-rate biochar combined with organic fertilizer and low-rate inorganic fertilizer was the most suitable application mode in rapeseed production in purple soil area of Southwest China.

Improving RGB-D Salient Object Detection via Modality-Aware Decoder.

Most existing RGB-D salient object detection (SOD) methods are primarily focusing on cross-modal and cross-level saliency fusion, which has been proved to be efficient and effective. However, these methods still have a critical limitation, i.e., their fusion patterns - typically the combination of selective characteristics and its variations, are too highly dependent on the network's non-linear adaptability. In such methods, the balances between RGB and D (Depth) are formulated individually considering the intermediate feature slices, but the relation at the modality level may not be learned properly. The optimal RGB-D combinations differ depending on the RGB-D scenarios, and the exact complementary status is frequently determined by multiple modality-level factors, such as D quality, the complexity of the RGB scene, and degree of harmony between them. Therefore, given the existing approaches, it may be difficult for them to achieve further performance breakthroughs, as their methodologies belong to some methods that are somewhat less modality sensitive. To conquer this problem, this paper presents the Modality-aware Decoder (MaD). The critical technical innovations include a series of feature embedding, modality reasoning, and feature back-projecting and collecting strategies, all of which upgrade the widely-used multi-scale and multi-level decoding process to be modality-aware. Our MaD achieves competitive performance over other state-of-the-art (SOTA) models without using any fancy tricks in the decoder's design. Codes and results will be publicly available at https://github.com/MengkeSong/MaD.

Antihypertension Nanoblockers Increase Intratumoral Perfusion of Sequential Cytotoxic Nanoparticles to Enhance Chemotherapy Efficacy against Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC), one of the worst prognosis types of tumors, is characterized by dense extracellular matrix, which compresses tumor vessels and forms a physical barrier to inhibit therapeutic drug penetration and efficacy. Herein, losartan, an antihypertension agent, is applied as a tumor stroma modulator and developed into a nanosystem. A series of lipophilic losartan prodrugs are constructed by esterification of the hydroxyl group on losartan to fatty acids. Based on the self-assembly ability and hydrodynamic diameter, the losartan-linoleic acid conjugate is selected for further investigation. To improve the stability in vivo, nanoassemblies are refined with PEGylation to form losartan nanoblocker (Los NB), and administered via intravenous injection for experiments. On murine models of pancreatic cancer, Los NB shows a greater ability to remodel the tumor microenvironment than free losartan, including stromal depletion, vessel perfusion increase, and hypoxia relief. Furthermore, Los NB pretreatment remarkably enhances the accumulation and penetration of 7-ethyl-10-hydroxycamptothecin (SN38)-loaded nanodrugs (SN38 NPs) in tumor tissues. Expectedly, overall therapeutic efficacy of SN38 NPs is significantly enhanced after Los NB pretreatment. Since losartan is one of the most commonly used antihypertension agents, this study may provide a potential for clinical transformation in stroma-rich PDAC treatment.

Asialoglycoprotein Receptor 1 Functions as a Tumor Suppressor in Liver Cancer via Inhibition of STAT3.

Liver cancer is characterized by aggressive growth and high mortality. Asialoglycoprotein receptor 1 (ASGR1), which is expressed almost exclusively in liver cells, is reduced in liver cancer. However, the specific mechanism of ASGR1 function in liver cancer has not been fully elucidated. On the basis of database screening, we identified ASGR1 as a tumor suppressor regulated by DNA methylation. Expression of ASGR1 was downregulated in liver cancer and correlated with tumor size, grade, and survival. Functional gain and loss experiments showed that ASGR1 suppresses the progression of liver cancer in vivo and in vitro. RNA sequencing and mass spectrometry showed that ASGR1 inhibits tyrosine phosphorylation of STAT3 by interacting with Nemo-like kinase (NLK). NLK bound the SH2 domain of STAT3 in an ATP-dependent manner and competed with glycoprotein 130 (GP130), ultimately suppressing GP130/JAK1-mediated phosphorylation of STAT3. ASGR1 altered the binding strength of NLK and STAT3 by interacting with GP130. Furthermore, the domain region of NLK was crucial for binding STAT3 and curbing its phosphorylation. Collectively, these results confirm that ASGR1 suppresses the progression of liver cancer by promoting the binding of NLK to STAT3 and inhibiting STAT3 phosphorylation, suggesting that approaches to activate the ASGR1-NLK axis may be a potential therapeutic strategy in this disease. SIGNIFICANCE: ASGR1 downregulation by DNA methylation facilitates liver tumorigenesis by increasing STAT3 phosphorylation.

The effect of sulfur on the leaching of Cr3+, Cr6+, Pb2+ and Zn2+ from fly ash glass.

This work assessed the capture and subsequent release of potentially harmful Cr(VI), Cr(III), Pb(II) and Zn(II) ions in and from dechlorinated fly ash glass. Differential scanning calorimetry, Fourier transform infrared spectroscopy, scanning electron microscopy - energy dispersive spectroscopy and inductively coupled plasma spectrometry along with other analytical techniques were used to explore the mechanism by which sulfur affected the immobilization and long-term leaching behavior of heavy metals in fly ash glass. Working with a CaO-MgO-Al2O3-SiO2-SO3 system, increasing the sulfur content was found to promote the leaching of Cr but had only a minimal effect on the loss of Pb and Zn. The concentrations of Pb and Zn in the leachate were found to remain at essentially nil over time while the Cr level increased up to 64 h and then decreased. The presence of Sulfur ions degraded the glass network and this promoted the leaching of S2-, Cr3+/Cr6+, Pb2+ and Zn2+. In addition, the S2- ions reacted with Pb2+ and Zn2+ to form needle-shaped and flocculent sulfide precipitates, thus trapping the Pb2+ and Zn2+. Si4+, Ca2+, Al3+ and Fe3+ were also found to migrate into the leaching solution where they combined to form a dendritic flocculent that adsorbed and encapsulated Cr. This phenomenon greatly reduced the concentration of Cr in the leachate. Thus, sulfur prevented the leaching of Cr, Pb and Zn via different mechanisms.

Targeting anillin inhibits tumorigenesis and tumor growth in hepatocellular carcinoma via impairing cytokinesis fidelity.

Targeting cytokinesis can suppress tumor growth by blocking cell division and promoting apoptosis. We aimed to characterize key cytokinesis regulator in hepatocellular carcinoma (HCC) progression, providing insights into identifying promising HCC therapeutic targets. The unbiased bioinformatic screening identified Anillin actin binding protein (ANLN) as a critical cytokinesis regulator involved in HCC development. Functional assay demonstrated that knockdown of ANLN inhibited HCC growth by inducing cytokinesis failure and DNA damage, leading to multinucleation and mitotic catastrophe. Mechanistically, ANLN acts as a scaffold to strengthen interaction between RACGAP1 and PLK1. ANLN promotes PLK1-mediated RACGAP1 phosphorylation and RhoA activation to ensure cytokinesis fidelity. To explore the function of ANLN in HCC tumorigenesis, we hydrodynamically transfected c-Myc and NRAS plasmids into Anln+/+, Anln+/-, and Anln-/- mice through tail vein injection. Hepatic Anln ablation significantly impaired c-Myc/NRAS-driven hepatocarcinogenesis. Moreover, enhanced hepatic polyploidization was observed in Anln ablation mice, manifesting as increasing proportion of cellular and nuclear polyploidy. Clinically, ANLN is upregulated in human HCC tissues and high level of ANLN is correlated with poor patients' prognosis. Additionally, the proportion of cellular polyploidy decreases during HCC progression and ANLN level is significantly correlated with cellular polyploidy proportion in human HCC samples. In conclusion, ANLN is identified as a key cytokinesis regulator contributing to HCC initiation and progression. Our findings revealed a novel mechanism of ANLN in the regulation of cytokinesis to promote HCC tumorigenesis and growth, suggesting targeting ANLN to inhibit cytokinesis may be a promising therapeutic strategy for HCC.

The Relationship Between Atrial Cardiopathy Biomarkers and Prognosis of Patients With Embolic Stroke of Undetermined Source.

Objective: To compare the proportion of atrial cardiopathy in patients with embolic stroke of undetermined source (ESUS) and other non-cardiac strokes, and to evaluate the prognostic value of atrial cardiopathy biomarkers in patients with ESUS. Methods: This retrospective study enrolled patients with ischemic stroke from January 2018 to April 2020 in a single stroke center, and compared the proportion of atrial cardiopathy in (1) ESUS group, (2) large artery atherosclerosis (LAA) group, and (3) small-vessel occlusion (SVO) group. Then, it compared the baseline characteristics between ESUS patients with atrial cardiopathy and cardioembolism (CE) group. In addition, the relationship was compared between the biomarkers of atrial cardiopathy and prognosis in patients with ESUS. Results: In total, 316 patients with ischemic stroke were included that included 105 (33.23%) ESUS, 84 (26.58%) LAA, 73 (23.10%) SVO, and 54 (17.09%) CE. Among these patients, patients with ESUS were younger, and had lower triglyceride, lower low-density lipoprotein than non-ESUS group. The proportion of atrial cardiopathy in ESUS group was higher than LAA group or SVO group (42.86 vs. 17.86 vs. 8.22%, p < 0.001). Compared with non-atrial cardiopathy group, patients with atrial cardiopathy were older, had lower EF value, larger left ventricular diameter, and longer PR interval. Among 105 patients with ESUS, 11 (10.78%) cases died, 32 (31.37%) cases had poor functional outcome (mRS >2). In the multivariable model, the risk factor associated with the death risk of patients with ESUS was N-terminal pro-B-type natriuretic peptide (NT-proBNP) >250 pg/ml [p = 0.025, hazard ratio (HR) = 4.626, 95% CI: 1.212-17.652] after a 1-year follow-up. Conclusions: Atrial cardiopathy is more common in patients with ESUS, and the characteristics of ESUS patients with atrial cardiopathy are similar to those in patients with CE. NT-proBNP >250 pg/ml is related to the risk of death in patients with ESUS.

Culture of patient-derived multicellular clusters in suspended hydrogel capsules for pre-clinical personalized drug screening.

A personalized medication regimen provides precise treatment for an individual and can be guided by pre-clinical drug screening. The economical and high-efficiency simulation of the liver tumor microenvironment (TME) in a drug-screening model has high value yet challenging to accomplish. Herein, we propose a simulation of the liver TME with suspended alginate-gelatin hydrogel capsules encapsulating patient-derived liver tumor multicellular clusters, and the culture of patient-derived tumor organoids(PDTOs) for personalized pre-clinical drug screening. The hydrogel capsule offers a 3D matrix environment with mechanical and biological properties similar to those of the liver in vivo. As a result, 18 of the 28 patient-derived multicellular clusters were successfully cultured as PDTOs. These PDTOs, along with hepatocyte growth factor (HGF) of non-cellular components, preserve stromal cells, including cancer-associated fibroblasts (CAFs) and vascular endothelial cells (VECs). They also maintain stable expression of molecular markers and tumor heterogeneity similar to those of the original liver tumors. Drugs, including cabazitaxel, oxaliplatin, and sorafenib, were tested in PDTOs. The sensitivity of PDTOs to these drugs differs between individuals. The sensitivity of one PDTO to oxaliplatin was validated using magnetic resonance imaging (MRI) and biochemical tests after oxaliplatin clinical treatment of the corresponding patient. Therefore, this approach is promising for economical, accurate, and high-throughput drug screening for personalized treatment.

Automatic Dental Plaque Segmentation Based on Local-to-Global Features Fused Self-Attention Network.

The accurate detection of dental plaque at an early stage will definitely prevent periodontal diseases and dental caries. However, it remains difficult for the current dental examination to accurately recognize dental plaque without using medical dyeing reagent due to the low contrast between dental plaque and healthy teeth. To combat this problem, this paper proposes a novel network enhanced by a self-attention module for intelligent dental plaque segmentation. The key motivation is to directly utilize oral endoscope images (bypassing the need for dyeing reagent) and get accurate pixel-level dental plaque segmentation results. The algorithm needs to conduct self-attention at the super-pixel level and fuse the super-pixels' local-to-global features. Our newly-designed network architecture will afford the simultaneous fusion of multiple-scale complementary information guided by the powerful deep learning paradigm. The critical fused information includes the statistical distribution of the plaques color, the heat kernel signature (HKS) based local-to-global structure relationship, and the circle-LBP based local texture pattern in the nearby regions centering around the plaque area. To further refine the fuzed multiple-scale features, we devise an attention module based on CNN, which could focalize the regions of interest in plaque more easily, especially for many challenging cases. Extensive experiments and comprehensive evaluations confirm that, for a small-scale training dataset, our method could outperform the state-of-the-art methods. Meanwhile, the user studies verify the claim that our method is more accurate than conventional dental practice conducted by experienced dentists.

Bioaugmentation with syntrophic volatile fatty acids-oxidizing consortia to alleviate the ammonia inhibition in continuously anaerobic digestion of municipal sludge.

Ammonia inhibition easily affects the performance of anaerobic digestion (AD) for municipal sludge and the oxidization of volatile fatty acids (VFAs) is the rate-limiting step of this process. Bioaugmentation is considered to be an effective method to alleviate ammonia inhibition of AD, but most study used the hydrogenotrophic methanogens as the bioaugmentation culture. In this study, bioaugmentation of mesophilic AD (MAD) and thermophilic AD (TAD) under ammonia inhibition with syntrophic acetate and propionate oxidizing consortia was investigated. The results showed that the bioaugmented reactors recovered earlier than control reactors with 20 (MAD) and 8 (TAD) days, respectively. The high-throughput 16S rRNA gene sequencing indicated that the relative abundance of carbohydrates fermenter (Lentimicrobium), syntrophic VFAs-oxidizing bacteria (Rikenellaceae_DMER64, Smithella and Syntrophobacter) and acetoclastic and hydrogenotrophic methanogens (Methanosaeta, Methanolinea and Methanospirillum) increased in MAD after bioaugmentation. However, part of the bioaugmentation culture could not adapt to the high free ammonia (FAN) concentration in MAD and the effect was weakened. In TAD, proteolytic bacteria (Keratinibaculum and Tepidimicrobium), syntrophic VFAs-oxidizing bacteria (Syntrophomonas) and hydrogenotrophic methanogen (Methanosarcina) were strengthened. The effect of bioaugmentation in TAD was durable even at higher organic loading rate (OLR), due to its positive influence on microbial community. These results suggested that the different bioaugmentation mechanism occurred in MAD and TAD, which are derived from the synergetic effects of ammonia tolerance and microbial interactions. Our study revealed the VFAs-oxidizing consortia as bioaugmented culture could be the potential strategy to alleviate the ammonia stress of AD.

Conductivity and Stability Properties of Anion Exchange Membranes: Cation Effect and Backbone Effect.

The rise of heterocycle cations, a new class of stable cations, has fueled faster growth of research interest in heterocycle cation-attached anion exchange membranes (AEMs). However, once cations are grafted onto backbones, the effect of backbones on properties of AEMs must also be taken into account. In order to comprehensively study the influence of cations effect and backbones effect on AEMs performance, a series of AEMs were prepared by grafting spacer cations, heterocycles cations, and aromatic cations onto brominated poly(2,6-dimethyl-1,4-phenylene oxide) (BPPO) or poly(vinylbenzyl chloride) (PVB) backbones, respectively. Spacer cation [trimethylamine (TMA), N,N-dimethylethylamine (DMEA)]-attached AEMs showed general ion transportation and stability behaviors, but exhibited high cationic reaction efficiency. Heterocycle cation [1-methylpyrrolidine (MPY), 1-methylpiperidine (MPrD)]-attached AEMs showed excellent chemical stability, but their ion conduction properties were unimpressive. Aromatic cation [1-methylimidazole (MeIm), N,N-dimethylaniline (DMAni)]-attached AEMs exhibited superior ionic conductivity, while their poor cations stabilities hindered the application of the membranes. Besides, it was found that PVB-based AEMs had excellent backbone stability, but BPPO-based AEMs exhibited higher OH- conductivity and cation stability than those of the same cations grafted PVB-based AEMs due to their higher water uptake (WU). For example, the ionic conductivities (ICs) of BPPO-TMA and PVB-TMA at 80 °C were 53.1 and 38.3 mS cm-1 , and their WU was 152.3 and 95.1 %, respectively. After the stability test, the IC losses of BPPO-TMA and PVB-TMA were 21.4 and 32.2 %, respectively. The result demonstrated that the conductivity and stability properties of the AEMs could be enhanced by increasing the WU of the membranes. These findings allowed the matching of cations to the appropriate backbones and reasonable modification of the AEM structure. In addition, these results helped to fundamentally understand the influence of cation effect and backbone effect on AEM performance.

Targeting WEE1 by adavosertib inhibits the malignant phenotypes of hepatocellular carcinoma.

Targeting the cell cycle checkpoints and DNA damage response are promising therapeutic strategies for cancer. Adavosertib is a potent inhibitor of WEE1 kinase, which plays a critical role in regulating cell cycle checkpoints. However, the effect of adavosertib on hepatocellular carcinoma (HCC) treatment, including sorafenib-resistant HCC, has not been thoroughly studied. In this study, we comprehensively investigated the efficacy and pharmacology of adavosertib in HCC therapy. Adavosertib effectively inhibited the proliferation of HCC cells in vitro and suppressed tumor growth in HCC xenografts and patient-derived xenograft (PDX) models in vivo. Additionally, adavosertib treatment effectively inhibited the motility of HCC cells by impairing pseudopodia formation. Further, we revealed that adavosertib induced DNA damage and premature mitosis entrance by disturbing the cell cycle. Thus, HCC cells accumulating DNA damage underwent mitosis without G2/M checkpoint arrest, thereby leading to mitotic catastrophe and apoptosis under adavosertib administration. Given that sorafenib resistance is common in HCC in clinical practice, we also explored the efficacy of adavosertib in sorafenib-resistant HCC. Notably, adavosertib still showed a desirable inhibitory effect on the growth of sorafenib-resistant HCC cells. Adavosertib markedly induced G2/M checkpoint arrest and cell apoptosis in a dose-dependent manner, confirming the similar efficacy of adavosertib in sorafenib-resistant HCC. Collectively, our results highlight the treatment efficacy of adavosertib in HCC regardless of sorafenib resistance, providing insights into exploring novel strategies for HCC therapy.

Hypermethylation of GNA14 and its tumor-suppressive role in hepatitis B virus-related hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide, and its specific mechanism has not been fully elucidated. Inactivation of tumor suppressors may contribute to the occurrence, progression, and recurrence of HCC. DNA methylation is a crucial mechanism involved in regulating the occurrence of HCC. Herein, we aimed to identify the key methylation-related tumor suppressors as well as potential biomarkers and therapeutic targets in HCC. Methods: Combined analysis of TCGA and GEO databases was performed to obtain potential methylation-related tumor suppressors in HCC. Methyl-target sequencing was performed to analyze the methylation level of the GNA14 promoter. The diagnostic value of GNA14 as a predictor of HCC was evaluated in HCC tumor samples and compared with normal tissues. The functional role of GNA14 and its upstream and downstream regulatory factors were investigated by gain-of-function and loss-of-function assays in vitro. Subcutaneous tumorigenesis, lung colonization, and orthotopic liver tumor model were performed to analyze the role of GNA14 in vivo.Results: The expression of GNA14 was found to be downregulated in HCC and it was negatively correlated with hepatitis B virus (HBV) infection, vascular invasion, and prognosis of HCC. DNA methylation was demonstrated to be responsible for the altered expression of GNA14 and was regulated by HBV-encoded X protein (HBx). GNA14 regulated the RB pathway by promoting Notch1 cleavage to inhibit tumor proliferation, and might inhibit tumor metastasis by inhibiting the expression of JMJD6. Conclusion: GNA14 could be regulated by HBx by modulating the methylation status of its promoter. We identified GNA14 as a potential biomarker and therapeutic target for HCC.