AnyFace++: A Unified Framework for Free-style Text-to-Face Synthesis and Manipulation.

Human faces contain rich semantic information that could hardly be described without a large vocabulary and complex sentence patterns. However, most existing text-to-image synthesis methods could only generate meaningful results based on limited sentence templates with words contained in the training set, which heavily impairs the generalization ability of these models. In this paper, we define a novel 'free-style' text-to-face generation and manipulation problem, and propose an effective solution, named AnyFace++, which is applicable to a much wider range of open-world scenarios. The CLIP model is involved in AnyFace++ for learning an aligned language-vision feature space, which also expands the range of acceptable vocabulary as it is trained on a large-scale dataset. To further improve the granularity of semantic alignment between text and images, a memory module is incorporated to convert the description with arbitrary length, format, and modality into regularized latent embeddings representing discriminative attributes of the target face. Moreover, the diversity and semantic consistency of generation results are improved by a novel semi-supervised training scheme and a series of newly proposed objective functions. Compared to state-of-the-art methods, AnyFace++ is capable of synthesizing and manipulating face images based on more flexible descriptions and producing realistic images with higher diversity.

A fluorescent probe for imaging nitroreductase with signal amplification in high-viscosity environments.

Herein, we developed a fluorescent probe ENBT for in vitro detection of nitroreductase (NTR) as well as imaging intracellular NTR. ENBT itself is non-fluorescent and it could be catalyzed by NTR to generate a viscosity-sensitive fluorophore EBT. The fluorescence intensity of EBT could be further enhanced in cancer cells with relatively high viscosity due to the inhibition of the twisted intramolecular charge transfer effect. The probe ENBT has a good response to NTR with a detection limit of 36.8 ng mL-1, and EBT has a good response to viscosity. Furthermore, different concentrations of NTR (0-1.4 µg mL-1) were used to react with the probe and the reaction systems were subjected to different viscosity solutions, and the fluorescence signals of the products in the viscosity range of 45.86-163.60 cP were increased up to 1.69-fold. ENBT was successfully used to image NTR in cells under different hypoxic conditions as well as in Staphylococcus aureus. Finally, lipopolysaccharide was added to stimulate an increase in cellular viscosity after ENBT was catalyzed by intracellular NTR into EBT, and the fluorescence signals were observed to increase by 1.72-fold. The signal amplification capability gives ENBT higher sensitivity and immunity to interference. Moreover, it has the advantages of mitochondrial targeting, large Stokes shift (190 nm), high selectivity, and can be easily synthesized.

MRI Radiomics-Based Machine Learning Models for Ki67 Expression and Gleason Grade Group Prediction in Prostate Cancer.

PURPOSE: The Ki67 index and the Gleason grade group (GGG) are vital prognostic indicators of prostate cancer (PCa). This study investigated the value of biparametric magnetic resonance imaging (bpMRI) radiomics feature-based machine learning (ML) models in predicting the Ki67 index and GGG of PCa. METHODS: A total of 122 patients with pathologically proven PCa who had undergone preoperative MRI were retrospectively included. Radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. Then, recursive feature elimination (RFE) was applied to remove redundant features. ML models for predicting Ki67 expression and GGG were constructed based on bpMRI and different algorithms, including logistic regression (LR), support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN). The performances of different models were evaluated with receiver operating characteristic (ROC) analysis. In addition, a joint analysis of Ki67 expression and GGG was performed by assessing their Spearman correlation and calculating the diagnostic accuracy for both indices. RESULTS: The ML model based on LR and ADC + T2 (LR_ADC + T2, AUC = 0.8882) performed best in predicting Ki67 expression, and ADC_wavelet-LHH_firstorder_Maximum had the highest feature weighting. The SVM_DWI + T2 (AUC = 0.9248) performed best in predicting GGG, and DWI_wavelet HLL_glcm_SumAverage had the highest feature weighting. The Ki67 and GGG exhibited a weak positive correlation (r = 0.382, p < 0.001), and LR_ADC + DWI had the highest diagnostic accuracy in predicting both (0.6230). CONCLUSION: The proposed ML models are suitable for predicting both Ki67 expression and GGG in PCa. This algorithm could be used to identify indolent or invasive PCa with a noninvasive, repeatable, and accurate diagnostic method.

Peritumoral Radiomics Strategy Based on Ensemble Learning for the Prediction of Gleason Grade Group of Prostate Cancer.

RATIONALE AND OBJECTIVES: To develop and evaluate a peritumoral radiomic-based machine learning model to differentiate low-Gleason grade group (L-GGG) and high-GGG (H-GGG) prostate lesions. MATERIALS AND METHODS: In this retrospective study, a total of 175 patients with prostate cancer (PCa) confirmed by puncture biopsy were recruited and included 59 patients with L-GGG and 116 patients with H-GGG. The original PCa regions of interest (ROIs) were delineated on T2-weighted (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps, and then centra-tumoral and peritumoral ROIs were defined. Features were meticulously extracted from each ROI to establish radiomics models, employing distinct sequence datasets. Peritumoral radiomics models were specifically developed for both the peripheral zone (PZ) and transitional zone (TZ), utilizing dedicated PZ and TZ datasets, respectively. The performances of the models were evaluated by using the receiver operating characteristic (ROC) curve and precision-recall curve. RESULTS: The classification model with combined peritumoral features based on T2 + DWI + ADC sequence dataset demonstrated superior performance compared to the original tumor and centra-tumoral classification models. It achieved an area under the ROC curve (AUC) of 0.850 [95% confidence interval, 0.849, 0.860] and an average accuracy of 0.950. The combined peritumoral model outperformed the regional peritumoral models with AUC of 0.85 versus 0.75 for PZ lesions and 0.88 versus 0.69 for TZ lesions, respectively. The peritumoral classification models exhibit greater efficacy in predicting PZ lesions as opposed to TZ lesions. CONCLUSION: The peritumoral radiomics features showed excellent performance in predicting GGG in PCa patients and might be a valuable addition to the non-invasive assessment of PCa aggressiveness.

GAN-Based Facial Attribute Manipulation.

Facial Attribute Manipulation (FAM) aims to aesthetically modify a given face image to render desired attributes, which has received significant attention due to its broad practical applications ranging from digital entertainment to biometric forensics. In the last decade, with the remarkable success of Generative Adversarial Networks (GANs) in synthesizing realistic images, numerous GAN-based models have been proposed to solve FAM with various problem formulation approaches and guiding information representations. This paper presents a comprehensive survey of GAN-based FAM methods with a focus on summarizing their principal motivations and technical details. The main contents of this survey include: (i) an introduction to the research background and basic concepts related to FAM, (ii) a systematic review of GAN-based FAM methods in three main categories, and (iii) an in-depth discussion of important properties of FAM methods, open issues, and future research directions. This survey not only builds a good starting point for researchers new to this field but also serves as a reference for the vision community.

3D-Aware Adversarial Makeup Generation for Facial Privacy Protection.

The privacy and security of face data on social media are facing unprecedented challenges as it is vulnerable to unauthorized access and identification. A common practice for solving this problem is to modify the original data so that it could be protected from being recognized by malicious face recognition (FR) systems. However, such "adversarial examples" obtained by existing methods usually suffer from low transferability and poor image quality, which severely limits the application of these methods in real-world scenarios. In this paper, we propose a 3D-Aware Adversarial Makeup Generation GAN (3DAM-GAN). which aims to improve the quality and transferability of synthetic makeup for identity information concealing. Specifically, a UV-based generator consisting of a novel Makeup Adjustment Module (MAM) and Makeup Transfer Module (MTM) is designed to render realistic and robust makeup with the aid of symmetric characteristics of human faces. Moreover, a makeup attack mechanism with an ensemble training strategy is proposed to boost the transferability of black-box models. Extensive experiment results on several benchmark datasets demonstrate that 3DAM-GAN could effectively protect faces against various FR models, including both publicly available state-of-the-art models and commercial face verification APIs, such as Face++, Baidu, and Aliyun.

Design, synthesis, and evaluation of 1H-benzo[d]imidazole-4-carboxamide PARP-1 inhibitors using different saturated nitrogen-contained heterocycle as linker group.

Poly (ADP-ribose) polymerase-1 (PARP-1) inhibitors have been successfully applied in the clinical treatment of various cancer. Side effects and drug resistant cases were reported, and more effective PARP-1 inhibitors were required. However, studies on the AD site of PARP-1 inhibitors are currently incomplete. Therefore, to synthesize more potential candidate PARP-1 inhibitors and disclose some AD site SAR of the PARP-1 inhibitors, herein, a series of 2-phenyl-benzimidazole-4-carboxamide derivatives using different saturated nitrogen-contained heterocycles as linker group (6a-6t) have been designed, synthesized, and evaluated PARP-1 inhibitory activity and proliferation inhibitory against BRCA-1 mutant MDA-MB-436 cell line in vitro. The results showed 6b (IC50 = 8.65 nM) exhibited the most PARP-1 enzyme inhibitory activity comparable with Veliparib (IC50 = 15.54 nM) and Olaparib (IC50 = 2.77 nM); 6m exhibited the strongest MDA-MB-436 cell anti-proliferation activity (IC50 = 25.36 ± 6.06 µM) comparable with Olaparib (IC50 = 23.89 ± 3.81 µM). The compounds 6b, 6r, and 6m could be potential candidates for effective PARP-1 inhibitors and valuable for further optimization. The analysis of activity data also showed that the holistically anti-proliferation activity of the 1,4-diazepane group was about~twofold than that of the piperazine group. Meanwhile, the terminal 3-methyl-furanyl group exhibited the most robust PARP-1 inhibitory and anti-proliferation activity. It is hoped that the results could benefitable for further optimization of PARP-1 inhibitors. Furthermore, we note that some compounds (6d,6g,6n,6p,6s) showed poor PARP-1 inhibitory (>500 nM) but relatively good anti-proliferation activity, which indicates the proliferation inhibitory mechanism against MDA-MB-436 cell line was worth investigating in-depth.

Iron scraps packing rapidly enhances nitrogen removal in an aerobic sludge system and the mechanism.

Simultaneous nitrification and denitrification (SND) has the advantage of energy saving and carbon demand reduction. Here, readily available low-cost iron scraps packing was added to an aerobic sludge system. This successfully enhanced the efficiency of total nitrogen removal from 37.7 ± 13.2 % to 62.7 ± 7.9 % over 2 days. While electrons from iron biocorrosion did not contribute to nitrate reduction, iron promoted heterotrophic denitrification. The iron scraps changed the spatial distribution of the microbial community, where more denitrification bacteria accumulated around the packing and higher denitrification capacity was noted. Metagenomic analysis of the sludge cultured in the presence of iron scraps for 2 days revealed that, with the exception of the enriched amoA/B/C gene expression, the abundance of other key nitrogen removal genes showed little variation. Furthermore, the structure of the microbial community was unchanged probably due to the relatively short culturing period. However, metatranscriptomic analysis indicated that iron increased the abundance of nitrifying bacteria (i.e. unclassified Nitrosomonas, Nitrosomonas sp. Is79A3 and Nitrospira defluvii) and promoted higher expression of nitrification genes. Notably, iron scraps packing decreased the abundance of the key denitrification bacteria Thauera sp. MZ1T from 52.92 to 7.58 %. The expression of napA/B also decreased, while expression of narG/H/I increased by 9 to 23 fold and a 2 to 3 fold over expression was noted for nirS, norB/C and nosZ in the presence of iron scraps. This suggested that aerobic denitrification was inhibited and anaerobic denitrification was promoted. This study has provided in-depth understanding of the influence of iron on SND to improve the application of iron-supported biological processes.

Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification.

OBJECTIVES: To precisely predict prostate cancer (PCa) risk stratification, we constructed a machine learning (ML) model based on magnetic resonance imaging (MRI) radiomic features. METHODS: Between August 2016 and May 2021, patients with histologically proven PCa who underwent pre-operative MRI and prostate-specific antigen screening were included. The patients were grouped into different risk categories as defined by the European Association of Urology-European Association of Nuclear Medicine-European Society for Radiotherapy and Oncology-European Society of Urogenital Radiology-International Society of Geriatric Oncology guidelines. Using Artificial Intelligence Kit software, PCa regions of interest were delineated and radiomic features were extracted. Subsequently, predictable models were built by utilising five traditional ML approaches: support vector machine, logistic regression, gradient boosting decision tree, k-nearest neighbour and random forest (RF) classifiers. The classification capacity of the developed models was assessed by area under the receiver operating characteristic curve (AUC) analysis. RESULTS: A total of 213 patients were enrolled, including 16 low-risk, 65 intermediate-risk, and 132 high-risk PCa patients. The risk stratification of PCa could be revealed by MRI radiomic features, and second-order features accounted for most of the selected features. Among the five established ML models, the RF model showed the best overall predictive performance (AUC = 0.87). After further analysis of the subgroups based on the RF model, the prediction of the high-risk group was the best (AUC = 0.89). CONCLUSION: This study demonstrated that the MR radiomics-based ML method could be a promising tool for predicting PCa risk stratification precisely. ADVANCES IN KNOWLEDGE: The ML models have valuable prospect for accurate PCa risk assessment, which might contribute to customize treatment and surveillance strategies.

Cascade filtration and droplet digital detection integrated microfluidic assay enables isolating culture-free phenotypic identification of carbapenem-resistant organisms.

Carbapenem-resistant organisms (CROs) are characterized by high drug resistance, rapid transmission, and high lethality. Therefore, rapid detection for CROs is essential for appropriate applying antibiotics and implementing quarantine. Droplet digital chromogenic assays (DDCA) have been accepted as an effective means for rapid microbial detection as the small droplet volumes facilitate a significant enhancement in the local concentration of chromogenic factors and, therefore, reduce the required time of the test. Nevertheless, as their dependence on the time-consuming isolation culture, the DDCA is still associated with a long turnaround time. To overcome this limitation, we develop here a microfluidic chip-based CRO phenotypic identification method that integrates cascade filtration (CF) with DDCA (CF-DDCA). After a body fluid sample is introduced to the microfluidic chip, particles with sizes >5 µm are removed out by the primary filter, and Gram (+) cocci with sizes <1 µm removed out by the secondary filter so that only Gram (-) bacilli with sizes between 1.5 and 5 µm are selectively retained. The purified Gram (-) bacilli, along with chromogenic reagents and carbapenem antibiotics, are then subjected to the DDCA. We demonstrate that the CF can remove 99.9% of the interfering microorganisms and thus eliminates the isolating culture. Benefited from the isolating culture-free DDCA, phenotypic identification of CROs can be achieved within 3.5 h. Clinical urine sample testing shows that the sensitivity and specificity of the CF-DDCA for CRO identification are all 100%, and the total coincidence rate between CF-DDCA and the conventional assay is also 100%.

Radiomics-Based Machine Learning Models for Predicting P504s/P63 Immunohistochemical Expression: A Noninvasive Diagnostic Tool for Prostate Cancer.

Objective: To develop and validate a noninvasive radiomic-based machine learning (ML) model to identify P504s/P63 status and further achieve the diagnosis of prostate cancer (PCa). Methods: A retrospective dataset of patients with preoperative prostate MRI examination and P504s/P63 pathological immunohistochemical results between June 2016 and February 2021 was conducted. As indicated by P504s/P63 expression, the patients were divided into label 0 (atypical prostatic hyperplasia), label 1 (benign prostatic hyperplasia, BPH) and label 2 (PCa) groups. This study employed T2WI, DWI and ADC sequences to assess prostate diseases and manually segmented regions of interest (ROIs) with Artificial Intelligence Kit software for radiomics feature acquisition. Feature dimensionality reduction and selection were performed by using a mutual information algorithm. Based on screened features, P504s/P63 prediction models were established by random forest (RF), gradient boosting decision tree (GBDT), logistic regression (LR), adaptive boosting (AdaBoost) and k-nearest neighbor (KNN) algorithms. The performance was evaluated by the area under the ROC curve (AUC) and accuracy. Results: A total of 315 patients were enrolled. Among the 851 radiomic features, the 32 top features were derived from T2WI, in which the gray-level run length matrix (GLRLM) and gray-level cooccurrence matrix (GLCM) features accounted for the largest proportion. Among the five models, the RF algorithm performed best in general evaluations (microaverage AUC=0.920, macroaverage AUC=0.870) and provided the most accurate result in further sublabel prediction (the accuracies of label 0, 1, and 2 were 0.831, 0.831, and 0.932, respectively). In comparative sequence analyses, T2WI was the best single-sequence candidate (microaverage AUC=0.94 and macroaverage AUC=0.78). The merged datasets of T2WI, DWI, and ADC yielded optimal AUCs (microaverage AUC=0.930 and macroaverage AUC=0.900). Conclusions: The radiomic-based RF classifier has the potential to be used to evaluate the presurgical P504s/P63 status and further diagnose PCa noninvasively and accurately.

Development and Verification Experiment of In-Situ Friction Experiment Device for Simulating UV Irradiation in Space.

In order to explore the influence of space ultraviolet radiation on spacecraft lubricating materials, an in-situ friction experimental device simulating space ultraviolet radiation was developed in the laboratory, and the experimental verification was carried out. This paper firstly introduced the design index, structure and working principle of the space ultraviolet irradiation simulation device, and then calibrated and tested the parameters of the whole device, and also conducted a virtual operation of the device's operation effect by simulation software, and the results showed that it met the design index. Finally, the validation tested of the ultraviolet irradiated in-situ friction experimental device were described in detail. By using the device to irradiate the samples, it was found that the in-situ ultraviolet irradiation device could achieve the expected irradiation effect, and the irradiation would lead to changes in the surface structure and properties of the PTFE material, while also achieving the need for in-situ spatial friction property testing of the material, providing favorable conditions for future testing.

Synthesis and evaluation of 2-(4-[4-acetylpiperazine-1-carbonyl] phenyl)-1H-benzo[d]imidazole-4-carboxamide derivatives as potential PARP-1 inhibitors and preliminary study on structure-activity relationship.

Although 1H-benzo[d]imidazole-4-carboxamide derivatives have been explored for a long time, the structure-activity relationship of the substituents in the hydrophobic pocket (AD binding sites) has not thoroughly discovered. Here in, a series of 2-(4-[4-acetylpiperazine-1-carbonyl]phenyl)-1H-benzo[d]imidazole-4-carboxamide derivatives have been designed, synthesized, and successful characterization as novel and effective poly ADP-ribose polymerases (PARP)-1 inhibitors to improve the structure-activity relationships about the substituents in the hydrophobic pocket. These derivatives were evaluated for their PARP-1 inhibitory activity and cellular inhibitory against BRCA-1 deficient cells (MDA-MB-436) and wild cells (MCF-7) using PARP kit assay and MTT method. The results indicated that compared with other heterocyclic compounds, furan ring-substituted derivatives 14n-14q showed better PARP-1 inhibitory activity. Among this derivatives, compound 14p displayed the strongest inhibitory effects on PARP-1 enzyme (IC50  = 0.023 µM), which was close to that of Olaparib. 14p (IC50  = 43.56 ± 0.69 µM) and 14q (IC50  = 36.69 ± 0.83 µM) displayed good antiproliferation activity on MDA-MB-436 cells and inactivity on MCF-7 cells, indicating that 14p and 14q have high selectivity and targeting. The molecular docking method was used to explore the binding mode of compound 14p and PARP-1, and implied that the formation of hydrogen bond was essential for PARP-1 inhibition activities. This study also showed that in the hydrophobic pocket (AD binding sites), the introduction of strong electronegative groups (furan ring, e.g.) or halogen atoms in the side chain of benzimidazole might improve its inhibitory activity and this strategy could be applied in further research.

Terahertz-Based Method for Accurate Characterization of Early Water Absorption Properties of Epoxy Resins and Rapid Detection of Water Absorption.

Moisture is detrimental to the performance of epoxy resin material for electrical equipment in long-term operation and insulation. Therefore, moisture absorption is one of the critical indicators for insulation of the material. However, some relevant test methods, e.g., the direct weighing method, are time-consuming, and it usually takes months to complete a test. For this, it is necessary to have some modification to save the test time. Firstly, the study analyzes the present prediction method (according to ISO 62:2008). Under the same accuracy, the time required is reduced from 104 days to 71 days. Subsequently, the Langmuir curve-fitting method for water absorption of epoxy resin is analyzed, and the initial values of diffusion coefficient, bonding coefficient, and de-bonding coefficient are determined based on the results of molecular simulation, relevant experiment, and literature review. With the optimized prediction model, it takes only 1.5 days (reduced by 98% as compared with the standard prediction method) to determine the moisture absorbability. Then, the factors influencing the prediction accuracy are discussed. The results have shown that the fluctuation of balance at the initial stage will affect the test precision significantly. Accordingly, this study proposes a quantitative characterization method for initial trace moisture based on the terahertz method, by which the trace moisture in epoxy resin is represented precisely through the established terahertz time-domain spectroscopy system. When this method is used to predict the moisture absorbability, the experimental time may be further shortened by 33% to 1 day. For the whole water absorption cycle curve, the error is less than 5%.

Membrane-Activated Fluorescent Probe for High-Fidelity Imaging of Mitochondrial Membrane Potential.

Mitochondrial membrane potential (ΔΨm) is a key indicator of cell health or injury due to its vital roles in adenosine 5'-triphosphate synthesis. Thus, monitoring ΔΨm is of great significance for the assessment of cell status, diagnosis of diseases, and medicament screening. Cationic fluorescent probes suffer from severe photobleaching or false positive signals due to the luminescence of the probe on non-mitochondria. Herein, we report a lipophilic cationic fluorescent probe [1-methyl-2-(4-(1,2,2-triphenylvinyl)styryl)-ß-naphthothiazol-1-ium trifluoromethanesulfonate (TPE-NT)] with the features of aggregation-induced emission and intramolecular charge transfer for imaging ΔΨm in live cells. TPE-NT is enriched on the surface of the mitochondrial inner membrane due to the negative ΔΨm, and its fluorescence is activated in the high-viscosity microenvironment. The false positive signals of emission from TPE-NT on non-mitochondria are therefore effectively eliminated. Moreover, TPE-NT exhibits a Stokes shift of >200 nm, near-infrared (∼675 nm) emission, excellent photostability, and low cytotoxicity, which facilitate real-time imaging in live cells. Cell imaging confirmed that the probe can rapidly and reliably report mitochondrial depolarization (decrement of ΔΨm) during cell damage caused by CCCP and H2O2 as well as mitochondrial polarization (increment of ΔΨm) by oligomycin. Furthermore, the probe successfully detected the reduction of ΔΨm in these cell models of hypoxia, heat damage, acidification, aging, inflammation, mitophagy, and apoptosis caused by hypoxia, heatstroke, lactate/pyruvate, doxorubicin, lipopolysaccharide, rapamycin, monensin, and nystatin, respectively.

EMT and Cancer Cell Stemness Associated With Chemotherapeutic Resistance in Esophageal Cancer.

Drug resistance often occurs after chemotherapy in esophageal cancer patients, leading to cancer metastasis and recurrence. However, the relationship among cancer cell migration, recurrence and drug resistance in esophageal cancer drug-resistant cells has not been clearly explained. In this study, we constructed paclitaxel (PTX)-resistant esophageal cancer cells to explore the causes of drug resistance and poor prognosis after chemotherapy in esophageal cancer. Colony formation assay was used to evaluate the difference of colony formation between parental cells and drug resistance cells. Microsphere formation assay was used to examine the phenotype of stem cells. Wound healing and Transwell assays were used to detect the migration ability of drug-resistant cells. Western blotting and immunofluorescence assays were used to explore the mechanisms. Finally, we used nude mouse xenograft model to explore the tumor characteristics and the expression of relative proteins to verify our findings in vivo. Our study demonstrated that the cancer cell stemness characteristics exist in drug-resistant esophageal cancer cells, that expressed the biomarkers of stem cells and were prone to epithelial-mesenchymal transition (EMT). Our results suggested that the expression of EMT biomarkers and stemness-related proteins increased in esophageal cancer cells after continuously using chemotherapeutic drugs for a period of time. This study indicated that simultaneously targeting EMT and stemness could be a better strategy for the treatment of esophageal cancer drug resistance.

How does iron facilitate the aerated biofilter for tertiary simultaneous nutrient and refractory organics removal from real dyeing wastewater?

Textile dyeing wastewater is characterized by low biodegradability and high nitrogen strength, which is difficult to meet the increasingly stringent discharge requirements. Therefore, the tertiary nutrient and refractory organics removal is considered and aerated biofilter is often adopted. However, the aerobic condition and carbon source shortage restrict tertiary biological nitrogen removal. In this study, iron scrap was introduced as the filter medium to enhance the pollutant removal capacity, and three aerobic biofilters were constructed. Biofilter Fe-CE was filled with iron scrap and ceramisite; biofilter Fe-AC was added with iron scrap and granular activated carbon, and biofilter CE only had ceramisite to pad as control system. After the biofilters were acclimatized by synthetic wastewater and actual dyeing wastewater, the optimal operation parameters based on nitrogen removal were determined as pH 7, gas-water ratio 5:1, hydraulic retention time 8 h and C/N ratio 8.5:1. The iron scraps improved total nitrogen (TN) removal significantly, with TN removal efficiency of 68.7% and 57.3% in biofilter Fe-AC and biofilter Fe-CE, comparing with biofilter CE of 29.9%. Additionally, phosphorus and COD had better removal performance as well when iron scrap existed. Further investigation interpreted the reason for iron's facilitating effect on tertiary nutrient and refractory organics removal. The introduction of iron scrap made the habitat conditions such as pH values, DO concentrations and biomass contents inside the biofilters change towards the direction beneficial for pollutant elimination especially for nitrogen removal. In iron containing biofilters, the majority of nitrogen, phosphorus and organic pollutants were removed in the iron scrap layers, and more pollutants types appeared, implying that iron triggered pollutants to go through more diverse degradation or transformation pathways. Moreover, the phylum Proteoabcteria dominated in samples of ceramisite-containing biofilters, with abundances more than 40%. The iron scrap existence increased the abundances of phyla Bacteroidetes and Firmicutes, and triggered higher abundance of denitrification bacteria.

Evaluation of miR-122-regulated suicide gene therapy for hepatocellular carcinoma in an orthotopic mouse model.

OBJECTIVE: Intratumoral administration of adenoviral vector encoding herpes simplex virus (HSV) thymidine kinase (TK) gene (Ad-TK) followed by systemic ganciclovir (GCV) is an effective approach in treating experimental hepatocellular carcinoma (HCC). However, hepatotoxicity due to unwanted vector spread and suicide gene expression limited the application of this therapy. miR-122 is an abundant, liver-specific microRNA whose expression is decreased in human primary HCC and HCC-derived cell lines. These different expression profiles provide an opportunity to induce tumor-specific gene expression by miR-122 regulation. METHODS: By inserting miR-122 target sequences (miR-122T) in the 3' untranslated region (UTR) of TK gene, we constructed adenovirus (Ad) vectors expressing miR-122-regulated TK (Ad-TK-122T) and report genes. After intratumoral administration of Ad vectors into an orthotopic miR-122-deficient HCC mouse model, we observed the miR-122-regulated transgene expression and assessed the antitumor activity and safety of Ad-TK-122T. RESULTS: Insertion of miR-122T specifically down-regulated transgene expression in vitro and selectively protected the miR-122-positive cells from killing by TK/GCV treatment. Insertion of miR-122T led to significant reduction of tansgene expression in the liver without inhibition of its expression in tumors in vivo, resulting in an 11-fold improvement of tumor-specific transgene expression. Intratumoral injection of Ad vectors mediated TK/GCV system led to a vector dosage-dependent regression of tumor. The insertion of miR-122T does not influence the antitumor effects of suicide gene therapy. Whereas mice administrated with Ad-TK showed severe lethal hepatotoxicity at the effective therapeutic dose, no liver damage was found in Ad-TK-122T group. CONCLUSIONS: miR-122-regulated TK expression achieved effective anti-tumor effects and increased the safety of intratumoral delivery of adenovirus-mediated TK/GCV gene therapy for miR-122-deficient HCC.

[Comparison of the rescue efficiency of Sendai virus minigenome mediated by CMV and T7 promoter].

In this study, we constructed the plasmid of Sendai virus (SeV) BB1 strain minigenome with Gaussia luciferase (Gluc) as reporter and compared the rescue efficiency of SeV minigenome mediated by T7 promoter with that by CMV promoter. Firstly, the sequence was designed and synthesized which contained hammerhead ribozyme, sequence composed of the trailer, untranslated region of L gene, untranslated region of N gene, and the leader from SeV, and mutant hepatitis delta virus ribozyme sequence. Then, the synthesized sequence was inserted into pVAX1 containing CMV and T7 promoters and the general vector for SeV minigenome pVAX-miniSeV was obtained. Furthermore, pVAX-miniSeV-Gluc (+) and pVAX-miniSeV-Gluc(-) were obtained by inserting Gluc gene into pVAX-miniSeV. From the supernatant of BHK-21 cell transfected with pVAX-miniSeV-Gluc(+), high level of Gluc expression was detection indicating the normal transcription function of CMV promoter. pVAX-SeV-miniGluc(-) and plasmids expressing N,P and L protein of SeV were co-transfected into BST T7/5 cell which derived from BHK-21 and expressed T7 RNA polymerase stably. And high expression of Gluc was found, which indicated that SeV minigenome was efficiently rescued. However, we failed to repeat the result on BHK-21 cell, implying that T7 promoter and CMV promoter may have different effects on the rescue efficiency of SeV minigenome. Therefore, we further constructed SeV minigenome vectors pT7-miniSeV-Gluc (-) and pCMV-miniSeV-Gluc(-) with single promoter of T7 or CMV. Then, these vectors were transfected into BSR T7/ 5 cells respectively accompanied with the N, P, and L protein expression vectors. The result demonstrated that high expression of Gluc was found in the group of pT7-miniSeV-Gluc(-), which failed in the group of pCMV-miniSeV-Gluc(-). It indicated that T7 promoter significantly increased the rescue efficiency of SeV minigenome. We successfully constructed a SeV minigenome vector with secreted luciferase gene as report er and proved T7 promoter can enhance the rescue efficiency of SeV minigenome, which provides basis for construction of infectious clone containing SeV full-length genome.

[Rapid expression and preparation of the recombinant fusion protein sTNFRII-gAD by adenovirus vector system].

We expressed and prepared the recombinant fusion protein sTNFRII-gAD consisted of soluble TNF receptor II and the globular domain of adiponectin by Adenovirus Vector System in mammalian BHK21c022 cells. First we used the adenovirus vector containing EGFP gene (rAd5-EGFP) to infect BHK21c022 cells at different MOI (from 0 to 1 000), and then evaluated their transduction efficiency and cytotoxicity. Similarly, we constructed the replication-deficient adenovirus type 5-sTNFRII-gAD (rAd5-sTNFRII-gAD). We collected the supernatants for Western blotting to determine the optimal MOI by comparing the expression levels of sTNFRII-gAD fusion protein, 48 h after the BHK21c022 cells were infected by rAd5-sTNFRII-gAD at different MOIs (from 0 to 1 000). Then, we chose rAd5-sTNFRII-gAD at MOI 100 to infect five bottles of BHK21c022 cells in 100 mL of serum-free chemically defined media 100 mL, harvested the supernatant every 48 h for 6 times, and condense and purify sTNFRII-gAD fusion protein by ammonium sulfate salt-out and size-exclusion chromatography, respectively. Finally, we analyzed anti-TNFalpha activity of sTNFRII-gAD fusion protein on L929 cells in vitro. The results showed that the number of BHK21c022 cells expressing EGFP protein was increased significantly with the increase of MOI. However, some cells died at MOI of 1 000 while there was no significant cytotoxicity at MOI from 0 to 100. Western blotting analysis showed that the more adenoviruses, the higher expression of sTNFRII-gAD fusion protein in the supernatant with the highest expression at MOI 1 000. We successfully obtained about 11 mg bioactive and purified sTNFRII-gAD fusion protein at last. The in vitro assay demonstrated that the sTNFRII-gAD fusion protein was potent to antagonize TNFalpha's cytotoxicity to L929 cells. Put together, we established a recombinant adenovirus vector/BHK21 cell expression system, characteristic of the efficient serum-free culture and easy scaling-up.