High biomass yields of Chlorella protinosa with efficient nitrogen removal from secondary effluent in a membrane photobioreactor.

Further treatment of secondary effluents before their discharge into the receiving water bodies could alleviate water eutrophication. In this study, the Chlorella proteinosa was cultured in a membrane photobioreactor to further remove nitrogen from the secondary effluents. The effect of hydraulic retention time (HRT) on microalgae biomass yields and nutrient removal was studied. The results showed that soluble algal products concentration reduced in the suspension at low HRT, thereby alleviating microalgal growth inhibition. In addition, the lower HRT reduced the nitrogen limitation for Chlorella proteinosa's growth through the phase-out of nitrogen-related functional bacteria. As a result, the productivity for Chlorella proteinosa increased from 6.12 mg/L/day at an HRT of 24 hr to 20.18 mg/L/day at an HRT of 8 hr. The highest removal rates of 19.7 mg/L/day, 23.8 mg/L/day, and 105.4 mg/L/day were achieved at an HRT of 8 hr for total nitrogen (TN), ammonia, and chemical oxygen demand (COD), respectively. However, in terms of removal rate, TN and COD were the largest when HRT is 24 hr, which were 74.5% and 82.6% respectively. The maximum removal rate of ammonia nitrogen was 99.2% when HRT was 8 hr.

Generating Multi-Depth 3D Holograms Using a Fully Convolutional Neural Network.

Efficiently generating 3D holograms is one of the most challenging research topics in the field of holography. This work introduces a method for generating multi-depth phase-only holograms using a fully convolutional neural network (FCN). The method primarily involves a forward-backward-diffraction framework to compute multi-depth diffraction fields, along with a layer-by-layer replacement method (L2RM) to handle occlusion relationships. The diffraction fields computed by the former are fed into the carefully designed FCN, which leverages its powerful non-linear fitting capability to generate multi-depth holograms of 3D scenes. The latter can smooth the boundaries of different layers in scene reconstruction by complementing information of occluded objects, thus enhancing the reconstruction quality of holograms. The proposed method can generate a multi-depth 3D hologram with a PSNR of 31.8 dB in just 90 ms for a resolution of 2160 × 3840 on the NVIDIA Tesla A100 40G tensor core GPU. Additionally, numerical and experimental results indicate that the generated holograms accurately reconstruct clear 3D scenes with correct occlusion relationships and provide excellent depth focusing.

Eu3+-Doped Anionic Zinc-Based Organic Framework Ratio Fluorescence Sensing Platform: Supersensitive Visual Identification of Prescription Drugs.

Advanced techniques for both environmental and biological prescription drug monitoring are of ongoing interest. In this work, a fluorescent sensor based on an Eu3+-doped anionic zinc-based metal-organic framework (Eu3+@Zn-MOF) was constructed for rapid visual analysis of the prescription drug molecule demecycline (DEM), achieving both high sensitivity and selectivity. The ligand 2-amino-[1,1'-biphenyl]-4,4'-dicarboxylic acid (bpdc-NH2) not only provides stable cyan fluorescence (467 nm) for the framework through intramolecular charge transfer of bpdc-NH2 infinitesimal disturbanced by Zn2+ but also chelates Eu3+, resulting in red (617 nm) fluorescence. Through the synergy of photoinduced electron transfer and the antenna effect, a bidirectional response to DEM is achieved, enabling concentration quantification. The Eu3+@Zn-MOF platform exhibits a wide linear range (0.25-2.5 µM) to DEM and a detection limit (LOD) of 10.9 nM. Further, we integrated the DEM sensing platform into a paper-based system and utilized a smartphone for the visual detection of DEM in water samples and milk products, demonstrating the potential for large-scale, low-cost utilization of the technology.

Synthesis of Imidazole-Based Deep Eutectic Solvents as Solid Lubricants: Lubricated State Transition.

The controllable character of the melting point of deep eutectic solvents (DESs) makes it easy to realize lubricated state transitions and produce excellent lubricating properties during friction. In this work, a series of novel imidazole-based DESs were synthesized to present a room-temperature solid state by shifting its eutectic point. Tribological test results show that the wear volume of these DESs decreases as the alkyl chains of the hydrogen bond donors increase. A proper deviation of the eutectic point in DESs produces stable lubricating properties. The present work provides a novel and simple method to prepare solid lubricants and enriches the use of DESs as lubricants. Simultaneously, the method expected to replace the use of conventional cutting fluids.

Classification regularized dimensionality reduction improves ultrasound thyroid nodule diagnostic accuracy and inter-observer consistency.

PROBLEM: Convolutional Neural Networks (CNNs) for medical image analysis usually only output a probability value, providing no further information about the original image or inter-relationships between different images. Dimensionality Reduction Techniques (DRTs) are used for visualization of high dimensional medical image data, but they are not intended for discriminative classification analysis. AIM: We develop an interactive phenotype distribution field visualization system for medical images to accurately reflect the pathological characteristics of lesions and their similarity to assist radiologists in diagnosis and medical research. METHODS: We propose a novel method, Classification Regularized Uniform Manifold Approximation and Projection (UMAP) referred as CReUMAP, combining the advantages of CNN and DRT, to project the extracted feature vector fused with the malignant probability predicted by a CNN to a two-dimensional space, and then apply a spatial segmentation classifier trained on 2614 ultrasound images for prediction of thyroid nodule malignancy and guidance to radiologists. RESULTS: The CReUMAP embedding correlates well with the TI-RADS categories of thyroid nodules. The parametric version that embeds external test dataset of 303 images in presence of the training data with known pathological diagnosis improves the benign and malignant nodule diagnostic accuracy (p-value = 0.016) and confidence (p-value = 1.902 × 10-6) of eight radiologists of different experience levels significantly as well as their inter-observer agreements (kappa≥0.75). CReUMAP achieve 90.8% accuracy, 92.1% sensitivity and 88.6% specificity in test set. CONCLUSION: CReUMAP embedding is well correlated with the pathological diagnosis of thyroid nodules, and helps radiologists achieve more accurate, confident and consistent diagnosis. It allows a medical center to generate its locally adapted embedding using an already-trained classification model in an updateable manner on an ever-growing local database as long as the extracted feature vectors and predicted diagnostic probabilities of the correspondent classification model can be outputted.

Novel Human Artificial Intelligence Hybrid Framework Pinpoints Thyroid Nodule Malignancy and Identifies Overlooked Second-Order Ultrasonographic Features.

We present a Human Artificial Intelligence Hybrid (HAIbrid) integrating framework that reweights Thyroid Imaging Reporting and Data System (TIRADS) features and the malignancy score predicted by a convolutional neural network (CNN) for nodule malignancy stratification and diagnosis. We defined extra ultrasonographical features from color Doppler images to explore malignancy-relevant features. We proposed Gated Attentional Factorization Machine (GAFM) to identify second-order interacting features trained via a 10 fold distribution-balanced stratified cross-validation scheme on ultrasound images of 3002 nodules all finally characterized by postoperative pathology (1270 malignant ones), retrospectively collected from 131 hospitals. Our GAFM-HAIbrid model demonstrated significant improvements in Area Under the Curve (AUC) value (p-value < 10−5), reaching about 0.92 over the standalone CNN (~0.87) and senior radiologists (~0.86), and identified a second-order vascularity localization and morphological pattern which was overlooked if only first-order features were considered. We validated the advantages of the integration framework on an already-trained commercial CNN system and our findings using an extra set of ultrasound images of 500 nodules. Our HAIbrid framework allows natural integration to clinical workflow for thyroid nodule malignancy risk stratification and diagnosis, and the proposed GAFM-HAIbrid model may help identify novel diagnosis-relevant second-order features beyond ultrasonography.

The Dual Roles of Nano Zero-Valent Iron and Zinc Oxide in Antibiotics Resistance Genes (ARGs) Spread in Sediment.

Nanoparticles (NPs) are widely used and ubiquitous in the environment, but the consequences of their release into the environment on antibiotics resistance genes (ARGs), microbial abundance, and community, are largely unknown. Therefore, this study examined the effect of nano zero-valent iron (nZVI) and zinc oxide (nZnO) on tetracycline resistance genes (tet-ARGs) and class 1 integron (intI1) in sediment under laboratory incubation. The coexistence of NPs and tetracycline (TC) on tet-ARGs/intI1 was also investigated. It was found that nZVI and nZnO promoted tet-ARGs/intI1 abundance in sediment without TC but reduced the inducing effect of TC on tet-ARGs/intI1 in sediment overlaid with TC solution. Without TC, nZVI, intI1, and the bacterial community could directly promote tet-ARGs spread in nZVI sediment, while intI1 and bacterial abundance were the most directly important reasons for tet-ARGs spread in nZnO sediment. With TC, nZVI and bacterial community could reduce tet-ARGs abundance in nZVI sediment, while nZnO and bacterial community could directly promote tet-ARGs in nZnO sediment. Finally, these findings provided valuable information for understanding the role of NPs in promoting and reducing ARGs in the environment.

Untargeted metabolomics and comparative flavonoid analysis reveal the nutritional aspects of pak choi.

Pak choi is a leafy vegetable with high economic value. Despite its importance, the information related to its metabolomics profile has still not been well-understood. This study aimed to determine the leaf metabolite composition of seven pak choi. In total, 513 metabolites belonging to 24 separate metabolite groups were detected. Pak choi leaves were rich in organic acids, amino acids, and flavonoids. There were ninety-two flavonoid compounds detected in pak choi leaves. Multivariate analysis revealed a distinct variation in the metabolite and flavonoid profile of green and purple leaved varieties. The flavonoid accumulation was comparatively greater in green leaved than purple leaf cultivar. This work provides novel insights into pak choi metabolomics profile, the flavonoids in particular, thus, to assess the nutritional value of this vegetable for humans.

Potential biomarkers of acute myocardial infarction based on co-expression network analysis.

Acute myocardial infarction (AMI) is a common cause of death in numerous countries. Understanding the molecular mechanisms of the disease and analyzing potential biomarkers of AMI is crucial. However, specific diagnostic biomarkers have thus far not been fully established and candidate regulatory targets for AMI remain to be determined. In the present study, the AMI gene chip dataset GSE48060 comprising blood samples from control subjects with normal cardiac function (n=21) and patients with AMI (n=26) was downloaded from Gene Expression Omnibus. The differentially expressed genes (DEGs) between the AMI and control groups were identified with the online tool GEO2R. The co-expression network of DEGs was analyzed by calculating the Pearson correlation coefficient of all gene pairs, mutual rank screening and cutoff threshold screening. Subsequently, the Gene Ontology (GO) database was used to analyze the genes' functions and pathway enrichment of genes in the most important modules was performed. Kyoto Encyclopedia of Genes and Genomes (KEGG) Disease and BioCyc were used to analyze the hub genes in the module to determine important sub-pathways. In addition, the expression of hub genes was confirmed by reverse transcription-quantitative PCR in AMI and control specimens. In the present study, 52 DEGs, including 26 upregulated and 26 downregulated genes, were identified. As key hub genes, three upregulated genes (AKR1C3, RPS24 and P2RY12) and three downregulated genes (ACSL1, B3GNT5 and MGAM) were identified from the co-expression network. Furthermore, GO enrichment analysis of all AMI co-expression network genes revealed functional enrichment mainly in 'RAGE receptor binding' and 'negative regulation of T cell cytokine production'. In addition, KEGG Disease and BioCyc analysis indicated functional enrichment of the genes RPS24 and P2RY12 in 'cardiovascular diseases', of AKR1C3 in 'cardenolide biosynthesis', of MGAM in 'glycogenolysis', of B3GNT5 in 'glycosphingolipid biosynthesis' and of ACSL1 in 'icosapentaenoate biosynthesis II'. In conclusion, the hub genes AKR1C3, RPS24, P2RY12, ACSL1, B3GNT5 and MGAM are potential markers of AMI, and have potential application value in the diagnosis of AMI.

Microstructure and Properties of Mg-Al-Ca-Mn Alloy with High Ca/Al Ratio Fabricated by Hot Extrusion.

Mg-Al-Ca-Mn alloys with Ca/Al ≥ 1 of AX33, AX44, and AX55 were prepared by combining three processes of water-cooling semi-continuous cast, homogenization heat treatment, and hot extrusion. The as-fabricated alloys translated into composites consisting of α-Mg solid solution + granular Al2Ca. These alloys exhibited some favourable properties such as a tensile strength of 324~350 MPa at room temperature and 187~210 MPa at elevated temperature of 423 K, an ignition temperature of 1292~1344 K, and so on. Variation trend between performance and content of Al and Ca is given in this paper. The result indicated that the emerged second-phase Al2Ca in the alloys was beneficial to the improvement in mechanical properties, heat resistance, flame retardation, and corrosion resistance.

Nanopore Sequencing and Hi-C Based De Novo Assembly of Trachidermus fasciatus Genome.

Trachidermus fasciatus is a roughskin sculpin fish widespread across the coastal areas of East Asia. Due to environmental destruction and overfishing, the population of this species is under threat. In order to protect this endangered species, it is important to have the genome sequenced. Reference genomes are essential for studying population genetics, domestic farming, and genetic resource protection. However, currently, no reference genome is available for Trachidermus fasciatus, and this has greatly hindered the research on this species. In this study, we integrated nanopore long-read sequencing, Illumina short-read sequencing, and Hi-C methods to thoroughly assemble the Trachidermus fasciatus genome. Our results provided a chromosome-level high-quality genome assembly with a predicted genome size of 542.6 Mbp (2n = 40) and a scaffold N50 of 24.9 Mbp. The BUSCO value for genome assembly completeness was higher than 96%, and the single-base accuracy was 99.997%. Based on EVM-StringTie genome annotation, a total of 19,147 protein-coding genes were identified, including 35,093 mRNA transcripts. In addition, a novel gene-finding strategy named RNR was introduced, and in total, 51 (82) novel genes (transcripts) were identified. Lastly, we present here the first reference genome for Trachidermus fasciatus; this sequence is expected to greatly facilitate future research on this species.

Tryptophan 2,3-dioxygenase inhibitory activities of tryptanthrin derivatives.

Tryptophan 2,3-dioxygenase (TDO) is becoming a promising therapeutic target due to its involvement in cancer and neurodegenerative diseases. Development of efficient TDO inhibitors is a prime strategy in disease treatment. However, the lack of a TDO inhibitor bioassay system slows the progress of TDO inhibitor research. Herein, an active recombinant human TDO (hTDO) was prepared under optimal expression conditions, an enzymatic assay was optimized, and two cellular assays of TDO activity were developed. Then, the potential TDO inhibitory activities of nine tryptanthrin derivatives (5a-5i) were evaluated, and the inhibitory constants (Ki), enzymatic and cellular half maximal inhibitory concentrations (IC50) were measured, and the type of inhibition was determined. The tryptanthrins had various levels of TDO inhibitory activities; tryptanthrins with a substituent at 8-position had stronger inhibitory activities than the other derivatives. Moreover, most of the compounds, except 5g and 5h, exhibited better inhibitory activities than the previously reported TDO inhibitor LM10. Furthermore, the molecular docking study of compounds 5c and 5d revealed that the O atom of the tryptanthrin ring is directed toward the heme iron (Fe) of hTDO via strong coordination interactions. These findings suggest that tryptanthrin and its derivatives have the potential to be developed as promising molecules for TDO-related target therapy.

Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles.

Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome.

Mutations in KCNJ11 are associated with the development of autosomal dominant, early-onset type 2 diabetes.

AIMS/HYPOTHESIS: More than 90% of Chinese familial early-onset type 2 diabetes mellitus is genetically unexplained. To investigate the molecular aetiology, we identified and characterised whether mutations in the KCNJ11 gene are responsible for these families. METHODS: KCNJ11 mutations were screened for 96 familial early-onset type 2 diabetic probands and their families. Functional significance of the identified mutations was confirmed by physiological analysis, molecular modelling and population survey. RESULTS: Three novel KCNJ11 mutations, R27H, R192H and S116F117del, were identified in three families with early-onset type 2 diabetes mellitus. Mutated KCNJ11 with R27H or R192H markedly reduced ATP sensitivity (E23K>R27H>C42R>R192H>R201H), but no ATP-sensitive potassium channel currents were detected in the loss-of-function S116F117del channel in vitro. Molecular modelling indicated that R192H had a larger effect on the channel ATP-binding pocket than R27H, which may qualitatively explain why the ATP sensitivity of the R192H mutation is seven times less than R27H. The shape of the S116F117del channel may be compressed, which may explain why the mutated channel had no currents. Discontinuation of insulin and implementation of sulfonylureas for R27H or R192H carriers and continuation/switch to insulin therapy for S116F117del carriers resulted in good glycaemic control. CONCLUSIONS/INTERPRETATION: Our results suggest that genetic diagnosis for the KCNJ11 mutations in familial early-onset type 2 diabetes mellitus may help in understanding the molecular aetiology and in providing more personalised treatment for these specific forms of diabetes in Chinese and other Asian patients.

A thienopyrimidine derivative induces growth inhibition and apoptosis in human cancer cell lines via inhibiting Aurora B kinase activity.

Aurora kinases play a key role in the regulation of mitosis and have been regarded as promising targets of cancer therapy. In this paper we describe a thienopyrimidine derivative (S7), a novel potent ATP-competitive hit inhibitor of Aurora B kinase screened through a HTS system, with the IC50 141.12 nM in the biochemical kinase activity assay. Human tumor cells treated with S7 showed dose-dependent inhibition of auto-phosphorylation of Aurora B on Thr232 and another widely-used marker specific for Aurora B kinase, the phosphorylation of Histone H3 (Ser 10), demonstrating endogenous Aurora B kinase activity were inhibited at cellular level. Moreover, S7 treatment induced proliferation inhibition, colony formation inhibition and apoptosis of human tumor cell lines in a dose- and time-dependent manner.

Design, synthesis and biological evaluation of benzothiazepinones (BTZs) as novel non-ATP competitive inhibitors of glycogen synthase kinase-3ß (GSK-3ß).

Glycogen synthase kinase-3ß (GSK-3ß) plays a key role in type II diabetes and Alzheimer's diseases, to which non-ATP competitive inhibitors represent an effectively therapeutical approach due to their good specificity. Herein, a series of small molecules benzothiazepinones (BTZs) as novel non-ATP competitive inhibitors of GSK-3ß have been designed and synthesized. The in vitro evaluation performed by luminescent assay showed most BTZ derivatives have inhibitory effects in micromolar scale. Among them compounds 6l, 6t and 6v have the IC50 values of 25.0 µM, 27.8 µM and 23.0 µM, respectively. Moreover 6v is devoid of any inhibitory activity in the assays to other thirteen protein kinases. Besides, SAR is analyzed and a hypothetical enzymatic binding mode is proposed by molecular docking study, which would be useful for new candidates design.

Identification of novel scaffold of benzothiazepinones as non-ATP competitive glycogen synthase kinase-3ß inhibitors through virtual screening.

Glycogen synthase kinase-3ß (GSK-3ß) is an important serine/threonine kinase that has been proved as a key target for neurodegenerative diseases and diabetes. Up to date, most of known inhibitors are bound to the ATP-binding pocket of GSK-3ß, which might lead widespread effects due to the high homology between kinases. Recently, some of its non-ATP competitive inhibitors had been confirmed having therapeutical effects owing to their high selectivity. This finding opens a new pathway to study hopeful drugs for treatment of these diseases. However, it is still a challenge nowadays on how to efficiently find non-ATP competitors. Here, we successfully discovered a novel scaffold of benzothiazepinones (BTZs) as selective non-ATP competitive GSK-3ß inhibitors through virtual screening approach. A 3D receptor model of substrate binding site of GSK-3ß was constructed and applied to screen against drug-like Maybridge database through Autodock program. BTZ compounds were top ranked as efficient hits and were then synthesized for further screening. Among them, the representative compound 4j showed activity to GSK-3ß (IC(50): 25 µM) in non-ATP competitive mechanism, and nearly no inhibitory effect on other 10 related protein kinases. Overall, the results point out that BTZ compounds might be useful in treatment of Alzheimer's disease and diabetes mellitus as novel GSK-3ß inhibitors. It also suggests, on the other hand, that virtual screening would provide a valuable tool in combination with in vitro assays for the identification of novel selective and potent inhibitors.

Carbonyl reductase 1 as a novel target of (-)-epigallocatechin gallate against hepatocellular carcinoma.

UNLABELLED: Human carbonyl reductase 1 (CBR1) converts the antitumor drug and anthracycline daunorubicin (DNR) into the alcohol metabolite daunorubicinol (DNROL) with significantly reduced antitumor activity and cardiotoxicity, and this limits the clinical use of DNR. Inhibition of CBR1 can thus increase the efficacy and decrease the toxicity of DNR. Here we report that (-)-epigallocatechin gallate (EGCG) from green tea is a promising inhibitor of CBR1. EGCG directly interacts with CBR1 and acts as a noncompetitive inhibitor with respect to the cofactor reduced nicotinamide adenine dinucleotide phosphate and the substrate isatin. The inhibition is dependent on the pH, and the gallate moiety of EGCG is required for activity. Molecular modeling has revealed that EGCG occupies the active site of CBR1. Furthermore, EGCG specifically enhanced the antitumor activity of DNR against hepatocellular carcinoma SMMC7721 cells expressing high levels of CBR1 and corresponding xenografts. We also demonstrated that EGCG could overcome the resistance to DNR by Hep3B cells stably expressing CBR1 but not by RNA interference of CBR1-HepG2 cells. The level of the metabolite DNROL was negatively correlated with that of EGCG in the cell extracts. Finally, EGCG decreased the cardiotoxicity of DNR in a human carcinoma xenograft model with both SMMC7721 and Hep3B cells in mice. CONCLUSION: These results strongly suggest that EGCG can inhibit CBR1 activity and enhance the effectiveness and decrease the cardiotoxicity of the anticancer drug DNR. These findings also indicate that a combination of EGCG and DNR might represent a novel approach for hepatocellular carcinoma therapy or chemoprevention.

Correlated mutation analysis on the catalytic domains of serine/threonine protein kinases.

BACKGROUND: Protein kinases (PKs) have emerged as the largest family of signaling proteins in eukaryotic cells and are involved in every aspect of cellular regulation. Great progresses have been made in understanding the mechanisms of PKs phosphorylating their substrates, but the detailed mechanisms, by which PKs ensure their substrate specificity with their structurally conserved catalytic domains, still have not been adequately understood. Correlated mutation analysis based on large sets of diverse sequence data may provide new insights into this question. METHODOLOGY/PRINCIPAL FINDINGS: Statistical coupling, residue correlation and mutual information analyses along with clustering were applied to analyze the structure-based multiple sequence alignment of the catalytic domains of the Ser/Thr PK family. Two clusters of highly coupled sites were identified. Mapping these positions onto the 3D structure of PK catalytic domain showed that these two groups of positions form two physically close networks. We named these two networks as theta-shaped and gamma-shaped networks, respectively. CONCLUSIONS/SIGNIFICANCE: The theta-shaped network links the active site cleft and the substrate binding regions, and might participate in PKs recognizing and interacting with their substrates. The gamma-shaped network is mainly situated in one side of substrate binding regions, linking the activation loop and the substrate binding regions. It might play a role in supporting the activation loop and substrate binding regions before catalysis, and participate in product releasing after phosphoryl transfer. Our results exhibit significant correlations with experimental observations, and can be used as a guide to further experimental and theoretical studies on the mechanisms of PKs interacting with their substrates.