Identification of Protein-Protein Interaction Associated Functions Based on Gene Ontology.

Protein-protein interactions (PPIs) involve the physical or functional contact between two or more proteins. Generally, proteins that can interact with each other always have special relationships. Some previous studies have reported that gene ontology (GO) terms are related to the determination of PPIs, suggesting the special patterns on the GO terms of proteins in PPIs. In this study, we explored the special GO term patterns on human PPIs, trying to uncover the underlying functional mechanism of PPIs. The experimental validated human PPIs were retrieved from STRING database, which were termed as positive samples. Additionally, we randomly paired proteins occurring in positive samples, yielding lots of negative samples. A simple calculation was conducted to count the number of positive samples for each GO term pair, where proteins in samples were annotated by GO terms in the pair individually. The similar number for negative samples was also counted and further adjusted due to the great gap between the numbers of positive and negative samples. The difference of the above two numbers and the relative ratio compared with the number on positive samples were calculated. This ratio provided a precise evaluation of the occurrence of GO term pairs for positive samples and negative samples, indicating the latent GO term patterns for PPIs. Our analysis unveiled several nuclear biological processes, including gene transcription, cell proliferation, and nutrient metabolism, as key biological functions. Interactions between major proliferative or metabolic GO terms consistently correspond with significantly reported PPIs in recent literature.

Engineered ß-glycosidase from Hyperthermophilic Sulfolobus solfataricus with Improved Rd-hydrolyzing Activity for Ginsenoside Compound K Production.

Hyperthermophilic Sulfolobus solfataricus ß-glycosidase (SS-ßGly), with higher stability and activity than mesophilic enzymes, has potential for industrial ginsenosides biotransformation. However, its relatively low ginsenoside Rd-hydrolyzing activity limits the production of pharmaceutically active minor ginsenoside compound K (CK). In this study, first, we used molecular docking to predict the key enzyme residues that may hypothetically interact with ginsenoside Rd. Then, based on sequence alignment and alanine scanning mutagenesis approach, key variant sites were identified that might improve the enzyme catalytic efficiency. The enzyme catalytic efficiency (kcat/Km) and substrate affinity (Km) of the N264D variant enzyme for ginsenoside Rd increased by 60% and decreased by 17.9% compared with WT enzyme, respectively, which may be due to a decrease in the binding free energy (∆G) between the variant enzyme and substrate Rd. In addition, Markov state models (MSM) analysis during the whole 1000-ns MD simulations indicated that altering N264 to D made the variant enzyme achieve a more stable SS-ßGly conformational state than the wild-type (WT) enzyme and corresponding Rd complex. Under identical conditions, the relative activities and the CK conversion rates of the N264D enzyme were 1.7 and 1.9 folds higher than those of the WT enzyme. This study identified an excellent hyperthermophilic ß-glycosidase candidate for industrial biotransformation of ginsenosides.

Residue Effect-Guided Design: Engineering of S. Solfataricus ß-Glycosidase to Enhance Its Thermostability and Bioproduction of Ginsenoside Compound K.

ß-Glycosidase from Sulfolobus solfataricus (SS-BGL) is a highly effective biocatalyst for the synthesis of compound K (CK) from glycosylated protopanaxadiol ginsenosides. In order to improve the thermal stability of SS-BGL, molecular dynamics simulations were used to determine the residue-level binding energetics of ginsenoside Rd in the SS-BGL-Rd docked complex and to identify the top ten critical contributors. Target sites for mutations were determined using dynamic cross-correlation mapping of residues via the Ohm server to identify networks of distal residues that interact with the key binding residues. Target mutations were determined rationally based on site characteristics. Single mutants and then recombination of top hits led to the two most promising variants SS-BGL-Q96E/N97D/N302D and SS-BGL-Q96E/N97D/N128D/N302D with 2.5-fold and 3.3-fold increased half-lives at 95 °C, respectively. The enzyme activities relative to those of wild-type for ginsenoside conversion were 161 and 116%, respectively..

Automated Detection of Endometrial Polyps from Hysteroscopic Videos Using Deep Learning.

Endometrial polyps are common gynecological lesions. The standard treatment for this condition is hysteroscopic polypectomy. However, this procedure may be accompanied by misdetection of endometrial polyps. To improve the diagnostic accuracy and reduce the risk of misdetection, a deep learning model based on YOLOX is proposed to detect endometrial polyps in real time. Group normalization is employed to improve its performance with large hysteroscopic images. In addition, we propose a video adjacent-frame association algorithm to address the problem of unstable polyp detection. Our proposed model was trained on a dataset of 11,839 images from 323 cases provided by a hospital and was tested on two datasets of 431 cases from two hospitals. The results show that the lesion-based sensitivity of the model reached 100% and 92.0% for the two test sets, compared with 95.83% and 77.33%, respectively, for the original YOLOX model. This demonstrates that the improved model may be used effectively as a diagnostic tool during clinical hysteroscopic procedures to reduce the risk of missing endometrial polyps.

Multimodal data fusion for supervised learning-based identification of USP7 inhibitors: a systematic comparison.

Ubiquitin-specific-processing protease 7 (USP7) is a promising target protein for cancer therapy, and great attention has been given to the identification of USP7 inhibitors. Traditional virtual screening methods have now been successfully applied to discover USP7 inhibitors aiming at reducing costs and speeding up time in several studies. However, due to their unsatisfactory accuracy, it is still a difficult task to develop USP7 inhibitors. In this study, multiple supervised learning classifiers were built to distinguish active USP7 inhibitors from inactive ligands. Physicochemical descriptors, MACCS keys, ECFP4 fingerprints and SMILES were first calculated to represent the compounds in our in-house dataset. Two deep learning (DL) models and nine classical machine learning (ML) models were then constructed based on different combinations of the above molecular representations under three activity cutoff values, and a total of 15 groups of experiments (75 experiments) were implemented. The performance of the models in these experiments was evaluated, compared and discussed using a variety of metrics. The optimal models are ensemble learning models when the dataset is balanced or severely imbalanced, and SMILES-based DL performs the best when the dataset is slightly imbalanced. Meanwhile, multimodal data fusion in some cases can improve the performance of ML and DL models. In addition, SMOTE, unbiased decoy selection and SMILES enumeration can improve the performance of ML and DL models when the dataset is severely imbalanced, and SMOTE works the best. Our study established highly accurate supervised learning classification models, which would accelerate the development of USP7 inhibitors. Some guidance was also provided for drug researchers in selecting supervised models and molecular representations as well as handling imbalanced datasets.

Prediction of Endometrial Carcinoma Using the Combination of Electronic Health Records and an Ensemble Machine Learning Method.

Endometrial carcinoma (EC) is a common cause of cancer death in women, and having an early accurate prediction model to identify this disease is crucial. The aim of this study was to develop a new machine learning (ML) model-based diagnostic prediction model for EC. We collected data from consecutive patients between November 2012 and January 2021 at tertiary hospitals in central China. Inclusion criteria included women undergoing endometrial biopsy, dilation and curettage, or hysterectomy. A total of 9 features, including patient demographics, vital signs, and laboratory and ultrasound results, were selected in the final analysis. This new model was combined with three top optimal ML methods, namely, logistic regression, gradient-boosted decision tree, and random forest. A total of 1,922 patients were eligible for final analysis and modeling. The ensemble model, called TJHPEC, was validated in an internal validation cohort and two external validation cohorts. The results showed that the AUC values were 0.9346, 0.8341, and 0.8649 for the prediction of total EC and 0.9347, 0.8073, and 0.871 for prediction of stage I EC. Nine clinical features were confirmed to be highly related to the prediction of EC in TJHPEC. In conclusion, our new model may be accurate for identifying EC, especially in the early stage, in the general population of central China.

[Differential Expression of Long Non-coding RNA Cancer Susceptibility Candidate 2 and Imprinted Gene H19 in Extrahepatic Cholangiocarcinoma].

Objective To investigate the expression and the potential roles of long non-coding RNA(lncRNA)cancer susceptibility candidate 2(CASC2)and imprinted gene H19 in extrahepatic cholangiocarcinoma(ECC). Methods Four samples from patients with ECC were collected for high-throughput sequencing which was conducted to reveal the transcriptomic profiles of lncRNA CASC2 and H19.Bioinformatics tools were employed to predict the potential roles of the two genes.Another 22 ECC tissue samples and the cholangiocarcinoma cell lines(RBE,QBC939,HuH-28,and HuCCT1)with different degrees of differentiation were selected for validation.The para-carcinoma tissue and normal human intrahepatic biliary epithelial cell(HIBEC)were used as the control groups.The expression levels of lncRNA CASC2 and H19 in carcinoma tissue,para-carcinoma tissue,and cell lines were determined by real-time quantitative polymerase chain reaction(qRT-PCR).The correlation analysis was carried out for the clinical indicators of patients with the expression levels of the target genes. Results The two target genes showed significantly different expression between carcinoma tissue and para-carcinoma tissue(all P<0.05).Specifically,CASC2 had higher expression level in the carcinoma tissue than in the para-carcinoma tissue(t=1.262,P=0.025),whereas the expression of H19 showed an opposite trend(t=1.285,P=0.005).The expression levels of CASC2 in QBC939(t=8.114,P=0.015)and HuH-28(t=9.202,P=0.012)cells were significantly higher than that in the control group.The expression levels of H19 were significantly lower in RBE(t=-10.244,P<0.001),QBC939(t=-10.476,P<0.001),HuH-28(t=-19.798,P<0.001),and HuCCT1(t=-16.193,P=0.004)cells than in the control group.Bioinformatics analysis showed that CASC2 was mainly involved in the metabolic process and H19 in the development of multicellular organisms.Both CASC2 and H19 were related to catalytic activity.The expression level of lncRNA CASC2 was correlated with pathological differentiation(χ 2=6.222,P=0.022)and lymph node metastasis(χ2=5.455,P=0.020),and that of lncRNA H19 with pathological differentiation(χ2=1.174,P=0.029)and tumor size(χ2=-0.507,P=0.037). Conclusions In the case of ECC,lncRNA CASC2 and H19 have transcription disorders.lncRNA CASC2 is generally up-regulated in the carcinoma tissue,while H19 is down-regulated.Both genes have the potential to become new molecular markers for ECC.

Nanosensor-Based Flexible Electronic Assisted with Light Fidelity Communicating Technology for Volatolomics-Based Telemedicine.

Telemedicine provides an attractive vision for tele-monitoring human health conditions and, thus, offers the opportunity for timely preventing chronic disease. A key limitation of promoting telemedicine in clinic application is the lack of a noninvasive med-tech and effective monitoring platform, which should be wearable and capable of high-performance tele-monitoring of health risk. Here we proposed a volatolomics-based telemedicine for continuously and noninvasively assessing human health status through continuously tracking the variation of volatile markers derived from human breath or skin. Particularly, a nanosensor-based flexible electronic was specifically designed to serve as a powerful platform for implementing the proposed cost-effective healthcare. An all-flexible and highly packed makeup (all functional units were integrated in a 2*2*0.19 cm3 plate) enables an electronic, compact configuration and the capability of resisting negative impact derived from customers' daily movement. Notably, the nanosensor-based electronic demonstrates high specificity, quick response rate (t90% = 4.5 s), and desirable low detection limit (down to 0.117 ppm) in continuous tele-monitoring chronic-disease-related volatile marker (e.g., acetone). Assisted by the power saved light fidelity (Li-Fi) communicating technology, a clinic proof on the specifically designed electronic for noninvasively and uninterrupted assessing potential health risk (e.g., diabetics) is successfully implemented, with the accuracy of around 81%. A further increase in the accuracy of prewarning is predicted by excluding the impact of individual differences such as the gender, age, and smoking status of the customer. These promising pilot results indicate a bright future for the tailor-made nanosensing-device-supported volatolomics-based telemedicine in preventing chronic diseases and increasing patients' survival rate.

Effect of Internal Curing by Super Absorbent Polymer on the Autogenous Shrinkage of Alkali-Activated Slag Mortars.

Alkali activated slag (AAS) mortar is becoming an increasingly popular green building material because of its excellent engineering properties and low CO2 emissions, promising to replace ordinary Portland cement (OPC) mortar. However, AAS's high shrinkage and short setting time are the important reasons to limit its wide application in engineering. This paper was conducted to investigate the effect of internal curing(IC) by super absorbent polymer (SAP) on the autogenous shrinkage of AAS mortars. For this, an experimental study was carried out to evaluate the effect of SAP dosage on the setting time, autogenous shrinkage, compressive strength, microstructure, and pore structure. The SAP were incorporated at different dosage of 0, 0.05, 0.1, 0.2, 0.3, 0.4, and 0.5 percent by weight of slag. The workability, physical (porosity), mechanical, and shrinkage properties of the mortars were evaluated, and a complementary study on microstructure was made. The results indicated that the setting time increased with an increase of SAP dosage due to the additional activator released by SAP. Autogenous shrinkage decreased with an increase of SAP dosage, and was mitigated completely when the dosage of SAP ≥ 0.2% wt of slag. Although IC by means of SAP reduced the compressive strength, this reduction (23% at 56 days for 0.2% SAP) was acceptable given the important role that it played on mitigating autogenous shrinkage. In the research, the 0.2% SAP dosage was the optimal content. The results can provide data and basis for practical application of AAS mortar.

Compact Yttria-Stabilized Zirconia Based Total NOx Sensor with a Dual Functional Co3O4/NiO Sensing Electrode.

Yttria-stabilized zirconia (YSZ) based potentiometric gas sensors have been widely utilized for detecting NOx (NO and NO2). Nevertheless, it is still remains challenging issue for YSZ-based sensors to sense total NOx due to the opposite response signals to NO and NO2. Herein, we report an efficient strategy to sense total NOx at high temperature (above 300 °C) by designing a dual functional sensing electrode (SE); namely, the SE will simultaneously convert NO (in NOx mixture) to NO2 and electrocatalyze all of the obtained NO2 to generate the response signal of total NOx. In comparison with those previously reported total NOx sensors, the proposed total NOx sensor will be featured with a simplified sensor configuration and desirable long-term stability. To confirm the practicability of the proposed strategy, the NO conversion rate of several metal oxides and their composites have been measured and it turns out that the Co3O4/NiO shows relatively high NO conversion rate. Further study indicates a YSZ-based sensor consisting of (Co3O4 + 20 wt % NiO)-SE and Mn-based RE demonstrates satisfactory performance in detecting total NOx. For instance, analogous response magnitude to NO and NO2 as well as the mixture of NO/NO2 (within 35 ppm) is witnessed for the sensor; particularly, the sensor gives acceptable stability and response/recovery rate at the operating temperature of 500 °C within the examined period. In summary, the use of dual functional SE (e.g., Co3O4/NiO composite SE) indeed addressed those issues of concern in monitoring the level of total NOx and has provided a promising alternative way for designing future high-performance total NOx sensor.

Light-Regulated Electrochemical Reaction Assisted Core-Shell Heterostructure for Detecting Specific Volatile Markers with Controllable Sensitivity and Selectivity.

Breath analysis has been considered a noninvasive, safe, and reliable way to diagnose cancer at very early stage. Rapid detection of cancer volatile markers in breath samples via a portable sensing device will lay the foundation of future early cancer diagnosis. Nevertheless, unsatisfactory sensitivity and specificity of these sensing devices restrain the clinical application of breath analysis. Herein, we proposed the strategy of designing the light-regulated electrochemical reaction assisted core-shell heterostructure to address the issue of concern; that is, the photoactive shell will be designed for trigging the light-regulated electrochemical reaction and enhancing the sensitivity while a catalytic active core will play the function of removing interference gases. After screening of various core candidates, Fe2O3 was found to exhibit relatively low conversion rate to 3-methylhexane, which is one of the representative volatile markers for breath analysis, suggesting that mutual interference would be eliminated by Fe2O3. Based on this assumption, an electrochemical sensor comprising core-shell Fe2O3@ZnO-SE (vs Mn-based RE) was fabricated and sensing properties to 6 kinds of volatile markers was evaluated. Interestingly, the thickness of ZnO shell significantly influenced the response behavior; typically, the Fe2O3@ZnO with shell thickness of 4.8 nm offers the sensor high selectivity to 3-methylhexane. In contrast, significantly mutual response interference is observed for the Fe2O3@ZnO with extremely thick/thin shell. Particularly, sensing properties are greatly enhanced upon illumination; a detection limit to 3-methylhexane can even be as low as 0.072 ppm which will be useful in clinic application. Besides, the high selectivity of the sensor to 3-methylhexane is further confirmed by the testing of simulated breath samples. In summary, we anticipate that the strategy proposed in this research will be a starting point for artificially tailoring the sensitivity and selectivity of future sensing devices.

Preparation and cold welding of silver nanowire based transparent electrodes with optical transmittances >90% and sheet resistances <10 ohm/sq.

In this article, silver nanowires (AgNWs) with aspect ratios of 1000 and lengths up to 200 µm are obtained by a modified polyol approach. These very long AgNWs are then utilized to prepare transparent electrodes (TEs) displaying a transmittance of 91.3% at a sheet resistance of 8.6 ohm/sq without any post-treatment. Furthermore, we also demonstrate a process for the cold welding of Ag NWs by simply dipping the AgNWs films into CTAB solutions, resulting in a further improvement for the optoelectronic performance. After the post-treatment, the AgNW-based TEs can achieve a transmittance of 93% at a sheet resistance of 9.5 ohm/sq. In addition, the electric behaviors of AgNW-based TEs are investigated. In the bulk-like regime, for the as-prepared AgNW-based TEs, the Figure of merit (FOM), DC to optical conductivity ratio reaches up to 566.8. After the cold welding process, the DC to optical conductivity ratio can reach even higher values (631.6). In the percolative regime, the as-prepared and welded AgNW-based TEs can achieve Π (FOM with percolative-like behavior) values of 166.8 and 242.1, respectively.

Highly thermostable, flexible, transparent, and conductive films on polyimide substrate with an AZO/AgNW/AZO structure.

Flexible transparent conductive films (TCFs) are used in a variety of optoelectronic devices. However, their use is limited due to poor thermostability. We report hybrid TCFs incorporation in both aluminum-doped zinc oxide (AZO) and silver nanowires (AgNWs). The layered AZO/AgNWs/AZO structure was deposited onto a transparent polyimide (PI) substrate and displayed excellent thermostability. When heated to 250 °C for 1 h, the change in resistivity (Rc) was less than 10% (Rc of pure AgNW film > 500) while retaining good photoelectric properties (Rsh = 8.6 Ohm/sq and T = 74.4%). Layering the AgNW network between AZO films decreased the surface roughness (Rrms < 8 nm) and enhances the mechanical flexibility of the hybrid films. The combination of these characteristics makes the hybrid film an excellent candidate for substrates of novel flexible optoelectronic devices which require high-temperature processing.

Preparation of solid silver nanoparticles for inkjet printed flexible electronics with high conductivity.

Silver nanoparticles (NPs) which could be kept in solid form and were easily stored without degeneration or oxidation at room temperature for a long period of time were synthesized by a simple and environmentally friendly wet chemistry method in an aqueous phase. Highly stable dispersions of aqueous silver NP inks, sintered at room temperature, for printing highly conductive tracks (∼8.0 µΩ cm) were prepared simply by dispersing the synthesized silver NP powder in water. These inks are stable, fairly homogeneous and suitable for a wide range of patterning techniques. The inks were successfully printed on paper and polyethylene terephthalate (PET) substrates using a common color printer. Upon annealing at 180 °C, the resistivity of the printed silver patterns decreased to 3.7 µΩ cm, which is close to twice that of bulk silver. Various factors affecting the resistivity of the printed silver patterns, such as annealing temperature and the number of printing cycles, were investigated. The resulting high conductivity of the printed silver patterns reached over 20% of the bulk silver value under ambient conditions, which enabled the fabrication of flexible electronic devices, as demonstrated by the inkjet printing of conductive circuits of LED devices.

Parallelized computation for computer simulation of electrocardiograms using personal computers with multi-core CPU and general-purpose GPU.

Biological computations like electrocardiological modelling and simulation usually require high-performance computing environments. This paper introduces an implementation of parallel computation for computer simulation of electrocardiograms (ECGs) in a personal computer environment with an Intel CPU of Core (TM) 2 Quad Q6600 and a GPU of Geforce 8800GT, with software support by OpenMP and CUDA. It was tested in three parallelization device setups: (a) a four-core CPU without a general-purpose GPU, (b) a general-purpose GPU plus 1 core of CPU, and (c) a four-core CPU plus a general-purpose GPU. To effectively take advantage of a multi-core CPU and a general-purpose GPU, an algorithm based on load-prediction dynamic scheduling was developed and applied to setting (c). In the simulation with 1600 time steps, the speedup of the parallel computation as compared to the serial computation was 3.9 in setting (a), 16.8 in setting (b), and 20.0 in setting (c). This study demonstrates that a current PC with a multi-core CPU and a general-purpose GPU provides a good environment for parallel computations in biological modelling and simulation studies.

Web-based sharing of electrocardiogram: a framework for information publishing.

Network-based data sharing is a current trend in medicine and healthcare. The search and retrieval architecture (SRA) we previously proposed for web-based sharing of electrocardiogram (ECG) facilitates the search and retrieval of ECG across hospitals via the Internet. The SRA has a triangle-like configuration including an ECG metadata registry, an ECG provider and an ECG querist. In this paper, we present a framework for ECG information publishing of an ECG provider. We also introduce a prototype of this framework, which was developed for an experimental scenario for assessment test based on MFER, an IEEE standard proposed from Japan. The assessment shows that the prototype of the framework can effectively publish the ECGs in a group of emulated MFER-conformant electrocardiographs, and the published ECGs can be successfully discovered and retrieved via the Internet.

Molecular simulation study of temperature effect on ionic hydration in carbon nanotubes.

Molecular dynamics simulations have been performed to investigate the hydration of Li(+), Na(+), K(+), F(-), and Cl(-) inside the carbon nanotubes at temperatures ranging from 298 to 683 K. The structural characteristics of the coordination shells of ions are studied, including the ion-oxygen radial distribution functions, the coordination numbers, and the orientation distributions of the water molecules. Simulation results show that the first coordination shells of the five ions still exist in the nanoscale confinement. Nevertheless, the first coordination shell structures of cations change more significantly than those of anions because of the preferential orientation of the water molecules induced by the carbon nanotube. The first coordination shells of cations are considerably less ordered in the nanotube than in the bulk solution, whereas the change of the first coordination shell structures of the anions is minor. Furthermore, the confinement induces the anomalous behavior of the coordination shells of the ions with temperature. The first coordination shell of K(+) are found to be more ordered as the temperature increases only in the carbon nanotube with the effective diameter of 1.0 nm, implying the enhancement of the ionic hydration with temperature. This is contrary to that in the bulk solution. The coordination shells of the other four ions do not have such behavior in the carbon nanotube with the effective diameter ranging from 0.73 to 1.00 nm. The easier distortion of the coordination shell of K(+) and the match of the shell size and the nanotube size may play roles in this phenomenon. The exchange of water molecules in the first coordination shells of the ions with the solution and the ion diffusion along the axial direction of the nanotube are also investigated. The mobility of the ions and the stability of the coordination shells are greatly affected by the temperature in the nanotube as in the bulk solutions. These results help to understand the biological and chemical processes at the high temperature.

Molecular dynamics simulation study of the structural characteristics of water molecules confined in functionalized carbon nanotubes.

Molecular dynamics (MD) simulations were performed to study the structural properties of water molecules confined in functionalized carbon nanotubes (CNTs). Four CNTs, two armchair-type (6, 6), (7, 7) and two zigzag-type (10, 0), (12, 0) CNTs, representing different helicities and different diameters, were chosen and functionalized at their open ends by the hydrophilic -COOH and the hydrophobic -CH3 groups. The structural properties of water molecules inside the functionalized CNTs, including the orientation distributions of dipole moment and O-H bonds, the length of the single-file water chain, and the average number of hydrogen bonds, were analyzed during a process of simulations. MD simulation results in this work showed that the -CH3 functional groups exert little special effects on the structural properties of water molecules. It is mainly due to the relatively small size of the -CH3 group and its hydrophobic nature, which is consistent with hydrophobic CNTs. For CNTs functionalized by -COOH groups, the configurations of -COOH groups, incurvature or excurvature, determine whether water molecules can enter the CNTs. The incurvature or excurvature configurations of -COOH groups are the results of synergy effects of the CNTs' helicity and diameter and control the flow direction of water molecules in CNTs.