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The single-component colistin E2, with superior antibacterial activity and lower toxicity, was being developed as the latest generation of polymyxin drugs. However, colistin E2 has not been tested quantitatively in biological matrices. In this study, based on the quantitative detection of CMS and colistin by Zhao et al., 15N-labeled colistin E2 was used as an internal standard (IS) for a more accurate quantitative detection of CMS E2 in human plasma. A rapid ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC–MS/MS) assay method was developed for determination of CMS E2 and colistin E2 in human plasma. After pretreatment of plasma samples by 96-well SPE Supra-Clean Weak Cation Exchange (WCX) plate, the formed colistin E2 was detected and quantified by UHPLC–MS/MS system. All plasma lots were found to be free of interferences with the analyte. The matrix has no effect on the quantitation of the analyte. No significant effect of the carryover was observed. The dilution integrity was demonstrated in plasma samples without the loss of accuracy and precision. The lower limit of quantification (LLOQ) was 0.0300 mg/L for colistin E2 in plasma with accuracy (relative error, 5.1 ~ 12.7%) and precision (relative standard deviation, -5.7 ~ 9.3%). Stability of CMS E2 and colistin E2 was demonstrated in biological samples before and during sample treatment, and in the extract. Furthermore, this method was successfully applied to the analysis of plasma samples obtained from Chinese healthy volunteers receiving a CMS E2 dose of 5 mg/kg. In conclusion, the detection method was characterized by speed and high accuracy, which laid a solid foundation for the subsequent development of CMS E2 drug.

Human Interleukin 2 (IL-2) has already achieved impressive results as a therapeutic agent for cancer and autoimmune diseases. However, one of the limitations associated with the clinical application of IL-2 is its short half-life owing to rapid clearance by the kidneys. Modification with fatty acids, as an albumin noncovalent ligand with the advantage of deep penetration into tissues and high activity-to-mass ratio, is a commonly used approach to improve the half-life of native peptides and proteins. In this investigation, we attempted to extend the half-life of IL-2 through conjugation with a fatty acid using sortase A (srtA). We initially designed and optimized three IL-2 analogues with different peptide linkers between the C-terminus of IL-2 and srtA recognition sequence (LPETG). Among these, analogue A3 was validated as the optimal IL-2 analogue for further modification. Next, six fatty acid moieties with the same fatty acid and different hydrophilic spacers were conjugated to A3 through srtA. The six bioconjugates generated were screened for in vitro biological activity, among which bioconjugate B6 was identified as near-optimal to IL-2. Additionally, B6 could effectively bind albumin through the conjugated fatty acid, which contributed to a significant improvement in its pharmacokinetic properties in vivo. In summary, we have developed a novel IL-2 bioconjugate, B6, modified with fatty acids using srtA, which may effectively serve as a new-generation long-acting IL-2 immunotherapeutic agent.

Adalimumab, a full-length monoclonal antibody, is widely used as an anti-tumor necrosis factor-α (anti-TNF-α) agent. In this article, we aimed to prolong the in vivo half-life of adalimumab antigen-binding fragment (Fab) through Sortase A (SrtA)-mediated conjugation of its Fab with fatty acid (FA). In our study, adalimumab Fab analog was prepared by adding an SrtA recognition sequence (LPETGG) and His6 tag to the heavy chain C-terminal of the Fab via (G4S)3 linker. Four FA motifs with different linkers were designed and synthesized by solid-phase methodology, then conjugated with the Fab analog using SrtA to produce Fab bioconjugates. The successful generation of four Fab bioconjugates (Fab–FA1, Fab–FA2, Fab–FA3, and Fab–FA4) was confirmed by SDS-PAGE (sodium dodecyl sulfate polyacrylamide gel electrophoresis) and mass spectrometry. Then, the bioactivities and half-life of these Fab bioconjugates were examined using TNF-α-/human serum albumin (HSA)-binding enzyme-linked immunosorbent assay, cytotoxicity assay, and pharmacokinetic study, respectively. All Fab bioconjugates exhibited similar TNF-α-neutralizing activities when compared with the Fab analog, even in the presence of albumin, indicating that there were no apparent influences on the functional site of Fab after FA modification. However, different degrees of affinity for HSA were observed among these Fab–FA bioconjugates, with Fab–FA3 exhibiting the maximal affinity. An in vivo study in mice further revealed remarkably improved pharmacokinetics of Fab– FA3 with a 15.2-fold longer plasma half-life (19.86 hours) compared with that of the Fab analog (1.31 hours). In summary, we have developed a novel long-acting adalimumab Fab bioconjugate, Fab–FA3, with more sustained in vivo activity, which can be used for drug development targeting TNF-α-mediated inflammatory diseases.

Head and neck cancer is a heterogeneous disease, originating in the squamous cells lining the larynx (voice box), mouth, pharynx (throat), nasal cavity and salivary glands. Head and neck cancer diagnosis at the later stage is greatly influencing the survival rate of the patient. It makes a mandatory situation to identify this cancer at the earlier stages of development with a suitable biomarker. Squamous cell carcinoma antigen (SCC-Ag) is a circulating serum tumour biomarker, and the elevated level has been found in the head and neck cancer patients and highly correlated with the tumour volume. The present research was carried out to detect and quantify the level of SCC-Ag on titanium oxide (TiO2)-modified interdigitated electrode sensor (IDE) by SCC-Ag antibody. The detection of SCC-Ag was found at the level of 100 fM, while it was improved to 10 fM when the antibody was conjugated with gold nanostar, representing a 10-fold improvement. Interestingly, this enhancement in sensitivity is 1000-folds higher than other substrates. Moreover, the specificity analysis was carried out using two different control proteins and noticed that the antibody only recognised SCC-Ag, indicating the specific detection on IDE-TiO2 sensing surface.

A convolutional neural network (CNN) has been used to successfully realize end-to-end bearing fault diagnosis due to its powerful feature extraction ability. However, the CNN is prone to focus on local information, ignoring the relationship between the whole and the part of the signal due to its unique structure. In addition, it extracts some fault features with poor robustness under noisy environment. A novel diagnosis model based on feature fusion and feature selection, GL-mRMR-SVM, is proposed to address this problem in this paper. First, the model combines the global features in the time-domain and frequency-domain of the raw data with the local features extracted by CNN to make full use of the signal information and overcome the weakness of traditional CNNs neglecting the overall signal. Then, the max-relevance min-redundancy (mRMR) algorithm is used to automatically extract the discriminative features from the fused features without any prior knowledge. Finally, the extracted discriminative features are input into the SVM for training and output the fault recognition results. The proposed GL-mRMR-SVM model was evaluated through experiments on bearing data of Case Western Reserve University (CWRU) and CUT-2 platform. The experimental results show that the proposed method is more effective than other intelligent diagnosis methods.

Antigen-binding fragments (Fabs) are preferred alternatives to antibodies for medical application, whereas their short half-lives limit therapeutic effectiveness. Albumin binding domain (ABD) with high affinity for albumin possesses a great potential in enhancing in vivo performance of biotherapeutics. In this study, to mitigate the poor pharmacokinetics of adalimumab Fab targeting tumor necrosis factor-α (TNFα), an ABD fusion strategy was applied innovatively using GA3, ABD035, ABD094 and ABDCon with high affinities for albumin. The prokaryotic expression, bioactivities and half-lives of those novel Fab-ABD fusions were investigated in vitro and in vivo. All Fab-ABD fusions were successfully purified, and they retained similar TNFα-binding activities with the unmodified Fab control, also presented high affinities for human/mouse serum albumin (HSA/MSA). Additionally, the simultaneous binding of the difunctional Fab-ABD fusions to TNFα and albumin was verified, and ABD fused to Fab neither interfered with Fab-TNFα binding nor impaired the association between Fc fragment of IgG receptor and transporter (FcRn) and albumin. Based on the highest binding affinity for HSA and maximal yield, Fab-ABDCon was selected for further evaluation. Fab-ABDCon showed similar thermostability with the Fab control and robust stability in human and mouse plasma. Most notably, the pharmacokinetics of Fab-ABDCon in mice was significantly improved with a 22-fold longer plasma half-life (28.2 h) compared with that of Fab control (1.31 h), which have contributed to its satisfactory therapeutic efficacy in murine TNFα-induced hepatonecrosis model. Thus, Fab-ABDCon could be a promising long-acting candidate suitable for drug development targeting TNFα-mediated inflammatory disease.

Gearbox fault diagnosis plays an irreplaceable role in ensuring the safe operation of rotating machinery equipment. However, many researches have only diagnosed single faults, and have not detected single faults from compound faults of gearbox. Therefore, in this paper, a framework based on random forest hybrid classifier (RFHC) is proposed for single fault detection, which not only identifies various fault types, but also separates the single fault from compound faults. Meanwhile, an improved Dempster–Shafer (IDS) information fusion method is developed to fuse the result obtained by the hybrid classifier. Extensive evaluations of the proposed methods on the QPZZ-II experimental platform datasets showed that the proposed framework detects the single faults from the compound faults effectively, which reduces the categorization complexity of a single classifier and improves the overall performance of the detection framework. Moreover, compared with the diagnosis result of a single sensor, IDS can achieve higher average fusion precision and improve the reliability of gearbox single fault detection.

The group preserving methods proposed by Liu [Int. J. Non-Linear Mech., 2001 and CMES-Comp. Model. Eng., 2006] for ordinary differential equations or differential algebraic equations (DAEs) adopted the Cayley transform or exponential mapping to formulate the Lie group from its Lie algebra. In this paper, we combine the Euler scheme with the group preserving methods to obtain the high accuracy group preserving techniques. We propose a group preserving correction scheme (GPCS) via exponential mapping and a modified group preserving correction scheme (MGPCS) by considering constraint. The two schemes provide single-step explicit time integrators for systems of DAEs. Some numerical examples are examined, showing that the GPCS and MGPCS work very well and have good computational efficiency and high accuracy.

Biosynthesis of Zinc oxide nanoparticles (ZnONPs) from natural plants stands as a promising nanodrug delivery system in cancer therapeutics. Marsdenia tenacissima (M.t), a Chinese medicinal plant has been extensively used as clinical remedy for treating several types of cancer. In this present study, ZnONPs were synthesized from Marsdenia tenacissima and its anti cancer potency was assessed against in vitro laryngeal cancer cell line Hep-2. The biosynthesized Marsdenia tenacissima Zinc Oxide Nanoparticles [M.t-ZnONPs] was characterized using UV-visible Spec, SEM, TEM and EDAX analysis. The cytotoxic and apoptotic inducing potential of M.t-ZnONPs was assessed by MTT assay and staining such as DCFH-DA, AO/EtBr, Rhodamine 123, DAPI and comet assay. The anticancer potential of M.t-ZnONPs was analysed by Real time PCR analysis of proapoptotic, antiapoptotic and caspases proteins. Our present findings showed characteristic and morphological representation of synthesized M.t-ZnONPs by UV-visible Spec, SEM, TEM and EDAX analysis. M.t-ZnONPs exhibits its cytotoxicity by inhibiting the viability of Hep-2 cells and IC50 value was obtained by MTT assay. The results of apoptotic staining techniques in M.t-ZnONPs treated Hep-2 cells confirm with excess ROS generation, disruption of mitochondrial membrane potential and nuclear damage. The apoptotic inducing potential of M.t-ZnONPs was also evidenced by upregulation of proapoptotic proteins Bax, Caspase 3 & 9 and downregultion of antiapoptotic protein Bcl-2 by RT-PCR analysis. Finally, these results suggested that biosynthesized M.t-ZnONPs is an effective anticancer agent which induces apoptosis in Hep-2 laryngeal cell line and thus conclude that M.t-ZnONPs, a valid anticancer strategy in treating various cancer.

In recent years, finite realtime nonlinear hybrid systems(FRNHS) have been widely used in the fields of biology, chemical control, embedded systems, etc. Its safety verification becomes more and more important. Compared with traditional hybrid systems, the safety verification of FRNHS is decidable, but the computational accuracy of its reach set demands higher. Group preserving scheme(GPS) achieves better accuracy and stabilization than traditional numerical algorithms due to its inherent properties in Minkowski space. This paper creatively applies GPS into the safety verification of FRNHS. Based on Euler method and GPS, we put forward the corresponding enhanced algorithms, which make the numerical computational accuracy higher. Through the experiment, the errors introduced by four various numerical computation methods are compared. The experimental results indicate that the proposed enhanced GPS in this paper has higher accuracy and can effectively make safety verification for FRNHS within the $$\epsilon \text {-}$$∈-error approximation.

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster–Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions.

Effective feature selection can help improve the classification performance in bearing fault diagnosis. This paper proposes a novel feature selection method based on bearing fault diagnosis called Feature-to-Feature and Feature-to-Category- Maximum Information Coefficient (FF-FC-MIC), which considers the relevance among features and relevance between features and fault categories by exploiting the nonlinearity capturing capability of maximum information coefficient. In this method, a weak correlation feature subset obtained by a Feature-to-Feature-Maximum Information Coefficient (FF-MIC) matrix and a strong correlation feature subset obtained by a Feature-to-Category-Maximum Information Coefficient (FC-MIC) matrix are merged into a final diagnostic feature set by an intersection operation. To evaluate the proposed FF-FC-MIC method, vibration data collected from two bearing fault experiment platforms (CWRU dataset and CUT-2 dataset) were employed. Experimental results showed that accuracy of FF-FC-MIC can achieve 97.50%, and 98.75% on the CWRU dataset at the motor speeds of 1750 rpm, and 1772 rpm, respectively, and reach 91.75%, 94.69%, and 99.07% on CUT-2 dataset at the motor speeds of 2000 rpm, 2500 rpm, 3000 rpm, respectively. A significant improvement of FF-FC-MIC has been confirmed, since the p-values between FF-FC-MIC and the other methods are 1.166 &times, 10 &minus, 3 , 2.509 &times, 5 , and 3.576 &times, 2 , respectively. Through comparison with other methods, FF-FC-MIC not only exceeds each of the baseline feature selection method in diagnosis accuracy, but also reduces the number of features.

The purpose of this study was to examine the expression of MMP-14, 15 and 16 (MT1, MT2 and MT3-MMP) in supraglottic carcinoma and to explore their clinical significance. Expression of MMP-14, 15 and 16 was examined using RT-PCR and immunohistochemistry methods in samples from 85 cases of supraglottic carcinoma. Results showed that both mRNA and protein expression of MMP-14, 15 and 16 were increased in supraglottic carcinoma tissues compared to expression in control adjacent non-neoplastic tissues (P < 0.05). Expression of MMP-14, but not MMP-15 and MMP-16, was significantly increased in the T3 and neck nodal metastasis groups compared with the T1-2 group and the group without nodal metastasis at both mRNA and protein levels (P < 0.05). Expression of MMP-14 mRNA and protein was also higher in tumors of patients with stage III-IV disease compared to patients with clinical stage I-II tumors (P < 0.05). Kaplan-Meier survival curves showed that the groups with high MMP-14 protein expression had a poorer prognosis than patients in the groups with weak or negative expression of MMP-14 protein (P < 0.05). In conclusion, MMP-14 may play an important role in the progression of supraglottic carcinoma and may be a novel prognostic factor for patients with supraglottic carcinoma.

The purpose of this study was to explore the inhibiting role of MMP-9 gene silence in the invasive ability and growth of laryngeal squamous cell carcinoma (LSCC) by lentivirus mediated RNA interference. MMP-9-RNAi-lentivirus and the control lentivirus (GFP-lentivirus) were transfected into Hep-2 cells. Gelatin zymography showed the proteins expression of MMP-9 were knockdown in the MMP-9 siRNA transfected Hep-2 cells. The invasive activity and viability of MMP-9 siRNA treated Hep-2 cells were decreased than the control cells measured with modified Boyden chamber assay and MTT assay. In animal experiment, 20 nude mice bearing Hep-2 cell tumor were randomly separated into the experimental and the control groups. The former were intratumorally injected with MMP-9-RNAi-lentivirus, and the later were injected with equivalent dose of GFP-lentivirus. Results showed the average weight and volume of tumor in MMP-9-RNAi-lentivirus treated group were significantly lower than those in the control group (P < .01). The protein expressions of MMP-9 were downregulated in tumors of MMP-9-RNAi-lentivirus treatment. The PCNA index was obviously lower in the tumors of treated group than that in the control group (P < .01). These results suggest that MMP-9 gene silence by lentivirus mediated RNA interference can inhibit invasion and growth of LSCC.

Dysregulation of a numerous microRNAs (miRNAs) has been implicated in laryngeal squamous cell carcinoma (LSCC). Among those miRNAs, miR‑21 and miR‑221 are co‑overexpressed and commonly target the phosphatase and tensin homolog protein (PTEN) that is located in the PTEN‑Akt signaling pathway. The present study investigated whether co‑inhibition of miR‑21 and miR‑221 induced synergistic apoptosis of human LSCC cells. Methyl thiazolyl tetrazolium (MTT) and terminal deoxynucleotidyl‑transferase‑mediated deoxynucleotide triphosphate nick end labeling (TUNEL) assays were used to observe the potential effect of miR‑21 and miR‑221 on cell viability and apoptosis in cells co‑transfected with anti‑miRNA oligonucleotide (AMO)‑21 and AMO‑221. The protein expression levels of PTEN, Akt and p53 were determined by western blotting. The cellular abundance of 6 pro‑apoptotic miRNAs transcribed by p53 mediation, consisting of miR‑15a, miR‑16‑1, miR‑26a, miR‑34a, miR‑143 and miR‑203, was measured with using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR). MTT results indicate that in vitro co‑transfection of AMO‑21 and AMO‑221 leads to a decline in cell viability, compared with the transfection of AMO alone. This result was verified by the detection of apoptosis using TUNEL assays. Co‑transfection of AMO‑21 and AMO‑221 resulted in a marked reduction in Akt phosphorylation and enhanced expression of PTEN and p53 were observed; consequently, leading to an amplification of the transcription of 6 pro‑apoptotic miRNAs. The present findings confirmed that co‑inhibition of miR‑21 and miR‑221 synergistically triggers cell apoptosis in vitro. The altered PTEN‑Akt signaling and p53‑mediated amplification of the transcription of pro‑apoptotic miRNAs may be involved in the observed synergistic effect. The present study provides novel insights into the mechanism underlying apoptosis‑associated miRNA‑miRNA mutual regulation in LSCC.

In order to solve the rapid decision of ore blending scheme in iron ore sintering process, the prediction model of the basic sintering characteristics of mixed iron ore and sinter quality has been established by three algorithms including the support vector machines, BP neural network and general regression neural network. The results show, the model based on support vector machine algorithm is better, which can accurately predict the basic sintering characteristics and sinter quality indexes; the accuracy of prediction for assimilation temperature, liquid fluidity and the binding phase strength are 90 % , 93% and 91 % respectively, based on the physical and chemical properties of raw material, and the accuracy of prediction for the drum strength and productivity are 89% and 88%, based on the basic sintering characteristics of mixed iron ore and technical parameters.

Serum exosomes containing noncoding RNA (ncRNA) play an important role in both physiological and pathological conditions. However, biological function of exosomal ncRNA remains unclear. The aim of the study was to investigate the prognostic and diagnostic values of exosomal ncRNA by comparing the amounts of exosomal miR-21 and HOTAIR in serum of laryngeal squamous cell carcinoma (LSCC) patients with those of polyps of vocal cords, and by determinating whether combined detection of the two molecules could provide useful information in the diagnosis of LSCC. Exosomes were isolated from the serum samples of 52 LSCC patients and those of 49 patients with polyps of vocal cords. TEM and Western blot were applied for the confirmation of isolated exosomes by observing the ultra structure and testing CD63 marker protein, respectively. RT-PCR was performed to detect the expression of miR-21 and HOTAIR in the exosomes. The receiver-operating characteristic (ROC) curve was generated to examine the prognostic value of the two molecules. The expression of exosomal miR-21 and HOTAIR was significantly higher in patients with LSCC than those with vocal cord polyps. There were significant differences of serum exosomal miR-21 and HOTAIR expressions between the advanced T classifications (T3/T4) or clinical stages (III/IV) and the early stages. The patients with lymph node metastasis had higher serum exosomal miR-21 and HOTAIR expressions than those without. There were no differences between patient sex, tumor locations and differentiations. The area under the ROC curve of combined examination of exosomal HOTAIR and miR-21 for diagnosing LSCC was 87.6 %, which was significantly higher than 80.1 % of miR-21 (p = 0.0359) or 72.7 % of HOTAIR (p = 0.0012), showing 94.2 and 73.5 % of sensitivity and specificity, respectively, in differentiating the malignant from benign laryngeal disease. Serum exosomal miR-21 and HOTAIR were significantly correlated with clinical parameters of LSCC, and combined evaluation of their serum expressions may be a valuable biomarker to screen LSCC and might be a promising predicting tool for LSCC patient.