Pharmacokinetics of ceftiofur sodium in cats following a single intravenous and subcutaneous injection.

Ceftiofur, a third-generation cephalosporin antibiotic, is being extensively used by pet doctors in China. In the current study, the detection method was developed for ceftiofur and its metabolites, desfuroylceftiofur (DCE) and desfuroylceftiofur conjugates (DCEC), in feline plasma. Then, the pharmacokinetics studies were performed following one single intravenous and subcutaneous injection of ceftiofur sodium in cats both at 5 mg/kg body weight (BW) (calculated as pure ceftiofur). Ceftiofur, DCE, and DCEC were extracted from plasma samples, then derivatized and further quantified by high-performance liquid chromatography. The concentrations versus time data were subjected to noncompartmental analysis to obtain the pharmacokinetics parameters. The terminal half-life (t1/2λz ) was calculated as 11.29 ± 1.09 and 10.69 ± 1.31 hr following intravenous and subcutaneous injections, respectively. After intravenous treatment, the total body clearance (Cl) and volume of distribution at steady-state (VSS ) were determined as 14.14 ± 1.09 ml hr-1  kg-1 and 241.71 ± 22.40 ml/kg, respectively. After subcutaneous injection, the peak concentration (Cmax ; 14.99 ± 2.29 µg/ml) was observed at 4.17 ± 0.41 hr, and the absorption half-life (t1/2ka ) and absolute bioavailability (F) were calculated as 2.83 ± 0.46 hr and 82.95%±9.59%, respectively. The pharmacokinetic profiles of ceftiofur sodium and its related metabolites demonstrated their relatively slow, however, good absorption after subcutaneous administration, poor distribution, and slow elimination in cats. Based on the time of drug concentration above the minimum inhibitory concentration (MIC) (T>MIC) calculated in the current study, an intravenous or subcutaneous dose at 5 mg/kg BW of ceftiofur sodium once daily is predicted to be effective for treating feline bacteria with a MIC value of ≤4.0 µg/ml.

Predicting MiRNA-Disease Associations by Graph Representation Learning Based on Jumping Knowledge Networks.

Growing studies have shown that miRNAs are inextricably linked with many human diseases, and a great deal of effort has been spent on identifying their potential associations. Compared with traditional experimental methods, computational approaches have achieved promising results. In this article, we propose a graph representation learning method to predict miRNA-disease associations. Specifically, we first integrate the verified miRNA-disease associations with the similarity information of miRNA and disease to construct a miRNA-disease heterogeneous graph. Then, we apply a graph attention network to aggregate the neighbor information of nodes in each layer, and then feed the representation of the hidden layer into the structure-aware jumping knowledge network to obtain the global features of nodes. The output features of miRNAs and diseases are then concatenated and fed into a fully connected layer to score the potential associations. Through five-fold cross-validation, the average AUC, accuracy and precision values of our model are 93.30%, 85.18% and 88.90%, respectively. In addition, for three case studies of the esophageal tumor, lymphoma and prostate tumor, 46, 45 and 45 of the top 50 miRNAs predicted by our model were confirmed by relevant databases. Overall, our method could provide a reliable alternative for miRNA-disease association prediction.

Identifying Pupylation Proteins and Sites by Incorporating Multiple Methods.

Pupylation is an important posttranslational modification in proteins and plays a key role in the cell function of microorganisms; an accurate prediction of pupylation proteins and specified sites is of great significance for the study of basic biological processes and development of related drugs since it would greatly save experimental costs and improve work efficiency. In this work, we first constructed a model for identifying pupylation proteins. To improve the pupylation protein prediction model, the KNN scoring matrix model based on functional domain GO annotation and the Word Embedding model were used to extract the features and Random Under-sampling (RUS) and Synthetic Minority Over-sampling Technique (SMOTE) were applied to balance the dataset. Finally, the balanced data sets were input into Extreme Gradient Boosting (XGBoost). The performance of 10-fold cross-validation shows that accuracy (ACC), Matthew's correlation coefficient (MCC), and area under the ROC curve (AUC) are 95.23%, 0.8100, and 0.9864, respectively. For the pupylation site prediction model, six feature extraction codes (i.e., TPC, AAI, One-hot, PseAAC, CKSAAP, and Word Embedding) served to extract protein sequence features, and the chi-square test was employed for feature selection. Rigorous 10-fold cross-validations indicated that the accuracies are very high and outperformed its existing counterparts. Finally, for the convenience of researchers, PUP-PS-Fuse has been established at https://bioinfo.jcu.edu.cn/PUP-PS-Fuse and http://121.36.221.79/PUP-PS-Fuse/as a backup.

Modified donor blood flow-preserved cross-leg anterolateral thigh flap procedure for complex lower extremity reconstruction.

BACKGROUND: Complex lower limb reconstruction due to severe trauma remains a challenge for reconstructive surgeons. Here, we introduce a modified donor blood flow-preserved cross-leg anterolateral thigh flap procedure and evaluate its clinical efficacy. METHODS: Between January 2013 and December 2019, 22 patients (range 10 to 64 years old) with unilateral lower limb injury underwent modified donor blood flow-preserved cross-leg anterolateral thigh flap procedures. Among them, 16 cases were traffic accidents, 5 cases were persistent ulcers, and 1 case was a degloving injury. The arterial pedicle of the flap was prepared in a Y-shaped fashion and microanastomosed to the posterior tibial artery of intact leg in a flow-through style. A split-thickness skin graft was applied to wrap the vascular pedicle after anastomosis. The flap was designed in a single or bilobed fashion according to the shape of the tissue defect. The operation time, the intraoperative blood loss and the length of hospital stays were recorded. The vascular pedicle was divided 4 weeks after anastomosis. Doppler ultrasound was performed to evaluate the blood flow of the donor posterior tibial artery during postoperative follow-up. RESULTS: All 22 flaps survived. The tissue defects ranged from 12 × 6 to 21 × 18 cm2. The flap sizes ranged from 14 × 7.5 to 24 × 21 cm2. The average operation time, intraoperative blood loss and length of hospital stays were 6.73 ± 1.49 h, 280.95 ± 59.25 ml and 30.55 ± 2.52 days, respectively. Eighteen flaps were designed in a single fashion, while four were in bilobed fashion. Twenty patients underwent fasciocutaneous flap transplantations, while two underwent musculocutaneous flap transplantations. Two cases developed local lysis of the flap which healed after further debridement. Direct suture of the incision after flap harvest was performed in 16 cases, while additional full-thickness skin grafting was performed in the remaining 6 cases. Further bone transport procedures were performed in 15 patients who had severe tibia bone defects. The blood flow of donor posterior tibial artery was confirmed in all patients during follow-ups. All patients recovered flap sensation at the final follow-up. The postoperative follow-ups ranged from 18 to 84 months, and no long-term complications were observed. CONCLUSIONS: The modified donor blood flow-preserved cross-leg anterolateral thigh flap procedure is an ideal method to repair severe lower limb trauma with tibial artery occlusion which avoids sacrificing the major artery of the uninjured lower limb.

Predicting S-nitrosylation proteins and sites by fusing multiple features.

Protein S-nitrosylation is one of the most important post-translational modifications, a well-grounded understanding of S-nitrosylation is very significant since it plays a key role in a variety of biological processes. For an uncharacterized protein sequence, it is a very meaningful problem for both basic research and drug development when we can firstly identify whether it is a S-nitrosylation protein or not, and then predict the specific S-nitrosylation site(s). This work has proposed two models for identifying S-nitrosylation protein and its PTM sites. Firstly, three kinds of features are extracted from protein sequence: KNN scoring of functional domain annotation, PseAAC and bag-of-words based on the physical and chemical properties of amino acids. Secondly, the synthetic minority oversampling technique is used to balance the data sets, and some state-of-the-art classifiers and feature fusion strategies are performed on the balanced data sets. In the five-fold cross-validation for predicting S-nitrosylation proteins, the results of Accuracy (ACC), Matthew's correlation coefficient (MCC) and area under ROC curve (AUC) are 81.84%, 0.5178, 0.8635, respectively. Finally, a model for predicting S-nitrosylation sites has been constructed on the basis of tripeptide composition (TPC) and the composition of k-spaced amino acid pairs (CKSAAP). To eliminate redundant information and improve work efficiency, elastic nets are employed for feature selection. The five-fold cross-validation tests have indicated the promising success rates of the proposed model. For the convenience of related researchers, the web-server named "RF-SNOPS" has been established at http://www.jci-bioinfo.cn/RF-SNOPS.

Pyrrolo[3,4- c]pyrazole Synthesis via Copper(Ι) Chloride-Catalyzed Oxidative Coupling of Hydrazones to Maleimides.

A variety of pyrrolo[3,4- c]pyrazole derivatives from readily available aldehyde hydrazones and maleimides via direct oxidative coupling under radical cascade reaction have been reported. This method offers satisfactory chemical yields and good functional group compatibility. Moreover, this practical approach is catalyzed by CuCl utilizing air as the oxidant and some control experiments were performed to elaborate the mechanism.

Multifunctional Silver Nanoparticle Interlayer-Modified ZnO as the Electron-Injection Layer for Efficient Inverted Organic Light-Emitting Diodes.

The insufficient electron injection constitutes the major obstacle to achieving high-performance inverted organic light-emitting diodes (OLEDs). Here, a facile electron-injection architecture featuring a silver nanoparticle (AgNPs) interlayer-modified sol-gel-derived transparent zinc oxide (ZnO) ultrathin film is proposed and demonstrated. The optimized external quantum efficiencies of the developed inverted fluorescent and phosphorescent OLEDs capitalized on our proposed electron-injection structure reached 4.0 and 21.2% at a current density of 20 mA cm-2 and increased by a factor of 1.90 and 2.86 relative to a reference device without the AgNP interlayer, while simultaneously reducing the operational voltage and substantially ameliorating the device efficiency. Detailed analyses reveal that the local surface plasmon resonance emanated from AgNPs plays three meaningful roles simultaneously: suppressing the surface plasmon polariton mode loss, aiding in energy-level alignments, and inducing and reinforcing the local exciton-plasmon coupling electric field. Among these interesting and multifunctional roles, the enhanced local exciton-plasmon coupling electric field dominates the electron injection enhancement and substantial increases the device efficiency. Additionally, the light-scattering effect also helps in recovering the trapped light energy flux and thus improves the device efficiency. The proposed approach and findings provide an alternative path to fabricate high-performance inverted OLEDs and other related organic electronic or optoelectronic devices.

The synthesis of multi-structured SnS nanocrystals toward enhanced performance for photovoltaic devices.

The synthesis of multi-scale SnS nanostructures with favorable fluorescence is facilely accomplished via a well-excogitated gentle process, involving simple precursors, stabilized chemical medium and primitive ligand exchange. The fabricated SnS nanocrystals can be adopted as hole transporting materials in photovoltaic devices for enhancing its power conversion efficiency.

HATCN-based charge recombination layers as effective interconnectors for tandem organic solar cells.

A comprehensive understanding of the energy-level alignment at the organic heterojunction interfaces is of paramount importance to optimize the performance of organic solar cells (OSCs). Here, the detailed electronic structures of organic interconnectors, consisting of cesium fluoride-doped 4,7-diphenyl-1,10-phenanthroline and hexaazatriphenylene-hexacarbonitrile (HATCN), have been investigated via in situ photoemission spectroscopy, and their impact on the charge recombination process in tandem OSCs has been identified. The experimental determination shows that the HATCN interlayer plays a significant role in the interface energetics with a dramatic decrease in the reverse built-in potential for electrons and holes from stacked subcells, which is beneficial to the charge recombination between HATCN and the adjacent layer. In accordance with the energy-level alignments, the open-circuit voltage of tandem OSC incorporating a HATCN-based interconnector is almost 2 times that of a single-cell OSC, revealing the effectiveness of the HATCN-based interconnectors in tandem organic devices.