Preparation of an amphiphilic peptide (P13) with proton sponge effect and analysis of its antitumor activity.

In order to prevent drugs from being captured and degraded by the acidic environment of organelles, such as lysosomes, after entering cells, this study designed and synthesized a novel carrier amphiphilic polypeptide (DGRHHHLLLAAAA), designated P13, for use as a tumor-targeting drug delivery vehicle. The P13 peptide was synthesized by the solid phase synthesis method, and its self-assembly behavior and drug-loading capacity in aqueous solution were studied and characterizedin vitro. Doxorubicin (DOX) was loaded by dialysis method, and P13 and DOX were mixed at a mass ratio of 6:1 to form regular rounded globules. The acid-base buffering capacity of P13 was investigated determined by acid-base titration. The results revealed that P13 had excellent acid-base buffering capacity, a critical micelle concentration value of about 0.000 21 g l-1, and the particle size of P13-Dox nanospheres was 167 nm. The drug encapsulation efficiency and drug loading capacity of micelles were 20.40 ± 1.21% and 21.25 ± 2.79%, respectively. At the concentration of 50µg ml-1of P13-DOX , the inhibition rate was 73.35%. The results of thein vivoantitumor activity assay in mice showed that P13-DOX also exhibited excellent inhibitory effect on tumor growth, compared with the tumor weight of 1.1 g in the control group, the tumor weight in the P13-DOX-treated group was only 0.26 g. Additionally, the results of hematoxylin and eosin staining of the organs showed that P13-DOX had no damaging effect on normal tissues. The novel amphiphilic peptide P13 with proton sponge effect designed and prepared in this study is expected to be a promising tumor-targeting drug carrier with excellent application potential.

Transcriptome Dynamics of Brassica juncea Leaves in Response to Omnivorous Beet Armyworm (Spodoptera exigua, Hübner).

Cruciferous plants manufacture glucosinolates (GSLs) as special and important defense compounds against insects. However, how insect feeding induces glucosinolates in Brassica to mediate insect resistance, and how plants regulate the strength of anti-insect defense response during insect feeding, remains unclear. Here, mustard (Brassica juncea), a widely cultivated Brassica plant, and beet armyworm (Spodoptera exigua), an economically important polyphagous pest of many crops, were used to analyze the changes in GSLs and transcriptome of Brassica during insect feeding, thereby revealing the plant-insect interaction in Brassica plants. The results showed that the content of GSLs began to significantly increase after 48 h of herbivory by S. exigua, with sinigrin as the main component. Transcriptome analysis showed that a total of 8940 DEGs were identified in mustard challenged with beet armyworm larvae. The functional enrichment results revealed that the pathways related to the biosynthesis of glucosinolate and jasmonic acid were significantly enriched by upregulated DEGs, suggesting that mustard might provide a defense against herbivory by inducing JA biosynthesis and then promoting GSL accumulation. Surprisingly, genes regulating JA catabolism and inactivation were also activated, and both JA signaling repressors (JAZs and JAMs) and activators (MYCs and NACs) were upregulated during herbivory. Taken together, our results indicate that the accumulation of GSLs regulated by JA signaling, and the regulation of active and inactive JA compound conversion, as well as the activation of JA signaling repressors and activators, collectively control the anti-insect defense response and avoid over-stunted growth in mustard during insect feeding.

Photonic arbitrary waveform generation based on the temporal Talbot effect.

In this paper, we propose a novel photonic approach for generating arbitrary waveform. The approach is based on the property of real-time Fourier transform in the temporal Talbot effect, where the spectrum of the modulating analog signal is converted into the output time-domain waveform in each period. We present a concise and strict theoretical framework to reveal the relationship of real-time Fourier transform between the optical signals before and after the dispersion. A proof-of-concept experiment is implemented to validate the presented theoretical model. We propose to generate symmetrical or asymmetrical arbitrary waveforms by using double-sideband or single-sideband modulation, respectively, which is verified by simulation results. It is shown that the given approach can be used to generate a repetition-rate multiplied optical pulse train with arbitrary waveform by simply using a multi-tone RF signal with appropriate frequencies and powers.

iRSpot-EL: identify recombination spots with an ensemble learning approach.

MOTIVATION: Coexisting in a DNA system, meiosis and recombination are two indispensible aspects for cell reproduction and growth. With the avalanche of genome sequences emerging in the post-genomic age, it is an urgent challenge to acquire the information of DNA recombination spots because it can timely provide very useful insights into the mechanism of meiotic recombination and the process of genome evolution. RESULTS: To address such a challenge, we have developed a predictor, called IRSPOT-EL: , by fusing different modes of pseudo K-tuple nucleotide composition and mode of dinucleotide-based auto-cross covariance into an ensemble classifier of clustering approach. Five-fold cross tests on a widely used benchmark dataset have indicated that the new predictor remarkably outperforms its existing counterparts. Particularly, far beyond their reach, the new predictor can be easily used to conduct the genome-wide analysis and the results obtained are quite consistent with the experimental map. AVAILABILITY AND IMPLEMENTATION: For the convenience of most experimental scientists, a user-friendly web-server for iRSpot-EL has been established at http://bioinformatics.hitsz.edu.cn/iRSpot-EL/, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. CONTACT: bliu@gordonlifescience.org or bliu@insun.hit.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.

Identification of microRNA precursor with the degenerate K-tuple or Kmer strategy.

The microRNA (miRNA), a small non-coding RNA molecule, plays an important role in transcriptional and post-transcriptional regulation of gene expression. Its abnormal expression, however, has been observed in many cancers and other disease states, implying that the miRNA molecules are also deeply involved in these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Most existing methods in this regard were based on the strategy in which RNA samples were formulated by a vector formed by their Kmer components. But the length of Kmers must be very short; otherwise, the vector's dimension would be extremely large, leading to the "high-dimension disaster" or overfitting problem. Inspired by the concept of "degenerate energy levels" in quantum mechanics, we introduced the "degenerate Kmer" (deKmer) to represent RNA samples. By doing so, not only we can accommodate long-range coupling effects but also we can avoid the high-dimension problem. Rigorous jackknife tests and cross-species experiments indicated that our approach is very promising. It has not escaped our notice that the deKmer approach can also be applied to many other areas of computational biology. A user-friendly web-server for the new predictor has been established at http://bioinformatics.hitsz.edu.cn/miRNA-deKmer/, by which users can easily get their desired results.

[Application of Nice knot technique in wound closure of Gustilo type â ¢A and â ¢B open tibial fractures].

Objective: To explore the effectiveness of Nice knot technique for wound closure in Gustilo type ⅢA and ⅢB open tibial fractures. Methods: A retrospective study was performed on 22 patients with Gustilo type ⅢA and ⅢB open tibial fractures, who underwent wound closure using the Nice knot technique and were admitted between June 2021 and June 2022. There were 15 males and 7 females. The age ranged from 18 to 67 years, with an average of 41.9 years. The causes of injury included traffic accident in 11 cases, falling from height in 7 cases, and heavy object injuries in 4 cases. Fractures were located on the left side in 9 cases and on the right side in 13 cases. And 9 cases were type ⅢA fractures and 13 were type ⅢB fractures according to Gustilo classification. All patients had extensive soft tissue injuries, and no vascular or neurological damage was observed. The time from injury to debridement was 3-8 hours (mean, 6.5 hours). The sizes of wounds before operation and at 2 weeks after operation were measured and wound healing rate at 2 weeks after operation were calculated. The wound healing time and wound healing grading were recorded. The Vancouver Scar Scale (VSS) score was used to assess the wound scar after wound healed and the excellent and good rate was calculated. Results: The wound area was 21.0-180.0 cm 2 (mean, 57.82 cm 2) before operation, and it was 1.2-27.0 cm 2 (mean, 6.57 cm 2) at 2 weeks after operation. The wound healing rate at 2 weeks after operation was 76%-98% (mean, 88.6%). After operation, 2 cases needed to adjust Nice knot due to skin cutting and 1 case occurred soft tissue infection on the wound. The other patient's wounds healed. The average wound healing time was 27.8 days (range, 18-44 days). And the wound healing were grade A in 13 cases and grade B in 9 cases. VSS score was 2-9, with an average of 4.1; 10 cases were rated as excellent, 10 as good, and 2 as poor, with an excellent and good rate of 90.9%. All patients were followed up 9-24 months (mean, 14.6 months). During follow-up, no deep infection or osteomyelitis occurred. Two cases experienced fracture non-union, and were treated with compression fixation and bone grafting. The fractures of the other patients all healed, with a healing time of 85-190 days (mean, 148.2 days). Conclusion: Nice knot technique can be used in wound closure of Gustilo type ⅢA and ⅢB open tibial fractures effectively, which is easy to operate.

In situ analysis of the bulk and surface chemical compositions of organic aerosol particles.

Understanding the chemical and physical properties of particles is an important scientific, engineering, and medical issue that is crucial to air quality, human health, and environmental chemistry. Of special interest are aerosol particles floating in the air for both indoor virus transmission and outdoor atmospheric chemistry. The growth of bio- and organic-aerosol particles in the air is intimately correlated with chemical structures and their reactions in the gas phase at aerosol particle surfaces and in-particle phases. However, direct measurements of chemical structures at aerosol particle surfaces in the air are lacking. Here we demonstrate in situ surface-specific vibrational sum frequency scattering (VSFS) to directly identify chemical structures of molecules at aerosol particle surfaces. Furthermore, our setup allows us to simultaneously probe hyper-Raman scattering (HRS) spectra in the particle phase. We examined polarized VSFS spectra of propionic acid at aerosol particle surfaces and in particle bulk. More importantly, the surface adsorption free energy of propionic acid onto aerosol particles was found to be less negative than that at the air/water interface. These results challenge the long-standing hypothesis that molecular behaviors at the air/water interface are the same as those at aerosol particle surfaces. Our approach opens a new avenue in revealing surface compositions and chemical aging in the formation of secondary organic aerosols in the atmosphere as well as chemical analysis of indoor and outdoor viral aerosol particles.

Simplified Ab Initio Molecular Dynamics-Based Raman Spectral Simulations.

We describe a simplified approach to simulating Raman spectra from ab initio molecular dynamics (AIMD) calculations. The protocol relies on on-the-fly calculations of approximate molecular polarizabilities using the well-known sum over orbitals (as opposed to states) method. This approach bypasses the more accurate but computationally expensive approach to calculating molecular polarizabilities along AIMD trajectories, i.e., solving the coupled perturbed Hartree-Fock/Kohn-Sham equations. We demonstrate the advantages and limitations of our method through a few case studies targeting molecular systems of interest to surface- and/or tip-enhanced Raman spectroscopy practitioners.

Spatio-Spectral Characterization of Multipolar Plasmonic Modes of Au Nanorods via Tip-Enhanced Raman Scattering.

Tip-enhanced Raman (TER) spectral images of 4-thiobenzonitrile-coated Au nanorods map the spatial profiles and trace the resonances of dipolar and multipolar plasmonic modes that are characteristic of the imaged particles. For any particular rod, we observe sequential transitions between high-order modes at low frequency shifts and lower-order modes at higher frequencies. We also notice that higher-order modes (up to m = 4) are generally observed for long rods as compared to their shorter analogues, where longitudinal dipolar resonances (m = 1) are observable. In effect, this work adds a new dimension to local optical field mapping via TERS, which we have previously explored. Not only can the magnitudes, vector components, local/nonlocal characters of local optical fields be imaged through molecular TERS, but spatially varying local optical resonances are also direct observables.

Production of a bioflocculant from Klebsiella sp. OS-1 using brewery wastewater as a source.

This study evaluated the potential of bioflocculant production from a Klebsiella strain using brewery wastewater as nutrients. The bioflocculant named OS-1B produced by Klebsiella sp. OS-1 exhibited a good flocculating activity to kaolin clay suspension (around 95%), when the diluted brewery wastewater with 7.2 mg/L total nitrogen and 1013 mg/L CODCr was used as a nitrogen source. Glucose (15 g/L) is the most favorable carbon source for Klebsiella sp. OS-1 in bioflocculant production from brewery wastewater. The yielded bioflocculant is pH tolerant and thermally stable, suggesting its good industrial potential. OS-1B mainly comprises polysaccharide (69.4%) and protein (24.5%). Fourier-transform infrared spectra indicate the presence of hydroxyl, carboxyl, esters and amino groups in the bioflocculant molecules. Combined with the results of zeta potential measurements, bridging is suggested as the main flocculation mechanism for OS-1B flocculation with kaolin. Overall, brewery wastewater can be used as a substrate to produce bioflocculants.

Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning.

DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. With the rapid development of next generation of sequencing technique, the number of protein sequences is unprecedentedly increasing. Thus it is necessary to develop computational methods to identify the DNA-binding proteins only based on the protein sequence information. In this study, a novel method called iDNA-KACC is presented, which combines the Support Vector Machine (SVM) and the auto-cross covariance transformation. The protein sequences are first converted into profile-based protein representation, and then converted into a series of fixed-length vectors by the auto-cross covariance transformation with Kmer composition. The sequence order effect can be effectively captured by this scheme. These vectors are then fed into Support Vector Machine (SVM) to discriminate the DNA-binding proteins from the non DNA-binding ones. iDNA-KACC achieves an overall accuracy of 75.16% and Matthew correlation coefficient of 0.5 by a rigorous jackknife test. Its performance is further improved by employing an ensemble learning approach, and the improved predictor is called iDNA-KACC-EL. Experimental results on an independent dataset shows that iDNA-KACC-EL outperforms all the other state-of-the-art predictors, indicating that it would be a useful computational tool for DNA binding protein identification. .

DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representation.

DNA-binding proteins play an important role in most cellular processes. Therefore, it is necessary to develop an efficient predictor for identifying DNA-binding proteins only based on the sequence information of proteins. The bottleneck for constructing a useful predictor is to find suitable features capturing the characteristics of DNA binding proteins. We applied PseAAC to DNA binding protein identification, and PseAAC was further improved by incorporating the evolutionary information by using profile-based protein representation. Finally, Combined with Support Vector Machines (SVMs), a predictor called iDNAPro-PseAAC was proposed. Experimental results on an updated benchmark dataset showed that iDNAPro-PseAAC outperformed some state-of-the-art approaches, and it can achieve stable performance on an independent dataset. By using an ensemble learning approach to incorporate more negative samples (non-DNA binding proteins) in the training process, the performance of iDNAPro-PseAAC was further improved. The web server of iDNAPro-PseAAC is available at http://bioinformatics.hitsz.edu.cn/iDNAPro-PseAAC/.