Core-shell poly(lactide-co-ε-caprolactone)-gelatin fiber scaffolds as pH-sensitive drug delivery systems

Dual-drug-loaded pH-responsive fiber scaffolds were successfully prepared by coaxial electrospinning. These were designed with the aim of being sutured into the resection site after tumor removal, to aid recovery and prevent cancer recurrence. The shell was made up of a mixture of gelatin and sodium bicarbonate (added to provide pH-sensitivity), and was loaded with the anti-inflammatory drug ciprofloxacin; the core comprised poly(lactide-co-ε-caprolactone) with the chemotherapeutic doxorubicin hydrochloride. Scanning electron microscopy revealed most fibers were smooth and homogeneous. Transmission electron microscopy demonstrated the presence of a clear core/shell structure. The fiber scaffolds were further characterized using infrared spectroscopy and X-ray diffraction, which proved that both drugs were present in the fibers in the amorphous form. The gelatin shells were cross-linked with glutaraldehyde to enhance their stability, and water contact angle measurements used to confirm they remained hydrophilic after this process, with angles between 10 and 35°. This is important for onward applications, since a hydrophilic surface is known to encourage cell proliferation. During in vitro drug release studies, a rapid and acid-responsive release of ciprofloxacin was seen, accompanied by sustained and long-term doxorubicin release. Both the release profiles and the mechanical strength of the fibers can effectively be tuned through the sodium bicarbonate content of the fibers: for instance, the break stress varies from 2.00 MPa to 2.57 MPa with an increase in sodium bicarbonate content. The pH values of aqueous media exposed to the scaffolds decrease only slightly, by less than 0.5 pH units, over the two-month timescale, suggesting that only minimal fiber degradation occurs during this time. The fiber scaffolds also have good biocompatibility, as revealed by in vitro cytotoxicity experiments. Overall, our results demonstrate that the novel scaffolds reported here are promising pH-sensitive drug delivery systems, and may be candidates for use after tumor resection surgery

A process for preparing an ultra-thin, adhesiveless, multi-layered, patterned polymer substrate

A process for preparing an ultra-thin, adhesiveless, multi-layered, patterned polymer substrate is disclosed. The process may be used to prepare both rigid and flexible cables and circuit boards. A substrate is provided and a polymeric solution comprising a self-bonding, soluble polymer and a solvent is applied to the substrate. Next, the polymer solution is dried to form a polymer coated substrate. The polymer coated substrate is metallized and patterned. At least one additional coating of the polymeric solution is applied to the metallized, patterned, polymer coated substrate and the steps of metallizing and patterning are repeated. Lastly, a cover coat is applied. When preparing a flexible cable and flexible circuit board, the polymer coating is removed from the substrate

Neural progenitor cells generate motoneuron-like cells to form functional connections with target muscles after transplantation into the musculocutaneous nerve

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Electrospun gelatin/sodium bicarbonate and poly(lactide-co-ε-caprolactone)/sodium bicarbonate nanofibers as drug delivery systems

In this work, we report electrospun nanofibers made of model hydrophobic (poly(lactide-co-ε-caprolactone); PLCL) and hydrophilic (gelatin) polymers. We explored the effect on drug release of the incorporation of sodium bicarbonate (SB) into these fibers, using the potent antibacterial agent ciprofloxacin as a model drug. The fibers prepared are smooth and have relatively uniform diameters lying between ca. 600 and 850nm. The presence of ciprofloxacin in the fibers was confirmed using IR spectroscopy. X-ray diffraction showed the drug to be incorporated into the fibers in the amorphous form. In vitro drug release studies revealed that, as expected, more rapid drug release was seen with gelatin fibers than those made of PLCL, and a greater final release percentage was obtained. The inclusion of SB in the gelatin fibers imparts them with pH sensitivity: gelatin/SB fibers showed faster release at pH5 than pH7.4, while fibers without SB gave the same release profiles at both pHs. The PLCL fibers have no pH sensitivity, even when SB was included, as a result of their hydrophobic structure precluding the ingress of solvent. In vitro cell culture studies showed that all the fibers are able to promote cell proliferation. The ciprofloxacin loaded fibers are effective in inhibiting Escherichia coli and Staphylococcus aureus growth in antibacterial tests. Thus, the gelatin-based fibers can be used as pH-responsive drug delivery systems, with potential applications for instance in the treatment of tumor resection sites. Should these become infected, the pH would drop, resulting in ciprofloxacin being released and the infection halted

Theoretical study of electronic Raman scattering of Borocarbide superconductors

The electronic Raman scattering of Borocarbide superconductors is studied based on the weak coupling theory with $s+g$-wave gap symmetry. The low energy behaviors and the relative peak positions can be naturally understood, while the explanation of the detailed shape of the $B_{1g}$ peak seems to require a strong inelastic interaction not present in the weak coupling theory.Comment: Revtex 4 file, 9 pages and 5 figure

Dr. Yang Zhong: an explorer on the road forever

On the morning of September 25th 2017, grievous news spread from the remote Ordos region of Inner Mongolia to Fudan University campus in Shanghai. Professor Yang Zhong, a famous botanist and the Dean of Fudan University’s graduate school, passed away in a tragic car accident while on a business trip

Pan-genome analysis highlights the role of structural variation in the evolution and environmental adaptation of Asian honeybees.

The Asian honeybee, Apis cerana, is an ecologically and economically important pollinator. Mapping its genetic variation is key to understanding population-level health, histories and potential capacities to respond to environmental changes. However, most efforts to date were focused on single nucleotide polymorphisms (SNPs) based on a single reference genome, thereby ignoring larger scale genomic variation. We employed long-read sequencing technologies to generate a chromosome-scale reference genome for the ancestral group of A. cerana. Integrating this with 525 resequencing data sets, we constructed the first pan-genome of A. cerana, encompassing almost the entire gene content. We found that 31.32% of genes in the pan-genome were variably present across populations, providing a broad gene pool for environmental adaptation. We identified and characterized structural variations (SVs) and found that they were not closely linked with SNP distributions; however, the formation of SVs was closely associated with transposable elements. Furthermore, phylogenetic analysis using SVs revealed a novel A. cerana ecological group not recoverable from the SNP data. Performing environmental association analysis identified a total of 44 SVs likely to be associated with environmental adaptation. Verification and analysis of one of these, a 330 bp deletion in the Atpalpha gene, indicated that this SV may promote the cold adaptation of A. cerana by altering gene expression. Taken together, our study demonstrates the feasibility and utility of applying pan-genome approaches to map and explore genetic feature variations of honeybee populations, and in particular to examine the role of SVs in the evolution and environmental adaptation of A. cerana

Computational Model for Urban Growth Using Socioeconomic Latent Parameters

Land use land cover changes (LULCC) are generally modeled using multi-scale spatio-temporal variables. Recently, Markov Chain (MC) has been used to model LULCC. However, the model is derived from the proportion of LULCC observed over a given period and it does not account for temporal factors such as macro-economic, socio-economic, etc. In this paper, we present a richer model based on Hidden Markov Model (HMM), grounded in the common knowledge that economic, social and LULCC processes are tightly coupled. We propose a HMM where LULCC classes represent hidden states and temporal fac-tors represent emissions that are conditioned on the hidden states. To our knowledge, HMM has not been used in LULCC models in the past. We further demonstrate its integration with other spatio-temporal models such as Logistic Regression. The integrated model is applied on the LULCC data of Pune district in the state of Maharashtra (India) to predict and visualize urban LULCC over the past 14 years. We observe that the HMM integrated model has improved prediction accuracy as compared to the corresponding MC integrated modelComment: 12 page