Polymer - Xerogel Composites for Controlled Release Wound Dressings

Many polymers and composites have been used to prepare active wound dressings. These materials have typically exhibited potentially toxic burst release of the drugs within the first few hours followed by a much slower, potentially ineffective drug release rate thereafter. Many of these materials also degraded to produce inflammatory and cytotoxic products. To overcome these limitations, composite active wound dressings were prepared here from two fully biodegradable and tissue compatible components, silicon oxide sol–gel (xerogel) microparticles that were embedded in tyrosine-poly(ethylene glycol)-derived poly(ether carbonate) copolymer matrices. Sustained, controlled release of drugs from these composites was demonstrated in vitro using bupivacaine and mepivacaine, two water-soluble local anesthetics commonly used in clinical applications. By systematically varying independent compositional parameters of the composites, including the hydrophilic:hydrophobic balance of the tyrosine-derived monomers and poly(ethylene glycol) in the copolymers and the porosity, weight ratio and drug content of the xerogels, drug release kinetics approaching zero-order were obtained. Composites with xerogel mass fractions up to 75% and drug payloads as high as 13% by weight in the final material were fabricated without compromising the physical integrity or the controlled release kinetics. The copolymer–xerogel composites thus provided a unique solution for the sustained delivery of therapeutic agents from tissue compatible wound dressings

A dynamic truck dispatching problem in marine container terminal

In this paper, a dynamic truck dispatching problem of a marine container terminal is described and discussed. In this problem, a few containers, encoded as work instructions, need to be transferred between yard blocks and vessels by a fleet of trucks. Both the yard blocks and the quay are equipped with cranes to support loading/unloading operations. In order to service more vessels, any unnecessary idle time between quay crane (QC) operations need to be minimised to speed up the container transfer process. Due to the unpredictable port situations that can affect routing plans and the short calculation time allowed to generate one, static solution methods are not suitable for this problem. In this paper, we introduce a new mathematical model that minimises both the QC makespan and the truck travelling time. Three dynamic heuristics are proposed and a genetic algorithm hyperheuristic (GAHH) under development is also described. Experiment results show promising capabilities the GAHH may offer

Cooperative Double-Layer Genetic Programming Hyper-Heuristic for Online Container Terminal Truck Dispatching

In a marine container terminal, truck dispatching is a crucial problem that impacts on the operation efficiency of the whole port. Traditionally, this problem is formulated as an offline optimisation problem, whose solutions are, however, impractical for most real-world scenarios primarily because of the uncertainties of dynamic events in both yard operations and seaside loading–unloading operations. These solutions are either unattractive or infeasible to execute. Herein, for more intelligent handling of these uncertainties and dynamics, a novel cooperative double-layer genetic programming hyper-heuristic (CD-GPHH) is proposed to tackle this challenging online optimisation problem. In this new CD-GPHH, a novel scenario genetic programming (GP) approach is added on top of a traditional GP method that chooses among different GP heuristics for different scenarios to facilitate optimised truck dispatching. In contrast to traditional arithmetic GP (AGP) and GP with logic operators (LGP) which only evolve on one population, our CD-GPHH method separates the scenario and the calculation into two populations, which improved the quality of solutions in multi-scenario problems while reducing the search space. Experimental results show that our CD-GPHH dominates AGP and LGP in solving a multi-scenario function fitting problem as well as a truck dispatching problem in container terminal

A novel AMPK activator, WS070117, improves lipid metabolism discords in hamsters and HepG2 cells

<p>Abstract</p> <p>Background</p> <p>WS070117 is a novel small molecule compound that significantly improves lipid metabolism disorders in high-fat-diet (HFD) induced hyperlipidemia in hamsters.</p> <p>Methods and Results</p> <p>We evaluated liver/body weight ratio, liver histology, serum and hepatic lipid content in HFD-fed hamsters treated with WS070117 for 8 weeks. Comparing with HFD fed hamsters, WS070117 (2 mg/kg per day and above) reduced serum triglyceride (TAG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) and hepatic cholesterol and triglyceride contents. Oil Red O staining of liver tissue also showed that WS070117 improved lipid accumulation. We then carried out an experiment in the oleic acid (OLA)-induced steatosis model in HepG2 cell to investigate the lipid-lowering effect of WS070117. Oleic acid (0.25 mM) markedly induced lipid accumulation in HepG2 cells, but WS070117 (10 μM) inhibited cellular lipid accumulation. In OLA-treated HepG2 cells, WS070117 (above 1 μM) treatment reduced lipid contents which synthesized from [1-¹⁴C] labeled acetic acid. Because WS070117 is an analog of adenosine, we evaluated the effect of WS070117 on AMP-activated protein kinase (AMPK) signaling. The results showed that the activation of AMPK in OLA-induced steatosis in HepG2 cells was up-regulated by treatment with 0.1, 1 and 10 μM WS070117. The hepatic cellular AMPK phosphorylation is also up regulated by WS070117 (6 and 18 mg/kg) treatment in HFD fed hamsters.</p> <p>Conclusion</p> <p>These new findings identify WS070117 as a novel molecule that regulates lipid metabolism in the hyperlipidemia hamster model. In vitro and in vivo studies suggested that WS070117 may regulate lipid metabolism through stimulating the activation of AMPK and its downstream pathways.</p

BER Analysis of SCMA-OFDM Systems in the Presence of Carrier Frequency Offset

Sparse code multiple access (SCMA) building upon orthogonal frequency division multiplexing (OFDM) is a promising wireless technology for supporting massive connectivity in future machine-type communication networks. However, the sensitivity of OFDM to carrier frequency offset (CFO) poses a major challenge because it leads to orthogonality loss and incurs intercarrier interference (ICI). In this paper, we investigate the bit error rate (BER) performance of SCMA-OFDM systems in the presence of CFO over both Gaussian and multipath Rayleigh fading channels. We first model the ICI in SCMA-OFDM as Gaussian variables conditioned on a single channel realization for fading channels. The BER is then evaluated by averaging over all codeword pairs considering the fading statistics. Through simulations, we validate the accuracy of our BER analysis and reveal that there is a significant BER degradation for SCMAOFDM systems when the normalized CFO exceeds 0.02

CERKL regulates autophagy via the NAD-dependent deacetylase SIRT1

<p>Macroautophagy/autophagy is an important intracellular mechanism for the maintenance of cellular homeostasis. Here we show that the <i>CERKL</i> (ceramide kinase like) gene, a retinal degeneration (RD) pathogenic gene, plays a critical role in regulating autophagy by stabilizing SIRT1. <i>In vitro</i> and <i>in vivo</i>, suppressing CERKL results in impaired autophagy. SIRT1 is one of the main regulators of acetylation/deacetylation in autophagy. In CERKL-depleted retinas and cells, SIRT1 is downregulated. ATG5 and ATG7, 2 essential components of autophagy, show a higher degree of acetylation in CERKL-depleted cells. Overexpression of SIRT1 rescues autophagy in CERKL-depleted cells, whereas CERKL loses its function of regulating autophagy in SIRT1-depleted cells, and overexpression of CERKL upregulates SIRT1. Finally, we show that CERKL directly interacts with SIRT1, and may regulate its phosphorylation at Ser27 to stabilize SIRT1. These results show that CERKL is an important regulator of autophagy and it plays this role by stabilizing the deacetylase SIRT1.</p

Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis

BackgroundStroke is the second leading cause of death worldwide, causing a considerable disease burden. Ischemic stroke is more frequent, but haemorrhagic stroke is responsible for more deaths. The clinical management and treatment are different, and it is advantageous to classify their risk as early as possible for disease prevention. Furthermore, retinal characteristics have been associated with stroke and can be used for stroke risk estimation. This study investigated machine learning approaches to retinal images for risk estimation and classification of ischemic and haemorrhagic stroke.Study designA case-control study was conducted in the Shenzhen Traditional Chinese Medicine Hospital. According to the computerized tomography scan (CT) or magnetic resonance imaging (MRI) results, stroke patients were classified as either ischemic or hemorrhage stroke. In addition, a control group was formed using non-stroke patients from the hospital and healthy individuals from the community. Baseline demographic and medical information was collected from participants' hospital medical records. Retinal images of both eyes of each participant were taken within 2 weeks of admission. Classification models using a machine-learning approach were developed. A 10-fold cross-validation method was used to validate the results.Results711 patients were included, with 145 ischemic stroke patients, 86 haemorrhagic stroke patients, and 480 controls. Based on 10-fold cross-validation, the ischemic stroke risk estimation has a sensitivity and a specificity of 91.0% and 94.8%, respectively. The area under the ROC curve for ischemic stroke is 0.929 (95% CI 0.900 to 0.958). The haemorrhagic stroke risk estimation has a sensitivity and a specificity of 93.0% and 97.1%, respectively. The area under the ROC curve is 0.951 (95% CI 0.918 to 0.983).ConclusionA fast and fully automatic method can be used for stroke subtype risk assessment and classification based on fundus photographs alone

Novel bi-allelic variants of CHMP1A contribute to pontocerebellar hypoplasia type 8: additional clinical and genetic evidence

Pontocerebellar hypoplasia type 8(PCH8) is a rare neurodegenerative disorder, reportedly caused by pathogenic variants of the CHMP1A in autosomal recessive inheritance, and CHMP1A variants have also been implicated in other diseases, and yet none of the prenatal fetal features were reported in PCH8. In this study, we investigated the phenotype and genotype in a human subject with global developmental delay, including clinical data from the prenatal stage through early childhood. Prenatally, the mother had polyhydramnios, and the bilateral ventricles of the fetus were slightly widened. Postnatally, the infant was observed to have severely delayed psychomotor development and was incapable of visual tracking before 2 years old and could not fix on small objects. The young child had hypotonia, increased knee tendon reflex, as well as skeletal malformations, and dental crowding; she also had severe and recurrent pulmonary infections. Magnetic resonance imaging of the brain revealed a severe reduction of the cerebellum (vermis and hemispheres) and a thin corpus callosum. Through whole exome sequencing and whole genomics sequencing, we identified two novel compound heterozygous variations in CHMP1A [c.53 T &gt; C(p.Leu18Pro)(NM_002768.5) and exon 1 deletion region (NC_000016.10:g.89656392_89674382del)]. cDNA analysis showed that the exon1 deletion region led to the impaired expression, and functional verification with zebrafish embryos using base edition indicated variant c.53 T &gt; C (p.Leu18Pro), causing dysplasia of the cerebellum and pons. These results provide further evidence that CHMP1A variants in a recessive inheritance pattern contribute to the clinical characteristics of PCH8 and further expand our knowledge of the phenotype and genotype spectrum of PCH8

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase&nbsp;chain&nbsp;reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of&nbsp;prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics