Potential of DNMT and its Epigenetic Regulation for Lung Cancer Therapy

Lung cancer, the leading cause of mortality in both men and women in the United States, is largely diagnosed at its advanced stages that there are no effective therapeutic alternatives. Although tobacco smoking is the well established cause of lung cancer, the underlying mechanism for lung tumorigenesis remains poorly understood. An important event in tumor development appears to be the epigenetic alterations, especially the change of DNA methylation patterns, which induce the most tumor suppressor gene silence. In one scenario, DNA methyltransferase (DNMT) that is responsible for DNA methylation accounts for the major epigenetic maintenance and alternation. In another scenario, DNMT itself is regulated by the environment carcinogens (smoke), epigenetic and genetic information. DNMT not only plays a pivotal role in lung tumorigenesis, but also is a promising molecular bio-marker for early lung cancer diagnosis and therapy. Therefore the elucidation of the DNMT and its related epigenetic regulation in lung cancer is of great importance, which may expedite the overcome of lung cancer

Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification

Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the significant data imbalance and obvious extraneous artifacts, i.e., the hair and ruler markings, discriminative feature extraction from dermoscopic images is very challenging. In this study, we seek to resolve these problems respectively towards better representation learning for lesion features. Specifically, a GAN-based data augmentation (GDA) strategy is adapted to generate synthetic melanoma-positive images, in conjunction with the proposed implicit hair denoising (IHD) strategy. Wherein the hair-related representations are implicitly disentangled via an auxiliary classifier network and reversely sent to the melanoma-feature extraction backbone for better melanoma-specific representation learning. Furthermore, to train the IHD module, the hair noises are additionally labeled on the ISIC2020 dataset, making it the first large-scale dermoscopic dataset with annotation of hair-like artifacts. Extensive experiments demonstrate the superiority of the proposed framework as well as the effectiveness of each component. The improved dataset publicly avaliable at https://github.com/kirtsy/DermoscopicDataset.Comment: ICONIP 2021 conferenc

Investigation of glucose-modified liposomes using polyethylene glycols with different chain lengths as the linkers for brain targeting

Background: An intimidating challenge to transporting drugs into the brain parenchyma is the presence of the blood-brain barrier (BBB). Glucose is an essential nutritional substance for brain function sustenance, which cannot be synthesized by the brain. Its transport primarily depends on the glucose transporters on the brain capillary endothelial cells. In this paper, the brain-targeted properties of glucose-modified liposomes using polyethylene glycols with different chain lengths as the linkers were compared and evaluated to establish an optimized drug-delivery system. Methods: Coumarin 6-loaded liposomes (GLU200-LIP, GLU400-LIP, GLU1000-LIP, and GLU2000-LIP) composed of phospholipids and glucose-derived cholesterols were prepared by thin-film dispersion-ultrasound method. The BBB model in vitro was developed to evaluate the transendothelial ability of the different liposomes crossing the BBB. The biodistribution of liposomes in the mice brains was identified by in vivo and ex vivo nearinfrared fluorescence imaging and confocal laser scanning microscopy and further analyzed quantitatively by high-performance liquid chromatography. Results: Glucose-derived cholesterols were synthesized and identified, and coumarin 6-loaded liposomes were prepared successfully. The particle sizes of the four types of glucose-modified liposomes were around or smaller than 100 nm with a polydispersity index less than 0.300. GLU400-LIP, GLU1000-LIP, and GLU2000-LIP achieved higher cumulative cleared volumes on BBB model in vitro after 6 hours compared with GLU200-LIP (P < 0.05) and were significantly higher than that of the conventional liposome (P < 0.001). The qualitative and quantitative biodistribution results in the mice showed that the accumulation of GLU1000-LIP in the brain was the highest among all the groups (P < 0.01 versus LIP). Conclusion: The data indicated that GLU400-LIP, GLU1000-LIP, and GLU2000-LIP all possess the potential of brain targeting, among which GLU1000-LIP, as a promising drug-delivery system, exhibited the strongest brain delivery capacity.Nanoscience & NanotechnologyPharmacology & PharmacySCI(E)0ARTICLE163-175

Linear brain measurement: a new screening method for cognitive impairment in elderly patients with cerebral small vessel disease

BackgroundThe old adults have high incidence of cognitive impairment, especially in patients with cerebral small vessel disease (CSVD). Cognitive impairment is not easy to be detected in such populations. We aimed to develop clinical prediction models for different degrees of cognitive impairments in elderly CSVD patients based on conventional imaging and clinical data to determine the better indicators for assessing cognitive function in the CSVD elderly.Methods210 CSVD patients were screened out by the evaluation of Magnetic Resonance Imaging (MRI). Then, participants were divided into the following three groups according to the cognitive assessment results: control, mild cognitive impairment (MCI), and dementia groups. Clinical data were collected from all patients, including demographic data, biochemical indicators, carotid ultrasound, transcranial Doppler (TCD) indicators, and linear measurement parameters based on MRI.ResultsOur results showed that the brain atrophy and vascular lesions developed progressive worsening with increased degree of cognitive impairment. Crouse score and Interuncal distance/Bitemporal distance (IUD/BTD) were independent risk factors for MCI in CSVD patients, and independent risk factors for dementia in CSVD were Crouse Score, the pulsatility index of the middle cerebral artery (MCAPI), IUD/BTD, and Sylvian fissure ratio (SFR). Overall, the parameters with high performance were the IUD/BTD (OR 2.28; 95% CI 1.26–4.10) and SFR (OR 3.28; 95% CI 1.54–6.91), and the AUC (area under the curve) in distinguishing between CSVD older adults with MCI and with dementia was 0.675 and 0.724, respectively. Linear brain measurement parameters had larger observed effect than other indexes to identify cognitive impairments in CSVD patients.ConclusionThis study shows that IUD/BTD and SFR are good predictors of cognitive impairments in CSVD elderly. Linear brain measurement showed a good predictive power for identifying MCI and dementia in elderly subjects with CSVD. Linear brain measurement could be a more suitable and novel method for screening cognitive impairment in aged CSVD patients in primary healthcare facilities, and worth further promotion among the rural population

Multi-Response Robust Parameter Optimization of Cemented Backfill Proportion with Ultra-Fine Tailings

Backfill of mined-out areas in Carlin-type gold mines always encounters the challenges of ultra-fine tailings, low backfill strength and difficult slurry transportation caused by fine tailings. To understand the influence of slurry mass concentration, waste rock content, and cement-sand ratio on the cemented backfill strength and fluidity, influential factors were determined by range analysis of orthogonal proportion experiments. Response surface methodology (RSM) was used to analyze the influence of each factor on response, and the backfill strength and slump were optimized using a robust optimization desirability function method. The results show that the cement-sand ratio has the highest effect on the backfill strength, and the slurry slump is dominated by the slurry mass concentration. The interaction between waste rock content and the cement-sand ratio significantly impacts the slump, while the interaction between the slurry mass concentration and the cement-sand ratio has a positive correlation with the backfill strength. The ultra-fine tailings cemented backfill proportion was optimized by using multi-response robust parameters as 68.36% slurry mass concentration, 36.72% waste rock content and 1:3 cement-sand ratio. The overall robust optimal desirability was 0.8165, and the validity of multi-response robust parameter optimization was verified by laboratory tests

IL-8 Secreted from M2 Macrophages Promoted Prostate Tumorigenesis via STAT3/MALAT1 Pathway

Prostate cancer (PCa) is a major health problem in males. Metastasis-associated with lung adenocarcinoma transcript-1 (MALAT1), which is overexpressed in PCa tissue, is associated with physiological and pathological conditions of PCa. M2 macrophages are major immune cells abundant in the tumor microenvironment. However, it remains unknown whether M2 macrophages are involved in the effects or not, and molecular mechanisms of MALAT1 on PCa progression have not yet been comprehensively explored. Here we reported that, M2 macrophages (PMA/IL-4 treated THP1) induced MALAT1 expression in PCa cell lines. Knockdown MALAT1 expression level in PCa cell lines inhibited cellular proliferation, invasion, and tumor formation. Further mechanistic dissection revealed that M2 macrophages secreted IL-8 was sufficient to drive up MALAT1 expression level via activating STAT3 signaling pathway. Additional chromatin immunoprecipitation (ChIP) and luciferase reporter assays displayed that STAT3 could bind to the MALAT1 promoter region and transcriptionally stimulate the MALAT1 expression. In summary, our present study identified the IL-8/STAT3/MALAT1 axis as key regulators during prostate tumorigenesis and therefore demonstrated a new mechanism for the MALAT1 transcriptional regulation

A new development of non-local image denoising using fixed-point iteration for non-convex ℓp sparse optimization.

We proposed a new efficient image denoising scheme, which mainly leads to four important contributions whose approaches are different from existing ones. The first is to show the equivalence between the group-based sparse representation and the Schatten-p norm minimization problem, so that the sparsity of the coefficients for each group can be measured by estimating the underlying singular values. The second is that we construct the proximal operator for sparse optimization in ℓp space with p ∈ (0, 1] by using fixed-point iteration and obtained a new solution of Schatten-p norm minimization problem, which is more rigorous and accurate than current available results. The third is that we analyze the suitable setting of power p for each noise level σ = 20, 30, 50, 60, 75, 100, respectively. We find that the optimal value of p is inversely proportional to the noise level except for high level of noise, where the best values of p are 1 and 0.95, when the noise levels are respectively 75 and 100. Last we measure the structural similarity between two image patches and extends previous deterministic annealing-based solution to sparsity optimization problem through incorporating the idea of dictionary learning. Experimental results demonstrate that for every given noise level, the proposed Spatially Adaptive Fixed Point Iteration (SAFPI) algorithm attains the best denoising performance on the value of Peak Signal-to-Noise Ratio (PSNR) and structure similarity (SSIM), being able to retain the image structure information, which outperforms many state-of-the-art denoising methods such as Block-matching and 3D filtering (BM3D), Weighted Nuclear Norm Minimization (WNNM) and Weighted Schatten p-Norm Minimization (WSNM)

A pH-responsive α-helical cell penetrating peptide-mediated liposomal delivery system

Tumor-oriented nanocarrier drug delivery approaches with pH-sensitivity have been drawing considerable attentions over the years. Here we described a liposomal delivery system modified with pH-responsive cell penetrating peptide TH (TH-Lip). Conventional cell penetrating peptide (CPP)-related drug delivery tactics sometimes seemed limited due to the extensive in vivo penetration and the lack of proper selectivity of conventional CPPs. In this study, TH (AGYLLGHINLHHLAHL(Aib)HHIL-NH2), an engineered α-helical cell penetrating peptide originated from peptide TK (AGYLLGKINLKKLAKL(Aib)LLIL-NH2), was endowed pH-responsiveness after complete replacement of all lysines in the sequence of TK into histidines, and was introduced onto the surface of liposomes. Accordingly, TH-Lip could benefit from the unique property of TH, as the cell penetrating capacity of TH was concealed during the blood circulation and in normal tissues because of the neutral pH under those conditions. However, when TH-Lip reached the tumor, and as pH declined, histidines in TH peptide protonated and the surface charge of TH-Lip converted from negative to positive, initiating activated cell penetrating capacity and leading to enhanced cellular and tumor spheroid uptake. The endocytosis inhibition assay demonstrated that the endocytosis of TH-Lip was influenced by the positively charged surface of the liposomes in acidic environment and was mediated by clathrin, and the intracellular trafficking study suggested that the liposomes were mainly accumulated in endoplasmic reticulum and Golgi apparatus. After systemic administration in mice, TH-Lip could be internalized into tumor cells efficaciously. When it comes to the delivery of paclitaxel (PTX), the pH-responsiveness of TH-Lip led to strong inhibition against tumor cell growth which occurred both in vitro (under pH 6.3) and in vivo, and the tumor inhibition rate reached 86.3% on C26 tumor-bearing mice for PTX-loaded TH-Lip. Therefore, TH-Lip proved itself to be a promising pH-responsive strategy for drug delivery within acidified tumor microenvironment