Dihydroorotase (DHOase) is the third enzyme in the de novo biosynthesis pathway for pyrimidine nucleotides, and an attractive target for potential anticancer chemotherapy. By screening plant extracts ...and performing GC-MS analysis, we identified and characterized that the potent anticancer drug plumbagin (PLU), isolated from the carnivorous plant
, was a competitive inhibitor of DHOase. We also solved the complexed crystal structure of yeast DHOase with PLU (PDB entry 7CA1), to determine the binding interactions and investigate the binding modes. Mutational and structural analyses indicated the binding of PLU to DHOase through loop-in mode, and this dynamic loop may serve as a drug target. PLU exhibited cytotoxicity on the survival, migration, and proliferation of 4T1 cells and induced apoptosis. These results provide structural insights that may facilitate the development of new inhibitors targeting DHOase, for further clinical anticancer chemotherapies.
Colonoscopy is a useful method for the diagnosis and management of colorectal diseases. Many computer-aided systems have been developed to assist clinicians in detecting colorectal lesions by ...analyzing colonoscopy images. However, fisheye-lens distortion and light reflection in colonoscopy images can substantially affect the clarity of these images and their utility in detecting polyps. This study proposed a two-stage deep-learning model to correct distortion and reflections in colonoscopy images and thus facilitate polyp detection.
Images were collected from the PolypSet dataset, the Kvasir-SEG dataset, and one medical center's patient archiving and communication system. The training, validation, and testing datasets comprised 808, 202, and 1100 images, respectively. The first stage involved the correction of fisheye-related distortion in colonoscopy images and polyp detection, which was performed using a convolutional neural network. The second stage involved the use of generative and adversarial networks for correcting reflective colonoscopy images before the convolutional neural network was used for polyp detection.
The model had higher accuracy when it was validated using corrected images than when it was validated using uncorrected images (96.8% vs 90.8%, P < 0.001). The model's accuracy in detecting polyps in the Kvasir-SEG dataset reached 96%, and the area under the receiver operating characteristic curve was 0.94.
The proposed model can facilitate the clinical diagnosis of colorectal polyps and improve the quality of colonoscopy.
Aberrant expression of transforming growth factor‐β1 (TGF‐β1) is associated with renal cell carcinoma (RCC) progression by inducing cancer metastasis. However, the downstream effector(s) in TGF‐β ...signaling pathway is not fully characterized. In the present study, the elevation of secreted protein acidic and rich in cysteine (SPARC) as a TGF‐β regulated gene in RCC was identified by applying differentially expressed gene analysis and microarray analysis, we further confirmed this result in several RCC cell lines. Clinically, the expression of these two genes is positively correlated in RCC patient specimens. Furthermore, elevated SPARC expression is found in all the subtypes of RCC and positively correlated with the RCC stage and grade. In contrast, SPARC expression is inversely correlated with overall and disease‐free survival of patients with RCC, suggesting SPARC as a potent prognostic marker of RCC patient survival. Knocking down SPARC significantly inhibits RCC cell invasion and metastasis both in vitro and in vivo. Similarly, in vitro cell invasion can be diminished by using a specific monoclonal antibody. Mechanistically, SPARC activates protein kinase B (AKT) pathway leading to elevated expression of matrix metalloproteinase‐2 that can facilitate RCC invasion. Altogether, our data support that SPARC is a critical role of TGF‐β signaling network underlying RCC progression and a potential therapeutic target as well as a prognostic marker.
Abstract
Oral squamous cell carcinoma (OSCC) is a common malignant disease associated with a high mortality rate and heterogeneous disease aetiology. Cyclin dependent kinase inhibitor 2B antisense ...RNA 1 (CDKN2B‐AS1), is a long noncoding RNA that has been shown to act as a scaffold, sponge, or signal hub to promote carcinogenesis. Here, we attempted to assess the effect of
CDKN2B‐AS1
single‐nucleotide polymorphisms (SNPs) on the susceptibility to OSCC. Five
CDKN2B‐AS1
SNPs, including rs564398, rs1333048, rs1537373, rs2151280 and rs8181047, were analysed in 1060 OSCC cases and 1183 cancer‐free controls. No significant association of these five SNPs with the risk of developing OSCC was detected between the case and control group. However, while examining the clinical characteristics, patients bearing at least one minor allele of rs1333048 (CA and CC) were more inclined to develop late‐stage (stage III/IV, adjusted OR, 1.480; 95% CI, 1.129–1.940;
p
= 0.005) and large‐size (greater than 2 cm in the greatest dimension, adjusted OR, 1.347; 95% CI, 1.028–1.765;
p
= 0.031) tumours, as compared with those homologous for the major allele (AA). Further stratification analyses demonstrated that this genetic correlation with the advanced stage of disease was observed only in habitual betel quid chewers (adjusted OR, 1.480; 95% CI, 1.076–2.035;
p
= 0.016) or cigarette smokers (adjusted OR, 1.531; 95% CI, 1.136–2.063;
p
= 0.005) but not in patients who were not exposed to these major habitual risks. These data reveal an interactive effect of
CDKN2B‐AS1
rs1333048 with habitual exposure to behavioural risks on the progression of oral cancer.
TMPRSS2 is an important membrane-anchored serine protease involved in human prostate cancer progression and metastasis. A serine protease physiologically often comes together with a cognate inhibitor ...for execution of proteolytically biologic function; however, TMPRSS2's cognate inhibitor is still elusive. To identify the cognate inhibitor of TMPRSS2, in this study, we applied co-immunoprecipitation and LC/MS/MS analysis and isolated hepatocyte growth factor activator inhibitors (HAIs) to be potential inhibitor candidates for TMPRSS2. Moreover, the recombinant HAI-2 proteins exhibited a better inhibitory effect on TMPRSS2 proteolytic activity than HAI-1, and recombinant HAI-2 proteins had a high affinity to form a complex with TMPRSS2. The immunofluorescence images further showed that TMPRSS2 was co-localized to HAI-2. Both KD1 and KD2 domain of HAI-2 showed comparable inhibitory effects on TMPRSS2 proteolytic activity. In addition, HAI-2 overexpression could suppress the induction effect of TMPRSS2 on pro-HGF activation, extracellular matrix degradation and prostate cancer cell invasion. We further determined that the expression levels of TMPRSS2 were inversely correlated with HAI-2 levels during prostate cancer progression. In orthotopic xenograft animal model, TMPRSS2 overexpression promoted prostate cancer metastasis, and HAI-2 overexpression efficiently blocked TMPRSS2-induced metastasis. In summary, the results together indicate that HAI-2 can function as a cognate inhibitor for TMPRSS2 in human prostate cancer cells and may serve as a potential factor to suppress TMPRSS2-mediated malignancy.
Alternative splicing was found to be a common phenomenon after the advent of whole transcriptome analyses or next generation sequencing. Over 90% of human genes were demonstrated to undergo at least ...one alternative splicing event. Alternative splicing is an effective mechanism to spatiotemporally expand protein diversity, which influences the cell fate and tissue development. The first focus of this review is to highlight recent studies, which demonstrated effects of alternative splicing on the differentiation of adipocytes. Moreover, use of evolving high-throughput approaches, such as transcriptome analyses (RNA sequencing), to profile adipogenic transcriptomes, is also addressed.
A simple and convergent synthetic strategy used to increase the diversity of the carbodicarbene ligand framework through incorporation of unsymmetrical pendant groups is reported. Structural analysis ...and spectroscopic studies of ligands and their Rh complexes are reported. Reactivity studies reveal carbodicarbenes as competent organocatalysts for amine methylation using CO2 as a synthon. A unique BH‐activated boron–carbodicarbene complex was isolated as a reaction intermediate, providing mechanistic insight into the CO2 functionalization process.
Expanding the family: A simple and convergent synthetic strategy was developed to increase the diversity of the carbodicarbene ligand framework by incorporation of unsymmetrical pendant groups. Reactivity studies revealed that carbodicarbenes are competent organocatalysts for amine methylation using CO2 as a synthon.
Inflammatory bowel disease (IBD) is a chronic inflammatory disorder. Previous studies have suggested that chronic systemic inflammation increases the risk of Parkinson's disease (PD). This study ...examined the effects of IBD on the development of PD.
In a nationwide population-based cohort of 23.22 million insured residents of Taiwan aged ≥ 20 years, we compared people diagnosed with IBD during 2000 to 2011 (n = 8373) with IBD-free individuals. Patients with PD were identified in the National Health Insurance Research Database. Using univariable and multivariable Cox proportion hazard regression models, we estimated the adjusted hazard ratio (aHR) for PD with a 95% confidence interval (CI) with adjustment for age, sex, and comorbidities.
In the cohort, IBD was associated with an increased incidence of PD (crude hazard ratio = 1.43, 95% CI = 1.15-1.79). The risk was highest among individuals with Crohn's disease (aHR = 1.40, 95% CI = 1.11-1.77). In the multivariable model, the risk of PD was increased for men (aHR = 1.28, 95% CI = 1.05-1.56) and higher for patients with hypertension (aHR = 1.72, 95% CI = 1.33-2.24), coronary artery disease (aHR = 1.31, 95% CI = 1.04-1.66), or depression (aHR = 2.51, 95% CI = 1.82-3.46).
We suggest that IBD is associated with an increased risk of PD. Patients with IBD should be aware of the potential risk for PD development.
Ferroelectric materials provide a new pathway to convert thermal energy into electricity based on the pyroelectric effect. How to modulate the pyroelectric property of ferroelectric materials through ...UV–light is still an urgent problem that needs to be solved. Here, a self‐powered sensor is demonstrated based on 0.94(Bi0.5Na0.5)TiO3‐0.06Ba(Zr0.25Ti0.75)O3 nanoparticles, exhibiting high output electric performance under temperature variation and UV–light illumination conditions. Compared with a purely pyroelectric system, the corresponding current peaks of “UV–light + heating” and “UV–light + cooling” states are 88.6% higher and 37.3% smaller in the coupled system. The fabricated pyroelectric system shows excellent performance with detection sensitivities of 0.9 (heating) and 1.48 nA K−1 (cooling) with 0.7 × 10−3 and 0.2 × 10−3 nA lux−1 illuminated by 395 nm UV–light as a temperature sensor. Furthermore, a self‐powered sensor that is suitable for detecting both UV–light and temperature variations by recording the output current signals are demonstrated, which provides a basis for the development of the next generation of UV–light‐modulated ferroelectric devices.
A self‐powered sensor is demonstrated based on 0.94(Bi0.5Na0.5)TiO3‐0.06Ba(Zr0.25Ti0.75)O3 nanoparticles, exhibiting high output electric performance under temperature variation and UV–light illumination conditions. The fabricated pyroelectric system shows excellent performance with detection sensitivities of 0.9 nA K−1 (heating) and 1.48 nA K−1 (cooling) with 0.7 × 10–3 and 0.2 × 10–3 nA lux−1 illuminated by 395 nm UV–light as a temperature sensor. Furthermore, a self‐powered sensor that is suitable for detecting both UV–light and temperature variations by recording the output current signals are demonstrated, which provides a basis for the development of the next generation of UV–light‐modulated ferroelectric devices.
Current methods for sleep stage detection rely on sensors to collect physiological data. These methods are inaccurate and take up considerable medical resources. Thus, in this study, we propose a ...Taguchi-based multiscale convolutional compensatory fuzzy neural network (T-MCCFNN) model to automatically detect and classify sleep stages. In the proposed T-MCCFNN model, multiscale convolution kernels extract features of the input electroencephalogram signal and a compensatory fuzzy neural network is used in place of a traditional fully connected network as a classifier to improve the convergence rate during learning and to reduce the number of model parameters required. Due to the complexity of general deep learning networks, trial and error methods are often used to determine their parameters. However, this method is very time-consuming. Therefore, this study uses the Taguchi method instead, where the optimal parameter combination is identified over a minimal number of experiments. We use the Sleep-EDF database to evaluate the proposed model. The results indicate that the proposed T-MCCFNN sleep stage classification accuracy is 85.3%, which is superior to methods proposed by other scholars.
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