Fluorophore Label-Free Light-up Near Infrared Deoxyribonucleic Acid Nanosensor for Monitoring Extracellular Potassium Levels.

Fluorescent DNA nanosensors have been widely used due to their unique advantages, among which the near-infrared (NIR) imaging mode can provide deeper penetration depth and lower biological background for the nanosensors. However, efficient NIR quenchers require ingenious design, complex synthesis, and modification, which severely limit the development of NIR DNA nanosensors. Label-free strategies based on G-quadruplex (G4) and NIR G4 dyes were first introduced into in situ extracellular imaging, and a novel NIR sensing strategy for the specific detection of extracellular targets is proposed. The strategy avoids complex synthesis and site-specific modification by controlling the change of the NIR signal through the formation of a G4 nanostructure. A light-up NIR DNA nanosensor based on potassium ion (K+)-sensitive G4 chain PS2.M was constructed to verify the strategy. PS2.M forms a stable G4 nanostructure in the presence of K+ and activates the NIR G4 dye CSTS, thus outputting NIR signals. The nanosensor can rapidly respond to K+ with a linear range of 5-50 mM and has good resistance to interference. The nanosensor with cholesterol can provide feedback on the changes in extracellular K+ concentration in many kinds of cells, serving as a potential tool for the study of diseases such as epilepsy and cancer, as well as the development of related drugs. The strategy can be potentially applied to the NIR detection of a variety of extracellular targets with the help of functional DNAs such as aptamer and DNAzyme.

Chemical Composition and Potential Antimicrobial and Anti-Inflammatory Activities of Essential Oil from Fruits of Alpinia zerumbet (Pers.) B.L.Burtt & R.M.Sm.

Alpinia zerumbet (Pers.) B.L.Burtt & R.M.Sm. was extensively used in traditional medicine for its several properties, but continuous investigation is needed to discover the properties of its essential oils (EOs). This work evaluated the properties of an EO obtained by steam distillation (named ESD) as well as extracts obtained by petroleum ether (named EP) both from Alpinia zerumbet fruits. Gas chromatography-mass spectrometry (GC-MS) was chosen to identify the composition, and eleven compounds were identified as the main components of the EO and EP of Alpinia zerumbet fruits. The antimicrobial properties were investigated by minimum inhibitory concentration (MIC) and the inhibition area. The results identified the differences in antimicrobial activities attributed to different extraction methods. Enzyme-linked immunosorbent assay (ELISA) and Western Blot (WB) assay were conducted to assess the anti-inflammatory effects of ESD. In conclusion, our study suggested that EO from Alpinia zerumbet fruits might be a prospective candidate for antimicrobial and anti-inflammatory therapy.

Beneficial effects of endoscopic screening on gastric cancer and optimal screening interval: a population-based study.

BACKGROUND : The effectiveness of endoscopic screening on gastric cancer has not been widely investigated in China and the screening interval of repeated screening has not been determined. METHODS : In a population-based prospective study, we included 375,800 individuals, 14,670 of whom underwent endoscopic screening (2012-2018). We assessed the associations between endoscopic screening and risk of incident gastric cancer and gastric cancer-specific mortality, and examined changes in overall survival and disease-specific survival following screening. The optimal screening interval for repeated endoscopy for early detection of gastric cancer was explored. RESULTS : Ever receiving endoscopic screening significantly decreased the risk of invasive gastric cancer (age- and sex-adjusted relative risk [RR] 0.69, 95 % confidence interval [CI] 0.52-0.92) and gastric cancer-specific mortality (RR 0.33, 95 %CI 0.20-0.56), particularly for noncardia gastric cancer. Repeated screening strengthened the beneficial effect on invasive gastric cancer-specific mortality of one-time screening. Among invasive gastric cancers, screening-detected individuals had significantly better overall survival (RR 0.18, 95 %CI 0.13-0.25) and disease-specific survival (RR 0.18, 95 %CI 0.13-0.25) than unscreened individuals, particularly for those receiving repeated endoscopy. For individuals with intestinal metaplasia or low grade intraepithelial neoplasia, repeated endoscopy at an interval of < 2 years, particularly within 1 year, significantly enhanced the detection of early gastric cancer, compared with repeated screening after 2 years (P-trend = 0.02). CONCLUSION : Endoscopic screening prevented gastric cancer occurrence and death, and improved its prognosis in a population-based study. Repeated endoscopy enhanced the effectiveness. Screening interval should be based on gastric lesion severity.

Screening for gastric cancer in China: Advances, challenges and visions.

Gastric cancer (GC) is one of the major cancers in China and all over the world. Most GCs are diagnosed at an advanced stage with unfavorable prognosis. Along with some other countries, China has developed the government-funded national screening programs for GC and other major cancers. GC screening has been shown to effectively decrease the incidence of and mortality from GC in countries adopting nationwide screening programs (Japan and Korea) and in studies based on selected Chinese populations. The screening of GC relies mostly on gastroendoscopy, the accuracy, reliability and safety of which have been indicated by previous studies. However, considering its invasive screening approach, requirements on skilled endoscopists and pathologists, and a high cost, developing noninvasive methods to amend endoscopic screening would be highly needed. Numerous studies have examined biomarkers for GC screening and the combination of biomarkers involving pepsinogen, gastrin, and Helicobacter pylori antibodies has been proposed for risk stratification, seeking to narrow down the high-risk populations for further endoscopy. Despite all the achievements of endoscopic screening, evidence on appropriate screening age, intervals for repeated screening, novel biomarkers promoting precision prevention, and health economics need to be accumulated to inform policymakers on endoscopic screening in China. With the guide of Health China 2030 Planning Outline, we have golden opportunities to promote prevention and control of GC. In this review, we summarize the characteristics of screening programs in China and other East Asian countries and introduce the past and current approaches and strategies for GC screening, aiming for featuring the latest advances and key challenges, and illustrating future visions of GC screening.

The association between gut microbiota composition and BMI in Chinese male college students, as analysed by next-generation sequencing.

Altered gut microbial ecology contributes to the development of metabolic diseases including obesity. However, studies based on different populations have generated conflicting results due to diet, environment, methodologies, etc. The aim of our study was to explore the association between gut microbiota and BMI in Chinese college students. The 16S next-generation sequencing (NGS) was used to test the gut microbiota of nine lean, nine overweight/obesity and ten normal-weight male college students. The differences in gut microbiota distribution among three groups were compared, and the relationship between the richness, diversity, composition of gut microbiota and BMI were analysed. The predominant phyla Bacteroidetes and Firmicutes were further confirmed by real-time PCR. Metagenomic biomarker discovery was conducted by linear discriminant analysis (LDA) effect size (LEfSe). NGS revealed that gut microbiota composition was different among three groups, but there was no difference in the abundance ratio of Firmicutes:Bacteroidetes. Several bacterial taxa were in linear relationship with BMI (positive relationship: uncultured bacterium (Bacteroides genus); negative relationship: Porphyromonadaceae, Acidaminococcaceae, Rikenellaceae, Desulfovibrionaceae, Blautia, Anaerotruncus, Parabacteroides, Alistipes). Moreover, gut microbiota diversity decreased with the increase in BMI. And LEfSe analysis indicated that Blautia, Anaerotruncus and its uncultured species were significantly enriched in the lean group (LDA score ≥ 3), Parasuterella and its uncultured species were significantly enriched in the overweight/obese groups (LDA score ≥ 3). In general, gut microbiota composition and microbial diversity were associated with BMI in Chinese male college students. Our results might enrich the understanding between gut microbiota and obesity.

Lanthanide terbium complex: synthesis, electrochemiluminescence (ECL) performance, and sensing application.

In this study, a new lanthanide terbium complex, Tb(pzda)3(NO3)3·nH2O, was synthesized by a hydrothermal method and characterized by Fourier transform infrared spectroscopy (FT-IR) and energy-dispersive X-ray spectroscopy (EDS). It was found that the as-synthesized Tb-complex exhibited good electrochemiluminescence (ECL) behavior in the presence of triethanolamine (TEOA) in a HAc-NaAc buffer solution on a glassy carbon electrode. The possible reaction mechanism has been discussed based on the fluorescence spectra and ECL spectra. For sensing applications, it was found that protocatechuic acid (PCA) had an obvious quenching effect on the ECL signal of the Tb-complex, and this resulted in a decreased ECL signal associated with the concentration of PCA. Therefore, a highly sensitive method for the detection of PCA was established with a linear range of 1.283 × 10-10 M to 3.845 × 10-4 M and a detection limit of 0.085 nM at an S/N ratio of 3. This novel ECL assay strategy with an outstanding ECL efficiency offers great potential for pharmaceutical analyses.

Structural characterization and anti-inflammatory activities of a purified polysaccharide from fruits remnants of Alpinia zerumbet (Pers.) Burtt. et Smith.

We reported here an interesting source of Alpinia zerumbet Polysaccharides (named AZPs) from the residues after extracting essential oil by steam distillation from Alpinia zerumbet fructus. After a series of purifications, a homogeneous polysaccharide (AZP-2) of molecular weight 1.25 × 105 Da was obtained. Structure, anti-inflammatory activity, and anti-inflammatory mechanism were investigated. AZP-2 was mainly composed of galactose, arabinose, xylopyranose, glucose, and galacturonic acid. The main linkage structure of AZP-2 was determined after integrating the nuclear magnetic resonance (NMR) and methylation analysis, and the structure was comparatively complex. The results indicated that AZP-2 significantly decreased the production of NO and ROS in the inflammatory model established by lipopolysaccharide (LPS) stimulated RAW264.7, particularly at the concentration of 200 µg/mL. Furthermore, AZP-2 significantly modulated the secretion of both pro-inflammatory and anti-inflammatory cytokines. Notably, the mechanism of AZP-2 exhibiting inhibitory effects was related to regulating the NF-κB signaling pathway. Overall, AZP-2 could be used as a potential anti-inflammatory agent for further in-depth studies.

Self-assembly of DNA nanospheres with controllable size and self-degradable property for enhanced antitumor chemotherapy.

Controllable size, self-degradability and targeting property are important for a precise improvement of anticancer effects and reduction of side effects of drug vehicles. Here, a series of DNA nanospheres with controllable size and self-degradation ability were constructed through the hybridization of two i-motif strands and two linker strands for targeted cancer therapy. DNA nanospheres with different sizes were fabricated by regulating the linker sequence, and their pH-responsive self-degradation property was realized by the introduction of the i-motif strand. Moreover, the ZY11 aptamer was introduced to endow the DNA nanospheres with targeting property toward SMMC-7721 cancer cells. The results revealed that the appropriate size of DNA nanospheres (80 nm) highly promoted the internalization by mammalian cells. The results of DLS, AFM and CD spectra showed that the DNA nanospheres were stable in a physiological environment but they self-degraded in a slightly acidic environment due to the existence of the i-motif strand. Moreover, the fluorescence of DOX@AP-NSs2 was triple at pH = 5.0 than at pH = 7.4, which further confirmed the pH-responsive drug release performance. The above results proved that the use of DOX@AP-NSs2 is a promising approach to accelerate the rapid release of drugs into the tumors and avoid drug leakage into the normal tissue. The results at a cellular level and in vivo confirmed the pH-responsive targeted antitumor effect. Hence, the novel DNA nanospheres with controllable size and self-degradable property represent a potential tool for targeted drug delivery and cancer therapy.

Multi-scale discriminative network for prostate cancer lesion segmentation in multiparametric MR images.

PURPOSE: The accurate and reliable segmentation of prostate cancer (PCa) lesions using multiparametric magnetic resonance imaging (mpMRI) sequences, is crucial to the image-guided intervention and treatment of prostate disease. For PCa lesion segmentation, it is essential to reliably combine local and global information to retain the features of small targets at multiple scales. Therefore, this study proposes a multi-scale segmentation network with a cascading pyramid convolution module (CPCM) and a double-input channel attention module (DCAM) for the automated and accurate segmentation of PCa lesions using mpMRI. METHODS: First, the region of interest was extracted from the data by clipping to enlarge the target region and reduce the background noise interference. Next, four CPCMs with large convolution kernels in their skip connection paths were designed to improve the feature extraction capability of the network for small targets. At the same time, a convolution decomposition was applied to reduce the computational complexity. Finally, the DCAM was adopted in the decoder to provide bottom-up semantic discriminative guidance; it can use the semantic information of the network's deep features to guide the shallow output of features with a higher discriminant ability. A residual refinement module (RRM) was also designed to strengthen the recognition ability of each stage. The feature maps of the skip connection and the decoder all go through the RRM. RESULTS: For the Initiative for Collaborative Computer Vision Benchmarking (I2CVB) dataset, our proposed model achieved a Dice similarity coefficient (DSC) of 79.31% and an average boundary distance (ABD) of 4.15 mm. For the Prostate Multiparametric MRI (PROMM) dataset, our method greatly improved the DSC to 82.11% and obtained an ABD of 3.64 mm. CONCLUSIONS: The experimental results of two different mpMRI prostate datasets demonstrate that our model is more accurate and reliable on small targets. In addition, it outperforms other state-of-the-art methods.

A multi-class COVID-19 segmentation network with pyramid attention and edge loss in CT images.

At the end of 2019, a novel coronavirus COVID-19 broke out. Due to its high contagiousness, more than 74 million people have been infected worldwide. Automatic segmentation of the COVID-19 lesion area in CT images is an effective auxiliary medical technology which can quantitatively diagnose and judge the severity of the disease. In this paper, a multi-class COVID-19 CT image segmentation network is proposed, which includes a pyramid attention module to extract multi-scale contextual attention information, and a residual convolution module to improve the discriminative ability of the network. A wavelet edge loss function is also proposed to extract edge features of the lesion area to improve the segmentation accuracy. For the experiment, a dataset of 4369 CT slices is constructed, including three symptoms: ground glass opacities, interstitial infiltrates, and lung consolidation. The dice similarity coefficients of three symptoms of the model achieve 0.7704, 0.7900, 0.8241 respectively. The performance of the proposed network on public dataset COVID-SemiSeg is also evaluated. The results demonstrate that this model outperforms other state-of-the-art methods and can be a powerful tool to assist in the diagnosis of positive infection cases, and promote the development of intelligent technology in the medical field.