Synergistic Anticancer Response of Curcumin and Piperine Loaded Lignin-g-p (NIPAM-co-DMAEMA) Gold Nanogels Against Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most aggressive and commonly diag- 11 nosed brain cancer and presents a strong resistance to routine chemotherapeutic drugs. 12 The present study involves the synthesis of Lignin-g- p (NIPAM-co-DMAEMA) gold 13 nanogel, loaded with curcumin and piperine to treat GBM. The application has three 14 functions: (1) overcome the limitations of biodistribution, (2) enhance the toxicity of an- 15 ticancer drugs against GBM, (3) identify the uptake pathway. Atom transfer radical 16 polymerization was used to synthesize the Lignin-g-PNIPAM network, crosslinked with 17 the gold nanoparticles (GNPs) to self-assemble into nanogels. The size distribution and 18 morphological analysis confirmed that the drug-loaded gold nanogels are spherical and 19 exist in the size of 180 nm. The single and combinatorial toxicity effects of curcumin and 20 piperine loaded Lignin-g- p (NIPAM-co-DMAEMA) gold nanogels were studied against 21 GBM cells. A cytotoxicity analysis against glioblastoma cells (U-251 MG) displayed an- 22 ticancer properties. IC50 of curcumin and piperine-loaded gold nanogels were recorded 23 at 30 μM and 35 μM respectively. Immunostaining analysis of the drug-loaded nanogel 24 treated cells shows that the F-actin induced cytoskeletal deformations result in the trig- 25 gering of caspase-3 apoptotic pathways. Kinetic drug release revealed the 86% release of 26 hybrid curcumin-piperine from nanogel after 250 mins at pH 4. Atomic absorption 27 spectroscopic analysis confirmed that the drug-loaded nanogels have better internaliza- 28 tion or association with the cancer cells than the GNPs or nanogels alone. Morphology 29 studies further confirmed that the curcumin and piperine nanogels penetrate the cells via 30 endocytic pathways and induce caspase-3 related apoptosis. The experimental evidence 31 shows the enhanced synergistic properties of combinatorial curcumin-piperine gold 32 nanogels (IC 50 : 21 μM) to overcome the limitations of conventional chemotherapeutic 33 treatments of glioma cells

Effective detection of seismic events by non-classical receptive field visual cognitive modelling.

The detection and up-picking of the seismic events are critical for seismic data analysis and interpretation. Events picking can be used for sequence stratigraphic analysis, reservoir feature extraction, the determining of the subsequent reflection interface, the improving of the SNR and the storage prediction. The research of the events picking is very significant for the seismic exploration. In order to overcome the existing events picking methods have the same sensitivity to noise, we propose a non-classical receptive field visual cognitive method for the events picking UP. Vision is an important functional organ for human beings to observe and recognize the world. About 80% of the information obtained by human beings from the outside world comes from the visual system, which fully shows that visual information is huge_ and also shows that human beings have a high utilization rate of visual information. How to transfer some typical information processing mechanism and target recognition function of human vision to machine is one of the most important and urgent tasks in the field of computer vision and artificial intelligence. The introduction of computer vision technology into geophysical prospecting is still in its infancy in the field of seismic exploration, our research fill the blank of this field, where the use of visual features to improve the seismic data processing and rapid realization of oil and gas exploration, will become the vane of the future direction of research and development. As a basic research work in the crossing field, this paper has made a breakthrough in the research methods and ideas, and the research content can be summarized as the following four aspects: 1. The proposed method implements the function of environmental suppression and spatial enhancement of the bio-visual primary visual cortex, which is applies to the ore-stack seismic data, as ore-stack seismic data contains abundant information such as amplitude and frequency to reflect tiny structures of the formation. 2. The seismic data is preprocessed to obtain the wavelet fusion of the envelope peak instantaneous frequency (EPIF) and the slant stack peak amplitude (SSPA), which can maximum the limit to provide optimal quality data. 3. An adaptive Gabor filter direction selection method is proposed to provide a reliable angle range and improve the recognition rate of filter decomposition. In addition. by adopting an anisotropic environmental suppression method, our method can detect edge variability more accurately than the isotropic method. 4. With the enhanced contour aggregation, cocircular constraint is adopted and combined with the characteristics of low curvature and continuous changing curvature, which is unique to the seismic events, to establish a consistent spatial structure perception model. The events picked by our method is more continuous and accurate than the existing methods, and doesn't require human interaction, which is beneficial for subsequent seismic interpretation and reservoir prediction

A trade-off formula in designing asymmetric neural networks

NNSF of China [11205032, 11147191, 10925525]; NSF of Fujian province [2013J05008]; Fuzhou University [022390]We show that for asymmetric neural networks the symmetric degree eta of the synaptic coupling can be related to the two main network parameters, the storage capacity alpha and another designing parameter kappa by the formula eta = alpha kappa(2). Such a relation has been well verified by the simulations of our neural network designing. The formula suggests that we cannot improve the network performances by tuning the parameters alpha and kappa simultaneously. The result may provide useful information for optimizing the designing of asymmetric neural networks

Automatic events extraction in pre-stack seismic data based on edge detection in slant-stacked peak amplitude profiles

Events picking is one of the fundamental tasks in interpreting seismic data. To extract the correct travel-time of reflected waves, picking events in a wide range of source-receiver offsets is needed. Compared to post-stack seismic data, pre-stack seismic data has an accurate horizon and abundant travel-time, amplitude, and frequency while the waveform of post-stack data is damaged by normal move-out (NMO) applications. In this paper, we focus on automatic event extraction from pre-stack reflection seismic data. With the deep development of oil-gas exploration, the difficulty of petroleum exploration is being increased. Auto recognition and picking of seismic horizon is presented as the basis for oil-gas detection. There is a correspondence between the real geology horizon and events of seismic profiles. As a result, firstly, recognizing and tracing continuous events from real seismic records are needed to acquire significant horizon locations. Picking events is in this context the recognition and tracing of waves reflected from the same interfaces according to kinematics and dynamic characteristics of seismic waves. Current extraction algorithms are well able to trace these events of the seismic profile and are undergoing great development and utilization. In this paper, a method is proposed to pick travel-time and local continuous events based on edges obtained by slant-stacked peak amplitude section (SSPA). How to calculate the SSPA section is discussed in detail. The new method can improve the efficiency and accuracy without windowing and manual picking of seed points. The event curves obtained from both the synthetic layered model and field record have validated the high accuracy and efficiency of the proposed methodology

Chinese herbal compound for multidrug-resistant or extensively drug-resistant bacterial pneumonia: a meta-analysis and trial sequential analysis with association rule mining to identify core herb combinations

Purpose: Antibiotic-resistant bacterial pneumonia poses a significant therapeutic challenge. In China, Chinese herbal compound (CHC) is commonly used to treat bacterial pneumonia. We aimed to evaluate the efficacy and safety of CHC and identify core herb combinations for the treatment of multidrug-resistant or extensively drug-resistant bacterial pneumonia.Methods: Stata 16 and TSA 0.9.5.10 beta software were used for meta-analysis and trial sequential analysis (TSA), respectively. Exploring the sources of heterogeneity through meta-regression and subgroup analysis.Results: Thirty-eight studies involving 2890 patients were included in the analyses. Meta-analysis indicated that CHC combined with antibiotics improved the response rate (RR = 1.24; 95% CI: 1.19–1.28; p < 0.0001) and microbiological eradication (RR = 1.41; 95% CI: 1.27–1.57; p < 0.0001), lowered the white blood cell count (MD = −2.09; 95% CI: −2.65 to −1.53; p < 0.0001), procalcitonin levels (MD = −0.49; 95% CI: −0.59 to −0.40; p < 0.0001), C-reactive protein levels (MD = −11.80; 95% CI: −15.22 to −8.39; p < 0.0001), Clinical Pulmonary Infection Scores (CPIS) (MD = −1.97; 95% CI: −2.68 to −1.26; p < 0.0001), and Acute Physiology and Chronic Health Evaluation (APACHE)-II score (MD = −4.08; 95% CI: −5.16 to −3.00; p < 0.0001), shortened the length of hospitalization (MD = −4.79; 95% CI: −6.18 to −3.40; p < 0.0001), and reduced the number of adverse events. TSA indicated that the response rate and microbiological eradication results were robust. Moreover, Scutellaria baicalensis Georgi, Fritillaria thunbergii Miq, Lonicera japonica Thunb, and Glycyrrhiza uralensis Fisch were identified as core CHC prescription herbs.Conclusion: Compared with antibiotic treatment, CHC + antibiotic treatment was superior in improving response rate, microbiological eradication, inflammatory response, CPIS, and APACHE-II score and shortening the length of hospitalization. Association rule analysis identified four core herbs as promising candidates for treating antibiotic-resistant bacterial pneumonia. However, large-scale clinical studies are still required.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier CRD42023410587

Risk factors for posttraumatic stress reactions among chinese students following exposure to a snowstorm disaster

<p>Abstract</p> <p>Background</p> <p>It is important to understand which factors increase the risk of posttraumatic stress disorder (PTSD) in adolescents. Previous studies have shown that the most important risk factors for PTSD include the type, severity, and duration of exposure to the traumatic events.</p> <p>Methods</p> <p>A cross-sectional survey was used to investigate the psychological symptoms associated with the aftermath of a snowstorm disaster in the Hunan province of China in January 2008. Students living in Hunan were surveyed at a three<b>-</b>month follow-up after the disaster. The questionnaire battery included the Impact of Event Scale-Revised (IES-R, trauma and symptoms associated with PTSD), the Chinese version of the Life Orientation Test-Revised (LOT-R, optimism and pessimism), the Chinese version of the Eysenck Personality Questionnaire (EPQ, neuroticism and extraversion), the Chinese Trait Coping Style Questionnaire (TCSQ, positive and negative coping styles), and a range of questions addressing social demographic characteristics and factors relating to the snowstorm. The survey was administered in school, and 968 students completed and returned the questionnaires.</p> <p>Results</p> <p>The results showed that 14.5% of the students had a total IES-R score ≥20. Students with greater school-to-home distances showed higher levels of posttraumatic stress symptoms than students who lived shorter distances from school. Students with emotional support from their teachers reported higher levels of posttraumatic stress symptoms (21.20%) than students without a teacher's emotional support (11.07%). The IES-R total and subscale scores correlated with all variables except extraversion. The binary logistic regression analysis results showed that the teacher's emotional support [odds ratio (OR) = 1.72, 95% confidence interval (CI) = 1.13-2.62], school-to-home distance (OR = 1.01, 95% CI = 1.00-1.01), negative coping (OR = 1.05; 95% CI = 1.02-1.08), and neuroticism (OR = 1.04, 95% CI = 1.02-1.06) were risk factors that predicted PTSD frequency and severity (percentage correct = 85.5%).</p> <p>Conclusions</p> <p>The risk factors that significantly impacted the onset of posttraumatic stress reactions in students living in Hunan, China following a snowstorm disaster were the school-to-home distance, negative coping, neuroticism, and teacher's emotional support.</p

Determination of Rare Earth Elements in a New Type of Sedimentary Rare Earth Ore by ICP-MS

This is an essay in the field of mineral analysis. In recent years, Chinese geological researchers have discovered a new type of sedimentary rare earth ore in Yunnan and Guizhou regions, which is not only different from bastnaesite and monazite, but also different from ionic rare earth ore in south of China, but a unique rare earth ore in clay rocks. In this paper, the ore dissolution methods of two rare earth samples with different grade from different mineral sites in adjacent areas of Yunnan and Guizhou are compared, and the distribution of key rare earth elements（Pr、Nd、Tb、Dy）, the optimization of instrument parameters and the accuracy and precision of the determination method of key rare earth elements are studied in detail. The results show that the closed digestion system is the best method for the new deposit of rare earth ore, and ICP-MS is an accurate and efficient determination method with good precision and accuracy

Adaptive Fringe Projection for 3D Shape Measurement with Large Reflectivity Variations by Using Image Fusion and Predicted Search

There is always a great challenge for the structured light technique that it is difficult to deal with the surface with large reflectivity variations or specular reflection. This paper proposes a flexible and adaptive digital fringe projection method based on image fusion and interpolated prediction search algorithm. The multiple mask images are fused to obtain the required saturation threshold, and the interpolated prediction search algorithm is used to calculate the optimal projection gray-level intensity. Then, the projection intensity is reduced to achieve coordinate matching in the unsaturated condition, and the adaptive digital fringes with the optimal projection intensity are subsequently projected for phase calculation by using the heterodyne multifrequency phase-shifted method. The experiments demonstrate that the proposed method is effective for measuring the high-reflective surface and unwrapping the phase in the local overexposure region completely. Compared with the traditional structured light measurement methods, our method can decrease the number of projected and captured images with higher modulation and better contrast. In addition, the measurement process only needs two prior steps and avoids hardware complexity, which is more convenient to apply to the industry

Long-period gratings written in the PANDA-Air fiber

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