Effect of pH on the Structure, Functional Properties and Rheological Properties of Collagen from Greenfin Horse-Faced Filefish (Thamnaconus septentrionalis) Skin.

Collagen is an important biopolymer widely used in food, cosmetics and biomedical applications. Understanding the effect of pH on the structure and properties of collagen is beneficial for its further processing and exploitation. In this study, greenfin horse-faced filefish skin collagen (GHSC) was prepared and identified as a type I collagen. We systematically investigated the effect of pH on the structural, functional and rheological properties of GHSC. Scanning electron microscopy showed that the collagen morphology changed from an ordered stacked sheet structure to a rough silk-like structure as pH increased. Gaussian-fitted Fourier infrared spectroscopy results of the collagen revealed that it unfolded with increasing pH. Moreover, the ordered structure was reduced, and random coils became the dominant conformation. Its ß-sheet and random coil contents increased from 18.43 ± 0.08 and 33.62 ± 0.17 to 19.72 ± 0.02 and 39.53 ± 1.03%, respectively, with increasing pH. α-helices and ß-turns decreased from 35.00 ± 0.26 and 12.95 ± 0.01 to 29.39 ± 0.92 and 11.36 ± 0.10%, respectively. The increase in ß-sheets and random coils allowed the pI-treated collagen to exhibit maximum water contact angle. The emulsification and foaming properties decreased and then increased with increasing pH in a V-shape. The increased net surface charge and ß-sheets in collagen benefited its emulsification and foaming properties. The rheological results showed that the protoprotein exhibited shear-thinning properties in all pH ranges. The collagen solutions showed liquid-like behaviour in low-pH (2, 4) solutions and solid-like behaviour in high-pH (6, 7.83 and 10) solutions. Moreover, the frequency-dependent properties of the storage modulus (G') and loss modulus (G″) of the collagen solutions weakened with increasing pH. Collagen has considerable frequency-dependent properties of G' and G″ at low pH (2, 4). Thus, the importance of collagen raw material preparation for subsequent processing was emphasised, which may provide new insights into applying collagen-based materials in food, biomaterials and tissue engineering.

Vertical Distribution Mapping for Methane Fugitive Emissions Using Laser Path-Integral Sensing in Non-Cooperative Open Paths.

Observing the vertical diffusion distribution of methane fugitive emissions from oil/gas facilities is significant for predicting the pollutant's spatiotemporal transport and quantifying the random emission sources. A method is proposed for methane's vertical distribution mapping by combining the laser path-integral sensing in non-non-cooperative open paths and the computer-assisted tomography (CAT) techniques. It uses a vertical-plume-mapping optical path configuration and adapts the developed dynamic relaxation and simultaneous algebraic reconstruction technique (DR-SART) into methane-emission-distribution reconstruction. A self-made miniaturized TDLAS telemetry sensor provides a reliable path to integral concentration information in non-non-cooperative open paths, with Allan variance analysis yielding a 3.59 ppm·m sensitivity. We employed a six-indexes system for the reconstruction performance analysis of four potential optical path-projection configurations and conducted the corresponding validation experiment. The results have shown that that of multiple fan-beams combined with parallel-beam modes (MFPM) is better than the other optical path-projection configurations, and its reconstruction similarity coefficient (ε) is at least 22.4% higher. For the different methane gas bag-layout schemes, the reconstruction errors of maximum concentration (γm) are consistently around 0.05, with the positional errors of maximum concentration (δ) falling within the range of 0.01 to 0.025. Moreover, considering the trade-off between scanning duration and reconstruction accuracy, it is recommended to appropriately extend the sensor measurement time on a single optical path to mitigate the impact of mechanical vibrations induced by scanning motion.

Source apportionment and risk assessment of heavy metals in typical greenhouse vegetable soils in Shenyang, China.

In this study, the concentrations of Cr, Cu, Ni, Pb, Zn, Cd, As, and Hg in the typical greenhouse vegetable soils in Shenyang, Northeast of China, were determined, and the pollution characteristics and primary sources of heavy mental pollution in soil were analyzed. Results showed that the sum of the mean values of eight typical heavy metals in the soil of the greenhouse soils was 219.79 mg/kg. According to the "Chinese Environmental Quality Evaluation Standard for Farmland of Greenhouse Vegetables Production" (HJ/T 333-2006), the concentrations of Cu (33.50 ± 11.99 mg/kg), Cd (0.246 ± 0.156 mg/kg), and Hg (0.214 ± 0.177 mg/kg) exceeded the limit values in 14.29%, 39.29%, and 39.29% of sampling points, respectively. The single factor pollution index and the Nemerow comprehensive pollution index of heavy metal elements showed that most greenhouse soils were at safety, alert, or light pollution levels. The potential ecological risk index (RI = 505.19) showed that 42.86% of the samples were at high or very high risk and Cd and Hg were the main ecological risk factors. Based on the result of correlation analysis, the Positive Matrix Factorization (PMF) differentiated sources of heavy metal pollution in the study area into four components, including fertilizer input, soil parent material, pesticide spraying and raw coal combustion, and plastic film mulching, which accounted for 36.76%, 22.64%, 20.89%, and 19.71%, respectively, of the total sources of heavy metals.

Prediction of wavefront distortion for wavefront sensorless adaptive optics based on deep learning.

Aimed at the slow detection speed and low measurement accuracy of wavefront aberration in current wavefront sensorless adaptive optic technology, different convolution neural networks (CNNs) are established to detect the turbulence wavefront, including an ordinary convolutional neural network, a ResNet network, and an EfficientNet-B0 network. By using the nonlinear fitting ability of deep neural networks, the mapping relationship between Zernike coefficients and focal degraded image can be established. The simulation results show that the optimal network model after training can quickly and efficiently predict the Zernike coefficients directly from a single focal degraded image. The root-mean-square errors of the wavefront detection accuracy of the three networks are 0.075λ, 0.058λ, and 0.013λ, and the time consumed for predicting the wavefront from the single degraded image are 2.3, 4.6, and 3.4 ms, respectively. Among the three networks presented, the EfficientNet-B0 CNN has obvious advantages in wavefront detection accuracy and speed under different turbulence intensities than the ordinary CNN and ResNet networks. Compared with the traditional method, the deep learning method has the advantages of high precision and fast speed, without iteration and the local minimum problem, when solving wavefront aberration.

Preparation and Characterization of Thermally Stable Collagens from the Scales of Lizardfish (Synodus macrops).

Marine collagen is gaining vast interest because of its high biocompatibility and lack of religious and social restrictions compared with collagen from terrestrial sources. In this study, lizardfish (Synodus macrops) scales were used to isolate acid-soluble collagen (ASC) and pepsin-soluble collagen (PSC). Both ASC and PSC were identified as type I collagen with intact triple-helix structures by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and spectroscopy. The ASC and PSC had high amino acids of 237 residues/1000 residues and 236 residues/1000 residues, respectively. Thus, the maximum transition temperature (Tmax) of ASC (43.2 °C) was higher than that of PSC (42.5 °C). Interestingly, the Tmax of both ASC and PSC was higher than that of rat tail collagen (39.4 °C) and calf skin collagen (35.0 °C), the terrestrial collagen. Solubility tests showed that both ASC and PSC exhibited high solubility in the acidic pH ranges. ASC was less susceptible to the "salting out" effect compared with PSC. Both collagen types were nontoxic to HaCaT and MC3T3-E1 cells, and ASC was associated with a higher cell viability than PSC. These results indicated that ASC from lizardfish scales could be an alternative to terrestrial sources of collagen, with potential for biomedical applications.

Piston Error Measurement for Segmented Telescopes with an Artificial Neural Network.

A piston error detection method is proposed based on the broadband intensity distribution on the image plane using a back-propagation (BP) artificial neural network. By setting a mask with a sparse circular clear multi-subaperture configuration in the exit pupil plane of a segmented telescope to fragment the pupil, the relation between the piston error of segments and amplitude of the modulation transfer function (MTF) sidelobes is strictly derived according to the Fourier optics principle. Then the BP artificial neural network is utilized to establish the mapping relation between them, where the amplitudes of the MTF sidelobes directly calculated from theoretical relationship and the introduced piston errors are used as inputs and outputs respectively to train the network. With the well trained-network, the piston errors are measured to a good precision using one in-focused broadband image without defocus division as input, and the capture range achieving the coherence length of the broadband light is available. Adequate simulations demonstrate the effectiveness and accuracy of the proposed method; the results show that the trained network has high measurement accuracy, wide detection range, quite good noise immunity and generalization ability. This method provides a feasible and easily implemented way to measure piston error and can simultaneously detect the multiple piston errors of the entire aperture of the segmented telescope.

Comprehensive anticancer drug response prediction based on a simple cell line-drug complex network model.

BACKGROUND: Accurate prediction of anticancer drug responses in cell lines is a crucial step to accomplish the precision medicine in oncology. Although many popular computational models have been proposed towards this non-trivial issue, there is still room for improving the prediction performance by combining multiple types of genome-wide molecular data. RESULTS: We first demonstrated an observation on the CCLE and GDSC datasets, i.e., genetically similar cell lines always exhibit higher response correlations to structurally related drugs. Based on this observation we built a cell line-drug complex network model, named CDCN model. It captures different contributions of all available cell line-drug responses through cell line similarities and drug similarities. We executed anticancer drug response prediction on CCLE and GDSC independently. The result is significantly superior to that of some existing studies. More importantly, our model could predict the response of new drug to new cell line with considerable performance. We also divided all possible cell lines into "sensitive" and "resistant" groups by their response values to a given drug, the prediction accuracy, sensitivity, specificity and goodness of fit are also very promising. CONCLUSION: CDCN model is a comprehensive tool to predict anticancer drug responses. Compared with existing methods, it is able to provide more satisfactory prediction results with less computational consumption.

Physicochemical and Functional Properties of Type I Collagens in Red Stingray (Dasyatis akajei) Skin.

Collagen is widely used in the pharmaceutical, tissue engineering, nutraceutical, and cosmetic industries. In this study, acid-soluble collagen (ASC) and pepsin-soluble collagen (PSC) were extracted from the skin of red stingray, and its physicochemical and functional properties were investigated. The yields of ASC and PSC were 33.95 ± 0.7% and 37.18 ± 0.71% (on a dry weight basis), respectively. ASC and PSC were identified as type I collagen by Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) analysis, possessing a complete triple helix structure as determined by UV absorption, Fourier transform infrared, circular dichroism, and X-ray diffraction spectroscopy. Contact angle experiments indicated that PSC was more hydrophobic than ASC. Thermal stability tests revealed that the melting temperature of PSC from red stingray skin was higher than that of PSC from duck skin, and the difference in the melting temperature between these two PSCs was 9.24 °C. Additionally, both ASC and PSC were functionally superior to some other proteins from terrestrial sources, such as scallop gonad protein, whey protein, and goose liver protein. These results suggest that PSC from red stingray skin could be used instead of terrestrial animal collagen in drugs, foods, cosmetics, and biological functional materials, and as scaffolds for bone regeneration.

Notch Signaling Regulates Microglial Activation and Inflammatory Reactions in a Rat Model of Temporal Lobe Epilepsy.

The inflammatory response mediated by microglia in the central nervous system is closely related to epilepsy. Notch signaling plays an important role in the microglial activation during hypoxia. This study aimed to investigate whether Notch signaling is involved in microglial activation and subsequent inflammation-related neuronal injury during the process of epileptogenesis in a rat model of temporal lobe epilepsy. By using western blotting, real-time quantitative PCR, immunohistochemistry and immunofluorescence labeling, we found that the expression of Notch signaling increased after status epilepticus and that a γ-secretase inhibitor could significantly inhibit the upregulation of Notch signaling, the activation of microglia, and the release of proinflammatory cytokines. Likewise, the neuronal apoptosis and loss in the hippocampus after SE were attenuated by the γ-secretase inhibitor. These results suggest that Notch signaling plays a key role in neuroinflammation and inflammation-related neuronal damage in epilepsy, and γ-secretase inhibitors may become a novel prospective therapeutic agent for epilepsy.

Sequence comparison and essential gene identification with new inter-nucleotide distance sequences.

Four new inter-nucleotide distance sequences for a DNA sequence are defined. They are different from ones presented by Afreixo et al., and overcome the irreversible defect of the global inter-nucleotide distance sequence proposed by Nair and Mahalakshmi. Five basic statistical quantities are extracted from (ordered) precise inter-nucleotide distance sequences to construct a 20 dimensional feature vector. This simple mathematical descriptor of DNA sequence plays crucial roles in sequence comparison and essential gene identification. Euclidean distance between feature vectors is utilized to compare similarities among whole mitochondrial genomes of 18 eutherian mammals and 23 sequences of 16S ribosomal RNA, respectively. Derived phylogenetic trees are quite agreement with a few popular studies. Furthermore, using feature vector as input a support vector machine (SVM)-based method are developed to identify essential genes and non-essential genes of 5 bacteria. Higher AUC values (the minimum is 0.7971, the highest reaches 0.8751 and the average is 0.8174) than some well-known results confirm the performance of the method.

Predicted no-effect concentration and risk assessment for 17-[beta]-estradiol in waters of China.

Contamination of the aquatic environment by EDCs has received considerable attention from scientists, government officials, and the public. E2, one of the EDCs with high estrogenic effect, has the potential to cause multiple endocrine-disrupting effects, even at small concentrations. In the present review, the toxicity of E2 to aquatic organisms was reviewed. Results of published studies show that, for aquatic species, reproductive effects were the most sensitive endpoint for E2 exposure.Although the risks posed by EDCs have caused much attention, the research on the WQC 'for EDCs is still at the initial stage. It has been suggested in several reports that the PNEC can be regarded as the most appropriate reference value for developing WQC for the EDCs. The SSD method was applied to derive PNECs that were based on reproductive effects endpoints. In the present review, 31 NOECs, based on reproductive effect endpoints for different species, were selected to construct the curve. ThePNEC value was determined to be 0.73 ng E2/L, which could protect the biodiversity of aquatic ecosystems. Moreover, 6 NOECs for multigeneration species were also analyzed in anticipation of sensitivity comparison between the Fa and the F1 generations.When multiple generations of aquatic species were exposed to concentrations no greater than 100 ng E2/L, nearly 71.4% of the F 1 generation individuals were more sensitive to the effects of E2 than those of the Fa generation. This result indicated that different generations of the same species may respond differently to EDCs exposure.Individuals of the F 1 generation were slightly more sensitive than those of the Fa generation,in general. Therefore, protecting the F1 generation of aquatic organisms is particularly important when WQC values for the EDCs are established.Considering the toxic effects of EDCs on reproduction, long-term toxic effects(viz., full-life cycle study and the most sensitive life stage) should be used in settingWQC. Unfortunately, the NOECs of E2 for multigeneration species did not meet the requirement of PNEC derivation for protecting the Fl generation. Therefore, further research results are needed on the Fl generation of aquatic species to provide more insight into what constitutes adequate protection for aquatics lives. In the present review, the PNEC values derived in the study were compared to thePNEC values developed by others, and the results showed that they were highly consistent. In addition, we also compared the PNEC value for E2 to the PNEC value for EE2, a similar estrogen, and the result was also highly consistent when their EEFs were considered. These comparisons affirmed that the method we used for deriving the PNEC value of E2 was reasonable and the PNEC values we derived were acceptable for protecting aquatic organisms. By comparing the PNEC values we calculated to actual E2 concentrations in the natural water environment, we found that E2 in surface waters may pose high risks in many countries, especially China, Japan, the USA, Great Britain, and Italy.

Assessing the policy benefits of constructing "Zero-waste Cities" in China: From the perspective of hazardous waste lifecycle management.

Based on China's quasi-natural experiment of constructing "Zero-waste Cities", this study assessed its policy benefits on hazardous waste lifecycle management. Utilizing the theory of difference-in-differences analysis, the study quantifies the net benefits of the policy in 10 pilot cities using an average treatment effect formula, and the results indicate a reduction of 162,900 tons/year in waste generation, an increase of 2.3 % in utilization and disposal rate, and a decrease of 28,200 tons/year in end-of-pipe storage. By constructing a regression model and employing robustness tests such as changing control variables, substituting the explained variable, re-matching control groups, and random assignment of pilot sites, the study confirms that the significant policy benefits primarily lie in source reduction, with a reduction intensity of approximately 1.73 tons/100 million yuan of industrial GDP. Additionally, by applying the mixed-effects model and mediation-analysis model, the study finds that the policy benefit of source reduction exhibits a lag effect, and during the pilot period, the main approach to achieving the benefit was through enhancing cleaner production in companies rather than adjusting industrial structures in cites.

Fabrication and characterisation of collagen/pullulan ultra-thin fibers by electrospinning.

Collagen electrospun fibers are promising materials for food packaging and tissue engineering. The conventional electrospinning of collagen, however, is usually carried out by dissolving it in organic reagents, which are toxic. In this study, collagen/pullulan (COL/PUL) ultra-thin fibers were prepared by electrospinning using acetic acid as a solvent. Compared to the conventional preparation method, the proposed method is safe and does not produce toxic solvent residues. The introduction of PUL increased the degree of molecular entanglement in the solution, so the viscosity of the COL/PUL electrospun solution increased from 0.50 ± 0.01 Pa∙s to 4.40 ± 0.08 Pa∙s, and the electrical conductivity decreased from 1954.00 ± 1.00 mS/cm to 1372.33 ± 0.58 mS/cm. Scanning electron microscopy analysis confirmed that PUL improved the spinnability of COL, and smooth, defect-free COL/PUL ultra-thin fibers with diameters of 215.32 ± 40.56 nm and 240.97 ± 53.93 nm were successfully prepared at a viscosity of greater than 1.18 Pa∙s. As the proportion of PUL increased, intramolecular hydrogen bonds became the dominant interaction between COL and PUL. The intermolecular hydrogen bonding content decreased from 52.05 % to 36.45 %, and the intramolecular hydrogen bonding content increased from 46.11 % to 62.95 %. The COL was gradually unfolded, the content of α-helices decreased from 33.57 % to 25.91 % and the random coils increased from 34.22 % to 40.09 %. More than 36 % of the triple helix fraction of COL was retained by the COL/PUL ultra-thin fibers, whereas only 16 % of the triple helix fraction of COL was retained by the COL nanofibers prepared with 2.2.2-trifluoroethanol. These results could serve as a reference for the development of green food COL-based fibers.

SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.

The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predicting drug synergy, but high computational cost for training models as well as great diversity and limited size in screening data escalate the difficulty of prediction. To address this challenge, we propose a simple machine learning framework, namely Similarity Network-based Synergy prediction (SNSynergy), for predicting synergistic effects towards new cell lines and new drug combinations by two locally weighted models CLSN and DCSN. This framework only requires a small amount of auxiliary data, like genomics information of cell lines and the molecular fingerprints or targets of drugs. Based on the assumption that similar cell lines and similar drug combinations have similar synergistic effects, CLSN and DCSN predict synergy scores through capturing individual synergy contributions of nearest cell line and drug combination neighbors, respectively. High correlations between predicted and measured synergy scores on two leading cancer cell line pharmacogenomic screening datasets (the O'Neil dataset and the NCI-ALMANAC dataset) demonstrate the effectiveness and robustness of SNSynergy. Many of the identified drug combinations are consistent with previous studies, or have been explored in clinical settings against the specific cancer type, showing that SNSynergy has the potential to supply cost-saving and effective high-throughput screening for prioritizing the most applicable cell lines and the most promising drug combinations.

Comparison of Structural and Physicochemical Characteristics of Skin Collagen from Chum Salmon (Cold-Water Fish) and Nile Tilapia (Warm-Water Fish).

This study compared collagens from cold-water and warm-water fish for their structural, rheological, and functional properties, and explored their potential applications, aiming to realize the high-value utilization of marine biological resources. To this end, chum salmon skin collagen (CSSC) and Nile tilapia skin collagen (NTSC) were both successfully extracted. Collagens from the two species had different primary and secondary structures, with NTSC having a higher molecular weight, imino acid content, and α-helices and ß-turns content. The denaturation temperatures were 12.01 °C for CSSC and 31.31 °C for NTSC. CSSC was dominated by viscous behavior and its structure varied with temperature, while NTSC was dominated by elastic behavior and its structure remained stable with temperature. Both collagens had good oil holding capacity, foaming capacity, and emulsifying activity, but NTSC had better water holding capacity and foaming and emulsifying stability. Their different properties make CSSC more suitable for the preservation of frozen and chilled foods and the production of sparkling beverages, and give NTSC greater potential in biofunctional materials and solid food processing.

Clinical characteristics of adolescent-onset gout in Chinese: A hospital-based cross-sectional study.

OBJECTIVE: Adolescent-onset gout has a greater impact on the lives and health of patients than adult-onset gout. However, there is a relative lack of clinical information on adolescent-onset gout. Hence, we analyzed a Chinese cohort. METHODS: We studied clinical features of 9,003 Chinese patients. Gout onset age of 12 - 19 years is defined as adolescent-onset group (AG), 20 - 40 years as early-onset group (EG), and 41 - 64 years as late-onset group (LG). Multivariable regression analysis evaluated factors associated with recurrent flares, serum urate (SU) levels, and underexcretion type in AG. RESULTS: Compared with EG and LG, the AG had higher SU levels [AG: 9.5 (2.2) mg/dL, EG: 8.6 (2.1) mg/dL, LG: 7.73 (2.0) mg/dL, P < 0.001], higher percentage of positive family history of gout (AG: 41.8 %, EG: 29.6 %, LG: 24.6 %, P < 0.001), underexcretion type (AG: 62.4 %, EG: 62.5 %, LG: 58.8 %, P = 0.04), recurrent flares (AG: 78.1 %, EG: 70.3 %, LG: 68.9 %, P = 0.01). Urate-lowering therapy (ULT) initiated [OR 6.58 (95 % CI 1.35 - 32.00)] and hypercholesterolemia [OR 4.16 (95 % CI 1.28 - 13.53)] were associated with recurrent flares. eGFR was identified to be a significant variable of increasing SU levels [beta -0.24 (95 % CI -0.04 to -0.01)]. Hypertriglyceridemia [OR 0.35 (95 % CI 0.17 - 0.71)] was related to underexcretion type. CONCLUSION: Adolescent-onset gout patients had clinically distinctive features with higher SU levels, BMI, positive gout family history, underexcretion type and recurrent flares. These specific populations were less likely to achieve ULT target, requiring more clinical attention.

Distribution and sources of polycyclic aromatic hydrocarbons in the surface water of Taizi River, Northeast of China.

Spatial and seasonal distribution and sources of 16 polycyclic aromatic hydrocarbons (PAHs), identified as priority pollutants by the US Environmental Protection Agency, were investigated in the surface water of the Taizi River in Liaoning Province, northeast of China. Samples were collected from the mainstream, and tributaries of the Taizi River in dry, wet, and normal seasons. Five important industrial point sources were also monitored. The total PAH concentrations ranged from 454.5 to 1,379.7 ng l(-1) in the dry season, 1,801.6 to 5,868.9 ng l(-1) in the wet season, and 367.0 to 5,794.5 ng l(-1) in the normal season. The total PAH concentrations were significantly increased in the order of wet season > normal season > dry season. The profile of PAHs in the surface water samples was dominated by low molecular weight PAHs particularly with two- and three-ring components in the three seasons, suggesting that the PAHs were from a relatively recent local source. Source identification inferred that the PAHs in the surface water of the Taizi River came from both petrogenic inputs and pyrogenic sources.

Suppression of P2X7R by Local Treatment Alleviates Acute Gouty Inflammation.

Objective: Gout is the most common inflammatory arthritis associated with interleukin-1ß (IL-1ß) accumulation during exacerbation. In this study, we aimed to clarify whether potassium channel antagonists attenuate local inflammation in mice with monosodium urate (MSU)-induced gout. Methods: We cultured human macrophage THP-1 cells and evaluated the molecular levels of both IL-1ß and potassium channels stimulated with MSU and/or potassium channel antagonists. Acute gout models were generated in IL-1ß luciferase transgenic male mice using synovium-like subcutaneous air pouches with MSU injection. Their luciferase activities were monitored following potassium channel blocker treatment using the IVIS Spectrum CT imaging system. The lavages and tissues were extracted from their air pouches, followed by cell counting and pathological analysis. Results: MSU stimulation increased the gene expression levels of pro-IL-1ß, P2x7r and Kv1.3, whereas the expression of Kcnq1 was decreased in phorbol 12-myristate 13-acetate-induced THP-1 cells. Both high and low concentrations of the P2x7 receptor inhibitor adenosine 5'-triphosphate (ATP) derivative periodate oxidized ATP (oATP) decreased the production of IL-1ß in the supernatant of THP-1 cells. The sixth hour was the peak time of IL-1ß luciferase activity after MSU intervention in vivo. oATP ameliorated the synovial IL-1ß luciferase activity, reduced inflammatory cell infiltration and alleviated the erosive damage in the cartilage. Conclusion: The anti-inflammatory properties of potassium channel inhibitors, especially of oATP, might point to new strategies for local anti-inflammatory therapy for acute gout.

Identification of ground spilled oil of buried pipeline based on laser absorption spectroscopy: Numerical investigation and experimental verification.

The ground diffusion characteristics of buried oil pipeline after leakage and the laser optical transmission mechanism of surface oil film are the basis of spectral detection technology. Based on the computational fluid dynamics to solve the diffusion equation of multiphase flow in porous media, the leakage law of oil under different soil porosity is analyzed in two dimensions: surface diffusion diameter and oil film thickness. TracePro optical simulation is used to study the absorption and reflection patterns of laser at the oil-gas interface, and validation experiments are carried out based on the tunable diode laser absorption spectroscopy method. The results show that oil is easily accumulated on the ground surface with larger soil porosity and in the depressions of the ground surface. When the oil film thickness is greater than 2 mm, the laser cannot transmit the oil layer and the received light intensity is only provided by the mirror reflection at the oil-gas interface. The mechanism of laser detection of oil leaks is the spectral absorption of volatile alkane gases in the upper layer of the oil film by a laser of a specific wavelength.

Hippocampal Subfield Volumes in Amateur Marathon Runners.

PURPOSE: Numerous studies have implicated the involvement of structure and function of the hippocampus in physical exercise, and the larger hippocampal volume is one of the relevant benefits reported in exercise. It remains to be determined how the different subfields of hippocampus respond to physical exercise. METHODS: A 3D T1-weighted magnetic resonance imaging was acquired in 73 amateur marathon runners (AMR) and 52 healthy controls (HC) matched with age, sex, and education. The Montreal Cognitive Assessment, the Pittsburgh Sleep Quality Index (PSQI), and the Fatigue Severity Scale were assessed in all participants. We obtained hippocampal subfield volumes using FreeSurfer 6.0. We compared the volumes of the hippocampal subfield between the two groups and ascertained correlation between the significant subfield metrics and the significant behavioral measure in AMR group. RESULTS: The AMR had significantly better sleep than HC, manifested as with lower score of PSQI. Sleep duration in AMR and HC was not significantly different from each other. In the AMR group, the left and right hippocampus, cornu ammonis 1 (CA1), CA4, granule cell and molecular layers of the dentate gyrus, molecular layer, left CA2-3, and left hippocampal-amygdaloid transition area volumes were significantly larger compared with those in the HC group. In AMR group, the correlations between the PSQI and the hippocampal subfield volumes were not significant. No correlations were found between hippocampal subfield volumes and sleep duration in AMR group. CONCLUSIONS: We reported larger volumes of specific hippocampal subfields in AMR, which may provide a hippocampal volumetric reserve that protects against age-related hippocampal deterioration. These findings should be further investigated in longitudinal studies.