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Background: This study investigated the trends, motivations and preferences of rhinoplasty in China. Methods: Data on rhinoplasty were collected from Xiaohongshu and analyzed for trends. Text analysis and word frequency statistics were performed on the notes and comments using Python modules. Results: We obtained 1065 notes with 102,153 comments, 239,383 collections and 640,579 likes. The number of rhinoplasty-related publications increased annually, correlating with per capita disposable income of households (DI) growth (r2 = 0.609, P = 0.041 < 0.05). In the Southern provinces, there was a notably higher volume of publications compared to the Northern provinces (P = 0.001). Furthermore, a significant correlation was observed between publication data, population size, and the DI (r2 = 0.786, P < 0.001). The nasal tip (3197) and nasion (1409) were the most mentioned nasal subunits. "Good-looking" (9672) and "natural" (2811) were the most used words to describe the nose shape. The "doctor" (4377), the "hospital" (2182) and "hyaluronic acid" (2106) were the most mentioned rhinoplasty procedure related vocabulary. Conclusions: Discussions about rhinoplasty in China are increasing, and more people express their desire for rhinoplasty on social networks, related to China's DI growth. The Southern provinces show a higher inclination toward these discussions, a trend that correlates with our findings of a positive association between NOPs and both DI and population size. Netizens pay more attention to the shape of nasal tip and nasion, and prefer the good-looking and natural appearance. Most people consider autologous cartilage or hyaluronic acid injection for rhinoplasty. Doctors are the primary consideration for patients. Level of Evidence V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266. [ABSTRACT FROM AUTHOR]

In comparison with traditional mesoporous materials, dendritic mesoporous silica&titania nanospheres (DMSTNs) with three-dimensional central radial pore channels and multiscale pores have larger pore volume, higher specific surface area, and easier accessible surfaces, making them promising carrier platforms for the applications in catalysis, drug delivery, heavy metals adsorption, etc. In this study, DMSTNs have been manufactured by a one-pot co-condensation method using titanium(diisopropoxide)bis(2,4-pentanedionate) (TDA) as the titanium source. Their morphologies and structures have been finely tuned by TDA content, reaction temperature, stirring rate, solvents, and so forth. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) have been utilized to directly reveal their differences. Two typical kinds of DMSTNs synthesized at different temperatures have been compared, covering N2 adsorption-desorption isotherms, X-ray photoelectron spectroscopy (XPS), Raman spectrum, ultraviolet-visible diffuse reflectance spectroscopy (UV-Vis-DRS), Fourier Transform Infrared spectroscopy (FT-IR), etc. XPS and Raman results testify that the chemical composition and architecture of these DMSTNs resemble those of titanium silicalite-1 (TS-1) zeolite. The hydrogen yield and the corresponding rate of DMSTNs synthesized at 120 ℃ are 3.56 µmol·g-1 and 0.71 µmol·g-1·h-1, being about 2.99 times higher than those of DMSNs that solely own SiO2 in the skeleton. Nevertheless, DMSTNs synthesized at 70 ℃ possess a 10.08 µmol·g-1 yield and a 2.04 µmol·g-1·h-1 rate, nearly 8.47 times higher than those of DMSNs. [ABSTRACT FROM AUTHOR]

Dendritic mesoporous silica nanospheres (DMSNs) possess excellent specific surface areas, pore volumes, and extremely accessible internal spaces. DMSNs have experienced high-speed development in the aspects of synthesis techniques, functionalization strategies, and application fields. It is proved that DMSNs own inherent structural superiorities as catalysts, adsorbents, or reaction platforms. Naturally, researchers are enlightened to conceive and attempt to synthesize dendritic mesoporous titania nanospheres (DMTNs) by replacing Si in DMSNs with Ti, in view of the superior activity and catalytic performance from TiO2. Nevertheless, the hydrolysis and condensation rates of the titanium precursors are too fast to develop ideal dendritic textures. To get the goal in a roundabout way, hybrid dendritic mesoporous silica&titania nanospheres (DMSTNs) come into sight. In this work, a series of DMSTNs have been synthesized by the one-pot co-condensation method. For the first time, their morphologies and architectures have been controlled by adjusting the ratio of titanium to silica, stirring speed, reaction temperature, co-solvent, etc. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) have been utilized to directly reveal their differences. The basic physicochemical properties of DMSTNs with fine topological structures have been compared, covering Fourier Transform Infrared spectroscopy (FT-IR), X-ray diffraction (XRD), N2 adsorption–desorption isotherms, Raman spectrum, X-ray photoelectron spectroscopy (XPS), ultraviolet–visible diffuse reflectance spectroscopy (UV-Vis-DRS), photoluminescence (PL) spectra, etc. Most importantly, these typical DMSTNs can photo-catalytically produce more hydrogen (2.4 ~ 3.6 times) within 1% Pt than that of bare DMSNs under simulated sunlight, owing to Ti in their skeletons. [ABSTRACT FROM AUTHOR]

The determination of potential glaucoma cases often relies on the vertical cup-to-disc ratio, which is directly derived from segmentation results. This study introduces an approach that leverages the geometric attributes of the optic disc (OD) and optic cup (OC) by employing a sector-based segmentation method to generate accurate segmentation results. This technique treats the OD and OC as approximate ellipses, partitioned into sectors. We propose a deep learning architecture named Sector Association and Multi-Coordinate Transformation Fusion (SAMF) network to address the problems that Convolutional Neural Networks struggle to learn long-range features. Meanwhile, our network possesses the capability to reduce the discontinuity of the boundaries of the OD and OC when inputs are images transformed into polar coordinates. The proposed SAMF network mainly consists of a Sector Association Layer and a Multi-Coordinate Transformation Fusion module. The Sector Association Layer models the interrelationships among sectors, especially the first and the last sectors, which are not contiguous in the polar transformed image. While the Multi-Coordinate Transformation Fusion module considers complementary representations in different coordinate systems, and it should be noted that the Multi-Coordinate Transformation Fusion component for various segmentation tasks. We perform experiments on the public datasets of REFUGE, Drishti-GS1 and a private dataset. Experimental results indicate that our SAMF network provides a significant boost to the performance of neural networks. The proposed method exhibits remarkable advancements in glaucoma screening through improved segmentation outcomes. The key code can be accessed at https://github.com/JieGenius/SAMFNetwork. [ABSTRACT FROM AUTHOR]

Acute lung injury (ALI) is a life-threatening disorder stemmed mainly from an uncontrolled inflammatory response. Lipopolysaccharide (LPS) is commonly used to induce ALI animal models. Toll-like receptor 4 (TLR4) is the main receptor for LPS, and myeloid differentiation factor 88 (MyD88) is a key adaptor protein molecule in the Toll-like receptor (TLR) signaling pathway. Thus, MyD88 knockdown heterozygous mice (MyD88+/−) were used to investigate the effect of incomplete knockout of the MyD88 gene on indirect LPS-induced ALI through intraperitoneal injection of LPS. The LPS-induced ALI significantly upregulated MyD88 expression, and heterozygous mice with incomplete knockout of the MyD88 gene (MyD88+/−) ameliorated LPS-induced histopathological injury and collagen fiber deposition. Heterozygous mice with incomplete knockout of the MyD88 gene (MyD88+/−) inhibited LPS-induced nuclear factor-κB (NF-κB) pathway activation, but TLR-4 expression tended to be upregulated. Incomplete knockdown of the MyD88 gene also downregulated LPS-induced expression of IL1-β, IL-6, TNF-α, TGF-β, SMAD2, and α-SMA. The transcriptome sequencing also revealed significant changes in LPS-regulated genes (such as IL-17 signaling pathway genes) after the incomplete knockdown of MyD88. In conclusion, this paper clarified that LPS activates the downstream NF-κB pathway depending on the MyD88 signaling pathway, which induces the secretion of inflammatory cytokines such as IL-1β/IL-6/TNF-α and ultimately triggers ALI. Incomplete knockdown of the MyD88 reverses LPS-induced lung fibrosis, which confirmed the vital role of MyD88 in LPS-induced ALI. [ABSTRACT FROM AUTHOR]

The instantaneous frequency (IF) provides important characteristic information for analyzing signals. To improve the accuracy of IF estimation, time–frequency (TF) analysis with high resolution and high aggregation is necessary. A new IF estimation method is proposed in this paper, which is referred to as ridge path regrouping based on an adaptive short-time Fourier high-order synchrosqueezing transform (AFSST). In the TF analysis of the non-stationary signal, we optimize the window function of the short-time Fourier transform to be adaptive to signal characteristics, and then perform the high-order synchrosqueezing transform. Based on the high-resolution time–frequency distribution (TFD), the frequency ridge of the signal is extracted, and the ridge of the modal aliasing at the intersection is discarded and reorganized according to the fundamentals. Experiments on multicomponent nonstationary signals were performed, and the results show that AFSST has satisfactory TF aggregation and TF resolution. IF estimation experiment based on AFSST, the results indicate that the proposed method can estimate the IF accurately even under a low signal-to-noise ratio (SNR). [ABSTRACT FROM AUTHOR]

Introduction: Cicatricial alopecia not only affects the appearance of children's heads and faces but also their mental health in the long term. This study aims to explore the therapeutic characteristics and clinical effects of autologous hair transplantation technology in children with cicatricial alopecia. Methods: Children in our department who received autologous hair transplantation technology for cicatricial baldness of the scalp from February 2019 to October 2022 were collected. Their basic information was analyzed, and postoperative follow-up was conducted, including calculation of hair follicle survival rate, hair growth, complications, and an efficacy satisfaction survey given to the children's family members. Results: Thirteen children were included in this study (10 males and 3 females), aged from 4 years 1 month to 12 years 10 months, with an average age of 7 years 5 months. Two hundred to 2500 hair follicular units were extracted, with an average recipient area of 22.7 cm2, an average hair follicle unit density of 55.3 ± 9.1 per cm2, and an average hair/follicular unit (hair/FU) ratio of 1.75 ± 0.07. Thirteen children in this group were followed up for 6–12 months with the following treatment options: FUE (follicular unit extraction, 9 cases), FUT (follicular unit transplantation, 3 cases), and FUT combined with FUE (1 case). The average hair survival rate was 85.3%. Except for one child with temporary folliculitis, there were no complications. The GAIS score is divided into five levels: complete improvement (2 cases), obvious improvement (10 cases), partial improvement (1 case), no improvement (0 cases), and deterioration (0 cases). The patient satisfaction results included very satisfied (2 cases), mostly satisfied (10 cases), and dissatisfied (1 case). Conclusion: Autologous hair transplantation technology is a safe and effective method for children with cicatricial alopecia. [ABSTRACT FROM AUTHOR]

Potato has a great diversity of cultivars which differ in chemical composition. At present, effects of meteorological factors on dry matter accumulation and yield increase of potato are relatively well known, but there are few studies on variation in internal quality indicators critical for potato postharvest treatment. In this experiment, samples from 9 cultivars were collected during the five growing seasons of 2016 to 2020. Contents of 8 nutritional and physicochemical indicators of potato tubers were determined. The overall stability and sources of variation in quality were evaluated by the multiple comparison method and by the bubble chart analysis. Moreover, in order to evaluate the influence of climate change on potato quality, 16 meteorological factors were analysed by using data measured during the potato growing seasons of 2016 to 2020. Stepwise regression analysis (SRA) was used to establish statistical models of climate impact on different cultivars. The results showed that the internal quality could be quantitatively evaluated by the variation in meteorological factors. The maximum Variance Inflation Factor (VIF) of each model was less than 10. The adjusted R2 values (> 0.7) and probability of F values (≤ 0.05) indicated a high degree of fit and good predicting effect, which can provide guidance for efficient and rational utilization of ecological and environmental resources. [ABSTRACT FROM AUTHOR]

In order to solve the problem of weak detection of small targets in traditional methods, an improved object detection algorithm is proposed. First, the six multi-scale feature maps extracted from the original SSD algorithm are fused in turn to form a new feature map with detailed information and semantic information based on the feature pyramid network and the idea of single shot multibox detector algorithm. Then, the attention model is added to the fused feature map, and the feature information of small targets can be extracted effectively. With PASCAL VOC2007 and VOC2012 as the training set, the mean average precision tested in the VOC2007 test set reached 78.3%, which is 1.1% higher than the original algorithms. In different environments, the algorithm has accurate detection effect on densely distributed small objects, and the missed detection and robustness are better than other algorithms. At the same time, the detection speed can still meet the real-time requirements. [ABSTRACT FROM AUTHOR]

As for supported noble metal catalysts, the aggregation, leaching, and migration of the noble metals are fatal to their catalytic performances. Up to now, it is still challengeable to not only highly load and finely disperse noble metal nanopartcicles (NPs) onto the support platforms, but also maintain the physicochemical state of the already anchored NPs. Herein, for the first time, we have found that hybrid dendritic mesoporous silica&titania nanospheres (DMSTNs) and the coupled mercapto groups (–SH) on their surface could remarkably load and disperse ultrafine silver (Ag) NPs simultaneously. The as-prepared DMSTNs-SH-Ag composite catalyst exhibits more superior abilities for photocatalytic water splitting, p-nitrophenol reduction without light irritation, and antibacteria, in comparison to pure dendritic mesoporous silica nanospheres (DMSNs)-based catalysts like DMSNs-SH-Ag or amino groups (–NH2) functionalized ones (e.g., DMSTNs-NH2-Ag and DMSNs-NH2-Ag). The improvement can be attributed to the unique physicochemical and structural advantages of DMSTNs-SH supports that bring about desirable loading and dispersion of Ag NPs, the decreased recombination rate of the photo-generated electron–hole pair, the longer route of electron migration, etc. DMSTNs-SH-Ag also exhibit stable recycling and leaching-resistant abilities. The access to DMSTNs-SH-Ag is simple, facile, and economical, which could be versatile for anchoring other noble metals as well theoretically. [ABSTRACT FROM AUTHOR]

Psychological fatigue includes mental fatigue and burnout. In order to investigate the impact of psychological fatigue on athletes' response monitoring, event-related potentials technique is typically used, and the most critical indicator is error-related negativity. Two experiments were carried out to explore cause-effect relationships of psychological fatigue and response monitoring. The event-related potentials data processing was based on Artificial Intelligence computing methods, including wavelet transform, grayscale transformation and other algorithms. The first experiment was done to explain mental fatigue and response monitoring. 15 participants operated continuously 60 min Flanker task, and then operated 15 min task accompanied by light music. From the results of behavioral performances, the fatigue period compared with the fatigue-free period showed significant differences, including reaction time (p = 0.029) and correct rate (p = 0.046). From the results of error-related negativity, the amplitude of the fatigue-free period was bigger than that of the music adjustment period, the latter was bigger than that of the fatigue period (p < 0.001). The second experiment was conducted to explore burnout and response monitoring. Twenty-four participants were separated averagely into two groups. One group was burnout group, the other group was no burnout group. They both operated 15 min task. From the results of behavioral performances, no burnout group was better than burnout group. From the results of error-related negativity, no burnout group's amplitude was bigger than that of burnout group, but the difference was marginally significant. The conclusions are as follows: Artificial intelligence technology is feasible for processing event-related potentials data. Psychological fatigue weakens athletes' response monitoring ability, and the effect of mental fatigue is significant. In future researches, the following topics should be concerned, including the mediating or moderating effects of third variables, different ways of recovering from mental fatigue, computer data simulator and date accuracy, brain-computer interfaces and error-related negativity, etc. [ABSTRACT FROM AUTHOR]

Aiming at improving the accuracy of current tracking algorithms and tracking the target more quickly, a new target tracking method that is from multiscale analysis is presented, which is combined with combinatorial polygon matching. First, a target's range is estimated by analyzing multiple scales in the reference frame. Then, the pixels are judged as the target pixels within the target range determined in the previous step by calculating the relevant radial distance and judging the similarity of radial distance between target pixels to be detected and its background pixels. At the same time, the background modeling is updated according to the similarity between the incremental code of the background pixels and the corresponding pixels in the observed images. Last, the target trajectory is obtained by dynamic polygon matching. When encountering external interference, the performance of the improved algorithm is relatively stable. Compared with the existing methods, the proposed algorithm in this paper is verified by simulation, which is simple in operation and can track the target quickly and accurately. [ABSTRACT FROM AUTHOR]

Immunotherapy has emerged as an effective therapeutic strategy for various cancers, including colorectal cancer (CRC), but only a subset of MSI-H patients can benefit from such therapy. Patched1 (PTCH1) is a frequently altered gene in CRCs and its mutations contribute to unregulated Hedgehog (Hh) signaling. In the study, we evaluated the association of PTCH1 mutations with CRC immunity based on our single-center cohort and multiple cancer genomic datasets. Among 21 enrolled patients, six (28.6%) harbored a PTCH1 mutation based on WES analyses. In CRC patients, the PTCH1 mutation subgroup experienced a higher durable clinical benefit rate than the PTCH1 wild-type subgroup (100% vs. 40%, P = 0.017). In addition, patients with the PTCH1 mutation experienced greater progression-free survival (PFS, P = 0.037; HR, 0.208) and overall survival (OS, P = 0.045; HR, 0.185). A validation cohort from the MSKCC also confirmed the correlation between PTCH1 mutation and better prognosis (P = 0.022; HR, 0.290). Mechanically, diverse antitumor immune signatures were more highly enriched in PTCH1-mutated tumors than in PTCH1 wild-type tumors. Furthermore, PTCH1-mutated tumors had higher proportions of CD8 + T cells, activated NK cells, and M1 type macrophage infiltration, as well as elevated gene signatures of several steps in the cancer-immunity cycle. Notably, the PTCH1 mutation was correlated with tumor mutational burden (TMB), loss of heterozygosity score, and copy number variation burden. Our results show that the mutation of PTCH1 is a potential biomarker for predicting the response of CRC patients to immunotherapy. [ABSTRACT FROM AUTHOR]

Three-dimensional nitrogen-doped graphene aerogels (3D N-GAs) were prepared by ultrasonic stripping, hydrothermal reduction and freeze drying. Those N-GAs exhibited high-specific surface area, high nitrogen doping amount, and 3D porous network structure. Soft electro-active ionic polymer actuators were developed for the first time using this 3D N-GA soft electrode. The developed soft actuator exhibited large peak-to-peak displacement of 11.8 mm (3 V and 0.1 Hz) and high air working durability for 93.8% after 6 h cycles. These successful demonstrations elucidated the wide potential of 3D N-GA soft actuators for the next-generation soft robotic devices. [ABSTRACT FROM AUTHOR]

Aluminum demonstrates clear neurotoxicity and can cause Alzheimer's disease (AD)-like symptoms, including cognitive impairment. One toxic effect of aluminum is a decrease in synaptic plasticity, but the specific mechanism remains unclear. In this study, PC12 cells were treated with Al(mal)3 to construct a toxic cell model. (S)-3,5-Dihydroxyphenylglycine (DHPG), α-methyl-4-carboxyphenylglycine (MCPG), and mGluR1-siRNA were used to interfere with the expression of metabotropic glutamate receptor subtype 1 (mGluR1). Polymerase chain reaction and western blotting were used to investigate the expression of mGluR1, protein kinase C (PKC), and N-methyl-D-aspartate receptor (NMDAR) subunits. ELISA was used to detect PKC enzyme activity. In PC12 cells, mRNA and protein expressions of PKC and NMDAR subunits were inhibited by Al(mal)3. Aluminum may further regulate the expression of NMDAR1 and NMDAR2B through mGluR1 to regulate PKC enzyme activity, thereby affecting learning and memory functions. Furthermore, the results implied that the mGluR1-PKC-NMDAR signaling pathway may predominately involve positive regulation. These findings provide new targets for studying the neurotoxic mechanism of aluminum. [ABSTRACT FROM AUTHOR]

The association between genetic variations and immunotherapy benefit has been widely recognized, while such evidence in gastrointestinal cancer remains limited. We analyzed the genomic profile of 227 immunotherapeutic gastrointestinal cancer patients treated with immunotherapy, from the Memorial Sloan Kettering (MSK) Cancer Center cohort. A gastrointestinal immune prognostic signature (GIPS) was constructed using LASSO Cox regression. Based on this signature, patients were classified into two subgroups with distinctive prognoses (p < 0.001). The prognostic value of the GIPS was consistently validated in the Janjigian and Pender cohort (N = 54) and Peking University Cancer Hospital cohort (N = 92). Multivariate analysis revealed that the GIPS was an independent prognostic biomarker. Notably, the GIPS-high tumor was indicative of a T-cell-inflamed phenotype and immune activation. The findings demonstrated that GIPS was a powerful predictor of immunotherapeutic survival in gastrointestinal cancer and may serve as a potential biomarker guiding immunotherapy treatment decisions. [ABSTRACT FROM AUTHOR]

Nanoparticle internalisation is crucial for the precise delivery of drug/genes to its intracellular targets. Conventional quantification strategies can provide the overall profiling of nanoparticle biodistribution, but fail to unambiguously differentiate the intracellularly bioavailable particles from those in tumour intravascular and extracellular microenvironment. Herein, we develop a binary ratiometric nanoreporter (BiRN) that can specifically convert subtle pH variations involved in the endocytic events into digitised signal output, enabling the accurately quantifying of cellular internalisation without introducing extracellular contributions. Using BiRN technology, we find only 10.7–28.2% of accumulated nanoparticles are internalised into intracellular compartments with high heterogeneity within and between different tumour types. We demonstrate the therapeutic responses of nanomedicines are successfully predicted based on intracellular nanoparticle exposure rather than the overall accumulation in tumour mass. This nonlinear optical nanotechnology offers a valuable imaging tool to evaluate the tumour targeting of new nanomedicines and stratify patients for personalised cancer therapy. Quantification of intratumoral nanoparticles internalisation in vivo is crucial but challenging. Here, the authors develop a binary ratiometric nanoreporter that can quantify internalisation and predict nanotherapeutic responses based on intracellular nanoparticle exposure. [ABSTRACT FROM AUTHOR]

Aluminum (Al) is an environmental neurotoxin with extensive exposure by humans, but the molecular mechanism of its toxicity is still unclear. Several studies have indicated that exposure to aluminum can impair learning and memory function. The purpose of this study was to investigate the mechanism of LTP injury and the effect of aluminum exposure on related signal pathways. The results showed that the axonal dendrites of neurons in the hippocampal CA1 area of rats exposed to maltol aluminum showed neuritic beading and the dendritic spines were reduced. This resulted in dose-dependent LTP inhibition and led to impaired learning and memory function in rats. The PI3K-Akt-mTOR pathway may play a crucial role in this process. [ABSTRACT FROM AUTHOR]

Gene deletion or gene amplification acts as a driving factor of onset, progress, and metastasis in various cancers, including ovarian cancers. By mining the whole genome data of ovarian cancer patients, we identify the long noncoding RNA PVT1 as the most amplified gene. Knockdown of PVT1 was then achieved using a shRNA in two ovarian cancer cell lines, and cell viability was determined by trypan blue exclusion assay, cell metabolism by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assay, and cell cycle alteration by propidium iodide cell cycle analysis. Potential targeting microRNAs were predicted with starBase v2.0, and direct binding of miR-140 on PVT1 was confirmed by luciferase reporter assay and microRNA pull-down assay. Evolutionary conserved transcription factor-binding site was predicted via rVista 2.0. Our results show that PVT1 was the most amplified gene in ovarian cancer patients, and it was highly correlated with poor survival outcomes. Knockdown of PVT1 caused decreased cell viability, metabolic activity, and smaller proportion of S-phase cells. PVT1 directly bound to miR-140 and acted as a microRNA sponge, while transcription of PVT1 was regulated by the transcription factor FOXO4. In conclusion, viability, metabolism, and cell cycle of ovarian cancers are regulated by the FOXO4/PVT1/miR-140 signaling pathway. [ABSTRACT FROM AUTHOR]

Sedimentary soil was selected as the original sample (SOS). The adsorption fractions were obtained by the removal of dissolved organic matter (SRDOM), removal of minerals (SRM), removal of free fat (SRLF), and removal of nonhydrolyzable organic carbon (SNHC) respectively to investigate the adsorption characteristic of oxytetracycline (OTC) by different fractions of organic matter in sedimentary soil. The adsorption mechanism was investigated by elemental analysis, infrared spectra, and UV-visible spectroscopy. The results showed that the DOM in the sedimentary soil inhibited the adsorption of OTC, but the adsorption of different fractions of organic matter was quite different. The sorption kinetics of OTC were fitted to the pseudo-second-order model and the adsorption capacity of each fraction was: SNHC≈SRDOM > SOS > SRLF> SRM. The adsorption processes of OTC by different fractions were spontaneous. Alkaline pH condition had an effect on the adsorption of four fractions except for SNHC, while neutral and acidic pH affects SOS and SRDOM more obviously, the SNHC fraction was almost free from pH varies. Mechanism analysis showed that the main factors determining the adsorption capacity were the aromaticity and polarity of organic matter fractions. For the organic matter-based fractions (SRM, SRLF, and SNHC), the adsorption coefficient was positively correlated with the aromaticity. Furthermore, for SOS and SRDOM based on inorganic minerals, it was not only related to aromaticity, but also the content and composition of inorganic minerals. [ABSTRACT FROM AUTHOR]

Intrauterine infection with hepatitis B virus (HBV) has been suggested to accounting for most cases of chronic HBV infection, which cannot be blocked by combined immunoprophylaxis. The fact that the genetic background might impact the susceptibility to intrauterine infection of HBV has been identified by recent researches. A case-control study included sixty-nine HBsAg-positive mother-newborn pairs with intrauterine infection as cases compared to 138 mother-newborn pairs without intrauterine infection as controls. We studied the correlations between HBV intrauterine transmission and 15 maternal SNPs in eight genes (LTA, LTBR, TNFSF14, PDCD1, APOBEC3B, CD274, CD40 and CD40LG). There was a substantially significantly decreased risk of intrauterine infection of HBV in mothers with the rs2227981 TT genotype in PDCD1 gene compared to those with the rs2227981 GG genotype (OR 0.11, 95% CI 0.01-0.95, P = 0.045). Under recessive model (OR 0.51, 95% CI 0.26-1, P = 0.050) and additive model (OR 0.50, 95% CI 0.28-0.88, P = 0.017), we also found a marginally significantly decreased risk of intrauterine infection of HBV. Furthermore, under additive model, maternal genotype for rs2239704 in LTA gene was marginally significantly related to an increased risk of intrauterine HBV infection (OR 1.62, 95% CI 1-6.66, P = 0.055). However, there were no statistically significant associations among the remaining 13 SNPs and the risk of intrauterine infection of HBV. The examination implied that hereditary variants of PDCD1 and LTA genes were associated with intrauterine infection of HBV. [ABSTRACT FROM AUTHOR]

The 'solvate' ionic liquid (IL), comprising of a 1:1 complex of lithium bis(trifluoromethanesulfonyl)amide (LiTfN) and tetraglyme (G4), denoted herein by [Li(G4)][TfN], is promising as a relatively nonvolatile, nonflammable, and safer electrolyte for lithium-ion batteries. It, however, suffers from the drawback of low ionic conductivity compared with the conventional organic carbonate electrolytes. We report herein the enhancement in the thermal and transport properties of [Li(G4)][TfN] by blending it with an ether-derivatized imidazolium IL, namely 1-(2-methoxyethyl)-3-methylimidazolium bis(trifluoromethanesulfonyl)amide, [mEtMeIm][TfN]. The volumetric and transport properties of [mEtMeIm][TfN], and its blends with [Li(G4)][TfN], were investigated at temperatures in the range of 10-85 °C using oscillating U-tube densitometry, cone and plate viscometry, and electrochemical impedance spectroscopy. The addition of [mEtMeIm][TfN] to [Li(G4)][TfN] lowered the viscosity and increased the ionic conductivity of the blends. The blends also exhibited improved thermal stability in thermogravimetry experiments. Notwithstanding the complex intermolecular interactions existing in the mixture of the [mEtMeIm][TfN], LiTfN, and G4, the density, viscosity, and conductivity data could be modeled assuming the blend to be a simple binary mixture of [Li(G4)][TfN] and [mEtMeIm][TfN], instead of a ternary mixture of [mEtMeIm][TfN], LiTfN, and G4. The addition of unchelated LiTfN to [mEtMeIm][TfN] resulted in a decrease in ionic conductivity at all temperatures of measurement. However, when LiTfN was added as a 1:1 complex with G4, the conductivity was higher, at the same molar concentration of LiTfN. The implications of these results are discussed in view of developing thermally and chemically stable IL-based electrolytes for Li ion batteries, especially for operation at elevated temperatures. [ABSTRACT FROM AUTHOR]

Purpose: Every year, almost one million individuals are diagnosed with hepatocellular carcinoma (HCC) worldwide and more than 690,000 patients die of it. At present, most therapeutic anti-HCC agents are not effective, which is due to the appearance of chemo-resistance and/or toxic side effects. Therefore, it is imperative to find novel more effective anti-HCC agents. Here, we evaluated the effect of giganteaside D (GD), an oleanolic acid saponin from P. scabiosaefolia, on the growth and apoptosis of HCC cells. Methods and results: Using MTT and clonogenic assays, we found that GD exhibited a significant growth inhibitory effect on the HCC-derived cell lines HepG2 and Bel-7402. In addition, we found that GD induced mitochondria-mediated apoptosis in these HCC-derived cells, as indicated by a decreased mitochondrial potential, activation of Caspase-9 and Caspase-3, cleavage of PARP and release of Cytochrome C from the mitochondria. Besides, we found that GD stimulated the generation of reactive oxygen species (ROS) and that blockage of ROS attenuated the GD-induced mitochondria-mediated apoptosis. Additionally, we found that GD treatment led to a decrease in phosphorylated Erk (p-Erk) and triggered the generation of p-JNK, both components of the mitogen-activated protein kinase (MAPK) signaling pathway. Inhibition of Erk or JNK by specific inhibitors or siRNAs augmented or attenuated the cytotoxic and apoptotic effects of GD. Conclusions: From our results we conclude that GD can induce ROS-mediated apoptosis in HCC-derived cells through the MAPK pathway. This observation may open up avenues to explore the future use of GD as a HCC chemotherapeutic agent. [ABSTRACT FROM AUTHOR]

Energy conservation is one of the central challenges for the transportation system today. A variety of microscopic vehicle fuel consumption models have been developed to support eco-friendly transport strategies. However, most existing models are regression based and are sensitive to the vehicle-specific parameters and the operating conditions, therefore, an expensive and time-consuming calibration procedure is always indispensable in these models' application. In this paper, we propose an artificial neural network-based model to avoid the calibration problem. The main works include: (1) collect extensive field datasets such as large-scale controller area network bus to reflect the local transportation environment's fuel consumption characteristics; (2) conduct correlational analysis to identify the key fuel consumption influence factors; (3) develop a radial basis function neural network-based learning model to capture the nonlinear relationship between the key factors and the corresponding fuel consumption values based on the collected training datasets. The proposed model can give a reasonable prediction of instantaneous fuel consumption without calibration. The effectiveness of the proposed model is validated from a combination of both in-lab and field experiments. [ABSTRACT FROM AUTHOR]

Reports that an additional kind of elastic nano-conductive fibers (nano-f) was produced in a polymerization reaction of acetylene with nano-copper as catalyst. Preparation and structure characteristics of nano-copper; Morphology of nano-copper particles observed by TEM experiment; Demonstration of the nano-conductive fiber and its characteristics in microstructure; Change of resistance of the polyacetylene with temperature.